Closeup view of a general electric company demand meter which ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Close-up view of a general electric company demand meter which formerly monitored railroad power usage obtained from Philadelphia Electric Company sources. - Thirtieth Street Station, Load Dispatch Center, Thirtieth & Market Streets, Railroad Station, Amtrak (formerly Pennsylvania Railroad Station), Philadelphia, Philadelphia County, PA

Transactive control of fast-acting demand response based on thermostatic loads in real-time retail electricity markets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Behboodi, Sahand; Chassin, David P.; Djilali, Ned

Coordinated operation of distributed thermostatic loads such as heat pumps and air conditioners can reduce energy costs and prevents grid congestion, while maintaining room temperatures in the comfort range set by consumers. This paper furthers efforts towards enabling thermostatically controlled loads (TCLs) to participate in real-time retail electricity markets under a transactive control paradigm. An agent-based approach is used to develop an effective and low complexity demand response control scheme for TCLs. The proposed scheme adjusts aggregated thermostatic loads according to real-time grid conditions under both heating and cooling modes. Here, a case study is presented showing the method reducesmore » consumer electricity costs by over 10% compared to uncoordinated operation.« less

Transactive control of fast-acting demand response based on thermostatic loads in real-time retail electricity markets

DOE PAGES

Behboodi, Sahand; Chassin, David P.; Djilali, Ned; ...

2017-07-29

Coordinated operation of distributed thermostatic loads such as heat pumps and air conditioners can reduce energy costs and prevents grid congestion, while maintaining room temperatures in the comfort range set by consumers. This paper furthers efforts towards enabling thermostatically controlled loads (TCLs) to participate in real-time retail electricity markets under a transactive control paradigm. An agent-based approach is used to develop an effective and low complexity demand response control scheme for TCLs. The proposed scheme adjusts aggregated thermostatic loads according to real-time grid conditions under both heating and cooling modes. Here, a case study is presented showing the method reducesmore » consumer electricity costs by over 10% compared to uncoordinated operation.« less

Mechanics of Flapping Flight: Analytical Formulations of Unsteady Aerodynamics, Kinematic Optimization, Flight Dynamics, and Control

NASA Astrophysics Data System (ADS)

Taneja, Jayant Kumar

Electricity is an indispensable commodity to modern society, yet it is delivered via a grid architecture that remains largely unchanged over the past century. A host of factors are conspiring to topple this dated yet venerated design: developments in renewable electricity generation technology, policies to reduce greenhouse gas emissions, and advances in information technology for managing energy systems. Modern electric grids are emerging as complex distributed systems in which a portfolio of power generation resources, often incorporating fluctuating renewable resources such as wind and solar, must be managed dynamically to meet uncontrolled, time-varying demand. Uncertainty in both supply and demand makes control of modern electric grids fundamentally more challenging, and growing portfolios of renewables exacerbate the challenge. We study three electricity grids: the state of California, the province of Ontario, and the country of Germany. To understand the effects of increasing renewables, we develop a methodology to scale renewables penetration. Analyzing these grids yields key insights about rigid limits to renewables penetration and their implications in meeting long-term emissions targets. We argue that to achieve deep penetration of renewables, the operational model of the grid must be inverted, changing the paradigm from load-following supplies to supply-following loads. To alleviate the challenge of supply-demand matching on deeply renewable grids, we first examine well-known techniques, including altering management of existing supply resources, employing utility-scale energy storage, targeting energy efficiency improvements, and exercising basic demand-side management. Then, we create several instantiations of supply-following loads -- including refrigerators, heating and cooling systems, and laptop computers -- by employing a combination of sensor networks, advanced control techniques, and enhanced energy storage. We examine the capacity of each load for supply-following and study the behaviors of populations of these loads, assessing their potential at various levels of deployment throughout the California electricity grid. Using combinations of supply-following strategies, we can reduce peak natural gas generation by 19% on a model of the California grid with 60% renewables. We then assess remaining variability on this deeply renewable grid incorporating supply-following loads, characterizing additional capabilities needed to ensure supply-demand matching in future sustainable electricity grids.

An integrated eVoucher mechanism for flexible loads in real-time retail electricity market

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Tao; Pourbabak, Hajir; Liang, Zheming

This study proposes an innovative economic and engineering coupled framework to encourage typical flexible loads or load aggregators, such as parking lots with high penetration of electric vehicles, to participate directly in the real-time retail electricity market based on an integrated eVoucher program. The integrated eVoucher program entails demand side management, either in the positive or negative direction, following a popular customer-centric design principle. It provides the extra economic benefit to end-users and reduces the risk associated with the wholesale electricity market for electric distribution companies (EDCs), meanwhile improving the potential resilience of the distribution networks with consideration for frequencymore » deviations. When implemented, the eVoucher program allows typical flexible loads, such as electric vehicle parking lots, to adjust their demand and consumption behavior according to financial incentives from an EDC. A distribution system operator (DSO) works as a third party to hasten negotiations between such parking lots and EDCs, as well as the price clearing process. Eventually, both electricity retailers and power system operators will benefit from the active participation of the flexible loads and energy customers.« less

An integrated eVoucher mechanism for flexible loads in real-time retail electricity market

DOE PAGES

Chen, Tao; Pourbabak, Hajir; Liang, Zheming; ...

2017-01-26

This study proposes an innovative economic and engineering coupled framework to encourage typical flexible loads or load aggregators, such as parking lots with high penetration of electric vehicles, to participate directly in the real-time retail electricity market based on an integrated eVoucher program. The integrated eVoucher program entails demand side management, either in the positive or negative direction, following a popular customer-centric design principle. It provides the extra economic benefit to end-users and reduces the risk associated with the wholesale electricity market for electric distribution companies (EDCs), meanwhile improving the potential resilience of the distribution networks with consideration for frequencymore » deviations. When implemented, the eVoucher program allows typical flexible loads, such as electric vehicle parking lots, to adjust their demand and consumption behavior according to financial incentives from an EDC. A distribution system operator (DSO) works as a third party to hasten negotiations between such parking lots and EDCs, as well as the price clearing process. Eventually, both electricity retailers and power system operators will benefit from the active participation of the flexible loads and energy customers.« less

Key Residential Building Equipment Technologies for Control and Grid Support PART I (Residential)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Starke, Michael R; Onar, Omer C; DeVault, Robert C

2011-09-01

Electrical energy consumption of the residential sector is a crucial area of research that has in the past primarily focused on increasing the efficiency of household devices such as water heaters, dishwashers, air conditioners, and clothes washer and dryer units. However, the focus of this research is shifting as objectives such as developing the smart grid and ensuring that the power system remains reliable come to the fore, along with the increasing need to reduce energy use and costs. Load research has started to focus on mechanisms to support the power system through demand reduction and/or reliability services. The powermore » system relies on matching generation and load, and day-ahead and real-time energy markets capture most of this need. However, a separate set of grid services exist to address the discrepancies in load and generation arising from contingencies and operational mismatches, and to ensure that the transmission system is available for delivery of power from generation to load. Currently, these grid services are mostly provided by generation resources. The addition of renewable resources with their inherent variability can complicate the issue of power system reliability and lead to the increased need for grid services. Using load as a resource, through demand response programs, can fill the additional need for flexible resources and even reduce costly energy peaks. Loads have been shown to have response that is equal to or better than generation in some cases. Furthermore, price-incentivized demand response programs have been shown to reduce the peak energy requirements, thereby affecting the wholesale market efficiency and overall energy prices. The residential sector is not only the largest consumer of electrical energy in the United States, but also has the highest potential to provide demand reduction and power system support, as technological advancements in load control, sensor technologies, and communication are made. The prevailing loads based on the largest electrical energy consumers in the residential sector are space heating and cooling, washer and dryer, water heating, lighting, computers and electronics, dishwasher and range, and refrigeration. As the largest loads, these loads provide the highest potential for delivering demand response and reliability services. Many residential loads have inherent flexibility that is related to the purpose of the load. Depending on the load type, electric power consumption levels can either be ramped, changed in a step-change fashion, or completely removed. Loads with only on-off capability (such as clothes washers and dryers) provide less flexibility than resources that can be ramped or step-changed. Add-on devices may be able to provide extra demand response capabilities. Still, operating residential loads effectively requires awareness of the delicate balance of occupants health and comfort and electrical energy consumption. This report is Phase I of a series of reports aimed at identifying gaps in automated home energy management systems for incorporation of building appliances, vehicles, and renewable adoption into a smart grid, specifically with the intent of examining demand response and load factor control for power system support. The objective is to capture existing gaps in load control, energy management systems, and sensor technology with consideration of PHEV and renewable technologies to establish areas of research for the Department of Energy. In this report, (1) data is collected and examined from state of the art homes to characterize the primary residential loads as well as PHEVs and photovoltaic for potential adoption into energy management control strategies; and (2) demand response rules and requirements across the various demand response programs are examined for potential participation of residential loads. This report will be followed by a Phase II report aimed at identifying the current state of technology of energy management systems, sensors, and communication technologies for demand response and load factor control applications for the residential sector. The purpose is to cover the gaps that exist in the information captured by the sensors for energy management system to be able to provide demand response and load factor control. The vision is the development of an energy management system or other controlling enterprise hardware and software that is not only able to control loads, PHEVs, and renewable generation for demand response and load factor control, but also to do so with consumer comforts in mind and in an optimal fashion.« less

Electric load management and energy conservation

NASA Technical Reports Server (NTRS)

Kheir, N. A.

1976-01-01

Electric load management and energy conservation relate heavily to the major problems facing power industry at present. The three basic modes of energy conservation are identified as demand reduction, increased efficiency and substitution for scarce fuels. Direct and indirect load management objectives are to reduce peak loads and have future growth in electricity requirements in such a manner to cause more of it to fall off the system's peak. In this paper, an overview of proposed and implemented load management options is presented. Research opportunities exist for the evaluation of socio-economic impacts of energy conservation and load management schemes specially on the electric power industry itself.

A Study of Demand Response Effect of Thermal Storage Air-Conditioning Systems in Consideration of Electricity Market Prices

NASA Astrophysics Data System (ADS)

Omagari, Yuko; Sugihara, Hideharu; Tsuji, Kiichiro

This paper evaluates the economic impact of the introduction of customer-owned Thermal Storage Air-conditioning (TSA) systems, in an electricity market, from the viewpoint of the load service entity. We perform simulations on the condition that several thousand customers install TSA systems and shift peak demand in an electricity market by one percent. Our numerical results indicate that the purchase cost of the LSE was reduced through load management of customers with TSA systems. The introduction of TSA systems also reduced the volatility of market clearing price and reduced the whole-trade cost in an electricity market.

The value of demand response in Florida

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stoll, Brady; Buechler, Elizabeth; Hale, Elaine

Many electrical loads may be operated flexibly to provide grid services, including peaking capacity, reserves, and load shifting. The authors model 14 demand end uses in Florida and analyze their operational impacts and overall value for a wide range of solar penetrations and grid flexibility options. They find demand response is able to reduce production costs, reduce the number of low-load hours for traditional generators, reduce starting of gas generators, and reduce curtailment.

The value of demand response in Florida

DOE PAGES

Stoll, Brady; Buechler, Elizabeth; Hale, Elaine

2017-11-10

Many electrical loads may be operated flexibly to provide grid services, including peaking capacity, reserves, and load shifting. The authors model 14 demand end uses in Florida and analyze their operational impacts and overall value for a wide range of solar penetrations and grid flexibility options. They find demand response is able to reduce production costs, reduce the number of low-load hours for traditional generators, reduce starting of gas generators, and reduce curtailment.

Electric terminal performance and characterization of solid oxide fuel cells and systems

NASA Astrophysics Data System (ADS)

Lindahl, Peter Allan

Solid Oxide Fuel Cells (SOFCs) are electrochemical devices which can effect efficient, clean, and quiet conversion of chemical to electrical energy. In contrast to conventional electricity generation systems which feature multiple discrete energy conversion processes, SOFCs are direct energy conversion devices. That is, they feature a fully integrated chemical to electrical energy conversion process where the electric load demanded of the cell intrinsically drives the electrochemical reactions and associated processes internal to the cell. As a result, the cell's electric terminals provide a path for interaction between load side electric demand and the conversion side processes. The implication of this is twofold. First, the magnitude and dynamic characteristics of the electric load demanded of the cell can directly impact the long-term efficacy of the cell's chemical to electrical energy conversion. Second, the electric terminal response to dynamic loads can be exploited for monitoring the cell's conversion side processes and used in diagnostic analysis and degradation-mitigating control schemes. This dissertation presents a multi-tier investigation into this electric terminal based performance characterization of SOFCs through the development of novel test systems, analysis techniques and control schemes. First, a reference-based simulation system is introduced. This system scales up the electric terminal performance of a prototype SOFC system, e.g. a single fuel cell, to that of a full power-level stack. This allows realistic stack/load interaction studies while maintaining explicit ability for post-test analysis of the prototype system. Next, a time-domain least squares fitting method for electrochemical impedance spectroscopy (EIS) is developed for reduced-time monitoring of the electrochemical and physicochemical mechanics of the fuel cell through its electric terminals. The utility of the reference-based simulator and the EIS technique are demonstrated through their combined use in the performance testing of a hybrid-source power management (HSPM) system designed to allow in-situ EIS monitoring of a stack under dynamic loading conditions. The results from the latter study suggest that an HSPM controller allows an opportunity for in-situ electric terminal monitoring and control-based mitigation of SOFC degradation. As such, an exploration of control-based SOFC degradation mitigation is presented and ideas for further work are suggested.

Optimal Scheduling of Time-Shiftable Electric Loads in Expeditionary Power Grids

DTIC Science & Technology

2015-09-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS OPTIMAL SCHEDULING OF TIME-SHIFTABLE ELECTRIC LOADS IN EXPEDITIONARY POWER GRIDS by John G...to 09-25-2015 4. TITLE AND SUBTITLE OPTIMAL SCHEDULING OF TIME-SHIFTABLE ELECTRIC LOADS IN EXPEDI- TIONARY POWER GRIDS 5. FUNDING NUMBERS 6. AUTHOR(S...eliminate unmanaged peak demand, reduce generator peak-to-average power ratios, and facilitate a persistent shift to higher fuel efficiency. Using

DOE Office of Scientific and Technical Information (OSTI.GOV)

Piette, Mary Ann; Sezgen, Osman; Watson, David S.

This report describes the results of a research project to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve electric grid reliability, manage electricity costs, and ensure that customers receive signals that encourage load reduction during times when the electric grid is near its capacity. The two main drivers for widespread demand responsiveness are the prevention of future electricity crises and the reduction of electricity prices. Additional goals for price responsiveness include equity through costmore » of service pricing, and customer control of electricity usage and bills. The technology developed and evaluated in this report could be used to support numerous forms of DR programs and tariffs. For the purpose of this report, we have defined three levels of Demand Response automation. Manual Demand Response involves manually turning off lights or equipment; this can be a labor-intensive approach. Semi-Automated Response involves the use of building energy management control systems for load shedding, where a preprogrammed load shedding strategy is initiated by facilities staff. Fully-Automated Demand Response is initiated at a building or facility through receipt of an external communications signal--facility staff set up a pre-programmed load shedding strategy which is automatically initiated by the system without the need for human intervention. We have defined this approach to be Auto-DR. An important concept in Auto-DR is that a facility manager is able to ''opt out'' or ''override'' an individual DR event if it occurs at a time when the reduction in end-use services is not desirable. This project sought to improve the feasibility and nature of Auto-DR strategies in large facilities. The research focused on technology development, testing, characterization, and evaluation relating to Auto-DR. This evaluation also included the related decisionmaking perspectives of the facility owners and managers. Another goal of this project was to develop and test a real-time signal for automated demand response that provided a common communication infrastructure for diverse facilities. The six facilities recruited for this project were selected from the facilities that received CEC funds for new DR technology during California's 2000-2001 electricity crises (AB970 and SB-5X).« less

Thermal energy storage heat exchanger: Molten salt heat exchanger design for utility power plants

NASA Technical Reports Server (NTRS)

Ferarra, A.; Yenetchi, G.; Haslett, R.; Kosson, R.

1977-01-01

The use of thermal energy storage (TES) in the latent heat of molten salts as a means of conserving fossil fuels and lowering the cost of electric power was evaluated. Public utility systems provided electric power on demand. This demand is generally maximum during late weekday afternoons, with considerably lower overnight and weekend loads. Typically, the average demand is only 60% to 80% of peak load. As peak load increases, the present practice is to purchase power from other grid facilities or to bring older less efficient fossil-fuel plants on line which increase the cost of electric power. The widespread use of oil-fired boilers, gas turbine and diesel equipment to meet peaking loads depletes our oil-based energy resources. Heat exchangers utilizing molten salts can be used to level the energy consumption curve. The study begins with a demand analysis and the consideration of several existing modern fossil-fuel and nuclear power plants for use as models. Salts are evaluated for thermodynamic, economic, corrosive, and safety characteristics. Heat exchanger concepts are explored and heat exchanger designs are conceived. Finally, the economics of TES conversions in existing plants and new construction is analyzed. The study concluded that TES is feasible in electric power generation. Substantial data are presented for TES design, and reference material for further investigation of techniques is included.

Autonomous Hybrid Priority Queueing for Scheduling Residential Energy Demands

NASA Astrophysics Data System (ADS)

Kalimullah, I. Q.; Shamroukh, M.; Sahar, N.; Shetty, S.

2017-05-01

The advent of smart grid technologies has opened up opportunities to manage the energy consumption of the users within a residential smart grid system. Demand response management is particularly being employed to reduce the overall load on an electricity network which could in turn reduce outages and electricity costs. The objective of this paper is to develop an intelligible scheduler to optimize the energy available to a micro grid through hybrid queueing algorithm centered around the consumers’ energy demands. This is achieved by shifting certain schedulable load appliances to light load hours. Various factors such as the type of demand, grid load, consumers’ energy usage patterns and preferences are considered while formulating the logical constraints required for the algorithm. The algorithm thus obtained is then implemented in MATLAB workspace to simulate its execution by an Energy Consumption Scheduler (ECS) found within smart meters, which automatically finds the optimal energy consumption schedule tailor made to fit each consumer within the micro grid network.

Neural network based short-term load forecasting using weather compensation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chow, T.W.S.; Leung, C.T.

This paper presents a novel technique for electric load forecasting based on neural weather compensation. The proposed method is a nonlinear generalization of Box and Jenkins approach for nonstationary time-series prediction. A weather compensation neural network is implemented for one-day ahead electric load forecasting. The weather compensation neural network can accurately predict the change of actual electric load consumption from the previous day. The results, based on Hong Kong Island historical load demand, indicate that this methodology is capable of providing a more accurate load forecast with a 0.9% reduction in forecast error.

Time-varying value of electric energy efficiency

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mims, Natalie A.; Eckman, Tom; Goldman, Charles

Electric energy efficiency resources save energy and may reduce peak demand. Historically, quantification of energy efficiency benefits has largely focused on the economic value of energy savings during the first year and lifetime of the installed measures. Due in part to the lack of publicly available research on end-use load shapes (i.e., the hourly or seasonal timing of electricity savings) and energy savings shapes, consideration of the impact of energy efficiency on peak demand reduction (i.e., capacity savings) has been more limited. End-use load research and the hourly valuation of efficiency savings are used for a variety of electricity planningmore » functions, including load forecasting, demand-side management and evaluation, capacity and demand response planning, long-term resource planning, renewable energy integration, assessing potential grid modernization investments, establishing rates and pricing, and customer service. This study reviews existing literature on the time-varying value of energy efficiency savings, provides examples in four geographically diverse locations of how consideration of the time-varying value of efficiency savings impacts the calculation of power system benefits, and identifies future research needs to enhance the consideration of the time-varying value of energy efficiency in cost-effectiveness screening analysis. Findings from this study include: -The time-varying value of individual energy efficiency measures varies across the locations studied because of the physical and operational characteristics of the individual utility system (e.g., summer or winter peaking, load factor, reserve margin) as well as the time periods during which savings from measures occur. -Across the four locations studied, some of the largest capacity benefits from energy efficiency are derived from the deferral of transmission and distribution system infrastructure upgrades. However, the deferred cost of such upgrades also exhibited the greatest range in value of all the components of avoided costs across the locations studied. -Of the five energy efficiency measures studied, those targeting residential air conditioning in summer-peaking electric systems have the most significant added value when the total time-varying value is considered. -The increased use of rooftop solar systems, storage, and demand response, and the addition of electric vehicles and other major new electricity-consuming end uses are anticipated to significantly alter the load shape of many utility systems in the future. Data used to estimate the impact of energy efficiency measures on electric system peak demands will need to be updated periodically to accurately reflect the value of savings as system load shapes change. -Publicly available components of electric system costs avoided through energy efficiency are not uniform across states and utilities. Inclusion or exclusion of these components and differences in their value affect estimates of the time-varying value of energy efficiency. -Publicly available data on end-use load and energy savings shapes are limited, are concentrated regionally, and should be expanded.« less

Load research manual. Volume 2: Fundamentals of implementing load research procedures

NASA Astrophysics Data System (ADS)

1980-11-01

This manual will assist electric utilities and state regulatory authorities in investigating customer electricity demand as part of cost-of-service studies, rate design, marketing research, system design, load forecasting, rate reform analysis, and load management research. Load research procedures are described in detail. Research programs at three utilities are compared: Carolina Power and Light Company, Long Island Lighting Company, and Southern California Edison Company. A load research bibliography and glossaries of load research and statistical terms are also included.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Piette, Mary Ann

California needs new, responsive, demand-side energy technologies to ensure that periods of tight electricity supply on the grid don't turn into power outages. Led by Berkeley Lab's Mary Ann Piette, the California Energy Commission (through its Public Interest Energy Research Program) has established a Demand Response Research Center that addresses two motivations for adopting demand responsiveness: reducing average electricity prices and preventing future electricity crises. The research seeks to understand factors that influence "what works" in Demand Response. Piette's team is investigating the two types of demand response, load response and price response, that may influence and reduce the usemore » of peak electric power through automated controls, peak pricing, advanced communications, and other strategies.« less

Saving Power at Peak Hours (LBNL Science at the Theater)

ScienceCinema

Piette, Mary Ann [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2018-05-23

California needs new, responsive, demand-side energy technologies to ensure that periods of tight electricity supply on the grid don't turn into power outages. Led by Berkeley Lab's Mary Ann Piette, the California Energy Commission (through its Public Interest Energy Research Program) has established a Demand Response Research Center that addresses two motivations for adopting demand responsiveness: reducing average electricity prices and preventing future electricity crises. The research seeks to understand factors that influence "what works" in Demand Response. Piette's team is investigating the two types of demand response, load response and price response, that may influence and reduce the use of peak electric power through automated controls, peak pricing, advanced communications, and other strategies.

Climate change is projected to have severe impacts on the frequency and intensity of peak electricity demand across the United States.

PubMed

Auffhammer, Maximilian; Baylis, Patrick; Hausman, Catherine H

2017-02-21

It has been suggested that climate change impacts on the electric sector will account for the majority of global economic damages by the end of the current century and beyond [Rose S, et al. (2014) Understanding the Social Cost of Carbon: A Technical Assessment ]. The empirical literature has shown significant increases in climate-driven impacts on overall consumption, yet has not focused on the cost implications of the increased intensity and frequency of extreme events driving peak demand, which is the highest load observed in a period. We use comprehensive, high-frequency data at the level of load balancing authorities to parameterize the relationship between average or peak electricity demand and temperature for a major economy. Using statistical models, we analyze multiyear data from 166 load balancing authorities in the United States. We couple the estimated temperature response functions for total daily consumption and daily peak load with 18 downscaled global climate models (GCMs) to simulate climate change-driven impacts on both outcomes. We show moderate and heterogeneous changes in consumption, with an average increase of 2.8% by end of century. The results of our peak load simulations, however, suggest significant increases in the intensity and frequency of peak events throughout the United States, assuming today's technology and electricity market fundamentals. As the electricity grid is built to endure maximum load, our findings have significant implications for the construction of costly peak generating capacity, suggesting additional peak capacity costs of up to 180 billion dollars by the end of the century under business-as-usual.

A Generalized Formulation of Demand Response under Market Environments

NASA Astrophysics Data System (ADS)

Nguyen, Minh Y.; Nguyen, Duc M.

2015-06-01

This paper presents a generalized formulation of Demand Response (DR) under deregulated electricity markets. The problem is scheduling and controls the consumption of electrical loads according to the market price to minimize the energy cost over a day. Taking into account the modeling of customers' comfort (i.e., preference), the formulation can be applied to various types of loads including what was traditionally classified as critical loads (e.g., air conditioning, lights). The proposed DR scheme is based on Dynamic Programming (DP) framework and solved by DP backward algorithm in which the stochastic optimization is used to treat the uncertainty, if any occurred in the problem. The proposed formulation is examined with the DR problem of different loads, including Heat Ventilation and Air Conditioning (HVAC), Electric Vehicles (EVs) and a newly DR on the water supply systems of commercial buildings. The result of simulation shows significant saving can be achieved in comparison with their traditional (On/Off) scheme.

Feasibility of solid oxide fuel cell dynamic hydrogen coproduction to meet building demand

NASA Astrophysics Data System (ADS)

Shaffer, Brendan; Brouwer, Jacob

2014-02-01

A dynamic internal reforming-solid oxide fuel cell system model is developed and used to simulate the coproduction of electricity and hydrogen while meeting the measured dynamic load of a typical southern California commercial building. The simulated direct internal reforming-solid oxide fuel cell (DIR-SOFC) system is controlled to become an electrical load following device that well follows the measured building load data (3-s resolution). The feasibility of the DIR-SOFC system to meet the dynamic building demand while co-producing hydrogen is demonstrated. The resulting thermal responses of the system to the electrical load dynamics as well as those dynamics associated with the filling of a hydrogen collection tank are investigated. The DIR-SOFC system model also allows for resolution of the fuel cell species and temperature distributions during these dynamics since thermal gradients are a concern for DIR-SOFC.

Solar heating and the electric utilities

NASA Astrophysics Data System (ADS)

Maidique, M. A.; Woo, B.

1980-05-01

The article considers the effect of widespread use of solar thermal systems on the role of electric utilities, emphasizing the foreseen short term economic problems. While the average electricity demand will be reduced, infrequent high demand peaks could occur when on nights and certain days, solar users with inadequate storage capacity are forced to depend upon conventional energy sources. Since utility costs are closely related to changes in peak demands, the modification of electricity rate structures as a load management technique is discussed. Some advantages of wide solar energy application for electric utilities are cited including the possibility of their key role in the development of solar heating.

Climate change is projected to have severe impacts on the frequency and intensity of peak electricity demand across the United States

PubMed Central

Auffhammer, Maximilian; Baylis, Patrick; Hausman, Catherine H.

2017-01-01

It has been suggested that climate change impacts on the electric sector will account for the majority of global economic damages by the end of the current century and beyond [Rose S, et al. (2014) Understanding the Social Cost of Carbon: A Technical Assessment]. The empirical literature has shown significant increases in climate-driven impacts on overall consumption, yet has not focused on the cost implications of the increased intensity and frequency of extreme events driving peak demand, which is the highest load observed in a period. We use comprehensive, high-frequency data at the level of load balancing authorities to parameterize the relationship between average or peak electricity demand and temperature for a major economy. Using statistical models, we analyze multiyear data from 166 load balancing authorities in the United States. We couple the estimated temperature response functions for total daily consumption and daily peak load with 18 downscaled global climate models (GCMs) to simulate climate change-driven impacts on both outcomes. We show moderate and heterogeneous changes in consumption, with an average increase of 2.8% by end of century. The results of our peak load simulations, however, suggest significant increases in the intensity and frequency of peak events throughout the United States, assuming today’s technology and electricity market fundamentals. As the electricity grid is built to endure maximum load, our findings have significant implications for the construction of costly peak generating capacity, suggesting additional peak capacity costs of up to 180 billion dollars by the end of the century under business-as-usual. PMID:28167756

The potential of magneto-electric nanocarriers for drug delivery.

PubMed

Kaushik, Ajeet; Jayant, Rahul Dev; Sagar, Vidya; Nair, Madhavan

2014-10-01

The development and design of personalized nanomedicine for better health quality is receiving great attention. In order to deliver and release a therapeutic concentration at the target site, novel nanocarriers (NCs) were designed, for example, magneto-electric (ME) which possess ideal properties of high drug loading, site-specificity and precise on-demand controlled drug delivery. This review explores the potential of ME-NCs for on-demand and site-specific drug delivery and release for personalized therapeutics. The main features including effect of magnetism, improvement in drug loading, drug transport across blood-brain barriers and on-demand controlled release are also discussed. The future directions and possible impacts on upcoming nanomedicine are highlighted. Numerous reports suggest that there is an urgent need to explore novel NC formulations for safe and targeted drug delivery and release at specific disease sites. The challenges of formulation lie in the development of NCs that improve biocompatibility and surface modifications for optimum drug loading/preservation/transmigration and tailoring of electrical-magnetic properties for on-demand drug release. Thus, the development of novel NCs is anticipated to overcome the problems of targeted delivery of therapeutic agents with desired precision that may lead to better patient compliance.

Bulk electric system reliability evaluation incorporating wind power and demand side management

NASA Astrophysics Data System (ADS)

Huang, Dange

Electric power systems are experiencing dramatic changes with respect to structure, operation and regulation and are facing increasing pressure due to environmental and societal constraints. Bulk electric system reliability is an important consideration in power system planning, design and operation particularly in the new competitive environment. A wide range of methods have been developed to perform bulk electric system reliability evaluation. Theoretically, sequential Monte Carlo simulation can include all aspects and contingencies in a power system and can be used to produce an informative set of reliability indices. It has become a practical and viable tool for large system reliability assessment technique due to the development of computing power and is used in the studies described in this thesis. The well-being approach used in this research provides the opportunity to integrate an accepted deterministic criterion into a probabilistic framework. This research work includes the investigation of important factors that impact bulk electric system adequacy evaluation and security constrained adequacy assessment using the well-being analysis framework. Load forecast uncertainty is an important consideration in an electrical power system. This research includes load forecast uncertainty considerations in bulk electric system reliability assessment and the effects on system, load point and well-being indices and reliability index probability distributions are examined. There has been increasing worldwide interest in the utilization of wind power as a renewable energy source over the last two decades due to enhanced public awareness of the environment. Increasing penetration of wind power has significant impacts on power system reliability, and security analyses become more uncertain due to the unpredictable nature of wind power. The effects of wind power additions in generating and bulk electric system reliability assessment considering site wind speed correlations and the interactive effects of wind power and load forecast uncertainty on system reliability are examined. The concept of the security cost associated with operating in the marginal state in the well-being framework is incorporated in the economic analyses associated with system expansion planning including wind power and load forecast uncertainty. Overall reliability cost/worth analyses including security cost concepts are applied to select an optimal wind power injection strategy in a bulk electric system. The effects of the various demand side management measures on system reliability are illustrated using the system, load point, and well-being indices, and the reliability index probability distributions. The reliability effects of demand side management procedures in a bulk electric system including wind power and load forecast uncertainty considerations are also investigated. The system reliability effects due to specific demand side management programs are quantified and examined in terms of their reliability benefits.

Smart Grid Risk Management

NASA Astrophysics Data System (ADS)

Abad Lopez, Carlos Adrian

Current electricity infrastructure is being stressed from several directions -- high demand, unreliable supply, extreme weather conditions, accidents, among others. Infrastructure planners have, traditionally, focused on only the cost of the system; today, resilience and sustainability are increasingly becoming more important. In this dissertation, we develop computational tools for efficiently managing electricity resources to help create a more reliable and sustainable electrical grid. The tools we present in this work will help electric utilities coordinate demand to allow the smooth and large scale integration of renewable sources of energy into traditional grids, as well as provide infrastructure planners and operators in developing countries a framework for making informed planning and control decisions in the presence of uncertainty. Demand-side management is considered as the most viable solution for maintaining grid stability as generation from intermittent renewable sources increases. Demand-side management, particularly demand response (DR) programs that attempt to alter the energy consumption of customers either by using price-based incentives or up-front power interruption contracts, is more cost-effective and sustainable in addressing short-term supply-demand imbalances when compared with the alternative that involves increasing fossil fuel-based fast spinning reserves. An essential step in compensating participating customers and benchmarking the effectiveness of DR programs is to be able to independently detect the load reduction from observed meter data. Electric utilities implementing automated DR programs through direct load control switches are also interested in detecting the reduction in demand to efficiently pinpoint non-functioning devices to reduce maintenance costs. We develop sparse optimization methods for detecting a small change in the demand for electricity of a customer in response to a price change or signal from the utility, dynamic learning methods for scheduling the maintenance of direct load control switches whose operating state is not directly observable and can only be inferred from the metered electricity consumption, and machine learning methods for accurately forecasting the load of hundreds of thousands of residential, commercial and industrial customers. These algorithms have been implemented in the software system provided by AutoGrid, Inc., and this system has helped several utilities in the Pacific Northwest, Oklahoma, California and Texas, provide more reliable power to their customers at significantly reduced prices. Providing power to widely spread out communities in developing countries using the conventional power grid is not economically feasible. The most attractive alternative source of affordable energy for these communities is solar micro-grids. We discuss risk-aware robust methods to optimally size and operate solar micro-grids in the presence of uncertain demand and uncertain renewable generation. These algorithms help system operators to increase their revenue while making their systems more resilient to inclement weather conditions.

Analysis of the electricity demand of Greece for optimal planning of a large-scale hybrid renewable energy system

NASA Astrophysics Data System (ADS)

Tyralis, Hristos; Karakatsanis, Georgios; Tzouka, Katerina; Mamassis, Nikos

2015-04-01

The Greek electricity system is examined for the period 2002-2014. The demand load data are analysed at various time scales (hourly, daily, seasonal and annual) and they are related to the mean daily temperature and the gross domestic product (GDP) of Greece for the same time period. The prediction of energy demand, a product of the Greek Independent Power Transmission Operator, is also compared with the demand load. Interesting results about the change of the electricity demand scheme after the year 2010 are derived. This change is related to the decrease of the GDP, during the period 2010-2014. The results of the analysis will be used in the development of an energy forecasting system which will be a part of a framework for optimal planning of a large-scale hybrid renewable energy system in which hydropower plays the dominant role. Acknowledgement: This research was funded by the Greek General Secretariat for Research and Technology through the research project Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO; grant number 5145)

Long term load forecasting accuracy in electric utility integrated resource planning

DOE PAGES

Carvallo, Juan Pablo; Larsen, Peter H.; Sanstad, Alan H.; ...

2018-05-23

Forecasts of electricity consumption and peak demand over time horizons of one or two decades are a key element in electric utilities’ meeting their core objective and obligation to ensure reliable and affordable electricity supplies for their customers while complying with a range of energy and environmental regulations and policies. These forecasts are an important input to integrated resource planning (IRP) processes involving utilities, regulators, and other stake-holders. Despite their importance, however, there has been little analysis of long term utility load forecasting accuracy. We conduct a retrospective analysis of long term load forecasts on twelve Western U. S. electricmore » utilities in the mid-2000s to find that most overestimated both energy consumption and peak demand growth. A key reason for this was the use of assumptions that led to an overestimation of economic growth. We find that the complexity of forecast methods and the accuracy of these forecasts are mildly correlated. In addition, sensitivity and risk analysis of load growth and its implications for capacity expansion were not well integrated with subsequent implementation. As a result, we review changes in the utilities load forecasting methods over the subsequent decade, and discuss the policy implications of long term load forecast inaccuracy and its underlying causes.« less

Long term load forecasting accuracy in electric utility integrated resource planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carvallo, Juan Pablo; Larsen, Peter H.; Sanstad, Alan H.

Forecasts of electricity consumption and peak demand over time horizons of one or two decades are a key element in electric utilities’ meeting their core objective and obligation to ensure reliable and affordable electricity supplies for their customers while complying with a range of energy and environmental regulations and policies. These forecasts are an important input to integrated resource planning (IRP) processes involving utilities, regulators, and other stake-holders. Despite their importance, however, there has been little analysis of long term utility load forecasting accuracy. We conduct a retrospective analysis of long term load forecasts on twelve Western U. S. electricmore » utilities in the mid-2000s to find that most overestimated both energy consumption and peak demand growth. A key reason for this was the use of assumptions that led to an overestimation of economic growth. We find that the complexity of forecast methods and the accuracy of these forecasts are mildly correlated. In addition, sensitivity and risk analysis of load growth and its implications for capacity expansion were not well integrated with subsequent implementation. As a result, we review changes in the utilities load forecasting methods over the subsequent decade, and discuss the policy implications of long term load forecast inaccuracy and its underlying causes.« less

Electrical Load Profile Analysis Using Clustering Techniques

NASA Astrophysics Data System (ADS)

Damayanti, R.; Abdullah, A. G.; Purnama, W.; Nandiyanto, A. B. D.

2017-03-01

Data mining is one of the data processing techniques to collect information from a set of stored data. Every day the consumption of electricity load is recorded by Electrical Company, usually at intervals of 15 or 30 minutes. This paper uses a clustering technique, which is one of data mining techniques to analyse the electrical load profiles during 2014. The three methods of clustering techniques were compared, namely K-Means (KM), Fuzzy C-Means (FCM), and K-Means Harmonics (KHM). The result shows that KHM is the most appropriate method to classify the electrical load profile. The optimum number of clusters is determined using the Davies-Bouldin Index. By grouping the load profile, the demand of variation analysis and estimation of energy loss from the group of load profile with similar pattern can be done. From the group of electric load profile, it can be known cluster load factor and a range of cluster loss factor that can help to find the range of values of coefficients for the estimated loss of energy without performing load flow studies.

An adaptive load-following control system for a space nuclear power system

NASA Astrophysics Data System (ADS)

Metzger, John D.; El-Genk, Mohamed S.

An adaptive load-following control system is proposed for a space nuclear power system. The conceptual design of the SP-100 space nuclear power system proposes operating the nuclear reactor at a base thermal power and accommodating changes in the electrical power demand with a shunt regulator. It is necessary to increase the reactor thermal power if the payload electrical demand exceeds the peak system electrical output for the associated reactor power. When it is necessary to change the nuclear reactor power to meet a change in the power demand, the power ascension or descension must be accomplished in a predetermined manner to avoid thermal stresses in the system and to achieve the desired reactor period. The load-following control system described has the ability to adapt to changes in the system and to changes in the satellite environment. The application is proposed of the model reference adaptive control (MRAC). The adaptive control system has the ability to control the dynamic response of nonlinear systems. Three basic subsets of adaptive control are: (1) gain scheduling, (2) self-tuning regulators, and (3) model reference adaptive control.

Co-optimization of Energy and Demand-Side Reserves in Day-Ahead Electricity Markets

NASA Astrophysics Data System (ADS)

Surender Reddy, S.; Abhyankar, A. R.; Bijwe, P. R.

2015-04-01

This paper presents a new multi-objective day-ahead market clearing (DAMC) mechanism with demand-side reserves/demand response (DR) offers, considering realistic voltage-dependent load modeling. The paper proposes objectives such as social welfare maximization (SWM) including demand-side reserves, and load served error (LSE) minimization. In this paper, energy and demand-side reserves are cleared simultaneously through co-optimization process. The paper clearly brings out the unsuitability of conventional SWM for DAMC in the presence of voltage-dependent loads, due to reduction of load served (LS). Under such circumstances multi-objective DAMC with DR offers is essential. Multi-objective Strength Pareto Evolutionary Algorithm 2+ (SPEA 2+) has been used to solve the optimization problem. The effectiveness of the proposed scheme is confirmed with results obtained from IEEE 30 bus system.

Impacts of Climate Change on Electricity Consumption in Baden-Wuerttemberg

NASA Astrophysics Data System (ADS)

Mimler, S.

2009-04-01

Changes in electricity consumption due to changes in mean air temperatures were examined for the German federal state Baden-Wuerttemberg. Unlike in most recent studies on future electricity demand variations due to climate change, other load influencing factors like the economic, technological and demographic situation were fixed to the state of 2006. This allows isolating the climate change effect on electricity demand. The analysis was realised in two major steps. Firstly, an electricity forecast model based on multiple regressions was estimated on the region of Baden-Wuerttemberg by using historical load and temperature data. The estimation of the forecast model provides information on the temperature sensitivity of electricity demand in the given region. The overall heating and cooling gradients are estimated with -59 and 84 MW / °C respectively. These results already point out a low temperature sensitivity of demand in the region of Baden-Wuerttemberg mostly due to a low share of households equipped with electric heating and air conditioning systems. Secondly, near surface air temperature data of the regional climate model REMO [1] was used to simulate load curves for the control period 1971 to 2000 and for three future scenarios 2006 to 2035, 2036 to 2065 and 2066 to 2095. The results show that the overall load decreases throughout all future scenario periods in comparison to the control period. This is due to a higher decrease in heating than increase in cooling load. Nevertheless, the weather dependent part in Baden-Wuerttemberg loads only accounts for 0.05 % of the average load level. Within this weather dependent part, the heating load decreases are highest in June to September concentrated on the day times evening and afternoon. The cooling period broadens from May to September in the control period to April to October by 2095. The highest relative increases occur in October. Regarding day times, the increase in cooling load is concentrated on afternoons, evenings and nights. [1] Jacob, D. (2005a), "REMO A1B Scenario run, UBA project, 0.088 degree resolution, run no.006211, 1H data", World Data Center for Climate, CERA-DB "REMO_UBA_A1B_1_R006211_1H", http://cera-www.dkrz.de/WDCC/ui/Compact.jsp? acronym=REMO_UBA_A1B_1_R006211_1H Jacob, D. (2005b), "REMO climate of the 20th century run, UBA project, 0.088 degree resolution, run no. 006210, 1H data", World Data Center for Climate, CERA-DB "REMO_UBA_C20_1_R006210_1H", http://cera-www.dkrz.de/WDCC/ui/Compact. jsp?acronym=REMO_UBA_C20_1_R006210_1H

Towards smart energy systems: application of kernel machine regression for medium term electricity load forecasting.

PubMed

Alamaniotis, Miltiadis; Bargiotas, Dimitrios; Tsoukalas, Lefteri H

2016-01-01

Integration of energy systems with information technologies has facilitated the realization of smart energy systems that utilize information to optimize system operation. To that end, crucial in optimizing energy system operation is the accurate, ahead-of-time forecasting of load demand. In particular, load forecasting allows planning of system expansion, and decision making for enhancing system safety and reliability. In this paper, the application of two types of kernel machines for medium term load forecasting (MTLF) is presented and their performance is recorded based on a set of historical electricity load demand data. The two kernel machine models and more specifically Gaussian process regression (GPR) and relevance vector regression (RVR) are utilized for making predictions over future load demand. Both models, i.e., GPR and RVR, are equipped with a Gaussian kernel and are tested on daily predictions for a 30-day-ahead horizon taken from the New England Area. Furthermore, their performance is compared to the ARMA(2,2) model with respect to mean average percentage error and squared correlation coefficient. Results demonstrate the superiority of RVR over the other forecasting models in performing MTLF.

Demand Side Management: An approach to peak load smoothing

NASA Astrophysics Data System (ADS)

Gupta, Prachi

A preliminary national-level analysis was conducted to determine whether Demand Side Management (DSM) programs introduced by electric utilities since 1992 have made any progress towards their stated goal of reducing peak load demand. Estimates implied that DSM has a very small effect on peak load reduction and there is substantial regional and end-user variability. A limited scholarly literature on DSM also provides evidence in support of a positive effect of demand response programs. Yet, none of these studies examine the question of how DSM affects peak load at the micro-level by influencing end-users' response to prices. After nearly three decades of experience with DSM, controversy remains over how effective these programs have been. This dissertation considers regional analyses that explore both demand-side solutions and supply-side interventions. On the demand side, models are estimated to provide in-depth evidence of end-user consumption patterns for each North American Electric Reliability Corporation (NERC) region, helping to identify sectors in regions that have made a substantial contribution to peak load reduction. The empirical evidence supports the initial hypothesis that there is substantial regional and end-user variability of reductions in peak demand. These results are quite robust in rapidly-urbanizing regions, where air conditioning and lighting load is substantially higher, and regions where the summer peak is more pronounced than the winter peak. It is also evident from the regional experiences that active government involvement, as shaped by state regulations in the last few years, has been successful in promoting DSM programs, and perhaps for the same reason we witness an uptick in peak load reductions in the years 2008 and 2009. On the supply side, we estimate the effectiveness of DSM programs by analyzing the growth of capacity margin with the introduction of DSM programs. The results indicate that DSM has been successful in offsetting the need for additional production capacity by the means of demand response measures, but the success is limited to only a few regions. The rate of progress in the future will depend on a wide range of improved technologies and a continuous government monitoring for successful adoption of demand response programs to manage growing energy demand.

[Demography perspectives and forecasts of the demand for electricity].

PubMed

Roy, L; Guimond, E

1995-01-01

"Demographic perspectives form an integral part in the development of electric load forecasts. These forecasts in turn are used to justify the addition and repair of generating facilities that will supply power in the coming decades. The goal of this article is to present how demographic perspectives are incorporated into the electric load forecasting in Quebec. The first part presents the methods, hypotheses and results of population and household projections used by Hydro-Quebec in updating its latest development plan. The second section demonstrates applications of such demographic projections for forecasting the electric load, with a focus on the residential sector." (SUMMARY IN ENG AND SPA) excerpt

Forecasting Strategies for Predicting Peak Electric Load Days

NASA Astrophysics Data System (ADS)

Saxena, Harshit

Academic institutions spend thousands of dollars every month on their electric power consumption. Some of these institutions follow a demand charges pricing structure; here the amount a customer pays to the utility is decided based on the total energy consumed during the month, with an additional charge based on the highest average power load required by the customer over a moving window of time as decided by the utility. Therefore, it is crucial for these institutions to minimize the time periods where a high amount of electric load is demanded over a short duration of time. In order to reduce the peak loads and have more uniform energy consumption, it is imperative to predict when these peaks occur, so that appropriate mitigation strategies can be developed. The research work presented in this thesis has been conducted for Rochester Institute of Technology (RIT), where the demand charges are decided based on a 15 minute sliding window panned over the entire month. This case study makes use of different statistical and machine learning algorithms to develop a forecasting strategy for predicting the peak electric load days of the month. The proposed strategy was tested for a whole year starting May 2015 to April 2016 during which a total of 57 peak days were observed. The model predicted a total of 74 peak days during this period, 40 of these cases were true positives, hence achieving an accuracy level of 70 percent. The results obtained with the proposed forecasting strategy are promising and demonstrate an annual savings potential worth about $80,000 for a single submeter of RIT.

An econometric simulation model of income and electricity demand in Alaska's Railbelt, 1982-2022

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maddigan, R.J.; Hill, L.J.; Hamblin, D.M.

1987-01-01

This report describes the specification of-and forecasts derived from-the Alaska Railbelt Electricity Load, Macroeconomic (ARELM) model. ARELM was developed as an independent, modeling tool for the evaluation of the need for power from the Susitna Hydroelectric Project which has been proposed by the Alaska Power Authority. ARELM is an econometric simulation model consisting of 61 equations - 46 behavioral equations and 15 identities. The system includes two components: (1) ARELM-MACRO which is a system of equations that simulates the performance of both the total Alaskan and Railbelt macroeconomies and (2) ARELM-LOAD which projects electricity-related activity in the Alaskan Railbelt region.more » The modeling system is block recursive in the sense that forecasts of population, personal income, and employment in the Railbelt derived from ARELM-MACRO are used as explanatory variables in ARELM-LOAD to simulate electricity demand, the real average price of electricity, and the number of customers in the Railbelt. Three scenarios based on assumptions about the future price of crude oil are simulated and documented in the report. The simulations, which do not include the cost-of-power impacts of Susitna-based generation, show that the growth rate in Railbelt electricity load is between 2.5 and 2.7% over the 1982 to 2022 forecast period. The forecasting results are consistent with other projections of load growth in the region using different modeling approaches.« less

Short term load forecasting of anomalous load using hybrid soft computing methods

NASA Astrophysics Data System (ADS)

Rasyid, S. A.; Abdullah, A. G.; Mulyadi, Y.

2016-04-01

Load forecast accuracy will have an impact on the generation cost is more economical. The use of electrical energy by consumers on holiday, show the tendency of the load patterns are not identical, it is different from the pattern of the load on a normal day. It is then defined as a anomalous load. In this paper, the method of hybrid ANN-Particle Swarm proposed to improve the accuracy of anomalous load forecasting that often occur on holidays. The proposed methodology has been used to forecast the half-hourly electricity demand for power systems in the Indonesia National Electricity Market in West Java region. Experiments were conducted by testing various of learning rate and learning data input. Performance of this methodology will be validated with real data from the national of electricity company. The result of observations show that the proposed formula is very effective to short-term load forecasting in the case of anomalous load. Hybrid ANN-Swarm Particle relatively simple and easy as a analysis tool by engineers.

Modeling Hybrid Nuclear Systems With Chilled-Water Storage

DOE PAGES

Misenheimer, Corey T.; Terry, Stephen D.

2016-06-27

Air-conditioning loads during the warmer months of the year are large contributors to an increase in the daily peak electrical demand. Traditionally, utility companies boost output to meet daily cooling load spikes, often using expensive and polluting fossil fuel plants to match the demand. Likewise, heating, ventilation, and air conditioning (HVAC) system components must be sized to meet these peak cooling loads. However, the use of a properly sized stratified chilled-water storage system in conjunction with conventional HVAC system components can shift daily energy peaks from cooling loads to off-peak hours. This process is examined in light of the recentmore » development of small modular nuclear reactors (SMRs). In this paper, primary components of an air-conditioning system with a stratified chilled-water storage tank were modeled in FORTRAN 95. A basic chiller operation criterion was employed. Simulation results confirmed earlier work that the air-conditioning system with thermal energy storage (TES) capabilities not only reduced daily peaks in energy demand due to facility cooling loads but also shifted the energy demand from on-peak to off-peak hours, thereby creating a more flattened total electricity demand profile. Thus, coupling chilled-water storage-supplemented HVAC systems to SMRs is appealing because of the decrease in necessary reactor power cycling, and subsequently reduced associated thermal stresses in reactor system materials, to meet daily fluctuations in cooling demand. Finally and also, such a system can be used as a thermal sink during reactor transients or a buffer due to renewable intermittency in a nuclear hybrid energy system (NHES).« less

Modeling Hybrid Nuclear Systems With Chilled-Water Storage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Misenheimer, Corey T.; Terry, Stephen D.

Air-conditioning loads during the warmer months of the year are large contributors to an increase in the daily peak electrical demand. Traditionally, utility companies boost output to meet daily cooling load spikes, often using expensive and polluting fossil fuel plants to match the demand. Likewise, heating, ventilation, and air conditioning (HVAC) system components must be sized to meet these peak cooling loads. However, the use of a properly sized stratified chilled-water storage system in conjunction with conventional HVAC system components can shift daily energy peaks from cooling loads to off-peak hours. This process is examined in light of the recentmore » development of small modular nuclear reactors (SMRs). In this paper, primary components of an air-conditioning system with a stratified chilled-water storage tank were modeled in FORTRAN 95. A basic chiller operation criterion was employed. Simulation results confirmed earlier work that the air-conditioning system with thermal energy storage (TES) capabilities not only reduced daily peaks in energy demand due to facility cooling loads but also shifted the energy demand from on-peak to off-peak hours, thereby creating a more flattened total electricity demand profile. Thus, coupling chilled-water storage-supplemented HVAC systems to SMRs is appealing because of the decrease in necessary reactor power cycling, and subsequently reduced associated thermal stresses in reactor system materials, to meet daily fluctuations in cooling demand. Finally and also, such a system can be used as a thermal sink during reactor transients or a buffer due to renewable intermittency in a nuclear hybrid energy system (NHES).« less

North–south polarization of European electricity consumption under future warming

PubMed Central

Wenz, Leonie; Levermann, Anders; Auffhammer, Maximilian

2017-01-01

There is growing empirical evidence that anthropogenic climate change will substantially affect the electric sector. Impacts will stem both from the supply side—through the mitigation of greenhouse gases—and from the demand side—through adaptive responses to a changing environment. Here we provide evidence of a polarization of both peak load and overall electricity consumption under future warming for the world’s third-largest electricity market—the 35 countries of Europe. We statistically estimate country-level dose–response functions between daily peak/total electricity load and ambient temperature for the period 2006–2012. After removing the impact of nontemperature confounders and normalizing the residual load data for each country, we estimate a common dose–response function, which we use to compute national electricity loads for temperatures that lie outside each country’s currently observed temperature range. To this end, we impose end-of-century climate on today’s European economies following three different greenhouse-gas concentration trajectories, ranging from ambitious climate-change mitigation—in line with the Paris agreement—to unabated climate change. We find significant increases in average daily peak load and overall electricity consumption in southern and western Europe (∼3 to ∼7% for Portugal and Spain) and significant decreases in northern Europe (∼−6 to ∼−2% for Sweden and Norway). While the projected effect on European total consumption is nearly zero, the significant polarization and seasonal shifts in peak demand and consumption have important ramifications for the location of costly peak-generating capacity, transmission infrastructure, and the design of energy-efficiency policy and storage capacity. PMID:28847939

North-south polarization of European electricity consumption under future warming.

PubMed

Wenz, Leonie; Levermann, Anders; Auffhammer, Maximilian

2017-09-19

There is growing empirical evidence that anthropogenic climate change will substantially affect the electric sector. Impacts will stem both from the supply side-through the mitigation of greenhouse gases-and from the demand side-through adaptive responses to a changing environment. Here we provide evidence of a polarization of both peak load and overall electricity consumption under future warming for the world's third-largest electricity market-the 35 countries of Europe. We statistically estimate country-level dose-response functions between daily peak/total electricity load and ambient temperature for the period 2006-2012. After removing the impact of nontemperature confounders and normalizing the residual load data for each country, we estimate a common dose-response function, which we use to compute national electricity loads for temperatures that lie outside each country's currently observed temperature range. To this end, we impose end-of-century climate on today's European economies following three different greenhouse-gas concentration trajectories, ranging from ambitious climate-change mitigation-in line with the Paris agreement-to unabated climate change. We find significant increases in average daily peak load and overall electricity consumption in southern and western Europe (∼3 to ∼7% for Portugal and Spain) and significant decreases in northern Europe (∼-6 to ∼-2% for Sweden and Norway). While the projected effect on European total consumption is nearly zero, the significant polarization and seasonal shifts in peak demand and consumption have important ramifications for the location of costly peak-generating capacity, transmission infrastructure, and the design of energy-efficiency policy and storage capacity.

Using high frequency consumption data to identify demand response potential for solar energy integration

NASA Astrophysics Data System (ADS)

Jin, L.; Borgeson, S.; Fredman, D.; Hans, L.; Spurlock, A.; Todd, A.

2015-12-01

California's renewable portfolio standard (2012) requires the state to get 33% of its electricity from renewable sources by 2020. Increased share of variable renewable sources such as solar and wind in the California electricity system may require more grid flexibility to insure reliable power services. Such grid flexibility can be potentially provided by changes in end use electricity consumptions in response to grid conditions (demand-response). In the solar case, residential consumption in the late afternoon can be used as reserve capacity to balance the drop in solar generation. This study presents our initial attempt to identify, from a behavior perspective, residential demand response potentials in relation to solar ramp events using a data-driven approach. Based on hourly residential energy consumption data, we derive representative daily load shapes focusing on discretionary consumption with an innovative clustering analysis technique. We aggregate the representative load shapes into behavior groups in terms of the timing and rhythm of energy use in the context of solar ramp events. Households of different behavior groups that are active during hours with high solar ramp rates are identified for capturing demand response potential. Insights into the nature and predictability of response to demand-response programs are provided.

Economically dispatching cogeneration facilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hernandez, E.

Economic dispatching has been used by utilities to meet the energy demands of their customers for decades. The objective was to first load those units which cost the least to run and slowly increase the loading of more expensive units as the incremental energy price increased. Although this concept worked well for utility based systems where incremental costs rose with peak demand, the independent power producers(IPPs) and the power purchase agreements (PPAs) have drastically changed this notion. Most PPAs structured for the IPP environment have negotiated rates which remain the same during peak periods and base their electrical generation onmore » specific process steam requirements. They also must maintain the required production balance of process steam and electrical load in order to qualify as a Public Utility Regulatory Policies Act (PURPA) facility. Consequently, economically dispatching Cogeneration facilities becomes an exercise in adhering to contractual guidelines while operating the equipment in the most efficient manner possible for the given condition. How then is it possible to dispatch a Cogeneration facility that maintains the electrical load demand of JFK Airport while satisfying all of its heating and cooling needs? Contractually, Kennedy International Airport Cogen (KIAC) has specific obligations concerning electrical and thermal energy exported to JFK Airport. The facility`s impressive array of heating and cooling apparatuses together with the newly installed cogen fulfilled the airport`s needs by utilizing an endless combination of new and previously installed equipment. Moreover, in order to economically operate the plant a well structured operating curriculum was necessary.« less

Energy efficiency to reduce residential electricity and natural gas use under climate change.

PubMed

Reyna, Janet L; Chester, Mikhail V

2017-05-15

Climate change could significantly affect consumer demand for energy in buildings, as changing temperatures may alter heating and cooling loads. Warming climates could also lead to the increased adoption and use of cooling technologies in buildings. We assess residential electricity and natural gas demand in Los Angeles, California under multiple climate change projections and investigate the potential for energy efficiency to offset increased demand. We calibrate residential energy use against metered data, accounting for differences in building materials and appliances. Under temperature increases, we find that without policy intervention, residential electricity demand could increase by as much as 41-87% between 2020 and 2060. However, aggressive policies aimed at upgrading heating/cooling systems and appliances could result in electricity use increases as low as 28%, potentially avoiding the installation of new generation capacity. We therefore recommend aggressive energy efficiency, in combination with low-carbon generation sources, to offset projected increases in residential energy demand.

Energy efficiency to reduce residential electricity and natural gas use under climate change

NASA Astrophysics Data System (ADS)

Reyna, Janet L.; Chester, Mikhail V.

2017-05-01

Climate change could significantly affect consumer demand for energy in buildings, as changing temperatures may alter heating and cooling loads. Warming climates could also lead to the increased adoption and use of cooling technologies in buildings. We assess residential electricity and natural gas demand in Los Angeles, California under multiple climate change projections and investigate the potential for energy efficiency to offset increased demand. We calibrate residential energy use against metered data, accounting for differences in building materials and appliances. Under temperature increases, we find that without policy intervention, residential electricity demand could increase by as much as 41-87% between 2020 and 2060. However, aggressive policies aimed at upgrading heating/cooling systems and appliances could result in electricity use increases as low as 28%, potentially avoiding the installation of new generation capacity. We therefore recommend aggressive energy efficiency, in combination with low-carbon generation sources, to offset projected increases in residential energy demand.

The Potential of Combined Heat and Power Generation, Wind Power Generation and Load Management Techniques for Cost Reduction in Small Electricity Supply Systems.

NASA Astrophysics Data System (ADS)

Bass, Jeremy Hugh

Available from UMI in association with The British Library. Requires signed TDF. An evaluation is made of the potential fuel and financial savings possible when a small, autonomous diesel system sized to meet the demands of an individual, domestic consumer is adapted to include: (1) combined heat and power (CHP) generation, (2) wind turbine generation, (3) direct load control. The potential of these three areas is investigated by means of time-step simulation modelling on a microcomputer. Models are used to evaluate performance and a Net Present Value analysis used to assess costs. A cost/benefit analysis then enables those areas, or combination of areas, that facilitate and greatest savings to be identified. The modelling work is supported by experience gained from the following: (1) field study of the Lundy Island wind/diesel system, (2) laboratory testing of a small diesel generator set, (3) study of a diesel based CHP unit, (4) study of a diesel based direct load control system, (5) statistical analysis of data obtained from the long-term monitoring of a large number of individual household's electricity consumption. Rather than consider the consumer's electrical demand in isolation, a more flexible approach is adopted, with consumer demand being regarded as the sum of primarily two components: a small, electricity demand for essential services and a large, reschedulable demand for heating/cooling. The results of the study indicate that: (1) operating a diesel set in a CHP mode is the best strategy for both financial and fuel savings. A simple retrofit enables overall conversion efficiencies to be increased from 25% to 60%, or greater, at little cost. (2) wind turbine generation in association with direct load control is a most effective combination. (3) a combination of both the above areas enables greatest overall financial savings, in favourable winds resulting in unit energy costs around 20% of those of diesel only operation.

Optimizing Aggregation Scenarios for Integrating Renewable Energy into the U.S. Electric Grid

NASA Astrophysics Data System (ADS)

Corcoran, B. A.; Jacobson, M. Z.

2010-12-01

This study is an analysis of 2006 and 2007 electric load data, wind speed and solar irradiance data, and existing hydroelectric, geothermal, and other power plant data to quantify benefits of aggregating clean electric power from various Federal Energy Regulatory Commission (FERC) regions in the contiguous United States. First, various time series, statistics, and probability methods are applied to the electric load data to determine if there are any desirable demand-side results—specifically reducing variability and/or coincidence of peak events, which could reduce the amount of required carbon-based generators—in combining the electricity demands from geographically and temporally diverse areas. Second, an optimization algorithm is applied to determine the least-cost portfolio of energy resources to meet the electric load for a range of renewable portfolio standards (RPS’s) for each FERC region and for various aggregation scenarios. Finally, the installed capacities, ramp rates, standard deviation, and corresponding generator requirements from these optimization test runs are compared against the transmission requirements to determine the most economical organizational structure of the contiguous U.S. electric grid. Ideally, results from this study will help to justify and identify a possible structure of a federal RPS and offer insight into how to best organize regions for transmission planning.

Forecasting electricity usage using univariate time series models

NASA Astrophysics Data System (ADS)

Hock-Eam, Lim; Chee-Yin, Yip

2014-12-01

Electricity is one of the important energy sources. A sufficient supply of electricity is vital to support a country's development and growth. Due to the changing of socio-economic characteristics, increasing competition and deregulation of electricity supply industry, the electricity demand forecasting is even more important than before. It is imperative to evaluate and compare the predictive performance of various forecasting methods. This will provide further insights on the weakness and strengths of each method. In literature, there are mixed evidences on the best forecasting methods of electricity demand. This paper aims to compare the predictive performance of univariate time series models for forecasting the electricity demand using a monthly data of maximum electricity load in Malaysia from January 2003 to December 2013. Results reveal that the Box-Jenkins method produces the best out-of-sample predictive performance. On the other hand, Holt-Winters exponential smoothing method is a good forecasting method for in-sample predictive performance.

Resident Load Influence Analysis Method for Price Based on Non-intrusive Load Monitoring and Decomposition Data

NASA Astrophysics Data System (ADS)

Jiang, Wenqian; Zeng, Bo; Yang, Zhou; Li, Gang

2018-01-01

In the non-invasive load monitoring mode, the load decomposition can reflect the running state of each load, which will help the user reduce unnecessary energy costs. With the demand side management measures of time of using price, a resident load influence analysis method for time of using price (TOU) based on non-intrusive load monitoring data are proposed in the paper. Relying on the current signal of the resident load classification, the user equipment type, and different time series of self-elasticity and cross-elasticity of the situation could be obtained. Through the actual household load data test with the impact of TOU, part of the equipment will be transferred to the working hours, and users in the peak price of electricity has been reduced, and in the electricity at the time of the increase Electrical equipment, with a certain regularity.

Electricity Market Module - NEMS Documentation

EIA Publications

2017-01-01

Documents the Electricity Market Module as it was used for the Annual Energy Outlook. The Electricity Market Module (EMM) is the electricity supply component of the National Energy Modeling System (NEMS). The EMM represents the generation, transmission, and pricing of electricity. It consists of four submodules: the Electricity Capacity Planning (ECP) Submodule, the Electricity Fuel Dispatch (EFD) Submodule, the Electricity Finance and Pricing (EFP) Submodule, and the Electricity Load and Demand (ELD) Submodule.

75 FR 8895 - Basin Electric Power Cooperative: Deer Creek Station

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-26

.... The purpose of the proposed Project is to help serve increased load demand for electric power in the... Basin Electric Power Cooperative: Deer Creek Station AGENCY: Rural Utilities Service, USDA. ACTION...) and the Western Area Power Administration (Western) have issued a Draft Environmental Impact Statement...

Development and Simulation of Increased Generation on a Secondary Circuit of a Microgrid

NASA Astrophysics Data System (ADS)

Reyes, Karina

As fossil fuels are depleted and their environmental impacts remain, other sources of energy must be considered to generate power. Renewable sources, for example, are emerging to play a major role in this regard. In parallel, electric vehicle (EV) charging is evolving as a major load demand. To meet reliability and resiliency goals demanded by the electricity market, interest in microgrids are growing as a distributed energy resource (DER). In this thesis, the effects of intermittent renewable power generation and random EV charging on secondary microgrid circuits are analyzed in the presence of a controllable battery in order to characterize and better understand the dynamics associated with intermittent power production and random load demands in the context of the microgrid paradigm. For two reasons, a secondary circuit on the University of California, Irvine (UCI) Microgrid serves as the case study. First, the secondary circuit (UC-9) is heavily loaded and an integral component of a highly characterized and metered microgrid. Second, a unique "next-generation" distributed energy resource has been deployed at the end of the circuit that integrates photovoltaic power generation, battery storage, and EV charging. In order to analyze this system and evaluate the impact of the DER on the secondary circuit, a model was developed to provide a real-time load flow analysis. The research develops a power management system applicable to similarly integrated systems. The model is verified by metered data obtained from a network of high resolution electric meters and estimated load data for the buildings that have unknown demand. An increase in voltage is observed when the amount of photovoltaic power generation is increased. To mitigate this effect, a constant power factor is set. Should the real power change dramatically, the reactive power is changed to mitigate voltage fluctuations.

The Future of Low-Carbon Electricity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greenblatt, Jeffery B.; Brown, Nicholas R.; Slaybaugh, Rachel

Here, we review future global demand for electricity and major technologies positioned to supply itwith minimal greenhouse gas (GHG) emissions: renewables (wind, solar, water, geothermal and biomass), nuclear fission, and fossil power with CO 2 capture and sequestration. Two breakthrough technologies (space solar power and nuclear fusion) are discussed as exciting but uncertain additional options for low net GHG emissions (“low-carbon”) electricity generation. Grid integration technologies (monitoring and forecasting of transmission and distribution systems, demand-side load management, energy storage, and load balancing with low-carbon fuel substitutes) are also discussed. For each topic, recent historical trends and future prospects are reviewed,more » along with technical challenges, costs and other issues as appropriate. While no technology represents an ideal solution, their strengths can be enhanced by deployment in combination, along with grid integration that forms a critical set of enabling technologies to assure a reliable and robust future low-carbon electricity system.« less

The Future of Low-Carbon Electricity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greenblatt, Jeffery B.; Brown, Nicholas R.; Slaybaugh, Rachel

We review future global demand for electricity and major technologies positioned to supply it with minimal greenhouse gas (GHG) emissions: renewables (wind, solar, water, geothermal, and biomass), nuclear fission, and fossil power with CO2 capture and sequestration. We discuss two breakthrough technologies (space solar power and nuclear fusion) as exciting but uncertain additional options for low-net GHG emissions (i.e., low-carbon) electricity generation. In addition, we discuss grid integration technologies (monitoring and forecasting of transmission and distribution systems, demand-side load management, energy storage, and load balancing with low-carbon fuel substitutes). For each topic, recent historical trends and future prospects are reviewed,more » along with technical challenges, costs, and other issues as appropriate. Although no technology represents an ideal solution, their strengths can be enhanced by deployment in combination, along with grid integration that forms a critical set of enabling technologies to assure a reliable and robust future low-carbon electricity system.« less

The Future of Low-Carbon Electricity

DOE PAGES

Greenblatt, Jeffery B.; Brown, Nicholas R.; Slaybaugh, Rachel; ...

2017-07-10

Here, we review future global demand for electricity and major technologies positioned to supply itwith minimal greenhouse gas (GHG) emissions: renewables (wind, solar, water, geothermal and biomass), nuclear fission, and fossil power with CO 2 capture and sequestration. Two breakthrough technologies (space solar power and nuclear fusion) are discussed as exciting but uncertain additional options for low net GHG emissions (“low-carbon”) electricity generation. Grid integration technologies (monitoring and forecasting of transmission and distribution systems, demand-side load management, energy storage, and load balancing with low-carbon fuel substitutes) are also discussed. For each topic, recent historical trends and future prospects are reviewed,more » along with technical challenges, costs and other issues as appropriate. While no technology represents an ideal solution, their strengths can be enhanced by deployment in combination, along with grid integration that forms a critical set of enabling technologies to assure a reliable and robust future low-carbon electricity system.« less

Analysis and Representation of Miscellaneous Electric Loads in NEMS

EIA Publications

2017-01-01

Miscellaneous Electric Loads (MELs) comprise a growing portion of delivered energy consumption in residential and commercial buildings. Miscellaneous end uses—including televisions, personal computers, security systems, data center servers, and many other devices—have continued to penetrate into building-related market segments. Part of this proliferation of devices and equipment can be attributed to increased service demand for entertainment, computing, and convenience appliances.

Control of dispatch dynamics for lowering the cost of distributed generation in the built environment

NASA Astrophysics Data System (ADS)

Flores, Robert Joseph

Distributed generation can provide many benefits over traditional central generation such as increased reliability and efficiency while reducing emissions. Despite these potential benefits, distributed generation is generally not purchased unless it reduces energy costs. Economic dispatch strategies can be designed such that distributed generation technologies reduce overall facility energy costs. In this thesis, a microturbine generator is dispatched using different economic control strategies, reducing the cost of energy to the facility. Several industrial and commercial facilities are simulated using acquired electrical, heating, and cooling load data. Industrial and commercial utility rate structures are modeled after Southern California Edison and Southern California Gas Company tariffs and used to find energy costs for the simulated buildings and corresponding microturbine dispatch. Using these control strategies, building models, and utility rate models, a parametric study examining various generator characteristics is performed. An economic assessment of the distributed generation is then performed for both the microturbine generator and parametric study. Without the ability to export electricity to the grid, the economic value of distributed generation is limited to reducing the individual costs that make up the cost of energy for a building. Any economic dispatch strategy must be built to reduce these individual costs. While the ability of distributed generation to reduce cost depends of factors such as electrical efficiency and operations and maintenance cost, the building energy demand being serviced has a strong effect on cost reduction. Buildings with low load factors can accept distributed generation with higher operating costs (low electrical efficiency and/or high operations and maintenance cost) due to the value of demand reduction. As load factor increases, lower operating cost generators are desired due to a larger portion of the building load being met in an effort to reduce demand. In addition, buildings with large thermal demand have access to the least expensive natural gas, lowering the cost of operating distributed generation. Recovery of exhaust heat from DG reduces cost only if the buildings thermal demand coincides with the electrical demand. Capacity limits exist where annual savings from operation of distributed generation decrease if further generation is installed. For low operating cost generators, the approximate limit is the average building load. This limit decreases as operating costs increase. In addition, a high capital cost of distributed generation can be accepted if generator operating costs are low. As generator operating costs increase, capital cost must decrease if a positive economic performance is desired.

Optimization and Performance Study of Select Heating Ventilation and Air Conditioning Technologies for Commercial Buildings

NASA Astrophysics Data System (ADS)

Kamal, Rajeev

Buildings contribute a significant part to the electricity demand profile and peak demand for the electrical utilities. The addition of renewable energy generation adds additional variability and uncertainty to the power system. Demand side management in the buildings can help improve the demand profile for the utilities by shifting some of the demand from peak to off-peak times. Heating, ventilation and air-conditioning contribute around 45% to the overall demand of a building. This research studies two strategies for reducing the peak as well as shifting some demand from peak to off-peak periods in commercial buildings: 1. Use of gas heat pumps in place of electric heat pumps, and 2. Shifting demand for air conditioning from peak to off-peak by thermal energy storage in chilled water and ice. The first part of this study evaluates the field performance of gas engine-driven heat pumps (GEHP) tested in a commercial building in Florida. Four GEHP units of 8 Tons of Refrigeration (TR) capacity each providing air-conditioning to seven thermal zones in a commercial building, were instrumented for measuring their performance. The operation of these GEHPs was recorded for ten months, analyzed and compared with prior results reported in the literature. The instantaneous COPunit of these systems varied from 0.1 to 1.4 during typical summer week operation. The COP was low because the gas engines for the heat pumps were being used for loads that were much lower than design capacity which resulted in much lower efficiencies than expected. The performance of equivalent electric heat pump was simulated from a building energy model developed to mimic the measured building loads. An economic comparison of GEHPs and conventional electrical heat pumps was done based on the measured and simulated results. The average performance of the GEHP units was estimated to lie between those of EER-9.2 and EER-11.8 systems. The performance of GEHP systems suffers due to lower efficiency at part load operation. The study highlighted the need for optimum system sizing for GEHP/HVAC systems to meet the building load to obtain better performance in buildings. The second part of this study focusses on using chilled water or ice as thermal energy storage for shifting the air conditioning load from peak to off-peak in a commercial building. Thermal energy storage can play a very important role in providing demand-side management for diversifying the utility demand from buildings. Model of a large commercial office building is developed with thermal storage for cooling for peak power shifting. Three variations of the model were developed and analyzed for their performance with 1) ice storage, 2) chilled water storage with mixed storage tank and 3) chilled water storage with stratified tank, using EnergyPlus 8.5 software developed by the US Department of Energy. Operation strategy with tactical control to incorporate peak power schedule was developed using energy management system (EMS). The modeled HVAC system was optimized for minimum cost with the optimal storage capacity and chiller size using JEPlus. Based on the simulation, an optimal storage capacity of 40-45 GJ was estimated for the large office building model along with 40% smaller chiller capacity resulting in higher chiller part-load performance. Additionally, the auxiliary system like pump and condenser were also optimized to smaller capacities and thus resulting in less power demand during operation. The overall annual saving potential was found in the range of 7-10% for cooling electricity use resulting in 10-17% reduction in costs to the consumer. A possible annual peak shifting of 25-78% was found from the simulation results after comparing with the reference models. Adopting TES in commercial buildings and achieving 25% peak shifting could result in a reduction in peak summer demand of 1398 MW in Tampa.

An electrical betweenness approach for vulnerability assessment of power grids considering the capacity of generators and load

NASA Astrophysics Data System (ADS)

Wang, Kai; Zhang, Bu-han; Zhang, Zhe; Yin, Xiang-gen; Wang, Bo

2011-11-01

Most existing research on the vulnerability of power grids based on complex networks ignores the electrical characteristics and the capacity of generators and load. In this paper, the electrical betweenness is defined by considering the maximal demand of load and the capacity of generators in power grids. The loss of load, which reflects the ability of power grids to provide sufficient power to customers, is introduced to measure the vulnerability together with the size of the largest cluster. The simulation results of the IEEE-118 bus system and the Central China Power Grid show that the cumulative distributions of node electrical betweenness follow a power-law and that the nodes with high electrical betweenness play critical roles in both topological structure and power transmission of power grids. The results prove that the model proposed in this paper is effective for analyzing the vulnerability of power grids.

The Demand Reduction Potential of Smart Appliances in U.S. Homes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Makhmalbaf, Atefe; Srivastava, Viraj; Parker, Graham B.

The widespread deployment of demand respond (DR) enabled home appliances is expected to have significant reduction in the demand of electricity during peak hours. The work documented in this paper focuses on estimating the energy shift resulting from the installation of DR enabled smart appliances in the U.S. This estimation is based on analyzing the market for smart appliances and calculating the total energy demand that can potentially be shifted by DR control in appliances. Appliance operation is examined by considering their sub components individually to identify their energy consumptions and savings resulting from interrupting and shifting their load, e.g.,more » by delaying the refrigerator defrost cycle. In addition to major residential appliances, residential pool pumps are also included in this study given their energy consumption profiles that make them favorable for DR applications. In the market analysis study documented in this paper, the U.S. Energy Information Administration's (EIA) Residential Energy Consumption Survey (RECS) and National Association of Home Builders (NAHB) databases are used to examine the expected life of an appliance, the number of appliances installed in homes constructed in 10 year intervals after 1940 and home owner income. Conclusions about the effectiveness of the smart appliances in reducing electrical demand have been drawn and a ranking of appliances in terms of their contribution to load shift is presented. E.g., it was concluded that DR enabled water heaters result in the maximum load shift; whereas, dishwashers have the highest user elasticity and hence the highest potential for load shifting through DR. This work is part of a larger effort to bring novel home energy management concepts and technologies to reduce energy consumption, reduce peak electricity demand, integrate renewables and storage technology, and change homeowner behavior to manage and consume less energy and potentially save consumer energy costs.« less

The design of optimal electric power demand management contracts

NASA Astrophysics Data System (ADS)

Fahrioglu, Murat

1999-11-01

Our society derives a quantifiable benefit from electric power. In particular, forced outages or blackouts have enormous consequences on society, one of which is loss of economic surplus. Electric utilities try to provide reliable supply of electric power to their customers. Maximum customer benefit derives from minimum cost and sufficient supply availability. Customers willing to share in "availability risk" can derive further benefit by participating in controlled outage programs. Specifically, whenever utilities foresee dangerous loading patterns, there is a need for a rapid reduction in demand either system-wide or at specific locations. The utility needs to get relief in order to solve its problems quickly and efficiently. This relief can come from customers who agree to curtail their loads upon request in exchange for an incentive fee. This thesis shows how utilities can get efficient load relief while maximizing their economic benefit. This work also shows how estimated customer cost functions can be calibrated, using existing utility data, to help in designing efficient demand management contracts. In order to design such contracts, optimal mechanism design is adopted from "Game Theory" and applied to the interaction between a utility and its customers. The idea behind mechanism design is to design an incentive structure that encourages customers to sign up for the right contract and reveal their true value of power. If a utility has demand management contracts with customers at critical locations, most operational problems can be solved efficiently. This thesis illustrates how locational attributes of customers incorporated into demand management contract design can have a significant impact in solving system problems. This kind of demand management contracts can also be used by an Independent System Operator (ISO). During times of congestion a loss of economic surplus occurs. When the market is too slow or cannot help relieve congestion, demand management can help solve the problem. Another tool the ISO requires for security purposes is reserves. Even though demand management contracts may not be a good substitute for spinning reserves, they are adequate to augment or replace supplemental and backup reserves.

Opportunities for Automated Demand Response in California Wastewater Treatment Facilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aghajanzadeh, Arian; Wray, Craig; McKane, Aimee

Previous research over a period of six years has identified wastewater treatment facilities as good candidates for demand response (DR), automated demand response (Auto-­DR), and Energy Efficiency (EE) measures. This report summarizes that work, including the characteristics of wastewater treatment facilities, the nature of the wastewater stream, energy used and demand, as well as details of the wastewater treatment process. It also discusses control systems and automated demand response opportunities. Furthermore, this report summarizes the DR potential of three wastewater treatment facilities. In particular, Lawrence Berkeley National Laboratory (LBNL) has collected data at these facilities from control systems, submetered processmore » equipment, utility electricity demand records, and governmental weather stations. The collected data were then used to generate a summary of wastewater power demand, factors affecting that demand, and demand response capabilities. These case studies show that facilities that have implemented energy efficiency measures and that have centralized control systems are well suited to shed or shift electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. In summary, municipal wastewater treatment energy demand in California is large, and energy-­intensive equipment offers significant potential for automated demand response. In particular, large load reductions were achieved by targeting effluent pumps and centrifuges. One of the limiting factors to implementing demand response is the reaction of effluent turbidity to reduced aeration at an earlier stage of the process. Another limiting factor is that cogeneration capabilities of municipal facilities, including existing power purchase agreements and utility receptiveness to purchasing electricity from cogeneration facilities, limit a facility’s potential to participate in other DR activities.« less

Electric power supply and demand for the contiguous United States, 1981 - 1990

NASA Astrophysics Data System (ADS)

1981-07-01

The outlook for electric power supply and demand in the United States decade 1981 to 1990 is reviewed from the perspective of reliability and adequacy of service. Electric power supply adequacy as projected for the nine Regional Reliability Council areas of the contiguous United States is reported as well as interruptible load data reported by the Councils. cogeneration is discussed. Each of the 27 electric regions (sub-areas of the nine Council areas) in the contiguous US are studied. A glossary of terms is given. Appendices describe the Council structure, and include a copy of the ERA-411 Manual, which contains all the items to which the Councils were asked to respond. The utilities with included data, the Staff Report, Estimated Electric Demand and Supply for Summer 1981, Contiguous United States dated May 1981 are included.

The potential of magneto-electric nanocarriers for drug delivery

PubMed Central

Kaushik, Ajeet; Jayant, Rahul Dev; Sagar, Vidya; Nair, Madhavan

2015-01-01

Introduction The development and design of personalized nanomedicine for better health quality is receiving great attention. In order to deliver and release a therapeutic concentration at the target site, novel nanocarriers (NCs) were designed, for example, magneto-electric (ME) which possess ideal properties of high drug loading, site-specificity and precise on-demand controlled drug delivery. Areas covered This review explores the potential of ME-NCs for on-demand and site-specific drug delivery and release for personalized therapeutics. The main features including effect of magnetism, improvement in drug loading, drug transport across blood-brain barriers and on-demand controlled release are also discussed. The future directions and possible impacts on upcoming nanomedicine are highlighted. Expert opinion Numerous reports suggest that there is an urgent need to explore novel NC formulations for safe and targeted drug delivery and release at specific disease sites. The challenges of formulation lie in the development of NCs that improve biocompatibility and surface modifications for optimum drug loading/preservation/transmigration and tailoring of electrical–magnetic properties for on-demand drug release. Thus, the development of novel NCs is anticipated to overcome the problems of targeted delivery of therapeutic agents with desired precision that may lead to better patient compliance. PMID:24986772

Energy efficiency to reduce residential electricity and natural gas use under climate change

PubMed Central

Reyna, Janet L.; Chester, Mikhail V.

2017-01-01

Climate change could significantly affect consumer demand for energy in buildings, as changing temperatures may alter heating and cooling loads. Warming climates could also lead to the increased adoption and use of cooling technologies in buildings. We assess residential electricity and natural gas demand in Los Angeles, California under multiple climate change projections and investigate the potential for energy efficiency to offset increased demand. We calibrate residential energy use against metered data, accounting for differences in building materials and appliances. Under temperature increases, we find that without policy intervention, residential electricity demand could increase by as much as 41–87% between 2020 and 2060. However, aggressive policies aimed at upgrading heating/cooling systems and appliances could result in electricity use increases as low as 28%, potentially avoiding the installation of new generation capacity. We therefore recommend aggressive energy efficiency, in combination with low-carbon generation sources, to offset projected increases in residential energy demand. PMID:28504255

DOE Office of Scientific and Technical Information (OSTI.GOV)

Konis, Kyle; Orosz, Michael; Sintov, Nicole

Competition-based “energy saving” interventions are increasingly promoted as an effective strategy for reducing energy consumption in buildings with large occupant controlled electrical loads. However, the factors that drive energy savings in such interventions are not well understood, nor are the impacts of short-term competitions on long-term energy performance. A total of 39 8-occupant suites in a freshman residence hall were instrumented with “smart” electric meters, which recorded circuit-level electricity consumption at 15-minute intervals. During a three-week Fall 2014 competition, suites competed to reduce their overall electricity demand and achieved a 6.4% reduction in whole-building demand overall and a 12% reductionmore » during hours of peak demand (from 12:00 to 19:00), despite peak seasonal temperatures and all-time record electricity demand. Analysis incorporating weather-normalized HVAC demand after the competition showed a significant “rebound” for a large portion of the suites (19), however 12 suites made further reductions, and the remainder maintained demand at the competition level. As a result, we compared energy data with self-reported survey data and identified self-efficacy beliefs, pro-environmental behaviors, and sense of affiliation with other residents of the hall as key factors distinguishing the suites with the greatest and most persistent reductions in demand from suites that maintained or increased demand.« less

Optimal Operation of Data Centers in Future Smart Grid

NASA Astrophysics Data System (ADS)

Ghamkhari, Seyed Mahdi

The emergence of cloud computing has established a growing trend towards building massive, energy-hungry, and geographically distributed data centers. Due to their enormous energy consumption, data centers are expected to have major impact on the electric grid by significantly increasing the load at locations where they are built. However, data centers also provide opportunities to help the grid with respect to robustness and load balancing. For instance, as data centers are major and yet flexible electric loads, they can be proper candidates to offer ancillary services, such as voluntary load reduction, to the smart grid. Also, data centers may better stabilize the price of energy in the electricity markets, and at the same time reduce their electricity cost by exploiting the diversity in the price of electricity in the day-ahead and real-time electricity markets. In this thesis, such potentials are investigated within an analytical profit maximization framework by developing new mathematical models based on queuing theory. The proposed models capture the trade-off between quality-of-service and power consumption in data centers. They are not only accurate, but also they posses convexity characteristics that facilitate joint optimization of data centers' service rates, demand levels and demand bids to different electricity markets. The analysis is further expanded to also develop a unified comprehensive energy portfolio optimization for data centers in the future smart grid. Specifically, it is shown how utilizing one energy option may affect selecting other energy options that are available to a data center. For example, we will show that the use of on-site storage and the deployment of geographical workload distribution can particularly help data centers in utilizing high-risk energy options such as renewable generation. The analytical approach in this thesis takes into account service-level-agreements, risk management constraints, and also the statistical characteristics of the Internet workload and the electricity prices. Using empirical data, the performance of our proposed profit maximization models for data centers are evaluated, and the capability of data centers to benefit from participation in a variety of Demand Response programs is assessed.

Assessment of Optimal Flexibility in Ensemble of Frequency Responsive Loads

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kundu, Soumya; Hansen, Jacob; Lian, Jianming

2018-04-19

Potential of electrical loads in providing grid ancillary services is often limited due to the uncertainties associated with the load behavior. A knowledge of the expected uncertainties with a load control program would invariably yield to better informed control policies, opening up the possibility of extracting the maximal load control potential without affecting grid operations. In the context of frequency responsive load control, a probabilistic uncertainty analysis framework is presented to quantify the expected error between the target and actual load response, under uncertainties in the load dynamics. A closed-form expression of an optimal demand flexibility, minimizing the expected errormore » in actual and committed flexibility, is provided. Analytical results are validated through Monte Carlo simulations of ensembles of electric water heaters.« less

Solar + Storage Synergies for Managing Commercial-Customer Demand Charges

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gagnon, P.; Govindarajan, A.; Bird, L.

Demand charges, which are based on a customer’s maximum demand in kilowatts (kW), are a common element of electricity rate structures for commercial customers. Customer-sited solar photovoltaic (PV) systems can potentially reduce demand charges, but the level of savings is difficult to predict, given variations in demand charge designs, customer loads, and PV generation profiles. Lawrence Berkeley National Laboratory (Berkeley Lab) and the National Renewable Energy Laboratory (NREL) are collaborating on a series of studies to understand how solar PV can impact demand charges. Prior studies in the series examined demand charge reductions from solar on a stand-alone basis formore » residential and commercial customers. Those earlier analyses found that solar, alone, has limited ability to reduce demand charges depending on the specific design of the demand charge and on the shape of the customer’s load profile. This latest analysis estimates demand charge savings from solar in commercial buildings when co-deployed with behind-the-meter storage, highlighting the complementary roles of the two technologies. The analysis is based on simulated loads, solar generation, and storage dispatch across a wide variety of building types, locations, system configurations, and demand charge designs.« less

Impact of Rate Design Alternatives on Residential Solar Customer Bills. Increased Fixed Charges, Minimum Bills and Demand-based Rates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bird, Lori; Davidson, Carolyn; McLaren, Joyce

With rapid growth in energy efficiency and distributed generation, electric utilities are anticipating stagnant or decreasing electricity sales, particularly in the residential sector. Utilities are increasingly considering alternative rates structures that are designed to recover fixed costs from residential solar photovoltaic (PV) customers with low net electricity consumption. Proposed structures have included fixed charge increases, minimum bills, and increasingly, demand rates - for net metered customers and all customers. This study examines the electricity bill implications of various residential rate alternatives for multiple locations within the United States. For the locations analyzed, the results suggest that residential PV customers offset,more » on average, between 60% and 99% of their annual load. However, roughly 65% of a typical customer's electricity demand is non-coincidental with PV generation, so the typical PV customer is generally highly reliant on the grid for pooling services.« less

Optimal scheduling and its Lyapunov stability for advanced load-following energy plants with CO 2 capture

DOE PAGES

Bankole, Temitayo; Jones, Dustin; Bhattacharyya, Debangsu; ...

2017-11-03

In this study, a two-level control methodology consisting of an upper-level scheduler and a lower-level supervisory controller is proposed for an advanced load-following energy plant with CO 2 capture. With the use of an economic objective function that considers fluctuation in electricity demand and price at the upper level, optimal scheduling of energy plant electricity production and carbon capture with respect to several carbon tax scenarios is implemented. The optimal operational profiles are then passed down to corresponding lower-level supervisory controllers designed using a methodological approach that balances control complexity with performance. Finally, it is shown how optimal carbon capturemore » and electricity production rate profiles for an energy plant such as the integrated gasification combined cycle (IGCC) plant are affected by electricity demand and price fluctuations under different carbon tax scenarios. As a result, the paper also presents a Lyapunov stability analysis of the proposed scheme.« less

Optimal scheduling and its Lyapunov stability for advanced load-following energy plants with CO 2 capture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bankole, Temitayo; Jones, Dustin; Bhattacharyya, Debangsu

In this study, a two-level control methodology consisting of an upper-level scheduler and a lower-level supervisory controller is proposed for an advanced load-following energy plant with CO 2 capture. With the use of an economic objective function that considers fluctuation in electricity demand and price at the upper level, optimal scheduling of energy plant electricity production and carbon capture with respect to several carbon tax scenarios is implemented. The optimal operational profiles are then passed down to corresponding lower-level supervisory controllers designed using a methodological approach that balances control complexity with performance. Finally, it is shown how optimal carbon capturemore » and electricity production rate profiles for an energy plant such as the integrated gasification combined cycle (IGCC) plant are affected by electricity demand and price fluctuations under different carbon tax scenarios. As a result, the paper also presents a Lyapunov stability analysis of the proposed scheme.« less

"Watts per person" paradigm to design net zero energy buildings: Examining technology interventions and integrating occupant feedback to reduce plug loads in a commercial building

NASA Astrophysics Data System (ADS)

Yagi Kim, Mika

As building envelopes have improved due to more restrictive energy codes, internal loads have increased largely due to the proliferation of computers, electronics, appliances, imaging and audio visual equipment that continues to grow in commercial buildings. As the dependency on the internet for information and data transfer increases, the electricity demand will pose a challenge to design and operate Net Zero Energy Buildings (NZEBs). Plug Loads (PLs) as a proportion of the building load has become the largest non-regulated building energy load and represents the third highest electricity end-use in California's commercial office buildings, accounting for 23% of the total building electricity consumption (Ecova 2011,2). In the Annual Energy Outlook 2008 (AEO2008), prepared by the Energy Information Administration (EIA) that presents long-term projections of energy supply and demand through 2030 states that office equipment and personal computers are the "fastest growing electrical end uses" in the commercial sector. This thesis entitled "Watts Per Person" Paradigm to Design Net Zero Energy Buildings, measures the implementation of advanced controls and behavioral interventions to study the reduction of PL energy use in the commercial sector. By integrating real world data extracted from an energy efficient commercial building of its energy use, the results produce a new methodology on estimating PL energy use by calculating based on "Watts Per Person" and analyzes computational simulation methods to design NZEBs.

On the integration of wind and solar energy to provide a total energy supply in the USA

NASA Astrophysics Data System (ADS)

Archer, Cristina; Mills, David; Cheng, Weili; Sloggy, Matthew; Liebig, Edwin; Rhoades, Alan

2010-05-01

This study examines the feasibility of using renewable energy - mostly wind and solar radiation - as the primary source of energy in the USA, under the assumption that a nationwide electric transmission grid is in place. Previous studies have shown that solar or wind alone can power the present U.S. grid on average. Other studies have shown that solar output from California and Texas using energy storage is well correlated with the state energy load on an hour by hour basis throughout the year and with the U.S. national load on a monthly basis. This study explores scenarios for use of wind and solar energy together at the national scale on an hour by hour basis to determine if such a combination is a better match to national seasonal load scenarios than either of the two alone on an hour-by-hour basis. Actual hour by hour national load data from the year 2006 are used as a basis, with some scenarios incorporating vehicle sector electrification and building heating and cooling using electric heat pumps. Hourly wind speed data were calculated at the hub height of 80 m above the ground for the year 2006 at over 150 windy locations in the continental U.S. using an extrapolation technique based on 10-m wind speed measurements and vertical sounding profiles. Using a 1.5 MW wind turbine as benchmark, the hourly wind power production nationwide was determined at all suitable locations. Similarly, the hourly output from solar plants, with and without thermal storage, was calculated based on Ausra's model assuming that the solar production would occur in the Southwest, the area with the greatest solar radiation density in the U.S. Hourly electricity demand for the year 2006 was obtained nationwide from a variety of sources, including the Federal Energy Regulation Commission. Hourly residential heating and cooking, industrial heat processing, and future electrified transportation loads were calculated from monthly and yearly energy consumption data from the Energy Information Administration. Using different scenarios of wind power penetration (between 10% and 120% of the average national electricity and/or energy demand), the remaining hourly electricity and/or energy load was covered by solar thermal electricity produced via the Ausra's innovative linear reflective system, with various amounts of storage. With a 20% redundancy (i.e., an average production of 120% of the demand), a match of ~98% for electric load and ~96% for total energy load were found for the 60%wind-60%solar combination and with 12-hr storage. Work is continuing on improving that match through more sophisticated storage usage strategies and by looking at other options for the few days in the year for which wind and solar might be insufficient.

Generalized Aggregation and Coordination of Residential Loads in a Smart Community

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hao, He; Somani, Abhishek; Lian, Jianming

2015-11-02

Flexibility from residential loads presents an enormous potential to provide various services to the smart grid. In this paper, we propose a unified hierarchical framework for aggregation and coordination of various residential loads in a smart community, such as Thermostatically Controlled Loads (TCLs), Distributed Energy Storages (DESs), residential Pool Pumps (PPs), and Electric Vehicles (EVs). A central idea of this framework is a virtual battery model, which provides a simple and intuitive tool to aggregate the flexibility of distributed loads. Moreover, a multi-stage Nash-bargainingbased coordination strategy is proposed to coordinate different aggregations of residential loads for demand response. Case studiesmore » are provided to demonstrate the efficacy of our proposed framework and coordination strategy in managing peak power demand in a smart residential community.« less

Battery resource assessment. Battery demands scenarios materials

NASA Astrophysics Data System (ADS)

Sullivan, D.

1980-12-01

Projections of demand for batteries and battery materials between 1980 and 2000 are presented. The estimates are based on existing predictions for the future of the electric vehicle, photovoltaic, utility load-leveling, and existing battery industry. Battery demand was first computed as kilowatt-hours of storage for various types of batteries. Using estimates for the materials required for each battery, the maximum demand that could be expected for each battery material was determined.

Impact of the electric compressor for automotive air conditioning system on fuel consumption and performance analysis

NASA Astrophysics Data System (ADS)

Zulkifli, A. A.; Dahlan, A. A.; Zulkifli, A. H.; Nasution, H.; Aziz, A. A.; Perang, M. R. M.; Jamil, H. M.; Misseri, M. N.

2015-12-01

Air conditioning system is the biggest auxiliary load in a vehicle where the compressor consumed the largest. Problem with conventional compressor is the cooling capacity cannot be control directly to fulfill the demand of thermal load inside vehicle cabin. This study is conducted experimentally to analyze the difference of fuel usage and air conditioning performance between conventional compressor and electric compressor of the air conditioning system in automobile. The electric compressor is powered by the car battery in non-electric vehicle which the alternator will recharge the battery. The car is setup on a roller dynamometer and the vehicle speed is varied at 0, 30, 60, 90 and 110 km/h at cabin temperature of 25°C and internal heat load of 100 and 400 Watt. The results shows electric compressor has better fuel consumption and coefficient of performance compared to the conventional compressor.

Analysis of stationary fuel cell dynamic ramping capabilities and ultra capacitor energy storage using high resolution demand data

NASA Astrophysics Data System (ADS)

Meacham, James R.; Jabbari, Faryar; Brouwer, Jacob; Mauzey, Josh L.; Samuelsen, G. Scott

Current high temperature fuel cell (HTFC) systems used for stationary power applications (in the 200-300 kW size range) have very limited dynamic load following capability or are simply base load devices. Considering the economics of existing electric utility rate structures, there is little incentive to increase HTFC ramping capability beyond 1 kWs -1 (0.4% s -1). However, in order to ease concerns about grid instabilities from utility companies and increase market adoption, HTFC systems will have to increase their ramping abilities, and will likely have to incorporate electrical energy storage (EES). Because batteries have low power densities and limited lifetimes in highly cyclic applications, ultra capacitors may be the EES medium of choice. The current analyses show that, because ultra capacitors have a very low energy storage density, their integration with HTFC systems may not be feasible unless the fuel cell has a ramp rate approaching 10 kWs -1 (4% s -1) when using a worst-case design analysis. This requirement for fast dynamic load response characteristics can be reduced to 1 kWs -1 by utilizing high resolution demand data to properly size ultra capacitor systems and through demand management techniques that reduce load volatility.

Thermal Energy Storage for Electricity Peak-demand Mitigation: A Solution in Developing and Developed World Alike

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeForest, Nicholas; Mendes, Goncalo; Stadler, Michael

2013-06-02

In much of the developed world, air-conditioning in buildings is the dominant driver of summer peak electricity demand. In the developing world a steadily increasing utilization of air-conditioning places additional strain on already-congested grids. This common thread represents a large and growing threat to the reliable delivery of electricity around the world, requiring capital-intensive expansion of capacity and draining available investment resources. Thermal energy storage (TES), in the form of ice or chilled water, may be one of the few technologies currently capable of mitigating this problem cost effectively and at scale. The installation of TES capacity allows a buildingmore » to meet its on-peak air conditioning load without interruption using electricity purchased off-peak and operating with improved thermodynamic efficiency. In this way, TES has the potential to fundamentally alter consumption dynamics and reduce impacts of air conditioning. This investigation presents a simulation study of a large office building in four distinct geographical contexts: Miami, Lisbon, Shanghai, and Mumbai. The optimization tool DER-CAM (Distributed Energy Resources Customer Adoption Model) is applied to optimally size TES systems for each location. Summer load profiles are investigated to assess the effectiveness and consistency in reducing peak electricity demand. Additionally, annual energy requirements are used to determine system cost feasibility, payback periods and customer savings under local utility tariffs.« less

Peak load demand forecasting using two-level discrete wavelet decomposition and neural network algorithm

NASA Astrophysics Data System (ADS)

Bunnoon, Pituk; Chalermyanont, Kusumal; Limsakul, Chusak

2010-02-01

This paper proposed the discrete transform and neural network algorithms to obtain the monthly peak load demand in mid term load forecasting. The mother wavelet daubechies2 (db2) is employed to decomposed, high pass filter and low pass filter signals from the original signal before using feed forward back propagation neural network to determine the forecasting results. The historical data records in 1997-2007 of Electricity Generating Authority of Thailand (EGAT) is used as reference. In this study, historical information of peak load demand(MW), mean temperature(Tmean), consumer price index (CPI), and industrial index (economic:IDI) are used as feature inputs of the network. The experimental results show that the Mean Absolute Percentage Error (MAPE) is approximately 4.32%. This forecasting results can be used for fuel planning and unit commitment of the power system in the future.

Electricity by intermittent sources: An analysis based on the German situation 2012

NASA Astrophysics Data System (ADS)

Wagner, Friedrich

2014-02-01

The 2012 data of the German load, the on- and offshore and the photo-voltaic energy production are used and scaled to the limit of supplying the annual demand (100% case). The reference mix of the renewable energy (RE) forms is selected such that the remaining back-up energy is minimised. For the 100% case, the RE power installation has to be about 3 times the present peak load. The back-up system can be reduced by 12% in this case. The surplus energy corresponds to 26% of the demand. The back-up system and more so the grid must be able to cope with large power excursions. All components of the electricity supply system operate at low capacity factors. Large-scale storage can hardly be motivated by the effort to further reduce CO2 emission. Demand-side management will intensify the present periods of high economic activities. Its rigorous implementation will expand the economic activities into the weekends. On the basis of a simple criterion, the increase of periods with negative electricity prices in Germany is assessed. It will be difficult with RE to meet the low CO2 emission factors which characterise those European Countries which produce electricity mostly by nuclear and hydro power.

Commercial equipment loads: End-Use Load and Consumer Assessment Program (ELCAP)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pratt, R.G.; Williamson, M.A.; Richman, E.E.

1990-07-01

The Office of Energy Resources of the Bonneville Power Administration is generally responsible for the agency's power and conservation resource planning. As associated responsibility which supports a variety of office functions is the analysis of historical trends in and determinants of energy consumption. The Office of Energy Resources' End-Use Research Section operates a comprehensive data collection program to provide pertinent information to support demand-side planning, load forecasting, and demand-side program development and delivery. Part of this on-going program is known as the End-Use Load and Consumer Assessment Program (ELCAP), an effort designed to collect electricity usage data through direct monitoringmore » of end-use loads in buildings. This program is conducted for Bonneville by the Pacific Northwest Laboratory. This report provides detailed information on electricity consumption of miscellaneous equipment from the commercial portion of ELCAP. Miscellaneous equipment includes all commercial end-uses except heating, ventilating, air conditioning, and central lighting systems. Some examples of end-uses covered in this report are office equipment, computers, task lighting, refrigeration, and food preparation. Electricity consumption estimates, in kilowatt-hours per square food per year, are provided for each end-use by building type. The following types of buildings are covered: office, retail, restaurant, grocery, warehouse, school, university, and hotel/motel. 6 refs., 35 figs., 12 tabs.« less

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

For nearly a century, global power systems have focused on three key functions: generating, transmitting, and distributing electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load-despite variability in load on time scales ranging from subsecond disturbances to multiyear trends. With the increasing role of variable generation from wind and solar, the retirement of fossil-fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

David Palchak | NREL

Science.gov Websites

Electrical load forecasting with artificial neural networks Demand-side management optimization with Matlab -58491. D. Palchak, S. Suryanarayanan, and D. Zimmerle. "An Artificial Neural Network in Short-Term

ELECTRICAL LOAD ANTICIPATOR AND RECORDER

DOEpatents

Werme, J.E.

1961-09-01

A system is described in which an indication of the prevailing energy consumption in an electrical power metering system and a projected power demand for one demand in terval is provided at selected increments of time within the demand interval. Each watt-hour meter in the system is provided with an impulse generator that generates two impulses for each revolution of the meter disc. In each demand interval, for example, one half-hour, of the metering system, the total impulses received from all of the meters are continuously totaled for each 5-minute interval and multiplied by a number from 6 to 1 depending upon which 5- minute interval the impulses were received. This value is added to the total pulses received in the intervals preceding the current 5-minute interval within the half-hour demand interval tc thereby provide an indication of the projected power demand every 5 minutes in the demand interval.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marks, Gary; Wilcox, Edmund; Olsen, Daniel

California agricultural irrigation consumes more than ten billion kilowatt hours of electricity annually and has significant potential for contributing to a reduction of stress on the grid through demand response, permanent load shifting, and energy efficiency measures. To understand this potential, a scoping study was initiated for the purpose of determining the associated opportunities, potential, and adoption challenges in California agricultural irrigation. The primary research for this study was conducted in two ways. First, data was gathered and parsed from published sources that shed light on where the best opportunities for load shifting and demand response lie within the agriculturalmore » irrigation sector. Secondly, a small limited survey was conducted as informal face-to-face interviews with several different California growers to get an idea of their ability and willingness to participate in permanent load shifting and/or demand response programs. Analysis of the data obtained from published sources and the survey reveal demand response and permanent load shifting opportunities by growing region, irrigation source, irrigation method, grower size, and utility coverage. The study examines some solutions for demand response and permanent load shifting in agricultural irrigation, which include adequate irrigation system capacity, automatic controls, variable frequency drives, and the contribution from energy efficiency measures. The study further examines the potential and challenges for grower acceptance of demand response and permanent load shifting in California agricultural irrigation. As part of the examination, the study considers to what extent permanent load shifting, which is already somewhat accepted within the agricultural sector, mitigates the need or benefit of demand response for agricultural irrigation. Recommendations for further study include studies on how to gain grower acceptance of demand response as well as other related studies such as conducting a more comprehensive survey of California growers.« less

Refrigerated Warehouse Demand Response Strategy Guide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scott, Doug; Castillo, Rafael; Larson, Kyle

This guide summarizes demand response measures that can be implemented in refrigerated warehouses. In an appendix, it also addresses related energy efficiency opportunities. Reducing overall grid demand during peak periods and energy consumption has benefits for facility operators, grid operators, utility companies, and society. State wide demand response potential for the refrigerated warehouse sector in California is estimated to be over 22.1 Megawatts. Two categories of demand response strategies are described in this guide: load shifting and load shedding. Load shifting can be accomplished via pre-cooling, capacity limiting, and battery charger load management. Load shedding can be achieved by lightingmore » reduction, demand defrost and defrost termination, infiltration reduction, and shutting down miscellaneous equipment. Estimation of the costs and benefits of demand response participation yields simple payback periods of 2-4 years. To improve demand response performance, it’s suggested to install air curtains and another form of infiltration barrier, such as a rollup door, for the passageways. Further modifications to increase efficiency of the refrigeration unit are also analyzed. A larger condenser can maintain the minimum saturated condensing temperature (SCT) for more hours of the day. Lowering the SCT reduces the compressor lift, which results in an overall increase in refrigeration system capacity and energy efficiency. Another way of saving energy in refrigerated warehouses is eliminating the use of under-floor resistance heaters. A more energy efficient alternative to resistance heaters is to utilize the heat that is being rejected from the condenser through a heat exchanger. These energy efficiency measures improve efficiency either by reducing the required electric energy input for the refrigeration system, by helping to curtail the refrigeration load on the system, or by reducing both the load and required energy input.« less

Residential Simulation Tool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Starke, Michael R; Abdelaziz, Omar A; Jackson, Rogerick K

Residential Simulation Tool was developed to understand the impact of residential load consumption on utilities including the role of demand response. This is complicated as many different residential loads exist and are utilized for different purposes. The tool models human behavior and contributes this to load utilization, which contributes to the electrical consumption prediction by the tool. The tool integrates a number of different databases from Department of Energy and other Government websites to support the load consumption prediction.

Study on probability distribution of prices in electricity market: A case study of zhejiang province, china

NASA Astrophysics Data System (ADS)

Zhou, H.; Chen, B.; Han, Z. X.; Zhang, F. Q.

2009-05-01

The study on probability density function and distribution function of electricity prices contributes to the power suppliers and purchasers to estimate their own management accurately, and helps the regulator monitor the periods deviating from normal distribution. Based on the assumption of normal distribution load and non-linear characteristic of the aggregate supply curve, this paper has derived the distribution of electricity prices as the function of random variable of load. The conclusion has been validated with the electricity price data of Zhejiang market. The results show that electricity prices obey normal distribution approximately only when supply-demand relationship is loose, whereas the prices deviate from normal distribution and present strong right-skewness characteristic. Finally, the real electricity markets also display the narrow-peak characteristic when undersupply occurs.

Performance Assessment of Flashed Steam Geothermal Power Plant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alt, Theodore E.

1980-12-01

Five years of operating experience at the Comision Federal de Electricidad (CFE) Cerro Prieto flashed steam geothermal power plant are evaluated from the perspective of U. S. utility operations. We focus on the design and maintenance of the power plant that led to the achievement of high plant capacity factors for Units No. 1 and 2 since commercial operation began in 1973. For this study, plant capacity factor is the ratio of the average load on the machines or equipment for the period of time considered to the capacity rating of the machines or equipment. The plant capacity factor ismore » the annual gross output in GWh compared to 657 GWh (2 x 37.5 MW x 8760 h). The CFE operates Cerro Prieto at base load consistent with the system connected electrical demand of the Baja California Division. The plant output was curtailed during the winter months of 1973-1975 when the system electric demand was less than the combined output capability of Cerro Prieto and the fossil fuel plant near Tijuana. Each year the system electric demand has increased and the Cerro Prieto units now operate at full load all the time. The CFE added Units 3 and 4 to Cerro Prieto in 1979 which increased the plant name plate capacity to 150 MW. Part of this additional capacity will supply power to San Diego Gas and Electric Company through an interconnection across the border. The achievement of a high capacity factor over an extensive operating period was influenced by operation, design, and maintenance of the geothermal flash steam power plant.« less

Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lekov, Alex; Thompson, Lisa; McKane, Aimee

2009-05-11

This report summarizes the Lawrence Berkeley National Laboratory's research to date in characterizing energy efficiency and open automated demand response opportunities for industrial refrigerated warehouses in California. The report describes refrigerated warehouses characteristics, energy use and demand, and control systems. It also discusses energy efficiency and open automated demand response opportunities and provides analysis results from three demand response studies. In addition, several energy efficiency, load management, and demand response case studies are provided for refrigerated warehouses. This study shows that refrigerated warehouses can be excellent candidates for open automated demand response and that facilities which have implemented energy efficiencymore » measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for open automated demand response (OpenADR) at little additional cost. These improved controls may prepare facilities to be more receptive to OpenADR due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.« less

Simulation of demand management and grid balancing with electric vehicles

NASA Astrophysics Data System (ADS)

Druitt, James; Früh, Wolf-Gerrit

2012-10-01

This study investigates the potential role of electric vehicles in an electricity network with a high contribution from variable generation such as wind power. Electric vehicles are modelled to provide demand management through flexible charging requirements and energy balancing for the network. Balancing applications include both demand balancing and vehicle-to-grid discharging. This study is configured to represent the UK grid with balancing requirements derived from wind generation calculated from weather station wind speeds on the supply side and National Grid data from on the demand side. The simulation models 1000 individual vehicle entities to represent the behaviour of larger numbers of vehicles. A stochastic trip generation profile is used to generate realistic journey characteristics, whilst a market pricing model allows charging and balancing decisions to be based on realistic market price conditions. The simulation has been tested with wind generation capacities representing up to 30% of UK consumption. Results show significant improvements to load following conditions with the introduction of electric vehicles, suggesting that they could substantially facilitate the uptake of intermittent renewable generation. Electric vehicle owners would benefit from flexible charging and selling tariffs, with the majority of revenue derived from vehicle-to-grid participation in balancing markets.

40 CFR 1065.110 - Work inputs and outputs, accessory work, and operator demand.

Code of Federal Regulations, 2013 CFR

2013-07-01

...-current and water-brake dynamometers for any testing that does not involve engine motoring, which is... resistor load bank to simulate electrical loads. (3) Pump, compressor, and turbine work. Use pumps, compressors, and turbines that are of the type and capacity installed in use. Use working fluids that are of...

40 CFR 1065.110 - Work inputs and outputs, accessory work, and operator demand.

Code of Federal Regulations, 2014 CFR

2014-07-01

...-current and water-brake dynamometers for any testing that does not involve engine motoring, which is... resistor load bank to simulate electrical loads. (3) Pump, compressor, and turbine work. Use pumps, compressors, and turbines that are of the type and capacity installed in use. Use working fluids that are of...

40 CFR 1065.110 - Work inputs and outputs, accessory work, and operator demand.

Code of Federal Regulations, 2012 CFR

2012-07-01

...-current and water-brake dynamometers for any testing that does not involve engine motoring, which is... resistor load bank to simulate electrical loads. (3) Pump, compressor, and turbine work. Use pumps, compressors, and turbines that are of the type and capacity installed in use. Use working fluids that are of...

40 CFR 1065.110 - Work inputs and outputs, accessory work, and operator demand.

Code of Federal Regulations, 2011 CFR

2011-07-01

...-current and water-brake dynamometers for any testing that does not involve engine motoring, which is... resistor load bank to simulate electrical loads. (3) Pump, compressor, and turbine work. Use pumps, compressors, and turbines that are of the type and capacity installed in use. Use working fluids that are of...

40 CFR 1065.110 - Work inputs and outputs, accessory work, and operator demand.

Code of Federal Regulations, 2010 CFR

2010-07-01

...-current and water-brake dynamometers for any testing that does not involve engine motoring, which is... resistor load bank to simulate electrical loads. (3) Pump, compressor, and turbine work. Use pumps, compressors, and turbines that are of the type and capacity installed in use. Use working fluids that are of...

Field Experience with and Potential for Multi-time Scale Grid Transactions from Responsive Commercial Buildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Piette, Mary Ann; Kiliccote, Sila; Ghatikar, Girish

2014-08-01

The need for and concepts behind demand response are evolving. As the electric system changes with more intermittent renewable electric supply systems, there is a need to allow buildings to provide more flexible demand. This paper presents results from field studies and pilots, as well as engineering estimates of the potential capabilities of fast load responsiveness in commercial buildings. We present a sector wide analysis of flexible loads in commercial buildings, which was conducted to improve resource planning and determine which loads to evaluate in future demonstrations. These systems provide important capabilities for future transactional systems. The field analysis ismore » based on results from California, plus projects in the northwest and east coast. End-uses considered include heating, ventilation, air conditioning and lighting. The timescales of control include day-ahead, as well as day-of, 10-minute ahead and even faster response. This technology can provide DR signals on different times scales to interact with responsive building loads. We describe the latency of the control systems in the building and the round trip communications with the wholesale grid operators.« less

Three empirical essays on energy and labor economics

NASA Astrophysics Data System (ADS)

Chow, Melissa

This dissertation analyzes the differences between private and non-private firms in two contexts. Chapters 1 and 2 examine the electricity industry in the United States and the motivation behind electric utilities' usage of demand side management programs. The first chapter focuses on load management programs, which decrease electricity demand during the peak hours of the day. It looks into the impact of a plausibly exogenous decrease in natural gas prices on the utilization and capacity of these programs. The second chapter analyzes the relationship between electricity market deregulation and electric utilities' energy efficiency activity. The third chapter investigates the impact of Chinese enterprise restructuring on employment, wage bills, and productivity. All three chapters show that different objectives due to ownership type lead to differences in firm behavior.

A window into occupant-driven energy outcomes: Leveraging sub-metering infrastructure to examine psychosocial factors driving long-term outcomes of short-term competition-based energy interventions

DOE PAGES

Konis, Kyle; Orosz, Michael; Sintov, Nicole

2016-01-07

Competition-based “energy saving” interventions are increasingly promoted as an effective strategy for reducing energy consumption in buildings with large occupant controlled electrical loads. However, the factors that drive energy savings in such interventions are not well understood, nor are the impacts of short-term competitions on long-term energy performance. A total of 39 8-occupant suites in a freshman residence hall were instrumented with “smart” electric meters, which recorded circuit-level electricity consumption at 15-minute intervals. During a three-week Fall 2014 competition, suites competed to reduce their overall electricity demand and achieved a 6.4% reduction in whole-building demand overall and a 12% reductionmore » during hours of peak demand (from 12:00 to 19:00), despite peak seasonal temperatures and all-time record electricity demand. Analysis incorporating weather-normalized HVAC demand after the competition showed a significant “rebound” for a large portion of the suites (19), however 12 suites made further reductions, and the remainder maintained demand at the competition level. As a result, we compared energy data with self-reported survey data and identified self-efficacy beliefs, pro-environmental behaviors, and sense of affiliation with other residents of the hall as key factors distinguishing the suites with the greatest and most persistent reductions in demand from suites that maintained or increased demand.« less

Opportunities for Open Automated Demand Response in Wastewater Treatment Facilities in California - Phase II Report. San Luis Rey Wastewater Treatment Plant Case Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, Lisa; Lekov, Alex; McKane, Aimee

2010-08-20

This case study enhances the understanding of open automated demand response opportunities in municipal wastewater treatment facilities. The report summarizes the findings of a 100 day submetering project at the San Luis Rey Wastewater Treatment Plant, a municipal wastewater treatment facility in Oceanside, California. The report reveals that key energy-intensive equipment such as pumps and centrifuges can be targeted for large load reductions. Demand response tests on the effluent pumps resulted a 300 kW load reduction and tests on centrifuges resulted in a 40 kW load reduction. Although tests on the facility?s blowers resulted in peak period load reductions ofmore » 78 kW sharp, short-lived increases in the turbidity of the wastewater effluent were experienced within 24 hours of the test. The results of these tests, which were conducted on blowers without variable speed drive capability, would not be acceptable and warrant further study. This study finds that wastewater treatment facilities have significant open automated demand response potential. However, limiting factors to implementing demand response are the reaction of effluent turbidity to reduced aeration load, along with the cogeneration capabilities of municipal facilities, including existing power purchase agreements and utility receptiveness to purchasing electricity from cogeneration facilities.« less

Optimal Scheduling Method of Controllable Loads in DC Smart Apartment Building

NASA Astrophysics Data System (ADS)

Shimoji, Tsubasa; Tahara, Hayato; Matayoshi, Hidehito; Yona, Atsushi; Senjyu, Tomonobu

2015-12-01

From the perspective of global warming suppression and the depletion of energy resources, renewable energies, such as the solar collector (SC) and photovoltaic generation (PV), have been gaining attention in worldwide. Houses or buildings with PV and heat pumps (HPs) are recently being used in residential areas widely due to the time of use (TOU) electricity pricing scheme which is essentially inexpensive during middle-night and expensive during day-time. If fixed batteries and electric vehicles (EVs) can be introduced in the premises, the electricity cost would be even more reduced. While, if the occupants arbitrarily use these controllable loads respectively, power demand in residential buildings may fluctuate in the future. Thus, an optimal operation of controllable loads such as HPs, batteries and EV should be scheduled in the buildings in order to prevent power flow from fluctuating rapidly. This paper proposes an optimal scheduling method of controllable loads, and the purpose is not only the minimization of electricity cost for the consumers, but also suppression of fluctuation of power flow on the power supply side. Furthermore, a novel electricity pricing scheme is also suggested in this paper.

Charge scheduling of an energy storage system under time-of-use pricing and a demand charge.

PubMed

Yoon, Yourim; Kim, Yong-Hyuk

2014-01-01

A real-coded genetic algorithm is used to schedule the charging of an energy storage system (ESS), operated in tandem with renewable power by an electricity consumer who is subject to time-of-use pricing and a demand charge. Simulations based on load and generation profiles of typical residential customers show that an ESS scheduled by our algorithm can reduce electricity costs by approximately 17%, compared to a system without an ESS and by 8% compared to a scheduling algorithm based on net power.

Charge Scheduling of an Energy Storage System under Time-of-Use Pricing and a Demand Charge

PubMed Central

Yoon, Yourim

2014-01-01

A real-coded genetic algorithm is used to schedule the charging of an energy storage system (ESS), operated in tandem with renewable power by an electricity consumer who is subject to time-of-use pricing and a demand charge. Simulations based on load and generation profiles of typical residential customers show that an ESS scheduled by our algorithm can reduce electricity costs by approximately 17%, compared to a system without an ESS and by 8% compared to a scheduling algorithm based on net power. PMID:25197720

The building loads analysis system thermodynamics (BLAST) program, Version 2. 0: input booklet. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sowell, E.

1979-06-01

The Building Loads Analysis and System Thermodynamics (BLAST) program is a comprehensive set of subprograms for predicting energy consumption in buildings. There are three major subprograms: (1) the space load predicting subprogram, which computes hourly space loads in a building or zone based on user input and hourly weather data; (2) the air distribution system simulation subprogram, which uses the computed space load and user inputs describing the building air-handling system to calculate hot water or steam, chilled water, and electric energy demands; and (3) the central plant simulation program, which simulates boilers, chillers, onsite power generating equipment and solarmore » energy systems and computes monthly and annual fuel and electrical power consumption and plant life cycle cost.« less

Last Mile Asset Monitoring; Low Cost Rapid Deployment Asset Monitoring

NASA Astrophysics Data System (ADS)

Zumr, Zdenek

Installation and utilization of residential distribution transformers has not changed substantially over a long period of time. Utilities typically size their transformers based on a formula that takes into account broadly what types and how many dwellings will be connected. Most new residential dwellings feature 200 Amp service per household with an anticipated energy demand of under 20,000 kWh per year. Average electrical energy consumption varies from state to state but averages to 11,280 kWh per year. Energy demand is expected to fall into a typical residential load curve that shows increased demand early in the morning, then decreasing during the day and another peak early to late evening. Distribution transformers are sized at the limit of the combined evening peak with the assumption that the transformer has enough thermal mass to absorb short overloads that may occur when concurrent loading situations among multiple dwellings arise. The assumption that concurrent loading is of short duration and the transformer can cool off during the night time has been validated over the years and has become standard practice. This has worked well when dwelling loads follow an averaging scheme and low level of coincidence. With the arrival of electric vehicles (EV's) this assumption has to be reevaluated. The acquisition of an electric vehicle in a household can drive up energy demand by over 4000 kWh per year. Potentially problematic is the increased capacity of battery packs and the resulting proliferation of Level 2 chargers. The additional load of a single Level 2 charger concurring with the combined evening peak load will push even conservatively sized distribution transformers over their nameplate rating for a substantial amount of time. Additionally, unlike common household appliances of similar power requirements such as ovens or water heaters, a Level 2 battery charger will run at peak power consumption for several hours, and the current drawn by the EVs has very high levels of harmonic distortion. The excessive loading and harmonic profile can potentially result in damaging heat build-up resulting in asset degradation. In this thesis I present a device and method that monitors pole mounted distribution transformers for overheating, collect and wirelessly upload data and initiate commands to chargers to change output levels from Level 2 to Level 1 or shut down EV charging altogether until the transformer returns into safe operational range.

Vulnerability of the US western electric grid to hydro-climatological conditions: How bad can it get?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Voisin, N.; Kintner-Meyer, M.; Skaggs, R.

Recent studies have highlighted the potential impact of climate change on US electricity generation capacity by exploring the effect of changes in stream temperatures on available capacity of thermo-electric plants that rely on fresh-water cooling. However, little is known about the electric system impacts under extreme climate event such as drought. Vulnerability assessments are usually performed for a baseline water year or a specific drought, which do not provide insights into the full grid stress distribution across the diversity of climate events. In this paper we estimate the impacts of the water availability on the electricity generation and transmission inmore » the Western US grid for a range of historical water availability combinations. We softly couple an integrated water model, which includes climate, hydrology, routing, water resources management and socio-economic water demand models, into a grid model (production cost model) and simulate 30 years of historical hourly power flow conditions in the Western US grid. The experiment allows estimating the grid stress distribution as a function of inter-annual variability in regional water availability. Results indicate a clear correlation between grid vulnerability (as quantified in unmet energy demand and increased production cost) for the summer month of August and annual water availability. There is a 3% chance that at least 6% of the electricity demand cannot be met in August, and 21% chance of not meeting 0.5% of the load in the Western US grid. There is a 3% chance that at least 6% of the electricity demand cannot be met in August, and 21% chance of not meeting 0.1% or more of the load in the Western US grid. The regional variability in water availability contributes significantly to the reliability of the grid and could provide trade off opportunities in times of stress. This paper is the first to explore operational grid impacts imposed by droughts in the Western U.S. grid.« less

Small Business Voucher CRADA Report: Natural Gas Powered HVAC System for Commercial and Residential Buildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Betts, Daniel; Ally, Moonis Raza; Mudiraj, Shyam

Be Power Tech is commercializing BeCool, the first integrated electricity-producing heating, ventilation, and air conditioning (HVAC) system using a non-vapor compression cycle (VCC), packaged rooftop HVAC unit that also produces base-load electricity, heating, ventilation, and air conditioning. BeCool is a distributed energy resource with energy storage that eliminates the tremendous peak electricity demand associated with commonly used electricity-powered vapor compression air conditioning systems.

Residential load management system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Uhr, C.W.

1986-03-01

The MAX load management system marketed by the UHR Corporation is described. The system completely replaces conventional heating, cooling, and hot water equipment. It is designed to reduce significantly the home's peak demand during the electric utility's system-wide peak load periods while at the same time maintain the homeowner's comfort. The integration of microprocessor, thermal storage, and heat pump technologies allows for broad flexibility in terms of tailoring the system to a specific electric utility's needs. Twelve pilot systems installed in Northern Virginia outside of Washington, DC have been operational since early 1985. The test results to date have confirmedmore » both the system's load management capability and its comfort improvement characteristics. The fundamental characteristics and hardware for the system are described. 9 figures.« less

Tunable actuation of dielectric elastomer by electromechanical loading rates

NASA Astrophysics Data System (ADS)

Li, Guorui; Zhang, Mingqi; Chen, Xiangping; Yang, Xuxu; Wong, Tuck-Whye; Li, Tiefeng; Huang, Zhilong

2017-10-01

Dielectric elastomer (DE) membranes are able to self-deform with the application of an electric field through the thickness direction. In comparison to conventional rigid counterparts, soft actuators using DE provide a variety of advantages such as high compliance, low noise, and light weight. As one of the challenges in the development of DE actuating devices, tuning the electromechanical actuating behavior is crucial in order to achieve demanded loading paths and to avoid electromechanical failures. In this paper, our experimental results show that the electromechanical loading conditions affect the actuating behaviors of the DE. The electrical actuating force can be tuned by 29.4% with the control of the electrical charging rate. In addition, controllable actuations have been investigated by the mechanical model in manipulating the electromechanical loading rate. The calculated results agree well with the experimental data. Lastly, it is believed that the mechanisms of controlling the electromechanical loading rate may serve as a guide for the design of DE devices and high performance soft robots in the near future.

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

For nearly a century, global power systems have focused on three key functions: to generate, transmit, and distribute electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load, despite variability in load on timescales ranging from sub-second disturbances to multi-year trends. With the increasing role of variable generation from wind and solar, retirements of fossil fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

DOE PAGES

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

2017-10-17

For nearly a century, global power systems have focused on three key functions: to generate, transmit, and distribute electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load, despite variability in load on timescales ranging from sub-second disturbances to multi-year trends. With the increasing role of variable generation from wind and solar, retirements of fossil fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

Optimal load scheduling in commercial and residential microgrids

NASA Astrophysics Data System (ADS)

Ganji Tanha, Mohammad Mahdi

Residential and commercial electricity customers use more than two third of the total energy consumed in the United States, representing a significant resource of demand response. Price-based demand response, which is in response to changes in electricity prices, represents the adjustments in load through optimal load scheduling (OLS). In this study, an efficient model for OLS is developed for residential and commercial microgrids which include aggregated loads in single-units and communal loads. Single unit loads which include fixed, adjustable and shiftable loads are controllable by the unit occupants. Communal loads which include pool pumps, elevators and central heating/cooling systems are shared among the units. In order to optimally schedule residential and commercial loads, a community-based optimal load scheduling (CBOLS) is proposed in this thesis. The CBOLS schedule considers hourly market prices, occupants' comfort level, and microgrid operation constraints. The CBOLS' objective in residential and commercial microgrids is the constrained minimization of the total cost of supplying the aggregator load, defined as the microgrid load minus the microgrid generation. This problem is represented by a large-scale mixed-integer optimization for supplying single-unit and communal loads. The Lagrangian relaxation methodology is used to relax the linking communal load constraint and decompose the independent single-unit functions into subproblems which can be solved in parallel. The optimal solution is acceptable if the aggregator load limit and the duality gap are within the bounds. If any of the proposed criteria is not satisfied, the Lagrangian multiplier will be updated and a new optimal load schedule will be regenerated until both constraints are satisfied. The proposed method is applied to several case studies and the results are presented for the Galvin Center load on the 16th floor of the IIT Tower in Chicago.

Reducing Demand Charges and Onsite Generation Variability Using Behind-the-Meter Energy Storage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhattarai, Bishnu P.; Myers, Kurt S.; Bush, Jason W.

Electric utilities in the United States are increasingly employing demand charges and/or real-time pricing. This directive is bringing potential opportunities in deploying behindthe-meter energy storage (BMES) systems for various grid functionalities. This study quantifies techno-economic benefits of BMES in reducing demand charge and smoothing load/generation intermittencies, and determines how those benefits vary with onsite distributed photovoltaic. We proposed a two-stage control algorithm, whereby the first stage proactively determines costoptimal BMES configuration for reducing peak-demands and demand charges, and the second stage adaptively compensates intermittent generations and short load spikes that may otherwise increase the demand charges. The performance of themore » proposed algorithm is evaluated through a 24 hours time sweep simulation performed using data from smart microgrid testbed at Idaho National Laboratory (INL). The simulation results demonstrated that this research provides a simple but effective solution for peak shaving, demand charge reductions, and smoothing onsite PV variability.« less

A future Demand Side Management (DSM) opportunity for utility as variable renewable penetrate scale up using agriculture.

NASA Astrophysics Data System (ADS)

Ines, A.; Bhattacharjee, A.; Modi, V.; Robertson, A. W.; Lall, U.; Kocaman Ayse, S.; Chaudhary, S.; Kumar, A.; Ganapathy, A.; Kumar, A.; Mishra, V.

2015-12-01

Energy demand management, also known as demand side management (DSM), is the modification of consumer demand for energy through various methods such as smart metering, incentive based schemes, payments for turning off loads or rescheduling loads. Usually, the goal of demand side management is to encourage the consumer to use less power during periods of peak demand, or to move the time of energy use to off-peak times. Peak demand management does not necessarily decrease total energy consumption, but could be expected to reduce the need for investments in networks and/or power plants for meeting peak demands. Electricity use can vary dramatically on short and medium time frames, and the pricing system may not reflect the instantaneous cost as additional higher-cost that are brought on-line. In addition, the capacity or willingness of electricity consumers to adjust to prices by altering elasticity of demand may be low, particularly over short time frames. In the scenario of Indian grid setup, the retail customers do not follow real-time pricing and it is difficult to incentivize the utility companies for continuing the peak demand supply. A question for the future is how deeper penetration of renewable will be handled? This is a challenging problem since one has to deal with high variability, while managing loss of load probabilities. In the case of managing the peak demand using agriculture, in the future as smart metering matures with automatic turn on/off for a pump, it will become possible to provide an ensured amount of water or energy to the farmer while keeping the grid energized for 24 hours. Supply scenarios will include the possibility of much larger penetration of solar and wind into the grid. While, in absolute terms these sources are small contributors, their role will inevitably grow but DSM using agriculture could help reduce the capital cost. The other option is of advancing or delaying pump operating cycle even by several hours, will still ensure soil moisture requirements met while, balancing the overall system load with generation, reducing critical power mismatches. Through this presentation the author will describe different techniques and results from field experiments in India.

Design and Development of a Residential Gas-Fired Heat Pump

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vineyard, Edward Allan; Abu-Heiba, Ahmad; Mahderekal, Dr. Isaac

2017-01-01

Heating, ventilating, and air-conditioning equipment consumes 43% of the total primary energy consumption in U.S. households. Presently, conventional gas furnaces have maximum heating efficiencies of 98%. Electric air conditioners used in association with the furnace for cooling have a minimum seasonal energy efficiency ratio (SEER) of 14.0. A residential gas-fired heat pump (RGHP) was developed and tested under standard rating conditions, resulting in a significant increase in heating efficiency of over 40% versus conventional natural gas furnaces. The associated efficiency of the RGHP in cooling mode is comparable in efficiency to an electric air conditioner (14.0 SEER) when compared onmore » a primary energy basis. The RGHP is similar in nature to a conventional heat pump but with two main differences. First, the primary energy savings are higher, based on a site versus source comparison, as the result of using natural gas to supply shaft power to the compressor rather than an electric motor. Second, waste heat is recovered from the engine to supplement space heating and reduce the energy input. It can also be used to provide supplemental water heating. The system utilizes a programmable logic controller that allows variable-speed operation to achieve improved control to meet building loads. RGHPs significantly reduce peak electric use during periods of high demand, especially peak summer loads, as well as peak winter loads in regions with widespread use of electric heating. This contributes to leveling year-round gas loads, with the potential to increase annual gas demand in some regions. The widespread adoption of RGHPs will contribute to significant reductions in primary energy consumption and carbon emissions through improved efficiencies.« less

Development of an Advanced Grid-Connected PV-ECS System Considering Solar Energy Estimation

NASA Astrophysics Data System (ADS)

Rahman, Md. Habibur; Yamashiro, Susumu; Nakamura, Koichi

In this paper, the development and the performance of a viable distributed grid-connected power generation system of Photovoltaic-Energy Capacitor System (PV-ECS) considering solar energy estimation have been described. Instead of conventional battery Electric Double Layer Capacitors (EDLC) are used as storage device and Photovoltaic (PV) panel to generate power from solar energy. The system can generate power by PV, store energy when the demand of load is low and finally supply the stored energy to load during the period of peak demand. To realize the load leveling function properly the system will also buy power from grid line when load demand is high. Since, the power taken from grid line depends on the PV output power, a procedure has been suggested to estimate the PV output power by calculating solar radiation. In order to set the optimum value of the buy power, a simulation program has also been developed. Performance of the system has been studied for different load patterns in different weather conditions by using the estimated PV output power with the help of the simulation program.

Low cost electronic ultracapacitor interface technique to provide load leveling of a battery for pulsed load or motor traction drive applications

DOEpatents

King, Robert Dean; DeDoncker, Rik Wivina Anna Adelson

1998-01-01

A battery load leveling arrangement for an electrically powered system in which battery loading is subject to intermittent high current loading utilizes a passive energy storage device and a diode connected in series with the storage device to conduct current from the storage device to the load when current demand forces a drop in battery voltage. A current limiting circuit is connected in parallel with the diode for recharging the passive energy storage device. The current limiting circuit functions to limit the average magnitude of recharge current supplied to the storage device. Various forms of current limiting circuits are disclosed, including a PTC resistor coupled in parallel with a fixed resistor. The current limit circuit may also include an SCR for switching regenerative braking current to the device when the system is connected to power an electric motor.

An electric vehicle propulsion system's impact on battery performance: An overview

NASA Technical Reports Server (NTRS)

Bozek, J. M.; Smithrick, J. J.; Cataldo, R. C.; Ewashinka, J. G.

1980-01-01

The performance of two types of batteries, lead-acid and nickel-zinc, was measured as a function of the charging and discharging demands anticipated from electric vehicle propulsion systems. The benefits of rapid high current charging were mixed: although it allowed quick charges, the energy efficiency was reduced. For low power (overnight) charging the current wave shapes delivered by the charger to the battery tended to have no effect on the battery cycle life. The use of chopper speed controllers with series traction motors resulted in a significant reduction in the energy available from a battery whenever the motor operates at part load. The demand placed on a battery by an electric vehicle propulsion system containing electrical regenerative braking confirmed significant improvment in short term performance of the battery.

Climate change and peak demand for electricity: Evaluating policies for reducing peak demand under different climate change scenarios

NASA Astrophysics Data System (ADS)

Anthony, Abigail Walker

This research focuses on the relative advantages and disadvantages of using price-based and quantity-based controls for electricity markets. It also presents a detailed analysis of one specific approach to quantity based controls: the SmartAC program implemented in Stockton, California. Finally, the research forecasts electricity demand under various climate scenarios, and estimates potential cost savings that could result from a direct quantity control program over the next 50 years in each scenario. The traditional approach to dealing with the problem of peak demand for electricity is to invest in a large stock of excess capital that is rarely used, thereby greatly increasing production costs. Because this approach has proved so expensive, there has been a focus on identifying alternative approaches for dealing with peak demand problems. This research focuses on two approaches: price based approaches, such as real time pricing, and quantity based approaches, whereby the utility directly controls at least some elements of electricity used by consumers. This research suggests that well-designed policies for reducing peak demand might include both price and quantity controls. In theory, sufficiently high peak prices occurring during periods of peak demand and/or low supply can cause the quantity of electricity demanded to decline until demand is in balance with system capacity, potentially reducing the total amount of generation capacity needed to meet demand and helping meet electricity demand at the lowest cost. However, consumers need to be well informed about real-time prices for the pricing strategy to work as well as theory suggests. While this might be an appropriate assumption for large industrial and commercial users who have potentially large economic incentives, there is not yet enough research on whether households will fully understand and respond to real-time prices. Thus, while real-time pricing can be an effective tool for addressing the peak load problems, pricing approaches are not well suited to ensure system reliability. This research shows that direct quantity controls are better suited for avoiding catastrophic failure that results when demand exceeds supply capacity.

Operational experience and performance characteristics of a valve-regulated lead-acid battery energy-storage system for providing the customer with critical load protection and energy-management benefits at a lead-recycling plant

NASA Astrophysics Data System (ADS)

Hunt, G. W.

The Power Control Division of GNB Technologies, commissioned on May 13, 1996 a new facility which houses a 5-MW battery energy-storage system (BESS) at GNB's Lead Recycling Centre in Vernon, CA. When the plant loses utility power (which typically happens two or three times a year), the BESS will provide up to 5 MW of power at 4160 VAC in support of all the plant loads. Since the critical loads are not isolated, it is necessary to carry the entire plant load (maximum of 5 MVA) for a short period immediately following an incident until non-critical loads have been automatically shed. Plant loading typically peaks at 3.5 MVA with critical loads of about 2.1 MVA. The BESS also provides the manufacturing plant with customer-side-of-the-meter energy management options to reduce its energy demand during peak periods of the day. The BESS has provided a reduction in monthly electric bills through daily peak-shaving. By design, the battery can provide up to 2.5 MWh of energy and still retain 2.5 MWh of capacity in reserve to handle the possibility of a power outage in protecting the critical loads for up to 1 h. By storing energy from the utility during off-peak hours of the night in the batteries when the cost is low (US4.5¢ per kWh), GNB can then discharge this energy during high demand periods of the day (US14.50 per kW). For example, by reducing its peak demand by 300 kW, the lead-recycling centre can save over US4000 per month in its electric bills. The BESS at Vernon represents a first large-scale use of valve-regulated lead-acid batteries in such a demanding application. This paper presents a summary of the operational experience and performance characteristics of the BESS over the past 2 years.

Demand Response Resource Quantification with Detailed Building Energy Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hale, Elaine; Horsey, Henry; Merket, Noel

Demand response is a broad suite of technologies that enables changes in electrical load operations in support of power system reliability and efficiency. Although demand response is not a new concept, there is new appetite for comprehensively evaluating its technical potential in the context of renewable energy integration. The complexity of demand response makes this task difficult -- we present new methods for capturing the heterogeneity of potential responses from buildings, their time-varying nature, and metrics such as thermal comfort that help quantify likely acceptability of specific demand response actions. Computed with an automated software framework, the methods are scalable.

Climate Change Impacts on Peak Electricity Consumption: US vs. Europe.

NASA Astrophysics Data System (ADS)

Auffhammer, M.

2016-12-01

It has been suggested that climate change impacts on the electric sector will account for the majority of global economic damages by the end of the current century and beyond. This finding is at odds with the relatively modest increase in climate driven impacts on consumption. Comprehensive high frequency load balancing authority level data have not been used previously to parameterize the relationship between electric demand and temperature for any major economy. Using statistical models we analyze multi-year data from load balancing authorities in the United States of America and the European Union, which are responsible for more than 90% of the electricity delivered to residential, industrial, commercial and agricultural customers. We couple the estimated response functions between total daily consumption and daily peak load with an ensemble of downscaled GCMs from the CMIP5 archive to simulate climate change driven impacts on both outcomes. We show moderate and highly spatially heterogeneous changes in consumption. The results of our peak load simulations, however, suggest significant changes in the intensity and frequency of peak events throughout the United States and Europe. As the electricity grid is built to endure maximum load, which usually occurs on the hottest day of the year, our findings have significant implications for the construction of costly peak generating and transmission capacity.

Short-term forecasting of individual household electricity loads with investigating impact of data resolution and forecast horizon

NASA Astrophysics Data System (ADS)

Yildiz, Baran; Bilbao, Jose I.; Dore, Jonathon; Sproul, Alistair B.

2018-05-01

Smart grid components such as smart home and battery energy management systems, high penetration of renewable energy systems, and demand response activities, require accurate electricity demand forecasts for the successful operation of the electricity distribution networks. For example, in order to optimize residential PV generation and electricity consumption and plan battery charge-discharge regimes by scheduling household appliances, forecasts need to target and be tailored to individual household electricity loads. The recent uptake of smart meters allows easier access to electricity readings at very fine resolutions; hence, it is possible to utilize this source of available data to create forecast models. In this paper, models which predominantly use smart meter data alongside with weather variables, or smart meter based models (SMBM), are implemented to forecast individual household loads. Well-known machine learning models such as artificial neural networks (ANN), support vector machines (SVM) and Least-Square SVM are implemented within the SMBM framework and their performance is compared. The analysed household stock consists of 14 households from the state of New South Wales, Australia, with at least a year worth of 5 min. resolution data. In order for the results to be comparable between different households, our study first investigates household load profiles according to their volatility and reveals the relationship between load standard deviation and forecast performance. The analysis extends previous research by evaluating forecasts over four different data resolution; 5, 15, 30 and 60 min, each resolution analysed for four different horizons; 1, 6, 12 and 24 h ahead. Both, data resolution and forecast horizon, proved to have significant impact on the forecast performance and the obtained results provide important insights for the operation of various smart grid applications. Finally, it is shown that the load profile of some households vary significantly across different days; as a result, providing a single model for the entire period may result in limited performance. By the use of a pre-clustering step, similar daily load profiles are grouped together according to their standard deviation, and instead of applying one SMBM for the entire data-set of a particular household, separate SMBMs are applied to each one of the clusters. This preliminary clustering step increases the complexity of the analysis however it results in significant improvements in forecast performance.

The equal load-sharing model of cascade failures in power grids

NASA Astrophysics Data System (ADS)

Scala, Antonio; De Sanctis Lucentini, Pier Giorgio

2016-11-01

Electric power-systems are one of the most important critical infrastructures. In recent years, they have been exposed to extreme stress due to the increasing power demand, the introduction of distributed renewable energy sources, and the development of extensive interconnections. We investigate the phenomenon of abrupt breakdown of an electric power-system under two scenarios: load growth (mimicking the ever-increasing customer demand) and power fluctuations (mimicking the effects of renewable sources). Our results indicate that increasing the system size causes breakdowns to become more abrupt; in fact, mapping the system to a solvable statistical-physics model indicates the occurrence of a first order transition in the large size limit. Such an enhancement for the systemic risk failures (black-outs) with increasing network size is an effect that should be considered in the current projects aiming to integrate national power-grids into ;super-grids;.

Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lekov, Alex; Thompson, Lisa; McKane, Aimee

This report summarizes the Lawrence Berkeley National Laboratory?s research to date in characterizing energy efficiency and automated demand response opportunities for wastewater treatment facilities in California. The report describes the characteristics of wastewater treatment facilities, the nature of the wastewater stream, energy use and demand, as well as details of the wastewater treatment process. It also discusses control systems and energy efficiency and automated demand response opportunities. In addition, several energy efficiency and load management case studies are provided for wastewater treatment facilities.This study shows that wastewater treatment facilities can be excellent candidates for open automated demand response and thatmore » facilities which have implemented energy efficiency measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for automated demand response at little additional cost. These improved controls may prepare facilities to be more receptive to open automated demand response due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.« less

Solar Heating And Cooling Of Buildings (SHACOB): Requirements definition and impact analysis-2. Volume 3: Customer load management systems

NASA Astrophysics Data System (ADS)

Cretcher, C. K.; Rountredd, R. C.

1980-11-01

Customer Load Management Systems, using off-peak storage and control at the residences, are analyzed to determine their potential for capacity and energy savings by the electric utility. Areas broadly representative of utilities in the regions around Washington, DC and Albuquerque, NM were of interest. Near optimum tank volumes were determined for both service areas, and charging duration/off-time were identified as having the greatest influence on tank performance. The impacts on utility operations and corresponding utility/customer economics were determined in terms of delta demands used to estimate the utilities' generating capacity differences between the conventional load management, (CLM) direct solar with load management (DSLM), and electric resistive systems. Energy differences are also determined. These capacity and energy deltas are translated into changes in utility costs due to penetration of the CLM or DSLM systems into electric resistive markets in the snapshot years of 1990 and 2000.

Impacts of Various Characteristics of Electricity and Heat Demand on the Optimal Configuration of a Microgrid

NASA Astrophysics Data System (ADS)

Bando, Shigeru; Watanabe, Hiroki; Asano, Hiroshi; Tsujita, Shinsuke

A methodology was developed to design the number and capacity for each piece of equipment (e.g. gas engines, batteries, thermal storage tanks) in microgrids with combined heat and power systems. We analyzed three types of microgrids; the first one consists of an office building and an apartment, the second one consists of a hospital and an apartment, the third one consists of a hotel, office and retails. In the methodology, annual cost is minimized by considering the partial load efficiency of a gas engine and its scale economy, and the optimal number and capacity of each piece of equipment and the annual operational schedule are determined by using the optimal planning method. Based on calculations using this design methodology, it is found that the optimal number of gas engines is determined by the ratio of bottom to peak of the electricity demand and the ratio of heat to electricity demand. The optimal capacity of a battery required to supply electricity for a limited time during a peak demand period is auxiliary. The thermal storage tank for space cooling and space heating is selected to minimize the use of auxiliary equipment such as a gas absorption chiller.

Fuel cell system

DOEpatents

Early, Jack; Kaufman, Arthur; Stawsky, Alfred

1982-01-01

A fuel cell system is comprised of a fuel cell module including sub-stacks of series-connected fuel cells, the sub-stacks being held together in a stacked arrangement with cold plates of a cooling means located between the sub-stacks to function as electrical terminals. The anode and cathode terminals of the sub-stacks are connected in parallel by means of the coolant manifolds which electrically connect selected cold plates. The system may comprise a plurality of the fuel cell modules connected in series. The sub-stacks are designed to provide a voltage output equivalent to the desired voltage demand of a low voltage, high current DC load such as an electrolytic cell to be driven by the fuel cell system. This arrangement in conjunction with switching means can be used to drive a DC electrical load with a total voltage output selected to match that of the load being driven. This arrangement eliminates the need for expensive voltage regulation equipment.

Testing activities at the National Battery Test Laboratory

NASA Astrophysics Data System (ADS)

Hornstra, F.; Deluca, W. H.; Mulcahey, T. P.

The National Battery Test Laboratory (NBTL) is an Argonne National Laboratory facility for testing, evaluating, and studying advanced electric storage batteries. The facility tests batteries developed under Department of Energy programs and from private industry. These include batteries intended for future electric vehicle (EV) propulsion, electric utility load leveling (LL), and solar energy storage. Since becoming operational, the NBTL has evaluated well over 1400 cells (generally in the form of three- to six-cell modules, but up to 140-cell batteries) of various technologies. Performance characterization assessments are conducted under a series of charge/discharge cycles with constant current, constant power, peak power, and computer simulated dynamic load profile conditions. Flexible charging algorithms are provided to accommodate the specific needs of each battery under test. Special studies are conducted to explore and optimize charge procedures, to investigate the impact of unique load demands on battery performance, and to analyze the thermal management requirements of battery systems.

A sustainable development of a city electrical grid via a non-contractual Demand-Side Management

NASA Astrophysics Data System (ADS)

Samoylenko, Vladislav O.; Pazderin, Andrew V.

2017-06-01

An increasing energy consumption of large cities as well as an extreme high density of city electrical loads leads to the necessity to search for an alternative approaches to city grid development. The ongoing implementation of the energy accounting tariffs with differentiated rates depending upon the market conditions and changing in a short-term perspective, provide the possibility to use it as a financial incentive base of a Demand-Side Management (DSM). Modern hi-technology energy metering and accounting systems with a large number of functions and consumer feedback are supposed to be the good means of DSM. Existing systems of Smart Metering (SM) billing usually provide general information about consumption curve, bills and compared data, but not the advanced statistics about the correspondence of financial and electric parameters. Also, consumer feedback is usually not fully used. So, the efforts to combine the market principle, Smart Metering and a consumer feedback for an active non-contractual load control are essential. The paper presents the rating-based multi-purpose system of mathematical statistics and algorithms of DSM efficiency estimation useful for both the consumers and the energy companies. The estimation is performed by SM Data processing systems. The system is aimed for load peak shaving and load curve smoothing. It is focused primarily on a retail market support. The system contributes to the energy efficiency and a distribution process improvement by the manual management or by the automated Smart Appliances interaction.

Load Forecasting in Electric Utility Integrated Resource Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carvallo, Juan Pablo; Larsen, Peter H.; Sanstad, Alan H

Integrated resource planning (IRP) is a process used by many vertically-integrated U.S. electric utilities to determine least-cost/risk supply and demand-side resources that meet government policy objectives and future obligations to customers and, in many cases, shareholders. Forecasts of energy and peak demand are a critical component of the IRP process. There have been few, if any, quantitative studies of IRP long-run (planning horizons of two decades) load forecast performance and its relationship to resource planning and actual procurement decisions. In this paper, we evaluate load forecasting methods, assumptions, and outcomes for 12 Western U.S. utilities by examining and comparing plansmore » filed in the early 2000s against recent plans, up to year 2014. We find a convergence in the methods and data sources used. We also find that forecasts in more recent IRPs generally took account of new information, but that there continued to be a systematic over-estimation of load growth rates during the period studied. We compare planned and procured resource expansion against customer load and year-to-year load growth rates, but do not find a direct relationship. Load sensitivities performed in resource plans do not appear to be related to later procurement strategies even in the presence of large forecast errors. These findings suggest that resource procurement decisions may be driven by other factors than customer load growth. Our results have important implications for the integrated resource planning process, namely that load forecast accuracy may not be as important for resource procurement as is generally believed, that load forecast sensitivities could be used to improve the procurement process, and that management of load uncertainty should be prioritized over more complex forecasting techniques.« less

User's manual for the Shuttle Electric Power System analysis computer program (SEPS), volume 2 of program documentation

NASA Technical Reports Server (NTRS)

Bains, R. W.; Herwig, H. A.; Luedeman, J. K.; Torina, E. M.

1974-01-01

The Shuttle Electric Power System Analysis SEPS computer program which performs detailed load analysis including predicting energy demands and consumables requirements of the shuttle electric power system along with parameteric and special case studies on the shuttle electric power system is described. The functional flow diagram of the SEPS program is presented along with data base requirements and formats, procedure and activity definitions, and mission timeline input formats. Distribution circuit input and fixed data requirements are included. Run procedures and deck setups are described.

Intelligent power consumption with two-way shift able feature and its implementation

NASA Astrophysics Data System (ADS)

Xu, Jing; Liu, Youwei

2017-10-01

This paper proposes an intelligent power consumption system with two-way shift able feature and its implementation. Based on power consumption information of standby load and load in working state, a dispatching system decomposes load regulation demand top-down to smart appliances and makes them response orderly as required. It designs a code-based representation method for power consumption information and takes account of standby load, which lays the information foundation for load increment. It also presents a shift able index, which can be used to comprehensively reflect feature of electrical equipment and users and provides a basis for load priority.

Real-Time Load-Side Control of Electric Power Systems

NASA Astrophysics Data System (ADS)

Zhao, Changhong

Two trends are emerging from modern electric power systems: the growth of renewable (e.g., solar and wind) generation, and the integration of information technologies and advanced power electronics. The former introduces large, rapid, and random fluctuations in power supply, demand, frequency, and voltage, which become a major challenge for real-time operation of power systems. The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate. Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators. This thesis focuses on controlling power systems in real time, using these load side resources. Specifically, it studies two problems. (1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads. In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage. By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers. This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios. We first consider a dynamically coherent power system which can be equivalently modeled with a single synchronous machine. We then extend our framework to a multi-machine power network, where we consider primary and secondary frequency controls, linear and nonlinear power flow models, and the interactions between generator dynamics and load control. (2) Two-timescale voltage control: The voltage of a power distribution system must be maintained closely around its nominal value in real time, even in the presence of highly volatile power supply or demand. For this purpose, we jointly control two types of reactive power sources: a capacitor operating at a slow timescale, and a power electronic device, such as a smart inverter or a D-STATCOM, operating at a fast timescale. Their control actions are solved from optimal power flow problems at two timescales. Specifically, the slow-timescale problem is a chance-constrained optimization, which minimizes power loss and regulates the voltage at the current time instant while limiting the probability of future voltage violations due to stochastic changes in power supply or demand. This control framework forms the basis of an optimal sizing problem, which determines the installation capacities of the control devices by minimizing the sum of power loss and capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments show that the proposed sizing and control schemes significantly improve the reliability of voltage control with a moderate increase in cost.

Optimization of a hybrid electric power system design for large commercial buildings: An application design guide

NASA Astrophysics Data System (ADS)

Lee, Keun

Renewable energy in different forms has been used in various applications for survival since the beginning of human existence. However, there is a new dire need to reevaluate and recalibrate the overall energy issue both nationally and globally. This includes, but is not limited to, the finite availability of fossil fuel, energy sustainability with an increasing demand, escalating energy costs, environmental impact such as global warming and green-house gases, to name a few. This dissertation is primarily focused and related to the production and usage of electricity from non-hydro renewable sources. Among non-hydro renewable energy sources, electricity generation from wind and solar energy are the fastest-growing technologies in the United States and in the world. However, due to the intermittent nature of such renewable sources, energy storage devices are required to maintain proper operation of the grid system and in order to increase reliability. A hybrid system, as the name suggests, is a combination of different forms of non-renewable and renewable energy generation, with or without storage devices. Hybrid systems, when applied properly, are able to improve reliability and enhance stability, reduce emissions and noise pollution, provide continuous power, increase operation life, reduce cost, and efficiently use all available energy. In the United States (U.S.), buildings consume approximately 40% of the total primary energy and 74% of the total electricity. Therefore, reduction of energy consumption and improved energy efficiency in U.S. buildings will play a vital role in the overall energy picture. Electrical energy usage for any such building varies widely depending on age (construction technique), electricity and natural gas usage, appearance, location and climate. In this research, a hybrid system including non-renewable and renewable energy generation with storage devices specifically for building applications, is studied in detail. This research deals with the optimization of the hybrid system design (which consists of PV panels and/or wind turbines and/or storage devices for building applications) by developing an algorithm designed to make the system cost effective and energy efficient. Input data includes electrical load demand profile of the buildings, buildings' structural and geographical characteristics, real time pricing of electricity, and the costs of hybrid systems and storage devices. When the electrical load demand profile of a building that is being studied is available, a measured demand profile is directly used as input data. However, if that information is not available, a building's electric load demand is estimated using a developed algorithm based on three large data sources from a public domain, and used as input data. Using the acquired input data, the algorithm of this research is designed and programmed in order to determine the size of renewable components and to minimize the total yearly net cost. This dissertation also addresses the parametric sensitivity analysis to determine which factors are more significant and are expected to produce useful guidelines in the decision making process. An engineered and more practical, simplified solution has been provided for the optimized design process.

Demand side management in recycling and electricity retail pricing

NASA Astrophysics Data System (ADS)

Kazan, Osman

This dissertation addresses several problems from the recycling industry and electricity retail market. The first paper addresses a real-life scheduling problem faced by a national industrial recycling company. Based on their practices, a scheduling problem is defined, modeled, analyzed, and a solution is approximated efficiently. The recommended application is tested on the real-life data and randomly generated data. The scheduling improvements and the financial benefits are presented. The second problem is from electricity retail market. There are well-known patterns in daily usage in hours. These patterns change in shape and magnitude by seasons and days of the week. Generation costs are multiple times higher during the peak hours of the day. Yet most consumers purchase electricity at flat rates. This work explores analytic pricing tools to reduce peak load electricity demand for retailers. For that purpose, a nonlinear model that determines optimal hourly prices is established based on two major components: unit generation costs and consumers' utility. Both are analyzed and estimated empirically in the third paper. A pricing model is introduced to maximize the electric retailer's profit. As a result, a closed-form expression for the optimal price vector is obtained. Possible scenarios are evaluated for consumers' utility distribution. For the general case, we provide a numerical solution methodology to obtain the optimal pricing scheme. The models recommended are tested under various scenarios that consider consumer segmentation and multiple pricing policies. The recommended model reduces the peak load significantly in most cases. Several utility companies offer hourly pricing to their customers. They determine prices using historical data of unit electricity cost over time. In this dissertation we develop a nonlinear model that determines optimal hourly prices with parameter estimation. The last paper includes a regression analysis of the unit generation cost function obtained from Independent Service Operators. A consumer experiment is established to replicate the peak load behavior. As a result, consumers' utility function is estimated and optimal retail electricity prices are computed.

Tablet based distributed intelligent load management

DOEpatents

Lu, Yan; Zhou, Siyuan

2018-01-09

A facility is connected to an electricity utility and is responsive to Demand Response Events. A plurality of devices is each individually connected to the electricity grid via an addressable switch connected to a secure network that is enabled to be individually switched off by a server. An occupant of a room in control of the plurality of devices provides via a Human Machine Interface on a tablet a preferred order of switching off the plurality of devices in case of a Demand Response Event. A configuration file based at least partially on the preferred order and on a severity of the Demand Response Events determines which devices which of the plurality devices will be switched off. The server accesses the configuration file and switches off the devices included in the configuration file.

Tool Helps Utilities Assess Readiness for Electric Vehicle Charging (Fact Sheet)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

NREL research helps answer a fundamental question regarding electric vehicles: Is the grid ready to handle them? Environmental, economic and security concerns regarding oil consumption make electrifying the transportation sector a high national priority. NREL's Center for Transportation Technologies & Systems (CTTS) has developed a framework for utilities to evaluate the plug-in vehicle (PEV) readiness of distribution transformers. Combining a wealth of vehicle performance statistics with load data from partner utilities including the Hawaiian Electric Company and Xcel Energy, NREL analyzed the thermal loading characteristics of distribution transformers due to vehicle charging. After running millions of simulations replicating varying climatesmore » and conditions, NREL is now able to predict aging rates for transformers when PEVs are added to existing building loads. With the NREL tool, users define simulation parameters by inputting vehicle trip and weather data; transformer load profiles and ratings; PEV penetration, charging rates and battery sizes; utility rates; the number of houses on each transformer; and public charging availability. Transformer load profiles, drive cycles, and ambient temperature data are then run through the thermal model to produce a one-year timeseries of the hotspot temperature. Annual temperature durations are calculated to help determine the annual aging rate. Annual aging rate results are grouped by independent variables. The most useful measure is transformer mileage, a measure of how many electrically-driven miles must be supplied by the transformer. Once the spectrum analysis has been conducted for an area or utility, the outputs can be used to help determine if more detailed evaluation is necessary, or if transformer replacement is required. In the majority of scenarios, transformers have enough excess capacity to charge PEVs. Only in extreme cases does vehicle charging have negative long-term impact on transformers. In those cases, upgrades to larger transformers would be recommended. NREL analysis also showed opportunity for newly-installed smart grids to offset distribution demands by time-shifting the charging loads. Most importantly, the model demonstrated synergies between PEVs and distributed renewables, not only providing clean renewable energy for vehicles, but also reducing demand on the entire distribution infrastructure by supplying loads at the point of consumption.« less

Estimating the stability of electrical conductivity of filled polymers under the influence of negative temperatures

NASA Astrophysics Data System (ADS)

Minakova, N. N.; Ushakov, V. Ya.

2017-12-01

One of the key problems in modern materials technology is synthesis of materials for electrotechnical devices capable of operating under severe conditions. Electrical and power engineering, in particular, demands for electrically conductive composite materials operating at high and low temperatures, various mechanical loads, electric fields, etc. Chaotic arrangement of electrically conductive component in the matrix and its structural and geometrical inhomogeneity can increase the local electric and thermal energy flux densities up to critical values even when their average values remain moderate. Elastomers filled with technical carbon being a promising component for electrotechnical devices was chosen as an object of study.

ELECTRICAL LOAD ANTICIPATOR AND RECORDER

DOEpatents

Russell, J.B.; Thomas, R.J.

1961-07-25

A system is descrbied in which an indication of the prevailing energy consumption in an electrical power metering system and a projected Power demand for one demand interval is provided at selected increments of time withm the demand interval. Each watthour meter in the system is provided with an impulse generator that generates two impulses for each revolution of the meter disc. The total pulses received frorn all the meters are continuously totaled and are fed to a plurality of parallel connected gated counters. Each counter has its gate opened at different sub-time intervals during the demand interval. A multiplier is connected to each of the gated counters except the last one and each multiplier is provided with a different multiplier constant so as to provide an estimate of the power to be drawn over the entire demand interval at the end of each of the different sub-time intervals. Means are provided for recording the ontputs from the different circuits in synchronism with the actuation oi each gate circuit.

Advanced secondary batteries: Their applications, technological status, market and opportunity

NASA Astrophysics Data System (ADS)

Yao, M.

1989-03-01

Program planning for advanced battery energy storage technology is supported within the NEMO Program. Specifically this study had focused on the review of advanced battery applications; the development and demonstration status of leading battery technologies; and potential marketing opportunity. Advanced secondary (or rechargeable) batteries have been under development for the past two decades in the U.S., Japan, and parts of Europe for potential applications in electric utilities and for electric vehicles. In the electric utility applications, the primary aim of a battery energy storage plant is to facilitate peak power load leveling and/or dynamic operations to minimize the overall power generation cost. In the application for peak power load leveling, the battery stores the off-peak base load energy and is discharged during the period of peak power demand. This allows a more efficient use of the base load generation capacity and reduces the need for conventional oil-fired or gas-fire peak power generation equipment. Batteries can facilitate dynamic operations because of their basic characteristics as an electrochemical device capable of instantaneous response to the changing load. Dynamic operating benefits results in cost savings of the overall power plant operation. Battery-powered electric vehicles facilitate conservation of petroleum fuel in the transportation sector, but more importantly, they reduce air pollution in the congested inner cities.

Short-term load and wind power forecasting using neural network-based prediction intervals.

PubMed

Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

2014-02-01

Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

Concept of intellectual charging system for electrical and plug-in hybrid vehicles in Russian Federation

NASA Astrophysics Data System (ADS)

Kolbasov, A.; Karpukhin, K.; Terenchenko, A.; Kavalchuk, I.

2018-02-01

Electric vehicles have become the most common solution to improve sustainability of the transportation systems all around the world. Despite all benefits, wide adaptation of electric vehicles requires major changes in the infrastructure, including grid adaptation to the rapidly increased power demand and development of the Connected Car concept. This paper discusses the approaches to improve usability of electric vehicles, by creating suitable web-services, with possible connections vehicle-to-vehicle, vehicle-to-infrastructure, and vehicle-to-grid. Developed concept combines information about electrical loads on the grid in specific direction, navigation information from the on-board system, existing and empty charging slots and power availability. In addition, this paper presents the universal concept of the photovoltaic integrated charging stations, which are connected to the developed information systems. It helps to achieve rapid adaptation of the overall infrastructure to the needs of the electric vehicles users with minor changes in the existing grid and loads.

Potential Impacts of Plug-in Hybrid Electric Vehicles on Regional Power Generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hadley, Stanton W; Tsvetkova, Alexandra A

2008-01-01

Plug-in hybrid electric vehicles (PHEVs) are being developed around the world, with much work aiming to optimize engine and battery for efficient operation, both during discharge and when grid electricity is available for recharging. However, the general expectation has been that the grid will not be greatly affected by the use of PHEVs because the recharging will occur during off-peak hours, or the number of vehicles will grow slowly enough so that capacity planning will respond adequately. This expectation does not consider that drivers will control the timing of recharging, and their inclination will be to plug in when convenient,more » rather than when utilities would prefer. It is important to understand the ramifications of adding load from PHEVs onto the grid. Depending on when and where the vehicles are plugged in, they could cause local or regional constraints on the grid. They could require the addition of new electric capacity and increase the utilization of existing capacity. Usage patterns of local distribution grids will change, and some lines or substations may become overloaded sooner than expected. Furthermore, the type of generation used to meet the demand for recharging PHEVs will depend on the region of the country and the timing of recharging. This paper analyzes the potential impacts of PHEVs on electricity demand, supply, generation structure, prices, and associated emission levels in 2020 and 2030 in 13 regions specified by the North American Electric Reliability Corporation (NERC) and the U.S. Department of Energy's (DOE's) Energy Information Administration (EIA), and on which the data and analysis in EIA's Annual Energy Outlook 2007 are based (Figure ES-1). The estimates of power plant supplies and regional hourly electricity demand come from publicly available sources from EIA and the Federal Energy Regulatory Commission. Electricity requirements for PHEVs are based on analysis from the Electric Power Research Institute, with an optimistic projection of 25% market penetration by 2020, involving a mixture of sedans and sport utility vehicles. The calculations were done using the Oak Ridge Competitive Electricity Dispatch (ORCED) model, a model developed over the past 12 years to evaluate a wide variety of critical electricity sector issues. Seven scenarios were run for each region for 2020 and 2030, for a total of 182 scenarios. In addition to a base scenario of no PHEVs, the authors modeled scenarios assuming that vehicles were either plugged in starting at 5:00 p.m. (evening) or at 10:00 p.m.(night) and left until fully charged. Three charging rates were examined: 120V/15A (1.4 kW), 120V/20A (2 kW), and 220V/30A (6 kW). Most regions will need to build additional capacity or utilize demand response to meet the added demand from PHEVs in the evening charging scenarios, especially by 2030 when PHEVs have a larger share of the installed vehicle base and make a larger demand on the system. The added demands of evening charging, especially at high power levels, can impact the overall demand peaks and reduce the reserve margins for a region's system. Night recharging has little potential to influence peak loads, but will still influence the amount and type of generation.« less

Transformer Efficiency Assessment - Okinawa, Japan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas L. Baldwin; Robert J. Turk; Kurt S. Myers

The US Army Engineering & Support Center, Huntsville (USAESCH), and the US Marine Corps Base (MCB), Okinawa, Japan retained Idaho National Laboratory (INL) to conduct a Transformer Efficiency Assessment of “key” transformers located at multiple military bases in Okinawa, Japan. The purpose of this assessment is to support the Marine Corps Base, Okinawa in evaluating medium voltage distribution transformers for potential efficiency upgrades. The original scope of work included the MCB providing actual transformer nameplate data, manufacturer’s factory test sheets, electrical system data (kWh), demand data (kWd), power factor data, and electricity cost data. Unfortunately, the MCB’s actual data ismore » not available and therefore making it necessary to de-scope the original assessment. Note: Any similar nameplate data, photos of similar transformer nameplates, and basic electrical details from one-line drawings (provided by MCB) are not a replacement for actual load loss test data. It is recommended that load measurements are performed on the high and low sides of transformers to better quantify actual load losses, demand data, and power factor data. We also recommend that actual data, when available, be inserted by MCB Okinawa where assumptions have been made and then the LCC analysis updated. This report covers a generalized assessment of modern U.S. transformers in a three level efficiency category, Low-Level efficiency, Medium-Level efficiency, and High-Level efficiency.« less

Transformer Efficiency Assessment - Okinawa, Japan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas L. Baldwin; Robert J. Turk; Kurt S. Myers

2012-05-01

The US Army Engineering & Support Center, Huntsville (USAESCH), and the US Marine Corps Base (MCB), Okinawa, Japan retained Idaho National Laboratory (INL) to conduct a Transformer Efficiency Assessment of “key” transformers located at multiple military bases in Okinawa, Japan. The purpose of this assessment is to support the Marine Corps Base, Okinawa in evaluating medium voltage distribution transformers for potential efficiency upgrades. The original scope of work included the MCB providing actual transformer nameplate data, manufacturer’s factory test sheets, electrical system data (kWh), demand data (kWd), power factor data, and electricity cost data. Unfortunately, the MCB’s actual data ismore » not available and therefore making it necessary to de-scope the original assessment. Note: Any similar nameplate data, photos of similar transformer nameplates, and basic electrical details from one-line drawings (provided by MCB) are not a replacement for actual load loss test data. It is recommended that load measurements are performed on the high and low sides of transformers to better quantify actual load losses, demand data, and power factor data. We also recommend that actual data, when available, be inserted by MCB Okinawa where assumptions have been made and then the LCC analysis updated. This report covers a generalized assessment of modern U.S. transformers in a three level efficiency category, Low-Level efficiency, Medium-Level efficiency, and High-Level efficiency.« less

Reduced-Order Models for Load Management in the Power Grid

NASA Astrophysics Data System (ADS)

Alizadeh, Mahnoosh

In recent years, considerable research efforts have been directed towards designing control schemes that can leverage the inherent flexibility of electricity demand that is not tapped into in today's electricity markets. It is expected that these control schemes will be carried out by for-profit entities referred to as aggregators that operate at the edge of the power grid network. While the aggregator control problem is receiving much attention, more high-level questions of how these aggregators should plan their market participation, interact with the main grid and with each other, remain rather understudied. Answering these questions requires a large-scale model for the aggregate flexibility that can be harnessed from the a population of customers, particularly for residences and small businesses. The contribution of this thesis towards this goal is divided into three parts: In Chapter 3, a reduced-order model for a large population of heterogeneous appliances is provided by clustering load profiles that share similar degrees of freedom together. The use of such reduced-order model for system planning and optimal market decision making requires a foresighted approximation of the number of appliances that will join each cluster. Thus, Chapter 4 provides a systematic framework to generate such forecasts for the case of Electric Vehicles, based on real-world battery charging data. While these two chapters set aside the economic side that is naturally involved with participation in demand response programs and mainly focus on the control problem, Chapter 5 is dedicated to the study of optimal pricing mechanisms in order to recruit heterogeneous customers in a demand response program in which an aggregator can directly manage their appliances' load under their specified preferences. Prices are proportional to the wholesale market savings that can result from each recruitment event.

Northwest Open Automated Demand Response Technology Demonstration Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kiliccote, Sila; Piette, Mary Ann; Dudley, Junqiao

The Lawrence Berkeley National Laboratory (LBNL) Demand Response Research Center (DRRC) demonstrated and evaluated open automated demand response (OpenADR) communication infrastructure to reduce winter morning and summer afternoon peak electricity demand in commercial buildings the Seattle area. LBNL performed this demonstration for the Bonneville Power Administration (BPA) in the Seattle City Light (SCL) service territory at five sites: Seattle Municipal Tower, Seattle University, McKinstry, and two Target stores. This report describes the process and results of the demonstration. OpenADR is an information exchange model that uses a client-server architecture to automate demand-response (DR) programs. These field tests evaluated the feasibilitymore » of deploying fully automated DR during both winter and summer peak periods. DR savings were evaluated for several building systems and control strategies. This project studied DR during hot summer afternoons and cold winter mornings, both periods when electricity demand is typically high. This is the DRRC project team's first experience using automation for year-round DR resources and evaluating the flexibility of commercial buildings end-use loads to participate in DR in dual-peaking climates. The lessons learned contribute to understanding end-use loads that are suitable for dispatch at different times of the year. The project was funded by BPA and SCL. BPA is a U.S. Department of Energy agency headquartered in Portland, Oregon and serving the Pacific Northwest. BPA operates an electricity transmission system and markets wholesale electrical power at cost from federal dams, one non-federal nuclear plant, and other non-federal hydroelectric and wind energy generation facilities. Created by the citizens of Seattle in 1902, SCL is the second-largest municipal utility in America. SCL purchases approximately 40% of its electricity and the majority of its transmission from BPA through a preference contract. SCL also provides ancillary services within its own balancing authority. The relationship between BPA and SCL creates a unique opportunity to create DR programs that address both BPA's and SCL's markets simultaneously. Although simultaneously addressing both market could significantly increase the value of DR programs for BPA, SCL, and the end user, establishing program parameters that maximize this value is challenging because of complex contractual arrangements and the absence of a central Independent System Operator or Regional Transmission Organization in the northwest.« less

Dispatch Control with PEV Charging and Renewables for Multiplayer Game Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, Nathan; Johnson, Brian; McJunkin, Timothy

This paper presents a demand response model for a hypothetical microgrid that integrates renewable resources and plug-in electric vehicle (PEV) charging systems. It is assumed that the microgrid has black start capability and that external generation is available for purchase while grid connected to satisfy additional demand. The microgrid is developed such that in addition to renewable, non-dispatchable generation from solar, wind and run of the river hydroelectric resources, local dispatchable generation is available in the form of small hydroelectric and moderately sized gas and coal fired facilities. To accurately model demand, the load model is separated into independent residential,more » commercial, industrial, and PEV charging systems. These are dispatched and committed based on a mixed integer linear program developed to minimize the cost of generation and load shedding while satisfying constraints associated with line limits, conservation of energy, and ramp rates of the generation units. The model extends a research tool to longer time frames intended for policy setting and educational environments and provides a realistic and intuitive understanding of beneficial and challenging aspects of electrification of vehicles combined with integration of green electricity production.« less

Integrated thermal and energy management of plug-in hybrid electric vehicles

NASA Astrophysics Data System (ADS)

Shams-Zahraei, Mojtaba; Kouzani, Abbas Z.; Kutter, Steffen; Bäker, Bernard

2012-10-01

In plug-in hybrid electric vehicles (PHEVs), the engine temperature declines due to reduced engine load and extended engine off period. It is proven that the engine efficiency and emissions depend on the engine temperature. Also, temperature influences the vehicle air-conditioner and the cabin heater loads. Particularly, while the engine is cold, the power demand of the cabin heater needs to be provided by the batteries instead of the waste heat of engine coolant. The existing energy management strategies (EMS) of PHEVs focus on the improvement of fuel efficiency based on hot engine characteristics neglecting the effect of temperature on the engine performance and the vehicle power demand. This paper presents a new EMS incorporating an engine thermal management method which derives the global optimal battery charge depletion trajectories. A dynamic programming-based algorithm is developed to enforce the charge depletion boundaries, while optimizing a fuel consumption cost function by controlling the engine power. The optimal control problem formulates the cost function based on two state variables: battery charge and engine internal temperature. Simulation results demonstrate that temperature and the cabin heater/air-conditioner power demand can significantly influence the optimal solution for the EMS, and accordingly fuel efficiency and emissions of PHEVs.

Performance Analysis of Isolated Hybrid Power Plant Model with Dynamic Load Conditions - Morning, Noon and Afternoon Transitions

NASA Astrophysics Data System (ADS)

Irawati, Rina

2018-02-01

Diesel Generator with Photovoltaic Hybrid Power Plant is one of the solutions for supply electric demand to isolated area. The energy sources that can be used for hybrid system are such as photovoltaic, wind turbine, and biomass or biogas, because these sources are almost available in every isolated area. This research used a model of hybrid system from diesel generator and 1.28 kWp photovoltaic power plant. The reliability and some of power quality of this system tested by 1300VA house hold daily load characteristic effectively 24 hour. Power quality and some electricity parameters during transition mode for each resource will be analyzed. Furthermore the power quality analyze will be conducted and evaluated base on Electrical Engineers' Association (EEA).

Energy performance and savings potentials with skylights

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arasteh, D.; Johnson, R.; Selkowitz, S.

1984-12-01

This study systematically explores the energy effects of skylight systems in a prototypical office building module and examines the savings from daylighting. For specific climates, roof/skylight characteristics are identified that minimize total energy or peak electrical demand. Simplified techniques for energy performance calculation are also presented based on a multiple regression analysis of our data base so that one may easily evaluate daylighting's effects on total and component energy loads and electrical peaks. This provides additional insights into the influence of skylight parameters on energy consumption and electrical peaks. We use the DOE-2.1B energy analysis program with newly incorporated daylightingmore » algorithms to determine hourly, monthly, and annual impacts of daylighting strategies on electrical lighting consumption, cooling, heating, fan power, peak electrical demands, and total energy use. A data base of more than 2000 parametric simulations for 14 US climates has been generated. Parameters varied include skylight-to-roof ratio, shading coefficient, visible transmittance, skylight well light loss, electric lighting power density, roof heat transfer coefficient, and electric lighting control type. 14 references, 13 figures, 4 tables.« less

A two-stage stochastic optimization model for scheduling electric vehicle charging loads to relieve distribution-system constraints

DOE PAGES

Wu, Fei; Sioshansi, Ramteen

2017-05-25

Electric vehicles (EVs) hold promise to improve the energy efficiency and environmental impacts of transportation. However, widespread EV use can impose significant stress on electricity-distribution systems due to their added charging loads. This paper proposes a centralized EV charging-control model, which schedules the charging of EVs that have flexibility. This flexibility stems from EVs that are parked at the charging station for a longer duration of time than is needed to fully recharge the battery. The model is formulated as a two-stage stochastic optimization problem. The model captures the use of distributed energy resources and uncertainties around EV arrival timesmore » and charging demands upon arrival, non-EV loads on the distribution system, energy prices, and availability of energy from the distributed energy resources. We use a Monte Carlo-based sample-average approximation technique and an L-shaped method to solve the resulting optimization problem efficiently. We also apply a sequential sampling technique to dynamically determine the optimal size of the randomly sampled scenario tree to give a solution with a desired quality at minimal computational cost. Here, we demonstrate the use of our model on a Central-Ohio-based case study. We show the benefits of the model in reducing charging costs, negative impacts on the distribution system, and unserved EV-charging demand compared to simpler heuristics. Lastly, we also conduct sensitivity analyses, to show how the model performs and the resulting costs and load profiles when the design of the station or EV-usage parameters are changed.« less

An open data repository for steady state analysis of a 100-node electricity distribution network with moderate connection of renewable energy sources.

PubMed

Lazarou, Stavros; Vita, Vasiliki; Ekonomou, Lambros

2018-02-01

The data of this article represent a real electricity distribution network on twenty kilovolts (20 kV) at medium voltage level of the Hellenic electricity distribution system [1]. This network has been chosen as suitable for smart grid analysis. It demonstrates moderate penetration of renewable sources and it has capability in part of time for reverse power flows. It is suitable for studies of load aggregation, storage, demand response. It represents a rural line of fifty-five kilometres (55 km) total length, a typical length for this type. It serves forty-five (45) medium to low voltage transformers and twenty-four (24) connections to photovoltaic plants. The total installed load capacity is twelve mega-volt-ampere (12 MVA), however the maximum observed load is lower. The data are ready to perform load flow simulation on Matpower [2] for the maximum observed load power on the half production for renewables. The simulation results and processed data for creating the source code are also provided on the database available at http://dx.doi.org/10.7910/DVN/1I6MKU.

A method for estimating the performance of photovoltaic systems

NASA Astrophysics Data System (ADS)

Clark, D. R.; Klein, S. A.; Beckman, W. A.

A method is presented for predicting the long-term average performance of photovoltaic systems having storage batteries and subject to any diurnal load profile. The monthly-average fraction of the load met by the system is estimated from array parameters and monthly-average meteorological data. The method is based on radiation statistics, and utilizability, and can account for variability in the electrical demand as well as for the variability in solar radiation.

Impacts of Demand-Side Resources on Electric Transmission Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hadley, Stanton W.; Sanstad, Alan H.

2015-01-01

Will demand resources such as energy efficiency (EE), demand response (DR), and distributed generation (DG) have an impact on electricity transmission requirements? Five drivers for transmission expansion are discussed: interconnection, reliability, economics, replacement, and policy. With that background, we review the results of a set of transmission studies that were conducted between 2010 and 2013 by electricity regulators, industry representatives, and other stakeholders in the three physical interconnections within the United States. These broad-based studies were funded by the US Department of Energy and included scenarios of reduced load growth due to EE, DR, and DG. While the studies weremore » independent and used different modeling tools and interconnect-specific assumptions, all provided valuable results and insights. However, some caveats exist. Demand resources were evaluated in conjunction with other factors, and limitations on transmission additions between scenarios made understanding the role of demand resources difficult. One study, the western study, included analyses over both 10- and 20-year planning horizons; the 10-year analysis did not show near-term reductions in transmission, but the 20-year indicated fewer transmission additions, yielding a 36percent capital cost reduction. In the eastern study the reductions in demand largely led to reductions in local generation capacity and an increased opportunity for low-cost and renewable generation to export to other regions. The Texas study evaluated generation changes due to demand, and is in the process of examining demand resource impacts on transmission.« less

Design and Implementation of Demand Response Information Interactive Service Platform Based on “Internet Plus” Smart Energy

NASA Astrophysics Data System (ADS)

Cui, Gaoying; Fan, Jie; Qin, Yuchen; Wang, Dong; Chen, Guangyan

2017-05-01

In order to promote the effective use of demand response load side resources, promote the interaction between supply and demand, enhance the level of customer service and achieve the overall utilization of energy, this paper briefly explain the background significance of design demand response information platform and current situation of domestic and foreign development; Analyse the new demand of electricity demand response combined with the application of Internet and big data technology; Design demand response information platform architecture, construct demand responsive system, analyse process of demand response strategy formulate and intelligent execution implement; study application which combined with the big data, Internet and demand response technology; Finally, from information interaction architecture, control architecture and function design perspective design implementation of demand response information platform, illustrate the feasibility of the proposed platform design scheme implemented in a certain extent.

Modeling, Analysis, and Control of Demand Response Resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mathieu, Johanna L.

2012-05-01

While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can plan an active role in power systems via Demand Response (DR), defined by the Department of Energy (DOE) as “a tariff or program established to motivate changes in electric use by end-use customers in response to changes in the price of electricity over time, or to give incentive payments designed to induce lower electricity use at times of high market prices or when grid reliability is jeopardized” [29]. DR can provide a variety of benefits including reducing peak electric loadsmore » when the power system is stressed and fast timescale energy balancing. Therefore, DR can improve grid reliability and reduce wholesale energy prices and their volatility. This dissertation focuses on analyzing both recent and emerging DR paradigms. Recent DR programs have focused on peak load reduction in commercial buildings and industrial facilities (C&I facilities). We present methods for using 15-minute-interval electric load data, commonly available from C&I facilities, to help building managers understand building energy consumption and ‘ask the right questions’ to discover opportunities for DR. Additionally, we present a regression-based model of whole building electric load, i.e., a baseline model, which allows us to quantify DR performance. We use this baseline model to understand the performance of 38 C&I facilities participating in an automated dynamic pricing DR program in California. In this program, facilities are expected to exhibit the same response each DR event. We find that baseline model error makes it difficult to precisely quantify changes in electricity consumption and understand if C&I facilities exhibit event-to-event variability in their response to DR signals. Therefore, we present a method to compute baseline model error and a metric to determine how much observed DR variability results from baseline model error rather than real variability in response. We find that, in general, baseline model error is large. Though some facilities exhibit real DR variability, most observed variability results from baseline model error. In some cases, however, aggregations of C&I facilities exhibit real DR variability, which could create challenges for power system operation. These results have implications for DR program design and deployment. Emerging DR paradigms focus on faster timescale DR. Here, we investigate methods to coordinate aggregations of residential thermostatically controlled loads (TCLs), including air conditioners and refrigerators, to manage frequency and energy imbalances in power systems. We focus on opportunities to centrally control loads with high accuracy but low requirements for sensing and communications infrastructure. Specifically, we compare cases when measured load state information (e.g., power consumption and temperature) is 1) available in real time; 2) available, but not in real time; and 3) not available. We develop Markov Chain models to describe the temperature state evolution of heterogeneous populations of TCLs, and use Kalman filtering for both state and joint parameter/state estimation. We present a look-ahead proportional controller to broadcast control signals to all TCLs, which always remain in their temperature dead-band. Simulations indicate that it is possible to achieve power tracking RMS errors in the range of 0.26–9.3% of steady state aggregated power consumption. Results depend upon the information available for system identification, state estimation, and control. We find that, depending upon the performance required, TCLs may not need to provide state information to the central controller in real time or at all. We also estimate the size of the TCL potential resource; potential revenue from participation in markets; and break-even costs associated with deploying DR-enabling technologies. We find that current TCL energy storage capacity in California is 8–11 GWh, with refrigerators contributing the most. Annual revenues from participation in regulation vary from $10 to $220 per TCL per year depending upon the type of TCL and climate zone, while load following and arbitrage revenues are more modest at $2 to $35 per TCL per year. These results lead to a number of policy recommendations that will make it easier to engage residential loads in fast timescale DR.« less

Load allocation of power plant using multi echelon economic dispatch

NASA Astrophysics Data System (ADS)

Wahyuda, Santosa, Budi; Rusdiansyah, Ahmad

2017-11-01

In this paper, the allocation of power plant load which is usually done with a single echelon as in the load flow calculation, is expanded into a multi echelon. A plant load allocation model based on the integration of economic dispatch and multi-echelon problem is proposed. The resulting model is called as Single Objective Multi Echelon Economic Dispatch (SOME ED). This model allows the distribution of electrical power in more detail in the transmission and distribution substations along the existing network. Considering the interconnection system where the distance between the plant and the load center is usually far away, therefore the loss in this model is seen as a function of distance. The advantages of this model is its capability of allocating electrical loads properly, as well as economic dispatch information with the flexibility of electric power system as a result of using multi-echelon. In this model, the flexibility can be viewed from two sides, namely the supply and demand sides, so that the security of the power system is maintained. The model was tested on a small artificial data. The results demonstrated a good performance. It is still very open to further develop the model considering the integration with renewable energy, multi-objective with environmental issues and applied to the case with a larger scale.

An Overview of Conceptual Frameworks

DTIC Science & Technology

2008-05-01

197 and references therein). The list given here varies somewhat to that in Frawley [13] Ch 5. No theoretical commitment is made here to the...equal Balance the electrical loads on each generator oald_v_2 to be equal in value, amount, etc. to sth else that has the opposite effect AM is a...actually or potentially circular (as when, for example, to demand is defined as ‘to request firmly’, and to request as ‘to demand gently

A novel microgrid demand-side management system for manufacturing facilities

NASA Astrophysics Data System (ADS)

Harper, Terance J.

Thirty-one percent of annual energy consumption in the United States occurs within the industrial sector, where manufacturing processes account for the largest amount of energy consumption and carbon emissions. For this reason, energy efficiency in manufacturing facilities is increasingly important for reducing operating costs and improving profits. Using microgrids to generate local sustainable power should reduce energy consumption from the main utility grid along with energy costs and carbon emissions. Also, microgrids have the potential to serve as reliable energy generators in international locations where the utility grid is often unstable. For this research, a manufacturing process that had approximately 20 kW of peak demand was matched with a solar photovoltaic array that had a peak output of approximately 3 KW. An innovative Demand-Side Management (DSM) strategy was developed to manage the process loads as part of this smart microgrid system. The DSM algorithm managed the intermittent nature of the microgrid and the instantaneous demand of the manufacturing process. The control algorithm required three input signals; one from the microgrid indicating the availability of renewable energy, another from the manufacturing process indicating energy use as a percent of peak production, and historical data for renewable sources and facility demand. Based on these inputs the algorithm had three modes of operation: normal (business as usual), curtailment (shutting off non-critical loads), and energy storage. The results show that a real-time management of a manufacturing process with a microgrid will reduce electrical consumption and peak demand. The renewable energy system for this research was rated to provide up to 13% of the total manufacturing capacity. With actively managing the process loads with the DSM program alone, electrical consumption from the utility grid was reduced by 17% on average. An additional 24% reduction was accomplished when the microgrid and DSM program was enabled together, resulting in a total reduction of 37%. On average, peak demand was reduced by 6%, but due to the intermittency of the renewable source and the billing structure for peak demand, only a 1% reduction was obtained. During a billing period, it only takes one day when solar irradiance is poor to affect the demand reduction capabilities. To achieve further demand reduction, energy storage should be introduced and integrated.

Life cycle assessment of flexibly fed biogas processes for an improved demand-oriented biogas supply.

PubMed

Ertem, Funda Cansu; Martínez-Blanco, Julia; Finkbeiner, Matthias; Neubauer, Peter; Junne, Stefan

2016-11-01

This paper analyses concepts to facilitate a demand oriented biogas supply at an agricultural biogas plant of a capacity of 500kWhel, operated with the co-digestion of maize, grass, rye silage and chicken manure. In contrast to previous studies, environmental impacts of flexible and the traditional baseload operation are compared. Life Cycle Assessment (LCA) was performed to detect the environmental impacts of: (i) variety of feedstock co-digestion scenarios by substitution of maize and (ii) loading rate scenarios with a focus on flexible feedstock utilization. Demand-driven biogas production is critical for an overall balanced power supply to the electrical grid. It results in lower amounts of emissions; feedstock loading rate scenarios resulted in 48%, 20%, 11% lower global warming (GWP), acidification (AP) and eutrophication potentials, and a 16% higher cumulative energy demand. Substitution of maize with biogenic-waste regarding to feedstock substitution scenarios could create 10% lower GWP and AP. Copyright © 2016 Elsevier Ltd. All rights reserved.

Impacts of Using Distributed Energy Resources to Reduce Peak Loads in Vermont

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruth, Mark F.; Lunacek, Monte S.; Jones, Birk

To help the United States develop a modern electricity grid that provides reliable power from multiple resources as well as resiliency under extreme conditions, the U.S. Department of Energy (DOE) is leading the Grid Modernization Initiative (GMI) to help shape the future of the nation's grid. Under the GMI, DOE funded the Vermont Regional Initiative project to provide the technical support and analysis to utilities that need to mitigate possible impacts of increasing renewable generation required by statewide goals. Advanced control of distributed energy resources (DER) can both support higher penetrations of renewable energy by balancing controllable loads to windmore » and photovoltaic (PV) solar generation and reduce peak demand by shedding noncritical loads. This work focuses on the latter. This document reports on an experiment that evaluated and quantified the potential benefits and impacts of reducing the peak load through demand response (DR) using centrally controllable electric water heaters (EWHs) and batteries on two Green Mountain Power (GMP) feeders. The experiment simulated various hypothetical scenarios that varied the number of controllable EWHs, the amount of distributed PV systems, and the number of distributed residential batteries. The control schemes were designed with several objectives. For the first objective, the primary simulations focused on reducing the load during the independent system operator (ISO) peak when capacity charges were the primary concern. The second objective was to mitigate DR rebound to avoid new peak loads and high ramp rates. The final objective was to minimize customers' discomfort, which is defined by the lack of hot water when it is needed. We performed the simulations using the National Renewable Energy Laboratory's (NREL's) Integrated Energy System Model (IESM) because it can simulate both electric power distribution feeder and appliance end use performance and it includes the ability to simulate multiple control strategies.« less

Modeling Chilled-Water Storage System Components for Coupling to a Small Modular Reactor in a Nuclear Hybrid Energy System

NASA Astrophysics Data System (ADS)

Misenheimer, Corey Thomas

The intermittency of wind and solar power puts strain on electric grids, often forcing carbonbased and nuclear sources of energy to operate in a load-follow mode. Operating nuclear reactors in a load-follow fashion is undesirable due to the associated thermal and mechanical stresses placed on the fuel and other reactor components. Various Thermal Energy Storage (TES) elements and ancillary energy applications can be coupled to nuclear (or renewable) power sources to help absorb grid instabilities caused by daily electric demand changes and renewable intermittency, thereby forming the basis of a candidate Nuclear Hybrid Energy System (NHES). During the warmer months of the year in many parts of the country, facility air-conditioning loads are significant contributors to the increase in the daily peak electric demand. Previous research demonstrated that a stratified chilled-water storage tank can displace peak cooling loads to off-peak hours. Based on these findings, the objective of this work is to evaluate the prospect of using a stratified chilled-water storage tank as a potential TES reservoir for a nuclear reactor in a NHES. This is accomplished by developing time-dependent models of chilled-water system components, including absorption chillers, cooling towers, a storage tank, and facility cooling loads appropriate for a large office space or college campus, as a callable FORTRAN subroutine. The resulting TES model is coupled to a high-fidelity mPower-sized Small Modular Reactor (SMR) Simulator, with the goal of utilizing excess reactor capacity to operate several sizable chillers in order to keep reactor power constant. Chilled-water production via single effect, lithium bromide (LiBr) absorption chillers is primarily examined in this study, although the use of electric chillers is briefly explored. Absorption chillers use hot water or low-pressure steam to drive an absorption-refrigeration cycle. The mathematical framework for a high-fidelity dynamic absorption chiller model is presented. The transient FORTRAN model is grounded on time-dependent mass, species, and energy conservation equations. Due to the vast computational costs of the high-fidelity model, a low-fidelity absorption chiller model is formulated and calibrated to mimic the behavior of the high-fidelity model. Stratified chilled-water storage tank performance is characterized using Computational Fluid Dynamics (CFD). The geometry employed in the CFD model represents a 5-million-gallon storage tank currently in use at a North Carolina college campus. Simulation results reveal the laminar numerical model most closely aligns with actual tank charging and discharging data. A subsequent parametric study corroborates storage tank behavior documented throughout literature and industry. Two absorption chiller configurations are considered. The first involves bypassing lowpressure steam from the low-pressure turbine to absorption chillers during periods of excess reactor capacity in order to keep reactor power constant. Simulation results show steam conditions downstream of the turbine control valves are a strong function of turbine load, and absorption chiller performance is hindered by reduced turbine impulse pressures at reduced turbine demands. A more suitable configuration entails integrating the absorption chillers into a flash vessel system that is thermally coupled to a sensible heat storage system. The sensible heat storage system is able to maintain reactor thermal output constant at 100% and match turbine output with several different electric demand profiles. High-pressure condensate in the sensible heat storage system is dropped across a let-down orifice and flashed in an ideal separator. Generated steam is sent to a bank of absorption chillers. Simulation results show enough steam is available during periods of reduced turbine demand to power four large absorption chillers to charge a 5-million-gallon stratified chilled-water storage tank, which is used to offset cooling loads in an adjacent facility. The coupled TES systems operating in conjunction with an SMR comprise the foundation of a tightly coupled NHES.

Optimizing the U.S. Electric System with a High Penetration of Renewables

NASA Astrophysics Data System (ADS)

Corcoran, B. A.; Jacobson, M. Z.

2012-12-01

As renewable energy generators are increasingly being installed throughout the U.S., there is growing interest in interconnecting diverse renewable generators (primarily wind and solar) across large geographic areas through an enhanced transmission system. This reduces variability in the aggregate power output, increases system reliability, and allows for the development of the best overall group of renewable technologies and sites to meet the load. Studies are therefore needed to determine the most efficient and economical plan to achieve large area interconnections in a future electric system with a high penetration of renewables. This research quantifies the effects of aggregating electric load and, separately, electric load together with diverse renewable generation throughout the ten Federal Energy Regulatory Commission (FERC) regions in the contiguous U.S. The effects of aggregating electric load alone -- including generator capacity capital cost savings, load energy shift operating cost savings, reserve requirement cost savings, and transmission costs -- were calculated for various groupings of FERC regions using 2006 data. Transmission costs outweighed cost savings due to aggregation in nearly all cases. East-west transmission layouts had the highest overall cost, and interconnecting ERCOT to adjacent FERC regions resulted in increased costs, both due to limited existing transmission capacity. Scenarios consisting of smaller aggregation groupings had the lowest overall cost. This analysis found no economic case for further aggregation of load alone within the U.S., except possibly in the West and Northwest. If aggregation of electric load is desired, then small, regional consolidations yield the lowest overall system cost. Next, the effects of aggregating electric load together with renewable electricity generation are being quantified through the development and use of an optimization tool in AMPL (A Mathematical Programming Language). This deterministic linear program solves for the least-cost organizational structure and system (generator, transmission, storage, and reserve requirements) for a highly renewable U.S. electric grid. The analysis will 1) examine a highly renewable 2006 electric system, and 2) create a "roadmap" from the existing 2006 system to a highly renewable system in 2030, accounting for projected price and demand changes and generator retirements based on age and environmental regulations. Ideally, results from this study will offer insight for a federal renewable energy policy (such as a renewable portfolio standard) and how to best organize regions for transmission planning.

Comparing post-combustion CO2 capture operation at retrofitted coal-fired power plants in the Texas and Great Britain electric grids

NASA Astrophysics Data System (ADS)

Cohen, Stuart M.; Chalmers, Hannah L.; Webber, Michael E.; King, Carey W.

2011-04-01

This work analyses the carbon dioxide (CO2) capture system operation within the Electric Reliability Council of Texas (ERCOT) and Great Britain (GB) electric grids using a previously developed first-order hourly electricity dispatch and pricing model. The grids are compared in their 2006 configuration with the addition of coal-based CO2 capture retrofits and emissions penalties from 0 to 100 US dollars per metric ton of CO2 (USD/tCO2). CO2 capture flexibility is investigated by comparing inflexible CO2 capture systems to flexible ones that can choose between full- and zero-load CO2 capture depending on which operating mode has lower costs or higher profits. Comparing these two grids is interesting because they have similar installed capacity and peak demand, and both are isolated electricity systems with competitive wholesale electricity markets. However, differences in capacity mix, demand patterns, and fuel markets produce diverging behaviours of CO2 capture at coal-fired power plants. Coal-fired facilities are primarily base load in ERCOT for a large range of CO2 prices but are comparably later in the dispatch order in GB and consequently often supply intermediate load. As a result, the ability to capture CO2 is more important for ensuring dispatch of coal-fired facilities in GB than in ERCOT when CO2 prices are high. In GB, higher overall coal prices mean that CO2 prices must be slightly higher than in ERCOT before the emissions savings of CO2 capture offset capture energy costs. However, once CO2 capture is economical, operating CO2 capture on half the coal fleet in each grid achieves greater emissions reductions in GB because the total coal-based capacity is 6 GW greater than in ERCOT. The market characteristics studied suggest greater opportunity for flexible CO2 capture to improve operating profits in ERCOT, but profit improvements can be offset by a flexibility cost penalty.

On the Integration of Wind and Solar Energy to Provide a Total Energy Supply in the U.S

NASA Astrophysics Data System (ADS)

Liebig, E. C.; Rhoades, A.; Sloggy, M.; Mills, D.; Archer, C. L.

2009-12-01

This study examines the feasibility of using renewable energy - mostly wind and solar radiation - as the primary sources of energy in the U.S., under the assumption that a nationwide electric transmission grid is in place. Previous studies have shown that solar output from California and Texas using energy storage is well correlated with the state energy load on an hour by hour basis throughout the year and with the US national load on a monthly basis. Other studies have shown that solar or wind alone can power the present US grid on average. This study explores scenarios for use of wind and solar energy together at the national scale on an hour by hour basis to determine if such a combination is a better match to national seasonal load scenarios than either of the two alone on an hour-by-hour basis. Actual hour by hour national load data from a particular year will be used as a basis, with some scenarios incorporating vehicle sector electrification and building heating and cooling using electric heat pumps. Hydro and geothermal generation can provide additional controllable output, when needed, to fulfill the hourly electricity and/or energy needs. Hourly wind speed data were calculated at the hub height of 80 m above the ground for the year 2006 at over 150 windy locations in the continental US using an extrapolation technique based on 10-m wind speed measurements and vertical sounding profiles. Using a 1.5 MW wind turbine as benchmark, the hourly wind power production nationwide was determined at all locations. Similarly, the hourly output from solar plants, with and without thermal storage, was calculated based on Ausra’s model assuming that the solar production would occur in the Southwest, the area with the greatest solar radiation density in the U.S. Hourly electricity demand for the year 2006 was obtained nationwide from a variety of sources, including the Federal Energy Regulation Commission. Hourly residential heating and cooking, industrial heat processing, and future electrified transportation loads were calculated from monthly energy consumption data from the Energy Information Administration. Using different scenarios of wind power penetration (10%, 20%, 30%, 50%, 80%, 100% of the average national electricity and/or energy demand), the remaining hourly electricity and/or energy load was covered by various combinations of solar, hydro, and geothermal generation. Statistics of the reliability of the various scenarios, as well as details on the area covered by wind and solar farms per each scenario, will be analyzed and presented.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhattarai, Bishnu; Kouzelis, Konstantinos; Mendaza, Iker

The gradual active load penetration in low voltage distribution grids is expected to challenge their network capacity in the near future. Distribution system operators should for this reason resort to either costly grid reinforcements or to demand side management mechanisms. Since demand side management implementation is usually cheaper, it is also the favorable solution. To this end, this article presents a framework for handling grid limit violations, both voltage and current, to ensure a secure and qualitative operation of the distribution grid. This framework consists of two steps, namely a proactive centralized and subsequently a reactive decentralized control scheme. Themore » former is employed to balance the one hour ahead load while the latter aims at regulating the consumption in real-time. In both cases, the importance of fair use of electricity demand flexibility is emphasized. Thus, it is demonstrated that this methodology aids in keeping the grid status within preset limits while utilizing flexibility from all flexibility participants.« less

Mathematical Model and Artificial Intelligent Techniques Applied to a Milk Industry through DSM

NASA Astrophysics Data System (ADS)

Babu, P. Ravi; Divya, V. P. Sree

2011-08-01

The resources for electrical energy are depleting and hence the gap between the supply and the demand is continuously increasing. Under such circumstances, the option left is optimal utilization of available energy resources. The main objective of this chapter is to discuss about the Peak load management and overcome the problems associated with it in processing industries such as Milk industry with the help of DSM techniques. The chapter presents a generalized mathematical model for minimizing the total operating cost of the industry subject to the constraints. The work presented in this chapter also deals with the results of application of Neural Network, Fuzzy Logic and Demand Side Management (DSM) techniques applied to a medium scale milk industrial consumer in India to achieve the improvement in load factor, reduction in Maximum Demand (MD) and also the consumer gets saving in the energy bill.

Robust optimization based energy dispatch in smart grids considering demand uncertainty

NASA Astrophysics Data System (ADS)

Nassourou, M.; Puig, V.; Blesa, J.

2017-01-01

In this study we discuss the application of robust optimization to the problem of economic energy dispatch in smart grids. Robust optimization based MPC strategies for tackling uncertain load demands are developed. Unexpected additive disturbances are modelled by defining an affine dependence between the control inputs and the uncertain load demands. The developed strategies were applied to a hybrid power system connected to an electrical power grid. Furthermore, to demonstrate the superiority of the standard Economic MPC over the MPC tracking, a comparison (e.g average daily cost) between the standard MPC tracking, the standard Economic MPC, and the integration of both in one-layer and two-layer approaches was carried out. The goal of this research is to design a controller based on Economic MPC strategies, that tackles uncertainties, in order to minimise economic costs and guarantee service reliability of the system.

Interface Control Document for the EMPACT Module that Estimates Electric Power Transmission System Response to EMP-Caused Damage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Werley, Kenneth Alan; Mccown, Andrew William

The EPREP code is designed to evaluate the effects of an Electro-Magnetic Pulse (EMP) on the electric power transmission system. The EPREP code embodies an umbrella framework that allows a user to set up analysis conditions and to examine analysis results. The code links to three major physics/engineering modules. The first module describes the EM wave in space and time. The second module evaluates the damage caused by the wave on specific electric power (EP) transmission system components. The third module evaluates the consequence of the damaged network on its (reduced) ability to provide electric power to meet demand. Thismore » third module is the focus of the present paper. The EMPACT code serves as the third module. The EMPACT name denotes EMP effects on Alternating Current Transmission systems. The EMPACT algorithms compute electric power transmission network flow solutions under severely damaged network conditions. Initial solutions are often characterized by unacceptible network conditions including line overloads and bad voltages. The EMPACT code contains algorithms to adjust optimally network parameters to eliminate network problems while minimizing outages. System adjustments include automatically adjusting control equipment (generator V control, variable transformers, and variable shunts), as well as non-automatic control of generator power settings and minimal load shedding. The goal is to evaluate the minimal loss of customer load under equilibrium (steady-state) conditions during peak demand.« less

Analysis of the Pricing Process in Electricity Market using Multi-Agent Model

NASA Astrophysics Data System (ADS)

Shimomura, Takahiro; Saisho, Yuichi; Fujii, Yasumasa; Yamaji, Kenji

Many electric utilities world-wide have been forced to change their ways of doing business, from vertically integrated mechanisms to open market systems. We are facing urgent issues about how we design the structures of power market systems. In order to settle down these issues, many studies have been made with market models of various characteristics and regulations. The goal of modeling analysis is to enrich our understanding of fundamental process that may appear. However, there are many kinds of modeling methods. Each has drawback and advantage about validity and versatility. This paper presents two kinds of methods to construct multi-agent market models. One is based on game theory and another is based on reinforcement learning. By comparing the results of the two methods, they can advance in validity and help us figure out potential problems in electricity markets which have oligopolistic generators, demand fluctuation and inelastic demand. Moreover, this model based on reinforcement learning enables us to consider characteristics peculiar to electricity markets which have plant unit characteristics, seasonable and hourly demand fluctuation, real-time regulation market and operating reserve market. This model figures out importance of the share of peak-load-plants and the way of designing operating reserve market.

Costs for integrating wind into the future ERCOT system with related costs for savings in CO2 emissions.

PubMed

Lu, Xi; McElroy, Michael B; Sluzas, Nora A

2011-04-01

Wind power can make an important contribution to the goal of reducing emissions of CO2. The major problem relates to the intrinsic variability of the source and the difficulty of reconciling the supply of electricity with demand particularly at high levels of wind penetration. This challenge is explored for the case of the ERCOT system in Texas. Demand for electricity in Texas is projected to increase by approximately 60% by 2030. Considering hourly load data reported for 2006, assuming that the pattern of demand in 2030 should be similar to 2006, and adopting as a business as usual (BAU) reference an assumption that the anticipated additional electricity should be supplied by a combination of coal and gas with prices, discounted to 2007 dollars of $2 and $6 per MMBTU respectively, we conclude that the bus-bar price for electricity would increase by about 1.1 ¢/kWh at a wind penetration level of 30%, by about 3.4 ¢/kWh at a penetration level of 80%. Corresponding costs for reductions in CO2 range from $20/ton to $60/ton. A number of possibilities are discussed that could contribute to a reduction in these costs including the impact of an expanded future fleet of electrically driven vehicles.

An implementation of particle swarm optimization to evaluate optimal under-voltage load shedding in competitive electricity markets

NASA Astrophysics Data System (ADS)

Hosseini-Bioki, M. M.; Rashidinejad, M.; Abdollahi, A.

2013-11-01

Load shedding is a crucial issue in power systems especially under restructured electricity environment. Market-driven load shedding in reregulated power systems associated with security as well as reliability is investigated in this paper. A technoeconomic multi-objective function is introduced to reveal an optimal load shedding scheme considering maximum social welfare. The proposed optimization problem includes maximum GENCOs and loads' profits as well as maximum loadability limit under normal and contingency conditions. Particle swarm optimization (PSO) as a heuristic optimization technique, is utilized to find an optimal load shedding scheme. In a market-driven structure, generators offer their bidding blocks while the dispatchable loads will bid their price-responsive demands. An independent system operator (ISO) derives a market clearing price (MCP) while rescheduling the amount of generating power in both pre-contingency and post-contingency conditions. The proposed methodology is developed on a 3-bus system and then is applied to a modified IEEE 30-bus test system. The obtained results show the effectiveness of the proposed methodology in implementing the optimal load shedding satisfying social welfare by maintaining voltage stability margin (VSM) through technoeconomic analyses.

Essays on Mathematical Optimization for Residential Demand Response in the Energy Sector

NASA Astrophysics Data System (ADS)

Palaparambil Dinesh, Lakshmi

In the electric utility industry, it could be challenging to adjust supply to match demand due to large generator ramp up times, high generation costs and insufficient in-house generation capacity. Demand response (DR) is a technique for adjusting the demand for electric power instead of the supply. Direct Load Control (DLC) is one of the ways to implement DR. DLC program participants sign up for power interruption contracts and are given financial incentives for curtailing electricity usage during peak demand time periods. This dissertation studies a DLC program for residential air conditioners using mathematical optimization models. First, we develop a model that determines what contract parameters to use in designing contracts between the provider and residential customers, when to turn which power unit on or off and how much power to cut during peak demand hours. The model uses information on customer preferences for choice of contract parameters such as DLC financial incentives and energy usage curtailment. In numerical experiments, the proposed model leads to projected cost savings of the order of 20%, compared to a current benchmark model used in practice. We also quantify the impact of factors leading to cost savings and study characteristics of customers picked by different contracts. Second, we study a DLC program in a macro economic environment using a Computable General Equilibrium (CGE) model. A CGE model is used to study the impact of external factors such as policy and technology changes on different economic sectors. Here we differentiate customers based on their preference for DLC programs by using different values for price elasticity of demand for electricity commodity. Consequently, DLC program customers could substitute demand for electricity commodity with other commodities such as transportation sector. Price elasticity of demand is calculated using a novel methodology that incorporates customer preferences for DLC contracts from the first model. The calculation of elasticity based on our methodology is useful since the prices of commodities are not only determined by aggregate demand and supply but also by customers' relative preferences for commodities. In addition to this we quantify the indirect substitution and rebound effects on sectoral activity levels, incomes and prices based on customer differences, when DLC is implemented.

Smart Energy Management of Multiple Full Cell Powered Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

MOhammad S. Alam

2007-04-23

In this research project the University of South Alabama research team has been investigating smart energy management and control of multiple fuel cell power sources when subjected to varying demands of electrical and thermal loads together with demands of hydrogen production. This research has focused on finding the optimal schedule of the multiple fuel cell power plants in terms of electric, thermal and hydrogen energy. The optimal schedule is expected to yield the lowest operating cost. Our team is also investigating the possibility of generating hydrogen using photoelectrochemical (PEC) solar cells through finding materials for efficient light harvesting photoanodes. Themore » goal is to develop an efficient and cost effective PEC solar cell system for direct electrolysis of water. In addition, models for hydrogen production, purification, and storage will be developed. The results obtained and the data collected will be then used to develop a smart energy management algorithm whose function is to maximize energy conservation within a managed set of appliances, thereby lowering O/M costs of the Fuel Cell power plant (FCPP), and allowing more hydrogen generation opportunities. The Smart Energy Management and Control (SEMaC) software, developed earlier, controls electrical loads in an individual home to achieve load management objectives such that the total power consumption of a typical residential home remains below the available power generated from a fuel cell. In this project, the research team will leverage the SEMaC algorithm developed earlier to create a neighborhood level control system.« less

Reducing Gridlock on the Grid: Utility Trends in Managing Peak Electric Load through Residential Demand Response

NASA Astrophysics Data System (ADS)

McDonald, Betsy

Utilities across the United States are piloting residential demand response programs to help manage peak electric demand. Using publicly available program evaluations, this thesis analyzes nine such programs to uncover and synthesize the range of program offerings, goals, enrollment strategies, and customer experiences. This review reveals that program participation, components, and results differ based on a variety of factors, including geographic characteristics, program goals, and implementation strategies. The diversity of program designs and evaluation findings suggests an underlying tension between the need to generate cost-effective program impacts and the desire to increase accessibility so that program benefits are not exclusive to certain segments of the population. For more significant and impactful engagement, program goals may need to shift. State level policy support could help shift program goals toward increasing program accessibility. Future research should explore creative strategies that target existing barriers and allow for more inclusive deployment.

Climate change, renewable energy and population impact on future energy demand for Burkina Faso build environment

NASA Astrophysics Data System (ADS)

Ouedraogo, B. I.

This research addresses the dual challenge faced by Burkina Faso engineers to design sustainable low-energy cost public buildings and domestic dwellings while still providing the required thermal comfort under warmer temperature conditions caused by climate change. It was found base don climate change SRES scenario A2 that predicted mean temperature in Burkina Faso will increase by 2oC between 2010 and 2050. Therefore, in order to maintain a thermally comfortable 25oC inside public buildings, the projected annual energy consumption for cooling load will increase by 15%, 36% and 100% respectively for the period between 2020 to 2039, 2040 to 2059 and 2070 to 2089 when compared to the control case. It has also been found that a 1% increase in population growth will result in a 1.38% and 2.03% increase in carbon emission from primary energy consumption and future electricity consumption respectively. Furthermore, this research has investigated possible solutions for adaptation to the severe climate change and population growth impact on energy demand in Burkina Faso. Shading devices could potentially reduce the cooling load by up to 40%. Computer simulation programming of building energy consumption and a field study has shown that adobe houses have the potential of significantly reducing energy demand for cooling and offer a formidable method for climate change adaptation. Based on the Net Present Cost, hybrid photovoltaic (PV) and Diesel generator energy production configuration is the most cost effective local electricity supply system, for areas without electricity at present, with a payback time of 8 years when compared to diesel generator stand-alone configuration. It is therefore a viable solution to increase electricity access to the majority of the population.

Real-time pricing strategy of micro-grid energy centre considering price-based demand response

NASA Astrophysics Data System (ADS)

Xu, Zhiheng; Zhang, Yongjun; Wang, Gan

2017-07-01

With the development of energy conversion technology such as power to gas (P2G), fuel cell and so on, the coupling between energy sources becomes more and more closely. Centralized dispatch among electricity, natural gas and heat will become a trend. With the goal of maximizing the system revenue, this paper establishes the model of micro-grid energy centre based on energy hub. According to the proposed model, the real-time pricing strategy taking into account price-based demand response of load is developed. And the influence of real-time pricing strategy on the peak load shifting is discussed. In addition, the impact of wind power predicted inaccuracy on real-time pricing strategy is analysed.

Demand response-enabled model predictive HVAC load control in buildings using real-time electricity pricing

NASA Astrophysics Data System (ADS)

Avci, Mesut

A practical cost and energy efficient model predictive control (MPC) strategy is proposed for HVAC load control under dynamic real-time electricity pricing. The MPC strategy is built based on a proposed model that jointly minimizes the total energy consumption and hence, cost of electricity for the user, and the deviation of the inside temperature from the consumer's preference. An algorithm that assigns temperature set-points (reference temperatures) to price ranges based on the consumer's discomfort tolerance index is developed. A practical parameter prediction model is also designed for mapping between the HVAC load and the inside temperature. The prediction model and the produced temperature set-points are integrated as inputs into the MPC controller, which is then used to generate signal actions for the AC unit. To investigate and demonstrate the effectiveness of the proposed approach, a simulation based experimental analysis is presented using real-life pricing data. An actual prototype for the proposed HVAC load control strategy is then built and a series of prototype experiments are conducted similar to the simulation studies. The experiments reveal that the MPC strategy can lead to significant reductions in overall energy consumption and cost savings for the consumer. Results suggest that by providing an efficient response strategy for the consumers, the proposed MPC strategy can enable the utility providers to adopt efficient demand management policies using real-time pricing. Finally, a cost-benefit analysis is performed to display the economic feasibility of implementing such a controller as part of a building energy management system, and the payback period is identified considering cost of prototype build and cost savings to help the adoption of this controller in the building HVAC control industry.

Predictive Scheduling for Electric Vehicles Considering Uncertainty of Load and User Behaviors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Bin; Huang, Rui; Wang, Yubo

2016-05-02

Un-coordinated Electric Vehicle (EV) charging can create unexpected load in local distribution grid, which may degrade the power quality and system reliability. The uncertainty of EV load, user behaviors and other baseload in distribution grid, is one of challenges that impedes optimal control for EV charging problem. Previous researches did not fully solve this problem due to lack of real-world EV charging data and proper stochastic model to describe these behaviors. In this paper, we propose a new predictive EV scheduling algorithm (PESA) inspired by Model Predictive Control (MPC), which includes a dynamic load estimation module and a predictive optimizationmore » module. The user-related EV load and base load are dynamically estimated based on the historical data. At each time interval, the predictive optimization program will be computed for optimal schedules given the estimated parameters. Only the first element from the algorithm outputs will be implemented according to MPC paradigm. Current-multiplexing function in each Electric Vehicle Supply Equipment (EVSE) is considered and accordingly a virtual load is modeled to handle the uncertainties of future EV energy demands. This system is validated by the real-world EV charging data collected on UCLA campus and the experimental results indicate that our proposed model not only reduces load variation up to 40% but also maintains a high level of robustness. Finally, IEC 61850 standard is utilized to standardize the data models involved, which brings significance to more reliable and large-scale implementation.« less

Optimal Operation Method of Smart House by Controllable Loads based on Smart Grid Topology

NASA Astrophysics Data System (ADS)

Yoza, Akihiro; Uchida, Kosuke; Yona, Atsushi; Senju, Tomonobu

2013-08-01

From the perspective of global warming suppression and depletion of energy resources, renewable energy such as wind generation (WG) and photovoltaic generation (PV) are getting attention in distribution systems. Additionally, all electrification apartment house or residence such as DC smart house have increased in recent years. However, due to fluctuating power from renewable energy sources and loads, supply-demand balancing fluctuations of power system become problematic. Therefore, "smart grid" has become very popular in the worldwide. This article presents a methodology for optimal operation of a smart grid to minimize the interconnection point power flow fluctuations. To achieve the proposed optimal operation, we use distributed controllable loads such as battery and heat pump. By minimizing the interconnection point power flow fluctuations, it is possible to reduce the maximum electric power consumption and the electric cost. This system consists of photovoltaics generator, heat pump, battery, solar collector, and load. In order to verify the effectiveness of the proposed system, MATLAB is used in simulations.

Quantifying the Opportunity Space for Future Electricity Generation: An Application to Offshore Wind Energy in the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marcy, Cara; Beiter, Philipp

2016-09-01

This report provides a high-level indicator of the future electricity demand for additional electric power generation that is not met by existing generation sources between 2015 and 2050. The indicator is applied to coastal regions, including the Great Lakes, to assess the regional opportunity space for offshore wind. An assessment of opportunity space can be a first step in determining the prospects and the system value of a technology. The metric provides the maximal amount of additional generation that is likely required to satisfy load in future years.

Assessment and Methods for Supply-Following Loads in Modern Electricity Grids with Deep Renewables Penetration

DTIC Science & Technology

2013-12-18

from a combination of increased electricity demand, poor output from the large contingent of wind turbines in Texas (the most in the U.S.), and...2.8 GW of wind power farms in California are onshore, consist of low-altitude (m) wind turbines , and are located in 8 of California’s 58 counties...offshore wind turbines , and the improvement of turbine efficiency will enable massive potential wind resources. Looking more closely at the temporal

Active colloids as mobile microelectrodes for unified label-free selective cargo transport.

PubMed

Boymelgreen, Alicia M; Balli, Tov; Miloh, Touvia; Yossifon, Gilad

2018-02-22

Utilization of active colloids to transport both biological and inorganic cargo has been widely examined in the context of applications ranging from targeted drug delivery to sample analysis. In general, carriers are customized to load one specific target via a mechanism distinct from that driving the transport. Here we unify these tasks and extend loading capabilities to include on-demand selection of multiple nano/micro-sized targets without the need for pre-labelling or surface functionalization. An externally applied electric field is singularly used to drive the active cargo carrier and transform it into a mobile floating electrode that can attract (trap) or repel specific targets from its surface by dielectrophoresis, enabling dynamic control of target selection, loading and rate of transport via the electric field parameters. In the future, dynamic selectivity could be combined with directed motion to develop building blocks for bottom-up fabrication in applications such as additive manufacturing and soft robotics.

Mechanical failure of fine root cortical cells initiates plant hydraulic decline during drought

USDA-ARS?s Scientific Manuscript database

Root systems perform the crucial task of absorbing water from the soil to meet the demands of a transpiring canopy. Roots are thought to operate like electrical fuses, which break when carrying an excessive load under conditions of drought stress. Yet the exact site and sequence of this dysfunction ...

Modeling and stability analysis for the upper atmosphere research satellite auxiliary array switch component

NASA Technical Reports Server (NTRS)

Wolfgang, R.; Natarajan, T.; Day, J.

1987-01-01

A feedback control system, called an auxiliary array switch, was designed to connect or disconnect auxiliary solar panel segments from a spacecraft electrical bus to meet fluctuating demand for power. A simulation of the control system was used to carry out a number of design and analysis tasks that could not economically be performed with a breadboard of the hardware. These tasks included: (1) the diagnosis of a stability problem, (2) identification of parameters to which the performance of the control system was particularly sensitive, (3) verification that the response of the control system to anticipated fluctuations in the electrical load of the spacecraft was satisfactory, and (4) specification of limitations on the frequency and amplitude of the load fluctuations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kung, Feitau; Frank, Stephen; Scheib, Jennifer

A zero energy building (ZEB)—also known as a net zero energy or zero net energy building—is a building that exports as much renewable energy as the total energy it imports from other sources on an annual basis (DOE 2015). Large-scale and commercially viable ZEBs are now in the marketplace, and they are expected to become a larger share of the commercial building footprint as government and private sector policies continue to promote the development of buildings that produce more on-site energy than they use. However, the load profiles of ZEBs are currently perceived by electric utilities to be unfavorable andmore » unpredictable. As shown in Figure ES-1, ZEB load profiles can have abrupt changes in magnitude, at times switching rapidly between exporting and importing electricity. This is a challenge for utilities, which are responsible for constantly balancing electricity supply and demand across the grid. Addressing these concerns will require new strategies and tools.« less

Multiobjective Model of Time-of-Use and Stepwise Power Tariff for Residential Consumers in Regulated Power Markets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Bin; Yang, Rui; Li, Canbing

Here, time-of-use (TOU) rates and stepwise power tariff (SPT) are important economic levers to motivate residents to shift their electricity usage in response to electricity price. In this paper, a new multiobjective optimal tariff-making model of time-of-use and stepwise power tariff (TOUSPT) is proposed, which combines the complementary characteristics of two power tariffs, for residential energy conservation and peak load shaving. In the proposed approach, the residential demand response with price elasticity in regulated power market is considered to determine the optimum peak-valley TOU tariffs for each stepwise electricity partition. Furthermore, a practical case study is implemented to test themore » effectiveness of the proposed TOUSPT, and the results demonstrate that TOUSPT can achieve efficient end-use energy saving and also shift load from peak to off-peak periods.« less

Multiobjective Model of Time-of-Use and Stepwise Power Tariff for Residential Consumers in Regulated Power Markets

DOE PAGES

Zhou, Bin; Yang, Rui; Li, Canbing; ...

2017-07-04

Here, time-of-use (TOU) rates and stepwise power tariff (SPT) are important economic levers to motivate residents to shift their electricity usage in response to electricity price. In this paper, a new multiobjective optimal tariff-making model of time-of-use and stepwise power tariff (TOUSPT) is proposed, which combines the complementary characteristics of two power tariffs, for residential energy conservation and peak load shaving. In the proposed approach, the residential demand response with price elasticity in regulated power market is considered to determine the optimum peak-valley TOU tariffs for each stepwise electricity partition. Furthermore, a practical case study is implemented to test themore » effectiveness of the proposed TOUSPT, and the results demonstrate that TOUSPT can achieve efficient end-use energy saving and also shift load from peak to off-peak periods.« less

Thermal energy storage for power generation applications

NASA Astrophysics Data System (ADS)

Drost, M. K.; Antoniak, Zen I.; Brown, D. R.

1990-03-01

Studies strongly indicate that the United States will face widespread electrical power constraints in the 1990s. In many cases, the demand for increased power will occur during peak and intermediate demand periods. While natural gas is currently plentiful and economically attractive for meeting peak and intermediate loads, the development of a coal-fired peaking option would give utilities insurance against unexpected supply shortages or cost increases. This paper discusses a conceptual evaluation of using thermal energy storage (TES) to improve the economics of coal-fired peak and intermediate load power generation. The use of TES can substantially improve the economic attractiveness of meeting peak and intermediate loads with coal-fired power generation. In this case, conventional pulverized coal combustion equipment is continuously operated to heat molten nitrate salt, which is then stored. During peak demand periods, hot salt is withdrawn from storage and used to generate steam for a Rankine steam power cycle. This allows the coal-fired salt heater to be approximately one-third the size of a coal-fired boiler in a conventional cycling plant. The general impact is to decouple the generation of thermal energy from its conversion to electricity. The present study compares a conventional cycling pulverized coal-fired power plant to a pulverized coal-fired plant using nitrate salt TES. The study demonstrates that a coal-fired salt heater is technically feasible and should be less expensive than a similar coal-fired boiler. The results show the use of nitrate salt TES reduced the levelized cost of power by between 5 and 24 percent, depending on the operating schedule.

Electricity exchange and the valuation of transnational transmission access: A case study of intra-regional integration of the electric industries of Argentina and Chile

NASA Astrophysics Data System (ADS)

Brereton, Beverly Ann

The interconnection of neighboring electricity networks provides opportunities for the realization of synergies between electricity systems. Examples of the synergies to be realized are the rationalized management of the electricity networks whose fuel source domination differs, and the exploitation of non-coincident system peak demands. These factors allow technology diversity in the satisfaction of electricity demand, the coordination of planning and maintenance schedules between the networks by exploiting the cost differences in the pool of generation assets and the load configuration differences in the neighboring locations. The interconnection decision studied in this dissertation focused on the electricity networks of Argentina and Chile whose electricity systems operate in isolation at the current time. The cooperative game-theoretic framework was applied in the analysis of the decision facing the two countries and the net surplus to be derived from interconnection was evaluated. Measurement of the net gains from interconnection used in this study were reflected in changes in generating costs under the assumption that demand is fixed under all scenarios. With the demand for electricity assumed perfectly inelastic, passive or aggressive bidding strategies were considered under the scenarios for the generators in the two countries. The interconnection decision was modeled using a linear power flow model which utilizes linear programming techniques to reflect dispatch procedures based on generation bids. Results of the study indicate that the current interconnection project between Argentina and Chile will not result in positive net surplus under a variety of scenarios. Only under significantly reduced interconnection cost will the venture prove attractive. Possible sharing mechanisms were also explored in the research and a symmetric distribution of the net surplus to be derived under the reduced interconnection cost scenario was recommended to preserve equity in the allocation of the interconnection gains.

Managing Sustainable Demand-side Infrastructure for Power System Ancillary Services

NASA Astrophysics Data System (ADS)

Parkinson, Simon Christopher

Widespread access to renewable electricity is seen as a viable method to mitigate carbon emissions, although problematic are the issues associated with the integration of the generation systems within current power system configurations. Wind power plants are the primary large-scale renewable generation technology applied globally, but display considerable short-term supply variability that is difficult to predict. Power systems are currently not designed to operate under these conditions, and results in the need to increase operating reserve in order to guarantee stability. Often, operating conventional generation as reserve is both technically and economically inefficient, which can overshadow positive benefits associated with renewable energy exploitation. The purpose of this thesis is to introduce and assess an alternative method of enhancing power system operations through the control of electric loads. In particular, this thesis focuses on managing highly-distributed sustainable demand-side infrastructure, in the form of heat pumps, electric vehicles, and electrolyzers, as dispatchable short-term energy balancing resources. The main contribution of the thesis is an optimal control strategy capable of simultaneously balancing grid- and demand-side objectives. The viability of the load control strategy is assessed through model-based simulations that explicitly track end-use functionality of responsive devices within a power systems analysis typically implemented to observe the effects of integrated wind energy systems. Results indicate that there is great potential for the proposed method to displace the need for increased reserve capacity in systems considering a high penetration of wind energy, thereby allowing conventional generation to operate more efficiently and avoid the need for possible capacity expansions.

Demand Response Potential for California SubLAPs and Local Capacity Planning Areas: An Addendum to the 2025 California Demand Response Potential Study – Phase 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alstone, Peter; Potter, Jennifer; Piette, Mary Ann

The 2025 California Demand Response Potential Study Phase 2 Report1 was released on March 1, 2017, and described a range of pathways for Demand Response (DR) to support a clean, stable, and cost-effective electric grid for California. One of the Report’s key findings was that while there appears to be very low future value for untargeted DR Shed aimed at system-wide peak load conditions, there could be significant value for locally focused Shed resources. Although the dynamics of renewable capacity expansion have reduced the pressure to build new thermal generation in general, there are still transmission-constrained areas of the statemore » where load growth needs to be managed with the addition of new local capacity, which could include DERs and/or DR. This Addendum to the Phase 2 Report presents a breakdown of the expected future “Local Shed” DR potential at a finer geographic resolution than what is available in the original report, with results summarized by SubLAP and Local Capacity Area (LCA).« less

Improving electrical power systems reliability through locally controlled distributed curtailable load

NASA Astrophysics Data System (ADS)

Dehbozorgi, Mohammad Reza

2000-10-01

Improvements in power system reliability have always been of interest to both power companies and customers. Since there are no sizable electrical energy storage elements in electrical power systems, the generated power should match the load demand at any given time. Failure to meet this balance may cause severe system problems, including loss of generation and system blackouts. This thesis proposes a methodology which can respond to either loss of generation or loss of load. It is based on switching of electric water heaters using power system frequency as the controlling signal. The proposed methodology encounters, and the thesis has addressed, the following associated problems. The controller must be interfaced with the existing thermostat control. When necessary to switch on loads, the water in the tank should not be overheated. Rapid switching of blocks of load, or chattering, has been considered. The contributions of the thesis are: (A) A system has been proposed which makes a significant portion of the distributed loads connected to a power system to behave in a predetermined manner to improve the power system response during disturbances. (B) The action of the proposed system is transparent to the customers. (C) The thesis proposes a simple analysis for determining the amount of such loads which might be switched and relates this amount to the size of the disturbances which can occur in the utility. (D) The proposed system acts without any formal communication links, solely using the embedded information present system-wide. (E) The methodology of the thesis proposes switching of water heater loads based on a simple, localized frequency set-point controller. The thesis has identified the consequent problem of rapid switching of distributed loads, which is referred to as chattering. (F) Two approaches have been proposed to reduce chattering to tolerable levels. (G) A frequency controller has been designed and built according to the specifications required to switch electric water heater loads in response to power system disturbances. (H) A cost analysis for building and installing the distributed frequency controller has been carried out. (I) The proposed equipment and methodology has been implemented and tested successfully. (Abstract shortened by UMI.)

Optimization of 10 kW solar photovoltaic – diesel generator hybrid energy system for different load factors at Jaisalmer location of Rajasthan, India

NASA Astrophysics Data System (ADS)

Saraswat, S. K.; Rao, K. V. S.

2018-03-01

Jaisalmer town in Rajasthan, India is having annual average solar insolation of 5.80 kWh/m2/day and 270 – 300 clear sky days in a year. A 10 kW off-grid hybrid energy system (HES) consisting of solar photovoltaic panels – diesel generator – bidirectional converter and batteries with zero percentage loss of load for Jaisalmer is designed using HOMER (version 3.4.3) software. Different system load factors of 0.33, 0.50, 0.67, 0.83 and 1 corresponding to fraction of running hours per day of the system are considered. The system is analyzed for all three aspects, namely, electrical, economic and emission point of view. Least levelized cost of electricity (LCOE) of Rs. 8.43/kWh is obtained at a load factor value of 0.5. If diesel generator alone (without Solar PV) is used to fulfil the demand for a load factor of 0.5the value of LCOE is obtained Rs.19.23/kWh. Comparison of results obtained for HES and diesel generator are made for load factor of 0.5 and 1.

Design of capacity incentive and energy compensation for demand response programs

NASA Astrophysics Data System (ADS)

Liu, Zhoubin; Cui, Wenqi; Shen, Ran; Hu, Yishuang; Wu, Hui; Ye, Chengjin

2018-02-01

Variability and Uncertainties caused by renewable energy sources have called for large amount of balancing services. Demand side resources (DSRs) can be a good alternative of traditional generating units to provide balancing service. In the areas where the electricity market has not been fully established, e.g., China, DSRs can help balance the power system with incentive-based demand response programs. However, there is a lack of information about the interruption cost of consumers in these areas, making it hard to determine the rational amount of capacity incentive and energy compensation for the participants of demand response programs. This paper proposes an algorithm to calculate the amount of capacity incentive and energy compensation for demand response programs when there lacks the information about interruption cost. Available statistical information of interruption cost in referenced areas is selected as the referenced data. Interruption cost of the targeted area is converted from the referenced area by product per electricity consumption. On this basis, capacity incentive and energy compensation are obtained to minimize the payment to consumers. Moreover, the loss of consumers is guaranteed to be covered by the revenue they earned from load serving entities.

Effects of precision demands and mental pressure on muscle activation and hand forces in computer mouse tasks.

PubMed

Visser, Bart; De Looze, Michiel; De Graaff, Matthijs; Van Dieën, Jaap

2004-02-05

The objective of the present study was to gain insight into the effects of precision demands and mental pressure on the load of the upper extremity. Two computer mouse tasks were used: an aiming and a tracking task. Upper extremity loading was operationalized as the myo-electric activity of the wrist flexor and extensor and of the trapezius descendens muscles and the applied grip- and click-forces on the computer mouse. Performance measures, reflecting the accuracy in both tasks and the clicking rate in the aiming task, indicated that the levels of the independent variables resulted in distinguishable levels of accuracy and work pace. Precision demands had a small effect on upper extremity loading with a significant increase in the EMG-amplitudes (21%) of the wrist flexors during the aiming tasks. Precision had large effects on performance. Mental pressure had substantial effects on EMG-amplitudes with an increase of 22% in the trapezius when tracking and increases of 41% in the trapezius and 45% and 140% in the wrist extensors and flexors, respectively, when aiming. During aiming, grip- and click-forces increased by 51% and 40% respectively. Mental pressure had small effects on accuracy but large effects on tempo during aiming. Precision demands and mental pressure in aiming and tracking tasks with a computer mouse were found to coincide with increased muscle activity in some upper extremity muscles and increased force exertion on the computer mouse. Mental pressure caused significant effects on these parameters more often than precision demands. Precision and mental pressure were found to have effects on performance, with precision effects being significant for all performance measures studied and mental pressure effects for some of them. The results of this study suggest that precision demands and mental pressure increase upper extremity load, with mental pressure effects being larger than precision effects. The possible role of precision demands as an indirect mental stressor in working conditions is discussed.

Bifurcation Analysis of a DC-DC Bidirectional Power Converter Operating with Constant Power Loads

NASA Astrophysics Data System (ADS)

Cristiano, Rony; Pagano, Daniel J.; Benadero, Luis; Ponce, Enrique

Direct current (DC) microgrids (MGs) are an emergent option to satisfy new demands for power quality and integration of renewable resources in electrical distribution systems. This work addresses the large-signal stability analysis of a DC-DC bidirectional converter (DBC) connected to a storage device in an islanding MG. This converter is responsible for controlling the balance of power (load demand and generation) under constant power loads (CPLs). In order to control the DC bus voltage through a DBC, we propose a robust sliding mode control (SMC) based on a washout filter. Dynamical systems techniques are exploited to assess the quality of this switching control strategy. In this sense, a bifurcation analysis is performed to study the nonlinear stability of a reduced model of this system. The appearance of different bifurcations when load parameters and control gains are changed is studied in detail. In the specific case of Teixeira Singularity (TS) bifurcation, some experimental results are provided, confirming the mathematical predictions. Both a deeper insight in the dynamic behavior of the controlled system and valuable design criteria are obtained.

Modeling of plug-in electric vehicle travel patterns and charging load based on trip chain generation

NASA Astrophysics Data System (ADS)

Wang, Dai; Gao, Junyu; Li, Pan; Wang, Bin; Zhang, Cong; Saxena, Samveg

2017-08-01

Modeling PEV travel and charging behavior is the key to estimate the charging demand and further explore the potential of providing grid services. This paper presents a stochastic simulation methodology to generate itineraries and charging load profiles for a population of PEVs based on real-world vehicle driving data. In order to describe the sequence of daily travel activities, we use the trip chain model which contains the detailed information of each trip, namely start time, end time, trip distance, start location and end location. A trip chain generation method is developed based on the Naive Bayes model to generate a large number of trips which are temporally and spatially coupled. We apply the proposed methodology to investigate the multi-location charging loads in three different scenarios. Simulation results show that home charging can meet the energy demand of the majority of PEVs in an average condition. In addition, we calculate the lower bound of charging load peak on the premise of lowest charging cost. The results are instructive for the design and construction of charging facilities to avoid excessive infrastructure.

A Flipped Mode Teaching Approach for Large and Advanced Electrical Engineering Courses

ERIC Educational Resources Information Center

Ravishankar, Jayashri; Epps, Julien; Ambikairajah, Eliathamby

2018-01-01

A fully flipped mode teaching approach is challenging for students in advanced engineering courses, because of demanding pre-class preparation load, due to the complex and analytical nature of the topics. When this is applied to large classes, it brings an additional complexity in terms of promoting the intended active learning. This paper…

76 FR 66211 - Enhancement of Electricity Market Surveillance and Analysis Through Ongoing Electronic Delivery...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-26

... indicating the price at which they are willing to supply various quantities of energy. Load- serving entities submit demand bids indicating the price at which they are willing to buy various quantities of energy... resources can affect the market price and whether the offers should be mitigated. If an energy supply offer...

Returning vacationers face heavy reading loads. [Reports, surveys and projections on the national energy supply

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berg, T.F.

1991-10-01

This article reviews the various reports, surveys and projections on the national energy supply of the summer of 1991. Discussed are the natural gas supplies, competitive electric power production, reliability of independent power, public attitudes toward natural gas, the market share of natural gas, and projection of US energy supply and demand.

The Energy Imperative: Report Update

DTIC Science & Technology

2008-11-01

projections for 2030.2 • Renewable power generation from solar , wind, biomass, and geothermal resources is growing rapidly, but these sources still...consistent policy approach to address cost, regulatory, and transmission infrastructure challenges. For solar photovoltaic (PV) technology, basic...research is particularly important to make the needed improvements in cost and performance. • Solar power can help meet peak load electricity demand

Solar energy thermally powered electrical generating system

NASA Technical Reports Server (NTRS)

Owens, William R. (Inventor)

1989-01-01

A thermally powered electrical generating system for use in a space vehicle is disclosed. The rate of storage in a thermal energy storage medium is controlled by varying the rate of generation and dissipation of electrical energy in a thermally powered electrical generating system which is powered from heat stored in the thermal energy storage medium without exceeding a maximum quantity of heat. A control system (10) varies the rate at which electrical energy is generated by the electrical generating system and the rate at which electrical energy is consumed by a variable parasitic electrical load to cause storage of an amount of thermal energy in the thermal energy storage system at the end of a period of insolation which is sufficient to satisfy the scheduled demand for electrical power to be generated during the next period of eclipse. The control system is based upon Kalman filter theory.

Energy efficiency design strategies for buildings with grid-connected photovoltaic systems

NASA Astrophysics Data System (ADS)

Yimprayoon, Chanikarn

The building sector in the United States represents more than 40% of the nation's energy consumption. Energy efficiency design strategies and renewable energy are keys to reduce building energy demand. Grid-connected photovoltaic (PV) systems installed on buildings have been the fastest growing market in the PV industry. This growth poses challenges for buildings qualified to serve in this market sector. Electricity produced from solar energy is intermittent. Matching building electricity demand with PV output can increase PV system efficiency. Through experimental methods and case studies, computer simulations were used to investigate the priorities of energy efficiency design strategies that decreased electricity demand while producing load profiles matching with unique output profiles from PV. Three building types (residential, commercial, and industrial) of varying sizes and use patterns located in 16 climate zones were modeled according to ASHRAE 90.1 requirements. Buildings were analyzed individually and as a group. Complying with ASHRAE energy standards can reduce annual electricity consumption at least 13%. With energy efficiency design strategies, the reduction could reach up to 65%, making it possible for PV systems to meet reduced demands in residential and industrial buildings. The peak electricity demand reduction could be up to 71% with integration of strategies and PV. Reducing lighting power density was the best single strategy with high overall performances. Combined strategies such as zero energy building are also recommended. Electricity consumption reductions are the sum of the reductions from strategies and PV output. However, peak electricity reductions were less than their sum because they reduced peak at different times. The potential of grid stress reduction is significant. Investment incentives from government and utilities are necessary. The PV system sizes on net metering interconnection should not be limited by legislation existing in some states. Data from this study provides insight of impacts from applying energy efficiency design strategies in buildings with grid-connected PV systems. With the current transition from traditional electric grids to future smart grids, this information plus large database of various building conditions allow possible investigations needed by governments or utilities in large scale communities for implementing various measures and policies.

Smart Grid Constraint Violation Management for Balancing and Regulating Purposes

DOE PAGES

Bhattarai, Bishnu; Kouzelis, Konstantinos; Mendaza, Iker; ...

2017-03-29

The gradual active load penetration in low voltage distribution grids is expected to challenge their network capacity in the near future. Distribution system operators should for this reason resort to either costly grid reinforcements or to demand side management mechanisms. Since demand side management implementation is usually cheaper, it is also the favorable solution. To this end, this article presents a framework for handling grid limit violations, both voltage and current, to ensure a secure and qualitative operation of the distribution grid. This framework consists of two steps, namely a proactive centralized and subsequently a reactive decentralized control scheme. Themore » former is employed to balance the one hour ahead load while the latter aims at regulating the consumption in real-time. In both cases, the importance of fair use of electricity demand flexibility is emphasized. Thus, it is demonstrated that this methodology aids in keeping the grid status within preset limits while utilizing flexibility from all flexibility participants.« less

A clustering-based fuzzy wavelet neural network model for short-term load forecasting.

PubMed

Kodogiannis, Vassilis S; Amina, Mahdi; Petrounias, Ilias

2013-10-01

Load forecasting is a critical element of power system operation, involving prediction of the future level of demand to serve as the basis for supply and demand planning. This paper presents the development of a novel clustering-based fuzzy wavelet neural network (CB-FWNN) model and validates its prediction on the short-term electric load forecasting of the Power System of the Greek Island of Crete. The proposed model is obtained from the traditional Takagi-Sugeno-Kang fuzzy system by replacing the THEN part of fuzzy rules with a "multiplication" wavelet neural network (MWNN). Multidimensional Gaussian type of activation functions have been used in the IF part of the fuzzyrules. A Fuzzy Subtractive Clustering scheme is employed as a pre-processing technique to find out the initial set and adequate number of clusters and ultimately the number of multiplication nodes in MWNN, while Gaussian Mixture Models with the Expectation Maximization algorithm are utilized for the definition of the multidimensional Gaussians. The results corresponding to the minimum and maximum power load indicate that the proposed load forecasting model provides significantly accurate forecasts, compared to conventional neural networks models.

The impact of monsoon intraseasonal variability on renewable power generation in India

NASA Astrophysics Data System (ADS)

Dunning, C. M.; Turner, A. G.; Brayshaw, D. J.

2015-06-01

India is increasingly investing in renewable technology to meet rising energy demands, with hydropower and other renewables comprising one-third of current installed capacity. Installed wind-power is projected to increase 5-fold by 2035 (to nearly 100GW) under the International Energy Agency's New Policies scenario. However, renewable electricity generation is dependent upon the prevailing meteorology, which is strongly influenced by monsoon variability. Prosperity and widespread electrification are increasing the demand for air conditioning, especially during the warm summer. This study uses multi-decadal observations and meteorological reanalysis data to assess the impact of intraseasonal monsoon variability on the balance of electricity supply from wind-power and temperature-related demand in India. Active monsoon phases are characterized by vigorous convection and heavy rainfall over central India. This results in lower temperatures giving lower cooling energy demand, while strong westerly winds yield high wind-power output. In contrast, monsoon breaks are characterized by suppressed precipitation, with higher temperatures and hence greater demand for cooling, and lower wind-power output across much of India. The opposing relationship between wind-power supply and cooling demand during active phases (low demand, high supply) and breaks (high demand, low supply) suggests that monsoon variability will tend to exacerbate fluctuations in the so-called demand-net-wind (i.e., electrical demand that must be supplied from non-wind sources). This study may have important implications for the design of power systems and for investment decisions in conventional schedulable generation facilities (such as coal and gas) that are used to maintain the supply/demand balance. In particular, if it is assumed (as is common) that the generated wind-power operates as a price-taker (i.e., wind farm operators always wish to sell their power, irrespective of price) then investors in conventional facilities will face additional weather-volatility through the monsoonal impact on the length and frequency of production periods (i.e. their load-duration curves).

Power-based Shift Schedule for Pure Electric Vehicle with a Two-speed Automatic Transmission

NASA Astrophysics Data System (ADS)

Wang, Jiaqi; Liu, Yanfang; Liu, Qiang; Xu, Xiangyang

2016-11-01

This paper introduces a comprehensive shift schedule for a two-speed automatic transmission of pure electric vehicle. Considering about driving ability and efficiency performance of electric vehicles, the power-based shift schedule is proposed with three principles. This comprehensive shift schedule regards the vehicle current speed and motor load power as input parameters to satisfy the vehicle driving power demand with lowest energy consumption. A simulation model has been established to verify the dynamic and economic performance of comprehensive shift schedule. Compared with traditional dynamic and economic shift schedules, simulation results indicate that the power-based shift schedule is superior to traditional shift schedules.

Prediction-based manufacturing center self-adaptive demand side energy optimization in cyber physical systems

NASA Astrophysics Data System (ADS)

Sun, Xinyao; Wang, Xue; Wu, Jiangwei; Liu, Youda

2014-05-01

Cyber physical systems(CPS) recently emerge as a new technology which can provide promising approaches to demand side management(DSM), an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufacturing center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method.

Automated Dynamic Demand Response Implementation on a Micro-grid

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuppannagari, Sanmukh R.; Kannan, Rajgopal; Chelmis, Charalampos

In this paper, we describe a system for real-time automated Dynamic and Sustainable Demand Response with sparse data consumption prediction implemented on the University of Southern California campus microgrid. Supply side approaches to resolving energy supply-load imbalance do not work at high levels of renewable energy penetration. Dynamic Demand Response (D 2R) is a widely used demand-side technique to dynamically adjust electricity consumption during peak load periods. Our D 2R system consists of accurate machine learning based energy consumption forecasting models that work with sparse data coupled with fast and sustainable load curtailment optimization algorithms that provide the ability tomore » dynamically adapt to changing supply-load imbalances in near real-time. Our Sustainable DR (SDR) algorithms attempt to distribute customer curtailment evenly across sub-intervals during a DR event and avoid expensive demand peaks during a few sub-intervals. It also ensures that each customer is penalized fairly in order to achieve the targeted curtailment. We develop near linear-time constant-factor approximation algorithms along with Polynomial Time Approximation Schemes (PTAS) for SDR curtailment that minimizes the curtailment error defined as the difference between the target and achieved curtailment values. Our SDR curtailment problem is formulated as an Integer Linear Program that optimally matches customers to curtailment strategies during a DR event while also explicitly accounting for customer strategy switching overhead as a constraint. We demonstrate the results of our D 2R system using real data from experiments performed on the USC smartgrid and show that 1) our prediction algorithms can very accurately predict energy consumption even with noisy or missing data and 2) our curtailment algorithms deliver DR with extremely low curtailment errors in the 0.01-0.05 kWh range.« less

Multivariate exploration of non-intrusive load monitoring via spatiotemporal pattern network

DOE PAGES

Liu, Chao; Akintayo, Adedotun; Jiang, Zhanhong; ...

2017-12-18

Non-intrusive load monitoring (NILM) of electrical demand for the purpose of identifying load components has thus far mostly been studied using univariate data, e.g., using only whole building electricity consumption time series to identify a certain type of end-use such as lighting load. However, using additional variables in the form of multivariate time series data may provide more information in terms of extracting distinguishable features in the context of energy disaggregation. In this work, a novel probabilistic graphical modeling approach, namely the spatiotemporal pattern network (STPN) is proposed for energy disaggregation using multivariate time-series data. The STPN framework is shownmore » to be capable of handling diverse types of multivariate time-series to improve the energy disaggregation performance. The technique outperforms the state of the art factorial hidden Markov models (FHMM) and combinatorial optimization (CO) techniques in multiple real-life test cases. Furthermore, based on two homes' aggregate electric consumption data, a similarity metric is defined for the energy disaggregation of one home using a trained model based on the other home (i.e., out-of-sample case). The proposed similarity metric allows us to enhance scalability via learning supervised models for a few homes and deploying such models to many other similar but unmodeled homes with significantly high disaggregation accuracy.« less

Multivariate exploration of non-intrusive load monitoring via spatiotemporal pattern network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Chao; Akintayo, Adedotun; Jiang, Zhanhong

Non-intrusive load monitoring (NILM) of electrical demand for the purpose of identifying load components has thus far mostly been studied using univariate data, e.g., using only whole building electricity consumption time series to identify a certain type of end-use such as lighting load. However, using additional variables in the form of multivariate time series data may provide more information in terms of extracting distinguishable features in the context of energy disaggregation. In this work, a novel probabilistic graphical modeling approach, namely the spatiotemporal pattern network (STPN) is proposed for energy disaggregation using multivariate time-series data. The STPN framework is shownmore » to be capable of handling diverse types of multivariate time-series to improve the energy disaggregation performance. The technique outperforms the state of the art factorial hidden Markov models (FHMM) and combinatorial optimization (CO) techniques in multiple real-life test cases. Furthermore, based on two homes' aggregate electric consumption data, a similarity metric is defined for the energy disaggregation of one home using a trained model based on the other home (i.e., out-of-sample case). The proposed similarity metric allows us to enhance scalability via learning supervised models for a few homes and deploying such models to many other similar but unmodeled homes with significantly high disaggregation accuracy.« less

Time-Varying Value of Energy Efficiency in Michigan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mims, Natalie; Eckman, Tom; Schwartz, Lisa C.

Quantifying the time-varying value of energy efficiency is necessary to properly account for all of its benefits and costs and to identify and implement efficiency resources that contribute to a low-cost, reliable electric system. Historically, most quantification of the benefits of efficiency has focused largely on the economic value of annual energy reduction. Due to the lack of statistically representative metered end-use load shape data in Michigan (i.e., the hourly or seasonal timing of electricity savings), the ability to confidently characterize the time-varying value of energy efficiency savings in the state, especially for weather-sensitive measures such as central air conditioning,more » is limited. Still, electric utilities in Michigan can take advantage of opportunities to incorporate the time-varying value of efficiency into their planning. For example, end-use load research and hourly valuation of efficiency savings can be used for a variety of electricity planning functions, including load forecasting, demand-side management and evaluation, capacity planning, long-term resource planning, renewable energy integration, assessing potential grid modernization investments, establishing rates and pricing, and customer service (KEMA 2012). In addition, accurately calculating the time-varying value of efficiency may help energy efficiency program administrators prioritize existing offerings, set incentive or rebate levels that reflect the full value of efficiency, and design new programs.« less

The effect of real-time pricing on load shifting in a highly renewable power system dominated by generation from the renewable sources of wind and photovoltaics

NASA Astrophysics Data System (ADS)

Kies, Alexander; Brown, Tom; Schlachtberger, David; Schramm, Stefan

2017-04-01

The supply-demand imbalance is a major concern in the presence of large shares of highly variable renewable generation from sources like wind and photovoltaics (PV) in power systems. Other than the measures on the generation side, such as flexible backup generation or energy storage, sector coupling or demand side management are the most likely option to counter imbalances, therefore to ease the integration of renewable generation. Demand side management usually refers to load shifting, which comprises the reaction of electricity consumers to price fluctuations. In this work, we derive a novel methodology to model the interplay of load shifting and provided incentives via real-time pricing in highly renewable power systems. We use weather data to simulate generation from the renewable sources of wind and photovoltaics, as well as historical load data, split into different consumption categories, such as, heating, cooling, domestic, etc., to model a simplified power system. Together with renewable power forecast data, a simple market model and approaches to incorporate sector coupling [1] and load shifting [2,3], we model the interplay of incentives and load shifting for different scenarios (e.g., in dependency of the risk-aversion of consumers or the forecast horizon) and demonstrate the practical benefits of load shifting. First, we introduce the novel methodology and compare it with existing approaches. Secondly, we show results of numerical simulations on the effects of load shifting: It supports the integration of PV power by providing a storage, which characteristics can be described as "daily" and provides a significant amount of balancing potential. Lastly, we propose an experimental setup to obtain empirical data on end-consumer load-shifting behaviour in response to price incentives. References [1] Brown, T., Schlachtberger, D., Kies. A., Greiner, M., Sector coupling in a highly renewable European energy system, Proc. of the 15th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants, Vienna, Austria, 15.-17. November 2016 [2] Kleinhans, D.: Towards a systematic characterization of the potential of demand side management, arXiv preprint arXiv:1401.4121, 2014 [3] Kies, A., Schyska, B. U., von Bremen, L., The Demand Side Management Potential to Balance a Highly Renewable European Power System. Energies, 9(11), 955, 2016

Photovoltaic electricity generation: Value for residential and commercial sectors

NASA Astrophysics Data System (ADS)

Bhattacharjee, Ujjwal

The photovoltaic (PV) industry in the US has seen an upsurge in recent years, and PV holds great promise as a renewable technology with no greenhouse gas emissions with its use. We aim to assess the value of PV based electricity for users in the residential and commercial sectors focusing on the financial impacts it has, which may not be greatly recognized. Specifically, we pursue two goals. First, the emerging 'renewable portfolio standard (RPS)' adopted in several states in the country has been a driving force for large scale PV deployment, but financial incentives offered to PV in different RPS states differ considerably. We use life cycle cost model to estimate the cost of PV based electricity for thirty-two RPS states in the country. Results indicate that the levelized cost of PV electricity is high (40 to 60 Cents/kWh). When the contribution of the financial incentives (along with the cost of energy saved) is taken into account, the cost of PV based electricity is negative in some RPS states such as California, New Jersey, New York, while for most of the RPS states the cost of PV electricity continues to remain high. In addition, the states with negative or low cost of PV electricity have been driving the PV diffusion in the residential sector. Therefore, a need to adjust the financial incentive structure in different RPS states is recommended for homogenous development of the residential PV market in the country. Second, we assess the value of the PV in reducing the highest peak load demand in commercial buildings and hence the high value demand charge. The Time-of-Use (TOU) based electricity tariff is widely used by electric utilities in the commercial sector. Energy and peak load are two important facets of the TOU tariff regime. Tools are well established to estimate the energy contribution from a PV system (installed in a commercial building), but not power output on a short time interval. A joint conditional probability model has been developed that enables estimation of the PV contribution towards the peak load reduction for a given high building load. Results indicate a significant cost saving (15% to 40%) with application of the model. This will encourage commercial entities (building owners) to adopt PV as a distributed energy source. The tool would be useful for energy modelers and green building architects as it will enable them to estimate cost savings due to PV deployment in commercial buildings. Moreover, the model tested for three different commercial buildings indicates that school buildings show the best promise for PV deployment followed, respectively, by office buildings and manufacturing facilities. This will help PV incentive programs in the country to use resources effectively to enhance the diffusion of PV in the commercial sector.

Optimizing the U.S. Electric System with a High Penetration of Renewables

NASA Astrophysics Data System (ADS)

Corcoran, B. A.; Jacobson, M. Z.

2013-12-01

As renewable energy generators are increasingly being installed throughout the U.S., there is growing interest in interconnecting diverse renewable generators (primarily wind and solar) across large geographic areas through an enhanced transmission system. This reduces variability in the aggregate power output, increases system reliability, and allows for the development of the best overall group of renewable technologies and sites to meet the load. Studies are therefore needed to determine the most efficient and economical plan to achieve large area interconnections in a future electric system with a high penetration of renewables. This research quantifies the effects of aggregating electric load together with diverse renewable generation throughout the ten Federal Energy Regulatory Commission (FERC) regions in the contiguous U.S. A deterministic linear program has been built in AMPL (A Mathematical Programming Language) to solve for the least-cost organizational structure and system (generators, transmission, and storage) for a highly renewable electric grid. The analysis will 1) examine a highly renewable 2006 electric system, including various sensitivity cases and additional system components such as additional load from electric vehicles, and 2) create a 'roadmap' from the existing 2006 system to a highly renewable system in 2030, accounting for projected price and demand changes and generator retirements based on age and environmental regulations. Ideally, results from this study will offer insight for a federal renewable energy policy (such as a renewable portfolio standard) and how to best organize U.S. regions for transmission planning.

Distributed Energy Resources On-Site Optimization for Commercial Buildings with Electric and Thermal Storage Technologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lacommare, Kristina S H; Stadler, Michael; Aki, Hirohisa

The addition of storage technologies such as flow batteries, conventional batteries, and heat storage can improve the economic as well as environmental attractiveness of on-site generation (e.g., PV, fuel cells, reciprocating engines or microturbines operating with or without CHP) and contribute to enhanced demand response. In order to examine the impact of storage technologies on demand response and carbon emissions, a microgrid's distributed energy resources (DER) adoption problem is formulated as a mixed-integer linear program that has the minimization of annual energy costs as its objective function. By implementing this approach in the General Algebraic Modeling System (GAMS), the problemmore » is solved for a given test year at representative customer sites, such as schools and nursing homes, to obtain not only the level of technology investment, but also the optimal hourly operating schedules. This paper focuses on analysis of storage technologies in DER optimization on a building level, with example applications for commercial buildings. Preliminary analysis indicates that storage technologies respond effectively to time-varying electricity prices, i.e., by charging batteries during periods of low electricity prices and discharging them during peak hours. The results also indicate that storage technologies significantly alter the residual load profile, which can contribute to lower carbon emissions depending on the test site, its load profile, and its adopted DER technologies.« less

A Nuclear Renaissance: The Role of Nuclear Power in Mitigating Climate Change

NASA Astrophysics Data System (ADS)

Winslow, Anne

2011-06-01

The U. N. Framework Convention on Climate Change calls for the stabilization of greenhouse gas (GHG) emissions at double the preindustrial atmospheric carbon dioxide concentration to avoid dangerous anthropogenic interference with the climate system. To achieve this goal, carbon emissions in 2050 must not exceed their current level, despite predictions of a dramatic increase in global electricity demand. The need to reduce GHG emissions and simultaneously provide for additional electricity demand has led to a renewed interest in the expansion of alternatives to fossil fuels—particularly renewable energy and nuclear power. As renewable energy sources are often constrained by the intermittency of natural energy forms, scale-ability concerns, cost and environmental barriers, many governments and even prominent environmentalist turn to nuclear energy as a source of clean, reliable base-load electricity. Described by some as a "nuclear renaissance", this trend of embracing nuclear power as a tool to mitigate climate change will dramatically influence the feasibility of emerging nuclear programs around the world.

A Nuclear Renaissance: The Role of Nuclear Power in Mitigating Climate Change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winslow, Anne

2011-06-28

The U. N. Framework Convention on Climate Change calls for the stabilization of greenhouse gas (GHG) emissions at double the preindustrial atmospheric carbon dioxide concentration to avoid dangerous anthropogenic interference with the climate system. To achieve this goal, carbon emissions in 2050 must not exceed their current level, despite predictions of a dramatic increase in global electricity demand. The need to reduce GHG emissions and simultaneously provide for additional electricity demand has led to a renewed interest in the expansion of alternatives to fossil fuels--particularly renewable energy and nuclear power. As renewable energy sources are often constrained by the intermittencymore » of natural energy forms, scale-ability concerns, cost and environmental barriers, many governments and even prominent environmentalist turn to nuclear energy as a source of clean, reliable base-load electricity. Described by some as a ''nuclear renaissance'', this trend of embracing nuclear power as a tool to mitigate climate change will dramatically influence the feasibility of emerging nuclear programs around the world.« less

Incentive-compatible demand-side management for smart grids based on review strategies

NASA Astrophysics Data System (ADS)

Xu, Jie; van der Schaar, Mihaela

2015-12-01

Demand-side load management is able to significantly improve the energy efficiency of smart grids. Since the electricity production cost depends on the aggregate energy usage of multiple consumers, an important incentive problem emerges: self-interested consumers want to increase their own utilities by consuming more than the socially optimal amount of energy during peak hours since the increased cost is shared among the entire set of consumers. To incentivize self-interested consumers to take the socially optimal scheduling actions, we design a new class of protocols based on review strategies. These strategies work as follows: first, a review stage takes place in which a statistical test is performed based on the daily prices of the previous billing cycle to determine whether or not the other consumers schedule their electricity loads in a socially optimal way. If the test fails, the consumers trigger a punishment phase in which, for a certain time, they adjust their energy scheduling in such a way that everybody in the consumer set is punished due to an increased price. Using a carefully designed protocol based on such review strategies, consumers then have incentives to take the socially optimal load scheduling to avoid entering this punishment phase. We rigorously characterize the impact of deploying protocols based on review strategies on the system's as well as the users' performance and determine the optimal design (optimal billing cycle, punishment length, etc.) for various smart grid deployment scenarios. Even though this paper considers a simplified smart grid model, our analysis provides important and useful insights for designing incentive-compatible demand-side management schemes based on aggregate energy usage information in a variety of practical scenarios.

Energy Management Policies in Distributed Residential Energy Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duan, Sisi; Sun, Jingtao

2016-01-01

In this paper, we study energy management problems in communities with several neighborhood-level Residential Energy Systems (RESs). We consider control problems from both community level and residential level to handle external changes such as restriction on peak demand and restriction on the total demand from the electricity grid. We propose three policies to handle the problems at community level. Based on the collected data from RESs such as predicted energy load, the community controller analyzes the policies, distribute the results to the RES, and each RES can then control and schedule its own energy load based on different coordination functions.more » We utilize a framework to integrate both policy analysis and coordination of functions. With the use of our approach, we show that the policies are useful to resolve the challenges of energy management under external changes.« less

Turnkey Heating, Ventilating, and Air Conditioning and Lighting Retrofit Solution Combining Energy Efficiency and Demand Response Benefits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doebber, Ian; Deru, Michael; Trenbath, Kim

NREL worked with the Bonneville Power Administration's Technology Innovation Office to demonstrate a turnkey, retrofit technology that combines demand response (DR) and energy efficiency (EE) benefits for HVAC and lighting in retail buildings. As a secondary benefit, we also controlled various plug loads and electric hot water heaters (EHWH). The technology demonstrated was Transformative Wave's eIQ Building Management System (BMS) automatically responding to DR signals. The BMS controlled the HVAC rooftop units (RTU) using the CATALYST retrofit solution also developed by Transformative Wave. The non-HVAC loads were controlled using both hardwired and ZigBee wireless communication. The wireless controllers, manufactured bymore » Autani, were used when the building's electrical layout was too disorganized to leverage less expensive hardwired control. The six demonstration locations are within the Seattle metro area. Based on the assets curtailed by the BMS at each location, we projected the DR resource. We were targeting a 1.7 W/ft2 shed for the summer Day-Ahead events and a 0.7 W/ft2 shed for the winter events. While summarized in Table ES-1, only one summer DR event was conducted at Casino #2.« less

Using Hydrated Salt Phase Change Materials for Residential Air Conditioning Peak Demand Reduction and Energy Conservation in Coastal and Transitional Climates in the State of California

NASA Astrophysics Data System (ADS)

Lee, Kyoung Ok

The recent rapid economic and population growth in the State of California have led to a significant increase in air conditioning use, especially in areas of the State with coastal and transitional climates. This fact makes that the electric peak demand be dominated by air conditioning use of residential buildings in the summer time. This extra peak demand caused by the use of air conditioning equipment lasts only a few days out of the year. As a result, unavoidable power outages have occurred when electric supply could not keep up with such electric demand. This thesis proposed a possible solution to this problem by using building thermal mass via phase change materials to reduce peak air conditioning demand loads. This proposed solution was tested via a new wall called Phase Change Frame Wall (PCFW). The PCFW is a typical residential frame wall in which Phase Change Materials (PCMs) were integrated to add thermal mass. The thermal performance of the PCFWs was first evaluated, experimentally, in two test houses, built for this purpose, located in Lawrence, KS and then via computer simulations of residential buildings located in coastal and transitional climates in California. In this thesis, a hydrated salt PCM was used, which was added in concentrations of 10% and 20% by weight of the interior sheathing of the walls. Based on the experimental results, under Lawrence, KS weather, the PCFWs at 10% and 20% of PCM concentrations reduced the peak heat transfer rates by 27.0% and 27.3%, on average, of all four walls, respectively. Simulated results using California climate data indicated that PCFWs would reduce peak heat transfer rates by 8% and 19% at 10% PCM concentration and 12.2% and 27% at 20% PCM concentration for the coastal and transitional climates, respectively. Furthermore, the PCFWs, at 10% PCM concentration, would reduce the space cooling load and the annual energy consumption by 10.4% and 7.2%, on average in both climates, respectively.

Results of the Grid Friendly Appliance Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hammerstrom, Donald J.

2010-04-14

As part of the Pacific Northwest GridWise™ Testbed Demonstration funded by the U.S. Department of Energy and others, Pacific Northwest National Laboratory (PNNL) collaborated with Whirlpool Corporation, Invensys Controls, the Bonneville Power Administration, PacifiCorp, Portland General Electric and several smaller utilities to install 150 new Sears Kenmore clothes dryers and to retrofit 50 existing electric water heaters in homes in Washington and Oregon. Each dryer and water heater was configured to respond to the Grid Friendly™ appliance controller, a small electronic circuit that sensed underfrequency grid conditions and requested that electric load be shed by the appliances. These controllers andmore » appliances were observed for over a year in residences spread over a wide geographic area. The controllers were found to respond predictably and reliably despite their geographic separation. Over 350 minor underfrequency events were observed during the experiment. This paper presents the distributions of these events by season and by time of day. Based on measured load profiles for the dryers and water heaters, the average electrical load that can be shed by each of the two appliance types was estimated by time of day and by season. Battelle Memorial Institute and PNNL have been assembling a suite of grid-responsive functions and benefits that can be achieved through the control of relatively small, distributed loads and resources on a power grid. These controllers should eventually receive acceptance for the opportunities they offer for circuit protection, regulation services, facilitation of demand responsiveness, and even power quality.« less

An analytics of electricity consumption characteristics based on principal component analysis

NASA Astrophysics Data System (ADS)

Feng, Junshu

2018-02-01

Abstract . More detailed analysis of the electricity consumption characteristics can make demand side management (DSM) much more targeted. In this paper, an analytics of electricity consumption characteristics based on principal component analysis (PCA) is given, which the PCA method can be used in to extract the main typical characteristics of electricity consumers. Then, electricity consumption characteristics matrix is designed, which can make a comparison of different typical electricity consumption characteristics between different types of consumers, such as industrial consumers, commercial consumers and residents. In our case study, the electricity consumption has been mainly divided into four characteristics: extreme peak using, peak using, peak-shifting using and others. Moreover, it has been found that industrial consumers shift their peak load often, meanwhile commercial and residential consumers have more peak-time consumption. The conclusions can provide decision support of DSM for the government and power providers.

Control and Coordination of Frequency Responsive Residential Water Heaters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Tess L.; Kalsi, Karanjit; Elizondo, Marcelo A.

2016-07-31

Demand-side frequency control can complement traditional generator controls to maintain the stability of large electric systems in the face of rising uncertainty and variability associated with renewable energy resources. This paper presents a hierarchical frequency-based load control strategy that uses a supervisor to flexibly adjust control gains that a population of end-use loads respond to in a decentralized manner to help meet the NERC BAL-003-1 frequency response standard at both the area level and interconnection level. The load model is calibrated and used to model populations of frequency-responsive water heaters in a PowerWorld simulation of the U.S. Western Interconnection (WECC).more » The proposed design is implemented and demonstrated on physical water heaters in a laboratory setting. A significant fraction of the required frequency response in the WECC could be supplied by electric water heaters alone at penetration levels of less than 15%, while contributing to NERC requirements at the interconnection and area levels.« less

Smart PV grid to reinforce the electrical network

NASA Astrophysics Data System (ADS)

AL-Hamad, Mohamed Y.; Qamber, Isa S.

2017-11-01

Photovoltaic (PV) became the new competitive energy resources of the planet and needs to be engaged in grid to break up the congestion in both Distribution and Transmission systems. The objective of this research is to reduce the load flow through the distribution and transmission equipment by 20%. This reduction will help in relief networks loaded equipment's in all networks. Many projects are starting to develop in the GCC countries and need to be organized to achieve maximum benefits from involving the Renewable Energy Sources (RES) in the network. The GCC countries have a good location for solar energy with high intensity of the solar radiation and clear sky along the year. The opportunities of the solar energy is to utilize and create a sustainable energy resource for this region. Moreover, the target of this research is to engage the PV technology in such a way to lower the over loaded equipment and increases the electricity demand at the consumer's side.

A Novel Control Strategy for Autonomous Operation of Isolated Microgrid with Prioritized Loads

NASA Astrophysics Data System (ADS)

Kumar, R. Hari; Ushakumari, S.

2018-05-01

Maintenance of power balance between generation and demand is one of the most critical requirements for the stable operation of a power system network. To mitigate the power imbalance during the occurrence of any disturbance in the system, fast acting algorithms are inevitable. This paper proposes a novel algorithm for load shedding and network reconfiguration in an isolated microgrid with prioritized loads and multiple islands, which will help to quickly restore the system in the event of a fault. The performance of the proposed algorithm is enhanced using genetic algorithm and its effectiveness is illustrated with simulation results on modified Consortium for Electric Reliability Technology Solutions (CERTS) microgrid.

A nuclear wind/solar oil-shale system for variable electricity and liquid fuels production

DOE Office of Scientific and Technical Information (OSTI.GOV)

Forsberg, C.

2012-07-01

The recoverable reserves of oil shale in the United States exceed the total quantity of oil produced to date worldwide. Oil shale contains no oil, rather it contains kerogen which when heated decomposes into oil, gases, and a carbon char. The energy required to heat the kerogen-containing rock to produce the oil is about a quarter of the energy value of the recovered products. If fossil fuels are burned to supply this energy, the greenhouse gas releases are large relative to producing gasoline and diesel from crude oil. The oil shale can be heated underground with steam from nuclear reactorsmore » leaving the carbon char underground - a form of carbon sequestration. Because the thermal conductivity of the oil shale is low, the heating process takes months to years. This process characteristic in a system where the reactor dominates the capital costs creates the option to operate the nuclear reactor at base load while providing variable electricity to meet peak electricity demand and heat for the shale oil at times of low electricity demand. This, in turn, may enable the large scale use of renewables such as wind and solar for electricity production because the base-load nuclear plants can provide lower-cost variable backup electricity. Nuclear shale oil may reduce the greenhouse gas releases from using gasoline and diesel in half relative to gasoline and diesel produced from conventional oil. The variable electricity replaces electricity that would have been produced by fossil plants. The carbon credits from replacing fossil fuels for variable electricity production, if assigned to shale oil production, results in a carbon footprint from burning gasoline or diesel from shale oil that may half that of conventional crude oil. The U.S. imports about 10 million barrels of oil per day at a cost of a billion dollars per day. It would require about 200 GW of high-temperature nuclear heat to recover this quantity of shale oil - about two-thirds the thermal output of existing nuclear reactors in the United States. With the added variable electricity production to enable renewables, additional nuclear capacity would be required. (authors)« less

The performance of residential micro-cogeneration coupled with thermal and electrical storage

NASA Astrophysics Data System (ADS)

Kopf, John

Over 80% of residential secondary energy consumption in Canada and Ontario is used for space and water heating. The peak electricity demands resulting from residential energy consumption increase the reliance on fossil-fuel generation stations. Distributed energy resources can help to decrease the reliance on central generation stations. Presently, distributed energy resources such as solar photovoltaic, wind and bio-mass generation are subsidized in Ontario. Micro-cogeneration is an emerging technology that can be implemented as a distributed energy resource within residential or commercial buildings. Micro-cogeneration has the potential to reduce a building's energy consumption by simultaneously generating thermal and electrical power on-site. The coupling of a micro-cogeneration device with electrical storage can improve the system's ability to reduce peak electricity demands. The performance potential of micro-cogeneration devices has yet to be fully realized. This research addresses the performance of a residential micro-cogeneration device and it's ability to meet peak occupant electrical loads when coupled with electrical storage. An integrated building energy model was developed of a residential micro-cogeneration system: the house, the micro-cogeneration device, all balance of plant and space heating components, a thermal storage device, an electrical storage device, as well as the occupant electrical and hot water demands. This model simulated the performance of a micro-cogeneration device coupled to an electrical storage system within a Canadian household. A customized controller was created in ESP-r to examine the impact of various system control strategies. The economic performance of the system was assessed from the perspective of a local energy distribution company and an end-user under hypothetical electricity export purchase price scenarios. It was found that with certain control strategies the micro-cogeneration system was able to improve the economic performance for both the end user and local distribution company.

Decentralized control of units in smart grids for the support of renewable energy supply

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sonnenschein, Michael, E-mail: Michael.Sonnenschein@Uni-Oldenburg.DE; Lünsdorf, Ontje, E-mail: Ontje.Luensdorf@OFFIS.DE; Bremer, Jörg, E-mail: Joerg.Bremer@Uni-Oldenburg.DE

Due to the significant environmental impact of power production from fossil fuels and nuclear fission, future energy systems will increasingly rely on distributed and renewable energy sources (RES). The electrical feed-in from photovoltaic (PV) systems and wind energy converters (WEC) varies greatly both over short and long time periods (from minutes to seasons), and (not only) by this effect the supply of electrical power from RES and the demand for electrical power are not per se matching. In addition, with a growing share of generation capacity especially in distribution grids, the top-down paradigm of electricity distribution is gradually replaced bymore » a bottom-up power supply. This altogether leads to new problems regarding the safe and reliable operation of power grids. In order to address these challenges, the notion of Smart Grids has been introduced. The inherent flexibilities, i.e. the set of feasible power schedules, of distributed power units have to be controlled in order to support demand–supply matching as well as stable grid operation. Controllable power units are e.g. combined heat and power plants, power storage systems such as batteries, and flexible power consumers such as heat pumps. By controlling the flexibilities of these units we are particularly able to optimize the local utilization of RES feed-in in a given power grid by integrating both supply and demand management measures with special respect to the electrical infrastructure. In this context, decentralized systems, autonomous agents and the concept of self-organizing systems will become key elements of the ICT based control of power units. In this contribution, we first show how a decentralized load management system for battery charging/discharging of electrical vehicles (EVs) can increase the locally used share of supply from PV systems in a low voltage grid. For a reliable demand side management of large sets of appliances, dynamic clustering of these appliances into uniformly controlled appliance sets is necessary. We introduce a method for self-organized clustering for this purpose and show how control of such clusters can affect load peaks in distribution grids. Subsequently, we give a short overview on how we are going to expand the idea of self-organized clusters of units into creating a virtual control center for dynamic virtual power plants (DVPP) offering products at a power market. For an efficient organization of DVPPs, the flexibilities of units have to be represented in a compact and easy to use manner. We give an introduction how the problem of representing a set of possibly 10{sup 100} feasible schedules can be solved by a machine-learning approach. In summary, this article provides an overall impression how we use agent based control techniques and methods of self-organization to support the further integration of distributed and renewable energy sources into power grids and energy markets. - Highlights: • Distributed load management for electrical vehicles supports local supply from PV. • Appliances can self-organize into so called virtual appliances for load control. • Dynamic VPPs can be controlled by extensively decentralized control centers. • Flexibilities of units can efficiently be represented by support-vector descriptions.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, D.; Winkler, J.

As energy-efficiency efforts focus increasingly on existing homes, we scratch our heads about construction decisions made 30, 40, 50-years ago and ask: 'What were they thinking?' A logical follow-on question is: 'What will folks think in 2050 about the homes we're building today?' This question can lead to a lively discussion, but the current practice that we find most alarming is placing ducts in the attic. In this paper, we explore through literature and analysis the impact duct location has on cooling load, peak demand, and energy cost in hot climates. For a typical new home in these climates, wemore » estimate that locating ducts in attics rather than inside conditioned space increases the cooling load 0.5 to 1 ton, increases cooling costs 15% and increases demand by 0.75 kW. The aggregate demand to service duct loss in homes built in Houston, Las Vegas, and Phoenix during the period 2000 through 2009 is estimated to be 700 MW. We present options for building homes with ducts in conditioned space and demonstrate that these options compare favorably with other common approaches to achieving electricity peak demand and consumption savings in homes.« less

Microgrid Selection and Operation for Commercial Buildings in California and New York States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Environmental Energy Technologies Division; Lacommare, Kristina S H; Marnay, Chris

The addition of storage technologies such as lead-acid batteries, flow batteries, or heat storage can potentially improve the economic and environmental attractiveness of on-site generation such as PV, fuel cells, reciprocating engines or microturbines (with or without CHP), and can contribute to enhanced demand response. Preliminary analyses for a Californian nursing home indicate that storage technologies respond effectively to time-varying electricity prices, i.e., by charging batteries during periods of low electricity prices and discharging them during peak hours. While economic results do not make a compelling case for storage, they indicate that storage technologies significantly alter the residual load profile,more » which may lower carbon emissions as well as energy costs depending on the test site, its load profile, and DER technology adoption.« less

Costs and Operating Dynamics of Integrating Distributed Energy Resources in Commercial and Industrial Buildings with Electric Vehicle Charging

NASA Astrophysics Data System (ADS)

Flores, Robert Joseph

Growing concerns over greenhouse gas and pollutant emissions have increased the pressure to shift energy conversion paradigms from current forms to more sustainable methods, such as through the use of distributed energy resources (DER) at industrial and commercial buildings. This dissertation is concerned with the optimal design and dispatch of a DER system installed at an industrial or commercial building. An optimization model that accurately captures typical utility costs and the physical constraints of a combined cooling, heating, and power (CCHP) system is designed to size and operate a DER system at a building. The optimization model is then used with cooperative game theory to evaluate the financial performance of a CCHP investment. The CCHP model is then modified to include energy storage, solar powered generators, alternative fuel sources, carbon emission limits, and building interactions with public and fleet PEVs. Then, a separate plugin electric vehicle (PEV) refueling model is developed to determine the cost to operate a public Level 3 fast charging station. The CCHP design and dispatch results show the size of the building load and consistency of the thermal loads are critical to positive financial performance. While using the CCHP system to produce cooling can provide savings, heat production drives positive financial performance. When designing the DER system to reduce carbon emissions, the use of renewable fuels can allow for a gas turbine system with heat recovery to reduce carbon emissions for a large university by 67%. Further reductions require large photovoltaic installations coupled with energy storage or the ability to export electricity back to the grid if costs are to remain relatively low. When considering Level 3 fast charging equipment, demand charges at low PEV travel levels are sufficiently high to discourage adoption. Integration of the equipment can reduce demand charge costs only if the building maximum demand does not coincide with PEV refueling. Electric vehicle refueling does not typically affect DER design at low PEV travel levels, but can as electric vehicle travel increases. However, as PEV travel increases, the stochastic nature of PEV refueling disappears, and the optimization problem may become deterministic.

Solar electricity: An effective asset to supply urban loads in hot climates

NASA Astrophysics Data System (ADS)

Robert, Fabien Chidanand; Gopalan, Sundararaman

2018-04-01

While human population has been multiplied by four in the last hundred years, the world energy consumption was multiplied by ten. The common method of using fossil fuels to provide energy and electricity has dangerously disturbed nature's and climate's balance. It has become urgent and crucial to find sustainable and eco-friendly alternatives to preserve a livable environment with unpolluted air and water. Renewable energy is the unique eco-friendly opportunity known today. The main challenge of using renewable energy is to ensure the constant balance of electricity demand and generation on the electrical grid. This paper investigates whether the solar electricity generation is correlated with the urban electricity consumption in hot climates. The solar generation and total consumption have been compared for three cities in Florida. The hourly solar generation has been found to be highly correlated with the consumption that occurs 6 h later, while the monthly solar generation is correlated with the monthly energy consumption. Producing 30% of the electricity using solar energy has been found to compensate partly for the monthly variation in the urban electricity demand. In addition, if 30% of the world electricity is produced using solar, global CO2 emissions would be reduced by 11.7% (14.6% for India). Thus, generating 30% solar electricity represents a valuable asset for urban areas situated in hot climates, reducing the need for electrical operating reserve, providing local supply with minimal transmission losses, but above all reducing the need for fossil fuel electricity and reducing global CO2 emission.

Coordinated control of micro-grid based on distributed moving horizon control.

PubMed

Ma, Miaomiao; Shao, Liyang; Liu, Xiangjie

2018-05-01

This paper proposed the distributed moving horizon coordinated control scheme for the power balance and economic dispatch problems of micro-grid based on distributed generation. We design the power coordinated controller for each subsystem via moving horizon control by minimizing a suitable objective function. The objective function of distributed moving horizon coordinated controller is chosen based on the principle that wind power subsystem has the priority to generate electricity while photovoltaic power generation coordinates with wind power subsystem and the battery is only activated to meet the load demand when necessary. The simulation results illustrate that the proposed distributed moving horizon coordinated controller can allocate the output power of two generation subsystems reasonably under varying environment conditions, which not only can satisfy the load demand but also limit excessive fluctuations of output power to protect the power generation equipment. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Transactive Control of Commercial Buildings for Demand Response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hao, He; Corbin, Charles D.; Kalsi, Karanjit

Transactive control is a type of distributed control strategy that uses market mechanism to engage self-interested responsive loads to achieve power balance in the electrical power grid. In this paper, we propose a transactive control approach of commercial building Heating, Ventilation, and Air- Conditioning (HVAC) systems for demand response. We first describe the system models, and identify their model parameters using data collected from Systems Engineering Building (SEB) located on our Pacific Northwest National Laboratory (PNNL) campus. We next present a transactive control market structure for commercial building HVAC system, and describe its agent bidding and market clearing strategies. Severalmore » case studies are performed in a simulation environment using Building Control Virtual Test Bed (BCVTB) and calibrated SEB EnergyPlus model. We show that the proposed transactive control approach is very effective at peak clipping, load shifting, and strategic conservation for commercial building HVAC systems.« less

Drought Vulnerability of Thermoelectric Generation using Texas as a Case Study

NASA Astrophysics Data System (ADS)

Scanlon, B. R.; Duncan, I.; Reedy, R. C.

2013-12-01

Increasing extent, frequency, and intensity of droughts raises concerns about the vulnerability of thermoelectricity generation to water-shortages. In this study we evaluated the impact of the 2011 flash drought in Texas on electricity demand and water supply for power plants. The impacts of the drought were greater in sub-humid east Texas than in semiarid west Texas because most power plants are pre-adapted to low water availability in west Texas. This comparison between sub-humid and semiarid regions in Texas serves as a proxy for climatic differences between the eastern and western US. High temperatures with ≥100 days of triple digit temperatures raised annual electricity demands/generation by 6% and peak demands in August by 4% relative to 2010. The corresponding water demands/consumption for 2011 for thermoelectric generation was increased by ~10% relative to 2010. While electricity demand only increased slightly during the drought, water supply decreased markedly with statewide reservoir storage at record lows (58% of capacity). Reductions in reservoir storage would suggest that power plants should be vulnerable to water shortages; however, data show that power plants subjected to water shortages were flexible enough to adapt by switching to less water-intensive technologies. Some power plants switched from once-through cooling to cooling towers with more than an order of magnitude reduction in water withdrawals whereas others switched from steam turbines to combustion turbines (no cooling water requirements) when both were available. Recent increases in natural gas production by an order of magnitude and use in combined cycle plants enhances the robustness of the power-plant fleet to drought by reducing water consumption (~1/3rd of that for steam turbines), allowing plants to operate with (combined cycle generator) or without (combustion turbine generator) water, and as base-load or peaking plants to complement increasing wind generation. Drought vulnerability of the power plant fleet can be further enhanced by reducing demand and/or increasing supplies of water (e.g. use of nontraditional water sources: municipal waste water or brackish water) and increasing supplies of electricity. Our ability to cope with projected increases in droughts would be greatly improved by joint management of water and electricity.

The Magnitude and Regional Distribution of Needs for Hydropower - Phase II Future Electric Power Supply and Demand. Volume 4

DTIC Science & Technology

1981-09-01

ACfNT) Flf~OURC~S TO S£ RVF DEMANOiGW) LOAD FACT~RCPERCENT) e.a 25.~ llob e.a 25o9 "·" e.u zs,q 4,, •~oTfl T~E GROWTH RATES ARE AVf~AGE...operations as meat packing (SIC 2011), fluid milk (SIC 2026), canned fruits and vegetables (SIC 2033), frozen ~/ Quotes from the Rand Report: Energy...meat packing, 27 percent in milk processing, about 5 percent in canning and 2 7 percent in bread products." The average reduction in electric-energy

Economic Analysis Case Studies of Battery Energy Storage with SAM

DOE Office of Scientific and Technical Information (OSTI.GOV)

DiOrio, Nicholas; Dobos, Aron; Janzou, Steven

2015-11-01

Interest in energy storage has continued to increase as states like California have introduced mandates and subsidies to spur adoption. This energy storage includes customer sited behind-the-meter storage coupled with photovoltaics (PV). This paper presents case study results from California and Tennessee, which were performed to assess the economic benefit of customer-installed systems. Different dispatch strategies, including manual scheduling and automated peak-shaving were explored to determine ideal ways to use the storage system to increase the system value and mitigate demand charges. Incentives, complex electric tariffs, and site specific load and PV data were used to perform detailed analysis. Themore » analysis was performed using the free, publically available System Advisor Model (SAM) tool. We find that installation of photovoltaics with a lithium-ion battery system priced at $300/kWh in Los Angeles under a high demand charge utility rate structure and dispatched using perfect day-ahead forecasting yields a positive net-present value, while all other scenarios cost the customer more than the savings accrued. Different dispatch strategies, including manual scheduling and automated peak-shaving were explored to determine ideal ways to use the storage system to increase the system value and mitigate demand charges. Incentives, complex electric tariffs, and site specific load and PV data were used to perform detailed analysis. The analysis was performed using the free, publically available System Advisor Model (SAM) tool. We find that installation of photovoltaics with a lithium-ion battery system priced at $300/kWh in Los Angeles under a high demand charge utility rate structure and dispatched using perfect day-ahead forecasting yields a positive net-present value, while all other scenarios cost the customer more than the savings accrued.« less

ESTIMATING RISK TO CALIFORNIA ENERGY INFRASTRUCTURE FROM PROJECTED CLIMATE CHANGE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sathaye, Jayant; Dale, Larry; Larsen, Peter

2011-06-22

This report outlines the results of a study of the impact of climate change on the energy infrastructure of California and the San Francisco Bay region, including impacts on power plant generation; transmission line and substation capacity during heat spells; wildfires near transmission lines; sea level encroachment upon power plants, substations, and natural gas facilities; and peak electrical demand. Some end-of-century impacts were projected:Expected warming will decrease gas-fired generator efficiency. The maximum statewide coincident loss is projected at 10.3 gigawatts (with current power plant infrastructure and population), an increase of 6.2 percent over current temperature-induced losses. By the end ofmore » the century, electricity demand for almost all summer days is expected to exceed the current ninetieth percentile per-capita peak load. As much as 21 percent growth is expected in ninetieth percentile peak demand (per-capita, exclusive of population growth). When generator losses are included in the demand, the ninetieth percentile peaks may increase up to 25 percent. As the climate warms, California's peak supply capacity will need to grow faster than the population.Substation capacity is projected to decrease an average of 2.7 percent. A 5C (9F) air temperature increase (the average increase predicted for hot days in August) will diminish the capacity of a fully-loaded transmission line by an average of 7.5 percent.The potential exposure of transmission lines to wildfire is expected to increase with time. We have identified some lines whose probability of exposure to fire are expected to increase by as much as 40 percent. Up to 25 coastal power plants and 86 substations are at risk of flooding (or partial flooding) due to sea level rise.« less

Abruptness of Cascade Failures in Power Grids

NASA Astrophysics Data System (ADS)

Pahwa, Sakshi; Scoglio, Caterina; Scala, Antonio

2014-01-01

Electric power-systems are one of the most important critical infrastructures. In recent years, they have been exposed to extreme stress due to the increasing demand, the introduction of distributed renewable energy sources, and the development of extensive interconnections. We investigate the phenomenon of abrupt breakdown of an electric power-system under two scenarios: load growth (mimicking the ever-increasing customer demand) and power fluctuations (mimicking the effects of renewable sources). Our results on real, realistic and synthetic networks indicate that increasing the system size causes breakdowns to become more abrupt; in fact, mapping the system to a solvable statistical-physics model indicates the occurrence of a first order transition in the large size limit. Such an enhancement for the systemic risk failures (black-outs) with increasing network size is an effect that should be considered in the current projects aiming to integrate national power-grids into ``super-grids''.

Abruptness of cascade failures in power grids.

PubMed

Pahwa, Sakshi; Scoglio, Caterina; Scala, Antonio

2014-01-15

Electric power-systems are one of the most important critical infrastructures. In recent years, they have been exposed to extreme stress due to the increasing demand, the introduction of distributed renewable energy sources, and the development of extensive interconnections. We investigate the phenomenon of abrupt breakdown of an electric power-system under two scenarios: load growth (mimicking the ever-increasing customer demand) and power fluctuations (mimicking the effects of renewable sources). Our results on real, realistic and synthetic networks indicate that increasing the system size causes breakdowns to become more abrupt; in fact, mapping the system to a solvable statistical-physics model indicates the occurrence of a first order transition in the large size limit. Such an enhancement for the systemic risk failures (black-outs) with increasing network size is an effect that should be considered in the current projects aiming to integrate national power-grids into "super-grids".

Abruptness of Cascade Failures in Power Grids

PubMed Central

Pahwa, Sakshi; Scoglio, Caterina; Scala, Antonio

2014-01-01

Electric power-systems are one of the most important critical infrastructures. In recent years, they have been exposed to extreme stress due to the increasing demand, the introduction of distributed renewable energy sources, and the development of extensive interconnections. We investigate the phenomenon of abrupt breakdown of an electric power-system under two scenarios: load growth (mimicking the ever-increasing customer demand) and power fluctuations (mimicking the effects of renewable sources). Our results on real, realistic and synthetic networks indicate that increasing the system size causes breakdowns to become more abrupt; in fact, mapping the system to a solvable statistical-physics model indicates the occurrence of a first order transition in the large size limit. Such an enhancement for the systemic risk failures (black-outs) with increasing network size is an effect that should be considered in the current projects aiming to integrate national power-grids into “super-grids”. PMID:24424239

Exploring Demand Charge Savings from Commercial Solar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Darghouth, Naim; Barbose, Galen; Mills, Andrew

Commercial retail electricity rates commonly include a demand charge component, based on some measure of the customer’s peak demand. Customer-sited solar PV can potentially reduce demand charges, but the magnitude of these savings can be difficult to predict, given variations in demand charge designs, customer loads, and PV generation profiles. Moreover, depending on the circumstances, demand charges from solar may or may not align well with associated utility cost savings. Lawrence Berkeley National Laboratory (Berkeley Lab) and the National Renewable Energy Laboratory (NREL) are collaborating in a series of studies to understand how solar PV can reduce demand charge levelsmore » for a variety of customer types and demand charges designs. Previous work focused on residential customs with solar. This study, instead, focuses on commercial customers and seeks to understand the extent and conditions under which rooftop can solar reduce commercial demand charges. To answer these questions, we simulate demand charge savings for a broad range of commercial customer types, demand charge designs, locations, and PV system characteristics. This particular analysis does not include storage, but a subsequent analysis in this series will evaluate demand charge savings for commercial customers with solar and storage.« less

NREL's Energy-Saving Technology for Air Conditioning Cuts Peak Power Loads Without Using Harmful Refrigerants (Fact Sheet)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

2012-07-01

This fact sheet describes how the DEVAP air conditioner was invented, explains how the technology works, and why it won an R&D 100 Award. Desiccant-enhanced evaporative (DEVAP) air-conditioning will provide superior comfort for commercial buildings in any climate at a small fraction of the electricity costs of conventional air-conditioning equipment, releasing far less carbon dioxide and cutting costly peak electrical demand by an estimated 80%. Air conditioning currently consumes about 15% of the electricity generated in the United States and is a major contributor to peak electrical demand on hot summer days, which can lead to escalating power costs, brownouts,more » and rolling blackouts. DEVAP employs an innovative combination of air-cooling technologies to reduce energy use by up to 81%. DEVAP also shifts most of the energy needs to thermal energy sources, reducing annual electricity use by up to 90%. In doing so, DEVAP is estimated to cut peak electrical demand by nearly 80% in all climates. Widespread use of this cooling cycle would dramatically cut peak electrical loads throughout the country, saving billions of dollars in investments and operating costs for our nation's electrical utilities. Water is already used as a refrigerant in evaporative coolers, a common and widely used energy-saving technology for arid regions. The technology cools incoming hot, dry air by evaporating water into it. The energy absorbed by the water as it evaporates, known as the latent heat of vaporization, cools the air while humidifying it. However, evaporative coolers only function when the air is dry, and they deliver humid air that can lower the comfort level for building occupants. And even many dry climates like Phoenix, Arizona, have a humid season when evaporative cooling won't work well. DEVAP extends the applicability of evaporative cooling by first using a liquid desiccant-a water-absorbing material-to dry the air. The dry air is then passed to an indirect evaporative cooling stage, in which the incoming air is in thermal contact with a moistened surface that evaporates the water into a separate air stream. As the evaporation cools the moistened surface, it draws heat from the incoming air without adding humidity to it. A number of cooling cycles have been developed that employ indirect evaporative cooling, but DEVAP achieves a superior efficiency relative to its technological siblings.« less

Mongolia's potential in international cooperation in the Asian energy space

NASA Astrophysics Data System (ADS)

Batmunkh, Sereeter; Stennikov, Valery; Bat-Erdene, Bayar; Erdenebaatar, Altay

2018-01-01

The paper is concerned with the issues of interstate electric power interconnections to be created in the countries of Northeast Asia. The conditions are formulated, the problems are stated, and solutions for Mongolia's entry into the Asian energy space are proposed. The electricity consumption rates are growing, however, the Northeast Asia countries differ considerably in available energy resources to cope with this growth. Therefore, the need to build international electric power interconnections that take into account climatic features, seasonal peak load differences and other factors in order to rationally match power demand and supply is getting increasingly more obvious. Mongolia can take an active part in this process, as the country is rich in energy resources and interested in their development to meet their domestic needs and exchange with neighboring countries. The establishment of interstate power interconnections in the Northeast Asia countries represents a topical task whose solution will make it possible to meet the demand of this region for electricity on mutually beneficial terms. Mongolia has a good spatial position, energy resources and is interested in ensuring domestic energy balance. Therefore, the country can be an active participant in such an integration process.

Assessing summertime urban air conditioning consumption in a semiarid environment

NASA Astrophysics Data System (ADS)

Salamanca, F.; Georgescu, M.; Mahalov, A.; Moustaoui, M.; Wang, M.; Svoma, B. M.

2013-09-01

Evaluation of built environment energy demand is necessary in light of global projections of urban expansion. Of particular concern are rapidly expanding urban areas in environments where consumption requirements for cooling are excessive. Here, we simulate urban air conditioning (AC) electric consumption for several extreme heat events during summertime over a semiarid metropolitan area with the Weather Research and Forecasting (WRF) model coupled to a multilayer building energy scheme. Observed total load values obtained from an electric utility company were split into two parts, one linked to meteorology (i.e., AC consumption) which was compared to WRF simulations, and another to human behavior. WRF-simulated non-dimensional AC consumption profiles compared favorably to diurnal observations in terms of both amplitude and timing. The hourly ratio of AC to total electricity consumption accounted for ˜53% of diurnally averaged total electric demand, ranging from ˜35% during early morning to ˜65% during evening hours. Our work highlights the importance of modeling AC electricity consumption and its role for the sustainable planning of future urban energy needs. Finally, the methodology presented in this article establishes a new energy consumption-modeling framework that can be applied to any urban environment where the use of AC systems is prevalent.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Auslander, David; Culler, David; Wright, Paul

The goal of the 2.5 year Distributed Intelligent Automated Demand Response (DIADR) project was to reduce peak electricity load of Sutardja Dai Hall at UC Berkeley by 30% while maintaining a healthy, comfortable, and productive environment for the occupants. We sought to bring together both central and distributed control to provide “deep” demand response1 at the appliance level of the building as well as typical lighting and HVAC applications. This project brought together Siemens Corporate Research and Siemens Building Technology (the building has a Siemens Apogee Building Automation System (BAS)), Lawrence Berkeley National Laboratory (leveraging their Open Automated Demand Responsemore » (openADR), Auto-­Demand Response, and building modeling expertise), and UC Berkeley (related demand response research including distributed wireless control, and grid-­to-­building gateway development). Sutardja Dai Hall houses the Center for Information Technology Research in the Interest of Society (CITRIS), which fosters collaboration among industry and faculty and students of four UC campuses (Berkeley, Davis, Merced, and Santa Cruz). The 141,000 square foot building, occupied in 2009, includes typical office spaces and a nanofabrication laboratory. Heating is provided by a district heating system (steam from campus as a byproduct of the campus cogeneration plant); cooling is provided by one of two chillers: a more typical electric centrifugal compressor chiller designed for the cool months (Nov-­ March) and a steam absorption chiller for use in the warm months (April-­October). Lighting in the open office areas is provided by direct-­indirect luminaries with Building Management System-­based scheduling for open areas, and occupancy sensors for private office areas. For the purposes of this project, we focused on the office portion of the building. Annual energy consumption is approximately 8053 MWh; the office portion is estimated as 1924 MWh. The maximum peak load during the study period was 1175 kW. Several new tools facilitated this work, such as the Smart Energy Box, the distributed load controller or Energy Information Gateway, the web-­based DR controller (dubbed the Central Load-­Shed Coordinator or CLSC), and the Demand Response Capacity Assessment & Operation Assistance Tool (DRCAOT). In addition, an innovative data aggregator called sMAP (simple Measurement and Actuation Profile) allowed data from different sources collected in a compact form and facilitated detailed analysis of the building systems operation. A smart phone application (RAP or Rapid Audit Protocol) facilitated an inventory of the building’s plug loads. Carbon dioxide sensors located in conference rooms and classrooms allowed demand controlled ventilation. The extensive submetering and nimble access to this data provided great insight into the details of the building operation as well as quick diagnostics and analyses of tests. For example, students discovered a short-­cycling chiller, a stuck damper, and a leaking cooling coil in the first field tests. For our final field tests, we were able to see how each zone was affected by the DR strategies (e.g., the offices on the 7th floor grew very warm quickly) and fine-­tune the strategies accordingly.« less

Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

NASA Technical Reports Server (NTRS)

Momoh, James; Chattopadhyay, Deb; Elfayoumy, Mahmoud

1996-01-01

The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the GP model which in turn produces the pre-schedule of the optimal control model. Some preliminary results based on a hypothetical test case will be presented for the load forecasting module. The computer codes for the three modules will be made available fe adoption by bus operating agencies. Sample results will be provided using these models. The software will be a useful tool for supporting the control systems for the Electric Bus project of NASA.

Using a hot dry rock geothermal reservoir for load following

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, D.W.; Duteau, R.J.

1995-01-01

Field measurements and modeling have shown the potential for using a Hot Dry Rock (HDR) geothermal reservoir for electric load following: either with Power-Peaking from a base-load operating condition, or for Pumped Storage of off-peak electric energy with a very significant thermal augmentation of the stored mechanical energy during periods of power production. For the base-load with power- peaking mode of operation, and HDR reservoir appears capable of producing over twice its nominal power output for short -- 2 to 4 hour -- periods of time. In this mode of operation, the reservoir normally would be produced under a high-backpressuremore » condition with the HDR reservoir region near the production well highly inflated. Upon demand, the production backpressure would be sharply reduced, surging the production flow. The analytical tool used in these investigations has been the transient finite element model of the an HDR reservoir called GEOCRACK, which is being developed by Professor Dan Swenson and his students at Kansas State University. This discrete-element representation of a jointed rock mass has recently been validated for transient operations using the set of cyclic reservoir operating data obtained at the end of the LTFT.« less

Development of a differentially balanced magnetic bearing and control system for use with a flywheel energy storage system

NASA Technical Reports Server (NTRS)

Higgins, Mark A.; Plant, David P.; Ries, Douglas M.; Kirk, James A.; Anand, Davinder K.

1992-01-01

The purpose of a magnetically suspended flywheel energy storage system for electric utility load leveling is to provide a means to store energy during times when energy is inexpensive to produce and then return it to the customer during times of peak power demand when generated energy is most expensive. The design of a 20 kWh flywheel energy storage system for electric utility load leveling applications involves the successful integration of a number of advanced technologies so as to minimize the size and cost of the system without affecting its efficiency and reliability. The flywheel energy storage system uses a carbon epoxy flywheel, two specially designed low loss magnetic bearings, a high efficiency motor generator, and a 60 cycle AC power converter all integrated through a microprocessor controller. The basic design is discussed of each of the components that is used in the energy storage design.

Quantifying the Impacts of Timebased Rates, Enabling Technology, and Other Treatments in Consumer Behavior Studies: Protocols and Guidelines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cappers, Peter; Todd, Annika; Perry, Michael

2013-06-27

This report offers guidelines and protocols for measuring the effects of time-based rates, enabling technology, and various other treatments on customers’ levels and patterns of electricity usage. Although the focus is on evaluating consumer behavior studies (CBS) that involve field trials and pilots, the methods can be extended to assessing the large-scale programs that may follow. CBSs are undertaken to resolve uncertainties and ambiguities about how consumers respond to inducements to modify their electricity demand. Those inducements include price structures; feedback and information; and enabling technologies embedded in programs such as: critical peak, time-of use, real-time pricing; peak time rebatemore » or critical peak rebate; home energy reports and in-home displays; and all manner of device controls for appliances and plug loads. Although the focus of this report is on consumer studies—where the subjects are households—the behavioral sciences principles discussed and many of the methods recommended apply equally to studying commercial and industrial customer electricity demand.« less

Selection of battery technology to support grid-integrated renewable electricity

NASA Astrophysics Data System (ADS)

Leadbetter, Jason; Swan, Lukas G.

2012-10-01

Operation of the electricity grid has traditionally been done using slow responding base and intermediate load generators with fast responding peak load generators to capture the chaotic behavior of end-use demands. Many modern electricity grids are implementing intermittent non-dispatchable renewable energy resources. As a result, the existing support services are becoming inadequate and technological innovation in grid support services are necessary. Support services fall into short (seconds to minutes), medium (minutes to hours), and long duration (several hours) categories. Energy storage offers a method of providing these services and can enable increased penetration rates of renewable energy generators. Many energy storage technologies exist. Of these, batteries span a significant range of required storage capacity and power output. By assessing the energy to power ratio of electricity grid services, suitable battery technologies were selected. These include lead-acid, lithium-ion, sodium-sulfur, and vanadium-redox. Findings show the variety of grid services require different battery technologies and batteries are capable of meeting the short, medium, and long duration categories. A brief review of each battery technology and its present state of development, commercial implementation, and research frontiers is presented to support these classifications.

Bi-level Optimization Method of Air-conditioning System Based on Office Building Energy Storage Characteristics

NASA Astrophysics Data System (ADS)

Wang, Qingze; Chen, Xingying; Ji, Li; Liao, Yingchen; Yu, Kun

2017-05-01

The air-conditioning system of office building is a large power consumption terminal equipment, whose unreasonable operation mode leads to low energy efficiency. Realizing the optimization of the air-conditioning system has become one of the important research contents of the electric power demand response. In this paper, in order to save electricity cost and improve energy efficiency, bi-level optimization method of air-conditioning system based on TOU price is put forward by using the energy storage characteristics of the office building itself. In the upper level, the operation mode of the air-conditioning system is optimized in order to minimize the uses’ electricity cost in the premise of ensuring user’ comfort according to the information of outdoor temperature and TOU price, and the cooling load of the air-conditioning is output to the lower level; In the lower level, the distribution mode of cooling load among the multi chillers is optimized in order to maximize the energy efficiency according to the characteristics of each chiller. Finally, the experimental results under different modes demonstrate that the strategy can improve the energy efficiency of chillers and save the electricity cost for users.

Energy conservation and management system using efficient building automation

NASA Astrophysics Data System (ADS)

Ahmed, S. Faiz; Hazry, D.; Tanveer, M. Hassan; Joyo, M. Kamran; Warsi, Faizan A.; Kamarudin, H.; Wan, Khairunizam; Razlan, Zuradzman M.; Shahriman A., B.; Hussain, A. T.

2015-05-01

In countries where the demand and supply gap of electricity is huge and the people are forced to endure increasing hours of load shedding, unnecessary consumption of electricity makes matters even worse. So the importance and need for electricity conservation increases exponentially. This paper outlines a step towards the conservation of energy in general and electricity in particular by employing efficient Building Automation technique. It should be noted that by careful designing and implementation of the Building Automation System, up to 30% to 40% of energy consumption can be reduced, which makes a huge difference for energy saving. In this study above mentioned concept is verified by performing experiment on a prototype experimental room and by implementing efficient building automation technique. For the sake of this efficient automation, Programmable Logic Controller (PLC) is employed as a main controller, monitoring various system parameters and controlling appliances as per required. The hardware test run and experimental findings further clarifies and proved the concept. The added advantage of this project is that it can be implemented to both small and medium level domestic homes thus greatly reducing the overall unnecessary load on the Utility provider.

Creep of Hi-Nicalon S Fiber Tows at Elevated Temperature in Air and in Steam

DTIC Science & Technology

2013-03-01

materials”[28]. Materials have always been a limiting factor in the advancements of technology. The ever increasing demand for aerospace vehicles that are...matrix composites are designed to have load-carrying capacity at high temperatures in extreme environments. Ceramic matrix composites are prime...engines, gas turbines for electrical power/steam cogeneration , as well as nuclear power plant components. It is recognized that the structural

Status Report on Modelling and Simulation Capabilities for Nuclear-Renewable Hybrid Energy Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rabiti, C.; Epiney, A.; Talbot, P.

This report summarizes the current status of the modeling and simulation capabilities developed for the economic assessment of Nuclear-Renewable Hybrid Energy Systems (N-R HES). The increasing penetration of variable renewables is altering the profile of the net demand, with which the other generators on the grid have to cope. N-R HES analyses are being conducted to determine the potential feasibility of mitigating the resultant volatility in the net electricity demand by adding industrial processes that utilize either thermal or electrical energy as stabilizing loads. This coordination of energy generators and users is proposed to mitigate the increase in electricity costmore » and cost volatility through the production of a saleable commodity. Overall, the financial performance of a system that is comprised of peaking units (i.e. gas turbine), baseload supply (i.e. nuclear power plant), and an industrial process (e.g. hydrogen plant) should be optimized under the constraint of satisfying an electricity demand profile with a certain level of variable renewable (wind) penetration. The optimization should entail both the sizing of the components/subsystems that comprise the system and the optimal dispatch strategy (output at any given moment in time from the different subsystems). Some of the capabilities here described have been reported separately in [1, 2, 3]. The purpose of this report is to provide an update on the improvement and extension of those capabilities and to illustrate their integrated application in the economic assessment of N-R HES.« less

Supply and Demand Control of Distributed Generators in a Microgrid for New Energy

NASA Astrophysics Data System (ADS)

Shimakage, Toyonari; Sumita, Jiro; Uchiyama, Noriyuki; Kato, Takeyoshi; Suzuoki, Yasuo

We report the operational results of distributed generators (DGs) in a microgrid and present the effects after incorporating photovoltaic power generation (PV) systems into the microgrid for electric power system. The microgrid was constructed at the EXPO 2005 Aichi site as part of a demonstration promoted by NEDO. A solution is needed to problems where instability in the DGs that utilize natural energy such as solar light and wind force negatively influence existing electric power systems. So, we developed energy control system and controlled DGs output to reduce the fluctuation at the grid connected point caused by PV system's instability output. Our microgrid consists of DGs such as PV systems, fuel cells, and NaS batteries, and these DGs are controlled by an energy control system. We verified practical effectiveness of the installing the microgrid as follows. (1) 99.5% of the power imbalance in the supply and demand over 30 minutes was within a range of ±3% under normal operating conditions, (2) the microgrid contributes to the load leveling, (3) energy control system smoothes the power flow fluctuation of PV system output at the grid connected point, (4) in the future, installing a microgrid will help reduce the additional LFC (Load Frequency Control) capacity.

Sustainable electricity generation by solar pv/diesel hybrid system without storage for off grids areas

NASA Astrophysics Data System (ADS)

Azoumah, Y.; Yamegueu, D.; Py, X.

2012-02-01

Access to energy is known as a key issue for poverty reduction. The electrification rate of sub Saharan countries is one of the lowest among the developing countries. However this part of the world has natural energy resources that could help raising its access to energy, then its economic development. An original "flexy energy" concept of hybrid solar pv/diesel/biofuel power plant, without battery storage, is developed in order to not only make access to energy possible for rural and peri-urban populations in Africa (by reducing the electricity generation cost) but also to make the electricity production sustainable in these areas. Some experimental results conducted on this concept prototype show that the sizing of a pv/diesel hybrid system by taking into account the solar radiation and the load/demand profile of a typical area may lead the diesel generator to operate near its optimal point (70-90 % of its nominal power). Results also show that for a reliability of a PV/diesel hybrid system, the rated power of the diesel generator should be equal to the peak load. By the way, it has been verified through this study that the functioning of a pv/Diesel hybrid system is efficient for higher load and higher solar radiation.

Impacts of Extreme Hot Weather Events on Electricity Consumption in Baden-Wuerttemberg

NASA Astrophysics Data System (ADS)

Mimler, S.

2009-04-01

Changes in electricity consumption due to hot weather events were examined for the German federal state Baden-Württemberg. The analysis consists of three major steps: Firstly, an analysis of the media coverage on the hot summer of 2003 gives direct and indirect information about changes in electricity demand due to changes in consumption patterns. On the one hand there was an overall increase in electricity demand due to the more frequent use of air conditionings, fans, cooling devices and water pumps. On the other hand shifts in electricity consumption took place due to modifications in daily routines: if possible, core working times were scheduled earlier, visitor streams in gastronomy and at events shifted from noon to evening hours, a temporal shifting of purchases took place in early morning or evening hours, and an increased night-activity was documented by a higher number of police operations due to noise disturbances. In a second step, some of the findings of the media analysis were quantified for households in the city region of Karlsruhe. For the chosen electric device groups refrigerators, mini-coolers, air conditionings, fans and electric stoves the difference between the consumption on a hot summer day and a normal summer day was computed. For this purpose, assumptions had to be made on the share of affected households, affected devices or usage patterns. These assumptions were summarized into three scenarios on low, medium and high heat induced changes in electricity consumption. In total, the quantification resulted in a range of about 7.5 to 9.2 % of heat-induced over-consumption related to the average amount of electrical load that is normally provided to Karlsruhe households on a summer's day. A third analysis of summer load curves aimed at testing the following hypotheses derived from the media analysis regarding changes in every-day routines and their effects on shifts in load profiles. To test the hypotheses, correlation tests were applied. (1) The higher the temperature the higher the daily electricity consumption. This hypothesis was confirmed for workdays and weekends at a significance level of 99 %. (2) The higher the temperature the lower the electricity consumption at noon. This hypothesis was confirmed at 99 % for workdays only while it was declined for weekends. (3) The higher the temperature the higher the electricity consumption during evening hours. This hypothesis was declined both for workdays and weekends. (4) The higher the temperature the higher the electricity consumption during night. This hypothesis was confirmed at 95 % for workdays and at 99 % for weekends. (5) The higher the temperature the later the decrease of the consumption curve in the evening. This hypothesis was confirmed at 90 % for workdays only. (6) The higher the temperature the earlier the increase of the consumption curve in the morning. This hypothesis was declined both for workdays and weekends.

System and method employing a minimum distance and a load feature database to identify electric load types of different electric loads

DOEpatents

Lu, Bin; Yang, Yi; Sharma, Santosh K; Zambare, Prachi; Madane, Mayura A

2014-12-23

A method identifies electric load types of a plurality of different electric loads. The method includes providing a load feature database of a plurality of different electric load types, each of the different electric load types including a first load feature vector having at least four different load features; sensing a voltage signal and a current signal for each of the different electric loads; determining a second load feature vector comprising at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the different electric loads; and identifying by a processor one of the different electric load types by determining a minimum distance of the second load feature vector to the first load feature vector of the different electric load types of the load feature database.

An electrical load measurements dataset of United Kingdom households from a two-year longitudinal study

PubMed Central

Murray, David; Stankovic, Lina; Stankovic, Vladimir

2017-01-01

Smart meter roll-outs provide easy access to granular meter measurements, enabling advanced energy services, ranging from demand response measures, tailored energy feedback and smart home/building automation. To design such services, train and validate models, access to data that resembles what is expected of smart meters, collected in a real-world setting, is necessary. The REFIT electrical load measurements dataset described in this paper includes whole house aggregate loads and nine individual appliance measurements at 8-second intervals per house, collected continuously over a period of two years from 20 houses. During monitoring, the occupants were conducting their usual routines. At the time of publishing, the dataset has the largest number of houses monitored in the United Kingdom at less than 1-minute intervals over a period greater than one year. The dataset comprises 1,194,958,790 readings, that represent over 250,000 monitored appliance uses. The data is accessible in an easy-to-use comma-separated format, is time-stamped and cleaned to remove invalid measurements, correctly label appliance data and fill in small gaps of missing data. PMID:28055033

An electrical load measurements dataset of United Kingdom households from a two-year longitudinal study

NASA Astrophysics Data System (ADS)

Murray, David; Stankovic, Lina; Stankovic, Vladimir

2017-01-01

Smart meter roll-outs provide easy access to granular meter measurements, enabling advanced energy services, ranging from demand response measures, tailored energy feedback and smart home/building automation. To design such services, train and validate models, access to data that resembles what is expected of smart meters, collected in a real-world setting, is necessary. The REFIT electrical load measurements dataset described in this paper includes whole house aggregate loads and nine individual appliance measurements at 8-second intervals per house, collected continuously over a period of two years from 20 houses. During monitoring, the occupants were conducting their usual routines. At the time of publishing, the dataset has the largest number of houses monitored in the United Kingdom at less than 1-minute intervals over a period greater than one year. The dataset comprises 1,194,958,790 readings, that represent over 250,000 monitored appliance uses. The data is accessible in an easy-to-use comma-separated format, is time-stamped and cleaned to remove invalid measurements, correctly label appliance data and fill in small gaps of missing data.

An electrical load measurements dataset of United Kingdom households from a two-year longitudinal study.

PubMed

Murray, David; Stankovic, Lina; Stankovic, Vladimir

2017-01-05

Smart meter roll-outs provide easy access to granular meter measurements, enabling advanced energy services, ranging from demand response measures, tailored energy feedback and smart home/building automation. To design such services, train and validate models, access to data that resembles what is expected of smart meters, collected in a real-world setting, is necessary. The REFIT electrical load measurements dataset described in this paper includes whole house aggregate loads and nine individual appliance measurements at 8-second intervals per house, collected continuously over a period of two years from 20 houses. During monitoring, the occupants were conducting their usual routines. At the time of publishing, the dataset has the largest number of houses monitored in the United Kingdom at less than 1-minute intervals over a period greater than one year. The dataset comprises 1,194,958,790 readings, that represent over 250,000 monitored appliance uses. The data is accessible in an easy-to-use comma-separated format, is time-stamped and cleaned to remove invalid measurements, correctly label appliance data and fill in small gaps of missing data.

Low-cost solution to the grid reliability problem with 100% penetration of intermittent wind, water, and solar for all purposes.

PubMed

Jacobson, Mark Z; Delucchi, Mark A; Cameron, Mary A; Frew, Bethany A

2015-12-08

This study addresses the greatest concern facing the large-scale integration of wind, water, and solar (WWS) into a power grid: the high cost of avoiding load loss caused by WWS variability and uncertainty. It uses a new grid integration model and finds low-cost, no-load-loss, nonunique solutions to this problem on electrification of all US energy sectors (electricity, transportation, heating/cooling, and industry) while accounting for wind and solar time series data from a 3D global weather model that simulates extreme events and competition among wind turbines for available kinetic energy. Solutions are obtained by prioritizing storage for heat (in soil and water); cold (in ice and water); and electricity (in phase-change materials, pumped hydro, hydropower, and hydrogen), and using demand response. No natural gas, biofuels, nuclear power, or stationary batteries are needed. The resulting 2050-2055 US electricity social cost for a full system is much less than for fossil fuels. These results hold for many conditions, suggesting that low-cost, reliable 100% WWS systems should work many places worldwide.

Low-cost solution to the grid reliability problem with 100% penetration of intermittent wind, water, and solar for all purposes

PubMed Central

Jacobson, Mark Z.; Delucchi, Mark A.; Cameron, Mary A.; Frew, Bethany A.

2015-01-01

This study addresses the greatest concern facing the large-scale integration of wind, water, and solar (WWS) into a power grid: the high cost of avoiding load loss caused by WWS variability and uncertainty. It uses a new grid integration model and finds low-cost, no-load-loss, nonunique solutions to this problem on electrification of all US energy sectors (electricity, transportation, heating/cooling, and industry) while accounting for wind and solar time series data from a 3D global weather model that simulates extreme events and competition among wind turbines for available kinetic energy. Solutions are obtained by prioritizing storage for heat (in soil and water); cold (in ice and water); and electricity (in phase-change materials, pumped hydro, hydropower, and hydrogen), and using demand response. No natural gas, biofuels, nuclear power, or stationary batteries are needed. The resulting 2050–2055 US electricity social cost for a full system is much less than for fossil fuels. These results hold for many conditions, suggesting that low-cost, reliable 100% WWS systems should work many places worldwide. PMID:26598655

Exploiting the Potential of Data Centers in the Smart Grid

NASA Astrophysics Data System (ADS)

Wang, Xiaoying; Zhang, Yu-An; Liu, Xiaojing; Cao, Tengfei

As the number of cloud computing data centers grows rapidly in recent years, from the perspective of smart grid, they are really large and noticeable electric load. In this paper, we focus on the important role and the potential of data centers as controllable loads in the smart grid. We reviewed relevant research in the area of letting data centers participate in the ancillary services market and demand response programs of the grid, and further investigate the possibility of exploiting the impact of data center placement on the grid. Various opportunities and challenges are summarized, which could provide more chances for researches to explore this field.

Stochastic and Statistical Analysis of Utility Revenues and Weather Data Analysis for Consumer Demand Estimation in Smart Grids

PubMed Central

Ali, S. M.; Mehmood, C. A; Khan, B.; Jawad, M.; Farid, U; Jadoon, J. K.; Ali, M.; Tareen, N. K.; Usman, S.; Majid, M.; Anwar, S. M.

2016-01-01

In smart grid paradigm, the consumer demands are random and time-dependent, owning towards stochastic probabilities. The stochastically varying consumer demands have put the policy makers and supplying agencies in a demanding position for optimal generation management. The utility revenue functions are highly dependent on the consumer deterministic stochastic demand models. The sudden drifts in weather parameters effects the living standards of the consumers that in turn influence the power demands. Considering above, we analyzed stochastically and statistically the effect of random consumer demands on the fixed and variable revenues of the electrical utilities. Our work presented the Multi-Variate Gaussian Distribution Function (MVGDF) probabilistic model of the utility revenues with time-dependent consumer random demands. Moreover, the Gaussian probabilities outcome of the utility revenues is based on the varying consumer n demands data-pattern. Furthermore, Standard Monte Carlo (SMC) simulations are performed that validated the factor of accuracy in the aforesaid probabilistic demand-revenue model. We critically analyzed the effect of weather data parameters on consumer demands using correlation and multi-linear regression schemes. The statistical analysis of consumer demands provided a relationship between dependent (demand) and independent variables (weather data) for utility load management, generation control, and network expansion. PMID:27314229

Stochastic and Statistical Analysis of Utility Revenues and Weather Data Analysis for Consumer Demand Estimation in Smart Grids.

PubMed

Ali, S M; Mehmood, C A; Khan, B; Jawad, M; Farid, U; Jadoon, J K; Ali, M; Tareen, N K; Usman, S; Majid, M; Anwar, S M

2016-01-01

In smart grid paradigm, the consumer demands are random and time-dependent, owning towards stochastic probabilities. The stochastically varying consumer demands have put the policy makers and supplying agencies in a demanding position for optimal generation management. The utility revenue functions are highly dependent on the consumer deterministic stochastic demand models. The sudden drifts in weather parameters effects the living standards of the consumers that in turn influence the power demands. Considering above, we analyzed stochastically and statistically the effect of random consumer demands on the fixed and variable revenues of the electrical utilities. Our work presented the Multi-Variate Gaussian Distribution Function (MVGDF) probabilistic model of the utility revenues with time-dependent consumer random demands. Moreover, the Gaussian probabilities outcome of the utility revenues is based on the varying consumer n demands data-pattern. Furthermore, Standard Monte Carlo (SMC) simulations are performed that validated the factor of accuracy in the aforesaid probabilistic demand-revenue model. We critically analyzed the effect of weather data parameters on consumer demands using correlation and multi-linear regression schemes. The statistical analysis of consumer demands provided a relationship between dependent (demand) and independent variables (weather data) for utility load management, generation control, and network expansion.

A distributed algorithm for demand-side management: Selling back to the grid.

PubMed

Latifi, Milad; Khalili, Azam; Rastegarnia, Amir; Zandi, Sajad; Bazzi, Wael M

2017-11-01

Demand side energy consumption scheduling is a well-known issue in the smart grid research area. However, there is lack of a comprehensive method to manage the demand side and consumer behavior in order to obtain an optimum solution. The method needs to address several aspects, including the scale-free requirement and distributed nature of the problem, consideration of renewable resources, allowing consumers to sell electricity back to the main grid, and adaptivity to a local change in the solution point. In addition, the model should allow compensation to consumers and ensurance of certain satisfaction levels. To tackle these issues, this paper proposes a novel autonomous demand side management technique which minimizes consumer utility costs and maximizes consumer comfort levels in a fully distributed manner. The technique uses a new logarithmic cost function and allows consumers to sell excess electricity (e.g. from renewable resources) back to the grid in order to reduce their electric utility bill. To develop the proposed scheme, we first formulate the problem as a constrained convex minimization problem. Then, it is converted to an unconstrained version using the segmentation-based penalty method. At each consumer location, we deploy an adaptive diffusion approach to obtain the solution in a distributed fashion. The use of adaptive diffusion makes it possible for consumers to find the optimum energy consumption schedule with a small number of information exchanges. Moreover, the proposed method is able to track drifts resulting from changes in the price parameters and consumer preferences. Simulations and numerical results show that our framework can reduce the total load demand peaks, lower the consumer utility bill, and improve the consumer comfort level.

Modelling energy efficiency of an integrated anaerobic digestion and photodegradation of distillery effluent using response surface methodology.

PubMed

Apollo, Seth; Onyango, Maurice S; Ochieng, Aoyi

2016-10-01

Anaerobic digestion (AD) is efficient in organic load removal and bioenergy recovery when applied in treating distillery effluent; however, it is ineffective in colour reduction. In contrast, ultraviolet (UV) photodegradation post-treatment for the AD-treated distillery effluent is effective in colour reduction but has high energy requirement. The effects of operating parameters on bioenergy production and energy demand of photodegradation were modelled using response surface methodology (RSM) with a view of developing a sustainable process in which the biological step could supply energy to the energy-intensive photodegradation step. The organic loading rate (OLRAD) and hydraulic retention time (HRTAD) of the initial biological step were the variables investigated. It was found that the initial biological step removed about 90% of COD and only about 50% colour while photodegradation post-treatment removed 98% of the remaining colour. Maximum bioenergy production of 180.5 kWh/m(3) was achieved. Energy demand of the UV lamp was lowest at low OLRAD irrespective of HRTAD, with values ranging between 87 and 496 kWh/m(3). The bioenergy produced formed 93% of the UV lamp energy demand when the system was operated at OLRAD of 3 kg COD/m(3) d and HRT of 20 days. The presumed carbon dioxide emission reduction when electricity from bioenergy was used to power the UV lamp was 28.8 kg CO2 e/m(3), which could reduce carbon emission by 31% compared to when electricity from the grid was used, leading to environmental conservation.

Can storage reduce electricity consumption? A general equation for the grid-wide efficiency impact of using cooling thermal energy storage for load shifting

NASA Astrophysics Data System (ADS)

Deetjen, Thomas A.; Reimers, Andrew S.; Webber, Michael E.

2018-02-01

This study estimates changes in grid-wide, energy consumption caused by load shifting via cooling thermal energy storage (CTES) in the building sector. It develops a general equation for relating generator fleet fuel consumption to building cooling demand as a function of ambient temperature, relative humidity, transmission and distribution current, and baseline power plant efficiency. The results present a graphical sensitivity analysis that can be used to estimate how shifting load from cooling demand to cooling storage could affect overall, grid-wide, energy consumption. In particular, because power plants, air conditioners and transmission systems all have higher efficiencies at cooler ambient temperatures, it is possible to identify operating conditions such that CTES increases system efficiency rather than decreasing it as is typical for conventional storage approaches. A case study of the Dallas-Fort Worth metro area in Texas, USA shows that using CTES to shift daytime cooling load to nighttime cooling storage can reduce annual, system-wide, primary fuel consumption by 17.6 MWh for each MWh of installed CTES capacity. The study concludes that, under the right circumstances, cooling thermal energy storage can reduce grid-wide energy consumption, challenging the perception of energy storage as a net energy consumer.

46 CFR 111.60-7 - Demand loads.

Code of Federal Regulations, 2010 CFR

2010-10-01

... REQUIREMENTS Wiring Materials and Methods § 111.60-7 Demand loads. Generator, feeder, and bus-tie cables must be selected on the basis of a computed load of not less than the demand load given in Table 111.60-7... 46 Shipping 4 2010-10-01 2010-10-01 false Demand loads. 111.60-7 Section 111.60-7 Shipping COAST...

46 CFR 111.60-7 - Demand loads.

Code of Federal Regulations, 2011 CFR

2011-10-01

... REQUIREMENTS Wiring Materials and Methods § 111.60-7 Demand loads. Generator, feeder, and bus-tie cables must be selected on the basis of a computed load of not less than the demand load given in Table 111.60-7... 46 Shipping 4 2011-10-01 2011-10-01 false Demand loads. 111.60-7 Section 111.60-7 Shipping COAST...

Short Term Load Forecasting with Fuzzy Logic Systems for power system planning and reliability-A Review

NASA Astrophysics Data System (ADS)

Holmukhe, R. M.; Dhumale, Mrs. Sunita; Chaudhari, Mr. P. S.; Kulkarni, Mr. P. P.

2010-10-01

Load forecasting is very essential to the operation of Electricity companies. It enhances the energy efficient and reliable operation of power system. Forecasting of load demand data forms an important component in planning generation schedules in a power system. The purpose of this paper is to identify issues and better method for load foecasting. In this paper we focus on fuzzy logic system based short term load forecasting. It serves as overview of the state of the art in the intelligent techniques employed for load forecasting in power system planning and reliability. Literature review has been conducted and fuzzy logic method has been summarized to highlight advantages and disadvantages of this technique. The proposed technique for implementing fuzzy logic based forecasting is by Identification of the specific day and by using maximum and minimum temperature for that day and finally listing the maximum temperature and peak load for that day. The results show that Load forecasting where there are considerable changes in temperature parameter is better dealt with Fuzzy Logic system method as compared to other short term forecasting techniques.

Solar energy system performance evaluation. Seasonal report for Wormser, Columbia, South Carolina

NASA Technical Reports Server (NTRS)

1980-01-01

The Wormser Solar Energy System's operational performance from April 1979 through March 1980 was evaluated. The space heating subsystem met 42 percent of the measured space heating load and the hot water subsystem met 23 percent of the measured hot water demand. Net electrical energy savings were 4.36 million Btu's or 1277 kwh. Fossil energy savings will increase considerably if the uncontrolled solar energy input to the building is considered.

Gas hydrate cool storage system

DOEpatents

Ternes, M.P.; Kedl, R.J.

1984-09-12

The invention presented relates to the development of a process utilizing a gas hydrate as a cool storage medium for alleviating electric load demands during peak usage periods. Several objectives of the invention are mentioned concerning the formation of the gas hydrate as storage material in a thermal energy storage system within a heat pump cycle system. The gas hydrate was formed using a refrigerant in water and an example with R-12 refrigerant is included. (BCS)

Survey State of the Art: Electrical Load Management Techniques and Equipment.

DTIC Science & Technology

1986-10-31

automobiles and even appliances. Applications in the area of demand and energy management have been multifaceted, given the needs involved and rapid paybacks...copy of the programming to be reloaded into the controller at any time and by designing this module with erasable and reprogrammable memory, the...points and performs DDC programming is stored in (direct digital control) of output reprogrammable , permanent memory points. A RIM may accommodate up

Better Building Alliance, Plug and Process Loads in Commercial Buildings: Capacity and Power Requirement Analysis (Brochure)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

2014-09-01

This brochure addresses gaps in actionable knowledge that can help reduce the plug load capacities designed into buildings. Prospective building occupants and real estate brokers lack accurate references for plug and process load (PPL) capacity requirements, so they often request 5-10 W/ft2 in their lease agreements. This brochure should be used to make these decisions so systems can operate more energy efficiently; upfront capital costs will also decrease. This information can also be used to drive changes in negotiations about PPL energy demands. It should enable brokers and tenants to agree about lower PPL capacities. Owner-occupied buildings will also benefit.more » Overestimating PPL capacity leads designers to oversize electrical infrastructure and cooling systems.« less

Modeling and Economic Analysis of Power Grid Operations in a Water Constrained System

NASA Astrophysics Data System (ADS)

Zhou, Z.; Xia, Y.; Veselka, T.; Yan, E.; Betrie, G.; Qiu, F.

2016-12-01

The power sector is the largest water user in the United States. Depending on the cooling technology employed at a facility, steam-electric power stations withdrawal and consume large amounts of water for each megawatt hour of electricity generated. The amounts are dependent on many factors, including ambient air and water temperatures, cooling technology, etc. Water demands from most economic sectors are typically highest during summertime. For most systems, this coincides with peak electricity demand and consequently a high demand for thermal power plant cooling water. Supplies however are sometimes limited due to seasonal precipitation fluctuations including sporadic droughts that lead to water scarcity. When this occurs there is an impact on both unit commitments and the real-time dispatch. In this work, we model the cooling efficiency of several different types of thermal power generation technologies as a function of power output level and daily temperature profiles. Unit specific relationships are then integrated in a power grid operational model that minimizes total grid production cost while reliably meeting hourly loads. Grid operation is subject to power plant physical constraints, transmission limitations, water availability and environmental constraints such as power plant water exit temperature limits. The model is applied to a standard IEEE-118 bus system under various water availability scenarios. Results show that water availability has a significant impact on power grid economics.

Impacts of High Variable Renewable Energy Futures on Wholesale Electricity Prices, and on Electric-Sector Decision Making

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seel, Joachim; Mills, Andrew D.; Wiser, Ryan H.

Increasing penetrations of variable renewable energy (VRE) can affect wholesale electricity price patterns and make them meaningfully different from past, traditional price patterns. Many long-lasting decisions for supply- and demand-side electricity infrastructure and programs are based on historical observations or assume a business-as-usual future with low shares of VRE. Our motivating question is whether certain electric-sector decisions that are made based on assumptions reflecting low VRE levels will still achieve their intended objective in a high VRE future. We qualitatively describe how various decisions may change with higher shares of VRE and outline an analytical framework for quantitatively evaluating themore » impacts of VRE on long-lasting decisions. We then present results from detailed electricity market simulations with capacity expansion and unit commitment models for multiple regions of the U.S. for low and high VRE futures. We find a general decrease in average annual hourly wholesale energy prices with more VRE penetration, increased price volatility and frequency of very low-priced hours, and changing diurnal price patterns. Ancillary service prices rise substantially and peak net-load hours with high capacity value are shifted increasingly into the evening, particularly for high solar futures. While in this report we only highlight qualitatively the possible impact of these altered price patterns on other demand- and supply-side electric sector decisions, the core set of electricity market prices derived here provides a foundation for later planned quantitative evaluations of these decisions in low and high VRE futures.« less

Application of the Software as a Service Model to the Control of Complex Building Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stadler, Michael; Donadee, Jonathan; Marnay, Chris

2011-03-17

In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building.more » The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analysed.« less

Application of the Software as a Service Model to the Control of Complex Building Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stadler, Michael; Donadee, Jon; Marnay, Chris

2011-03-18

In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building.more » The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analyzed.« less

Field Testing of Telemetry for Demand Response Control of Small Loads

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lanzisera, Steven; Weber, Adam; Liao, Anna

The electricity system in California, from generation through loads, must be prepared for high renewable penetration and increased electrification of end uses while providing increased resilience and lower operating cost. California has an aggressive renewable portfolio standard that is complemented by world-leading greenhouse gas goals. The goal of this project was to evaluate methods of enabling fast demand response (DR) signaling to small loads for low-cost site enablement. We used OpenADR 2.0 to meet telemetry requirements for providing ancillary services, and we used a variety of low-cost devices coupled with open-source software to enable an end-to-end fast DR. The devices,more » architecture, implementation, and testing of the system is discussed in this report. We demonstrate that the emerging Internet of Things (IoT) and Smart Home movements provide an opportunity for diverse small loads to provide fast, low-cost demand response. We used Internet-connected lights, thermostats, load interruption devices, and water heaters to demonstrate an ecosystem of controllable devices. The system demonstrated is capable of providing fast load shed for between 20 dollars and $300 per kilowatt (kW) of available load. The wide range results from some loads may have very low cost but also very little shed capability (a 10 watt [W] LED light can only shed a maximum of 10 W) while some loads (e.g., water heaters or air conditioners) can shed several kilowatts but have a higher initial cost. These costs, however, compare well with other fast demand response costs, with typically are over $100/kilowatt of shed. We contend these loads are even more attractive than their price suggests because many of them will be installed for energy efficiency or non-energy benefits (e.g., improved lighting quality or controllability), and the ability to use them for fast DR is a secondary benefit. Therefore the cost of enabling them for DR may approach zero if a software-only solution can be deployed to enable fast DR after devices are installed for other reasons. We recommend that the DR research community continue to engage with the IoT community to encourage the use of documented and open development interfaces. A library of device drivers and machine-readable interface specifications would significantly reduce the burden on users or system integrators for deploying systems in large numbers of buildings in California.« less

A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cui, Xiaohui; Liu, Cheng; Kim, Hoe Kyoung

2011-01-01

The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level.more » It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.« less

Evaluating the Impacts of Real-Time Pricing on the Cost and Value of Wind Generation

DOE PAGES

Siohansi, Ramteen

2010-05-01

One of the costs associated with integrating wind generation into a power system is the cost of redispatching the system in real-time due to day-ahead wind resource forecast errors. One possible way of reducing these redispatch costs is to introduce demand response in the form of real-time pricing (RTP), which could allow electricity demand to respond to actual real-time wind resource availability using price signals. A day-ahead unit commitment model with day-ahead wind forecasts and a real-time dispatch model with actual wind resource availability is used to estimate system operations in a high wind penetration scenario. System operations are comparedmore » to a perfect foresight benchmark, in which actual wind resource availability is known day-ahead. The results show that wind integration costs with fixed demands can be high, both due to real-time redispatch costs and lost load. It is demonstrated that introducing RTP can reduce redispatch costs and eliminate loss of load events. Finally, social surplus with wind generation and RTP is compared to a system with neither and the results demonstrate that introducing wind and RTP into a market can result in superadditive surplus gains.« less

Feasibility Study of Grid Connected PV-Biomass Integrated Energy System in Egypt

NASA Astrophysics Data System (ADS)

Barakat, Shimaa; Samy, M. M.; Eteiba, Magdy B.; Wahba, Wael Ismael

2016-10-01

The aim of this paper is to present a feasibility study of a grid connected photovoltaic (PV) and biomass Integrated renewable energy (IRE) system providing electricity to rural areas in the Beni Suef governorate, Egypt. The system load of the village is analyzed through the environmental and economic aspects. The model has been designed to provide an optimal system configuration based on daily data for energy availability and demands. A case study area, Monshaet Taher village (29° 1' 17.0718"N, 30° 52' 17.04"E) is identified for economic feasibility in this paper. HOMER optimization model plan imputed from total daily load demand, 2,340 kWh/day for current energy consuming of 223 households with Annual Average Insolation Incident on a Horizontal Surface of 5.79 (kWh/m2/day) and average biomass supplying 25 tons / day. It is found that a grid connected PV-biomass IRE system is an effective way of emissions reduction and it does not increase the investment of the energy system.

Space Cooling in North America: Market Overview and Future Impacts

DOE PAGES

Baxter, Van D; Khowailed, Gannate; Sikes, Karen; ...

2015-01-01

The North American space cooling market, particularly in the United States, is experiencing shifts in regulatory regimes, population patterns, economic conditions, and consumer preferences-all catalyzed further by rapid technological innovation. Taken together these factors may result in a slight reduction in air conditioning shipments in the short term, however the longer term trends indicate a continuing increase in the number of air conditioning systems in the U.S. markets. These increases will be greatest in the warmer and more humid (e.g. higher load demand) regions. This will result in increasing pressure on the U.S. electricity supply system to meet the energymore » peak and consumption demands for building space cooling.« less

Identification of Characterization Factor for Power System Oscillation Based on Multiple Synchronized Phasor Measurements

NASA Astrophysics Data System (ADS)

Hashiguchi, Takuhei; Watanabe, Masayuki; Matsushita, Akihiro; Mitani, Yasunori; Saeki, Osamu; Tsuji, Kiichiro; Hojo, Masahide; Ukai, Hiroyuki

Electric power systems in Japan are composed of remote and distributed location of generators and loads mainly concentrated in large demand areas. The structures having long distance transmission tend to produce heavy power flow with increasing electric power demand. In addition, some independent power producers (IPP) and power producer and suppliers (PPS) are participating in the power generation business, which makes power system dynamics more complex. However, there was little observation as a whole power system. In this paper the authors present a global monitoring system of power system dynamics by using the synchronized phasor measurement of demand side outlets. Phasor Measurement Units (PMU) are synchronized based on the global positioning system (GPS). The purpose of this paper is to show oscillation characteristics and methods for processing original data obtained from PMU after certain power system disturbances triggered by some accidents. This analysis resulted in the observation of the lowest and the second lowest frequency mode. The derivation of eigenvalue with two degree of freedom model brings a monitoring of two oscillation modes. Signal processing based on Wavelet analysis and simulation studies to illustrate the obtained phenomena are demonstrated in detail.

Effects of recent energy system changes on CO2 projections for the United States.

PubMed

Lenox, Carol S; Loughlin, Daniel H

2017-09-21

Recent projections of future United States carbon dioxide (CO 2 ) emissions are considerably lower than projections made just a decade ago. A myriad of factors have contributed to lower forecasts, including reductions in end-use energy service demands, improvements in energy efficiency, and technological innovations. Policies that have encouraged these changes include renewable portfolio standards, corporate vehicle efficiency standards, smart growth initiatives, revisions to building codes, and air and climate regulations. Understanding the effects of these and other factors can be advantageous as society evaluates opportunities for achieving additional CO 2 reductions. Energy system models provide a means to develop such insights. In this analysis, the MARKet ALlocation (MARKAL) model was applied to estimate the relative effects of various energy system changes that have happened since the year 2005 on CO 2 projections for the year 2025. The results indicate that transformations in the transportation and buildings sectors have played major roles in lowering projections. Particularly influential changes include improved vehicle efficiencies, reductions in projected travel demand, reductions in miscellaneous commercial electricity loads, and higher efficiency lighting. Electric sector changes have also contributed significantly to the lowered forecasts, driven by demand reductions, renewable portfolio standards, and air quality regulations.

Cut Electric Bills by Controlling Demand

ERIC Educational Resources Information Center

Grumman, David L.

1974-01-01

Electric bills can be reduced by lowering electric consumption and by controlling demand -- the amount of electricity used at a certain point in time. Gives tips to help reduce electric demand at peak power periods. (Author/DN)

Fuel and power coproduction: The Liquid Phase Methanol (LPMEOH{trademark}) process demonstration at Kingsport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drown, D.P.; Brown, W.R.; Heydorn, E.C.

1997-12-31

The Liquid Phase Methanol (LPMEOH{trademark}) process uses a slurry bubble column reactor to convert syngas (primarily a mixture of carbon monoxide and hydrogen) to methanol. Because of its superior heat management, the process is able to be designed to directly handle the carbon monoxide (CO)-rich syngas characteristic of the gasification of coal, petroleum coke, residual oil, wastes, or of other hydrocarbon feedstocks. When added to an integrated gasification combined cycle (IGCC) power plant, the LPMEOH{trademark} process converts a portion of the CO-rich syngas produced by the gasifier to methanol, and the remainder of the unconverted gas is used to fuelmore » the gas turbine combined-cycle power plant. The LPMEOH{trademark} process has the flexibility to operate in a daily electricity demand load-following manner. Coproduction of power and methanol via IGCC and the LPMEOH{trademark} process provides opportunities for energy storage for electrical demand peak shaving, clean fuel for export, and/or chemical methanol sales.« less

Increasing nuclear power at liberalised energy markets- case Finland

NASA Astrophysics Data System (ADS)

Syri, S.; Kurki-Suonio, T.; Satka, V.

2012-10-01

Several Finnish projections for future electricity demand and the need for peak load capacity indicate a demand growth of about 2 GW from the present to the year 2030. The retirement of existing fossil fuel plants and old nuclear power plants will cause increased net import needs during 2020's, even when assuming additional energy efficiency measures and the commissioning of two new nuclear power plants recently approved by the Finnish Parliament. By the year 2030, the need for additional new capacity will be about 6 GW. The increased dependence on import is in contradiction with the official Government targets. This situation is not unique to Finland, but rather is likely to be the case in many other European countries as well. Both the energy company Fortum and energy-intensive industry in Finland see nuclear energy as a viable future generation technology. We describe the « Mankala » concept which is successfully used to build new nuclear capacity at liberalised electricity market in Finland.

Study on Fuel Cell Network System Considering Reduction in Fuel Cell Capacity Using Load Leveling and Heat Release Loss

NASA Astrophysics Data System (ADS)

Obara, Shin'ya; Kudo, Kazuhiko

Reduction in fuel cell capacity linked to a fuel cell network system is considered. When the power demand of the whole network is small, some of the electric power generated by the fuel cell is supplied to a water electrolysis device, and hydrogen and oxygen gases are generated. Both gases are compressed with each compressor and they are stored in cylinders. When the electric demand of the whole network is large, both gases are supplied to the network, and fuel cells are operated by these hydrogen and oxygen gases. Furthermore, an optimization plan is made to minimize the quantity of heat release of the hot water piping that connects each building. Such an energy network is analyzed assuming connection of individual houses, a hospital, a hotel, a convenience store, an office building, and a factory. Consequently, compared with the conventional system, a reduction of 46% of fuel cell capacity is expected.

Modeling plug-in electric vehicle charging demand with BEAM: the framework for behavior energy autonomy mobility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheppard, Colin; Waraich, Rashid; Campbell, Andrew

This report summarizes the BEAM modeling framework (Behavior, Energy, Mobility, and Autonomy) and its application to simulating plug-in electric vehicle (PEV) mobility, energy consumption, and spatiotemporal charging demand. BEAM is an agent-based model of PEV mobility and charging behavior designed as an extension to MATSim (the Multi-Agent Transportation Simulation model). We apply BEAM to the San Francisco Bay Area and conduct a preliminary calibration and validation of its prediction of charging load based on observed charging infrastructure utilization for the region in 2016. We then explore the impact of a variety of common modeling assumptions in the literature regarding chargingmore » infrastructure availability and driver behavior. We find that accurately reproducing observed charging patterns requires an explicit representation of spatially disaggregated charging infrastructure as well as a more nuanced model of the decision to charge that balances tradeoffs people make with regards to time, cost, convenience, and range anxiety.« less

Multi-Temporal Decomposed Wind and Load Power Models for Electric Energy Systems

NASA Astrophysics Data System (ADS)

Abdel-Karim, Noha

This thesis is motivated by the recognition that sources of uncertainties in electric power systems are multifold and may have potentially far-reaching effects. In the past, only system load forecast was considered to be the main challenge. More recently, however, the uncertain price of electricity and hard-to-predict power produced by renewable resources, such as wind and solar, are making the operating and planning environment much more challenging. The near-real-time power imbalances are compensated by means of frequency regulation and generally require fast-responding costly resources. Because of this, a more accurate forecast and look-ahead scheduling would result in a reduced need for expensive power balancing. Similarly, long-term planning and seasonal maintenance need to take into account long-term demand forecast as well as how the short-term generation scheduling is done. The better the demand forecast, the more efficient planning will be as well. Moreover, computer algorithms for scheduling and planning are essential in helping the system operators decide what to schedule and planners what to build. This is needed given the overall complexity created by different abilities to adjust the power output of generation technologies, demand uncertainties and by the network delivery constraints. Given the growing presence of major uncertainties, it is likely that the main control applications will use more probabilistic approaches. Today's predominantly deterministic methods will be replaced by methods which account for key uncertainties as decisions are made. It is well-understood that although demand and wind power cannot be predicted at very high accuracy, taking into consideration predictions and scheduling in a look-ahead way over several time horizons generally results in more efficient and reliable utilization, than when decisions are made assuming deterministic, often worst-case scenarios. This change is in approach is going to ultimately require new electricity market rules capable of providing the right incentives to manage uncertainties and of differentiating various technologies according to the rate at which they can respond to ever changing conditions. Given the overall need for modeling uncertainties in electric energy systems, we consider in this thesis the problem of multi-temporal modeling of wind and demand power, in particular. Historic data is used to derive prediction models for several future time horizons. Short-term prediction models derived can be used for look-ahead economic dispatch and unit commitment, while the long-term annual predictive models can be used for investment planning. As expected, the accuracy of such predictive models depends on the time horizons over which the predictions are made, as well as on the nature of uncertain signals. It is shown that predictive models obtained using the same general modeling approaches result in different accuracy for wind than for demand power. In what follows, we introduce several models which have qualitatively different patterns, ranging from hourly to annual. We first transform historic time-stamped data into the Fourier Transform (Fr) representation. The frequency domain data representation is used to decompose the wind and load power signals and to derive predictive models relevant for short-term and long-term predictions using extracted spectral techniques. The short-term results are interpreted next as a Linear Prediction Coding Model (LPC) and its accuracy is analyzed. Next, a new Markov-Based Sensitivity Model (MBSM) for short term prediction has been proposed and the dispatched costs of uncertainties for different predictive models with comparisons have been developed. Moreover, the Discrete Markov Process (DMP) representation is applied to help assess probabilities of most likely short-, medium- and long-term states and the related multi-temporal risks. In addition, this thesis discusses operational impacts of wind power integration in different scenario levels by performing more than 9,000 AC Optimal Power Flow runs. The effects of both wind and load variations on system constraints and costs are presented. The limitations of DC Optimal Power Flow (DCOPF) vs. ACOPF are emphasized by means of system convergence problems due to the effect of wind power on changing line flows and net power injections. By studying the effect of having wind power on line flows, we found that the divergence problem applies in areas with high wind and hydro generation capacity share (cheap generations). (Abstract shortened by UMI.).

Residential Variable-Capacity Heat Pumps Sized to Heating Loads

DOE Office of Scientific and Technical Information (OSTI.GOV)

Munk, Jeffrey D.; Jackson, Roderick K.; Odukomaiya, Adewale

2014-01-01

Variable capacity heat pumps are an emerging technology offering significant energy savings potential and improved efficiency. With conventional single-speed systems, it is important to appropriately size heat pumps for the cooling load as over-sizing would result in cycling and insufficient latent capacity required for humidity control. These appropriately sized systems are often under-sized for the heating load and require inefficient supplemental electric resistance heat to meet the heating demand. Variable capacity heat pumps address these shortcomings by providing an opportunity to intentionally size systems for the dominant heating season load without adverse effects of cycling or insufficient dehumidification in themore » cooling season. This intentionally-sized system could result in significant energy savings in the heating season, as the need for inefficient supplemental electric resistance heat is drastically reduced. This is a continuation of a study evaluating the energy consumption of variable capacity heat pumps installed in two unoccupied research homes in Farragut, a suburb of Knoxville, Tennessee. In this particular study, space conditioning systems are intentionally sized for the heating season loads to provide an opportunity to understand and evaluate the impact this would have on electric resistance heat use and dehumidification. The results and conclusions drawn through this research are valid and specific for portions of the Southeastern and Midwestern United States falling in the mixed-humid climate zone. While other regions in the U.S. do not experience this type of climate, this work provides a basis for, and can help understand the implications of other climate zones on residential space conditioning energy consumption. The data presented here will provide a framework for fine tuning residential building EnergyPlus models that are being developed.« less

Design and Testing of a Breadboard Electrical Power Control Unit for the Fluid Combustion Facility Experiment

NASA Technical Reports Server (NTRS)

Kimnach, Greg L.; Lebron, Ramon C.

1999-01-01

The Fluid Combustion Facility (FCF) Project and the Power Technology Division at the NASA Glenn Research Center (GRC) at Lewis Field in Cleveland, OH along with the Sundstrand Corporation in Rockford, IL are jointly developing an Electrical Power Converter Unit (EPCU) for the Fluid Combustion Facility to be flown on the International Space Station (ISS). The FCF facility experiment contains three racks: A core rack, a combustion rack, and a fluids rack. The EPCU will be used as the power interface to the ISS 120V(sub dc) power distribution system by each FCF experiment rack which requires 28V(sub dc). The EPCU is a modular design which contains three 120V(sub dc)-to-28V(sub dc) full-bridge, power converters rated at 1 kW(sub e) each bus transferring input relays and solid-state, current-limiting input switches, 48 current-limiting, solid-state, output switches; and control and telemetry hardware. The EPCU has all controls required to autonomously share load demand between the power feeds and--if absolutely necessary--shed loads. The EPCU, which maximizes the usage of allocated ISS power and minimizes loss of power to loads, can be paralleled with other EPCUs. This paper overviews the electrical design and operating characteristics of the EPCU and presents test data from the breadboard design.

Agent-Based Simulation for Interconnection-Scale Renewable Integration and Demand Response Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chassin, David P.; Behboodi, Sahand; Crawford, Curran

This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council (WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methodsmore » presented.« less

Agent-Based Simulation for Interconnection-Scale Renewable Integration and Demand Response Studies

DOE PAGES

Chassin, David P.; Behboodi, Sahand; Crawford, Curran; ...

2015-12-23

This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council (WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methodsmore » presented.« less

Sustainable Electricity and Water for Europe, Middle East and North Africa

NASA Astrophysics Data System (ADS)

Müller-Steinhagen, H.; Trieb, F.

2009-04-01

Sufficient supply of energy and water are among the key requirements for a sustainable development of nations. Both depend strongly on energy carriers such as oil, gas, coal and uranium which have limited availability and a negative impact on the environment during their use. Within the framework of a series of detailed studies, conventional and renewable energy sources available for electricity production and desalination in Europe, North Africa and the Middle East (EU-MENA) have been analysed. Scenarios have been developed for a sustainable electricity supply based on increased plant and user efficiency, and an accelerated introduction of renewable energy sources. Even if all potential exclusion criteria are applied and only those technologies are considered which will become economically competitive within the next decades, a potential has been identified which exceeds the present electricity demand by orders of magnitude. Solar energy is, in this context, the by far largest resource which will most economically be exploited in centralised solar thermal power plants. In combination with heat storage, these power plants can provide bulk and peak electricity, and can be combined with thermal or reverse osmosis desalination plants. At present, solar thermal power plants with a total capacity exceeding 10 GW are in operation or under construction in Abu Dhabi, Algeria, Egypt, Iran, Israel, Italy, Morocco, Spain and the USA. Ultimately, the increasing electricity demand of EU-MENA can only be secured in conjunction with the required climate and resource protection targets, if all renewable energy sources are exploited where appropriate, and conversion and user efficiency are increased. To utilise the enormous energy resources of the Mediterranean countries, high voltage direct current power lines will have to be built, linking the most abundant and economic resources with the load centres in the North. With electricity losses below 10% over a distance of 3000 km, HVDC lines may provide up to 15% of the total European electricity demand by 2050. For the MENA region, this scenario will provide most promising opportunities: in addition to the export of electricity replacing revenues from dwindling oil and gas resources, solar thermal power plants will provide a major share of their own electricity demands at competitive costs and will provide fresh water by seawater desalination, the latter becoming an urgent requirement over the next decades. This presentation outlines the assumptions and results of the studies which have been performed by an international consortium for 50 EU-MENA countries, as well as the technological and economic implications of the suggested scenario.

Demand forecasting of electricity in Indonesia with limited historical data

NASA Astrophysics Data System (ADS)

Dwi Kartikasari, Mujiati; Rohmad Prayogi, Arif

2018-03-01

Demand forecasting of electricity is an important activity for electrical agents to know the description of electricity demand in future. Prediction of demand electricity can be done using time series models. In this paper, double moving average model, Holt’s exponential smoothing model, and grey model GM(1,1) are used to predict electricity demand in Indonesia under the condition of limited historical data. The result shows that grey model GM(1,1) has the smallest value of MAE (mean absolute error), MSE (mean squared error), and MAPE (mean absolute percentage error).

Electrical properties of multiphase composites based on carbon nanotubes and an optimized clay content

NASA Astrophysics Data System (ADS)

Egiziano, Luigi; Lamberti, Patrizia; Spinelli, Giovanni; Tucci, Vincenzo; Guadagno, Liberata; Vertuccio, Luigi

2016-05-01

The experimental results concerning the characterization of a multiphase nanocomposite systems based on epoxy matrix, loaded with different amount of multi-walled carbon nanotubes (MWCNTs) and an optimized Hydrotalcite (HT) clay content (i.e. 0.6 wt%), duly identified by an our previous theoretical study based on Design of Experiment (DoE), are presented. Dynamic-mechanical analysis (DMA) reveal that even the introduction of higher HT loading (up to 1%wt) don't affect significantly the mechanical properties of the nanocomposites while morphological investigations show an effective synergy between clay and carbon nanotubes that leads to peculiar micro/nanostructures that favor the creation of the electrical conductive network inside the insulating resin. An electrical characterization is carried out in terms of DC electrical conductivity, percolation threshold (EPT) and frequency response in the range 10Hz-1MHz. In particular, the measurements of the DC conductivity allow to obtain the typical "percolation" curve also found for classical CNT-polymer mixtures and a value of about 2 S/m for the electrical conductivity is achieved at the highest considered CNTs concentration (i.e. 1 wt%). The results suggest that multiphase nanocomposites obtained incorporating dispersive nanofillers, in addition to the conductive one, may be a valid alternative to the polymer blends, to improve the properties of the polymeric materials thus able to meet high demands, particularly concerning their mechanical and thermal stability and electrical features required in the aircraft engineering.

Guest Editorial Introduction to the Special Issue on 'Advanced Signal Processing Techniques and Telecommunications Network Infrastructures for Smart Grid Analysis, Monitoring, and Management'

DOE PAGES

Bracale, Antonio; Barros, Julio; Cacciapuoti, Angela Sara; ...

2015-06-10

Electrical power systems are undergoing a radical change in structure, components, and operational paradigms, and are progressively approaching the new concept of smart grids (SGs). Future power distribution systems will be characterized by the simultaneous presence of various distributed resources, such as renewable energy systems (i.e., photovoltaic power plant and wind farms), storage systems, and controllable/non-controllable loads. Control and optimization architectures will enable network-wide coordination of these grid components in order to improve system efficiency and reliability and to limit greenhouse gas emissions. In this context, the energy flows will be bidirectional from large power plants to end users andmore » vice versa; producers and consumers will continuously interact at different voltage levels to determine in advance the requests of loads and to adapt the production and demand for electricity flexibly and efficiently also taking into account the presence of storage systems.« less

Emissions and Cost Implications of Controlled Electric Vehicle Charging in the U.S. PJM Interconnection.

PubMed

Weis, Allison; Michalek, Jeremy J; Jaramillo, Paulina; Lueken, Roger

2015-05-05

We develop a unit commitment and economic dispatch model to estimate the operation costs and the air emissions externality costs attributable to new electric vehicle electricity demand under controlled vs uncontrolled charging schemes. We focus our analysis on the PJM Interconnection and use scenarios that characterize (1) the most recent power plant fleet for which sufficient data are available, (2) a hypothetical 2018 power plant fleet that reflects upcoming plant retirements, and (3) the 2018 fleet with increased wind capacity. We find that controlled electric vehicle charging can reduce associated generation costs by 23%-34% in part by shifting loads to lower-cost, higher-emitting coal plants. This shift results in increased externality costs of health and environmental damages from increased air pollution. On balance, we find that controlled charging of electric vehicles produces negative net social benefits in the recent PJM grid but could have positive net social benefits in a future grid with sufficient coal retirements and wind penetration.

Creating the electric energy mix of a non-connected Aegean island

NASA Astrophysics Data System (ADS)

Stamou, Paraskevi; Karali, Sophia; Chalakatevaki, Maria; Daniil, Vasiliki; Tzouka, Katerina; Dimitriadis, Panayiotis; Iliopoulou, Theano; Papanicolaou, Panos; Koutsoyiannis, Demetris; Mamasis, Nikos

2017-04-01

As the electric energy in the non-connected islands is mainly produced by oil-fueled power plants, the unit cost is extremely high. Here the various energy sources are examined in order to create the appropriate electric energy mix for a non-connected Aegean island. All energy sources (renewable and fossil fuels) are examined and each one is evaluated using technical, environmental and economic criteria. Finally the most appropriate energy sources are simulated considering the corresponding energy works. Special emphasis is given to the use of biomass and the possibility of replacing (even partially) the existing oil-fueled power plant. Finally, a synthesis of various energy sources is presented that satisfies the electric energy demand taking into account the base and peak electric loads of the island. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

Modeling renewable portfolio standards for the annual energy outlook 1998 - electricity market module

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

The Electricity Market Module (EMM) is the electricity supply component of the National Energy Modeling System (NEMS). The EMM represents the generation, transmission, and pricing of electricity. It consists of four submodules: the Electricity Capacity Planning (ECP) Submodule, the Electricity Fuel Dispatch (EFD) Submodule, the Electricity Finance and Pricing (EFP) Submodule, and the Load and Demand-Side Management (LDSM) Submodule. For the Annual Energy Outlook 1998 (AEO98), the EMM has been modified to represent Renewable Portfolio Standards (RPS), which are included in many of the Federal and state proposals for deregulating the electric power industry. A RPS specifies that electricity suppliersmore » must produce a minimum level of generation using renewable technologies. Producers with insufficient renewable generating capacity can either build new plants or purchase {open_quotes}credits{close_quotes} from other suppliers with excess renewable generation. The representation of a RPS involves revisions to the ECP, EFD, and the EFP. The ECP projects capacity additions required to meet the minimum renewable generation levels in future years. The EFD determines the sales and purchases of renewable credits for the current year. The EFP incorporates the cost of building capacity and trading credits into the price of electricity.« less

Dielectric properties of inorganic fillers filled epoxy thin film

NASA Astrophysics Data System (ADS)

Norshamira, A.; Mariatti, M.

2015-07-01

The demand on the small size and high performance electronics has driven changes in the electronic packaging requirements from discrete capacitor to embedded capacitor. Embedded capacitor can improve electrical performance compared with discrete capacitor. This study aimed to achieve high dielectric of epoxy thin film composite that were targeted for application as embedded capacitor. In this study, inorganic fillers such as Calcium Copper Titanate (CCTO), Iron(III) Oxide (Fe2O3) and Titanium Dioxide (TiO2) were loaded in epoxy system at 5 and 20vol%. Morphology and dielectric properties were investigated to identify the effect of fillers loading and types of fillers on the properties of epoxy thin film composite. Based on the study, CCTO with 20vol% loading was found to have good dielectric properties compared to other type of fillers.

Interconnection-wide hour-ahead scheduling in the presence of intermittent renewables and demand response: A surplus maximizing approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Behboodi, Sahand; Chassin, David P.; Djilali, Ned

This study describes a new approach for solving the multi-area electricity resource allocation problem when considering both intermittent renewables and demand response. The method determines the hourly inter-area export/import set that maximizes the interconnection (global) surplus satisfying transmission, generation and load constraints. The optimal inter-area transfer set effectively makes the electricity price uniform over the interconnection apart from constrained areas, which overall increases the consumer surplus more than it decreases the producer surplus. The method is computationally efficient and suitable for use in simulations that depend on optimal scheduling models. The method is demonstrated on a system that represents Northmore » America Western Interconnection for the planning year of 2024. Simulation results indicate that effective use of interties reduces the system operation cost substantially. Excluding demand response, both the unconstrained and the constrained scheduling solutions decrease the global production cost (and equivalently increase the global economic surplus) by 12.30B and 10.67B per year, respectively, when compared to the standalone case in which each control area relies only on its local supply resources. This cost saving is equal to 25% and 22% of the annual production cost. Including 5% demand response, the constrained solution decreases the annual production cost by 10.70B, while increases the annual surplus by 9.32B in comparison to the standalone case.« less

Interconnection-wide hour-ahead scheduling in the presence of intermittent renewables and demand response: A surplus maximizing approach

DOE PAGES

Behboodi, Sahand; Chassin, David P.; Djilali, Ned; ...

2016-12-23

This study describes a new approach for solving the multi-area electricity resource allocation problem when considering both intermittent renewables and demand response. The method determines the hourly inter-area export/import set that maximizes the interconnection (global) surplus satisfying transmission, generation and load constraints. The optimal inter-area transfer set effectively makes the electricity price uniform over the interconnection apart from constrained areas, which overall increases the consumer surplus more than it decreases the producer surplus. The method is computationally efficient and suitable for use in simulations that depend on optimal scheduling models. The method is demonstrated on a system that represents Northmore » America Western Interconnection for the planning year of 2024. Simulation results indicate that effective use of interties reduces the system operation cost substantially. Excluding demand response, both the unconstrained and the constrained scheduling solutions decrease the global production cost (and equivalently increase the global economic surplus) by 12.30B and 10.67B per year, respectively, when compared to the standalone case in which each control area relies only on its local supply resources. This cost saving is equal to 25% and 22% of the annual production cost. Including 5% demand response, the constrained solution decreases the annual production cost by 10.70B, while increases the annual surplus by 9.32B in comparison to the standalone case.« less

2015 California Demand Response Potential Study - Charting California’s Demand Response Future. Interim Report on Phase 1 Results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alstone, Peter; Potter, Jennifer; Piette, Mary Ann

Demand response (DR) is an important resource for keeping the electricity grid stable and efficient; deferring upgrades to generation, transmission, and distribution systems; and providing other customer economic benefits. This study estimates the potential size and cost of the available DR resource for California’s three investor-owned utilities (IOUs), as the California Public Utilities Commission (CPUC) evaluates how to enhance the role of DR in meeting California’s resource planning needs and operational requirements. As the state forges a clean energy future, the contributions of wind and solar electricity from centralized and distributed generation will fundamentally change the power grid’s operational dynamics.more » This transition requires careful planning to ensure sufficient capacity is available with the right characteristics – flexibility and fast response – to meet reliability needs. Illustrated is a snapshot of how net load (the difference between demand and intermittent renewables) is expected to shift. Increasing contributions from renewable generation introduces steeper ramps and a shift, into the evening, of the hours that drive capacity needs. These hours of peak capacity need are indicated by the black dots on the plots. Ultimately this study quantifies the ability and the cost of using DR resources to help meet the capacity need at these forecasted critical hours in the state.« less

Thermal performance of phase change wallboard for residential cooling application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feustel, H.E.; Stetiu, C.

1997-04-01

Cooling of residential California buildings contributes significantly to electrical consumption and peak power demand mainly due to very poor load factors in milder climates. Thermal mass can be utilized to reduce the peak-power demand, downsize the cooling systems, and/or switch to low-energy cooling sources. Large thermal storage devices have been used in the past to overcome the shortcomings of alternative cooling sources, or to avoid high demand charges. The manufacturing of phase change material (PCM) implemented in gypsum board, plaster or other wall-covering material, would permit the thermal storage to become part of the building structure. PCMs have two importantmore » advantages as storage media: they can offer an order-of-magnitude increase in thermal storage capacity, and their discharge is almost isothermal. This allows the storage of high amounts of energy without significantly changing the temperature of the room envelope. As heat storage takes place inside the building, where the loads occur, rather than externally, additional transport energy is not required. RADCOOL, a thermal building simulation program based on the finite difference approach, was used to numerically evaluate the latent storage performance of treated wallboard. Extended storage capacity obtained by using double PCM-wallboard is able to keep the room temperatures close to the upper comfort limits without using mechanical cooling. Simulation results for a living room with high internal loads and weather data for Sunnyvale, California, show significant reduction of room air temperature when heat can be stored in PCM-treated wallboards.« less

Influence of Shading on Cooling Energy Demand

NASA Astrophysics Data System (ADS)

Rabczak, Sławomir; Bukowska, Maria; Proszak-Miąsik, Danuta; Nowak, Krzysztof

2017-10-01

The article presents an analysis of the building cooling load taking into account the variability of the factors affecting the size of the heat gains. In order to minimize the demand for cooling, the effect of shading elements installed on the outside on the windows and its effect on size of the cooling capacity of air conditioning system for the building has been estimated. Multivariate building cooling load calculations to determine the size of the reduction in cooling demand has derived. Determination of heat gain from the sun is laborious, but gives a result which reflects the influence of the surface transparent partitions, devices used as sunscreen and its location on the building envelope in relation to the world, as well as to the internal heat gains has great attention in obtained calculation. In this study, included in the balance sheet of solar heat gains are defined in three different shading of windows. Calculating the total demand cooling is made for variants assuming 0% shading baffles transparent, 50% shading baffles transparent external shutters at an angle of 45 °, 100% shading baffles transparent hours 12 from the N and E and from 12 from the S and W of the outer slat blinds. The calculation of the average hourly cooling load was taken into account the option assuming the hypothetical possibility of default by up to 10% of the time assumed the cooling season temperatures in the rooms. To reduce the consumption of electricity energy in the cooling system of the smallest variant identified the need for the power supply for the operation of the cooling system. Also assessed the financial benefits of the temporary default of comfort.

Optimal policies for simultaneous energy consumption and ancillary service provision for flexible loads under stochastic prices and no capacity reservation constraint

NASA Astrophysics Data System (ADS)

Kefayati, Mahdi; Baldick, Ross

2015-07-01

Flexible loads, i.e. the loads whose power trajectory is not bound to a specific one, constitute a sizable portion of current and future electric demand. This flexibility can be used to improve the performance of the grid, should the right incentives be in place. In this paper, we consider the optimal decision making problem faced by a flexible load, demanding a certain amount of energy over its availability period, subject to rate constraints. The load is also capable of providing ancillary services (AS) by decreasing or increasing its consumption in response to signals from the independent system operator (ISO). Under arbitrarily distributed and correlated Markovian energy and AS prices, we obtain the optimal policy for minimising expected total cost, which includes cost of energy and benefits from AS provision, assuming no capacity reservation requirement for AS provision. We also prove that the optimal policy has a multi-threshold form and can be computed, stored and operated efficiently. We further study the effectiveness of our proposed optimal policy and its impact on the grid. We show that, while optimal simultaneous consumption and AS provision under real-time stochastic prices are achievable with acceptable computational burden, the impact of adopting such real-time pricing schemes on the network might not be as good as suggested by the majority of the existing literature. In fact, we show that such price responsive loads are likely to induce peak-to-average ratios much more than what is observed in the current distribution networks and adversely affect the grid.

Long-term power generation expansion planning with short-term demand response: Model, algorithms, implementation, and electricity policies

NASA Astrophysics Data System (ADS)

Lohmann, Timo

Electric sector models are powerful tools that guide policy makers and stakeholders. Long-term power generation expansion planning models are a prominent example and determine a capacity expansion for an existing power system over a long planning horizon. With the changes in the power industry away from monopolies and regulation, the focus of these models has shifted to competing electric companies maximizing their profit in a deregulated electricity market. In recent years, consumers have started to participate in demand response programs, actively influencing electricity load and price in the power system. We introduce a model that features investment and retirement decisions over a long planning horizon of more than 20 years, as well as an hourly representation of day-ahead electricity markets in which sellers of electricity face buyers. This combination makes our model both unique and challenging to solve. Decomposition algorithms, and especially Benders decomposition, can exploit the model structure. We present a novel method that can be seen as an alternative to generalized Benders decomposition and relies on dynamic linear overestimation. We prove its finite convergence and present computational results, demonstrating its superiority over traditional approaches. In certain special cases of our model, all necessary solution values in the decomposition algorithms can be directly calculated and solving mathematical programming problems becomes entirely obsolete. This leads to highly efficient algorithms that drastically outperform their programming problem-based counterparts. Furthermore, we discuss the implementation of all tailored algorithms and the challenges from a modeling software developer's standpoint, providing an insider's look into the modeling language GAMS. Finally, we apply our model to the Texas power system and design two electricity policies motivated by the U.S. Environment Protection Agency's recently proposed CO2 emissions targets for the power sector.

Research on electricity market operation mechanism and its benefit of demand side participation

NASA Astrophysics Data System (ADS)

Han, Shuai; Yan, Xu; Qin, Li-juan; Lin, Xi-qiao; Zeng, Bo

2017-08-01

Demand response plays an important role in maintaining the economic stability of the system, and has the characteristics of high efficiency, low cost, fast response, good environmental benefits and so on. Demand side resource is an important part of electricity market. The research of demand side resources in our country is still in the initial stage, but the opening of the electricity sales side provides a broad prospect for the development of electricity market. This paper summarizes the main types of demand side resources in our country, analyzes the economic principle of demand response from the micro perspective, puts forward some suggestions on the operation mechanism of China’s demand side resources participating in the electricity market under the condition of electricity sales side opening, analyzes the current situation of pricing in the electricity wholesale market and sets up the pricing strategy of the centralized wholesale market with the demand side power supply participating in quotation, which makes the social and economic benefits reach the maximum.

Foundational Report Series: Advanced Distribution Management Systems for Grid Modernization, DMS Integration of Distributed Energy Resources and Microgrids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singh, Ravindra; Reilly, James T.; Wang, Jianhui

Deregulation of the electric utility industry, environmental concerns associated with traditional fossil fuel-based power plants, volatility of electric energy costs, Federal and State regulatory support of “green” energy, and rapid technological developments all support the growth of Distributed Energy Resources (DERs) in electric utility systems and ensure an important role for DERs in the smart grid and other aspects of modern utilities. DERs include distributed generation (DG) systems, such as renewables; controllable loads (also known as demand response); and energy storage systems. This report describes the role of aggregators of DERs in providing optimal services to distribution networks, through DERmore » monitoring and control systems—collectively referred to as a Distributed Energy Resource Management System (DERMS)—and microgrids in various configurations.« less

Smart signal processing for an evolving electric grid

NASA Astrophysics Data System (ADS)

Silva, Leandro Rodrigues Manso; Duque, Calos Augusto; Ribeiro, Paulo F.

2015-12-01

Electric grids are interconnected complex systems consisting of generation, transmission, distribution, and active loads, recently called prosumers as they produce and consume electric energy. Additionally, these encompass a vast array of equipment such as machines, power transformers, capacitor banks, power electronic devices, motors, etc. that are continuously evolving in their demand characteristics. Given these conditions, signal processing is becoming an essential assessment tool to enable the engineer and researcher to understand, plan, design, and operate the complex and smart electronic grid of the future. This paper focuses on recent developments associated with signal processing applied to power system analysis in terms of characterization and diagnostics. The following techniques are reviewed and their characteristics and applications discussed: active power system monitoring, sparse representation of power system signal, real-time resampling, and time-frequency (i.e., wavelets) applied to power fluctuations.

How to select electrical end-use meters for proper measurement of DSM impact estimates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bowman, M.

1994-12-31

Does metering actually provide higher accuracy impact estimates? The answer is sometimes yes, sometimes no. It depends on how the metered data will be used. DSM impact estimates can be achieved in a variety of ways, including engineering algorithms, modeling and statistical methods. Yet for all of these methods, impacts can be calculated as the difference in pre- and post-installation annual load shapes. Increasingly, end-use metering is being used to either adjust and calibrate a particular estimate method, or measure load shapes directly. It is therefore not surprising that metering has become synonymous with higher accuracy impact estimates. If meteredmore » data is used as a component in an estimating methodology, its relative contribution to accuracy can be analyzed through propagation of error or {open_quotes}POE{close_quotes} analysis. POE analysis is a framework which can be used to evaluate different metering options and their relative effects on cost and accuracy. If metered data is used to directly measure pre- and post-installation load shapes to calculate energy and demand impacts, then the accuracy of the whole metering process directly affects the accuracy of the impact estimate. This paper is devoted to the latter case, where the decision has been made to collect high-accuracy metered data of electrical energy and demand. The underlying assumption is that all meters can yield good results if applied within the scope of their limitations. The objective is to know the application, understand what meters are actually doing to measure and record power, and decide with confidence when a sophisticated meter is required, and when a less expensive type will suffice.« less

Distributed Energy Systems Integration and Demand Optimization for Autonomous Operations and Electric Grid Transactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghatikar, Girish; Mashayekh, Salman; Stadler, Michael

Distributed power systems in the U.S. and globally are evolving to provide reliable and clean energy to consumers. In California, existing regulations require significant increases in renewable generation, as well as identification of customer-side distributed energy resources (DER) controls, communication technologies, and standards for interconnection with the electric grid systems. As DER deployment expands, customer-side DER control and optimization will be critical for system flexibility and demand response (DR) participation, which improves the economic viability of DER systems. Current DER systems integration and communication challenges include leveraging the existing DER and DR technology and systems infrastructure, and enabling optimized cost,more » energy and carbon choices for customers to deploy interoperable grid transactions and renewable energy systems at scale. Our paper presents a cost-effective solution to these challenges by exploring communication technologies and information models for DER system integration and interoperability. This system uses open standards and optimization models for resource planning based on dynamic-pricing notifications and autonomous operations within various domains of the smart grid energy system. It identifies architectures and customer engagement strategies in dynamic DR pricing transactions to generate feedback information models for load flexibility, load profiles, and participation schedules. The models are tested at a real site in California—Fort Hunter Liggett (FHL). Furthermore, our results for FHL show that the model fits within the existing and new DR business models and networked systems for transactive energy concepts. Integrated energy systems, communication networks, and modeling tools that coordinate supply-side networks and DER will enable electric grid system operators to use DER for grid transactions in an integrated system.« less

Stratum Electricity Markets: Toward Multi-temporal Distributed Risk Management for Sustainable Electricity Provision

NASA Astrophysics Data System (ADS)

Wu, Zhiyong (Richard)

Motivated by the overall challenge of ensuring long-term sustainable electricity service, we view this challenge as a long-term decision making problem under uncertainties. We start by recognizing that, independent of the industry organization, the uncertainties are enormous and often exogenous to the energy service providers. They are multi-dimensional and are result of fundamental drivers, ranging from the supply side, through the demand side, to the regulatory and policy sides. The basic contribution of this thesis comes from the recognition that long-term investments for ensuring reliable and stable electricity service critically depend on how these uncertainties are perceived, valued and managed by the different stakeholders within the complex industry organization such as the electric power industry. We explain several reasons why price signals obtained from current short-term electricity markets alone are not sufficient enough for long-term sustainable provision. Some enhancements are presented in the thesis to improve the short-term electricity market price signals to reflect the true cost of operation. New market mechanisms and instruments are needed to facilitate the stakeholders to better deal with long-term risks. The problems of ensuring long-term stable reliable service in the sense of the traditional resource adequacy requirements are revisited in both the restructuring industry and regulated industry. We introduce a so-called Stratum Electricity Market (SEM) design as the basic market mechanism for solving the problem of long-term reliable electricity service through a series of interactive multi-lateral market exchange platforms for risks communication, management and evaluations over various time horizons and by the different groups of stakeholders. In other words, our proposed SEM is a basic IT-enabled framework for the decision making processes by various parties over different time. Because of the uniqueness of electricity as a commodity, the values for the same amount of energy during different time and at different location can vary dramatically. Moreover, for the same hour, the values for the same amount of power at base load level or at peak load level are different due to the different generation technologies and other non-convex constraints like unit commitment. The multiple market products at zonal/nodal levels with different time horizon and time of use categories are designed to reflect more realistic demand and supply conditions at various temporal and spatial granularities. Detailed market rules, rights and regulations (3Rs) concerning the sub-markets interactions, product hierarchy and financial settlements are also examined.

Method and system employing graphical electric load categorization to identify one of a plurality of different electric load types

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Yi; Du, Liang

A system for different electric loads includes sensors structured to sense voltage and current signals for each of the different electric loads; a hierarchical load feature database having a plurality of layers, with one of the layers including a plurality of different load categories; and a processor. The processor acquires voltage and current waveforms from the sensors for a corresponding one of the different electric loads; maps a voltage-current trajectory to a grid including a plurality of cells, each of which is assigned a binary value of zero or one; extracts a plurality of different features from the mapped gridmore » of cells as a graphical signature of the corresponding one of the different electric loads; derives a category of the corresponding one of the different electric loads from the database; and identifies one of a plurality of different electric load types for the corresponding one of the different electric loads.« less

Seasonal Thermal Energy Storage Program

NASA Technical Reports Server (NTRS)

Minor, J. E.

1980-01-01

The Seasonal Thermal Energy Storage (STES) Program designed to demonstrate the storage and retrieval of energy on a seasonal basis using heat or cold available from waste or other sources during a surplus period is described. Factors considered include reduction of peak period demand and electric utility load problems and establishment of favorable economics for district heating and cooling systems for commercialization of the technology. The initial thrust of the STES Program toward utilization of ground water systems (aquifers) for thermal energy storage is emphasized.

Improving the Investment Potential of the Evenkiiskaya HPP When Working Jointly with HPPS of the Volga – Kama Cascade

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aleksandrovskii, A. Yu., E-mail: ayaleksand@mail.ru; Soldatkin, A. Yu.; Volkov, D. M.

The capability is studied of improving the investment potential of the Evenkiiskaya HPP by using the power it generates in the United Power System of the European part of Russia by transitioning to a compensated electrical regime of water reservoir resource usage. A quantitative assessment of Evenkiiskaya HPP usage is presented using daily load demand. Increasing the guaranteed HPP power is proposed as an alternative to new nuclear power stations.

Reliability evaluation of microgrid considering incentive-based demand response

NASA Astrophysics Data System (ADS)

Huang, Ting-Cheng; Zhang, Yong-Jun

2017-07-01

Incentive-based demand response (IBDR) can guide customers to adjust their behaviour of electricity and curtail load actively. Meanwhile, distributed generation (DG) and energy storage system (ESS) can provide time for the implementation of IBDR. The paper focus on the reliability evaluation of microgrid considering IBDR. Firstly, the mechanism of IBDR and its impact on power supply reliability are analysed. Secondly, the IBDR dispatch model considering customer’s comprehensive assessment and the customer response model are developed. Thirdly, the reliability evaluation method considering IBDR based on Monte Carlo simulation is proposed. Finally, the validity of the above models and method is studied through numerical tests on modified RBTS Bus6 test system. Simulation results demonstrated that IBDR can improve the reliability of microgrid.

A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Long, Matthew; Simpkins, Travis; Cutler, Dylan

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape ofmore » the load profile is the most significant predictor of the size of the battery.« less

A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Long, Matthew; Simpkins, Travis; Cutler, Dylan

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape ofmore » the load profile is the most significant predictor of the size of the battery.« less

NREL Integrate: RCS-4-42326

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hudgins, Andrew P.; Waight, Jim; Grover, Shailendra

OMNETRIC Corp., Duke Energy, CPS Energy, and the University of Texas at San Antonio (UTSA) created a project team to execute the project 'OpenFMB Reference Architecture Demonstration.' The project included development and demonstration of concepts that will enable the electric utility grid to host larger penetrations of renewable resources. The project concept calls for the aggregation of renewable resources and loads into microgrids and the control of these microgrids with an implementation of the OpenFMB Reference Architecture. The production of power from the renewable resources that are appearing on the grid today is very closely linked to the weather. Themore » difficulty of forecasting the weather, which is well understood, leads to difficulty in forecasting the production of renewable resources. The current state of the art in forecasting the power production from renewables (solar PV and wind) are accuracies in the range of 12-25 percent NMAE. In contrast the demand for electricity aggregated to the system level, is easier to predict. The state of the art of demand forecasting done, 24 hours ahead, is about 2-3% MAPE. Forecasting the load to be supplied from conventional resources (demand minus generation from renewable resources) is thus very hard to forecast. This means that even a few hours before the time of consumption, there can be considerable uncertainty over what must be done to balance supply and demand. Adding to the problem of difficulty of forecasting, is the reality of the variability of the actual production of power from renewables. Due to the variability of wind speeds and solar insolation, the actual output of power from renewable resources can vary significantly over a short period of time. Gusts of winds result is variation of power output of wind turbines. The shadows of clouds moving over solar PV arrays result in the variation of power production of the array. This compounds the problem of balancing supply and demand in real time. Establishing a control system that can manage distribution systems with large penetrations of renewable resources is difficult due to two major issues: (1) the lack of standardization and interoperability between the vast array of equipment in operation and on the market, most of which use different and proprietary means of communication and (2) the magnitude of the network and the information it generates and consumes. The objective of this project is to provide the industry with a design concept and tools that will enable the electric power grid to overcome these barriers and support a larger penetration of clean energy from renewable resources.« less

Justification of the Utility of Introducing Smart Meters in Latvia

NASA Astrophysics Data System (ADS)

Kunickis, M.; Dandens, A.; Bariss, U.

2015-12-01

Automatic data reading from smart meters is being developed in many parts of the world, including Latvia. The key drivers for that are developments of smart technologies and economic benefits for consumers. Deployment of smart meters could be launched in a massive scale. Several pilot projects were implemented to verify the feasibility of smart meters for individual consumer groups. Preliminary calculations indicate that installation of smart meters for approximately 23 % of electricity consumers would be economically viable. Currently, the data for the last two years is available for an in-depth mathematical analysis. The continuous analysis of consumption data would be established, when more measurements from smart meters are available. The extent of introduction of smart meters should be specified during this process in order to gain the maximum benefit for the whole society (consumers, grid companies, state authorities), because there are still many uncertain and variable factors. For example, it is necessary to consider statistical load variations by hour, dependence of electricity consumption on temperature fluctuations, consumer behaviour and demand response to market signals to reduce electricity consumption in the short and long term, consumer's ambitions and capability to install home automation for regulation of electricity consumption. To develop the demand response, it is necessary to analyse the whole array of additional factors, such as expected cost reduction of smart meters, possible extension of their functionality, further development of information exchange systems, as well as standard requirements and different political and regulatory decisions regarding the reduction of electricity consumption and energy efficiency.

Laser power beaming: an emerging technology for power transmission and propulsion in space

NASA Astrophysics Data System (ADS)

Bennett, Harold E.

1997-05-01

A ground based laser beam transmitted to space can be used as an electric utility for satellites. It can significantly increase the electric power available to operate a satellite or to transport it from low earth orbit (LEO) to mid earth or geosynchronous orbits. The increase in electrical power compared to that obtainable from the sun is as much as 1000% for the same size solar panels. An increase in satellite electric power is needed to meet the increasing demands for power caused by the advent of 'direct to home TV,' for increased telecommunications, or for other demands made by the burgeoning 'space highway.' Monetary savings as compared to putting up multiple satellites in the same 'slot' can be over half a billion dollars. To obtain propulsion, the laser power can be beamed through the atmosphere to an 'orbit transfer vehicle' (OTV) satellite which travels back and forth between LEO and higher earth orbits. The OTV will transport the satellite into orbit as does a rocket but does not require the heavy fuel load needed if rocket propulsion is used. Monetary savings of 300% or more in launch costs are predicted. Key elements in the proposed concept are a 100 to 200 kW free- electron laser operating at 0.84 m in the photographic infrared region of the spectrum and a novel adaptive optic telescope.

Power control and management of the grid containing largescale wind power systems

NASA Astrophysics Data System (ADS)

Aula, Fadhil Toufick

The ever increasing demand for electricity has driven many countries toward the installation of new generation facilities. However, concerns such as environmental pollution and global warming issues, clean energy sources, high costs associated with installation of new conventional power plants, and fossil fuels depletion have created many interests in finding alternatives to conventional fossil fuels for generating electricity. Wind energy is one of the most rapidly growing renewable power sources and wind power generations have been increasingly demanded as an alternative to the conventional fossil fuels. However, wind power fluctuates due to variation of wind speed. Therefore, large-scale integration of wind energy conversion systems is a threat to the stability and reliability of utility grids containing these systems. They disturb the balance between power generation and consumption, affect the quality of the electricity, and complicate load sharing and load distribution managing and planning. Overall, wind power systems do not help in providing any services such as operating and regulating reserves to the power grid. In order to resolve these issues, research has been conducted in utilizing weather forecasting data to improve the performance of the wind power system, reduce the influence of the fluctuations, and plan power management of the grid containing large-scale wind power systems which consist of doubly-fed induction generator based energy conversion system. The aims of this research, my dissertation, are to provide new methods for: smoothing the output power of the wind power systems and reducing the influence of their fluctuations, power managing and planning of a grid containing these systems and other conventional power plants, and providing a new structure of implementing of latest microprocessor technology for controlling and managing the operation of the wind power system. In this research, in order to reduce and smooth the fluctuations, two methods are presented. The first method is based on a de-loaded technique while the other method is based on utilizing multiple storage facilities. The de-loaded technique is based on characteristics of the power of a wind turbine and estimation of the generated power according to weather forecasting data. The technique provides a reference power by which the wind power system will operate and generate a smooth power. In contrast, utilizing storage facilities will allow the wind power system to operate at its maximum tracking power points' strategy. Two types of energy storages are considered in this research, battery energy storage system (BESS) and pumped-hydropower storage system (PHSS), to suppress the output fluctuations and to support the wind power system to follow the system load demands. Furthermore, this method provides the ability to store energy when there is a surplus of the generated power and to reuse it when there is a shortage of power generation from wind power systems. Both methods are new in terms of utilizing of the techniques and wind speed data. A microprocessor embedded system using an IntelRTM Atom(TM) processor is presented for controlling the wind power system and for providing the remote communication for enhancing the operation of the individual wind power system in a wind farm. The embedded system helps the wind power system to respond and to follow the commands of the central control of the power system. Moreover, it enhances the performance of the wind power system through self-managing, self-functioning, and self-correcting. Finally, a method of system power management and planning is modeled and studied for a grid containing large-scale wind power systems. The method is based on a new technique through constructing a new load demand curve (NLDC) from merging the estimation of generated power from wind power systems and forecasting of the load. To summarize, the methods and their results presented in this dissertation, enhance the operation of the large-scale wind power systems and reduce their drawbacks on the operation of the power grid.

An analysis of the factors influencing demand-side management activity in the electric utility industry

NASA Astrophysics Data System (ADS)

Bock, Mark Joseph

Demand-side management (DSM), defined as the "planning, implementation, and monitoring of utility activities designed to encourage consumers to modify their pattern of electricity usage, including the timing and level of electricity demand," is a relatively new concept in the U.S. electric power industry. Nevertheless, in twenty years since it was first introduced, utility expenditures on DSM programs, as well as the number of such programs, have grown rapidly. At first glance, it may seem peculiar that a firm would actively attempt to reduce demand for its primary product. There are two primary explanations as to why a utility might pursue DSM: regulatory mandate, and self-interest. The purpose of this dissertation is to determine the impact these influences have on the amount of DSM undertaken by utilities. This research is important for two reasons. First, it provides insight into whether DSM will continue to exist as competition becomes more prevalent in the industry. Secondly, it is important because no one has taken a comprehensive look at firm-level DSM activity on an industry-wide basis. The primary data set used in this dissertation is the U.S. Department of Energy's Annual Electric Utility Report, Form EIA-861, which represents the most comprehensive data set available for analyzing DSM activity in the U.S. There are four measures of DSM activity in this data set: (1) utility expenditures on DSM programs; (2) energy savings by DSM program participants; and (3) the actual and (4) the potential reductions in peak load resulting from utility DSM measures. Each is used as the dependent variable in an econometric analysis where independent variables include various utility characteristics, regulatory characteristics, and service territory and customer characteristics. In general, the results from the econometric analysis suggest that in 1993, DSM activity was primarily the result of regulatory pressure. All of the evidence suggests that if DSM continues to exist in a deregulated environment, it will be at a greatly reduced level. This conclusion holds unless utilities see advantages to DSM as a marketing tool to increase customer satisfaction and loyalty.

Prediction on the charging demand for electric vehicles in Chengdu

NASA Astrophysics Data System (ADS)

yun, Cai; wanquan, Zhang; wei, You; pan, Mao

2018-03-01

The development of the electric vehicle charging station facilities speed directly affect the development of electric vehicle speed. And the charging demand of electric vehicles is one of the main factors influencing the electric vehicle charging facilities. The paper collected and collated car ownership in recent years, the use of elastic coefficient to predict Chengdu electric vehicle ownership, further modeling to give electric vehicle charging demand.

U.S. Electric System Operating Data

EIA Publications

EIA provides hourly electricity operating data, including actual and forecast demand, net generation, and the power flowing between electric systems. EIA's new U.S. Electric System Operating Data tool provides nearly real-time demand data, plus analysis and visualizations of hourly, daily, and weekly electricity supply and demand on a national and regional level for all of the 66 electric system balancing authorities that make up the U.S. electric grid.

Solar plus: Optimization of distributed solar PV through battery storage and dispatchable load in residential buildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Shaughnessy, Eric; Cutler, Dylan; Ardani, Kristen

As utility electricity rates evolve, pairing solar photovoltaic (PV) systems with battery storage has potential to ensure the value proposition of residential solar by mitigating economic uncertainty. In addition to batteries, load control technologies can reshape customer load profiles to optimize PV system use. The combination of PV, energy storage, and load control provides an integrated approach to PV deployment, which we call 'solar plus'. The U.S. National Renewable Energy Laboratory's Renewable Energy Optimization (REopt) model is utilized to evaluate cost-optimal technology selection, sizing, and dispatch in residential buildings under a variety of rate structures and locations. The REopt modelmore » is extended to include a controllable or 'smart' domestic hot water heater model and smart air conditioner model. We find that the solar plus approach improves end user economics across a variety of rate structures - especially those that are challenging for PV - including lower grid export rates, non-coincident time-of-use structures, and demand charges.« less

Solar plus: Optimization of distributed solar PV through battery storage and dispatchable load in residential buildings

DOE PAGES

O'Shaughnessy, Eric; Cutler, Dylan; Ardani, Kristen; ...

2018-01-11

As utility electricity rates evolve, pairing solar photovoltaic (PV) systems with battery storage has potential to ensure the value proposition of residential solar by mitigating economic uncertainty. In addition to batteries, load control technologies can reshape customer load profiles to optimize PV system use. The combination of PV, energy storage, and load control provides an integrated approach to PV deployment, which we call 'solar plus'. The U.S. National Renewable Energy Laboratory's Renewable Energy Optimization (REopt) model is utilized to evaluate cost-optimal technology selection, sizing, and dispatch in residential buildings under a variety of rate structures and locations. The REopt modelmore » is extended to include a controllable or 'smart' domestic hot water heater model and smart air conditioner model. We find that the solar plus approach improves end user economics across a variety of rate structures - especially those that are challenging for PV - including lower grid export rates, non-coincident time-of-use structures, and demand charges.« less

Targeted and controlled anticancer drug delivery and release with magnetoelectric nanoparticles

NASA Astrophysics Data System (ADS)

Rodzinski, Alexandra; Guduru, Rakesh; Liang, Ping; Hadjikhani, Ali; Stewart, Tiffanie; Stimphil, Emmanuel; Runowicz, Carolyn; Cote, Richard; Altman, Norman; Datar, Ram; Khizroev, Sakhrat

2016-02-01

It is a challenge to eradicate tumor cells while sparing normal cells. We used magnetoelectric nanoparticles (MENs) to control drug delivery and release. The physics is due to electric-field interactions (i) between MENs and a drug and (ii) between drug-loaded MENs and cells. MENs distinguish cancer cells from normal cells through the membrane’s electric properties; cancer cells have a significantly smaller threshold field to induce electroporation. In vitro and in vivo studies (nude mice with SKOV-3 xenografts) showed that (i) drug (paclitaxel (PTX)) could be attached to MENs (30-nm CoFe2O4@BaTiO3 nanostructures) through surface functionalization to avoid its premature release, (ii) drug-loaded MENs could be delivered into cancer cells via application of a d.c. field (~100 Oe), and (iii) the drug could be released off MENs on demand via application of an a.c. field (~50 Oe, 100 Hz). The cell lysate content was measured with scanning probe microscopy and spectrophotometry. MENs and control ferromagnetic and polymer nanoparticles conjugated with HER2-neu antibodies, all loaded with PTX were weekly administrated intravenously. Only the mice treated with PTX-loaded MENs (15/200 μg) in a field for three months were completely cured, as confirmed through infrared imaging and post-euthanasia histology studies via energy-dispersive spectroscopy and immunohistochemistry.

Photovoltaic stand-alone modular systems, phase 2

NASA Technical Reports Server (NTRS)

Naff, G. J.; Marshall, N. A.

1983-01-01

The final hardware and system qualification phase of a two part stand-alone photovoltaic (PV) system development is covered. The final design incorporated modular, power blocks capable of expanding incrementally from 320 watts to twenty kilowatts (PK). The basic power unit (PU) was nominally rated 1.28 kWp. The controls units, power collection buses and main lugs, electrical protection subsystems, power switching, and load management circuits are housed in a common control enclosure. Photo-voltaic modules are electrically connected in a horizontal daisy-chain method via Amp Solarlok plugs mating with compatible connectors installed on the back side of each photovoltaic module. A pair of channel rails accommodate the mounting of the modules into a frameless panel support structure. Foundations are of a unique planter (tub-like) configuration to allow for world-wide deployment without restriction as to types of soil. One battery string capable of supplying approximately 240 ampere hours nominal of carryover power is specified for each basic power unit. Load prioritization and shedding circuits are included to protect critical loads and selectively shed and defer lower priority or noncritical power demands. The baseline system, operating at approximately 2 1/2 PUs (3.2 kW pk.) was installed and deployed. Qualification was successfully complete in March 1983; since that time, the demonstration system has logged approximately 3000 hours of continuous operation under load without major incident.

Photovoltaic stand-alone modular systems, phase 2

NASA Astrophysics Data System (ADS)

Naff, G. J.; Marshall, N. A.

1983-07-01

The final hardware and system qualification phase of a two part stand-alone photovoltaic (PV) system development is covered. The final design incorporated modular, power blocks capable of expanding incrementally from 320 watts to twenty kilowatts (PK). The basic power unit (PU) was nominally rated 1.28 kWp. The controls units, power collection buses and main lugs, electrical protection subsystems, power switching, and load management circuits are housed in a common control enclosure. Photo-voltaic modules are electrically connected in a horizontal daisy-chain method via Amp Solarlok plugs mating with compatible connectors installed on the back side of each photovoltaic module. A pair of channel rails accommodate the mounting of the modules into a frameless panel support structure. Foundations are of a unique planter (tub-like) configuration to allow for world-wide deployment without restriction as to types of soil. One battery string capable of supplying approximately 240 ampere hours nominal of carryover power is specified for each basic power unit. Load prioritization and shedding circuits are included to protect critical loads and selectively shed and defer lower priority or noncritical power demands. The baseline system, operating at approximately 2 1/2 PUs (3.2 kW pk.) was installed and deployed. Qualification was successfully complete in March 1983; since that time, the demonstration system has logged approximately 3000 hours of continuous operation under load without major incident.

Deep carbon reductions in California require electrification and integration across economic sectors

NASA Astrophysics Data System (ADS)

Wei, Max; Nelson, James H.; Greenblatt, Jeffery B.; Mileva, Ana; Johnston, Josiah; Ting, Michael; Yang, Christopher; Jones, Chris; McMahon, James E.; Kammen, Daniel M.

2013-03-01

Meeting a greenhouse gas (GHG) reduction target of 80% below 1990 levels in the year 2050 requires detailed long-term planning due to complexity, inertia, and path dependency in the energy system. A detailed investigation of supply and demand alternatives is conducted to assess requirements for future California energy systems that can meet the 2050 GHG target. Two components are developed here that build novel analytic capacity and extend previous studies: (1) detailed bottom-up projections of energy demand across the building, industry and transportation sectors; and (2) a high-resolution variable renewable resource capacity planning model (SWITCH) that minimizes the cost of electricity while meeting GHG policy goals in the 2050 timeframe. Multiple pathways exist to a low-GHG future, all involving increased efficiency, electrification, and a dramatic shift from fossil fuels to low-GHG energy. The electricity system is found to have a diverse, cost-effective set of options that meet aggressive GHG reduction targets. This conclusion holds even with increased demand from transportation and heating, but the optimal levels of wind and solar deployment depend on the temporal characteristics of the resulting load profile. Long-term policy support is found to be a key missing element for the successful attainment of the 2050 GHG target in California.

HOMER Economic Models - US Navy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bush, Jason William; Myers, Kurt Steven

This LETTER REPORT has been prepared by Idaho National Laboratory for US Navy NAVFAC EXWC to support in testing pre-commercial SIREN (Simulated Integration of Renewable Energy Networks) computer software models. In the logistics mode SIREN software simulates the combination of renewable power sources (solar arrays, wind turbines, and energy storage systems) in supplying an electrical demand. NAVFAC EXWC will create SIREN software logistics models of existing or planned renewable energy projects at five Navy locations (San Nicolas Island, AUTEC, New London, & China Lake), and INL will deliver additional HOMER computer models for comparative analysis. In the transient mode SIRENmore » simulates the short time-scale variation of electrical parameters when a power outage or other destabilizing event occurs. In the HOMER model, a variety of inputs are entered such as location coordinates, Generators, PV arrays, Wind Turbines, Batteries, Converters, Grid costs/usage, Solar resources, Wind resources, Temperatures, Fuels, and Electric Loads. HOMER's optimization and sensitivity analysis algorithms then evaluate the economic and technical feasibility of these technology options and account for variations in technology costs, electric load, and energy resource availability. The Navy can then use HOMER’s optimization and sensitivity results to compare to those of the SIREN model. The U.S. Department of Energy (DOE) Idaho National Laboratory (INL) possesses unique expertise and experience in the software, hardware, and systems design for the integration of renewable energy into the electrical grid. NAVFAC EXWC will draw upon this expertise to complete mission requirements.« less

Plug and Process Loads Capacity and Power Requirements Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheppy, M.; Gentile-Polese, L.

2014-09-01

This report addresses gaps in actionable knowledge that would help reduce the plug load capacities designed into buildings. Prospective building occupants and real estate brokers lack accurate references for plug and process load (PPL) capacity requirements, so they often request 5-10 W/ft2 in their lease agreements. Limited initial data, however, suggest that actual PPL densities in leased buildings are substantially lower. Overestimating PPL capacity leads designers to oversize electrical infrastructure and cooling systems. Better guidance will enable improved sizing and design of these systems, decrease upfront capital costs, and allow systems to operate more energy efficiently. The main focus ofmore » this report is to provide industry with reliable, objective third-party guidance to address the information gap in typical PPL densities for commercial building tenants. This could drive changes in negotiations about PPL energy demands.« less

Dielectric properties of inorganic fillers filled epoxy thin film

DOE Office of Scientific and Technical Information (OSTI.GOV)

Norshamira, A., E-mail: myra.arshad@gmail.com; Mariatti, M., E-mail: mariatti@usm.my

2015-07-22

The demand on the small size and high performance electronics has driven changes in the electronic packaging requirements from discrete capacitor to embedded capacitor. Embedded capacitor can improve electrical performance compared with discrete capacitor. This study aimed to achieve high dielectric of epoxy thin film composite that were targeted for application as embedded capacitor. In this study, inorganic fillers such as Calcium Copper Titanate (CCTO), Iron(III) Oxide (Fe{sub 2}O{sub 3}) and Titanium Dioxide (TiO{sub 2}) were loaded in epoxy system at 5 and 20vol%. Morphology and dielectric properties were investigated to identify the effect of fillers loading and types ofmore » fillers on the properties of epoxy thin film composite. Based on the study, CCTO with 20vol% loading was found to have good dielectric properties compared to other type of fillers.« less

Projected electric power demands for the Potomac Electric Power Company

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilson, J.W.

1975-07-01

Included are chapters on the background of the Potomac Electric Power Company, forecasting future power demand, demand modeling, accuracy of market predictions, and total power system requirements. (DG)

Essays on measurement and evaluation of demand side management programs in the electricity industry, and impacts of firm strategy on stock price in the biotechnology industry

NASA Astrophysics Data System (ADS)

Bandres Motola, Miguel A.

Essay one estimates changes in small business customer energy consumption (kWh) patterns resulting from a seasonally differentiated pricing structure. Econometric analysis leverages cross-sectional time series data across the entire population of affected customers, from 2007 through the present. Observations include: monthly energy usage (kWh), relevant customer segmentations, local daily temperature, energy price, and region-specific economic conditions, among other variables. The study identifies the determinants of responsiveness to seasonal price differentiation. In addition, estimated energy consumption changes occurring during the 2010 summer season are reported for the average customer and in aggregate grouped by relevant customer segments, climate zone, and total customer base. Essay two develops an econometric modeling methodology to evaluate load impacts for short duration demand response events. The study analyzes time series data from a season of direct load control program tests aimed at integrating demand response into the wholesale electricity market. I have combined "fuzzy logic" with binary variables to create "fuzzy indicator variables" that allow for measurement of short duration events while using industry standard model specifications. Typically, binary variables for every hour are applied in load impact analysis of programs dispatched in hourly intervals. As programs evolve towards integration with the wholesale market, event durations become irregular and often occur for periods of only a few minutes. This methodology is innovative in that it conserves the degrees of freedom in the model while allowing for analysis of high frequency data using fixed effects. Essay three examines the effects of strategies, intangibles, and FDA news on the stocks of young biopharmaceutical firms. An event study methodology is used to explore those effects. This study investigates 20,839 announcements from 1990 to 2005. Announcements on drug development, alliances, publications, presentations, and FDA approval have a positive effect on the short-term performance of young biopharmaceutical firms. Announcements on goals not met, FDA drug approval denied, and changes in structural organizations have a negative effect on the short-term performance of young biopharmaceutical firms.

Design and Implementation of a Thermal Load Reduction System for a Hyundai Sonata PHEV for Improved Range

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rugh, John P; Kreutzer, Cory J; Scott, Matthew

Increased adoption of electric-drive vehicles requires overcoming hurdles including limited vehicle range. Vehicle cabin heating and cooling demand for occupant climate control requires energy from the main battery and has been shown to significantly degrade vehicle range. During peak cooling and heating conditions, climate control can require as much as or more energy than propulsion. As part of an ongoing project, the National Renewable Energy Laboratory and project partners Hyundai America Technical Center, Inc., Gentherm, Pittsburgh Glass Works, PPG Industries, Sekisui, 3 M, and Hanon Systems developed a thermal load reduction system to reduce the range penalty associated with electricmore » vehicle climate control. Solar reflective paint, solar control glass, heated and cooled/ventilated seats, heated surfaces, and a heated windshield with door demisters were integrated into a Hyundai Sonata plug-in hybrid electric vehicle. Cold weather field-testing was conducted in Fairbanks, Alaska, and warm weather testing was conducted in Death Valley, California, to assess the system performance in comparison to the baseline production vehicle. In addition, environmental chamber testing at peak heating and cooling conditions was performed to assess the performance of the system in standardized conditions compared to the baseline. Experimental results are presented in this paper, providing quantitative data to automobile manufacturers on the impact of climate control thermal load reduction technologies to increase the advanced thermal technology adoption and market penetration of electric drive vehicles.« less

Performance Evaluation of a Thermal Load Reduction System in a Hyundai Sonata PHEV

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kreutzer, Cory J; Rugh, John P; Titov, Eugene V

Increased adoption of electric-drive vehicles (EDVs) requires overcoming hurdles including limited vehicle range. Vehicle cabin heating and cooling demand for occupant climate control requires energy from the main battery and has been shown to significantly degrade vehicle range. During peak cooling and heating conditions, climate control can require as much or more energy as propulsion. As part of an ongoing project, NREL and project partners Hyundai America Technical Center, Inc. (HATCI), Gentherm , Pittsburgh Glass Works (PGW), PPG Industries, Sekisui, 3M, and Hanon Systems developed a thermal load reduction system in order to reduce the range penalty associated with electricmore » vehicle climate control. Solar reflective paint, solar control glass, heated and cooled/ventilated seats, heated surfaces, and heated windshield with door demisters were integrated into a Hyundai Sonata plug-in hybrid electric vehicle (PHEV). Cold weather field-testing was conducted in Fairbanks, Alaska while warm weather testing was conducted in Death Valley, California to assess the system performance in comparison to the baseline production vehicle. In addition, environmental chamber testing at peak heating and cooling conditions was performed to assess the performance of the system in standardized conditions compared to the baseline. Experimental results are presented in this paper providing quantitative data to automobile manufacturers on the impact of climate control thermal load reduction technologies to increase the advanced thermal technology adoption and market penetration of electric drive vehicles.« less

2003 Pacific Northwest Loads and Resources Study.

DOE Office of Scientific and Technical Information (OSTI.GOV)

United States. Bonneville Power Administration.

2003-12-01

The Pacific Northwest Loads and Resources Study (White Book), which is published annually by the Bonneville Power Administration (BPA), establishes one of the planning bases for supplying electricity to customers. The White Book contains projections of regional and Federal system load and resource capabilities, along with relevant definitions and explanations. The White Book also contains information obtained from formalized resource planning reports and data submittals including those from individual utilities, the Northwest Power and Conservation Council (Council), and the Pacific Northwest Utilities Conference Committee (PNUCC). The White Book is not an operational planning guide, nor is it used for determiningmore » BPA revenues, although the database that generates the data for the White Book analysis contributes to the development of BPA's inventory and ratemaking processes. Operation of the Federal Columbia River Power System (FCRPS) is based on a set of criteria different from that used for resource planning decisions. Operational planning is dependent upon real-time or near-term knowledge of system conditions that include expectations of river flows and runoff, market opportunities, availability of reservoir storage, energy exchanges, and other factors affecting the dynamics of operating a power system. In this loads and resources study, resource availability is compared to an expected level of total retail electricity consumption. The forecasted annual energy electricity retail load plus contract obligations are subtracted from the sum of the projected annual energy capability of existing resources and contract purchases to determine whether BPA and/or the region will be surplus or deficit. Surplus energy is available when resources are greater than loads. This energy could be marketed to increase revenues. Deficits occur when resources are less than loads. Energy deficits could be met by any combination of the following: better-than-critical water conditions, demand-side management and conservation programs, permanent loss of a load (i.e., due to economic conditions or closures), additional contract purchases, and/or new generating resources. The loads and resources analysis in this study simulates the operation of the power system under the Pacific Northwest Coordination Agreement (PNCA). The PNCA defines the planning and operation of seventeen U.S. Pacific Northwest utilities and other parties with generating facilities within the region's hydroelectric (hydro) system. The hydroregulation study used for the 2003 White Book incorporates measures from the National Oceanographic and Atmospheric Administration Fisheries (NOAA Fisheries) Biological Opinion dated December 2000, and the U.S. Fish and Wildlife Service's 2000 Biological Opinion (2000 FCRPS BiOps) for the Snake River and Columbia River projects. These measures include: (1) Increased flow augmentation for juvenile fish migrations in the Snake and Columbia rivers in the spring and summer; (2) Mandatory spill requirements at the Lower Snake and Columbia dams to provide for non-turbine passage routes for juvenile fish migrants; and (3) Additional flows for Kootenai River white sturgeon in the spring. The hydroregulation criteria for this analysis includes: an updated Detailed Operation Plan for Treaty reservoirs for Operating Year (OY) 2004, updated PNCA planning criteria for OY 2003, and revised juvenile fish bypass spill levels for 2000 FCRPS BiOps implementation. The 2003 White Book is presented in two documents: (1) this summary document of Federal system and PNW region loads and resources, and (2) a technical appendix which presents regional loads, grouped by major PNW utility categories, and detailed contract and resource information. The technical appendix is available only in electronic form. Individual customer information regarding marketer contracts is not detailed due to confidentiality agreements. The 2003 White Book analysis updates the December 2002 White Book. This analysis projects the yearly average energy consumption and resource availability for the study period, OY 2005 through 2014. The study shows the Federal system's and the region's expected monthly peak demand, monthly energy demand, monthly peak generating capability, and monthly energy generation for OY 2005, 2009, and 2014. The Federal system and regional monthly capacity surplus/deficit projections are summarized for the 10 operating years of the study period. This document analyzes the PNW's projected loads and available generating resources in two parts: (1) the loads and resources of the Federal system, for which BPA is the marketing agency; and (2) the larger PNW regional power system loads and resources that include the Federal system as well other PNW entities.« less

Optimal scheduling of micro grids based on single objective programming

NASA Astrophysics Data System (ADS)

Chen, Yue

2018-04-01

Faced with the growing demand for electricity and the shortage of fossil fuels, how to optimally optimize the micro-grid has become an important research topic to maximize the economic, technological and environmental benefits of the micro-grid. This paper considers the role of the battery and the micro-grid and power grid to allow the exchange of power not exceeding 150kW preconditions, the main study of the economy to load for the goal is to minimize the electricity cost (abandonment of wind), to establish an optimization model, and to solve the problem by genetic algorithm. The optimal scheduling scheme is obtained and the utilization of renewable energy and the impact of the battery involved in regulation are analyzed.

Study on the Effect of a Cogeneration System Capacity on its CO2 Emissions

NASA Astrophysics Data System (ADS)

Fonseca, J. G. S., Jr.; Asano, Hitoshi; Fujii, Terushige; Hirasawa, Shigeki

With the global warming problem aggravating and subsequent implementation of the Kyoto Protocol, CO2 emissions are becoming an important factor when verifying the usability of cogeneration systems. Considering this, the purpose of this work is to study the effect of the capacity of a cogeneration system on its CO2 emissions under two kinds of operation strategies: one focused on exergetic efficiency and another on running cost. The system meets the demand pattern typical of a hospital in Japan, operating during one year with an average heat-to-power ratio of 1.3. The main equipments of the cogeneration system are: a gas turbine with waste heat boiler, a main boiler and an auxiliary steam turbine. Each of these equipments was characterized with partial load models, and the turbine efficiencies at full load changed according to the system capacity. Still, it was assumed that eventual surplus of electricity generated could be sold. The main results showed that for any of the capacities simulated, an exergetic efficiency-focused operational strategy always resulted in higher CO2 emissions reduction when compared to the running cost-focused strategy. Furthermore, the amount of reduction in emissions decreased when the system capacity decreased, reaching a value of 1.6% when the system capacity was 33% of the maximum electricity demand with a heat-to-power ratio of 4.1. When the system operated focused on running cost, the economic savings increased with the capacity and reached 42% for a system capacity of 80% of maximum electricity demand and with a heat-to-power ratio of 2.3. In such conditions however, there was an increase in emissions of 8.5%. Still for the same capacity, an exergetic efficiency operation strategy presented the best balance between cost and emissions, generating economic savings of 29% with a decrease in CO2 emissions of 7.1%. The results found showed the importance of an exergy-focused operational strategy and also indicated that lower capacities resulted in lesser gains of both CO2 emissions and running cost reduction.

Policy impacts on agricultural irrigation electricity demand in the Columbia Basin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martin, M.; Cox, L.; Nakamoto, S.

Accurately estimating the price elasticity of demand for irrigation electricity is important to major electricity suppliers such as the Bonneville Power Administration (BPA) of the Pacific Northwest. The BPA has a revenue maximization objective, and the elasticity of demand is central to its rate setting process. Several studies have attempted to estimate demand for irrigation electricity, but none has explicitly included federal agricultural policy and program variables. Tins paper discusses how agricultural programs may influence farmers' irrigation decisions and thus their demand for irrigation electricity. It suggests that existing programs serve to make farmers more responsive to electricity rate increasesmore » than would otherwise be the case. Thus, studies that fail to include them may underestimate the responsiveness of farmers to electricity rate increases.« less

Impacts of climate change on sub-regional electricity demand and distribution in the southern United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allen, Melissa R.; Fernandez, Steven J.; Fu, Joshua S.

New tools are employed to develop an electricity demand map for the southeastern United States at neighborhood resolution to serve as a baseline from which to project increases in electricity demand due to a rise in global and local temperature and to population shifts motivated by increases in extreme weather events due to climate change. We find that electricity demand increases due to temperature rise over the next 40 years have a much smaller impact than those due to large population influx. In addition, we find evidence that some, sections of the national electrical grid are more adaptable to thesemore » population shifts and changing demand than others are; and that detailed projections of changing local electricity demand patterns are viable and important for planning at the urban level.« less

Impacts of climate change on sub-regional electricity demand and distribution in the southern United States

DOE PAGES

Allen, Melissa R.; Fernandez, Steven J.; Fu, Joshua S.; ...

2016-07-25

New tools are employed to develop an electricity demand map for the southeastern United States at neighborhood resolution to serve as a baseline from which to project increases in electricity demand due to a rise in global and local temperature and to population shifts motivated by increases in extreme weather events due to climate change. We find that electricity demand increases due to temperature rise over the next 40 years have a much smaller impact than those due to large population influx. In addition, we find evidence that some, sections of the national electrical grid are more adaptable to thesemore » population shifts and changing demand than others are; and that detailed projections of changing local electricity demand patterns are viable and important for planning at the urban level.« less

The role of temperature in the variability and extremes of electricity and gas demand in Great Britain

NASA Astrophysics Data System (ADS)

Thornton, H. E.; Hoskins, B. J.; Scaife, A. A.

2016-11-01

The daily relationship of electricity and gas demand with temperature in Great Britain is analysed from 1975 to 2013 and 1996 to 2013 respectively. The annual mean and annual cycle amplitude of electricity demand exhibit low frequency variability. This low frequency variability is thought to be predominantly driven by socio-economic changes rather than temperature variation. Once this variability is removed, both daily electricity and gas demand have a strong anti-correlation with temperature (r elec = -0.90 , r gas = -0.94). However these correlations are inflated by the changing demand-temperature relationship during spring and autumn. Once the annual cycles of temperature and demand are removed, the correlations are {r}{{elec}}=-0.60 and {r}{{gas}}=-0.83. Winter then has the strongest demand-temperature relationship, during which a 1 °C reduction in daily temperature typically gives a ˜1% increase in daily electricity demand and a 3%-4% increase in gas demand. Extreme demand periods are assessed using detrended daily temperature observations from 1772. The 1 in 20 year peak day electricity and gas demand estimates are, respectively, 15% (range 14%-16%) and 46% (range 44%-49%) above their average winter day demand during the last decade. The risk of demand exceeding recent extreme events, such as during the winter of 2009/2010, is also quantified.

Customer response to day-ahead wholesale market electricity prices: Case study of RTP program experience in New York

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldman, C.; Hopper, N.; Sezgen, O.

2004-07-01

There is growing interest in policies, programs and tariffs that encourage customer loads to provide demand response (DR) to help discipline wholesale electricity markets. Proposals at the retail level range from eliminating fixed rate tariffs as the default service for some or all customer groups to reinstituting utility-sponsored load management programs with market-based inducements to curtail. Alternative rate designs include time-of-use (TOU), day-ahead real-time pricing (RTP), critical peak pricing, and even pricing usage at real-time market balancing prices. Some Independent System Operators (ISOs) have implemented their own DR programs whereby load curtailment capabilities are treated as a system resource andmore » are paid an equivalent value. The resulting load reductions from these tariffs and programs provide a variety of benefits, including limiting the ability of suppliers to increase spot and long-term market-clearing prices above competitive levels (Neenan et al., 2002; Boren stein, 2002; Ruff, 2002). Unfortunately, there is little information in the public domain to characterize and quantify how customers actually respond to these alternative dynamic pricing schemes. A few empirical studies of large customer RTP response have shown modest results for most customers, with a few very price-responsive customers providing most of the aggregate response (Herriges et al., 1993; Schwarz et al., 2002). However, these studies examined response to voluntary, two-part RTP programs implemented by utilities in states without retail competition.1 Furthermore, the researchers had limited information on customer characteristics so they were unable to identify the drivers to price response. In the absence of a compelling characterization of why customers join RTP programs and how they respond to prices, many initiatives to modernize retail electricity rates seem to be stymied.« less

A flipped mode teaching approach for large and advanced electrical engineering courses

NASA Astrophysics Data System (ADS)

Ravishankar, Jayashri; Epps, Julien; Ambikairajah, Eliathamby

2018-05-01

A fully flipped mode teaching approach is challenging for students in advanced engineering courses, because of demanding pre-class preparation load, due to the complex and analytical nature of the topics. When this is applied to large classes, it brings an additional complexity in terms of promoting the intended active learning. This paper presents a novel selective flipped mode teaching approach designed for large and advanced courses that has two aspects: (i) it provides selective flipping of a few topics, while delivering others in traditional face-to-face teaching, to provide an effective trade-off between the two approaches according to the demands of individual topics and (ii) it introduces technology-enabled live in-class quizzes to obtain instant feedback and facilitate collaborative problem-solving exercises. The proposed approach was implemented for a large fourth year course in electrical power engineering over three successive years and the criteria for selecting between the flipped mode teaching and traditional teaching modes are outlined. Results confirmed that the proposed approach improved both students' academic achievements and their engagement in the course, without overloading them during the teaching period.

Plug-In Electric Vehicle Fast Charge Station Operational Analysis with Integrated Renewables: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simpson, M.; Markel, T.

2012-08-01

The growing, though still nascent, plug-in electric vehicle (PEV) market currently operates primarily via level 1 and level 2 charging in the United States. Fast chargers are still a rarity, but offer a confidence boost to oppose 'range anxiety' in consumers making the transition from conventional vehicles to PEVs. Because relatively no real-world usage of fast chargers at scale exists yet, the National Renewable Energy Laboratory developed a simulation to help assess fast charging needs based on real-world travel data. This study documents the data, methods, and results of the simulation run for multiple scenarios, varying fleet sizes, and themore » number of charger ports. The grid impact of this usage is further quantified to assess the opportunity for integration of renewables; specifically, a high frequency of fast charging is found to be in demand during the late afternoons and evenings coinciding with grid peak periods. Proper integration of a solar array and stationary battery thus helps ease the load and reduces the need for new generator construction to meet the demand of a future PEV market.« less

Relative Economic Merits of Storage and Combustion Turbines for Meeting Peak Capacity Requirements under Increased Penetration of Solar Photovoltaics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Denholm, Paul; Diakov, Victor; Margolis, Robert

Batteries with several hours of capacity provide an alternative to combustion turbines for meeting peak capacity requirements. Even when compared to state-of-the-art highly flexible combustion turbines, batteries can provide a greater operational value, which is reflected in a lower system-wide production cost. By shifting load and providing operating reserves, batteries can reduce the cost of operating the power system to a traditional electric utility. This added value means that, depending on battery life, batteries can have a higher cost than a combustion turbine of equal capacity and still produce a system with equal or lower overall life-cycle cost. For amore » utility considering investing in new capacity, the cost premium for batteries is highly sensitive to a variety of factors, including lifetime, natural gas costs, PV penetration, and grid generation mix. In addition, as PV penetration increases, the net electricity demand profile changes, which may reduce the amount of battery energy capacity needed to reliably meet peak demand.« less

30 CFR 56.6602 - Static electricity dissipation during loading.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Static electricity dissipation during loading... Explosives Extraneous Electricity § 56.6602 Static electricity dissipation during loading. When explosive material is loaded pneumatically into a blasthole in a manner that generates a static electricity hazard...

30 CFR 56.6602 - Static electricity dissipation during loading.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Static electricity dissipation during loading... Explosives Extraneous Electricity § 56.6602 Static electricity dissipation during loading. When explosive material is loaded pneumatically into a blasthole in a manner that generates a static electricity hazard...

30 CFR 56.6602 - Static electricity dissipation during loading.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Static electricity dissipation during loading... Explosives Extraneous Electricity § 56.6602 Static electricity dissipation during loading. When explosive material is loaded pneumatically into a blasthole in a manner that generates a static electricity hazard...

30 CFR 56.6602 - Static electricity dissipation during loading.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Static electricity dissipation during loading... Explosives Extraneous Electricity § 56.6602 Static electricity dissipation during loading. When explosive material is loaded pneumatically into a blasthole in a manner that generates a static electricity hazard...

30 CFR 56.6602 - Static electricity dissipation during loading.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Static electricity dissipation during loading... Explosives Extraneous Electricity § 56.6602 Static electricity dissipation during loading. When explosive material is loaded pneumatically into a blasthole in a manner that generates a static electricity hazard...

The impact of hybrid energy storage on power quality, when high power pulsed DC loads are operated on a microgrid testbed

NASA Astrophysics Data System (ADS)

Kelley, Jay Paul

As the Navy's demands for high power transient loads evolves, so too does the need for alternative energy sources to back-up the more traditional power generation. Such applications in need of support include electrical grid backup and directed energy weapon systems such as electromagnetic launchers, laser systems, and high power microwave generators, among others. Among the alternative generation sources receiving considerable attention are energy storage devices such as rechargeable electrochemical batteries and capacitors. In such applications as those mentioned above, these energy storage devices offer the ability to serve a dual role as both a power source to the various loads as well high power loads themselves to the continual generation when the high power transient loads are in periods of downtime. With the recent developments in electrochemical energy storage, lithium-ion batteries (LIBs) seem like the obvious choice, but previous research has shown that the elevated rates of charging can be detrimental to both the cycle life and the operational life span of the device. In order to preserve the batteries, their charge rate must be limited. One proposed method to accomplish the dual role task mentioned above, while preserving the life of the batteries, is by combining high energy density LIBs with high power density electric double layer capacitors (EDLCs) or lithium-ion capacitors (LICs) using controllable power electronics to adjust the flow of power to and from each device. Such a configuration is typically referred to as hybrid energy storage module (HESM). While shipboard generators start up, the combined high energy density and high power density of the HESM provides the capability to source critical loads for an extended period of time at the high rates they demand. Once the generator is operationally efficient, the HESM can act as a high energy reservoir to harvest the energy from the generator while the loads are in short periods of inactivity. This enables the generator to maintain its operation at levels of high efficiency thereby increasing the power quality of the AC bus. The work discussed here is aimed at evaluating how the use of energy storage impacts the power quality on MicroGrid's AC bus when high rate DC and AC loads are sourced simultaneously. Also HESM has been developed and evaluated as a mean to optimizing both the power and energy density of the energy storage installed.

The research and application of the power big data

NASA Astrophysics Data System (ADS)

Zhang, Suxiang; Zhang, Dong; Zhang, Yaping; Cao, Jinping; Xu, Huiming

2017-01-01

Facing the increasing environment crisis, how to improve energy efficiency is the important problem. Power big data is main support tool to realize demand side management and response. With the promotion of smart power consumption, distributed clean energy and electric vehicles etc get wide application; meanwhile, the continuous development of the Internet of things technology, more applications access the endings in the grid power link, which leads to that a large number of electric terminal equipment, new energy access smart grid, and it will produce massive heterogeneous and multi-state electricity data. These data produce the power grid enterprise's precious wealth, as the power big data. How to transform it into valuable knowledge and effective operation becomes an important problem, it needs to interoperate in the smart grid. In this paper, we had researched the various applications of power big data and integrate the cloud computing and big data technology, which include electricity consumption online monitoring, the short-term power load forecasting and the analysis of the energy efficiency. Based on Hadoop, HBase and Hive etc., we realize the ETL and OLAP functions; and we also adopt the parallel computing framework to achieve the power load forecasting algorithms and propose a parallel locally weighted linear regression model; we study on energy efficiency rating model to comprehensive evaluate the level of energy consumption of electricity users, which allows users to understand their real-time energy consumption situation, adjust their electricity behavior to reduce energy consumption, it provides decision-making basis for the user. With an intelligent industrial park as example, this paper complete electricity management. Therefore, in the future, power big data will provide decision-making support tools for energy conservation and emissions reduction.

A wavelet-fuzzy logic based energy management strategy for a fuel cell/battery/ultra-capacitor hybrid vehicular power system

NASA Astrophysics Data System (ADS)

Erdinc, O.; Vural, B.; Uzunoglu, M.

Due to increasing concerns on environmental pollution and depleting fossil fuels, fuel cell (FC) vehicle technology has received considerable attention as an alternative to the conventional vehicular systems. However, a FC system combined with an energy storage system (ESS) can display a preferable performance for vehicle propulsion. As the additional ESS can fulfill the transient power demand fluctuations, the fuel cell can be downsized to fit the average power demand without facing peak loads. Besides, braking energy can be recovered by the ESS. This study focuses on a vehicular system powered by a fuel cell and equipped with two secondary energy storage devices: battery and ultra-capacitor (UC). However, an advanced energy management strategy is quite necessary to split the power demand of a vehicle in a suitable way for the on-board power sources in order to maximize the performance while promoting the fuel economy and endurance of hybrid system components. In this study, a wavelet and fuzzy logic based energy management strategy is proposed for the developed hybrid vehicular system. Wavelet transform has great capability for analyzing signals consisting of instantaneous changes like a hybrid electric vehicle (HEV) power demand. Besides, fuzzy logic has a quite suitable structure for the control of hybrid systems. The mathematical and electrical models of the hybrid vehicular system are developed in detail and simulated using MATLAB ®, Simulink ® and SimPowerSystems ® environments.

INNOVATIVE HYBRID GAS/ELECTRIC CHILLER COGENERATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Todd Kollross; Mike Connolly

2004-06-30

Engine-driven chillers are quickly gaining popularity in the market place (increased from 7,000 tons in 1994 to greater than 50,000 tons in 1998) due to their high efficiency, electric peak shaving capability, and overall low operating cost. The product offers attractive economics (5 year pay back or less) in many applications, based on areas cooling requirements and electric pricing structure. When heat is recovered and utilized from the engine, the energy resource efficiency of a natural gas engine-driven chiller is higher than all competing products. As deregulation proceeds, real time pricing rate structures promise high peak demand electric rates, butmore » low off-peak electric rates. An emerging trend with commercial building owners and managers who require air conditioning today is to reduce their operating costs by installing hybrid chiller systems that combine gas and electric units. Hybrid systems not only reduce peak electric demand charges, but also allow customers to level their energy load profiles and select the most economical energy source, gas or electricity, from hour to hour. Until recently, however, all hybrid systems incorporated one or more gas-powered chillers (engine driven and/or absorption) and one or more conventional electric units. Typically, the cooling capacity of hybrid chiller plants ranges from the hundreds to thousands of refrigeration tons, with multiple chillers affording the user a choice of cooling systems. But this flexibility is less of an option for building operators who have limited room for equipment. To address this technology gap, a hybrid chiller was developed by Alturdyne that combines a gas engine, an electric motor and a refrigeration compressor within a single package. However, this product had not been designed to realize the full features and benefits possible by combining an engine, motor/generator and compressor. The purpose of this project is to develop a new hybrid chiller that can (1) reduce end-user energy costs, (2) lower building peak electric load, (3) increase energy efficiency, and (4) provide standby power. This new hybrid product is designed to allow the engine to generate electricity or drive the chiller's compressor, based on the market price and conditions of the available energy sources. Building owners can minimize cooling costs by operating with natural gas or electricity, depending on time of day energy rates. In the event of a backout, the building owner could either operate the product as a synchronous generator set, thus providing standby power, or continue to operate a chiller to provide air conditioning with support of a small generator set to cover the chiller's electric auxiliary requirements. The ability to utilize the same piece of equipment as a hybrid gas/electric chiller or a standby generator greatly enhances its economic attractiveness and would substantially expand the opportunities for high efficiency cooling products.« less

The Ames Power Monitoring System

NASA Technical Reports Server (NTRS)

Osetinsky, Leonid; Wang, David

2003-01-01

The Ames Power Monitoring System (APMS) is a centralized system of power meters, computer hardware, and specialpurpose software that collects and stores electrical power data by various facilities at Ames Research Center (ARC). This system is needed because of the large and varying nature of the overall ARC power demand, which has been observed to range from 20 to 200 MW. Large portions of peak demand can be attributed to only three wind tunnels (60, 180, and 100 MW, respectively). The APMS helps ARC avoid or minimize costly demand charges by enabling wind-tunnel operators, test engineers, and the power manager to monitor total demand for center in real time. These persons receive the information they need to manage and schedule energy-intensive research in advance and to adjust loads in real time to ensure that the overall maximum allowable demand is not exceeded. The APMS (see figure) includes a server computer running the Windows NT operating system and can, in principle, include an unlimited number of power meters and client computers. As configured at the time of reporting the information for this article, the APMS includes more than 40 power meters monitoring all the major research facilities, plus 15 Windows-based client personal computers that display real-time and historical data to users via graphical user interfaces (GUIs). The power meters and client computers communicate with the server using Transmission Control Protocol/Internet Protocol (TCP/IP) on Ethernet networks, variously, through dedicated fiber-optic cables or through the pre-existing ARC local-area network (ARCLAN). The APMS has enabled ARC to achieve significant savings ($1.2 million in 2001) in the cost of power and electric energy by helping personnel to maintain total demand below monthly allowable levels, to manage the overall power factor to avoid low power factor penalties, and to use historical system data to identify opportunities for additional energy savings. The APMS also provides power engineers and electricians with the information they need to plan modifications in advance and perform day-to-day maintenance of the ARC electric-power distribution system.

Study on High Efficient Electric Vehicle Wireless Charging System

NASA Astrophysics Data System (ADS)

Chen, H. X.; Liu, Z. Z.; Zeng, H.; Qu, X. D.; Hou, Y. J.

2016-08-01

Electric and unmanned is a new trend in the development of automobile, cable charging pile can not meet the demand of unmanned electric vehicle. Wireless charging system for electric vehicle has a high level of automation, which can be realized by unmanned operation, and the wireless charging technology has been paid more and more attention. This paper first analyses the differences in S-S (series-series) and S-P (series-parallel) type resonant wireless power supply system, combined with the load characteristics of electric vehicle, S-S type resonant structure was used in this system. This paper analyses the coupling coefficient of several common coil structure changes with the moving distance of Maxwell Ansys software, the performance of disc type coil structure is better. Then the simulation model is established by Simulink toolbox in Matlab, to analyse the power and efficiency characteristics of the whole system. Finally, the experiment platform is set up to verify the feasibility of the whole system and optimize the system. Based on the theoretical and simulation analysis, the higher charging efficiency is obtained by optimizing the magnetic coupling mechanism.

Technical and legal considerations and solutions in the area of battery charging for electric vehicles

NASA Astrophysics Data System (ADS)

Juda, Z.

2016-09-01

The issue of protecting health of residents of urbanized areas from the effect of excessive particulate matter and toxic components of car exhaust gases imposes the need of introduction of clean electric vehicles to the market. The increasing market availability of electric vehicles, especially in the segment of short-range (neighborhood) vehicles is followed by development of new and advanced infrastructure solutions. This also applies to the increasingly popular hybrid vehicles PHEV (Plug-in Hybrid Electric Vehicles). However, problems with the existing designs are primarily associated with limited driving range on a single battery charge, the density of charging stations in urban and suburban area, energy system efficiency due to increased electricity demand and the unification of solutions for charging stations, on-board chargers and the necessary accessories. Technical solutions are dependent on many factors, including the type and size of battery in the vehicle and access to power grid with increased load capacity. The article discusses the legal and technical actions outlined in the above directions. It shows the available and planned solutions in this area.

Near-term implications of a ban on new coal-fired power plants in the United States.

PubMed

Newcomer, Adam; Apt, Jay

2009-06-01

Large numbers of proposed new coal power generators in the United States have been canceled, and some states have prohibited new coal power generators. We examine the effects on the U.S. electric power system of banning the construction of coal-fired electricity generators, which has been proposed as a means to reduce U.S. CO2 emissions. The model simulates load growth, resource planning, and economic dispatch of the Midwest Independent Transmission System Operator (ISO), Inc., Electric Reliability Council of Texas (ERCOT), and PJM under a ban on new coal generation and uses an economic dispatch model to calculate the resulting changes in dispatch order, CO2 emissions, and fuel use under three near-term (until 2030) future electric power sector scenarios. A national ban on new coal-fired power plants does not lead to CO2 reductions of the scale required under proposed federal legislation such as Lieberman-Warner but would greatly increase the fraction of time when natural gas sets the price of electricity, even with aggressive wind and demand response policies.

How to Obtain a 100% Reliable Grid with Clean, Renewable Wind, Water, and Solar Providing 100% of all Raw Energy for All Purposes

NASA Astrophysics Data System (ADS)

Jacobson, M. Z.; Delucchi, M. A.; Cameron, M. A.; Frew, B. A.

2016-12-01

The greatest concern facing the large-scale integration of wind, water, and solar (WWS) into a power grid is the high cost of avoiding load loss caused by WWS variability and uncertainty. This talk discusses the recent development of a new grid integration model to address this issue. The model finds low-cost, no-load-loss, non-unique solutions to this problem upon electrification of all U.S. energy sectors (electricity, transportation, heating/cooling, and industry) while accounting for wind and solar time-series data from a 3-D global weather model that simulates extreme events and competition among wind turbines for available kinetic energy. Solutions are obtained by prioritizing storage for heat (in soil and water); cold (in ice and water); and electricity (in phase-change materials, pumped hydro, hydropower, and hydrogen); and using demand response. No natural gas, biofuels, or stationary batteries are needed. The resulting 2050-2055 U.S. electricity social cost for a full system is much less than for fossil fuels. These results hold for many conditions, suggesting that low-cost, stable 100% WWS systems should work many places worldwide. The paper this talk is based on was published in PNAS, 112, 15,060-15,065, 2015, doi:10.1073/pnas.1510028112.

Solar energy system performance evaluation: Seasonal report for IBM system 1A, Huntsville, Alabama

NASA Technical Reports Server (NTRS)

1980-01-01

The operational and thermal performance of the solar energy system, Sims Prototype System 1A, is described. The system was designed by IBM to provide 50 to 60 percent of the space heating and domestic hot water preheating load to a 2,000 square foot floor space single family residence in the Huntsville area. The load design temperature inside the building was to be maintained at 70 degrees fahrenheit with auxiliary energy for heating supplied by an electric heat pump assisted by an electric resistance strip heater. In general the disappointing operation of this system is attributed to the manner in which it was used. The system was designed for residential application and used to satisfy the demands of an office environment. The differences were: (1) inside temperature was not maintained at 70 F as expected; and (2) hot water usage was much lower than expected. The conclusion is that the solar energy system must be designed for the type of application in which it is used. Misapplication usually will have an adverse affect on system performance.

Electrical Assessment, Capacity, and Demand Study for Fort Wainwright, Alaska

DTIC Science & Technology

2007-09-01

0 108 5 117 20 97 5 127 40 87 5 136 60 76 5 147 80 67 5 157 100 57 5 167 120 47 5 169 125 44 Several lessons can be learned from the curves and...Note: a. The legibility of the original is extremely marginal, and the steam rates may be incorrect. Several important lessons can be learned from...Loads with inductive motors and little or no compensating capacitance would have a PF of less than one. PFs assumed for design are commonly taken as 0.80

Multi-time scale dynamics in power electronics-dominated power systems

NASA Astrophysics Data System (ADS)

Yuan, Xiaoming; Hu, Jiabing; Cheng, Shijie

2017-09-01

Electric power infrastructure has recently undergone a comprehensive transformation from electromagnetics to semiconductors. Such a development is attributed to the rapid growth of power electronic converter applications in the load side to realize energy conservation and on the supply side for renewable generations and power transmissions using high voltage direct current transmission. This transformation has altered the fundamental mechanism of power system dynamics, which demands the establishment of a new theory for power system control and protection. This paper presents thoughts on a theoretical framework for the coming semiconducting power systems.

Altitude Wind Tunnel Operating at Night

NASA Image and Video Library

1945-04-21

The Altitude Wind Tunnel (AWT) during one of its overnight runs at the National Advisory Committee for Aeronautics (NACA) Aircraft Engine Research Laboratory in Cleveland, Ohio. The AWT was run during night hours so that its massive power loads were handled when regional electric demands were lowest. At the time the AWT was among the most complex wind tunnels ever designed. In order to simulate conditions at high altitudes, NACA engineers designed innovative new systems that required tremendous amounts of electricity. The NACA had an agreement with the local electric company that it would run its larger facilities overnight when local demand was at its lowest. In return the utility discounted its rates for the NACA during those hours. The AWT could produce wind speeds up to 500 miles per hour through its 20-foot-diameter test section at the standard operating altitude of 30,000 feet. The airflow was created by a large fan that was driven by an 18,000-horsepower General Electric induction motor. The altitude simulation was accomplished by large exhauster and refrigeration systems. The cold temperatures were created by 14 Carrier compressors and the thin atmosphere by four 1750-horsepower exhausters. The first and second shifts usually set up and broke down the test articles, while the third shift ran the actual tests. Engineers would often have to work all day, then operate the tunnel overnight, and analyze the data the next day. The night crew usually briefed the dayshift on the tests during morning staff meetings.

Study on Improving Partial Load by Connecting Geo-thermal Heat Pump System to Fuel Cell Network

NASA Astrophysics Data System (ADS)

Obara, Shinya; Kudo, Kazuhiko

Hydrogen piping, the electric power line, and exhaust heat recovery piping of the distributed fuel cells are connected with network, and operational planning is carried out. Reduction of the efficiency in partial load is improved by operation of the geo-thermal heat pump linked to the fuel cell network. The energy demand pattern of the individual houses in Sapporo was introduced. And the analysis method aiming at minimization of the fuel rate by the genetic algorithm was described. The fuel cell network system of an analysis example assumed connecting the fuel cell co-generation of five houses. When geo-thermal heat pump was introduced into fuel cell network system stated in this paper, fuel consumption was reduced 6% rather than the conventional method

Simulations of the Fuel Economy and Emissions of Hybrid Transit Buses over Planned Local Routes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Zhiming; LaClair, Tim J; Daw, C Stuart

2014-01-01

We present simulated fuel economy and emissions city transit buses powered by conventional diesel engines and diesel-hybrid electric powertrains of varying size. Six representative city drive cycles were included in the study. In addition, we included previously published aftertreatment device models for control of CO, HC, NOx, and particulate matter (PM) emissions. Our results reveal that bus hybridization can significantly enhance fuel economy by reducing engine idling time, reducing demands for accessory loads, exploiting regenerative braking, and shifting engine operation to speeds and loads with higher fuel efficiency. Increased hybridization also tends to monotonically reduce engine-out emissions, but trends inmore » the tailpipe (post-aftertreatment) emissions involve more complex interactions that significantly depend on motor size and drive cycle details.« less

System and method employing a self-organizing map load feature database to identify electric load types of different electric loads

DOEpatents

Lu, Bin; Harley, Ronald G.; Du, Liang; Yang, Yi; Sharma, Santosh K.; Zambare, Prachi; Madane, Mayura A.

2014-06-17

A method identifies electric load types of a plurality of different electric loads. The method includes providing a self-organizing map load feature database of a plurality of different electric load types and a plurality of neurons, each of the load types corresponding to a number of the neurons; employing a weight vector for each of the neurons; sensing a voltage signal and a current signal for each of the loads; determining a load feature vector including at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the loads; and identifying by a processor one of the load types by relating the load feature vector to the neurons of the database by identifying the weight vector of one of the neurons corresponding to the one of the load types that is a minimal distance to the load feature vector.

2006 Pacific Northwest Loads and Resources Study.

DOE Office of Scientific and Technical Information (OSTI.GOV)

United States. Bonneville Power Administration.

2006-03-01

The Pacific Northwest Loads and Resources Study (White Book), which is published annually by the Bonneville Power Administration (BPA), establishes one of the planning bases for supplying electricity to customers. The White Book contains projections of regional and Federal system load and resource capabilities, along with relevant definitions and explanations. The White Book also contains information obtained from formalized resource planning reports and data submittals including those from individual utilities, the Northwest Power and Conservation Council (Council), and the Pacific Northwest Utilities Conference Committee (PNUCC). The White Book is not an operational planning guide, nor is it used for determiningmore » BPA revenues, although the database that generates the data for the White Book analysis contributes to the development of BPA's inventory and ratemaking processes. Operation of the Federal Columbia River Power System (FCRPS) is based on a set of criteria different from that used for resource planning decisions. Operational planning is dependent upon real-time or near-term knowledge of system conditions that include expectations of river flows and runoff, market opportunities, availability of reservoir storage, energy exchanges, and other factors affecting the dynamics of operating a power system. The load resource balance of both the Federal system and the region is determined by comparing resource availability to an expected level of total retail electricity consumption. Resources include projected energy capability plus contract purchases. Loads include a forecast of retail obligations plus contract obligations. Surplus energy is available when resources are greater than loads. This surplus energy could be marketed to increase revenues. Energy deficits occur when resources are less than loads. These energy deficits will be met by any combination of the following: better-than-critical water conditions, demand-side management and conservation programs, permanent loss of loads due to economic conditions or closures, additional contract purchases, and/or the addition of new generating resources. This study incorporates information on Pacific Northwest (PNW) regional retail loads, contract obligations, and contract resources. This loads and resources analysis simulates the operation of the power system in the PNW. The simulated hydro operation incorporates plant characteristics, streamflows, and non-power requirements from the current Pacific Northwest Coordination Agreement (PNCA). Additional resource capability estimates were provided by BPA, PNW Federal agency, public agency, cooperative, U.S. Bureau of Reclamation (USBR), and investor-owned utility (IOU) customers furnished through annual PNUCC data submittals for 2005 and/or direct submittals to BPA. The 2006 White Book is presented in two documents: (1) this summary document of Federal system and PNW region loads and resources, and (2) a technical appendix which presents regional loads, grouped by major PNW utility categories, and detailed contract and resource information. The technical appendix is available only in electronic form. Individual customer information for marketer contracts is not detailed due to confidentiality agreements. The 2006 White Book analysis updates the 2004 White Book. This analysis shows projections of the Federal system and region's yearly average annual energy consumption and resource availability for the study period, OY 2007-2016. The study also presents projections of Federal system and region expected 1-hour monthly peak demand, monthly energy demand, monthly 1-hour peak generating capability, and monthly energy generation for OY 2007, 2011, and 2016. BPA is investigating a new approach in capacity planning depicting the monthly Federal system 120-hour peak generating capability and 120-hour peak surplus/deficit for OY 2007, 2011, and 2016. This document analyzes the PNW's projected loads and available generating resources in two parts: (1) the loads and resources of the Federal system, for which BPA is the marketing agency; and (2) the larger PNW regional power system loads and resources that include the Federal system as well other PNW entities.« less

Method for estimating power outages and restoration during natural and man-made events

DOEpatents

Omitaomu, Olufemi A.; Fernandez, Steven J.

2016-01-05

A method of modeling electric supply and demand with a data processor in combination with a recordable medium, and for estimating spatial distribution of electric power outages and affected populations. A geographic area is divided into cells to form a matrix. Within the matrix, supply cells are identified as containing electric substations and demand cells are identified as including electricity customers. Demand cells of the matrix are associated with the supply cells as a function of the capacity of each of the supply cells and the proximity and/or electricity demand of each of the demand cells. The method includes estimating a power outage by applying disaster event prediction information to the matrix, and estimating power restoration using the supply and demand cell information of the matrix and standardized and historical restoration information.

The Effect of Mitigation Policy on Regional Climate Impacts on the U.S. Electric Sector

NASA Astrophysics Data System (ADS)

Cohen, S. M.; Sun, Y.; Strzepek, K.; McFarland, J.; Boehlert, B.; Fant, C.

2017-12-01

Climate change can influence the U.S. electricity sector in many ways, the nature of which can be shaped by energy and environmental policy choices. Changing temperatures affect electricity demand largely through heating and cooling needs, and temperatures also affect generation and transmission system performance. Altered precipitation patterns affect the regional and seasonal distribution of surface water runoff, which changes hydropower operation and thermal cooling water availability. The extent to which these stimuli influence U.S. power sector operation and planning will depend to some extent on whether or not proactive policies are enacted to mitigate these impacts. Mitigation policies such as CO2 emissions limits or technology restrictions can change the makeup of the electricity system while reducing the extent of climate change itself. We use the National Renewable Energy Laboratory's Regional Energy Deployment System (ReEDS), a U.S. electric sector capacity expansion model, to explore electric sector evolution through 2050 under alternative climate and policy assumptions. The model endogenously represents climate impacts on load, power system performance, cooling water availability, and hydropower, allowing internally consistent system responses to climate change along with projected technology, market, and policy conditions. We compare climate impacts across 5 global circulation models for a 8.5 W/m2 representative concentration pathway (RCP) without a climate mitigation policy and a 4.5 W/m2 RCP with climate mitigation. Climate drivers affect the capacity and generation mix at the national and regional levels, with relative growth of wind, solar, and natural gas-based technologies depending on local electricity system characteristics. These differences affect regional economic impacts, measured here as changes to electricity price and system costs. Mitigation policy reduces the economic and system impacts of climate change largely by moderating temperature-induced load but also by lessening water- and temperature-based performance constraints. Policy impacts are nuanced and region-specific, and this analysis underscores the importance of climate mitigation policy to regional electricity system planning decisions.

30 CFR 56.6600 - Loading practices.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Electricity § 56.6600 Loading practices. If extraneous electricity is suspected in an area where electric... levels of extraneous electricity are found, the source shall be determined and no loading shall take...

30 CFR 56.6600 - Loading practices.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Electricity § 56.6600 Loading practices. If extraneous electricity is suspected in an area where electric... levels of extraneous electricity are found, the source shall be determined and no loading shall take...

30 CFR 56.6600 - Loading practices.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Electricity § 56.6600 Loading practices. If extraneous electricity is suspected in an area where electric... levels of extraneous electricity are found, the source shall be determined and no loading shall take...

30 CFR 56.6600 - Loading practices.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Electricity § 56.6600 Loading practices. If extraneous electricity is suspected in an area where electric... levels of extraneous electricity are found, the source shall be determined and no loading shall take...

30 CFR 56.6600 - Loading practices.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Electricity § 56.6600 Loading practices. If extraneous electricity is suspected in an area where electric... levels of extraneous electricity are found, the source shall be determined and no loading shall take...

Power-to-heat in adiabatic compressed air energy storage power plants for cost reduction and increased flexibility

NASA Astrophysics Data System (ADS)

Dreißigacker, Volker

2018-04-01

The development of new technologies for large-scale electricity storage is a key element in future flexible electricity transmission systems. Electricity storage in adiabatic compressed air energy storage (A-CAES) power plants offers the prospect of making a substantial contribution to reach this goal. This concept allows efficient, local zero-emission electricity storage on the basis of compressed air in underground caverns. The compression and expansion of air in turbomachinery help to balance power generation peaks that are not demand-driven on the one hand and consumption-induced load peaks on the other. For further improvements in cost efficiencies and flexibility, system modifications are necessary. Therefore, a novel concept regarding the integration of an electrical heating component is investigated. This modification allows increased power plant flexibilities and decreasing component sizes due to the generated high temperature heat with simultaneously decreasing total round trip efficiencies. For an exemplarily A-CAES case simulation studies regarding the electrical heating power and thermal energy storage sizes were conducted to identify the potentials in cost reduction of the central power plant components and the loss in round trip efficiency.

Providing Reliability Services through Demand Response: A Prelimnary Evaluation of the Demand Response Capabilities of Alcoa Inc.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Starke, Michael R; Kirby, Brendan J; Kueck, John D

2009-02-01

Demand response is the largest underutilized reliability resource in North America. Historic demand response programs have focused on reducing overall electricity consumption (increasing efficiency) and shaving peaks but have not typically been used for immediate reliability response. Many of these programs have been successful but demand response remains a limited resource. The Federal Energy Regulatory Commission (FERC) report, 'Assessment of Demand Response and Advanced Metering' (FERC 2006) found that only five percent of customers are on some form of demand response program. Collectively they represent an estimated 37,000 MW of response potential. These programs reduce overall energy consumption, lower greenmore » house gas emissions by allowing fossil fuel generators to operate at increased efficiency and reduce stress on the power system during periods of peak loading. As the country continues to restructure energy markets with sophisticated marginal cost models that attempt to minimize total energy costs, the ability of demand response to create meaningful shifts in the supply and demand equations is critical to creating a sustainable and balanced economic response to energy issues. Restructured energy market prices are set by the cost of the next incremental unit of energy, so that as additional generation is brought into the market, the cost for the entire market increases. The benefit of demand response is that it reduces overall demand and shifts the entire market to a lower pricing level. This can be very effective in mitigating price volatility or scarcity pricing as the power system responds to changing demand schedules, loss of large generators, or loss of transmission. As a global producer of alumina, primary aluminum, and fabricated aluminum products, Alcoa Inc., has the capability to provide demand response services through its manufacturing facilities and uniquely through its aluminum smelting facilities. For a typical aluminum smelter, electric power accounts for 30% to 40% of the factory cost of producing primary aluminum. In the continental United States, Alcoa Inc. currently owns and/or operates ten aluminum smelters and many associated fabricating facilities with a combined average load of over 2,600 MW. This presents Alcoa Inc. with a significant opportunity to respond in areas where economic opportunities exist to help mitigate rising energy costs by supplying demand response services into the energy system. This report is organized into seven chapters. The first chapter is the introduction and discusses the intention of this report. The second chapter contains the background. In this chapter, topics include: the motivation for Alcoa to provide demand response; ancillary service definitions; the basics behind aluminum smelting; and a discussion of suggested ancillary services that would be particularly useful for Alcoa to supply. Chapter 3 is concerned with the independent system operator, the Midwest ISO. Here the discussion examines the evolving Midwest ISO market structure including specific definitions, requirements, and necessary components to provide ancillary services. This section is followed by information concerning the Midwest ISO's classifications of demand response parties. Chapter 4 investigates the available opportunities at Alcoa's Warrick facility. Chapter 5 involves an in-depth discussion of the regulation service that Alcoa's Warrick facility can provide and the current interactions with Midwest ISO. Chapter 6 reviews future plans and expectations for Alcoa providing ancillary services into the market. Last, chapter 7, details the conclusion and recommendations of this paper.« less

Reserve valuation in electric power systems

NASA Astrophysics Data System (ADS)

Ruiz, Pablo Ariel

Operational reliability is provided in part by scheduling capacity in excess of the load forecast. This reserve capacity balances the uncertain power demand with the supply in real time and provides for equipment outages. Traditionally, reserve scheduling has been ensured by enforcing reserve requirements in the operations planning. An alternate approach is to employ a stochastic formulation, which allows the explicit modeling of the sources of uncertainty. This thesis compares stochastic and reserve methods and evaluates the benefits of a combined approach for the efficient management of uncertainty in the unit commitment problem. Numerical studies show that the unit commitment solutions obtained for the combined approach are robust and superior with respect to the traditional approach. These robust solutions are especially valuable in areas with a high proportion of wind power, as their built-in flexibility allows the dispatch of practically all the available wind power while minimizing the costs of operation. The scheduled reserve has an economic value since it reduces the outage costs. In several electricity markets, reserve demand functions have been implemented to take into account the value of reserve in the market clearing process. These often take the form of a step-down function at the reserve requirement level, and as such they may not appropriately represent the reserve value. The value of reserve is impacted by the reliability, dynamic and stochastic characteristics of system components, the system operation policies, and the economic aspects such as the risk preferences of the demand. In this thesis, these aspects are taken into account to approximate the reserve value and construct reserve demand functions. Illustrative examples show that the demand functions constructed have similarities with those implemented in some markets.

Utilizing Thermal Mass in Refrigerated Display Cases to Reduce Peak Demand

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fricke, Brian A; Kuruganti, Teja; Nutaro, James J

The potential to store energy within refrigerated food products presents convenience store and supermarket operators with an opportunity to participate in utility sponsored demand response programs, whereby electricity usage can be shifted or reduced during peak periods. To determine the feasibility of reducing peak demand by shifting the refrigeration load to off-peak times, experimental and analytical analyses were performed. Simulated product, consisting of one-pint containers filled with a 50% ethylene glycol and 50% water solution, were stored in a medium-temperature vertical open refrigerated display case. Product temperature rise as a function of time was determined by turning off the refrigerationmore » to the display case, while product temperature pull-down time was subsequently determined by turning on the refrigeration to the display case. It was found that the thermal mass of the product in a medium-temperature display case was such that during a 2.5 hour period with no refrigeration, the average product temperature increased by 5.5 C. In addition, it took approximately 3.5 hours for the product to recover to its initial temperature after the refrigeration was turned on. Transient heat conduction analyses for one-dimensional objects is in good agreement with the experimental results obtained in this study. From the analysis, it appears that the thermal mass of the stored product in refrigerated display cases is sufficient to allow product temperatures to safely drift for a significant time under reduced refrigeration system operation. Thus, strategies for shifting refrigeration system electrical demand can be developed. The use of an advanced refrigeration system controller that can respond to utility signals can enable demand shifting with minimal impact.« less

Opportunities for Joint Water–Energy Management: Sensitivity of the 2010 Western U.S. Electricity Grid Operations to Climate Oscillations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Voisin, N.; Kintner-Meyer, M.; Wu, D.

The 2016 SECURE Water Act report’s natural water availability benchmark, combined with the 2010 level of water demand from an integrated assessment model, is used as input to drive a large-scale water management model. The regulated flow at hydropower plants and thermoelectric plants in the Western U.S. electricity grid (WECC) is translated into potential hydropower generation and generation capacity constraints. The impact on reliability (unserved energy, reserve margin) and cost (production cost, carbon emissions) of water constraints on 2010-level WECC power system operations is assessed using an electricity production cost model (PCM). Use of the PCM reveals the changes inmore » generation dispatch that reflect the inter-regional interdependencies in water-constrained generation and the ability to use other generation resources to meet all electricity loads in the WECC. August grid operational benchmarks show a range of sensitivity in production cost (-8 to +11%) and carbon emissions (-7 to 11%). The reference reserve margin threshold of 15% above peak load is maintained in the scenarios analyzed, but in 5 out of 55 years unserved energy is observed when normal operations are maintained. There is 1 chance in 10 that a year will demonstrate unserved energy in August, which defines the system’s historical performance threshold to support impact, vulnerability, and adaptation analysis. For seasonal and longer term planning, i.e., multi-year drought, we demonstrate how the Water Scarcity Grid Impact Factor and climate oscillations (ENSO, PDO) can be used to plan for joint water-electricity management to maintain grid reliability.« less

Feasibility study for the Swaziland/Mozambique interconnector. Final report. Export trade information

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1997-11-01

This study, conducted by Black & Veatch, was funded by the U.S. Trade and Development Agency. The report, produced for the Ministry of National Resources, Energy and Environment (MNRE) of Swaziland, determines the least cost capacity expansion option to meet the future power demand and system reliability criteria of Swaziland, with particular emphasis on the proposed interconnector between Swaziland and Mozambique. Volume 2, the Final Report, contains the following sections: (1.0) Introduction; (2.0) Review of SEB Power System; (3.0) SEB Load Forecast and Review; (4.0) SEB Load Forecast Revision; (5.0) The SEB Need for Power; (6.0) SEB System Development Planmore » Review; (7.0) Southern Mozambique EdM power System Review; (8.0) Southern Mozambique EdM Energy and Demand; (9.0) Supply Side Capacity Options for Swaziland and Mozambique; (10.0) SEB Expansion Plan Development; (11.0) EdM Expansion Plan Development; (12.0) Cost Sharing of the Interconnector; (13.0) Enviroinmental Evaluation of Interconnector Options; (14.0) Generation/Transmission Trade Offs; (15.0) Draft Interconnection Agreement and Contract Packages; (16.0) Transmission System Study; (17.0) Automatic General Control; (18.0) Automatic Startup and Shutdown of Hydro Electric Power Plants; (19.0) Communications and Metering; (20.0) Conclusions and Recommendations; Appendix A: Demand Side Management Primer; Appendix B. PURPA and Avoided Cost Calculations.« less

Interoperability Context-Setting Framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Widergren, Steven E.; Hardin, Dave; Ambrosio, Ron

2007-01-31

As the deployment of automation technology advances, it touches upon many areas of our corporate and personal lives. A trend is emerging where systems are growing to the extent that integration is taking place with other systems to provide even greater capabilities more efficiently and effectively. GridWise™ provides a vision for this type of integration as it applies to the electric system. Imagine a time in the not too distant future when homeowners can offer the management of their electricity demand to participate in a more efficient and environmentally friendly operation of the electric power grid. They will do thismore » using technology that acts on their behalf in response to information from other components of the electric system. This technology will recognize their preferences to parameters such as comfort and the price of energy to form responses that optimize the local need to a signal that satisfies a higher-level need in the grid. For example, consider a particularly hot day with air stagnation in an area with a significant dependence on wind generation. To manage the forecasted peak electricity demand, the bulk system operator issues a critical peak price warning. Their automation systems alert electric service providers who distribute electricity from the wholesale electricity system to consumers. In response, the electric service providers use their automation systems to inform consumers of impending price increases for electricity. This information is passed to an energy management system at the premises, which acts on the homeowner’s behalf, to adjust the electricity usage of the onsite equipment (which might include generation from such sources as a fuel cell). The objective of such a system is to honor the agreement with the electricity service provider and reduce the homeowner’s bill while keeping the occupants as comfortable as possible. This will include actions such as moving the thermostat on the heating, ventilation, and air-conditioning (HVAC) unit up several degrees. The resulting load reduction becomes part of an aggregated response from the electricity service provider to the bulk system operator who is now in a better position to manage total system load with available generation. Looking across the electric system, from generating plants, to transmission substations, to the distribution system, to factories, office parks, and buildings, automation is growing, and the opportunities for unleashing new value propositions are exciting. How can we facilitate this change and do so in a way that ensures the reliability of electric resources for the wellbeing of our economy and security? The GridWise Architecture Council (GWAC) mission is to enable interoperability among the many entities that interact with the electric power system. A good definition of interoperability is, “The capability of two or more networks, systems, devices, applications, or components to exchange information between them and to use the information so exchanged.” As a step in the direction of enabling interoperability, the GWAC proposes a context-setting framework to organize concepts and terminology so that interoperability issues can be identified and debated, improvements to address issues articulated, and actions prioritized and coordinated across the electric power community.« less

The analysis of Taiwan's residential electricity demand under the electricity tariff policy

NASA Astrophysics Data System (ADS)

Chen, Po-Jui

In October 2013, the Taiwan Power Company (Taipower), the monopolized state utility service in Taiwan, implemented an electricity tariff adjustment policy to reduce residential electricity demand. Using bi-monthly billing data from 6,932 electricity consumers, this study examine how consumers respond to an increase in electricity prices. This study employs an empirical approach that takes advantage of quasi-random variation over a period of time when household bills were affected by a change in electricity price. The study found that this price increase caused a 1.78% decline in residential electricity consumption, implying a price elasticity of -0.19 for summer-season months and -0.15 for non-summer-season months. The demand for electricity is therefore relatively inelastic, likely because it is hard for people to change their electricity consumption behavior in the short-term. The results of this study highlight that demand-side management cannot be the only lever used to address Taiwan's forecasted decrease in electricity supply.

Advanced Stirling Convertor Dual Convertor Controller Testing at NASA Glenn Research Center in the Radioisotope Power Systems System Integration Laboratory

NASA Technical Reports Server (NTRS)

Dugala, Gina M.; Taylor, Linda M.; Bell, Mark E.; Dolce, James L.; Fraeman, Martin; Frankford, David P.

2015-01-01

NASA Glenn Research Center developed a nonnuclear representation of a Radioisotope Power System (RPS) consisting of a pair of Advanced Stirling Convertors (ASCs), Dual Convertor Controller (DCC) EMs (engineering models) 2 and 3, and associated support equipment, which were tested in the Radioisotope Power Systems System Integration Laboratory (RSIL). The DCC was designed by the Johns Hopkins University Applied Physics Laboratory (JHU/APL) to actively control a pair of ASCs. The first phase of testing included a Dual Advanced Stirling Convertor Simulator (DASCS), which was developed by JHU/APL and simulates the operation and electrical behavior of a pair of ASCs in real time via a combination of hardware and software. RSIL provides insight into the electrical interactions between a representative radioisotope power generator, its associated control schemes, and realistic electric system loads. The first phase of integration testing included the following spacecraft bus configurations: capacitive, battery, and super-capacitor. A load profile, created based on data from several missions, tested the RPS's and RSIL's ability to maintain operation during load demands above and below the power provided by the RPS. The integration testing also confirmed the DCC's ability to disconnect from the spacecraft when the bus voltage dipped below 22 volts or exceeded 36 volts. Once operation was verified with the DASCS, the tests were repeated with actual operating ASCs. The goal of this integration testing was to verify operation of the DCC when connected to a spacecraft and to verify the functionality of the newly designed RSIL. The results of these tests are presented in this paper.

Energy manager design for microgrids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Firestone, Ryan; Marnay, Chris

2005-01-01

On-site energy production, known as distributed energy resources (DER), offers consumers many benefits, such as bill savings and predictability, improved system efficiency, improved reliability, control over power quality, and in many cases, greener electricity. Additionally, DER systems can benefit electric utilities by reducing congestion on the grid, reducing the need for new generation and transmission capacity, and offering ancillary services such as voltage support and emergency demand response. Local aggregations of distributed energy resources (DER) that may include active control of on-site end-use energy devices can be called microgrids. Microgrids require control to ensure safe operation and to make dispatchmore » decisions that achieve system objectives such as cost minimization, reliability, efficiency and emissions requirements, while abiding by system constraints and regulatory rules. This control is performed by an energy manager (EM). Preferably, an EM will achieve operation reasonably close to the attainable optimum, it will do this by means robust to deviations from expected conditions, and it will not itself incur insupportable capital or operation and maintenance costs. Also, microgrids can include supervision over end-uses, such as curtailing or rescheduling certain loads. By viewing a unified microgrid as a system of supply and demand, rather than simply a system of on-site generation devices, the benefits of integrated supply and demand control can be exploited, such as economic savings and improved system energy efficiency.« less

Estimating Elasticity for Residential Electricity Demand in China

PubMed Central

Shi, G.; Zheng, X.; Song, F.

2012-01-01

Residential demand for electricity is estimated for China using a unique household level dataset. Household electricity demand is specified as a function of local electricity price, household income, and a number of social-economic variables at household level. We find that the residential demand for electricity responds rather sensitively to its own price in China, which implies that there is significant potential to use the price instrument to conserve electricity consumption. Electricity elasticities across different heterogeneous household groups (e.g., rich versus poor and rural versus urban) are also estimated. The results show that the high income group is more price elastic than the low income group, while rural families are more price elastic than urban families. These results have important policy implications for designing an increasing block tariff. PMID:22997492

Nuclear electric generation: Political, social, and economic cost and benefit to Indonesia. Master`s thesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waliyo

Indonesia, the largest archipelagic country with a population the fourth biggest in the world, is now in the process of development. It needs a large quantity of energy electricity to meet the industrial and household demands. The currently available generating capacity is not sufficient to meet the electricity demand for the rapidly growing industries and the increasing population. In order to meet the future demand for electricity, new generating capacity is required to be added to the current capacity. Nuclear electricity generation is one possible alternative to supplement Indonesia`s future demand of electricity. This thesis investigates the possibility of developingmore » nuclear electricity generation in Indonesia, considering the political, social, and economic cost and benefit to Indonesia.« less

Estimating elasticity for residential electricity demand in China.

PubMed

Shi, G; Zheng, X; Song, F

2012-01-01

Residential demand for electricity is estimated for China using a unique household level dataset. Household electricity demand is specified as a function of local electricity price, household income, and a number of social-economic variables at household level. We find that the residential demand for electricity responds rather sensitively to its own price in China, which implies that there is significant potential to use the price instrument to conserve electricity consumption. Electricity elasticities across different heterogeneous household groups (e.g., rich versus poor and rural versus urban) are also estimated. The results show that the high income group is more price elastic than the low income group, while rural families are more price elastic than urban families. These results have important policy implications for designing an increasing block tariff.

A multifunctional energy-storage system with high-power lead-acid batteries

NASA Astrophysics Data System (ADS)

Wagner, R.; Schroeder, M.; Stephanblome, T.; Handschin, E.

A multifunctional energy storage system is presented which is used to improve the utilization of renewable energy supplies. This system includes three different functions: (i) uninterruptible power supply (UPS); (ii) improvement of power quality; (iii) peak-load shaving. The UPS application has a long tradition and is used whenever a reliable power supply is needed. Additionally, nowadays, there is a growing demand for high quality power arising from an increase of system perturbation of electric grids. Peak-load shaving means in this case the use of renewable energy stored in a battery for high peak-load periods. For such a multifunctional application large lead-acid batteries with high power and good charge acceptance, as well as good cycle life are needed. OCSM batteries as with positive tubular plates and negative copper grids have been used successfully for a multitude of utility applications. This paper gives two examples where multifunctional energy storage systems have started operation recently in Germany. One system was installed in combination with a 1 MW solar plant in Herne and another one was installed in combination with a 2 MW wind farm in Bocholt. At each place, a 1.2 MW h (1 h-rate) lead-acid battery has been installed. The batteries consist of OCSM cells with the standard design but modified according to the special demand of a multifunctional application.

Medium- and long-term electric power demand forecasting based on the big data of smart city

NASA Astrophysics Data System (ADS)

Wei, Zhanmeng; Li, Xiyuan; Li, Xizhong; Hu, Qinghe; Zhang, Haiyang; Cui, Pengjie

2017-08-01

Based on the smart city, this paper proposed a new electric power demand forecasting model, which integrates external data such as meteorological information, geographic information, population information, enterprise information and economic information into the big database, and uses an improved algorithm to analyse the electric power demand and provide decision support for decision makers. The data mining technology is used to synthesize kinds of information, and the information of electric power customers is analysed optimally. The scientific forecasting is made based on the trend of electricity demand, and a smart city in north-eastern China is taken as a sample.

Interaction among general practitioners age and patient load in the prediction of job strain, decision latitude and perception of job demands. A cross-sectional study.

PubMed

Vanagas, Giedrius; Bihari-Axelsson, Susanna

2004-12-07

It is widely recognized and accepted that job strain adversely impacts the workforce. Individual responses to stressful situations can vary greatly and it has been shown that certain people are more likely to experience high levels of stress in their job than others. Studies highlighted that there can be age differences in job strain perception. Cross-sectional postal survey of 300 Lithuanian general practitioners. Psychosocial stress was investigated with a questionnaire based on the Reeder scale. Job demands were investigated with the Karasek scale. The analysis included descriptive statistics; logistic regression beta coefficients to find out predictors and interactions between characteristics and predictors. Response rate was 66% (N = 197). Logistic regression as significant predictors for job strain assigned - duration of work in primary care; for job demands- age and duration of working in primary care; for decision latitude- age and patient load.The interactions with regard to job strain showed that GP's age and job strain are negatively associated to a low patient load. Lower decision latitude for older GP age is strongly related to higher patient load. Job demands and GP age are slightly positively related at low patient load. Lithuanian GP's have high patient load and are at risk of stress, they have high job demands and low decision latitude. Older GP's perceive less strain, lower job demands and higher decision latitude in case of low patient load. Young GP's decision latitude has week association to patient load. Regarding to the changes in patient load younger GP's perceive it more sensitively as changes in job demands.

Climate Change Impacts on Electricity Demand and Supply in the United States: A Multi-Model Comparison

EPA Science Inventory

This paper compares the climate change impacts on U.S. electricity demand and supply from three models: the Integrated Planning Model (IPM), the Regional Energy Deployment System (ReEDS) model, and GCAM. Rising temperatures cause an appreciable net increase in electricity demand....

Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect

PubMed Central

Shiraki, Hiroto; Ashina, Shuichi

2018-01-01

After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE). However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan’s NDC (nationally determined contribution) assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price). Our result clearly shows that consumers’ electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%–6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2–2.26 MtCO2 (−4.5% on average compared to the zero-ECE case). The time-varying ECE is necessary for predicting Japan’s electricity demand and CO2 emissions after the earthquake. PMID:29708988

Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect.

PubMed

Honjo, Keita; Shiraki, Hiroto; Ashina, Shuichi

2018-01-01

After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE). However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan's NDC (nationally determined contribution) assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price). Our result clearly shows that consumers' electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%-6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2-2.26 MtCO2 (-4.5% on average compared to the zero-ECE case). The time-varying ECE is necessary for predicting Japan's electricity demand and CO2 emissions after the earthquake.

Forward and Spot Prices in Multi-Settlement Wholesale Electricity Markets

NASA Astrophysics Data System (ADS)

Larrieu, Jeremy

In organized wholesale electricity markets, power is sold competitively in a multi-unit multi-settlement single-price auction comprised of a forward and a spot market. This dissertation attempts to understand the structure of the forward premium in these markets, and to identify the factors that may lead forward and spot prices to converge or diverge. These markets are unique in that the forward demand is price-sensitive, while spot residual demand is perfectly inelastic and must be met in full, a crucial design feature the literature often glosses over. An important contribution of this dissertation is the explicit modeling of each market separately in order to understand how generation and load choose to act in each one, and the consequences of these actions on equilibrium prices and quantities given that firms maximize joint profits over both markets. In the first essay, I construct a two-settlement model of electricity prices in which firms that own asymmetric capacity-constrained units facing convex costs compete to meet demand from consumers, first in quantities, then in prices. I show that the forward premium depends on the costliness of spot production relative to firms' ability to exercise market power by setting quantities in the forward market. In the second essay, I test the model from the first essay with unit-level capacity and marginal cost data from the California Independent System Operator (CAISO). I show that the model closely replicates observed price formation in the CAISO. In the third essay, I estimate a time series model of the CAISO forward premium in order to measure the impact that virtual bidding has had on forward and spot price convergence in California between April 2009 and March 2014. I find virtual bidding to have caused forward and spot prices to diverge due to the large number of market participants looking to hedge against - or speculate on - the occurrence of infrequent but large spot price spikes by placing virtual demand bids.

Restrictive loads powered by separate or by common electrical sources

NASA Technical Reports Server (NTRS)

Appelbaum, J.

1989-01-01

In designing a multiple load electrical system, the designer may wish to compare the performance of two setups: a common electrical source powering all loads, or separate electrical sources powering individual loads. Three types of electrical sources: an ideal voltage source, an ideal current source, and solar cell source powering resistive loads were analyzed for their performances in separate and common source systems. A mathematical proof is given, for each case, indicating the merit of the separate or common source system. The main conclusions are: (1) identical resistive loads powered by ideal voltage sources perform the same in both system setups, (2) nonidentical resistive loads powered by ideal voltage sources perform the same in both system setups, (3) nonidentical resistive loads powered by ideal current sources have higher performance in separate source systems, and (4) nonidentical resistive loads powered by solar cells have higher performance in a common source system for a wide range of load resistances.

Hybrid Geo-Energy Systems for Energy Storage and Dispatchable Renewable and Low-Carbon Electricity

NASA Astrophysics Data System (ADS)

Buscheck, Thomas; Bielicki, Jeffrey; Ogland-Hand, Jonathan; Hao, Yue; Sun, Yunwei; Randolph, Jimmy; Saar, Martin

2015-04-01

Three primary challenges for energy systems are to (1) reduce the amount of carbon dioxide (CO2) being emitted to the atmosphere, (2) increase the penetration of renewable energy technologies, and (3) reduce the water intensity of energy production. Integrating variable renewable energy sources (wind, sunlight) into electric grids requires advances in energy storage approaches, which are currently expensive, and tend to have limited capacity and/or geographic deployment potential. Our approach uses CO2, that would otherwise be emitted to the atmosphere, to generate electricity from geothermal resources, to store excess energy from variable (wind, solar photovoltaic) and thermal (nuclear, fossil, concentrated solar power) sources, and to thus enable increased penetration of renewable energy technologies. We take advantage of the enormous fluid and thermal storage capacity of the subsurface to harvest, store, and dispatch energy. Our approach uses permeable geologic formations that are vertically bounded by impermeable layers to constrain pressure and the migration of buoyant CO2 and heated brine. Supercritical CO2 captured from fossil power plants is injected into these formations as a cushion gas to store pressure (bulk energy), provide an heat efficient extraction fluid for efficient power conversion in Brayton Cycle turbines, and generate artesian flow of brine -- which can be used to cool power plants and/or pre-heated (thermal storage) prior to re-injection. Concentric rings of injection and production wells create a hydraulic divide to store pressure, CO2, and thermal energy. The system is pressurized and/or heated when power supply exceeds demand and depressurized when demand exceeds supply. Time-shifting the parasitic loads from pressurizing and injecting brine and CO2 provides bulk energy storage over days to months, whereas time-shifting thermal-energy supply provides dispatchable power and addresses seasonal mismatches between supply and demand. These conditions enable efficient fluid recirculation, heat extraction, power conversion, and add operational flexibility to dispatch electricity. Overall, the system can (a) levelize concentrating solar power, (b) mitigate variability of wind and solar power, (c) reduce water and carbon intensity of energy systems, (d) avoid wasting or curtailing high-capital cost, low-carbon energy resources and (e) allow low-carbon, base-load power to operate at full capacity. This work was performed under the auspices of the U.S. DOE by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344, and has been funded by the U.S. National Science Foundation Sustainable Energy Pathways Program (1230691) and the U.S. Department of Energy Geothermal Technologies Office (DE-FOA-0000336).

Dynamic management of integrated residential energy systems

NASA Astrophysics Data System (ADS)

Muratori, Matteo

This study combines principles of energy systems engineering and statistics to develop integrated models of residential energy use in the United States, to include residential recharging of electric vehicles. These models can be used by government, policymakers, and the utility industry to provide answers and guidance regarding the future of the U.S. energy system. Currently, electric power generation must match the total demand at each instant, following seasonal patterns and instantaneous fluctuations. Thus, one of the biggest drivers of costs and capacity requirement is the electricity demand that occurs during peak periods. These peak periods require utility companies to maintain operational capacity that often is underutilized, outdated, expensive, and inefficient. In light of this, flattening the demand curve has long been recognized as an effective way of cutting the cost of producing electricity and increasing overall efficiency. The problem is exacerbated by expected widespread adoption of non-dispatchable renewable power generation. The intermittent nature of renewable resources and their non-dispatchability substantially limit the ability of electric power generation of adapting to the fluctuating demand. Smart grid technologies and demand response programs are proposed as a technical solution to make the electric power demand more flexible and able to adapt to power generation. Residential demand response programs offer different incentives and benefits to consumers in response to their flexibility in the timing of their electricity consumption. Understanding interactions between new and existing energy technologies, and policy impacts therein, is key to driving sustainable energy use and economic growth. Comprehensive and accurate models of the next-generation power system allow for understanding the effects of new energy technologies on the power system infrastructure, and can be used to guide policy, technology, and economic decisions. This dissertation presents a bottom-up highly resolved model of a generic residential energy eco-system in the United States. The model is able to capture the entire energy footprint of an individual household, to include all appliances, space conditioning systems, in-home charging of plug-in electric vehicles, and any other energy needs, viewing residential and transportation energy needs as an integrated continuum. The residential energy eco-system model is based on a novel bottom-up approach that quantifies consumer energy use behavior. The incorporation of stochastic consumer behaviors allows capturing the electricity consumption of each residential specific end-use, providing an accurate estimation of the actual amount of available controllable resources, and for a better understanding of the potential of residential demand response programs. A dynamic energy management framework is then proposed to manage electricity consumption inside each residential energy eco-system. Objective of the dynamic energy management framework is to optimize the scheduling of all the controllable appliances and in-home charging of plug-in electric vehicles to minimize cost. Such an automated energy management framework is used to simulate residential demand response programs, and evaluate their impact on the electric power infrastructure. For instance, time-varying electricity pricing might lead to synchronization of the individual residential demands, creating pronounced rebound peaks in the aggregate demand that are higher and steeper than the original demand peaks that the time-varying electricity pricing structure intended to eliminate. The modeling tools developed in this study can serve as a virtual laboratory for investigating fundamental economic and policy-related questions regarding the interplay of individual consumers with energy use. The models developed allow for evaluating the impact of different energy policies, technology adoption, and electricity price structures on the total residential electricity demand. In particular, two case studies are reported in this dissertation to illustrate application of the tools developed. The first considers the impact of market penetration of plug-in electric vehicles on the electric power infrastructure. The second provides a quantitative comparison of the impact of different electricity price structures on residential demand response. Simulation results and an electricity price structure, called Multi-TOU, aimed at solving the rebound peak issue, are presented.

The planning and implementation of a demand-side management/distribution automation system at Taiwan Power Company

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, S.S.; Chen, Yun-Wu

1994-12-31

This paper would describe the Taipower`s experience of DSM/DAS development. For the past 5 years, the demand of electricity has maintained a high annual growth rate of 8.45% due to economic prosperity in Taiwan. As the environmental protection consciousness has recently made Taipower difficult to develope and construct new power plants, substations, transmission and distribution lines, and our power grid is an independent system, we do need to concern how to do DSM to manage the load problems. Since 1984, Taipower has established two pilot systems and these systems performed the functions of fault detect and isolation certainly good formore » Distribution Automation. With the rapid development of computer, communication and control technology, the concept of the DAS has gradually been implemented in real cases. Taipower organized an engineering task group to study DAS several years ago, and based on the operation experience of the existing systems, today Taipower is planning to launch a new DAS project for Tai-Chung area. According to Taipower requirements, the DAS will have the functions of feeder automation, automatic meter reading, load management and disteibution system analysis.« less

Power Management Based Current Control Technique for Photovoltaic-Battery Assisted Wind-Hydro Hybrid System

NASA Astrophysics Data System (ADS)

Ram Prabhakar, J.; Ragavan, K.

2013-07-01

This article proposes new power management based current control strategy for integrated wind-solar-hydro system equipped with battery storage mechanism. In this control technique, an indirect estimation of load current is done, through energy balance model, DC-link voltage control and droop control. This system features simpler energy management strategy and necessitates few power electronic converters, thereby minimizing the cost of the system. The generation-demand (G-D) management diagram is formulated based on the stochastic weather conditions and demand, which would likely moderate the gap between both. The features of management strategy deploying energy balance model include (1) regulating DC-link voltage within specified tolerances, (2) isolated operation without relying on external electric power transmission network, (3) indirect current control of hydro turbine driven induction generator and (4) seamless transition between grid-connected and off-grid operation modes. Furthermore, structuring of the hybrid system with appropriate selection of control variables enables power sharing among each energy conversion systems and battery storage mechanism. By addressing these intricacies, it is viable to regulate the frequency and voltage of the remote network at load end. The performance of the proposed composite scheme is demonstrated through time-domain simulation in MATLAB/Simulink environment.

Hybrid solar converters for maximum exergy and inexpensive dispatchable electricity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Branz, Howard M.; Regan, William; Gerst, Kacy J.

Photovoltaic (PV) solar energy systems are being deployed at an accelerating rate to supply low-carbon electricity worldwide. However, PV is unlikely to economically supply much more than 10% of the world's electricity unless there is a dramatic reduction in the cost of electricity storage. There is an important scientific and technological opportunity to address the storage challenge by developing inexpensive hybrid solar converters that collect solar heat at temperatures between about 200 and 600 °C and also incorporate PV. Since heat can be stored and converted to electricity at relatively low cost, collection of high exergy content (high temperature) solarmore » heat can provide energy that is dispatchable on demand to meet loads that are not well matched to solar insolation. However, PV cells can collect and convert much of the solar spectrum to electricity more efficiently and inexpensively than solar thermal systems. Advances in spectrum-splitting optics, high-temperature PV cells, thermal management and system design are needed for transformational hybrid converters. We propose that maximizing the exergy output from the solar converters while minimizing the cost of exergy can help propel solar energy toward a higher contribution to carbon-free electricity in the long term than the prevailing paradigm of maximizing the energy output while minimizing the cost of energy« less

Options for near-term phaseout of CO(2) emissions from coal use in the United States.

PubMed

Kharecha, Pushker A; Kutscher, Charles F; Hansen, James E; Mazria, Edward

2010-06-01

The global climate problem becomes tractable if CO(2) emissions from coal use are phased out rapidly and emissions from unconventional fossil fuels (e.g., oil shale and tar sands) are prohibited. This paper outlines technology options for phasing out coal emissions in the United States by approximately 2030. We focus on coal for physical and practical reasons and on the U.S. because it is most responsible for accumulated fossil fuel CO(2) in the atmosphere today, specifically targeting electricity production, which is the primary use of coal. While we recognize that coal emissions must be phased out globally, we believe U.S. leadership is essential. A major challenge for reducing U.S. emissions is that coal provides the largest proportion of base load power, i.e., power satisfying minimum electricity demand. Because this demand is relatively constant and coal has a high carbon intensity, utility carbon emissions are largely due to coal. The current U.S. electric grid incorporates little renewable power, most of which is not base load power. However, this can readily be changed within the next 2-3 decades. Eliminating coal emissions also requires improved efficiency, a "smart grid", additional energy storage, and advanced nuclear power. Any further coal usage must be accompanied by carbon capture and storage (CCS). We suggest that near-term emphasis should be on efficiency measures and substitution of coal-fired power by renewables and third-generation nuclear plants, since these technologies have been successfully demonstrated at the relevant (commercial) scale. Beyond 2030, these measures can be supplemented by CCS at power plants and, as needed, successfully demonstrated fourth-generation reactors. We conclude that U.S. coal emissions could be phased out by 2030 using existing technologies or ones that could be commercially competitive with coal within about a decade. Elimination of fossil fuel subsidies and a substantial rising price on carbon emissions are the root requirements for a clean, emissions-free future.

Hybrid power system intelligent operation and protection involving distributed architectures and pulsed loads

NASA Astrophysics Data System (ADS)

Mohamed, Ahmed

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system's dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.

Flexible Demand Management under Time-Varying Prices

NASA Astrophysics Data System (ADS)

Liang, Yong

In this dissertation, the problem of flexible demand management under time-varying prices is studied. This generic problem has many applications, which usually have multiple periods in which decisions on satisfying demand need to be made, and prices in these periods are time-varying. Examples of such applications include multi-period procurement problem, operating room scheduling, and user-end demand scheduling in the Smart Grid, where the last application is used as the main motivating story throughout the dissertation. The current grid is experiencing an upgrade with lots of new designs. What is of particular interest is the idea of passing time-varying prices that reflect electricity market conditions to end users as incentives for load shifting. One key component, consequently, is the demand management system at the user-end. The objective of the system is to find the optimal trade-off between cost saving and discomfort increment resulted from load shifting. In this dissertation, we approach this problem from the following aspects: (1) construct a generic model, solve for Pareto optimal solutions, and analyze the robust solution that optimizes the worst-case payoffs, (2) extend to a distribution-free model for multiple types of demand (appliances), for which an approximate dynamic programming (ADP) approach is developed, and (3) design other efficient algorithms for practical purposes of the flexible demand management system. We first construct a novel multi-objective flexible demand management model, in which there are a finite number of periods with time-varying prices, and demand arrives in each period. In each period, the decision maker chooses to either satisfy or defer outstanding demand to minimize costs and discomfort over a certain number of periods. We consider both the deterministic model, models with stochastic demand or prices, and when only partial information about the stochastic demand or prices is known. We first analyze the stochastic optimization problem when the objective is to minimize the expected total cost and discomfort, then since the decision maker is likely to be risk-averse, and she wants to protect herself from price spikes, we study the robust optimization problem to address the risk-aversion of the decision maker. We conduct numerical studies to evaluate the price of robustness. Next, we present a detailed model that manages multiple types of flexible demand in the absence of knowledge regarding the distributions of related stochastic processes. Specifically, we consider the case in which time-varying prices with general structures are offered to users, and an energy management system for each household makes optimal energy usage, storage, and trading decisions according to the preferences of users. Because of the uncertainties associated with electricity prices, local generation, and the arrival processes of demand, we formulate a stochastic dynamic programming model, and outline a novel and tractable ADP approach to overcome the curses of dimensionality. Then, we perform numerical studies, whose results demonstrate the effectiveness of the ADP approach. At last, we propose another approximation approach based on Q-learning. In addition, we also develop another decentralization-based heuristic. Both the Q-learning approach and the heuristic make necessary assumptions on the knowledge of information, and each of them has unique advantages. We conduct numerical studies on a testing problem. The simulation results show that both the Q-learning and the decentralization based heuristic approaches work well. Lastly, we conclude the paper with some discussions on future extension directions.

Drawer compacted sand filter: a new and innovative method for on-site grey water treatment.

PubMed

Assayed, Almoayied; Chenoweth, Jonathan; Pedley, Steven

2014-01-01

In this paper, results ofa new sand filter design were presented. The drawer compacted sand filter (DCSF) is a modified design for a sand filter in which the sand layer is broken down into several layers, each of which is 10 cm high and placed in a movable drawer separated by a 10 cm space. A lab-scale DCSF was designed and operated for 330 days fed by synthetic grey water. The response of drawer sand filters to variable hydraulic and organic loading rates (HLR and OLR) in terms of biological oxygen demand (BODs), chemical oxygen demand (COD), total suspended solids (TSS), pH, electrical conductivity and Escherichia coli reductions were evaluated. The HLR was studied by increasing from 72 to 142 L m(-2) day(-1) and OLR was studied by increasing it from 23 to 30 g BOD5 m(-2) day(-1) while keeping the HLR constant at 142 L m(-2) day(-1). Each loading regime was applied for 110 days. Results showed that DCSF was able to remove >90% of organic matter and total suspended solids for all doses. No significant difference was noticed in terms of overall filter efficiency between different loads for all parameters. Significant reduction in BOD5 and COD (P < .05) was noticed after water was drained through the third drawer in all tested loads. The paper concludes that DCSF would be appropriate for use in dense urban areas as its footprint is small and is appropriate for a wide range of users because of its convenience and low maintenance requirements.

Automated Demand Response for Energy Sustainability

DTIC Science & Technology

2015-05-01

project’s stated performance objectives. Emerging opportunities to participate in wholesale electricity markets can provide important economic, energy, and...Response in Wholesale Electricity Markets ..................................................... 7 Figure 5. Demand Bidding Communication and Control...resource in response to market or reliability conditions Demand Bidding Program DR programs that encourage customers to bid into an electricity market

The Effect of Temperature on the Electricity Demand: An Empirical Investigation

NASA Astrophysics Data System (ADS)

Kim, H.; Kim, I. G.; Park, K. J.; Yoo, S. H.

2015-12-01

This paper attempts to estimate the electricity demand function in Korea with quarterly data of average temperature, GDP and electricity price over the period 2005-2013. We apply lagged dependent variable model and ordinary least square method as a robust approach to estimating the parameters of the electricity demand function. The results show that short-run price and income elasticities of the electricity demand are estimated to be -0.569 and 0.631 respectively. They are statistically significant at the 1% level. Moreover, long-run income and price elasticities are estimated to be 1.589 and -1.433 respectively. Both of results reveal that the demand for electricity demand is about 15.2℃. It is shown that power of explanation and goodness-of-fit statistics are improved in the use of the lagged dependent variable model rather than conventional model. Acknowledgements: This research was carried out as a part of "Development and application of technology for weather forecast" supported by the 2015 National Institute of Meteorological Research (NIMR) in the Korea Meteorological Administration.

Developement of watershed and reference loads for a TMDL in Charleston Harbor System, SC.

Treesearch

Silong Lu; Devenra Amatya; Jamie Miller

2005-01-01

It is essential to determine point and non-point source loads and their distribution for development of a dissolved oxygen (DO) Total Maximum Daily Load (TMDL). A series of models were developed to assess sources of oxygen-demand loadings in Charleston Harbor, South Carolina. These oxygen-demand loadings included nutrients and BOD. Stream flow and nutrient...

Improving flexibility characteristics of 200 MW unit

NASA Astrophysics Data System (ADS)

Taler, Jan; Trojan, Marcin; Taler, Dawid; Dzierwa, Piotr; Kaczmarski, Karol

2017-03-01

Calculations were performed of the thermal system of a power plant with installed water pressure tanks. The maximum rise in the block electric power resulting from the shut-off of low-pressure regenerative heaters is determined. At that time, the boiler is fed with hot water from water pressure tanks acting as heat accumulators. Accumulation of hot water in water tanks is also proposed in the periods of the power unit small load. In order to lower the plant electric power in the off-peak night hours, water heated in low-pressure regenerative heaters and feed water tank to the nominal temperature is directed to water pressure tanks. The water accumulated during the night is used to feed the boiler during the period of peak demand for electricity. Drops in the power block electric power were determined for different capacities of the tanks and periods when they are charged. A financial and economic profitability analysis (of costs and benefits) is made of the use of tanks for a 200 MW power unit. Operating in the automatic system of frequency and power control, the tanks may also be used to ensure a sudden increase in the electric power of the unit. The results of the performed calculations and analyses indicate that installation of water pressure tanks is well justified. The investment is profitable. Water pressure tanks may not only be used to reduce the power unit power during the off-peak night hours and raise it in the periods of peak demand, but also to increase the power capacity fast at any time. They may also be used to fill the boiler evaporator with hot water during the power unit start-up from the cold state.

Electric energy demand and supply prospects for California

NASA Technical Reports Server (NTRS)

Jones, H. G. M.

1978-01-01

A recent history of electricity forecasting in California is given. Dealing with forecasts and regulatory uncertainty is discussed. Graphs are presented for: (1) Los Angeles Department of Water and Power and Pacific Gas and Electric present and projected reserve margins; (2) California electricity peak demand forecast; and (3) California electricity production.

The dynamic simulation of the Progetto Energia combined cycle power plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giglio, R.; Cerabolini, M.; Pisacane, F.

1996-12-31

Over the next four years, the Progetto Energia project is building several cogeneration plants to satisfy the increasing demands of Italy`s industrial complex and the country`s demand for electrical power. Located at six different sites within Italy`s borders these Combined Cycle Cogeneration Plants will supply a total of 500 MW of electricity and 100 tons/hr of process steam to Italian industries and residences. To ensure project success, a dynamic model of the 50 MW base unit was developed. The goal established for the model was to predict the dynamic behavior of the complex thermodynamic system in order to assess equipmentmore » performance and control system effectiveness for normal operation and, more importantly, abrupt load changes. In addition to fulfilling its goals, the dynamic study guided modifications to controller logic that significantly improved steam drum pressure control and bypassed steam de-superheating performance. Simulations of normal and abrupt transient events allowed engineers to define optimum controller gain coefficients. The paper discusses the Combined Cycle plant configuration, its operating modes and control system, the dynamic model representation, the simulation results and project benefits.« less

Thermal Profiling of Residential Energy Use

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albert, A; Rajagopal, R

This work describes a methodology for informing targeted demand-response (DR) and marketing programs that focus on the temperature-sensitive part of residential electricity demand. Our methodology uses data that is becoming readily available at utility companies-hourly energy consumption readings collected from "smart" electricity meters, as well as hourly temperature readings. To decompose individual consumption into a thermal-sensitive part and a base load (non-thermally-sensitive), we propose a model of temperature response that is based on thermal regimes, i.e., unobserved decisions of consumers to use their heating or cooling appliances. We use this model to extract useful benchmarks that compose thermal profiles ofmore » individual users, i.e., terse characterizations of the statistics of these users' temperature-sensitive consumption. We present example profiles generated using our model on real consumers, and show its performance on a large sample of residential users. This knowledge may, in turn, inform the DR program by allowing scarce operational and marketing budgets to be spent on the right users-those whose influencing will yield highest energy reductions-at the right time. We show that such segmentation and targeting of users may offer savings exceeding 100% of a random strategy.« less

Lead-free bearing alloys for engine applications

NASA Astrophysics Data System (ADS)

Ratke, Lorenz; Ågren, John; Ludwig, Andreas; Tonn, Babette; Gránásy, László; Mathiesen, Ragnvald; Arnberg, Lars; Anger, Gerd; Reifenhäuser, Bernd; Lauer, Michael; Garen, Rune; Gust, Edgar

2005-10-01

Recent developments to reduce the fuel consumption, emission and air pollution, size and weight of engines for automotive, truck, ship propulsion and electrical power generation lead to temperature and load conditions within the engines that cannot be borne by conventional bearings. Presently, only costly multilayer bearings with electroplated or sputtered surface coatings can cope with the load/speed combinations required. Ecological considerations in recent years led to a ban by the European Commission on the use of lead in cars a problem for the standard bronze-lead bearing material. This MAP project is therefore developing an aluminium-based lead-free bearing material with sufficient hardness, wear and friction properties and good corrosion resistance. Only alloys made of components immiscible in the molten state can meet the demanding requirements. Space experimentation plays a crucial role in optimising the cast microstructure for such applications.

Optimization of enhanced bioelectrical reactor with electricity from microbial fuel cells for groundwater nitrate removal.

PubMed

Liu, Ye; Zhang, Baogang; Tian, Caixing; Feng, Chuanping; Wang, Zhijun; Cheng, Ming; Hu, Weiwu

2016-01-01

Factors influencing the performance of a continual-flow bioelectrical reactor (BER) intensified by microbial fuel cells for groundwater nitrate removal, including nitrate load, carbon source and hydraulic retention time (HRT), were investigated and optimized by response surface methodology (RSM). With the target of maximum nitrate removal and minimum intermediates accumulation, nitrate load (for nitrogen) of 60.70 mg/L, chemical oxygen demand (COD) of 849.55 mg/L and HRT of 3.92 h for the BER were performed. COD was the dominant factor influencing performance of the system. Experimental results indicated the undistorted simulation and reliable optimized values. These demonstrate that RSM is an effective method to evaluate and optimize the nitrate-reducing performance of the present system and can guide mathematical models development to further promote its practical applications.

Experiences in solar cooling systems

NASA Astrophysics Data System (ADS)

Ward, D. S.

The results of performance evaluations for nine solar cooling systems are presented, and reasons fow low or high net energy balances are discussed. Six of the nine systems are noted to have performed unfavorably compared to standard cooling systems due to thermal storage losses, excessive system electrical demands, inappropriate control strategies, poor system-to-load matching, and poor chiller performance. A reduction in heat losses in one residential unit increased the total system efficiency by 2.5%, while eliminating heat losses to the building interior increased the efficiency by 3.3%. The best system incorporated a lithium bromide absorption chiller and a Rankine cycle compression unit for a commercial application. Improvements in the cooling tower and fan configurations to increase the solar cooling system efficiency are indicated. Best performances are expected to occur in climates inducing high annual cooling loads.

Dispatchable hydrogen production at the forecourt for electricity grid balancing

NASA Astrophysics Data System (ADS)

Rahil, Abdulla; Gammon, Rupert; Brown, Neil

2017-02-01

The rapid growth of renewable energy (RE) generation and its integration into electricity grids has been motivated by environmental issues and the depletion of fossil fuels. For the same reasons, an alternative to hydrocarbon fuels is needed for vehicles; hence the anticipated uptake of electric and fuel cell vehicles. High penetrations of RE generators with variable and intermittent output threaten to destabilise electricity networks by reducing the ability to balance electricity supply and demand. This can be greatly mitigated by the use of energy storage and demand-side response (DSR) techniques. Hydrogen production by electrolysis is a promising option for providing DSR as well as an emission-free vehicle fuel. Tariff structures can be used to incentivise the operating of electrolysers as controllable (dispatchable) loads. This paper compares the cost of hydrogen production by electrolysis at garage forecourts under both dispatchable and continuous operation, while ensuring no interruption of fuel supply to fuel cell vehicles. An optimisation algorithm is applied to investigate a hydrogen refueling station in both dispatchable and continuous operation. Three scenarios are tested to see whether a reduced off-peak electricity price could lower the cost of electrolytic hydrogen. These scenarios are: 1) "Standard Continuous", where the electrolyser is operated continuously on a standard all-day tariff of 12p/kWh; 2) "Off-peak Only", where it runs only during off-peak periods in a 2-tier tariff system at the lower price of 5p/kWh; and 3) "2-Tier Continuous", operating continuously and paying a low tariff at off- peak times and a high tariff at other times. This study uses the Libyan coastal city of Derna as a case study. The cheapest electricity cost per kg of hydrogen produced was £2.8, which occurred in Scenario 2. The next cheapest, at £5.8 - £6.3, was in Scenario 3, and the most expensive was £6.8/kg in Scenario 1.

The Use of Artificial Neural Networks for Forecasting the Electric Demand of Stand-Alone Consumers

NASA Astrophysics Data System (ADS)

Ivanin, O. A.; Direktor, L. B.

2018-05-01

The problem of short-term forecasting of electric power demand of stand-alone consumers (small inhabited localities) situated outside centralized power supply areas is considered. The basic approaches to modeling the electric power demand depending on the forecasting time frame and the problems set, as well as the specific features of such modeling, are described. The advantages and disadvantages of the methods used for the short-term forecast of the electric demand are indicated, and difficulties involved in the solution of the problem are outlined. The basic principles of arranging artificial neural networks are set forth; it is also shown that the proposed method is preferable when the input information necessary for prediction is lacking or incomplete. The selection of the parameters that should be included into the list of the input data for modeling the electric power demand of residential areas using artificial neural networks is validated. The structure of a neural network is proposed for solving the problem of modeling the electric power demand of residential areas. The specific features of generation of the training dataset are outlined. The results of test modeling of daily electric demand curves for some settlements of Kamchatka and Yakutia based on known actual electric demand curves are provided. The reliability of the test modeling has been validated. A high value of the deviation of the modeled curve from the reference curve obtained in one of the four reference calculations is explained. The input data and the predicted power demand curves for the rural settlement of Kuokuiskii Nasleg are provided. The power demand curves were modeled for four characteristic days of the year, and they can be used in the future for designing a power supply system for the settlement. To enhance the accuracy of the method, a series of measures based on specific features of a neural network's functioning are proposed.

Analysis of recent projections of electric power demand

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hudson, Jr, D V

1993-08-01

This report reviews the changes and potential changes in the outlook for electric power demand since the publication of Review and Analysis of Electricity Supply Market Projections (B. Swezey, SERI/MR-360-3322, National Renewable Energy Laboratory). Forecasts of the following organizations were reviewed: DOE/Energy Information Administration, DOE/Policy Office, DRI/McGraw-Hill, North American Electric Reliability Council, and Gas Research Institute. Supply uncertainty was briefly reviewed to place the uncertainties of the demand outlook in perspective. Also discussed were opportunities for modular technologies, such as renewable energy technologies, to fill a potential gap in energy demand and supply.

The Influence of Load and Speed on Individuals' Movement Behavior.

PubMed

Frost, David M; Beach, Tyson A C; Callaghan, Jack P; McGill, Stuart M

2015-09-01

Because individuals' movement patterns have been linked to their risk of future injury, movement evaluations have become a topic of interest. However, if individuals adapt their movement behavior in response to the demands of a task, the utility of evaluations comprising only low-demand activities could have limited application with regard to the prediction of future injury. This investigation examined the impact of load and speed on individuals' movement behavior. Fifty-two firefighters performed 5 low-demand (i.e., light load, low movement speed) whole-body tasks (i.e., lift, squat, lunge, push, and pull). Each task was then modified by increasing the speed, external load, or speed and load. Select measures of motion were used to characterize the performance of each task, and comparisons were made between conditions. The participants adapted their movement behavior in response to the external demands of a task (64 and 70% of all the variables were influenced [p ≤ 0.05] by changing the load and speed, respectively), but in a manner unique to the task and type of demand. The participants exhibited greater spine and frontal plane knee motion in response to an increase in speed when compared with increasing loads. However, there were a large number of movement strategies exhibited by individual firefighters that differed from the group's response. The data obtained here imply that individuals may not be physically prepared to perform safely or effectively when a task's demands are elevated simply because they exhibit the ability to perform a low-demand activity with competence. Therefore, movement screens comprising only low-demand activities may not adequately reflect an individual's capacity, or their risk of injury, and could adversely affect any recommendations that are made for training or job performance.

An expert system for simulating electric loads aboard Space Station Freedom

NASA Technical Reports Server (NTRS)

Kukich, George; Dolce, James L.

1990-01-01

Space Station Freedom will provide an infrastructure for space experimentation. This environment will feature regulated access to any resources required by an experiment. Automated systems are being developed to manage the electric power so that researchers can have the flexibility to modify their experiment plan for contingencies or for new opportunities. To define these flexible power management characteristics for Space Station Freedom, a simulation is required that captures the dynamic nature of space experimentation; namely, an investigator is allowed to restructure his experiment and to modify its execution. This changes the energy demands for the investigator's range of options. An expert system competent in the domain of cryogenic fluid management experimentation was developed. It will be used to help design and test automated power scheduling software for Freedom's electric power system. The expert system allows experiment planning and experiment simulation. The former evaluates experimental alternatives and offers advice on the details of the experiment's design. The latter provides a real-time simulation of the experiment replete with appropriate resource consumption.

Integrating Demand-Side Resources into the Electric Grid: Economic and Environmental Considerations

NASA Astrophysics Data System (ADS)

Fisher, Michael J.

Demand-side resources are taking an increasingly prominent role in providing essential grid services once provided by thermal power plants. This thesis considers the economic feasibility and environmental effects of integrating demand-side resources into the electric grid with consideration given to the diversity of market and environmental conditions that can affect their behavior. Chapter 2 explores the private economics and system-level carbon dioxide reduction when using demand response for spinning reserve. Steady end uses like lighting are more than twice as profitable as seasonal end uses because spinning reserve is needed year-round. Avoided carbon emission damages from using demand response instead of fossil fuel generation for spinning reserve are sufficient to justify incentives for demand response resources. Chapter 3 quantifies the system-level net emissions rate and private economics of behind-the-meter energy storage. Net emission rates are lower than marginal emission rates for power plants and in-line with estimates of net emission rates from grid-level storage. The economics are favorable for many buildings in regions with high demand charges like California and New York, even without subsidies. Future penetration into regions with average charges like Pennsylvania will depend greatly on installation cost reductions and wholesale prices for ancillary services. Chapter 4 outlines a novel econometric model to quantify potential revenues from energy storage that reduces demand charges. The model is based on a novel predictive metric that is derived from the building's load profile. Normalized revenue estimates are independent of the power capacity of the battery holding other performance characteristics equal, which can be used to calculate the profit-maximizing storage size. Chapter 5 analyzes the economic feasibility of flow batteries in the commercial and industrial market. Flow batteries at a 4-hour duration must be less expensive on a dollar per installed kWh basis, often by 20-30%, to break even with shorter duration li-ion or lead-acid despite allowing for deeper depth of discharge and superior cycle life. These results are robust to assumptions of tariff rates, battery round-trip efficiencies, amount of solar generation and whether the battery can participate in the wholesale energy and ancillary services markets.

Impact of Uncoordinated Plug-in Electric Vehicle Charging on Residential Power Demand

DOE Office of Scientific and Technical Information (OSTI.GOV)

Muratori, Matteo

Electrification of transport offers opportunities to increase energy security, reduce carbon emissions, and improve local air quality. Plug-in electric vehicles (PEVs) are creating new connections between the transportation and electric sectors, and PEV charging will create opportunities and challenges in a system of growing complexity. Here, I use highly resolved models of residential power demand and PEV use to assess the impact of uncoordinated in-home PEV charging on residential power demand. While the increase in aggregate demand might be minimal even for high levels of PEV adoption, uncoordinated PEV charging could significantly change the shape of the aggregate residential demand,more » with impacts for electricity infrastructure, even at low adoption levels. Clustering effects in vehicle adoption at the local level might lead to high PEV concentrations even if overall adoption remains low, significantly increasing peak demand and requiring upgrades to the electricity distribution infrastructure. This effect is exacerbated when adopting higher in-home power charging.« less

Impact of uncoordinated plug-in electric vehicle charging on residential power demand

NASA Astrophysics Data System (ADS)

Muratori, Matteo

2018-03-01

Electrification of transport offers opportunities to increase energy security, reduce carbon emissions, and improve local air quality. Plug-in electric vehicles (PEVs) are creating new connections between the transportation and electric sectors, and PEV charging will create opportunities and challenges in a system of growing complexity. Here, I use highly resolved models of residential power demand and PEV use to assess the impact of uncoordinated in-home PEV charging on residential power demand. While the increase in aggregate demand might be minimal even for high levels of PEV adoption, uncoordinated PEV charging could significantly change the shape of the aggregate residential demand, with impacts for electricity infrastructure, even at low adoption levels. Clustering effects in vehicle adoption at the local level might lead to high PEV concentrations even if overall adoption remains low, significantly increasing peak demand and requiring upgrades to the electricity distribution infrastructure. This effect is exacerbated when adopting higher in-home power charging.

DOD fuel cell demonstration program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holcomb, F.H.; Binder, M.J.; Taylor, W.R.

The supply of reliable, cost-effective electric power with minimal environmental impact is a constant concern of Department of Defense (DOD) installation energy personnel. Electricity purchased from the local utility is expensive and represents only about 30% of the original energy input at the generating station due to generation and distribution inefficiencies. Because of master metering and large air conditioning loads, the demand portion of the installation`s electric bill can be in excess of 50% of the total bill. While the electric utilities in the United States have a very good record of reliability, there is significant potential for improving themore » security of electrical power supplied by using on-site power generation. On-site, dispersed power generation can reduce power outages due to weather, terrorist activities, or lack of utility generating capacity. In addition, as increased emphasis is placed on global warming, acid rain, and air pollution in general, the development of clean, highly efficient power producing technologies is not only desirable, but mandatory. Since the majority of central heat plants on U.S. military installations are nearing the end of their useful life, there is an opportunity to replace outdated existing equipment with modem technologies.« less

Near-term implications of a ban on new coal-fired power plants in the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adam Newcomer; Jay Apt

2009-06-15

Large numbers of proposed new coal power generators in the United States have been cancelled, and some states have prohibited new coal power generators. We examine the effects on the U.S. electric power system of banning the construction of coal-fired electricity generators, which has been proposed as a means to reduce U.S. CO{sub 2} emissions. The model simulates load growth, resource planning, and economic dispatch of the Midwest Independent Transmission System Operator (ISO), Inc., Electric Reliability Council of Texas (ERCOT), and PJM under a ban on new coal generation and uses an economic dispatch model to calculate the resulting changesmore » in dispatch order, CO{sub 2} emissions, and fuel use under three near-term (until 2030) future electric power sector scenarios. A national ban on new coal-fired power plants does not lead to CO{sub 2} reductions of the scale required under proposed federal legislation such as Lieberman-Warner but would greatly increase the fraction of time when natural gas sets the price of electricity, even with aggressive wind and demand response policies. 50 refs., 5 figs., 4 tabs.« less

Usage monitoring of electrical devices in a smart home.

PubMed

Rahimi, Saba; Chan, Adrian D C; Goubran, Rafik A

2011-01-01

Profiling the usage of electrical devices within a smart home can be used as a method for determining an occupant's activities of daily living. A nonintrusive load monitoring system monitors the electrical consumption at a single electrical source (e.g., main electric utility service entry) and the operating schedules of individual devices are determined by disaggregating the composite electrical consumption waveforms. An electrical device's load signature plays a key role in nonintrusive load monitoring systems. A load signature is the unique electrical behaviour of an individual device when it is in operation. This paper proposes a feature-based model, using the real power and reactive power as features for describing the load signatures of individual devices. Experimental results for single device recognition for 7 devices show that the proposed approach can achieve 100% classification accuracy with discriminant analysis using Mahalanobis distances.

Energy management system saves $250,000 + fuel -with 4-mo payback

DOE Office of Scientific and Technical Information (OSTI.GOV)

Massey, C.L.; Robe, K.

1980-09-01

Innovations made at Hershey Chocolate Company's Oakdale, California plant eliminated simultaneous cool-reheat-cycles by incorporating dead band controls into existing HVAC systems. Calculated savings of the project are about 90% of former heating and cooling energy usage for HVAC operation. Electric power savings amount to about $75,000/y, and natural gas savings about $185,000/y, using 1980 fuel costs, with an approximate 4-month payback. Because of the reduced demand for chilled water, a smaller water chiller carries full plant load for 4 to 5 months of the year without operating two existing 500-ton units.

Satellite Power Systems (SPS) concept definition study, exhibit C. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

Hanley, G. M.

1979-01-01

The Department of Energy (DOE) is currently conducting an evaluation of approaches to provide energy to meet demands in the post-2000 time period. The Satellite Power System (SPS) is a candidate for producing significant quantities of base-load power using solar energy as the source. The SPS concept is illustrated for a solar photovoltaic concept. A satellite, located at geosynchronous orbit, converts solar energy to dc electrical energy using large solar arrays. This study is a continuing effort to provide system definition data to aid in the evaluation of the SPS concept.

Combined heat and power supply using Carnot engines

NASA Astrophysics Data System (ADS)

Horlock, J. H.

The Marshall Report on the thermodynamic and economic feasibility of introducing large scale combined heat and electrical power generation (CHP) into the United Kingdom is summarized. Combinations of reversible power plant (Carnot engines) to meet a given demand of power and heat production are analyzed. The Marshall Report states that fairly large scale CHP plants are an attractive energy saving option for areas of high heat load densities. Analysis shows that for given requirements, the total heat supply and utilization factor are functions of heat output, reservoir supply temperature, temperature of heat rejected to the reservoir, and an intermediate temperature for district heating.

Transmission congestion management in the electricity market

NASA Astrophysics Data System (ADS)

Chen, Yue

2018-04-01

In this paper we mainly discuss how to optimize the arrangement to decrease the loss of each line when the power generation side of the system transmission congestion occurs in a safe and economical manner. We respectively set the adjust model if the transmission can be eliminated which can calculate the best scheme and safety margin model when transmission cannot be eliminated which is a multi-objective planning problem. We solve the two models on the condition of the load power demands are 982.4MW and 1052.8 MW by Lingo and get the optimal management scheme.

Solar water heater for NASA's Space Station

NASA Technical Reports Server (NTRS)

Somers, Richard E.; Haynes, R. Daniel

1988-01-01

The feasibility of using a solar water heater for NASA's Space Station is investigated using computer codes developed to model the Space Station configuration, orbit, and heating systems. Numerous orbit variations, system options, and geometries for the collector were analyzed. Results show that a solar water heater, which would provide 100 percent of the design heating load and would not impose a significant impact on the Space Station overall design is feasible. A heat pipe or pumped fluid radial plate collector of about 10-sq m, placed on top of the habitat module was found to be well suited for satisfying water demand of the Space Station. Due to the relatively small area required by a radial plate, a concentrator is unnecessary. The system would use only 7 to 10 percent as much electricity as an electric water-heating system.

Design of a high voltage input - output ratio dc-dc converter dedicated to small power fuel cell systems

NASA Astrophysics Data System (ADS)

Béthoux, O.; Cathelin, J.

2010-12-01

Consuming chemical energy, fuel cells produce simultaneously heat, water and useful electrical power [J.M. Andújar, F. Segura, Renew. Sust. Energy Rev. 13, 2309 (2009)], [J. Larminie, A. Dicks, Fuel Cell Systems Explained, 2nd edn. (John Wiley & Sons, 2003)]. As a matter of fact, the voltage generated by a fuel cell strongly depends on both the load power demand and the operating conditions. Besides, as a result of many design aspects, fuel cells are low voltage and high current electric generators. On the contrary, electric loads are commonly designed for small voltage swing and a high V/I ratio in order to minimize Joule losses. Therefore, electric loads supplied by fuel cells are typically fed by means of an intermediate power voltage regulator. The specifications of such a power converter are to be able to step up the input voltage with a high ratio (a ratio of 10 is a classic situation) and also to work with an excellent efficiency (in order to minimize its size, its weight and its losses) [A. Shahin, B. Huang, J.P. Martin, S. Pierfederici, B. Davat, Energy Conv. Manag. 51, 56 (2010)]. This paper deals with the design of this essential ancillary device. It intends to bring out the best structure for fulfilling this function. Several dc-dc converters with large voltage step-up ratios are introduced. A topology based on a coupled inductor or tapped inductor is closely studied. A detailed modelling is performed with the purpose of providing designing rules. This model is validated with both simulation and implementation. The experimental prototype is based on the following specifications: the fuel cell output voltage ranges from a 50 V open-voltage to a 25 V rated voltage while the load requires a constant 250 V voltage. The studied coupled inductor converter is compared with a classic boost converter commonly used in this voltage elevating application. Even though the voltage regulator faces severe FC specifications, the measured efficiency reaches 96% at the rated power whereas conventional boost efficiency barely achieves 91.5% in the same operating conditions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Melton, Ron

The Pacific Northwest Smart Grid Demonstration (PNWSGD), a $179 million project that was co-funded by the U.S. Department of Energy (DOE) in late 2009, was one of the largest and most comprehensive demonstrations of electricity grid modernization ever completed. The project was one of 16 regional smart grid demonstrations funded by the American Recovery and Reinvestment Act. It was the only demonstration that included multiple states and cooperation from multiple electric utilities, including rural electric co-ops, investor-owned, municipal, and other public utilities. No fewer than 55 unique instantiations of distinct smart grid systems were demonstrated at the projects’ sites. Themore » local objectives for these systems included improved reliability, energy conservation, improved efficiency, and demand responsiveness. The demonstration developed and deployed an innovative transactive system, unique in the world, that coordinated many of the project’s distributed energy resources and demand-responsive components. With the transactive system, additional regional objectives were also addressed, including the mitigation of renewable energy intermittency and the flattening of system load. Using the transactive system, the project coordinated a regional response across the 11 utilities. This region-wide connection from the transmission system down to individual premises equipment was one of the major successes of the project. The project showed that this can be done and assets at the end points can respond dynamically on a wide scale. In principle, a transactive system of this type might eventually help coordinate electricity supply, transmission, distribution, and end uses by distributing mostly automated control responsibilities among the many distributed smart grid domain members and their smart devices.« less

Using Seasonal Forecasts for medium-term Electricity Demand Forecasting on Italy

NASA Astrophysics Data System (ADS)

De Felice, M.; Alessandri, A.; Ruti, P.

2012-12-01

Electricity demand forecast is an essential tool for energy management and operation scheduling for electric utilities. In power engineering, medium-term forecasting is defined as the prediction up to 12 months ahead, and commonly is performed considering weather climatology and not actual forecasts. This work aims to analyze the predictability of electricity demand on seasonal time scale, considering seasonal samples, i.e. average on three months. Electricity demand data has been provided by Italian Transmission System Operator for eight different geographical areas, in Fig. 1 for each area is shown the average yearly demand anomaly for each season. This work uses data for each summer during 1990-2010 and all the datasets have been pre-processed to remove trends and reduce the influence of calendar and economic effects. The choice of focusing this research on the summer period is due to the critical peaks of demand that power grid is subject during hot days. Weather data have been included considering observations provided by ECMWF ERA-INTERIM reanalyses. Primitive variables (2-metres temperature, pressure, etc) and derived variables (cooling and heating degree days) have been averaged for summer months. A particular attention has been given to the influence of persistence of positive temperature anomaly and a derived variable which count the number of consecutive days of extreme-days has been used. Electricity demand forecast has been performed using linear and nonlinear regression methods and stepwise model selection procedures have been used to perform a variable selection with respect to performance measures. Significance tests on multiple linear regression showed the importance of cooling degree days during summer in the North-East and South of Italy with an increase of statistical significance after 2003, a result consistent with the diffusion of air condition and ventilation equipment in the last decade. Finally, using seasonal climate forecasts we evaluate the performances of electricity demand forecast performed with predicted variables on Italian regions with encouraging results on the South of Italy. This work gives an initial assessment on the predictability of electricity demand on seasonal time scale, evaluating the relevance of climate information provided by seasonal forecasts for electricity management during high-demand periods.;

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blair, Jeff L.; Glenn, Lee J.

The Smart Grid opens the door to the development of many companion technologies which will in turn enable the development of a variety of devices for household electricity-consuming appliances that can communicate with it; especially, many major appliance manufacturers (such as Whirlpool and General Electric) have made public commitments to design their appliances to be Smart Grid-compatible over the next several years. Yet during that same time period, customers will purchase many millions of long-lasting appliances which are not compatible with the Smart Grid. This research project's purpose is to bring significant Smart Grid compatibility to previously-installed appliances that weremore » not specifically designed for any Smart Grid communications, in a way that is both economical and attractive for users who want to share in the energy cost savings and reduction of peak power demand opportunities provided by the evolving Smart Grid infrastructure. The focus of this effort is to identify and research smart control solutions which take advantage of the effective strategies of demand-response (DR) communications from utilities [including time-of-day (TOD) and peak-demand pricing options] and function apart from any need for operational changes to be designed into the non-smart appliances. Our Phase I concepts promote technological advancements for enabling devices that shift the available-use time of millions of different appliances which otherwise have no Smart Grid capability. We researched low-cost microcontroller-based ways of creating devices with the ability to: (1) maintain an accurate time and day (with no need for battery backup throughout a power outage); (2) perform two-way wired and wireless communications directly with the utility company's demand management signals, to identify both low-cost time periods as well as critical-reduction periods when the cost of energy use would otherwise be much higher; (3) measure the power usage of the connected non-smart appliance; and (4) remove power for a period of time from the appliance (such as a dehumidifier, portable heater, or pool pump) in response to both time-pricing schedule and critical peak-load information from the utility, or inform the user of a batch-type appliance (such as a clothes dryer or dishwasher) regarding the current cost associated with using the appliance. The new products that could be developed as a result of this research into new consumer-centric features and characteristics includes smart wall outlets, smart outlet power-monitoring adapters, smart load switches and smart remote electric rate indicators associated with the non-smart appliances. Our Phase I goal of determining the feasibility of the above technologies was successful. The objectives were also met of developing concepts for a family of microprocessor-based control/indicator devices that can provide the above capabilities while connected in series between an appliance and its electrical power source and/or while indicating cost-of-use status to the appliance user.« less

Stability analysis of electrical powered wheelchair-mounted robotic-assisted transfer device.

PubMed

Wang, Hongwu; Tsai, Chung-Ying; Jeannis, Hervens; Chung, Cheng-Shiu; Kelleher, Annmarie; Grindle, Garrett G; Cooper, Rory A

2014-01-01

The ability of people with disabilities to live in their homes and communities with maximal independence often hinges, at least in part, on their ability to transfer or be transferred by an assistant. Because of limited resources and the expense of personal care, robotic transfer assistance devices will likely be in great demand. An easy-to-use system for assisting with transfers, attachable to electrical powered wheelchairs (EPWs) and readily transportable, could have a significant positive effect on the quality of life of people with disabilities. We investigated the stability of our newly developed Strong Arm, which is attached and integrated with an EPW to assist with transfers. The stability of the system was analyzed and verified by experiments applying different loads and using different system configurations. The model predicted the distributions of the system's center of mass very well compared with the experimental results. When real transfers were conducted with 50 and 75 kg loads and an 83.25 kg dummy, the current Strong Arm could transfer all weights safely without tip-over. Our modeling accurately predicts the stability of the system and is suitable for developing better control algorithms to enhance the safety of the device.

CELCAP: A Computer Model for Cogeneration System Analysis

NASA Technical Reports Server (NTRS)

1985-01-01

A description of the CELCAP cogeneration analysis program is presented. A detailed description of the methodology used by the Naval Civil Engineering Laboratory in developing the CELCAP code and the procedures for analyzing cogeneration systems for a given user are given. The four engines modeled in CELCAP are: gas turbine with exhaust heat boiler, diesel engine with waste heat boiler, single automatic-extraction steam turbine, and back-pressure steam turbine. Both the design point and part-load performances are taken into account in the engine models. The load model describes how the hourly electric and steam demand of the user is represented by 24 hourly profiles. The economic model describes how the annual and life-cycle operating costs that include the costs of fuel, purchased electricity, and operation and maintenance of engines and boilers are calculated. The CELCAP code structure and principal functions of the code are described to how the various components of the code are related to each other. Three examples of the application of the CELCAP code are given to illustrate the versatility of the code. The examples shown represent cases of system selection, system modification, and system optimization.

Integrated topology for an aircraft electric power distribution system using MATLAB and ILP optimization technique and its implementation

NASA Astrophysics Data System (ADS)

Madhikar, Pratik Ravindra

The most important and crucial design feature while designing an Aircraft Electric Power Distribution System (EPDS) is reliability. In EPDS, the distribution of power is from top level generators to bottom level loads through various sensors, actuators and rectifiers with the help of AC & DC buses and control switches. As the demands of the consumer is never ending and the safety is utmost important, there is an increase in loads and as a result increase in power management. Therefore, the design of an EPDS should be optimized to have maximum efficiency. This thesis discusses an integrated tool that is based on a Need Based Design method and Fault Tree Analysis (FTA) to achieve the optimum design of an EPDS to provide maximum reliability in terms of continuous connectivity, power management and minimum cost. If an EPDS is formulated as an optimization problem then it can be solved with the help of connectivity, cost and power constraints by using a linear solver to get the desired output of maximum reliability at minimum cost. Furthermore, the thesis also discusses the viability and implementation of the resulted topology on typical large aircraft specifications.

Modeling of Electric Demand for Sustainable Energy and Management in India Using Spatio-Temporal DMSP-OLS Night-Time Data.

PubMed

Tripathy, Bismay Ranjan; Sajjad, Haroon; Elvidge, Christopher D; Ting, Yu; Pandey, Prem Chandra; Rani, Meenu; Kumar, Pavan

2018-04-01

Changes in the pattern of electric power consumption in India have influenced energy utilization processes and socio-economic development to greater extent during the last few decades. Assessment of spatial distribution of electricity consumption is, thus, essential for projecting availability of energy resource and planning its infrastructure. This paper makes an attempt to model the future electricity demand for sustainable energy and its management in India. The nighttime light database provides a good approximation of availability of energy. We utilized defense meteorological satellite program-operational line-scan system (DMSP-OLS) nighttime satellite data, electricity consumption (1993-2013), gross domestic product (GDP) and population growth to construct the model. We also attempted to examine the sensitiveness of electricity consumption to GDP and population growth. The results revealed that the calibrated DMSP and model has provided realistic information on the electric demand with respect to GDP and population, with a better accuracy of r 2  = 0.91. The electric demand was found to be more sensitive to GDP (r = 0.96) than population growth (r = 0.76) as envisaged through correlation analysis. Hence, the model proved to be useful tool in predicting electric demand for its sustainable use and management.

Modeling of Electric Demand for Sustainable Energy and Management in India Using Spatio-Temporal DMSP-OLS Night-Time Data

NASA Astrophysics Data System (ADS)

Tripathy, Bismay Ranjan; Sajjad, Haroon; Elvidge, Christopher D.; Ting, Yu; Pandey, Prem Chandra; Rani, Meenu; Kumar, Pavan

2018-04-01

Changes in the pattern of electric power consumption in India have influenced energy utilization processes and socio-economic development to greater extent during the last few decades. Assessment of spatial distribution of electricity consumption is, thus, essential for projecting availability of energy resource and planning its infrastructure. This paper makes an attempt to model the future electricity demand for sustainable energy and its management in India. The nighttime light database provides a good approximation of availability of energy. We utilized defense meteorological satellite program-operational line-scan system (DMSP-OLS) nighttime satellite data, electricity consumption (1993-2013), gross domestic product (GDP) and population growth to construct the model. We also attempted to examine the sensitiveness of electricity consumption to GDP and population growth. The results revealed that the calibrated DMSP and model has provided realistic information on the electric demand with respect to GDP and population, with a better accuracy of r 2 = 0.91. The electric demand was found to be more sensitive to GDP ( r = 0.96) than population growth ( r = 0.76) as envisaged through correlation analysis. Hence, the model proved to be useful tool in predicting electric demand for its sustainable use and management.

Increased Coal Plant Flexibility Can Improve Renewables Integration |

Science.gov Websites

practices that enable lower turndowns, faster starts and stops, and faster ramping between load set-points faster ramp rates and faster and less expensive starts. Flexible Load - Demand Response Resources Demand response (DR) is a load management practice of deliberately reducing or adding load to balance the system

Practical Methods for the Analysis of Voltage Collapse in Electric Power Systems: a Stationary Bifurcations Viewpoint.

NASA Astrophysics Data System (ADS)

Jean-Jumeau, Rene

1993-03-01

Voltage collapse (VC) is generally caused by either of two types of system disturbances: load variations and contingencies. In this thesis, we study VC resulting from load variations. This is termed static voltage collapse. This thesis deals with this type of voltage collapse in electrical power systems by using a stationary bifurcations viewpoint by associating it with the occurrence of saddle node bifurcations (SNB) in the system. Approximate models are generically used in most VC analyses. We consider the validity of these models for the study of SNB and, thus, of voltage collapse. We justify the use of saddle node bifurcation as a model for VC in power systems. In particular, we prove that this leads to definition of a model and--since load demand is used as a parameter for that model--of a mode of parameterization of that model in order to represent actual power demand variations within the power system network. Ill-conditioning of the set of nonlinear equations defining a dynamical system is a generic occurence near the SNB point. We suggest a reparameterization of the set of nonlinear equations which allows to avoid this problem. A new indicator for the proximity of voltage collapse, the voltage collapse index (VCI), is developed. A new (n + 1)-dimensional set of characteristic equations for the computation of the exact SNB point, replacing the standard (2n + 1)-dimensional one is presented for general parameter -dependent nonlinear dynamical systems. These results are then applied to electric power systems for the analysis and prediction of voltage collapse. The new methods offer the potential of faster computation and greater flexibility. For reasons of theoretical development and clarity, the preceding methodologies are developed under the assumption of the absence of constraints on the system parameters and states, and the full differentiability of the functions defining the power system model. In the latter part of this thesis, we relax these assumptions in order to develop a framework and new formulation for application of the tools previously developed for the analysis and prediction of voltage collapse in practical power system models which include numerous constraints and discontinuities. Illustrations and numerical simulations throughout the thesis support our results.

Community-driven demand creation for the use of routine viral load testing: a model to scale up routine viral load testing.

PubMed

Killingo, Bactrin M; Taro, Trisa B; Mosime, Wame N

2017-11-01

HIV treatment outcomes are dependent on the use of viral load measurement. Despite global and national guidelines recommending the use of routine viral load testing, these policies alone have not translated into widespread implementation or sufficiently increased access for people living with HIV (PLHIV). Civil society and communities of PLHIV recognize the need to close this gap and to enable the scale up of routine viral load testing. The International Treatment Preparedness Coalition (ITPC) developed an approach to community-led demand creation for the use of routine viral load testing. Using this Community Demand Creation Model, implementers follow a step-wise process to capacitate and empower communities to address their most pressing needs. This includes utlizing a specific toolkit that includes conducting a baseline assessment, developing a treatment education toolkit, organizing mobilization workshops for knowledge building, provision of small grants to support advocacy work and conducting benchmark evaluations. The Community Demand Creation Model to increase demand for routine viral load testing services by PLHIV has been delivered in diverse contexts including in the sub-Saharan African, Asian, Latin American and the Caribbean regions. Between December 2015 and December 2016, ITPC trained more than 240 PLHIV activists, and disbursed US$90,000 to network partners in support of their national advocacy work. The latter efforts informed a regional, community-driven campaign calling for domestic investment in the expeditious implementation of national viral load testing guidelines. HIV treatment education and community mobilization are critical components of demand creation for access to optimal HIV treatment, especially for the use of routine viral load testing. ITPC's Community Demand Creation Model offers a novel approach to achieving this goal. © 2017 The Authors. Journal of the International AIDS Society published by John Wiley & sons Ltd on behalf of the International AIDS Society.

Advanced Stirling Convertor Dual Convertor Controller Testing at NASA Glenn Research Center in the Radioisotope Power Systems System Integration Laboratory

NASA Technical Reports Server (NTRS)

Dugala, Gina M.; Taylor, Linda M.; Bell, Mark E.; Dolce, James L.; Fraeman, Martin; Frankford, David P.

2015-01-01

NASA Glenn Research Center (GRC) developed a non-nuclear representation of a Radioisotope Power System (RPS) consisting of a pair of Advanced Stirling Convertors (ASC), a Dual Convertor Controller (DCC) EM (engineering model) 2 & 3, and associated support equipment, which were tested in the Radioisotope Power Systems System Integration Laboratory (RSIL). The DCC was designed by the Johns Hopkins University/Applied Physics Laboratory (JHU/APL) to actively control a pair of Advanced Stirling Convertors (ASC). The first phase of testing included a Dual Advanced Stirling Convertor Simulator (DASCS) which was developed by JHU/APL and simulates the operation and electrical behavior of a pair of ASC's in real time via a combination of hardware and software. RSIL provides insight into the electrical interactions between a representative radioisotope power generator, its associated control schemes, and realistic electric system loads. The first phase of integration testing included the following spacecraft bus configurations: capacitive, battery, and supercapacitor. A load profile, created based on data from several missions, tested the RPS and RSIL ability to maintain operation during load demands above and below the power provided by the RPS. The integration testing also confirmed the DCC's ability to disconnect from the spacecraft when the bus voltage dipped below 22 V or exceeded 36 V. Once operation was verified with the DASCS, the tests were repeated with actual operating ASC's. The goal of this integration testing was to verify operation of the DCC when connected to a spacecraft and to verify the functionality of the newly designed RSIL. The results of these tests are presented in this paper.

Long-term monitoring FBG-based cable load sensor

NASA Astrophysics Data System (ADS)

Zhang, Zhichun; Zhou, Zhi; Wang, Chuan; Ou, Jinping

2006-03-01

Stay cables are the main load-bearing components of stayed-cable bridges. The cables stress status is an important factor to the stayed-cable bridge structure safety evaluation. So it's very important not only to the bridge construction, but also to the long-term safety evaluation for the bridge structure in-service. The accurate measurement for cable load depends on an effective sensor, especially to meet the long time durability and measurement demand. FBG, for its great advantage of corrosion resistance, absolute measurement, high accuracy, electro-magnetic resistance, quasi-distribution sensing, absolute measurement and so on, is the most promising sensor, which can cater for the cable force monitoring. In this paper, a load sensor has been developed, which is made up of a bushing elastic supporting body, 4 FBGs uniformly-spaced attached outside of the bushing supporting body, and a temperature compensation FBG for other four FBGs, moreover a cover for protection of FBGs. Firstly, the sensor measuring principle is analyzed, and relationship equation of FBG wavelength shifts and extrinsic load has also been gotten. And then the sensor calibration experiments of a steel cable stretching test with the FBG load sensor and a reference electric pressure sensor is finished, and the results shows excellent linearity of extrinsic load and FBG wavelength shifts, and good repeatability, which indicates that such kind of FBG-based load sensor is suitable for load measurement, especially for long-term, real time monitoring of stay-cables.

Demand Response Compensation Methodologies: Case Studies for Mexico

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gagne, Douglas A; Settle, Donald E; Aznar, Alexandra Y

This report examines various compensation methodologies for demand response programs in Mexico. This report presents three case studies, including New England, California, and Hawaii. Demand response (DR) can refer to a variety of approaches to changing the amount and timing of customers' electricity use, allowing the electricity supplier to more easily balance electricity supply and demand. The level of compensation for a DR program will depend greatly upon both the regulatory context of the electricity supplier, as well as the economic circumstances of the DR providers. For a regulated utility, a proposed compensation level may need to pass regulatory approval.more » To determine the value of DR resources, a regulatory body typically seeks to determine the costs that the utility would avoid if demand-side resources 'produce' energy.« less

Method and system employing finite state machine modeling to identify one of a plurality of different electric load types

DOE Office of Scientific and Technical Information (OSTI.GOV)

Du, Liang; Yang, Yi; Harley, Ronald Gordon

A system is for a plurality of different electric load types. The system includes a plurality of sensors structured to sense a voltage signal and a current signal for each of the different electric loads; and a processor. The processor acquires a voltage and current waveform from the sensors for a corresponding one of the different electric load types; calculates a power or current RMS profile of the waveform; quantizes the power or current RMS profile into a set of quantized state-values; evaluates a state-duration for each of the quantized state-values; evaluates a plurality of state-types based on the powermore » or current RMS profile and the quantized state-values; generates a state-sequence that describes a corresponding finite state machine model of a generalized load start-up or transient profile for the corresponding electric load type; and identifies the corresponding electric load type.« less

Performance of fuzzy approach in Malaysia short-term electricity load forecasting

NASA Astrophysics Data System (ADS)

Mansor, Rosnalini; Zulkifli, Malina; Yusof, Muhammad Mat; Ismail, Mohd Isfahani; Ismail, Suzilah; Yin, Yip Chee

2014-12-01

Many activities such as economic, education and manafucturing would paralyse with limited supply of electricity but surplus contribute to high operating cost. Therefore electricity load forecasting is important in order to avoid shortage or excess. Previous finding showed festive celebration has effect on short-term electricity load forecasting. Being a multi culture country Malaysia has many major festive celebrations such as Eidul Fitri, Chinese New Year and Deepavali but they are moving holidays due to non-fixed dates on the Gregorian calendar. This study emphasis on the performance of fuzzy approach in forecasting electricity load when considering the presence of moving holidays. Autoregressive Distributed Lag model was estimated using simulated data by including model simplification concept (manual or automatic), day types (weekdays or weekend), public holidays and lags of electricity load. The result indicated that day types, public holidays and several lags of electricity load were significant in the model. Overall, model simplification improves fuzzy performance due to less variables and rules.

The potential for distributed generation in Japanese prototype buildings: A DER-CAM analysis of policy, tariff design, building energy use, and technology development (English Version)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Nan; Marnay, Chris; Firestone, Ryan

The August 2003 blackout of the northeastern U.S. and CANADA caused great economic losses and inconvenience to New York City and other affected areas. The blackout was a warning to the rest of the world that the ability of conventional power systems to meet growing electricity demand is questionable. Failure of large power systems can lead to serious emergencies. Introduction of on-site generation, renewable energy such as solar and wind power and the effective utilization of exhaust heat is needed, to meet the growing energy demands of the residential and commercial sectors. Additional benefit can be achieved by integrating thesemore » distributed technologies into distributed energy resource (DER) systems. This work demonstrates a method for choosing and designing economically optimal DER systems. An additional purpose of this research is to establish a database of energy tariffs, DER technology cost and performance characteristics, and building energy consumption for Japan. This research builds on prior DER studies at the Ernest Orlando Lawrence Berkeley National Laboratory (LBNL) and with their associates in the Consortium for Electric Reliability Technology Solutions (CERTS) and operation, including the development of the microgrid concept, and the DER selection optimization program, the Distributed Energy Resources Customer Adoption Model (DER-CAM). DER-CAM is a tool designed to find the optimal combination of installed equipment and an idealized operating schedule to minimize a site's energy bills, given performance and cost data on available DER technologies, utility tariffs, and site electrical and thermal loads over a test period, usually an historic year. Since hourly electric and thermal energy data are rarely available, they are typically developed by building simulation for each of six end use loads used to model the building: electric-only loads, space heating, space cooling, refrigeration, water heating, and natural-gas-only loads. DER-CAM provides a global optimization, albeit idealized, that shows how the necessary useful energy loads can be provided for at minimum cost by selection and operation of on-site generation, heat recovery, cooling, and efficiency improvements. This study examines five prototype commercial buildings and uses DER-CAM to select the economically optimal DER system for each. The five building types are office, hospital, hotel, retail, and sports facility. Each building type was considered for both 5,000 and 10,000 square meter floor sizes. The energy consumption of these building types is based on building energy simulation and published literature. Based on the optimization results, energy conservation and the emissions reduction were also evaluated. Furthermore, a comparison study between Japan and the U.S. has been conducted covering the policy, technology and the utility tariffs effects on DER systems installations. This study begins with an examination of existing DER research. Building energy loads were then generated through simulation (DOE-2) and scaled to match available load data in the literature. Energy tariffs in Japan and the U.S. were then compared: electricity prices did not differ significantly, while commercial gas prices in Japan are much higher than in the U.S. For smaller DER systems, the installation costs in Japan are more than twice those in the U.S., but this difference becomes smaller with larger systems. In Japan, DER systems are eligible for a 1/3 rebate of installation costs, while subsidies in the U.S. vary significantly by region and application. For 10,000 m{sup 2} buildings, significant decreases in fuel consumption, carbon emissions, and energy costs were seen in the economically optimal results. This was most noticeable in the sports facility, followed the hospital and hotel. This research demonstrates that office buildings can benefit from CHP, in contrast to popular opinion. For hospitals and sports facilities, the use of waste heat is particularly effective for water and space heating. For the other building types, waste heat is most effectively used for both heating and cooling. The same examination was done for the 5,000 m{sup 2} buildings. Although CHP installation capacity is smaller and the payback periods are longer, economic, fuel efficiency, and environmental benefits are still seen. While these benefits remain even when subsidies are removed, the increased installation costs lead to lower levels of installation capacity and thus benefit.« less

Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gregor P. Henze; Moncef Krarti

2005-09-30

Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid. Time-of-use electricity rates encourage shifting of electrical loads to off-peak periods at night and weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building's massive structure or the use of active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this project investigated the merits of harnessing both storage media concurrently in the context of predictive optimal control. To pursue the analysis, modeling, and simulationmore » research of Phase 1, two separate simulation environments were developed. Based on the new dynamic building simulation program EnergyPlus, a utility rate module, two thermal energy storage models were added. Also, a sequential optimization approach to the cost minimization problem using direct search, gradient-based, and dynamic programming methods was incorporated. The objective function was the total utility bill including the cost of reheat and a time-of-use electricity rate either with or without demand charges. An alternative simulation environment based on TRNSYS and Matlab was developed to allow for comparison and cross-validation with EnergyPlus. The initial evaluation of the theoretical potential of the combined optimal control assumed perfect weather prediction and match between the building model and the actual building counterpart. The analysis showed that the combined utilization leads to cost savings that is significantly greater than either storage but less than the sum of the individual savings. The findings reveal that the cooling-related on-peak electrical demand of commercial buildings can be considerably reduced. A subsequent analysis of the impact of forecasting uncertainty in the required short-term weather forecasts determined that it takes only very simple short-term prediction models to realize almost all of the theoretical potential of this control strategy. Further work evaluated the impact of modeling accuracy on the model-based closed-loop predictive optimal controller to minimize utility cost. The following guidelines have been derived: For an internal heat gain dominated commercial building, reasonable geometry simplifications are acceptable without a loss of cost savings potential. In fact, zoning simplification may improve optimizer performance and save computation time. The mass of the internal structure did not show a strong effect on the optimization. Building construction characteristics were found to impact building passive thermal storage capacity. It is thus advisable to make sure the construction material is well modeled. Zone temperature setpoint profiles and TES performance are strongly affected by mismatches in internal heat gains, especially when they are underestimated. Since they are a key factor in determining the building cooling load, efforts should be made to keep the internal gain mismatch as small as possible. Efficiencies of the building energy systems affect both zone temperature setpoints and active TES operation because of the coupling of the base chiller for building precooling and the icemaking TES chiller. Relative efficiencies of the base and TES chillers will determine the balance of operation of the two chillers. The impact of mismatch in this category may be significant. Next, a parametric analysis was conducted to assess the effects of building mass, utility rate, building location and season, thermal comfort, central plant capacities, and an economizer on the cost saving performance of optimal control for active and passive building thermal storage inventory. The key findings are: (1) Heavy-mass buildings, strong-incentive time-of-use electrical utility rates, and large on-peak cooling loads will likely lead to attractive savings resulting from optimal combined thermal storage control. (2) By using economizer to take advantage of the cool fresh air during the night, the building electrical cost can be reduced by using less mechanical cooling. (3) Larger base chiller and active thermal storage capacities have the potential of shifting more cooling loads to off-peak hours and thus higher savings can be achieved. (4) Optimal combined thermal storage control with a thermal comfort penalty included in the objective function can improve the thermal comfort levels of building occupants when compared to the non-optimized base case. Lab testing conducted in the Larson HVAC Laboratory during Phase 2 showed that the EnergyPlus-based simulation was a surprisingly accurate prediction of the experiment. Therefore, actual savings of building energy costs can be expected by applying optimal controls from simulation results.« less

Water-Constrained Electric Sector Capacity Expansion Modeling Under Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Cohen, S. M.; Macknick, J.; Miara, A.; Vorosmarty, C. J.; Averyt, K.; Meldrum, J.; Corsi, F.; Prousevitch, A.; Rangwala, I.

2015-12-01

Over 80% of U.S. electricity generation uses a thermoelectric process, which requires significant quantities of water for power plant cooling. This water requirement exposes the electric sector to vulnerabilities related to shifts in water availability driven by climate change as well as reductions in power plant efficiencies. Electricity demand is also sensitive to climate change, which in most of the United States leads to warming temperatures that increase total cooling-degree days. The resulting demand increase is typically greater for peak demand periods. This work examines the sensitivity of the development and operations of the U.S. electric sector to the impacts of climate change using an electric sector capacity expansion model that endogenously represents seasonal and local water resource availability as well as climate impacts on water availability, electricity demand, and electricity system performance. Capacity expansion portfolios and water resource implications from 2010 to 2050 are shown at high spatial resolution under a series of climate scenarios. Results demonstrate the importance of water availability for future electric sector capacity planning and operations, especially under more extreme hotter and drier climate scenarios. In addition, region-specific changes in electricity demand and water resources require region-specific responses that depend on local renewable resource availability and electricity market conditions. Climate change and the associated impacts on water availability and temperature can affect the types of power plants that are built, their location, and their impact on regional water resources.

Synthesis of Trigeneration Systems: Sensitivity Analyses and Resilience

PubMed Central

Carvalho, Monica; Lozano, Miguel A.; Ramos, José; Serra, Luis M.

2013-01-01

This paper presents sensitivity and resilience analyses for a trigeneration system designed for a hospital. The following information is utilized to formulate an integer linear programming model: (1) energy service demands of the hospital, (2) technical and economical characteristics of the potential technologies for installation, (3) prices of the available utilities interchanged, and (4) financial parameters of the project. The solution of the model, minimizing the annual total cost, provides the optimal configuration of the system (technologies installed and number of pieces of equipment) and the optimal operation mode (operational load of equipment, interchange of utilities with the environment, convenience of wasting cogenerated heat, etc.) at each temporal interval defining the demand. The broad range of technical, economic, and institutional uncertainties throughout the life cycle of energy supply systems for buildings makes it necessary to delve more deeply into the fundamental properties of resilient systems: feasibility, flexibility and robustness. The resilience of the obtained solution is tested by varying, within reasonable limits, selected parameters: energy demand, amortization and maintenance factor, natural gas price, self-consumption of electricity, and time-of-delivery feed-in tariffs. PMID:24453881

Synthesis of trigeneration systems: sensitivity analyses and resilience.

PubMed

Carvalho, Monica; Lozano, Miguel A; Ramos, José; Serra, Luis M

2013-01-01

This paper presents sensitivity and resilience analyses for a trigeneration system designed for a hospital. The following information is utilized to formulate an integer linear programming model: (1) energy service demands of the hospital, (2) technical and economical characteristics of the potential technologies for installation, (3) prices of the available utilities interchanged, and (4) financial parameters of the project. The solution of the model, minimizing the annual total cost, provides the optimal configuration of the system (technologies installed and number of pieces of equipment) and the optimal operation mode (operational load of equipment, interchange of utilities with the environment, convenience of wasting cogenerated heat, etc.) at each temporal interval defining the demand. The broad range of technical, economic, and institutional uncertainties throughout the life cycle of energy supply systems for buildings makes it necessary to delve more deeply into the fundamental properties of resilient systems: feasibility, flexibility and robustness. The resilience of the obtained solution is tested by varying, within reasonable limits, selected parameters: energy demand, amortization and maintenance factor, natural gas price, self-consumption of electricity, and time-of-delivery feed-in tariffs.

Evaluating the impacts of real-time pricing on the usage of wind generation

DOE PAGES

Sioshansi, Ramteen; Short, Walter

2009-02-13

One of the impediments to large-scale use of wind generation within power systems is its nondispatchability and variable and uncertain real-time availability. Operating constraints on conventional generators such as minimum generation points, forbidden zones, and ramping limits as well as system constraints such as power flow limits and ancillary service requirements may force a system operator to curtail wind generation in order to ensure feasibility. Furthermore, the pattern of wind availability and electricity demand may not allow wind generation to be fully utilized in all hours. One solution to these issues, which could reduce these inflexibilities, is the use ofmore » real-time pricing (RTP) tariffs which can both smooth-out the diurnal load pattern in order to reduce the impact of binding unit operating and system constraints on wind utilization, and allow demand to increase in response to the availability of costless wind generation. As a result, we use and analyze a detailed unit commitment model of the Texas power system with different estimates of demand elasticities to demonstrate the potential increases in wind generation from implementing RTP.« less

The added economic and environmental value of plug-in electric vehicles connected to commercial building microgrids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stadler, Michael; Momber, Ilan; Megel, Olivier

2010-08-25

Connection of electric storage technologies to smartgrids or microgrids will have substantial implications for building energy systems. In addition to potentially supplying ancillary services directly to the traditional centralized grid (or macrogrid), local storage will enable demand response. As an economically attractive option, mobile storage devices such as plug-in electric vehicles (EVs) are in direct competition with conventional stationary sources and storage at the building. In general, it is assumed that they can improve the financial as well as environmental attractiveness of renewable and fossil based on-site generation (e.g. PV, fuel cells, or microturbines operating with or without combined heatmore » and power). Also, mobile storage can directly contribute to tariff driven demand response in commercial buildings. In order to examine the impact of mobile storage on building energy costs and carbon dioxide (CO2) emissions, a microgrid/distributed-energy-resources (DER) adoption problem is formulated as a mixed-integer linear program with minimization of annual building energy costs applying CO2 taxes/CO2 pricing schemes. The problem is solved for a representative office building in the San Francisco Bay Area in 2020. By using employees' EVs for energy management, the office building can arbitrage its costs. But since the car battery lifetime is reduced, a business model that also reimburses car owners for the degradation will be required. In general, the link between a microgrid and an electric vehicle can create a win-win situation, wherein the microgrid can reduce utility costs by load shifting while the electric vehicle owner receives revenue that partially offsets his/her expensive mobile storage investment. For the California office building with EVs connected under a business model that distributes benefits, it is found that the economic impact is very limited relative to the costs of mobile storage for the site analyzed, i.e. cost reductions from electric vehicle connections are modest. Nonetheless, this example shows that some economic benefit is created because of avoided demand charges and on-peak energy. The strategy adopted by the office building is to avoid these high on-peak costs by using energy from the mobile storage in the business hours. CO2 emission reduction strategy results indicate that EVs' contribution at the selected office building are minor.« less

Short-term electric power demand forecasting based on economic-electricity transmission model

NASA Astrophysics Data System (ADS)

Li, Wenfeng; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Wang, Yubin Mao; Wang, Jiangbo; He, Dandan

2018-04-01

Short-term electricity demand forecasting is the basic work to ensure safe operation of the power system. In this paper, a practical economic electricity transmission model (EETM) is built. With the intelligent adaptive modeling capabilities of Prognoz Platform 7.2, the econometric model consists of three industrial added value and income levels is firstly built, the electricity demand transmission model is also built. By multiple regression, moving averages and seasonal decomposition, the problem of multiple correlations between variables is effectively overcome in EETM. The validity of EETM is proved by comparison with the actual value of Henan Province. Finally, EETM model is used to forecast the electricity consumption of the 1-4 quarter of 2018.

Medium Duty ARRA Data Reporting and Analysis; NREL (National Renewable Energy Laboratory)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelly, Kenneth; Duran, Adam; Ragatz, Adam

Medium-duty (MD) electric vehicle (EV) data collection and analysis will help drive design, purchase, and research investments. Over 4 million miles and 160,000 driving days of EV driving data were collected under this project. Publicly available data help drive technology research, development, and deployment. Feeding the vocational database for future analysis will lead to a better understanding of usage and will result in better design optimization and technology implementation. The performance of a vehicle varies with drive cycle and cargo load - MD vehicles are 'multi-functional.' Environment and accessory loads affect vehicle range and in turn add cost by addingmore » battery capacity. MD EV vehicles can function in vocations traditionally serviced by gasoline or diesel vehicles. Facility implications (i.e., demand charges) need to be understood as part of site-based analysis for EV implementation.« less

Automatic remote-integration metering center. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Philippidis, P.A.; Weinreb, M.; de Gil, B.F.

1988-11-01

The report documents a multi-phase program for the development and demonstration of a unique automatic and remote metering system. The system consists of a solid-state meter module to provide electrical consumption data, tamper detection, and load control functions; a central master station to interrogate the meter modules for their data and also to transmit load control signals; and a data display module to be accessible to tenants wishing to obtain their meter readings. The system has the capability to measure and allocate demand and to process time of use rates. It also has a meter accuracy self-test feature. The systemmore » is suitable for both direct metering of multi-family buildings and the sub-metering of master-metered apartment buildings. In addition to describing the system, the report documents the results of a 371-point field trial at Scott Tower, a cooperative apartment building in the Bronx, New York.« less

A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hong, Tianzhen; Chang, Wen-Kuei; Lin, Hung-Wen

Buildings consume more than one third of the world?s total primary energy. Weather plays a unique and significant role as it directly affects the thermal loads and thus energy performance of buildings. The traditional simulated energy performance using Typical Meteorological Year (TMY) weather data represents the building performance for a typical year, but not necessarily the average or typical long-term performance as buildings with different energy systems and designs respond differently to weather changes. Furthermore, the single-year TMY simulations do not provide a range of results that capture yearly variations due to changing weather, which is important for building energymore » management, and for performing risk assessments of energy efficiency investments. This paper employs large-scale building simulation (a total of 3162 runs) to study the weather impact on peak electricity demand and energy use with the 30-year (1980 to 2009) Actual Meteorological Year (AMY) weather data for three types of office buildings at two design efficiency levels, across all 17 ASHRAE climate zones. The simulated results using the AMY data are compared to those from the TMY3 data to determine and analyze the differences. Besides further demonstration, as done by other studies, that actual weather has a significant impact on both the peak electricity demand and energy use of buildings, the main findings from the current study include: 1) annual weather variation has a greater impact on the peak electricity demand than it does on energy use in buildings; 2) the simulated energy use using the TMY3 weather data is not necessarily representative of the average energy use over a long period, and the TMY3 results can be significantly higher or lower than those from the AMY data; 3) the weather impact is greater for buildings in colder climates than warmer climates; 4) the weather impact on the medium-sized office building was the greatest, followed by the large office and then the small office; and 5) simulated energy savings and peak demand reduction by energy conservation measures using the TMY3 weather data can be significantly underestimated or overestimated. It is crucial to run multi-decade simulations with AMY weather data to fully assess the impact of weather on the long-term performance of buildings, and to evaluate the energy savings potential of energy conservation measures for new and existing buildings from a life cycle perspective.« less