Modeling Framework and Validation of a Smart Grid and Demand Response System for Wind Power Integration

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

Broeer, Torsten; Fuller, Jason C.; Tuffner, Francis K.

2014-01-31

Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generatormore » and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.« less

Projecting Electricity Demand in 2050

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

Hostick, Donna J.; Belzer, David B.; Hadley, Stanton W.

2014-07-01

This paper describes the development of end-use electricity projections and load curves that were developed for the Renewable Electricity (RE) Futures Study (hereafter RE Futures), which explored the prospect of higher percentages (30% - 90%) of total electricity generation that could be supplied by renewable sources in the United States. As input to RE Futures, two projections of electricity demand were produced representing reasonable upper and lower bounds of electricity demand out to 2050. The electric sector models used in RE Futures required underlying load profiles, so RE Futures also produced load profile data in two formats: 8760 hourly datamore » for the year 2050 for the GridView model, and in 2-year increments for 17 time slices as input to the Regional Energy Deployment System (ReEDS) model. The process for developing demand projections and load profiles involved three steps: discussion regarding the scenario approach and general assumptions, literature reviews to determine readily available data, and development of the demand curves and load profiles.« less

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)

Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System

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

NONE

1998-01-01

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. The NEMS Commercial Sector Demand Module is a simulation tool based upon economic and engineering relationships that models commercial sector energy demands at the nine Census Division level of detail for eleven distinct categories of commercial buildings. Commercial equipment selections are performed for the major fuels of electricity, natural gas,more » and distillate fuel, for the major services of space heating, space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The algorithm also models demand for the minor fuels of residual oil, liquefied petroleum gas, steam coal, motor gasoline, and kerosene, the renewable fuel sources of wood and municipal solid waste, and the minor services of office equipment. Section 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMS system. Section 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized in the model development process to this point. Section 3 also reviews alternative commercial sector modeling methodologies drawn from existing literature, providing a comparison to the chosen approach. Section 4 details the model structure, using graphics and text to illustrate model flows and key computations.« less

An approach to modeling and optimization of integrated renewable energy system (ires)

NASA Astrophysics Data System (ADS)

Maheshwari, Zeel

The purpose of this study was to cost optimize electrical part of IRES (Integrated Renewable Energy Systems) using HOMER and maximize the utilization of resources using MATLAB programming. IRES is an effective and a viable strategy that can be employed to harness renewable energy resources to energize remote rural areas of developing countries. The resource- need matching, which is the basis for IRES makes it possible to provide energy in an efficient and cost effective manner. Modeling and optimization of IRES for a selected study area makes IRES more advantageous when compared to hybrid concepts. A remote rural area with a population of 700 in 120 households and 450 cattle is considered as an example for cost analysis and optimization. Mathematical models for key components of IRES such as biogas generator, hydropower generator, wind turbine, PV system and battery banks are developed. A discussion of the size of water reservoir required is also presented. Modeling of IRES on the basis of need to resource and resource to need matching is pursued to help in optimum use of resources for the needs. Fixed resources such as biogas and water are used in prioritized order whereas movable resources such as wind and solar can be used simultaneously for different priorities. IRES is cost optimized for electricity demand using HOMER software that is developed by the NREL (National Renewable Energy Laboratory). HOMER optimizes configuration for electrical demand only and does not consider other demands such as biogas for cooking and water for domestic and irrigation purposes. Hence an optimization program based on the need-resource modeling of IRES is performed in MATLAB. Optimization of the utilization of resources for several needs is performed. Results obtained from MATLAB clearly show that the available resources can fulfill the demand of the rural areas. Introduction of IRES in rural communities has many socio-economic implications. It brings about improvement in living

Aggregate modeling of fast-acting demand response and control under real-time pricing

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

Chassin, David P.; Rondeau, Daniel

This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop amore » more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. Finally, the results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.« less

Aggregate modeling of fast-acting demand response and control under real-time pricing

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

Chassin, David P.; Rondeau, Daniel

This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop amore » more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. The results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.« less

Aggregate modeling of fast-acting demand response and control under real-time pricing

DOE PAGES

Chassin, David P.; Rondeau, Daniel

2016-08-24

This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop amore » more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. Finally, the results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.« less

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.

A non-autonomous optimal control model of renewable energy production under the aspect of fluctuating supply and learning by doing.

PubMed

Moser, Elke; Grass, Dieter; Tragler, Gernot

Given the constantly raising world-wide energy demand and the accompanying increase in greenhouse gas emissions that pushes the progression of climate change, the possibly most important task in future is to find a carbon-low energy supply that finds the right balance between sustainability and energy security. For renewable energy generation, however, especially the second aspect turns out to be difficult as the supply of renewable sources underlies strong volatility. Further on, investment costs for new technologies are so high that competitiveness with conventional energy forms is hard to achieve. To address this issue, we analyze in this paper a non-autonomous optimal control model considering the optimal composition of a portfolio that consists of fossil and renewable energy and which is used to cover the energy demand of a small country. While fossil energy is assumed to be constantly available, the supply of the renewable resource fluctuates seasonally. We further on include learning effects for the renewable energy technology, which will underline the importance of considering the whole life span of such a technology for long-term energy planning decisions.

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

Energy demand forecasting

NASA Astrophysics Data System (ADS)

Energy demand forecasting and its connection with national energy policies and decisions is examined in light of recent, sharply revised estimates of future energy requirements. Techniques of economic projects are examined. Modeling of energy demands is discussed. Renewable energy sources are discussed. The shift away from reliance of domestic users on oil and natural gas toward electricity as a primary energy resource is examined in the context of the need to conserve energy and expand generating capacity in order to avoid a significant electricity shortfall.

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

Renewable Electricity Futures Study. Volume 2: Renewable Electricity Generation and Storage Technologies

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

Augustine, C.; Bain, R.; Chapman, J.

2012-06-01

The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a futuremore » through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).« 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

Renewable Electricity Futures Study. Volume 1: Exploration of High-Penetration Renewable Electricity Futures

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

Mai, T.; Wiser, R.; Sandor, D.

2012-06-01

The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a futuremore » through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).« less

Renewable Electricity Futures Study. Volume 2. Renewable Electricity Generation and Storage Technologies

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

Augustine, Chad; Bain, Richard; Chapman, Jamie

2012-06-15

The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a futuremore » through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%–90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT). Learn more at the RE Futures website. http://www.nrel.gov/analysis/re_futures/« less

Michigan's Statewide Travel Demand Model

DOT National Transportation Integrated Search

1999-09-01

The Travel Demand and Intermodal Services Section of Michigan's Department of Transportation is responsible for the development, maintenance and application of the Statewide Travel Demand Model. Michigan's Statewide and Urban Travel Demand Models are...

Renewable Electricity Futures: Exploration of a U.S. Grid with 80% Renewable Electricity

NASA Astrophysics Data System (ADS)

Mai, Trieu

2013-04-01

Renewable Electricity Futures is an initial investigation of the extent to which renewable energy supply can meet the electricity demands of the contiguous United States over the next several decades. This study explores the implications and challenges of very high renewable electricity generation levels: from 30% up to 90% (focusing on 80%) of all U.S. electricity generation from renewable technologies in 2050. At such high levels of renewable electricity penetration, the unique characteristics of some renewable resources, specifically geographical distribution and variability and un-certainty in output, pose challenges to the operability of the nation's electric system. The study focuses on key technical implications of this environment from a national perspective, exploring whether the U.S. power system can supply electricity to meet customer demand on an hourly basis with high levels of renewable electricity, including variable wind and solar generation. The study also identifies some of the potential economic, environmental, and social implications of deploying and integrating high levels of renewable electricity in the U.S. The full report and associated supporting information is available at: http://www.nrel.gov/analysis/refutures/.

Renewable Electricity Futures Study. Volume 1. Exploration of High-Penetration Renewable Electricity Futures

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

Hand, M. M.; Baldwin, S.; DeMeo, E.

2012-06-15

The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a futuremore » through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%–90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT). Learn more at the RE Futures website. http://www.nrel.gov/analysis/re_futures/« less

Small modular reactor modeling using modelica for nuclear-renewable hybrid energy systems applications

DOE PAGES

Mikkelson, Daniel; Chang, Chih -Wei; Cetiner, Sacit M.; ...

2015-10-01

Here, the U.S. Department of Energy (DOE) supports research and development (R&D) that could lead to more efficient utilization of clean energy generation sources, including renewable and nuclear options, to meet grid demand and industrial thermal energy needs [1]. One hybridization approach being investigated by the DOE Offices of Nuclear Energy (NE) and the DOE Energy Efficiency and Renewable Energy (EERE) is tighter coupling of nuclear and renewable energy sources to better manage overall energy use for the combined electricity, industrial manufacturing, and transportation sectors.

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

An integrated communications demand model

NASA Astrophysics Data System (ADS)

Doubleday, C. F.

1980-11-01

A computer model of communications demand is being developed to permit dynamic simulations of the long-term evolution of demand for communications media in the U.K. to be made under alternative assumptions about social, economic and technological trends in British Telecom's business environment. The context and objectives of the project and the potential uses of the model are reviewed, and four key concepts in the demand for communications media, around which the model is being structured are discussed: (1) the generation of communications demand; (2) substitution between media; (3) technological convergence; and (4) competition. Two outline perspectives on the model itself are given.

Optimization modeling of U.S. renewable electricity deployment using local input variables

NASA Astrophysics Data System (ADS)

Bernstein, Adam

For the past five years, state Renewable Portfolio Standard (RPS) laws have been a primary driver of renewable electricity (RE) deployments in the United States. However, four key trends currently developing: (i) lower natural gas prices, (ii) slower growth in electricity demand, (iii) challenges of system balancing intermittent RE within the U.S. transmission regions, and (iv) fewer economical sites for RE development, may limit the efficacy of RPS laws over the remainder of the current RPS statutes' lifetime. An outsized proportion of U.S. RE build occurs in a small number of favorable locations, increasing the effects of these variables on marginal RE capacity additions. A state-by-state analysis is necessary to study the U.S. electric sector and to generate technology specific generation forecasts. We used LP optimization modeling similar to the National Renewable Energy Laboratory (NREL) Renewable Energy Development System (ReEDS) to forecast RE deployment across the 8 U.S. states with the largest electricity load, and found state-level RE projections to Year 2031 significantly lower than thoseimplied in the Energy Information Administration (EIA) 2013 Annual Energy Outlook forecast. Additionally, the majority of states do not achieve their RPS targets in our forecast. Combined with the tendency of prior research and RE forecasts to focus on larger national and global scale models, we posit that further bottom-up state and local analysis is needed for more accurate policy assessment, forecasting, and ongoing revision of variables as parameter values evolve through time. Current optimization software eliminates much of the need for algorithm coding and programming, allowing for rapid model construction and updating across many customized state and local RE parameters. Further, our results can be tested against the empirical outcomes that will be observed over the coming years, and the forecast deviation from the actuals can be attributed to discrete parameter

Dynamic modeling of hybrid renewable energy systems for off-grid applications

NASA Astrophysics Data System (ADS)

Hasemeyer, Mark David

The volatile prices of fossil fuels and their contribution to global warming have caused many people to turn to renewable energy systems. Many developing communities are forced to use these systems as they are too far from electrical distribution. As a result, numerous software models have been developed to simulate hybrid renewable energy systems. However almost, if not all, implementations are static in design. A static design limits the ability of the model to account for changes over time. Dynamic modeling can be used to fill the gaps where other modeling techniques fall short. This modeling practice allows the user to account for the effects of technological and economic factors over time. These factors can include changes in energy demand, energy production, and income level. Dynamic modeling can be particularly useful for developing communities who are off-grid and developing at rapid rates. In this study, a dynamic model was used to evaluate a real world system. A non-governmental organization interested in improving their current infrastructure was selected. Five different scenarios were analyzed and compared in order to discover which factors the model is most sensitive to. In four of the scenarios, a new energy system was purchased in order to account for the opening of a restaurant that would be used as a source of local income generation. These scenarios were then compared to a base case in which a new system was not purchased, and the restaurant was not opened. Finally, the results were used to determine which variables had the greatest impact on the various outputs of the simulation.

Demand forecast model based on CRM

NASA Astrophysics Data System (ADS)

Cai, Yuancui; Chen, Lichao

2006-11-01

With interiorizing day by day management thought that regarding customer as the centre, forecasting customer demand becomes more and more important. In the demand forecast of customer relationship management, the traditional forecast methods have very great limitation because much uncertainty of the demand, these all require new modeling to meet the demands of development. In this paper, the notion is that forecasting the demand according to characteristics of the potential customer, then modeling by it. The model first depicts customer adopting uniform multiple indexes. Secondly, the model acquires characteristic customers on the basis of data warehouse and the technology of data mining. The last, there get the most similar characteristic customer by their comparing and forecast the demands of new customer by the most similar characteristic customer.

Fundamental Travel Demand Model Example

NASA Technical Reports Server (NTRS)

Hanssen, Joel

2010-01-01

Instances of transportation models are abundant and detailed "how to" instruction is available in the form of transportation software help documentation. The purpose of this paper is to look at the fundamental inputs required to build a transportation model by developing an example passenger travel demand model. The example model reduces the scale to a manageable size for the purpose of illustrating the data collection and analysis required before the first step of the model begins. This aspect of the model development would not reasonably be discussed in software help documentation (it is assumed the model developer comes prepared). Recommendations are derived from the example passenger travel demand model to suggest future work regarding the data collection and analysis required for a freight travel demand model.

Regional Renewable Energy Cooperatives

NASA Astrophysics Data System (ADS)

Hazendonk, P.; Brown, M. B.; Byrne, J. M.; Harrison, T.; Mueller, R.; Peacock, K.; Usher, J.; Yalamova, R.; Kroebel, R.; Larsen, J.; McNaughton, R.

2014-12-01

We are building a multidisciplinary research program linking researchers in agriculture, business, earth science, engineering, humanities and social science. Our goal is to match renewable energy supply and reformed energy demands. The program will be focused on (i) understanding and modifying energy demand, (ii) design and implementation of diverse renewable energy networks. Geomatics technology will be used to map existing energy and waste flows on a neighbourhood, municipal, and regional level. Optimal sites and combinations of sites for solar and wind electrical generation (ridges, rooftops, valley walls) will be identified. Geomatics based site and grid analyses will identify best locations for energy production based on efficient production and connectivity to regional grids and transportation. Design of networks for utilization of waste streams of heat, water, animal and human waste for energy production will be investigated. Agriculture, cities and industry produce many waste streams that are not well utilized. Therefore, establishing a renewable energy resource mapping and planning program for electrical generation, waste heat and energy recovery, biomass collection, and biochar, biodiesel and syngas production is critical to regional energy optimization. Electrical storage and demand management are two priorities that will be investigated. Regional scale cooperatives may use electric vehicle batteries and innovations such as pump storage and concentrated solar molten salt heat storage for steam turbine electrical generation. Energy demand management is poorly explored in Canada and elsewhere - our homes and businesses operate on an unrestricted demand. Simple monitoring and energy demand-ranking software can easily reduce peaks demands and move lower ranked uses to non-peak periods, thereby reducing the grid size needed to meet peak demands. Peak demand strains the current energy grid capacity and often requires demand balancing projects and

Development of robust building energy demand-side control strategy under uncertainty

NASA Astrophysics Data System (ADS)

Kim, Sean Hay

The potential of carbon emission regulations applied to an individual building will encourage building owners to purchase utility-provided green power or to employ onsite renewable energy generation. As both cases are based on intermittent renewable energy sources, demand side control is a fundamental precondition for maximizing the effectiveness of using renewable energy sources. Such control leads to a reduction in peak demand and/or in energy demand variability, therefore, such reduction in the demand profile eventually enhances the efficiency of an erratic supply of renewable energy. The combined operation of active thermal energy storage and passive building thermal mass has shown substantial improvement in demand-side control performance when compared to current state-of-the-art demand-side control measures. Specifically, "model-based" optimal control for this operation has the potential to significantly increase performance and bring economic advantages. However, due to the uncertainty in certain operating conditions in the field its control effectiveness could be diminished and/or seriously damaged, which results in poor performance. This dissertation pursues improvements of current demand-side controls under uncertainty by proposing a robust supervisory demand-side control strategy that is designed to be immune from uncertainty and perform consistently under uncertain conditions. Uniqueness and superiority of the proposed robust demand-side controls are found as below: a. It is developed based on fundamental studies about uncertainty and a systematic approach to uncertainty analysis. b. It reduces variability of performance under varied conditions, and thus avoids the worst case scenario. c. It is reactive in cases of critical "discrepancies" observed caused by the unpredictable uncertainty that typically scenario uncertainty imposes, and thus it increases control efficiency. This is obtainable by means of i) multi-source composition of weather forecasts

Renewable Electricity Futures Study. Executive Summary

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

Mai, T.; Sandor, D.; Wiser, R.

2012-12-01

The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a futuremore » through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).« less

GMLC Extreme Event Modeling -- Slow-Dynamics Models for Renewable Energy Resources

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

Korkali, M.; Min, L.

The need for slow dynamics models of renewable resources in cascade modeling essentially arises from the challenges associated with the increased use of solar and wind electric power. Indeed, the main challenge is that the power produced by wind and sunlight is not consistent; thus, renewable energy resources tend to have variable output power on many different timescales, including the timescales that a cascade unfolds.

Travel Demand Modeling

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

Southworth, Frank; Garrow, Dr. Laurie

This chapter describes the principal types of both passenger and freight demand models in use today, providing a brief history of model development supported by references to a number of popular texts on the subject, and directing the reader to papers covering some of the more recent technical developments in the area. Over the past half century a variety of methods have been used to estimate and forecast travel demands, drawing concepts from economic/utility maximization theory, transportation system optimization and spatial interaction theory, using and often combining solution techniques as varied as Box-Jenkins methods, non-linear multivariate regression, non-linear mathematical programming,more » and agent-based microsimulation.« less

HOMER: The hybrid optimization model for electric renewable

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

Lilienthal, P.; Flowers, L.; Rossmann, C.

1995-12-31

Hybrid renewable systems are often more cost-effective than grid extensions or isolated diesel generators for providing power to remote villages. There are a wide variety of hybrid systems being developed for village applications that have differing combinations of wind, photovoltaics, batteries, and diesel generators. Due to variations in loads and resources determining the most appropriate combination of these components for a particular village is a difficult modelling task. To address this design problem the National Renewable Energy Laboratory has developed the Hybrid Optimization Model for Electric Renewables (HOMER). Existing models are either too detailed for screening analysis or too simplemore » for reliable estimation of performance. HOMER is a design optimization model that determines the configuration, dispatch, and load management strategy that minimizes life-cycle costs for a particular site and application. This paper describes the HOMER methodology and presents representative results.« less

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

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

A population-induced renewable energy timeline in nine world regions

NASA Astrophysics Data System (ADS)

Warner, Kevin; Jones, Glenn

2016-04-01

Population growth and increasing energy access are incongruous with forecasts of declining non-renewable energy production and climate change concerns. The current world population of 7.3 billion is projected to reach 8.4 billion by 2030 and 11.2 billion by 2100. Currently, 1.2 billion people worldwide do not have access to electricity. The World Bank's Sustainable Energy for All initiative seeks to provide universal global access to energy by the year 2030. Though universal energy access is desirable, a significant reduction in fossil fuel usage is required before mid-century if global warming is to be limited to <2°C. Today, the global energy mix is derived from 91% non-renewable (oil, coal, natural gas, nuclear) and 9% renewable (e.g., hydropower, wind, solar, biofuels) sources. Here we use a nine region model of the world to quantify the changes in the global energy mix necessary to address population and climate change under two energy-use scenarios and find that significant restructuring of the current energy mix will be necessary to support the 2014 UN population projections. We also find that renewable energy production must comprise 87-94% of global energy consumption by 2100. Our study suggests >50% renewable energy needs to occur by 2028 in a <2°C warming scenario, but not until 2054 in an unconstrained energy use scenario. Each of the nine regions faces unique energy-population challenges in the coming decades. We find that global energy demand in 2100 will be more than double that of today; of this demand, 82% will need to be derived from renewable sources. More renewable energy production will be required in 2100 than the 2014 total global energy production. Given the required rate and magnitude of this transition to renewable energy, it is unlikely that the <2°C goal can be met. Focus should be placed on expanding renewable energy as quickly as possible in order to supply the projected world energy demand and to limit warming to 2.5-3°C by 2100.

Optimization under Uncertainty of a Biomass-integrated Renewable Energy Microgrid with Energy Storage

NASA Astrophysics Data System (ADS)

Zheng, Yingying

The growing energy demands and needs for reducing carbon emissions call more and more attention to the development of renewable energy technologies and management strategies. Microgrids have been developed around the world as a means to address the high penetration level of renewable generation and reduce greenhouse gas emissions while attempting to address supply-demand balancing at a more local level. This dissertation presents a model developed to optimize the design of a biomass-integrated renewable energy microgrid employing combined heat and power with energy storage. A receding horizon optimization with Monte Carlo simulation were used to evaluate optimal microgrid design and dispatch under uncertainties in the renewable energy and utility grid energy supplies, the energy demands, and the economic assumptions so as to generate a probability density function for the cost of energy. Case studies were examined for a conceptual utility grid-connected microgrid application in Davis, California. The results provide the most cost effective design based on the assumed energy load profile, local climate data, utility tariff structure, and technical and financial performance of the various components of the microgrid. Sensitivity and uncertainty analyses are carried out to illuminate the key parameters that influence the energy costs. The model application provides a means to determine major risk factors associated with alternative design integration and operating strategies.

Distributed Generation Market Demand Model | NREL

Science.gov Websites

Demand Model The Distributed Generation Market Demand (dGen) model simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the dGen model can help develop deployment forecasts for distributed resources, including sensitivity to

A Mixed Kijima Model Using the Weibull-Based Generalized Renewal Processes

PubMed Central

2015-01-01

Generalized Renewal Processes are useful for approaching the rejuvenation of dynamical systems resulting from planned or unplanned interventions. We present new perspectives for the Generalized Renewal Processes in general and for the Weibull-based Generalized Renewal Processes in particular. Disregarding from literature, we present a mixed Generalized Renewal Processes approach involving Kijima Type I and II models, allowing one to infer the impact of distinct interventions on the performance of the system under study. The first and second theoretical moments of this model are introduced as well as its maximum likelihood estimation and random sampling approaches. In order to illustrate the usefulness of the proposed Weibull-based Generalized Renewal Processes model, some real data sets involving improving, stable, and deteriorating systems are used. PMID:26197222

Model documentation renewable fuels module of the National Energy Modeling System

NASA Astrophysics Data System (ADS)

1995-06-01

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1995 Annual Energy Outlook (AEO95) forecasts. The report catalogs and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. The RFM consists of six analytical submodules that represent each of the major renewable energy resources -- wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. The RFM also reads in hydroelectric facility capacities and capacity factors from a data file for use by the NEMS Electricity Market Module (EMM). The purpose of the RFM is to define the technological, cost, and resource size characteristics of renewable energy technologies. These characteristics are used to compute a levelized cost to be competed against other similarly derived costs from other energy sources and technologies. The competition of these energy sources over the NEMS time horizon determines the market penetration of these renewable energy technologies. The characteristics include available energy capacity, capital costs, fixed operating costs, variable operating costs, capacity factor, heat rate, construction lead time, and fuel product price.

Quantifying Co-benefits of Renewable Energy through Integrated Electricity and Air Quality Modeling

NASA Astrophysics Data System (ADS)

Abel, D.

2016-12-01

This work focuses on the coordination of electricity sector changes with air quality and health improvement strategies through the integration of electricity and air quality models. Two energy models are used to calculate emission perturbations associated with changes in generation technology (20% generation from solar photovoltaics) and demand (future electricity use under a warmer climate). Impacts from increased solar PV penetration are simulated with the electricity model GridView, in collaboration with the National Renewable Energy Laboratory (NREL). Generation results are used to scale power plant emissions from an inventory developed by the Lake Michigan Air Directors Consortium (LADCO). Perturbed emissions and are used to calculate secondary particulate matter with the Community Multiscale Air Quality (CMAQ) model. We find that electricity NOx and SO2 emissions decrease at a rate similar to the total fraction of electricity supplied by solar. Across the Eastern U.S. region, average PM2.5 is reduced 5% over the summer, with highest reduction in regions and on days of greater PM2.5. A similar approach evaluates the air quality impacts of elevated electricity demand under a warmer climate. Meteorology is selected from the North American Regional Climate Change Assessment Program (NARCCAP) and input to a building energy model, eQUEST, to assess electricity demand as a function of ambient temperature. The associated generation and emissions are calculated on a plant-by-plant basis by the MyPower power sector model. These emissions are referenced to the 2011 National Emissions Inventory to be modeled in CMAQ for the Eastern U.S. and extended to health impact evaluation with the Environmental Benefits Mapping and Analysis Program (BenMAP). All results focus on the air quality and health consequences of energy system changes, considering grid-level changes to meet climate and air quality goals.

Revisions to the Wharton EFA Automobile Demand Model : The Wharton EFA Motor Vehicle Demand Model (Mark I)

DOT National Transportation Integrated Search

1980-12-01

The report documents revisions made to the Wharton EFA Automobile Demand Model to produce the Wharton EFA Motor Vehicle Demand Model (Mark I). Equations are reestimated for the total desired stock of autos and for desired shares by size class, includ...

Analysis and comparison of methods for the preparation of domestic hot water from district heating system, selected renewable and non-renewable sources in low-energy buildings

NASA Astrophysics Data System (ADS)

Knapik, Maciej

2018-02-01

The article presents an economic analysis and comparison of selected (district heating, natural gas, heat pump with renewable energy sources) methods for the preparation of domestic hot water in a building with low energy demand. In buildings of this type increased demand of energy for domestic hot water preparation in relation to the total energy demand can be observed. As a result, the proposed solutions allow to further lower energy demand by using the renewable energy sources. This article presents the results of numerical analysis and calculations performed mainly in MATLAB software, based on typical meteorological years. The results showed that system with heat pump and renewable energy sources Is comparable with district heating system.

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

Development of the Optimum Operation Scheduling Model of Domestic Electric Appliances for the Supply-Demand Adjustment in a Power System

NASA Astrophysics Data System (ADS)

Ikegami, Takashi; Iwafune, Yumiko; Ogimoto, Kazuhiko

The high penetration of variable renewable generation such as Photovoltaic (PV) systems will cause the issue of supply-demand imbalance in a whole power system. The activation of the residential power usage, storage and generation by sophisticated scheduling and control using the Home Energy Management System (HEMS) will be needed to balance power supply and demand in the near future. In order to evaluate the applicability of the HEMS as a distributed controller for local and system-wide supply-demand balances, we developed an optimum operation scheduling model of domestic electric appliances using the mixed integer linear programming. Applying this model to several houses with dynamic electricity prices reflecting the power balance of the total power system, it was found that the adequate changes in electricity prices bring about the shift of residential power usages to control the amount of the reverse power flow due to excess PV generation.

Electricity demand and storage dispatch modeling for buildings and implications for the smartgrid

NASA Astrophysics Data System (ADS)

Zheng, Menglian; Meinrenken, Christoph

2013-04-01

As an enabler for demand response (DR), electricity storage in buildings has the potential to lower costs and carbon footprint of grid electricity while simultaneously mitigating grid strain and increasing its flexibility to integrate renewables (central or distributed). We present a stochastic model to simulate minute-by-minute electricity demand of buildings and analyze the resulting electricity costs under actual, currently available DR-enabling tariffs in New York State, namely a peak/offpeak tariff charging by consumed energy (monthly total kWh) and a time of use tariff charging by power demand (monthly peak kW). We then introduce a variety of electrical storage options (from flow batteries to flywheels) and determine how DR via temporary storage may increase the overall net present value (NPV) for consumers (comparing the reduced cost of electricity to capital and maintenance costs of the storage). We find that, under the total-energy tariff, only medium-term storage options such as batteries offer positive NPV, and only at the low end of storage costs (optimistic scenario). Under the peak-demand tariff, however, even short-term storage such as flywheels and superconducting magnetic energy offer positive NPV. Therefore, these offer significant economic incentive to enable DR without affecting the consumption habits of buildings' residents. We discuss implications for smartgrid communication and our future work on real-time price tariffs.

Demand Response and Energy Storage Integration Study

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

Ma, Ookie; Cheung, Kerry; Olsen, Daniel J.

2016-03-01

Demand response and energy storage resources present potentially important sources of bulk power system services that can aid in integrating variable renewable generation. While renewable integration studies have evaluated many of the challenges associated with deploying large amounts of variable wind and solar generation technologies, integration analyses have not yet fully incorporated demand response and energy storage resources. This report represents an initial effort in analyzing the potential integration value of demand response and energy storage, focusing on the western United States. It evaluates two major aspects of increased deployment of demand response and energy storage: (1) Their operational valuemore » in providing bulk power system services and (2) Market and regulatory issues, including potential barriers to deployment.« less

Demand Response and Energy Storage Integration Study

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

Ma, Ookie; Cheung, Kerry

Demand response and energy storage resources present potentially important sources of bulk power system services that can aid in integrating variable renewable generation. While renewable integration studies have evaluated many of the challenges associated with deploying large amounts of variable wind and solar generation technologies, integration analyses have not yet fully incorporated demand response and energy storage resources. This report represents an initial effort in analyzing the potential integration value of demand response and energy storage, focusing on the western United States. It evaluates two major aspects of increased deployment of demand response and energy storage: (1) Their operational valuemore » in providing bulk power system services and (2) Market and regulatory issues, including potential barriers to deployment.« less

Distributed Energy Generation Systems Based on Renewable Energy and Natural Gas Blending: New Business Models for Economic Incentives, Electricity Market Design and Regulatory Innovation

NASA Astrophysics Data System (ADS)

Nyangon, Joseph

Expansion of distributed energy resources (DERs) including solar photovoltaics, small- and medium-sized wind farms, gas-fired distributed generation, demand-side management, and energy storage poses significant complications to the design, operation, business model, and regulation of electricity systems. Using statistical regression analysis, this dissertation assesses if increased use of natural gas results in reduced renewable energy capacity, and if natural gas growth is correlated with increased or decreased non-fossil renewable fuels demand. System Generalized Method of Moments (System GMM) estimation of the dynamic relationship was performed on the indicators in the econometric model for the ten states with the fastest growth in solar generation capacity in the U.S. (e.g., California, North Carolina, Arizona, Nevada, New Jersey, Utah, Massachusetts, Georgia, Texas, and New York) to analyze the effect of natural gas on renewable energy diffusion and the ratio of fossil fuels increase for the period 2001-2016 to policy driven solar demand. The study identified ten major drivers of change in electricity systems, including growth in distributed energy generation systems such as intermittent renewable electricity and gas-fired distributed generation; flat to declining electricity demand growth; aging electricity infrastructure and investment gaps; proliferation of affordable information and communications technologies (e.g., advanced meters or interval meters), increasing innovations in data and system optimization; and greater customer engagement. In this ongoing electric power sector transformation, natural gas and fast-flexing renewable resources (mostly solar and wind energy) complement each other in several sectors of the economy. The dissertation concludes that natural gas has a positive impact on solar and wind energy development: a 1% rise in natural gas capacity produces 0.0304% increase in the share of renewable energy in the short-run (monthly) compared

Teaching Aggregate Demand and Supply Models

ERIC Educational Resources Information Center

Wells, Graeme

2010-01-01

The author analyzes the inflation-targeting model that underlies recent textbook expositions of the aggregate demand-aggregate supply approach used in introductory courses in macroeconomics. He shows how numerical simulations of a model with inflation inertia can be used as a tool to help students understand adjustments in response to demand and…

Development of Ensemble Model Based Water Demand Forecasting Model

NASA Astrophysics Data System (ADS)

Kwon, Hyun-Han; So, Byung-Jin; Kim, Seong-Hyeon; Kim, Byung-Seop

2014-05-01

In recent years, Smart Water Grid (SWG) concept has globally emerged over the last decade and also gained significant recognition in South Korea. Especially, there has been growing interest in water demand forecast and optimal pump operation and this has led to various studies regarding energy saving and improvement of water supply reliability. Existing water demand forecasting models are categorized into two groups in view of modeling and predicting their behavior in time series. One is to consider embedded patterns such as seasonality, periodicity and trends, and the other one is an autoregressive model that is using short memory Markovian processes (Emmanuel et al., 2012). The main disadvantage of the abovementioned model is that there is a limit to predictability of water demands of about sub-daily scale because the system is nonlinear. In this regard, this study aims to develop a nonlinear ensemble model for hourly water demand forecasting which allow us to estimate uncertainties across different model classes. The proposed model is consist of two parts. One is a multi-model scheme that is based on combination of independent prediction model. The other one is a cross validation scheme named Bagging approach introduced by Brieman (1996) to derive weighting factors corresponding to individual models. Individual forecasting models that used in this study are linear regression analysis model, polynomial regression, multivariate adaptive regression splines(MARS), SVM(support vector machine). The concepts are demonstrated through application to observed from water plant at several locations in the South Korea. Keywords: water demand, non-linear model, the ensemble forecasting model, uncertainty. Acknowledgements This subject is supported by Korea Ministry of Environment as "Projects for Developing Eco-Innovation Technologies (GT-11-G-02-001-6)

Demand Response Availability Profiles for California in the Year 2020

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

Olsen, Daniel; Sohn, Michael; Piette, Mary Ann

2014-11-01

Demand response (DR) is being considered as a valuable resource for keeping the electrical grid stable and efficient, and deferring upgrades to generation, transmission, and distribution systems. However, simulations to determine how much infrastructure upgrades can be deferred are necessary in order to plan optimally. Production cost modeling is a technique, which simulates the dispatch of generators to meet demand and reserves in each hour of the year, at minimal cost. By integrating demand response resources into a production cost model (PCM), their value to the grid can be estimated and used to inform operations and infrastructure planning. DR availabilitymore » profiles and constraints for 13 end-uses in California for the year 2020 were developed by Lawrence Berkeley National Laboratory (LBNL), and integrated into a production cost model by Lawrence Livermore National Laboratory (LLNL), for the California Energy Commission’s Value of Energy Storage and Demand Response for Renewable Integration in California Study. This report summarizes the process for developing the DR availability profiles for California, and their aggregate capabilities. While LBNL provided potential DR hourly profiles for regulation product in the ancillary services market and five-minute load following product in the energy market for LLNL’s study, additional results in contingency reserves and an assumed flexible product are also defined. These additional products are included in the analysis for managing high ramps associated with renewable generation and capacity products and they are also presented in this report.« less

The bright side of snow cover effects on PV production - How to lower the seasonal mismatch between electricity supply and demand in a fully renewable Switzerland

NASA Astrophysics Data System (ADS)

Kahl, Annelen; Dujardin, Jérôme; Dupuis, Sonia; Lehning, Michael

2017-04-01

One of the major problems with solar PV in the context of a fully renewable electricity production at mid-latitudes is the trend of higher production in summer and lower production in winter. This trend is most often exactly opposite to demand patterns, causing a seasonal mismatch that requires extensive balancing power from other production sources or large storage capacities. Which possibilities do we have to bring PV production into closer correlation with demand? This question motivated our research and in response we investigated the effects of placing PV panels at different tilt angles in regions with extensive snow cover to increase winter production from ground reflected short wave radiation. The aim of this project is therefore to quantify the effect of varying snow cover duration (SCD) and of panel tilt angle on the annual total production and on production during winter months when electricity is most needed. We chose Switzerland as ideal test site, because it has a wide range of snow cover conditions and a high potential for renewable electricity production. But methods can be applied to other regions of comparable conditions for snow cover and irradiance. Our analysis can be separated into two steps: 1. A systematic, GIS and satellite-based analysis for all of Switzerland: We use time series of satellite-derived irradiance, and snow cover characteristics together with land surface cover types and elevation information to quantify the environmental conditions and to estimate potential production and ideal tilt angles. 2. A scenario-based analysis that contrasts the production patterns of different placement scenarios for PV panels in urban, rural and mountainous areas. We invoke a model of a fully renewable electricity system (including Switzerland's large hydropower system) at national level to compute the electricity import and storage capacity that will be required to balance the remaining mismatch between production and demand to further illuminate

Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective

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

Cole, Wesley; Frew, Bethany; Mai, Trieu

Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision-makers. With the recent surge in variable renewable energy (VRE) generators — primarily wind and solar photovoltaics — the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. This report summarizes the analyses and model experiments that were conducted as part of two workshops on modeling VRE for national-scale capacity expansion models. It discusses the various methods for treatingmore » VRE among four modeling teams from the Electric Power Research Institute (EPRI), the U.S. Energy Information Administration (EIA), the U.S. Environmental Protection Agency (EPA), and the National Renewable Energy Laboratory (NREL). The report reviews the findings from the two workshops and emphasizes the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making. This research is intended to inform the energy modeling community on the modeling of variable renewable resources, and is not intended to advocate for or against any particular energy technologies, resources, or policies.« less

A generation-attraction model for renewable energy flows in Italy: A complex network approach

NASA Astrophysics Data System (ADS)

Valori, Luca; Giannuzzi, Giovanni Luca; Facchini, Angelo; Squartini, Tiziano; Garlaschelli, Diego; Basosi, Riccardo

2016-10-01

In recent years, in Italy, the trend of the electricity demand and the need to connect a large number of renewable energy power generators to the power-grid, developed a novel type of energy transmission/distribution infrastructure. The Italian Transmission System Operator (TSO) and the Distribution System Operator (DSO), worked on a new infrastructural model, based on electronic meters and information technology. In pursuing this objective it is crucial importance to understand how even more larger shares of renewable energy can be fully integrated, providing a constant and reliable energy background over space and time. This is particularly true for intermittent sources as photovoltaic installations due to the fine-grained distribution of them across the Country. In this work we use an over-simplified model to characterize the Italian power grid as a graph whose nodes are Italian municipalities and the edges cross the administrative boundaries between a selected municipality and its first neighbours, following a Delaunay triangulation. Our aim is to describe the power flow as a diffusion process over a network, and using open data on the solar irradiation at the ground level, we estimate the production of photovoltaic energy in each node. An attraction index was also defined using demographic data, in accordance with average per capita energy consumption data. The available energy on each node was calculated by finding the stationary state of a generation-attraction model.

An optimal renewable energy mix for Indonesia

NASA Astrophysics Data System (ADS)

Leduc, Sylvain; Patrizio, Piera; Yowargana, Ping; Kraxner, Florian

2016-04-01

Indonesia has experienced a constant increase of the use of petroleum and coal in the power sector, while the share of renewable sources has remained stable at 6% of the total energy production during the last decade. As its domestic energy demand undeniably continues to grow, Indonesia is committed to increase the production of renewable energy. Mainly to decrease its dependency on fossil fuel-based resources, and to decrease the anthropogenic emissions, the government of Indonesia has established a 23 percent target for renewable energy by 2025, along with a 100 percent electrification target by 2020 (the current rate is 80.4 percent). In that respect, Indonesia has abundant resources to meet these targets, but there is - inter alia - a lack of proper integrated planning, regulatory support, investment, distribution in remote areas of the Archipelago, and missing data to back the planning. To support the government of Indonesia in its sustainable energy system planning, a geographic explicit energy modeling approach is applied. This approach is based on the energy systems optimization model BeWhere, which identifies the optimal location of energy conversion sites based on the minimization of the costs of the supply chain. The model will incorporate the existing fossil fuel-based infrastructures, and evaluate the optimal costs, potentials and locations for the development of renewable energy technologies (i.e., wind, solar, hydro, biomass and geothermal based technologies), as well as the development of biomass co-firing in existing coal plants. With the help of the model, an optimally adapted renewable energy mix - vis-à-vis the competing fossil fuel based resources and applicable policies in order to promote the development of those renewable energy technologies - will be identified. The development of the optimal renewable energy technologies is carried out with special focus on nature protection and cultural heritage areas, where feedstock (e.g., biomass

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.

A Small Aircraft Transportation System (SATS) Demand Model

NASA Technical Reports Server (NTRS)

Long, Dou; Lee, David; Johnson, Jesse; Kostiuk, Peter; Yackovetsky, Robert (Technical Monitor)

2001-01-01

The Small Aircraft Transportation System (SATS) demand modeling is a tool that will be useful for decision-makers to analyze SATS demands in both airport and airspace. We constructed a series of models following the general top-down, modular principles in systems engineering. There are three principal models, SATS Airport Demand Model (SATS-ADM), SATS Flight Demand Model (SATS-FDM), and LMINET-SATS. SATS-ADM models SATS operations, by aircraft type, from the forecasts in fleet, configuration and performance, utilization, and traffic mixture. Given the SATS airport operations such as the ones generated by SATS-ADM, SATS-FDM constructs the SATS origin and destination (O&D) traffic flow based on the solution of the gravity model, from which it then generates SATS flights using the Monte Carlo simulation based on the departure time-of-day profile. LMINET-SATS, an extension of LMINET, models SATS demands at airspace and airport by all aircraft operations in US The models use parameters to provide the user with flexibility and ease of use to generate SATS demand for different scenarios. Several case studies are included to illustrate the use of the models, which are useful to identify the need for a new air traffic management system to cope with SATS.

Potential for deserts to supply reliable renewable electric power

NASA Astrophysics Data System (ADS)

Labordena, Mercè; Lilliestam, Johan

2015-04-01

transmission corridors from the generation areas to the demand centers in the target regions, using a GIS-based transmission algorithm that minimizes economic, social and environmental costs. Third, we use the multi-scale energy system model Calliope to specify the optimal configuration and operation of the CSP fleet to reliably follow the demand every hour of the year in the target regions, and to calculate the levelized cost of doing so, including both generation and transmission costs. The final output will show whether and how much reliable renewable electricity can be supplied from CSP fleets in deserts to demand centers in adjacent regions, at which costs this is possible, as well as a detailed description of the routes of HVDC transmission links. We expect to find that the potential for deserts to supply reliable CSP to the regions in focus is very large in all cases, despite the long distances.

Model Scaling of Hydrokinetic Ocean Renewable Energy Systems

NASA Astrophysics Data System (ADS)

von Ellenrieder, Karl; Valentine, William

2013-11-01

Numerical simulations are performed to validate a non-dimensional dynamic scaling procedure that can be applied to subsurface and deeply moored systems, such as hydrokinetic ocean renewable energy devices. The prototype systems are moored in water 400 m deep and include: subsurface spherical buoys moored in a shear current and excited by waves; an ocean current turbine excited by waves; and a deeply submerged spherical buoy in a shear current excited by strong current fluctuations. The corresponding model systems, which are scaled based on relative water depths of 10 m and 40 m, are also studied. For each case examined, the response of the model system closely matches the scaled response of the corresponding full-sized prototype system. The results suggest that laboratory-scale testing of complete ocean current renewable energy systems moored in a current is possible. This work was supported by the U.S. Southeast National Marine Renewable Energy Center (SNMREC).

Impacts of demand response and renewable generation in electricity power market

NASA Astrophysics Data System (ADS)

Zhao, Zhechong

This thesis presents the objective of the research which is to analyze the impacts of uncertain wind power and demand response on power systems operation and power market clearing. First, in order to effectively utilize available wind generation, it is usually given the highest priority by assigning zero or negative energy bidding prices when clearing the day-ahead electric power market. However, when congestion occurs, negative wind bidding prices would aggravate locational marginal prices (LMPs) to be negative in certain locations. A load shifting model is explored to alleviate possible congestions and enhance the utilization of wind generation, by shifting proper amount of load from peak hours to off peaks. The problem is to determine proper amount of load to be shifted, for enhancing the utilization of wind generation, alleviating transmission congestions, and making LMPs to be non-negative values. The second piece of work considered the price-based demand response (DR) program which is a mechanism for electricity consumers to dynamically manage their energy consumption in response to time-varying electricity prices. It encourages consumers to reduce their energy consumption when electricity prices are high, and thereby reduce the peak electricity demand and alleviate the pressure to power systems. However, it brings additional dynamics and new challenges on the real-time supply and demand balance. Specifically, price-sensitive DR load levels are constantly changing in response to dynamic real-time electricity prices, which will impact the economic dispatch (ED) schedule and in turn affect electricity market clearing prices. This thesis adopts two methods for examining the impacts of different DR price elasticity characteristics on the stability performance: a closed-loop iterative simulation method and a non-iterative method based on the contraction mapping theorem. This thesis also analyzes the financial stability of DR load consumers, by incorporating

A Simultaneous Equation Demand Model for Block Rates

NASA Astrophysics Data System (ADS)

Agthe, Donald E.; Billings, R. Bruce; Dobra, John L.; Raffiee, Kambiz

1986-01-01

This paper examines the problem of simultaneous-equations bias in estimation of the water demand function under an increasing block rate structure. The Hausman specification test is used to detect the presence of simultaneous-equations bias arising from correlation of the price measures with the regression error term in the results of a previously published study of water demand in Tucson, Arizona. An alternative simultaneous equation model is proposed for estimating the elasticity of demand in the presence of block rate pricing structures and availability of service charges. This model is used to reestimate the price and rate premium elasticities of demand in Tucson, Arizona for both the usual long-run static model and for a simple short-run demand model. The results from these simultaneous equation models are consistent with a priori expectations and are unbiased.

Energy and other non-renewable resources

NASA Technical Reports Server (NTRS)

1975-01-01

Anticipated U.S. demands for non-renewable energy and mineral resources exceed domestic supplies essential for economic growth. For the long term changes necessary in the energy supply and demand gap, new technologies and substitute materials as well as legislation and socio-economic strategies are elaborated.

System Dynamic Model for the Accumulation of Renewable Electricity using Power-to-Gas and Power-to-Liquid Concepts

NASA Astrophysics Data System (ADS)

Blumberga, Andra; Timma, Lelde; Blumberga, Dagnija

2015-12-01

When the renewable energy is used, the challenge is match the supply of intermittent energy with the demand for energy therefore the energy storage solutions should be used. This paper is dedicated to hydrogen accumulation from wind sources. The case study investigates the conceptual system that uses intermitted renewable energy resources to produce hydrogen (power-to-gas concept) and fuel (power-to-liquid concept). For this specific case study hydrogen is produced from surplus electricity generated by wind power plant trough electrolysis process and fuel is obtained by upgrading biogas to biomethane using hydrogen. System dynamic model is created for this conceptual system. The developed system dynamics model has been used to simulate 2 different scenarios. The results show that in both scenarios the point at which the all electricity needs of Latvia are covered is obtained. Moreover, the methodology of system dynamics used in this paper is white-box model that allows to apply the developed model to other case studies and/or to modify model based on the newest data. The developed model can be used for both scientific research and policy makers to better understand the dynamic relation within the system and the response of system to changes in both internal and external factors.

Examination of simplified travel demand model. [Internal volume forecasting model

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

Smith, R.L. Jr.; McFarlane, W.J.

1978-01-01

A simplified travel demand model, the Internal Volume Forecasting (IVF) model, proposed by Low in 1972 is evaluated as an alternative to the conventional urban travel demand modeling process. The calibration of the IVF model for a county-level study area in Central Wisconsin results in what appears to be a reasonable model; however, analysis of the structure of the model reveals two primary mis-specifications. Correction of the mis-specifications leads to a simplified gravity model version of the conventional urban travel demand models. Application of the original IVF model to ''forecast'' 1960 traffic volumes based on the model calibrated for 1970more » produces accurate estimates. Shortcut and ad hoc models may appear to provide reasonable results in both the base and horizon years; however, as shown by the IVF mode, such models will not always provide a reliable basis for transportation planning and investment decisions.« less

Modeling demand for public transit services in rural areas

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

Attaluri, P.; Seneviratne, P.N.; Javid, M.

1997-05-01

Accurate estimates of demand are critical for planning, designing, and operating public transit systems. Previous research has demonstrated that the expected demand in rural areas is a function of both demographic and transit system variables. Numerous models have been proposed to describe the relationship between the aforementioned variables. However, most of them are site specific and their validity over time and space is not reported or perhaps has not been tested. Moreover, input variables in some cases are extremely difficult to quantify. In this article, the estimation of demand using the generalized linear modeling technique is discussed. Two separate models,more » one for fixed-route and another for demand-responsive services, are presented. These models, calibrated with data from systems in nine different states, are used to demonstrate the appropriateness and validity of generalized linear models compared to the regression models. They explain over 70% of the variation in expected demand for fixed-route services and 60% of the variation in expected demand for demand-responsive services. It was found that the models are spatially transferable and that data for calibration are easily obtainable.« less

Transmission expansion with smart switching under demand uncertainty and line failures

DOE PAGES

Schumacher, Kathryn M.; Chen, Richard Li-Yang; Cohn, Amy E. M.

2016-06-07

One of the major challenges in deciding where to build new transmission lines is that there is uncertainty regarding future loads, renewal generation output and equipment failures. We propose a robust optimization model whose transmission expansion solutions ensure that demand can be met over a wide range of conditions. Specifically, we require feasible operation for all loads and renewable generation levels within given ranges, and for all single transmission line failures. Furthermore, we consider transmission switching as an allowable recovery action. This relatively inexpensive method of redirecting power flows improves resiliency, but introduces computational challenges. Lastly, we present a novelmore » algorithm to solve this model. Computational results are discussed.« less

Experimental study of mini SCADA renewable energy management system on microgrid using Raspberry Pi

NASA Astrophysics Data System (ADS)

Tridianto, E.; Permatasari, P. D.; Ali, I. R.

2018-03-01

Renewable Energy Management System (REMS) is a device that can be able to monitor power through a microgrid. The purpose of this system is to optimize power usage that produced from renewable energy with the result that reduces power demand from the grid. To reach the goal this device manage the load power needs fully supplied by renewable energy when the power produced from renewable energy is higher than load demand, besides power surplus will be stored in battery in this way energy stored in battery can be used when it needed. When the power produced from renewable energy can not satisfy the power demand, power will supply by renewable energy and grid. This device uses power meters for record any power flow through microgrid. In order to manage power flow in microgrid this system use relay module. The user can find out energy consumption (consumed by the load) and production (produced by renewable energy) in a period of time so that the user can switch on the load in right time.

Model documentation Renewable Fuels Module of the National Energy Modeling System

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

NONE

1996-01-01

This report documents the objectives, analaytical approach and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1996 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described.

Economic lot sizing in a production system with random demand

NASA Astrophysics Data System (ADS)

Lee, Shine-Der; Yang, Chin-Ming; Lan, Shu-Chuan

2016-04-01

An extended economic production quantity model that copes with random demand is developed in this paper. A unique feature of the proposed study is the consideration of transient shortage during the production stage, which has not been explicitly analysed in existing literature. The considered costs include set-up cost for the batch production, inventory carrying cost during the production and depletion stages in one replenishment cycle, and shortage cost when demand cannot be satisfied from the shop floor immediately. Based on renewal reward process, a per-unit-time expected cost model is developed and analysed. Under some mild condition, it can be shown that the approximate cost function is convex. Computational experiments have demonstrated that the average reduction in total cost is significant when the proposed lot sizing policy is compared with those with deterministic demand.

Modelling supply and demand of bioenergy from short rotation coppice and Miscanthus in the UK.

PubMed

Bauen, A W; Dunnett, A J; Richter, G M; Dailey, A G; Aylott, M; Casella, E; Taylor, G

2010-11-01

Biomass from lignocellulosic energy crops can contribute to primary energy supply in the short term in heat and electricity applications and in the longer term in transport fuel applications. This paper estimates the optimal feedstock allocation of herbaceous and woody lignocellulosic energy crops for England and Wales based on empirical productivity models. Yield maps for Miscanthus, willow and poplar, constrained by climatic, soil and land use factors, are used to estimate the potential resource. An energy crop supply-cost curve is estimated based on the resource distribution and associated production costs. The spatial resource model is then used to inform the supply of biomass to geographically distributed demand centres, with co-firing plants used as an illustration. Finally, the potential contribution of energy crops to UK primary energy and renewable energy targets is discussed. Copyright 2010 Elsevier Ltd. All rights reserved.

When to Renew Software Licences at HPC Centres? A Mathematical Analysis

NASA Astrophysics Data System (ADS)

Baolai, Ge; MacIsaac, Allan B.

2010-11-01

In this paper we study a common problem faced by many high performance computing (HPC) centres: When and how to renew commercial software licences. Software vendors often sell perpetual licences along with forward update and support contracts at an additional, annual cost. Every year or so, software support personnel and the budget units of HPC centres are required to make the decision of whether or not to renew such support, and usually such decisions are made intuitively. The total cost for a continuing support contract can, however, be costly. One might therefore want a rational answer to the question of whether the option for a renewal should be exercised and when. In an attempt to study this problem within a market framework, we present the mathematical problem derived for the day to day operation of a hypothetical HPC centre that charges for the use of software packages. In the mathematical model, we assume that the uncertainty comes from the demand, number of users using the packages, as well as the price. Further we assume the availability of up to date software versions may also affect the demand. We develop a renewal strategy that aims to maximize the expected profit from the use the software under consideration. The derived problem involves a decision tree, which constitutes a numerical procedure that can be processed in parallel.

NREL: Renewable Resource Data Center - Biomass Resource Models and Tools

Science.gov Websites

Models and Tools The Renewable Resource Data Center (RReDC) features the following biomass models Models & Tools Publications Related Links Geothermal Resource Information Solar Resource Information

A longitudinal test of the demand-control model using specific job demands and specific job control.

PubMed

de Jonge, Jan; van Vegchel, Natasja; Shimazu, Akihito; Schaufeli, Wilmar; Dormann, Christian

2010-06-01

Supportive studies of the demand-control (DC) model were more likely to measure specific demands combined with a corresponding aspect of control. A longitudinal test of Karasek's (Adm Sci Q. 24:285-308, 1) job strain hypothesis including specific measures of job demands and job control, and both self-report and objectively recorded well-being. Job strain hypothesis was tested among 267 health care employees from a two-wave Dutch panel survey with a 2-year time lag. Significant demand/control interactions were found for mental and emotional demands, but not for physical demands. The association between job demands and job satisfaction was positive in case of high job control, whereas this association was negative in case of low job control. In addition, the relation between job demands and psychosomatic health symptoms/sickness absence was negative in case of high job control and positive in case of low control. Longitudinal support was found for the core assumption of the DC model with specific measures of job demands and job control as well as self-report and objectively recorded well-being.

Modelling Per Capita Water Demand Change to Support System Planning

NASA Astrophysics Data System (ADS)

Garcia, M. E.; Islam, S.

2016-12-01

Water utilities have a number of levers to influence customer water usage. These include levers to proactively slow demand growth over time such as building and landscape codes as well as levers to decrease demands quickly in response to water stress including price increases, education campaigns, water restrictions, and incentive programs. Even actions aimed at short term reductions can result in long term water usage declines when substantial changes are made in water efficiency, as in incentives for fixture replacement or turf removal, or usage patterns such as permanent lawn watering restrictions. Demand change is therefore linked to hydrological conditions and to the effects of past management decisions - both typically included in water supply planning models. Yet, demand is typically incorporated exogenously using scenarios or endogenously using only price, though utilities also use rules and incentives issued in response to water stress and codes specifying standards for new construction to influence water usage. Explicitly including these policy levers in planning models enables concurrent testing of infrastructure and policy strategies and illuminates interactions between the two. The City of Las Vegas is used as a case study to develop and demonstrate this modeling approach. First, a statistical analysis of system data was employed to rule out alternate hypotheses of per capita demand decrease such as changes in population density and economic structure. Next, four demand sub-models were developed including one baseline model in which demand is a function of only price. The sub-models were then calibrated and tested using monthly data from 1997 to 2012. Finally, the best performing sub-model was integrated with a full supply and demand model. The results highlight the importance of both modeling water demand dynamics endogenously and taking a broader view of the variables influencing demand change.

Pressure retarded osmosis as a controlling system for traditional renewables

NASA Astrophysics Data System (ADS)

Carravetta, Armando; Fecarotta, Oreste; La Rocca, Michele; Martino, Riccardo

2015-04-01

Pressure retarded osmosis (PRO) is a viable but still not diffused form of renewable energy (see Maisonneuve et al., 2015 for a recent literature review). In PRO, water from a low salinity feed solution permeates through a membrane into a pressurized, high salinity draw solution, giving rise to a positive pressure drop; then energy is obtained by depressurizing the permeate through a hydro-turbine and brackish water is discharged. Many technological, environmental and economical aspects are obstacles in the diffusion of PRO, like the vulnerability of the membranes to fouling, the impact of the brackish water on the local marine environment, the high cost of membranes, etc. We are interested in the use of PRO as a combined form of energy with other renewable energy source like solar, wind or mini hydro in water supply networks (WSN). For the wide diffusion of renewables one of the major concerns of commercial power companies is to obtain very stable form of energy to comply with prescriptions of electricity grid operators and with the instant energy demand curve. Renewables are generally very variable form of energy, for the influence of climatic conditions on available power, and of the fluctuation in water demand in WSN. PRO is a very flexible technology where with appropriate turbines and control system power can be varied continuously to compensate for variation of other source of energy. Therefore, PRO is suitable to be used as a balancing system for commercial power system. We will present a simulation of the performance of a PRO used in combination with three different renewables. In the first two scenarios PRO compensate the difference between energy demand and energy production of a solar power plant and hydro power plant in a WSN. In the third scenario PRO is used to compensate daily variation of energy production in a wind power plant. Standard curves of energy production and energy demand for southern Italy are used. In order to control PRO production an

The class of L ∩ D and its application to renewal reward process

NASA Astrophysics Data System (ADS)

Kamışlık, Aslı Bektaş; Kesemen, Tülay; Khaniyev, Tahir

2018-01-01

The class of L ∩ D is generated by intersection of two important subclasses of heavy tailed distributions: The long tailed distributions and dominated varying distributions. This class itself is also an important member of heavy tailed distributions and has some principal application areas especially in renewal, renewal reward and random walk processes. The aim of this study is to observe some well and less known results on renewal functions generated by the class of L ∩ D and apply them into a special renewal reward process which is known in the literature a semi Markovian inventory model of type (s, S). Especially we focused on Pareto distribution which belongs to the L ∩ D subclass of heavy tailed distributions. As a first step we obtained asymptotic results for renewal function generated by Pareto distribution from the class of L ∩ D using some well-known results by Embrechts and Omey [1]. Then we applied the results we obtained for Pareto distribution to renewal reward processes. As an application we investigate inventory model of type (s, S) when demands have Pareto distribution from the class of L ∩ D. We obtained asymptotic expansion for ergodic distribution function and finally we reached asymptotic expansion for nth order moments of distribution of this process.

Integrated renewable energy networks

NASA Astrophysics Data System (ADS)

Mansouri Kouhestani, F.; Byrne, J. M.; Hazendonk, P.; Brown, M. B.; Spencer, L.

2015-12-01

This multidisciplinary research is focused on studying implementation of diverse renewable energy networks. Our modern economy now depends heavily on large-scale, energy-intensive technologies. A transition to low carbon, renewable sources of energy is needed. We will develop a procedure for designing and analyzing renewable energy systems based on the magnitude, distribution, temporal characteristics, reliability and costs of the various renewable resources (including biomass waste streams) in combination with various measures to control the magnitude and timing of energy demand. The southern Canadian prairies are an ideal location for developing renewable energy networks. The region is blessed with steady, westerly winds and bright sunshine for more hours annually than Houston Texas. Extensive irrigation agriculture provides huge waste streams that can be processed biologically and chemically to create a range of biofuels. The first stage involves mapping existing energy and waste flows on a neighbourhood, municipal, and regional level. Optimal sites and combinations of sites for solar and wind electrical generation, such as ridges, rooftops and valley walls, will be identified. Geomatics based site and grid analyses will identify best locations for energy production based on efficient production and connectivity to regional grids.

Chance-constrained economic dispatch with renewable energy and storage

DOE PAGES

Cheng, Jianqiang; Chen, Richard Li-Yang; Najm, Habib N.; ...

2018-04-19

Increased penetration of renewables, along with uncertainties associated with them, have transformed how power systems are operated. High levels of uncertainty means that it is not longer possible to guarantee operational feasibility with certainty, instead constraints are required to be satisfied with high probability. We present a chance-constrained economic dispatch model that efficiently integrates energy storage and high renewable penetration to satisfy renewable portfolio requirements. Specifically, it is required that wind energy contributes at least a prespecified ratio of the total demand and that the scheduled wind energy is dispatchable with high probability. We develop an approximated partial sample averagemore » approximation (PSAA) framework to enable efficient solution of large-scale chanceconstrained economic dispatch problems. Computational experiments on the IEEE-24 bus system show that the proposed PSAA approach is more accurate, closer to the prescribed tolerance, and about 100 times faster than sample average approximation. Improved efficiency of our PSAA approach enables solution of WECC-240 system in minutes.« less

Chance-constrained economic dispatch with renewable energy and storage

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

Cheng, Jianqiang; Chen, Richard Li-Yang; Najm, Habib N.

Increased penetration of renewables, along with uncertainties associated with them, have transformed how power systems are operated. High levels of uncertainty means that it is not longer possible to guarantee operational feasibility with certainty, instead constraints are required to be satisfied with high probability. We present a chance-constrained economic dispatch model that efficiently integrates energy storage and high renewable penetration to satisfy renewable portfolio requirements. Specifically, it is required that wind energy contributes at least a prespecified ratio of the total demand and that the scheduled wind energy is dispatchable with high probability. We develop an approximated partial sample averagemore » approximation (PSAA) framework to enable efficient solution of large-scale chanceconstrained economic dispatch problems. Computational experiments on the IEEE-24 bus system show that the proposed PSAA approach is more accurate, closer to the prescribed tolerance, and about 100 times faster than sample average approximation. Improved efficiency of our PSAA approach enables solution of WECC-240 system in minutes.« less

Effects of dynamic-demand-control appliances on the power grid frequency.

PubMed

Tchuisseu, E B Tchawou; Gomila, D; Brunner, D; Colet, P

2017-08-01

Power grid frequency control is a demanding task requiring expensive idle power plants to adapt the supply to the fluctuating demand. An alternative approach is controlling the demand side in such a way that certain appliances modify their operation to adapt to the power availability. This is especially important to achieve a high penetration of renewable energy sources. A number of methods to manage the demand side have been proposed. In this work we focus on dynamic demand control (DDC), where smart appliances can delay their switchings depending on the frequency of the system. We introduce a simple model to study the effects of DDC on the frequency of the power grid. The model includes the power plant equations, a stochastic model for the demand that reproduces, adjusting a single parameter, the statistical properties of frequency fluctuations measured experimentally, and a generic DDC protocol. We find that DDC can reduce small and medium-size fluctuations but it can also increase the probability of observing large frequency peaks due to the necessity of recovering pending task. We also conclude that a deployment of DDC around 30-40% already allows a significant reduction of the fluctuations while keeping the number of pending tasks low.

Effects of dynamic-demand-control appliances on the power grid frequency

NASA Astrophysics Data System (ADS)

Tchuisseu, E. B. Tchawou; Gomila, D.; Brunner, D.; Colet, P.

2017-08-01

Power grid frequency control is a demanding task requiring expensive idle power plants to adapt the supply to the fluctuating demand. An alternative approach is controlling the demand side in such a way that certain appliances modify their operation to adapt to the power availability. This is especially important to achieve a high penetration of renewable energy sources. A number of methods to manage the demand side have been proposed. In this work we focus on dynamic demand control (DDC), where smart appliances can delay their switchings depending on the frequency of the system. We introduce a simple model to study the effects of DDC on the frequency of the power grid. The model includes the power plant equations, a stochastic model for the demand that reproduces, adjusting a single parameter, the statistical properties of frequency fluctuations measured experimentally, and a generic DDC protocol. We find that DDC can reduce small and medium-size fluctuations but it can also increase the probability of observing large frequency peaks due to the necessity of recovering pending task. We also conclude that a deployment of DDC around 30-40% already allows a significant reduction of the fluctuations while keeping the number of pending tasks low.

The job demands-resources model of burnout.

PubMed

Demerouti, E; Bakker, A B; Nachreiner, F; Schaufeli, W B

2001-06-01

The job demands-resources (JD-R) model proposes that working conditions can be categorized into 2 broad categories, job demands and job resources. that are differentially related to specific outcomes. A series of LISREL analyses using self-reports as well as observer ratings of the working conditions provided strong evidence for the JD-R model: Job demands are primarily related to the exhaustion component of burnout, whereas (lack of) job resources are primarily related to disengagement. Highly similar patterns were observed in each of 3 occupational groups: human services, industry, and transport (total N = 374). In addition, results confirmed the 2-factor structure (exhaustion and disengagement) of a new burnout instrument--the Oldenburg Burnout Inventory--and suggested that this structure is essentially invariant across occupational groups.

The Cycle of Renewal.

ERIC Educational Resources Information Center

Farrell, Edmund J.

To avoid "burn out" from the general tensions of the times and from the severe demands of the teaching profession, English teachers need to exploit the means of renewal. Having literature at their command, English teachers can reconstruct themselves again and again through the dynamic interplay of human imagination and language artistically…

Prediction Models for Dynamic Demand Response

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

Aman, Saima; Frincu, Marc; Chelmis, Charalampos

2015-11-02

As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D 2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D 2R, which we address inmore » this paper. Our first contribution is the formal definition of D 2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D 2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D 2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D 2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D 2R. Also, prediction models require just few days’ worth of data indicating that small amounts of historical training data can be used to make reliable predictions

Assessing long-term water demand of constantine province in Kébir-Rhumel Mediterranean catchment

NASA Astrophysics Data System (ADS)

Kiniouar, H.; Hani, A.; Younsi, A.

2017-02-01

By mid-century, in the southern Mediterranean countries, levies probably reach the limit level of renewable water resources. Algeria is one of the poorest countries in renewable water resources, with an annual storage capacity of 14.6 million m3 in the Mediterranean coastal watersheds, representing 7% of the land area and accounts for 90 % of total surface runoff of the country. In this paper, we assess water demand to meet the needs of water users in Constantine province. The latter is located in the Kébir-Rhumel Mediterranean basin under semi-arid climate with relatively high growth rate of population, agricultural and industrial activities. Using Water Evaluation And Planning system (WEAP), we built a model for managing water demand of Constantine province. A business as usual and five scenarii of «water demand " were calculated by WEAP model to simulate the uncertainties over the period of 20 years (2008-2027) : (1) Population growth, (2) increase in irrigated crop lands, (3) decrease in basic drinking water consumption, (4) decrease in basic irrigation water consumption and (5) increase in basic industrial water consumption. The results showed that scenario 3 is the best alternative scenario and the most efficient by reducing drinking water demand for about 12 Mm3 in 20 years, and thus preserve reaching the limits of water resources potentialities.

Renewable Energy Deployment in Colorado and the West: A Modeling Sensitivity and GIS Analysis

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

Barrows, Clayton; Mai, Trieu; Haase, Scott

2016-03-01

The Resource Planning Model is a capacity expansion model designed for a regional power system, such as a utility service territory, state, or balancing authority. We apply a geospatial analysis to Resource Planning Model renewable energy capacity expansion results to understand the likelihood of renewable development on various lands within Colorado.

Indonesia’s Electricity Demand Dynamic Modelling

NASA Astrophysics Data System (ADS)

Sulistio, J.; Wirabhuana, A.; Wiratama, M. G.

2017-06-01

Electricity Systems modelling is one of the emerging area in the Global Energy policy studies recently. System Dynamics approach and Computer Simulation has become one the common methods used in energy systems planning and evaluation in many conditions. On the other hand, Indonesia experiencing several major issues in Electricity system such as fossil fuel domination, demand - supply imbalances, distribution inefficiency, and bio-devastation. This paper aims to explain the development of System Dynamics modelling approaches and computer simulation techniques in representing and predicting electricity demand in Indonesia. In addition, this paper also described the typical characteristics and relationship of commercial business sector, industrial sector, and family / domestic sector as electricity subsystems in Indonesia. Moreover, it will be also present direct structure, behavioural, and statistical test as model validation approach and ended by conclusions.

Supply based on demand dynamical model

NASA Astrophysics Data System (ADS)

Levi, Asaf; Sabuco, Juan; Sanjuán, Miguel A. F.

2018-04-01

We propose and numerically analyze a simple dynamical model that describes the firm behaviors under uncertainty of demand. Iterating this simple model and varying some parameter values, we observe a wide variety of market dynamics such as equilibria, periodic, and chaotic behaviors. Interestingly, the model is also able to reproduce market collapses.

Forecasting Hourly Water Demands With Seasonal Autoregressive Models for Real-Time Application

NASA Astrophysics Data System (ADS)

Chen, Jinduan; Boccelli, Dominic L.

2018-02-01

Consumer water demands are not typically measured at temporal or spatial scales adequate to support real-time decision making, and recent approaches for estimating unobserved demands using observed hydraulic measurements are generally not capable of forecasting demands and uncertainty information. While time series modeling has shown promise for representing total system demands, these models have generally not been evaluated at spatial scales appropriate for representative real-time modeling. This study investigates the use of a double-seasonal time series model to capture daily and weekly autocorrelations to both total system demands and regional aggregated demands at a scale that would capture demand variability across a distribution system. Emphasis was placed on the ability to forecast demands and quantify uncertainties with results compared to traditional time series pattern-based demand models as well as nonseasonal and single-seasonal time series models. Additional research included the implementation of an adaptive-parameter estimation scheme to update the time series model when unobserved changes occurred in the system. For two case studies, results showed that (1) for the smaller-scale aggregated water demands, the log-transformed time series model resulted in improved forecasts, (2) the double-seasonal model outperformed other models in terms of forecasting errors, and (3) the adaptive adjustment of parameters during forecasting improved the accuracy of the generated prediction intervals. These results illustrate the capabilities of time series modeling to forecast both water demands and uncertainty estimates at spatial scales commensurate for real-time modeling applications and provide a foundation for developing a real-time integrated demand-hydraulic model.

On the battleground of environmental and competition policy: The renewable electricity market

NASA Astrophysics Data System (ADS)

Meszaros, Matyas Tamas

Renewable energy sources have become increasingly important in the efforts to provide energy security and to fight global warming. In the last decade environmental policy has increased the support for renewable electricity. At the same time the electricity sector was often subject of antitrust investigation because of relevant market concentration, and market power. This dissertation looks at the renewable electricity market to analyze the effect of environmental policy on competition. The first chapter provides a short introduction into the regulatory schemes of electricity markets. The second chapter analyzes the demand side of the electricity market. The estimations show that there was no significant change in the income and price elasticity in the electricity consumption of the US households between 1993 an 2001, although there was several policy initiatives to increase energy efficiency and decrease consumption. The third chapter derives a theoretical model where the feed-in tariff and the tradable green certificate system can be analyzed under oligopolistic market structure. The results of the model suggest that the introduction of the environmentally friendly regulatory schemes can decrease the electricity prices compared to the case when there is no support for renewable energy. The other findings of this model is that the price of electricity rises when the requirement for renewable energy increases. In the fourth chapter a simulation model of the UK electricity market is used to test the effect of mergers and acquisitions under the environmental support scheme. The results emphasize the importance of the capacity limit, because it can constrain the strategic action of the electricity producers. The results of the simulation also suggest that the increasing concentration can increase the production and lower the price of electricity and renewable energy certificates in the British Renewable Obligation system.

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

Effect of policy-based bioenergy demand on southern timber markets: A case study of North Carolina

Treesearch

Robert C. Abt; Karen L. Abt; Frederick W. Cubbage; Jesse D. Henderson

2010-01-01

Key factors driving renewable energy demand are state and federal policies requiring the use of renewable feedstocks to produce energy (renewable portfolio standards) and liquid fuels (renewable fuel standards). However, over the next decade, the infrastructure for renewable energy supplies is unlikely to develop as fast as both policy- and market-motivated renewable...

Renewable generation technology choice and policies in a competitive electricity supply industry

NASA Astrophysics Data System (ADS)

Sarkar, Ashok

Renewable energy generation technologies have lower externality costs but higher private costs than fossil fuel-based generation. As a result, the choice of renewables in the future generation mix could be affected by the industry's future market-oriented structure because market objectives based on private value judgments may conflict with social policy objectives toward better environmental quality. This research assesses how renewable energy generation choices would be affected in a restructured electricity generation market. A multi-period linear programming-based model (Resource Planning Model) is used to characterize today's electricity supply market in the United States. The model simulates long-range (2000-2020) generation capacity planning and operation decisions under alternative market paradigms. Price-sensitive demand is used to simulate customer preferences in the market. Dynamically changing costs for renewables and a two-step load duration curve are used. A Reference Case represents the benchmark for a socially-optimal diffusion of renewables and a basis for comparing outcomes under alternative market structures. It internalizes externality costs associated with emissions of sulfur dioxide (SOsb2), nitrous oxides (NOsbx), and carbon dioxide (COsb2). A Competitive Case represents a market with many generation suppliers and decision-making based on private costs. Finally, a Market Power Case models the extreme case of market power: monopoly. The results suggest that the share of renewables would decrease (and emissions would increase) considerably in both the Competitive and the Market Power Cases with respect to the Reference Case. The reduction is greater in the Market Power Case due to pricing decisions under existing supply capability. The research evaluates the following environmental policy options that could overcome market failures in achieving an appropriate level of renewable generation: COsb2 emissions tax, SOsb2 emissions cap, renewable

Chapter 7: Renewable Energy Options and Considerations for Net Zero Installations

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

Booth, Samuel

This chapter focuses on renewable energy options for military installations. It discusses typical renewable technologies, project development, and gives examples. Renewable energy can be combined with conventional energy sources to provide part or all of the energy demand at an installation. The appropriate technology mix for an installation will depend on site-specific factors such as renewable resources, energy costs, local energy policies and incentives, available land, mission compatibility, and other factors. The objective of this chapter is to provide basic background information and resources on renewable energy options for NATO leaders and energy personnel.

Indicators to determine winning renewable energy technologies with an application to photovoltaics.

PubMed

Grossmann, Wolf D; Grossmann, Iris; Steininger, Karl

2010-07-01

Several forms of renewable energy compete for supremacy or for an appropriate role in global energy supply. A form of renewable energy can only play an important role in global energy supply if it fulfills several basic requirements. Its capacity must allow supplying a considerable fraction of present and future energy demand, all materials for its production must be readily available, land demand must not be prohibitive, and prices must reach grid parity in the nearer future. Moreover, a renewable energy technology can only be acceptable if it is politically safe. We supply a collection of indicators which allow assessing competing forms of renewable energy and elucidate why surprise is still a major factor in this field, calling for adaptive management. Photovoltaics (PV) are used as an example of a renewable energy source that looks highly promising, possibly supplemented by solar thermal electricity production (ST). We also show why energy use will contribute to land use problems and discuss ways in which the right choice of renewables may be indispensible in solving these problems.

A Contingent Trip Model for Estimating Rail-trail Demand

Treesearch

Carter J. Betz; John C. Bergstrom; J. Michael Bowker

2003-01-01

The authors develop a contingent trip model to estimate the recreation demand for and value of a potential rail-trail site in north-east Georgia. The contingent trip model is an alternative to travel cost modelling useful for ex ante evaluation of proposed recreation resources or management alternatives. The authors estimate the empirical demand for trips using a...

Projections of the demand for national forest stumpage by region: 1980-2030.

Treesearch

Richard W. Haynes; Kent P. Connaughton; Darius M. Adams

1981-01-01

The concept of regional demand is described and applied to the demand for National Forest stumpage. Specifically, demand functions for stumpage (price-quantity relationships) are developed by decade for the major National Forest Regions. The' demand functions are consistent with the 1980 timber program prepared under requirements of the Renewable Resources...

Defining Toll Fee of Wheeling Renewable with Reference to a Gas Pipeline in Indonesia

NASA Astrophysics Data System (ADS)

Hakim, Amrullah

2017-07-01

Indonesia has a huge number of renewable energy sources (RE) however; the utilization of these is currently very low. The main challenge of power production is its alignment with consumption levels; supply should equal demand at all times. There is a strong initiative from corporations with high energy demand, compared to other sectors, to apply a renewable portfolio standard for their energy input, e.g. 15% of their energy consumption requirement must come from a renewable energy source. To support this initiative, the utilization of power wheeling will help large factories on industrial estates to source firm and steady renewables from remote sites. The wheeling renewable via PLN’s transmission line has been regulated under the Ministry Decree in 2015 however; the tariff or toll fee has not yet been defined. The potential project to apply wheeling renewable will obtain power supply from a geothermal power plant, with power demand from the scattered factories under one company. This is the concept driving the application of power wheeling in the effort to push the growth of renewable energy in Indonesia. Given that the capacity of PLN’s transmission line are normally large and less congested compared to distribution line, the wheeling renewable can accommodate the scattered factories locations which then results in the cheaper toll fee of the wheeling renewable. Defining the best toll fee is the main topic of this paper with comparison of the toll fee of the gas pipeline infrastructure in Indonesia, so that it can be applied massively to achieve COP21’s commitment.

Assessment of Renewable Energy Sources & Municipal Solid Waste for Sustainable Power Generation in Nigeria

NASA Astrophysics Data System (ADS)

Aderoju, Olaide M.; Dias, Guerner A.; Echakraoui, Zhour

2017-12-01

The demand for Energy in most Sub-Saharan African countries has become unimaginable despite its high potential of natural and renewable resources. The deficit has impeded the regions’ economic growth and sustainability. Nigeria as a nation is blessed with fossil fuels, abundant sunlight, hydro, wind and many among others, but the energy output to its population (185 million) still remains less than 4000MW. Currently, the clamour for an alternative but renewable energy source is the demand of the globe but it is quite expensive to achieve the yield that meets the Nigeria demand. Hence, this study aims at identifying and mapping out various regions with renewable energy potentials. The study also considers municipal solid waste as a consistent and available resource for power generation. Furthermore, this study examines the drawbacks inhibiting the inability to harness these renewable, energy generating potentials in full capacity. The study will enable the authorities and other stakeholders to invest and plan on providing a sustainable energy for the people.

Residential green power demand in the United States

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

Dagher, Leila; Bird, Lori; Heeter, Jenny

This paper investigates the demand determinants of green power in the U.S. residential sector. The data employed were collected by the National Renewable Energy Laboratory and consist of a cross-section of seven utilities observed over 13 years. A series of tests are performed that resulted in estimating a demand equation using the one-way cross-section random effects model. As expected, we find that demand is highly price inelastic. More interestingly though, is that elasticity with respect to number of customers is 0.52 leading to the conclusion that new subscribers tend to purchase less green power on average than the existing customers.more » Another compelling finding is that obtaining accreditation will have a 28.5% positive impact on consumption. Knowing that gaining green accreditation is important to the success of programs, utilities may want to seek certification and highlight it in their advertising campaigns.« less

Planning a Target Renewable Portfolio using Atmospheric Modeling and Stochastic Optimization

NASA Astrophysics Data System (ADS)

Hart, E.; Jacobson, M. Z.

2009-12-01

A number of organizations have suggested that an 80% reduction in carbon emissions by 2050 is a necessary step to mitigate climate change and that decarbonization of the electricity sector is a crucial component of any strategy to meet this target. Integration of large renewable and intermittent generators poses many new problems in power system planning. In this study, we attempt to determine an optimal portfolio of renewable resources to meet best the fluctuating California load while also meeting an 80% carbon emissions reduction requirement. A stochastic optimization scheme is proposed that is based on a simplified model of the California electricity grid. In this single-busbar power system model, the load is met with generation from wind, solar thermal, photovoltaic, hydroelectric, geothermal, and natural gas plants. Wind speeds and insolation are calculated using GATOR-GCMOM, a global-through-urban climate-weather-air pollution model. Fields were produced for California and Nevada at 21km SN by 14 km WE spatial resolution every 15 minutes for the year 2006. Load data for 2006 were obtained from the California ISO OASIS database. Maximum installed capacities for wind and solar thermal generation were determined using a GIS analysis of potential development sites throughout the state. The stochastic optimization scheme requires that power balance be achieved in a number of meteorological and load scenarios that deviate from the forecasted (or modeled) data. By adjusting the error distributions of the forecasts, the model describes how improvements in wind speed and insolation forecasting may affect the optimal renewable portfolio. Using a simple model, we describe the diversity, size, and sensitivities of a renewable portfolio that is best suited to the resources and needs of California and that contributes significantly to reduction of the state’s carbon emissions.

Renewable Electricity Futures Study. Volume 4: Bulk Electric Power Systems: Operations and Transmission Planning

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

Milligan, M.; Ela, E.; Hein, J.

2012-06-01

The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a futuremore » through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).« less

Global renewable energy-based electricity generation and smart grid system for energy security.

PubMed

Islam, M A; Hasanuzzaman, M; Rahim, N A; Nahar, A; Hosenuzzaman, M

2014-01-01

Energy is an indispensable factor for the economic growth and development of a country. Energy consumption is rapidly increasing worldwide. To fulfill this energy demand, alternative energy sources and efficient utilization are being explored. Various sources of renewable energy and their efficient utilization are comprehensively reviewed and presented in this paper. Also the trend in research and development for the technological advancement of energy utilization and smart grid system for future energy security is presented. Results show that renewable energy resources are becoming more prevalent as more electricity generation becomes necessary and could provide half of the total energy demands by 2050. To satisfy the future energy demand, the smart grid system can be used as an efficient system for energy security. The smart grid also delivers significant environmental benefits by conservation and renewable generation integration.

Global Renewable Energy-Based Electricity Generation and Smart Grid System for Energy Security

PubMed Central

Islam, M. A.; Hasanuzzaman, M.; Rahim, N. A.; Nahar, A.; Hosenuzzaman, M.

2014-01-01

Energy is an indispensable factor for the economic growth and development of a country. Energy consumption is rapidly increasing worldwide. To fulfill this energy demand, alternative energy sources and efficient utilization are being explored. Various sources of renewable energy and their efficient utilization are comprehensively reviewed and presented in this paper. Also the trend in research and development for the technological advancement of energy utilization and smart grid system for future energy security is presented. Results show that renewable energy resources are becoming more prevalent as more electricity generation becomes necessary and could provide half of the total energy demands by 2050. To satisfy the future energy demand, the smart grid system can be used as an efficient system for energy security. The smart grid also delivers significant environmental benefits by conservation and renewable generation integration. PMID:25243201

Eastern Renewable Generation Integration Study

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

Bloom, Aaron; Townsend, Aaron; Palchak, David

2016-08-01

The Eastern Interconnection (EI) is one of the largest power systems in the world, and its size and complexity have historically made it difficult to study in high levels of detail in a modeling environment. In order to understand how this system might be impacted by high penetrations (30% of total annual generation) of wind and solar photovoltaic (PV) during steady state operations, the National Renewable Energy Laboratory (NREL) and the U.S. Department of Energy (DOE) conducted the Eastern Renewable Generation Integration Study (ERGIS). This study investigates certain aspects of the reliability and economic efficiency problem faced by power systemmore » operators and planners. Specifically, the study models the ability to meet electricity demand at a 5-minute time interval by scheduling resources for known ramping events, while maintaining adequate reserves to meet random variation in supply and demand, and contingency events. To measure the ability to meet these requirements, a unit commitment and economic dispatch (UC&ED) model is employed to simulate power system operations. The economic costs of managing this system are presented using production costs, a traditional UC&ED metric that does not include any consideration of long-term fixed costs. ERGIS simulated one year of power system operations to understand regional and sub-hourly impacts of wind and PV by developing a comprehensive UC&ED model of the EI. In the analysis, it is shown that, under the study assumptions, generation from approximately 400 GW of combined wind and PV capacity can be balanced on the transmission system at a 5-minute level. In order to address the significant computational burdens associated with a model of this detail we apply novel computing techniques to dramatically reduce simulation solve time while simultaneously increasing the resolution and fidelity of the analysis. Our results also indicate that high penetrations of wind and PV (collectively variable generation (VG

Hybrid Hydro Renewable Energy Storage Model

NASA Astrophysics Data System (ADS)

Dey, Asit Kr

2018-01-01

This paper aims at presenting wind & tidal turbine pumped-storage solutions for improving the energy efficiency and economic sustainability of renewable energy systems. Indicated a viable option to solve problems of energy production, as well as in the integration of intermittent renewable energies, providing system flexibility due to energy load’s fluctuation, as long as the storage of energy from intermittent sources. Sea water storage energy is one of the best and most efficient options in terms of renewable resources as an integrated solution allowing the improvement of the energy system elasticity and the global system efficiency.

The role of renewable energy on animal farms

NASA Astrophysics Data System (ADS)

Csatári, Nándor; Vántus, András

2015-04-01

The recent measures in the European Union promote the usage of renewable energies and enhancing the energy efficiency. These measures also effect agriculture, on the one hand by using biofuels mixed into fuel for machinery. Besides biofuels animal farms have opportunities in using renewable energy in several other ways. There are sectors in animal farming, where the energy demand is continuously high in electricity (e.g. forage grinders, mixers, milk coolers, air ventilation systems) or in heating (e.g. stables for poultry or piglets). Beside the energy demand in agricultural sector there are several products and side products suitable for energy production. For example different kinds of organic manures and corn silage could be raw materials for biogas production; plant residues like cereal straw and corn stalk bales could be combusted in boilers. Furthermore solar cells or solar collectors can be mounted on the big roof surfaces of animal farm buildings. Among animal farming sectors, dairy farming in the most energy intensive, and uses the widest variety of energy forms. It is often mentioned as the "heavy industry" of animal farming. In this research 14 dairy farms were examined in Hajdú-Bihar County in the topic of energy demand, renewable energy usage. The questioned farms covers 35% of the dairy cow population in Hajdú-Bihar County. The questions covered the general attributes of the farms and the details of the (existing or planned) renewable energy application. In terms of economic analysis saving, the investment return time and the employment effect was examined. The results show wide variety of applied renewable energy application. Fifty percent of farms uses at least one kind of renewable energy. Two biogas plants, 6 boilers for solid biomass, 2 solar cells. Regarding employment effect biogas plants created some full time workplaces, biomass boilers also needs some work hours to maintain, but none of the farms applied more labour. Besides renewable

Issues in Renewable Energy Education

ERIC Educational Resources Information Center

Thomas, Chacko; Jennings, Philip; Lloyd, Bob

2008-01-01

Renewable energy education is evolving rapidly in response to drivers such as oil depletion and global warming. There is a rapidly increasing level of student interest in these topics and a growing demand from industry and government for skilled personnel to develop sustainable energy systems and greenhouse solutions. Several Australian and New…

Self-Renewal for Self-Preservation.

ERIC Educational Resources Information Center

Sistrunk, Walter E.

This speech explores the concept of professional self-renewal. The presenter seeks to understand why some professionals always seem fresh, energetic, and ready for new challenges, whereas others are perpetually tired, bored, and irritated with the demands of their work. Referring to McGregor's management theories, the paper infers that Theory X…

A Modeling Study of Deep Water Renewal in the Red Sea

NASA Astrophysics Data System (ADS)

Yao, F.; Hoteit, I.

2016-02-01

Deep water renewal processes in the Red Sea are examined in this study using a 50-year numerical simulation from 1952-2001. The deep water in the Red Sea below the thermocline ( 200 m) exhibits a near-uniform vertical structure in temperature and salinity, but geochemical tracer distributions, such as 14C and 3He, and dissolved oxygen concentrations indicate that the deep water is renewed on time scales as short as 36 years. The renewal process is accomplished through a deep overturning cell that consists of a southward bottom current and a northward returning current at depths of 400-600 m. Three sources regions are proposed for the formation of the deep water, including two deep outflows from the Gulfs of Aqaba and Suez and winter deep convections in the northern Red Sea. The MITgcm (MIT general circulation model), which has been used to simulate the shallow overturning circulations in the Red Sea, is configured in this study with increased resolutions in the deep water. During the 50 years of simulation, artificial passive tracers added in the model indicate that the deep water in the Red Sea was only episodically renewed during some anomalously cold years; two significant episodes of deep water renewal are reproduced in the winters of 1983 and 1992, in accordance with reported historical hydrographic observations. During these renewal events, deep convections reaching the bottom of the basin occurred, which further facilitated deep sinking of the outflows from the Gulfs of Aqaba and Suez. Ensuing spreading of the newly formed deep water along the bottom caused upward displacements of thermocline, which may have profound effects on the water exchanges in the Strait of Bab el Mandeb between the Red Sea and the Gulf of Aden and the functioning of the ecosystem in the Red Sea by changing the vertical distributions of nutrients.

Renewable Energy Implementation Analysis and Recommendations to Meet District of Columbia's Renewable Portfolio Standard (RPS) Expansion Act

NASA Astrophysics Data System (ADS)

DuBrey, Stephen

Due to federal mandates, there is an increasing demand to advance renewable energy in the District of Columbia (D.C.) to deliver power. Utilities must find ways to achieve objectives while avoiding costly alternative compliance payments. In 2016, the District of Columbia's Renewable Portfolio Standard (RPS) Expansion Act made significant amendments expanding renewable energy source requirements to 50% by 2032 and solar requirements to 5% by 2032, while current utility renewable energy percentages are at 4% and solar is at ˜0.1%. With the RPS mandate, utilities will need to improve and enhance facilitation of the interconnection of renewable energy within the power delivery system. This study will focus on the evaluation and implementation of various renewable energy systems in the District of Columbia. The main objective is to analyze the best feasible options available to meet RPS targets. If electricity suppliers are unable to meet requirements, suppliers must pay both renewable energy credits (RECs) and alternative compliance fees (ACFs) and the financial burden of compliance will ultimately be passed on to customers of the electricity suppliers. This study will also review and present the cost-effective means of REC's can be used for RPS compliance and results will provide policymakers a better understanding of how to address renewable energy requirements locally in the District.

Renewable Electricity Futures for the United States

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

Mai, Trieu; Hand, Maureen; Baldwin, Sam F.

2014-04-14

This paper highlights the key results from the Renewable Electricity (RE) Futures Study. It is a detailed consideration of renewable electricity in the United States. The paper focuses on technical issues related to the operability of the U. S. electricity grid and provides initial answers to important questions about the integration of high penetrations of renewable electricity technologies from a national perspective. The results indicate that the future U. S. electricity system that is largely powered by renewable sources is possible and the further work is warranted to investigate this clean generation pathway. The central conclusion of the analysis ismore » that renewable electricity generation from technologies that are commercially available today, in combination with a more flexible electric system, is more than adequate to supply 80% of the total U. S. electricity generation in 2050 while meeting electricity demand on an hourly basis in every region of the United States.« less

Using Enrollment Demand Models in Institutional Pricing Decisions.

ERIC Educational Resources Information Center

Weiler, William C.

1984-01-01

Issues in the application of enrollment demand analysis to institutions' pricing policy are discussed, including price change impact on enrollment, the role of enrollment demand models on long-range financial and personnel planning, use of tuition and financial aid policy in optimizing policymakers' enrollment objectives, and the redistribution…

Energy efficiency, renewable energy and sustainable development

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

Ervin, C.A.

1994-12-31

The Office of Energy Efficiency and Renewable Energy (EE) is part of the U.S. Department of Energy that is specifically charged with encouraging the more efficient use of energy resources, and the use of renewable energy resources - such as solar power, wind power, biomass energy and geothermal energy. In the past several years, EE has increased its emphasis on technology deployment through partnerships with states, local governments and private companies. Partnerships move new discoveries more quickly into the marketplace, where they can create jobs, prevent pollution, save resources, and produce many other benefits. The author then emphasizes the importancemore » of this effort in a number of different sections of the paper: energy consumption pervades everything we do; U.S. energy imports are rising to record levels; transportation energy demand is increasing; U.S. energy use is increasing; population growth increases world energy demand; total costs of energy consumption aren`t always counted; world energy markets offer incredible potential; cost of renewables is decreasing; clean energy is essential to sustainable development; sustainable energy policy; sustainable energy initiatives: utilities, buildings, and transportation.« less

Taxonomy for Modeling Demand Response Resources

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

Olsen, Daniel; Kiliccote, Sila; Sohn, Michael

2014-08-01

Demand response resources are an important component of modern grid management strategies. Accurate characterizations of DR resources are needed to develop systems of optimally managed grid operations and to plan future investments in generation, transmission, and distribution. The DOE Demand Response and Energy Storage Integration Study (DRESIS) project researched the degree to which demand response (DR) and energy storage can provide grid flexibility and stability in the Western Interconnection. In this work, DR resources were integrated with traditional generators in grid forecasting tools, specifically a production cost model of the Western Interconnection. As part of this study, LBNL developed amore » modeling framework for characterizing resource availability and response attributes of DR resources consistent with the governing architecture of the simulation modeling platform. In this report, we identify and describe the following response attributes required to accurately characterize DR resources: allowable response frequency, maximum response duration, minimum time needed to achieve load changes, necessary pre- or re-charging of integrated energy storage, costs of enablement, magnitude of controlled resources, and alignment of availability. We describe a framework for modeling these response attributes, and apply this framework to characterize 13 DR resources including residential, commercial, and industrial end-uses. We group these end-uses into three broad categories based on their response capabilities, and define a taxonomy for classifying DR resources within these categories. The three categories of resources exhibit different capabilities and differ in value to the grid. Results from the production cost model of the Western Interconnection illustrate that minor differences in resource attributes can have significant impact on grid utilization of DR resources. The implications of these findings will be explored in future DR valuation studies.« less

Renewable energy - Target for 2050

NASA Astrophysics Data System (ADS)

Rowe, W. D.

1982-02-01

The possibilities of various renewable energy technologies to supply a projected world demand for 40,000 GW years of energy each year by the year 2050 are examined. Noting that industrial processes consume 50% of all energy needs, fossil fuel reserves are shown to be sufficient for a maximum of 370 yr in the U.S., when all supplies become depleted. Breeder reactors have a doubling time which is 30 yr too long for meeting more than 0.5% of world energy demand in 2050, while fusion, even considering ocean-derived deuterium as a fuel source, will not be supplying energy for another 35-70 yr. Among the solar technologies, the installation of ten million 100 m tall 4 MW wind generators is feasible to meet all the projected energy needs, and solar cells with 10% conversion efficiency could do the same with 14 times less land. Further discussion is given to geothermal, fuel cell, and OTEC technologies, as well as the forty trillion dollars necessary to erect the fully renewable systems.

Renewable Electricity Futures Study. Volume 4: Bulk Electric Power Systems. Operations and Transmission Planning

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

Milligan, Michael; Ela, Erik; Hein, Jeff

2012-06-15

The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a futuremore » through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%–90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT). Learn more at the RE Futures website. http://www.nrel.gov/analysis/re_futures/« less

Stochastic optimization model for order acceptance with multiple demand classes and uncertain demand/supply

NASA Astrophysics Data System (ADS)

Yang, Wen; Fung, Richard Y. K.

2014-06-01

This article considers an order acceptance problem in a make-to-stock manufacturing system with multiple demand classes in a finite time horizon. Demands in different periods are random variables and are independent of one another, and replenishments of inventory deviate from the scheduled quantities. The objective of this work is to maximize the expected net profit over the planning horizon by deciding the fraction of the demand that is going to be fulfilled. This article presents a stochastic order acceptance optimization model and analyses the existence of the optimal promising policies. An example of a discrete problem is used to illustrate the policies by applying the dynamic programming method. In order to solve the continuous problems, a heuristic algorithm based on stochastic approximation (HASA) is developed. Finally, the computational results of a case example illustrate the effectiveness and efficiency of the HASA approach, and make the application of the proposed model readily acceptable.

Theory and Techniques for Assessing the Demand and Supply of Outdoor Recreation in the United States

Treesearch

H. Ken Cordell; John C. Bergstrom

1989-01-01

As the central analysis for the 1989 Renewable Resources planning Act Assessment, a household market model covering 37 recreational activities was computed for the United States. Equilibrium consumption and costs were estimated, as were likely future changes in consumption and costs in response to expected demand growth and alternative development and access policies...

Microgrid to enable optimal distributed energy retail and end-user demand response

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

Jin, Ming; Feng, Wei; Marnay, Chris

In the face of unprecedented challenges in environmental sustainability and grid resilience, there is an increasingly held consensus regarding the adoption of distributed and renewable energy resources such as microgrids (MGs), and the utilization of flexible electric loads by demand response (DR) to potentially drive a necessary paradigm shift in energy production and consumption patterns. However, the potential value of distributed generation and demand flexibility has not yet been fully realized in the operation of MGs. This study investigates the pricing and operation strategy with DR for a MG retailer in an integrated energy system (IES). Based on co-optimizing retailmore » rates and MG dispatch formulated as a mixed integer quadratic programming (MIQP) problem, our model devises a dynamic pricing scheme that reflects the cost of generation and promotes DR, in tandem with an optimal dispatch plan that exploits spark spread and facilitates the integration of renewables, resulting in improved retailer profits and system stability. Main issues like integrated energy coupling and customer bill reduction are addressed during pricing to ensure rates competitiveness and customer protection. By evaluating on real datasets, the system is demonstrated to optimally coordinate storage, renewables, and combined heat and power (CHP), reduce carbon dioxide emission while maintaining profits, and effectively alleviate the PV curtailment problem. Finally, the model can be used by retailers and MG operators to optimize their operations, as well as regulators to design new utility rates in support of the ongoing transformation of energy systems.« less

Microgrid to enable optimal distributed energy retail and end-user demand response

DOE PAGES

Jin, Ming; Feng, Wei; Marnay, Chris; ...

2018-06-07

In the face of unprecedented challenges in environmental sustainability and grid resilience, there is an increasingly held consensus regarding the adoption of distributed and renewable energy resources such as microgrids (MGs), and the utilization of flexible electric loads by demand response (DR) to potentially drive a necessary paradigm shift in energy production and consumption patterns. However, the potential value of distributed generation and demand flexibility has not yet been fully realized in the operation of MGs. This study investigates the pricing and operation strategy with DR for a MG retailer in an integrated energy system (IES). Based on co-optimizing retailmore » rates and MG dispatch formulated as a mixed integer quadratic programming (MIQP) problem, our model devises a dynamic pricing scheme that reflects the cost of generation and promotes DR, in tandem with an optimal dispatch plan that exploits spark spread and facilitates the integration of renewables, resulting in improved retailer profits and system stability. Main issues like integrated energy coupling and customer bill reduction are addressed during pricing to ensure rates competitiveness and customer protection. By evaluating on real datasets, the system is demonstrated to optimally coordinate storage, renewables, and combined heat and power (CHP), reduce carbon dioxide emission while maintaining profits, and effectively alleviate the PV curtailment problem. Finally, the model can be used by retailers and MG operators to optimize their operations, as well as regulators to design new utility rates in support of the ongoing transformation of energy systems.« less

Comparing Exponential and Exponentiated Models of Drug Demand in Cocaine Users

PubMed Central

Strickland, Justin C.; Lile, Joshua A.; Rush, Craig R.; Stoops, William W.

2016-01-01

Drug purchase tasks provide rapid and efficient measurement of drug demand. Zero values (i.e., prices with zero consumption) present a quantitative challenge when using exponential demand models that exponentiated models may resolve. We aimed to replicate and advance the utility of using an exponentiated model by demonstrating construct validity (i.e., association with real-world drug use) and generalizability across drug commodities. Participants (N = 40 cocaine-using adults) completed Cocaine, Alcohol, and Cigarette Purchase Tasks evaluating hypothetical consumption across changes in price. Exponentiated and exponential models were fit to these data using different treatments of zero consumption values, including retaining zeros or replacing them with 0.1, 0.01, 0.001. Excellent model fits were observed with the exponentiated model. Means and precision fluctuated with different replacement values when using the exponential model, but were consistent for the exponentiated model. The exponentiated model provided the strongest correlation between derived demand intensity (Q0) and self-reported free consumption in all instances (Cocaine r = .88; Alcohol r = .97; Cigarette r = .91). Cocaine demand elasticity was positively correlated with alcohol and cigarette elasticity. Exponentiated parameters were associated with real-world drug use (e.g., weekly cocaine use), whereas these correlations were less consistent for exponential parameters. Our findings show that selection of zero replacement values impact demand parameters and their association with drug-use outcomes when using the exponential model, but not the exponentiated model. This work supports the adoption of the exponentiated demand model by replicating improved fit and consistency, in addition to demonstrating construct validity and generalizability. PMID:27929347

NREL: Renewable Resource Data Center - Geothermal Resource Models and Tools

Science.gov Websites

allow users to determine locations that are favorable to geothermal energy development. List of software Models and Tools The Renewable Resource Data Center (RReDC) features the following geothermal models and tools. Geothermal Prospector The Geothermal Prospector tool provides the information needed to

Some comments on the World Energy Conference (WEC) energy demand model

NASA Astrophysics Data System (ADS)

Brandell, L.

1982-04-01

The WEC model, relating the energy demand for a region in a year to gross national product (GNP), aggregated energy prices and elasticity constants, is generalized. The changes that result from the assumption that the elasticity factors are not constant are examined. The resulting differential equation contains the variables energy demand per capita and GNP per capita for the region considered. The effect of time lag in energy demand and the influence of the population growth rate are also included in the model. No projections of the future energy demand were made, but model sensitiveness to the modifications were studied. Time lag effects and population growth effects can raise the projected energy demand for a region by 10% or more.

Psychosocial work environment and health in U.S. metropolitan areas: a test of the demand-control and demand-control-support models.

PubMed

Muntaner, C; Schoenbach, C

1994-01-01

The authors use confirmatory factor analysis to investigate the psychosocial dimensions of work environments relevant to health outcomes, in a representative sample of five U.S. metropolitan areas. Through an aggregated inference system, scales from Schwartz and associates' job scoring system and from the Dictionary of Occupational Titles (DOT) were employed to examine two alternative models: the demand-control model of Karasek and Theorell and Johnson's demand-control-support model. Confirmatory factor analysis was used to test the two models. The two multidimensional models yielded better fits than an unstructured model. After allowing for the measurement error variance due to the method of assessment (Schwartz and associates' system or DOT), both models yielded acceptable goodness-of-fit indices, but the fit of the demand-control-support model was significantly better. Overall these results indicate that the dimensions of Control (substantive complexity of work, skill discretion, decision authority), Demands (physical exertion, physical demands and hazards), and Social Support (coworker and supervisor social supports) provide an acceptable account of the psychosocial dimensions of work associated with health outcomes.

Cellular automata and integrodifferential equation models for cell renewal in mosaic tissues

PubMed Central

Bloomfield, J. M.; Sherratt, J. A.; Painter, K. J.; Landini, G.

2010-01-01

Mosaic tissues are composed of two or more genetically distinct cell types. They occur naturally, and are also a useful experimental method for exploring tissue growth and maintenance. By marking the different cell types, one can study the patterns formed by proliferation, renewal and migration. Here, we present mathematical modelling suggesting that small changes in the type of interaction that cells have with their local cellular environment can lead to very different outcomes for the composition of mosaics. In cell renewal, proliferation of each cell type may depend linearly or nonlinearly on the local proportion of cells of that type, and these two possibilities produce very different patterns. We study two variations of a cellular automaton model based on simple rules for renewal. We then propose an integrodifferential equation model, and again consider two different forms of cellular interaction. The results of the continuous and cellular automata models are qualitatively the same, and we observe that changes in local environment interaction affect the dynamics for both. Furthermore, we demonstrate that the models reproduce some of the patterns seen in actual mosaic tissues. In particular, our results suggest that the differing patterns seen in organ parenchymas may be driven purely by the process of cell replacement under different interaction scenarios. PMID:20375040

Monopoly models with time-varying demand function

NASA Astrophysics Data System (ADS)

Cavalli, Fausto; Naimzada, Ahmad

2018-05-01

We study a family of monopoly models for markets characterized by time-varying demand functions, in which a boundedly rational agent chooses output levels on the basis of a gradient adjustment mechanism. After presenting the model for a generic framework, we analytically study the case of cyclically alternating demand functions. We show that both the perturbation size and the agent's reactivity to profitability variation signals can have counterintuitive roles on the resulting period-2 cycles and on their stability. In particular, increasing the perturbation size can have both a destabilizing and a stabilizing effect on the resulting dynamics. Moreover, in contrast with the case of time-constant demand functions, the agent's reactivity is not just destabilizing, but can improve stability, too. This means that a less cautious behavior can provide better performance, both with respect to stability and to achieved profits. We show that, even if the decision mechanism is very simple and is not able to always provide the optimal production decisions, achieved profits are very close to those optimal. Finally, we show that in agreement with the existing empirical literature, the price series obtained simulating the proposed model exhibit a significant deviation from normality and large volatility, in particular when underlying deterministic dynamics become unstable and complex.

The role of workaholism in the job demands-resources model.

PubMed

Molino, Monica; Bakker, Arnold B; Ghislieri, Chiara

2016-07-01

The present study tries to gain more insight in workaholism by investigating its antecedents and consequences using the job demands-resources model. We hypothesized that job demands would be positively related to workaholism, particularly when job resources are low. In addition, we hypothesized that workaholism would be positively related to negative outcomes in three important life domains: health, family, and work. The research involved 617 Italian workers (employees and self-employed). To test the hypotheses we applied structural equation modeling (SEM) and moderated structural equation modeling (MSEM) using Mplus 6. The results of SEM showed a good model where workload, cognitive demands, emotional demands, and customer-related social stressors were positively related to workaholism and work-family conflict (WFC) (partial mediation). Additionally, workaholism was indirectly related to exhaustion and intentions to change jobs through WFC. Moreover, MSEM analyses confirmed that job resources (job security and opportunities for development) buffered the relationship between job demands and workaholism. Particularly, the interaction effects were statistically significant in five out of eight combinations. These findings suggest that workaholism is a function of a suboptimal work environment and predicts unfavorable employee outcomes. We discuss the theoretical and practical implications of these findings.

Demand for Light Duty Trucks : The Wharton EFA Motor Vehicle Demand Model (Mark II).

DOT National Transportation Integrated Search

1981-01-01

A preliminary model of U.S. light-duty vehicle demand is presented which contains an integrated analysis of automobiles and light trucks (under 10,000 lbs. GVW). The model has been estimated using both cross-section and time-series data, and is a dev...

Remote sensing inputs to water demand modeling

NASA Technical Reports Server (NTRS)

Estes, J. E.; Jensen, J. R.; Tinney, L. R.; Rector, M.

1975-01-01

In an attempt to determine the ability of remote sensing techniques to economically generate data required by water demand models, the Geography Remote Sensing Unit, in conjunction with the Kern County Water Agency of California, developed an analysis model. As a result it was determined that agricultural cropland inventories utilizing both high altitude photography and LANDSAT imagery can be conducted cost effectively. In addition, by using average irrigation application rates in conjunction with cropland data, estimates of agricultural water demand can be generated. However, more accurate estimates are possible if crop type, acreage, and crop specific application rates are employed. An analysis of the effect of saline-alkali soils on water demand in the study area is also examined. Finally, reference is made to the detection and delineation of water tables that are perched near the surface by semi-permeable clay layers. Soil salinity prediction, automated crop identification on a by-field basis, and a potential input to the determination of zones of equal benefit taxation are briefly touched upon.

Scenarios for Demand Growth of Metals in Electricity Generation Technologies, Cars, and Electronic Appliances

PubMed Central

2018-01-01

This study provides scenarios toward 2050 for the demand of five metals in electricity production, cars, and electronic appliances. The metals considered are copper, tantalum, neodymium, cobalt, and lithium. The study shows how highly technology-specific data on products and material flows can be used in integrated assessment models to assess global resource and metal demand. We use the Shared Socio-economic Pathways as implemented by the IMAGE integrated assessment model as a starting point. This allows us to translate information on the use of electronic appliances, cars, and renewable energy technologies into quantitative data on metal flows, through application of metal content estimates in combination with a dynamic stock model. Results show that total demand for copper, neodymium, and tantalum might increase by a factor of roughly 2 to 3.2, mostly as a result of population and GDP growth. The demand for lithium and cobalt is expected to increase much more, by a factor 10 to more than 20, as a result of future (hybrid) electric car purchases. This means that not just demographics, but also climate policies can strongly increase metal demand. This shows the importance of studying the issues of climate change and resource depletion together, in one modeling framework. PMID:29533657

Scenarios for Demand Growth of Metals in Electricity Generation Technologies, Cars, and Electronic Appliances.

PubMed

Deetman, Sebastiaan; Pauliuk, Stefan; van Vuuren, Detlef P; van der Voet, Ester; Tukker, Arnold

2018-04-17

This study provides scenarios toward 2050 for the demand of five metals in electricity production, cars, and electronic appliances. The metals considered are copper, tantalum, neodymium, cobalt, and lithium. The study shows how highly technology-specific data on products and material flows can be used in integrated assessment models to assess global resource and metal demand. We use the Shared Socio-economic Pathways as implemented by the IMAGE integrated assessment model as a starting point. This allows us to translate information on the use of electronic appliances, cars, and renewable energy technologies into quantitative data on metal flows, through application of metal content estimates in combination with a dynamic stock model. Results show that total demand for copper, neodymium, and tantalum might increase by a factor of roughly 2 to 3.2, mostly as a result of population and GDP growth. The demand for lithium and cobalt is expected to increase much more, by a factor 10 to more than 20, as a result of future (hybrid) electric car purchases. This means that not just demographics, but also climate policies can strongly increase metal demand. This shows the importance of studying the issues of climate change and resource depletion together, in one modeling framework.

Modeling water demand when households have multiple sources of water

NASA Astrophysics Data System (ADS)

Coulibaly, Lassina; Jakus, Paul M.; Keith, John E.

2014-07-01

A significant portion of the world's population lives in areas where public water delivery systems are unreliable and/or deliver poor quality water. In response, people have developed important alternatives to publicly supplied water. To date, most water demand research has been based on single-equation models for a single source of water, with very few studies that have examined water demand from two sources of water (where all nonpublic system water sources have been aggregated into a single demand). This modeling approach leads to two outcomes. First, the demand models do not capture the full range of alternatives, so the true economic relationship among the alternatives is obscured. Second, and more seriously, economic theory predicts that demand for a good becomes more price-elastic as the number of close substitutes increases. If researchers artificially limit the number of alternatives studied to something less than the true number, the price elasticity estimate may be biased downward. This paper examines water demand in a region with near universal access to piped water, but where system reliability and quality is such that many alternative sources of water exist. In extending the demand analysis to four sources of water, we are able to (i) demonstrate why households choose the water sources they do, (ii) provide a richer description of the demand relationships among sources, and (iii) calculate own-price elasticity estimates that are more elastic than those generally found in the literature.

An inventory model with random demand

NASA Astrophysics Data System (ADS)

Mitsel, A. A.; Kritski, O. L.; Stavchuk, LG

2017-01-01

The article describes a three-product inventory model with random demand at equal frequencies of delivery. A feature of this model is that the additional purchase of resources required is carried out within the scope of their deficit. This fact allows reducing their storage costs. A simulation based on the data on arrival of raw and materials at an enterprise in Kazakhstan has been prepared. The proposed model is shown to enable savings up to 40.8% of working capital.

Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective

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

Cole, Wesley J.; Frew, Bethany A.; Mai, Trieu T.

Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision makers. With the recent surge in variable renewable energy (VRE) generators - primarily wind and solar photovoltaics - the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. To assess current best practices, share methods and data, and identify future research needs for VRE representation in capacity expansion models, four capacity expansion modeling teams from the Electric Powermore » Research Institute, the U.S. Energy Information Administration, the U.S. Environmental Protection Agency, and the National Renewable Energy Laboratory conducted two workshops of VRE modeling for national-scale capacity expansion models. The workshops covered a wide range of VRE topics, including transmission and VRE resource data, VRE capacity value, dispatch and operational modeling, distributed generation, and temporal and spatial resolution. The objectives of the workshops were both to better understand these topics and to improve the representation of VRE across the suite of models. Given these goals, each team incorporated model updates and performed additional analyses between the first and second workshops. This report summarizes the analyses and model 'experiments' that were conducted as part of these workshops as well as the various methods for treating VRE among the four modeling teams. The report also reviews the findings and learnings from the two workshops. We emphasize the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making.« less

Comparing exponential and exponentiated models of drug demand in cocaine users.

PubMed

Strickland, Justin C; Lile, Joshua A; Rush, Craig R; Stoops, William W

2016-12-01

Drug purchase tasks provide rapid and efficient measurement of drug demand. Zero values (i.e., prices with zero consumption) present a quantitative challenge when using exponential demand models that exponentiated models may resolve. We aimed to replicate and advance the utility of using an exponentiated model by demonstrating construct validity (i.e., association with real-world drug use) and generalizability across drug commodities. Participants (N = 40 cocaine-using adults) completed Cocaine, Alcohol, and Cigarette Purchase Tasks evaluating hypothetical consumption across changes in price. Exponentiated and exponential models were fit to these data using different treatments of zero consumption values, including retaining zeros or replacing them with 0.1, 0.01, or 0.001. Excellent model fits were observed with the exponentiated model. Means and precision fluctuated with different replacement values when using the exponential model but were consistent for the exponentiated model. The exponentiated model provided the strongest correlation between derived demand intensity (Q0) and self-reported free consumption in all instances (Cocaine r = .88; Alcohol r = .97; Cigarette r = .91). Cocaine demand elasticity was positively correlated with alcohol and cigarette elasticity. Exponentiated parameters were associated with real-world drug use (e.g., weekly cocaine use) whereas these correlations were less consistent for exponential parameters. Our findings show that selection of zero replacement values affects demand parameters and their association with drug-use outcomes when using the exponential model but not the exponentiated model. This work supports the adoption of the exponentiated demand model by replicating improved fit and consistency and demonstrating construct validity and generalizability. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Beyond Renewable Portfolio Standards: An Assessment of Regional Supply and Demand Conditions Affecting the Future of Renewable Energy in the West; Report and Executive Summary

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

Hurlbut, D. J.; McLaren, J.; Gelman, R.

2013-08-01

This study assesses the outlook for utility-scale renewable energy development in the West once states have met their renewable portfolio standard (RPS) requirements. In the West, the last state RPS culminates in 2025, so the analysis uses 2025 as a transition point on the timeline of RE development. Most western states appear to be on track to meet their final requirements, relying primarily on renewable resources located relatively close to the customers being served. What happens next depends on several factors including trends in the supply and price of natural gas, greenhouse gas and other environmental regulations, consumer preferences, technologicalmore » breakthroughs, and future public policies and regulations. Changes in any one of these factors could make future renewable energy options more or less attractive.« less

A novel medical information management and decision model for uncertain demand optimization.

PubMed

Bi, Ya

2015-01-01

Accurately planning the procurement volume is an effective measure for controlling the medicine inventory cost. Due to uncertain demand it is difficult to make accurate decision on procurement volume. As to the biomedicine sensitive to time and season demand, the uncertain demand fitted by the fuzzy mathematics method is obviously better than general random distribution functions. To establish a novel medical information management and decision model for uncertain demand optimization. A novel optimal management and decision model under uncertain demand has been presented based on fuzzy mathematics and a new comprehensive improved particle swarm algorithm. The optimal management and decision model can effectively reduce the medicine inventory cost. The proposed improved particle swarm optimization is a simple and effective algorithm to improve the Fuzzy interference and hence effectively reduce the calculation complexity of the optimal management and decision model. Therefore the new model can be used for accurate decision on procurement volume under uncertain demand.

Greening the Grid: Advances in Production Cost Modeling for India Renewable Energy Grid Integration Study

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

Cochran, Jaquelin; Palchak, David

The Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid study uses advanced weather and power system modeling to explore the operational impacts of meeting India's 2022 renewable energy targets and identify actions that may be favorable for integrating high levels of renewable energy into the Indian grid. The study relies primarily on a production cost model that simulates optimal scheduling and dispatch of available generation in a future year (2022) by minimizing total production costs subject to physical, operational, and market constraints. This fact sheet provides a detailed look at each of thesemore » models, including their common assumptions and the insights provided by each.« less

Joint Real-Time Energy and Demand-Response Management using a Hybrid Coalitional-Noncooperative Game

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

He, Fulin; Gu, Yi; Hao, Jun

In order to model the interactions among utility companies, building demands and renewable energy generators (REGs), a hybrid coalitional-noncooperative game framework has been proposed. We formulate a dynamic non-cooperative game to study the energy dispatch within multiple utility companies, while we take a coalitional perspective on REGs and buildings demands through a hedonic coalition formation game approach. In this case, building demands request different power supply from REGs, then the building demands can be organized into an ultimate coalition structure through a distributed hedonic shift algorithm. At the same time, utility companies can also obtain a stable power generation profile.more » In addition, the interactive progress among the utility companies and building demands which cannot be supplied by REGs is implemented by distributed game theoretic algorithms. Numerical results illustrate that the proposed hybrid coalitional-noncooperative game scheme reduces the cost of both building demands and utility companies compared with the initial scene.« less

Off-stream Pumped Storage Hydropower plant to increase renewable energy penetration in Santiago Island, Cape Verde

NASA Astrophysics Data System (ADS)

Barreira, Inês; Gueifão, Carlos; Ferreira de Jesus, J.

2017-04-01

In order to reduce the high dependence on imported fuels and to meet the ongoing growth of electricity demand, Cape Verde government set the goal to increase renewable energy penetration in Santiago Island until 2020. To help maximize renewable energy penetration, an off-stream Pumped Storage Hydropower (PSH) plant will be installed in Santiago, in one of the following locations: Chã Gonçalves, Mato Sancho and Ribeira dos Picos. This paper summarizes the studies carried out to find the optimal location and connection point of the PSH plant in Santiago’s electricity network. This goal was achieved by assessing the impact of the PSH plant, in each location, on power system stability. The simulation tool PSS/E of Siemens was used to study the steady-state and dynamic behavior of the future (2020) Santiago MV grid. Different scenarios of demand and renewable resources were created. Each hydro unit of the PSH plant was modeled as an adjustable speed reversible turbine employing a DFIM. The results show that Santiago’s grid with the PSH plant in Chã Gonçalves is the one that has the best performance.

Model documentation report: Residential sector demand module of the national energy modeling system

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

NONE

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This reference document provides a detailed description for energy analysts, other users, and the public. The NEMS Residential Sector Demand Module is currently used for mid-term forecasting purposes and energy policy analysis over the forecast horizon of 1993 through 2020. The model generates forecasts of energy demand for the residential sector by service, fuel, and Census Division. Policy impacts resulting from new technologies,more » market incentives, and regulatory changes can be estimated using the module. 26 refs., 6 figs., 5 tabs.« less

The Job Demands-Resources Model: An Analysis of Additive and Joint Effects of Demands and Resources

ERIC Educational Resources Information Center

Hu, Qiao; Schaufeli, Wilmar B.; Taris, Toon W.

2011-01-01

The present study investigated the additive, synergistic, and moderating effects of job demands and job resources on well-being (burnout and work engagement) and organizational outcomes, as specified by the Job Demands-Resources (JD-R) model. A survey was conducted among two Chinese samples: 625 blue collar workers and 761 health professionals. A…

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

Reconciling Reinforcement Learning Models with Behavioral Extinction and Renewal: Implications for Addiction, Relapse, and Problem Gambling

ERIC Educational Resources Information Center

Redish, A. David; Jensen, Steve; Johnson, Adam; Kurth-Nelson, Zeb

2007-01-01

Because learned associations are quickly renewed following extinction, the extinction process must include processes other than unlearning. However, reinforcement learning models, such as the temporal difference reinforcement learning (TDRL) model, treat extinction as an unlearning of associated value and are thus unable to capture renewal. TDRL…

Accounting for Water Insecurity in Modeling Domestic Water Demand

NASA Astrophysics Data System (ADS)

Galaitsis, S. E.; Huber-lee, A. T.; Vogel, R. M.; Naumova, E.

2013-12-01

Water demand management uses price elasticity estimates to predict consumer demand in relation to water pricing changes, but studies have shown that many additional factors effect water consumption. Development scholars document the need for water security, however, much of the water security literature focuses on broad policies which can influence water demand. Previous domestic water demand studies have not considered how water security can affect a population's consumption behavior. This study is the first to model the influence of water insecurity on water demand. A subjective indicator scale measuring water insecurity among consumers in the Palestinian West Bank is developed and included as a variable to explore how perceptions of control, or lack thereof, impact consumption behavior and resulting estimates of price elasticity. A multivariate regression model demonstrates the significance of a water insecurity variable for data sets encompassing disparate water access. When accounting for insecurity, the R-squaed value improves and the marginal price a household is willing to pay becomes a significant predictor for the household quantity consumption. The model denotes that, with all other variables held equal, a household will buy more water when the users are more water insecure. Though the reasons behind this trend require further study, the findings suggest broad policy implications by demonstrating that water distribution practices in scarcity conditions can promote consumer welfare and efficient water use.

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.

Renewable energy scenario in India: Opportunities and challenges

NASA Astrophysics Data System (ADS)

Sen, Souvik; Ganguly, Sourav; Das, Ayanangshu; Sen, Joyjeet; Dey, Sourav

2016-10-01

Majority of the power generation in India is carried out by conventional energy sources, coal and fossil fuels being the primary ones, which contribute heavily to greenhouse gas emission and global warming. The Indian power sector is witnessing a revolution as excitement grips the nation about harnessing electricity from various renewable energy sources. Electricity generation from renewable sources is increasingly recognized to play an important role for the achievement of a variety of primary and secondary energy policy goals, such as improved diversity and security of energy supply, reduction of local pollutant and global greenhouse gas emissions, regional and rural development, and exploitation of opportunities for fostering social cohesion, value addition and employment generation at the local and regional level. This focuses the solution of the energy crisis on judicious utilization of abundant the renewable energy resources, such as biomass, solar, wind, geothermal and ocean tidal energy. This paper reviews the renewable energy scenario of India as well as extrapolates the future developments keeping in view the consumption, production and supply of power. Research, development, production and demonstration have been carried out enthusiastically in India to find a feasible solution to the perennial problem of power shortage for the past three decades. India has obtained application of a variety of renewable energy technologies for use in different sectors too. There are ample opportunities with favorable geology and geography with huge customer base and widening gap between demand and supply. Technological advancement, suitable regulatory policies, tax rebates, efficiency improvement in consequence to R&D efforts are the few pathways to energy and environment conservation and it will ensure that these large, clean resource bases are exploited as quickly and cost effectively as possible. This paper gives an overview of the potential renewable energy resources

Integrated water and renewable energy management: the Acheloos-Peneios region case study

NASA Astrophysics Data System (ADS)

Koukouvinos, Antonios; Nikolopoulos, Dionysis; Efstratiadis, Andreas; Tegos, Aristotelis; Rozos, Evangelos; Papalexiou, Simon-Michael; Dimitriadis, Panayiotis; Markonis, Yiannis; Kossieris, Panayiotis; Tyralis, Christos; Karakatsanis, Georgios; Tzouka, Katerina; Christofides, Antonis; Karavokiros, George; Siskos, Alexandros; Mamassis, Nikos; Koutsoyiannis, Demetris

2015-04-01

Within the ongoing research project "Combined Renewable Systems for Sustainable Energy Development" (CRESSENDO), we have developed a novel stochastic simulation framework for optimal planning and management of large-scale hybrid renewable energy systems, in which hydropower plays the dominant role. The methodology and associated computer tools are tested in two major adjacent river basins in Greece (Acheloos, Peneios) extending over 15 500 km2 (12% of Greek territory). River Acheloos is characterized by very high runoff and holds ~40% of the installed hydropower capacity of Greece. On the other hand, the Thessaly plain drained by Peneios - a key agricultural region for the national economy - usually suffers from water scarcity and systematic environmental degradation. The two basins are interconnected through diversion projects, existing and planned, thus formulating a unique large-scale hydrosystem whose future has been the subject of a great controversy. The study area is viewed as a hypothetically closed, energy-autonomous, system, in order to evaluate the perspectives for sustainable development of its water and energy resources. In this context we seek an efficient configuration of the necessary hydraulic and renewable energy projects through integrated modelling of the water and energy balance. We investigate several scenarios of energy demand for domestic, industrial and agricultural use, assuming that part of the demand is fulfilled via wind and solar energy, while the excess or deficit of energy is regulated through large hydroelectric works that are equipped with pumping storage facilities. The overall goal is to examine under which conditions a fully renewable energy system can be technically and economically viable for such large spatial scale.

A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response

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

Anderson, C. Lindsay; Zéphyr, Luckny; Liu, Jialin

The evolution of the power system to the reliable, effi- cient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of re- newable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distri- bution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for co- optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this frame- work, microgrids encompass consumers, distributed renewablesmore » and storage. The energy management system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the devel- opment of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic op- timization, including decomposition and stochastic dual dynamic programming.« less

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

NASA Technical Reports Server (NTRS)

Viken, Jeff; Dollyhigh, Samuel; Smith, Jeremy; Trani, Antonio; Baik, Hojong; Hinze, Nicholas; Ashiabor, Senanu

2006-01-01

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These

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.

Spatial optimization of an ideal wind energy system as a response to the intermittency of renewable energies?

NASA Astrophysics Data System (ADS)

Lassonde, Sylvain; Boucher, Olivier; Breon, François-Marie; Tobin, Isabelle; Vautard, Robert

2016-04-01

The share of renewable energies in the mix of electricity production is increasing worldwide. This trend is driven by environmental and economic policies aiming at a reduction of greenhouse gas emissions and an improvement of energy security. It is expected to continue in the forthcoming years and decades. Electricity production from renewables is related to weather and climate factors such as the diurnal and seasonal cycles of sunlight and wind, but is also linked to variability on all time scales. The intermittency in the renewable electricity production (solar, wind power) could eventually hinder their future deployment. Intermittency is indeed a challenge as demand and supply of electricity need to be balanced at any time. This challenge can be addressed by the deployment of an overcapacity in power generation (from renewable and/or thermal sources), a large-scale energy storage system and/or improved management of the demand. The main goal of this study is to optimize a hypothetical renewable energy system at the French and European scales in order to investigate if spatial diversity of the production (here electricity from wind energy) could be a response to the intermittency. We use ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-interim meteorological reanalysis and meteorological fields from the Weather Research and Forecasts (WRF) model to estimate the potential for wind power generation. Electricity demand and production are provided by the French electricity network (RTE) at the scale of administrative regions for years 2013 and 2014. Firstly we will show how the simulated production of wind power compares against the measured production at the national and regional scale. Several modelling and bias correction methods of wind power production will be discussed. Secondly, we will present results from an optimization procedure that aims to minimize some measure of the intermittency of wind energy. For instance we estimate the optimal

On- and off-grid operation of hybrid renewable power plants: When are the economics favorable?

NASA Astrophysics Data System (ADS)

Petrakopoulou, F.; Santana, D.

2016-12-01

Hybrid renewable energy conversion systems offer a good alternative to conventional systems in locations where the extension of the electrical grid is difficult or not economical or where the cost of electricity is high. However, stand-alone operation implies net energy output restrictions (limited to exclusively serve the energy demand of a region), capacity oversizing and large storage facilities. In interconnected areas, on the other hand, the operational restrictions of the power stations change significantly and the efficiencies and costs of renewable technologies become more favorable. In this paper, the operation of three main renewable technologies (CSP, PV and wind) is studied assuming both hybrid and individual operation for both autonomous and inter-connected operation. The case study used is a Mediterranean island of ca. 3,000 inhabitants. Each system is optimized to fully cover the energy demand of the community. In addition, in the on-grid operation cases, it is required that the annual energy generated from the renewable sources is net positive (i.e., the island generates at least as much energy as it uses). It is found that when connected to the grid, hybridization of more than one technology is not required to satisfy the energy demand, as expected. Each of the renewable technologies investigated can satisfy the annual energy demand individually, without significant complications. In addition, the cost of electricity generated with the three studied technologies drops significantly for on-grid applications, when compared to off-grid operation. However, when compared to business-as-usual scenarios in both the on- and off-grid cases, both investigated hybrid and single-technology renewable scenarios are found to be economically viable. A sensitivity analysis reveals the limits of the acceptable costs that make the technologies favorable when compared to conventional alternatives.

How might renewable energy technologies fit in the food-water-energy nexus?

NASA Astrophysics Data System (ADS)

Newmark, R. L.; Macknick, J.; Heath, G.; Ong, S.; Denholm, P.; Margolis, R.; Roberts, B.

2011-12-01

Feeding the growing population in the U.S. will require additional land for crop and livestock production. Similarly, a growing population will require additional sources of energy. Renewable energy is likely to play an increased role in meeting the new demands of electricity consumers. Renewable energy technologies can differ from conventional technologies in their operation and their siting locations. Many renewable energy technologies have a lower energy density than conventional technologies and can also have large land use requirements. Much of the prime area suitable for renewable energy development in the U.S. has historically been used for agricultural production, and there is some concern that renewable energy installations could displace land currently producing food crops. In addition to requiring vast expanses of land, both agriculture and renewable energy can require water. The agriculture and energy sectors are responsible for the majority of water withdrawals in the U.S. Increases in both agricultural and energy demand can lead to increases in water demands, depending on crop management and energy technologies employed. Water is utilized in the energy industry primarily for power plant cooling, but it is also required for steam cycle processes and cleaning. Recent characterizations of water use by different energy and cooling system technologies demonstrate the choice of fuel and cooling system technologies can greatly impact the withdrawals and the consumptive use of water in the energy industry. While some renewable and conventional technology configurations can utilize more water per unit of land than irrigation-grown crops, other renewable technology configurations utilize no water during operations and could lead to reduced stress on water resources. Additionally, co-locating agriculture and renewable energy production is also possible with many renewable technologies, avoiding many concerns about reductions in domestic food production. Various

The Analysis of Renewable Energy Researches in Turkey

NASA Astrophysics Data System (ADS)

Tan, S. O.; Toku, T.; Türker, İ.

2016-11-01

The rapid consumption of limited conventional energy resources mobilizes many countries in the world against global energy crisis. As well as the energy crisis, the environmental pollution caused by existing energy sources also encourages the researchers to study in new energy technologies and also renewable energy resources. From this point of view, it is important for each country to identify its wind, solar, geothermal, biomass, hydro and other renewable energy potentials. Considering this urgent energy requirement, the researches and especially the academic studies have been increased on renewable energy resources to meet the energy demand by means of indigenous resources in each country. Consequently, the main purpose of this study is to analyze the academic studies in Turkey to find out the increment rate of researches, their publication years and the more focusing branch on renewable energy by illustrating the statistical distribution of these data. Automated Data Retrieval Methods have been employed to achieve data from Web of Science database and statistical analyses have been made by SQL server management studio program. The academic studies in all variety of renewable energy areas have a tendency to increase which indicates the importance ratio of renewable energy in Turkey.

Energy in buildings: Efficiency, renewables and storage

NASA Astrophysics Data System (ADS)

Koebel, Matthias M.

2017-07-01

This lecture summary provides a short but comprehensive overview on the "energy and buildings" topic. Buildings account for roughly 40% of the global energy demands. Thus, an increased adoption of existing and upcoming materials and solutions for the building sector represents an enormous potential to reduce building related energy demands and greenhouse gas emissions. The central question is how the building envelope (insulation, fenestration, construction style, solar control) affects building energy demands. Compared to conventional insulation materials, superinsulation materials such as vacuum insulation panels and silica aerogel achieve the same thermal performance with significantly thinner insulation layers. With low-emissivity coatings and appropriate filler gasses, double and triple glazing reduce thermal losses by up to an order of magnitude compared to old single pane windows, while vacuum insulation and aerogel filled glazing could reduce these even further. Electrochromic and other switchable glazing solutions maximize solar gains during wintertime and minimize illumination demands whilst avoiding overheating in summer. Upon integration of renewable energy systems into the building energy supply, buildings can become both producers and consumers of energy. Combined with dynamic user behavior, temporal variations in the production of renewable energy require appropriate storage solutions, both thermal and electrical, and the integration of buildings into smart grids and energy district networks. The combination of these measures allows a reduction of the existing building stock by roughly a factor of three —a promising, but cost intensive way, to prepare our buildings for the energy turnaround.

A Data Envelopment Analysis Model for Renewable Energy Technology Selection

USDA-ARS?s Scientific Manuscript database

Public and media interest in alternative energy sources, such as renewable fuels, has rapidly increased in recent years due to higher prices for oil and natural gas. However, the current body of research providing comparative decision making models that either rank these alternative energy sources a...

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

Self-Efficacy and Workaholism as Initiators of the Job Demands-Resources Model

ERIC Educational Resources Information Center

Guglielmi, Dina; Simbula, Silvia; Schaufeli, Wilmar B.; Depolo, Marco

2012-01-01

Purpose: This study aims to investigate school principals' well-being by using the job demands-resources (JD-R) model as a theoretical framework. It aims at making a significant contribution to the development of this model by considering not only job demands and job resources, but also the role of personal resources and personal demands as…

Multi-state time-varying reliability evaluation of smart grid with flexible demand resources utilizing Lz transform

NASA Astrophysics Data System (ADS)

Jia, Heping; Jin, Wende; Ding, Yi; Song, Yonghua; Yu, Dezhao

2017-01-01

With the expanding proportion of renewable energy generation and development of smart grid technologies, flexible demand resources (FDRs) have been utilized as an approach to accommodating renewable energies. However, multiple uncertainties of FDRs may influence reliable and secure operation of smart grid. Multi-state reliability models for a single FDR and aggregating FDRs have been proposed in this paper with regard to responsive abilities for FDRs and random failures for both FDR devices and information system. The proposed reliability evaluation technique is based on Lz transform method which can formulate time-varying reliability indices. A modified IEEE-RTS has been utilized as an illustration of the proposed technique.

Geological subsurface will contribute significantly to the implementation of the energy policy towards renewables in Germany

NASA Astrophysics Data System (ADS)

Martens, Sonja; Kühn, Michael

2015-04-01

The demands to exploit the geological subsurface are increasing. In addition to the traditional production of raw materials such as natural gas and petroleum, or potable groundwater extraction the underground will most likely also be used to implement the climate and energy policy objectives in the context of the energy transition to renewables. These include the storage of energy from renewable sources (e.g. hydrogen and methane), the use of geothermal energy and possibly the long-term storage of carbon dioxide to reduce the release of greenhouse gases into the atmosphere. The presentation addresses the question which realistic contribution can be expected from the geo-resource subsurface for the energy revolution, the detachment of fossil and nuclear fuels as well as the reduction of CO2 emissions. The study of Henning and Palzer [1] that models the energy balance of the electricity and heat sector including all renewable energy converters, storage components and loads for a future German energy system shows that provision with 100% renewables is economically feasible by 2050. Based on their work, our estimates underline that already in 2015 more than 100% of the required methane storage capacities therein are available and more than 100% of the heat pump demands might be covered by shallow and deep geothermal energy production in the future. In addition we show that a newly developed energy storage system [2-3] could be applied to store 20-60% of the surplus energy from renewables expected for 2050 with integrated gas storage of methane and CO2. [1] Henning H-M, Palzer A (2014) A comprehensive model for the German electricity and heat sector in a future energy system with a dominant contribution from renewable energy technologies -- Part I: Methodology. Renewable and Sustainable Energy Reviews 30, 1003-1018. doi: 10.1016/j.rser.2013.09.012 [2] Kühn M, Nakaten N, Streibel M, Kempka T (2014) CO2 geological storage and utilization for a carbon neutral "power

Development of S-ARIMA Model for Forecasting Demand in a Beverage Supply Chain

NASA Astrophysics Data System (ADS)

Mircetic, Dejan; Nikolicic, Svetlana; Maslaric, Marinko; Ralevic, Nebojsa; Debelic, Borna

2016-11-01

Demand forecasting is one of the key activities in planning the freight flows in supply chains, and accordingly it is essential for planning and scheduling of logistic activities within observed supply chain. Accurate demand forecasting models directly influence the decrease of logistics costs, since they provide an assessment of customer demand. Customer demand is a key component for planning all logistic processes in supply chain, and therefore determining levels of customer demand is of great interest for supply chain managers. In this paper we deal with exactly this kind of problem, and we develop the seasonal Autoregressive IntegratedMoving Average (SARIMA) model for forecasting demand patterns of a major product of an observed beverage company. The model is easy to understand, flexible to use and appropriate for assisting the expert in decision making process about consumer demand in particular periods.

Using Count Data and Ordered Models in National Forest Recreation Demand Analysis

NASA Astrophysics Data System (ADS)

Simões, Paula; Barata, Eduardo; Cruz, Luis

2013-11-01

This research addresses the need to improve our knowledge on the demand for national forests for recreation and offers an in-depth data analysis supported by the complementary use of count data and ordered models. From a policy-making perspective, while count data models enable the estimation of monetary welfare measures, ordered models allow for the wider use of the database and provide a more flexible analysis of data. The main purpose of this article is to analyse the individual forest recreation demand and to derive a measure of its current use value. To allow a more complete analysis of the forest recreation demand structure the econometric approach supplements the use of count data models with ordered category models using data obtained by means of an on-site survey in the Bussaco National Forest (Portugal). Overall, both models reveal that travel cost and substitute prices are important explanatory variables, visits are a normal good and demographic variables seem to have no influence on demand. In particular, estimated price and income elasticities of demand are quite low. Accordingly, it is possible to argue that travel cost (price) in isolation may be expected to have a low impact on visitation levels.

Economic concepts to address future water supply-demand imbalances in Iran, Morocco and Saudi Arabia

NASA Astrophysics Data System (ADS)

Hellegers, Petra; Immerzeel, Walter; Droogers, Peter

2013-10-01

In Middle East and North Africa (MENA) countries, renewable groundwater and surface water supply are limited while demand for water is growing rapidly. Climate change is expected to increase water demand even further. The main aim of this paper is to evaluate the water supply-demand imbalances in Iran, Morocco and Saudi Arabia in 2040-2050 under dry, average and wet climate change projections and to show on the basis of the marginal cost and marginal value of water the optimum mix of supply-side and demand-side adjustments to address the imbalance. A hydrological model has been used to estimate the water supply-demand imbalance. Water supply and demand curves have been used to explore for which (marginal value of) water usage the marginal cost of supply-enhancement becomes too expensive. The results indicate that in the future in all cases, except in Iran under the wet climate projection, the quantity of water demanded has to be reduced considerably to address the imbalance, which is indeed what is currently happening already.

RENEW v3.2 user's manual, maintenance estimation simulation for Space Station Freedom Program

NASA Technical Reports Server (NTRS)

Bream, Bruce L.

1993-01-01

RENEW is a maintenance event estimation simulation program developed in support of the Space Station Freedom Program (SSFP). This simulation uses reliability and maintainability (R&M) and logistics data to estimate both average and time dependent maintenance demands. The simulation uses Monte Carlo techniques to generate failure and repair times as a function of the R&M and logistics parameters. The estimates are generated for a single type of orbital replacement unit (ORU). The simulation has been in use by the SSFP Work Package 4 prime contractor, Rocketdyne, since January 1991. The RENEW simulation gives closer estimates of performance since it uses a time dependent approach and depicts more factors affecting ORU failure and repair than steady state average calculations. RENEW gives both average and time dependent demand values. Graphs of failures over the mission period and yearly failure occurrences are generated. The averages demand rate for the ORU over the mission period is also calculated. While RENEW displays the results in graphs, the results are also available in a data file for further use by spreadsheets or other programs. The process of using RENEW starts with keyboard entry of the R&M and operational data. Once entered, the data may be saved in a data file for later retrieval. The parameters may be viewed and changed after entry using RENEW. The simulation program runs the number of Monte Carlo simulations requested by the operator. Plots and tables of the results can be viewed on the screen or sent to a printer. The results of the simulation are saved along with the input data. Help screens are provided with each menu and data entry screen.

Analysis on the accommodation of renewable energy in northeast China

NASA Astrophysics Data System (ADS)

Liu, Jun; Zhang, Jinfang; Tian, Feng; Mi, Zhe

2017-01-01

The accommodation and curtailment of renewable energy in northeast China have attracted much attention with the rapid growth of wind and solar power generation. Large amount of wind power has been curtailed or abandoned in northeast China due to several reasons, such as, the redundancy of power supplies, inadequate power demands, imperfect power structure with less flexibility and limited cross-regional transmission capacity. In this paper, we use multi-area production simulation to analyse the accommodation of renewable energy in northeast China by 2020. Furthermore, we suggest the measures that could be adopted in generation, grid and load side to reduce curtailment of renewables.

Demands For Solar Electricity From The BRICS Countries In The Future

NASA Astrophysics Data System (ADS)

Fan, Y.

2015-12-01

BRICS countries are presently among the leading the economic powers globally, but their increasing demands for energy and sustainable future requires renewed technical progress on implementation of renewable energy (e.g., solar energy) and a sustainable solution rather than extracting finite natural resources. BRICS countries (Brazil, Russia, India, China and South Africa) face both social and environmental pressures as their economy keeps growing. The rapid development of technology in BRICS inevitably altered their culture and behavior, as reflected by education, gender equality, health, and other demographic/socio-economic indicators. These changes coupled with land use/land cover change have altered ecosystem services, as reflected by NEE (Net Ecosystem Exchange of CO2) and NDVI (Normalized Difference Vegetation Index). Global climatic changes also drives the demand for sustainable energy. With a focus on solar energy, we analyzed time series of energy consuming behaviors, government policies, and the ecosystem services. Structural equation modeling was applied to confirm the relationships among societal transition, ecosystem services, and climate change. We compared the energy consumption patterns for the five countries and forecasted the changes through 2025. We found that government policies significantly influenced energy consumption behaviors for BRICS and that solar energy usage would continue to increase to 2025 and beyond.

Travel demand modeling for the small and medium sized MPOs in Illinois.

DOT National Transportation Integrated Search

2011-09-01

Travel demand modeling is an important tool in the transportation planning community. It helps forecast travel : characteristics into the future at various planning levels such as state, region and corridor. Using travel demand : modeling to evaluate...

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: Renewable Resource Data Center - Solar Resource Models and Tools

Science.gov Websites

Solar Resource Models and Tools The Renewable Resource Data Center (RReDC) features the following -supplied hourly average measured global horizontal data. NSRDB Data Viewer Visualize, explore, and download solar resource data from the National Solar Radiation Database. PVWatts® Calculator PVWattsÂ

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

NASA Technical Reports Server (NTRS)

Viken, Jeff; Dollyhigh, Samuel; Smith, Jeremy; Trani, Antonio; Baik, Hojong; Hinze, Nicholas; Ashiabor, Senanu

2006-01-01

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These

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.

A multivariate time series approach to modeling and forecasting demand in the emergency department.

PubMed

Jones, Spencer S; Evans, R Scott; Allen, Todd L; Thomas, Alun; Haug, Peter J; Welch, Shari J; Snow, Gregory L

2009-02-01

The goals of this investigation were to study the temporal relationships between the demands for key resources in the emergency department (ED) and the inpatient hospital, and to develop multivariate forecasting models. Hourly data were collected from three diverse hospitals for the year 2006. Descriptive analysis and model fitting were carried out using graphical and multivariate time series methods. Multivariate models were compared to a univariate benchmark model in terms of their ability to provide out-of-sample forecasts of ED census and the demands for diagnostic resources. Descriptive analyses revealed little temporal interaction between the demand for inpatient resources and the demand for ED resources at the facilities considered. Multivariate models provided more accurate forecasts of ED census and of the demands for diagnostic resources. Our results suggest that multivariate time series models can be used to reliably forecast ED patient census; however, forecasts of the demands for diagnostic resources were not sufficiently reliable to be useful in the clinical setting.

A multiple perspective modeling and simulation approach for renewable energy policy evaluation

NASA Astrophysics Data System (ADS)

Alyamani, Talal M.

Environmental issues and reliance on fossil fuel sources, including coal, oil, and natural gas, are the two most common energy issues that are currently faced by the United States (U.S.). Incorporation of renewable energy sources, a non-economical option in electricity generation compared to conventional sources that burn fossil fuels, single handedly promises a viable solution for both of these issues. Several energy policies have concordantly been suggested to reduce the financial burden of adopting renewable energy technologies and make such technologies competitive with conventional sources throughout the U.S. This study presents a modeling and analysis approach for comprehensive evaluation of renewable energy policies with respect to their benefits to various related stakeholders--customers, utilities, governmental and environmental agencies--where the debilitating impacts, advantages, and disadvantages of such policies can be assessed and quantified at the state level. In this work, a novel simulation framework is presented to help policymakers promptly assess and evaluate policies from different perspectives of its stakeholders. The proposed framework is composed of four modules: 1) a database that collates the economic, operational, and environmental data; 2) elucidation of policy, which devises the policy for the simulation model; 3) a preliminary analysis, which makes predictions for consumption, supply, and prices; and 4) a simulation model. After the validity of the proposed framework is demonstrated, a series of planned Florida and Texas renewable energy policies are implemented into the presented framework as case studies. Two solar and one energy efficiency programs are selected as part of the Florida case study. A utility rebate and federal tax credit programs are selected as part of the Texas case study. The results obtained from the simulation and conclusions drawn on the assessment of current energy policies are presented with respect to the

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.

A System Dynamics Modeling of Water Supply and Demand in Las Vegas Valley

NASA Astrophysics Data System (ADS)

Parajuli, R.; Kalra, A.; Mastino, L.; Velotta, M.; Ahmad, S.

2017-12-01

The rise in population and change in climate have posed the uncertainties in the balance between supply and demand of water. The current study deals with the water management issues in Las Vegas Valley (LVV) using Stella, a system dynamics modeling software, to model the feedback based relationship between supply and demand parameters. Population parameters were obtained from Center for Business and Economic Research while historical water demand and conservation practices were modeled as per the information provided by local authorities. The water surface elevation of Lake Mead, which is the prime source of water supply to the region, was modeled as the supply side whereas the water demand in LVV was modeled as the demand side. The study was done from the period of 1989 to 2049 with 1989 to 2012 as the historical one and the period from 2013 to 2049 as the future period. This study utilizes Coupled Model Intercomparison Project data sets (2013-2049) (CMIP3&5) to model different future climatic scenarios. The model simulates the past dynamics of supply and demand, and then forecasts the future water budget for the forecasted future population and future climatic conditions. The results can be utilized by the water authorities in understanding the future water status and hence plan suitable conservation policies to allocate future water budget and achieve sustainable water management.

Analysis of renewable energy sources and electric vehicle penetration into energy systems predominantly based on lignite

NASA Astrophysics Data System (ADS)

Dedinec, A.; Jovanovski, B.; Gajduk, A.; Markovska, N.; Kocarev, L.

2016-05-01

We consider an integration of renewable energy into transport and electricity sectors through vehicle to grid (V2G) technologies for an energy system that is predominantly based on lignite. The national energy system of Macedonia is modeled using EnergyPLAN which integrates energy for electricity, transport and heat, and includes hourly fluctuations in human needs and the environment. We show that electric-vehicles can provide the necessary storage enabling a fully renewable energy profile for Macedonia that can match the country's growing demand for energy. Furthermore, a large penetration of electric vehicles leads to a dramatic reduction of 47% of small particles and other air pollutants generated by car traffic in 2050.

[Application of job demands-resources model in research on relationships between job satisfaction, job resources, individual resources and job demands].

PubMed

Potocka, Adrianna; Waszkowska, Małgorzata

2013-01-01

The aim of this study was to explore the relationships between job demands, job resourses, personal resourses and job satisfaction and to assess the usefulness of the Job Demands-Resources (JD-R) model in the explanation of these phenomena. The research was based on a sample of 500 social workers. The "Psychosocial Factors" and "Job satisfaction" questionnaires were used to test the hypothesis. The results showed that job satisfaction increased with increasing job accessibility and personal resources (r = 0.44; r = 0.31; p < 0.05). The analysis of variance (ANOVA) indicated that job resources and job demands [F(1.474) = 4.004; F(1.474) = 4.166; p < 0.05] were statistically significant sources of variation in job satisfaction. Moreover, interactions between job demands and job resources [F(3,474) = 2.748; p <0.05], as well as between job demands and personal resources [F(3.474) = 3.021; p <0.05] had a significant impact on job satisfaction. The post hoc tests showed that 1) in low job demands, but high job resources employees declared higher job satisfaction, than those who perceived them as medium (p = 0.0001) or low (p = 0.0157); 2) when the level of job demands was perceived as medium, employees with high personal resources declared significantly higher job satisfaction than those with low personal resources (p = 0.0001). The JD-R model can be used to investigate job satisfaction. Taking into account fundamental factors of this model, in organizational management there are possibilities of shaping job satisfaction among employees.

Renewable Electricity Futures. Operational Analysis of the Western Interconnection at Very High Renewable Penetrations

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

Brinkman, Gregory

2015-09-01

The Renewable Electricity Futures Study (RE Futures)--an analysis of the costs and grid impacts of integrating large amounts of renewable electricity generation into the U.S. power system--examined renewable energy resources, technical issues regarding the integration of these resources into the grid, and the costs associated with high renewable penetration scenarios. These scenarios included up to 90% of annual generation from renewable sources, although most of the analysis was focused on 80% penetration scenarios. Hourly production cost modeling was performed to understand the operational impacts of high penetrations. One of the conclusions of RE Futures was that further work was necessarymore » to understand whether the operation of the system was possible at sub-hourly time scales and during transient events. This study aimed to address part of this by modeling the operation of the power system at sub-hourly time scales using newer methodologies and updated data sets for transmission and generation infrastructure. The goal of this work was to perform a detailed, sub-hourly analysis of very high penetration scenarios for a single interconnection (the Western Interconnection). It focused on operational impacts, and it helps verify that the operational results from the capacity expansion models are useful. The primary conclusion of this study is that sub-hourly operation of the grid is possible with renewable generation levels between 80% and 90%.« less

Dispatchable Renewable Energy Model for Microgrid Power System

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

Chiou, Fred; Gentle, Jake P.; McJunkin, Timothy R.

2017-04-01

Over the years, many research projects have been performed and focused on finding out the effective ways to balance the power demands and supply on the utility grid. The causes of the imbalance could be the increasing demands from the end users, the loss of power generation (generators down), faults on the transmission lines, power tripped due to overload, and weather conditions, etc. An efficient Load Frequency Control (LFC) can assure the desired electricity quality provided to the residential, commercial and industrial end users. A simulation model is built in this project to investigate the contribution of the modeling ofmore » dispatchable energy such as solar energy, wind power, hydro power and energy storage to the balance of the microgrid power system. An analysis of simplified feedback control system with proportional, integral, and derivative (PID) controller was performed. The purpose of this research is to investigate a simulation model that achieves certain degree of the resilient control for the microgrid.« less

On the renewal risk model under a threshold strategy

NASA Astrophysics Data System (ADS)

Dong, Yinghui; Wang, Guojing; Yuen, Kam C.

2009-08-01

In this paper, we consider the renewal risk process under a threshold dividend payment strategy. For this model, the expected discounted dividend payments and the Gerber-Shiu expected discounted penalty function are investigated. Integral equations, integro-differential equations and some closed form expressions for them are derived. When the claims are exponentially distributed, it is verified that the expected penalty of the deficit at ruin is proportional to the ruin probability.

Modeling hurricane evacuation traffic : development of a time-dependent hurricane evacuation demand model.

DOT National Transportation Integrated Search

2008-04-01

The objective of this research is to develop alternative time-dependent travel demand models of hurricane evacuation travel and to compare the performance of these models with each other and with the state-of-the-practice models in current use. Speci...

Robust analysis of semiparametric renewal process models

PubMed Central

Lin, Feng-Chang; Truong, Young K.; Fine, Jason P.

2013-01-01

Summary A rate model is proposed for a modulated renewal process comprising a single long sequence, where the covariate process may not capture the dependencies in the sequence as in standard intensity models. We consider partial likelihood-based inferences under a semiparametric multiplicative rate model, which has been widely studied in the context of independent and identical data. Under an intensity model, gap times in a single long sequence may be used naively in the partial likelihood with variance estimation utilizing the observed information matrix. Under a rate model, the gap times cannot be treated as independent and studying the partial likelihood is much more challenging. We employ a mixing condition in the application of limit theory for stationary sequences to obtain consistency and asymptotic normality. The estimator's variance is quite complicated owing to the unknown gap times dependence structure. We adapt block bootstrapping and cluster variance estimators to the partial likelihood. Simulation studies and an analysis of a semiparametric extension of a popular model for neural spike train data demonstrate the practical utility of the rate approach in comparison with the intensity approach. PMID:24550568

Multivariate time series modeling of short-term system scale irrigation demand

NASA Astrophysics Data System (ADS)

Perera, Kushan C.; Western, Andrew W.; George, Biju; Nawarathna, Bandara

2015-12-01

Travel time limits the ability of irrigation system operators to react to short-term irrigation demand fluctuations that result from variations in weather, including very hot periods and rainfall events, as well as the various other pressures and opportunities that farmers face. Short-term system-wide irrigation demand forecasts can assist in system operation. Here we developed a multivariate time series (ARMAX) model to forecast irrigation demands with respect to aggregated service points flows (IDCGi, ASP) and off take regulator flows (IDCGi, OTR) based across 5 command areas, which included area covered under four irrigation channels and the study area. These command area specific ARMAX models forecast 1-5 days ahead daily IDCGi, ASP and IDCGi, OTR using the real time flow data recorded at the service points and the uppermost regulators and observed meteorological data collected from automatic weather stations. The model efficiency and the predictive performance were quantified using the root mean squared error (RMSE), Nash-Sutcliffe model efficiency coefficient (NSE), anomaly correlation coefficient (ACC) and mean square skill score (MSSS). During the evaluation period, NSE for IDCGi, ASP and IDCGi, OTR across 5 command areas were ranged 0.98-0.78. These models were capable of generating skillful forecasts (MSSS ⩾ 0.5 and ACC ⩾ 0.6) of IDCGi, ASP and IDCGi, OTR for all 5 lead days and IDCGi, ASP and IDCGi, OTR forecasts were better than using the long term monthly mean irrigation demand. Overall these predictive performance from the ARMAX time series models were higher than almost all the previous studies we are aware. Further, IDCGi, ASP and IDCGi, OTR forecasts have improved the operators' ability to react for near future irrigation demand fluctuations as the developed ARMAX time series models were self-adaptive to reflect the short-term changes in the irrigation demand with respect to various pressures and opportunities that farmers' face, such as

Identifying Pathways toward Sustainable Electricity Supply and Demand Using an Integrated Resource Strategic Planning Model for Saudi Arabia

NASA Astrophysics Data System (ADS)

Alabbas, Nabeel H.

Despite holding 16% of proved oil reserves in the world, Saudi Arabia might be on an unsustainable path to become a net oil importer by the 2030s. Decades of domestic energy subsidies accompanied by a high population growth rate have encouraged inefficient production and high domestic consumption of fossil fuel energy, which has resulted in environmental degradation, and significant social and economic consequences. In addition, the government's dependence on oil as a main source of revenue (89%) to finance its development programs cannot be sustained due to oil's exhaustible nature and rapidly increasing domestic consumption. The electricity and water sectors consume more energy than other sectors. The literature review revealed that electricity use in Saudi Arabia is following an unsustainable path (7-8% annual growth over the last decade). The water sector is another major energy consumer due to an unprecedented demand for water in the Kingdom (18% of world's total desalinated water output with per capita consumption is twice the world average). Multiple entities have been involved in fragmented planning activities on the supply-side as well as to a certain extent on the demand-side; moreover, comprehensive integrated resource strategic plans have been lacking at the national level. This dissertation established an integrated resource strategic planning (IRSP) model for Saudi Arabia's electricity and water sectors. The IRSP can clearly determine the Kingdom's future vision of its utility sector, including goals, policies, programs, and an execution timetable, taking into consideration economic, environmental and social benefits. Also, a weather-based hybrid end-use econometric demand forecasting model was developed to project electricity demand until 2040. The analytical economic efficiency and technical assessments reveal that Saudi Arabia can supply almost 75% of its electricity from renewable energy sources with a significant achievable potential for saving

Demand modelling of passenger air travel: An analysis and extension, volume 2

NASA Technical Reports Server (NTRS)

Jacobson, I. D.

1978-01-01

Previous intercity travel demand models in terms of their ability to predict air travel in a useful way and the need for disaggregation in the approach to demand modelling are evaluated. The viability of incorporating non-conventional factors (i.e. non-econometric, such as time and cost) in travel demand forecasting models are determined. The investigation of existing models is carried out in order to provide insight into their strong points and shortcomings. The model is characterized as a market segmentation model. This is a consequence of the strengths of disaggregation and its natural evolution to a usable aggregate formulation. The need for this approach both pedagogically and mathematically is discussed. In addition this volume contains two appendices which should prove useful to the non-specialist in the area.

European energy and transport: scenarios on energy efficiency and renewables

DOT National Transportation Integrated Search

2006-07-01

Energy efficiency and renewables are central to the EU and Member State's energy and climate policies. Reducing CO2 emissions, curbing the energy demand and/or provide alternative carbon-free supplies. The EU energy policies have three main objective...

A genetic-algorithm-based remnant grey prediction model for energy demand forecasting.

PubMed

Hu, Yi-Chung

2017-01-01

Energy demand is an important economic index, and demand forecasting has played a significant role in drawing up energy development plans for cities or countries. As the use of large datasets and statistical assumptions is often impractical to forecast energy demand, the GM(1,1) model is commonly used because of its simplicity and ability to characterize an unknown system by using a limited number of data points to construct a time series model. This paper proposes a genetic-algorithm-based remnant GM(1,1) (GARGM(1,1)) with sign estimation to further improve the forecasting accuracy of the original GM(1,1) model. The distinctive feature of GARGM(1,1) is that it simultaneously optimizes the parameter specifications of the original and its residual models by using the GA. The results of experiments pertaining to a real case of energy demand in China showed that the proposed GARGM(1,1) outperforms other remnant GM(1,1) variants.

A genetic-algorithm-based remnant grey prediction model for energy demand forecasting

PubMed Central

2017-01-01

Energy demand is an important economic index, and demand forecasting has played a significant role in drawing up energy development plans for cities or countries. As the use of large datasets and statistical assumptions is often impractical to forecast energy demand, the GM(1,1) model is commonly used because of its simplicity and ability to characterize an unknown system by using a limited number of data points to construct a time series model. This paper proposes a genetic-algorithm-based remnant GM(1,1) (GARGM(1,1)) with sign estimation to further improve the forecasting accuracy of the original GM(1,1) model. The distinctive feature of GARGM(1,1) is that it simultaneously optimizes the parameter specifications of the original and its residual models by using the GA. The results of experiments pertaining to a real case of energy demand in China showed that the proposed GARGM(1,1) outperforms other remnant GM(1,1) variants. PMID:28981548

Jobs and Renewable Energy Project

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

Sterzinger, George

2006-12-19

Early in 2002, REPP developed the Jobs Calculator, a tool that calculates the number of direct jobs resulting from renewable energy development under RPS (Renewable Portfolio Standard) legislation or other programs to accelerate renewable energy development. The calculator is based on a survey of current industry practices to assess the number and type of jobs that will result from the enactment of a RPS. This project built upon and significantly enhanced the initial Jobs Calculator model by (1) expanding the survey to include other renewable technologies (the original model was limited to wind, solar PV and biomass co-firing technologies); (2)more » more precisely calculating the economic development benefits related to renewable energy development; (3) completing and regularly updating the survey of the commercially active renewable energy firms to determine kinds and number of jobs directly created; and (4) developing and implementing a technology to locate where the economic activity related to each type of renewable technology is likely to occur. REPP worked directly with groups in the State of Nevada to interpret the results and develop policies to capture as much of the economic benefits as possible for the state through technology selection, training program options, and outreach to manufacturing groups.« less

Will Renewable Energy Save Our Planet?

NASA Astrophysics Data System (ADS)

Bojić, Milorad

2010-06-01

This paper discusses some important fundamental issues behind application of renewable energy (RE) to evaluate its impact as a climate change mitigation technology. The discussed issues are the following: definition of renewable energy, concentration of RE by weight and volume, generation of electrical energy and its power at unit area, electrical energy demand per unit area, life time approach vs. layman approach, energy return time, energy return ratio, CO2 return time, energy mix for RES production and use, geographical distribution of RES use, huge scale of energy shift from RES to non-RES, increase in energy consumption, Thermodynamic equilibrium of earth, and probable solutions for energy future of our energy and environmental crisis of today. The future solution (that would enable to human civilization further welfare, and good living, but with lower release of CO2 in atmosphere) may not be only RES. This will rather be an energy mix that may contain nuclear energy, non-nuclear renewable energy, or fossil energy with CO2 sequestration, efficient energy technologies, energy saving, and energy consumption decrease.

Dissecting Embryonic Stem Cell Self-Renewal and Differentiation Commitment from Quantitative Models.

PubMed

Hu, Rong; Dai, Xianhua; Dai, Zhiming; Xiang, Qian; Cai, Yanning

2016-10-01

To model quantitatively embryonic stem cell (ESC) self-renewal and differentiation by computational approaches, we developed a unified mathematical model for gene expression involved in cell fate choices. Our quantitative model comprised ESC master regulators and lineage-specific pivotal genes. It took the factors of multiple pathways as input and computed expression as a function of intrinsic transcription factors, extrinsic cues, epigenetic modifications, and antagonism between ESC master regulators and lineage-specific pivotal genes. In the model, the differential equations of expression of genes involved in cell fate choices from regulation relationship were established according to the transcription and degradation rates. We applied this model to the Murine ESC self-renewal and differentiation commitment and found that it modeled the expression patterns with good accuracy. Our model analysis revealed that Murine ESC was an attractor state in culture and differentiation was predominantly caused by antagonism between ESC master regulators and lineage-specific pivotal genes. Moreover, antagonism among lineages played a critical role in lineage reprogramming. Our results also uncovered that the ordered expression alteration of ESC master regulators over time had a central role in ESC differentiation fates. Our computational framework was generally applicable to most cell-type maintenance and lineage reprogramming.

Integration and dynamics of a renewable regenerative hydrogen fuel cell system

NASA Astrophysics Data System (ADS)

Bergen, Alvin Peter

2008-10-01

This thesis explores the integration and dynamics of residential scale renewable-regenerative energy systems which employ hydrogen for energy buffering. The development of the Integrated Renewable Energy Experiment (IRENE) test-bed is presented. IRENE is a laboratory-scale distributed energy system with a modular structure which can be readily re-configured to test newly developed components for generic regenerative systems. Key aspects include renewable energy conversion, electrolysis, hydrogen and electricity storage, and fuel cells. A special design feature of this test bed is the ability to accept dynamic inputs from and provide dynamic loads to real devices as well as from simulated energy sources/sinks. The integration issues encountered while developing IRENE and innovative solutions devised to overcome these barriers are discussed. Renewable energy systems that employ a regenerative approach to enable intermittent energy sources to service time varying loads rely on the efficient transfer of energy through the storage media. Experiments were conducted to evaluate the performance of the hydrogen energy buffer under a range of dynamic operating conditions. Results indicate that the operating characteristics of the electrolyser under transient conditions limit the production of hydrogen from excess renewable input power. These characteristics must be considered when designing or modeling a renewable-regenerative system. Strategies to mitigate performance degradation due to interruptions in the renewable power supply are discussed. Experiments were conducted to determine the response of the IRENE system to operating conditions that are representative of a residential scale, solar based, renewable-regenerative system. A control algorithm, employing bus voltage constraints and device current limitations, was developed to guide system operation. Results for a two week operating period that indicate that the system response is very dynamic but repeatable are

Modelling global water stress of the recent past: on the relative importance of trends in water demand and climate variability

NASA Astrophysics Data System (ADS)

Wada, Y.; van Beek, L. P. H.; Bierkens, M. F. P.

2011-12-01

During the past decades, human water use has more than doubled, yet available freshwater resources are finite. As a result, water scarcity has been prevalent in various regions of the world. Here, we present the first global assessment of past development of water stress considering not only climate variability but also growing water demand, desalinated water use and non-renewable groundwater abstraction over the period 1960-2001 at a spatial resolution of 0.5°. Agricultural water demand is estimated based on past extents of irrigated areas and livestock densities. We approximate past economic development based on GDP, energy and household consumption and electricity production, which are subsequently used together with population numbers to estimate industrial and domestic water demand. Climate variability is expressed by simulated blue water availability defined by freshwater in rivers, lakes, wetlands and reservoirs by means of the global hydrological model PCR-GLOBWB. We thus define blue water stress by comparing blue water availability with corresponding net total blue water demand by means of the commonly used, Water Scarcity Index. The results show a drastic increase in the global population living under water-stressed conditions (i.e. moderate to high water stress) due to growing water demand, primarily for irrigation, which has more than doubled from 1708/818 to 3708/1832 km3 yr-1 (gross/net) over the period 1960-2000. We estimate that 800 million people or 27% of the global population were living under water-stressed conditions for 1960. This number is eventually increased to 2.6 billion or 43% for 2000. Our results indicate that increased water demand is a decisive factor for heightened water stress in various regions such as India and North China, enhancing the intensity of water stress up to 200%, while climate variability is often a main determinant of extreme events. However, our results also suggest that in several emerging and developing economies

Integrating the simulation of domestic water demand behaviour to an urban water model using agent based modelling

NASA Astrophysics Data System (ADS)

Koutiva, Ifigeneia; Makropoulos, Christos

2015-04-01

The urban water system's sustainable evolution requires tools that can analyse and simulate the complete cycle including both physical and cultural environments. One of the main challenges, in this regard, is the design and development of tools that are able to simulate the society's water demand behaviour and the way policy measures affect it. The effects of these policy measures are a function of personal opinions that subsequently lead to the formation of people's attitudes. These attitudes will eventually form behaviours. This work presents the design of an ABM tool for addressing the social dimension of the urban water system. The created tool, called Urban Water Agents' Behaviour (UWAB) model, was implemented, using the NetLogo agent programming language. The main aim of the UWAB model is to capture the effects of policies and environmental pressures to water conservation behaviour of urban households. The model consists of agents representing urban households that are linked to each other creating a social network that influences the water conservation behaviour of its members. Household agents are influenced as well by policies and environmental pressures, such as drought. The UWAB model simulates behaviour resulting in the evolution of water conservation within an urban population. The final outcome of the model is the evolution of the distribution of different conservation levels (no, low, high) to the selected urban population. In addition, UWAB is implemented in combination with an existing urban water management simulation tool, the Urban Water Optioneering Tool (UWOT) in order to create a modelling platform aiming to facilitate an adaptive approach of water resources management. For the purposes of this proposed modelling platform, UWOT is used in a twofold manner: (1) to simulate domestic water demand evolution and (2) to simulate the response of the water system to the domestic water demand evolution. The main advantage of the UWAB - UWOT model

Renewable power needs smart storage solutions

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

Madison, Alison L.

2010-10-24

Ancient Greek philosopher Heraclitus claimed that the only thing constant in life is change, a truth we must accept and even celebrate. Another truth we face today is a growing demand for more energy to help us power the kind and pace of change we’ve become accustomed to, while minimizing environmental consequences. Renewable energy--two words that often find themselves woven into environmentally conscious dialogue. And according to Dave Lucero, director of alternative energy storage at EaglePicher Technologies LLC, the Tri-Cities should be thinking about two more: energy storage. Lucero recently addressed the Tri-Cities Research District about tackling the persistent challengemore » of maximizing renewable energy, which is inherently variable due to changing weather patterns. Capturing that energy and making it available for later use is vital.« less

Algae Oil: A Sustainable Renewable Fuel of Future

PubMed Central

Paul Abishek, Monford; Prem Rajan, Anand

2014-01-01

A nonrenewable fuel like petroleum has been used from centuries and its usage has kept on increasing day by day. This also contributes to increased production of greenhouse gases contributing towards global issues like global warming. In order to meet environmental and economic sustainability, renewable, carbon neutral transport fuels are necessary. To meet these demands microalgae are the key source for production of biodiesel. These microalgae do produce oil from sunlight like plants but in a much more efficient manner. Biodiesel provides more environmental benefits, and being a renewable resource it has gained lot of attraction. However, the main obstacle to commercialization of biodiesel is its cost and feasibility. Biodiesel is usually used by blending with petro diesel, but it can also be used in pure form. Biodiesel is a sustainable fuel, as it is available throughout the year and can run any engine. It will satisfy the needs of the future generation to come. It will meet the demands of the future generation to come. PMID:24883211

Renewable Energy Data Explorer User Guide

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

Cox, Sarah L; Grue, Nicholas W; Tran, July

This publication provides a user guide for the Renewable Energy Data Explorer and technical potential tool within the Explorer. The Renewable Energy Data Explorer is a dynamic, web-based geospatial analysis tool that facilitates renewable energy decision-making, investment, and deployment. It brings together renewable energy resource data and other modeled or measured geographic information system (GIS) layers, including land use, weather, environmental, population density, administrative, and grid data.

Calibrating Physical Parameters in House Models Using Aggregate AC Power Demand

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

Sun, Yannan; Stevens, Andrew J.; Lian, Jianming

For residential houses, the air conditioning (AC) units are one of the major resources that can provide significant flexibility in energy use for the purpose of demand response. To quantify the flexibility, the characteristics of all the houses need to be accurately estimated, so that certain house models can be used to predict the dynamics of the house temperatures in order to adjust the setpoints accordingly to provide demand response while maintaining the same comfort levels. In this paper, we propose an approach using the Reverse Monte Carlo modeling method and aggregate house models to calibrate the distribution parameters ofmore » the house models for a population of residential houses. Given the aggregate AC power demand for the population, the approach can successfully estimate the distribution parameters for the sensitive physical parameters based on our previous uncertainty quantification study, such as the mean of the floor areas of the houses.« less

Analysis of a 10% Renewable Portfolio Standard

EIA Publications

2003-01-01

On May 8, 2003, Senator Jeff Bingaman, the Ranking Minority Member of the Senate Committee on Energy and Natural Resources, requested an analysis of a nationwide Renewable Portfolio Standard (RPS) program proposed to be amended to energy legislation currently pending before the U.S. Senate. With his request Sen. Bingaman provided specific information on the program to be analyzed. This analysis was prepared in response to his request and projects the impact of the proposed program on energy supply, demand, prices, and emissions. The analysis is based on the Annual Energy Outlook 2003 (AEO2003) projections of energy supply, demand, and prices through 2025, as updated in May 2003.

Switch: a planning tool for power systems with large shares of intermittent renewable energy.

PubMed

Fripp, Matthias

2012-06-05

Wind and solar power are highly variable, so it is it unclear how large a role they can play in future power systems. This work introduces a new open-source electricity planning model--Switch--that identifies the least-cost strategy for using renewable and conventional generators and transmission in a large power system over a multidecade period. Switch includes an unprecedented amount of spatial and temporal detail, making it possible to address a new type of question about the optimal design and operation of power systems with large amounts of renewable power. A case study of California for 2012-2027 finds that there is no maximum possible penetration of wind and solar power--these resources could potentially be used to reduce emissions 90% or more below 1990 levels without reducing reliability or severely raising the cost of electricity. This work also finds that policies that encourage customers to shift electricity demand to times when renewable power is most abundant (e.g., well-timed charging of electric vehicles) could make it possible to achieve radical emission reductions at moderate costs.

Cancer Modeling: From Optimal Cell Renewal to Immunotherapy

NASA Astrophysics Data System (ADS)

Alvarado Alvarado, Cesar Leonardo

Cancer is a disease caused by mutations in normal cells. According to the National Cancer Institute, in 2016, an estimated 1.6 million people were diagnosed and approximately 0.5 million people died from the disease in the United States. There are many factors that shape cancer at the cellular and organismal level, including genetic, immunological, and environmental components. In this thesis, we show how mathematical modeling can be used to provide insight into some of the key mechanisms underlying cancer dynamics. First, we use mathematical modeling to investigate optimal homeostatic cell renewal in tissues such as the small intestine with an emphasis on division patterns and tissue architecture. We find that the division patterns that delay the accumulation of mutations are strictly associated with the population sizes of the tissue. In particular, patterns with long chains of differentiation delay the time to observe a second-hit mutant, which is important given that for many cancers two mutations are enough to initiate a tumor. We also investigated homeostatic cell renewal under a selective pressure and find that hierarchically organized tissues act as suppressors of selection; we find that an architecture with a small number of stem cells and larger pools of transit amplifying cells and mature differentiated cells, together with long chains of differentiation, form a robust evolutionary strategy to delay the time to observe a second-hit mutant when mutations acquire a fitness advantage or disadvantage. We also formulate a model of the immune response to cancer in the presence of costimulatory and inhibitory signals. We demonstrate that the coordination of such signals is crucial to initiate an effective immune response, and while immunotherapy has become a promising cancer treatment over the past decade, these results offer some explanations for why it can fail.

A global food demand model for the assessment of complex human-earth systems

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

EDMONDS, JAMES A.; LINK, ROBERT; WALDHOFF, STEPHANIE T.

Demand for agricultural products is an important problem in climate change economics. Food consumption will shape and shaped by climate change and emissions mitigation policies through interactions with bioenergy and afforestation, two critical issues in meeting international climate goals such as two-degrees. We develop a model of food demand for staple and nonstaple commodities that evolves with changing incomes and prices. The model addresses a long-standing issue in estimating food demands, the evolution of demand relationships across large changes in income and prices. We discuss the model, some of its properties and limitations. We estimate parameter values using pooled cross-sectional-time-seriesmore » observations and the Metropolis Monte Carlo method and cross-validate the model by estimating parameters using a subset of the observations and test its ability to project into the unused observations. Finally, we apply bias correction techniques borrowed from the climate-modeling community and report results.« less

Energy demand analytics using coupled technological and economic models

EPA Science Inventory

Impacts of a range of policy scenarios on end-use energy demand are examined using a coupling of MARKAL, an energy system model with extensive supply and end-use technological detail, with Inforum LIFT, a large-scale model of the us. economy with inter-industry, government, and c...

47 CFR 101.1327 - Renewal expectancy for EA licensees.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., including a timetable of the construction of new facilities to meet changes in demand for services provided...) In determining whether a renewal applicant has complied with the “substantial service” requirement by the end of the ten-year initial license term, the Commission may consider factors such as: (1) Whether...

Stochastic multi-objective model for optimal energy exchange optimization of networked microgrids with presence of renewable generation under risk-based strategies.

PubMed

Gazijahani, Farhad Samadi; Ravadanegh, Sajad Najafi; Salehi, Javad

2018-02-01

The inherent volatility and unpredictable nature of renewable generations and load demand pose considerable challenges for energy exchange optimization of microgrids (MG). To address these challenges, this paper proposes a new risk-based multi-objective energy exchange optimization for networked MGs from economic and reliability standpoints under load consumption and renewable power generation uncertainties. In so doing, three various risk-based strategies are distinguished by using conditional value at risk (CVaR) approach. The proposed model is specified as a two-distinct objective function. The first function minimizes the operation and maintenance costs, cost of power transaction between upstream network and MGs as well as power loss cost, whereas the second function minimizes the energy not supplied (ENS) value. Furthermore, the stochastic scenario-based approach is incorporated into the approach in order to handle the uncertainty. Also, Kantorovich distance scenario reduction method has been implemented to reduce the computational burden. Finally, non-dominated sorting genetic algorithm (NSGAII) is applied to minimize the objective functions simultaneously and the best solution is extracted by fuzzy satisfying method with respect to risk-based strategies. To indicate the performance of the proposed model, it is performed on the modified IEEE 33-bus distribution system and the obtained results show that the presented approach can be considered as an efficient tool for optimal energy exchange optimization of MGs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Including Energy Efficiency and Renewable Energy Policies in Electricity Demand Projections

EPA Pesticide Factsheets

Find more information on how state and local air agencies can identify on-the-books EE/RE policies, develop a methodology for projecting a jurisdiction's energy demand, and estimate the change in power sector emissions.

The production of hydrogen fuel from renewable sources and its role in grid operations

NASA Astrophysics Data System (ADS)

Barton, John; Gammon, Rupert

Understanding the scale and nature of hydrogen's potential role in the development of low carbon energy systems requires an examination of the operation of the whole energy system, including heat, power, industrial and transport sectors, on an hour-by-hour basis. The Future Energy Scenario Assessment (FESA) software model used for this study is unique in providing a holistic, high resolution, functional analysis, which incorporates variations in supply resulting from weather-dependent renewable energy generators. The outputs of this model, arising from any given user-definable scenario, are year round supply and demand profiles that can be used to assess the market size and operational regime of energy technologies. FESA was used in this case to assess what - if anything - might be the role for hydrogen in a low carbon economy future for the UK. In this study, three UK energy supply pathways were considered, all of which reduce greenhouse gas emissions by 80% by 2050, and substantially reduce reliance on oil and gas while maintaining a stable electricity grid and meeting the energy needs of a modern economy. All use more nuclear power and renewable energy of all kinds than today's system. The first of these scenarios relies on substantial amounts of 'clean coal' in combination with intermittent renewable energy sources by year the 2050. The second uses twice as much intermittent renewable energy as the first and virtually no coal. The third uses 2.5 times as much nuclear power as the first and virtually no coal. All scenarios clearly indicate that the use of hydrogen in the transport sector is important in reducing distributed carbon emissions that cannot easily be mitigated by Carbon Capture and Storage (CCS). In the first scenario, this hydrogen derives mainly from steam reformation of fossil fuels (principally coal), whereas in the second and third scenarios, hydrogen is made mainly by electrolysis using variable surpluses of low-carbon electricity. Hydrogen

Building renewable electricity supply in Bangladesh

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

Fulton, L.M.

1997-12-31

Bangladesh is experiencing a severe electric power capacity crisis that is only likely to worsen over the next 15 years. Further, over 80% of Bangladesh`s population still lives with no electricity, and the rate of grid expansion to connect rural villages is threatened by the looming capacity shortage. There are a number of underlying reasons for the crisis, but ultimately the country lacks the fossil fuel resources required to conduct a large scale grid-expansion program. Alternative approaches to electrifying the country must be found. This paper outlines the prospects for wind and solar power in Bangladesh, and estimates the potentialmore » for commercial applications now and in the future. This includes a technical assessment, a market assessment, an environmental assessment, and a policy assessment. The paper concludes that Bangladesh holds the potential to cost-effectively meet a significant fraction of its future electricity demand through the use of renewable generation technologies, possibly adding as much renewable capacity as the current overall electric power capacity of the country. Many parts of the country have favorable solar and wind conditions and there are many potentially cost-effective applications. But the country must develop a policy framework that allows and encourages private investors to develop renewable energy projects in order to realize the enormous potential of renewables.« less

Renewable Energy Production and Urban Remediation: Modeling the biogeochemical cycle at contaminated urban brownfields and the potential for renewable energy production and mitigation of greenhouse gases

NASA Astrophysics Data System (ADS)

Gopalakrishnan, G.

2014-12-01

Brownfields or urban sites that have been contaminated as a result of historic practices are present throughout the world. In the United States alone, the National Research Council has estimated that there are approximately 300,000 to 400,000 sites which have been contaminated by improper use and disposal of chemicals (NRC 1993). The land available at these sites is estimated at several million acres; however, the presence of high levels of contamination in the soil and groundwater makes it difficult to utilize these sites for traditional purposes such as agriculture. Further, the time required to remediate these contaminants to regulated levels is in the order of decades, which often results in long-term economic consequences for the areas near these sites. There has been significant interest in developing these sites as potential sources of renewable energy production in order to increase the economic viability of these sites and to provide alternative land resources for renewable energy production (EPA 2012). Solar energy, wind energy, and bioenergy from lignocellulosic biomass production have been identified as the main sources of renewable energy that can be produced at these locations. However, the environmental impacts of such a policy and the implications for greenhouse gas emissions, particularly resulting from changes in land-use impacting the biogeochemical cycle at these sites, have not been studied extensively to date. This study uses the biogeochemical process-based model DNDC to simulate carbon sequestration, nitrous oxide emissions and methane emissions from typical urban brownfield systems in the United States, when renewable energy systems are deployed. Photovoltaic solar energy and lignocellulosic biomass energy systems are evaluated here. Plants modeled include those most widely used for both bioenergy and remediation such as woody trees. Model sensitivity to soil conditions, contaminant levels and local weather data and the resulting impacts on

Energy Policy Case Study - California: Renewables and Distributed Energy Resources

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

Homer, Juliet S.; Bender, Sadie R.; Weimar, Mark R.

2016-09-19

The purpose of this document is to present a case study of energy policies in California related to power system transformation and renewable and distributed energy resources (DERs). Distributed energy resources represent a broad range of technologies that can significantly impact how much, and when, electricity is demanded from the grid. Key policies and proceedings related to power system transformation and DERs are grouped into the following categories: 1.Policies that support achieving environmental and climate goals 2.Policies that promote deployment of DERs 3.Policies that support reliability and integration of DERs 4.Policies that promote market animation and support customer choice. Majormore » challenges going forward are forecasting and modeling DERs, regulatory and utility business model issues, reliability, valuation and pricing, and data management and sharing.« less

Study on reasonable curtailment rate of large scale renewable energy

NASA Astrophysics Data System (ADS)

Li, Nan; Yuan, Bo; Zhang, Fuqiang

2018-02-01

Energy curtailment rate of renewable energy generation is an important indicator to measure renewable energy consumption, it is also an important parameters to determine the other power sources and grids arrangement in the planning stage. In general, to consume the spike power of the renewable energy which is just a small proportion, it is necessary to dispatch a large number of peaking resources, which will reduce the safety and stability of the system. In planning aspect, if it is allowed to give up a certain amount of renewable energy, overall peaking demand of the system will be reduced, the peak power supply construction can be put off to avoid the expensive cost of marginal absorption. In this paper, we introduce the reasonable energy curtailment rate into the power system planning, and use the GESP power planning software, conclude that the reasonable energy curtailment rate of the regional grids in China is 3% -10% in 2020.

Modelling a demand driven biogas system for production of electricity at peak demand and for production of biomethane at other times.

PubMed

O'Shea, R; Wall, D; Murphy, J D

2016-09-01

Four feedstocks were assessed for use in a demand driven biogas system. Biomethane potential (BMP) assays were conducted for grass silage, food waste, Laminaria digitata and dairy cow slurry. Semi-continuous trials were undertaken for all feedstocks, assessing biogas and biomethane production. Three kinetic models of the semi-continuous trials were compared. A first order model most accurately correlated with gas production in the pulse fed semi-continuous system. This model was developed for production of electricity on demand, and biomethane upgrading. The model examined a theoretical grass silage digester that would produce 435kWe in a continuous fed system. Adaptation to demand driven biogas required 187min to produce sufficient methane to run a 2MWe combined heat and power (CHP) unit for 60min. The upgrading system was dispatched 71min following CHP shutdown. Of the biogas produced 21% was used in the CHP and 79% was used in the upgrading system. Copyright © 2016 Elsevier Ltd. All rights reserved.

Integrated Mode Choice, Small Aircraft Demand, and Airport Operations Model User's Guide

NASA Technical Reports Server (NTRS)

Yackovetsky, Robert E. (Technical Monitor); Dollyhigh, Samuel M.

2004-01-01

A mode choice model that generates on-demand air travel forecasts at a set of GA airports based on changes in economic characteristics, vehicle performance characteristics such as speed and cost, and demographic trends has been integrated with a model to generate itinerate aircraft operations by airplane category at a set of 3227 airports. Numerous intermediate outputs can be generated, such as the number of additional trips diverted from automobiles and schedule air by the improved performance and cost of on-demand air vehicles. The total number of transported passenger miles that are diverted is also available. From these results the number of new aircraft to service the increased demand can be calculated. Output from the models discussed is in the format to generate the origin and destination traffic flow between the 3227 airports based on solutions to a gravity model.

NREL, Giner Evaluated Polymer Electrolyte Membrane for Maximizing Renewable

Science.gov Websites

Energy on Grid | Energy Systems Integration Facility | NREL Giner NREL, Giner Evaluated Polymer -scale polymer electrolyte membrane (PEM) stack designed to maximize renewable energy on the grid by converting it to hydrogen when supply exceeds demand. Photo of a polymer electrolyte membrane stack in a

Residential demand for energy. Volume 1: Residential energy demand in the US

NASA Astrophysics Data System (ADS)

Taylor, L. D.; Blattenberger, G. R.; Rennhack, R. K.

1982-04-01

Updated and improved versions of the residential energy demand models that are currently used in EPRI's Demand 80/81 Model are presented. The primary objective of the study is the development and estimation of econometric demand models that take into account in a theoretically appropriate way the problems caused by decreasing-block pricing in the sale of electricity and natural gas. An ancillary objective is to take into account the impact on electricity, natural gas, and fuel oil demands of differences and changes in the availability of natural gas. Econometric models of residential demand are estimated for all three fuel tyes using time series data by state. Price and income elasticities for a number of alternative models are presented.

Synthesis of renewable bisphenols from creosol.

PubMed

Meylemans, Heather A; Groshens, Thomas J; Harvey, Benjamin G

2012-01-09

A series of renewable bisphenols has been synthesized from creosol (2-methoxy-4-methylphenol) through stoichiometric condensation with short-chain aldehydes. Creosol can be readily produced from lignin, potentially allowing for the large scale synthesis of bisphenol A replacements from abundant waste biomass. The renewable bisphenols were isolated in good yields and purities without resorting to solvent-intense purification methods. Zinc acetate was shown to be a selective catalyst for the ortho-coupling of formaldehyde, but was unreactive when more sterically demanding aldehydes were used. Dilute HCl and HBr solutions were shown to be effective catalysts for the selective coupling of aldehydes in the position meta to the hydroxyl group. The acid solutions could be recycled and reused multiple times without decrease in activity or yield. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A model of the demand for Islamic banks debt-based financing instrument

NASA Astrophysics Data System (ADS)

Jusoh, Mansor; Khalid, Norlin

2013-04-01

This paper presents a theoretical analysis of the demand for debt-based financing instruments of the Islamic banks. Debt-based financing, such as through baibithamanajil and al-murabahah, is by far the most prominent of the Islamic bank financing and yet it has been largely ignored in Islamic economics literature. Most studies instead have been focusing on equity-based financing of al-mudharabah and al-musyarakah. Islamic bank offers debt-based financing through various instruments derived under the principle of exchange (ukud al-mu'awadhat) or more specifically, the contract of deferred sale. Under such arrangement, Islamic debt is created when goods are purchased and the payments are deferred. Thus, unlike debt of the conventional bank which is a form of financial loan contract to facilitate demand for liquid assets, this Islamic debt is created in response to the demand to purchase goods by deferred payment. In this paper we set an analytical framework that is based on an infinitely lived representative agent model (ILRA model) to analyze the demand for goods to be purchased by deferred payment. The resulting demand will then be used to derive the demand for Islamic debt. We also investigate theoretically, factors that may have an impact on the demand for Islamic debt.

Component Design Report: International Transportation Energy Demand Determinants Model

EIA Publications

2017-01-01

This Component Design Report discusses working design elements for a new model to replace the International Transportation Model (ITran) in the World Energy Projection System Plus (WEPS ) that is maintained by the U.S. Energy Information Administration. The key objective of the new International Transportation Energy Demand Determinants (ITEDD) model is to enable more rigorous, quantitative research related to energy consumption in the international transportation sectors.

School Burnout and Engagement in the Context of Demands-Resources Model

ERIC Educational Resources Information Center

Salmela-Aro, Katariina; Upadyaya, Katja

2014-01-01

Background: A four-wave longitudinal study tested the demands-resources model in the school context. Aim: To examine the applicability of the demands-resources to the school context. Method: Data of 1,709 adolescents were gathered, once during the transition from comprehensive to post-comprehensive education, twice during post-comprehensive…

Modelling global water stress of the recent past: on the relative importance of trends in water demand and climate variability

NASA Astrophysics Data System (ADS)

Wada, Y.; van Beek, L. P. H.; Bierkens, M. F. P.

2011-08-01

During the past decades, human water use more than doubled, yet available freshwater resources are finite. As a result, water scarcity has been prevalent in various regions of the world. Here, we present the first global assessment of past development of water scarcity considering not only climate variability but also growing water demand, desalinated water use and non-renewable groundwater abstraction over the period 1960-2001 at a spatial resolution of 0.5°. Agricultural water demand is estimated based on past extents of irrigated areas and livestock densities. We approximate past economic development based on GDP, energy and household consumption and electricity production, which is subsequently used together with population numbers to estimate industrial and domestic water demand. Climate variability is expressed by simulated blue water availability defined by freshwater in rivers, lakes and reservoirs by means of the global hydrological model PCR-GLOBWB. The results show a drastic increase in the global population living under water-stressed conditions (i.e., moderate to high water stress) due to the growing water demand, primarily for irrigation, which more than doubled from 1708/818 to 3708/1832 km3 yr-1 (gross/net) over the period 1960-2000. We estimate that 800 million people or 27 % of the global population were under water-stressed conditions for 1960. This number increased to 2.6 billion or 43 % for 2000. Our results indicate that increased water demand is the decisive factor for the heightened water stress, enhancing the intensity of water stress up to 200 %, while climate variability is often the main determinant of onsets for extreme events, i.e. major droughts. However, our results also suggest that in several emerging and developing economies (e.g., India, Turkey, Romania and Cuba) some of the past observed droughts were anthropogenically driven due to increased water demand rather than being climate-induced. In those countries, it can be seen

Air freight demand models: An overview

NASA Technical Reports Server (NTRS)

Dajani, J. S.; Bernstein, G. W.

1978-01-01

A survey is presented of some of the approaches which have been considered in freight demand estimation. The few existing continuous time computer simulations of aviation systems are reviewed, with a view toward the assessment of this approach as a tool for structuring air freight studies and for relating the different components of the air freight system. The variety of available data types and sources, without which the calibration, validation and the testing of both modal split and simulation models would be impossible are also reviewed.

Factors that promote renewable energy production in U.S. states: A fixed effect estimation

NASA Astrophysics Data System (ADS)

Nwokeji, Ekwuniru Chika

2011-12-01

The unsustainability of conventional energy sources and its environmental destructions are well-known; the sustainability of renewable energy and its environmental benefits are also well-documented. The United States in common with many other countries is increasingly focused on developing renewable energy. At first, the pursuit of this strategy in U.S. was seen more as a way to reduce dependence on oil importation. With increased awareness of environmental challenges resulting from the consumption and production of conventional energy, an additional strategy for the continued interest in renewable energy development in the United States was as a result of its potential to ameliorate environmental problems. The U.S. government are utilizing policy measures and dedicating funding to encourage the development of renewable energy technologies. Beside government policies, there are contextual factors that also affect renewable energy production. These include, but not limited to population growth, energy demand, economic growth, and public acceptance. Given the pressing need to develop a sustainable energy, this study embarks on an outcome assessment of the nature of relationship of renewable energy policy incentives, and selected contextual factors on renewable energy production in the United States. The policy incentive evaluated in this study is the Renewable Energy Production Incentive program. The contextual factors evaluated in this study are energy consumption, population growth, employment, and poverty. Understanding the contextual factors within which policies are placed is essential to defining the most appropriate policy features. The methodological approach to the study is quantitative, using panel data from 1976 to 2007. The study tested two hypotheses using fixed effect estimation with robust standard error as a statistical model. Statistical analyses reveal several interesting results which lend support that besides policy incentives, contextual factors

The development of marine renewable energy in China: prospects, challenges and recommendations

NASA Astrophysics Data System (ADS)

Wang, Ji; Wang, Haifeng; Liu, Yuxin; Chen, Libo; Tang, Jiuting

2018-02-01

In this paper, resources distribution and technology status of tidal energy, wave energy, tidal current energy, ocean thermal energy and salinity gradient energy in China is reviewed, and assessment and advices are given for each category. By analysis, we believe that marine renewable energy is a necessary addition to existent renewable energy to meet the energy demand of the areas and islands where traditional forms of energy are not applicable and it is of great importance in adjusting energy structure of China. This paper describes the potential of marine renewable energy in China, and explores the possible role in future energy systems. As the paper discusses, building on these initiatives, and “realizing” the accelerated development of marine energy, presents a number of challenges. This paper describes a scenario for the accelerated development of marine renewable energy in China from now to 2030. Finally, this paper provides recommendations for future development of marine renewable energy in China.

Testing simulation and structural models with applications to energy demand

NASA Astrophysics Data System (ADS)

Wolff, Hendrik

2007-12-01

This dissertation deals with energy demand and consists of two parts. Part one proposes a unified econometric framework for modeling energy demand and examples illustrate the benefits of the technique by estimating the elasticity of substitution between energy and capital. Part two assesses the energy conservation policy of Daylight Saving Time and empirically tests the performance of electricity simulation. In particular, the chapter "Imposing Monotonicity and Curvature on Flexible Functional Forms" proposes an estimator for inference using structural models derived from economic theory. This is motivated by the fact that in many areas of economic analysis theory restricts the shape as well as other characteristics of functions used to represent economic constructs. Specific contributions are (a) to increase the computational speed and tractability of imposing regularity conditions, (b) to provide regularity preserving point estimates, (c) to avoid biases existent in previous applications, and (d) to illustrate the benefits of our approach via numerical simulation results. The chapter "Can We Close the Gap between the Empirical Model and Economic Theory" discusses the more fundamental question of whether the imposition of a particular theory to a dataset is justified. I propose a hypothesis test to examine whether the estimated empirical model is consistent with the assumed economic theory. Although the proposed methodology could be applied to a wide set of economic models, this is particularly relevant for estimating policy parameters that affect energy markets. This is demonstrated by estimating the Slutsky matrix and the elasticity of substitution between energy and capital, which are crucial parameters used in computable general equilibrium models analyzing energy demand and the impacts of environmental regulations. Using the Berndt and Wood dataset, I find that capital and energy are complements and that the data are significantly consistent with duality

Flexible operation of batteries in power system scheduling with renewable energy

DOE PAGES

Li, Nan; Uckun, Canan; Constantinescu, Emil M.; ...

2015-12-17

The fast growing expansion of renewable energy increases the complexities in balancing generation and demand in the power system. The energy-shifting and fast-ramping capability of energy storage has led to increasing interests in batteries to facilitate the integration of renewable resources. In this paper, we present a two-step framework to evaluate the potential value of energy storage in power systems with renewable generation. First, we formulate a stochastic unit commitment approach with wind power forecast uncertainty and energy storage. Second, the solution from the stochastic unit commitment is used to derive a flexible schedule for energy storage in economic dispatchmore » where the look-ahead horizon is limited. Here, analysis is conducted on the IEEE 24-bus system to demonstrate the benefits of battery storage in systems with renewable resources and the effectiveness of the proposed battery operation strategy.« less

Towards a Job Demands-Resources Health Model: Empirical Testing with Generalizable Indicators of Job Demands, Job Resources, and Comprehensive Health Outcomes.

PubMed

Brauchli, Rebecca; Jenny, Gregor J; Füllemann, Désirée; Bauer, Georg F

2015-01-01

Studies using the Job Demands-Resources (JD-R) model commonly have a heterogeneous focus concerning the variables they investigate-selective job demands and resources as well as burnout and work engagement. The present study applies the rationale of the JD-R model to expand the relevant outcomes of job demands and job resources by linking the JD-R model to the logic of a generic health development framework predicting more broadly positive and negative health. The resulting JD-R health model was operationalized and tested with a generalizable set of job characteristics and positive and negative health outcomes among a heterogeneous sample of 2,159 employees. Applying a theory-driven and a data-driven approach, measures which were generally relevant for all employees were selected. Results from structural equation modeling indicated that the model fitted the data. Multiple group analyses indicated invariance across six organizations, gender, job positions, and three times of measurement. Initial evidence was found for the validity of an expanded JD-R health model. Thereby this study contributes to the current research on job characteristics and health by combining the core idea of the JD-R model with the broader concepts of salutogenic and pathogenic health development processes as well as both positive and negative health outcomes.

Towards a Job Demands-Resources Health Model: Empirical Testing with Generalizable Indicators of Job Demands, Job Resources, and Comprehensive Health Outcomes

PubMed Central

Brauchli, Rebecca; Jenny, Gregor J.; Füllemann, Désirée; Bauer, Georg F.

2015-01-01

Studies using the Job Demands-Resources (JD-R) model commonly have a heterogeneous focus concerning the variables they investigate—selective job demands and resources as well as burnout and work engagement. The present study applies the rationale of the JD-R model to expand the relevant outcomes of job demands and job resources by linking the JD-R model to the logic of a generic health development framework predicting more broadly positive and negative health. The resulting JD-R health model was operationalized and tested with a generalizable set of job characteristics and positive and negative health outcomes among a heterogeneous sample of 2,159 employees. Applying a theory-driven and a data-driven approach, measures which were generally relevant for all employees were selected. Results from structural equation modeling indicated that the model fitted the data. Multiple group analyses indicated invariance across six organizations, gender, job positions, and three times of measurement. Initial evidence was found for the validity of an expanded JD-R health model. Thereby this study contributes to the current research on job characteristics and health by combining the core idea of the JD-R model with the broader concepts of salutogenic and pathogenic health development processes as well as both positive and negative health outcomes. PMID:26557718

Abundant Renewable Energy Resources Exist in Lao PDR | News | NREL

Science.gov Websites

electricity generation, assessing the technical potential of domestic solar, wind, and biomass. The report set renewable energy targets; identify opportunities to meet growing domestic electricity demand ; offset current electricity import trends; and position the country as an exporter of electricity. Read

Gaps of Decision Support Models for Pipeline Renewal and Recommendations for Improvement

EPA Science Inventory

In terms of the development of software for decision support for pipeline renewal, more attention to date has been paid to the development of asset management models that help an owner decide on which portions of a system to prioritize needed actions. There has been much less w...

International Data Base for the U.S. Renewable Energy Industry

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

none

1986-05-01

The International Data Base for the US Renewable Energy Industry was developed to provide the US renewable energy industry with background data for identifying and analyzing promising foreign market opportunities for their products and services. Specifically, the data base provides the following information for 161 developed and developing countries: (1) General Country Data--consisting of general energy indicators; (2) Energy Demand Data--covering commercial primary energy consumption; (3) Energy Resource Data--identifying annual average insolation, wind power, and river flow data; (4) Power System Data--indicating a wide range of electrical parameters; and (5) Business Data--including currency and credit worthiness data.

The significance of renewable energy use for economic output and environmental protection: evidence from the Next 11 developing economies.

PubMed

Paramati, Sudharshan Reddy; Sinha, Avik; Dogan, Eyup

2017-05-01

Increasing economic activities in developing economies raise demand for energy mainly sourced from conventional sources. The consumption of more conventional energy will have a significant negative impact on the environment. Therefore, attention of policy makers has recently shifted towards the promotion of renewable energy generation and uses across economic activities to ensure low carbon economy. Given the recent scenario, in this paper, we aim to examine the role of renewable energy consumption on the economic output and CO 2 emissions of the next fastest developing economies of the world. The study employs several robust panel econometric models by using annual data from 1990 to 2012. Empirical findings confirm the significant long-run association among the variables. Similarly, results show that renewable energy consumption positively contributes to economic output and has an adverse effect on CO 2 emissions. Given our findings, we suggest policy makers of those economies to initiate further effective policies to promote more renewable energy generation and uses across economic activities to ensure sustainable economic development.

Balancing autonomy and utilization of solar power and battery storage for demand based microgrids

NASA Astrophysics Data System (ADS)

Lawder, Matthew T.; Viswanathan, Vilayanur; Subramanian, Venkat R.

2015-04-01

The growth of intermittent solar power has developed a need for energy storage systems in order to decouple generation and supply of energy. Microgrid (MG) systems comprising of solar arrays with battery energy storage studied in this paper desire high levels of autonomy, seeking to meet desired demand at all times. Large energy storage capacity is required for high levels of autonomy, but much of this expensive capacity goes unused for a majority of the year due to seasonal fluctuations of solar generation. In this paper, a model-based study of MGs comprised of solar generation and battery storage shows the relationship between system autonomy and battery utilization applied to multiple demand cases using a single particle battery model (SPM). The SPM allows for more accurate state-of-charge and utilization estimation of the battery than previous studies of renewably powered systems that have used empirical models. The increased accuracy of battery state estimation produces a better assessment of system performance. Battery utilization will depend on the amount of variation in solar insolation as well as the type of demand required by the MG. Consumers must balance autonomy and desired battery utilization of a system within the needs of their grid.

City-integrated renewable energy for urban sustainability.

PubMed

Kammen, Daniel M; Sunter, Deborah A

2016-05-20

To prepare for an urban influx of 2.5 billion people by 2050, it is critical to create cities that are low-carbon, resilient, and livable. Cities not only contribute to global climate change by emitting the majority of anthropogenic greenhouse gases but also are particularly vulnerable to the effects of climate change and extreme weather. We explore options for establishing sustainable energy systems by reducing energy consumption, particularly in the buildings and transportation sectors, and providing robust, decentralized, and renewable energy sources. Through technical advancements in power density, city-integrated renewable energy will be better suited to satisfy the high-energy demands of growing urban areas. Several economic, technical, behavioral, and political challenges need to be overcome for innovation to improve urban sustainability. Copyright © 2016, American Association for the Advancement of Science.

Renewable Chemicals: Dehydroxylation of Glycerol and Polyols

PubMed Central

ten Dam, Jeroen; Hanefeld, Ulf

2011-01-01

The production of renewable chemicals is gaining attention over the past few years. The natural resources from which they can be derived in a sustainable way are most abundant in sugars, cellulose and hemicellulose. These highly functionalized molecules need to be de-functionalized in order to be feedstocks for the chemical industry. A fundamentally different approach to chemistry thus becomes necessary, since the traditionally employed oil-based chemicals normally lack functionality. This new chemical toolbox needs to be designed to guarantee the demands of future generations at a reasonable price. The surplus of functionality in sugars and glycerol consists of alcohol groups. To yield suitable renewable chemicals these natural products need to be defunctionalized by means of dehydroxylation. Here we review the possible approaches and evaluate them from a fundamental chemical aspect. PMID:21887771

Worldwide transportation/energy demand, 1975-2000. Revised Variflex model projections

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

Ayres, R.U.; Ayres, L.W.

1980-03-01

The salient features of the transportation-energy relationships that characterize the world of 1975 are reviewed, and worldwide (34 countries) long-range transportation demand by mode to the year 2000 is reviewed. A worldwide model is used to estimate future energy demand for transportation. Projections made by the forecasting model indicate that in the year 2000, every region will be more dependent on petroleum for the transportation sector than it was in 1975. This report is intended to highlight certain trends and to suggest areas for further investigation. Forecast methodology and model output are described in detail in the appendices. The reportmore » is one of a series addressing transportation energy consumption; it supplants and replaces an earlier version published in October 1978 (ORNL/Sub-78/13536/1).« less

Multimodal Transportation Analysis Process (MTAP): A Travel Demand Forecasting Model

DOT National Transportation Integrated Search

1990-01-01

In 1986, the North Central Texas Council of Governments (NCTCOG) undertook the revision of its travel demand forecasting model. The outcome was a model which was developed based on travel patterns in the Dallas-Forth Worth area and used jointly by th...

Analysis of a 10% Renewable Portfolio Standard, Addendum

EIA Publications

2003-01-01

On May 8, 2003, Senator Jeff Bingaman, the Ranking Minority Member of the Senate Committee on Energy and Natural Resources, requested an analysis of a nationwide Renewable Portfolio Standard (RPS) program proposed to be amended to energy legislation currently pending before the U.S. Senate. With his request Sen. Bingaman provided specific information on the program to be analyzed. This analysis was prepared in response to his request and projects the impact of the proposed program on energy supply, demand, prices, and emissions. The analysis is based on the Annual Energy Outlook 2003 (AEO2003) projections of energy supply, demand, and prices through 2025, as updated in May 2003.

Green power: A renewable energy resources marketing plan

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

Barr, R.C.

Green power is electricity generated from renewable energy sources such as power generated from the sun, the wind, the heat of the earth, and biomass. Green pricing is the marketing strategy to sell green power to customers who voluntarily pay a premium for it. Green pricing is evolving from the deregulation of the electric industry, the need for clean air, reflected in part as concern over global warming, and technology advances. The goal of the renewable energy marketing plan is to generate enough revenues for a utility to fund power purchase agreements (PPAs) with renewable energy developers or construct itsmore » own renewable facilities. Long-term, fixed price PPAs enable developers to obtain financing to construct new facilities, sometimes taking technological risks which a utility might not take otherwise. The marketing plan is built around different rate premiums for different categories of ratepayers, volunteer customer participation, customer participation recognition, and budget allocations between project costs and power marketing costs. Green prices are higher than those for conventional sources, particularly prices from natural gas fired plants. Natural gas is abundant relative to oil in price per British thermal unit (Btu). Green pricing can help bridge the gap between the current oversupply of gas and the time, not far off, when all petroleum prices will exceed those for renewable energy. The rapid implementation of green pricing is important. New marketing programs will bolster the growing demand for renewable energy evidenced in many national surveys thus decreasing the consumption of power now generated by burning hydrocarbons. This paper sets forth a framework to implement a green power marketing plan for renewable energy developers and utilities working together.« less

Spatial demographic models to inform conservation planning of golden eagles in renewable energy landscapes

USGS Publications Warehouse

Wiens, J. David; Schumaker, Nathan H.; Inman, Richard D.; Esque, Todd C.; Longshore, Kathleen M.; Nussear, Kenneth E

2017-01-01

Spatial demographic models can help guide monitoring and management activities targeting at-risk species, even in cases where baseline data are lacking. Here, we provide an example of how site-specific changes in land use and anthropogenic stressors can be incorporated into a spatial demographic model to investigate effects on population dynamics of Golden Eagles (Aquila chrysaetos). Our study focused on a population of Golden Eagles exposed to risks associated with rapid increases in renewable energy development in southern California, U.S.A. We developed a spatially explicit, individual-based simulation model that integrated empirical data on demography of Golden Eagles with spatial data on the arrangement of nesting habitats, prey resources, and planned renewable energy development sites. Our model permitted simulated eagles of different stage-classes to disperse, establish home ranges, acquire prey resources, prospect for breeding sites, and reproduce. The distribution of nesting habitats, prey resources, and threats within each individual's home range influenced movement, reproduction, and survival. We used our model to explore potential effects of alternative disturbance scenarios, and proposed conservation strategies, on the future distribution and abundance of Golden Eagles in the study region. Results from our simulations suggest that probable increases in mortality associated with renewable energy infrastructure (e.g., collisions with wind turbines and vehicles, electrocution on power poles) could have negative consequences for population trajectories, but that site-specific conservation actions could reduce the magnitude of negative effects. Our study demonstrates the use of a flexible and expandable modeling framework to incorporate spatially dependent processes when determining relative effects of proposed management options to Golden Eagles and their habitats.

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

The welfare effects of integrating renewable energy into electricity markets

NASA Astrophysics Data System (ADS)

Lamadrid, Alberto J.

The challenges of deploying more renewable energy sources on an electric grid are caused largely by their inherent variability. In this context, energy storage can help make the electric delivery system more reliable by mitigating this variability. This thesis analyzes a series of models for procuring electricity and ancillary services for both individuals and social planners with high penetrations of stochastic wind energy. The results obtained for an individual decision maker using stochastic optimization are ambiguous, with closed form solutions dependent on technological parameters, and no consideration of the system reliability. The social planner models correctly reflect the effect of system reliability, and in the case of a Stochastic, Security Constrained Optimal Power Flow (S-SC-OPF or SuperOPF), determine reserve capacity endogenously so that system reliability is maintained. A single-period SuperOPF shows that including ramping costs in the objective function leads to more wind spilling and increased capacity requirements for reliability. However, this model does not reflect the inter temporal tradeoffs of using Energy Storage Systems (ESS) to improve reliability and mitigate wind variability. The results with the multiperiod SuperOPF determine the optimum use of storage for a typical day, and compare the effects of collocating ESS at wind sites with the same amount of storage (deferrable demand) located at demand centers. The collocated ESS has slightly lower operating costs and spills less wind generation compared to deferrable demand, but the total amount of conventional generating capacity needed for system adequacy is higher. In terms of the total system costs, that include the capital cost of conventional generating capacity, the costs with deferrable demand is substantially lower because the daily demand profile is flattened and less conventional generation capacity is then needed for reliability purposes. The analysis also demonstrates that the

A Survey on Renewable Energy Development in Malaysia: Current Status, Problems and Prospects

NASA Astrophysics Data System (ADS)

Alam, Syed Shah; Nor, Nor Fariza Mohd; Ahmad, Maisarah; Hashim, Nik Hazrul Nik

2016-05-01

Energy demand in Malaysia is increasing over seven per cent a year, while forty per cent of the energy is supplied from conventional fossil fuel. However, a number of social barriers have mired the social acceptance of renewable energy among the users. This study investigates the current status of renewable energy, problems and future outlook of renewable energy in Malaysia. A total of 200 respondents were surveyed from Klang Valley in Malaysia. Majority of the respondents use energy to generate electricity. Although some respondents reported using solar energy, there is lack of retail availability for solar energy. The findings show that limited information on renewable energy technologies, lack of awareness, and limited private sector engagement emerged as major barriers to sustainable renewable energy development. In addition, the respondents suggest for increasing policy support from the government to make information more accessible to mass users, provide economic incentives to investors and users, and promote small-community based renewable energy projects. The study suggests that the government begin small scale projects to build awareness on renewable energy, while academically, higher learning institutions include renewable energy syllabus in their academic curriculum. The study concluded that to have sustainable renewable energy development, government's initiative, private sector engagement and users awareness must be given priority.

National Freight Demand Modeling - Bridging the Gap between Freight Flow Statistics and U.S. Economic Patterns

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

Chin, Shih-Miao; Hwang, Ho-Ling

2007-01-01

This paper describes a development of national freight demand models for 27 industry sectors covered by the 2002 Commodity Flow Survey. It postulates that the national freight demands are consistent with U.S. business patterns. Furthermore, the study hypothesizes that the flow of goods, which make up the national production processes of industries, is coherent with the information described in the 2002 Annual Input-Output Accounts developed by the Bureau of Economic Analysis. The model estimation framework hinges largely on the assumption that a relatively simple relationship exists between freight production/consumption and business patterns for each industry defined by the three-digit Northmore » American Industry Classification System industry codes (NAICS). The national freight demand model for each selected industry sector consists of two models; a freight generation model and a freight attraction model. Thus, a total of 54 simple regression models were estimated under this study. Preliminary results indicated promising freight generation and freight attraction models. Among all models, only four of them had a R2 value lower than 0.70. With additional modeling efforts, these freight demand models could be enhanced to allow transportation analysts to assess regional economic impacts associated with temporary lost of transportation services on U.S. transportation network infrastructures. Using such freight demand models and available U.S. business forecasts, future national freight demands could be forecasted within certain degrees of accuracy. These freight demand models could also enable transportation analysts to further disaggregate the CFS state-level origin-destination tables to county or zip code level.« less

Research on the spatial-temporal distribution and development mode for renewable energy in Germany and Denmark

NASA Astrophysics Data System (ADS)

Li, Nana; Xie, Guohui

2018-06-01

Abstract—Global renewable energy have maintained a steady growth in recent years under the support of national policies and energy demand. Resource distribution, land supply, economy, voltage class and other relevant conditions affect the renewable energy distribution and development mode. Therefore, is necessary to analyze the spatial-temporal distribution and development modes for renewable energy, so as to provide reference and guidance for the renewable energy development around world. Firstly, the definitions and influence factors the renewable energy development mode are compared and summarized. Secondly, the renewable energy spatial-temporal distribution in Germany and Denmark are provided. Wind and solar power installations account for the largest proportion of all renewable energy in Germany and Denmark. Finally, renewable energy development modes are studied. The distributed photovoltaic generation accounts for more than 95%, and distributed wind power generation installations account for over 85% in Germany. Solar and wind resources are developed with distributed development mode, in which distributed wind power installation accounts for over 75%.

An evaluation of the impact of state Renewable Portfolio Standards (RPS) on retail, commercial, and industrial electricity prices

NASA Astrophysics Data System (ADS)

Puram, Rakesh

renewable energy generation as well as non-renewable energy generation have an impact on residential, industrial, and commercial price. In addition coal price, personal income, and the number of net metering customers in a state impact commercial, industrial and residential electricity rates. There are two main policy implications that stem from this study. First is that while RPS has an impact on residential and commercial electricity rates, the magnitude is small, especially given the average consumption patterns of households and commercial customers. The second policy implication is that it is that given the significance of several explanatory variables in the theoretical model it is important to discuss the relevance of RPS within the context of electricity sources, both renewable and non-renewable, demand side programs, economic factors, as well as fuel costs.

Electricity Capacity Expansion Modeling, Analysis, and Visualization. A Summary of High-Renewable Modeling Experience for China

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

Blair, Nate; Zhou, Ella; Getman, Dan

2015-10-01

Mathematical and computational models are widely used for the analysis and design of both physical and financial systems. Modeling the electric grid is of particular importance to China for three reasons. First, power-sector assets are expensive and long-lived, and they are critical to any country's development. China's electric load, transmission, and other energy-related infrastructure are expected to continue to grow rapidly; therefore it is crucial to understand and help plan for the future in which those assets will operate (NDRC ERI 2015). Second, China has dramatically increased its deployment of renewable energy (RE), and is likely to continue further acceleratingmore » such deployment over the coming decades. Careful planning and assessment of the various aspects (technical, economic, social, and political) of integrating a large amount of renewables on the grid is required. Third, companies need the tools to develop a strategy for their own involvement in the power market China is now developing, and to enable a possible transition to an efficient and high RE future.« less

Microbial Production of l-Serine from Renewable Feedstocks.

PubMed

Zhang, Xiaomei; Xu, Guoqiang; Shi, Jinsong; Koffas, Mattheos A G; Xu, Zhenghong

2018-07-01

l-Serine is a non-essential amino acid that has wide and expanding applications in industry with a fast-growing market demand. Currently, extraction and enzymatic catalysis are the main processes for l-serine production. However, such approaches limit the industrial-scale applications of this important amino acid. Therefore, shifting to the direct fermentative production of l-serine from renewable feedstocks has attracted increasing attention. This review details the current status of microbial production of l-serine from renewable feedstocks. We also summarize the current trends in metabolic engineering strategies and techniques for the typical industrial organisms Corynebacterium glutamicum and Escherichia coli that have been developed to address and overcome major challenges in the l-serine production process. Copyright © 2018 Elsevier Ltd. All rights reserved.

Capacity Payments in Restructured Markets under Low and High Penetration Levels of Renewable Energy

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

Jenkin, Thomas; Beiter, Philipp; Margolis, Robert

2016-02-01

Growing levels of variable renewable energy resources arguably create new challenges for capacity market designs, because variable renewable energy suppresses wholesale energy prices while providing relatively little capacity. This effect becomes more pronounced the higher the variable renewable energy penetration in a market. The purpose of this report is threefold. First, we provide a brief outline of the purpose and design of various capacity markets using administratively determined capacity demand curves. Second, we discuss some of the main challenges raised in existing literature and a set of interviews that we conducted with market participants, regulators, and observers. Third, we considermore » some of the challenges to capacity markets that arise with higher variable renewable energy penetration.« less

Outlook and application analysis of energy storage in power system with high renewable energy penetration

NASA Astrophysics Data System (ADS)

Feng, Junshu; Zhang, Fuqiang

2018-02-01

To realize low-emission and low-carbon energy production and consumption, large-scale development and utilization of renewable energy has been put into practice in China. And it has been recognized that power system of future high renewable energy shares can operate more reliably with the participation of energy storage. Considering the significant role of storage playing in the future power system, this paper focuses on the application of energy storage with high renewable energy penetration. Firstly, two application modes are given, including demand side application mode and centralized renewable energy farm application mode. Afterwards, a high renewable energy penetration scenario of northwest region in China is designed, and its production simulation with application of energy storage in 2050 has been calculated and analysed. Finally, a development path and outlook of energy storage is given.

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.

Electric Water Heater Modeling and Control Strategies for Demand Response

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

Diao, Ruisheng; Lu, Shuai; Elizondo, Marcelo A.

2012-07-22

Abstract— Demand response (DR) has a great potential to provide balancing services at normal operating conditions and emergency support when a power system is subject to disturbances. Effective control strategies can significantly relieve the balancing burden of conventional generators and reduce investment on generation and transmission expansion. This paper is aimed at modeling electric water heaters (EWH) in households and tests their response to control strategies to implement DR. The open-loop response of EWH to a centralized signal is studied by adjusting temperature settings to provide regulation services; and two types of decentralized controllers are tested to provide frequency supportmore » following generator trips. EWH models are included in a simulation platform in DIgSILENT to perform electromechanical simulation, which contains 147 households in a distribution feeder. Simulation results show the dependence of EWH response on water heater usage . These results provide insight suggestions on the need of control strategies to achieve better performance for demand response implementation. Index Terms— Centralized control, decentralized control, demand response, electrical water heater, smart grid« less

Design, analysis, operation, and advanced control of hybrid renewable energy systems

NASA Astrophysics Data System (ADS)

Whiteman, Zachary S.

Because using non-renewable energy systems (e.g., coal-powered co-generation power plants) to generate electricity is an unsustainable, environmentally hazardous practice, it is important to develop cost-effective and reliable renewable energy systems, such as photovoltaics (PVs), wind turbines (WTs), and fuel cells (FCs). Non-renewable energy systems, however, are currently less expensive than individual renewable energy systems (IRESs). Furthermore, IRESs based on intermittent natural resources (e.g., solar irradiance and wind) are incapable of meeting continuous energy demands. Such shortcomings can be mitigated by judiciously combining two or more complementary IRESs to form a hybrid renewable energy system (HRES). Although previous research efforts focused on the design, operation, and control of HRESs has proven useful, no prior HRES research endeavor has taken a systematic and comprehensive approach towards establishing guidelines by which HRESs should be designed, operated, and controlled. The overall goal of this dissertation, therefore, is to establish the principles governing the design, operation, and control of HRESs resulting in cost-effective and reliable energy solutions for stationary and mobile applications. To achieve this goal, we developed and demonstrated four separate HRES principles. Rational selection of HRES type: HRES components and their sizes should be rationally selected using knowledge of component costs, availability of renewable energy resources, and expected power demands of the application. HRES design: by default, the components of a HRES should be arranged in parallel for increased efficiency and reliability. However, a series HRES design may be preferred depending on the operational considerations of the HRES components. HRES control strategy selection: the choice of HRES control strategy depends on the dynamics of HRES components, their operational considerations, and the practical limitations of the HRES end-use. HRES data

Job Demand and Job Resources related to the turnover intention of public health nurses: An analysis using a Job Demands-Resources model.

PubMed

Iguchi, Aya

2016-01-01

Objectives The purpose of this study was to investigate the job demands and job resources of public health nurses based on the Job Demands-Resources (JD-R) model, and to build a model that can estimate turnover intention based on job demands and job resources.Method By adding 12 items to the existing questionnaire, the author created a questionnaire consisting of 10 factors and 167 items, and used statistical analysis to examine job demands and job resources in relation to turnover intention.Results Out of 2,668 questionnaires sent, 1993 (72.5%) were returned. Considering sex-based differences in occupational stress, I analyzed women's answers in 1766 (66.2%) mails among the 1798 valid responses. The average age of respondents was 41.0±9.8 years, and the mean service duration was 17.0±10.0 years. For public health nurses, there was a turnover intention of 9.2%. The "job demands" section consisted of 29 items and 10 factors, while the "job resources" section consisted of 54 items and 22 factors. The result of examining the structure of job demands and job resources, leading to turnover intention was supported by the JD-R model. Turnover intention was strong and the Mental Component Summary (MCS) is low in those who had many job demands and few job resources (experiencing 'burn-out'). Enhancement of work engagement and turnover intention was weak in those who had many job resources. This explained approximately 60% of the dispersion to "burn-out", and approximately 40% to "work engagement", with four factors: work suitability, work significance, positive work self-balance, and growth opportunity of job resources.Conclusion This study revealed that turnover intention is strong in those who are burned out because of many job demands. Enhancement of work engagement and turnover intention is weak in those with many job resources. This suggests that suitable staffing and organized efforts to raise awareness of job significance are effective in reducing

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.

U.S. Renewables Portfolio Standards: 2017 Annual Status Report

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

Barbose, Galen

Berkeley Lab’s annual status report on U.S. renewables portfolio standards (RPS) provides an overview of key trends associated with U.S. state RPS policies. The report, published in slide-deck form, describes recent legislative revisions, key policy design features, compliance with interim targets, past and projected impacts on renewables development, and compliance costs. The 2017 edition of the report presents historical data through year-end 2016 and projections through 2030. Key trends from this edition of the report include the following: -Evolution of state RPS programs: Significant RPS-related policy revisions since the start of 2016 include increased RPS targets in DC, MD, MI,more » NY, RI, and OR; requirements for new wind and solar projects and other major reforms to the RPS procurement process in IL; and a new offshore wind carve-out and solar procurement program in MA. -Historical impacts on renewables development: Roughly half of all growth in U.S. renewable electricity (RE) generation and capacity since 2000 is associated with state RPS requirements. Nationally, the role of RPS policies has diminished over time, representing 44% of all U.S. RE capacity additions in 2016. However, within particular regions, RPS policies continue to play a central role in supporting RE growth, constituting 70-90% of 2016 RE capacity additions in the West, Mid-Atlantic, and Northeast. -Future RPS demand and incremental needs: Meeting RPS demand growth will require roughly a 50% increase in U.S. RE generation by 2030, equating to 55 GW of new RE capacity. To meet future RPS demand, total U.S. RE generation will need to reach 13% of electricity sales by 2030 (compared to 10% today), though other drivers will also continue to influence RE growth. -RPS target achievement to-date: States have generally met their interim RPS targets in recent years, with only a few exceptions reflecting unique state-specific policy designs. -REC pricing trends: Prices for renewable energy

Are shocks to renewable energy consumption permanent or temporary? Evidence from 54 developing and developed countries.

PubMed

Demir, Ender; Gozgor, Giray

2018-02-01

The renewable energy sources are considered as the important factor to decrease the level of carbon emissions and to promote the global green economy. Understanding the dynamics of renewable energy consumption, this paper analyzes whether there is a unit root in renewable energy consumption in 54 countries over the period 1971-2016. To this end, the unit root test of Narayan-Popp with two endogenous (unknown) breaks is implemented. The paper finds that renewable energy consumption series are stationary around a level and the time trend in 45 of 54 countries. In other words, renewable energy consumption follows a unit root process only in nine countries: Brazil, China, Colombia, India, Israel, Japan, the Netherlands, Spain, and Turkey. The evidence implies that renewable energy demand policies, which aimed to decrease the carbon emissions, will only have permanent effects in those nine countries.

Progress of succinic acid production from renewable resources: Metabolic and fermentative strategies.

PubMed

Jiang, Min; Ma, Jiangfeng; Wu, Mingke; Liu, Rongming; Liang, Liya; Xin, Fengxue; Zhang, Wenming; Jia, Honghua; Dong, Weiliang

2017-12-01

Succinic acid is a four-carbon dicarboxylic acid, which has attracted much interest due to its abroad usage as a precursor of many industrially important chemicals in the food, chemicals, and pharmaceutical industries. Facing the shortage of crude oil supply and demand of sustainable development, biological production of succinic acid from renewable resources has become a topic of worldwide interest. In recent decades, robust producing strain selection, metabolic engineering of model strains, and process optimization for succinic acid production have been developed. This review provides an overview of succinic acid producers and cultivation technology, highlight some of the successful metabolic engineering approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

Universality classes of foraging with resource renewal

NASA Astrophysics Data System (ADS)

Chupeau, M.; Bénichou, O.; Redner, S.

2016-03-01

We determine the impact of resource renewal on the lifetime of a forager that depletes its environment and starves if it wanders too long without eating. In the framework of a minimal starving random-walk model with resource renewal, there are three universal classes of behavior as a function of the renewal time. For sufficiently rapid renewal, foragers are immortal, while foragers have a finite lifetime otherwise. In the specific case of one dimension, there is a third regime, for sufficiently slow renewal, in which the lifetime of the forager is independent of the renewal time. We outline an enumeration method to determine the mean lifetime of the forager in the mortal regime.

Renewable energy and power cooperation between China and six Latin American nations

NASA Astrophysics Data System (ADS)

Xie, Yuetao; Yan, Bingzhong; Zhou, Shichun

2018-02-01

China has been entitled the biggest supplier and largest market of renewable energy for the past few years. With One Belt and One Road initiative carrying on, the China’s renewable energy industry is looking for opportunities across the world. Latin America, which has rich renewable energy resources and urge demand for a cleaner and more sustainable energy system, may become an important target market for China. The prospect and potential of renewable energy cooperation between China and Latin America are promising. In this paper, six Latin American nations of varied background were selected as study cases. Their nation profile, energy resources, power market, and energy development trends were analysed, and the cooperation prospect and potential between these nations and China in renewable energy sector were discussed. The results indicate that Argentina and Bolivia are most potential cooperation partners, and project development and equipment manufacturing of non-hydro renewable energy, along with power grid upgrading are the prioritized areas. In addition, recommendations and solutions addressing the issues and challenges incurred in the current bilateral energy cooperation between China and Latin American nations were proposed.

Development and bottlenecks of renewable electricity generation in China: a critical review.

PubMed

Hu, Yuanan; Cheng, Hefa

2013-04-02

This review provides an overview on the development and status of electricity generation from renewable energy sources, namely hydropower, wind power, solar power, biomass energy, and geothermal energy, and discusses the technology, policy, and finance bottlenecks limiting growth of the renewable energy industry in China. Renewable energy, dominated by hydropower, currently accounts for more than 25% of the total electricity generation capacity. China is the world's largest generator of both hydropower and wind power, and also the largest manufacturer and exporter of photovoltaic cells. Electricity production from solar and biomass energy is at the early stages of development in China, while geothermal power generation has received little attention recently. The spatial mismatch in renewable energy supply and electricity demand requires construction of long-distance transmission networks, while the intermittence of renewable energy poses significant technical problems for feeding the generated electricity into the power grid. Besides greater investment in research and technology development, effective policies and financial measures should also be developed and improved to better support the healthy and sustained growth of renewable electricity generation. Meanwhile, attention should be paid to the potential impacts on the local environment from renewable energy development, despite the wider benefits for climate change.

Evaluating Outdoor Water Use Demand under Changing Climatic and Demographic Conditions: An Agent-based Modeling Approach

NASA Astrophysics Data System (ADS)

Kanta, L.

2016-12-01

Outdoor water use for landscape and irrigation constitutes a significant end use in residential water demand. In periods of water shortages, utilities may reduce garden demands by implementing irrigation system audits, rebate programs, local ordinances, and voluntary or mandatory water use restrictions. Because utilities do not typically record outdoor and indoor water uses separately, the effects of policies for reducing garden demands cannot be readily calculated. The volume of water required to meet garden demands depends on the housing density or lawn size, type of vegetation, climatic conditions, efficiency of garden irrigation systems, and consumer water-use behaviors. Many existing outdoor demand estimation methods are deterministic and do not include consumer responses to conservation campaigns. In addition, mandatory restrictions may have a substantial impact on reducing outdoor demands, but the effectiveness of mandatory restrictions depends on the timing and the frequency of restrictions, in addition to the distribution of housing density and consumer types within a community. This research investigates a garden end-use model by coupling an agent-based modeling approach and a mechanistic-stochastic water demand model to create a methodology for estimating garden demand and evaluating demand reduction policies. The garden demand model is developed for two water utilities, using a diverse data sets, including residential customer billing records, records of outdoor conservation programs, frequency and type of mandatory water use restrictions, lot size distribution, population growth, and climatic data. A set of garden irrigation parameter values, which are based on the efficiency of irrigation systems and irrigation habits of consumers, are determined for a set of conservation ordinances and restrictions. The model parameters are then validated using customer water usage data from the participating water utilities. A sensitivity analysis is conducted for

Evaluating Outdoor Water Use Demand under Changing Climatic and Demographic Conditions: An Agent-based Modeling Approach

NASA Astrophysics Data System (ADS)

Kanta, L.; Berglund, E. Z.; Soh, M. H.

2017-12-01

Outdoor water-use for landscape and irrigation constitutes a significant end-use in total residential water demand. In periods of water shortages, utilities may reduce garden demands by implementing irrigation system audits, rebate programs, local ordinances, and voluntary or mandatory water-use restrictions. Because utilities do not typically record outdoor and indoor water-uses separately, the effects of policies for reducing garden demands cannot be readily calculated. The volume of water required to meet garden demands depends on the housing density, lawn size, type of vegetation, climatic conditions, efficiency of garden irrigation systems, and consumer water-use behaviors. Many existing outdoor demand estimation methods are deterministic and do not include consumer responses to conservation campaigns. In addition, mandatory restrictions may have a substantial impact on reducing outdoor demands, but the effectiveness of mandatory restrictions depends on the timing and the frequency of restrictions, in addition to the distribution of housing density and consumer types within a community. This research investigates a garden end-use model by coupling an agent-based modeling approach and a mechanistic-stochastic water demand model to create a methodology for estimating garden demand and evaluating demand reduction policies. The garden demand model is developed for two water utilities, using a diverse data sets, including residential customer billing records, outdoor conservation programs, frequency and type of mandatory water-use restrictions, lot size distribution, population growth, and climatic data. A set of garden irrigation parameter values, which are based on the efficiency of irrigation systems and irrigation habits of consumers, are determined for a set of conservation ordinances and restrictions. The model parameters are then validated using customer water usage data from the participating water utilities. A sensitivity analysis is conducted for garden

Analysis of Modeling Assumptions used in Production Cost Models for Renewable Integration Studies

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

Stoll, Brady; Brinkman, Gregory; Townsend, Aaron

2016-01-01

Renewable energy integration studies have been published for many different regions exploring the question of how higher penetration of renewable energy will impact the electric grid. These studies each make assumptions about the systems they are analyzing; however the effect of many of these assumptions has not been yet been examined and published. In this paper we analyze the impact of modeling assumptions in renewable integration studies, including the optimization method used (linear or mixed-integer programming) and the temporal resolution of the dispatch stage (hourly or sub-hourly). We analyze each of these assumptions on a large and a small systemmore » and determine the impact of each assumption on key metrics including the total production cost, curtailment of renewables, CO2 emissions, and generator starts and ramps. Additionally, we identified the impact on these metrics if a four-hour ahead commitment step is included before the dispatch step and the impact of retiring generators to reduce the degree to which the system is overbuilt. We find that the largest effect of these assumptions is at the unit level on starts and ramps, particularly for the temporal resolution, and saw a smaller impact at the aggregate level on system costs and emissions. For each fossil fuel generator type we measured the average capacity started, average run-time per start, and average number of ramps. Linear programming results saw up to a 20% difference in number of starts and average run time of traditional generators, and up to a 4% difference in the number of ramps, when compared to mixed-integer programming. Utilizing hourly dispatch instead of sub-hourly dispatch saw no difference in coal or gas CC units for either start metric, while gas CT units had a 5% increase in the number of starts and 2% increase in the average on-time per start. The number of ramps decreased up to 44%. The smallest effect seen was on the CO2 emissions and total production cost, with a 0

Potential for natural evaporation as a reliable renewable energy resource.

PubMed

Cavusoglu, Ahmet-Hamdi; Chen, Xi; Gentine, Pierre; Sahin, Ozgur

2017-09-26

About 50% of the solar energy absorbed at the Earth's surface drives evaporation, fueling the water cycle that affects various renewable energy resources, such as wind and hydropower. Recent advances demonstrate our nascent ability to convert evaporation energy into work, yet there is little understanding about the potential of this resource. Here we study the energy available from natural evaporation to predict the potential of this ubiquitous resource. We find that natural evaporation from open water surfaces could provide power densities comparable to current wind and solar technologies while cutting evaporative water losses by nearly half. We estimate up to 325 GW of power is potentially available in the United States. Strikingly, water's large heat capacity is sufficient to control power output by storing excess energy when demand is low, thus reducing intermittency and improving reliability. Our findings motivate the improvement of materials and devices that convert energy from evaporation.The evaporation of water represents an alternative source of renewable energy. Building on previous models of evaporation, Cavusoglu et al. show that the power available from this natural resource is comparable to wind and solar power, yet it does not suffer as much from varying weather conditions.

0-6759 : developing a business process and logical model to support a tour-based travel demand model design for TxDOT.

DOT National Transportation Integrated Search

2013-08-01

The Texas Department of Transportation : (TxDOT) created a standardized trip-based : modeling approach for travel demand modeling : called the Texas Package Suite of Travel Demand : Models (referred to as the Texas Package) to : oversee the travel de...

Explaining Employees' Evaluations of Organizational Change with the Job-Demands Resources Model

ERIC Educational Resources Information Center

van Emmerik, I. J. Hetty; Bakker, Arnold B.; Euwema, Martin C.

2009-01-01

Purpose: Departing from the Job Demands-Resources (JD-R) model, the paper examined the relationship between job demands and resources on the one hand, and employees' evaluations of organizational change on the other hand. Design/methodology/approach: Participants were 818 faculty members within six faculties of a Dutch university. Data were…

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

Factor demand in Swedish manufacturing industry with special reference to the demand for energy. Instantaneous adjustment models; some results

NASA Astrophysics Data System (ADS)

Sjoeholm, K. R.

1981-02-01

The dual approach to the theory of production is used to estimate factor demand functions of the Swedish manufacturing industry. Two approximations of the cost function, the translog and the generalized Leontief models, are used. The price elasticities of the factor demand do not seem to depend on the choice of model. This is at least true as to the sign pattern and as to the inputs capital, labor, total energy and other materials. Total energy is separated into solid fuels, gasoline, fuel oil, electricity and a residual. Fuel oil and electricity are found to be substitutes by both models. Capital and energy are shown to be substitutes. This implies that Swedish industry will save more energy if the capital cost can be reduced. Both models are, in the best versions, able to detect an inappropriate variable. The assumption of perfect competition on the product market, is shown to be inadequate by both models. When this assumption is relaxed, the normal substitution pattern among the inputs is resumed.

Hybrid PV/Wind Power Systems Incorporating Battery Storage and Considering the Stochastic Nature of Renewable Resources

NASA Astrophysics Data System (ADS)

Barnawi, Abdulwasa Bakr

Hybrid power generation system and distributed generation technology are attracting more investments due to the growing demand for energy nowadays and the increasing awareness regarding emissions and their environmental impacts such as global warming and pollution. The price fluctuation of crude oil is an additional reason for the leading oil producing countries to consider renewable resources as an alternative. Saudi Arabia as the top oil exporter country in the word announced the "Saudi Arabia Vision 2030" which is targeting to generate 9.5 GW of electricity from renewable resources. Two of the most promising renewable technologies are wind turbines (WT) and photovoltaic cells (PV). The integration or hybridization of photovoltaics and wind turbines with battery storage leads to higher adequacy and redundancy for both autonomous and grid connected systems. This study presents a method for optimal generation unit planning by installing a proper number of solar cells, wind turbines, and batteries in such a way that the net present value (NPV) is minimized while the overall system redundancy and adequacy is maximized. A new renewable fraction technique (RFT) is used to perform the generation unit planning. RFT was tested and validated with particle swarm optimization and HOMER Pro under the same conditions and environment. Renewable resources and load randomness and uncertainties are considered. Both autonomous and grid-connected system designs were adopted in the optimal generation units planning process. An uncertainty factor was designed and incorporated in both autonomous and grid connected system designs. In the autonomous hybrid system design model, the strategy including an additional amount of operation reserve as a percent of the hourly load was considered to deal with resource uncertainty since the battery storage system is the only backup. While in the grid-connected hybrid system design model, demand response was incorporated to overcome the impact of

Military Base Off-Taker Opportunities for Tribal Renewable Energy Projects

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

Nangle, J.

This white paper surveys DOD installations that could have an increased potential interest in the purchase of energy from renewable energy projects on tribal lands. Identification of likely purchasers of renewable energy is a first step in the energy project development process, and this paper aims to identify likely electricity customers that tribal commercial-scale projects could serve. This white paper builds on a geospatial analysis completed in November 2012 identifying 53 reservations within 10 miles of military bases (DOE 2012). This analysis builds on those findings by further refining the list of potential opportunity sites to 15 reservations (Table ES-1),more » based on five additional factors: 1) The potential renewable resources required to meet the installation energy loads; 2) Proximity to transmission lines; 3) Military installation energy demand; 4) State electricity prices; 5) Local policy and regulatory environment.« less

Comparing microscopic activity-based and traditional models of travel demand : an Austin area case study

DOT National Transportation Integrated Search

2007-09-01

Two competing approaches to travel demand modeling exist today. The more traditional 4-step travel demand models rely on aggregate demographic data at a traffic analysis zone (TAZ) level. Activity-based microsimulation methods employ more robus...

Study of an intraurban travel demand model incorporating commuter preference variables

NASA Technical Reports Server (NTRS)

Holligan, P. E.; Coote, M. A.; Rushmer, C. R.; Fanning, M. L.

1971-01-01

The model is based on the substantial travel data base for the nine-county San Francisco Bay Area, provided by the Metropolitan Transportation Commission. The model is of the abstract type, and makes use of commuter attitudes towards modes and simple demographic characteristics of zones in a region to predict interzonal travel by mode for the region. A characterization of the STOL/VTOL mode was extrapolated by means of a subjective comparison of its expected characteristics with those of modes characterized by the survey. Predictions of STOL demand were made for the Bay Area and an aircraft network was developed to serve this demand. When this aircraft system is compared to the base case system, the demand for STOL service has increased five fold and the resulting economics show considerable benefit from the increased scale of operations. In the previous study all systems required subsidy in varying amounts. The new system shows a substantial profit at an average fare of $3.55 per trip.

GAPS OF DECISION SUPPORT MODELS FOR PIPELINE RENEWAL AND RECOMMENDATIONS FOR IMPROVEMENT (SLIDE)

EPA Science Inventory

In terms of the development of software for decision support for pipeline renewal, more attention to date has been paid to the development of asset management models that help an owner decide on which portions of a system to prioritize needed actions. There has been much less wor...

Systems Modelling of the Socio-Technical Aspects of Residential Electricity Use and Network Peak Demand.

PubMed

Lewis, Jim; Mengersen, Kerrie; Buys, Laurie; Vine, Desley; Bell, John; Morris, Peter; Ledwich, Gerard

2015-01-01

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers' peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers' location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price, managed supply, etc., in a conceptual 'map' of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tickbox interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations

Systems Modelling of the Socio-Technical Aspects of Residential Electricity Use and Network Peak Demand

PubMed Central

Lewis, Jim; Mengersen, Kerrie; Buys, Laurie; Vine, Desley; Bell, John; Morris, Peter; Ledwich, Gerard

2015-01-01

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price, managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tickbox interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the

Using Supply, Demand, and the Cournot Model to Understand Corruption

ERIC Educational Resources Information Center

Hayford, Marc D.

2007-01-01

The author combines the supply and demand model of taxes with a Cournot model of bribe takers to develop a simple and useful framework for understanding the effect of corruption on economic activity. There are many examples of corruption in both developed and developing countries. Because corruption decreases the level of economic activity and…

A hybrid inventory management system respondingto regular demand and surge demand

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

Mohammad S. Roni; Mingzhou Jin; Sandra D. Eksioglu

2014-06-01

This paper proposes a hybrid policy for a stochastic inventory system facing regular demand and surge demand. The combination of two different demand patterns can be observed in many areas, such as healthcare inventory and humanitarian supply chain management. The surge demand has a lower arrival rate but higher demand volume per arrival. The solution approach proposed in this paper incorporates the level crossing method and mixed integer programming technique to optimize the hybrid inventory policy with both regular orders and emergency orders. The level crossing method is applied to obtain the equilibrium distributions of inventory levels under a givenmore » policy. The model is further transformed into a mixed integer program to identify an optimal hybrid policy. A sensitivity analysis is conducted to investigate the impact of parameters on the optimal inventory policy and minimum cost. Numerical results clearly show the benefit of using the proposed hybrid inventory model. The model and solution approach could help healthcare providers or humanitarian logistics providers in managing their emergency supplies in responding to surge demands.« less

Estimating future dental services' demand and supply: a model for Northern Germany.

PubMed

Jäger, Ralf; van den Berg, Neeltje; Hoffmann, Wolfgang; Jordan, Rainer A; Schwendicke, Falk

2016-04-01

To plan dental services, a spatial estimation of future demands and supply is required. We aimed at estimating demand and supply in 2030 in Northern Germany based on the expected local socio-demography and oral-health-related morbidity, and the predicted number of dentists and their working time. All analyses were performed on zip-code level. Register data were used to determine the number of retiring dentists and to construct regression models for estimating the number of dentists moving into each zip-code area until 2030. Demand was modelled using projected demography and morbidities. Demand-supply ratios were evaluated and spatial analyses applied. Sensitivity analyses were employed to assess robustness of our findings. Compared with 2011, the population decreased (-7% to -11%) and aged (from mean 46 to 51 years) until 2030. Oral-health-related morbidity changed, leading to more periodontal and fewer prosthetic treatments needs, with the overall demand decreasing in all scenarios (-25% to -33%). In contrast, the overall number of dentists did only limitedly change, resulting in moderate decrease in the supplied service quantities (max. -22%). Thus, the demand-supply ratio increased in all but the worst case scenario, but was unequally distributed between spatial units, with several areas being over- and some being under- or none-serviced in 2030. Within the limitations of the underlying data and the required assumptions, this study expects an increasingly polarized ratio of dental services demand and supply in Northern Germany. Our estimation allows to assess the impact of different influence factors on demand or supply and to specifically identify potential challenges for workforce planning and regulation in different spatial units. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Demand Activated Manufacturing Architecture (DAMA) model for supply chain collaboration

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

CHAPMAN,LEON D.; PETERSEN,MARJORIE B.

The Demand Activated Manufacturing Architecture (DAMA) project during the last five years of work with the U.S. Integrated Textile Complex (retail, apparel, textile, and fiber sectors) has developed an inter-enterprise architecture and collaborative model for supply chains. This model will enable improved collaborative business across any supply chain. The DAMA Model for Supply Chain Collaboration is a high-level model for collaboration to achieve Demand Activated Manufacturing. The five major elements of the architecture to support collaboration are (1) activity or process, (2) information, (3) application, (4) data, and (5) infrastructure. These five elements are tied to the application of themore » DAMA architecture to three phases of collaboration - prepare, pilot, and scale. There are six collaborative activities that may be employed in this model: (1) Develop Business Planning Agreements, (2) Define Products, (3) Forecast and Plan Capacity Commitments, (4) Schedule Product and Product Delivery, (5) Expedite Production and Delivery Exceptions, and (6) Populate Supply Chain Utility. The Supply Chain Utility is a set of applications implemented to support collaborative product definition, forecast visibility, planning, scheduling, and execution. The DAMA architecture and model will be presented along with the process for implementing this DAMA model.« less

A Demands-Resources Model of Work Pressure in IT Student Task Groups

ERIC Educational Resources Information Center

Wilson, E. Vance; Sheetz, Steven D.

2010-01-01

This paper presents an initial test of the group task demands-resources (GTD-R) model of group task performance among IT students. We theorize that demands and resources in group work influence formation of perceived group work pressure (GWP) and that heightened levels of GWP inhibit group task performance. A prior study identified 11 factors…

Modeling the demand-price relations in a high-frequency foreign exchange market

NASA Astrophysics Data System (ADS)

Schmidt, Anatoly B.

1999-09-01

A stochastic nonlinear dynamics model is introduced in terms of observable variables (price and excess demand assumed to be proportional to the number of buyers) to describe a high-frequency foreign exchange market. It is shown how the fundamentalist and chartist patterns of the trader behavior affect the correlation between excess demand and exchange rates.

Integrated Agent-Based and Production Cost Modeling Framework for Renewable Energy Studies

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

Gallo, Giulia

The agent-based framework for renewable energy studies (ARES) is an integrated approach that adds an agent-based model of industry actors to PLEXOS and combines the strengths of the two to overcome their individual shortcomings. It can examine existing and novel wholesale electricity markets under high penetrations of renewables. ARES is demonstrated by studying how increasing levels of wind will impact the operations and the exercise of market power of generation companies that exploit an economic withholding strategy. The analysis is carried out on a test system that represents the Electric Reliability Council of Texas energy-only market in the year 2020.more » The results more realistically reproduce the operations of an energy market under different and increasing penetrations of wind, and ARES can be extended to address pressing issues in current and future wholesale electricity markets.« less

Model for Assembly Line Re-Balancing Considering Additional Capacity and Outsourcing to Face Demand Fluctuations

NASA Astrophysics Data System (ADS)

Samadhi, TMAA; Sumihartati, Atin

2016-02-01

The most critical stage in a garment industry is sewing process, because generally, it consists of a number of operations and a large number of sewing machines for each operation. Therefore, it requires a balancing method that can assign task to work station with balance workloads. Many studies on assembly line balancing assume a new assembly line, but in reality, due to demand fluctuation and demand increased a re-balancing is needed. To cope with those fluctuating demand changes, additional capacity can be carried out by investing in spare sewing machine and paying for sewing service through outsourcing. This study develops an assembly line balancing (ALB) model on existing line to cope with fluctuating demand change. Capacity redesign is decided if the fluctuation demand exceeds the available capacity through a combination of making investment on new machines and outsourcing while considering for minimizing the cost of idle capacity in the future. The objective of the model is to minimize the total cost of the line assembly that consists of operating costs, machine cost, adding capacity cost, losses cost due to idle capacity and outsourcing costs. The model develop is based on an integer programming model. The model is tested for a set of data of one year demand with the existing number of sewing machines of 41 units. The result shows that additional maximum capacity up to 76 units of machine required when there is an increase of 60% of the average demand, at the equal cost parameters..

Modelling inter-supply chain competition with resource limitation and demand disruption

NASA Astrophysics Data System (ADS)

Chen, Zhaobo; Teng, Chunxian; Zhang, Ding; Sun, Jiayi

2016-05-01

This paper proposes a comprehensive model for studying supply chain versus supply chain competition with resource limitation and demand disruption. We assume that there are supply chains with heterogeneous supply network structures that compete at multiple demand markets. Each supply chain is comprised of internal and external firms. The internal firms are coordinated in production and distribution and share some common but limited resources within the supply chain, whereas the external firms are independent and do not share the internal resources. The supply chain managers strive to develop optimal strategies in terms of production level and resource allocation in maximising their profit while facing competition at the end market. The Cournot-Nash equilibrium of this inter-supply chain competition is formulated as a variational inequality problem. We further study the case when there is demand disruption in the plan-execution phase. In such a case, the managers need to revise their planned strategy in order to maximise their profit with the new demand under disruption and minimise the cost of change. We present a bi-criteria decision-making model for supply chain managers and develop the optimal conditions in equilibrium, which again can be formulated by another variational inequality problem. Numerical examples are presented for illustrative purpose.

Understanding well-being and learning of Nigerian nurses: a job demand control support model approach.

PubMed

van Doorn, Yvonne; van Ruysseveldt, Joris; van Dam, Karen; Mistiaen, Wilhelm; Nikolova, Irina

2016-10-01

This study investigated whether Nigerian nurses' emotional exhaustion and active learning were predicted by job demands, control and social support. Limited research has been conducted concerning nurses' work stress in developing countries, such as Nigeria. Accordingly, it is not clear whether work interventions for improving nurses' well-being in these countries can be based on work stress models that are developed in Western countries, such as the job demand control support model, as well as on empirical findings of job demand control support research. Nurses from Nurses Across the Borders Nigeria were invited to complete an online questionnaire containing validated scales; 210 questionnaires were fully completed and analysed. Multiple regression analysis was used to test the hypotheses. Emotional exhaustion was higher for nurses who experienced high demands and low supervisor support. Active learning occurred when nurses worked under conditions of high control and high supervisor support. The findings suggest that the job demand control support model is applicable in a Nigerian nursing situation; the model indicates which occupational stressors contribute to poor well-being in Nigerian nurses and which work characteristics may boost nurses' active learning. Job (re)design interventions can enhance nurses' well-being and learning by guarding nurses' job demands, and stimulating job control and supervisor support. © 2016 John Wiley & Sons Ltd.

Sustainable infrastructure system modeling under uncertainties and dynamics

NASA Astrophysics Data System (ADS)

Huang, Yongxi

Infrastructure systems support human activities in transportation, communication, water use, and energy supply. The dissertation research focuses on critical transportation infrastructure and renewable energy infrastructure systems. The goal of the research efforts is to improve the sustainability of the infrastructure systems, with an emphasis on economic viability, system reliability and robustness, and environmental impacts. The research efforts in critical transportation infrastructure concern the development of strategic robust resource allocation strategies in an uncertain decision-making environment, considering both uncertain service availability and accessibility. The study explores the performances of different modeling approaches (i.e., deterministic, stochastic programming, and robust optimization) to reflect various risk preferences. The models are evaluated in a case study of Singapore and results demonstrate that stochastic modeling methods in general offers more robust allocation strategies compared to deterministic approaches in achieving high coverage to critical infrastructures under risks. This general modeling framework can be applied to other emergency service applications, such as, locating medical emergency services. The development of renewable energy infrastructure system development aims to answer the following key research questions: (1) is the renewable energy an economically viable solution? (2) what are the energy distribution and infrastructure system requirements to support such energy supply systems in hedging against potential risks? (3) how does the energy system adapt the dynamics from evolving technology and societal needs in the transition into a renewable energy based society? The study of Renewable Energy System Planning with Risk Management incorporates risk management into its strategic planning of the supply chains. The physical design and operational management are integrated as a whole in seeking mitigations against the

Mindfulness as a personal resource to reduce work stress in the job demands-resources model.

PubMed

Grover, Steven L; Teo, Stephen T T; Pick, David; Roche, Maree

2017-10-01

Based on the job demands-resources (JD-R) model, this study examines the different ways that the personal resource of mindfulness reduces stress. Structural equation modeling based on data from 415 Australian nurses shows that mindfulness relates directly and negatively to work stress and perceptions of emotional demands as well as buffering the relation of emotional demands on psychological stress. This study contributes to the literature by employing empirical analysis to the task of unravelling how personal resources function within the JD-R model. It also introduces mindfulness as a personal resource in the JD-R model. Copyright © 2016 John Wiley & Sons, Ltd.

Comparing supply and demand models for future photovoltaic power generation in the USA

DOE PAGES

Basore, Paul A.; Cole, Wesley J.

2018-02-22

We explore the plausible range of future deployment of photovoltaic generation capacity in the USA using a supply-focused model based on supply-chain growth constraints and a demand-focused model based on minimizing the overall cost of the electricity system. Both approaches require assumptions based on previous experience and anticipated trends. For each of the models, we assign plausible ranges for the key assumptions and then compare the resulting PV deployment over time. Each model was applied to 2 different future scenarios: one in which PV market penetration is ultimately constrained by the uncontrolled variability of solar power and one in whichmore » low-cost energy storage or some equivalent measure largely alleviates this constraint. The supply-focused and demand-focused models are in substantial agreement, not just in the long term, where deployment is largely determined by the assumed market penetration constraints, but also in the interim years. For the future scenario without low-cost energy storage or equivalent measures, the 2 models give an average plausible range of PV generation capacity in the USA of 150 to 530 GWdc in 2030 and 260 to 810 GWdc in 2040. With low-cost energy storage or equivalent measures, the corresponding ranges are 160 to 630 GWdc in 2030 and 280 to 1200 GWdc in 2040. The latter range is enough to supply 10% to 40% of US electricity demand in 2040, based on current demand growth.« less

Comparing supply and demand models for future photovoltaic power generation in the USA

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

Basore, Paul A.; Cole, Wesley J.

We explore the plausible range of future deployment of photovoltaic generation capacity in the USA using a supply-focused model based on supply-chain growth constraints and a demand-focused model based on minimizing the overall cost of the electricity system. Both approaches require assumptions based on previous experience and anticipated trends. For each of the models, we assign plausible ranges for the key assumptions and then compare the resulting PV deployment over time. Each model was applied to 2 different future scenarios: one in which PV market penetration is ultimately constrained by the uncontrolled variability of solar power and one in whichmore » low-cost energy storage or some equivalent measure largely alleviates this constraint. The supply-focused and demand-focused models are in substantial agreement, not just in the long term, where deployment is largely determined by the assumed market penetration constraints, but also in the interim years. For the future scenario without low-cost energy storage or equivalent measures, the 2 models give an average plausible range of PV generation capacity in the USA of 150 to 530 GWdc in 2030 and 260 to 810 GWdc in 2040. With low-cost energy storage or equivalent measures, the corresponding ranges are 160 to 630 GWdc in 2030 and 280 to 1200 GWdc in 2040. The latter range is enough to supply 10% to 40% of US electricity demand in 2040, based on current demand growth.« less

Renewable Energy Resources in Lebanon

NASA Astrophysics Data System (ADS)

Hamdy, R.

2010-12-01

The energy sector in Lebanon plays an important role in the overall development of the country, especially that it suffers from many serious problems. The fact that Lebanon is among the few countries that are not endowed with fossil fuels in the Middle East made this sector cause one third of the national debt in Lebanon. Despite the large government investments in the power sector, demand still exceeds supply and Lebanon frequently goes through black out in peak demand times or has to resort to importing electricity from Syria. The Energy production sector has dramatic environmental and economical impacts in the form of emitted gasses and environment sabotage, accordingly, it is imperative that renewable energy (RE) be looked at as an alternative energy source. Officials at the Ministry of Energy and Water (MEW) and Lebanese Electricity (EDL) have repeatedly expressed their support to renewable energy utilization. So far, only very few renewable energy applications can be observed over the country. Major efforts are still needed to overcome this situation and promote the use of renewable energy. These efforts are the shared responsibility of the government, EDL, NGO's and educational and research centers. Additionally, some efforts are being made by some international organizations such as UNDP, ESCWA, EC and other donor agencies operating in Lebanon. This work reviews the status of Energy in Lebanon, the installed RE projects, and the potential projects. It also reviews the stakeholders in the field of RE in Lebanon Conclusion In considering the best R.E. alternative, it is important to consider all potential R.E. sources, their costs, market availability, suitability for the selected location, significance of the energy produced and return on investment. Several RE resources in Lebanon have been investigated; Tides and waves energy is limited and not suitable two tentative sites for geothermal energy are available but not used. Biomass resources badly affect the

Intermittent Renewable Management Pilot Phase 2

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

Kiliccote, Sila; Homan, Gregory; Anderson, Robert

The Intermittent Renewable Management Pilot - Phase 2 (IRM2) was designed to study the feasibility of demand-side resources to participate into the California Independent System Operator (CAISO) wholesale market as proxy demand resources (PDR). The pilot study focused on understanding the issues related with direct participation of third-parties and customers including customer acceptance; market transformation challenges (wholesale market, technology); technical and operational feasibility; and value to the rate payers, DR resource owners and the utility on providing an enabling mechanism for DR resources into the wholesale markets. The customer had the option of committing to either three contiguous hour blocksmore » for 24 days or six contiguous hours for 12 days a month with day-ahead notification that aligned with the CAISO integrated forward market. As a result of their being available, the customer was paid $10/ kilowatt (kW)-month for capacity in addition to CAISO energy settlements. The participants were limited to no more than a 2 megawatt (MW) capacity with a six-month commitment. Four participants successfully engaged in the pilot. In this report, we provide the description of the pilot, participant performance results, costs and value to participants as well as outline some of the issues encountered through the pilot. Results show that participants chose to participate with storage and the value of CAISO settlements were significantly lower than the capacity payments provided by the utility as incentive payments. In addition, this pilot revealed issues both on the participant side and system operations side. These issues are summarized in the report.The Intermittent Renewable Management Pilot - Phase 2 (IRM2) was designed to study the feasibility of demand-side resources to participate into the California Independent System Operator (CAISO) wholesale market as proxy demand resources (PDR). The pilot study focused on understanding the issues related

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....

Modeling sustainability in renewable energy supply chain systems

NASA Astrophysics Data System (ADS)

Xie, Fei

This dissertation aims at modeling sustainability of renewable fuel supply chain systems against emerging challenges. In particular, the dissertation focuses on the biofuel supply chain system design, and manages to develop advanced modeling framework and corresponding solution methods in tackling challenges in sustaining biofuel supply chain systems. These challenges include: (1) to integrate "environmental thinking" into the long-term biofuel supply chain planning; (2) to adopt multimodal transportation to mitigate seasonality in biofuel supply chain operations; (3) to provide strategies in hedging against uncertainty from conversion technology; and (4) to develop methodologies in long-term sequential planning of the biofuel supply chain under uncertainties. All models are mixed integer programs, which also involves multi-objective programming method and two-stage/multistage stochastic programming methods. In particular for the long-term sequential planning under uncertainties, to reduce the computational challenges due to the exponential expansion of the scenario tree, I also developed efficient ND-Max method which is more efficient than CPLEX and Nested Decomposition method. Through result analysis of four independent studies, it is found that the proposed modeling frameworks can effectively improve the economic performance, enhance environmental benefits and reduce risks due to systems uncertainties for the biofuel supply chain systems.

A MODEL FOR THE DEMAND FOR HIGHER EDUCATION IN THE UNITED STATES, 1919-64.

ERIC Educational Resources Information Center

CAMPBELL, ROBERT; SIEGEL, BARRY N.

STATISTICAL DEMAND ANALYSIS, WHICH EMPHASIZES THE INFLUENCE OF RELATIVE PRICES AND REAL INCOME UPON THE DEMAND FOR A COMMODITY, WAS USED TO DEVELOP A MODEL OF THE DEMAND FOR HIGHER EDUCATION. THE STUDY IS BASED ON THE FACT THAT COLLEGE ENROLLMENT REPRESENTS THE PURCHASE OF BOTH A PRODUCER AND CONSUMER DURABLE, AND IS AN ACT OF INVESTMENT.…

Renewable Energy Zone (REZ) Transmission Planning Process: A Guidebook for Practitioners

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

Lee, Nathan; Flores-Espino, Francisco; Hurlbut, David J.

Achieving clean energy goals may require new investments in transmission, especially if planners anticipate economic growth and increased demand for electricity. The renewable energy zone (REZ) transmission planning process can help policymakers ensure their infrastructure investments achieve national goals in the most economical manner. Policymakers, planners, and system operators around the world have used variations of the REZ process to chart the expansion of their transmission networks and overcome the barriers of traditional transmission planning. This guidebook seeks to help power system planners, key decision makers, and stakeholders understand and use the REZ transmission planning process to integrate transmission expansionmore » planning and renewable energy generation planning.« less

Renewable Substitutability Index: Maximizing Renewable Resource Use in Buildings

EPA Science Inventory

In order to achieve a material and energy balance in buildings that is sustainable in the long run, there is an urgent need to assess the renewable and non-renewable resources used in the manufacturing process and to progressively replace non-renewable resources with renewables. ...

Renewable Energy used in State Renewable Portfolio Standards Yielded

Science.gov Websites

. Renewable Portfolio Standards also shows national water withdrawals and water consumption by fossil-fuel methodologies, while recognizing that states could perform their own more-detailed assessments," NREL's , respectively. Ranges are presented as the models and methodologies used are sensitive to multiple parameters

An Interdisciplinary Approach to Developing Renewable Energy Mixes at the Community Scale

NASA Astrophysics Data System (ADS)

Gormally, Alexandra M.; Whyatt, James D.; Timmis, Roger J.; Pooley, Colin G.

2013-04-01

Renewable energy has risen on the global political agenda due to concerns over climate change and energy security. The European Union (EU) currently has a target of 20% renewable energy by the year 2020 and there is increasing focus on the ways in which these targets can be achieved. Here we focus on the UK context which could be considered to be lagging behind other EU countries in terms of targets and implementation. The UK has a lower overall target of 15% renewable energy by 2020 and in 2011 reached only 3.8 % (DUKES, 2012), one of the lowest progressions compared to other EU Member States (European Commission, 2012). The reticence of the UK to reach such targets could in part be due to their dependence on their current energy mix and a highly centralised electricity grid system, which does not lend itself easily to the adoption of renewable technologies. Additionally, increasing levels of demand and the need to raise energy awareness are key concerns in terms of achieving energy security in the UK. There is also growing concern from the public about increasing fuel and energy bills. One possible solution to some of these problems could be through the adoption of small-scale distributed renewable schemes implemented at the community-scale with local ownership or involvement, for example, through energy co-operatives. The notion of the energy co-operative is well understood elsewhere in Europe but unfamiliar to many UK residents due to its centralised approach to energy provision. There are many benefits associated with engaging in distributed renewable energy systems. In addition to financial benefits, participation may raise energy awareness and can lead to positive responses towards renewable technologies. Here we briefly explore how a mix of small-scale renewables, including wind, hydro-power and solar PV, have been implemented and managed by a small island community in the Scottish Hebrides to achieve over 90% of their electricity needs from renewable

NRASG12V oncogene facilitates self-renewal in a murine model of acute myelogenous leukemia

PubMed Central

LaRue, Rebecca S.; Nguyen, Hanh T.; Sachs, Karen; Noble, Klara E.; Mohd Hassan, Nurul Azyan; Diaz-Flores, Ernesto; Rathe, Susan K.; Sarver, Aaron L.; Bendall, Sean C.; Ha, Ngoc A.; Diers, Miechaleen D.; Nolan, Garry P.; Shannon, Kevin M.; Largaespada, David A.

2014-01-01

Mutant RAS oncoproteins activate signaling molecules that drive oncogenesis in multiple human tumors including acute myelogenous leukemia (AML). However, the specific functions of these pathways in AML are unclear, thwarting the rational application of targeted therapeutics. To elucidate the downstream functions of activated NRAS in AML, we used a murine model that harbors Mll-AF9 and a tetracycline-repressible, activated NRAS (NRASG12V). Using computational approaches to explore our gene-expression data sets, we found that NRASG12V enforced the leukemia self-renewal gene-expression signature and was required to maintain an MLL-AF9– and Myb-dependent leukemia self-renewal gene-expression program. NRASG12V was required for leukemia self-renewal independent of its effects on growth and survival. Analysis of the gene-expression patterns of leukemic subpopulations revealed that the NRASG12V-mediated leukemia self-renewal signature is preferentially expressed in the leukemia stem cell–enriched subpopulation. In a multiplexed analysis of RAS-dependent signaling, Mac-1Low cells, which harbor leukemia stem cells, were preferentially sensitive to NRASG12V withdrawal. NRASG12V maintained leukemia self-renewal through mTOR and MEK pathway activation, implicating these pathways as potential targets for cancer stem cell–specific therapies. Together, these experimental results define a RAS oncogene–driven function that is critical for leukemia maintenance and represents a novel mechanism of oncogene addiction. PMID:25316678

Renewable energy rebound effect?: Estimating the impact of state renewable energy financial incentives on residential electricity consumption

NASA Astrophysics Data System (ADS)

Stephenson, Beth A.

Climate change is a well-documented phenomenon. If left unchecked greenhouse gas emissions will continue global surface warming, likely leading to severe and irreversible impacts. Generating renewable energy has become an increasingly salient topic in energy policy as it may mitigate the impact of climate change. State renewable energy financial incentives have been in place since the mid-1970s in some states and over 40 states have adopted one or more incentives at some point since then. Using multivariate linear and fixed effects regression for the years 2002 through 2012, I estimate the relationship between state renewable energy financial incentives and residential electricity consumption, along with the associated policy implications. My hypothesis is that a renewable energy rebound effect is present; therefore, states with renewable energy financial incentives have a higher rate of residential electricity consumption. I find a renewable energy rebound effect is present in varying degrees for each model, but the results do not definitively indicate how particular incentives influence consumer behavior. States should use caution when adopting and keeping renewable energy financial incentives as this may increase consumption in the short-term. The long-term impact is unclear, making it worthwhile for policymakers to continue studying the potential for renewable energy financial incentives to alter consumer behavior.

Evaluating Water Demand Using Agent-Based Modeling

NASA Astrophysics Data System (ADS)

Lowry, T. S.

2004-12-01

The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage

Analysis of an inventory model for both linearly decreasing demand and holding cost

NASA Astrophysics Data System (ADS)

Malik, A. K.; Singh, Parth Raj; Tomar, Ajay; Kumar, Satish; Yadav, S. K.

2016-03-01

This study proposes the analysis of an inventory model for linearly decreasing demand and holding cost for non-instantaneous deteriorating items. The inventory model focuses on commodities having linearly decreasing demand without shortages. The holding cost doesn't remain uniform with time due to any form of variation in the time value of money. Here we consider that the holding cost decreases with respect to time. The optimal time interval for the total profit and the optimal order quantity are determined. The developed inventory model is pointed up through a numerical example. It also includes the sensitivity analysis.

Energy Management Challenges and Opportunities with Increased Intermittent Renewable Generation on the California Electrical Grid

NASA Astrophysics Data System (ADS)

Eichman, Joshua David

Renewable resources including wind, solar, geothermal, biomass, hydroelectric, wave and tidal, represent an opportunity for environmentally preferred generation of electricity that also increases energy security and independence. California is very proactive in encouraging the implementation of renewable energy in part through legislation like Assembly Bill 32 and the development and execution of Renewable Portfolio Standards (RPS); however renewable technologies are not without challenges. All renewable resources have some resource limitations, be that from location, capacity, cost or availability. Technologies like wind and solar are intermittent in nature but represent one of the most abundant resources for generating renewable electricity. If RPS goals are to be achieved high levels of intermittent renewables must be considered. This work explores the effects of high penetration of renewables on a grid system, with respect to resource availability and identifies the key challenges from the perspective of the grid to introducing these resources. The HiGRID tool was developed for this analysis because no other tool could explore grid operation, while maintaining system reliability, with a diverse set of renewable resources and a wide array of complementary technologies including: energy efficiency, demand response, energy storage technologies and electric transportation. This tool resolves the hourly operation of conventional generation resources (nuclear, coal, geothermal, natural gas and hydro). The resulting behavior from introducing additional renewable resources and the lifetime costs for each technology is analyzed.

An assessment of renewable energy in Southern Africa: Wind, solar, hydro

NASA Astrophysics Data System (ADS)

Fant, Charles William, IV

While electricity demand is rising quickly in the Southern African Power Pool (SAPP), the nations involved struggle to build the necessary infrastructure to meet the demand. In addition, the principal member---the Republic of South Africa---has made ambitious targets to reduce emissions via renewable energy technology. In this dissertation, three stand-alone studies on this subject are presented that address the future reliability of renewable energy in southern Africa, considering climate variability as well as long-term trends caused by climate change. In the first study, a suite of models are used to assess the vulnerability of the countries dependent on resources from the Zambezi River Basin to changes in climate. The study finds that the sectors most vulnerable to climate change are: hydropower in Zambia, irrigation in Zimbabwe and Mozambique, and flooding in Mozambique. In the second study, hourly reanalysis data is used to characterize wind power intermittency and assess the value of interconnection in southern Africa. The study finds that wind potential is high in Kenya, central Tanzania, and southern South Africa. With a closer look, wind power resource in South Africa is unreliable (i.e. intermittent) and is weak when power demand is highest on all relevant time-scales. In the third study, presented in Chapter 4, we develop a risk profile for changes in the long-term mean of wind and solar power sources. To do this, we use a statistical relationship between global mean temperature and each local gridded wind speed and solar radiation from the GCMs. We find that only small changes in wind speed and solar radiation are predicted in the median of the distributions projected to 2050. Furthermore, at the extremes of the distribution, relatively significant changes are predicted in some parts of southern Africa, and are associated with low probability. Finally, in the conclusion chapter, limitations and assumptions are listed for each of the three studies

A frequency quantum interpretation of the surface renewal model of mass transfer

PubMed Central

Mondal, Chanchal

2017-01-01

The surface of a turbulent liquid is visualized as consisting of a large number of chaotic eddies or liquid elements. Assuming that surface elements of a particular age have renewal frequencies that are integral multiples of a fundamental frequency quantum, and further assuming that the renewal frequency distribution is of the Boltzmann type, performing a population balance for these elements leads to the Danckwerts surface age distribution. The basic quantum is what has been traditionally called the rate of surface renewal. The Higbie surface age distribution follows if the renewal frequency distribution of such elements is assumed to be continuous. Four age distributions, which reflect different start-up conditions of the absorption process, are then used to analyse transient physical gas absorption into a large volume of liquid, assuming negligible gas-side mass-transfer resistance. The first two are different versions of the Danckwerts model, the third one is based on the uniform and Higbie distributions, while the fourth one is a mixed distribution. For the four cases, theoretical expressions are derived for the rates of gas absorption and dissolved-gas transfer to the bulk liquid. Under transient conditions, these two rates are not equal and have an inverse relationship. However, with the progress of absorption towards steady state, they approach one another. Assuming steady-state conditions, the conventional one-parameter Danckwerts age distribution is generalized to a two-parameter age distribution. Like the two-parameter logarithmic normal distribution, this distribution can also capture the bell-shaped nature of the distribution of the ages of surface elements observed experimentally in air–sea gas and heat exchange. Estimates of the liquid-side mass-transfer coefficient made using these two distributions for the absorption of hydrogen and oxygen in water are very close to one another and are comparable to experimental values reported in the literature

Predictors of new graduate nurses' workplace well-being: testing the job demands-resources model.

PubMed

Spence Laschinger, Heather K; Grau, Ashley L; Finegan, Joan; Wilk, Piotr

2012-01-01

New graduate nurses currently experience a stressful transition into the workforce, resulting in high levels of burnout and job turnover in their first year of practice. This study tested a theoretical model of new graduate nurses' worklife derived from the job demands-resources model to better understand how job demands (workload and bullying), job resources (job control and supportive professional practice environments), and a personal resource (psychological capital) combine to influence new graduate experiences of burnout and work engagement and, ultimately, health and job outcomes. A descriptive correlational design was used to test the hypothesized model in a sample of newly graduated nurses (N = 420) working in acute care hospitals in Ontario, Canada. Data were collected from July to November 2009. Participants were mailed questionnaires to their home address using the Total Design Method to improve response rates. All variables were measured using standardized questionnaires, and structural equation modeling was used to test the model. The final model fit statistics partially supported the original hypothesized model. In the final model, job demands (workload and bullying) predicted burnout and, subsequently, poor mental health. Job resources (supportive practice environment and control) predicted work engagement and, subsequently, lower turnover intentions. Burnout also was a significant predictor of turnover intent (a crossover effect). Furthermore, personal resources (psychological capital) significantly influenced both burnout and work engagement. The model suggests that managerial strategies targeted at specific job demands and resources can create workplace environments that promote work engagement and prevent burnout to support the retention and well-being of the new graduate nurse population.

Electricity Capacity Expansion Modeling, Analysis, and Visualization: A Summary of High-Renewable Modeling Experiences (Chinese Translation) (in Chinese)

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

Blair, Nate; Zhou, Ella; Getman, Dan

2015-10-01

This is the Chinese translation of NREL/TP-6A20-64831. Mathematical and computational models are widely used for the analysis and design of both physical and financial systems. Modeling the electric grid is of particular importance to China for three reasons. First, power-sector assets are expensive and long-lived, and they are critical to any country's development. China's electric load, transmission, and other energy-related infrastructure are expected to continue to grow rapidly; therefore it is crucial to understand and help plan for the future in which those assets will operate. Second, China has dramatically increased its deployment of renewable energy (RE), and is likelymore » to continue further accelerating such deployment over the coming decades. Careful planning and assessment of the various aspects (technical, economic, social, and political) of integrating a large amount of renewables on the grid is required. Third, companies need the tools to develop a strategy for their own involvement in the power market China is now developing, and to enable a possible transition to an efficient and high RE future.« less

How Low Can You Go? The Importance of Quantifying Minimum Generation Levels for Renewable Integration

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

Denholm, Paul L; Brinkman, Gregory L; Mai, Trieu T

One of the significant limitations of solar and wind deployment is declining value caused by the limited correlation of renewable energy supply and electricity demand as well as limited flexibility of the power system. Limited flexibility can result from thermal and hydro plants that cannot turn off or reduce output due to technical or economic limits. These limits include the operating range of conventional thermal power plants, the need for process heat from combined heat and power plants, and restrictions on hydro unit operation. To appropriately analyze regional and national energy policies related to renewable deployment, these limits must bemore » accurately captured in grid planning models. In this work, we summarize data sources and methods for U.S. power plants that can be used to capture minimum generation levels in grid planning tools, such as production cost models. We also provide case studies for two locations in the U.S. (California and Texas) that demonstrate the sensitivity of variable generation (VG) curtailment to grid flexibility assumptions which shows the importance of analyzing (and documenting) minimum generation levels in studies of increased VG penetration.« less

Motor Vehicle Demand Models : Assessment of the State of the Art and Directions for Future Research

DOT National Transportation Integrated Search

1981-04-01

The report provides an assessment of the current state of motor vehicle demand modeling. It includes a detailed evaluation of one leading large-scale econometric vehicle demand model, which is tested for both logical consistency and forecasting accur...

Residential water demand model under block rate pricing: A case study of Beijing, China

NASA Astrophysics Data System (ADS)

Chen, H.; Yang, Z. F.

2009-05-01

In many cities, the inconsistency between water supply and water demand has become a critical problem because of deteriorating water shortage and increasing water demand. Uniform price of residential water cannot promote the efficient water allocation. In China, block water price will be put into practice in the future, but the outcome of such regulation measure is unpredictable without theory support. In this paper, the residential water is classified by the volume of water usage based on economic rules and block water is considered as different kinds of goods. A model based on extended linear expenditure system (ELES) is constructed to simulate the relationship between block water price and water demand, which provide theoretical support for the decision-makers. Finally, the proposed model is used to simulate residential water demand under block rate pricing in Beijing.

Renewal models and coseismic stress transfer in the Corinth Gulf, Greece, fault system

NASA Astrophysics Data System (ADS)

Console, Rodolfo; Falcone, Giuseppe; Karakostas, Vassilis; Murru, Maura; Papadimitriou, Eleftheria; Rhoades, David

2013-07-01

model interevent times and Coulomb static stress transfer on the rupture segments along the Corinth Gulf extension zone, a region with a wealth of observations on strong-earthquake recurrence behavior. From the available information on past seismic activity, we have identified eight segments without significant overlapping that are aligned along the southern boundary of the Corinth rift. We aim to test if strong earthquakes on these segments are characterized by some kind of time-predictable behavior, rather than by complete randomness. The rationale for time-predictable behavior is based on the characteristic earthquake hypothesis, the necessary ingredients of which are a known faulting geometry and slip rate. The tectonic loading rate is characterized by slip of 6 mm/yr on the westernmost fault segment, diminishing to 4 mm/yr on the easternmost segment, based on the most reliable geodetic data. In this study, we employ statistical and physical modeling to account for stress transfer among these fault segments. The statistical modeling is based on the definition of a probability density distribution of the interevent times for each segment. Both the Brownian Passage-Time (BPT) and Weibull distributions are tested. The time-dependent hazard rate thus obtained is then modified by the inclusion of a permanent physical effect due to the Coulomb static stress change caused by failure of neighboring faults since the latest characteristic earthquake on the fault of interest. The validity of the renewal model is assessed retrospectively, using the data of the last 300 years, by comparison with a plain time-independent Poisson model, by means of statistical tools including the Relative Operating Characteristic diagram, the R-score, the probability gain and the log-likelihood ratio. We treat the uncertainties in the parameters of each examined fault source, such as linear dimensions, depth of the fault center, focal mechanism, recurrence time, coseismic slip, and

Limitations of demand- and pressure-driven modeling for large deficient networks

NASA Astrophysics Data System (ADS)

Braun, Mathias; Piller, Olivier; Deuerlein, Jochen; Mortazavi, Iraj

2017-10-01

The calculation of hydraulic state variables for a network is an important task in managing the distribution of potable water. Over the years the mathematical modeling process has been improved by numerous researchers for utilization in new computer applications and the more realistic modeling of water distribution networks. But, in spite of these continuous advances, there are still a number of physical phenomena that may not be tackled correctly by current models. This paper will take a closer look at the two modeling paradigms given by demand- and pressure-driven modeling. The basic equations are introduced and parallels are drawn with the optimization formulations from electrical engineering. These formulations guarantee the existence and uniqueness of the solution. One of the central questions of the French and German research project ResiWater is the investigation of the network resilience in the case of extreme events or disasters. Under such extraordinary conditions where models are pushed beyond their limits, we talk about deficient network models. Examples of deficient networks are given by highly regulated flow, leakage or pipe bursts and cases where pressure falls below the vapor pressure of water. These examples will be presented and analyzed on the solvability and physical correctness of the solution with respect to demand- and pressure-driven models.

CHLORINE DEMAND AND TTHM FORMATION KINETICS: A SECOND-ORDER MODEL

EPA Science Inventory

Much effort has been expended in attempting to develop mathematical models for chlorine demand in water and wastewater. Most of these efforts have centered around the use of first-order functions or modifications of first-order functions. Recently there has also been interest i...

The spread model of food safety risk under the supply-demand disturbance.

PubMed

Wang, Jining; Chen, Tingqiang

2016-01-01

In this paper, based on the imbalance of the supply-demand relationship of food, we design a spreading model of food safety risk, which is about from food producers to consumers in the food supply chain. We use theoretical analysis and numerical simulation to describe the supply-demand relationship and government supervision behaviors' influence on the risk spread of food safety and the behaviors of the food producers and the food retailers. We also analyze the influence of the awareness of consumer rights protection and the level of legal protection of consumer rights on the risk spread of food safety. This model contributes to the explicit investigation of the influence relationship among supply-demand factors, the regulation behavioral choice of government, the behavioral choice of food supply chain members and food safety risk spread. And this paper provides a new viewpoint for considering food safety risk spread in the food supply chain, which has a great reference for food safety management.

The active learning hypothesis of the job-demand-control model: an experimental examination.

PubMed

Häusser, Jan Alexander; Schulz-Hardt, Stefan; Mojzisch, Andreas

2014-01-01

The active learning hypothesis of the job-demand-control model [Karasek, R. A. 1979. "Job Demands, Job Decision Latitude, and Mental Strain: Implications for Job Redesign." Administration Science Quarterly 24: 285-307] proposes positive effects of high job demands and high job control on performance. We conducted a 2 (demands: high vs. low) × 2 (control: high vs. low) experimental office workplace simulation to examine this hypothesis. Since performance during a work simulation is confounded by the boundaries of the demands and control manipulations (e.g. time limits), we used a post-test, in which participants continued working at their task, but without any manipulation of demands and control. This post-test allowed for examining active learning (transfer) effects in an unconfounded fashion. Our results revealed that high demands had a positive effect on quantitative performance, without affecting task accuracy. In contrast, high control resulted in a speed-accuracy tradeoff, that is participants in the high control conditions worked slower but with greater accuracy than participants in the low control conditions.

Development of weekend travel demand and mode choice models : final report, June 2009.

DOT National Transportation Integrated Search

2010-06-30

Travel demand models are widely used for forecasting and analyzing policies for automobile and transit travel. However, these models are typically developed for average weekday travel when regular activities are routine. The weekday models focus prim...

Superior pseudocapacitive behavior of confined lignin nanocrystals for renewable energy-storage materials.

PubMed

Kim, Sung-Kon; Kim, Yun Ki; Lee, Hyunjoo; Lee, Sang Bok; Park, Ho Seok

2014-04-01

Strong demand for high-performance energy-storage devices has currently motivated the development of emerging capacitive materials that can resolve their critical challenge (i.e., low energy density) and that are renewable and inexpensive energy-storage materials from both environmental and economic viewpoints. Herein, the pseudocapacitive behavior of lignin nanocrystals confined on reduced graphene oxides (RGOs) used for renewable energy-storage materials is demonstrated. The excellent capacitive characteristics of the renewable hybrid electrodes were achieved by synergizing the fast and reversible redox charge transfer of surface-confined quinone and the interplay with electron-conducting RGOs. Accordingly, pseudocapacitors with remarkable rate and cyclic performances (~96 % retention after 3000 cycles) showed a maximum capacitance of 432 F g(-1), which was close to the theoretical capacitance of 482 F g(-1) and sixfold higher than that of RGO (93 F g(-1)). The chemical strategy delineated herein paves the way to develop advanced renewable electrodes for energy-storage applications and understand the redox chemistry of electroactive biomaterials. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Techno-economic feasibility and life cycle assessment of dairy effluent to renewable diesel via hydrothermal liquefaction.

PubMed

Summers, Hailey M; Ledbetter, Rhesa N; McCurdy, Alex T; Morgan, Michael R; Seefeldt, Lance C; Jena, Umakanta; Hoekman, S Kent; Quinn, Jason C

2015-11-01

The economic feasibility and environmental impact is investigated for the conversion of agricultural waste, delactosed whey permeate, through yeast fermentation to a renewable diesel via hydrothermal liquefaction. Process feasibility was demonstrated at laboratory-scale with data leveraged to validate systems models used to perform industrial-scale economic and environmental impact analyses. Results show a minimum fuel selling price of $4.78 per gallon of renewable diesel, a net energy ratio of 0.81, and greenhouse gas emissions of 30.0g-CO2-eqMJ(-1). High production costs and greenhouse gas emissions can be attributed to operational temperatures and durations of both fermentation and hydrothermal liquefaction. However, high lipid yields of the yeast counter these operational demands, resulting in a favorable net energy ratio. Results are presented on the optimization of the process based on economy of scale and a sensitivity analysis highlights improvements in conversion efficiency, yeast biomass productivity and hydrotreating efficiency can dramatically improve commercial feasibility. Copyright © 2015 Elsevier Ltd. All rights reserved.

An EOQ Model with Two-Parameter Weibull Distribution Deterioration and Price-Dependent Demand

ERIC Educational Resources Information Center

Mukhopadhyay, Sushanta; Mukherjee, R. N.; Chaudhuri, K. S.

2005-01-01

An inventory replenishment policy is developed for a deteriorating item and price-dependent demand. The rate of deterioration is taken to be time-proportional and the time to deterioration is assumed to follow a two-parameter Weibull distribution. A power law form of the price dependence of demand is considered. The model is solved analytically…

Integrated Agent-Based and Production Cost Modeling Framework for Renewable Energy Studies: Preprint

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

Gallo, Giulia

The agent-based framework for renewable energy studies (ARES) is an integrated approach that adds an agent-based model of industry actors to PLEXOS and combines the strengths of the two to overcome their individual shortcomings. It can examine existing and novel wholesale electricity markets under high penetrations of renewables. ARES is demonstrated by studying how increasing levels of wind will impact the operations and the exercise of market power of generation companies that exploit an economic withholding strategy. The analysis is carried out on a test system that represents the Electric Reliability Council of Texas energy-only market in the year 2020.more » The results more realistically reproduce the operations of an energy market under different and increasing penetrations of wind, and ARES can be extended to address pressing issues in current and future wholesale electricity markets.« less

Evaluating Renewable Cornstarch/biochar Fillers as Potential Substitutes for Carbon Black in SBR Composites

USDA-ARS?s Scientific Manuscript database

The continually growing demand for fossil fuels coupled with the potential risk of relying on foreign sources for these fuels strengthens the need to find renewable substitutes for petroleum products. Carbon black is a petroleum product that dominates the rubber composite filler market. Agricultur...

Demand modelling of passenger air travel: An analysis and extension. Volume 1: Background and summary

NASA Technical Reports Server (NTRS)

Jacobson, I. D.

1978-01-01

The framework for a model of travel demand which will be useful in predicting the total market for air travel between two cities is discussed. Variables to be used in determining the need for air transportation where none currently exists and the effect of changes in system characteristics on attracting latent demand are identified. Existing models are examined in order to provide insight into their strong points and shortcomings. Much of the existing behavioral research in travel demand is incorporated to allow the inclusion of non-economic factors, such as convenience. The model developed is characterized as a market segmentation model. This is a consequence of the strengths of disaggregation and its natural evolution to a usable aggregate formulation. The need for this approach both pedagogically and mathematically is discussed.

The impacts of renewable energy policies on renewable energy sources for electricity generating capacity

NASA Astrophysics Data System (ADS)

Koo, Bryan Bonsuk

Electricity generation from non-hydro renewable sources has increased rapidly in the last decade. For example, Renewable Energy Sources for Electricity (RES-E) generating capacity in the U.S. almost doubled for the last three year from 2009 to 2012. Multiple papers point out that RES-E policies implemented by state governments play a crucial role in increasing RES-E generation or capacity. This study examines the effects of state RES-E policies on state RES-E generating capacity, using a fixed effects model. The research employs panel data from the 50 states and the District of Columbia, for the period 1990 to 2011, and uses a two-stage approach to control endogeneity embedded in the policies adopted by state governments, and a Prais-Winsten estimator to fix any autocorrelation in the panel data. The analysis finds that Renewable Portfolio Standards (RPS) and Net-metering are significantly and positively associated with RES-E generating capacity, but neither Public Benefit Funds nor the Mandatory Green Power Option has a statistically significant relation to RES-E generating capacity. Results of the two-stage model are quite different from models which do not employ predicted policy variables. Analysis using non-predicted variables finds that RPS and Net-metering policy are statistically insignificant and negatively associated with RES-E generating capacity. On the other hand, Green Energy Purchasing policy is insignificant in the two-stage model, but significant in the model without predicted values.

Review of applications for SIMDEUM, a stochastic drinking water demand model with a small temporal and spatial scale

NASA Astrophysics Data System (ADS)

Blokker, Mirjam; Agudelo-Vera, Claudia; Moerman, Andreas; van Thienen, Peter; Pieterse-Quirijns, Ilse

2017-04-01

Many researchers have developed drinking water demand models with various temporal and spatial scales. A limited number of models is available at a temporal scale of 1 s and a spatial scale of a single home. The reasons for building these models were described in the papers in which the models were introduced, along with a discussion on their potential applications. However, the predicted applications are seldom re-examined. SIMDEUM, a stochastic end-use model for drinking water demand, has often been applied in research and practice since it was developed. We are therefore re-examining its applications in this paper. SIMDEUM's original purpose was to calculate maximum demands in order to design self-cleaning networks. Yet, the model has been useful in many more applications. This paper gives an overview of the many fields of application for SIMDEUM and shows where this type of demand model is indispensable and where it has limited practical value. This overview also leads to an understanding of the requirements for demand models in various applications.

Energy supply and demand modeling. (Latest citations from the NTIS bibliographic database). Published Search

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

Not Available

1994-01-01

The bibliography contains citations concerning the use of mathematical models in trend analysis and forecasting of energy supply and demand factors. Models are presented for the industrial, transportation, and residential sectors. Aspects of long term energy strategies and markets are discussed at the global, national, state, and regional levels. Energy demand and pricing, and econometrics of energy, are explored for electric utilities and natural resources, such as coal, oil, and natural gas. Energy resources are modeled both for fuel usage and for reserves. (Contains 250 citations and includes a subject term index and title list.)

Energy supply and demand modeling. (Latest citations from the NTIS data base). Published Search

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

Not Available

1992-10-01

The bibliography contains citations concerning the use of mathematical models in trend analysis and forecasting of energy supply and demand factors. Models are presented for the industrial, transportation, and residential sectors. Aspects of long term energy strategies and markets are discussed at the global, national, state, and regional levels. Energy demand and pricing, and econometrics of energy, are explored for electric utilities and natural resources, such as coal, oil, and natural gas. Energy resources are modeled both for fuel usage and for reserves. (Contains 250 citations and includes a subject term index and title list.)

Energy supply and demand modeling. (Latest citations from the NTIS bibliographic database). Published Search

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

Not Available

1994-12-01

The bibliography contains citations concerning the use of mathematical models in trend analysis and forecasting of energy supply and demand factors. Models are presented for the industrial, transportation, and residential sectors. Aspects of long term energy strategies and markets are discussed at the global, national, state, and regional levels. Energy demand and pricing, and econometrics of energy, are explored for electric utilities and natural resources, such as coal, oil, and natural gas. Energy resources are modeled both for fuel usage and for reserves. (Contains 250 citations and includes a subject term index and title list.)

Better Water Demand and Pipe Description Improve the Distribution Network Modeling Results

EPA Science Inventory

Distribution system modeling simplifies pipe network in skeletonization and simulates the flow and water quality by using generalized water demand patterns. While widely used, the approach has not been examined fully on how it impacts the modeling fidelity. This study intends to ...

The USAID/DOE Mexico Renewable Energy Program: Using technology to build new markets

NASA Astrophysics Data System (ADS)

Hanley, Charles J.

1997-02-01

Under the Mexico Renewable Energy Program, managed by Sandia National Laboratories, sustainable markets for renewable energy technologies are developed through the implementation of pilot projects. Sandia provides technical assistance to several Mexican rural development organizations so they can gain the technical and institutional capability to appropriately utilize renewables within their ongoing programs. Activities in the area of water pumping have shown great replication potential, where the tremendous rural demand for water represents a potential renewable market of over 2 billion. Thirty-six photovoltaic water pumping projects have been installed thus far in the Mexican states of Chihuahua, Sonora, Baja California Sur, and Quintana Roo, and 60 more will be implemented this year. The majority of these projects are in partnership with the Mexican Trust for Shared Risk (FIRCO), which has asked Sandia for assistance in extending the program nationwide. This replication is beginning in five new states, and will continue to grow. Sandia is keeping the U.S. renewable energy industry involved in the program through facilitating partnerships between U.S. and Mexican vendors, and through commercialization assistance with new systems technologies. The program is sponsored by the Department of Energy and the U.S. Agency for International Development.

A subjective supply-demand model: the maximum Boltzmann/Shannon entropy solution

NASA Astrophysics Data System (ADS)

Piotrowski, Edward W.; Sładkowski, Jan

2009-03-01

The present authors have put forward a projective geometry model of rational trading. The expected (mean) value of the time that is necessary to strike a deal and the profit strongly depend on the strategies adopted. A frequent trader often prefers maximal profit intensity to the maximization of profit resulting from a separate transaction because the gross profit/income is the adopted/recommended benchmark. To investigate activities that have different periods of duration we define, following the queuing theory, the profit intensity as a measure of this economic category. The profit intensity in repeated trading has a unique property of attaining its maximum at a fixed point regardless of the shape of demand curves for a wide class of probability distributions of random reverse transactions (i.e. closing of the position). These conclusions remain valid for an analogous model based on supply analysis. This type of market game is often considered in research aiming at finding an algorithm that maximizes profit of a trader who negotiates prices with the Rest of the World (a collective opponent), possessing a definite and objective supply profile. Such idealization neglects the sometimes important influence of an individual trader on the demand/supply profile of the Rest of the World and in extreme cases questions the very idea of demand/supply profile. Therefore we put forward a trading model in which the demand/supply profile of the Rest of the World induces the (rational) trader to (subjectively) presume that he/she lacks (almost) all knowledge concerning the market but his/her average frequency of trade. This point of view introduces maximum entropy principles into the model and broadens the range of economic phenomena that can be perceived as a sort of thermodynamical system. As a consequence, the profit intensity has a fixed point with an astonishing connection with Fibonacci classical works and looking for the quickest algorithm for obtaining the extremum of a

Incorporating home demands into models of job strain: findings from the work, family, and health network.

PubMed

Ertel, Karen A; Koenen, Karestan C; Berkman, Lisa F

2008-11-01

The purpose of this article was to integrate home demands with the demand-control-support model to test if home demands interact with job strain to increase depressive symptoms. Data were from 431 employees in four extended care facilities. Presence of a child younger than 18 years in the household signified home demands. The outcome was depressive symptoms based on a shortened version of the Center for Epidemiologic Studies Depression Scale. The association between job strain and depressive symptoms was moderated by social support (SS) and presence of a child in the household (child). There was no association among participants with high SS and no child, but a positive one among participants with low SS and a child. Job strain may be a particularly important determinant of depressive symptoms among employees with family demands. Models of job strain should expand to incorporate family demands.

RETHINKING THE FUTURE GRID: INTEGRATED NUCLEAR-RENEWABLE ENERGY SYSTEMS

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

S.M. Bragg-Sitton; R. Boardman

2014-12-01

The 2013 electricity generation mix in the United States consisted of ~13% renewables (hydropower, wind, solar, geothermal), 19% nuclear, 27% natural gas, and 39% coal. In the 2011 State of the Union Address, President Obama set a clean energy goal for the nation: “By 2035, 80 percent of America’s electricity will come from clean energy sources. Some folks want wind and solar. Others want nuclear, clean coal and natural gas. To meet this goal we will need them all.” The U.S. Department of Energy (DOE) Offices of Nuclear Energy (NE) and Energy Efficiency and Renewable Energy (EERE) recognize that “allmore » of the above” means that we are called to best utilize all available clean energy sources. To meet the stated environmental goals for electricity generation and for the broader energy sector, there is a need to transform the energy infrastructure of the U.S. and elsewhere. New energy systems must be capable of significantly reducing environmental impacts in an efficient and economically viable manner while utilizing both hydrocarbon resources and clean energy generation sources. The U.S. DOE is supporting research and development that could lead to more efficient utilization of clean energy generation sources, including renewable and nuclear options, to meet both grid demand and thermal energy needs in the industrial sector. A concept being advanced by the DOE-NE and DOE-EERE is tighter coupling of nuclear and renewable energy sources in a manner that better optimizes energy use for the combined electricity, industrial manufacturing, and the transportation sectors. This integration concept has been referred to as a “hybrid system” that is capable of apportioning thermal and electrical energy to first meet the grid demand (with appropriate power conversion systems), then utilizing excess thermal and, in some cases, electrical energy to drive a process that results in an additional product. For the purposes of the present work, the hybrid system

Different types of antagonists modify the outcome of complete denture renewal.

PubMed

Berteretche, Marie Violaine; Frot, Amélie; Woda, Alain; Pereira, Bruno; Hennequin, Martine

2015-01-01

The effect of renewing removable dentures on masticatory function was evaluated according to the occlusion offered by different types of mandibular arches. Twenty-eight patients with complete maxillary dentures were subdivided into three groups in terms of mandibular dentition type: dentate, partial denture, and complete denture. The participants were observed before and 8 weeks after maxillary denture renewal. The mandibular denture was also renewed in the partial and complete denture groups. The participants masticated carrots, peanuts, and three model foods of different hardnesses. The particle size distribution of the boluses obtained from natural foods was characterized by the median particle size (d50) in relation to the masticatory normative indicator (MNI). Chewing time (CT), number of chewing cycles (CC), and chewing frequency (CF) were video recorded. A self-assessment questionnaire for oral health-related quality of life (Geriatric Oral Health Assessment Index [GOHAI]) was used. Statistical analyses were carried out with a mixed model. Renewal of the dentures decreased d50 (P < .001). The number of participants with d50 values above the MNI cutoff decreased from 12 to 2 after renewal. Renewal induced an increase in mean CF while chewing model foods (P < .001). With all foods, renewal tended to affect CT, CC, and CF differently among the three groups (statistically significant renewal Å~ group interactions). The GOHAI score increased significantly for all groups. Denture renewal improves masticatory function. The complete denture group benefited least from renewal; the dentate group benefited most. This study confirmed the usefulness of denture renewal for improving functions and oral health- related quality of life.

Modelling and simulation of current fed dc to dc converter for PHEV applications using renewable source

NASA Astrophysics Data System (ADS)

Milind Metha, Manish; Tutki, Sanjay; Rajan, Aju; Elangovan, D.; Arunkumar, G.

2017-11-01

With the current rate of depletion of the fossil fuel the need to switch on to the renewable energy sources is the need of the hour. Thus the need for new and efficient converters arises so as to replace the existing less efficient diesel and petroleum IC engines with renewable energy sources. The PHEVs, which have been launched in the market, and Upcoming PHEVs have converters around 380V to 400V generated with a power range between 2KW to 2.8KW. The fundamental target of this paper is to plan a productive converter keeping in mind cost and size restriction. In this paper, a two-stage dc-dc converter is proposed. The proposed converter is utilized to venture up a voltage from 24V (photovoltaic source) to a yield voltage of 400V to take care of a power demand of 2.4kW for a plug-in hybrid electric vehicle (PHEV) application considering the real time scenario of PHEV. This paper talks about in detail why the current fed converter is utilized alongside a voltage doubler thus minimizing the transformer turns thereby reducing the overall size of the final product. Simulation results along with calculation for the duty cycle of the firing sequence for different value of transformer turns are presented for a prototype unit.

Predicting Urban Medical Services Demand in China: An Improved Grey Markov Chain Model by Taylor Approximation.

PubMed

Duan, Jinli; Jiao, Feng; Zhang, Qishan; Lin, Zhibin

2017-08-06

The sharp increase of the aging population has raised the pressure on the current limited medical resources in China. To better allocate resources, a more accurate prediction on medical service demand is very urgently needed. This study aims to improve the prediction on medical services demand in China. To achieve this aim, the study combines Taylor Approximation into the Grey Markov Chain model, and develops a new model named Taylor-Markov Chain GM (1,1) (T-MCGM (1,1)). The new model has been tested by adopting the historical data, which includes the medical service on treatment of diabetes, heart disease, and cerebrovascular disease from 1997 to 2015 in China. The model provides a predication on medical service demand of these three types of disease up to 2022. The results reveal an enormous growth of urban medical service demand in the future. The findings provide practical implications for the Health Administrative Department to allocate medical resources, and help hospitals to manage investments on medical facilities.

A Longitudinal Test of the Demand–Control Model Using Specific Job Demands and Specific Job Control

PubMed Central

van Vegchel, Natasja; Shimazu, Akihito; Schaufeli, Wilmar; Dormann, Christian

2010-01-01

Background Supportive studies of the demand–control (DC) model were more likely to measure specific demands combined with a corresponding aspect of control. Purpose A longitudinal test of Karasek’s (Adm Sci Q. 24:285–308, 1) job strain hypothesis including specific measures of job demands and job control, and both self-report and objectively recorded well-being. Method Job strain hypothesis was tested among 267 health care employees from a two-wave Dutch panel survey with a 2-year time lag. Results Significant demand/control interactions were found for mental and emotional demands, but not for physical demands. The association between job demands and job satisfaction was positive in case of high job control, whereas this association was negative in case of low job control. In addition, the relation between job demands and psychosomatic health symptoms/sickness absence was negative in case of high job control and positive in case of low control. Conclusion Longitudinal support was found for the core assumption of the DC model with specific measures of job demands and job control as well as self-report and objectively recorded well-being. PMID:20195810

Spatiotemporal Co-variability of Surface Climate for Renewable Energy across the Contiguous United States: Role of the North Atlantic Subtropical High

NASA Astrophysics Data System (ADS)

Doering, K.; Steinschneider, S.

2017-12-01

The variability of renewable energy supply and drivers of demand across space and time largely determines the energy balance within power systems with a high penetration of renewable technologies. This study examines the joint spatiotemporal variability of summertime climate linked to renewable energy production (precipitation, wind speeds, insolation) and energy demand (temperature) across the contiguous United States (CONUS) between 1948 and 2015. Canonical correlation analysis is used to identify the major modes of joint variability between summer wind speeds and precipitation and related patterns of insolation and temperature. Canonical variates are then related to circulation anomalies to identify common drivers of the joint modes of climate variability. Results show that the first two modes of joint variability between summer wind speeds and precipitation exhibit pan-US dipole patterns with centers of action located in the eastern and central CONUS. Temperature and insolation also exhibit related US-wide dipoles. The relationship between canonical variates and lower-tropospheric geopotential height indicates that these modes are related to variability in the North Atlantic subtropical high (NASH). This insight can inform optimal strategies for siting renewables in an interconnected electric grid, and has implications for the impacts of climate variability and change on renewable energy systems.

Accurate Estimation of Target amounts Using Expanded BASS Model for Demand-Side Management

NASA Astrophysics Data System (ADS)

Kim, Hyun-Woong; Park, Jong-Jin; Kim, Jin-O.

2008-10-01

The electricity demand in Korea has rapidly increased along with a steady economic growth since 1970s. Therefore Korea has positively propelled not only SSM (Supply-Side Management) but also DSM (Demand-Side Management) activities to reduce investment cost of generating units and to save supply costs of electricity through the enhancement of whole national energy utilization efficiency. However study for rebate, which have influence on success or failure on DSM program, is not sufficient. This paper executed to modeling mathematically expanded Bass model considering rebates, which have influence on penetration amounts for DSM program. To reflect rebate effect more preciously, the pricing function using in expanded Bass model directly reflects response of potential participants for rebate level.

Elucidating the role of recovery experiences in the job demands-resources model.

PubMed

Moreno-Jiménez, Bernardo; Rodríguez-Muñoz, Alfredo; Sanz-Vergel, Ana Isabel; Garrosa, Eva

2012-07-01

Based on the Job Demands-Resources (JD-R) model, the current study examined the moderating role of recovery experiences (i.e., psychological detachment from work, relaxation, mastery experiences, and control over leisure time) on the relationship between one job demand (i.e., role conflict) and work- and health-related outcomes. Results from our sample of 990 employees from Spain showed that psychological detachment from work and relaxation buffered the negative impact of role conflict on some of the proposed outcomes. Contrary to our expectations, we did not find significant results for mastery and control regarding moderating effects. Overall, findings suggest a differential pattern of the recovery experiences in the health impairment process proposed by the JD-R model.

System Dynamics of Polysilicon for Solar Photovoltaics: A Framework for Investigating the Energy Security of Renewable Energy Supply Chains

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

Sandor, Debra; Fulton, Sadie; Engel-Cox, Jill

Renewable energy, produced with widely available low-cost energy resources, is often included as a component of national strategies to address energy security and sustainability. Market and political forces cannot disrupt the sun or wind, unlike oil and gas supplies. However, the cost of renewable energy is highly dependent on technologies manufactured through global supply chains in leading manufacturing countries. The countries that contribute to the global supply chains may take actions that, directly or indirectly, influence global access to materials and components. For example, high-purity polysilicon, a key material in solar photovoltaics, has experienced significant price fluctuations, affecting the manufacturingmore » capacity and cost of both polysilicon and solar panels. This study has developed and validated an initial system dynamics framework to gain insights into global trade in polysilicon. The model represents an initial framework for exploration. Three regions were modeled-China, the United States, and the rest of the world - for a range of trade scenarios to understand the impacts of import duties and non-price drivers on the relative volumes of imports and domestic supply. The model was validated with the historical case of China imposing an import duty on polysilicon from the United States, the European Union, and South Korea, which altered the regional flows of polysilicon - in terms of imports, exports, and domestic production-to varying degrees. As expected, the model tracked how regional demand shares and influx volumes decrease as a duty on a region increases. Using 2016 as a reference point, in the scenarios examined for U.S. exports to China, each 10% increase in the import duty results in a 40% decrease in import volume. The model also indicates that, under the scenarios investigated, once a duty has been imposed on a region, the demand share from that region declines and does not achieve pre-duty levels, even as global demand

System Dynamics of Polysilicon for Solar Photovoltaics: A Framework for Investigating the Energy Security of Renewable Energy Supply Chains

DOE PAGES

Sandor, Debra; Fulton, Sadie; Engel-Cox, Jill; ...

2018-01-11

Renewable energy, produced with widely available low-cost energy resources, is often included as a component of national strategies to address energy security and sustainability. Market and political forces cannot disrupt the sun or wind, unlike oil and gas supplies. However, the cost of renewable energy is highly dependent on technologies manufactured through global supply chains in leading manufacturing countries. The countries that contribute to the global supply chains may take actions that, directly or indirectly, influence global access to materials and components. For example, high-purity polysilicon, a key material in solar photovoltaics, has experienced significant price fluctuations, affecting the manufacturingmore » capacity and cost of both polysilicon and solar panels. This study has developed and validated an initial system dynamics framework to gain insights into global trade in polysilicon. The model represents an initial framework for exploration. Three regions were modeled-China, the United States, and the rest of the world - for a range of trade scenarios to understand the impacts of import duties and non-price drivers on the relative volumes of imports and domestic supply. The model was validated with the historical case of China imposing an import duty on polysilicon from the United States, the European Union, and South Korea, which altered the regional flows of polysilicon - in terms of imports, exports, and domestic production-to varying degrees. As expected, the model tracked how regional demand shares and influx volumes decrease as a duty on a region increases. Using 2016 as a reference point, in the scenarios examined for U.S. exports to China, each 10% increase in the import duty results in a 40% decrease in import volume. The model also indicates that, under the scenarios investigated, once a duty has been imposed on a region, the demand share from that region declines and does not achieve pre-duty levels, even as global demand

The influence of renewable and non-renewable energy consumption and real income on CO2 emissions in the USA: evidence from structural break tests.

PubMed

Dogan, Eyup; Ozturk, Ilhan

2017-04-01

The objective of this study is to explore the influence of the real income (GDP), renewable energy consumption and non-renewable energy consumption on carbon dioxide (CO 2 ) emissions for the United States of America (USA) in the environmental Kuznets curve (EKC) model for the period 1980-2014. The Zivot-Andrews unit root test with a structural break and the Clemente-Montanes-Reyes unit root test with a structural break report that the analyzed variables become stationary at first-differences. The Gregory-Hansen cointegration test with a structural break and the bounds testing for cointegration in the presence of a structural break show CO 2 emissions, the real income, the quadratic real income, renewable and non-renewable energy consumption are cointegrated. The long-run estimates obtained from the ARDL model indicate that increases in renewable energy consumption mitigate environmental degradation whereas increases in non-renewable energy consumption contribute to CO 2 emissions. In addition, the EKC hypothesis is not valid for the USA. Since we use time-series econometric approaches that account for structural break in the data, findings of this study are robust, reliable and accurate. The US government is advised to put more weights on renewable sources in energy mix, to support and encourage the use and adoption of renewable energy and clean technologies, and to increase the public awareness of renewable energy for lower levels of emissions.

Automated Demand Response for Energy Sustainability Cost and Performance Report

DTIC Science & Technology

2015-09-01

Install solar thermal system for pool heating in fitness Bldg 325 2022 $ 21,359 $ 7,199 3.6 yrs Renewable energy project p. 124- 126 Note: All data...and R. Bienert, 2011. Smart Grid Standards and Systems Interoperability: A Precedent with OpenADR, Lawrence Berkeley National Laboratory, LBNL...response (DR) system at Fort Irwin, CA. This demonstration employed industry-standard OpenADR (Open Automated Demand Response) technology to perform

Nuclear-renewable hybrid energy systems: Opportunities, interconnections, and needs

DOE PAGES

Ruth, Mark F.; Zinaman, Owen R.; Antkowiak, Mark; ...

2013-12-20

As the U.S. energy system evolves, the amount of electricity from variable-generation sources is likely to increase, which could result in additional times when electricity demand is lower than available production. Therefore, purveyors of technologies that traditionally have provided base-load electricity—such as nuclear power plants—can explore new operating procedures to deal with the associated market signals. Concurrently, innovations in nuclear reactor design coupled with sophisticated control systems now allow for more complex apportionment of heat within an integrated system such as one linked to energy-intensive chemical processes. Our paper explores one opportunity – nuclear-renewable hybrid energy systems. These are definedmore » as integrated facilities comprised of nuclear reactors, renewable energy generation, and industrial processes that can simultaneously address the need for grid flexibility, greenhouse gas emission reductions, and optimal use of investment capital. Six aspects of interaction (interconnections) between elements of nuclear-renewable hybrid energy systems are identified: Thermal, electrical, chemical, hydrogen, mechanical, and information. In addition, system-level aspects affect selection, design, and operation of this hybrid system type. Throughout the paper, gaps and research needs are identified to promote further exploration of the topic.« less

Analysis of environmental impacts of renewable energy on the Moroccan electricity sector: A System Dynamics approach

NASA Astrophysics Data System (ADS)

Chentouf, M.; Allouch, M.

2018-05-01

Producing electricity at an affordable price while taking into account environmental concerns has become a major challenge in Morocco. Moreover, the technical and financial issues related to renewable electricity plants are still hindering their efficient integration in the country. In fact, the energy sector (both electricity and heat) accounted for more than half of all Greenhouse Gases (GHG) emissions in the kingdom due to the major reliance on fossil fuels for answering the growing local demand. The key strategies to alleviate this critical situation include the integration of more renewable energies in the total energy mix and the enhancement of energy efficiency measures in different sectors. This paper strives to (1) evaluate the potential of carbon dioxide mitigation in Moroccan electricity sector following the actual and projected strategies and (2) highlight the policy schemes to be taken in order to achieve the ambitious carbon dioxide mitigation targets in the mid-term. A system dynamics model was built in order to simulate different scenarios of carbon dioxide mitigation policies up to 2030. The results shows that the achievement of renewable energies projects by 2030 could save 228.143 MtCO2 between 2020 and 2030 and an additional 18.127 MtCO2 could be avoided in the same period by enhancing energy efficiency measures.

Does job burnout mediate negative effects of job demands on mental and physical health in a group of teachers? Testing the energetic process of Job Demands-Resources model.

PubMed

Baka, Łukasz

2015-01-01

The aim of the study was to investigate the direct and indirect - mediated by job burnout - effects of job demands on mental and physical health problems. The Job Demands-Resources model was the theoretical framework of the study. Three job demands were taken into account - interpersonal conflicts at work, organizational constraints and workload. Indicators of mental and physical health problems included depression and physical symptoms, respectively. Three hundred and sixteen Polish teachers from 8 schools participated in the study. The hypotheses were tested with the use of tools measuring job demands (Interpersonal Conflicts at Work, Organizational Constraints, Quantitative Workload), job burnout (the Oldenburg Burnout Inventory), depression (the Beck Hopelessness Scale), and physical symptoms (the Physical Symptoms Inventory). The regression analysis with bootstrapping, using the PROCESS macros of Hayes was applied. The results support the hypotheses partially. The indirect effect and to some extent the direct effect of job demands turned out to be statistically important. The negative impact of 3 job demands on mental (hypothesis 1 - H1) and physical (hypothesis 2 - H2) health were mediated by the increasing job burnout. Only organizational constraints were directly associated with mental (and not physical) health. The results partially support the notion of the Job Demands-Resources model and provide further insight into processes leading to the low well-being of teachers in the workplace. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

India Renewable Integration Study | Energy Analysis | NREL

Science.gov Websites

India Renewable Integration Study India Renewable Integration Study An NREL grid integration study Energy into India's Electric Grid Vol. I-National Study and Vol. II-Regional Study resolves many system modeling, the study explored operational impacts of meeting India's 2022 targets and identified

The Effect of the Demand Control and Effort Reward Imbalance Models on the Academic Burnout of Korean Adolescents

ERIC Educational Resources Information Center

Lee, Jayoung; Puig, Ana; Lee, Sang Min

2012-01-01

The purpose of this study was to examine the effects of the Demand Control Model (DCM) and the Effort Reward Imbalance Model (ERIM) on academic burnout for Korean students. Specifically, this study identified the effects of the predictor variables based on DCM and ERIM (i.e., demand, control, effort, reward, Demand Control Ratio, Effort Reward…

Cloud County Community College Wind Energy Technology Project and Renewable Energy Center of Excellence

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

Graham, Bruce

Cloud County Community College's (CCCC) Wind Energy Technology (WET) program is a leader in the renewable energy movement across Kansas and the USA. The field of renewable energy is a growing industry which continues to experience high demand for career opportunities. This CCCC/DOE project entailed two phases: 1) the installation of two Northwind 100 wind turbines, and 2) the continued development of the WET program curriculum, including enhancement of the CCCC Blade Repair Certificate program. This report provides a technical account of the total work performed, and is a comprehensive description of the results achieved.

Total Force Fitness in units part 1: military demand-resource model.

PubMed

Bates, Mark J; Fallesen, Jon J; Huey, Wesley S; Packard, Gary A; Ryan, Diane M; Burke, C Shawn; Smith, David G; Watola, Daniel J; Pinder, Evette D; Yosick, Todd M; Estrada, Armando X; Crepeau, Loring; Bowles, Stephen V

2013-11-01

The military unit is a critical center of gravity in the military's efforts to enhance resilience and the health of the force. The purpose of this article is to augment the military's Total Force Fitness (TFF) guidance with a framework of TFF in units. The framework is based on a Military Demand-Resource model that highlights the dynamic interactions across demands, resources, and outcomes. A joint team of subject-matter experts identified key variables representing unit fitness demands, resources, and outcomes. The resulting framework informs and supports leaders, support agencies, and enterprise efforts to strengthen TFF in units by (1) identifying TFF unit variables aligned with current evidence and operational practices, (2) standardizing communication about TFF in units across the Department of Defense enterprise in a variety of military organizational contexts, (3) improving current resources including evidence-based actions for leaders, (4) identifying and addressing of gaps, and (5) directing future research for enhancing TFF in units. These goals are intended to inform and enhance Service efforts to develop Service-specific TFF models, as well as provide the conceptual foundation for a follow-on article about TFF metrics for units. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.

Relationship of Solar Energy Installation Permits to Renewable Portfolio Standards and Insolation

NASA Astrophysics Data System (ADS)

Butler, Kirt Gordon

Legislated renewable portfolio standards (RPSs) may not be the key to ensure forecast energy demands are met. States without a legislated RPS and with efficient permitting procedures were found to have approved and issued 28.57% more permits on average than those with a legislated RPS. Assessment models to make informed decisions about the need and effect of legislated RPSs do not exist. Decision makers and policy creators need to use empirical data and a viable model to resolve the debate over a nationally legislated RPS. The purpose of this cross-sectional study was to determine if relationships between the independent variables of RPS and insolation levels and the dependent variable of the percentage of permits approved would prove to be a viable model. The research population was 68 cities in the United States, of which 55 were used in this study. The return on investment economic decision model provided the theoretical framework for this study and the model generated. The output of multiple regression analysis indicated a weak to medium positive relationship among the variables. None of these relationships were statistically significant at the 0.05 level. A model using site specific data might yield significant results and be useful for determining which solar energy projects to pursue and where to implement them without Federal or State mandated RPSs. A viable model would bring about efficiency gains in the permitting process and effectiveness gains in promoting installations of solar energy-based systems. Research leading to the development of a viable model would benefit society by encouraging the development of sustainable energy sources and helping to meet forecast energy demands.

Renewable energy education and industrial arts: linking knowledge producers with knowledge

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

Foley, R.L.

This study introduces renewable energy technology into the industrial arts programs in the State of New Hampshire by providing the following information for decision making: (1) a broad-based perspective on renewable energy technology; (2) the selection of an educational change model; (3) data from a needs analysis; (4) an initial screening of potential teacher-trainers. The Wolf-Welsh Linkage Model was selected as the knowledge production/utilization model for bridging the knowledge gap between renewable energy experts and industrial arts teachers. Ninety-six renewable energy experts were identified by a three-step peer nomination process (92% response rate). The experts stressed the conceptual foundations, economicmore » justifications, and the scientific and quantitative basics of renewable energy technology. The teachers focused on wood-burning technology, educational strategies, and the more popular alternative energy sources such as windpower, hydropower, photovoltaics, and biomass. The most emphatic contribution of the needs analysis was the experts' and teachers' shared perception that residential/commercial building design, retrofitting, and construction is the single most important practical, technical area for the application of renewable energy technology.« less

Operant models of relapse in zebrafish (Danio rerio): Resurgence, renewal, and reinstatement.

PubMed

Kuroda, Toshikazu; Mizutani, Yuto; Cançado, Carlos R X; Podlesnik, Christopher A

2017-09-29

Zebrafish are a widely used animal model in biomedical research, as an alternative to mammals, for having features such as a fully sequenced genome, high fecundity, and low-cost maintenance, but behavioral research with these fish remains scarce. The present study investigated whether zebrafish could be a new animal model for studies on the relapse of behavior (e.g., addiction and overeating) after the behavior has been extinguished. Specifically, we examined whether zebrafish would show three different types of relapse commonly studied with other species: resurgence, renewal, and reinstatement. For resurgence, a target response (i.e., approaching a sensor) was established by presenting a reinforcer (i.e., shrimp eggs) contingent upon the response in Phase 1; the target response was extinguished while introducing reinforcement for an alternative response in Phase 2; neither response produced the reinforcer in Phase 3. For renewal, a target response was established under Context A in Phase 1 and was extinguished under Context B in Phase 2; the fish were placed back in Context A in Phase 3, where extinction remained in effect. For reinstatement, a target response was established in Phase 1 and was extinguished in Phase 2; the reinforcer was presented independently of responding in Phase 3. Each type of relapse occurred in Phase 3. These results replicate and extend previous findings on relapse to a new species and suggest that zebrafish can be a useful animal model for studying the interactions of biological and environmental factors that lead to relapse. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Job stress, fatigue, and job dissatisfaction in Dutch lorry drivers: towards an occupation specific model of job demands and control

PubMed Central

de Croon, E M; Blonk, R; de Zwart, B C H; Frings-Dresen, M; Broersen, J

2002-01-01

Objectives: Building on Karasek's model of job demands and control (JD-C model), this study examined the effects of job control, quantitative workload, and two occupation specific job demands (physical demands and supervisor demands) on fatigue and job dissatisfaction in Dutch lorry drivers. Methods: From 1181 lorry drivers (adjusted response 63%) self reported information was gathered by questionnaire on the independent variables (job control, quantitative workload, physical demands, and supervisor demands) and the dependent variables (fatigue and job dissatisfaction). Stepwise multiple regression analyses were performed to examine the main effects of job demands and job control and the interaction effect between job control and job demands on fatigue and job dissatisfaction. Results: The inclusion of physical and supervisor demands in the JD-C model explained a significant amount of variance in fatigue (3%) and job dissatisfaction (7%) over and above job control and quantitative workload. Moreover, in accordance with Karasek's interaction hypothesis, job control buffered the positive relation between quantitative workload and job dissatisfaction. Conclusions: Despite methodological limitations, the results suggest that the inclusion of (occupation) specific job control and job demand measures is a fruitful elaboration of the JD-C model. The occupation specific JD-C model gives occupational stress researchers better insight into the relation between the psychosocial work environment and wellbeing. Moreover, the occupation specific JD-C model may give practitioners more concrete and useful information about risk factors in the psychosocial work environment. Therefore, this model may provide points of departure for effective stress reducing interventions at work. PMID:12040108

Job stress, fatigue, and job dissatisfaction in Dutch lorry drivers: towards an occupation specific model of job demands and control.

PubMed

de Croon, E M; Blonk, R W B; de Zwart, B C H; Frings-Dresen, M H W; Broersen, J P J

2002-06-01

Building on Karasek's model of job demands and control (JD-C model), this study examined the effects of job control, quantitative workload, and two occupation specific job demands (physical demands and supervisor demands) on fatigue and job dissatisfaction in Dutch lorry drivers. From 1181 lorry drivers (adjusted response 63%) self reported information was gathered by questionnaire on the independent variables (job control, quantitative workload, physical demands, and supervisor demands) and the dependent variables (fatigue and job dissatisfaction). Stepwise multiple regression analyses were performed to examine the main effects of job demands and job control and the interaction effect between job control and job demands on fatigue and job dissatisfaction. The inclusion of physical and supervisor demands in the JD-C model explained a significant amount of variance in fatigue (3%) and job dissatisfaction (7%) over and above job control and quantitative workload. Moreover, in accordance with Karasek's interaction hypothesis, job control buffered the positive relation between quantitative workload and job dissatisfaction. Despite methodological limitations, the results suggest that the inclusion of (occupation) specific job control and job demand measures is a fruitful elaboration of the JD-C model. The occupation specific JD-C model gives occupational stress researchers better insight into the relation between the psychosocial work environment and wellbeing. Moreover, the occupation specific JD-C model may give practitioners more concrete and useful information about risk factors in the psychosocial work environment. Therefore, this model may provide points of departure for effective stress reducing interventions at work.

Market Mechanism Design for Renewable Energy based on Risk Theory

NASA Astrophysics Data System (ADS)

Yang, Wu; Bo, Wang; Jichun, Liu; Wenjiao, Zai; Pingliang, Zeng; Haobo, Shi

2018-02-01

Generation trading between renewable energy and thermal power is an efficient market means for transforming supply structure of electric power into sustainable development pattern. But the trading is hampered by the output fluctuations of renewable energy and the cost differences between renewable energy and thermal power at present. In this paper, the external environmental cost (EEC) is defined and the EEC is introduced into the generation cost. At same time, the incentive functions of renewable energy and low-emission thermal power are designed, which are decreasing functions of EEC. On these bases, for the market risks caused by the random variability of EEC, the decision-making model of generation trading between renewable energy and thermal power is constructed according to the risk theory. The feasibility and effectiveness of the proposed model are verified by simulation results.

A comparison of multivariate and univariate time series approaches to modelling and forecasting emergency department demand in Western Australia.

PubMed

Aboagye-Sarfo, Patrick; Mai, Qun; Sanfilippo, Frank M; Preen, David B; Stewart, Louise M; Fatovich, Daniel M

2015-10-01

To develop multivariate vector-ARMA (VARMA) forecast models for predicting emergency department (ED) demand in Western Australia (WA) and compare them to the benchmark univariate autoregressive moving average (ARMA) and Winters' models. Seven-year monthly WA state-wide public hospital ED presentation data from 2006/07 to 2012/13 were modelled. Graphical and VARMA modelling methods were used for descriptive analysis and model fitting. The VARMA models were compared to the benchmark univariate ARMA and Winters' models to determine their accuracy to predict ED demand. The best models were evaluated by using error correction methods for accuracy. Descriptive analysis of all the dependent variables showed an increasing pattern of ED use with seasonal trends over time. The VARMA models provided a more precise and accurate forecast with smaller confidence intervals and better measures of accuracy in predicting ED demand in WA than the ARMA and Winters' method. VARMA models are a reliable forecasting method to predict ED demand for strategic planning and resource allocation. While the ARMA models are a closely competing alternative, they under-estimated future ED demand. Copyright © 2015 Elsevier Inc. All rights reserved.

Multikanban model for disassembly line with demand fluctuation

NASA Astrophysics Data System (ADS)

Udomsawat, Gun; Gupta, Surendra M.; Al-Turki, Yousef A. Y.

2004-02-01

In recent years, the continuous growth in consumer waste and dwindling natural resources has seriously threatened the environment. Realizing this, several countries have passed regulations that force manufacturers not only to manufacture environmentally conscious products, but also to take back their used products from consumers so that the components and materials recovered from the products may be reused and/or recycled. Disassembly plays an important role in product recovery. A disassembly line is perhaps the most suitable setting for disassembly of products in large quantities. Because a disassembly line has a tendency to generate excessive inventory, employing a kanban system can reduce the inventory level and let the system run more efficiently. A disassembly line is quite different from an assembly line. For example, not only can the demand arrive at the last station, it can also arrive at any of the other stations in the system. The demand for a component on the disassembly line could fluctuate widely. In fact, there are many other complicating matters that need to be considered to implement the concept of kanbans in such an environment. In this paper, we discuss the complications that are unique to a disassembly line. We discuss the complications in utilizing the conventional production control mechanisms in a disassembly line setting. We then show how to overcome them by implementing kanbans in a disassembly line setting with demand fluctuation and introduce the concept of multi-kanban mechanism. We demonstrate its effectiveness using a simulation model. An example is presented to illustrate the concept.

Solar energy demand (SED) of commodity life cycles.

PubMed

Rugani, Benedetto; Huijbregts, Mark A J; Mutel, Christopher; Bastianoni, Simone; Hellweg, Stefanie

2011-06-15

The solar energy demand (SED) of the extraction of 232 atmospheric, biotic, fossil, land, metal, mineral, nuclear, and water resources was quantified and compared with other energy- and exergy-based indicators. SED represents the direct and indirect solar energy required by a product or service during its life cycle. SED scores were calculated for 3865 processes, as implemented in the Ecoinvent database, version 2.1. The results showed that nonrenewable resources, and in particular minerals, formed the dominant contribution to SED. This large share is due to the indirect solar energy required to produce these resource inputs. Compared with other energy- and exergy-based indicators, SED assigns higher impact factors to minerals and metals and smaller impact factors to fossil energetic resources, land use, and nuclear energy. The highest differences were observed for biobased and renewable energy generation processes, whose relative contribution of renewable resources such as water, biomass, and land occupation was much lower in SED than in energy- and exergy-based indicators.

Talking Renewables; A renewable energy primer for everyone

NASA Astrophysics Data System (ADS)

Singh, Anirudh

2018-03-01

This book provides a clear and factual picture of the status of renewable energy and its capabilities today. The book covers all areas of renewable energy, starting from biomass energy and hydropower and proceeding to wind, solar and geothermal energy before ending with an overview of ocean energy. The book also explores how the technologies are being implemented today and takes a look at the future of renewable energy.

Coupling Agent-Based and Groundwater Modeling to Explore Demand Management Strategies for Shared Resources

NASA Astrophysics Data System (ADS)

Al-Amin, S.

2015-12-01

Municipal water demands in growing population centers in the arid southwest US are typically met through increased groundwater withdrawals. Hydro-climatic uncertainties attributed to climate change and land use conversions may also alter demands and impact the replenishment of groundwater supply. Groundwater aquifers are not necessarily confined within municipal and management boundaries, and multiple diverse agencies may manage a shared resource in a decentralized approach, based on individual concerns and resources. The interactions among water managers, consumers, and the environment influence the performance of local management strategies and regional groundwater resources. This research couples an agent-based modeling (ABM) framework and a groundwater model to analyze the effects of different management approaches on shared groundwater resources. The ABM captures the dynamic interactions between household-level consumers and policy makers to simulate water demands under climate change and population growth uncertainties. The groundwater model is used to analyze the relative effects of management approaches on reducing demands and replenishing groundwater resources. The framework is applied for municipalities located in the Verde River Basin, Arizona that withdraw groundwater from the Verde Formation-Basin Fill-Carbonate aquifer system. Insights gained through this simulation study can be used to guide groundwater policy-making under changing hydro-climatic scenarios for a long-term planning horizon.

EOQ model for perishable products with price-dependent demand, pre and post discounted selling price

NASA Astrophysics Data System (ADS)

Santhi, G.; Karthikeyan, K.

2017-11-01

In this article we introduce an economic order quantity model for perishable products like vegetables, fruits, milk, flowers, meat, etc.,with price-dependent demand, pre and post discounted selling price. Here we consider the demand is depending on selling price and deterioration rate is constant. Here we developed mathematical model to determine optimal discounton the unit selling price to maximize total profit. Numerical examples are given for illustrated.

A logistic regression approach to model the willingness of consumers to adopt renewable energy sources

NASA Astrophysics Data System (ADS)

Ulkhaq, M. M.; Widodo, A. K.; Yulianto, M. F. A.; Widhiyaningrum; Mustikasari, A.; Akshinta, P. Y.

2018-03-01

The implementation of renewable energy in this globalization era is inevitable since the non-renewable energy leads to climate change and global warming; hence, it does harm the environment and human life. However, in the developing countries, such as Indonesia, the implementation of the renewable energy sources does face technical and social problems. For the latter, renewable energy sources implementation is only effective if the public is aware of its benefits. This research tried to identify the determinants that influence consumers’ intention in adopting renewable energy sources. In addition, this research also tried to predict the consumers who are willing to apply the renewable energy sources in their houses using a logistic regression approach. A case study was conducted in Semarang, Indonesia. The result showed that only eight variables (from fifteen) that are significant statistically, i.e., educational background, employment status, income per month, average electricity cost per month, certainty about the efficiency of renewable energy project, relatives’ influence to adopt the renewable energy sources, energy tax deduction, and the condition of the price of the non-renewable energy sources. The finding of this study could be used as a basis for the government to set up a policy towards an implementation of the renewable energy sources.

Optimal Renewable Energy Integration into Refinery with CO2 Emissions Consideration: An Economic Feasibility Study

NASA Astrophysics Data System (ADS)

Alnifro, M.; Taqvi, S. T.; Ahmad, M. S.; Bensaida, K.; Elkamel, A.

2017-08-01

With increasing global energy demand and declining energy return on energy invested (EROEI) of crude oil, global energy consumption by the O&G industry has increased drastically over the past few years. In addition, this energy increase has led to an increase GHG emissions, resulting in adverse environmental effects. On the other hand, electricity generation through renewable resources have become relatively cost competitive to fossil based energy sources in a much ‘cleaner’ way. In this study, renewable energy is integrated optimally into a refinery considering costs and CO2 emissions. Using Aspen HYSYS, a refinery in the Middle East was simulated to estimate the energy demand by different processing units. An LP problem was formulated based on existing solar energy systems and wind potential in the region. The multi-objective function, minimizing cost as well as CO2 emissions, was solved using GAMS to determine optimal energy distribution from each energy source to units within the refinery. Additionally, an economic feasibility study was carried out to determine the viability of renewable energy technology project implementation to overcome energy requirement of the refinery. Electricity generation through all renewable energy sources considered (i.e. solar PV, solar CSP and wind) were found feasible based on their low levelized cost of electricity (LCOE). The payback period for a Solar CSP project, with an annual capacity of about 411 GWh and a lifetime of 30 years, was found to be 10 years. In contrast, the payback period for Solar PV and Wind were calculated to be 7 and 6 years, respectively. This opens up possibilities for integrating renewables into the refining sector as well as optimizing multiple energy carrier systems within the crude oil industry

Sustainability of biofuels and renewable chemicals production from biomass.

PubMed

Kircher, Manfred

2015-12-01

In the sectors of biofuel and renewable chemicals the big feedstock demand asks, first, to expand the spectrum of carbon sources beyond primary biomass, second, to establish circular processing chains and, third, to prioritize product sectors exclusively depending on carbon: chemicals and heavy-duty fuels. Large-volume production lines will reduce greenhouse gas (GHG) emission significantly but also low-volume chemicals are indispensable in building 'low-carbon' industries. The foreseeable feedstock change initiates innovation, securing societal wealth in the industrialized world and creating employment in regions producing biomass. When raising the investments in rerouting to sustainable biofuel and chemicals today competitiveness with fossil-based fuel and chemicals is a strong issue. Many countries adopted comprehensive bioeconomy strategies to tackle this challenge. These public actions are mostly biased to biofuel but should give well-balanced attention to renewable chemicals as well. Copyright © 2015 Elsevier Ltd. All rights reserved.

Improving cost-effectiveness and mitigating risks of renewable energy requirements

NASA Astrophysics Data System (ADS)

Griffin, James P.

Policy makers at the federal and state levels of government are debating actions to reduce U.S. greenhouse gas emissions and dependence on oil as an energy source. Several concerns drive this debate: sharp rises in energy prices, increasing unease about the risks of climate change, energy security, and interest in expanding the domestic renewable energy industry. Renewable energy requirements are frequently proposed to address these concerns, and are currently in place, in various forms, at the federal and state levels of government. These policies specify that a certain portion of the energy supply come from renewable energy sources. This dissertation focuses on a specific proposal, known as 25 X 25, which requires 25% of electricity and motor vehicle transportation fuels supplied to U.S. consumers to come from renewable energy sources, such as wind power and ethanol, by 2025. This dissertation builds on prior energy policy analysis, and more specifically analyses of renewable energy requirements, by assessing the social welfare implications of a 25 x 25 policy and applying new methods of uncertainty analysis to multiple policy options decision makers can use to implement the policy. These methods identify policy options that can improve the cost-effectiveness and reduce the risks of renewable energy requirements. While the dissertation focuses on a specific policy, the research methods and findings are applicable to other renewable energy requirement policies. In the dissertation, I analyze six strategies for implementing a 25 x 25 policy across several hundred scenarios that represent plausible futures for uncertainties in energy markets, such as renewable energy costs, energy demand, and fossil fuel prices. The strategies vary in the availability of resources that qualify towards the policy requirement and the use of a "safety valve" that allows refiners and utilities to pay a constant fee after renewable energy costs reach a predetermined threshold. I test

Heat demand mapping and district heating grid expansion analysis: Case study of Velika Gorica

NASA Astrophysics Data System (ADS)

Dorotić, Hrvoje; Novosel, Tomislav; Duić, Neven; Pukšec, Tomislav

2017-10-01

Highly efficient cogeneration and district heating systems have a significant potential for primary energy savings and the reduction of greenhouse gas emissions through the utilization of a waste heat and renewable energy sources. These potentials are still highly underutilized in most European countries. They also play a key role in the planning of future energy systems due to their positive impact on the increase of integration of intermittent renewable energy sources, for example wind and solar in a combination with power to heat technologies. In order to ensure optimal levels of district heating penetration into an energy system, a comprehensive analysis is necessary to determine the actual demands and the potential energy supply. Economical analysis of the grid expansion by using the GIS based mapping methods hasn't been demonstrated so far. This paper presents a heat demand mapping methodology and the use of its output for the district heating network expansion analysis. The result are showing that more than 59% of the heat demand could be covered by the district heating in the city of Velika Gorica, which is two times more than the present share. The most important reason of the district heating's unfulfilled potential is already existing natural gas infrastructure.

Simulated thermal energy demand and actual energy consumption in refurbished and non-refurbished buildings

NASA Astrophysics Data System (ADS)

Ilie, C. A.; Visa, I.; Duta, A.

2016-08-01

The EU legal frame imposes the Nearly Zero Energy Buildings (nZEB) status to any new public building starting with January 1st, 2019 and for any other new building starting with 2021. Basically, nZEB represents a Low Energy Building (LEB) that covers more than half of the energy demand by using renewable energy systems installed on or close to it. Thus, two steps have to be followed in developing nZEB: (1) reaching the LEB status through state- of-the art architectural and construction solutions (for the new buildings) or through refurbishing for the already existent buildings, followed by (2) implementing renewables; in Romania, over 65% of the energy demand in a building is directly linked to heating, domestic hot water (DHW), and - in certain areas - for cooling. Thus, effort should be directed to reduce the thermal energy demand to be further covered by using clean and affordable systems: solar- thermal systems, heat pumps, biomass, etc. or their hybrid combinations. Obviously this demand is influenced by the onsite climatic profile and by the building performance. An almost worst case scenario is approached in the paper, considering a community implemented in a mountain area, with cold and long winters and mild summers (Odorheiul Secuiesc city, Harghita county, Romania). Three representative types of buildings are analysed: multi-family households (in blocks of flats), single-family houses and administrative buildings. For the first two types, old and refurbished buildings were comparatively discussed.

An Econometric Model of Healthcare Demand With Nonlinear Pricing.

PubMed

Kunz, Johannes S; Winkelmann, Rainer

2017-06-01

From 2004 to 2012, the German social health insurance levied a co-payment for the first doctor visit in a calendar quarter. We develop a new model for estimating the effect of such a co-payment on the individual number of visits per quarter. The model combines a one-time increase in the otherwise constant hazard rate determining the timing of doctor visits with a difference-in-differences strategy to identify the reform effect. An extended version of the model accounts for a mismatch between reporting period and calendar quarter. Using data from the German Socio-Economic Panel, we do not find an effect of the co-payment on demand for doctor visits. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Modeling the Trajectory of Analgesic Demand Over Time After Total Knee Arthroplasty Using the Latent Curve Analysis.

PubMed

Lo, Po-Han; Tsou, Mei-Yung; Chang, Kuang-Yi

2015-09-01

Patient-controlled epidural analgesia (PCEA) is commonly used for pain relief after total knee arthroplasty (TKA). This study aimed to model the trajectory of analgesic demand over time after TKA and explore its influential factors using latent curve analysis. Data were retrospectively collected from 916 patients receiving unilateral or bilateral TKA and postoperative PCEA. PCEA demands during 12-hour intervals for 48 hours were directly retrieved from infusion pumps. Potentially influential factors of PCEA demand, including age, height, weight, body mass index, sex, and infusion pump settings, were also collected. A latent curve analysis with 2 latent variables, the intercept (baseline) and slope (trend), was applied to model the changes in PCEA demand over time. The effects of influential factors on these 2 latent variables were estimated to examine how these factors interacted with time to alter the trajectory of PCEA demand over time. On average, the difference in analgesic demand between the first and second 12-hour intervals was only 15% of that between the first and third 12-hour intervals. No significant difference in PCEA demand was noted between the third and fourth 12-hour intervals. Aging tended to decrease the baseline PCEA demand but body mass index and infusion rate were positively correlated with the baseline. Only sex significantly affected the trend parameter and male individuals tended to have a smoother decreasing trend of analgesic demands over time. Patients receiving bilateral procedures did not consume more analgesics than their unilateral counterparts. Goodness of fit analysis indicated acceptable model fit to the observed data. Latent curve analysis provided valuable information about how analgesic demand after TKA changed over time and how patient characteristics affected its trajectory.

A Review of Barriers to and Opportunities for the Integration of Renewable Energy in the Southeast

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

McConnell, Ben W; Hadley, Stanton W; Xu, Yan

2011-08-01

methods and the status of renewable resources, chapters devoted to each identified renewable resource, and a brief summary chapter. Chapter 2 on analysis methods and status summarizes the benefits of integrating renewable energy resources in the Southeast. The utilization of the existing fuels, both the fossil fuels and the renewable energy resources, is evaluated. The financial rewards of renewable resources are listed, which includes the amount of fuel imported from outside the Southeast to find the net benefit of local renewable generation, and both the typical and new green job opportunities that arise from renewable generation in the Southeast. With the load growth in the Southeast, the growth of transmission and fossil fuel generation may not meet the growing demands for energy. The load growth is estimated, and the benefits of renewable resources for solving local growing energy demands are evaluated. Chapters 3-7 discuss the key renewable energy resources in the Southeast. Six resources available in this region that are discussed are (1) wind, including both onshore and offshore; (2) solar, including passive, photovoltaic, and concentrating; (3) biomass energy, including switchgrass, biomass co-firing, wood, woody biomass, wood industry by-products (harvesting residues, mill waste, etc.), agricultural byproducts, landfill gas to energy and anaerobic digester gas; (4) hydro; and (5) geothermal. Because of limited development, ocean wave and tidal were not considered to be available in significant quantity before 2030 and are not presented in the final analysis. Estimates on the location of potential megawatt generation from these renewable resources in the Southeast are made. Each chapter will describe the existing base of the renewable electricity installations in the region now and, when available, the base of the existing manufacturing capacity in the region for renewable energy resources hardware and software. The possible barriers and considerations for

Harvesting and replenishment policies for renewable natural resources

USGS Publications Warehouse