Science.gov

Sample records for renewal demand models

  1. Renewable energy: GIS-based mapping and modelling of potentials and demand

    NASA Astrophysics Data System (ADS)

    Blaschke, Thomas; Biberacher, Markus; Schardinger, Ingrid.; Gadocha, Sabine; Zocher, Daniela

    2010-05-01

    Worldwide demand of energy is growing and will continue to do so for the next decades to come. IEA has estimated that global primary energy demand will increase by 40 - 50% from 2003 to 2030 (IEA, 2005) depending on the fact whether currently contemplated energy policies directed towards energy-saving and fuel-diversification will be effectuated. The demand for Renewable Energy (RE) is undenied but clear figures and spatially disaggregated potentials for the various energy carriers are very rare. Renewable Energies are expected to reduce pressures on the environment and CO2 production. In several studies in Germany (North-Rhine Westphalia and Lower Saxony) and Austria we studied the current and future pattern of energy production and consumption. In this paper we summarize and benchmark different RE carriers, namely wind, biomass (forest and non-forest, geothermal, solar and hydro power. We demonstrate that GIS-based scalable and flexible information delivery sheds new light on the prevailing metaphor of GIS as a processing engine serving needs of users more on demand rather than through ‘maps on stock'. We compare our finding with those of several energy related EU-FP7 projects in Europe where we have been involved - namely GEOBENE, REACCESS, ENERGEO - and demonstrate that more and more spatial data will become available together with tools that allow experts to do their own analyses and to communicate their results in ways which policy makers and the public can readily understand and use as a basis for their own actions. Geoportals in combination with standardised geoprocessing today supports the older vision of an automated presentation of data on maps, and - if user privileges are given - facilities to interactively manipulate these maps. We conclude that the most critical factor in modelling energy supply and demand remain the economic valuation of goods and services, especially the forecast of future end consumer energy costs.

  2. A Test Bed for Self-regulating Distribution Systems: Modeling Intergrated Renewable Energy and Demand Response in the GridLAB-D/MATLAB Environment

    SciTech Connect

    Wang, Dan; de Wit, Braydon; Parkinson, Simon; Fuller, Jason C.; Chassin, David P.; Crawford, Curran; Djilali, Ned

    2012-01-16

    This paper discusses the development of a simulation test bed permitting the study of integrated renewable energy generators and controlled distributed heat pumps operating within distribution systems. The test bed is demonstrated in this paper by addressing the important issue of the self-regulating effect of consumer-owned air-source heat pumps on the variability induced by wind power integration, particularly when coupled with increased access to demand response realized through a centralized load control strategy.

  3. Grid Integration of Aggregated Demand Response, Part 2: Modeling Demand Response in a Production Cost Model

    SciTech Connect

    Hummon, Marissa; Palchak, David; Denholm, Paul; Jorgenson, Jennie; Olsen, Daniel J.; Kiliccote, Sila; Matson, Nance; Sohn, Michael; Rose, Cody; Dudley, Junqiao; Goli, Sasank; Ma, Ookie

    2013-12-01

    This report is one of a series stemming from the U.S. Department of Energy (DOE) Demand Response and Energy Storage Integration Study. This study is a multi-national-laboratory effort to assess the potential value of demand response (DR) and energy storage to electricity systems with different penetration levels of variable renewable resources and to improve our understanding of associatedmarkets and institutions. This report implements DR resources in the commercial production cost model PLEXOS.

  4. 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.

  5. 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.

  6. Preliminary Examination of the Supply and Demand Balance for Renewable Electricity

    SciTech Connect

    Swezey, B.; Aabakken, J.; Bird, L.

    2007-10-01

    In recent years, the demand for renewable electricity has accelerated as a consequence of state and federal policies and the growth of voluntary green power purchase markets, along with the generally improving economics of renewable energy development. This paper reports on a preliminary examination of the supply and demand balance for renewable electricity in the United States, with a focus on renewable energy projects that meet the generally accepted definition of "new" for voluntary market purposes, i.e., projects installed on or after January 1, 1997. After estimating current supply and demand, this paper presents projections of the supply and demand balance out to 2010 and describe a number of key market uncertainties.

  7. Renewable Electricity Futures Study. Volume 3: End-Use Electricity Demand

    SciTech Connect

    Hostick, D.; Belzer, D.B.; Hadley, S.W.; Markel, T.; Marnay, C.; Kintner-Meyer, M.

    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 future 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).

  8. Renewable Electricity Futures Study. Volume 3. End-Use Electricity Demand

    SciTech Connect

    Hostick, Donna; Belzer, David B.; Hadley, Stanton W.; Markel, Tony; Marnay, Chris; Kintner-Meyer, Michael

    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 future 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/

  9. Modeling renewable energy resources in integrated resource planning

    SciTech Connect

    Logan, D.; Neil, C.; Taylor, A.

    1994-06-01

    Including renewable energy resources in integrated resource planning (IRP) requires that utility planning models properly consider the relevant attributes of the different renewable resources in addition to conventional supply-side and demand-side options. Otherwise, a utility`s resource plan is unlikely to have an appropriate balance of the various resource options. The current trend toward regulatory set-asides for renewable resources is motivated in part by the perception that the capabilities of current utility planning models are inadequate with regard to renewable resources. Adequate modeling capabilities and utility planning practices are a necessary prerequisite to the long-term penetration of renewable resources into the electric utility industry`s resource mix. This report presents a review of utility planning models conducted for the National Renewable Energy Laboratory (NREL). The review examines the capabilities of utility planning models to address key issues in the choice between renewable resources and other options. The purpose of this review is to provide a basis for identifying high priority areas for advancing the state of the art.

  10. Evaluation of tools for renewable energy policy analysis: The renewable energy penetration model

    SciTech Connect

    Engle, J.

    1994-04-01

    The Energy Policy Act of 1992 establishes a program to support development of renewable energy technologies including a production incentive to public power utilities. Because there is a wide range of possible policy actions that could be taken to increase electric market share for renewables, modeling tools are needed to help make informed decisions regarding future policy. Previous energy modeling tools did not contain the regional or infrastructure focus necessary to examine renewable technologies. As a result, the Department of Energy Office of Utility Technologies (OUT) supported the development of tools for renewable energy policy analysis. Three models were developed: The Renewable Energy Penetration (REP) model, which is a spreadsheet model for determining first-order estimates of policy effects for each of the ten federal regions; the Ten Federal Region Model (TFRM), which employs utility capacity expansion and dispatching decisions; and the Regional Electric Policy Analysis Model (REPAM) which was constructed to allow detailed insight into interactions between policy and technology within an individual region. In 1993, the OUT supported the Oak Ridge Institute of Science and Education (ORISE) to form an expert panel to provide an independent review of the REP model and TFRM. This report contains the panel`s evaluation of the REP model; the TFRM is evaluated in a companion report. The panel did not review the REPAM. The panel met for a second time in January 1994 to discuss model simulations and deliberate regarding evaluation outcomes. This report is largely a result of this second meeting. The remainder of this chapter provides a description of the REP model and summarizes the panel`s findings. Individual chapters examine various aspects of the model: demand and load, capacity expansion, dispatching and production costing, reliability, renewables, storage, transmission, financial and regulatory concerns, and environmental effects.

  11. Green marketing, renewables, and free riders: increasing customer demand for a public good

    SciTech Connect

    Wiser, R.; Pickle, S.

    1997-09-01

    Retail electricity competition will allow customers to select their own power suppliers and some customers will make purchase decisions based, in part, on their concern for the environment. Green power marketing targets these customers under the assumption that they will pay a premium for ``green`` energy products such as renewable power generation. But renewable energy is not a traditional product because it supplies public goods; for example, a customer supporting renewable energy is unable to capture the environmental benefits that their investment provides to non-participating customers. As with all public goods, there is a risk that few customers will purchase ``green`` power and that many will instead ``free ride`` on others` participation. By free riding, an individual is able to enjoy the benefits of the public good while avoiding payment. This report reviews current green power marketing activities in the electric industry, introduces the extensive academic literature on public goods, free riders, and collective action problems, and explores in detail the implications of this literature for the green marketing of renewable energy. Specifically, the authors highlight the implications of the public goods literature for green power product design and marketing communications strategies. They emphasize four mechanisms that marketers can use to increase customer demand for renewable energy. Though the public goods literature can also contribute insights into the potential rationale for renewable energy policies, they leave most of these implications for future work (see Appendix A for a possible research agenda).

  12. 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.

  13. 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…

  14. Evaluating the sustainability of an energy supply system using renewable energy sources: An energy demand assessment of South Carolina

    NASA Astrophysics Data System (ADS)

    Green, Cedric Fitzgerald

    Sustainable energy is defined as a dynamic harmony between the equitable availability of energy-intensive goods and services to all people and the preservation of the earth for future generations. Sustainable energy development continues to be a major focus within the government and regulatory governing bodies in the electric utility industry. This is as a result of continued demand for electricity and the impact of greenhouse gas emissions from electricity generating plants on the environment by way of the greenhouse effect. A culmination of increasing concerns about climate change, the nuclear incident in Fukushima four years ago, and discussions on energy security in a world with growing energy demand have led to a movement for increasing the share of power generation from renewable energy sources. This work studies demand for electricity from primarily residential, commercial, agricultural, and industrial customers in South Carolina (SC) and its effect on the environment from coal-fired electricity generating plants. Moreover, this work studies sustainable renewable energy source-options based on the renewable resources available in the state of SC, as viable options to supplement generation from coal-fired electricity generating plants. In addition, greenhouse gas emissions and other pollutants from primarily coal-fired plants will be defined and quantified. Fundamental renewable energy source options will be defined and quantified based on availability and sustainability of SC's natural resources. This work studies the environmental, economic, and technical aspects of each renewable energy source as a sustainable energy option to replace power generation from coal-fired plants. Additionally, social aspect implications will be incorporated into each of the three aspects listed above, as these aspects are explored during the research and analysis. Electricity demand data and alternative energy source-supply data in SC are carried out and are used to develop and

  15. Examination of the Regional Supply and Demand Balance for Renewable Electricity in the United States through 2015: Projecting from 2009 through 2015 (Revised)

    SciTech Connect

    Bird, L.; Hurlbut, D.; Donohoo, P.; Cory, K.; Kreycik, C.

    2010-06-01

    This report examines the balance between the demand and supply of new renewable electricity in the United States on a regional basis through 2015. It expands on a 2007 NREL study that assessed the supply and demand balance on a national basis. As with the earlier study, this analysis relies on estimates of renewable energy supplies compared to demand for renewable energy generation needed to meet existing state renewable portfolio standard (RPS) policies in 28 states, as well as demand by consumers who voluntarily purchase renewable energy. However, it does not address demand by utilities that may procure cost-effective renewables through an integrated resource planning process or otherwise.

  16. REGIONAL RECREATION DEMAND AND BENEFITS MODEL

    EPA Science Inventory

    This report describes a regional recreation demand and benefits model that is used to estimate recreation demand and value (consumers' surplus) of four activities at each of 195 sites in Washington, Oregon, Idaho, and western Montana. The recreation activities considered are camp...

  17. Prospects of Renewable Energy for Meeting Growing Electricity Demand in Pakistan

    NASA Astrophysics Data System (ADS)

    Uqaili, Mohammad Aslam; Harijan, Khanji; Memon, Mujeebuddin

    2007-10-01

    Pakistan is an energy deficit country. About half of the country's population has access to electricity and per capita supply is only 520 kWh. Majority of the country's population resides in rural areas and most of them are yet without electricity. Conventional electricity generation includes 66.8% thermal, 30% hydel and 3.3% nuclear. It has been projected that electricity demand in Pakistan will increase in the range of 12 MTOE to 17 MTOE by the year 2018, at an average growth rate of about 5% to 7% and will require installed capacity of about 35 GW to 50 GW. Indigenous reserves of oil and gas are limited and the country heavily depends on imported oil. Thermal power generation on the other hand also pollutes the environment. This paper presents the availability of renewables such as hydel, solar, wind and biomass energy, and their prospects for meeting growing electricity demand in Pakistan and subsequent contribution in air pollution abatement. The study concludes that there is substantial potential of these renewables and they have also bright prospects for meeting growing electricity demand in Pakistan.

  18. Flow based vs. demand based energy-water modelling

    NASA Astrophysics Data System (ADS)

    Rozos, Evangelos; Nikolopoulos, Dionysis; Efstratiadis, Andreas; Koukouvinos, Antonios; Makropoulos, Christos

    2015-04-01

    The water flow in hydro-power generation systems is often used downstream to cover other type of demands like irrigation and water supply. However, the typical case is that the energy demand (operation of hydro-power plant) and the water demand do not coincide. Furthermore, the water inflow into a reservoir is a stochastic process. Things become more complicated if renewable resources (wind-turbines or photovoltaic panels) are included into the system. For this reason, the assessment and optimization of the operation of hydro-power systems are challenging tasks that require computer modelling. This modelling should not only simulate the water budget of the reservoirs and the energy production/consumption (pumped-storage), but should also take into account the constraints imposed by the natural or artificial water network using a flow routing algorithm. HYDRONOMEAS, for example, uses an elegant mathematical approach (digraph) to calculate the flow in a water network based on: the demands (input timeseries), the water availability (simulated) and the capacity of the transmission components (properties of channels, rivers, pipes, etc.). The input timeseries of demand should be estimated by another model and linked to the corresponding network nodes. A model that could be used to estimate these timeseries is UWOT. UWOT is a bottom up urban water cycle model that simulates the generation, aggregation and routing of water demand signals. In this study, we explore the potentials of UWOT in simulating the operation of complex hydrosystems that include energy generation. The evident advantage of this approach is the use of a single model instead of one for estimation of demands and another for the system simulation. An application of UWOT in a large scale system is attempted in mainland Greece in an area extending over 130×170 km². The challenges, the peculiarities and the advantages of this approach are examined and critically discussed.

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

    SciTech Connect

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

    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 methods presented.

  20. Impacts of Western Area Power Administration`s power marketing alternatives on utility demand-side management and conservation and renewable energy programs

    SciTech Connect

    Cavallo, J.D.; Germer, M.F.; Tompkins, M.M.

    1995-03-01

    The Western Area Power Administration (Western) requires all of its long-term firm power customers to implement programs that promote the conservation of electric energy or facilitate the use of renewable energy resources. Western has also proposed that all customers develop integrated resource plans that include cost-effective demand-side management programs. As part of the preparation of Western`s Electric Power Marketing Environmental Impact Statement, Argonne National Laboratory (ANL) developed estimates of the reductions in energy demand resulting from Western`s conservation and renewable energy activities in its Salt Lake City Area Office. ANL has also estimated the energy-demand reductions from cost-effective, demand-side management programs that could be included in the integrated resource plans of the customers served by Western`s Salt Lake City Area Office. The results of this study have been used to adjust the expected hourly demand for Western`s major systems in the Salt Lake City Area. The expected hourly demand served as the basis for capacity expansion plans develops with ANL`s Production and Capacity Expansion (PACE) model.

  1. 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.

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

    DOE PAGESBeta

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

    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

  3. Taxonomy for Modeling Demand Response Resources

    SciTech Connect

    Olsen, Daniel; Kiliccote, Sila; Sohn, Michael; Dunn, Laura; Piette, Mary, A

    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 a 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.

  4. Integration of Renewables Via Demand Management: Highly Dispatchable and Distributed Demand Response for the Integration of Distributed Generation

    SciTech Connect

    2012-02-11

    GENI Project: AutoGrid, in conjunction with Lawrence Berkeley National Laboratory and Columbia University, will design and demonstrate automated control software that helps manage real-time demand for energy across the electric grid. Known as the Demand Response Optimization and Management System - Real-Time (DROMS-RT), the software will enable personalized price signal to be sent to millions of customers in extremely short timeframes—incentivizing them to alter their electricity use in response to grid conditions. This will help grid operators better manage unpredictable demand and supply fluctuations in short time-scales —making the power generation process more efficient and cost effective for both suppliers and consumers. DROMS-RT is expected to provide a 90% reduction in the cost of operating demand response and dynamic pricing Projects in the U.S.

  5. 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.

  6. Modeling Renewable Water Resources under Climate Change

    NASA Astrophysics Data System (ADS)

    Liu, X.; Tang, Q.

    2014-12-01

    The impacts of climate change on renewable water resources are usually assessed using hydrological models driven by downscaled climate outputs from global climate models. Most hydrological models do not have explicit parameterization of vegetation and thus are unable to assess the effects of elevated atmospheric CO2 on stomatal conductance and water loss of leaf. The response of vegetation to elevated atmospheric CO2 would reduce evaporation and affect runoff and renewable water resources. To date, the impacts of elevated CO2 on vegetation transpiration were not well addressed in assessment of water resources under climate change. In this study, the distributed biosphere-hydrological (DBH) model, which incorporates a simple biosphere model into a distributed hydrological scheme, was used to assess the impacts of elevated CO2 on vegetation transpiration and consequent runoff. The DBH model was driven by five General Circulation Models (GCMs) under four Representative Concentration Pathways (RCPs). For each climate scenario, two model experiments were conducted. The atmospheric CO2 concentration in one experiment was assumed to remain at the level of 2000 and increased as described by the RCPs in the other experiment. The results showed that the elevated CO2 would result in decrease in evapotranspiration, increase in runoff, and have considerable impacts on water resources. However, CO2 induced runoff change is generally small in dry areas likely because vegetation is usually sparse in the arid area.

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

    SciTech Connect

    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, 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.

  8. 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

  9. 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)

  10. 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)

  11. Model documentation: Renewable Fuels Module of the National Energy Modeling System

    SciTech Connect

    Not Available

    1994-04-01

    This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it related to the production of the 1994 Annual Energy Outlook (AEO94) 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. This documentation report serves two purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. 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. Of these six, four are documented in the following chapters: municipal solid waste, wind, solar and biofuels. Geothermal and wood are not currently working components of NEMS. The purpose of the RFM is to define the technological and cost characteristics of renewable energy technologies, and to pass these characteristics to other NEMS modules for the determination of mid-term forecasted renewable energy demand.

  12. A Simultaneous Model of Education Supply and Demand.

    ERIC Educational Resources Information Center

    McNamara, Kevin T.; And Others

    An economic model of educational supply and demand was tested using cross-sectional data for the 95 Virginia county school districts. Three equations were hypothesized: (1) the quantity supply functions; (2) the quantity demand function; and (3) the quality demand function. The variables in the equations are education expenditures, percent of 9th…

  13. Impact of the renewable oxygenate standard for reformulated gasoline on ethanol demand, energy use, and greenhouse gas emissions

    SciTech Connect

    Stork, K.C.; Singh, M.K.

    1995-04-01

    To assure a place for renewable oxygenates in the national reformulated gasoline (RFG) program, the US Environmental Protection Agency has promulgated the renewable oxygenate standard (ROS) for RFG. It is assumed that ethanol derived from corn will be the only broadly available renewable oxygenate during Phase I of the RFG program. This report analyzes the impact that the ROS could have on the supply of ethanol, its transported volume, and its displacement from existing markets. It also considers the energy and crude oil consumption and greenhouse gas (GHG) emissions that could result from the production and use of various RFGs that could meet the ROS requirements. The report concludes that on the basis of current and projected near-term ethanol capacity, if ethanol is the only available renewable oxygenate used to meet the requirements of the ROS, diversion of ethanol from existing use as a fuel is likely to be necessary. Year-round use of ethanol and ETBE would eliminate the need for diversion by reducing winter demand for ethanol. On an RFG-program-wide basis, using ethanol and ETBE to satisfy the ROS can be expected to slightly reduce fossil energy use, increase crude oil use, and have essentially no effect on GHG emissions or total energy use relative to using RFG oxygenated only with MTBE.

  14. Renewable Energy and Efficiency Modeling Analysis Partnership: An Analysis of How Different Energy Models Addressed a Common High Renewable Energy Penetration Scenario in 2025

    SciTech Connect

    Blair, N.; Jenkin, T.; Milford, J.; Short, W.; Sullivan, P.; Evans, D.; Lieberman, E.; Goldstein, G.; Wright, E.; Jayaraman, K.; Venkatech, B.; Kleiman, G.; Namovicz, C.; Smith, B.; Palmer, K.; Wiser, R.; Wood, F.

    2009-09-30

    /or different answers in response to a set of focused energy-related questions. The focus was on understanding reasons for model differences, not on policy implications, even though a policy of high renewable penetration was used for the analysis. A group process was used to identify the potential question (or questions) to be addressed through the project. In late 2006, increasing renewable energy penetration in the electricity sector was chosen from among several options as the general policy to model. From this framework, the analysts chose a renewable portfolio standard (RPS) as the way to implement the required renewable energy market penetration in the models. An RPS was chosen because it was (i) of interest and represented the group's consensus choice, and (ii) tractable and not too burdensome for the modelers. Because the modelers and analysts were largely using their own resources, it was important to consider the degree of effort required. In fact, several of the modelers who started this process had to discontinue participation because of other demands on their time. Federal and state RPS policy is an area of active political interest and debate. Recognizing this, participants used this exercise to gain insight into energy model structure and performance. The results are not intended to provide any particular insight into policy design or be used for policy advocacy, and participants are not expected to form a policy stance based on the outcomes of the modeling. The goals of this REMAP project - in terms of the main topic of renewable penetration - were to: (1) Compare models and understand why they may give different results to the same question, (2) Improve the rigor and consistency of assumptions used across models, and (3) Evaluate the ability of models to measure the impacts of high renewable-penetration scenarios.

  15. Residential end use demand modeling: Improvements to the ORNL model

    NASA Astrophysics Data System (ADS)

    McMahon, J. E.

    1981-10-01

    The ORNL/LBL Residential Energy Demand Model incorporated major improvements in three areas: efficiency of appliances, current construction practice in new houses, and appliance retirements. The new methodology is more general, and provides energy demand estimates in better agreement with recent data. Key areas for future improvements are indicated, including: quantifying the uncertainty in model simulation, redefining the set of end uses, updating the algorithm, and broadening the model's applicability to different geographic areas. A US Department of Energy survey of appliance manufacturers was used to determine new appliance efficiencies. Similarly, surveys of current housing practices (e.g., ceiling insulation level) were used to estimate changes in heating and cooling energy requirements. Appliances are assumed to retire as a function of their age.

  16. 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

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

    SciTech Connect

    Broeer, Torsten; Fuller, Jason C.; Tuffner, Francis K.; Chassin, David P.; Djilali, Ned

    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 generator 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.

  18. The interpersonal process model of demand/withdraw behavior.

    PubMed

    Baucom, Brian R; Dickenson, Janna A; Atkins, David C; Baucom, Donald H; Fischer, Melanie S; Weusthoff, Sarah; Hahlweg, Kurt; Zimmermann, Tanja

    2015-02-01

    The demand/withdraw interaction pattern is a destructive cycle of relationship communication behavior that is associated with negative individual and relationship outcomes. Demand/withdraw behavior is thought to be strongly linked to partners' emotional reactions, but current theories are inconsistent with empirical findings. The current study proposes the interpersonal process model of demand/withdraw behavior, which includes linkages between each partners' emotional reactions and the interpersonal behavior of demanding and withdrawing. Data come from problem solving discussions of 55 German couples with observationally coded demand/withdraw behavior and fundamental frequency (f₀) to measure vocally encoded emotional arousal. Actor-partner interdependence models (Kenny, Kashy, & Cook, 2006) were used to examine associations among demand/withdraw behavior and f₀ in the overall discussion and 5-min segments. Significant cross-partner associations emerged for demanding and withdrawing behavior across the whole conversation as well as within 5-min segments, and these associations are partially accounted for by each individual's f₀. When behaviorally coded demanders expressed more vocal arousal, they demanded more and withdrew less while their partners withdrew more. In contrast, when behaviorally coded withdrawers expressed more vocal arousal, their partners demanded less and withdrew more. Findings demonstrate that demand/withdraw behavior varies between couples (i.e., some couples engage in a stronger demand/withdraw cycle than others) and between segments (i.e., when 1 partner increases demanding, the other increases withdrawing). Findings support key elements of the interpersonal process model, showing intra- and interpersonal pathways linking demand/withdraw behavior and emotion and demonstrate the importance of partners' behavioral roles in these linkages. PMID:25495639

  19. RESRO: A spatio-temporal model to optimise regional energy systems emphasising renewable energies

    NASA Astrophysics Data System (ADS)

    Hausl, S.; Biberacher, M.; Gadocha, S.

    2012-10-01

    RESRO (Reference Energy System Regional Optimization) optimises the simultaneous fulfilment of the heat and power demand in regional energy systems. It is a mixed-integer program realised in the modelling language GAMS. The model handles information on geographically disaggregated data describing heat demand and renewable energy potentials (e.g. biomass, solar energy, ambient heat). Power demand is handled spatially aggregated in an hourly time resolution within 8 type days. The major idea is to use a high-spatial, low-temporal heat resolution and a low-spatial, hightemporal power resolution with both demand levels linked with each other. Due to high transport losses the possibilities for heat transport over long distances are unsatisfying. Thus, the spatial, raster-based approach is used to identify and utilise renewable energy resources for heat generation close to the customers as well as to optimize district heating grids and related energy flows fed by heating plants or combined heat and power (CHP) plants fuelled by renewables. By combining the heat and electricity sector within the model, it is possible to evaluate relationships between these energy fields such as the use of CHP or heat pump technologies and also to examine relationships between technologies such as solar thermal and photovoltaic facilities, which are in competition for available, suitable roof or ground areas.

  20. 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.

  1. 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.

  2. IDES: an integrated demand and energy supply equilibrium model. [IDES

    SciTech Connect

    Macal, C.M.

    1985-01-01

    The IDES (Integrated Demand and Energy Supply) Model is a price-quantity equilibrium model similar to the Long-Term Energy Analysis Package (LEAP) for projecting energy quantities and prices over a 30-year time horizon. The model integrates resource production activities, petroleum refining, electricity generation, fuel processing, and demand modules. The design objectives, mathematical formulation, iterative solution algorithm, and computer implementation are described in this paper.

  3. MODELING THE DEMAND FOR E85 IN THE UNITED STATES

    SciTech Connect

    Liu, Changzheng; Greene, David L

    2013-10-01

    How demand for E85 might evolve in the future in response to changing economics and policies is an important subject to include in the National Energy Modeling System (NEMS). This report summarizes a study to develop an E85 choice model for NEMS. Using the most recent data from the states of Minnesota, North Dakota, and Iowa, this study estimates a logit model that represents E85 choice as a function of prices of E10 and E85, as well as fuel availability of E85 relative to gasoline. Using more recent data than previous studies allows a better estimation of non-fleet demand and indicates that the price elasticity of E85 choice appears to be higher than previously estimated. Based on the results of the econometric analysis, a model for projecting E85 demand at the regional level is specified. In testing, the model produced plausible predictions of US E85 demand to 2040.

  4. 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.

  5. State of the Art of Demand Surge Modeling

    NASA Astrophysics Data System (ADS)

    Olsen, A.; Porter, K.

    2009-04-01

    Among other phenomena, many insurance loss models estimate the increased losses in large-scale disasters--referred to here as catastrophes--compared to the losses in small-scale disasters. This amplification of loss has been traditionally and loosely called "demand surge," although there is a clear need for more specific terminology. Many factors have been identified as drivers of demand surge. First among them is the sudden and temporary increased demand for construction materials and labor that overwhelms local supplies. The purpose of the present research is to describe in qualitative terms the current understanding of demand surge in the broad sense of amplification of insured loss. Aspects of demand surge were observed following the 1886 Charleston, South Carolina, and 1906 San Francisco, U.S. earthquakes. More recently, the aftermaths of Cyclone Tracy, Hurricane Andrew, the Northridge Earthquake, the 1999 windstorms in France, the 2004-5 hurricane seasons on the Gulf Coast, and the 2007 floods in the U.K. all evidenced demand surge in one form or another. Each event highlights particular aspects of the broader demand-surge phenomena. In other words, there are general themes associated with demand surge, which have greater or lesser expression in each historic event. Pieces of the broader demand-surge phenomena have been described by mathematical models, with varying degrees of complexity. For example, researchers have used linear input-output or nonlinear computable general equilibrium models to describe the response of construction costs to a catastrophe. Ultimately the present research will include the gathering of evidence through interviews, field observations, reviews of academic and insurance industry literature, and data collection. This evidence will then inform and validate a general quantitative, mathematical model of the demand-surge process.

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

    NASA Astrophysics Data System (ADS)

    Ouedraogo, B. I.

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

  7. Modeling of Electric Water Heaters for Demand Response: A Baseline PDE Model

    SciTech Connect

    Xu, Zhijie; Diao, Ruisheng; Lu, Shuai; Lian, Jianming; Zhang, Yu

    2014-09-05

    Demand response (DR)control can effectively relieve balancing and frequency regulation burdens on conventional generators, facilitate integrating more renewable energy, and reduce generation and transmission investments needed to meet peak demands. Electric water heaters (EWHs) have a great potential in implementing DR control strategies because: (a) the EWH power consumption has a high correlation with daily load patterns; (b) they constitute a significant percentage of domestic electrical load; (c) the heating element is a resistor, without reactive power consumption; and (d) they can be used as energy storage devices when needed. Accurately modeling the dynamic behavior of EWHs is essential for designing DR controls. Various water heater models, simplified to different extents, were published in the literature; however, few of them were validated against field measurements, which may result in inaccuracy when implementing DR controls. In this paper, a partial differential equation physics-based model, developed to capture detailed temperature profiles at different tank locations, is validated against field test data for more than 10 days. The developed model shows very good performance in capturing water thermal dynamics for benchmark testing purposes

  8. A dynamic model of industrial energy demand in Kenya

    SciTech Connect

    Haji, S.H.H.

    1994-12-31

    This paper analyses the effects of input price movements, technology changes, capacity utilization and dynamic mechanisms on energy demand structures in the Kenyan industry. This is done with the help of a variant of the second generation dynamic factor demand (econometric) model. This interrelated disequilibrium dynamic input demand econometric model is based on a long-term cost function representing production function possibilities and takes into account the asymmetry between variable inputs (electricity, other-fuels and Tabour) and quasi-fixed input (capital) by imposing restrictions on the adjustment process. Variations in capacity utilization and slow substitution process invoked by the relative input price movement justifies the nature of input demand disequilibrium. The model is estimated on two ISIS digit Kenyan industry time series data (1961 - 1988) using the Iterative Zellner generalized least square method. 31 refs., 8 tabs.

  9. Detailed Modeling and Response of Demand Response Enabled Appliances

    SciTech Connect

    Vyakaranam, Bharat; Fuller, Jason C.

    2014-04-14

    Proper modeling of end use loads is very important in order to predict their behavior, and how they interact with the power system, including voltage and temperature dependencies, power system and load control functions, and the complex interactions that occur between devices in such an interconnected system. This paper develops multi-state time variant residential appliance models with demand response enabled capabilities in the GridLAB-DTM simulation environment. These models represent not only the baseline instantaneous power demand and energy consumption, but the control systems developed by GE Appliances to enable response to demand response signals and the change in behavior of the appliance in response to the signal. These DR enabled appliances are simulated to estimate their capability to reduce peak demand and energy consumption.

  10. Modeling of materials supply, demand and prices

    NASA Technical Reports Server (NTRS)

    1982-01-01

    The societal, economic, and policy tradeoffs associated with materials processing and utilization, are discussed. The materials system provides the materials engineer with the system analysis required for formulate sound materials processing, utilization, and resource development policies and strategies. Materials system simulation and modeling research program including assessments of materials substitution dynamics, public policy implications, and materials process economics was expanded. This effort includes several collaborative programs with materials engineers, economists, and policy analysts. The technical and socioeconomic issues of materials recycling, input-output analysis, and technological change and productivity are examined. The major thrust areas in materials systems research are outlined.

  11. Modeling of an Integrated Renewable Energy System (IRES) with hydrogen storage

    NASA Astrophysics Data System (ADS)

    Shenoy, Navin Kodange

    2010-12-01

    Scope and Method of Study. The purpose of the study was to consider the integration of hydrogen storage technology as means of energy storage with renewable sources of energy. Hydrogen storage technology consists of an alkaline electrolyzer, gas storage tank and a fuel cell. The Integrated Renewable Energy System (IRES) under consideration includes wind energy, solar energy from photovoltaics, solar thermal energy and biomass energy in the form of biogas. Energy needs are categorized depending on the type and quality of the energy requirements. After meeting all the energy needs, any excess energy available from wind and PVs is converted into hydrogen using an electrolyzer for later use in a fuel cell. Similarly, when renewable energy generation is not able to supply the actual load demand, the stored hydrogen is utilized through fuel cell to fulfill load demand. Analysis of how IRES operates in order to satisfy different types of energy needs is discussed. Findings and Conclusions. All simulations are performed using MATLAB software. Hydrogen storage technology consisting of an electrolyzer, gas storage tank and a fuel cell is incorporated in the IRES design process for a hypothetical remote community. Results show that whenever renewable energy generated is greater than the electrical demand, excess energy is stored in the form of hydrogen and in case of energy shortfall, the stored hydrogen is utilized through the fuel cell to supply to excess power demand. The overall operation of IRES is enhanced as a result of energy storage in the form of hydrogen. Hydrogen has immense potential to be the energy carrier of the future because of its clean character and the model of hydrogen storage discussed here can form an integral part of IRES for remote area applications.

  12. 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...

  13. 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…

  14. Water supply and demand in an energy supply model

    SciTech Connect

    Abbey, D; Loose, V

    1980-12-01

    This report describes a tool for water and energy-related policy analysis, the development of a water supply and demand sector in a linear programming model of energy supply in the United States. The model allows adjustments in the input mix and plant siting in response to water scarcity. Thus, on the demand side energy conversion facilities can substitute more costly dry cooling systems for conventional evaporative systems. On the supply side groundwater and water purchased from irrigators are available as more costly alternatives to unappropriated surface water. Water supply data is developed for 30 regions in 10 Western states. Preliminary results for a 1990 energy demand scenario suggest that, at this level of spatial analysis, water availability plays a minor role in plant siting. Future policy applications of the modeling system are discussed including the evaluation of alternative patterns of synthetic fuels development.

  15. 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.

  16. Predictive models for forecasting hourly urban water demand

    NASA Astrophysics Data System (ADS)

    Herrera, Manuel; Torgo, Luís; Izquierdo, Joaquín; Pérez-García, Rafael

    2010-06-01

    SummaryOne of the goals of efficient water supply management is the regular supply of clean water at the pressure required by consumers. In this context, predicting water consumption in urban areas is of key importance for water supply management. This prediction is also relevant in processes for reviewing prices; as well as for operational management of a water network. In this paper, we describe and compare a series of predictive models for forecasting water demand. The models are obtained using time series data from water consumption in an urban area of a city in south-eastern Spain. This includes highly non-linear time series data, which has conditioned the type of models we have included in our study. Namely, we have considered artificial neural networks, projection pursuit regression, multivariate adaptive regression splines, random forests and support vector regression. Apart from these models, we also propose a simple model based on the weighted demand profile resulting from our exploratory analysis of the data. In our comparative study, all predictive models were evaluated using an experimental methodology for hourly time series data that detailed water demand in a hydraulic sector of a water supply network in a city in south-eastern Spain. The accuracy of the obtained results, together with the medium size of the demand area, suggests that this was a suitable environment for making adequate management decisions.

  17. Aggregate Model for Heterogeneous Thermostatically Controlled Loads with Demand Response

    SciTech Connect

    Zhang, Wei; Kalsi, Karanjit; Fuller, Jason C.; Elizondo, Marcelo A.; Chassin, David P.

    2012-07-22

    Due to the potentially large number of Distributed Energy Resources (DERs) – demand response, distributed generation, distributed storage - that are expected to be deployed, it is impractical to use detailed models of these resources when integrated with the transmission system. Being able to accurately estimate the fast transients caused by demand response is especially important to analyze the stability of the system under different demand response strategies. On the other hand, a less complex model is more amenable to design feedback control strategies for the population of devices to provide ancillary services. The main contribution of this paper is to develop aggregated models for a heterogeneous population of Thermostatic Controlled Loads (TCLs) to accurately capture their collective behavior under demand response and other time varying effects of the system. The aggregated model efficiently includes statistical information of the population and accounts for a second order effect necessary to accurately capture the collective dynamic behavior. The developed aggregated models are validated against simulations of thousands of detailed building models using GridLAB-D (an open source distribution simulation software) under both steady state and severe dynamic conditions caused due to temperature set point changes.

  18. A Data Envelopment Analysis Model for Renewable Energy Technology Selection

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  19. 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

    SciTech Connect

    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, technological breakthroughs, and future public policies and regulations. Changes in any one of these factors could make future renewable energy options more or less attractive.

  20. Water consumption patterns as a basis for water demand modeling

    NASA Astrophysics Data System (ADS)

    Avni, Noa; Fishbain, Barak; Shamir, Uri

    2015-10-01

    Future water demand is a main consideration in water system management. Consequently, water demand models (WDMs) have evolved in past decades, identifying principal demand-generating factors and modeling their influence on water demand. Regional water systems serve consumers of various types (e.g., municipalities, farmers, industrial regions) and consumption patterns. Thus, one of the challenges in regional water demand modeling is the heterogeneity of the consumers served by the water system. When a high-resolution, regional WDM is desired, accounting for this heterogeneity becomes all the more important. This paper presents a novel approach to regional water demand modeling. The two-step approach includes aggregating the data set into groups of consumers having similar consumption characteristics, and developing a WDM for each homogeneous group. The development of WDMs is widely applied in the literature and thus, the focus of this paper is to discuss the first step of data aggregation. The research hypothesis is that water consumption records in their original or transformed form can provide a basis for aggregating the data set into groups of consumers with similar consumption characteristics. This paper presents a methodology for water consumption data clustering by comparing several data representation methods (termed Feature Vectors): monthly normalized average, monthly consumption coefficient of variation, a combination of the monthly average and monthly variation, and the autocorrelation coefficients of the consumption time series. Clustering using solely normalized monthly average provided homogeneous and distinct clusters with respect to monthly consumption, which succeed in capturing different consumer characteristics (water use, geographical location) that were not specified a-priori. Clustering using the monthly coefficient of variation provided different, yet homogeneous clusters, clustering consumers characterized by similar variation trends that

  1. Drivers for the Value of Demand Response under Increased Levels of Wind and Solar Power; NREL (National Renewable Energy Laboratory)

    SciTech Connect

    Hale, Elaine

    2015-07-30

    Demand response may be a valuable flexible resource for low-carbon electric power grids. However, there are as many types of possible demand response as there are ways to use electricity, making demand response difficult to study at scale in realistic settings. This talk reviews our state of knowledge regarding the potential value of demand response in several example systems as a function of increasing levels of wind and solar power, sometimes drawing on the analogy between demand response and storage. Overall, we find demand response to be promising, but its potential value is very system dependent. Furthermore, demand response, like storage, can easily saturate ancillary service markets.

  2. 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.

  3. Marked renewal model of smoothed VBR MPEG coded traffic

    NASA Astrophysics Data System (ADS)

    Hui, Xiaoshi; Li, Jiaoyang; Liu, Xiande

    1998-08-01

    In this paper, a method of smoothing variable bit-rate (VBR) MPEG traffic is proposed. A buffer, which has capacity over the peak bandwidth of group of picture (GOP) sequence of an MPEG traffic and which output rate is controlled by the distribution of GOP sequence, is connected to a source. The degree of burst of output stream from the buffer is deceased, and the stream's autocorrelation function characterizes non-increased and non-convex property. For smoothed MPEG traffic stream, the GOP sequence is the element target source traffic using for modeling. We applied a marked renewal process to model the GOP smoothed VBR MPEG traffics. The numerical study of simulating target VBR MPEG video source with a marked renewal model shows that not only the model's bandwidth distribution can match accurately that of target source sequence, but also its leading autocorrelation can approximate the long-range dependence of a VBR MPEG traffic as well as the short-range dependence. In addition to that, the model's parameters estimation is very easy. We conclude that GOP smoothed VBR MPEG video traffic could be not only transferred more efficiently but also analyzed perfectly with a marked renewal traffic model.

  4. 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

  5. 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…

  6. A Multiple Equation Model of Demand for Health Care

    PubMed Central

    Wirick, Grover C.

    1966-01-01

    Planning health care facilities for the future requires a means of estimating future consumption of services. Demand for medical care is looked upon as demand for separate components (hospital, doctor, dentist, medicine, other) rather than for a single, homogeneous product. A simultaneous equation model is proposed, and measures representing the forces thought to influence consumption (need, realization, motivation, resources, and availability of service) are fitted into the five equations. An optimized analysis variance method is employed on data from a sample survey of Michigan's population in 1958 to obtain single equation estimates of the five demand functions as a preliminary test of the model. The optimizing feature, which also includes an examination of complex interactions, retains variables in the equation on the basis of their estimating ability. The results indicate that a high degree of joint dependency exists among the components and that a simultaneous equation model is warranted. The study, intended as a research design, also reveals considerable variety in component equations, certain relevant and irrelevant variables, several important interactions, and a need for refining some measures in future studies. PMID:5971639

  7. Hawaii Energy Strategy: Program guide. [Contains special sections on analytical energy forecasting, renewable energy resource assessment, demand-side energy management, energy vulnerability assessment, and energy strategy integration

    SciTech Connect

    Not Available

    1992-09-01

    The Hawaii Energy Strategy program, or HES, is a set of seven projects which will produce an integrated energy strategy for the State of Hawaii. It will include a comprehensive energy vulnerability assessment with recommended courses of action to decrease Hawaii's energy vulnerability and to better prepare for an effective response to any energy emergency or supply disruption. The seven projects are designed to increase understanding of Hawaii's energy situation and to produce recommendations to achieve the State energy objectives of: Dependable, efficient, and economical state-wide energy systems capable of supporting the needs of the people, and increased energy self-sufficiency. The seven projects under the Hawaii Energy Strategy program include: Project 1: Develop Analytical Energy Forecasting Model for the State of Hawaii. Project 2: Fossil Energy Review and Analysis. Project 3: Renewable Energy Resource Assessment and Development Program. Project 4: Demand-Side Management Program. Project 5: Transportation Energy Strategy. Project 6: Energy Vulnerability Assessment Report and Contingency Planning. Project 7: Energy Strategy Integration and Evaluation System.

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

    SciTech Connect

    CHAPMAN,LEON D.; PETERSEN,MARJORIE B.

    2000-03-13

    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 the 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.

  9. Electric Water Heater Modeling and Control Strategies for Demand Response

    SciTech Connect

    Diao, Ruisheng; Lu, Shuai; Elizondo, Marcelo A.; Mayhorn, Ebony T.; Zhang, Yu; Samaan, Nader 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 support 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

  10. Using transportation demand models to assess regional noise exposure

    NASA Astrophysics Data System (ADS)

    Kaliski, Kenneth

    2005-09-01

    In the United States, most metropolitan areas run some type of transportation demand model to estimate regional travel patterns, and, to some extent, air pollution. The more advanced of these models accurately represent the geographic contours of the roadways (in contrast to the older straight-line node and link models). This allows an almost seamless integration of these new transportation demand models into noise prediction models. Combined with the locations of individual homes from a separate E911 database, we can readily make estimates of the noise exposure of populations over large areas. In this paper, the regional traffic noise exposure of residences of Chittenden County, VT is estimated and mapped. It was found that 30% of the residences are exposed to noise levels exceeding the WHO sleep disturbance level of 45 dB LAeq(8) and 20% of residences are exposed to levels exceeding the WHO ``serious annoyance'' level of 55 dB LAeq(16). Maps show noise contours as well as individual homes color coded based on relative day and night noise exposure levels. Measured sound level data are given for particular locations to validate the predictions.

  11. Advanced Modeling of Renewable Energy Market Dynamics: May 2006

    SciTech Connect

    Evans, M.; Little, R.; Lloyd, K.; Malikov, G.; Passolt, G.; Arent, D.; Swezey, B.; Mosey, G.

    2007-08-01

    This report documents a year-long academic project, presenting selected techniques for analysis of market growth, penetration, and forecasting applicable to renewable energy technologies. Existing mathematical models were modified to incorporate the effects of fiscal policies and were evaluated using available data. The modifications were made based on research and classification of current mathematical models used for predicting market penetration. An analysis of the results was carried out, based on available data. MATLAB versions of existing and new models were developed for research and policy analysis.

  12. A model for statistical forecasting of menu item demand.

    PubMed

    Wood, S D

    1977-03-01

    Foodservice planning necessarily begins with a forecast of demand. Menu item demand forecasts are needed to make food item production decisions, work force and facility acquisition plans, and resource allocation and scheduling decisions. As these forecasts become more accurate, the tasks of adjusting original plans are minimized. Forecasting menu item demand need no longer be the tedious and inaccurate chore which is so prevalent in hospital food management systems today. In most instances, data may be easily collected as a by-product of existing activities to support accurate statistical time series predictions. Forecasts of meal tray count, based on a rather sophisticated model, multiplied by average menu item preference percentages can provide accurate predictions of demand. Once the forecasting models for tray count have been developed, simple worksheets can be prepared to facilitate manual generation of the forecasts on a continuing basis. These forecasts can then be recorded on a worksheet that reflects average patient preference percentages (of tray count), so that the product of the percentages with the tray count prediction produces menu item predictions on the same worksheet. As the patient preference percentages stabilize, data collection can be reduced to the daily recording of tray count and one-step-ahead forecase errors for each meal with a periodic gathering of patient preference percentages to update and/or verify the existing date. The author is more thoroughly investigating the cost/benefit relationship of such a system through the analysis of new empirical data. It is clear that the system offers potential for reducing costs at the diet category or total tray count levels. It is felt that these benefits transfer down to the meal item level as well as offer ways of generating more accurate predictions, with perhaps only minor (if any) labor time increments. Research in progress will delineate expected savings more explicitly. The approach

  13. 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.

  14. 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

  15. 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

  16. Value of Demand Response: Quantities from Production Cost Modeling (Presentation)

    SciTech Connect

    Hummon, M.

    2014-04-01

    Demand response (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind and solar power generation. However, managed loads in grid models are limited by data availability and modeling complexity. This presentation focuses on the value of co-optimized DR resources to provide energy and ancillary services in a production cost model. There are significant variations in the availabilities of different types of DR resources, which affect both the operational savings as well as the revenue for each DR resource. The results presented include the system-wide avoided fuel and generator start-up costs as well as the composite revenue for each DR resource by energy and operating reserves. In addition, the revenue is characterized by the capacity, energy, and units of DR enabled.

  17. Model documentation report: Short-term Integrated Forecasting System demand model 1985. [(STIFS)

    SciTech Connect

    Not Available

    1985-07-01

    The Short-Term Integrated Forecasting System (STIFS) Demand Model consists of a set of energy demand and price models that are used to forecast monthly demand and prices of various energy products up to eight quarters in the future. The STIFS demand model is based on monthly data (unless otherwise noted), but the forecast is published on a quarterly basis. All of the forecasts are presented at the national level, and no regional detail is available. The model discussed in this report is the April 1985 version of the STIFS demand model. The relationships described by this model include: the specification of retail energy prices as a function of input prices, seasonal factors, and other significant variables; and the specification of energy demand by product as a function of price, a measure of economic activity, and other appropriate variables. The STIFS demand model is actually a collection of 18 individual models representing the demand for each type of fuel. The individual fuel models are listed below: motor gasoline; nonutility distillate fuel oil, (a) diesel, (b) nondiesel; nonutility residual fuel oil; jet fuel, kerosene-type and naphtha-type; liquefied petroleum gases; petrochemical feedstocks and ethane; kerosene; road oil and asphalt; still gas; petroleum coke; miscellaneous products; coking coal; electric utility coal; retail and general industry coal; electricity generation; nonutility natural gas; and utility petroleum. The demand estimates produced by these models are used in the STIFS integrating model to produce a full energy balance of energy supply, demand, and stock change. These forecasts are published quarterly in the Outlook. Details of the major changes in the forecasting methodology and an evaluation of previous forecast errors are presented once a year in Volume 2 of the Outlook, the Methodology publication.

  18. An innovation in physical modelling for testing marine renewables technology

    NASA Astrophysics Data System (ADS)

    Todd, David; Whitehouse, Richard; Harris, John; Liddiard, Mark

    2015-04-01

    HR Wallingford has undertaken physical modelling of scour around structures since its creation as a government research laboratory in 1947. Since privatisation in 1982 HR Wallingford has carried out a large number of studies for offshore developments including renewable energy developments and offshore wind in particular, looking at scour around offshore foundations and cables. To maintain our position as both a research and consultancy organisation delivering high quality work we have developed a new purpose built physical modelling facility. The Fast Flow Facility is a dual-channel, race track shaped flume and the only large scale physical modelling facility of this kind offering wave, fast tidal current and recirculating sediment capabilities. The 75 m long, 8 m wide and 2.5 m deep Fast Flow Facility has two working channels of 4 m and 2.6 m width. Holding up to a million litres of water the facility can generate waves with significant wave heights, Hs, of up to 0.5 m and maximum wave heights of up to 1 m in combination with flows of up to 2 m/s (~4 knots). This state-of-the-art facility combines fast, reversible currents with wave generation and sediment transport modelling in a single flume, allowing us to further develop our understanding of sediment transport within the marine environment and keep us at the forefront of sediment transport research. The facility has been designed with the marine renewables sector in mind, with a 4 x 4 x 1m deep sediment pit in the centre of the flume allowing investigations to provide improved understanding of the detailed processes which lead to scour, and enabling improvements in prediction capabilities for marine scour in different sediment seabed compositions (non-cohesive and cohesive) for a range of structure types (monopiles, jackets, gravity base foundations, jack-ups etc.). The facility also enables the testing of scour protection methodologies at relatively large scale (typically 1: 10 - 1:20) and allows for

  19. 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

  20. The Integration of Energy Efficiency, Renewable Energy, DemandResponse and Climate Change: Challenges and Opportunities for Evaluatorsand Planners

    SciTech Connect

    Vine, Edward

    2007-05-29

    This paper explores the feasibility of integrating energyefficiency program evaluation with the emerging need for the evaluationof programs from different "energy cultures" (demand response, renewableenergy, and climate change). The paper reviews key features andinformation needs of the energy cultures and critically reviews theopportunities and challenges associated with integrating these withenergy efficiency program evaluation. There is a need to integrate thedifferent policy arenas where energy efficiency, demand response, andclimate change programs are developed, and there are positive signs thatthis integration is starting to occur.

  1. Job Demands-Control-Support model and employee safety performance.

    PubMed

    Turner, Nick; Stride, Chris B; Carter, Angela J; McCaughey, Deirdre; Carroll, Anthony E

    2012-03-01

    The aim of this study was to explore whether work characteristics (job demands, job control, social support) comprising Karasek and Theorell's (1990) Job Demands-Control-Support framework predict employee safety performance (safety compliance and safety participation; Neal and Griffin, 2006). We used cross-sectional data of self-reported work characteristics and employee safety performance from 280 healthcare staff (doctors, nurses, and administrative staff) from Emergency Departments of seven hospitals in the United Kingdom. We analyzed these data using a structural equation model that simultaneously regressed safety compliance and safety participation on the main effects of each of the aforementioned work characteristics, their two-way interactions, and the three-way interaction among them, while controlling for demographic, occupational, and organizational characteristics. Social support was positively related to safety compliance, and both job control and the two-way interaction between job control and social support were positively related to safety participation. How work design is related to employee safety performance remains an important area for research and provides insight into how organizations can improve workplace safety. The current findings emphasize the importance of the co-worker in promoting both safety compliance and safety participation. PMID:22269573

  2. Case of the Mathematics Team: Implementing a Team Model for Simultaneous Renewal

    ERIC Educational Resources Information Center

    Bay-Williams, Jennifer M.; Scott, Michael B.; Hancock, Melisa

    2007-01-01

    Simultaneous renewal in teacher education is based on the notion that improvement at 1 level requires improvement at all levels and that all stakeholders are responsible for such improvement. The authors discuss the creation and impact of a mathematics team as a vehicle for simultaneous renewal by using the team model for simultaneous renewal for…

  3. Modelling Approach to Assess Future Agricultural Water Demand

    NASA Astrophysics Data System (ADS)

    Spano, D.; Mancosu, N.; Orang, M.; Sarreshteh, S.; Snyder, R. L.

    2013-12-01

    The combination of long-term climate changes (e.g., warmer average temperatures) and extremes events (e.g., droughts) can have decisive impacts on water demand, with further implications on the ecosystems. In countries already affected by water scarcity, water management problems are becoming increasingly serious. The sustainable management of available water resources at the global, regional, and site-specific level is necessary. In agriculture, the first step is to compute how much water is needed by crops in regards to climate conditions. Modelling approach can be a way to compute crop water requirement (CWR). In this study, the improved version of the SIMETAW model was used. The model is a user friendly soil water balance model, developed by the University of California, Davis, the California Department of Water Resource, and the University of Sassari. The SIMETAW# model assesses CWR and generates hypothetical irrigation scheduling for a wide range of irrigated crops experiencing full, deficit, or no irrigation. The model computes the evapotranspiration of the applied water (ETaw), which is the sum of the net amount of irrigation water needed to match losses due to the crop evapotranspiration (ETc). ETaw is determined by first computing reference evapotranspiration (ETo) using the daily standardized Reference Evapotranspiration equation. ETaw is computed as ETaw = CETc - CEr, where CETc and CE are the cumulative total crop ET and effective rainfall values, respectively. Crop evapotranspiration is estimated as ETc = ETo x Kc, where Kc is the corrected midseason tabular crop coefficient, adjusted for climate conditions. The net irrigation amounts are determined from a daily soil water balance, using an integrated approach that considers soil and crop management information, and the daily ETc estimates. Using input information on irrigation system distribution uniformity and runoff, when appropriate, the model estimates the applied water to the low quarter of the

  4. A Functional Murine Model of Hind Limb Demand Ischemia

    PubMed Central

    Peck, Michael A.; Crawford, Robert S.; Abularrage, Christopher J.; Patel, Virendra I.; Conrad, Mark F.; Yoo, Jin Hyung; Watkins, Michael T.; Albadawi, Hassan

    2010-01-01

    Introduction To date murine models of treadmill exercise have been used to study general exercise physiology and angiogenesis in ischemic hind limbs. The purpose of these experiments was to develop a murine model of demand ischemia in an ischemic limb to mimic claudication in humans. The primary goal was to determine whether treadmill exercise reflected a hemodynamic picture which might be consistent with the hyperemic response observed in humans. Methods Aged hypercholesterolemic ApoE null mice ( ApoE−/−, n=13) were subjected to Femoral Artery Ligation (FAL), and allowed to recover from the acute ischemic response. Peripheral perfusion of the hind limbs at rest was determined by serial evaluation using laser Doppler imaging (LDI) on days 0, 7, and 14 following FAL. During the duration of the experiments, the mice were also assessed on an established 5 point clinical ischemic score which assessed the degree of digital amputation, necrosis, and cyanosis as compared to the non ischemic contralateral limb. After stabilization of the LDI ratio (ischemic limb flux/contralateral non ischemic limb flux) and clinical ischemic score, mice underwent two days of treadmill training (10 min @ 10 m/min, incline of 10°) followed by 60 minutes daily treadmill exercise (13 m/min, incline of 10°) through day 25. An evaluation of pre-exercise and post exercise perfusion using LDI was performed on two separate occasions following the onset of daily exercise. During the immediate 15 minute post exercise evaluation, LDI scanning was obtained in quadruplicate, to allow identification of peak flux ratios. Statistical analysis included unpaired t-tests and ANOVA. Results After FAL, the LDI Flux ratio reached a nadir between days one and two, then stabilized by day 14 and remained stable through day 25. The clinical ischemic score stabilized at day 7, and remained stable throughout the rest of the experiment. Based on stabilization of both the clinical ischemic score and LDI ratio

  5. 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.

  6. The Importance of High Temporal Resolution in Modeling Renewable Energy Penetration Scenarios

    SciTech Connect

    Nicolosi, Marco; Mills, Andrew D; Wiser, Ryan H

    2010-10-08

    Traditionally, modeling investment and dispatch problems in electricity economics has been limited by computation power. Due to this limitation, simplifications are applied. One common practice, for example, is to reduce the temporal resolution of the dispatch by clustering similar load levels. The increase of intermittent electricity from renewable energy sources (RES-E) changes the validity of this assumption. RES-E already cover a certain amount of the total demand. This leaves an increasingly volatile residual demand to be matched by the conventional power market. This paper quantifies differences in investment decisions by applying three different time-resolution residual load patterns in an investment and dispatch power system model. The model optimizes investment decisions in five year steps between today and 2030 with residual load levels for 8760, 288 and 16 time slices per year. The market under consideration is the four zone ERCOT market in Texas. The results show that investment decisions significantly differ across the three scenarios. In particular, investments into base-load technologies are substantially reduced in the high resolution scenario (8760 residual load levels) relative to the scenarios with lower temporal resolution. Additionally, the amount of RES-E curtailment and the market value of RES-E exhibit noteworthy differences.

  7. 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…

  8. Model documentation Renewable Fuels Module of the National Energy Modeling System

    SciTech Connect

    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.

  9. Modeling, Analysis, and Control of Demand Response Resources

    SciTech Connect

    Mathieu, Johanna L.

    2012-05-01

    While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can plan an active role in power systems via Demand Response (DR), defined by the Department of Energy (DOE) as “a tariff or program established to motivate changes in electric use by end-use customers in response to changes in the price of electricity over time, or to give incentive payments designed to induce lower electricity use at times of high market prices or when grid reliability is jeopardized” [29]. DR can provide a variety of benefits including reducing peak electric loads when the power system is stressed and fast timescale energy balancing. Therefore, DR can improve grid reliability and reduce wholesale energy prices and their volatility. This dissertation focuses on analyzing both recent and emerging DR paradigms. Recent DR programs have focused on peak load reduction in commercial buildings and industrial facilities (C&I facilities). We present methods for using 15-minute-interval electric load data, commonly available from C&I facilities, to help building managers understand building energy consumption and ‘ask the right questions’ to discover opportunities for DR. Additionally, we present a regression-based model of whole building electric load, i.e., a baseline model, which allows us to quantify DR performance. We use this baseline model to understand the performance of 38 C&I facilities participating in an automated dynamic pricing DR program in California. In this program, facilities are expected to exhibit the same response each DR event. We find that baseline model error makes it difficult to precisely quantify changes in electricity consumption and understand if C&I facilities exhibit event-to-event variability in their response to DR signals. Therefore, we present a method to compute baseline model error and a metric to determine how much observed DR variability results from baseline model error rather than real

  10. 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.

  11. Cotton production potential and water conservation impact using the regional irrigation demand model of northern Texas

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Revised irrigation demands are calculated for the 21 northernmost counties in Texas, identified as Panhandle Region (also known as Region A), using the TAMA (Texas A&M–Amarillo) agricultural water use demand estimation model. Year 2000 demands are presented using the existing mixture of crops, aver...

  12. Model documentation report: Industrial sector demand module of the national energy modeling system

    SciTech Connect

    1998-01-01

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirements of the Energy Information Administration (EIA) to provide adequate documentation in support of its model. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

  13. Model documentation report: Industrial sector demand module of the National Energy Modeling System

    SciTech Connect

    1997-01-01

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects. The NEMS Industrial Demand Model is a dynamic accounting model, bringing together the disparate industries and uses of energy in those industries, and putting them together in an understandable and cohesive framework. The Industrial Model generates mid-term (up to the year 2015) forecasts of industrial sector energy demand as a component of the NEMS integrated forecasting system. From the NEMS system, the Industrial Model receives fuel prices, employment data, and the value of industrial output. Based on the values of these variables, the Industrial Model passes back to the NEMS system estimates of consumption by fuel types.

  14. 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…

  15. Optimization of Evaporative Demand Models for Seasonal Drought Forecasting

    NASA Astrophysics Data System (ADS)

    McEvoy, D.; Huntington, J. L.; Hobbins, M.

    2015-12-01

    Providing reliable seasonal drought forecasts continues to pose a major challenge for scientists, end-users, and the water resources and agricultural communities. Precipitation (Prcp) forecasts beyond weather time scales are largely unreliable, so exploring new avenues to improve seasonal drought prediction is necessary to move towards applications and decision-making based on seasonal forecasts. A recent study has shown that evaporative demand (E0) anomaly forecasts from the Climate Forecast System Version 2 (CFSv2) are consistently more skillful than Prcp anomaly forecasts during drought events over CONUS, and E0 drought forecasts may be particularly useful during the growing season in the farming belts of the central and Midwestern CONUS. For this recent study, we used CFSv2 reforecasts to assess the skill of E0 and of its individual drivers (temperature, humidity, wind speed, and solar radiation), using the American Society for Civil Engineers Standardized Reference Evapotranspiration (ET0) Equation. Moderate skill was found in ET0, temperature, and humidity, with lesser skill in solar radiation, and no skill in wind. Therefore, forecasts of E0 based on models with no wind or solar radiation inputs may prove to be more skillful than the ASCE ET0. For this presentation we evaluate CFSv2 E0 reforecasts (1982-2009) from three different E0 models: (1) ASCE ET0; (2) Hargreaves and Samani (ET-HS), which is estimated from maximum and minimum temperature alone; and (3) Valiantzas (ET-V), which is a modified version of the Penman method for use when wind speed data are not available (or of poor quality) and is driven only by temperature, humidity, and solar radiation. The University of Idaho's gridded meteorological data (METDATA) were used as observations to evaluate CFSv2 and also to determine if ET0, ET-HS, and ET-V identify similar historical drought periods. We focus specifically on CFSv2 lead times of one, two, and three months, and season one forecasts; which are

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

    SciTech Connect

    1998-01-01

    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, market incentives, and regulatory changes can be estimated using the module. 26 refs., 6 figs., 5 tabs.

  17. MEASURING AND MODELING DISINFECTION WALL DEMAND IN METALLIC PIPES

    EPA Science Inventory

    A field test procedure was developed and implemented in Detroit to estimate chlorine loss due to wall demand in older 6" (152 mm) and 8" (203 mm) diameter, unlined cast iron pipes. The test results produced extremely high wall reaction rate coefficients that increased significan...

  18. 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.

  19. Defense Economic Impact Modeling System (DEIMS). Skill Categories Included within Defense Impact Modeling System Skilled Labor Demand Model.

    ERIC Educational Resources Information Center

    Department of Defense, Washington, DC.

    Updated Defense Economic Impact Modeling System (DEIMS) manpower data are provided. Skilled-labor demand by job categories and industrial sectors are estimated for 163 skill categories. Both defense and non-defense demands are presented for the years 1982 to 1987. The average annual percentage growth for the time period is also estimated. Data are…

  20. 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

  1. Model documentation renewable fuels module of the National Energy Modeling System

    SciTech Connect

    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 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. 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.

  2. 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.

  3. Renewable Energy and Efficiency Modeling Analysis Partnership (REMAP): An Analysis of How Different Energy Models Addressed a Common High Renewable Energy Penetration Scenario in 2025

    SciTech Connect

    Blair, Nate; Jenkin, Thomas; Milford, James; Short, Walter; Sullivan, Patrick; Evans, David; Lieberman, Elliot; Goldstein, Gary; Wright, Evelyn; Jayaraman, Kamala R.; Venkatesh, Boddu; Kleiman, Gary; Namovicz, Christopher; Smith, Bob; Palmer, Karen; Wiser, Ryan; Wood, Frances

    2009-09-01

    Energy system modeling can be intentionally or unintentionally misused by decision-makers. This report describes how both can be minimized through careful use of models and thorough understanding of their underlying approaches and assumptions. The analysis summarized here assesses the impact that model and data choices have on forecasting energy systems by comparing seven different electric-sector models. This analysis was coordinated by the Renewable Energy and Efficiency Modeling Analysis Partnership (REMAP), a collaboration among governmental, academic, and nongovernmental participants.

  4. Modeling Feasibility of a Proposed Renewable Energy System with Wind and Solar Resources and Hydro Storage in Complex Terrain

    NASA Astrophysics Data System (ADS)

    Jiang, J.; Koracin, D.; Hamilton, R.; Hagen, D.; King, K. C.

    2012-04-01

    High temporal and spatial variability in wind and solar power brings difficulties in integrating these resources into an electricity grid. These difficulties are even more emphasized in areas with complex topography due to complicated flow patterns and cloudiness evolution. This study investigates the feasibility and efficiency of a proposed renewable energy system with wind and solar resources and hydro storages in western Nevada, U.S.A. The state-of-the-art Weather Research and Forecasting (WRF) model was used for the prediction of wind fields and incoming solar radiation at the ground surface. Forecast winds and solar radiation were evaluated with observational data from four wind masts and four meteorological towers in two months, July 2007 and January 2010. Based on a hypothetical wind farm and an assumed neighboring solar power plant both located near the hydro storage facility, as well as considering local power demand, the efficiency of the renewable energy system is projected. One of the main questions was how to optimize a schedule of activating pump storages according to the characteristics of several available hydro pumps, and wind and/or solar power predictions. The results show that segmentation of the pump-storage channel provides improved efficiency of the entire system. This modeled renewable energy system shows promise for possible applications and grid integration.

  5. 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.

  6. Rethink, Retool, Renew: A Transitional Model for Institutions.

    ERIC Educational Resources Information Center

    Berry, Kathryn; And Others

    In 1980, the environment of Eastfield College was characterized by declining enrollments, reduced funding, staff unrest, and low morale. In response to a collegewide need, Eastfield's Quality of Life project, originally designed to increase community participation, was transformed to focus on participatory organizational renewal. The renewal…

  7. A Full Demand Response Model in Co-Optimized Energy and

    SciTech Connect

    Liu, Guodong; Tomsovic, Kevin

    2014-01-01

    It has been widely accepted that demand response will play an important role in reliable and economic operation of future power systems and electricity markets. Demand response can not only influence the prices in the energy market by demand shifting, but also participate in the reserve market. In this paper, we propose a full model of demand response in which demand flexibility is fully utilized by price responsive shiftable demand bids in energy market as well as spinning reserve bids in reserve market. A co-optimized day-ahead energy and spinning reserve market is proposed to minimize the expected net cost under all credible system states, i.e., expected total cost of operation minus total benefit of demand, and solved by mixed integer linear programming. Numerical simulation results on the IEEE Reliability Test System show effectiveness of this model. Compared to conventional demand shifting bids, the proposed full demand response model can further reduce committed capacity from generators, starting up and shutting down of units and the overall system operating costs.

  8. Developing a demand model integrating end uses of water (DMEUW): structure and process of integration.

    PubMed

    Sarker, R C; Gato-Trinidad, S

    2015-01-01

    The process of developing an integrated water demand model integrating end uses of water has been presented. The model estimates and forecasts average daily water demand based on the end-use pattern and trend of residential water consumption, daily rainfall and temperature, water restrictions and water conservation programmes. The end-use model uses the latest end-use data set collected from Yarra Valley Water, Australia. A computer interface has also been developed using hypertext markup language and hypertext pre-processor. The developed model can be used by water authorities and water resource planners in forecasting water demand and by household owners in determining household water consumption. PMID:25746644

  9. Appendix model performance - model documentation renewable fuels module of the National Energy Modeling System

    SciTech Connect

    Not Available

    1994-09-01

    This appendix discusses performance aspects of the Renewable Fuels Module (RFM). It is intended to present the pattern of response of the RFM to typical changes in its major inputs from other NEMS modules. The overall approach of this document, with the particular statistics presented, is designed to be comparable with similar analyses conducted for all of the modules of NEMS. While not always applicable, the overall approach has been to produce analyses and statistics that are as comparable as possible with model developer`s reports for other NEMS modules. Those areas where the analysis is somewhat limited or constrained are discussed. Because the RFM consists of independent submodules, this appendix is broken down by submodule.

  10. Residential energy demand models: Current status and future improvements

    NASA Astrophysics Data System (ADS)

    Peabody, G.

    1980-12-01

    Two models currently used to analyze energy use by the residential sector are described. The ORNL model is used to forecast energy use by fuel type for various end uses on a yearly basis. The MATH/CHRDS model analyzes variations in energy expenditures by households of various socioeconomic and demographic characteristics. The essential features of the ORNL and MATH/CHRDS models are retained in a proposed model and integrated into a framework that is more flexible than either model. The important determinants of energy use by households are reviewed.

  11. 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.

  12. 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

  13. 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

  14. MODELING SEDIMENT-NUTRIENT FLUX AND SEDIMENT OXYGEN DEMAND

    EPA Science Inventory

    This project builds upon previous advances in modeling bottom sediment processes in eutrophication models. It develops algorithms for simulating processes responsible for nitrogen (nitrate, ammonium, organic-N) and carbon transformation and cycling (organic-N and methane) in bott...

  15. Price and income elasticities of energy demand: Some estimates for Kuwait using two econometric models

    SciTech Connect

    Al-Mutairi, N.H.; Eltony, M.N.

    1995-12-31

    This paper estimates the demand for energy in Kuwait for the period 1965-1989 using two econometric models: a cointegration and error correction model (ECM) and a simultaneous-equation model (SEM). The results obtained from both models are similar. It is found that the energy demand is inelastic with respect to price in the short and long run, and while it is elastic in the long run, the energy demand is inelastic with respect to income in the short run. Both models` validation shows that the ECM performed better in replicating the past than the simultaneous model, suggesting the need to use the ECM to identify future prospects for energy demand in Kuwait.

  16. ReEDS Modeling of the President's 2020 U.S. Renewable Electricity Generation Goal (Presentation)

    SciTech Connect

    Zinaman, O.; Mai, T.; Lantz, E.; Gelman, R.; Porro, G.

    2014-05-01

    President Obama announced in 2012 an Administration Goal for the United States to double aggregate renewable electricity generation from wind, solar, and geothermal sources by 2020. This analysis, using the Regional Energy Deployment System (ReEDS) model, explores a full range of future renewable deployment scenarios out to 2020 to assess progress and outlook toward this goal. Under all modeled conditions, consisting of 21 scenarios, the Administration Goal is met before 2020, and as early as 2015.

  17. 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…

  18. 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…

  19. 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…

  20. 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…

  1. A new model for long-term global water demand projection

    NASA Astrophysics Data System (ADS)

    Chen, J.; Xing, B.; Shi, H.; Zhang, B.

    2015-12-01

    Rational projection of water demand is critically important to the future development of society. Achieving the desired accuracy for long-term water demand projection (WDP) is challenging due to the complex and uncertain relationships between water demand and various socio-economic indicators. At the same time, traditional forecasting methods, such as multivariate statistical analysis and time series analysis methods, are not adequate for long-term WDP because of the limitations in modelling structures. In this study, a five-staged WDP model is proposed and applied to the global WDPs. The hypothesis for the new model is that water demand is related to socio-economic development level. From the historic data in the Western Europe and United States, the five stages of water demand can be clearly observed. These stages are marked by evident change in water demand trend, and are categorized by the per capita GDP at that stage. The proposed WDP model is then validated with historic water consumption data in United Kingdom and Hong Kong, and the proposed model can explain the historic water consumption well. The developed five-staged WDP model is applied to the WDPs in Hong Kong and Pearl River Basin. Further, using the newly developed water consumption algorithm, this study investigates the global future water demand.

  2. Regression Models for Demand Reduction based on Cluster Analysis of Load Profiles

    SciTech Connect

    Yamaguchi, Nobuyuki; Han, Junqiao; Ghatikar, Girish; Piette, Mary Ann; Asano, Hiroshi; Kiliccote, Sila

    2009-06-28

    This paper provides new regression models for demand reduction of Demand Response programs for the purpose of ex ante evaluation of the programs and screening for recruiting customer enrollment into the programs. The proposed regression models employ load sensitivity to outside air temperature and representative load pattern derived from cluster analysis of customer baseline load as explanatory variables. The proposed models examined their performances from the viewpoint of validity of explanatory variables and fitness of regressions, using actual load profile data of Pacific Gas and Electric Company's commercial and industrial customers who participated in the 2008 Critical Peak Pricing program including Manual and Automated Demand Response.

  3. Model documentation renewable fuels module of the National Energy Modeling System

    SciTech Connect

    1997-04-01

    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 1997 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. This documentation report serves three purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Finally, such documentation facilitates continuity in EIA model development by providing information sufficient to perform model enhancements and data updates as part of EIA`s ongoing mission to provide analytical and forecasting information systems.

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

    SciTech Connect

    1995-02-01

    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. This report serves three purposes. First, it is a reference document providing a detailed description for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports (Public Law 93-275, section 57(b)(1)). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

  5. [The effects of the Demand-Support-Control model on construction workers' health].

    PubMed

    López-Araújo, Blanca; Osca Segovia, Amparo

    2011-02-01

    This work takes as reference the Demand-Control-Support model and analyzes the relation of job control and social support and some job demands and physical well-being in a sample of 285 construction workers. In general, job demands, exposure to harmful conditions, social support, and job control were found to be related to physical well-being. The modulator effects of job control and social support were verified. Job control modulates the negative effects of stress, mainly in situations of high demand. Moreover, social support modulates the negative effects of stress in situations of high exposure to harmful conditions. A three-way interaction effect was found but the increase in explained variance was not significant. Thus, the results do not reveal empirical evidence of the Demand-Control-Support model. The limitations and practical implications of this study are discussed. PMID:21266152

  6. 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..

  7. RENEW - MAINTENANCE ESTIMATION SIMULATION MODEL FOR SPACE STATION FREEDOM PROGRAM, VERSION 3.2

    NASA Technical Reports Server (NTRS)

    Bream, B. L.

    1994-01-01

    RENEW is a maintenance event estimation simulation program developed in support of the Space Station Freedom Program (SSFP) Work Package 4 at NASA Lewis Research Center. This simulation uses reliability and maintainability (R&M) data as well as logistics data to estimate both average and time dependent maintenance demands. RENEW 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 RENEW simulation gives closer estimates of performance than steady-state average calculations since it uses a time dependent approach and depicts more factors affecting ORU failure and repair. RENEW gives both average and time dependent demand values, and generates graphs of both failures over the mission period and yearly failure occurrences. The average 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 data tables. 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, and the parameters may be viewed and changed. 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. RENEW is written in BASIC and assembly language for IBM PC series and compatible computers running MS-DOS. Microsoft's QuickBasic Professional Development System and Crescent Software's QuickPak Professional are required to compile the source code. A CGA or VGA monitor is required. A sample executable is provided on the distribution media. The standard distribution medium for this program is one 5.25 inch 360K MS-DOS format diskette

  8. 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

  9. Demands for Partnership and Collaboration in Higher Education: A Model

    ERIC Educational Resources Information Center

    Amey, Marilyn J.; Eddy, Pamela L.; Ozaki, C. Casey

    2007-01-01

    This chapter describes a model that can serve as a lens for examining community college partnerships with a host of organizational collaborators, the overall potential for achieving intended outcomes, sustainability, and partner benefits. (Contains 1 figure.)

  10. Renewable Power Options for Electrical Generation on Kaua'i: Economics and Performance Modeling

    SciTech Connect

    Burman, K.; Keller, J.; Kroposki, B.; Lilienthal, P.; Slaughter, R.; Glassmire, J.

    2011-11-01

    The Hawaii Clean Energy Initiative (HCEI) is working with a team led by the U.S. Department of Energy's (DOE) National Renewable Energy Laboratory (NREL) to assess the economic and technical feasibility of increasing the contribution of renewable energy in Hawaii. This part of the HCEI project focuses on working with Kaua'i Island Utility Cooperative (KIUC) to understand how to integrate higher levels of renewable energy into the electric power system of the island of Kaua'i. NREL partnered with KIUC to perform an economic and technical analysis and discussed how to model PV inverters in the electrical grid.

  11. A Structural Model of Labor Supply and Child Care Demand.

    ERIC Educational Resources Information Center

    Michalopoulos, Charles; And Others

    1992-01-01

    With data from the Survey of Income Program Participation, a structural model analyzed decision to use child care of married and single mothers. Simulations indicated that a refundable child care tax credit would distribute child care benefits more equally and would also increase labor force participation of mothers. (SK)

  12. MODELING SEDIMENT-NUTRIENT FLUX AND SEDIMENT OXYGEN DEMAND

    EPA Science Inventory

    Depositional flux of particulate organic matter in bottom sediments affects nutrients cycling at the sediment-water interface and consumes oxygen from the overlying water in streams, lakes, and estuaries. This project deals with analytical modeling of nitrogen and carbon producti...

  13. Analysis of an Agent-based Electricity Market Model with Renewable Energy Power Plants by Wind and Solar Power

    NASA Astrophysics Data System (ADS)

    Iwagami, Akio; Suzuki, Hideyuki; Aihara, Kazuyuki

    In recent years, electricity markets were organized in many developed countries in the deregulation process of electric power industries. There have been many studies on electricity markets from the viewpoints of economics, mathematics, computer science, etc. Especially, agent-based models of electricity markets have been extensively studied. Meanwhile, many countries promote use of renewable energy for electricity generation. In this paper, we construct and analyze an agent-based model of electricity markets in which wind and photovoltaic power generation firms are introduced. Our results suggest that wind power generation needs to be improved in efficiency to survive in the market, and that bid prices of photovoltaic power generation are rather affected by change of the insolation amount than by change of the total demand.

  14. Model documentation report: Residential sector demand module of the National Energy Modeling System

    SciTech Connect

    1995-03-01

    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 document serves three purposes. First, it is a reference document providing a detailed description for energy analysts, other users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

  15. Model documentation report: Residential sector demand module of the National Energy Modeling System

    SciTech Connect

    1997-01-01

    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 document serves three purposes. First, it is a reference document that provides a detailed description for energy analysts, other users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

  16. On the Inclusion of Energy-Shifting Demand Response in Production Cost Models: Methodology and a Case Study

    SciTech Connect

    O'Connell, Niamh; Hale, Elaine; Doebber, Ian; Jorgenson, Jennie

    2015-07-20

    In the context of future power system requirements for additional flexibility, demand response (DR) is an attractive potential resource. Its proponents widely laud its prospective benefits, which include enabling higher penetrations of variable renewable generation at lower cost than alternative storage technologies, and improving economic efficiency. In practice, DR from the commercial and residential sectors is largely an emerging, not a mature, resource, and its actual costs and benefits need to be studied to determine promising combinations of physical DR resource, enabling controls and communications, power system characteristics, regulatory environments, market structures, and business models. The work described in this report focuses on the enablement of such analysis from the production cost modeling perspective. In particular, we contribute a bottom-up methodology for modeling load-shifting DR in production cost models. The resulting model is sufficiently detailed to reflect the physical characteristics and constraints of the underlying flexible load, and includes the possibility of capturing diurnal and seasonal variations in the resource. Nonetheless, the model is of low complexity and thus suitable for inclusion in conventional unit commitment and market clearing algorithms. The ability to simulate DR as an operational resource on a power system over a year facilitates an assessment of its time-varying value to the power system.

  17. Industrial process models of electricity demand. Volume 2. The pulp and paper industry. Final report

    SciTech Connect

    Pierce, B.L.; Pilati, D.A.; Chang, J.; Sparrow, F.T.

    1984-05-01

    The National Center for Analysis of Energy Systems at Brookhaven National Laboratory has developed a process model of the US pulp and paper industry. The model is based on data from economic and engineering analyses of the major manufacturing processes in pulp and papermaking and includes Standard Industrial Classifications 2611, 2621, 2631, and 2661. Energy conserving alternatives to conventional technologies are included. The pulp and paper model is a dynamic and regional process optimization model incorporating the Bureau of Census defined regions of the Northeast, North Central, South and West. It is dynamic in that it analyzes a 25-year time horizon. Given fuel prices and product demand projections, the model selects modes of operation and energy consumption characteristics that minimize the cost of meeting the projected demands. With a projected average annual growth rate of 3.3% for paper products, model results show a decline in the energy intensity of paper production and an increase in the demand for electricity.

  18. 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.

  19. Online, On Demand Access to Coastal Digital Elevation Models

    NASA Astrophysics Data System (ADS)

    Long, J.; Bristol, S.; Long, D.; Thompson, S.

    2014-12-01

    Process-based numerical models for coastal waves, water levels, and sediment transport are initialized with digital elevation models (DEM) constructed by interpolating and merging bathymetric and topographic elevation data. These gridded surfaces must seamlessly span the land-water interface and may cover large regions where the individual raw data sources are collected at widely different spatial and temporal resolutions. In addition, the datasets are collected from different instrument platforms with varying accuracy and may or may not overlap in coverage. The lack of available tools and difficulties in constructing these DEMs lead scientists to 1) rely on previously merged, outdated, or over-smoothed DEMs; 2) discard more recent data that covers only a portion of the DEM domain; and 3) use inconsistent methodologies to generate DEMs. The objective of this work is to address the immediate need of integrating land and water-based elevation data sources and streamline the generation of a seamless data surface that spans the terrestrial-marine boundary. To achieve this, the U.S. Geological Survey (USGS) is developing a web processing service to format and initialize geoprocessing tasks designed to create coastal DEMs. The web processing service is maintained within the USGS ScienceBase data management system and has an associated user interface. Through the map-based interface, users define a geographic region that identifies the bounds of the desired DEM and a time period of interest. This initiates a query for elevation datasets within federal science agency data repositories. A geoprocessing service is then triggered to interpolate, merge, and smooth the data sources creating a DEM based on user-defined configuration parameters. Uncertainty and error estimates for the DEM are also returned by the geoprocessing service. Upon completion, the information management platform provides access to the final gridded data derivative and saves the configuration parameters

  20. A comparison between the effort-reward imbalance and demand control models

    PubMed Central

    Ostry, Aleck S; Kelly, Shona; Demers, Paul A; Mustard, Cameron; Hertzman, Clyde

    2003-01-01

    Background To compare the predictive validity of the demand/control and reward/imbalance models, alone and in combination with each other, for self-reported health status and the self-reported presence of any chronic disease condition. Methods Self-reports for psychosocial work conditions were obtained in a sample of sawmill workers using the demand/control and effort/reward imbalance models. The relative predictive validity of task-level control was compared with effort/reward imbalance. As well, the predictive validity of a model developed by combining task-level control with effort/reward imbalance was determined. Logistic regression was utilized for all models. Results The demand/control and effort/reward imbalance models independently predicted poor self-reported health status. The effort-reward imbalance model predicted the presence of a chronic disease while the demand/control model did not. A model combining effort-reward imbalance and task-level control was a better predictor of self-reported health status and any chronic condition than either model alone. Effort reward imbalance modeled with intrinsic effort had marginally better predictive validity than when modeled with extrinsic effort only. Conclusions Future work should explore the combined effects of these two models of psychosocial stress at work on health more thoroughly. PMID:12636876

  1. 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.

  2. Development and Validation of Aggregated Models for Thermostatic Controlled Loads with Demand Response

    SciTech Connect

    Kalsi, Karanjit; Elizondo, Marcelo A.; Fuller, Jason C.; Lu, Shuai; Chassin, David P.

    2012-01-04

    Demand response is playing an increasingly important role in smart grid research and technologies being examined in recently undertaken demonstration projects. The behavior of load as it is affected by various load control strategies is important to understanding the degree to which different classes of end-use load can contribute to demand response programs at various times. This paper focuses on developing aggregated control models for a population of thermostatically controlled loads. The effects of demand response on the load population dynamics are investigated.

  3. Reduced-Order Modeling of Aggregated Thermostatic Loads With Demand Response

    SciTech Connect

    Zhang, Wei; Lian, Jianming; Chang, Chin-Yao; Kalsi, Karanjit; Sun, Yannan

    2012-12-12

    Demand Response is playing an increasingly important role in smart grid control strategies. Modeling the behavior of populations of appliances under demand response is especially important to evaluate the effectiveness of these demand response programs. In this paper, an aggregated model is proposed for a class of Thermostatically Controlled Loads (TCLs). The model efficiently includes statistical information of the population, systematically deals with heterogeneity, and accounts for a second-order effect necessary to accurately capture the transient dynamics in the collective response. However, an accurate characterization of the collective dynamics however requires the aggregate model to have a high state space dimension. Most of the existing model reduction techniques require the stability of the underlying system which does not hold for the proposed aggregated model. In this work, a novel model reduction approach is developed for the proposed aggregated model, which can significantly reduce its complexity with small performance loss. The original and the reducedorder aggregated models are validated against simulations of thousands of detailed building models using GridLAB-D, which is a realistic open source distribution simulation software. Index Terms – demand response, aggregated model, ancillary

  4. Modeling future demand for energy resources: A study of residential electricity usage in Thailand

    NASA Astrophysics Data System (ADS)

    Nilagupta, Prapassara

    1999-12-01

    Thailand has a critical need for effective long-term energy planning because of the country's rapidly increasing energy consumption. In this study, the demand for electricity by the residential sector is modeled using a framework that provides detailed estimates of the timing and spatial distribution of changes in energy demand. A population model was developed based on the Cohort-Component method to provide estimates of population by age, sex and urban/non-urban residency in each province. A residential electricity end user model was developed to estimate future electricity usage in urban and non-urban households of the seventy-six provinces in Thailand during the period 1999--2019. Key variables in this model include population, the number of households, family household size, and characteristics of eleven types of electric household appliance such as usage intensity, input power, and saturation rate. The methodology employed in this study is a trending method which utilizes expert opinion to estimate future variables based on a percentage change from the most current value. This study shows that from 1994 to 2019 Thailand will experience an increase in population from 55.4 to 83.6 million. Large percentage population increases will take place in Bangkok, Nonthaburi, Samut Prakarn, Nakhon Pathom and Chonburi. At a national level, the residential electricity consumption will increase from approximately 19,000 to 8 1,000 GWh annually. Consumption in non-urban households will be larger than in urban households, with respective annual increases of 8.0% and 6.2% in 2019. The percent increase of the average annual electricity consumption will be four times the average annual percent population increase. Increased electricity demand is largely a function of increased population and increased demand for high-energy appliances such as air conditioners. In 1994, air conditioning was responsible for xx% of total residential electricity demand. This study estimates that in

  5. Model documentation, Renewable Fuels Module of the National Energy Modeling System

    SciTech Connect

    1998-01-01

    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 Annual Energy Outlook 1998 (AEO98) 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. For AEO98, the RFM was modified in three principal ways, introducing capital cost elasticities of supply for new renewable energy technologies, modifying biomass supply curves, and revising assumptions for use of landfill gas from municipal solid waste (MSW). In addition, the RFM was modified in general to accommodate projections beyond 2015 through 2020. Two supply elasticities were introduced, the first reflecting short-term (annual) cost increases from manufacturing, siting, and installation bottlenecks incurred under conditions of rapid growth, and the second reflecting longer term natural resource, transmission and distribution upgrade, and market limitations increasing costs as more and more of the overall resource is used. Biomass supply curves were also modified, basing forest products supplies on production rather than on inventory, and expanding energy crop estimates to include states west of the Mississippi River using information developed by the Oak Ridge National Laboratory. Finally, for MSW, several assumptions for the use of landfill gas were revised and extended.

  6. Using count data and ordered models in national forest recreation demand analysis.

    PubMed

    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. PMID:23846130

  7. 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.

  8. 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. PMID:24274148

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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.

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

    SciTech Connect

    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.)

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

    SciTech Connect

    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.)

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

    SciTech Connect

    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.)

  17. 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…

  18. Burnout and Connectedness among Australian Volunteers: A Test of the Job Demands-Resources Model

    ERIC Educational Resources Information Center

    Lewig, Kerry A.; Xanthopoulou, Despoina; Bakker, Arnold B.; Dollard, Maureen F.; Metzer, Jacques C.

    2007-01-01

    This study used the Job Demands-Resources (JD-R) model, developed in the context of occupational well-being in the paid workforce, to examine the antecedents of burnout and connectedness in the formal volunteer rural ambulance officer vocation (N=487). Structural equation modeling using self-reports provide strong evidence for the central…

  19. The Future of Food Demand: Understanding Differences in Global Economic Models

    SciTech Connect

    Valin, Hugo; Sands, Ronald; van der Mensbrugghe, Dominique; Nelson, Gerald; Ahammad, Helal; Blanc, Elodie; Bodirsky, Benjamin; Fujimori, Shinichiro; Hasegawa, Tomoko; Havlik, Petr; Heyhoe, Edwina; Kyle, G. Page; Mason d'Croz, Daniel; Paltsev, S.; Rolinski, Susanne; Tabeau, Andrzej; van Meijl, Hans; von Lampe, Martin; Willenbockel, Dirk

    2014-01-01

    Understanding the capacity of agricultural systems to feed the world population under climate change requires a good prospective vision on the future development of food demand. This paper reviews modeling approaches from ten global economic models participating to the AgMIP project, in particular the demand function chosen and the set of parameters used. We compare food demand projections at the horizon 2050 for various regions and agricultural products under harmonized scenarios. Depending on models, we find for a business as usual scenario (SSP2) an increase in food demand of 59-98% by 2050, slightly higher than FAO projection (54%). The prospective for animal calories is particularly uncertain with a range of 61-144%, whereas FAO anticipates an increase by 76%. The projections reveal more sensitive to socio-economic assumptions than to climate change conditions or bioenergy development. When considering a higher population lower economic growth world (SSP3), consumption per capita drops by 9% for crops and 18% for livestock. Various assumptions on climate change in this exercise do not lead to world calorie losses greater than 6%. Divergences across models are however notable, due to differences in demand system, income elasticities specification, and response to price change in the baseline.

  20. A carbohydrate supply and demand model of vegetative growth: response to temperature and light.

    PubMed

    Gent, Martin P N; Seginer, Ido

    2012-07-01

    Photosynthesis is the limiting factor in crop growth models, but metabolism may also limit growth. We hypothesize that, over a wide range of temperature, growth is the minimum of the supply of carbohydrate from photosynthesis, and the demand of carbohydrate to synthesize new tissue. Biosynthetic demand limits growth at cool temperatures and increases exponentially with temperature. Photosynthesis limits growth at warm temperatures and decreases with temperature. Observations of tomato seedlings were used to calibrate a model based on this hypothesis. Model predictions were tested with published data for growth and carbohydrate content of sunflower and wheat. The model qualitatively fitted the response of growth of tomato and sunflower to both cool and warm temperatures. The transition between demand and supply limitation occurred at warmer temperatures under higher light and faster photosynthesis. Modifications were required to predict the observed non-structural carbohydrate (NSC). Some NSC was observed at warm temperatures, where demand should exceed supply. It was defined as a required reserve. Less NSC was found at cool temperatures than predicted from the difference between supply and demand. This was explained for tomato and sunflower, by feedback inhibition of NSC on photosynthesis. This inhibition was much less in winter wheat. PMID:22321060

  1. Renewable Energy Cost Modeling. A Toolkit for Establishing Cost-Based Incentives in the United States

    SciTech Connect

    Gifford, Jason S.; Grace, Robert C.; Rickerson, Wilson H.

    2011-05-01

    This report serves as a resource for policymakers who wish to learn more about levelized cost of energy (LCOE) calculations, including cost-based incentives. The report identifies key renewable energy cost modeling options, highlights the policy implications of choosing one approach over the other, and presents recommendations on the optimal characteristics of a model to calculate rates for cost-based incentives, FITs, or similar policies. These recommendations shaped the design of NREL's Cost of Renewable Energy Spreadsheet Tool (CREST), which is used by state policymakers, regulators, utilities, developers, and other stakeholders to assist with analyses of policy and renewable energy incentive payment structures. Authored by Jason S. Gifford and Robert C. Grace of Sustainable Energy Advantage LLC and Wilson H. Rickerson of Meister Consultants Group, Inc.

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

    SciTech Connect

    Stoll, Brady; Brinkman, Gregory; Townsend, Aaron; Bloom, 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 system 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 0.8% and 0

  3. Understanding the Effect of Baseline Modeling Implementation Choices on Analysis of Demand Response Performance

    SciTech Connect

    University of California, Berkeley; Addy, Nathan; Kiliccote, Sila; Mathieu, Johanna; Callaway, Duncan S.

    2012-06-13

    Accurate evaluation of the performance of buildings participating in Demand Response (DR) programs is critical to the adoption and improvement of these programs. Typically, we calculate load sheds during DR events by comparing observed electric demand against counterfactual predictions made using statistical baseline models. Many baseline models exist and these models can produce different shed calculations. Moreover, modelers implementing the same baseline model can make different modeling implementation choices, which may affect shed estimates. In this work, using real data, we analyze the effect of different modeling implementation choices on shed predictions. We focused on five issues: weather data source, resolution of data, methods for determining when buildings are occupied, methods for aligning building data with temperature data, and methods for power outage filtering. Results indicate sensitivity to the weather data source and data filtration methods as well as an immediate potential for automation of methods to choose building occupied modes.

  4. 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. PMID:27240240

  5. Modeling fossil energy demands of primary nonferrous metal production: the case of copper.

    PubMed

    Swart, Pilar; Dewulf, Jo

    2013-12-17

    The methodologies for life cycle impact assessment (LCIA) of metal resources are rather diverse. Some LCIA methods are based on ore grade changes, but they typically do not consider the impact of changes in primary metal extraction technology. To characterize the impact of technology changes for copper, we modeled and analyzed energy demand, expressed in fossil energy equivalents (FEE) per kilogram of primary copper, taking into account the applied mining method and processing technology. The model was able to capture variations in reported energy demands of selected mining sites (FEE: 0.07 to 0.84 MJ-eq/kg ore) with deviations of 1 to 30%. Applying the model to a database containing global mine production data resulted in energy demand median values of around 50 MJ/kg Cu irrespective of the processing route, even though median values of ore demands varied between processing routes from ca. 35 (underground, conventional processing) to 200 kg ore/kg Cu (open pit, solvent-extraction, and electrowinning), as high specific ore demands are typically associated with less energy intensive extraction technologies and vice versa. Thus, only considering ore grade in LCIA methods without making any differentiation with regard to employed technology can produce misleading results. PMID:24266773

  6. Aggregated Modeling of Thermostatic Loads in Demand Response: A Systems and Control Perspective

    SciTech Connect

    Kalsi, Karanjit; Chassin, Forrest S.; Chassin, David P.

    2011-12-12

    Demand response is playing an increasingly important role in smart grid research and technologies being examined in recently undertaken demonstration projects. The behavior of load as it is affected by various load control strategies is important to understanding the degree to which different classes of end-use load can contribute to demand response programs at various times. This paper focuses on developing aggregated models for a homogeneous population of thermostatically controlled loads. The different types of loads considered in this paper include, but are not limited to, water heaters and HVAC units. The effects of demand response and user over-ride on the load population dynamics are investigated. The controllability of the developed lumped models is validated which forms the basis for designing different control strategies.

  7. Modeling solute transport in distribution networks with variable demand and time step sizes.

    SciTech Connect

    Peyton, Chad E.; Bilisoly, Roger Lee; Buchberger, Steven G.; McKenna, Sean Andrew; Yarrington, Lane

    2004-06-01

    The effect of variable demands at short time scales on the transport of a solute through a water distribution network has not previously been studied. We simulate flow and transport in a small water distribution network using EPANET to explore the effect of variable demand on solute transport across a range of hydraulic time step scales from 1 minute to 2 hours. We show that variable demands at short time scales can have the following effects: smoothing of a pulse of tracer injected into a distribution network and increasing the variability of both the transport pathway and transport timing through the network. Variable demands are simulated for these different time step sizes using a previously developed Poisson rectangular pulse (PRP) demand generator that considers demand at a node to be a combination of exponentially distributed arrival times with log-normally distributed intensities and durations. Solute is introduced at a tank and at three different network nodes and concentrations are modeled through the system using the Lagrangian transport scheme within EPANET. The transport equations within EPANET assume perfect mixing of the solute within a parcel of water and therefore physical dispersion cannot occur. However, variation in demands along the solute transport path contribute to both removal and distortion of the injected pulse. The model performance measures examined are the distribution of the Reynolds number, the variation in the center of mass of the solute across time, and the transport path and timing of the solute through the network. Variation in all three performance measures is greatest at the shortest time step sizes. As the scale of the time step increases, the variability in these performance measures decreases. The largest time steps produce results that are inconsistent with the results produced by the smaller time steps.

  8. Surface-renewal models for heat-transfer between walls and fluidized beds

    NASA Technical Reports Server (NTRS)

    Patel, R. D.

    1969-01-01

    Two surface-renewed film penetration models describe transient heat-transfer between a wall and a fluidized bed. Methods are presented for estimation of mean residence times of particles at the transporting surface, their age densities and the average transport coefficients.

  9. 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...

  10. 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...

  11. Job strain (demands and control model) as a predictor of cardiovascular risk factors among petrochemical personnel

    PubMed Central

    Habibi, Ehsanollah; Poorabdian, Siamak; Shakerian, Mahnaz

    2015-01-01

    Background: One of the practical models for the assessment of stressful working conditions due to job strain is job demand and control model, which explains how physical and psychological adverse consequences, including cardiovascular risk factors can be established due to high work demands (the amount of workload, in addition to time limitations to complete that work) and low control of the worker on his/her work (lack of decision making) in the workplace. The aim of this study was to investigate how certain cardiovascular risk factors (including body mass index [BMI], heart rate, blood pressure, cholesterol and smoking) and the job demand and job control are related to each other. Materials and Methods: This prospective cohort study was conducted on 500 workers of the petrochemical industry in south of Iran, 2009. The study population was selected using simple random statistical method. They completed job demand and control questionnaire. The cardiovascular risk factors data was extracted from the workers hygiene profiles. Chi-square (χ2) test and hypothesis test (η) were used to assess the possible relationship between different quantified variables, individual demographic and cardiovascular risk factors. Results: The results of this study revealed that a significant relationship can be found between job demand control model and cardiovascular risk factors. Chi-square test result for the heart rate showed the highest (χ2 = 145.078) relationship, the corresponding results for smoking and BMI were χ2 = 85.652 and χ2 = 30.941, respectively. Subsequently, hypothesis testing results for cholesterol and hypertension was 0.469 and 0.684, respectively. Discussion: Job strain is likely to be associated with an increased risk of cardiovascular risk factors among male staff in a petrochemical company in Iran. The parameters illustrated in the Job demands and control model can act as acceptable predictors for the probability of job stress occurrence followed by showing

  12. Modeling demand and competing use of forestry commodities for material and energy use

    NASA Astrophysics Data System (ADS)

    Matzenberger, Julian

    2013-04-01

    Model-based scenarios of the global energy sector predict with high agreement that both demand and international trade of biomass will increase strongly over the coming years. Competition for forestry products (and by-products), particularly for low-grade goods, will increase in the coming years due to the growing demand for bioenergy. Modeling and describing the competition between material and energy use of biomass fractions is thus of crucial importance in energy-economic assessments and scenario-building but is, so far, in the fewest models mapped in detail. In scientific literature various approaches exist to formulate demand equations and interdependence due to competing uses. The complexity of the factors and interactions, which influence the demand for commodities from the forestry sector and biogenic fuels (as well as in principle all products and services), can, in general, only be captured to a certain degree by model equations. Usually far-reaching assumptions about function form of the demand need to be made. An innovative modeling approach, that is able to model demand patterns with uncertain function form, uses neural networks with multiple output variables in combination with system dynamic modeling. Neural networks allow integration of flexible function forms, whereas the iterative set up of system dynamic models allows a feedback with system variables and exogenous variables, such as economic growth, population or policy driven blend-in targets. An extensive database has been established, based on the FAO ForeStat database, the World Bank's world development indicators as well as other economic indicators. This global data set has been aggregated in a total of 30 world regions and several forest products (charcoal, firewood, fiberboard, paper fractions, etc.). It is shown, that a methodology can be developed, that principally enables to reflect the competing use of biogenic fuels, can be calibrated along historical data, and can be used to

  13. Projecting Electricity Demand in 2050

    SciTech Connect

    Hostick, Donna J.; Belzer, David B.; Hadley, Stanton W.; Markel, Tony; Marnay, Chris; Kintner-Meyer, Michael C. 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 data 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.

  14. Industrial process models of electricity demand. Volume 4. The aluminum industry. Final report

    SciTech Connect

    Pierce, B.L.; Coward, H.; Sparrow, F.T.; Pilati, D.A.

    1984-05-01

    The National Center for Analysis of Energy Systems at Brookhaven National Laboratory has developed a process model of the US aluminum industry. The model consists of the major process steps in the manufacture of milled and cast aluminum products and is designed to select modes of operation and energy consumption characteristics that minimize the cost of meeting projected demands for the industry's products. Domestic refineries and primary smelters are represented individually in the model. Industry structure in terms of plant ownership and allowed transfers of aluminum-bearing materials is explicitly modeled. With a growth in product demand of 4.2% per year, model results show a decline in electricity intensity of primary production.

  15. 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...

  16. Work at the Uddevalla Volvo Plant from the Perspective of the Demand-Control Model

    ERIC Educational Resources Information Center

    Lottridge, Danielle

    2004-01-01

    The Uddevalla Volvo plant represents a different paradigm for automotive assembly. In parallel-flow work, self-managed work groups assemble entire automobiles with comparable productivity as conventional series-flow assembly lines. From the perspective of the demand-control model, operators at the Uddevalla plant have low physical and timing…

  17. Predicting the impact of water demand and river flow regulation over riparian vegetation through mathematical modeling

    NASA Astrophysics Data System (ADS)

    Garcia-Arias, A.; Pons, C.; Frances, F.

    2013-12-01

    The vegetation of the riversides is a main part of the complex riparian ecosystems and has an important role maintaining the fluvial ecosystems. Biotic and abiotic interactions between the river and the riverbank are essential for the subsistence and the development of both ecosystems. In semi-arid Mediterranean areas, the riparian vegetation growth and distribution is especially controlled by the water accessibility, determining the limit between the lush riparian bands and the sparse upland. Human intervention can alter the river hydrology determining the riparian vegetation wellbeing and its distribution and, in consequence, affecting both riparian and fluvial ecosystems. Predictive models are necessary decision support tools for adequate river management and restoration initiatives. In this context, the RibAV model is useful to predict the impact of water demand and river flow regulation on the riparian vegetation. RibAV is able to reproduce the vegetation performance on the riverside allowing the scenarios analysis in terms of vegetation distribution and wellbeing. In this research several flow regulation and water demand scenarios are proposed and the impacts over three plant functional types (PFTs) are analyzed. The PFTs group the herbaceous riparian plants, the woody riparian plants and the terrestrial vegetation. The study site is the Terde reach at the Mijares River, a 539m length reach located in a semi-arid Mediterranean area in Spain. The scenarios represent river flow alterations required to attend different human demands. These demands encompass different seasonality, magnitude and location. The seasonality is represented as hydroelectric (constant all over the year), urban (increased during the summer period) and agricultural demands (monthly seasonality). The magnitude is varied considering the 20%, the 40% and the 80% of the mean daily flow. Two locations are considered, upstream or downstream the study site. To attend the demands located

  18. REVIEW: Zebrafish: A Renewed Model System For Functional Genomics

    NASA Astrophysics Data System (ADS)

    Wen, Xiao-Yan

    2008-01-01

    In the post genome era, a major goal in molecular biology is to determine the function of the many thousands of genes present in the vertebrate genome. The zebrafish (Danio rerio) provides an almost ideal genetic model to identify the biological roles of these novel genes, in part because their embryos are transparent and develop rapidly. The zebrafish has many advantages over mouse for genome-wide mutagenesis studies, allowing for easier, cheaper and faster functional characterization of novel genes in the vertebrate genome. Many molecular research tools such as chemical mutagenesis, transgenesis, gene trapping, gene knockdown, TILLING, gene targeting, RNAi and chemical genetic screen are now available in zebrafish. Combining all the forward, reverse, and chemical genetic tools, it is expected that zebrafish will make invaluable contribution to vertebrate functional genomics in functional annotation of the genes, modeling human diseases and drug discoveries.

  19. Forecasting Ability of a Multi-Renewal Seismicity Model

    NASA Astrophysics Data System (ADS)

    Molchan, George; Romashkova, Leontina

    2014-09-01

    The inter-event time (IET) is sometimes used as a basis for prediction of large earthquakes. It is the case when theoretical analysis of prediction is possible. Quite recently, a specific IET model was suggested for dynamic probabilistic prediction of events in Italy (http://earthquake.bo.ingv.it). In this study we analyze some aspects of the statistical estimation of the model and its predictive ability. We find that more or less effective prediction is possible within four out of 34 seismotectonic zones where seismicity rate or clustering of events is relatively high. We show that, in the framework of the model, one can suggest a simple zone-independent strategy, which practically optimizes the relative number of non-accidental successes, or the Hanssen-Kuiper (HK) skill score. This quasi-optimal strategy declares alarm in a zone for the first 2.67 years just after the occurrence of each large event in the zone. The optimal HK skill score values are about 26 % for the three most active zones, and 2-10 % for the 26 least active zones. However, the number of false alarm time intervals per one event in each of the zones is unusually high: about 0.7 and 0.8-0.95, respectively. Both these theoretical estimations are important because any prospective testing of the model is unrealistic in most of the zones during a reasonable time. This particular analysis requires a discussion of the following issues of general interest: a specific approach to the analysis of predictions vs. the standard CSEP testing approach; prediction vs. forecasting; HK skill score vs. probability gain; the total forecast error diagram and connected false alarms.

  20. Burnout in Medical Residents: A Study Based on the Job Demands-Resources Model

    PubMed Central

    2014-01-01

    Purpose. Burnout is a prolonged response to chronic emotional and interpersonal stressors on the job. The purpose of our cross-sectional study was to estimate the burnout rates among medical residents in the largest Greek hospital in 2012 and identify factors associated with it, based on the job demands-resources model (JD-R). Method. Job demands were examined via a 17-item questionnaire assessing 4 characteristics (emotional demands, intellectual demands, workload, and home-work demands' interface) and job resources were measured via a 14-item questionnaire assessing 4 characteristics (autonomy, opportunities for professional development, support from colleagues, and supervisor's support). The Maslach Burnout Inventory (MBI) was used to measure burnout. Results. Of the 290 eligible residents, 90.7% responded. In total 14.4% of the residents were found to experience burnout. Multiple logistic regression analysis revealed that each increased point in the JD-R questionnaire score regarding home-work interface was associated with an increase in the odds of burnout by 25.5%. Conversely, each increased point for autonomy, opportunities in professional development, and each extra resident per specialist were associated with a decrease in the odds of burnout by 37.1%, 39.4%, and 59.0%, respectively. Conclusions. Burnout among medical residents is associated with home-work interface, autonomy, professional development, and resident to specialist ratio. PMID:25531003

  1. A confirmatory investigation of a job demands-resources model using a categorical estimator.

    PubMed

    de Beer, Leon; Rothmann, Sebastiaan; Pienaar, Jaco

    2012-10-01

    A confirmatory investigation of a job demands-resources model was conducted with alternative methods, in a sample of 15,633 working adults aggregated from various economic sectors. The proposed model is in line with job demands-resources theory and assumes two psychological processes at work which are collectively coined "the dual process." The first process, the energetic, presents that job demands lead to ill-health outcomes due to burnout. The second process, the motivational, indicates that job resources lead to organizational commitment due to work engagement. Structural equation modelling analyses were implemented with a categorical estimator. Mediation analyses of each of the processes included bootstrapped indirect effects and kappa-squared values to apply qualitative labels to effect sizes. The relationship between job resources and organizational commitment was mediated by engagement with a large effect. The relationship between job demands and ill-health was mediated by burnout with a medium effect. The implications of the results for theory and practice were discussed. PMID:23234097

  2. 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.

  3. Modeling of GE Appliances in GridLAB-D: Peak Demand Reduction

    SciTech Connect

    Fuller, Jason C.; Vyakaranam, Bharat GNVSR; Prakash Kumar, Nirupama; Leistritz, Sean M.; Parker, Graham B.

    2012-04-29

    The widespread adoption of demand response enabled appliances and thermostats can result in significant reduction to peak electrical demand and provide potential grid stabilization benefits. GE has developed a line of appliances that will have the capability of offering several levels of demand reduction actions based on information from the utility grid, often in the form of price. However due to a number of factors, including the number of demand response enabled appliances available at any given time, the reduction of diversity factor due to the synchronizing control signal, and the percentage of consumers who may override the utility signal, it can be difficult to predict the aggregate response of a large number of residences. The effects of these behaviors can be modeled and simulated in open-source software, GridLAB-D, including evaluation of appliance controls, improvement to current algorithms, and development of aggregate control methodologies. This report is the first in a series of three reports describing the potential of GE's demand response enabled appliances to provide benefits to the utility grid. The first report will describe the modeling methodology used to represent the GE appliances in the GridLAB-D simulation environment and the estimated potential for peak demand reduction at various deployment levels. The second and third reports will explore the potential of aggregated group actions to positively impact grid stability, including frequency and voltage regulation and spinning reserves, and the impacts on distribution feeder voltage regulation, including mitigation of fluctuations caused by high penetration of photovoltaic distributed generation and the effects on volt-var control schemes.

  4. 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

  5. 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. PMID:26557718

  6. 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

  7. 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....

  8. A two process model of burnout and work engagement: distinct implications of demands and values.

    PubMed

    Leiter, M P

    2008-01-01

    A model of job burnout proposes two distinct processes. The first process concerns balance of demands to resources. A poor balance leads to chronic exhaustion, an integral aspect of the burnout syndrome. The second process concerns the congruence of individual and organizational values. The model proposes that value conflicts have implications for all three aspects of burnout. It also proposes that the impact of value conflicts has only minor implications for the exhaustion aspect of burnout; they are more relevant for the cynicism and inefficacy aspects of the syndrome. The model considers distinct processes at work that concern employees' perception of organizational justice and their trust in leadership. With a sample of 725 nurses, the analysis tested one component of the theory: the extent to which value congruence enhances the prediction of burnout beyond the prediction provided by demands and resources. Future directions are discussed. PMID:18700477

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

    SciTech Connect

    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 report 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).

  10. 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.

  11. Aggregated Modeling and Control of Air Conditioning Loads for Demand Response

    SciTech Connect

    Zhang, Wei; Lian, Jianming; Chang, Chin-Yao; Kalsi, Karanjit

    2013-06-21

    Demand response is playing an increasingly important role in the efficient and reliable operation of the electric grid. Modeling the dynamic behavior of a large population of responsive loads is especially important to evaluate the effectiveness of various demand response strategies. In this paper, a highly-accurate aggregated model is developed for a population of air conditioning loads. The model effectively includes statistical information of the population, systematically deals with load heterogeneity, and accounts for second-order dynamics necessary to accurately capture the transient dynamics in the collective response. Based on the model, a novel aggregated control strategy is designed for the load population under realistic conditions. The proposed controller is fully responsive and achieves the control objective without sacrificing end-use performance. The proposed aggregated modeling and control strategies are validated through realistic simulations using GridLAB-D. Extensive simulation results indicate that the proposed approach can effectively manage a large number of air conditioning systems to provide various demand response services, such as frequency regulation and peak load reduction.

  12. Modeling future water demand in California from developed and agricultural land uses

    NASA Astrophysics Data System (ADS)

    Wilson, T. S.; Sleeter, B. M.; Cameron, D. R.

    2015-12-01

    Municipal and urban land-use intensification in coming decades will place increasing pressure on water resources in California. The state is currently experiencing one of the most extreme droughts on record. This coupled with earlier spring snowmelt and projected future climate warming will increasingly constrain already limited water supplies. The development of spatially explicit models of future land use driven by empirical, historical land use change data allow exploration of plausible LULC-related water demand futures and potential mitigation strategies. We utilized the Land Use and Carbon Scenario Simulator (LUCAS) state-and-transition simulation model to project spatially explicit (1 km) future developed and agricultural land use from 2012 to 2062 and estimated the associated water use for California's Mediterranean ecoregions. We modeled 100 Monte Carlo simulations to better characterize and project historical land-use change variability. Under current efficiency rates, total water demand was projected to increase 15.1% by 2062, driven primarily by increases in urbanization and shifts to more water intensive crops. Developed land use was projected to increase by 89.8%-97.2% and result in an average 85.9% increase in municipal water use, while agricultural water use was projected to decline by approximately 3.9%, driven by decreases in row crops and increases in woody cropland. In order for water demand in 2062 to balance to current demand levels, the currently mandated 25% reduction in urban water use must remain in place in conjunction with a near 7% reduction in agricultural water use. Scenarios of land-use related water demand are useful for visualizing alternative futures, examining potential management approaches, and enabling better informed resource management decisions.

  13. 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.

  14. 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

  15. Estimating the population benefit of radiotherapy: using demand models to estimate achievable cancer outcomes.

    PubMed

    Hanna, T P; Shafiq, J

    2015-02-01

    The measurement of population benefits is important for priority setting, economic evaluation and quality improvement. It also informs advocacy. In this article, the use of demand models to estimate the achievable benefit of cancer therapy is reviewed. Achievable benefit refers to the treatment benefit achievable under optimal conditions. The population benefit of radiotherapy has been used as an example. Demand models provide a means of estimating the optimal proportion of patients with treatment indications when guidelines are followed. They may be used to estimate achievable benefit. The choice of end point should reflect the range of benefits associated with the treatment of interest. In some cases, further model development is needed if a pre-existing demand model is used. The benefit of treatment for each indication is estimated using a systematic review process. The highest level of evidence is used to define the benefit for each indication. In cases where multiple sources of the same level and quality of evidence exist, a meta-analysis is carried out. Population-based effectiveness data sources are considered, but three major challenges to their use are: (i) generalisability of the observed outcomes, (ii) data resolution and (iii) confounding and bias. The population benefit determined from this process describes the population proportion achieving a benefit due to the use of guideline-based treatment, compared with no use of that treatment. Sensitivity analysis provides a means for modelling the effect of model uncertainties. The predominant uncertainty is most often due to uncertainty in indication proportion. Preference-sensitive treatment decisions are a common example. The described approach to estimating the achievable benefit of cancer therapy is robust to model uncertainties, rapidly adaptable and is transparent. However, estimates rely on the quality of model data sources and may be affected by model assumptions. Models should be developed for a

  16. Urban water demand forecasting and uncertainty assessment using ensemble wavelet-bootstrap-neural network models

    NASA Astrophysics Data System (ADS)

    Tiwari, Mukesh K.; Adamowski, Jan

    2013-10-01

    A new hybrid wavelet-bootstrap-neural network (WBNN) model is proposed in this study for short term (1, 3, and 5 day; 1 and 2 week; and 1 and 2 month) urban water demand forecasting. The new method was tested using data from the city of Montreal in Canada. The performance of the WBNN method was compared with the autoregressive integrated moving average (ARIMA) and autoregressive integrated moving average model with exogenous input variables (ARIMAX), traditional NNs, wavelet analysis-based NNs (WNN), bootstrap-based NNs (BNN), and a simple naïve persistence index model. The WBNN model was developed as an ensemble of several NNs built using bootstrap resamples of wavelet subtime series instead of raw data sets. The results demonstrated that the hybrid WBNN and WNN models produced significantly more accurate forecasting results than the traditional NN, BNN, ARIMA, and ARIMAX models. It was also found that the WBNN model reduces the uncertainty associated with the forecasts, and the performance of WBNN forecasted confidence bands was found to be more accurate and reliable than BNN forecasted confidence bands. It was found in this study that maximum temperature and total precipitation improved the accuracy of water demand forecasts using wavelet analysis. The performance of WBNN models was also compared for different numbers of bootstrap resamples (i.e., 25, 50, 100, 200, and 500) and it was found that WBNN models produced optimum results with different numbers of bootstrap resamples for different lead time forecasts with considerable variability.

  17. Modeling regional crop yield and irrigation demand using SMAP type of soil moisture data

    NASA Astrophysics Data System (ADS)

    El Sharif, H. A.; Wang, J.; Georgakakos, A. P.; Bras, R. L.

    2013-12-01

    Agricultural models, such as Decision Support System for Agrotechnology Transfer - Cropping Systems Model (DSSAT-CSM) (Tsuji, et al., 1994), have been developed to predict the yield of various crops at field and regional scales. The model simulations of crop yields provide essential information for water resources management. One key input of the agricultural models is soil moisture. So far there are no observed soil moisture data covering the entire US with adequate time (daily) and space (1 km or less) resolutions preferred for model simulation of crop yields. Spatially and temporally downscaled data from the upcoming Soil Moisture Active Passive (SMAP) mission can fill this data gap through the generation of fine resolution soil moisture maps that can be incorporated into DSSAT-CSM model. This study will explore the impact downscaled remotely-sensed soil moisture data can have on agricultural model forecasts of agricultural yield and irrigation demand using synthetically generated data sets exhibiting statistical characteristics (uncertainty) similar to the upcoming SMAP products. It is expected that incorporating this data into agricultural model will prove especially useful for cases in which soil water conductivity characteristics and/or precipitation amount at a specific site of interest are not fully known; furthermore, a proposed Bayesian analysis is expected to generate a soil moisture sequence that reduces the uncertainty in modeled yield and irrigation demand compared to using downscaled remotely-sensed soil moisture or precipitation data alone. References Tsuji, G., Uehara, G., and Balas, S. (1994). DSSAT V3, University of Hawaii, Honolulu.

  18. Analysis of Neural-BOLD Coupling Through Four Models of the Neural Metabolic Demand

    PubMed Central

    Tyler, Christopher W.; Likova, Lora T.; Nicholas, Spero C.

    2015-01-01

    The coupling of the neuronal energetics to the blood-oxygen-level-dependent (BOLD) response is still incompletely understood. To address this issue, we compared the fits of four plausible models of neurometabolic coupling dynamics to available data for simultaneous recordings of the local field potential and the local BOLD response recorded from monkey primary visual cortex over a wide range of stimulus durations. The four models of the metabolic demand driving the BOLD response were: direct coupling with the overall LFP; rectified coupling to the LFP; coupling with a slow adaptive component of the implied neural population response; and coupling with the non-adaptive intracellular input signal defined by the stimulus time course. Taking all stimulus durations into account, the results imply that the BOLD response is most closely coupled with metabolic demand derived from the intracellular input waveform, without significant influence from the adaptive transients and nonlinearities exhibited by the LFP waveform. PMID:26696806

  19. Two-echelon competitive integrated supply chain model with price and credit period dependent demand

    NASA Astrophysics Data System (ADS)

    Pal, Brojeswar; Sankar Sana, Shib; Chaudhuri, Kripasindhu

    2016-04-01

    This study considers a two-echelon competitive supply chain consisting of two rivaling retailers and one common supplier with trade credit policy. The retailers hope that they can enhance their market demand by offering a credit period to the customers and the supplier also offers a credit period to the retailers. We assume that the market demand of the products of one retailer depends not only on their own market price and offering a credit period to the customers, but also on the market price and offering a credit period of the other retailer. The supplier supplies the product with a common wholesale price and offers the same credit period to the retailers. We study the model under a centralised (integrated) case and a decentralised (Vertical Nash) case and compare them numerically. Finally, we investigate the model by the collected numerical data.

  20. 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. PMID:22774440

  1. The demand for health: an empirical test of the Grossman model using panel data.

    PubMed

    Nocera, S; Zweifel, P

    1998-01-01

    Grossman derives the demand for health from an optimal control model in which health capital is both a consumption and an investment good. In his approach, the individual chooses his level of health and therefore his life span. Initially an individual is endowed with a certain amount of health capital, which depreciates over time but can be replenished by investments like medical care, diet, exercise, etc. Therefore, the level of health is not treated as exogenous but depends on the amount of resources the individual allocates to the production of health. The production of health capital also depends on variables which modify the efficiency of the production process, therefore changing the shadow price of health capital. For example, more highly educated people are expected to be more efficient producers of health who thus face a lower price of health capital, an effect that should increase their quantity of health demanded. While the Grossman model provides a suitable theoretical framework for explaining the demand for health and the demand for medical services, it has not been too successful empirically. However, empirical tests up to this date have been exclusively based on cross section data, thus failing to take the dynamic nature of the Grossman model into account. By way of contrast, the present paper contains individual time series information not only on the utilization of medical services but also on income, wealth, work, and life style. The data come from two surveys carried out in 1981 and 1993 among members of a Swiss sick fund, with the linkage between the two waves provided by insurance records. In all, this comparatively rich data set holds the promise of permitting the Grossman model to be adequately tested for the first time. PMID:10662408

  2. Effect of chlorine demand on the ammonia breakpoint curve: model development, validation with nitrite, and application to municipal wastewater.

    PubMed

    Chen, W L; Jensen, J N

    2001-01-01

    Chlorine added during wastewater disinfection may be consumed through reactions with chlorine-demanding chemical species. In this study, a mechanistically based kinetic model for chlorine demand in the presence of ammonia was developed and validated with laboratory studies on ammonia-nitrite systems, and then applied to breakpoint curves obtained with wastewater samples. The model is a modification of kinetic models for chlorine-ammonia systems to include hypochlorous acid-demand and monochloramine-demand reactions. The model accurately describes both laboratory-generated breakpoint curves with added nitrite and literature data. In a plant thought to be undergoing partial nitrification, breakpoint curves were consistent with high chlorine demand (i.e., small initial slopes and large doses to achieve the total chlorine maximum and breakpoint). A simplified kinetic model was also developed. Chlorine demand calculated from the simplified model was similar to chlorine demand from plant data. The simplified model was used to generate operating guidelines to calculate chlorine doses needed to overcome demand from nitrite or other sources. PMID:11833766

  3. Energy system modelling - interactions and synergies in a highly renewable Pan-European power system

    NASA Astrophysics Data System (ADS)

    Weitemeyer, Stefan; Kleinhans, David; Vogt, Thomas; Agert, Carsten

    2014-12-01

    It is very likely that the European power supply system will be transformed in the next decades to a low carbon system based almost entirely on Renewable Energy Sources (RES). However, due to the natural fluctuations of the most powerful RES (wind and solar energy), it is also very likely that a significant amount of balancing and controllable backup power capacities will be required to ensure a stable grid operation. This implies high additional investments and operating costs. Therefore this work provides an overview of potential options and possibly more cost-effective alternatives to the installation of costly storage capacities, namely grid expansion, demand side management, an optimised mix between different RES as well as the use of overcapacities. Furthermore, the paper provides an approximation of the maximum RES penetration of the German electricity system in the absence of significant storage capacities. Our calculations show that from a numerical perspective on average approximately half of the load can be met by RES if flexible conventional power stations would provide the remaining electricity demand. However, in a 100% RES scenario a significant amount of storage capacities as well as limited overcapacities are required to ensure a reliable electricity supply.

  4. Examining Uncertainty in Demand Response Baseline Models and Variability in Automated Response to Dynamic Pricing

    SciTech Connect

    Mathieu, Johanna L.; Callaway, Duncan S.; Kiliccote, Sila

    2011-08-15

    Controlling electric loads to deliver power system services presents a number of interesting challenges. For example, changes in electricity consumption of Commercial and Industrial (C&I) facilities are usually estimated using counterfactual baseline models, and model uncertainty makes it difficult to precisely quantify control responsiveness. Moreover, C&I facilities exhibit variability in their response. This paper seeks to understand baseline model error and demand-side variability in responses to open-loop control signals (i.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR) parameters, which characterize changes in electricity use on DR days, and then present a method for computing the error associated with DR parameter estimates. In addition to analyzing the magnitude of DR parameter error, we develop a metric to determine how much observed DR parameter variability is attributable to real event-to-event variability versus simply baseline model error. Using data from 38 C&I facilities that participated in an automated DR program in California, we find that DR parameter errors are large. For most facilities, observed DR parameter variability is likely explained by baseline model error, not real DR parameter variability; however, a number of facilities exhibit real DR parameter variability. In some cases, the aggregate population of C&I facilities exhibits real DR parameter variability, resulting in implications for the system operator with respect to both resource planning and system stability.

  5. 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.

  6. Research on the evolution model of an energy supply-demand network

    NASA Astrophysics Data System (ADS)

    Sun, Mei; Zhang, Pei-Pei; Shan, Tian-Hua; Fang, Cui-Cui; Wang, Xiao-Fang; Tian, Li-Xin

    2012-10-01

    A universal bipartite model is proposed based on an energy supply-demand network. The analytical expression of SPL distribution of the node weight, the “shifting coefficient” α and the scaling exponent γ are presented without edge weight growth by using the mean-field theory approach. The numerical results of SPL distribution of the node weight, the “shifting coefficient” α and the scaling exponent γ with edge weight growth are also presented. The production's SPL distribution of the US coal enterprizes from 1991 to 2009 is obtained from the empirical analysis. The numerical results obtained from the model are in good agreement with the empirical results.

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

    SciTech Connect

    Gallo, Giulia

    2015-10-07

    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. 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.

  8. Impacts of increased bioenergy demand on global food markets: an AgMIP economic model intercomparison

    SciTech Connect

    Lotze-Campen, Hermann; von Lampe, Martin; Kyle, G. Page; Fujimori, Shinichiro; Havlik, Petr; van Meijl, Hans; Hasegawa, Tomoko; Popp, Alexander; Schmitz, Christoph; Tabeau, Andrzej; Valin, Hugo; Willenbockel, Dirk; Wise, Marshall A.

    2014-01-01

    Integrated Assessment studies have shown that meeting ambitious greenhouse gas mitigation targets will require substantial amounts of bioenergy as part of the future energy mix. In the course of the Agricultural Model Comparison and Improvement Project (AgMIP), five global agro-economic models were used to analyze a future scenario with global demand for ligno-cellulosic bioenergy rising to about 100 ExaJoule in 2050. From this exercise a tentative conclusion can be drawn that ambitious climate change mitigation need not drive up global food prices much, if the extra land required for bioenergy production is accessible or if the feedstock, e.g. from forests, does not directly compete for agricultural land. Agricultural price effects across models by the year 2050 from high bioenergy demand in an RCP2.6-type scenario appear to be much smaller (+5% average across models) than from direct climate impacts on crop yields in an RCP8.5-type scenario (+25% average across models). However, potential future scarcities of water and nutrients, policy-induced restrictions on agricultural land expansion, as well as potential welfare losses have not been specifically looked at in this exercise.

  9. 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

  10. Availability analysis of subsea blowout preventer using Markov model considering demand rate

    NASA Astrophysics Data System (ADS)

    Kim, Sunghee; Chung, Soyeon; Yang, Youngsoon

    2014-12-01

    Availabilities of subsea Blowout Preventers (BOP) in the Gulf of Mexico Outer Continental Shelf (GoM OCS) is investigated using a Markov method. An updated β factor model by SINTEF is used for common-cause failures in multiple redundant systems. Coefficient values of failure rates for the Markov model are derived using the β factor model of the PDS (reliability of computer-based safety systems, Norwegian acronym) method. The blind shear ram preventer system of the subsea BOP components considers a demand rate to reflect reality more. Markov models considering the demand rate for one or two components are introduced. Two data sets are compared at the GoM OCS. The results show that three or four pipe ram preventers give similar availabilities, but redundant blind shear ram preventers or annular preventers enhance the availability of the subsea BOP. Also control systems (PODs) and connectors are contributable components to improve the availability of the subsea BOPs based on sensitivity analysis.

  11. Sensor Management for Applied Research Technologies (SMART)-On Demand Modeling (ODM) Project

    NASA Technical Reports Server (NTRS)

    Goodman, M.; Blakeslee, R.; Hood, R.; Jedlovec, G.; Botts, M.; Li, X.

    2006-01-01

    NASA requires timely on-demand data and analysis capabilities to enable practical benefits of Earth science observations. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep learning curve associated with each sensor and data type. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output. A three year project, entitled Sensor Management for Applied Research Technologies (SMART) - On Demand Modeling (ODM), will develop and demonstrate the readiness of Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities that integrate both Earth observations and forecast model output into new data acquisition and assimilation strategies. The advancement of SWE-enabled systems (i.e., use of SensorML, sensor planning services - SPS, sensor observation services - SOS, sensor alert services - SAS and common observation model protocols) will have practical and efficient uses in the Earth science community for enhanced data set generation, real-time data assimilation with operational applications, and for autonomous sensor tasking for unique data collection.

  12. Analysis of credit linked demand in an inventory model with varying ordering cost.

    PubMed

    Banu, Ateka; Mondal, Shyamal Kumar

    2016-01-01

    In this paper, we have considered an economic order quantity model for deteriorating items with two-level trade credit policy in which a delay in payment is offered by a supplier to a retailer and also an another delay in payment is offered by the retailer to his/her all customers. Here, it is proposed that the demand function is dependent on the length of the customer's credit period and also the duration of offering the credit period. In this article, it is considered that the retailer's ordering cost per order depends on the number of replenishment cycles. The objective of this model is to establish a deterministic EOQ model of deteriorating items for the retailer to decide the position of customers credit period and the number of replenishment cycles in finite time horizon such that the retailer gets the maximum profit. Also, the model is explained with the help of some numerical examples. PMID:27386370

  13. Inverse calculation of biochemical oxygen demand models based on time domain for the tidal Foshan River.

    PubMed

    Er, Li; Xiangying, Zeng

    2014-01-01

    To simulate the variation of biochemical oxygen demand (BOD) in the tidal Foshan River, inverse calculations based on time domain are applied to the longitudinal dispersion coefficient (E(x)) and BOD decay rate (K(x)) in the BOD model for the tidal Foshan River. The derivatives of the inverse calculation have been respectively established on the basis of different flow directions in the tidal river. The results of this paper indicate that the calculated values of BOD based on the inverse calculation developed for the tidal Foshan River match the measured ones well. According to the calibration and verification of the inversely calculated BOD models, K(x) is more sensitive to the models than E(x) and different data sets of E(x) and K(x) hardly affect the precision of the models. PMID:25026574

  14. 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

  15. Characterization of Cardiovascular Outcomes in a Type 2 Diabetes Glucose Supply and Insulin Demand Model

    PubMed Central

    Monte, Scott V.; Schentag, Jerome J.; Adelman, Martin H.; Paladino, Joseph A.

    2010-01-01

    Background The nonsignificant reduction in macrovascular outcomes observed in Action to Control Cardiovascular Risk in Diabetes; Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation; and the Veterans Affairs Diabetes Trial have collectively created uncertainty with respect toward the proper extent of blood glucose reduction and also the optimal therapeutic choice to attain the reduction. In the article entitled “Glucose Supply and Insulin Demand Dynamics of Antidiabetic Agents” in this issue of Journal of Diabetes Science and Technology, we presented data for a pharmacokinetic/pharmacodynamic model that characterizes the effect of conventional antidiabetic therapies on the glucose supply and insulin demand dynamic. Here, it is our objective to test the hypothesis that, in conjunction with hemoglobin A1c (HbA1c), patients managed on the glucose supply side of the model would have fewer cardiovascular events versus those managed on the insulin demand side. Methods To test this hypothesis, the electronic medical records of a group model health maintenance organization were queried to compile a population of patients meeting the following inclusion criteria: (1) type 2 diabetes mellitus (T2DM), (2) known date of T2DM diagnosis; (3) ICD-9 or CPT code identification and chart review confirmation of a first major cardiovascular event (myocardial infarction, coronary artery bypass graft, or angioplasty),(4) five years of continuous eligibility, and (5) on antidiabetic therapy at the beginning of the 5-year observation period. These patients were subsequently matched (1:1) to T2DM patients meeting the same criteria who had not experienced an event and were analyzed for differences in glucose control (HbA1C), the glucose supply:insulin demand dynamic (SD ratio), and categorical combinations of both parameters. Results Fifty cardiovascular event patients met inclusion criteria and were matched to controls. No difference

  16. Issues facing the future health care workforce: the importance of demand modelling.

    PubMed

    Segal, Leonie; Bolton, Tom

    2009-01-01

    allocation methods, such as the personnel-to-population ratios which are essentially circular in their rationale rather than evidence-based. This article highlights the importance of evidence-based demand modelling for those seeking to plan for the future Australian health care workforce. A model based on population health status and best practice protocols for health care is briefly outlined. PMID:19422686

  17. Can an Opportunity to Learn at Work Reduce Stress?: A Revisitation of the Job Demand-Control Model

    ERIC Educational Resources Information Center

    Panari, Chiara; Guglielmi, Dina; Simbula, Silvia; Depolo, Marco

    2010-01-01

    Purpose: This paper aims to extend the stress-buffering hypothesis of the demand-control model. In addition to the control variable, it seeks to analyse the role of an opportunity for learning and development (L&D) in the workplace as a moderator variable between increased demands and need for recovery. Design/methodology/approach: A questionnaire…

  18. The General Evolving Model for Energy Supply-Demand Network with Local-World

    NASA Astrophysics Data System (ADS)

    Sun, Mei; Han, Dun; Li, Dandan; Fang, Cuicui

    2013-10-01

    In this paper, two general bipartite network evolving models for energy supply-demand network with local-world are proposed. The node weight distribution, the "shifting coefficient" and the scaling exponent of two different kinds of nodes are presented by the mean-field theory. The numerical results of the node weight distribution and the edge weight distribution are also investigated. The production's shifted power law (SPL) distribution of coal enterprises and the installed capacity's distribution of power plants in the US are obtained from the empirical analysis. Numerical simulations and empirical results are given to verify the theoretical results.

  19. Can stochastic renewal of maps be a model for cerebral cortex?

    NASA Astrophysics Data System (ADS)

    Tsuda, Ichiro

    1994-08-01

    We introduce a new type of stochastic dynamics as stochastic renewal of maps, relating to the neurodynamics of cortical memory process. This stochastic dynamics can be reformulated by a skew product transformation of two kinds of variables, one of which describes an underlying dynamical system and the other describes chaotic dynamics, say, Bernoulli shift. The feature of orbits in phase space is investigated in the particular case of a neurodynamics model for cortical chaotic memories. A new computational result on the functional role of cortical chaos is obtained. We also present a neurobiological interpretation of psychological perception and memories by means of the notion of chaotic itinerancy.

  20. A two-equation integral model for particle transport in renewal statistical media

    SciTech Connect

    Zuchuat, O.; Sanchez, R.

    1995-12-31

    The authors consider the problem of particle transport including scattering in renewal statistical media. The general description of this problem leads to an infinite hierarchy of equations. A new closure scheme is developed to obtain a more tractable set of equations. Numerical results in planar geometry are given which compare the predictions of this new closure with exact benchmark results as well as with a previous model available in the literature. The development of the new closure and the comparisons the authors make underline the importance of having a physical basis in the elaboration of closure schemes for the hierarchy of equations describing the transport of particle with collisions in stochastic mixtures.

  1. A comparison of coal supply-demand in China and in the US based on a network model

    NASA Astrophysics Data System (ADS)

    Fang, Cui-Cui; Sun, Mei; Zhang, Pei-Pei; Gao, An-Na

    2013-10-01

    Through analysis the actual coal supply and demand in the US and China, the properties of the coal supply-demand market in both countries are investigated based on the energy supply-demand network. The validity of our model is verified by comparing numerical results with empirical results. The comparison of empirical results and the comparison of coal network model parameters between in the US and in China reveal the essence of the internal differences and similarities of coal supply and demand in these two countries. The third stage of China's coal network was close to that of the US in 1995, indicating that the evolutional situation of China's coal market begins to transit to an oligopolistic type. Finally, suggestions for China's coal supply-demand strategy are put forward.

  2. Development of Extended Period Pressure-Dependent Demand Water Distribution Models

    SciTech Connect

    Judi, David R.; Mcpherson, Timothy N.

    2015-03-20

    Los Alamos National Laboratory (LANL) has used modeling and simulation of water distribution systems for N-1 contingency analyses to assess criticality of water system assets. Critical components considered in these analyses include pumps, tanks, and supply sources, in addition to critical pipes or aqueducts. A contingency represents the complete removal of the asset from system operation. For each contingency, an extended period simulation (EPS) is run using EPANET. An EPS simulates water system behavior over a time period, typically at least 24 hours. It assesses the ability of a system to respond and recover from asset disruption through distributed storage in tanks throughout the system. Contingencies of concern are identified as those in which some portion of the water system has unmet delivery requirements. A delivery requirement is defined as an aggregation of water demands within a service area, similar to an electric power demand. The metric used to identify areas of unmet delivery requirement in these studies is a pressure threshold of 15 pounds per square inch (psi). This pressure threshold is used because it is below the required pressure for fire protection. Any location in the model with pressure that drops below this threshold at any time during an EPS is considered to have unmet service requirements and is used to determine cascading consequences. The outage area for a contingency is the aggregation of all service areas with a pressure below the threshold at any time during the EPS.

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

    SciTech Connect

    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 North 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.

  4. Integrating Land Conservation and Renewable Energy Goals in California: Assessing Land Use and Economic Cost Impacts Using the Optimal Renewable Energy Build-Out (ORB) Model.

    NASA Astrophysics Data System (ADS)

    Wu, G. C.; Schlag, N. H.; Cameron, D. R.; Brand, E.; Crane, L.; Williams, J.; Price, S.; Hernandez, R. R.; Torn, M. S.

    2015-12-01

    There is a lack of understanding of the environmental impacts and economic costs of potential renewable energy (RE) siting decisions that achieve ambitious RE targets. Such analyses are needed to inform policy recommendations that minimize potential conflicts between conservation and RE development. We use the state of California's rapid development of utility-scale RE as a case study to examine how possible land use constraints impact the total electricity land area, areas with conservation value, water use, and electricity cost of ambitious RE portfolios. We developed the Optimal Renewable energy Build-out (ORB) model, and used it in conjunction with the Renewable Portfolio Standard (RPS) Calculator, a RE procurement and transmission planning tool used by utilities within California, to generate environmentally constrained renewable energy potential and assess the cost and siting-associated impacts of wind, solar photovoltaic, concentrating solar power (CSP), and geothermal technologies. We find that imposing environmental constraints on RE development achieves lower conservation impacts and results in development of more fragmented land areas. With increased RE and environmental exclusions, generation becomes more widely distributed across the state, which results in more development on herbaceous agricultural vegetation, grasslands, and developed & urban land cover types. We find land use efficiencies of RE technologies are relatively inelastic to changes in environmental constraints, suggesting that cost-effective substitutions that reduce environmental impact and achieve RE goals is possible under most scenarios and exclusion categories. At very high RE penetration that is limited to in-state development, cost effectiveness decreases substantially under the highest level of environmental constraint due to the over-reliance on solar technologies. This additional cost is removed once the in-state constraint is lifted, suggesting that minimizing both negative

  5. Developing Passenger Demand Models for International Aviation from/to Egypt: A Case Study of Cairo Airport and Egyptair

    NASA Technical Reports Server (NTRS)

    Abbas, Khaled A.; Fattah, Nabil Abdel; Reda, Hala R.

    2003-01-01

    This research is concerned with developing passenger demand models for international aviation from/to Egypt. In this context, aviation sector in Egypt is represented by the biggest and main airport namely Cairo airport as well as by the main Egyptian international air carrier namely Egyptair. The developed models utilize two variables to represent aviation demand, namely total number of international flights originating from and attracted to Cairo airport as well as total number of passengers using Egyptair international flights originating from and attracted to Cairo airport. Such demand variables were related, using different functional forms, to several explanatory variables including population, GDP and number of foreign tourists. Finally, two models were selected based on their logical acceptability, best fit and statistical significance. To demonstrate usefulness of developed models, these were used to forecast future demand patterns.

  6. A Coupled Snow Operations-Skier Demand Model for the Ontario (Canada) Ski Region

    NASA Astrophysics Data System (ADS)

    Pons, Marc; Scott, Daniel; Steiger, Robert; Rutty, Michelle; Johnson, Peter; Vilella, Marc

    2016-04-01

    The multi-billion dollar global ski industry is one of the tourism subsectors most directly impacted by climate variability and change. In the decades ahead, the scholarly literature consistently projects decreased reliability of natural snow cover, shortened and more variable ski seasons, as well as increased reliance on snowmaking with associated increases in operational costs. In order to develop the coupled snow, ski operations and demand model for the Ontario ski region (which represents approximately 18% of Canada's ski market), the research utilized multiple methods, including: a in situ survey of over 2400 skiers, daily operations data from ski resorts over the last 10 years, climate station data (1981-2013), climate change scenario ensemble (AR5 - RCP 8.5), an updated SkiSim model (building on Scott et al. 2003; Steiger 2010), and an agent-based model (building on Pons et al. 2014). Daily snow and ski operations for all ski areas in southern Ontario were modeled with the updated SkiSim model, which utilized current differential snowmaking capacity of individual resorts, as determined from daily ski area operations data. Snowmaking capacities and decision rules were informed by interviews with ski area managers and daily operations data. Model outputs were validated with local climate station and ski operations data. The coupled SkiSim-ABM model was run with historical weather data for seasons representative of an average winter for the 1981-2010 period, as well as an anomalously cold winter (2012-13) and the record warm winter in the region (2011-12). The impact on total skier visits and revenues, and the geographic and temporal distribution of skier visits were compared. The implications of further climate adaptation (i.e., improving the snowmaking capacity of all ski areas to the level of leading resorts in the region) were also explored. This research advances system modelling, especially improving the integration of snow and ski operations models with

  7. 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

  8. Data-driven behavioural modelling of residential water consumption to inform water demand management strategies

    NASA Astrophysics Data System (ADS)

    Giuliani, Matteo; Cominola, Andrea; Alshaf, Ahmad; Castelletti, Andrea; Anda, Martin

    2016-04-01

    The continuous expansion of urban areas worldwide is expected to highly increase residential water demand over the next few years, ultimately challenging the distribution and supply of drinking water. Several studies have recently demonstrated that actions focused only on the water supply side of the problem (e.g., augmenting existing water supply infrastructure) will likely fail to meet future demands, thus calling for the concurrent deployment of effective water demand management strategies (WDMS) to pursue water savings and conservation. However, to be effective WDMS do require a substantial understanding of water consumers' behaviors and consumption patterns at different spatial and temporal resolutions. Retrieving information on users' behaviors, as well as their explanatory and/or causal factors, is key to spot potential areas for targeting water saving efforts and to design user-tailored WDMS, such as education campaigns and personalized recommendations. In this work, we contribute a data-driven approach to identify household water users' consumption behavioural profiles and model their water use habits. State-of-the-art clustering methods are coupled with big data machine learning techniques with the aim of extracting dominant behaviors from a set of water consumption data collected at the household scale. This allows identifying heterogeneous groups of consumers from the studied sample and characterizing them with respect to several consumption features. Our approach is validated onto a real-world household water consumption dataset associated with a variety of demographic and psychographic user data and household attributes, collected in nine towns of the Pilbara and Kimberley Regions of Western Australia. Results show the effectiveness of the proposed method in capturing the influence of candidate determinants on residential water consumption profiles and in attaining sufficiently accurate predictions of users' consumption behaviors, ultimately providing

  9. Seeing about soil — management lessons from a simple model for renewable resources

    NASA Astrophysics Data System (ADS)

    Lichtenegger, Klaus; Schappacher, Wilhelm

    2014-02-01

    Employing an effective cellular automata model, we investigate and analyze the build-up and erosion of soil. Depending on the strategy employed for handling agricultural production, in many cases we find a critical dependence on the prescribed production target, with a sharp transition between stable production and complete breakdown of the system. Strategies which are particularly well-suited for mimicking real-world management approaches can produce almost cyclic behavior, which can also either lead to sustainable production or to breakdown. While designed to describe the dynamics of soil evolution, this model is quite general and may also be useful as a model for other renewable resources and may even be employed in other disciplines like psychology.

  10. Modeling and managing urban water demand through smart meters: Benefits and challenges from current research and emerging trends

    NASA Astrophysics Data System (ADS)

    Cominola, A.; Giuliani, M.; Castelletti, A.; Piga, D.; Rizzoli, A. E.

    2015-12-01

    Urban population growth, climate and land use change are expected to boost residential water demand in urban contexts in the next decades. In such a context, developing suitable demand-side management strategies is essential to meet future water demands, pursue water savings, and reduce the costs for water utilities. Yet, the effectiveness of water demand management strategies (WDMS) relies on our understanding of water consumers' behavior, their consumption habits, and the water use drivers. While low spatial and temporal resolution water consumption data, as traditionally gathered for billing purposes, hardly support this understanding, the advent of high-resolution, smart metering technologies allowed for quasi real-time monitoring water consumption at the single household level. This, in turn, is advancing our ability in characterizing consumers' behavior, modeling, and designing user-oriented residential water demand management strategies. Several water smart metering programs have been rolled-out in the last two decades worldwide, addressing one or more of the following water demand management phases: (i) data gathering, (ii) water end-uses characterization, (iii) user modeling, (iv) design and implementation of personalized WDMS. Moreover, the number of research studies in this domain is quickly increasing and big economic investments are currently being devoted worldwide to smart metering programs. With this work, we contribute the first comprehensive review of more than 100 experiences in the field of residential water demand modeling and management, and we propose a general framework for their classification. We revise consolidated practices, identify emerging trends and highlight the challenges and opportunities for future developments given by the use of smart meters advancing residential water demand management. Our analysis of the status quo of smart urban water demand management research and market constitutes a structured collection of information

  11. Inbound Call Centers and Emotional Dissonance in the Job Demands – Resources Model

    PubMed Central

    Molino, Monica; Emanuel, Federica; Zito, Margherita; Ghislieri, Chiara; Colombo, Lara; Cortese, Claudio G.

    2016-01-01

    Background: Emotional labor, defined as the process of regulating feelings and expressions as part of the work role, is a major characteristic in call centers. In particular, interacting with customers, agents are required to show certain emotions that are considered acceptable by the organization, even though these emotions may be different from their true feelings. This kind of experience is defined as emotional dissonance and represents a feature of the job especially for call center inbound activities. Aim: The present study was aimed at investigating whether emotional dissonance mediates the relationship between job demands (workload and customer verbal aggression) and job resources (supervisor support, colleague support, and job autonomy) on the one hand, and, on the other, affective discomfort, using the job demands-resources model as a framework. The study also observed differences between two different types of inbound activities: customer assistance service (CA) and information service. Method: The study involved agents of an Italian Telecommunication Company, 352 of whom worked in the CA and 179 in the information service. The hypothesized model was tested across the two groups through multi-group structural equation modeling. Results: Analyses showed that CA agents experience greater customer verbal aggression and emotional dissonance than information service agents. Results also showed, only for the CA group, a full mediation of emotional dissonance between workload and affective discomfort, and a partial mediation of customer verbal aggression and job autonomy, and affective discomfort. Conclusion: This study’s findings contributed both to the emotional labor literature, investigating the mediational role of emotional dissonance in the job demands-resources model, and to call center literature, considering differences between two specific kinds of inbound activities. Suggestions for organizations and practitioners emerged in order to identify

  12. A multi-period distribution network design model under demand uncertainty

    NASA Astrophysics Data System (ADS)

    Tabrizi, Babak H.; Razmi, Jafar

    2013-05-01

    Supply chain management is taken into account as an inseparable component in satisfying customers' requirements. This paper deals with the distribution network design (DND) problem which is a critical issue in achieving supply chain accomplishments. A capable DND can guarantee the success of the entire network performance. However, there are many factors that can cause fluctuations in input data determining market treatment, with respect to short-term planning, on the one hand. On the other hand, network performance may be threatened by the changes that take place within practicing periods, with respect to long-term planning. Thus, in order to bring both kinds of changes under control, we considered a new multi-period, multi-commodity, multi-source DND problem in circumstances where the network encounters uncertain demands. The fuzzy logic is applied here as an efficient tool for controlling the potential customers' demand risk. The defuzzifying framework leads the practitioners and decision-makers to interact with the solution procedure continuously. The fuzzy model is then validated by a sensitivity analysis test, and a typical problem is solved in order to illustrate the implementation steps. Finally, the formulation is tested by some different-sized problems to show its total performance.

  13. Combining a Spatial Model and Demand Forecasts to Map Future Surface Coal Mining in Appalachia

    PubMed Central

    Strager, Michael P.; Strager, Jacquelyn M.; Evans, Jeffrey S.; Dunscomb, Judy K.; Kreps, Brad J.; Maxwell, Aaron E.

    2015-01-01

    Predicting the locations of future surface coal mining in Appalachia is challenging for a number of reasons. Economic and regulatory factors impact the coal mining industry and forecasts of future coal production do not specifically predict changes in location of future coal production. With the potential environmental impacts from surface coal mining, prediction of the location of future activity would be valuable to decision makers. The goal of this study was to provide a method for predicting future surface coal mining extents under changing economic and regulatory forecasts through the year 2035. This was accomplished by integrating a spatial model with production demand forecasts to predict (1 km2) gridded cell size land cover change. Combining these two inputs was possible with a ratio which linked coal extraction quantities to a unit area extent. The result was a spatial distribution of probabilities allocated over forecasted demand for the Appalachian region including northern, central, southern, and eastern Illinois coal regions. The results can be used to better plan for land use alterations and potential cumulative impacts. PMID:26090883

  14. Using NASA Satellite and Model Analysis for Renewable Energy and Energy Efficiency Applications

    NASA Astrophysics Data System (ADS)

    Hoell, J. M.; Stackhouse, P. W.; Chandler, W. S.; Whitlock, C. H.; Westberg, D. J.; Zhang, T.

    2009-12-01

    This presentation describes the successful tailoring of NASA research data sets to meet environmental information needs of the renewable energy sector. The data sets currently used for these purposes include the NASA/GEWEX (Global Energy and Water Cycle Experiment) Surface Radiation Budget data set (SRB), the FLASHFlux (Fast Longwave and SHortwave Fluxes from Global CERES and MODIS observations), and the NASA GSFC Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS) versions 4.0.3 and 5.0/5.1. These data are available through the Surface meteorology and Solar Energy (SSE) web interface (http://eosweb.larc.nasa.gov/sse). The NASA Earth Science Applied Science program has supported the development of the SSE web interface through a project called the Prediction of World Energy Resource (POWER, http://power.larc.nasa.gov/). The paths of modifying/preparing these data sets for energy applications for the SSE web site are described. These data help engineers, architects, and project analysts develop feasibility studies for renewable energy technology projects, make regional assessments and long-term energy market forecasts. Thus, small-scale projects to regional energy analysis may benefit from this information. The SSE web site has nearly 50,000 users worldwide and version 6.0 is now averaging 250,000 and 60,000 hits and data downloads per month, respectively. Examples of the usage of these data sets are shown to help describe the need and impact of this information. These examples come from the many collaborative partners in this work such as the DOE National Renewable Energy Laboratory (NREL), the Pacific Northwest National Laboratory (PNNL), and the Natural Resources Canada RETScreen project. The presentation also gives potential future data needs of these types of technologies and how NASA data could help contribute to meeting those needs. This is particularly pertinent facing the growing needs to develop clean energy sources to

  15. Sensor Management for Applied Research Technologies (SMART) On Demand Modeling (ODM) Project

    NASA Astrophysics Data System (ADS)

    Conover, H.; Berthiau, G.; Blakeslee, R.; Botts, M.; Goodman, M.; Hood, R.; Jedlovec, G.; Li, X.; Lu, J.; Maskey, M.

    2007-12-01

    On-demand data processing and analysis of Earth science observations will facilitate timely decision making that can lead to the realization of the practical benefits of satellite instruments, airborne and surface remote sensing systems. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep learning curve associated with each sensor, data type and associated products. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output. The authors will present initial results from Sensor Management for Applied Research Technologies (SMART) On Demand Modeling (ODM). This NASA- funded project is developing and demonstrating the readiness of Open Geospatial Consortium Sensor Web Enablement (SWE) capabilities that integrate both Earth observations and forecast model output into new data acquisition and assimilation strategies. First year accomplishments include development of numerous Sensor Observation Services (SOS) and an SOS registry for sensor data discovery and access, as well as a prototype user application, built on these services, for validating cloud types as observed by multiple instruments. The three-year goal of this project is to demonstration how SWE-enabled systems can have practical and efficient uses in the Earth science community for enhanced data set generation, real-time data assimilation with operational applications, and for autonomous sensor tasking for unique data collection.

  16. Renewable Energy Cost Modeling: A Toolkit for Establishing Cost-Based Incentives in the United States; March 2010 -- March 2011

    SciTech Connect

    Gifford, J. S.; Grace, R. C.; Rickerson, W. H.

    2011-05-01

    This report is intended to serve as a resource for policymakers who wish to learn more about establishing cost-based incentives. The report will identify key renewable energy cost modeling options, highlight the policy implications of choosing one approach over the other, and present recommendations on the optimal characteristics of a model to calculate rates for cost-based incentives, feed-in tariffs (FITs), or similar policies. These recommendations will be utilized in designing the Cost of Renewable Energy Spreadsheet Tool (CREST). Three CREST models will be publicly available and capable of analyzing the cost of energy associated with solar, wind, and geothermal electricity generators. The CREST models will be developed for use by state policymakers, regulators, utilities, developers, and other stakeholders to assist them in current and future rate-setting processes for both FIT and other renewable energy incentive payment structures and policy analyses.

  17. An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems

    PubMed Central

    Ranganayaki, V.; Deepa, S. N.

    2016-01-01

    Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature. PMID:27034973

  18. An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems.

    PubMed

    Ranganayaki, V; Deepa, S N

    2016-01-01

    Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature. PMID:27034973

  19. An EMQ inventory model for defective products involving rework and sales team's initiatives-dependent demand

    NASA Astrophysics Data System (ADS)

    Priyan, S.; Uthayakumar, R.

    2015-07-01

    This paper investigates the issue of an economic manufacturing quantity model for defective products involving imperfect production processes and rework. We consider that the demand is sensitive to promotional efforts/sales teams' initiatives as well as the setup cost can be reduced through further investment. It also assumes that fixed quantity multiple installments of the finished batch are delivered to customers at a fixed interval of time. The long-run average cost function is derived and its convexity is proved via differential calculus. An effective iterative solution procedure is developed to achieve optimal replenishment lot-size, setup cost and the initiatives of sales teams so that the total cost of system is minimized. Numerical and sensitivity analyses are performed to evaluate the outcome of the proposed solution procedure presented in this research.

  20. Accumulative job demands and support for strength use: Fine-tuning the job demands-resources model using conservation of resources theory.

    PubMed

    van Woerkom, Marianne; Bakker, Arnold B; Nishii, Lisa H

    2016-01-01

    Absenteeism associated with accumulated job demands is a ubiquitous problem. We build on prior research on the benefits of counteracting job demands with resources by focusing on a still untapped resource for buffering job demands-that of strengths use. We test the idea that employees who are actively encouraged to utilize their personal strengths on the job are better positioned to cope with job demands. Based on conservation of resources (COR) theory, we hypothesized that job demands can accumulate and together have an exacerbating effect on company registered absenteeism. In addition, using job demands-resources theory, we hypothesized that perceived organizational support for strengths use can buffer the impact of separate and combined job demands (workload and emotional demands) on absenteeism. Our sample consisted of 832 employees from 96 departments (response rate = 40.3%) of a Dutch mental health care organization. Results of multilevel analyses indicated that high levels of workload strengthen the positive relationship between emotional demands and absenteeism and that support for strength use interacted with workload and emotional job demands in the predicted way. Moreover, workload, emotional job demands, and strengths use interacted to predict absenteeism. Strengths use support reduced the level of absenteeism of employees who experienced both high workload and high emotional demands. We conclude that providing strengths use support to employees offers organizations a tool to reduce absenteeism, even when it is difficult to redesign job demands. PMID:26121090

  1. Modeling water renewal times in semi-enclosed seas; application in Amvrakikos Gulf, Greece

    NASA Astrophysics Data System (ADS)

    Stamou, A. I.; Papadonikolaki, G.; Nikiforakis, I.

    2012-04-01

    Water renewal of semi-enclosed coastal lagoons is vital for oxygen supply and the removal of pollution. There are various indicators of how fast the water is renewed via transport and mixing; the most common terms being used are the hydraulic retention time (HRT) and the residence time (RT). In the present work a computational determination of HRT and RT was performed for the Amvrakikos Gulf, a preserved ecosystem by national and international directives. The Amvrakikos Gulf is located in the north-western coast of Greece is one of the largest semi-enclosed embayments in the country being about 40 km long and 15 km wide. It is the largest wetland system in Greece consisting of the shallow marine waters of the Gulf, the deltas of Louros and Arachthos rivers and a lagoon system composed of 3 large and over 20 smaller lagoons. Water renewal of the Amvrakikos Gulf is of major importance since it is made exclusively via a narrow channel connecting the Gulf with the Ionian Sea that has a 3.0 km length, width ranging from 0.8 to 2.0 km and depth from 2.0 to 13.0 m. Computations were made using a 3-D integrated model that consists of the hydrodynamic sub-model FLOW-3DL and the water quality sub-model QUAL-3DL. FLOW-3DL; these models that have been developed in the NTUA involve the 3-D non-steady state continuity and momentum equations and the convection-diffusion equation for the concentration of a conservative pollutant expressed in layer formulation. A space-staggered computational grid was used that covered the area of the Amvrakikos Gulf and a small part of the Ionian Sea and consisted of 84x50 control volumes with constant resolution equal to 500 m and 7 layers in the direction of the depth. Calculations were performed for various environmental characteristics for tidal and wind hydrodynamic forcing, taking into account the input flow rates from the rivers Louros and Arachthos.

  2. An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud.

    PubMed

    Dinh, Thanh; Kim, Younghan

    2016-01-01

    This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud. PMID:27367689

  3. An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud

    PubMed Central

    Dinh, Thanh; Kim, Younghan

    2016-01-01

    This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud. PMID:27367689

  4. Experimental evidence for the effects of the Demand-Control model on the cognitive arousal: An EEG based study.

    PubMed

    Subhani, Ahmad Rauf; Malik, Aamir Saeed; Kamel, Nidal; Saad, Naufal; Nandagopal, D Nanda

    2015-08-01

    The Demand-Control (DC) model has been extensively researched to find the imbalance of demand and control that cause work-related stress. Past research has been exclusively dedicated to evaluate the impact of this model on employees' well-being and job environment. However, the impact of high demands (strain hypothesis) and the influence of control (buffer hypothesis) on cognitive arousal have yet to be identified. We aimed to fill this void by measuring the influence of the DC model on the cognitive arousal. Electroencephalogram (EEG) was recorded to extract the cognitive arousal in an experiment that implemented the DC model. The experiment comprised four conditions having combination of varying demand and control. The strain and the buffer hypothesis were separately validated by the cognitive arousal in association with the task performance and subjective feedbacks. Results showed the maximum arousal and the worst performance occurred in high demand and low control condition. Also high control proved to significantly lower arousal and improved performance than in low control condition with high demand. PMID:26737668

  5. Extending and applying the demand-control model: the role of soldier's coping on a peacekeeping deployment.

    PubMed

    Ippolito, Jessica; Adler, Amy B; Thomas, Jeffrey L; Litz, Brett T; Hölzl, Rupert

    2005-10-01

    The purpose of this study was to extend the demand-control model (R. A. Karasek, 1979) by examining coping as an additional factor. It was hypothesized that perceived job control only buffered the demand-strain relationship when individuals used active coping and exacerbated the relationship when individuals used passive coping. Soldiers (N=638) were surveyed before and during a 6-month peacekeeping deployment to Kosovo. Results partially confirmed the hypotheses. Even after controlling for general psychological health at predeployment, job control moderated the relationship between demands and psychological health during deployment when soldiers used active coping. No significant 3-way interactions were found for religious coping and passive coping. Implications for demand-control modeling and potential applications of the findings to soldier and leader training are discussed. PMID:16248692

  6. Before the Roof Caves in: A Predictive Model for Physical Plant Renewal--Part II. APPA Technical Paper.

    ERIC Educational Resources Information Center

    Hutson, Robert E.; Biedenweg, Frederick M.

    1982-01-01

    Examples of the use of a mathematical model to evaluate the future renewal and replacement, or maintenance requirements, of the college physical plant are provided. The model, which was developed at Stanford University, simulates actual conditions at a specific location and allows resource allocation to be based on a definable quantitative base.…

  7. Deep water renewal in Lake Baikal: A model for long-term analyses

    NASA Astrophysics Data System (ADS)

    Piccolroaz, Sebastiano; Toffolon, Marco

    2013-12-01

    The phenomenon of deep water renewal in the South Basin of Lake Baikal is investigated by means of a simplified one-dimensional model. The downwelling process, whereby large volumes of superficial, cold, and oxygenated water periodically sink to the lake bottom (>1400m) due to thermobaric instability, is simulated by means of three main submodules: a reaction-diffusion equation for temperature and other tracers, and two Lagrangian algorithms, the first for the vertical stabilization of unstable density regions (including thermobaric effects) and the second handling the downwelling mechanism. A self-consistent procedure for the dynamical reconstruction of the diapycnal diffusivity profile is included to account for the effect of the variability of external conditions. The model has been developed aimed at providing a detailed description of deep-ventilation and a quantification of its consequences at the basin scale; the core algorithms have been designed suitably to perform long-term simulations (hundreds of years) and to deal with a limited amount of information about boundary conditions, which are expressed in terms of wind forcing and surface water temperature. The main parameters have been calibrated using measured profiles of temperature and chlorofluorocarbons (CFC-12) concentration over a 40 year historical period. A long-term simulation (one millennium), in which the current meteorological conditions have been kept statistically unchanged, has been used to determine the asymptotic dynamics. The results are consistent with previous measurements and estimates, suggesting that the model is suitable to qualitatively and quantitatively simulate deep water renewal in deep, temperate lakes, capturing the relative contribution and interaction of the different processes involved.

  8. Computational modeling of on-demand solder delivery for fluxless MCM packaging applications

    SciTech Connect

    Essien, M.; Sackinger, P.A.; Peebles, H.C.

    1996-10-01

    The development of smaller circuit volumes in microelectronic applications, particularly Multichip Module (MCM) technology, entails deposition of minute quantities of solder, with volumes on the order of nanoliters. We propose a system for fluxless solder deposition which uses on-demand solder jetting for deposition of 200 micrometer diameter solder droplets onto aluminum pads. This work details the computational modeling performed to provide design parameters for a magneto-hydrodynamic solder jetter (MHD). A dimensionless analysis was used to relate the fluid properties, the orifice length and width, and the droplet size to the amplitude and duration of the pressure pulse. These results were used as the initial inputs for the fluid dynamics model, and subsequent iterations were performed to determine the operational parameters that lead to the formation of stable, single droplets. Results show that a maximum pulse amplitude on the order of 0.5 Mdynes/cm[sup 2] is necessary to dispense molten solder from a 200 micrometer diameter orifice. The size of the droplet was found to vary linearly with the applied pressure pulse. The duration of the pulse ranged from approximately 0.6 to 0.9 milliseconds. A theoretical description of the relationship between the orifice diameter, surface tension, and `Pinch-off` time is given, and is in agreement with the results of the computational model.

  9. The limits of the possible: models of power supply and demand in cycling.

    PubMed

    Olds, T; Norton, K; Craig, N; Olive, S; Lowe, E

    1995-06-01

    This paper outlines a general strategy for mathematical modeling of cycling performance. This strategy involves formulating one expression describing the power available for external work from physiological sources. The variables used in this expression include maximal aerobic power (VO2max), fractional utilisation of VO2max, mechanical efficiency, maximal accumulated oxygen deficit, and the time constants relating to the expression of aerobic and anaerobic capacities. A second expression describing the power demand of cycling is then constructed. The variables used in this expression include the mass, projected frontal area and drag characteristics of the system, the coefficient of rolling resistance, environmental variables such as temperature, barometric pressure, relative humidity, wind speed and direction and the slope of the course. The two expressions are equated and solved using an iterative procedure. Two series of trials were used to assess the predictive accuracy of the model, one using track endurance performances and the other a 26 km road time-trial. The correlations between actual and predicted times have been excellent (0.92-0.95, p < or = 0.0001), with small mean differences (0-1.83% of mean performance time) and mean absolute differences (1.07-3.24%). The model allows us to make predictions about the effect of equipment changes and environmental factors, to compare performances under very different conditions, and to predict the limits of the possible in cycling performance. A range of options designed to improve cycling performance is described. PMID:8521030

  10. Modeling relief demands in an emergency supply chain system under large-scale disasters based on a queuing network.

    PubMed

    He, Xinhua; Hu, Wenfa

    2014-01-01

    This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model. PMID:24688367

  11. Modeling Relief Demands in an Emergency Supply Chain System under Large-Scale Disasters Based on a Queuing Network

    PubMed Central

    He, Xinhua

    2014-01-01

    This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model. PMID:24688367

  12. Optimal Strategy for the Integrated Vendor-buyer Inventory Model with Fuzzy Annual Demand and Fuzzy Adjustable Production Rate

    NASA Astrophysics Data System (ADS)

    Yang, M. F.

    In this research we present a stylized model to find the optimal strategy for integrated vendor-buyer inventory model with fuzzy annual demand and fuzzy adjustable production rate. This model with such consideration is based on the total cost optimization under a common stock strategy. However, the supposition of known annual demand and adjustable production rate in most related publications may not be realistic. This paper proposes the triangular fuzzy number of annual demand and adjustable production rate and then employs the signed distance, to find the estimation of the common total cost in the fuzzy sense and derives the corresponding optimal buyer`s quantity consequently and the integer number of lots in which the items are delivered from the vendor to the purchaser. A numerical example is provided and the results of fuzzy and crisp models are compared.

  13. Development of an integrated modelling framework: comparing client-server and demand-driven control flow for model execution

    NASA Astrophysics Data System (ADS)

    Schmitz, Oliver; Karssenberg, Derek; de Jong, Kor; de Kok, Jean-Luc; de Jong, Steven M.

    2014-05-01

    The construction of hydrological models at the catchment or global scale depends on the integration of component models representing various environmental processes, often operating at different spatial and temporal discretisations. A flexible construction of spatio-temporal model components, a means to specify aggregation or disaggregation to bridge discretisation discrepancies, ease of coupling these into complex integrated models, and support for stochastic modelling and the assessment of model outputs are the desired functionalities for the development of integrated models. These functionalities are preferably combined into one modelling framework such that domain specialists can perform exploratory model development without the need to change their working environment. We implemented an integrated modelling framework in the Python programming language, providing support for 1) model construction and 2) model execution. The framework enables modellers to represent spatio-temporal processes or to specify spatio-temporal (dis)aggregation with map algebra operations provided by the PCRaster library. Model algebra operations can be used by the modeller to specify the exchange of data and therefore the coupling of components. The framework determines the control flow for the ordered execution based on the time steps and couplings of the model components given by the modeller. We implemented two different control flow mechanisms. First, a client-server approach is used with a central entity controlling the execution of the component models and steering the data exchange. Second, a demand-driven approach is used that triggers the execution of a component model when data is requested by a coupled component model. We show that both control flow mechanisms allow for the execution of stochastic, multi-scale integrated models. We examine the implications of each control flow mechanism on the terminology used by the modeller to specify integrated models, and illustrate the

  14. A renewal model for the emergence of anomalous solute crowding in liposomes

    PubMed Central

    2015-01-01

    A fundamental evolutionary step in the onset of living cells is thought to be the spontaneous formation of lipid vesicles (liposomes) in the pre-biotic mixture. Even though it is well known that hydrophobic forces drive spontaneous liposome formation in aqueous solutions, how the components of the earliest biochemical pathways were trapped and concentrated in the forming vesicles is an issue that still needs to be clarified. In recent years, some authors carried out a set of experiments where a unexpectedly high amount of solutes were found in a small number of liposomes, spontaneously formed in aqueous solution. A great number of empty liposomes were found in the same experiments and the global observed behavior was that of a distribution of solute particles into liposomes in agreement with a inverse power-law function rather than with the expected Poisson distribution. The chemical and physical mechanisms leading to the observed "anomalous solute crowding" are still unclear, but the non-Poisson power-law behavior is associated with some cooperative behavior with strong non-linear interactions in the biochemical processes occurring in the solution. For tackling this issue we propose a model grounding on the Cox's theory of renewal point processes, which many authors consider to play a central role in the description of complex cooperative systems. Starting from two very basic hypotheses and the renewal assumption, we derive a model reproducing the behavior outlined above. In particular, we show that the assumption of a "cooperative" interaction between the solute molecules and the forming liposomes is sufficient for the emergence of the observed power-law behavior. Even though our approach does not provide experimental evidences of the chemical and physical bases of the solute crowding, it suggests promising directions for experimental research and it also provide a first theoretical prediction that could possibly be tested in future experimental investigations

  15. Modeling Educational Choices. A Binomial Logit Model Applied to the Demand for Higher Education.

    ERIC Educational Resources Information Center

    Jimenez, Juan de Dios; Salas-Velasco, Manual

    2000-01-01

    Presents a microeconomic analysis of the choice of university degree course (3 year or 4 year course) Spanish students make on finishing their secondary studies and applies the developed binomial logit model to survey data from 388 high school graduates. Findings show the importance of various factors in determining the likelihood of choosing the…

  16. On inclusion of water resource management in Earth System models - Part 1: Problem definition and representation of water demand

    NASA Astrophysics Data System (ADS)

    Nazemi, A.; Wheater, H. S.

    2014-07-01

    Human activities have caused various changes in the Earth System, and hence, the interconnections between humans and the Earth System should be recognized and reflected in models that simulate the Earth System processes. One key anthropogenic activity is water resource management that determines the dynamics of human-water interactions in time and space. There are various reasons to include water resource management in Earth System models. First, the extent of human water requirements is increasing rapidly at the global scale and it is crucial to analyze the possible imbalance between water demands and supply under various scenarios of climate change and across various temporal and spatial scales. Second, recent observations show that human-water interactions, manifested through water resource management, can substantially alter the terrestrial water cycle, affect land-atmospheric feedbacks and may further interact with climate and contribute to sea-level change. Here, we divide the water resource management into two interdependent elements, related to water demand as well as water supply and allocation. In this paper, we survey the current literature on how various water demands have been included in large-scale models, including Land Surface Schemes and Global Hydrological Models. The available algorithms are classified based on the type of demand, mode of simulation and underlying modeling assumptions. We discuss the pros and cons of available algorithms, address various sources of uncertainty and highlight limitations in current applications. We conclude that current capability of large-scale models in terms of representing human water demands is rather limited, particularly with respect to future projections and online simulations. We argue that current limitations in simulating various human demands and their impact on the Earth System are mainly due to the uncertainties in data support, demand algorithms and large-scale models. To fill these gaps, the

  17. The Asymptotics of Recovery Probability in the Dual Renewal Risk Model with Constant Interest and Debit Force

    PubMed Central

    2015-01-01

    The asymptotic behavior of the recovery probability for the dual renewal risk model with constant interest and debit force is studied. By means the idea of Markov Skeleton method, we studied the times that the random premium incomes happened and transformed the continuous time model into a discrete time model. By investigating the fluctuations of this discrete time model, we obtained the asymptotic behavior when the random premium income belongs to a kind of heavy-tailed distributions.

  18. Survey of conditional energy demand models for estimating residential unit energy consumption coefficients. Final report

    SciTech Connect

    Lawrence, A.G.; Parti, M.

    1984-02-01

    Several recent econometric studies of residential energy use are reviewed. These studies specify residential energy use as the sum of energy use in each of several household appliances (including space conditioning systems). The energy used in each of the enumerated appliances (e.g., end-uses) is called its unit energy consumption (UEC) coefficient. Most of the studies use household survey data combined with utility billing records. In general, the UEC coefficients are parameterized as functions of weather conditions, household income, the size of the dwelling, the demographic composition of the household, the price of energy, and other variables from the survey data. A few of the studies have explored the econometric issues of demand analysis under the block tariff schedules prevalent in the utility industry. Some studies report price elasticities or income elasticities or both for specific end-uses. These studies show that such econometric estimation is a successful and efficient tool for measuring electricity consumption by end-use. Their results are compared with engineering estimates from other extant studies. Results from these econometric UEC models have improved the accuracy and end-use detail of the energy forecasting models of some utilities.

  19. Residential-energy-demand modeling and the NIECS data base: an evaluation

    SciTech Connect

    Cowing, T.G.; Dubin, J.A.; McFadden, D.

    1982-01-01

    The purpose of this report is to evaluate the 1978-1979 National Interim Energy Consumption Survey (NIECS) data base in terms of its usefulness for estimating residential energy demand models based on household appliance choice and utilization decisions. The NIECS contains detailed energy usage information at the household level for 4081 households during the April 1978 to March 1979 period. Among the data included are information on the structural and thermal characteristics of the housing unit, demographic characteristics of the household, fuel usage, appliance characteristics, and actual energy consumption. The survey covers the four primary residential fuels-electricity, natural gas, fuel oil, and liquefied petroleum gas - and includes detailed information on recent household conservation and retrofit activities. Section II contains brief descriptions of the major components of the NIECS data set. Discussions are included on the sample frame and the imputation procedures used in NIECS. There are also two extensive tables, giving detailed statistical and other information on most of the non-vehicle NIECS variables. Section III contains an assessment of the NIECS data, focusing on four areas: measurement error, sample design, imputation problems, and additional data needed to estimate appliance choice/use models. Section IV summarizes and concludes the report.

  20. Sleep Quality Among Latino Farmworkers in North Carolina: Examination of the Job Control-Demand-Support Model.

    PubMed

    Sandberg, Joanne C; Nguyen, Ha T; Quandt, Sara A; Chen, Haiying; Summers, Phillip; Walker, Francis O; Arcury, Thomas A

    2016-06-01

    Sleep problems are associated with physical and mental health disorders and place individuals at an increased risk of workplace injuries. The demand-control-support model posits that job demands and the capacity to control work processes influence workers' level of distress, thereby affecting their physical and mental health; supervisor support can buffer the negative effect of high demands and low control. Data on the sleep quality and the organization of work of Latino men were collected in agricultural areas in North Carolina in 2012. 147 Mexican-born farmworkers ages 30 and older, most of whom had H-2A visas, provided information about sleep quality and organization of work. Most (83 %) farmworkers reported good sleep quality. The association between working more than 40 h per week and reporting poor sleep quality approached statistical significance. Additional research is needed to understand whether job demands, job control, and social support affect farmworkers' sleep quality. PMID:26143366

  1. Predicting the demand of physician workforce: an international model based on "crowd behaviors"

    PubMed Central

    2012-01-01

    Background Appropriateness of physician workforce greatly influences the quality of healthcare. When facing the crisis of physician shortages, the correction of manpower always takes an extended time period, and both the public and health personnel suffer. To calculate an appropriate number of Physician Density (PD) for a specific country, this study was designed to create a PD prediction model, based on health-related data from many countries. Methods Twelve factors that could possibly impact physicians' demand were chosen, and data of these factors from 130 countries (by reviewing 195) were extracted. Multiple stepwise-linear regression was used to derive the PD prediction model, and a split-sample cross-validation procedure was performed to evaluate the generalizability of the results. Results Using data from 130 countries, with the consideration of the correlation between variables, and preventing multi-collinearity, seven out of the 12 predictor variables were selected for entry into the stepwise regression procedure. The final model was: PD = (5.014 - 0.128 × proportion under age 15 years + 0.034 × life expectancy)2, with R2 of 80.4%. Using the prediction equation, 70 countries had PDs with "negative discrepancy", while 58 had PDs with "positive discrepancy". Conclusion This study provided a regression-based PD model to calculate a "norm" number of PD for a specific country. A large PD discrepancy in a country indicates the needs to examine physician's workloads and their well-being, the effectiveness/efficiency of medical care, the promotion of population health and the team resource management. PMID:22448781

  2. Before the Roof Caves In: A Predictive Model for Physical Plant Renewal.

    ERIC Educational Resources Information Center

    Biedenweg, Frederick M.; Hutson, Robert E.

    1984-01-01

    Presents a quantitative method developed at Stanford University that allows administrators to accurately assess the future capital requirements necessary for renewal and replacement of campus buildings. (MLF)

  3. 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

  4. Comparison of the Effectiveness of Six Models in Forecasting Student Demand on Academic Departments. Final Report.

    ERIC Educational Resources Information Center

    Blake, R. John; Robertson, Leon B.

    An accurate forecast of the student demand by level on the academic departments of an institution is vital for budget and financial planning decisions, for faculty workload scheduling, and for physical facility planning. Many methods have been used to forecast this demand, ranging from "seat of your pants" guessing to highly complex computer…

  5. Dynamic modeling, experimental evaluation, optimal design and control of integrated fuel cell system and hybrid energy systems for building demands

    NASA Astrophysics Data System (ADS)

    Nguyen, Gia Luong Huu

    Fuel cells can produce electricity with high efficiency, low pollutants, and low noise. With the advent of fuel cell technologies, fuel cell systems have since been demonstrated as reliable power generators with power outputs from a few watts to a few megawatts. With proper equipment, fuel cell systems can produce heating and cooling, thus increased its overall efficiency. To increase the acceptance from electrical utilities and building owners, fuel cell systems must operate more dynamically and integrate well with renewable energy resources. This research studies the dynamic performance of fuel cells and the integration of fuel cells with other equipment in three levels: (i) the fuel cell stack operating on hydrogen and reformate gases, (ii) the fuel cell system consisting of a fuel reformer, a fuel cell stack, and a heat recovery unit, and (iii) the hybrid energy system consisting of photovoltaic panels, fuel cell system, and energy storage. In the first part, this research studied the steady-state and dynamic performance of a high temperature PEM fuel cell stack. Collaborators at Aalborg University (Aalborg, Denmark) conducted experiments on a high temperature PEM fuel cell short stack at steady-state and transients. Along with the experimental activities, this research developed a first-principles dynamic model of a fuel cell stack. The dynamic model developed in this research was compared to the experimental results when operating on different reformate concentrations. Finally, the dynamic performance of the fuel cell stack for a rapid increase and rapid decrease in power was evaluated. The dynamic model well predicted the performance of the well-performing cells in the experimental fuel cell stack. The second part of the research studied the dynamic response of a high temperature PEM fuel cell system consisting of a fuel reformer, a fuel cell stack, and a heat recovery unit with high thermal integration. After verifying the model performance with the

  6. Burnout and connectedness in the job demands-resources model: studying palliative care volunteers and their families.

    PubMed

    Huynh, Jasmine-Yan; Winefield, Anthony H; Xanthopoulou, Despoina; Metzer, Jacques C

    2012-09-01

    This study examined the role of burnout and connectedness in the job demands-resources (JD-R) model among palliative care volunteers. It was hypothesized that (a) exhaustion mediates the relationship between demands and depression, and between demands and retention; (b) cynicism mediates the relationship between resources and retention; and (c) connectedness mediates the relationship between resources and retention. Hypotheses were tested in 2 separate analyses: structural equation modeling (SEM) and path analyses. The first was based on volunteer self-reports (N = 204), while the second analysis concerned matched data from volunteers and their family members (N = 99). While strong support was found for cynicism and connectedness as mediators in both types of analyses, this was not altogether the case for exhaustion. Implications of these findings for the JD-R model and volunteer organizations are discussed. PMID:22207713

  7. Self-Adaptive Prediction of Cloud Resource Demands Using Ensemble Model and Subtractive-Fuzzy Clustering Based Fuzzy Neural Network

    PubMed Central

    Chen, Zhijia; Zhu, Yuanchang; Di, Yanqiang; Feng, Shaochong

    2015-01-01

    In IaaS (infrastructure as a service) cloud environment, users are provisioned with virtual machines (VMs). To allocate resources for users dynamically and effectively, accurate resource demands predicting is essential. For this purpose, this paper proposes a self-adaptive prediction method using ensemble model and subtractive-fuzzy clustering based fuzzy neural network (ESFCFNN). We analyze the characters of user preferences and demands. Then the architecture of the prediction model is constructed. We adopt some base predictors to compose the ensemble model. Then the structure and learning algorithm of fuzzy neural network is researched. To obtain the number of fuzzy rules and the initial value of the premise and consequent parameters, this paper proposes the fuzzy c-means combined with subtractive clustering algorithm, that is, the subtractive-fuzzy clustering. Finally, we adopt different criteria to evaluate the proposed method. The experiment results show that the method is accurate and effective in predicting the resource demands. PMID:25691896

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

    SciTech Connect

    Blair, Nate; Zhou, Ella; Getman, Dan; Arent, Douglas J.

    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 likely 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.

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

    SciTech Connect

    Blair, Nate; Zhou, Ella; Getman, Dan; Arent, Douglas J.

    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 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.

  10. On inclusion of water resource management in Earth system models - Part 1: Problem definition and representation of water demand

    NASA Astrophysics Data System (ADS)

    Nazemi, A.; Wheater, H. S.

    2015-01-01

    Human activities have caused various changes to the Earth system, and hence the interconnections between human activities and the Earth system should be recognized and reflected in models that simulate Earth system processes. One key anthropogenic activity is water resource management, which determines the dynamics of human-water interactions in time and space and controls human livelihoods and economy, including energy and food production. There are immediate needs to include water resource management in Earth system models. First, the extent of human water requirements is increasing rapidly at the global scale and it is crucial to analyze the possible imbalance between water demands and supply under various scenarios of climate change and across various temporal and spatial scales. Second, recent observations show that human-water interactions, manifested through water resource management, can substantially alter the terrestrial water cycle, affect land-atmospheric feedbacks and may further interact with climate and contribute to sea-level change. Due to the importance of water resource management in determining the future of the global water and climate cycles, the World Climate Research Program's Global Energy and Water Exchanges project (WRCP-GEWEX) has recently identified gaps in describing human-water interactions as one of the grand challenges in Earth system modeling (GEWEX, 2012). Here, we divide water resource management into two interdependent elements, related firstly to water demand and secondly to water supply and allocation. In this paper, we survey the current literature on how various components of water demand have been included in large-scale models, in particular land surface and global hydrological models. Issues of water supply and allocation are addressed in a companion paper. The available algorithms to represent the dominant demands are classified based on the demand type, mode of simulation and underlying modeling assumptions. We discuss

  11. Renewable energy development in China

    SciTech Connect

    Junfeng, Li

    1996-12-31

    This paper presents the resources availability, technologies development and their costs of renewable energies in China and introduces the programs of renewable energies technologies development and their adaptation for rural economic development in China. As the conclusion of this paper, renewable energies technologies are suitable for some rural areas, especially in the remote areas for both household energy and business activities energy demand. The paper looks at issues involving hydropower, wind energy, biomass combustion, geothermal energy, and solar energy.

  12. Predictors of the nicotine reinforcement threshold, compensation, and elasticity of demand in a rodent model of nicotine reduction policy*

    PubMed Central

    Grebenstein, Patricia E.; Burroughs, Danielle; Roiko, Samuel A.; Pentel, Paul R.; LeSage, Mark G.

    2015-01-01

    Background The FDA is considering reducing the nicotine content in tobacco products as a population-based strategy to reduce tobacco addiction. Research is needed to determine the threshold level of nicotine needed to maintain smoking and the extent of compensatory smoking that could occur during nicotine reduction. Sources of variability in these measures across sub-populations also need to be identified so that policies can take into account the risks and benefits of nicotine reduction in vulnerable populations. Methods The present study examined these issues in a rodent nicotine self- administration model of nicotine reduction policy to characterize individual differences in nicotine reinforcement thresholds, degree of compensation, and elasticity of demand during progressive reduction of the unit nicotine dose. The ability of individual differences in baseline nicotine intake and nicotine pharmacokinetics to predict responses to dose reduction was also examined. Results Considerable variability in the reinforcement threshold, compensation, and elasticity of demand was evident. High baseline nicotine intake was not correlated with the reinforcement threshold, but predicted less compensation and less elastic demand. Higher nicotine clearance predicted low reinforcement thresholds, greater compensation, and less elastic demand. Less elastic demand also predicted lower reinforcement thresholds. Conclusions These findings suggest that baseline nicotine intake, nicotine clearance, and the essential value of nicotine (i.e. elasticity of demand) moderate the effects of progressive nicotine reduction in rats and warrant further study in humans. They also suggest that smokers with fast nicotine metabolism may be more vulnerable to the risks of nicotine reduction. PMID:25891231

  13. The Efficacy of the RENEW Model: Individualized School-to-Career Services for Youth At Risk of School Dropout

    ERIC Educational Resources Information Center

    Malloy, JoAnne M.; Sundar, Vidyalakshmi; Hagner, David; Pierias, Leigh; Viet, Tara

    2010-01-01

    This article describes the results of a research project designed to assess the efficacy of a secondary transition model, RENEW (Rehabilitation, Empowerment, Natural supports, Education and Work), on the social and emotional functioning of 20 youth at risk of dropping out of high school using the Child and Adolescent Functional Assessment Scale…

  14. Sensitivity Analysis and Uncertainty Characterization of Subnational Building Energy Demand in an Integrated Assessment Model

    NASA Astrophysics Data System (ADS)

    Scott, M. J.; Daly, D.; McJeon, H.; Zhou, Y.; Clarke, L.; Rice, J.; Whitney, P.; Kim, S.

    2012-12-01

    Residential and commercial buildings are a major source of energy consumption and carbon dioxide emissions in the United States, accounting for 41% of energy consumption and 40% of carbon emissions in 2011. Integrated assessment models (IAMs) historically have been used to estimate the impact of energy consumption on greenhouse gas emissions at the national and international level. Increasingly they are being asked to evaluate mitigation and adaptation policies that have a subnational dimension. In the United States, for example, building energy codes are adopted and enforced at the state and local level. Adoption of more efficient appliances and building equipment is sometimes directed or actively promoted by subnational governmental entities for mitigation or adaptation to climate change. The presentation reports on new example results from the Global Change Assessment Model (GCAM) IAM, one of a flexibly-coupled suite of models of human and earth system interactions known as the integrated Regional Earth System Model (iRESM) system. iRESM can evaluate subnational climate policy in the context of the important uncertainties represented by national policy and the earth system. We have added a 50-state detailed U.S. building energy demand capability to GCAM that is sensitive to national climate policy, technology, regional population and economic growth, and climate. We are currently using GCAM in a prototype stakeholder-driven uncertainty characterization process to evaluate regional climate mitigation and adaptation options in a 14-state pilot region in the U.S. upper Midwest. The stakeholder-driven decision process involves several steps, beginning with identifying policy alternatives and decision criteria based on stakeholder outreach, identifying relevant potential uncertainties, then performing sensitivity analysis, characterizing the key uncertainties from the sensitivity analysis, and propagating and quantifying their impact on the relevant decisions. In the

  15. Sense of coherence and the motivational process of the job-demands-resources model.

    PubMed

    Vogt, Katharina; Hakanen, Jari J; Jenny, Gregor J; Bauer, Georg F

    2016-04-01

    This longitudinal study systematically examines the various roles played by the personal resource "sense of coherence" (SoC) in the motivational process described by the job-demands-resources model. SoC captures the extent to which people perceive their life as comprehensible, manageable and meaningful, and there is evidence of its influence in many health-related outcomes. The first aim here was to establish whether a resourceful working environment builds up SoC and whether SoC leads to work engagement. A second aim was to test reverse relationships: how work engagement leads to SoC and how SoC in turn relates to job resources. A third aim was to assess whether SoC boosts the relationship between job resources and work engagement. The study utilized a 3-wave, 3-month panel design, involving 940 employees working in a broad range of occupations and economic sectors. The results of longitudinal structural equation modeling show that job resources predict SoC and SoC predicts work engagement, suggesting a mediating role of SoC. In addition, SoC predicts job resources, suggesting reciprocal relationships between job resources and SoC. No boosting effect of SoC was found. Overall, the present findings support the view that providing employees with a resourceful working environment will help to build their SoC. The effects of SoC on perceptual, appraisal, and behavioral processes may in turn lead to enhanced job resources and positive outcomes such as greater work engagement. (PsycINFO Database Record PMID:26690920

  16. An inventory model with linear holding cost and stock-dependent demand for non-instantaneous deteriorating items

    NASA Astrophysics Data System (ADS)

    Kumar, Satish; Malik, A. K.; Sharma, Abhishek; Yadav, S. K.; Singh, Yashveer

    2016-03-01

    The importance of inventory models with non-instantaneously deteriorating items in the management system has been discussed. The holding cost is taken as in linear function of time and demand is stock dependent. For this inventory model, we obtained the optimal order quantity and the total present value of profits. Further, optimality and sensitivity analysis of the optimal profit of the inventory model with key constraints is followed with the help of numerical example.

  17. Applying the Job Demands--Resources Model to the Work--Home Interface: A Study among Medical Residents and Their Partners

    ERIC Educational Resources Information Center

    Bakker, Arnold B.; ten Brummelhuis, Lieke L.; Prins, Jelle T.; van der Heijden, Frank M. M. A.

    2011-01-01

    Work-home interference (WHI) is a prevalent problem because most employees have substantial family responsibilities on top of their work demands. The present study hypothesized that high job demands in combination with low job resources contribute to WHI. The job demands-resources (JD-R) model was used as a theoretical framework. Using a sample of…

  18. The Role of Personality in the Job Demands-Resources Model: A Study of Australian Academic Staff

    ERIC Educational Resources Information Center

    Bakker, Arnold B.; Boyd, Carolyn M.; Dollard, Maureen; Gillespie, Nicole; Winefield, Anthony H.; Stough, Con

    2010-01-01

    Purpose: The central aim of this study is to incorporate two core personality factors (neuroticism and extroversion) in the job demands-resources (JD-R) model. Design/methodology/approach: It was hypothesized that neuroticism would be most strongly related to the health impairment process, and that extroversion would be most strongly related to…

  19. Comparison of Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building

    SciTech Connect

    Dudley, Junqiao Han; Black, Doug; Apte, Mike; Piette, Mary Ann; Berkeley, Pam

    2010-05-14

    We have studied a low energy building on a campus of the University of California. It has efficient heating, ventilation, and air conditioning (HVAC) systems, consisting of a dual-fan/dual-duct variable air volume (VAV) system. As a major building on the campus, it was included in two demand response (DR) events in the summers of 2008 and 2009. With chilled water supplied by thermal energy storage in the central plant, cooling fans played a critical role during DR events. In this paper, an EnergyPlus model of the building was developed and calibrated. We compared both whole-building and HVAC fan energy consumption with model predictions to understand why demand savings in 2009 were much lower than in 2008. We also used model simulations of the study building to assess pre-cooling, a strategy that has been shown to improve demand saving and thermal comfort in many types of building. This study indicates a properly calibrated EnergyPlus model can reasonably predict demand savings from DR events and can be useful for designing or optimizing DR strategies.

  20. How sensitive is the estimation of renewable water resources on a global scale to input data and model structure?

    NASA Astrophysics Data System (ADS)

    Müller Schmied, Hannes; Eisner, Stephanie; Franz, Daniela; Wattenbach, Martin

    2013-04-01

    Large scale hydrological models and land surface models are applied to simulate the global terrestrial water cycle and to estimate global renewable water resources. In recent years the growing availability of global data sets to force and constrain these models, e.g. remote sensing and reanalysis products, has essentially improved estimates of renewable water resources. However, results still vary significantly between models and/or input data sets highlighting the uncertainty of those estimates. In this study, we will test the sensitivity of simulated renewable water resources to climate and land use data sets and to varying model complexity using the global hydrological model WaterGAP (Water Global Analysis and Prognosis), version 2.2. The model is calibrated against observed discharge records by adjusting one independent parameter, which controls the fraction of total runoff from effective precipitation. The aim is to minimize the discrepancy in simulated long-term annual discharge compared to measured ones. Due to e.g. model structure or input data uncertainty this calibration procedure is not successful in all river basins, i.e. simulated long-term annual discharge still deviates more than +/- 1 % from the observed one. In these cases, correction factors are applied to avoid error propagation to downstream catchments. In this context, we define calibration success as the ability to calibrate with a minimum of correction factors, which is an indicator of the model's ability (including the underlying input data) to reproduce observed long term discharge. In order to assess the impact of different input data sets and modified model structure on calibration success, model calibration was performed in three different experimental setups: (1) WaterGAP was forced with different climate input data sets (WATCH Forcing Data; CRU TS 3.2/GPCC v.6) to evaluate the impact of climate input, especially precipitation; (2) WaterGAP simulations were based on two different global

  1. Biomass Scenario Model: BETO Analysis Platform Peer Review; NREL (National Renewable Energy Laboratory)

    SciTech Connect

    Bush, B.

    2015-03-23

    The Biomass Scenario Model (BSM) is a unique, carefully validated, state-of-the-art fourth-generation model of the domestic bioenergy supply chain which explicitly focuses on policy issues and their potential side effects. It integrates resource availability, behavior, policy, and physical, technological, and economic constraints. The BSM uses system-dynamics simulation to model dynamic interactions across the supply chain; it tracks the deployment of biofuels given technological development and the reaction of the investment community to those technologies in the context of land availability, the competing oil market, consumer demand for biofuels, and government policies over time. It places a strong emphasis on the behavior and decision-making of various economic agents. The model treats the major infrastructure-compatible fuels. Scenario analysis based on the BSM shows that the biofuels industry tends not to rapidly thrive without significant external actions in the early years of its evolution. An initial focus for jumpstarting the industry typically has strongest results in the BSM in areas where effects of intervention have been identified to be multiplicative. In general, we find that policies which are coordinated across the whole supply chain have significant impact in fostering the growth of the biofuels industry and that the production of tens of billions of gallons of biofuels may occur under sufficiently favorable conditions.

  2. Short-time behaviour of demand and price viewed through an exactly solvable model for heterogeneous interacting market agents

    NASA Astrophysics Data System (ADS)

    Schütz, Gunter M.; de Almeida Prado, Fernando Pigeard; Harris, Rosemary J.; Belitsky, Vladimir

    2009-10-01

    We introduce a stochastic heterogeneous interacting-agent model for the short-time non-equilibrium evolution of excess demand and price in a stylized asset market. We consider a combination of social interaction within peer groups and individually heterogeneous fundamentalist trading decisions which take into account the market price and the perceived fundamental value of the asset. The resulting excess demand is coupled to the market price. Rigorous analysis reveals that this feedback may lead to price oscillations, a single bounce, or monotonic price behaviour. The model is a rare example of an analytically tractable interacting-agent model which allows us to deduce in detail the origin of these different collective patterns. For a natural choice of initial distribution, the results are independent of the graph structure that models the peer network of agents whose decisions influence each other.

  3. Structuring energy supply and demand networks in a general equilibrium model to simulate global warming control strategies

    SciTech Connect

    Hamilton, S.; Veselka, T.D.; Cirillo, R.R.

    1991-01-01

    Global warming control strategies which mandate stringent caps on emissions of greenhouse forcing gases can substantially alter a country's demand, production, and imports of energy products. Although there is a large degree of uncertainty when attempting to estimate the potential impact of these strategies, insights into the problem can be acquired through computer model simulations. This paper presents one method of structuring a general equilibrium model, the ENergy and Power Evaluation Program/Global Climate Change (ENPEP/GCC), to simulate changes in a country's energy supply and demand balance in response to global warming control strategies. The equilibrium model presented in this study is based on the principle of decomposition, whereby a large complex problem is divided into a number of smaller submodules. Submodules simulate energy activities and conversion processes such as electricity production. These submodules are linked together to form an energy supply and demand network. Linkages identify energy and fuel flows among various activities. Since global warming control strategies can have wide reaching effects, a complex network was constructed. The network represents all energy production, conversion, transportation, distribution, and utilization activities. The structure of the network depicts interdependencies within and across economic sectors and was constructed such that energy prices and demand responses can be simulated. Global warming control alternatives represented in the network include: (1) conservation measures through increased efficiency; and (2) substitution of fuels that have high greenhouse gas emission rates with fuels that have lower emission rates. 6 refs., 4 figs., 4 tabs.

  4. Job characteristics and safety climate: the role of effort-reward and demand-control-support models.

    PubMed

    Phipps, Denham L; Malley, Christine; Ashcroft, Darren M

    2012-07-01

    While safety climate is widely recognized as a key influence on organizational safety, there remain questions about the nature of its antecedents. One potential influence on safety climate is job characteristics (that is, psychosocial features of the work environment). This study investigated the relationship between two job characteristics models--demand-control-support (Karasek & Theorell, 1990) and effort-reward imbalance (Siegrist, 1996)--and safety climate. A survey was conducted with a random sample of 860 British retail pharmacists, using the job contents questionnaire (JCQ), effort-reward imbalance indicator (ERI) and a measure of safety climate in pharmacies. Multivariate data analyses found that: (a) both models contributed to the prediction of safety climate ratings, with the demand-control-support model making the largest contribution; (b) there were some interactions between demand, control and support from the JCQ in the prediction of safety climate scores. The latter finding suggests the presence of "active learning" with respect to safety improvement in high demand, high control settings. The findings provide further insight into the ways in which job characteristics relate to safety, both individually and at an aggregated level. PMID:22746367

  5. Geostatistical Modeling of the Spatial Distribution of Sediment Oxygen Demand Within a Coastal Plain Blackwater Watershed

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Blackwater streams of the Georgia Coastal Plain are often listed as impaired due to chronically low DO levels. Previous research has shown that high sediment oxygen demand (SOD) values, a hypothesized cause of lowered DO within these waters, are significantly positively correlated with TOC within th...

  6. Modelling the Effects of Teacher Demand Factors on Teacher Understaffing in Public Secondary Schools in Kenya

    ERIC Educational Resources Information Center

    Wamukuru, David Kuria

    2016-01-01

    The secondary school teacher labour market faces many challenges including, escalating teacher wage bill, teacher shortages that occur alongside teacher surpluses, inadequate teacher distribution and inefficient teacher utilization. There is the need therefore to understand the effects of the factors determining demand for secondary school…

  7. Telecommunications Information Network: A Model for On-Demand Transfer of Medical Information. Annual Report.

    ERIC Educational Resources Information Center

    Lorenzi, Nancy M.; And Others

    This report describes and evaluates the first year of a demonstration project to develop an on-demand telecommunications network linking four remote hospitals in southwestern Ohio to the University of Cincinnati Medical Center. The Telecommunications Information Network (TIN) is designed to allow health care professionals at those hospitals to…

  8. BASIC Programming for the Integration of Money, Demand Deposits Creation, and the Hicksian-Keynesian Model.

    ERIC Educational Resources Information Center

    Tom, C. F. Joseph

    Money, banking, and macroeconomic textbooks traditionally present the topics of money, the creation of demand deposits by depository institutions, and the Hicksian-Keynesian Theory of Income and Interest separately, as if they were unrelated. This paper presents an integrated approach to those subjects using computer programs written in BASIC, the…

  9. Predicting and Explaining Students' Stress with the Demand-Control Model: Does Neuroticism Also Matter?

    ERIC Educational Resources Information Center

    Schmidt, Laura I.; Sieverding, Monika; Scheiter, Fabian; Obergfell, Julia

    2015-01-01

    University students often report high stress levels, and studies even suggest a recent increase. However, there is a lack of theoretically based research on the structural conditions that influence students' perceived stress. The current study compared the effects of Karasek's demand-control dimensions with the influence of neuroticism to address…

  10. A modified exponential behavioral economic demand model to better describe consumption data.

    PubMed

    Koffarnus, Mikhail N; Franck, Christopher T; Stein, Jeffrey S; Bickel, Warren K

    2015-12-01

    Behavioral economic demand analyses that quantify the relationship between the consumption of a commodity and its price have proven useful in studying the reinforcing efficacy of many commodities, including drugs of abuse. An exponential equation proposed by Hursh and Silberberg (2008) has proven useful in quantifying the dissociable components of demand intensity and demand elasticity, but is limited as an analysis technique by the inability to correctly analyze consumption values of zero. We examined an exponentiated version of this equation that retains all the beneficial features of the original Hursh and Silberberg equation, but can accommodate consumption values of zero and improves its fit to the data. In Experiment 1, we compared the modified equation with the unmodified equation under different treatments of zero values in cigarette consumption data collected online from 272 participants. We found that the unmodified equation produces different results depending on how zeros are treated, while the exponentiated version incorporates zeros into the analysis, accounts for more variance, and is better able to estimate actual unconstrained consumption as reported by participants. In Experiment 2, we simulated 1,000 datasets with demand parameters known a priori and compared the equation fits. Results indicated that the exponentiated equation was better able to replicate the true values from which the test data were simulated. We conclude that an exponentiated version of the Hursh and Silberberg equation provides better fits to the data, is able to fit all consumption values including zero, and more accurately produces true parameter values. PMID:26280591

  11. Workplace Bullying Among Teachers: An Analysis From the Job Demands-Resources (JD-R) Model Perspective.

    PubMed

    Ariza-Montes, Antonio; Muniz R, Noel M; Leal-Rodríguez, Antonio L; Leal-Millán, Antonio G

    2016-08-01

    This paper adopts the Job Demands-Resources (JD-R) model to analyze workplace bullying among teachers. The data used for this research are obtained from the 5th European Working Conditions Survey. Given the objective of this work, a subsample of 261 education employees is collected: 48.7% of these teachers report having experienced workplace bullying (N = 127), while 51.3% indicate not considering themselves as bullied at work (N = 134). In order to test the research model and hypotheses, this study relies on the use of partial least squares (PLS-SEM), a variance-based structural equation modeling method. The study describes a workplace bullying prevalence rate of 4.4% among education employees. This work summarizes an array of outcomes with the aim of proposing, in general, that workplace bullying may be reduced by limiting job demands and increasing job resources. PMID:27305842

  12. Battery storage for supplementing renewable energy systems

    SciTech Connect

    None, None

    2009-01-18

    The battery storage for renewable energy systems section of the Renewable Energy Technology Characterizations describes structures and models to support the technical and economic status of emerging renewable energy options for electricity supply.

  13. TWO-COMPONENT GALACTIC BULGE PROBED WITH RENEWED GALACTIC CHEMICAL EVOLUTION MODEL

    SciTech Connect

    Tsujimoto, Takuji; Bekki, Kenji

    2012-03-10

    Results of recent observations of the Galactic bulge demand that we discard a simple picture of its formation, suggesting the presence of two stellar populations represented by two peaks of stellar metallicity distribution (MDF) in the bulge. To assess this issue, we construct Galactic chemical evolution models that have been updated in two respects: first, the delay time distribution of Type Ia supernovae (SNe Ia) recently revealed by extensive SN Ia surveys is incorporated into the models. Second, the nucleosynthesis clock, the s-processing in asymptotic giant branch stars, is carefully considered in this study. This novel model first shows that the Galaxy feature tagged by the key elements, Mg, Fe, and Ba, for the bulge as well as thin and thick disks is compatible with a short-delay SN Ia. We present a successful modeling of a two-component bulge including the MDF and the evolutions of [Mg/Fe] and [Ba/Mg], and reveal its origin as follows. A metal-poor component (([Fe/H]) {approx} -0.5) is formed with a relatively short timescale of {approx}1 Gyr. These properties are identical to the thick disk's characteristics in the solar vicinity. Subsequently from its remaining gas mixed with a gas flow from the disk outside the bulge, a metal-rich component (([Fe/H]) {approx} +0.3) is formed with a longer timescale ({approx}4 Gyr) together with a top-heavy initial mass function that might be identified with the thin disk component within the bulge.

  14. An integrated supply chain model for new products with imprecise production and supply under scenario dependent fuzzy random demand

    NASA Astrophysics Data System (ADS)

    Nagar, Lokesh; Dutta, Pankaj; Jain, Karuna

    2014-05-01

    In the present day business scenario, instant changes in market demand, different source of materials and manufacturing technologies force many companies to change their supply chain planning in order to tackle the real-world uncertainty. The purpose of this paper is to develop a multi-objective two-stage stochastic programming supply chain model that incorporates imprecise production rate and supplier capacity under scenario dependent fuzzy random demand associated with new product supply chains. The objectives are to maximise the supply chain profit, achieve desired service level and minimise financial risk. The proposed model allows simultaneous determination of optimum supply chain design, procurement and production quantities across the different plants, and trade-offs between inventory and transportation modes for both inbound and outbound logistics. Analogous to chance constraints, we have used the possibility measure to quantify the demand uncertainties and the model is solved using fuzzy linear programming approach. An illustration is presented to demonstrate the effectiveness of the proposed model. Sensitivity analysis is performed for maximisation of the supply chain profit with respect to different confidence level of service, risk and possibility measure. It is found that when one considers the service level and risk as robustness measure the variability in profit reduces.

  15. Power Transfer Potential to the Southeast in Response to a Renewable Portfolio Standard: Interim Report 1

    SciTech Connect

    Hadley, Stanton W; Key, Thomas S

    2009-03-01

    The power transfer potential for bringing renewable energy into the Southeast in response to a renewable portfolio standard (RPS) will depend not only on available transmission capacity but also on electricity supply and demand factors. This interim report examines how the commonly used EIA NEMS and EPRI NESSIE energy equilibrium models are considering such power transfers. Using regional estimates of capacity expansion and demand, a base case for 2008, 2020 and 2030 are compared relative to generation mix, renewable deployments, planned power transfers, and meeting RPS goals. The needed amounts of regional renewable energy to comply with possible RPS levels are compared to inter-regional transmission capacities to establish a baseline available for import into the Southeast and other regions. Gaps in the renewable generation available to meet RPS requirements are calculated. The initial finding is that the physical capability for transferring renewable energy into the SE is only about 10% of what would be required to meet a 20% RPS. Issues that need to be addressed in future tasks with respect to modeling are the current limitations for expanding renewable capacity and generation in one region to meet the demand in another and the details on transmission corridors required to deliver the power.

  16. CREST Cost of Renewable Energy Spreadsheet Tool: A Model for Developing Cost-based Incentives in the United States. User Manual Version 1

    SciTech Connect

    Gifford, Jason S.; Grace, Robert C.

    2011-03-01

    This user manual helps model users understands how to use the CREST model to support renewable energy incentives, FITs, and other renewable energy rate-setting processes. It reviews the spreadsheet tool, including its layout and conventions, offering context on how and why it was created. It also provides instructions on how to populate the model with inputs that are appropriate for a specific jurisdiction’s policymaking objectives and context. And, it describes the results and outlines how these results may inform decisions about long-term renewable energy support programs.

  17. Supply chain model with price- and trade credit-sensitive demand under two-level permissible delay in payments

    NASA Astrophysics Data System (ADS)

    Giri, B. C.; Maiti, T.

    2013-05-01

    This article develops a single-manufacturer and single-retailer supply chain model under two-level permissible delay in payments when the manufacturer follows a lot-for-lot policy in response to the retailer's demand. The manufacturer offers a trade credit period to the retailer with the contract that the retailer must share a fraction of the profit earned during the trade credit period. On the other hand, the retailer provides his customer a partial trade credit which is less than that of the manufacturer. The demand at the retailer is assumed to be dependent on the selling price and the trade credit period offered to the customers. The average net profit of the supply chain is derived and an algorithm for finding the optimal solution is developed. Numerical examples are given to demonstrate the coordination policy of the supply chain and examine the sensitivity of key model-parameters.

  18. New econometric approach to modelling peak load pricing policies: the case of electricity demand by large industrial customers

    SciTech Connect

    Jazayeri, A.A.

    1984-01-01

    This study relates the kWh consumption and the maximum instantaneous demand through a reasonable and simple inequity based on the property of the load curve. The model of analysis includes this inequality and two equations relating the kWh consumption and kW demand to their respective prices. The error term in the first equation is assumed to be normally distributed, and the error term in the second equation is assumed to have an asymptotic distribution similar to that of the largest extremes. Relating the two equations through the inequality necessitates the formation of the convolution of the normal and the extreme value distributions. Such a distribution is formed and the maximum-likelihood estimation technique along with methods of numerical analysis are utilized to estimate the parameters of this system of equations. In addition, the method of estimation is applied to time-of-use electricity pricing which preserve the basic structure of Hopkinson rate, introduction of demand and energy charges, and allows application of distinct demand and energy charges to different periods of the day or season.

  19. Demand-Supply Balancing Capability Analysis for a Future Power System

    NASA Astrophysics Data System (ADS)

    Ogimoto, Kazuhiko; Kataoka, Kazuto; Ikegami, Takashi; Nonaka, Shunsuke; Azuma, Hitoshi; Fukutome, Suguru

    Under the anticipated high penetration of variable renewable energy generation such as photovoltaics and higher share of nuclear generation, the issue of supply-demand balancing capability should be evaluated and fixed in a future power system. Improvement of existing balancing measures and new technologies such as demand activation and energy storage are expected to solve the issue. Under the situation, a long-range power system supply-demand analysis should have the capability to evaluate the balancing capability and balancing counter measures. This paper presents a new analysis methodology of activated demand model and evaluation of supply-demand balancing capability for a long-range power system demand-supply analysis model, ESPRIT. Model analysis was made to verify the new methodology of the tool including day-ahead scheduling of a heat pump water heater, an EV/PHEV and a battery.

  20. Modeling high resolution space-time variations in energy demand/CO2 emissions of human inhabited landscapes in the United States under a changing climate

    NASA Astrophysics Data System (ADS)

    Godbole, A. V.; Gurney, K. R.

    2010-12-01

    With urban and exurban areas now accounting for more than 50% of the world's population, projected to increase 20% by 2050 (UN World Urbanization Prospects, 2009), urban-climate interactions are of renewed interest to the climate change scientific community (Karl et. al, 1988; Kalnay and Cai, 2003; Seto and Shepherd, 2009). Until recently, climate modeling efforts treated urban-human systems as independent of the earth system. With studies pointing to the disproportionately large influence of urban areas on their surrounding environment (Small et. al, 2010), modeling efforts have begun to explicitly account for urban processes in land models, like the CLM 4.0 urban layer, for example (Oleson.et. al, 2008, 2010). A significant portion of the urban energy demand comes from the space heating and cooling requirement of the residential and commercial sectors - as much as 51% (DOE, RECS 2005) and 11% (Belzer, D. 2006) respectively, in the United States. Thus, these sectors are both responsible for a significant fraction of fossil fuel CO2 emissions and will be influenced by a changing climate through changes in energy use and energy supply planning. This points to the possibility of interactive processes and feedbacks with the climate system. Space conditioning energy demand is strongly driven by external air temperature (Ruth, M. et.al, 2006) in addition to other socio-economic variables such as building characteristics (age of structure, activity cycle, weekend/weekday usage profile), occupant characteristics (age of householder, household income) and energy prices (Huang, 2006; Santin et. al, 2009; Isaac and van Vuuren, 2009). All of these variables vary both in space and time. Projections of climate change have begun to simulate changes in temperature at much higher resolution than in the past (Diffenbaugh et. al, 2005). Hence, in order to understand how climate change and variability will potentially impact energy use/emissions and energy planning, these two

  1. 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

  2. An EPQ model for deteriorating items with inventory-level-dependent demand and permissible delay in payments

    NASA Astrophysics Data System (ADS)

    Min, Jie; Zhou, Yong-Wu; Liu, Gui-Qing; Wang, Sheng-Dong

    2012-06-01

    This article develops an inventory model for exponentially deteriorating items under conditions of permissible delay in payments. Unlike the existing related models, we assume that the items are replenished at a finite rate and the demand rate of the items is dependent on the current inventory level. The objective is to determine the optimal replenishment policies in order to maximise the system's average profit per unit of time. A simple method is shown for finding the optimal solution of the model based on the derived properties of the objective function. In addition, we deduce some previously published results as the special cases of the model. Finally, numerical examples are used to illustrate the proposed model. Some managerial insights are also inferred from the sensitive analysis of model parameters.

  3. Geostatistical modeling of the spatial distribution of sediment oxygen demand within a Coastal Plain blackwater watershed.

    PubMed

    Todd, M Jason; Lowrance, R Richard; Goovaerts, Pierre; Vellidis, George; Pringle, Catherine M

    2010-10-15

    Blackwater streams are found throughout the Coastal Plain of the southeastern United States and are characterized by a series of instream floodplain swamps that play a critical role in determining the water quality of these systems. Within the state of Georgia, many of these streams are listed in violation of the state's dissolved oxygen (DO) standard. Previous work has shown that sediment oxygen demand (SOD) is elevated in instream floodplain swamps and due to these areas of intense oxygen demand, these locations play a major role in determining the oxygen balance of the watershed as a whole. This work also showed SOD rates to be positively correlated with the concentration of total organic carbon. This study builds on previous work by using geostatistics and Sequential Gaussian Simulation to investigate the patchiness and distribution of total organic carbon (TOC) at the reach scale. This was achieved by interpolating TOC observations and simulated SOD rates based on a linear regression. Additionally, this study identifies areas within the stream system prone to high SOD at representative 3rd and 5th order locations. Results show that SOD was spatially correlated with the differences in distribution of TOC at both locations and that these differences in distribution are likely a result of the differing hydrologic regime and watershed position. Mapping of floodplain soils at the watershed scale shows that areas of organic sediment are widespread and become more prevalent in higher order streams. DO dynamics within blackwater systems are a complicated mix of natural and anthropogenic influences, but this paper illustrates the importance of instream swamps in enhancing SOD at the watershed scale. Moreover, our study illustrates the influence of instream swamps on oxygen demand while providing support that many of these systems are naturally low in DO. PMID:20938491

  4. Geostatistical modeling of the spatial distribution of sediment oxygen demand within a Coastal Plain blackwater watershed

    PubMed Central

    Todd, M. Jason; Lowrance, R. Richard; Goovaerts, Pierre; Vellidis, George; Pringle, Catherine M.

    2010-01-01

    Blackwater streams are found throughout the Coastal Plain of the southeastern United States and are characterized by a series of instream floodplain swamps that play a critical role in determining the water quality of these systems. Within the state of Georgia, many of these streams are listed in violation of the state’s dissolved oxygen (DO) standard. Previous work has shown that sediment oxygen demand (SOD) is elevated in instream floodplain swamps and due to these areas of intense oxygen demand, these locations play a major role in determining the oxygen balance of the watershed as a whole. This work also showed SOD rates to be positively correlated with the concentration of total organic carbon. This study builds on previous work by using geostatistics and Sequential Gaussian Simulation to investigate the patchiness and distribution of total organic carbon (TOC) at the reach scale. This was achieved by interpolating TOC observations and simulated SOD rates based on a linear regression. Additionally, this study identifies areas within the stream system prone to high SOD at representative 3rd and 5th order locations. Results show that SOD was spatially correlated with the differences in distribution of TOC at both locations and that these differences in distribution are likely a result of the differing hydrologic regime and watershed position. Mapping of floodplain soils at the watershed scale shows that areas of organic sediment are widespread and become more prevalent in higher order streams. DO dynamics within blackwater systems are a complicated mix of natural and anthropogenic influences, but this paper illustrates the importance of instream swamps in enhancing SOD at the watershed scale. Moreover, our study illustrates the influence of instream swamps on oxygen demand while providing support that many of these systems are naturally low in DO. PMID:20938491

  5. Towards a dynamic assessment of raw materials criticality: linking agent-based demand--with material flow supply modelling approaches.

    PubMed

    Knoeri, Christof; Wäger, Patrick A; Stamp, Anna; Althaus, Hans-Joerg; Weil, Marcel

    2013-09-01

    Emerging technologies such as information and communication-, photovoltaic- or battery technologies are expected to increase significantly the demand for scarce metals in the near future. The recently developed methods to evaluate the criticality of mineral raw materials typically provide a 'snapshot' of the criticality of a certain material at one point in time by using static indicators both for supply risk and for the impacts of supply restrictions. While allowing for insights into the mechanisms behind the criticality of raw materials, these methods cannot account for dynamic changes in products and/or activities over time. In this paper we propose a conceptual framework intended to overcome these limitations by including the dynamic interactions between different possible demand and supply configurations. The framework integrates an agent-based behaviour model, where demand emerges from individual agent decisions and interaction, into a dynamic material flow model, representing the materials' stocks and flows. Within the framework, the environmental implications of substitution decisions are evaluated by applying life-cycle assessment methodology. The approach makes a first step towards a dynamic criticality assessment and will enhance the understanding of industrial substitution decisions and environmental implications related to critical metals. We discuss the potential and limitation of such an approach in contrast to state-of-the-art methods and how it might lead to criticality assessments tailored to the specific circumstances of single industrial sectors or individual companies. PMID:23453658

  6. Two-warehouse partial backlogging inventory model for deteriorating items with linear trend in demand under inflationary conditions

    NASA Astrophysics Data System (ADS)

    Jaggi, Chandra K.; Khanna, Aditi; Verma, Priyanka

    2011-07-01

    In today's business transactions, there are various reasons, namely, bulk purchase discounts, re-ordering costs, seasonality of products, inflation induced demand, etc., which force the buyer to order more than the warehouse capacity. Such situations call for additional storage space to store the excess units purchased. This additional storage space is typically a rented warehouse. Inflation plays a very interesting and significant role here: It increases the cost of goods. To safeguard from the rising prices, during the inflation regime, the organisation prefers to keep a higher inventory, thereby increasing the aggregate demand. This additional inventory needs additional storage space, which is facilitated by a rented warehouse. Ignoring the effects of the time value of money and inflation might yield misleading results. In this study, a two-warehouse inventory model with linear trend in demand under inflationary conditions having different rates of deterioration has been developed. Shortages at the owned warehouse are also allowed subject to partial backlogging. The solution methodology provided in the model helps to decide on the feasibility of renting a warehouse. Finally, findings have been illustrated with the help of numerical examples. Comprehensive sensitivity analysis has also been provided.

  7. Consequences of increasing bioenergy demand on wood and forests: An application of the Global Forest Products Model

    USGS Publications Warehouse

    Buongiorno, J.; Raunikar, R.; Zhu, S.

    2011-01-01

    The Global Forest Products Model (GFPM) was applied to project the consequences for the global forest sector of doubling the rate of growth of bioenergy demand relative to a base scenario, other drivers being maintained constant. The results showed that this would lead to the convergence of the price of fuelwood and industrial roundwood, raising the price of industrial roundwood by nearly 30% in 2030. The price of sawnwood and panels would be 15% higher. The price of paper would be 3% higher. Concurrently, the demand for all manufactured wood products would be lower in all countries, but the production would rise in countries with competitive advantage. The global value added in wood processing industries would be 1% lower in 2030. The forest stock would be 2% lower for the world and 4% lower for Asia. These effects varied substantially by country. ?? 2011 Department of Forest Economics, SLU Ume??, Sweden.

  8. Water demands for electricity generation in the U.S.: Modeling different scenarios for the water–energy nexus

    SciTech Connect

    Liu, Lu; Hejazi, Mohamad I.; Patel, Pralit L.; Kyle, G. Page; Davies, Evan; Zhou, Yuyu; Clarke, Leon E.; Edmonds, James A.

    2015-05-01

    Water withdrawal for electricity generation in the United States accounts for approximately half the total freshwater withdrawal. With steadily growing electricity demands, a changing climate, and limited water supplies in many water-scarce states, meeting future energy and water demands poses a significant socio-economic challenge. Employing an integrated modeling approach that can capture the energy-water interactions at regional and national scales is essential to improve our understanding of the key drivers that govern those interactions and the role of national policies. In this study, the Global Change Assessment Model (GCAM), a technologically-detailed integrated model of the economy, energy, agriculture and land use, water, and climate systems, was extended to model the electricity and water systems at the state level in the U.S. (GCAM-USA). GCAM-USA was employed to estimate future state-level electricity generation and consumption, and their associated water withdrawals and consumption under a set of six scenarios with extensive details on the generation fuel portfolio, cooling technology mix, and their associated water use intensities. Six scenarios of future water demands of the U.S. electric-sector were explored to investigate the implications of socioeconomics development and growing electricity demands, climate mitigation policy, the transition of cooling systems, electricity trade, and water saving technologies. Our findings include: 1) decreasing water withdrawals and substantially increasing water consumption from both climate mitigation and the conversion from open-loop to closed-loop cooling systems; 2) open trading of electricity benefiting energy scarce yet demand intensive states; 3) within state variability under different driving forces while across state homogeneity under certain driving force ; 4) a clear trade-off between water consumption and withdrawal for the electricity sector in the U.S. The paper discusses this withdrawal

  9. Commercial-energy-use model for the ten US Federal regions. [Floor-space-demand forecast to 1995

    SciTech Connect

    Cohn, S.M.; Corum, K.R.; Kurish, J.; Emerson, C.

    1981-03-01

    Development of a regional forecasting tool for energy demand in the commercial sector of the US is described. Data bases for each of the ten Federal regions are developed as input to the ORNL commercial energy-demand model to evaluate conservation policies, new technologies, and fuel-price strategies on a regional basis from 1970 to 2000. Commercial-floor-space econometric models for each of ten commercial building types in each of the ten Federal regions are estimated to forecast the growth of energy using capital on a regional basis. In addition, regional energy-use indices (Btu/ft/sup 2/) are calculated using revised commercial energy-use and floor-space estimates. Comparisons are made between the commercial-floor-space forecasts of the regional models and the national commercial-energy-use model. In addition, validation of the forecasting accuracy of the regional models is made for a historical period. All regions show fuel switching away from fuel oil and natural gas to electricity. Regions 4, 6, and 10 (Southeastern, Southwestern, and Lower Western States) show the largest growth rates of projected primary energy consumption for the ten Federal regions with the Great Lakes states the lowest.

  10. Drosophila neuroblasts as a new model for the study of stem cell self-renewal and tumour formation

    PubMed Central

    Li, Song; Wang, Hongyan; Groth, Casper

    2014-01-01

    Drosophila larval brain stem cells (neuroblasts) have emerged as an important model for the study of stem cell asymmetric division and the mechanisms underlying the transformation of neural stem cells into tumour-forming cancer stem cells. Each Drosophila neuroblast divides asymmetrically to produce a larger daughter cell that retains neuroblast identity, and a smaller daughter cell that is committed to undergo differentiation. Neuroblast self-renewal and differentiation are tightly controlled by a set of intrinsic factors that regulate ACD (asymmetric cell division). Any disruption of these two processes may deleteriously affect the delicate balance between neuroblast self-renewal and progenitor cell fate specification and differentiation, causing neuroblast overgrowth and ultimately lead to tumour formation in the fly. In this review, we discuss the mechanisms underlying Drosophila neural stem cell self-renewal and differentiation. Furthermore, we highlight emerging evidence in support of the notion that defects in ACD in mammalian systems, which may play significant roles in the series of pathogenic events leading to the development of brain cancers. PMID:24965943

  11. Nonlinear and Nonparametric Stochastic Model to Represent Uncertainty of Renewable Generation in Operation and Expansion Planning Studies of Electrical Energy Systems

    NASA Astrophysics Data System (ADS)

    Martins, T. M.; Alberto, J.

    2015-12-01

    The uncertainties of wind and solar generation patterns tends to be a critical factor in operation and expansion planning studies of electrical energy systems, as these generations are highly dependent on atmospheric variables which are difficult to predict. Traditionally, the uncertainty of renewable generation has been represented through scenarios generated by autoregressive parametric models (ARMA, PAR(p), SARIMA, etc.), that have been widely used for simulating the uncertainty of inflows and electrical demand. These methods have 3 disadvantages: (i) it is assumed that the random variables can be modelled through a known probability distribution, usually Weibull, log-normal, or normal, which are not always adequate; (ii) the temporal and spatial coupling of the represented variables are generally constructed from the Pearson Correlation, strictly requiring the hypothesis of data normality, that in the case of wind and solar generation is not met; (iii) there is an exponential increase in the model complexity due to its dimensionality. This work proposes the use of a stochastic model built from the combination of a non-parametric approach of a probability density function (the kernel density estimation method) with a dynamic Bayesian network framework. The kernel density estimation method is used to obtain the probability density function of the random variables directly from historical records, eliminating the need of choosing prior distributions. The Bayesian network allows the representation of nonlinearities in the temporal coupling of the time series, since they allow reproducing a compact probability distribution of a variable, subject to preceding stages. The proposed model was used to the generate wind power scenarios in long-term operation studies of the Brazilian Electric System, in which inflows of major rivers were also represented. The results show a considerable quality gain when compared to scenarios generated by traditional approaches.

  12. Renewable Resources: a national catalog of model projects. Volume 4. Western Solar Utilization Network Region

    SciTech Connect

    1980-07-01

    This compilation of diverse conservation and renewable energy projects across the United States was prepared through the enthusiastic participation of solar and alternate energy groups from every state and region. Compiled and edited by the Center for Renewable Resources, these projects reflect many levels of innovation and technical expertise. In many cases, a critique analysis is presented of how projects performed and of the institutional conditions associated with their success or failure. Some 2000 projects are included in this compilation; most have worked, some have not. Information about all is presented to aid learning from these experiences. The four volumes in this set are arranged in state sections by geographic region, coinciding with the four Regional Solar Energy Centers. The table of contents is organized by project category so that maximum cross-referencing may be obtained. This volume includes information on the Western Solar Utilization Network Region. (WHK)

  13. Renewable Resources: a national catalog of model projects. Volume 3. Southern Solar Energy Center Region

    SciTech Connect

    1980-07-01

    This compilation of diverse conservation and renewable energy projects across the United States was prepared through the enthusiastic participation of solar and alternate energy groups from every state and region. Compiled and edited by the Center for Renewable Resources, these projects reflect many levels of innovation and technical expertise. In many cases, a critique analysis is presented of how projects performed and of the institutional conditions associated with their success or failure. Some 2000 projects are included in this compilation; most have worked, some have not. Information about all is presented to aid learning from these experiences. The four volumes in this set are arranged in state sections by geographic region, coinciding with the four Regional Solar Energy Centers. The table of contents is organized by project category so that maximum cross-referencing may be obtained. This volume includes information on the Southern Solar Energy Center Region. (WHK)

  14. Renewable Resources: a national catalog of model projects. Volume 1. Northeast Solar Energy Center Region

    SciTech Connect

    1980-07-01

    This compilation of diverse conservation and renewable energy projects across the United States was prepared through the enthusiastic participation of solar and alternate energy groups from every state and region. Compiled and edited by the Center for Renewable Resources, these projects reflect many levels of innovation and technical expertise. In many cases, a critique analysis is presented of how projects performed and of the institutional conditions associated with their success or failure. Some 2000 projects are included in this compilation; most have worked, some have not. Information about all is presented to aid learning from these experiences. The four volumes in this set are arranged in state sections by geographic region, coinciding with the four Regional Solar Energy Centers. The table of contents is organized by project category so that maximum cross-referencing may be obtained. This volume includes information on the Northeast Solar Energy Center Region. (WHK).

  15. [Institutional Renewal].

    ERIC Educational Resources Information Center

    Brown, Peggy, Ed.

    1983-01-01

    The theme of this journal issue is "Institutional Renewal." Projects designed to address the issues of the 1980s at 18 colleges are described, and 15 definitions of institutional renewal are presented. Participating colleges were provided expert advice through the Association of American College's (AAC) Project Lodestar (renamed Consultation and…

  16. ROS-Responsive Microspheres for On Demand Antioxidant Therapy in a Model of Diabetic Peripheral Arterial Disease

    PubMed Central

    Poole, KM; Nelson, CE; Joshi, RV; Martin, JR; Gupta, MK; Haws, SC; Kavanaugh, TE; Skala, MC; Duvall, CL

    2014-01-01

    A new microparticle-based delivery system was synthesized from reactive oxygen species (ROS)-responsive poly(propylene sulfide) (PPS) and tested for “on demand” antioxidant therapy. PPS is hydrophobic but undergoes a phase change to become hydrophilic upon oxidation and thus provides a useful platform for ROS-demanded drug release. This platform was tested for delivery of the promising anti-inflammatory and antioxidant therapeutic molecule curcumin, which is currently limited in use in its free form due to poor pharmacokinetic properties. PPS microspheres efficiently encapsulated curcumin through oil-in-water emulsion and provided sustained, on demand release that was modulated in vitro by hydrogen peroxide concentration. The cytocompatible, curcumin-loaded microspheres preferentially targeted and scavenged intracellular ROS in activated macrophages, reduced in vitro cell death in the presence of cytotoxic levels of ROS, and decreased tissue-level ROS in vivo in the diabetic mouse hind limb ischemia model of peripheral arterial disease. Interestingly, due to the ROS scavenging behavior of PPS, the blank microparticles also showed inherent therapeutic properties that were synergistic with the effects of curcumin in these assays. Functionally, local delivery of curcumin-PPS microspheres accelerated recovery from hind limb ischemia in diabetic mice, as demonstrated using non-invasive imaging techniques. This work demonstrates the potential for PPS microspheres as a generalizable vehicle for ROS-demanded drug release and establishes the utility of this platform for improving local curcumin bioavailability for treatment of chronic inflammatory diseases. PMID:25522975

  17. 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.

  18. Evaluation of Behavioral Demand Models of Consumer Choice in Health Care.

    ERIC Educational Resources Information Center

    Siddharthan, Kris

    1991-01-01

    Consumer choice of health provider plan and preference for a personal physician were studied for 1,438 elderly adults using a joint logit model (JL) and a nested logit model. Choice criteria used by senior citizens, and reasons the nested choice model explains choice behavior better than the JL are examined. (SLD)

  19. The Creative Imperative Model: A Four-Quadrant Approach to the Categorization of Industries and Firms by Types of Creativity Demanded

    ERIC Educational Resources Information Center

    Wise, Timothy D.

    2003-01-01

    Organizational creativity, in the model that follows, is subcategorized according to the type of creativity demanded by the industry in which a firm competes. Industries that demand the constant creation of new products are referred to as "creativity-centered" while others, which benefit from creative refinements to current services, are referred…

  20. DSM renewable opportunities in Boston

    SciTech Connect

    Tennis, M.W.; Nogee, A.J.; Coakley, S.; Schoengold, D.

    1995-11-01

    The Union of Concerned Scientists (UCS), in conjunction with MSB Energy Associates, conducted a study for the Boston Edison Demand-Side Management (DSM) Settlement Board on the potential for DSM renewables in the Boston area. DSM renewables are resources that can be used in a distributed utility approach to avoid transmission and distribution (T and D) costs, as well as costs associated with operating and building power plants. The results show that avoided costs in areas with deferrable T and D investments can be nearly twice as high as system-wide average avoided costs. As a result, renewable technologies that might not be considered cost effective as DSM under system-wide average criteria, can produce large shavings for the utility and its customers. Adopting a deliberate program designed to provide sustained orderly development of these renewables is essential in order for renewable technologies to achieve the maximum level of cost-effectiveness and net savings.

  1. Using the Job Demands-Resources model to investigate risk perception, safety climate and job satisfaction in safety critical organizations.

    PubMed

    Nielsen, Morten Birkeland; Mearns, Kathryn; Matthiesen, Stig Berge; Eid, Jarle

    2011-10-01

    Using the Job Demands-Resources model (JD-R) as a theoretical framework, this study investigated the relationship between risk perception as a job demand and psychological safety climate as a job resource with regard to job satisfaction in safety critical organizations. In line with the JD-R model, it was hypothesized that high levels of risk perception is related to low job satisfaction and that a positive perception of safety climate is related to high job satisfaction. In addition, it was hypothesized that safety climate moderates the relationship between risk perception and job satisfaction. Using a sample of Norwegian offshore workers (N = 986), all three hypotheses were supported. In summary, workers who perceived high levels of risk reported lower levels of job satisfaction, whereas this effect diminished when workers perceived their safety climate as positive. Follow-up analyses revealed that this interaction was dependent on the type of risks in question. The results of this study supports the JD-R model, and provides further evidence for relationships between safety-related concepts and work-related outcomes indicating that organizations should not only develop and implement sound safety procedures to reduce the effects of risks and hazards on workers, but can also enhance other areas of organizational life through a focus on safety. PMID:21534979

  2. Demand Response Dispatch Tool

    SciTech Connect

    2012-08-31

    The Demand Response (DR) Dispatch Tool uses price profiles to dispatch demand response resources and create load modifying profiles. These annual profiles are used as inputs to production cost models and regional planning tools (e.g., PROMOD). The tool has been effectively implemented in transmission planning studies conducted by the Western Electricity Coordinating Council via its Transmission Expansion Planning and Policy Committee. The DR Dispatch Tool can properly model the dispatch of DR resources for both reliability and economic conditions.

  3. Amarogentin regulates self renewal pathways to restrict liver carcinogenesis in experimental mouse model.

    PubMed

    Sur, Subhayan; Pal, Debolina; Banerjee, Kaustav; Mandal, Suvra; Das, Ashes; Roy, Anup; Panda, Chinmay Kumar

    2016-07-01

    Amarogentin, a secoiridoid glycoside isolated from medicinal plant Swertia chirata, was found to restrict CCl4 /N-nitrosodiethyl amine (NDEA) induced mouse liver carcinogenesis by modulating G1/S cell cycle check point and inducing apoptosis. To understand its therapeutic efficacy on stem cell self renewal pathways, prevalence of CD44 positive cancer stem cell (CSC) population, expressions (mRNA/protein) of some key regulatory genes of self renewal Wnt and Hedgehog pathways along with expressions of E-cadherin and EGFR were analyzed during the liver carcinogenesis and in liver cancer cell line HepG2. It was observed that amarogentin could significantly reduce CD44 positive CSCs in both pre and post initiation stages of carcinogenesis than carcinogen control mice. In Wnt pathway, amarogentin could inhibit expressions of β-catenin, phospho β-catenin (Y-654) and activate expressions of antagonists sFRP1/2 and APC in the liver lesions. In Hedgehog pathway, decreased expressions of Gli1, sonic hedgehog ligand, and SMO along with up-regulation of PTCH1 were seen in the liver lesions due to amarogentin treatment. Moreover, amarogentin could up-regulate E-cadherin expression and down-regulate expression of EGFR in the liver lesions. Similarly, amarogentin could inhibit HepG2 cell growth along with expression and prevalence of CD44 positive CSCs. Similar to in vivo analysis, amarogentin could modulate the expressions of the key regulatory genes of the Wnt and hedgehog pathways and EGFR in HepG2 cells. Thus, our data suggests that the restriction of liver carcinogenesis by amarogentin might be due to reduction of CD44 positive CSCs and modulation of the self renewal pathways. © 2015 Wiley Periodicals, Inc. PMID:26154024

  4. A New High Resolution Wave Modeling System for Renewable Energy Applications in California and the Mediterranean Sea

    NASA Astrophysics Data System (ADS)

    Galanis, G. N.; Kafatos, M.; Chu, P. C.; Hatzopoulos, N.; Emmanouil, G.; Kallos, G. B.

    2014-12-01

    The use of integrated high accuracy wave systems is of critical importance today for applications on renewable energy assessment and monitoring, especially over offshore areas where the availability of credible, quality controlled corresponding observations is limited. In this work a new wave modeling system developed by the Hellenic Naval Academy and the University of Athens, Greece, the Center of Excellence in Earth Systems Modeling & Observations of Schmid College of Science in Chapman University, USA and the Naval Ocean and Analysis Laboratory of the US-Naval Postgraduate School, is presented. The new wave system has been based on WAM (ECMWF parallel version) model and focuses on parameters that directly or not affect the estimation of wave power potential in offshore and near shore areas. The results obtained are utilized for monitoring the wave energy potential over the California and Eastern Mediterranean coastline. A detailed statistical analysis based on classical and non-conventional measures provides a solid framework for the quantification of the results. Extreme values-cases posing potential threats for renewable energy parks and platforms are particularly analyzed.

  5. The unavoidable uncertainty of renewable energy and its management

    NASA Astrophysics Data System (ADS)

    Koutsoyiannis, Demetris

    2016-04-01

    Conventional energy systems gave the luxury of a fully controllable and deterministically manageable energy production. Renewable energies are uncertain and often unavailable at the time of demand. Wind and solar energies are highly variable, dependent on atmospheric and climatic conditions and unpredictable. The related uncertainty is much higher than commonly thought, as both the wind and sunshine duration processes exhibit Hurst-Kolmogorov behaviour. Lack of proper modelling of this behaviour results in overestimation of wind and solar energy potentials, and frequent "surprises" of persisting low (or high) production. Proper modelling of the uncertainty is a necessary step for renewable energy management. This latter requires both structural measures - in particular integration with pumped storage hydropower systems - and optimization methodologies for the operation of large-scale hybrid renewable energy systems. These key ideas are illustrated with a case study for a big district of Greece.

  6. A Simple Forecasting Model Linking Macroeconomic Policy to Industrial Employment Demand.

    ERIC Educational Resources Information Center

    Malley, James R.; Hady, Thomas F.

    A study detailed further a model linking monetary and fiscal policy to industrial employment in metropolitan and nonmetropolitan areas of four United States regions. The model was used to simulate the impacts on area and regional employment of three events in the economy: changing real gross national product (GNP) via monetary policy, holding the…

  7. Tuition Elasticity of the Demand for Higher Education among Current Students: A Pricing Model.

    ERIC Educational Resources Information Center

    Bryan, Glenn A.; Whipple, Thomas W.

    1995-01-01

    A pricing model is offered, based on retention of current students, that colleges can use to determine appropriate tuition. A computer-based model that quantifies the relationship between tuition elasticity and projected net return to the college was developed and applied to determine an appropriate tuition rate for a small, private liberal arts…

  8. An integrated mathematical model for chemical oxygen demand (COD) removal in moving bed biofilm reactors (MBBR) including predation and hydrolysis.

    PubMed

    Revilla, Marta; Galán, Berta; Viguri, Javier R

    2016-07-01

    An integrated mathematical model is proposed for modelling a moving bed biofilm reactor (MBBR) for removal of chemical oxygen demand (COD) under aerobic conditions. The composite model combines the following: (i) a one-dimensional biofilm model, (ii) a bulk liquid model, and (iii) biological processes in the bulk liquid and biofilm considering the interactions among autotrophic, heterotrophic and predator microorganisms. Depending on the values for the soluble biodegradable COD loading rate (SCLR), the model takes into account a) the hydrolysis of slowly biodegradable compounds in the bulk liquid, and b) the growth of predator microorganisms in the bulk liquid and in the biofilm. The integration of the model and the SCLR allows a general description of the behaviour of COD removal by the MBBR under various conditions. The model is applied for two in-series MBBR wastewater plant from an integrated cellulose and viscose production and accurately describes the experimental concentrations of COD, total suspended solids (TSS), nitrogen and phosphorous obtained during 14 months working at different SCLRs and nutrient dosages. The representation of the microorganism group distribution in the biofilm and in the bulk liquid allow for verification of the presence of predator microorganisms in the second reactor under some operational conditions. PMID:27085154

  9. Involving regional expertise in nationwide modeling for adequate prediction of climate change effects on different demands for fresh water

    NASA Astrophysics Data System (ADS)

    de Lange, W. J.

    2014-05-01

    Wim J. de Lange, Geert F. Prinsen, Jacco H. Hoogewoud, Ab A Veldhuizen, Joachim Hunink, Erik F.W. Ruijgh, Timo Kroon Nationwide modeling aims to produce a balanced distribution of climate change effects (e.g. harm on crops) and possible compensation (e.g. volume fresh water) based on consistent calculation. The present work is based on the Netherlands Hydrological Instrument (NHI, www.nhi.nu), which is a national, integrated, hydrological model that simulates distribution, flow and storage of all water in the surface water and groundwater systems. The instrument is developed to assess the impact on water use on land-surface (sprinkling crops, drinking water) and in surface water (navigation, cooling). The regional expertise involved in the development of NHI come from all parties involved in the use, production and management of water, such as waterboards, drinking water supply companies, provinces, ngo's, and so on. Adequate prediction implies that the model computes changes in the order of magnitude that is relevant to the effects. In scenarios related to drought, adequate prediction applies to the water demand and the hydrological effects during average, dry, very dry and extremely dry periods. The NHI acts as a part of the so-called Deltamodel (www.deltamodel.nl), which aims to predict effects and compensating measures of climate change both on safety against flooding and on water shortage during drought. To assess the effects, a limited number of well-defined scenarios is used within the Deltamodel. The effects on demand of fresh water consist of an increase of the demand e.g. for surface water level control to prevent dike burst, for flushing salt in ditches, for sprinkling of crops, for preserving wet nature and so on. Many of the effects are dealt with by regional and local parties. Therefore, these parties have large interest in the outcome of the scenario analyses. They are participating in the assessment of the NHI previous to the start of the analyses

  10. Involving regional expertise in nationwide modeling for adequate prediction of climate change effects on different demands for fresh water

    NASA Astrophysics Data System (ADS)

    de Lange, Wim; Prinsen, Geert.; Hoogewoud, Jacco; Veldhuizen, Ab; Ruijgh, Erik; Kroon, Timo

    2013-04-01

    Nationwide modeling aims to produce a balanced distribution of climate change effects (e.g. harm on crops) and possible compensation (e.g. volume fresh water) based on consistent calculation. The present work is based on the Netherlands Hydrological Instrument (NHI, www.nhi.nu), which is a national, integrated, hydrological model that simulates distribution, flow and storage of all water in the surface water and groundwater systems. The instrument is developed to assess the impact on water use on land-surface (sprinkling crops, drinking water) and in surface water (navigation, cooling). The regional expertise involved in the development of NHI come from all parties involved in the use, production and management of water, such as waterboards, drinking water supply companies, provinces, ngo's, and so on. Adequate prediction implies that the model computes changes in the order of magnitude that is relevant to the effects. In scenarios related to drought, adequate prediction applies to the water demand and the hydrological effects during average, dry, very dry and extremely dry periods. The NHI acts as a part of the so-called Deltamodel (www.deltamodel.nl), which aims to predict effects and compensating measures of climate change both on safety against flooding and on water shortage during drought. To assess the effects, a limited number of well-defined scenarios is used within the Deltamodel. The effects on demand of fresh water consist of an increase of the demand e.g. for surface water level control to prevent dike burst, for flushing salt in ditches, for sprinkling of crops, for preserving wet nature and so on. Many of the effects are dealt with? by regional and local parties. Therefore, these parties have large interest in the outcome of the scenario analyses. They are participating in the assessment of the NHI previous to the start of the analyses. Regional expertise is welcomed in the calibration phase of NHI. It aims to reduce uncertainties by improving the

  11. Short-Term Energy Outlook Model Documentation: Hydrocarbon Gas Liquids Supply and Demand

    EIA Publications

    2015-01-01

    The hydrocarbon gas liquids (ethane, propane, butanes, and natural gasoline) module of the Short-Term Energy Outlook (STEO) model is designed to provide forecasts of U.S. production, consumption, refinery inputs, net imports, and inventories.

  12. A hybrid decomposition method for integrating coal supply and demand models

    SciTech Connect

    Shapiro, J.F.; White, D.E.

    1982-09-01

    A number of large scale models have been proposed and implemented in recent years to study the anticipated expansion of coal production and utilization in the United States. This paper reports on the application of mathematical programming decomposition methods to the constructive integration and optimization of these models. In particular, it was found that an implemented hybrid decomposition approach, part resource directed and part price directed, exhibited fast convergence to an optimal solution. (23 refs.)

  13. Model-Predictive Cascade Mitigation in Electric Power Systems With Storage and Renewables-Part II: Case-Study

    SciTech Connect

    Almassalkhi, MR; Hiskens, IA

    2015-01-01

    The novel cascade-mitigation scheme developed in Part I of this paper is implemented within a receding-horizon model predictive control (MPC) scheme with a linear controller model. This present paper illustrates the MPC strategy with a case-study that is based on the IEEE RTS-96 network, though with energy storage and renewable generation added. It is shown that the MPC strategy alleviates temperature overloads on transmission lines by rescheduling generation, energy storage, and other network elements, while taking into account ramp-rate limits and network limitations. Resilient performance is achieved despite the use of a simplified linear controller model. The MPC scheme is compared against a base-case that seeks to emulate human operator behavior.

  14. Model-Predictive Cascade Mitigation in Electric Power Systems With Storage and Renewables-Part I: Theory and Implementation

    SciTech Connect

    Almassalkhi, MR; Hiskens, IA

    2015-01-01

    A novel model predictive control (MPC) scheme is developed for mitigating the effects of severe line-overload disturbances in electrical power systems. A piece-wise linear convex approximation of line losses is employed to model the effect of transmission line power flow on conductor temperatures. Control is achieved through a receding-horizon model predictive control (MPC) strategy which alleviates line temperature overloads and thereby prevents the propagation of outages. The MPC strategy adjusts line flows by rescheduling generation, energy storage and controllable load, while taking into account ramp-rate limits and network limitations. In Part II of this paper, the MPC strategy is illustrated through simulation of the IEEE RTS-96 network, augmented to incorporate energy storage and renewable generation.

  15. An on-demand provision model for geospatial multisource information with active self-adaption services

    NASA Astrophysics Data System (ADS)

    Fan, Hong; Li, Huan

    2015-12-01

    Location-related data are playing an increasingly irreplaceable role in business, government and scientific research. At the same time, the amount and types of data are rapidly increasing. It is a challenge how to quickly find required information from this rapidly growing volume of data, as well as how to efficiently provide different levels of geospatial data to users. This paper puts forward a data-oriented access model for geographic information science data. First, we analyze the features of GIS data including traditional types such as vector and raster data and new types such as Volunteered Geographic Information (VGI). Taking into account these analyses, a classification scheme for geographic data is proposed and TRAFIE is introduced to describe the establishment of a multi-level model for geographic data. Based on this model, a multi-level, scalable access system for geospatial information is put forward. Users can select different levels of data according to their concrete application needs. Pull-based and push-based data access mechanisms based on this model are presented. A Service Oriented Architecture (SOA) was chosen for the data processing. The model of this study has been described by providing decision-making process of government departments with a simulation of fire disaster data collection. The use case shows this data model and the data provision system is flexible and has good adaptability.

  16. 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.

  17. The PEcAn Project: Accessible Tools for On-demand Ecosystem Modeling

    NASA Astrophysics Data System (ADS)

    Cowdery, E.; Kooper, R.; LeBauer, D.; Desai, A. R.; Mantooth, J.; Dietze, M.

    2014-12-01

    Ecosystem models play a critical role in understanding the terrestrial biosphere and forecasting changes in the carbon cycle, however current forecasts have considerable uncertainty. The amount of data being collected and produced is increasing on daily basis as we enter the "big data" era, but only a fraction of this data is being used to constrain models. Until we can improve the problems of model accessibility and model-data communication, none of these resources can be used to their full potential. The Predictive Ecosystem Analyzer (PEcAn) is an ecoinformatics toolbox and a set of workflows that wrap around an ecosystem model and manage the flow of information in and out of regional-scale TBMs. Here we present new modules developed in PEcAn to manage the processing of meteorological data, one of the primary driver dependencies for ecosystem models. The module downloads, reads, extracts, and converts meteorological observations to Unidata Climate Forecast (CF) NetCDF community standard, a convention used for most climate forecast and weather models. The module also automates the conversion from NetCDF to model specific formats, including basic merging, gap-filling, and downscaling procedures. PEcAn currently supports tower-based micrometeorological observations at Ameriflux and FluxNET sites, site-level CSV-formatted data, and regional and global reanalysis products such as the North American Regional Reanalysis and CRU-NCEP. The workflow is easily extensible to additional products and processing algorithms.These meteorological workflows have been coupled with the PEcAn web interface and now allow anyone to run multiple ecosystem models for any location on the Earth by simply clicking on an intuitive Google-map based interface. This will allow users to more readily compare models to observations at those sites, leading to better calibration and validation. Current work is extending these workflows to also process field, remotely-sensed, and historical

  18. Role of Storage and Demand Response, Greening the Grid

    SciTech Connect

    2015-09-01

    Greening the Grid provides technical assistance to energy system planners, regulators, and grid operators to overcome challenges associated with integrating variable renewable energy into the grid. This document, part of a Greening the Grid toolkit, examines storage and demand response as means to match renewable energy supply with demand.

  19. Study of the Bellman equation in a production model with unstable demand

    NASA Astrophysics Data System (ADS)

    Obrosova, N. K.; Shananin, A. A.

    2014-09-01

    A production model with allowance for a working capital deficit and a restricted maximum possible sales volume is proposed and analyzed. The study is motivated by the urgency of analyzing well-known problems of functioning low competitive macroeconomic structures. The original formulation of the task represents an infinite-horizon optimal control problem. As a result, the model is formalized in the form of a Bellman equation. It is proved that the corresponding Bellman operator is a contraction and has a unique fixed point in the chosen class of functions. A closed-form solution of the Bellman equation is found using the method of steps. The influence of the credit interest rate on the firm market value assessment is analyzed by applying the developed model.

  20. Multi-scale Drivers of Variations in Atmospheric Evaporative Demand Based on Observations and Physically-based Modeling

    NASA Astrophysics Data System (ADS)

    Peng, L.; Sheffield, J.; Li, D.

    2015-12-01

    Evapotranspiration (ET) is a key link between the availability of water resources and climate change and climate variability. Variability of ET has important environmental and socioeconomic implications for managing hydrological hazards, food and energy production. Although there have been many observational and modeling studies of ET, how ET has varied and the drivers of the variations at different temporal scales remain elusive. Much of the uncertainty comes from the atmospheric evaporative demand (AED), which is the combined effect of radiative and aerodynamic controls. The inconsistencies among modeled AED estimates and the limited observational data may originate from multiple sources including the limited time span and uncertainties in the data. To fully investigate and untangle the intertwined drivers of AED, we present a spectrum analysis to identify key controls of AED across multiple temporal scales. We use long-term records of observed pan evaporation for 1961-2006 from 317 weather stations across China and physically-based model estimates of potential evapotranspiration (PET). The model estimates are based on surface meteorology and radiation derived from reanalysis, satellite retrievals and station data. Our analyses show that temperature plays a dominant role in regulating variability of AED at the inter-annual scale. At the monthly and seasonal scales, the primary control of AED shifts from radiation in humid regions to humidity in dry regions. Unlike many studies focusing on the spatial pattern of ET drivers based on a traditional supply and demand framework, this study underlines the importance of temporal scales when discussing controls of ET variations.

  1. Renewable Energy - Growing Opportunities in our Backyard

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Economic growth requires energy. Historically the United States has met this demand for energy by utilizing nonrenewable fossil fuels. Economic and environmental concerns at local, regional, and international levels are shifting attention to cleaner alternatives which are sustainable and renewable...

  2. Factors Affecting Teaching the Concept of Renewable Energy in Technology Assisted Environments and Designing Processes in the Distance Education Model

    ERIC Educational Resources Information Center

    Yucel, A. Seda

    2007-01-01

    The energy policies of today focus mainly on sustainable energy systems and renewable energy resources. Chemistry is closely related to energy recycling, energy types, renewable energy, and nature-energy interaction; therefore, it is now an obligation to enrich chemistry classes with renewable energy concepts and related awareness. Before creating…

  3. Cognitive Demand of Model Tracing Tutor Tasks: Conceptualizing and Predicting How Deeply Students Engage

    ERIC Educational Resources Information Center

    Kessler, Aaron M.; Stein, Mary Kay; Schunn, Christian D.

    2015-01-01

    Model tracing tutors represent a technology designed to mimic key elements of one-on-one human tutoring. We examine the situations in which such supportive computer technologies may devolve into mindless student work with little conceptual understanding or student development. To analyze the support of student intellectual work in the model…

  4. The Push and the Pull: Deficit Models, Ruby Payne, and Becoming a "Warm Demander"

    ERIC Educational Resources Information Center

    Boucher, Michael L.; Helfenbein, Robert J.

    2015-01-01

    Despite a caveat at the end of "A Framework for Understanding Poverty"(1996/2005), Ruby Payne's deficit model has led researchers to criticize her effect on White pre-service teaching students (Smiley and Helfenbein in "Multicult Perspect" 13(1):5-15, 2011; Gorski in "Educ Leadersh" 65:32-36, 2008a, "Equity…

  5. The Differentiation of Social Demands in Europe. The Social Basis of the European Models of Capitalism

    ERIC Educational Resources Information Center

    Amable, Bruno

    2009-01-01

    This paper tests the impact of various determinants of the preference for two key elements of the European social models: redistribution and trade unions, using individual data from the first round of the European Social Survey. The basic hypothesis is that the main determinant of an individual's support for these elements of the European models…

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

    NASA Astrophysics Data System (ADS)

    Lohmann, Timo

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

  7. Demands on Intranets — Viable System Model as a Foundation for Intranet Design

    NASA Astrophysics Data System (ADS)

    Amcoff Nyström, Christina

    2006-06-01

    The number of Intranets increases in organizations but their potential to support viability is not fully exploited. The cybernetic model, the Viable System Model, has not been connected to the Intranet concept before. Characteristics of the VSM, such as highlighting the importance of production, monitoring of production units through Early Warning Systems, autonomy and empowerment, are used as patterns and a base for de-signing essential parts and/or functions of an Intranet. The result is a brief description of functions vital to the operational parts of organizations. Examples are Early Warning Systems, control systems, "gate-keepers," amplifying and damping information to and from the organization and "agents" supporting search abilities on an Intranet.

  8. Housing demand or money supply? A new Keynesian dynamic stochastic general equilibrium model on China's housing market fluctuations

    NASA Astrophysics Data System (ADS)

    Wen, Xing-Chun; He, Ling-Yun

    2015-08-01

    There is a bitter controversy over what drives the housing price in China in the existing literature. In this paper, we investigate the underlying driving force behind housing price fluctuations in China, especially focusing on the role of housing demand shock with that of money supply shock in explaining housing price movements, by a new Keynesian dynamic stochastic general equilibrium model. Empirical results suggest that it is housing demand, instead of money supply, that mainly drives China's housing price movements. Relevant policy implication is further discussed, namely, whether to consider the housing price fluctuations in the conduct of monetary policy. By means of the policy simulations, we find that a real house price-augmented money supply rule is a better monetary policy for China's economy stabilization. 1. Investment refers to fixed capital investment. 2. Housing price refers to national average housing price. Quarterly data on housing price during the period of our work are not directly available. However, monthly data of the value of sales on housing and sale volume on housing can be directly obtained from National Bureau of Statistics of China. We add up the monthly data and calculate one quarter's housing price by dividing the value of housing sales by its sale volume in one quarter. 3. M2 means the broad money supply in China.

  9. A two-level discount model for coordinating a decentralized supply chain considering stochastic price-sensitive demand

    NASA Astrophysics Data System (ADS)

    Heydari, Jafar; Norouzinasab, Yousef

    2015-07-01

    In this paper, a discount model is proposed to coordinate pricing and ordering decisions in a two-echelon supply chain (SC). Demand is stochastic and price sensitive while lead times are fixed. Decentralized decision making where downstream decides on selling price and order size is investigated. Then, joint pricing and ordering decisions are extracted where both members act as a single entity aim to maximize whole SC profit. Finally, a coordination mechanism based on quantity discount is proposed to coordinate both pricing and ordering decisions simultaneously. The proposed two-level discount policy can be characterized from two aspects: (1) marketing viewpoint: a retail price discount to increase the demand, and (2) operations management viewpoint: a wholesale price discount to induce the retailer to adjust its order quantity and selling price jointly. Results of numerical experiments demonstrate that the proposed policy is suitable to coordinate SC and improve the profitability of SC as well as all SC members in comparison with decentralized decision making.

  10. Daily fluctuations in teachers' well-being: a diary study using the Job Demands-Resources model.

    PubMed

    Simbula, Silvia

    2010-10-01

    The study tests the dynamic nature of the Job Demands-Resources model with regard to both motivational and health impairment processes. It does so by examining whether daily fluctuations in co-workers' support (i.e., a typical job resource) and daily fluctuations in work/family conflict (i.e., a typical job demand) predict day-levels of job satisfaction and mental health through work engagement and exhaustion, respectively. A total of 61 schoolteachers completed a general questionnaire and a daily survey over a period of five consecutive work days. Multilevel analyses provided evidence for both the above processes. Consistently with the hypotheses, our results showed that day-level work engagement mediated the impact of day-level co-workers' support on day-level job satisfaction and day-level mental health, after general levels of work engagement and outcome variables had been controlled for. Moreover, day-level exhaustion mediated the relationship between day-level work/family conflict and day-level job satisfaction and day-level mental health after general levels of exhaustion and outcome variables had been controlled for. These findings provide new insights into the dynamic psychological processes that determine daily fluctuations in employee well-being. Such insights may be transformed into job redesign strategies and other interventions designed to enhance work-related psychological well-being on a daily level. PMID:20352542

  11. Personality and leader effectiveness: a moderated mediation model of leadership self-efficacy, job demands, and job autonomy.

    PubMed

    Ng, Kok-Yee; Ang, Soon; Chan, Kim-Yin

    2008-07-01

    The trait theory of leadership is advanced by a joint investigation of the mediating role of (a) leadership self-efficacy (LSE = leader's perceived capabilities to perform leader roles) in linking neuroticism, extraversion, and conscientiousness with leader effectiveness and (b) the moderating role of job demands and job autonomy in influencing the mediation. Using K. J. Preacher, D. D. Rucker, and A. F. Hayes' (2007) moderated mediation framework, the authors tested the model (over a 2-year period) with matched data from 394 military leaders and their supervisors. Results showed that LSE mediated the relationships for neuroticism, extraversion, and conscientiousness with leader effectiveness. Moderated mediation analyses further revealed that LSE mediated the relationships for (a) all 3 personality variables for only those leaders with low job demands; (b) neuroticism and conscientiousness for only those leaders with high job autonomy; and (c) extraversion, regardless of a leader's level of job autonomy. Results underscore the importance of accounting for leaders' situational contexts when examining the relationships between personality, LSE, and effectiveness. PMID:18642980

  12. Bmi-1 Regulates Extensive Erythroid Self-Renewal

    PubMed Central

    Kim, Ah Ram; Olsen, Jayme L.; England, Samantha J.; Huang, Yu-Shan; Fegan, Katherine H.; Delgadillo, Luis F.; McGrath, Kathleen E.; Kingsley, Paul D.; Waugh, Richard E.; Palis, James

    2015-01-01

    Summary Red blood cells (RBCs), responsible for oxygen delivery and carbon dioxide exchange, are essential for our well-being. Alternative RBC sources are needed to meet the increased demand for RBC transfusions projected to occur as our population ages. We previously have discovered that erythroblasts derived from the early mouse embryo can self-renew extensively ex vivo for many months. To better understand the mechanisms regulating extensive erythroid self-renewal, global gene expression data sets from self-renewing and differentiating erythroblasts were analyzed and revealed the differential expression of Bmi-1. Bmi-1 overexpression conferred extensive self-renewal capacity upon adult bone-marrow-derived self-renewing erythroblasts, which normally have limited proliferative potential. Importantly, Bmi-1 transduction did not interfere with the ability of extensively self-renewing erythroblasts (ESREs) to terminally mature either in vitro or in vivo. Bmi-1-induced ESREs can serve to generate in vitro models of erythroid-intrinsic disorders and ultimately may serve as a source of cultured RBCs for transfusion therapy. PMID:26028528

  13. A hydraulic model is compatible with rapid changes in leaf elongation under fluctuating evaporative demand and soil water status.

    PubMed

    Caldeira, Cecilio F; Bosio, Mickael; Parent, Boris; Jeanguenin, Linda; Chaumont, François; Tardieu, François

    2014-04-01

    Plants are constantly facing rapid changes in evaporative demand and soil water content, which affect their water status and growth. In apparent contradiction to a hydraulic hypothesis, leaf elongation rate (LER) declined in the morning and recovered upon soil rehydration considerably quicker than transpiration rate and leaf water potential (typical half-times of 30 min versus 1-2 h). The morning decline of LER began at very low light and transpiration and closely followed the stomatal opening of leaves receiving direct light, which represent a small fraction of leaf area. A simulation model in maize (Zea mays) suggests that these findings are still compatible with a hydraulic hypothesis. The small water flux linked to stomatal aperture would be sufficient to decrease water potentials of the xylem and growing tissues, thereby causing a rapid decline of simulated LER, while the simulated water potential of mature tissues declines more slowly due to a high hydraulic capacitance. The model also captured growth patterns in the evening or upon soil rehydration. Changes in plant hydraulic conductance partly counteracted those of transpiration. Root hydraulic conductivity increased continuously in the morning, consistent with the transcript abundance of Zea maize Plasma Membrane Intrinsic Protein aquaporins. Transgenic lines underproducing abscisic acid, with lower hydraulic conductivity and higher stomatal conductance, had a LER declining more rapidly than wild-type plants. Whole-genome transcriptome and phosphoproteome analyses suggested that the hydraulic processes proposed here might be associated with other rapidly occurring mechanisms. Overall, the mechanisms and model presented here may be an essential component of drought tolerance in naturally fluctuating evaporative demand and soil moisture. PMID:24420931

  14. Impacts of Demand-Side Resources on Electric Transmission Planning

    SciTech Connect

    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 were 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.

  15. Testing water demand management scenarios in a water-stressed basin in South Africa: application of the WEAP model

    NASA Astrophysics Data System (ADS)

    Lévite, Hervé; Sally, Hilmy; Cour, Julien

    Like many river basins in South Africa, water resources in the Olifants river basin are almost fully allocated. Respecting the so-called “reserve” (water flow reservation for basic human needs and the environment) imposed by the Water Law of 1998 adds a further dimension, if not difficulty, to water resources management in the basin, especially during the dry periods. Decision makers and local stakeholders (i.e. municipalities, water users’ associations, interest groups), who will soon be called upon to work together in a decentralized manner within Catchment Management Agencies (CMAs) and Catchment Management Committees (CMCs), must therefore be able to get a rapid and simple understanding of the water balances at different levels in the basin. This paper seeks to assess the pros and cons of using the Water Evaluation and Planning (WEAP) model for this purpose via its application to the Steelpoort sub-basin of the Olifants river. This model allows the simulation and analysis of various water allocation scenarios and, above all, scenarios of users’ behavior. Water demand management is one of the options discussed in more detail here. Simulations are proposed for diverse climatic situations from dry years to normal years and results are discussed. It is evident that the quality of data (in terms of availability and reliability) is very crucial and must be dealt with carefully and with good judgment. Secondly, credible hypotheses have to be made about water uses (losses, return flow) if the results are to be meaningfully used in support of decision-making. Within the limits of data availability, it appears that some water users are not able to meet all their requirements from the river, and that even the ecological reserve will not be fully met during certain years. But the adoption of water demand management procedures offers opportunities for remedying this situation during normal hydrological years. However, it appears that demand management alone will not

  16. A production planning model considering uncertain demand using two-stage stochastic programming in a fresh vegetable supply chain context.

    PubMed

    Mateo, Jordi; Pla, Lluis M; Solsona, Francesc; Pagès, Adela

    2016-01-01

    Production planning models are achieving more interest for being used in the primary sector of the economy. The proposed model relies on the formulation of a location model representing a set of farms susceptible of being selected by a grocery shop brand to supply local fresh products under seasonal contracts. The main aim is to minimize overall procurement costs and meet future demand. This kind of problem is rather common in fresh vegetable supply chains where producers are located in proximity either to processing plants or retailers. The proposed two-stage stochastic model determines which suppliers should be selected for production contracts to ensure high quality products and minimal time from farm-to-table. Moreover, Lagrangian relaxation and parallel computing algorithms are proposed to solve these instances efficiently in a reasonable computational time. The results obtained show computational gains from our algorithmic proposals in front of the usage of plain CPLEX solver. Furthermore, the results ensure the competitive advantages of using the proposed model by purchase managers in the fresh vegetables industry. PMID:27386288

  17. U.S. federal agency models offer different visions for achieving Renewable Fuel Standard (RFS2) biofuel volumes.

    PubMed

    Keeler, Bonnie L; Krohn, Brian J; Nickerson, Thomas A; Hill, Jason D

    2013-09-17

    The Renewable Fuel Standard (RFS2) in the U.S. Energy Independence and Security Act of 2007 (EISA) sets annual volume targets for domestic renewable transportation fuel consumption through 2022, but allows for flexibility in the types of biomass used for biofuels and where and how they are grown. Spatially explicit feedstock scenarios for how the agricultural and forestry sectors can produce sufficient biomass to meet these targets have been developed by the U.S. Department of Energy (DOE), the U.S. Environmental Protection Agency (EPA), and the U.S. Department of Agriculture (USDA). Here we compare the models used to generate these scenarios and their underlying assumptions on crop yields, feedstock prices, biofuel conversion efficiencies, land availability, and other critical factors. We find key differences in the amount of land devoted to different biomass sources and their geographic distribution, most notably for perennial grasses. These different visions of land use and management for bioenergy in the U.S. are currently being used both for regulation and to set research funding priorities. Understanding the key assumptions and uncertainties that underlie these scenarios is important for accurate assessment of the potential economic and environmental impacts of RFS2, as well as for optimal design of future energy and agricultural policy. PMID:24010884

  18. 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…

  19. Renewable Diesel from Algal Lipids: An Integrated Baseline for Cost, Emissions, and Resource Potential from a Harmonized Model

    SciTech Connect

    Davis, R.; Fishman, D.; Frank, E. D.; Wigmosta, M. S.; Aden, A.; Coleman, A. M.; Pienkos, P. T.; Skaggs, R. J.; Venteris, E. R.; Wang, M. Q.

    2012-06-01

    The U.S. Department of Energy's Biomass Program has begun an initiative to obtain consistent quantitative metrics for algal biofuel production to establish an 'integrated baseline' by harmonizing and combining the Program's national resource assessment (RA), techno-economic analysis (TEA), and life-cycle analysis (LCA) models. The baseline attempts to represent a plausible near-term production scenario with freshwater microalgae growth, extraction of lipids, and conversion via hydroprocessing to produce a renewable diesel (RD) blendstock. Differences in the prior TEA and LCA models were reconciled (harmonized) and the RA model was used to prioritize and select the most favorable consortium of sites that supports production of 5 billion gallons per year of RD. Aligning the TEA and LCA models produced slightly higher costs and emissions compared to the pre-harmonized results. However, after then applying the productivities predicted by the RA model (13 g/m2/d on annual average vs. 25 g/m2/d in the original models), the integrated baseline resulted in markedly higher costs and emissions. The relationship between performance (cost and emissions) and either productivity or lipid fraction was found to be non-linear, and important implications on the TEA and LCA results were observed after introducing seasonal variability from the RA model. Increasing productivity and lipid fraction alone was insufficient to achieve cost and emission targets; however, combined with lower energy, less expensive alternative technology scenarios, emissions and costs were substantially reduced.

  20. Considering Renewables in Capacity Expansion Models: Capturing Flexibility with Hourly Dispatch

    SciTech Connect

    Barrows, Clayton; Mai, Trieu; Hale, Elaine; Lopez, Anthony; Eurek, Kelly

    2015-07-03

    The Resource Planning Model co-optimizes dispatch and capacity expansion using a simplified, chronological dispatch period representation and high-resolution resource, load and infrastructure data. The computational tractability of capacity expansion models depends on model simplifications. We demonstrate the effects of various dispatch period representations on model results using the Resource Planning Model.

  1. Substitution patterns across alternatives as a source of preference heterogeneity in recreation demand models.

    PubMed

    Bujosa Bestard, Angel

    2014-11-01

    Recent stated choice studies have shown that, in a context of inter-alternative correlation, individuals can assess alternatives differently. This asymmetry in perception between alternatives with different levels of substitutability becomes one additional, but usually overlooked, source of observed preference heterogeneity. In the context of beach recreation in Mallorca, Spain, this paper extends the investigation on this source of heterogeneity to a revealed preference setting. While the substitution pattern existent across sites is accounted for by means of a nested logit model, nest-specific coefficients are estimated to evaluate the utilities associated with different groups of sites. The results provide empirical evidence to suggest that substitution patterns across alternatives are a statistically significant source of influence on preference heterogeneity leading to different marginal sensitivities for a number of site attributes. PMID:24956466

  2. A multi-item maintenance center inventory model for low-demand reparable items

    NASA Technical Reports Server (NTRS)

    Schaefer, M. K.

    1983-01-01

    In many military and commercial contexts, complex equipment undergoes scheduled maintenance overhauls at regular intervals during which all failed components are replaced. Failure to have replacements on hand for all failed parts requires emergency measures at premium cost. When reparable parts are highly reliable and expensive, both holding and shortage costs are high. This model determines the reparable parts inventory for a maintenance center under three alternative criteria: (1) maximizing job-completion rate subject to constraint on total holding costs, (2) minimizing total holding costs plus expected job noncompletion costs, and (3) minimizing total holding costs subject to a required minimum job-completion rate. Exact solutions may be obtained using dynamic programming. Approximate solutions, found easily by marginal analysis, have readily computed bounds on possible error. The solution methods for the three formulations are illustrated in a simple example.

  3. Calculating impacts of energy standards on energy demand in U.S. buildings with uncertainty in an integrated assessment model

    SciTech Connect

    Scott, Michael J.; Daly, Don S.; Hathaway, John E.; Lansing, Carina S.; Liu, Ying; McJeon, Haewon C.; Moss, Richard H.; Patel, Pralit L.; Peterson, Marty J.; Rice, Jennie S.; Zhou, Yuyu

    2015-10-01

    In this paper, an integrated assessment model (IAM) uses a newly-developed Monte Carlo analysis capability to analyze the impacts of more aggressive U.S. residential and commercial building-energy codes and equipment standards on energy consumption and energy service costs at the state level, explicitly recognizing uncertainty in technology effectiveness and cost, socioeconomics, presence or absence of carbon prices, and climate impacts on energy demand. The paper finds that aggressive building-energy codes and equipment standards are an effective, cost-saving way to reduce energy consumption in buildings and greenhouse gas emissions in U.S. states. This conclusion is robust to significant uncertainties in population, economic activity, climate, carbon prices, and technology performance and costs.

  4. Treatment for life for severe haemophilia A- A cost-utility model for prophylaxis vs. on-demand treatment.

    PubMed

    Farrugia, A; Cassar, J; Kimber, M C; Bansal, M; Fischer, K; Auserswald, G; O'Mahony, B; Tolley, K; Noone, D; Balboni, S

    2013-07-01

    Prophylaxis has been established as the treatment of choice in children with haemophilia and its continuation into the adult years has been shown to decrease morbidity throughout life. The cost of factor therapy has made the option questionable in cost-effectiveness studies. The role of prophylaxis in pharmacokinetic dosage and tolerization against inhibitor formation were used to model the cost utility of prophylaxis vs. on-demand (OD) therapy over a lifetime horizon in severe haemophilia A. The model was applied to a single provider national health system exemplified by the United Kingdom's National Health Service and a third party provider in the United States. The incremental cost-effectiveness ratio (ICER) was estimated and compared to threshold values used by payer agencies to guide reimbursement decisions. A cost per quality-adjusted life year (QALY) was also estimated for Sweden. Prophylaxis was dominant over OD treatment in the UK. The model resulted in an ICER - $68 000 - within the range of treatments reimbursed in the USA. In Sweden, a cost/QALY of SEK 1.1 million was also within the range of reimbursed treatments in that country. Dosage- and treatment-induced inhibitor incidence were the most important variables in the model. Subject to continuing clinical evidence of the effectiveness of pharmacokinetic dosage and the role of prophylaxis in decreasing inhibitor incidence, treatment for life with prophylaxis is a cost-effective therapy, using current criteria for the reimbursement of health care technologies in a number of countries. PMID:23534877

  5. The bijection from data to parameter space with the standard DEB model quantifies the supply-demand spectrum.

    PubMed

    Lika, Konstadia; Augustine, Starrlight; Pecquerie, Laure; Kooijman, Sebastiaan A L M

    2014-08-01

    The standard Dynamic Energy Budget (DEB) model assumes that food is converted to reserve and a fraction κ of mobilised reserve of an individual is allocated to somatic maintenance plus growth, while the rest is allocated to maturity maintenance plus maturation (in embryos and juveniles) or reproduction (in adults). The add_my_pet collection of over 300 animal species from most larger phyla, and all chordate classes, shows that this model fits energy data very well. Nine parameters determine nine data points at abundant food: dry/wet weight ratio, age at birth, puberty, death, weight at birth, metamorphosis, puberty, ultimate weight and ultimate reproduction rate. We demonstrate that, given a few other parameters, these nine data points also determine the nine parameters uniquely that are independent of food availability: maturity at birth, metamorphosis and puberty, specific assimilation, somatic maintenance and costs for structure, allocation fraction of mobilised reserve to soma, energy conductance, and ageing acceleration. We provide an efficient algorithm for mapping between data and parameter space in both directions and found expressions for the boundaries of the parameter and data spaces. One of them quantifies the position of species in the supply-demand spectrum, which reflects the internalisation of energetic control. We link eco-physiological properties of species to their position in this spectrum and discuss it in the context of homeostasis. Invertebrates and ray-finned fish turn out to be close to the supply end of the spectrum, while other vertebrates, including cartilaginous fish, have stronger demand tendencies. We explain why birds and mammals up-regulate metabolism during reproduction. We study some properties of the bijection using elasticity coefficients. The properties have applications in parameter estimation and in the analysis of evolutionary constraints on parameter values; the relationship between DEB parameters and data has similarities

  6. A High-Resolution Spatially Explicit Monte-Carlo Simulation Approach to Commercial and Residential Electricity and Water Demand Modeling

    SciTech Connect

    Morton, April M; McManamay, Ryan A; Nagle, Nicholas N; Piburn, Jesse O; Stewart, Robert N; Surendran Nair, Sujithkumar

    2016-01-01

    Abstract As urban areas continue to grow and evolve in a world of increasing environmental awareness, the need for high resolution spatially explicit estimates for energy and water demand has become increasingly important. Though current modeling efforts mark significant progress in the effort to better understand the spatial distribution of energy and water consumption, many are provided at a course spatial resolution or rely on techniques which depend on detailed region-specific data sources that are not publicly available for many parts of the U.S. Furthermore, many existing methods do not account for errors in input data sources and may therefore not accurately reflect inherent uncertainties in model outputs. We propose an alternative and more flexible Monte-Carlo simulation approach to high-resolution residential and commercial electricity and water consumption modeling that relies primarily on publicly available data sources. The method s flexible data requirement and statistical framework ensure that the model is both applicable to a wide range of regions and reflective of uncertainties in model results. Key words: Energy Modeling, Water Modeling, Monte-Carlo Simulation, Uncertainty Quantification Acknowledgment This manuscript has been authored by employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. Accordingly, the United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

  7. The 1980 Report to Congress on the Nation's Renewable Resources.

    ERIC Educational Resources Information Center

    Wray, Bob; And Others

    This assessment describes the present renewable resources situation and projects future supplies of, and demands for, these resources. It also identifies various means to meet the demands. For selected resources, it also analyzes benefits and costs of meeting the demand. This assessment also shows that demand for forest and rangeland resources…

  8. Spatiotemporal Modeling for Assessing Complementarity of Renewable Energy Sources in Distributed Energy Systems

    NASA Astrophysics Data System (ADS)

    Ramirez Camargo, L.; Zink, R.; Dorner, W.

    2015-07-01

    Spatial assessments of the potential of renewable energy sources (RES) have become a valuable information basis for policy and decision-making. These studies, however, do not explicitly consider the variability in time of RES such as solar energy or wind. Until now, the focus is usually given to economic profitability based on yearly balances, which do not allow a comprehensive examination of RES-technologies complementarity. Incrementing temporal resolution of energy output estimation will permit to plan the aggregation of a diverse pool of RES plants i.e., to conceive a system as a virtual power plant (VPP). This paper presents a spatiotemporal analysis methodology to estimate RES potential of municipalities. The methodology relies on a combination of open source geographic information systems (GIS) processing tools and the in-memory array processing environment of Python and NumPy. Beyond the typical identification of suitable locations to build power plants, it is possible to define which of them are the best for a balanced local energy supply. A case study of a municipality, using spatial data with one square meter resolution and one hour temporal resolution, shows strong complementarity of photovoltaic and wind power. Furthermore, it is shown that a detailed deployment strategy of potential suitable locations for RES, calculated with modest computational requirements, can support municipalities to develop VPPs and improve security of supply.

  9. Multi-objective and Perishable Fuzzy Inventory Models Having Weibull Life-time With Time Dependent Demand, Demand Dependent Production and Time Varying Holding Cost: A Possibility/Necessity Approach

    NASA Astrophysics Data System (ADS)

    Pathak, Savita; Mondal, Seema Sarkar

    2010-10-01

    A multi-objective inventory model of deteriorating item has been developed with Weibull rate of decay, time dependent demand, demand dependent production, time varying holding cost allowing shortages in fuzzy environments for non- integrated and integrated businesses. Here objective is to maximize the profit from different deteriorating items with space constraint. The impreciseness of inventory parameters and goals for non-integrated business has been expressed by linear membership functions. The compromised solutions are obtained by different fuzzy optimization methods. To incorporate the relative importance of the objectives, the different cardinal weights crisp/fuzzy have been assigned. The models are illustrated with numerical examples and results of models with crisp/fuzzy weights are compared. The result for the model assuming them to be integrated business is obtained by using Generalized Reduced Gradient Method (GRG). The fuzzy integrated model with imprecise inventory cost is formulated to optimize the possibility necessity measure of fuzzy goal of the objective function by using credibility measure of fuzzy event by taking fuzzy expectation. The results of crisp/fuzzy integrated model are illustrated with numerical examples and results are compared.

  10. Coupled Mechanical-Electrochemical-Thermal Modeling for Accelerated Design of EV Batteries; NREL (National Renewable Energy Laboratory)

    SciTech Connect

    Pesaran, Ahmad; Zhang, Chao; Kim, Gi-heon; Santhanagopalan, Shriram

    2015-06-10

    The physical and chemical phenomena occurring in a battery are many and complex and in many different scales. Without a better knowledge of the interplay among the multi-physics occurring across the varied scales, it is very challenging and time consuming to design long-lasting, high-performing, safe, affordable large battery systems, enabling electrification of the vehicles and modernization of the grid. The National Renewable Energy Laboratory, a U.S. Department of Energy laboratory, has been developing thermal and electrochemical models for cells and battery packs. Working with software producers, carmakers, and battery developers, computer-aided engineering tools have been developed that can accelerate the electrochemical and thermal design of batteries, reducing time to develop and optimize them and thus reducing the cost of the system. In the past couple of years, we initiated a project to model the mechanical response of batteries to stress, strain, fracture, deformation, puncture, and crush and then link them to electrochemical and thermal models to predict the response of a battery. This modeling is particularly important for understanding the physics and processes that happen in a battery during a crush-inducing vehicle crash. In this paper, we provide an overview of electrochemical-thermal-mechanical models for battery system understanding and designing.

  11. M ≥ 7.0 earthquake recurrence on the San Andreas fault from a stress renewal model

    USGS Publications Warehouse

    Parsons, Thomas E.

    2006-01-01

     Forecasting M ≥ 7.0 San Andreas fault earthquakes requires an assessment of their expected frequency. I used a three-dimensional finite element model of California to calculate volumetric static stress drops from scenario M ≥ 7.0 earthquakes on three San Andreas fault sections. The ratio of stress drop to tectonic stressing rate derived from geodetic displacements yielded recovery times at points throughout the model volume. Under a renewal model, stress recovery times on ruptured fault planes can be a proxy for earthquake recurrence. I show curves of magnitude versus stress recovery time for three San Andreas fault sections. When stress recovery times were converted to expected M ≥ 7.0 earthquake frequencies, they fit Gutenberg-Richter relationships well matched to observed regional rates of M ≤ 6.0 earthquakes. Thus a stress-balanced model permits large earthquake Gutenberg-Richter behavior on an individual fault segment, though it does not require it. Modeled slip magnitudes and their expected frequencies were consistent with those observed at the Wrightwood paleoseismic site if strict time predictability does not apply to the San Andreas fault.

  12. Renewing Schools.

    ERIC Educational Resources Information Center

    McChesney, Jim

    1997-01-01

    This publication reviews works on educational reform that represent attempts to do more than merely respond in knee-jerk fashion to political pressure for reform. Bruce Joyce and Emily Calhoun, in "Learning Experiences in School Renewal: An Exploration of Five Successful Programs" (Eugene, Oregon: ERIC Clearinghouse on Educational Management,…

  13. Renewable Energy

    NASA Astrophysics Data System (ADS)

    Boyle, Godfrey

    2004-05-01

    Stimulated by recent technological developments and increasing concern over the sustainability and environmental impact of conventional fuel usage, the prospect of producing clean, sustainable power in substantial quantities from renewable energy sources arouses interest around the world. This book provides a comprehensive overview of the principal types of renewable energy--including solar, thermal, photovoltaics, bioenergy, hydro, tidal, wind, wave, and geothermal. In addition, it explains the underlying physical and technological principles of renewable energy and examines the environmental impact and prospects of different energy sources. With more than 350 detailed illustrations, more than 50 tables of data, and a wide range of case studies, Renewable Energy, 2/e is an ideal choice for undergraduate courses in energy, sustainable development, and environmental science. New to the Second Edition ·Full-color design ·Updated to reflect developments in technology, policy, attitides ·Complemented by Energy Systems and Sustainability edited by Godfrey Boyle, Bob Everett and Janet Ramage, all of the Open University, U.K.

  14. Performance Modeling and Testing of Distributed Electronics in PV Systems; NREL (National Renewable Energy Laboratory)

    SciTech Connect

    Deline, C.

    2015-03-18

    Computer modeling is able to predict the performance of distributed power electronics (microinverters, power optimizers) in PV systems. However, details about partial shade and other mismatch must be known in order to give the model accurate information to go on. This talk will describe recent updates in NREL’s System Advisor Model program to model partial shading losses with and without distributed power electronics, along with experimental validation results. Computer modeling is able to predict the performance of distributed power electronics (microinverters, power optimizers) in PV systems. However, details about partial shade and other mismatch must be known in order to give the model accurate information to go on. This talk will describe recent updates in NREL’s System Advisor Model program to model partial shading losses.

  15. The Negative Binomial Distribution as a Renewal Model for the Recurrence of Large Earthquakes

    NASA Astrophysics Data System (ADS)

    Tejedor, Alejandro; Gómez, Javier B.; Pacheco, Amalio F.

    2015-01-01

    The negative binomial distribution is presented as the waiting time distribution of a cyclic Markov model. This cycle simulates the seismic cycle in a fault. As an example, this model, which can describe recurrences with aperiodicities between 0 and 0.5, is used to fit the Parkfield, California earthquake series in the San Andreas Fault. The performance of the model in the forecasting is expressed in terms of error diagrams and compared with other recurrence models from literature.

  16. Demand Response Quick Assessment Tool

    Energy Science and Technology Software Center (ESTSC)

    2008-12-01

    DRQAT (Demand Response Quick Assessment Tool) is the tool for assessing demand response saving potentials for large commercial buildings. This tool is based on EnergyPlus simulations of prototypical buildings and HVAC equipment. The opportunities for demand reduction and cost savings with building demand responsive controls vary tremendously with building type and location. The assessment tools will predict the energy and demand savings, the economic savings, and the thermal comfor impact for various demand responsive strategies.more » Users of the tools will be asked to enter the basic building information such as types, square footage, building envelope, orientation, utility schedule, etc. The assessment tools will then use the prototypical simulation models to calculate the energy and demand reduction potential under certain demand responsive strategies, such as precooling, zonal temperature set up, and chilled water loop and air loop set points adjustment.« less

  17. Demand Response Quick Assessment Tool

    SciTech Connect

    Xu, Peng; Yin, Rongxin

    2008-12-01

    DRQAT (Demand Response Quick Assessment Tool) is the tool for assessing demand response saving potentials for large commercial buildings. This tool is based on EnergyPlus simulations of prototypical buildings and HVAC equipment. The opportunities for demand reduction and cost savings with building demand responsive controls vary tremendously with building type and location. The assessment tools will predict the energy and demand savings, the economic savings, and the thermal comfor impact for various demand responsive strategies. Users of the tools will be asked to enter the basic building information such as types, square footage, building envelope, orientation, utility schedule, etc. The assessment tools will then use the prototypical simulation models to calculate the energy and demand reduction potential under certain demand responsive strategies, such as precooling, zonal temperature set up, and chilled water loop and air loop set points adjustment.

  18. Understanding the responses of precipitation, evaporative demand, and terrestrial water availability to planetary temperature in climate models

    NASA Astrophysics Data System (ADS)

    Scheff, Jacob

    In many models of land hydrology, precipitation (P) and potential evapotranspiration (PET, a.k.a. evaporative demand) are the main inputs that determine actual evapotranspiration, runoff, soil moisture, and aridity or drought. In the first three chapters of this work, we attempt to understand the robust subtropical P declines, planet-wide PET increases, and widespread P/PET declines projected under strong greenhouse warming in CMIP5, a large suite of global climate models (GCMs). Motivated by the apparent absence of this aridification during past greenhouse eras (and the apparent aridity of the ice ages), in the final chapter we use a very simple land model coupled to an atmospheric GCM and a slab ocean to evaluate the relevance and robustness of the P/PET responses to warming across a wide range of boundary conditions and modeling choices. In the CMIP5 projections, robust P declines are almost entirely found within the equator-side flanks and extensions of the model extratropical P belts (including both dry and wet regions), not in the centers of the subtropical dry zones nor on the dry margins of the tropical wet belts. This implies that they are primarily caused by the dynamic poleward retreat of extratropically driven P, not by the thermodynamic increase in dry-zone moisture divergence (which occurs largely as an evaporation increase.) The robust P declines are largely found over the oceans and intersect land only in certain regions; most land locations see non-robust changes in P or robust increases in P. On the other hand, Penman-Monteith PET robustly increases everywhere on land, usually by a low double-digit percentage. This is because the simulated Penman-Monteith PET response is almost always dominated by the response to the local warming itself, not by the responses to concurrent changes in surface radiation, relative humidity (RH), or wind speed. For given values of the latter three variables, warming increases the numerator of the Penman

  19. A Mathematical Model to Predict Voltage Fluctuations in a Distribution System with Renewable Energy Sources

    NASA Astrophysics Data System (ADS)

    Iyer, Shivkumar Venkatraman; Wu, Bin; Li, Yunwei; Singh, Birendra

    2015-12-01

    This paper proposes a simplified mathematical model to predict the impact of connection of Distributed Generators (DGs) to the ac grid. The model allows the user to examine the fluctuations in the magnitude of voltages at different nodes in the distribution system. In order to use the model, the user does not require a commercial simulation software making it a handy tool for a practicing engineer. Analysis has been presented to describe how the detailed mathematical model of the system is reduced using elementary matrix manipulation techniques to obtain the final simplified mathematical model. Simulation results are presented to verify the mathematical model with a ring distribution system with three DGs connected to it and the results validate those attained from the mathematical model.

  20. 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.

  1. Hospital demand for physicians.

    PubMed

    Morrisey, M A; Jensen, G A

    1990-01-01

    This article develops a derived demand for physicians that is general enough to encompass physician control, simple profit maximization and hospital utility maximization models of the hospital. The analysis focuses on three special aspects of physician affiliations: the price of adding a physician to the staff is unobserved; the physician holds appointments at multiple hospitals, and physicians are not homogeneous. Using 1983 American Hospital Association data, a system of specialty-specific demand equations is estimated. The results are consistent with the model and suggest that physicians should be concerned about reduced access to hospitals, particularly as the stock of hospitals declines. PMID:10104050

  2. Demand Response Dispatch Tool

    Energy Science and Technology Software Center (ESTSC)

    2012-08-31

    The Demand Response (DR) Dispatch Tool uses price profiles to dispatch demand response resources and create load modifying profiles. These annual profiles are used as inputs to production cost models and regional planning tools (e.g., PROMOD). The tool has been effectively implemented in transmission planning studies conducted by the Western Electricity Coordinating Council via its Transmission Expansion Planning and Policy Committee. The DR Dispatch Tool can properly model the dispatch of DR resources for bothmore » reliability and economic conditions.« less

  3. EIA model documentation: World oil refining logistics demand model,``WORLD`` reference manual. Version 1.1

    SciTech Connect

    Not Available

    1994-04-11

    This manual is intended primarily for use as a reference by analysts applying the WORLD model to regional studies. It also provides overview information on WORLD features of potential interest to managers and analysts. Broadly, the manual covers WORLD model features in progressively increasing detail. Section 2 provides an overview of the WORLD model, how it has evolved, what its design goals are, what it produces, and where it can be taken with further enhancements. Section 3 reviews model management covering data sources, managing over-optimization, calibration and seasonality, check-points for case construction and common errors. Section 4 describes in detail the WORLD system, including: data and program systems in overview; details of mainframe and PC program control and files;model generation, size management, debugging and error analysis; use with different optimizers; and reporting and results analysis. Section 5 provides a detailed description of every WORLD model data table, covering model controls, case and technology data. Section 6 goes into the details of WORLD matrix structure. It provides an overview, describes how regional definitions are controlled and defines the naming conventions for-all model rows, columns, right-hand sides, and bounds. It also includes a discussion of the formulation of product blending and specifications in WORLD. Several Appendices supplement the main sections.

  4. Modeling Supply and Demand for Arts and Sciences Faculty: What Ten Years of Data Tell Us about the Labor Market Projections of Bowen and Sosa.

    ERIC Educational Resources Information Center

    Shapiro, Douglas T.

    2001-01-01

    The labor market projections of Bowen and Sosa's "Prospects for Faculty" (1989) are assessed by testing their assumptions about faculty supply and demand against data from the last decade. Improvements to the model are recommended, including the use of an inventory-attrition model to account for backlogs of supply. (Author)

  5. Industrial Demand Module - NEMS Documentation

    EIA Publications

    2014-01-01

    Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Module. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code.

  6. Residential Demand Module - NEMS Documentation

    EIA Publications

    2014-01-01

    Model Documentation - 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.

  7. Factors and Models Associated with the amount of Hospital Care Services as Demanded by Hospitalized Patients: A Systematic Review

    PubMed Central

    van Oostveen, Catharina J.; Ubbink, Dirk T.; Huis in het Veld, Judith G.; Bakker, Piet J.; Vermeulen, Hester

    2014-01-01

    Background Hospitals are constantly being challenged to provide high-quality care despite ageing populations, diminishing resources, and budgetary restraints. While the costs of care depend on the patients' needs, it is not clear which patient characteristics are associated with the demand for care and inherent costs. The aim of this study was to ascertain which patient-related characteristics or models can predict the need for medical and nursing care in general hospital settings. Methods We systematically searched MEDLINE, Embase, Business Source Premier and CINAHL. Pre-defined eligibility criteria were used to detect studies that explored patient characteristics and health status parameters associated to the use of hospital care services for hospitalized patients. Two reviewers independently assessed study relevance, quality with the STROBE instrument, and performed data analysis. Results From 2,168 potentially relevant articles, 17 met our eligibility criteria. These showed a large variety of factors associated with the use of hospital care services; models were found in only three studies. Age, gender, medical and nursing diagnoses, severity of illness, patient acuity, comorbidity, and complications were the characteristics found the most. Patient acuity and medical and nursing diagnoses were the most influencing characteristics. Models including medical or nursing diagnoses and patient acuity explain the variance in the use of hospital care services for at least 56.2%, and up to 78.7% when organizational factors were added. Conclusions A larger variety of factors were found to be associated with the use of hospital care services. Models that explain the extent to which hospital care services are used should contain patient characteristics, including patient acuity, medical or nursing diagnoses, and organizational and staffing characteristics, e.g., hospital size, organization of care, and the size and skill mix of staff. This would enable healthcare managers

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

    NASA Astrophysics Data System (ADS)

    Avci, Mesut

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

  9. Estimating Demand Response Load Impacts: Evaluation of BaselineLoad Models for Non-Residential Buildings in California

    SciTech Connect

    Coughlin, Katie; Piette, Mary Ann; Goldman, Charles; Kiliccote,Sila

    2008-01-01

    Both Federal and California state policymakers areincreasingly interested in developing more standardized and consistentapproaches to estimate and verify the load impacts of demand responseprograms and dynamic pricing tariffs. This study describes a statisticalanalysis of the performance of different models used to calculate thebaseline electric load for commercial buildings participating in ademand-response (DR) program, with emphasis onthe importance of weathereffects. During a DR event, a variety of adjustments may be made tobuilding operation, with the goal of reducing the building peak electricload. In order to determine the actual peak load reduction, an estimateof what the load would have been on the day of the event without any DRactions is needed. This baseline load profile (BLP) is key to accuratelyassessing the load impacts from event-based DR programs and may alsoimpact payment settlements for certain types of DR programs. We testedseven baseline models on a sample of 33 buildings located in California.These models can be loosely categorized into two groups: (1) averagingmethods, which use some linear combination of hourly load values fromprevious days to predict the load on the event, and (2) explicit weathermodels, which use a formula based on local hourly temperature to predictthe load. The models were tested both with and without morningadjustments, which use data from the day of the event to adjust theestimated BLP up or down.Key findings from this study are: - The accuracyof the BLP model currently used by California utilities to estimate loadreductions in several DR programs (i.e., hourly usage in highest 3 out of10 previous days) could be improved substantially if a morning adjustmentfactor were applied for weather-sensitive commercial and institutionalbuildings. - Applying a morning adjustment factor significantly reducesthe bias and improves the accuracy of all BLP models examined in oursample of buildings. - For buildings with low load

  10. Modelling the Demand for Higher Education by Local Authority Area in England Using Academic, Economic and Social Data

    ERIC Educational Resources Information Center

    Harrison, Neil

    2013-01-01

    Managing the demand for higher education has been a major concern of successive UK governments over the last 30 years. While initially they sought to increase demand, latterly the emphasis has been on widening participation to include demographic groups among which it has traditionally been low. There had long been an academic and policy interest…

  11. The Faculty Research Residency: A Model for Supporting Teacher Education Curriculum Renewal

    ERIC Educational Resources Information Center

    Salmon, Diane; Gardiner, Wendy

    2016-01-01

    The faculty research residency (FRR) model was launched in 2010, with the goal of transforming coursework to improve the preparation of teachers for high-need schools. The FRR model leveraged school-university partnerships and situated university faculty in high-need schools to conduct research related to the university courses they taught. This…

  12. Potential Teaching Model for Applying Novel Approaches of Renewed Estonian National Curriculum into Visual Art Classes in Primary School

    ERIC Educational Resources Information Center

    Vahter, Edna

    2015-01-01

    In 2010, the renewed national curriculum was legislated in Estonia. Major changes include a new list of cross-curricular topics, increased importance of integration and specification of the components of the art learning process. In this situation, the question arises--how to fully implement the challenges of the renewed curriculum in primary…

  13. Maximizing Energy Savings Reliability in BC Hydro Industrial Demand-side Management Programs: An Assessment of Performance Incentive Models

    NASA Astrophysics Data System (ADS)

    Gosman, Nathaniel

    For energy utilities faced with expanded jurisdictional energy efficiency requirements and pursuing demand-side management (DSM) incentive programs in the large industrial sector, performance incentive programs can be an effective means to maximize the reliability of planned energy savings. Performance incentive programs balance the objectives of high participation rates with persistent energy savings by: (1) providing financial incentives and resources to minimize constraints to investment in energy efficiency, and (2) requiring that incentive payments be dependent on measured energy savings over time. As BC Hydro increases its DSM initiatives to meet the Clean Energy Act objective to reduce at least 66 per cent of new electricity demand with DSM by 2020, the utility is faced with a higher level of DSM risk, or uncertainties that impact the costeffective acquisition of planned energy savings. For industrial DSM incentive programs, DSM risk can be broken down into project development and project performance risks. Development risk represents the project ramp-up phase and is the risk that planned energy savings do not materialize due to low customer response to program incentives. Performance risk represents the operational phase and is the risk that planned energy savings do not persist over the effective measure life. DSM project development and performance risks are, in turn, a result of industrial economic, technological and organizational conditions, or DSM risk factors. In the BC large industrial sector, and characteristic of large industrial sectors in general, these DSM risk factors include: (1) capital constraints to investment in energy efficiency, (2) commodity price volatility, (3) limited internal staffing resources to deploy towards energy efficiency, (4) variable load, process-based energy saving potential, and (5) a lack of organizational awareness of an operation's energy efficiency over time (energy performance). This research assessed the capacity

  14. A New Approach for On-Demand Generation of Various Oxygen Tensions for In Vitro Hypoxia Models

    PubMed Central

    Li, Chunyan; Chaung, Wayne; Mozayan, Cameron; Chabra, Ranjeev; Wang, Ping; Narayan, Raj K.

    2016-01-01

    The development of in vitro disease models closely mimicking the functions of human disease has captured increasing attention in recent years. Oxygen tensions and gradients play essential roles in modulating biological systems in both physiologic and pathologic events. Thus, controlling oxygen tension is critical for mimicking physiologically relevant in vivo environments for cell, tissue and organ research. We present a new approach for on-demand generation of various oxygen tensions for in vitro hypoxia models. Proof-of-concept prototypes have been developed for conventional cell culture microplate by immobilizing a novel oxygen-consuming biomaterial on the 3D-printed insert. For the first time, rapid (~3.8 minutes to reach 0.5% O2 from 20.9% O2) and precisely controlled oxygen tensions/gradients (2.68 mmHg per 50 μm distance) were generated by exposing the biocompatible biomaterial to the different depth of cell culture media. In addition, changing the position of 3D-printed inserts with immobilized biomaterials relative to the cultured cells resulted in controllable and rapid changes in oxygen tensions (<130 seconds). Compared to the current technologies, our approach allows enhanced spatiotemporal resolution and accuracy of the oxygen tensions. Additionally, it does not interfere with the testing environment while maintaining ease of use. The elegance of oxygen tension manipulation introduced by our new approach will drastically improve control and lower the technological barrier of entry for hypoxia studies. Since the biomaterials can be immobilized in any devices, including microfluidic devices and 3D-printed tissues or organs, it will serve as the basis for a new generation of experimental models previously impossible or very difficult to implement. PMID:27219067

  15. Renewable Electricity Futures Study. Executive Summary

    SciTech Connect

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

    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 future 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).

  16. Modeling Lithium Ion Battery Safety: Venting of Pouch Cells; NREL (National Renewable Energy Laboratory)

    SciTech Connect

    Santhanagopalan, Shriram.; Yang, Chuanbo.; Pesaran, Ahmad

    2013-07-01

    This report documents the successful completion of the NREL July milestone entitled “Modeling Lithium-Ion Battery Safety - Complete Case-Studies on Pouch Cell Venting,” as part of the 2013 Vehicle Technologies Annual Operating Plan with the U.S. Department of Energy (DOE). This work aims to bridge the gap between materials modeling, usually carried out at the sub-continuum scale, and the

  17. The basin-level water demand management driven by dualistic water cycle and the development of Dualistic Model for Hai River Basin

    NASA Astrophysics Data System (ADS)

    Yang, Guiyu; Wang, Hao; Gan, Hong; Jia, Yangwen

    2010-05-01

    The basin water resources management (BWRM) is a coordinated project focused on the relationship between water supply and demand, which involves a united regulation and coordinated management process to maximize the benefits of available water resources, to improve the relationship between humans and water, and to develop economic systems and ecosystems. However, a water resources management system stresses different content depending on supply requirements, economic development and eco-environment protection policies in different social stages. At present, with high-intensity impact of human activities and natural precipitation reduction, contradiction between supply and demand water resources has become increasing prominent. Water shortage became a global problem. In limited supply condition water demand management becomes the focus of water resources management. However, since there is no need of technical support means, the present water demand management basically focuses on single linkages in the water cycle process, and falls short of investigation into the essence of water demand associated with the entire water cycle process. For the above reasons, selecting Haihe River basin as study area, the paper fully analyzes the "natural-artificial" dual water cycle, put forward the water demand management with "the water consumption (ET) management as the core, the seven total amount control target as the management objective. Addition, the paper achieves the quantitative for "ET management as the core, the seven total amount control indexes" by the development of Haihe River basin-level Dualsitic model

  18. JEDI: Jobs and Economic Development Impacts Model, National Renewable Energy Laboratory (NREL) (Fact Sheet)

    SciTech Connect

    Not Available

    2009-12-01

    The Jobs and Economic Development Impact (JEDI) models are user-friendly tools that estimate the economic impacts of constructing and operating power generation and biofuel plants at the local (usually state) level. First developed by NREL's Wind Powering America program to model wind energy jobs and impacts, JEDI has been expanded to biofuels, concentrating solar power, coal, and natural gas power plants. Based on project-specific and default inputs (derived from industry norms), JEDI estimates the number of jobs and economic impacts to a local area (usually a state) that could reasonably be supported by a power generation project. For example, JEDI estimates the number of in-state construction jobs from a new wind farm. This fact sheet provides an overview of the JEDI model as it pertains to wind energy projects.

  19. Recommendations on Model Fidelity for Wind Turbine Gearbox Simulations; NREL (National Renewable Energy Laboratory)

    SciTech Connect

    Keller, J.; Lacava, W.; Austin, J.; Nejad, A.; Halse, C.; Bastard, L.; Helsen, J.

    2015-02-01

    This work investigates the minimum level of fidelity required to accurately simulate wind turbine gearboxes using state-of-the-art design tools. Excessive model fidelity including drivetrain complexity, gearbox complexity, excitation sources, and imperfections, significantly increases computational time, but may not provide a commensurate increase in the value of the results. Essential designparameters are evaluated, including the planetary load-sharing factor, gear tooth load distribution, and sun orbit motion. Based on the sensitivity study results, recommendations for the minimum model fidelities are provided.

  20. JEDI: Jobs and Economic Development Impact Model; NREL (National Renewable Energy Laboratory)

    SciTech Connect

    2015-08-01

    The Jobs and Economic Development Impact (JEDI) models are user-friendly tools that estimate the economic impacts of constructing and operating power generation and biofuel plants at the local (usually state) level. First developed by NREL’s researchers to model wind energy jobs and impacts, JEDI has been expanded to also estimate the economic impacts of biofuels, coal, conventional hydro, concentrating solar power, geothermal, marine and hydrokinetic power, natural gas, photovoltaics, and transmission lines. This fact sheet focuses on JEDI for wind energy projects.

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

    SciTech Connect

    He, Fulin; Gu, Yi; Hao, Jun; Zhang, Jun Jason; Wei, Jiaolong; Zhang, Yingchen

    2015-11-11

    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. 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.

  2. A Stochastic Power Network Calculus for Integrating Renewable Energy Sources into the Power Grid

    SciTech Connect

    Wang, K; Ciucu, F; Lin, C; Low, SH

    2012-07-01

    Renewable energy such as solar and wind generation will constitute an important part of the future grid. As the availability of renewable sources may not match the load, energy storage is essential for grid stability. In this paper we investigate the feasibility of integrating solar photovoltaic (PV) panels and wind turbines into the grid by also accounting for energy storage. To deal with the fluctuation in both the power supply and demand, we extend and apply stochastic network calculus to analyze the power supply reliability with various renewable energy configurations. To illustrate the validity of the model, we conduct a case study for the integration of renewable energy sources into the power system of an island off the coast of Southern California. In particular, we asses the power supply reliability in terms of the average Fraction of Time that energy is Not-Served (FTNS).

  3. Renewable energy: Renewing the environment

    SciTech Connect

    Noun, R.J.

    1996-12-31

    During the past 20 years, the United States has enacted some of the world`s most comprehensive legislation to protect and preserve its environmental heritage. These regulations have spawned a $115-billion-per-year industry for {open_quotes}green{close_quotes} products and services, with more than 35,000 companies providing jobs for American workers. On the other hand, environmental regulations have placed heavy cost burdens on many U.S. businesses as they struggle to remain competitive in both domestic and foreign markets. How, then, can one reconcile the growing need for environmental protection with the desire for a stronger, healthier economy? Even as Congress debates the value of existing environmental legislation, new threats are appearing on the horizon. For example, extensive storm damage from Hurricane Andrew and other natural disasters has prompted members of the $650-billion insurance industry to begin studying the effects that global warming may have on future property damage claims. More and more people are realizing that the most efficient and economical way to control pollution is to avoid creating it in the first place. And that`s where renewable energy comes in. Technologies based on nonpolluting renewable energy sources such as sunlight and wind can help preserve our environmental heritage without a tangled web of regulations to burden industry. Renewable energy technologies can also help the United States become a world leader in a potential $400-billion-a-year global market for environmentally friendly products.

  4. Alternating Renewal Process Models for Behavioral Observation: Simulation Methods, Software, and Validity Illustrations

    ERIC Educational Resources Information Center

    Pustejovsky, James E.; Runyon, Christopher

    2014-01-01

    Direct observation recording procedures produce reductive summary measurements of an underlying stream of behavior. Previous methodological studies of these recording procedures have employed simulation methods for generating random behavior streams, many of which amount to special cases of a statistical model known as the alternating renewal…

  5. Review of dWindDS Model Initial Results; NREL (National Renewable Energy Laboratory)

    SciTech Connect

    Baring-Gould, Ian; Gleason, Michael; Preus, Robert; Sigrin, Ben

    2015-06-17

    The dWindDS model analyses the market diffusion of distributed wind generation for behind the meter applications. It is consumer decision based and uses a variety of data sets including a high resolution wind data set. It projects market development through 2050 based on input on specified by the user. This presentation covers some initial runs with draft base case assumptions.

  6. The PDS Model as a Vehicle for Simultaneous Renewal in Mathematics Education

    ERIC Educational Resources Information Center

    Martinie, Sherri L.; Rumsey, Chepina; Allen, David S.

    2014-01-01

    For a quarter century, Kansas State University's College of Education has supported a Professional Development School (PDS) model involving professional collaboration with selected public school systems across Kansas. In that time, this relationship has proved to be an instrumental vehicle for educational change. The state of Kansas'…

  7. A Transmission Renewal Planning Method using Supply-end Reserves and Line Flow Sensitivities

    NASA Astrophysics Data System (ADS)

    Ueda, Keisuke; Takamizawa, Yu; Iwamoto, Shinichi; Kato, Yoshinori; Shimazu, Masayuki

    With the high economic growth era until 1990s, the power demand increased sharply year by year. Therefore, the electric power utilities installed many electric power facilities along with the predicted demand. However, in recent years, fewer infrastructures have been installed because electric power demand growth is saturated due to low economic growth. Therefore, in electric power facilities planning, it has been necessary to form a rational renewal planning which also considers social influence factors such as the construction quantity. In this paper, we propose a new transmission renewal planning method using Supply-end Reserves and Line Flow Sensitivities. We carry out simulations for the IEEJ EAST 10-machine -O/V model system and determine the transmission planning priority order to confirm the validity of the proposed method.

  8. Turnover intention and emotional exhaustion “at the top”: Adapting the job demands-resources model to leaders of addiction treatment organizations

    PubMed Central

    Knudsen, Hannah K.; Ducharme, Lori J.; Roman, Paul M.

    2009-01-01

    Compared to the large literature on subordinate employees, there are few studies of emotional exhaustion and turnover intention for organizational leaders. There is little research that has extended the job demands-resources (JD-R) model of emotional exhaustion to leaders. In this study, we adapted the JD-R framework in order to analyze data collected from a sample of 410 leaders of addiction treatment organizations. We considered whether two job demands (performance demands and centralization) and two job resources (innovation in decision-making and long-range strategic planning) were associated with emotional exhaustion and turnover intention. We also examined whether emotional exhaustion fully or partially mediated the associations between the job-related measures and turnover intention. The results supported the partially mediated model. Both job demands were positively associated with emotional exhaustion, while the association for long-range strategic planning was negative. Emotional exhaustion was positively associated with turnover intention. Centralization and innovation in decision-making were also directly associated with turnover intention. Future research should continue to examine this theoretical framework among leaders of other types of organizations using more refined measures of demands and resources. PMID:19210050

  9. Exploring Tradeoffs in Demand-side and Supply-side Management of Urban Water Resources using Agent-based Modeling and Evolutionary Computation

    NASA Astrophysics Data System (ADS)

    Kanta, L.; Berglund, E. Z.

    2015-12-01

    Urban water supply systems may be managed through supply-side and demand-side strategies, which focus on water source expansion and demand reductions, respectively. Supply-side strategies bear infrastructure and energy costs, while demand-side strategies bear costs of implementation and inconvenience to consumers. To evaluate the performance of demand-side strategies, the participation and water use adaptations of consumers should be simulated. In this study, a Complex Adaptive Systems (CAS) framework is developed to simulate consumer agents that change their consumption to affect the withdrawal from the water supply system, which, in turn influences operational policies and long-term resource planning. Agent-based models are encoded to represent consumers and a policy maker agent and are coupled with water resources system simulation models. The CAS framework is coupled with an evolutionary computation-based multi-objective methodology to explore tradeoffs in cost, inconvenience to consumers, and environmental impacts for both supply-side and demand-side strategies. Decisions are identified to specify storage levels in a reservoir that trigger (1) increases in the volume of water pumped through inter-basin transfers from an external reservoir and (2) drought stages, which restrict the volume of water that is allowed for residential outdoor uses. The proposed methodology is demonstrated for Arlington, Texas, water supply system to identify non-dominated strategies for an historic drought decade. Results demonstrate that pumping costs associated with maximizing environmental reliability exceed pumping costs associated with minimizing restrictions on consumer water use.

  10. Turnover intention and emotional exhaustion "at the top": adapting the job demands-resources model to leaders of addiction treatment organizations.

    PubMed

    Knudsen, Hannah K; Ducharme, Lori J; Roman, Paul M

    2009-01-01

    Compared with the large literature on subordinate employees, there are few studies of emotional exhaustion and turnover intention for organizational leaders. There is little research that has extended the job demands-resources (JD-R) model of emotional exhaustion to leaders. In this study, the authors adapted the JD-R framework to analyze data collected from a sample of 410 leaders of addiction treatment organizations. The authors considered whether two job demands (performance demands and centralization) and two job resources (innovation in decision making and long-range strategic planning) were associated with emotional exhaustion and turnover intention. The authors also examined whether emotional exhaustion fully or partially mediated the associations between the job-related measures and turnover intention. The results supported the partially mediated model. Both job demands were positively associated with emotional exhaustion, and the association for long-range strategic planning was negative. Emotional exhaustion was positively associated with turnover intention. Centralization and innovation in decision making were also directly associated with turnover intention. Future research should continue to examine this theoretical framework among leaders of other types of organizations using more refined measures of demands and resources. PMID:19210050

  11. Multi-physics Modeling for Improving Li-Ion Battery Safety; NREL (National Renewable Energy Laboratory)

    SciTech Connect

    Pesaran, A.; Kim, G.; Santhanagopalan, S.; Yang, C.

    2015-04-21

    Battery performance, cost, and safety must be further improved for larger market share of HEVs/PEVs and penetration into the grid. Significant investment is being made to develop new materials, fine tune existing ones, improve cell and pack designs, and enhance manufacturing processes to increase performance, reduce cost, and make batteries safer. Modeling, simulation, and design tools can play an important role by providing insight on how to address issues, reducing the number of build-test-break prototypes, and accelerating the development cycle of generating products.

  12. Estimating Maintenance Demands Of A Space Station

    NASA Technical Reports Server (NTRS)

    Bream, B. L.

    1995-01-01

    RENEW computer program simulates maintenance events and estimates data pertinent to maintenance demands. Developed in support of Space Station Freedom Program (SSFP) Work Package 4. Uses data on reliability and maintainability (R&M) as well as logistical data to estimate both average and time-dependent maintenance demands. Estimates failure and repair times by use of Monte Carlo simulations. Written in BASIC and Assembly language.

  13. 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

  14. Modeling Photovoltaic Module-Level Power Electronics in the System Advisor Model; NREL (National Renewable Energy Laboratory)

    SciTech Connect

    2015-07-01

    Module-level power electronics, such as DC power optimizers, microinverters, and those found in AC modules, are increasing in popularity in smaller-scale photovoltaic (PV) systems as their prices continue to decline. Therefore, it is important to provide PV modelers with guidelines about how to model these distributed power electronics appropriately in PV modeling software. This paper extends the work completed at NREL that provided recommendations to model the performance of distributed power electronics in NREL’s popular PVWatts calculator [1], to provide similar guidelines for modeling these technologies in NREL's more complex System Advisor Model (SAM). Module-level power electronics - such as DC power optimizers, microinverters, and those found in AC modules-- are increasing in popularity in smaller-scale photovoltaic (PV) systems as their prices continue to decline. Therefore, it is important to provide PV modelers with guidelines about how to model these distributed power electronics appropriately in PV modeling software.

  15. Renewable Fuels Module - NEMS Documentation

    EIA Publications

    2014-01-01

    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 Annual Energy Outlook forecasts.

  16. The dynamic model on the impact of biodiesel blend mandate (B5) on Malaysian palm oil domestic demand: A preliminary finding

    NASA Astrophysics Data System (ADS)

    Abidin, Norhaslinda Zainal; Applanaidu, Shri-Dewi; Sapiri, Hasimah

    2014-12-01

    Over the last ten years, world biofuels production has increased dramatically. The biodiesel demand is driven by the increases in fossil fuel prices, government policy mandates, income from gross domestic product and population growth. In the European Union, biofuel consumption is mostly driven by blending mandates in both France and Germany. In the case of Malaysia, biodiesel has started to be exported since 2006. The B5 of 5% blend of palm oil based biodiesel into diesel in all government vehicles was implemented in February 2009 and it is expected to be implemented nationwide in the nearest time. How will the blend mandate will project growth in the domestic demand of palm oil in Malaysia? To analyze this issue, a system dynamics model was constructed to evaluate the impact of blend mandate implementation on the palm oil domestic demand influence. The base run of simulation analysis indicates that the trend of domestic demand will increase until 2030 in parallel with the implementation of 5 percent of biodiesel mandate. Finally, this study depicts that system dynamics is a useful tool to gain insight and to experiment with the impact of changes in blend mandate implementation on the future growth of Malaysian palm oil domestic demand sector.

  17. 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

  18. Analysis of the validity of the coefficient estimates and forecasting properties of the RDFOR (Regional Demand FORcasting) models: A summary report: Validation report

    SciTech Connect

    Kuh, E.; Lahiri, S.; Minkoff, A.; Swartz, S.; Welsch, R.

    1982-11-01

    The Regional Demand FORcasting model (RDFOR) is a simple econometric model currently used by the DOE within the Midterm Energy Forecasting System. Econometric models are often used to provide baseline forecasts of near- to mid-term economic behavior. From the point of view of the policymaker, it is desirable to ascertain as objectively as possible the degree to which these econometric forecasts can be trusted. This paper illustrates, within the context of the industrial and residential sectors of RDFOR, a number of diagnostic tools of general interest which are useful in assessing model reliability.

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

    SciTech Connect

    Augustine, Chad; Bain, Richard; Chapman, Jamie; Denholm, Paul; Drury, Easan; Hall, Douglas G.; Lantz, Eric; Margolis, Robert; Thresher, Robert; Sandor, Debra; Bishop, Norman A.; Brown, Stephen R.; Felker, Fort; Fernandez, Steven J.; Goodrich, Alan C.; Hagerman, George; Heath, Garvin; O'Neil, Sean; Paquette, Joshua; Tegen, Suzanne; Young, Katherine

    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 future 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/

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

    SciTech Connect

    Augustine, C.; Bain, R.; Chapman, J.; Denholm, P.; Drury, E.; Hall, D.G.; Lantz, E.; Margolis, R.; Thresher, R.; Sandor, D.; Bishop, N.A.; Brown, S.R.; Cada, G.F.; Felker, F.

    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 future 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).

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

    SciTech Connect

    Hand, M. M.; Baldwin, S.; DeMeo, E.; Reilly, J. M.; Mai, T.; Arent, D.; Porro, G.; Meshek, M.; Sandor, D.

    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 future 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/

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

    SciTech Connect

    Mai, T.; Wiser, R.; Sandor, D.; Brinkman, G.; Heath, G.; Denholm, P.; Hostick, D.J.; Darghouth, N.; Schlosser, A.; Strzepek, K.

    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 future 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).

  3. Impacts of Rising Air Temperatures and Emissions Mitigation on Electricity Demand and Supply in the United States. A Multi-Model Comparison

    SciTech Connect

    McFarland, James; Zhou, Yuyu; Clarke, Leon; Sullivan, Patrick; Colman, Jesse; Jaglom, Wendy S.; Colley, Michelle; Patel, Pralit; Eom, Jiyon; Kim, Son H.; Kyle, G. Page; Schultz, Peter; Venkatesh, Boddu; Haydel, Juanita; Mack, Charlotte; Creason, Jared

    2015-06-10

    The electric power sector both affects and is affected by climate change. Numerous studies highlight the potential of the power sector to reduce greenhouse gas emissions. Fewer studies have explored the physical impacts of climate change on the power sector. Our present analysis examines how projected rising temperatures affect the demand for and supply of electricity. We apply a common set of temperature projections to three well-known electric sector models in the United States: the US version of the Global Change Assessment Model (GCAM-USA), the Regional Electricity Deployment System model (ReEDS), and the Integrated Planning Model (IPM®). Incorporating the effects of rising temperatures from a control scenario without emission mitigation into the models raises electricity demand by 1.6 to 6.5 % in 2050 with similar changes in emissions. Moreover, the increase in system costs in the reference scenario to meet this additional demand is comparable to the change in system costs associated with decreasing power sector emissions by approximately 50 % in 2050. This result underscores the importance of adequately incorporating the effects of long-run temperature change in climate policy analysis.

  4. Erratum to: Impacts of rising air temperatures and emissions mitigation on electricity demand and supply in the United States: a multi-model comparison

    SciTech Connect

    McFarland, James; Zhou, Yuyu; Clarke, Leon; Sullivan, Patrick; Colman, Jesse; Jaglom, Wendy S.; Colley, Michelle; Patel, Pralit; Eom, Jiyon; Kim, Son H.; Kyle, G. Page; Schultz, Peter; Venkatesh, Boddu; Haydel, Juanita; Mack, Charlotte; Creason, Jared

    2015-07-07

    The electric power sector both affects and is affected by climate change. Numerous studies highlight the potential of the power sector to reduce greenhouse gas emissions. Yet fewer studies have explored the physical impacts of climate change on the power sector. The present analysis examines how projected rising temperatures affect the demand for and supply of electricity. We apply a common set of temperature projections to three well-known electric sector models in the United States: the US version of the Global Change Assessment Model (GCAM-USA), the Regional Electricity Deployment System model (ReEDS), and the Integrated Planning Model (IPM®). Incorporating the effects of rising temperatures from a control scenario without emission mitigation into the models raises electricity demand by 1.6 to 6.5 % in 2050 with similar changes in emissions. The increase in system costs in the reference scenario to meet this additional demand is comparable to the change in system costs associated with decreasing power sector emissions by approximately 50 % in 2050. This result underscores the importance of adequately incorporating the effects of long-run temperature change in climate policy analysis.

  5. Impacts of rising air temperatures and emissions mitigation on electricity demand and supply in the United States: a multi-model comparison

    SciTech Connect

    McFarland, James; Zhou, Yuyu; Clarke, Leon; Sullivan, Patrick; Colman, Jesse; Jaglom, Wendy S.; Colley, Michelle; Patel, Pralit; Eom, Jiyon; Kim, Son H.; Kyle, G. Page; Schultz, Peter; Venkatesh, Boddu; Haydel, Juanita; Mack, Charlotte; Creason, Jared

    2015-06-10

    The electric power sector both affects and is affected by climate change. Numerous studies highlight the potential of the power sector to reduce greenhouse gas emissions. Yet fewer studies have explored the physical impacts of climate change on the power sector. The present analysis examines how projected rising temperatures affect the demand for and supply of electricity. We apply a common set of temperature projections to three well-known electric sector models in the United States: the US version of the Global Change Assessment Model (GCAM-USA), the Regional Electricity Deployment System model (ReEDS), and the Integrated Planning Model (IPM®). Incorporating the effects of rising temperatures from a control scenario without emission mitigation into the models raises electricity demand by 1.6 to 6.5 % in 2050 with similar changes in emissions. The increase in system costs in the reference scenario to meet this additional demand is comparable to the change in system costs associated with decreasing power sector emissions by approximately 50 % in 2050. This result underscores the importance of adequately incorporating the effects of long-run temperature change in climate policy analysis.

  6. Impacts of Rising Air Temperatures and Emissions Mitigation on Electricity Demand and Supply in the United States. A Multi-Model Comparison

    DOE PAGESBeta

    McFarland, James; Zhou, Yuyu; Clarke, Leon; Sullivan, Patrick; Colman, Jesse; Jaglom, Wendy S.; Colley, Michelle; Patel, Pralit; Eom, Jiyon; Kim, Son H.; et al

    2015-06-10

    The electric power sector both affects and is affected by climate change. Numerous studies highlight the potential of the power sector to reduce greenhouse gas emissions. Fewer studies have explored the physical impacts of climate change on the power sector. Our present analysis examines how projected rising temperatures affect the demand for and supply of electricity. We apply a common set of temperature projections to three well-known electric sector models in the United States: the US version of the Global Change Assessment Model (GCAM-USA), the Regional Electricity Deployment System model (ReEDS), and the Integrated Planning Model (IPM®). Incorporating the effectsmore » of rising temperatures from a control scenario without emission mitigation into the models raises electricity demand by 1.6 to 6.5 % in 2050 with similar changes in emissions. Moreover, the increase in system costs in the reference scenario to meet this additional demand is comparable to the change in system costs associated with decreasing power sector emissions by approximately 50 % in 2050. This result underscores the importance of adequately incorporating the effects of long-run temperature change in climate policy analysis.« less

  7. Jobs and Renewable Energy Project

    SciTech Connect

    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 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.

  8. CREST Cost of Renewable Energy Spreadsheet Tool: A Model for Developing Cost-Based Incentives in the United States; User Manual Version 4, August 2009 - March 2011 (Updated July 2013)

    SciTech Connect

    Gifford, J. S.; Grace, R. C.

    2013-07-01

    The objective of this document is to help model users understand how to use the CREST model to support renewable energy incentives, FITs, and other renewable energy rate-setting processes. This user manual will walk the reader through the spreadsheet tool, including its layout and conventions, offering context on how and why it was created. This user manual will also provide instructions on how to populate the model with inputs that are appropriate for a specific jurisdiction's policymaking objectives and context. Finally, the user manual will describe the results and outline how these results may inform decisions about long-term renewable energy support programs.

  9. Renewable Electricity Futures for the United States

    SciTech Connect

    Mai, Trieu; Hand, Maureen; Baldwin, Sam F.; Wiser , Ryan; Brinkman, G.; Denholm, Paul; Arent, Doug; Porro, Gian; Sandor, Debra; Hostick, Donna J.; Milligan, Michael; DeMeo, Ed; Bazilian, Morgan

    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 is 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.

  10. Factor Structure and Longitudinal Measurement Invariance of the Demand Control Support Model: An Evidence from the Swedish Longitudinal Occupational Survey of Health (SLOSH)

    PubMed Central

    Chungkham, Holendro Singh; Ingre, Michael; Karasek, Robert; Westerlund, Hugo; Theorell, Töres

    2013-01-01

    Objectives To examine the factor structure and to evaluate the longitudinal measurement invariance of the demand-control-support questionnaire (DCSQ), using the Swedish Longitudinal Occupational Survey of Health (SLOSH). Methods A confirmatory factor analysis (CFA) and multi-group confirmatory factor analysis (MGCFA) models within the framework of structural equation modeling (SEM) have been used to examine the factor structure and invariance across time. Results Four factors: psychological demand, skill discretion, decision authority and social support, were confirmed by CFA at baseline, with the best fit obtained by removing the item repetitive work of skill discretion. A measurement error correlation (0.42) between work fast and work intensively for psychological demands was also detected. Acceptable composite reliability measures were obtained except for skill discretion (0.68). The invariance of the same factor structure was established, but caution in comparing mean levels of factors over time is warranted as lack of intercept invariance was evident. However, partial intercept invariance was established for work intensively. Conclusion Our findings indicate that skill discretion and decision authority represent two distinct constructs in the retained model. However removing the item repetitive work along with either work fast or work intensively would improve model fit. Care should also be taken while making comparisons in the constructs across time. Further research should investigate invariance across occupations or socio-economic classes. PMID:23950957

  11. Renewing governance.

    PubMed

    Loos, Gregory P

    2003-01-01

    Globalization's profound influence on social and political institutions need not be negative. Critics of globalization have often referred to the "Impossible Trinity" because decision-making must 1. respect national sovereignty, 2. develop and implement firm regulation, and 3. allow capital markets to be as free as possible. To many, such goals are mutually exclusive because history conditions us to view policy-making and governance in traditional molds. Thus, transnational governance merely appears impossible because current forms of governance were not designed to provide it. The world needs new tools for governing, and its citizens must seize the opportunity to help develop them. The rise of a global society requires a greater level of generality and inclusion than is found in most policy bodies today. Politicians need to re-examine key assumptions about government. States must develop ways to discharge their regulatory responsibilities across borders and collaborate with neighboring jurisdictions, multilateral bodies, and business. Concepts such as multilateralism and tripartism show great promise. Governments must engage civil society in the spirit of shared responsibility and democratic decision-making. Such changes will result in a renewal of the state's purpose and better use of international resources and expertise in governance. PMID:17208717

  12. US Renewable Futures in the GCAM

    SciTech Connect

    Smith, Steven J.; Mizrahi, Andrew H.; Karas, Joseph F.; Nathan, Mayda

    2011-10-06

    This project examines renewable energy deployment in the United States using a version of the GCAM integrated assessment model with detailed a representation of renewables, the GCAM-RE. Electricity generation was modeled in four generation segments and 12-subregions. This level of regional and sectoral detail allows a more explicit representation of renewable energy generation. Wind, solar thermal power, and central solar PV plants are implemented in explicit resource classes with new intermittency parameterizations appropriate for each technology. A scenario analysis examines a range of assumptions for technology characteristics, climate policy, and long-distance transmission. We find that renewable generation levels grow over the century in all scenarios. As expected, renewable generation increases with lower renewable technology costs, more stringent climate policy, and if alternative low-carbon technology are not available. The availability of long distance transmission lowers policy costs and changes the renewable generation mix.

  13. Evaluating the Current and Future Water Supply and Demands in the Apurimac River Basin, in Peru. Sensitivity Analysis of a Hydrologic and Water Planning Model

    NASA Astrophysics Data System (ADS)

    Yi, S.; Sandoval Solis, S.; Bombardelli, F. A.

    2014-12-01

    This research presents an analysis to estimate water availability and water supply for current and future water management policies in the Apurimac River Basin (ARB), in Peru. The objective of this research is to build a coupled hydrologic and water planning model to simulate the water availability and water supply in the ARB. This model is used to evaluate the average (synthetic) and historic conditions to test current and future water demands that include the construction of a reservoir. The hydrologic model is a two bucket model, where the processes of direct runoff, interflow and baseflow are represented in the top bucket and the process of groundwater storage is represented in the bottom bucket. The water planning model is a routing model that calculates the water balance between water supply, water demand and change in storage throughout the basin. The Water Evaluation and Planning (WEAP) platform is used in this research. Model inputs are climate data (precipitation, air temperature, relative humidity and wind velocity) and land use data (land use cover and crop coefficients). Streamflow at different control points and water budgets for all the sub-basin have been calculated to calibrate the model. A sensitivity analysis for the input data was performed to identify parameters that affect the most the water budget for each sub-basin. Precipitation is the most sensitive input data and root zone conductivity is the most sensitive parameter in the model. This research explains the implications of these conditions, and their impact in the analysis of the water availability and water supply for current and future water demands in the ARB.

  14. The Anisa Model: A Comprehensive Plan for Educational Renewal. [And] A Summary Statement of the Anisa Model.

    ERIC Educational Resources Information Center

    Massachusetts Univ., Amherst. School of Education.

    The Anisa Model is presented as a way to educational reform and development. It is a scientifically based educational system that fosters a child's natural love of learning and helps him to become a confident and productive human being. Providing a comprehensive and interdisciplinary educational experience that will enable a child to develop to…

  15. Assessing Impact of Large-Scale Distributed Residential HVAC Control Optimization on Electricity Grid Operation and Renewable Energy Integration

    NASA Astrophysics Data System (ADS)

    Corbin, Charles D.

    Demand management is an important component of the emerging Smart Grid, and a potential solution to the supply-demand imbalance occurring increasingly as intermittent renewable electricity is added to the generation mix. Model predictive control (MPC) has shown great promise for controlling HVAC demand in commercial buildings, making it an ideal solution to this problem. MPC is believed to hold similar promise for residential applications, yet very few examples exist in the literature despite a growing interest in residential demand management. This work explores the potential for residential buildings to shape electric demand at the distribution feeder level in order to reduce peak demand, reduce system ramping, and increase load factor using detailed sub-hourly simulations of thousands of buildings coupled to distribution power flow software. More generally, this work develops a methodology for the directed optimization of residential HVAC operation using a distributed but directed MPC scheme that can be applied to today's programmable thermostat technologies to address the increasing variability in electric supply and demand. Case studies incorporating varying levels of renewable energy generation demonstrate the approach and highlight important considerations for large-scale residential model predictive control.

  16. Preparation of Power Distribution System for High Penetration of Renewable Energy Part I. Dynamic Voltage Restorer for Voltage Regulation Pat II. Distribution Circuit Modeling and Validation

    NASA Astrophysics Data System (ADS)

    Khoshkbar Sadigh, Arash

    by simulation and experimental tests under various conditions considering all possible cases such as different amounts of voltage sag depth (VSD), different amounts of point-on-wave (POW) at which voltage sag occurs, harmonic distortion, line frequency variation, and phase jump (PJ). Furthermore, the ripple amount of fundamental voltage amplitude calculated by the proposed method and its error is analyzed considering the line frequency variation together with harmonic distortion. The best and worst detection time of proposed method were measured 1ms and 8.8ms, respectively. Finally, the proposed method has been compared with other voltage sag detection methods available in literature. Part 2: Power System Modeling for Renewable Energy Integration: As power distribution systems are evolving into more complex networks, electrical engineers have to rely on software tools to perform circuit analysis. There are dozens of powerful software tools available in the market to perform the power system studies. Although their main functions are similar, there are differences in features and formatting structures to suit specific applications. This creates challenges for transferring power system circuit models data (PSCMD) between different software and rebuilding the same circuit in the second software environment. The objective of this part of thesis is to develop a Unified Platform (UP) to facilitate transferring PSCMD among different software packages and relieve the challenges of the circuit model conversion process. UP uses a commonly available spreadsheet file with a defined format, for any home software to write data to and for any destination software to read data from, via a script-based application called PSCMD transfer application. The main considerations in developing the UP are to minimize manual intervention and import a one-line diagram into the destination software or export it from the source software, with all details to allow load flow, short circuit and

  17. 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/.

  18. The construction of a decision tool to analyse local demand and local supply for GP care using a synthetic estimation model

    PubMed Central

    2013-01-01

    Background This study addresses the growing academic and policy interest in the appropriate provision of local healthcare services to the healthcare needs of local populations to increase health status and decrease healthcare costs. However, for most local areas information on the demand for primary care and supply is missing. The research goal is to examine the construction of a decision tool which enables healthcare planners to analyse local supply and demand in order to arrive at a better match. Methods National sample-based medical record data of general practitioners (GPs) were used to predict the local demand for GP care based on local populations using a synthetic estimation technique. Next, the surplus or deficit in local GP supply were calculated using the national GP registry. Subsequently, a dynamic internet tool was built to present demand, supply and the confrontation between supply and demand regarding GP care for local areas and their surroundings in the Netherlands. Results Regression analysis showed a significant relationship between sociodemographic predictors of postcode areas and GP consultation time (F [14, 269,467] = 2,852.24; P <0.001). The statistical model could estimate GP consultation time for every postcode area with >1,000 inhabitants in the Netherlands covering 97% of the total population. Confronting these estimated demand figures with the actual GP supply resulted in the average GP workload and the number of full-time equivalent (FTE) GP too much/too few for local areas to cover the demand for GP care. An estimated shortage of one FTE GP or more was prevalent in about 19% of the postcode areas with >1,000 inhabitants if the surrounding postcode areas were taken into consideration. Underserved areas were mainly found in rural regions. Conclusions The constructed decision tool is freely accessible on the Internet and can be used as a starting point in the discussion on primary care service provision in local communities and it can

  19. Waste-to-wheel analysis of anaerobic-digestion-based renewable natural gas pathways with the GREET model.

    SciTech Connect

    Han, J.; Mintz, M.; Wang, M.

    2011-12-14

    In 2009, manure management accounted for 2,356 Gg or 107 billion standard cubic ft of methane (CH{sub 4}) emissions in the United States, equivalent to 0.5% of U.S. natural gas (NG) consumption. Owing to the high global warming potential of methane, capturing and utilizing this methane source could reduce greenhouse gas (GHG) emissions. The extent of that reduction depends on several factors - most notably, how much of this manure-based methane can be captured, how much GHG is produced in the course of converting it to vehicular fuel, and how much GHG was produced by the fossil fuel it might displace. A life-cycle analysis was conducted to quantify these factors and, in so doing, assess the impact of converting methane from animal manure into renewable NG (RNG) and utilizing the gas in vehicles. Several manure-based RNG pathways were characterized in the GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation) model, and their fuel-cycle energy use and GHG emissions were compared to petroleum-based pathways as well as to conventional fossil NG pathways. Results show that despite increased total energy use, both fossil fuel use and GHG emissions decline for most RNG pathways as compared with fossil NG and petroleum. However, GHG emissions for RNG pathways are highly dependent on the specifics of the reference case, as well as on the process energy emissions and methane conversion factors assumed for the RNG pathways. The most critical factors are the share of flared controllable CH{sub 4} and the quantity of CH{sub 4} lost during NG extraction in the reference case, the magnitude of N{sub 2}O lost in the anaerobic digestion (AD) process and in AD residue, and the amount of carbon sequestered in AD residue. In many cases, data for these parameters are limited and uncertain. Therefore, more research is needed to gain a better understanding of the range and magnitude of environmental benefits from converting animal manure to RNG via AD.

  20. Demand Response for Ancillary Services

    SciTech Connect

    Alkadi, Nasr E; Starke, Michael R

    2013-01-01

    Many demand response resources are technically capable of providing ancillary services. In some cases, they can provide superior response to generators, as the curtailment of load is typically much faster than ramping thermal and hydropower plants. Analysis and quantification of demand response resources providing ancillary services is necessary to understand the resources economic value and impact on the power system. Methodologies used to study grid integration of variable generation can be adapted to the study of demand response. In the present work, we describe and illustrate a methodology to construct detailed temporal and spatial representations of the demand response resource and to examine how to incorporate those resources into power system models. In addition, the paper outlines ways to evaluate barriers to implementation. We demonstrate how the combination of these three analyses can be used to translate the technical potential for demand response providing ancillary services into a realizable potential.

  1. [An empirical investigation of the demand-control-social support model: effects on burnout and on somatic complaints among nursing staff].

    PubMed

    Pisanti, R

    2007-01-01

    The present study investigated the relationship between job characteristics and well-being dimensions (burnout and somatic complaints) in a group of 271 nurses. The study, based on Karasek and Theorell's theoretic model of demand-control-social support, aimed to test the following hypotheses: (a) that there is a linear association between each job dimension (demand, control, social support) and indexes of stress (emotional exhaustion, depersonalization, personal accomplishment and somatization); (b) whether there is an additive or interactive ("buffer") action among the model variables in predicting stress. Concerning the hypothesis of linearity, regression analysis revealed two non-linear associations: between job control and emotional exhaustion, and between social support and the level of somatic symptoms. Concerning the second hypothesis, controlling for age and gender, results of hierarchical regression indicated that job control and social support combine in different additive patterns with job demands to explain outcomes of well-being. Findings confirmed the significant role of socio-demographic variables (age and gender) in predicting occupational strain. PMID:17650740

  2. Regional Differences in Demand for Coal as A Basis for Development of A Product Distribution Model for Mining Companies in the Individual Customers Segment

    NASA Astrophysics Data System (ADS)

    Magda, Roman; Bogacz, Paweł; Franik, Tadeusz; Celej, Maciej; Migza, Marcin

    2014-10-01

    The article presents a proposal of methodology based on the process of relationship marketing, serving to determine the level of demand for coal in the individual customer segment, as well as fuel distribution model for this customer group in Poland developed on the basis of this methodology. It also includes selected results of tests carried out using the proposed methods. These proposals have been defined on the basis of market capacity indicators, which can be determined for the district level based on data from the Polish Central Statistical Office. The study also included the use of linear programming, based on the cost of coal logistics, data concerning railway, road and storage infrastructure present on the Polish market and taking into account the legal aspects. The presented results may provide a basis for mining companies to develop a system of coal distribution management in the locations with the highest demand values.

  3. Renewable Resources: a national catalog of model projects. Volume 2. Mid-American Solar Energy Complex Region

    SciTech Connect

    1980-07-01

    This compilation of diverse conservation and renewable energy projects across the United States was prepared through the enthusiastic participation of solar and alternate energy groups from every state and region. Compiled and edited by the Center for Renewable Resources, these projects reflect many levels of innovation and technical expertise. In many cases, a critique analysis is presented of how projects performed and of the institutional conditions associated with their success or failure. Some 2000 projects are included in this compilation; most have worked, some have not. Information about all is presented to aid learning from these experiences. The four volumes in this set are arranged in state sections by geographic region, coinciding with the four Regional Solar Energy Centers. The table of contents is organized by project category so that maximum cross-referencing may be obtained. This volume includes information on the Mid-American Solar Energy Complex Region. (WHK)

  4. 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.

  5. An integrated production-inventory model for the singlevendor two-buyer problem with partial backorder, stochastic demand, and service level constraints

    NASA Astrophysics Data System (ADS)

    Arfawi Kurdhi, Nughthoh; Adi Diwiryo, Toray; Sutanto

    2016-02-01

    This paper presents an integrated single-vendor two-buyer production-inventory model with stochastic demand and service level constraints. Shortage is permitted in the model, and partial backordered partial lost sale. The lead time demand is assumed follows a normal distribution and the lead time can be reduced by adding crashing cost. The lead time and ordering cost reductions are interdependent with logaritmic function relationship. A service level constraint policy corresponding to each buyer is considered in the model in order to limit the level of inventory shortages. The purpose of this research is to minimize joint total cost inventory model by finding the optimal order quantity, safety stock, lead time, and the number of lots delivered in one production run. The optimal production-inventory policy gained by the Lagrange method is shaped to account for the service level restrictions. Finally, a numerical example and effects of the key parameters are performed to illustrate the results of the proposed model.

  6. Costs of integrating demand-based reproductive health commodity model into the Government and NGO service delivery systems in Bangladesh: a supply side perspective.

    PubMed

    Islam, Ziaul; Sarker, Abdur Razzaque; Anwar, Shahela; Kabir, Humayun; Gazi, Rukhsana

    2015-01-01

    To estimate additional total cost and average cost of integrating the demand-based reproductive health commodity model into the existing Government and NGO facilities in Bangladesh. Activity based cost analysis was conducted during 2006-2008 in two low performing rural sub-districts (Nabigong and Raipur sub-district) and one urban slum area in Dhaka city, Bangladesh. Activity-based cost data were collected using ingredient approach, which comprised of listing all types of inputs by activity, quantities and prices for each input. Total cost was presented according to capital and recurrent items. The supply side perspective was considered for entire analysis. The total cost of integrating demand-based reproductive health commodity (DBRHC) model into the Government and NGO service delivery system was estimated to BDT 18,667,634 (US$274,524). The proportion of capital cost was 59 % and the recurrent cost was 41 % of the total cost. The average cost per beneficiaries was BDT 230 (US$3.38) only for introducing this model into the existing health system. The built-in interventions of DBRHC model were doable at low-cost at the selected Government and NGO settings at the grass-root level. The model has potential of further cost containment during scaling up-if the intervention costs are adjusted with the existing functionaries of the Government and NGOs. PMID:26722628

  7. Commercial Demand Module - NEMS Documentation

    EIA Publications

    2014-01-01

    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.

  8. Effects of water renewal estimates on the oyster aquaculture potential of an inshore area

    NASA Astrophysics Data System (ADS)

    Guyondet, Thomas; Koutitonsky, Vladimir G.; Roy, Suzanne

    2005-10-01

    Tidal and wind renewal of water in the coastal zone is important in the transport of natural and anthropogenic particles and solutes. Models of these systems require detailed parameterization of exchange processes. Renewal of seston food supplies for cultured suspension-feeding shellfish is one such application. This study examines the sensitivity of food limitation estimates of an inshore region for shellfish aquaculture to the methods used in calculating the region's water renewal time. The region is the Indian Island oyster culture site in the Richibucto estuary, New Brunswick, Canada, and the methods considered are the volume advection and the local conservative tracer methods. In both cases, water renewal is calculated from field time series measurements of hydrodynamic parameters and outputs of coupled hydrodynamic and advection-dispersion three-dimensional (3D) numerical models. A comparison of oyster food demand and supply is then made to estimate the food limitation risk in the region using field measurements of biological parameters and the renewal times previously estimated. It is found that water renewal by tides is efficient but it can be cancelled altogether by meteorological forcing. Contrary to the conservative tracer method, the tidal prism method proves to be inadequate when estimating water renewal in estuarine tidal channels and was replaced by another volume advection method. The preliminary results obtained using the depletion index estimates indicate that the Indian Island region could sustain a high oyster biomass. These simple calculations also show the importance of water renewal estimate for carrying capacity studies. Hence, the tidal prism method or other volume advection estimates should be used with great caution or be avoided altogether in such studies.

  9. 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…

  10. Application of stakeholder-based and modelling approaches for supporting robust adaptation decision making under future climatic uncertainty and changing urban-agricultural water demand

    NASA Astrophysics Data System (ADS)

    Bhave, Ajay; Dessai, Suraje; Conway, Declan; Stainforth, David

    2016-04-01

    Deep uncertainty in future climate change and socio-economic conditions necessitates the use of assess-risk-of-policy approaches over predict-then-act approaches for adaptation decision making. Robust Decision Making (RDM) approaches embody this principle and help evaluate the ability of adaptation options to satisfy stakeholder preferences under wide-ranging future conditions. This study involves the simultaneous application of two RDM approaches; qualitative and quantitative, in the Cauvery River Basin in Karnataka (population ~23 million), India. The study aims to (a) determine robust water resources adaptation options for the 2030s and 2050s and (b) compare the usefulness of a qualitative stakeholder-driven approach with a quantitative modelling approach. For developing a large set of future scenarios a combination of climate narratives and socio-economic narratives was used. Using structured expert elicitation with a group of climate experts in the Indian Summer Monsoon, climatic narratives were developed. Socio-economic narratives were developed to reflect potential future urban and agricultural water demand. In the qualitative RDM approach, a stakeholder workshop helped elicit key vulnerabilities, water resources adaptation options and performance criteria for evaluating options. During a second workshop, stakeholders discussed and evaluated adaptation options against the performance criteria for a large number of scenarios of climatic and socio-economic change in the basin. In the quantitative RDM approach, a Water Evaluation And Planning (WEAP) model was forced by precipitation and evapotranspiration data, coherent with the climatic narratives, together with water demand data based on socio-economic narratives. We find that compared to business-as-usual conditions options addressing urban water demand satisfy performance criteria across scenarios and provide co-benefits like energy savings and reduction in groundwater depletion, while options reducing

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. Simulation of dissolved oxygen and biochemical oxygen demand, Plantation Canal, Broward County, Florida with an evaluation of the QUAL-I model for use in south Florida

    USGS Publications Warehouse

    Russo, Thomas N.; McQuivey, Raul S.

    1975-01-01

    A mathematical model; QUAL-I, developed by the Texas Water Development Board, was evaluated as a management tool in predicting the spatial and temporal distribution of dissolved oxygen and biochemical oxygen demand in Plantation Canal. Predictions based on the QUAL-I model, which was verified only against midday summer-flow conditions, showed that improvement of quality of inflows from sewage treatment plants and use of at least 130 cubic feet per second of dilution water would improve water quality in the canal significantly. The model was not fully amenable to use on Plantation Canal because: (1) it did not consider photosynthetic production, nitrification, and benthic oxygen demand as sources and sinks of oxygen; (2) the model assumptions of complete mixing, transport, and steady state were not met; and (3) the data base was inadequate because it consisted of only one set of data for each case. However, it was felt that meaningful results could be obtained for some sets of conditions. (Woodard-USGS)

  17. Modeling the effect of climate change on U.S. state-level buildings energy demands in an integrated assessment framework

    SciTech Connect

    Zhou, Yuyu; Clarke, Leon E.; Eom, Jiyong; Kyle, G. Page; Patel, Pralit L.; Kim, Son H.; Dirks, James A.; Jensen, Erik A.; Liu, Ying; Rice, Jennie S.; Schmidt, Laurel C.; Seiple, Timothy E.

    2014-01-01

    As long-term socioeconomic transformation and energy service expansion show large spatial heterogeneity, advanced understanding of climate impact on building energy use at the sub-national level will offer useful insights into climate policy and regional energy system planning. In this study, we presented a detailed building energy model with a U.S. state-level representation, nested in the GCAM integrated assessment framework. We projected state-level building energy demand and its spatial pattern over the century, considering the impact of climate change based on the estimates of heating and cooling degree days derived from downscaled USGS CASCaDE temperature data. The result indicates that climate change has a large impact on heating and cooling building energy and fuel use at the state level, exhibiting large spatial heterogeneity across states (ranges from -10% to +10%). The sensitivity analysis reveals that the building energy demand is subject to multiple key factors, such as the magnitude of climate change, the choice of climate models, and the growth of population and GDP, and that their relative contributions vary greatly across the space. The scale impact in building energy use modeling highlights the importance of constructing a building energy model with the spatially-explicit representation of socioeconomics, energy system development, and climate change. These findings will help the climate-based policy decision and energy system, especially utility planning related to building sector at the U.S. state and regional level facing the potential climate change.

  18. User's instructions for the Guyton circulatory dynamics model using the Univac 1110 batch and demand processing (with graphic capabilities)

    NASA Technical Reports Server (NTRS)

    Archer, G. T.

    1974-01-01

    The model presents a systems analysis of a human circulatory regulation based almost entirely on experimental data and cumulative present knowledge of the many facets of the circulatory system. The model itself consists of eighteen different major systems that enter into circulatory control. These systems are grouped into sixteen distinct subprograms that are melded together to form the total model. The model develops circulatory and fluid regulation in a simultaneous manner. Thus, the effects of hormonal and autonomic control, electrolyte regulation, and excretory dynamics are all important and are all included in the model.

  19. Alaska's renewable energy potential.

    SciTech Connect

    Not Available

    2009-02-01

    This paper delivers a brief survey of renewable energy technologies applicable to Alaska's climate, latitude, geography, and geology. We first identify Alaska's natural renewable energy resources and which renewable energy technologies would be most productive. e survey the current state of renewable energy technologies and research efforts within the U.S. and, where appropriate, internationally. We also present information on the current state of Alaska's renewable energy assets, incentives, and commercial enterprises. Finally, we escribe places where research efforts at Sandia National Laboratories could assist the state of Alaska with its renewable energy technology investment efforts.

  20. Renewable energy annual 1996

    SciTech Connect

    1997-03-01

    This report presents summary data on renewable energy consumption, the status of each of the primary renewable technologies, a profile of each of the associated industries, an analysis of topical issues related to renewable energy, and information on renewable energy projects worldwide. It is the second in a series of annual reports on renewable energy. The renewable energy resources included in the report are biomass (wood and ethanol); municipal solid waste, including waste-to-energy and landfill gas; geothermal; wind; and solar energy, including solar thermal and photovoltaic. The report also includes various appendices and a glossary.

  1. International Oil Supplies and Demands

    SciTech Connect

    Not Available

    1991-09-01

    The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--90 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

  2. International Oil Supplies and Demands

    SciTech Connect

    Not Available

    1992-04-01

    The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--1990 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

  3. Renewable energy in Indian country

    SciTech Connect

    1995-12-31

    On June 25--27, 1995, at Mesa Verde National Park in southwestern Colorado, the Center for Resource Management (CRM), organized and sponsored a conference in conjunction with the Navajo Nation, EPA, and Bechtel Group, Inc., to deal with issues associated with developing renewable energy resources on Indian lands. Due to the remoteness of many reservation homes and the cost of traditional power line extensions, a large percentage of the Indian population is today without electricity or other energy services. In addition, while they continue to develop energy resources for export, seeing only minimal gain in their own economies, Indian people are also subject to the health and environmental consequences associated with proximity to traditional energy resource development. Renewable energy technologies, on the other hand, are often ideally suited to decentralized, low-density demand. These technologies--especially solar and wind power--have no adverse health impacts associated with generation, are relatively low cost, and can be used in applications as small as a single home, meeting power needs right at a site. Their minimal impact on the environment make them particularly compatible with American Indian philosophies and lifestyles. Unfortunately, the match between renewable energy and Indian tribes has been hampered by the lack of a comprehensive, coordinated effort to identify renewable energy resources located on Indian lands, to develop practical links between Indian people`s needs and energy producers, and to provide the necessary training for tribal leaders and members to plan, implement, and maintain renewable energy systems. Summaries of the presentations are presented.

  4. Preparation of Power Distribution System for High Penetration of Renewable Energy Part I. Dynamic Voltage Restorer for Voltage Regulation Pat II. Distribution Circuit Modeling and Validation

    NASA Astrophysics Data System (ADS)

    Khoshkbar Sadigh, Arash

    by simulation and experimental tests under various conditions considering all possible cases such as different amounts of voltage sag depth (VSD), different amounts of point-on-wave (POW) at which voltage sag occurs, harmonic distortion, line frequency variation, and phase jump (PJ). Furthermore, the ripple amount of fundamental voltage amplitude calculated by the proposed method and its error is analyzed considering the line frequency variation together with harmonic distortion. The best and worst detection time of proposed method were measured 1ms and 8.8ms, respectively. Finally, the proposed method has been compared with other voltage sag detection methods available in literature. Part 2: Power System Modeling for Renewable Energy Integration: As power distribution systems are evolving into more complex networks, electrical engineers have to rely on software tools to perform circuit analysis. There are dozens of powerful software tools available in the market to perform the power system studies. Although their main functions are similar, there are differences in features and formatting structures to suit specific applications. This creates challenges for transferring power system circuit models data (PSCMD) between different software and rebuilding the same circuit in the second software environment. The objective of this part of thesis is to develop a Unified Platform (UP) to facilitate transferring PSCMD among different software packages and relieve the challenges of the circuit model conversion process. UP uses a commonly available spreadsheet file with a defined format, for any home software to write data to and for any destination software to read data from, via a script-based application called PSCMD transfer application. The main considerations in developing the UP are to minimize manual intervention and import a one-line diagram into the destination software or export it from the source software, with all details to allow load flow, short circuit and

  5. Accurate market price formation model with both supply-demand and trend-following for global food prices providing policy recommendations.

    PubMed

    Lagi, Marco; Bar-Yam, Yavni; Bertrand, Karla Z; Bar-Yam, Yaneer

    2015-11-10

    Recent increases in basic food prices are severely affecting vulnerable populations worldwide. Proposed causes such as shortages of grain due to adverse weather, increasing meat consumption in China and India, conversion of corn to ethanol in the United States, and investor speculation on commodity markets lead to widely differing implications for policy. A lack of clarity about which factors are responsible reinforces policy inaction. Here, for the first time to our knowledge, we construct a dynamic model that quantitatively agrees with food prices. The results show that the dominant causes of price increases are investor speculation and ethanol conversion. Models that just treat supply and demand are not consistent with the actual price dynamics. The two sharp peaks in 2007/2008 and 2010/2011 are specifically due to investor speculation, whereas an underlying upward trend is due to increasing demand from ethanol conversion. The model includes investor trend following as well as shifting between commodities, equities, and bonds to take advantage of increased expected returns. Claims that speculators cannot influence grain prices are shown to be invalid by direct analysis of price-setting practices of granaries. Both causes of price increase, speculative investment and ethanol conversion, are promoted by recent regulatory changes-deregulation of the commodity markets, and policies promoting the conversion of corn to ethanol. Rapid action is needed to reduce the impacts of the price increases on global hunger. PMID:26504216

  6. Accurate market price formation model with both supply-demand and trend-following for global food prices providing policy recommendations

    PubMed Central

    Lagi, Marco; Bar-Yam, Yavni; Bertrand, Karla Z.; Bar-Yam, Yaneer

    2015-01-01

    Recent increases in basic food prices are severely affecting vulnerable populations worldwide. Proposed causes such as shortages of grain due to adverse weather, increasing meat consumption in China and India, conversion of corn to ethanol in the United States, and investor speculation on commodity markets lead to widely differing implications for policy. A lack of clarity about which factors are responsible reinforces policy inaction. Here, for the first time to our knowledge, we construct a dynamic model that quantitatively agrees with food prices. The results show that the dominant causes of price increases are investor speculation and ethanol conversion. Models that just treat supply and demand are not consistent with the actual price dynamics. The two sharp peaks in 2007/2008 and 2010/2011 are specifically due to investor speculation, whereas an underlying upward trend is due to increasing demand from ethanol conversion. The model includes investor trend following as well as shifting between commodities, equities, and bonds to take advantage of increased expected returns. Claims that speculators cannot influence grain prices are shown to be invalid by direct analysis of price-setting practices of granaries. Both causes of price increase, speculative investment and ethanol conversion, are promoted by recent regulatory changes—deregulation of the commodity markets, and policies promoting the conversion of corn to ethanol. Rapid action is needed to reduce the impacts of the price increases on global hunger. PMID:26504216

  7. Emotional Exhaustion and Job Satisfaction in Airport Security Officers - Work-Family Conflict as Mediator in the Job Demands-Resources Model.

    PubMed

    Baeriswyl, Sophie; Krause, Andreas; Schwaninger, Adrian

    2016-01-01

    The growing threat of terrorism has increased the importance of aviation security and the work of airport security officers (screeners). Nonetheless, airport security research has yet to focus on emotional exhaustion and job satisfaction as major determinants of screeners' job performance. The present study bridges this research gap by applying the job demands-resources (JD-R) model and using work-family conflict (WFC) as an intervening variable to study relationships between work characteristics (workload and supervisor support), emotional exhaustion, and job satisfaction in 1,127 screeners at a European airport. Results of structural equation modeling revealed that (a) supervisor support as a major job resource predicted job satisfaction among screeners; (b) workload as a major job demand predicted their emotional exhaustion; and (c) WFC proved to be a promising extension to the JD-R model that partially mediated the impact of supervisor support and workload on job satisfaction and emotional exhaustion. Theoretical and practical implications are discussed. PMID:27242581

  8. Technical note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models

    NASA Astrophysics Data System (ADS)

    Herman, J. D.; Kollat, J. B.; Reed, P. M.; Wagener, T.

    2013-04-01

    The increase in spatially distributed hydrologic modeling warrants a corresponding increase in diagnostic methods capable of analyzing complex models with large numbers of parameters. Sobol' sensitivity analysis has proven to be a valuable tool for diagnostic analyses of hydrologic models. However, for many spatially distributed models, the Sobol' method requires a prohibitive number of model evaluations to reliably decompose output variance across the full set of parameters. We investigate the potential of the method of Morris, a screening-based sensitivity approach, to provide results sufficiently similar to those of the Sobol' method at a greatly reduced computational expense. The methods are benchmarked on the Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) model over a six-month period in the Blue River Watershed, Oklahoma, USA. The Sobol' method required over six million model evaluations to ensure reliable sensitivity indices, corresponding to more than 30 000 computing hours and roughly 180 gigabytes of storage space. We find that the method of Morris is able to correctly identify sensitive and insensitive parameters with 300 times fewer model evaluations, requiring only 100 computing hours and 1 gigabyte of storage space. Method of Morris proves to be a promising diagnostic approach for global sensitivity analysis of highly parameterized, spatially distributed hydrologic models.

  9. Modelling climate change impacts on tourism demand: A comparative study from Sardinia (Italy) and Cap Bon (Tunisia).

    PubMed

    Köberl, Judith; Prettenthaler, Franz; Bird, David Neil

    2016-02-01

    Tourism represents an important source of income and employment in many Mediterranean regions, including the island of Sardinia (Italy) and the Cap Bon peninsula (Tunisia). Climate change may however impact tourism in both regions, for example, by altering the regions' climatic suitability for common tourism types or affecting water availability. This paper assesses the potential impacts of climate change on tourism in the case study regions of Sardinia and Cap Bon. Direct impacts are studied in a quantitative way by applying a range of climate scenario data on the empirically estimated relationship between climatic conditions and tourism demand, using two different approaches. Results indicate a potential for climate-induced tourism revenue gains especially in the shoulder seasons during spring and autumn, but also a threat of climate-induced revenue losses in the summer months due to increased heat stress. Annual direct net impacts are nevertheless suggested to be (slightly) positive in both case study regions. Significant climate-induced reductions in total available water may however somewhat counteract the positive direct impacts of climate change by putting additional water costs on the tourism industry. PMID:25891683

  10. Finite horizon EOQ model for non-instantaneous deteriorating items with price and advertisement dependent demand and partial backlogging under inflation

    NASA Astrophysics Data System (ADS)

    Palanivel, M.; Uthayakumar, R.

    2015-07-01

    This paper deals with an economic order quantity (EOQ) model for non-instantaneous deteriorating items with price and advertisement dependent demand pattern under the effect of inflation and time value of money over a finite planning horizon. In this model, shortages are allowed and partially backlogged. The backlogging rate is dependent on the waiting time for the next replenishment. This paper aids the retailer in minimising the total inventory cost by finding the optimal interval and the optimal order quantity. An algorithm is designed to find the optimum solution of the proposed model. Numerical examples are given to demonstrate the results. Also, the effect of changes in the different parameters on the optimal total cost is graphically presented and the implications are discussed in detail.

  11. Technical Note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models

    NASA Astrophysics Data System (ADS)

    Herman, J. D.; Kollat, J. B.; Reed, P. M.; Wagener, T.

    2013-07-01

    The increase in spatially distributed hydrologic modeling warrants a corresponding increase in diagnostic methods capable of analyzing complex models with large numbers of parameters. Sobol' sensitivity analysis has proven to be a valuable tool for diagnostic analyses of hydrologic models. However, for many spatially distributed models, the Sobol' method requires a prohibitive number of model evaluations to reliably decompose output variance across the full set of parameters. We investigate the potential of the method of Morris, a screening-based sensitivity approach, to provide results sufficiently similar to those of the Sobol' method at a greatly reduced computational expense. The methods are benchmarked on the Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) over a six-month period in the Blue River watershed, Oklahoma, USA. The Sobol' method required over six million model evaluations to ensure reliable sensitivity indices, corresponding to more than 30 000 computing hours and roughly 180 gigabytes of storage space. We find that the method of Morris is able to correctly screen the most and least sensitive parameters with 300 times fewer model evaluations, requiring only 100 computing hours and 1 gigabyte of storage space. The method of Morris proves to be a promising diagnostic approach for global sensitivity analysis of highly parameterized, spatially distributed hydrologic models.

  12. The Kinked Demand Curve When Demand Shifts.

    ERIC Educational Resources Information Center

    Frasco, Gregg P.

    1993-01-01

    Reviews recent research into the theory of the kinked demand curve in economics. Applies this theory to economic concepts such as marginal cost and price flexibility. Discusses the implications for corporations and government policymakers. (CFR)

  13. Worksite interventions for preventing physical deterioration among employees in job-groups with high physical work demands: Background, design and conceptual model of FINALE

    PubMed Central

    2010-01-01

    Background A mismatch between individual physical capacities and physical work demands enhance the risk for musculoskeletal disorders, poor work ability and sickness absence, termed physical deterioration. However, effective intervention strategies for preventing physical deterioration in job groups with high physical demands remains to be established. This paper describes the background, design and conceptual model of the FINALE programme, a framework for health promoting interventions at 4 Danish job groups (i.e. cleaners, health-care workers, construction workers and industrial workers) characterized by high physical work demands, musculoskeletal disorders, poor work ability and sickness absence. Methods/Design A novel approach of the FINALE programme is that the interventions, i.e. 3 randomized controlled trials (RCT) and 1 exploratory case-control study are tailored to the physical work demands, physical capacities and health profile of workers in each job-group. The RCT among cleaners, characterized by repetitive work tasks and musculoskeletal disorders, aims at making the cleaners less susceptible to musculoskeletal disorders by physical coordination training or cognitive behavioral theory based training (CBTr). Because health-care workers are reported to have high prevalence of overweight and heavy lifts, the aim of the RCT is long-term weight-loss by combined physical exercise training, CBTr and diet. Construction work, characterized by heavy lifting, pushing and pulling, the RCT aims at improving physical capacity and promoting musculoskeletal and cardiovascular health. At the industrial work-place characterized by repetitive work tasks, the intervention aims at reducing physical exertion and musculoskeletal disorders by combined physical exercise training, CBTr and participatory ergonomics. The overall aim of the FINALE programme is to improve the safety margin between individual resources (i.e. physical capacities, and cognitive and behavioral skills

  14. 77 FR 58206 - Agency Information Collection Activities: Requests for Comments; Clearance of Renewed Approval of...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-19

    ... of Renewed Approval of Information Collection: Operating Requirements: Commuter and On Demand... intention to request the Office of Management and Budget (OMB) approval to renew an information collection... INFORMATION: OMB Control Number: 2120-0039. Title: Operating Requirements: Commuter and On Demand...

  15. Production model in the conditions of unstable demand taking into account the influence of trading infrastructure: Ergodicity and its application

    NASA Astrophysics Data System (ADS)

    Obrosova, N. K.; Shananin, A. A.

    2015-04-01

    A production model with allowance for a working capital deficit and a restricted maximum possible sales volume is proposed and analyzed. The study is motivated by an attempt to analyze the problems of functioning of low competitive macroeconomic structures. The model is formalized in the form of a Bellman equation, for which a closed-form solution is found. The stochastic process of product stock variations is proved to be ergodic and its final probability distribution is found. Expressions for the average production load and the average product stock are found by analyzing the stochastic process. A system of model equations relating the model variables to official statistical parameters is derived. The model is identified using data from the Fiat and KAMAZ companies. The influence of the credit interest rate on the firm market value assessment and the production load level are analyzed using comparative statics methods.

  16. Renewable Electricity Futures (Presentation)

    SciTech Connect

    Mai, T.

    2012-10-01

    This presentation library summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050.

  17. Renewable energy technology characterizations

    SciTech Connect

    None, None

    1997-12-01

    The Renewable Energy Technology Characterizations front matter lists the chapters and tables that support this report on the technical and economic status of the major emerging renewable energy options for electricity supply.

  18. Renewable Electricity Futures (Presentation)

    SciTech Connect

    Mai, T.

    2013-04-01

    This presentation summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050.

  19. Renewable Electricity Futures (Presentation)

    SciTech Connect

    Hand, M. M.

    2012-09-01

    This presentation summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050.

  20. Renewable Electricity Futures (Presentation)

    SciTech Connect

    Mai, T.

    2012-11-01

    This presentation summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050.

  1. Modeling the demand reduction input-output (I-O) inoperability due to terrorism of interconnected infrastructures.

    PubMed

    Santos, Joost R; Haimes, Yacov Y

    2004-12-01

    Interdependency analysis in the context of this article is a process of assessing and managing risks inherent in a system of interconnected entities (e.g., infrastructures or industry sectors). Invoking the principles of input-output (I-O) and decomposition analysis, the article offers a framework for describing how terrorism-induced perturbations can propagate due to interconnectedness. Data published by the Bureau of Economic Analysis Division of the U.S. Department of Commerce is utilized to present applications to serve as test beds for the proposed framework. Specifically, a case study estimating the economic impact of airline demand perturbations to national-level U.S. sectors is made possible using I-O matrices. A ranking of the affected sectors according to their vulnerability to perturbations originating from a primary sector (e.g., air transportation) can serve as important input to risk management. For example, limited resources can be prioritized for the "top-n" sectors that are perceived to suffer the greatest economic losses due to terrorism. In addition, regional decomposition via location quotients enables the analysis of local-level terrorism events. The Regional I-O Multiplier System II (RIMS II) Division of the U.S. Department of Commerce is the agency responsible for releasing the regional multipliers for various geographical resolutions (economic areas, states, and counties). A regional-level case study demonstrates a process of estimating the economic impact of transportation-related scenarios on industry sectors within Economic Area 010 (the New York metropolitan region and vicinities). PMID:15660602

  2. 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.

  3. Bioenergetic model estimates of interannual and spatial patterns in consumption demand and growth potential of juvenile pink salmon ( Oncorhynchus gorbuscha) in the Gulf of Alaska

    NASA Astrophysics Data System (ADS)

    Moss, Jamal H.; Beauchamp, David A.; Cross, Alison D.; Farley, Edward V.; Murphy, James M.; Helle, John H.; Walker, Robert V.; Myers, Katherine W.

    2009-12-01

    A bioenergetic model of juvenile pink salmon ( Oncorhynchus gorbuscha) was used to estimate daily prey consumption and growth potential of four ocean habitats in the Gulf of Alaska during 2001 and 2002. Growth potential was not significantly higher in 2002 than in 2001 at an alpha level of 0.05 ( P=0.073). Average differences in growth potential across habitats were minimal (slope habitat=0.844 g d -1, shelf habitat=0.806 g d -1, offshore habitat=0.820 g d -1, and nearshore habitat=0.703 g d -1) and not significantly different ( P=0.630). Consumption demand differed significantly between hatchery and wild stocks ( P=0.035) when examined within year due to the interaction between hatchery verses wild origin and year. However, the overall effect of origin across years was not significant ( P=0.705) due to similar total amounts of prey consumed by all juvenile pink salmon in both study years. We anticipated that years in which ocean survival was high would have had high growth potential, but this relationship did not prove to be true. Therefore, modeled growth potential may not be useful as a tool for forecasting survival of Prince William Sound hatchery pink salmon stocks. Significant differences in consumption demand and a two-fold difference in nearshore abundance during 2001 of hatchery and wild pink salmon confirmed the existence of strong and variable interannual competition and the importance of the nearshore region as being a potential competitive bottleneck.

  4. Bioenergetic model estimates of interannual and spatial patterns in consumption demand and growth potential of juvenile pink salmon (Oncorhynchus gorbuscha) in the Gulf of Alaska

    USGS Publications Warehouse

    Moss, J.H.; Beauchamp, D.A.; Cross, A.D.; Farley, E.V.; Murphy, J.M.; Helle, J.H.; Walker, R.V.; Myers, K.W.

    2009-01-01

    A bioenergetic model of juvenile pink salmon (Oncorhynchus gorbuscha) was used to estimate daily prey consumption and growth potential of four ocean habitats in the Gulf of Alaska during 2001 and 2002. Growth potential was not significantly higher in 2002 than in 2001 at an alpha level of 0.05 (P=0.073). Average differences in growth potential across habitats were minimal (slope habitat=0.844 g d-1, shelf habitat=0.806 g d-1, offshore habitat=0.820 g d-1, and nearshore habitat=0.703 g d-1) and not significantly different (P=0.630). Consumption demand differed significantly between hatchery and wild stocks (P=0.035) when examined within year due to the interaction between hatchery verses wild origin and year. However, the overall effect of origin across years was not significant (P=0.705) due to similar total amounts of prey consumed by all juvenile pink salmon in both study years. We anticipated that years in which ocean survival was high would have had high growth potential, but this relationship did not prove to be true. Therefore, modeled growth potential may not be useful as a tool for forecasting survival of Prince William Sound hatchery pink salmon stocks. Significant differences in consumption demand and a two-fold difference in nearshore abundance during 2001 of hatchery and wild pink salmon confirmed the existence of strong and variable interannual competition and the importance of the nearshore region as being a potential competitive bottleneck.

  5. Beef Species Symposium: an assessment of the 1996 Beef NRC: metabolizable protein supply and demand and effectiveness of model performance prediction of beef females within extensive grazing systems.

    PubMed

    Waterman, R C; Caton, J S; Löest, C A; Petersen, M K; Roberts, A J

    2014-07-01

    Interannual variation of forage quantity and quality driven by precipitation events influence beef livestock production systems within the Southern and Northern Plains and Pacific West, which combined represent 60% (approximately 17.5 million) of the total beef cows in the United States. The beef cattle requirements published by the NRC are an important tool and excellent resource for both professionals and producers to use when implementing feeding practices and nutritional programs within the various production systems. The objectives of this paper include evaluation of the 1996 Beef NRC model in terms of effectiveness in predicting extensive range beef cow performance within arid and semiarid environments using available data sets, identifying model inefficiencies that could be refined to improve the precision of predicting protein supply and demand for range beef cows, and last, providing recommendations for future areas of research. An important addition to the current Beef NRC model would be to allow users to provide region-specific forage characteristics and the ability to describe supplement composition, amount, and delivery frequency. Beef NRC models would then need to be modified to account for the N recycling that occurs throughout a supplementation interval and the impact that this would have on microbial efficiency and microbial protein supply. The Beef NRC should also consider the role of ruminal and postruminal supply and demand of specific limiting AA. Additional considerations should include the partitioning effects of nitrogenous compounds under different physiological production stages (e.g., lactation, pregnancy, and periods of BW loss). The intent of information provided is to aid revision of the Beef NRC by providing supporting material for changes and identifying gaps in existing scientific literature where future research is needed to enhance the predictive precision and application of the Beef NRC models. PMID:24398839

  6. Predictive Uncertainty And Parameter Sensitivity Of A Sediment-Flux Model: Nitrogen Flux and Sediment Oxygen Demand

    EPA Science Inventory

    Estimating model predictive uncertainty is imperative to informed environmental decision making and management of water resources. This paper applies the Generalized Sensitivity Analysis (GSA) to examine parameter sensitivity and the Generalized Likelihood Uncertainty Estimation...

  7. [Psychosocial stress and disease risks in occupational life. Results of international studies on the demand-control and the effort-reward imbalance models].

    PubMed

    Siegrist, J; Dragano, N

    2008-03-01

    Given the far-reaching changes of modern working life, psychosocial stress at work has received increased attention. Its influence on stress-related disease risks is analysed with the help of standardised measurements based on theoretical models. Two such models have gained special prominence in recent years, the demand-control model and the effort-reward imbalance model. The former model places its emphasis on a distinct combination of job characteristics, whereas the latter model's focus is on the imbalance between efforts spent and rewards received in turn. The predictive power of these models with respect to coronary or cardiovascular disease and depression was tested in a number of prospective epidemiological investigations. In summary, twofold elevated disease risks are observed. Effects on cardiovascular disease are particularly pronounced among men, whereas no gender differences are observed for depression. Additional evidence derived from experimental and ambulatory monitoring studies supplements this body of findings. Current scientific evidence justifies an increased awareness and assessment of these newly discovered occupational risks, in particular by occupational health professionals. Moreover, structural and interpersonal measures of stress prevention and health promotion at work are warranted, with special emphasis on gender differences. PMID:18369565

  8. Modeling students’ instrumental (mis-) use of substances to enhance cognitive performance: Neuroenhancement in the light of job demands-resources theory

    PubMed Central

    2014-01-01

    Background Healthy university students have been shown to use psychoactive substances, expecting them to be functional means for enhancing their cognitive capacity, sometimes over and above an essentially proficient level. This behavior called Neuroenhancement (NE) has not yet been integrated into a behavioral theory that is able to predict performance. Job Demands Resources (JD-R) Theory for example assumes that strain (e.g. burnout) will occur and influence performance when job demands are high and job resources are limited at the same time. The aim of this study is to investigate whether or not university students’ self-reported NE can be integrated into JD-R Theory’s comprehensive approach to psychological health and performance. Methods 1,007 students (23.56 ± 3.83 years old, 637 female) participated in an online survey. Lifestyle drug, prescription drug, and illicit substance NE together with the complete set of JD-R variables (demands, burnout, resources, motivation, and performance) were measured. Path models were used in order to test our data’s fit to hypothesized main effects and interactions. Results JD-R Theory could successfully be applied to describe the situation of university students. NE was mainly associated with the JD-R Theory’s health impairment process: Lifestyle drug NE (p < .05) as well as prescription drug NE (p < .001) is associated with higher burnout scores, and lifestyle drug NE aggravates the study demands-burnout interaction. In addition, prescription drug NE mitigates the protective influence of resources on burnout and on motivation. Conclusion According to our results, the uninformed trying of NE (i.e., without medical supervision) might result in strain. Increased strain is related to decreased performance. From a public health perspective, intervention strategies should address these costs of non-supervised NE. With regard to future research we propose to model NE as a means to reach an end (i

  9. 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

  10. International cooperation for renewable energy transfer

    SciTech Connect

    Wolfe, M.H.

    1992-06-01

    This paper reports that in considering the potential of major renewable energy resources in relation to their remoteness from demand centers, it is necessary to take a global view of the implications of their utilization. The present concerns regarding global warming and environmental degradation from fossil fuel combustion could be given active direction if the positive benefits of renewable energy could be realized on a meaningful scale. The dire prospect of global warming looms large in the scientific consciousness, but strategies to counter the effects of increased release of carbon dioxide and other greenhouse gases are just beginning to emerge along with remedial measures to address other environmental threats. One of the ways to achieve this is to place more reliance on renewable energy. As the impact of small-scale dispersed sources of renewable energy is minimal in comparison with fossil fuel usage, a meaningful impact could only be made by drawing upon major sources of renewable energy, mainly hydropower, tidal, and solar, in large capacity installations concentrated at sites relatively far from demand centers. There are sites that warrant serious consideration in the face of the growing environmental impact of fossil fuel usage. However, to realize this objective, an environmental imperative should be adopted that would place the importance of global environmental security on a par with present concerns for national security.

  11. 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.

  12. Optimal transfer, ordering and payment policies for joint supplier-buyer inventory model with price-sensitive trapezoidal demand and net credit

    NASA Astrophysics Data System (ADS)

    Shah, Nita H.; Shah, Digeshkumar B.; Patel, Dushyantkumar G.

    2015-07-01

    This study aims at formulating an integrated supplier-buyer inventory model when market demand is variable price-sensitive trapezoidal and the supplier offers a choice between discount in unit price and permissible delay period for settling the accounts due against the purchases made. This type of trade credit is termed as 'net credit'. In this policy, if the buyer pays within offered time M1, then the buyer is entitled for a cash discount; otherwise the full account must be settled by the time M2; where M2 > M1 ⩾ 0. The goal is to determine the optimal selling price, procurement quantity, number of transfers from the supplier to the buyer and payment time to maximise the joint profit per unit time. An algorithm is worked out to obtain the optimal solution. A numerical example is given to validate the proposed model. The managerial insights based on sensitivity analysis are deduced.

  13. Demand Response Analysis Tool

    Energy Science and Technology Software Center (ESTSC)

    2012-03-01

    Demand Response Analysis Tool is a software developed at the Lawrence Berkeley National Laboratory. It is initially funded by Southern California Edison. Our goal in developing this tool is to provide an online, useable, with standardized methods, an analysis tool to evaluate demand and demand response performance of commercial and industrial facilities. The tool provides load variability and weather sensitivity analysis capabilities as well as development of various types of baselines. It can be usedmore » by researchers, real estate management firms, utilities, or any individuals who are interested in analyzing their demand and demand response capabilities.« less

  14. Demand Response Analysis Tool

    SciTech Connect

    2012-03-01

    Demand Response Analysis Tool is a software developed at the Lawrence Berkeley National Laboratory. It is initially funded by Southern California Edison. Our goal in developing this tool is to provide an online, useable, with standardized methods, an analysis tool to evaluate demand and demand response performance of commercial and industrial facilities. The tool provides load variability and weather sensitivity analysis capabilities as well as development of various types of baselines. It can be used by researchers, real estate management firms, utilities, or any individuals who are interested in analyzing their demand and demand response capabilities.

  15. Reducing energy demand: what are the practical limits?

    PubMed

    Cullen, Jonathan M; Allwood, Julian M; Borgstein, Edward H

    2011-02-15

    Concern over the global energy system, whether driven by climate change, national security, or fears of shortage, is being discussed widely and in every arena but with a bias toward energy supply options. While demand reduction is often mentioned in passing, it is rarely a priority for implementation, whether through policy or through the search for innovation. This paper aims to draw attention to the opportunity for major reduction in energy demand, by presenting an analysis of how much of current global energy demand could be avoided. Previous work led to a "map" of global energy use that traces the flow of energy from primary sources (fuels or renewable sources), through fuel refinery, electricity generation, and end-use conversion devices, to passive systems and the delivery of final energy services (transport, illumination, and sustenance). The key passive systems are presented here and analyzed through simple engineering models with scalar equations using data based on current global practice. Physically credible options for change to key design parameters are identified and used to predict the energy savings possible for each system. The result demonstrates that 73% of global energy use could be saved by practically achievable design changes to passive systems. This reduction could be increased by further efficiency improvements in conversion devices. A list of the solutions required to achieve these savings is provided. PMID:21226525

  16. User's instructions for the Grodins' respiratory control model using the UNIVAC 1110 remote batch and demand processing

    NASA Technical Reports Server (NTRS)

    1974-01-01

    The transient and steady state response of the respiratory control system for variations in volumetric fractions of inspired gases and special system parameters are modeled. The program contains the capability to change workload. The program is based on Grodins' respiratory control model and can be envisioned as a feedback control system comprised of a plant (the controlled system) and the regulating component (controlling system). The controlled system is partitioned into 3 compartments corresponding to lungs, brain, and tissue with a fluid interconnecting patch representing the blood.

  17. Agent-Based Modelling of Agricultural Water Abstraction in Response to Climate, Policy, and Demand Changes: Results from East Anglia, UK

    NASA Astrophysics Data System (ADS)

    Swinscoe, T. H. A.; Knoeri, C.; Fleskens, L.; Barrett, J.

    2014-12-01

    Freshwater is a vital natural resource for multiple needs, such as drinking water for the public, industrial processes, hydropower for energy companies, and irrigation for agriculture. In the UK, crop production is the largest in East Anglia, while at the same time the region is also the driest, with average annual rainfall between 560 and 720 mm (1971 to 2000). Many water catchments of East Anglia are reported as over licensed or over abstracted. Therefore, freshwater available for agricultural irrigation abstraction in this region is becoming both increasingly scarce due to competing demands, and increasingly variable and uncertain due to climate and policy changes. It is vital for water users and policy makers to understand how these factors will affect individual abstractors and water resource management at the system level. We present first results of an Agent-based Model that captures the complexity of this system as individual abstractors interact, learn and adapt to these internal and external changes. The purpose of this model is to simulate what patterns of water resource management emerge on the system level based on local interactions, adaptations and behaviours, and what policies lead to a sustainable water resource management system. The model is based on an irrigation abstractor typology derived from a survey in the study area, to capture individual behavioural intentions under a range of water availability scenarios, in addition to farm attributes, and demographics. Regional climate change scenarios, current and new abstraction licence reforms by the UK regulator, such as water trading and water shares, and estimated demand increases from other sectors were used as additional input data. Findings from the integrated model provide new understanding of the patterns of water resource management likely to emerge at the system level.

  18. Integrating Variable Renewable Energy: Challenges and Solutions

    SciTech Connect

    Bird, L.; Milligan, M.; Lew, D.

    2013-09-01

    In the U.S., a number of utilities are adopting higher penetrations of renewables, driven in part by state policies. While power systems have been designed to handle the variable nature of loads, the additional supply-side variability and uncertainty can pose new challenges for utilities and system operators. However, a variety of operational and technical solutions exist to help integrate higher penetrations of wind and solar generation. This paper explores renewable energy integration challenges and mitigation strategies that have been implemented in the U.S. and internationally, including forecasting, demand response, flexible generation, larger balancing areas or balancing area cooperation, and operational practices such as fast scheduling and dispatch.

  19. Renewable energy annual 1995

    SciTech Connect

    1995-12-01

    The Renewable Energy Annual 1995 is the first in an expected series of annual reports the Energy Information Administration (EIA) intends to publish to provide a comprehensive assessment of renewable energy. This report presents the following information on the history, status, and prospects of renewable energy data: estimates of renewable resources; characterizations of renewable energy technologies; descriptions of industry infrastructures for individual technologies; evaluations of current market status; and assessments of near-term prospects for market growth. An international section is included, as well as two feature articles that discuss issues of importance for renewable energy as a whole. The report also contains a number of technical appendices and a glossary. The renewable energy sources included are biomass (wood), municipal solid waste, biomass-derived liquid fuels, geothermal, wind, and solar and photovoltaic.

  20. World Natural Gas Model

    Energy Science and Technology Software Center (ESTSC)

    1994-12-01

    RAMSGAS, the Research and Development Analysis Modeling System World Natural Gas Model, was developed to support planning of unconventional gaseoues fuels research and development. The model is a scenario analysis tool that can simulate the penetration of unconventional gas into world markets for oil and gas. Given a set of parameter values, the model estimates the natural gas supply and demand for the world for the period from 1980 to 2030. RAMSGAS is based onmore » a supply/demand framwork and also accounts for the non-renewable nature of gas resources. The model has three fundamental components: a demand module, a wellhead production cost module, and a supply/demand interface module. The demand for gas is a product of total demand for oil and gas in each of 9 demand regions and the gas share. Demand for oil and gas is forecast from the base year of 1980 through 2030 for each demand region, based on energy growth rates and price-induced conservation. For each of 11 conventional and 19 unconventional gas supply regions, wellhead production costs are calculated. To these are added transportation and distribution costs estimates associated with moving gas from the supply region to each of the demand regions and any economic rents. Based on a weighted average of these costs and the world price of oil, fuel shares for gas and oil are computed for each demand region. The gas demand is the gas fuel share multiplied by the total demand for oil plus gas. This demand is then met from the available supply regions in inverse proportion to the cost of gas from each region. The user has almost complete control over the cost estimates for each unconventional gas source in each year and thus can compare contributions from unconventional resources under different cost/price/demand scenarios.« less