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. Renewable Energy Resources Portfolio Optimization in the Presence of Demand Response

    SciTech Connect

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

    2016-01-15

    In this paper we introduce a simple cost model of renewable integration and demand response that can be used to determine the optimal mix of generation and demand response resources. The model includes production cost, demand elasticity, uncertainty costs, capacity expansion costs, retirement and mothballing costs, and wind variability impacts to determine the hourly cost and revenue of electricity delivery. The model is tested on the 2024 planning case for British Columbia and we find that cost is minimized with about 31% renewable generation. We also find that demand responsive does not have a significant impact on cost at the hourly level. The results suggest that the optimal level of renewable resource is not sensitive to a carbon tax or demand elasticity, but it is highly sensitive to the renewable resource installation cost.

  3. 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.

  4. Travel Demand Modeling

    SciTech Connect

    Southworth, Frank; Garrow, Dr. Laurie

    2011-01-01

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

  5. 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.

  6. 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.

  7. 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.

  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. 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).

  10. 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.

  11. Modeling the Demand for Cocaine

    DTIC Science & Technology

    1994-01-01

    the Demand for Cocaine Susan S. Everingham C. Peter Rydell Pre~redfor the Office of NatinalDrug Control Policy United States Army DRUG POLICY...Demand for Cocaine . 60 50- sm 40- squared 30- delta prevalence 20- 10- 0.2 0 0.15 0.15 󈧄 b C; 0 i Sum squared delta 0.2 prevalence 0.195 EQ 50-50 0,19...model of the demand for cocaine that was fit to 20 years of data on the current cocaine epidemic in the United States. It also describes the analysis

  12. 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.

  13. 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.

  14. Developing estimates of potential demand for renewable wood energy products in Alaska

    Treesearch

    Allen M. Brackley; Valerie A. Barber; Cassie Pinkel

    2010-01-01

    Goal three of the current U.S. Department of Agriculture, Forest Service strategy for improving the use of woody biomass is to help develop and expand markets for woody biomass products. This report is concerned with the existing volumes of renewable wood energy products (RWEP) that are currently used in Alaska and the potential demand for RWEP for residential and...

  15. 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).

  16. 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.

  17. 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

  18. Renewable deployment: Model for a fairer distribution

    NASA Astrophysics Data System (ADS)

    Grunewald, Philipp

    2017-09-01

    Typically, the allocation of renewable power sources is determined by a desire to maximize output and reduce generation costs in order to satisfy the preferences of a small number of stakeholders. A new model broadens this perspective by considering societal equity and acceptability, with the aim of improving the siting process.

  19. 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.

  20. 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…

  1. 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…

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

    DOE PAGES

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

    2016-12-23

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

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

    SciTech Connect

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

    2016-12-23

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

  4. 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.

  5. 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.

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

    DOE PAGES

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

    2015-12-23

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

  7. Simulation of electricity demand in a remote island for optimal planning of a hybrid renewable energy system

    NASA Astrophysics Data System (ADS)

    Koskinas, Aristotelis; Zacharopoulou, Eleni; Pouliasis, George; Engonopoulos, Ioannis; Mavroyeoryos, Konstantinos; Deligiannis, Ilias; Karakatsanis, Georgios; Dimitriadis, Panayiotis; Iliopoulou, Theano; Koutsoyiannis, Demetris; Tyralis, Hristos

    2017-04-01

    We simulate the electrical energy demand in the remote island of Astypalaia. To this end we first obtain information regarding the local socioeconomic conditions and energy demand. Secondly, the available hourly demand data are analysed at various time scales (hourly, weekly, daily, seasonal). The cross-correlations between the electrical energy demand and the mean daily temperature as well as other climatic variables for the same time period are computed. Also, we investigate the cross-correlation between those climatic variables and other variables related to renewable energy resources from numerous observations around the globe in order to assess the impact of each one to a hybrid renewable energy system. An exploratory data analysis including all variables is performed with the purpose to find hidden relationships. Finally, the demand is simulated considering all the periodicities found in the analysis. The simulation time series will be used in the development of a framework for planning of a hybrid renewable energy system in Astypalaia. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

  8. 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.

  9. Regional recreation demand and benefits model

    SciTech Connect

    Sutherland, R.J.

    1983-03-01

    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 camping, fishing, swimming, and boating. The model is a generalization of the single-site travel-cost method of estimating a recreation demand curve to virtually an unlimited number of sites. The major components of the analysis include the theory of recreation benefits, a travel-cost recreation demand curve, and a gravity model of regional recreation travel flows. Existing recreation benefits are estimated for each site in the region and for each activity. Recreation benefits of improved water quality in degraded rivers and streams in the Pacific Northwest are estimated on a county basis for Washington, Oregon, and Idaho. Although water quality is emphasized, the model has the capability of estimating demand and value for new or improved recreation sites at lakes, streams, or reservoirs.

  10. Renewable Energy Zones: Delivering Clean Power to Meet Demand, Greening the Grid

    SciTech Connect

    Hurlbut, David; Chernyakhovskiy, Ilya; Cochran, Jaquelin

    2016-05-01

    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 describes the renewable energy zone concept that has emerged as a transmission planning tool to help scale up the penetration of solar, wind, and other resources on the power system.

  11. An inventory model with random demand

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

  12. 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

  13. Distributed Generation Market Demand Model (dGen): Documentation

    SciTech Connect

    Sigrin, Benjamin; Gleason, Michael; Preus, Robert; Baring-Gould, Ian; Margolis, Robert

    2016-02-01

    The Distributed Generation Market Demand model (dGen) is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The National Renewable Energy Laboratory (NREL) developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States. The new model builds off, extends, and replaces NREL's SolarDS model (Denholm et al. 2009a), which simulates the market penetration of distributed PV only. Unlike the SolarDS model, dGen can model various DER technologies under one platform--it currently can simulate the adoption of distributed solar (the dSolar module) and distributed wind (the dWind module) and link with the ReEDS capacity expansion model (Appendix C). The underlying algorithms and datasets in dGen, which improve the representation of customer decision making as well as the spatial resolution of analyses (Figure ES-1), also are improvements over SolarDS.

  14. 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.

  15. 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)

  16. Indonesia’s Electricity Demand Dynamic Modelling

    NASA Astrophysics Data System (ADS)

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

    2017-06-01

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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Zebrafish as a Model for Cancer Self-Renewal

    PubMed Central

    Ignatius, Myron S.

    2009-01-01

    Abstract Self-renewal is the process by which normal stem cells and cancer cells make more of themselves. In cancer, this process is ultimately responsible for the infinite replicative potential of malignant cells and is likely found in residual cell populations that evade conventional therapy. Two intrinsically opposing hypotheses have emerged to explain how self-renewal occurs in cancer. The cancer stem cell hypothesis states that self-renewal is confined to a discrete subpopulation of malignant cells, whereas the stochastic model suggests that all tumor cells have the potential to self-renew. Presently, the gold standard for measuring cancer self-renewal is limiting dilution cell transplantation into immune-matched or immune-deficient animals. From these experiments, tumor-initiating frequency can be calculated based on the number of animals that engraft disease following transplantation of various doses of tumor cells. Here, we describe how self-renewal assays are performed, summarize the current experimental models that support the cancer stem cell and stochastic models of cancer self-renewal, and enumerate how the zebrafish can be used to uncover important pathways in cancer self-renewal. PMID:19954344

  3. 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.

  4. 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.

  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. 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

  7. Evaluation of tools for renewable energy policy analysis: The ten federal region 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 region 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 decision; and the Region Electric Policy Analysis Model (REPAM), which was constructed to allow detailed insight into interactions between policy and technology within an individual region. These Models were developed to provide a suite of fast, personal-computer based policy analysis tools; as one moves from the REP model to the TFRM to the REPAM the level of detail (and complexity) increases. In 1993 a panel was formed to identify model strengths, weaknesses (including any potential biases) and to suggest potential improvements. The panel met in January 1994 to discuss model simulations and to deliberate regarding evaluation outcomes. This report is largely a result of this meeting. This report is organized as follows. It provides a description of the TFRM 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, financial and regulatory concerns, and environmental effects.

  8. Research on renewable energy power generation complementarity and storage distribution model

    NASA Astrophysics Data System (ADS)

    Wei, Xiaoxia; Zhang, Jinfang

    2017-01-01

    This paper mainly studied the equivalent conversion relationships and model of different “quality “energies in process of multi-energy conversion. In energy interconnection system containing wind turbine, photovoltaic cell and energy storage systems, it gives renewable energy and storage distribution development model, considering comprehensive effect of load demand characteristics on energy utilization mode, multi-objective optimization model is established with objectives of both maximized energy utilization ratio and minimized system operation costs. Then, take Chinese one certain area as scenario, and give out “renewable energy utilization“, “energy transfer” and “total operating cost” three different analyses, according to the connection model. The result is compared with that for traditional energy utilization model. Feasibility of the proposed model is verified with simulation results.

  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. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

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

    SciTech Connect

    Chassin, David P.; Rondeau, Daniel

    2016-11-01

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

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

    SciTech Connect

    Chassin, David P.; Rondeau, Daniel

    2016-08-24

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

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

    SciTech Connect

    Chassin, David P.; Rondeau, Daniel

    2016-08-24

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

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

    DOE PAGES

    Chassin, David P.; Rondeau, Daniel

    2016-08-24

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

  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. Model Scaling of Hydrokinetic Ocean Renewable Energy Systems

    NASA Astrophysics Data System (ADS)

    von Ellenrieder, Karl; Valentine, William

    2013-11-01

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

  19. A Contingent Trip Model for Estimating Rail-trail Demand

    Treesearch

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

    2003-01-01

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

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

    USDA-ARS?s Scientific Manuscript database

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

  1. 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.

  2. 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.

  3. Building Energy Modeling and Control Methods for Optimization and Renewables Integration

    NASA Astrophysics Data System (ADS)

    Burger, Eric M.

    This dissertation presents techniques for the numerical modeling and control of building systems, with an emphasis on thermostatically controlled loads. The primary objective of this work is to address technical challenges related to the management of energy use in commercial and residential buildings. This work is motivated by the need to enhance the performance of building systems and by the potential for aggregated loads to perform load following and regulation ancillary services, thereby enabling the further adoption of intermittent renewable energy generation technologies. To increase the generalizability of the techniques, an emphasis is placed on recursive and adaptive methods which minimize the need for customization to specific buildings and applications. The techniques presented in this dissertation can be divided into two general categories: modeling and control. Modeling techniques encompass the processing of data streams from sensors and the training of numerical models. These models enable us to predict the energy use of a building and of sub-systems, such as a heating, ventilation, and air conditioning (HVAC) unit. Specifically, we first present an ensemble learning method for the short-term forecasting of total electricity demand in buildings. As the deployment of intermittent renewable energy resources continues to rise, the generation of accurate building-level electricity demand forecasts will be valuable to both grid operators and building energy management systems. Second, we present a recursive parameter estimation technique for identifying a thermostatically controlled load (TCL) model that is non-linear in the parameters. For TCLs to perform demand response services in real-time markets, online methods for parameter estimation are needed. Third, we develop a piecewise linear thermal model of a residential building and train the model using data collected from a custom-built thermostat. This model is capable of approximating unmodeled

  4. A Simultaneous Equation Demand Model for Block Rates

    NASA Astrophysics Data System (ADS)

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

    1986-01-01

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

  5. Identification of alternating renewal electric load models from energy measurements

    NASA Astrophysics Data System (ADS)

    El-Ferik, Sami; Malhame, Roland P.

    1994-06-01

    In statistical load modeling methodologies, aggregate electric load behavior is derived by propagating the ensemble statistics of an individual load process which is representative of the loads in the aggregate. Such a modeling philosophy tends to yield models whereby if physical meaning is present at the elemental level, it is preserved at the aggregate level. This property is essential for applications involving direct control of power system loads (for peak load shaving purposes, for example). The potential applicability of statistical load models is a strong function of one's ability to limit the volume of unusual data required to build those. An identification algorithm for a previously proposed stochastic hybrid-state Markov model of individual heating-cooling loads is presented. It relies only on data routinely gathered in power systems (device energy consumption over constant time intervals). It exploits an alternating renewal viewpoint of the load dynamics. After deriving some general results on the occupation statistics of time homogeneous alternating renewal processes, the analysis is focused on the specific model. In the process, however, some intriguing features likely to be shared by a wide class of alternating renewal processes are revealed.

  6. Modelling Per Capita Water Demand Change to Support System Planning

    NASA Astrophysics Data System (ADS)

    Garcia, M. E.; Islam, S.

    2016-12-01

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

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Models for projecting supply and demand for nurses in Israel.

    PubMed

    Nirel, Nurit; Grinstien-Cohen, Orli; Eyal, Yonatan; Samuel, Hadar; Ben-Shoham, Assaf

    2015-01-01

    Concern is growing over serious shortages in the nursing workforce and imbalance between supply and demand. Projections indicate that the demand for the nursing workforce will increase due to the aging population and an increase of the percentage of elderly people requiring assistance. To examine the expected balance between supply and several demand projections for nurses in Israel in order to contribute to planning the nursing workforce. 1. Open interviews with key figures in the healthcare and nursing care systems; 2. Examination of supply and demand for nurses; 3. Examination of the balance between supply and demand projections. A considerable gap was found between the supply and demand projections for registered nurses, which will increase over time according to each of the demand projection models up to 2030. All of the models indicate that the projected shortage will be significantly affected by the age at which the nurses retire. Models based on a fixed ratio of nurses or infrastructure (beds, positions) per population show a particularly great gap between demand and supply. However, a more conservative model (based on hospital utilization), that takes the system's infrastructures and limitations, as well as the growing population and changes in its composition into account, without an increase in the direct ratio of the number of nurses, also predict a significant shortage of nurses within 20 years. The gaps between the demand and supply projections indicate the need to augment the workforce in addition to the steps currently taken to recruit nursing staff and increase the number of training institutions for nurses. The relatively simple supply prediction models, which are based on available sources of information that can be easily revised, will make it possible to monitor and update projections regularly over time. The models developed in this study should help the process of long-term strategic planning for the number of nurses in Israel.

  16. 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.

  17. Modelling renewable electric resources: A case study of wind

    SciTech Connect

    Bernow, S.; Biewald, B.; Hall, J.; Singh, D.

    1994-07-01

    The central issue facing renewables in the integrated resource planning process is the appropriate assessment of the value of renewables to utility systems. This includes their impact on both energy and capacity costs (avoided costs), and on emissions and environmental impacts, taking account of the reliability, system characteristics, interactions (in dispatch), seasonality, and other characteristics and costs of the technologies. These are system-specific considerations whose relationships may have some generic implications. In this report, we focus on the reliability contribution of wind electric generating systems, measured as the amount of fossil capacity they can displace while meeting the system reliability criterion. We examine this issue for a case study system at different wind characteristics and penetration, for different years, with different system characteristics, and with different modelling techniques. In an accompanying analysis we also examine the economics of wind electric generation, as well as its emissions and social costs, for the case study system. This report was undertaken for the {open_quotes}Innovative IRP{close_quotes} program of the U.S. Department of Energy, and is based on work by both Union of Concerned Scientists (UCS) and Tellus Institute, including America`s Energy Choices and the UCS Midwest Renewables Project.

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. Modeling Village Water Demand Behavior: A Discrete Choice Approach

    NASA Astrophysics Data System (ADS)

    Mu, Xinming; Whittington, Dale; Briscoe, John

    1990-04-01

    This study presents a discrete choice model of households' water source choice decisions in developing countries. This model is estimated with data collected by in-depth personal interviews with 69 households in Ukunda, Kenya, a small town south of Mombasa. The results suggest that households' source choice decisions are influenced by the time it takes to collect water from different sources, the price of water, and the number of women in a household. Household income, however, did not have a statistically significant effect. Essentially the same data were used to estimate a traditional water demand model which attempts to explain the quantity of water demanded by a household as a function of collection time, income, and other socioeconomic variables. The results of the discrete choice and traditional water demand models are compared in this paper.

  4. 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…

  5. 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...

  6. 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…

  7. 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...

  8. A structured review of long-term care demand modelling.

    PubMed

    Worrall, Philip; Chaussalet, Thierry J

    2015-06-01

    Long-term care (LTC) represents a significant and substantial proportion of healthcare spends across the globe. Its main aim is to assist individuals suffering with more or more chronic illnesses, disabilities or cognitive impairments, to carry out activities associated with daily living. Shifts in several economic, demographic and social factors have raised concerns surrounding the sustainability of current systems of LTC. Substantial effort has been put into modelling the LTC demand process itself so as to increase understanding of the factors driving demand for LTC and its related services. Furthermore, such modeling efforts have also been used to plan the operation and future composition of the LTC system itself. The main aim of this paper is to provide a structured review of the literature surrounding LTC demand modeling and any such industrial application, whilst highlighting any potential direction for future researchers.

  9. 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.

  10. 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.

  11. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  13. 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.

  14. ORNL rural electric-energy-demand forecasting model

    SciTech Connect

    Maddigan, R.J.; Chern, W.S.; Gallagher, C.A.; Holcomb, B.D.; Cobbs, J.C.

    1981-09-01

    The development of a forecasting model of annual electrical-energy sales for the Rural Electrification Administration (REA) borrowers is discussed. The Oak Ridge National Laboratory, Rural Electric Energy Demand (ORNL-REED) model highlights the unique features of rural electricity demand by empirically examining the customers of the electric cooperatives. The model is used to forecast annual electricity sales by state and sector for the next twenty years. REED is a nonlinear, simultaneous-equation econometric model. It consists of submodels for the residential, commercial, industrial and irrigation sectors. The construction of a data base which reflects the cooperatives' service areas is described. The nine structural equations of REED were estimated using pooled, cross-section, time-series data for the period 1969 through 1977 for five regions. In general, the residential and commercial own-price demand elasticities are lower for the rural cooperatives than they are for the rest of the electric utility industry. However, the elasticities estimated by REED for the industrial sector tend to be higher than those estimated for the total state. The price elasticities of demand for irrigation are greater than the other sectors, indicating that the farmer is especially sensitive to changing electricity prices. The forecasts of the cooperatives' electricity demand are estimated for six sets of input assumptions, These projections give a range of total demand growth between 5.4% and 6.6% depending upon the demographic and fuel-price assumptions, compared to the 9.8% growth the cooperatives experienced between 1969 and 1977. The projected growth figures vary across states and sectors.

  15. Component Design Report: International Transportation Energy Demand Determinants Model

    EIA Publications

    2017-01-01

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

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

    DOE PAGES

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

    2015-10-01

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

  17. Program Demand Cost Model for Alaskan Schools. Eighth Edition.

    ERIC Educational Resources Information Center

    Morgan, Michael; Mearig, Tim; Coffee, Nathan

    The State of Alaska Department of Education has created a handbook for establishing budgets for the following three types of construction projects: new schools or additions; renovations; and combined new work and renovations. The handbook supports a demand cost model computer program that includes detailed renovation cost data, itemized by…

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

    NASA Astrophysics Data System (ADS)

    Abel, D.

    2016-12-01

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

  19. 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.

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

    SciTech Connect

    Barrows, Clayton; Mai, Trieu; Haase, Scott; Melius, Jennifer; Mooney, Meghan

    2016-03-01

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

  1. 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.

  2. [A physician demand and supply forecast model for Nova Scotia].

    PubMed

    Basu, Kisalaya; Gupta, Anil

    2005-01-01

    There is well-founded concern about the current and future availability of Health Human Resources (HHR). Demographic trends are magnifying this concern -- an ageing population will require more medical interventions at a time when the HHR workforce itself is ageing. The lengthy and costly training period for most health care workers, especially physicians, poses a real challenge that requires planning these activities well in advance. Hence, there is definite need for a good HHR forecasting model. To present a physician forecasting model that projects the Full-Time Equivalent (FTE) demand for and supply of physicians in Nova Scotia to the year 2020 for three specialties: general practitioners, medical, and surgical. The model enables gap analysis and assessment of alternative policy options designed to close the gaps. The methodology for estimating demand fo physician services involves three steps: (i) Establishing the FT for each physician. To this end we calculate the income of each physician using Physician Billings Data and then identify the 40th and 60th percentile income levels for each of the 40 specialties. The income levels are then used to calculate the FTE using a formula developed at Health Canada; (ii) Calculating the FTE for each service by distributing the FTE of each physician at the service level (i.e., by patient age, sex, most responsible diagnosis, and hospital status group); and (iii) Using Statistics Canada's population projections to project future demand for three broad medical disciplines: general practitioners, medical specialist, and surgical specialists. The supply side of the model employs a stock/flow approach and exploits time-series and other data for variables, such as emigration, international medical graduates (IMGs), medical school entrants, retirements, mortality, and so on, which in turn allow us to access a host of policy parameters. Under the status quo assumption, demand for physician services will outstrip the growth in

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

    PubMed

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

    2010-11-01

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

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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…

  9. 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…

  10. 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…

  11. Evaluation of development prospects of renewable energy: agent based modelling

    NASA Astrophysics Data System (ADS)

    Klevakina, E. A.; Zabelina, I. A.; Murtazina, M. Sh

    2017-01-01

    The paper describes the agent-based model usage to evaluate the dynamics and the perspectives of alternative energy adopting in the Eastern regions of Russia. It includes a brief review of the agent-based models that can be used for estimation of alternatives in the process of transition to “green” economics. The authors show that active usage of solar energy in Russia is possible at the rural household level, when the climate conditions are appropriate. Adoption of solar energy sources decreases the energy production based on the conventional sources and improves the quality of environment in the regions. A complex regional multi-agent model is considered in this paper. The model consists of several private models and uses GIS technologies. These private models are a demographic and migration model of the region and a diffusion of the innovations model. In these models, agents are humans who live within the boundaries of the agents-municipalities, and agents as well are large-scale producers of electricity that pollutes the environment. Such a structure allows us to determine the changes in the demand for electricity generated by traditional sources. A simulation software will assist to identify the opportunities for implementation of alternative energy sources in the Eastern regions of Russia.

  12. 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

  13. A model of physician behaviour with demand inducement.

    PubMed

    De Jaegher, K; Jegers, M

    2000-03-01

    We present a model of the physician-patient relationship extending on the model by Farley [Farley, P.J., 1986. Theories of the price and quantity of physician services. Journal of Health Economics 5, 315-333] of supplier-induced demand (SID). First, we make a case for the way this model specifies professional ethics, physician competition, and SID itself. Second, we derive predictions from this model, and confront them with the neoclassical model. Finally, we stress the importance of considering how SID affects patient welfare in providing an example where physicians' ability to induce makes patients better off. To evaluate patient welfare, we derive approximations of the patients' welfare loss due to physician market power in both the neoclassical model and the inducement model.

  14. A Forecasting Model for Feed Grain Demand Based on Combined Dynamic Model.

    PubMed

    Yang, Tiejun; Yang, Na; Zhu, Chunhua

    2016-01-01

    In order to improve the long-term prediction accuracy of feed grain demand, a dynamic forecast model of long-term feed grain demand is realized with joint multivariate regression model, of which the correlation between the feed grain demand and its influence factors is analyzed firstly; then the change trend of various factors that affect the feed grain demand is predicted by using ARIMA model. The simulation results show that the accuracy of proposed combined dynamic forecasting model is obviously higher than that of the grey system model. Thus, it indicates that the proposed algorithm is effective.

  15. A Forecasting Model for Feed Grain Demand Based on Combined Dynamic Model

    PubMed Central

    Yang, Tiejun

    2016-01-01

    In order to improve the long-term prediction accuracy of feed grain demand, a dynamic forecast model of long-term feed grain demand is realized with joint multivariate regression model, of which the correlation between the feed grain demand and its influence factors is analyzed firstly; then the change trend of various factors that affect the feed grain demand is predicted by using ARIMA model. The simulation results show that the accuracy of proposed combined dynamic forecasting model is obviously higher than that of the grey system model. Thus, it indicates that the proposed algorithm is effective. PMID:27698661

  16. 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.

  17. Weather Driven Renewable Energy Analysis, Modeling New Technologies

    NASA Astrophysics Data System (ADS)

    Paine, J.; Clack, C.; Picciano, P.; Terry, L.

    2015-12-01

    Carbon emission reduction is essential to hampering anthropogenic climate change. While there are several methods to broach carbon reductions, the National Energy with Weather System (NEWS) model focuses on limiting electrical generation emissions by way of a national high-voltage direct-current transmission that takes advantage of the strengths of different regions in terms of variable sources of energy. Specifically, we focus upon modeling concentrating solar power (CSP) as another source to contribute to the electric grid. Power tower solar fields are optimized taking into account high spatial and temporal resolution, 13km and hourly, numerical weather prediction model data gathered by NOAA from the years of 2006-2008. Importantly, the optimization of these CSP power plants takes into consideration factors that decrease the optical efficiency of the heliostats reflecting solar irradiance. For example, cosine efficiency, atmospheric attenuation, and shadowing are shown here; however, it should be noted that they are not the only limiting factors. While solar photovoltaic plants can be combined for similar efficiency to the power tower and currently at a lower cost, they do not have a cost-effective capability to provide electricity when there are interruptions in solar irradiance. Power towers rely on a heat transfer fluid, which can be used for thermal storage changing the cost efficiency of this energy source. Thermal storage increases the electric stability that many other renewable energy sources lack, and thus, the ability to choose between direct electric conversion and thermal storage is discussed. The figure shown is a test model of a CSP plant made up of heliostats. The colors show the optical efficiency of each heliostat at a single time of the day.

  18. 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

  19. 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

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

    PubMed

    Ferreira, Ricardo José; Firmino, Paulo Renato Alves; Cristino, Cláudio Tadeu

    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.

  1. 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.

  2. An Econometric Model of Healthcare Demand With Nonlinear Pricing.

    PubMed

    Kunz, Johannes S; Winkelmann, Rainer

    2016-04-04

    From 2004 to 2012, the German social health insurance levied a co-payment for the first doctor visit in a calendar quarter. We develop a new model for estimating the effect of such a co-payment on the individual number of visits per quarter. The model combines a one-time increase in the otherwise constant hazard rate determining the timing of doctor visits with a difference-in-differences strategy to identify the reform effect. An extended version of the model accounts for a mismatch between reporting period and calendar quarter. Using data from the German Socio-Economic Panel, we do not find an effect of the co-payment on demand for doctor visits. Copyright © 2016 John Wiley & Sons, Ltd.

  3. 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.

  4. 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.

  5. 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.

  6. Solar Radiation Modeling and Measurements for Renewable Energy Applications: Data and Model Quality; Preprint

    SciTech Connect

    Myers, D. R.

    2003-03-01

    Measurement and modeling of broadband and spectral terrestrial solar radiation is important for the evaluation and deployment of solar renewable energy systems. We discuss recent developments in the calibration of broadband solar radiometric instrumentation and improving broadband solar radiation measurement accuracy. An improved diffuse sky reference and radiometer calibration and characterization software and for outdoor pyranometer calibrations is outlined. Several broadband solar radiation model approaches, including some developed at the National Renewable Energy Laboratory, for estimating direct beam, total hemispherical and diffuse sky radiation are briefly reviewed. The latter include the Bird clear sky model for global, direct beam, and diffuse terrestrial solar radiation; the Direct Insolation Simulation Code (DISC) for estimating direct beam radiation from global measurements; and the METSTAT (Meteorological and Statistical) and Climatological Solar Radiation (CSR) models that estimate solar radiation from meteorological data. We conclude that currently the best model uncertainties are representative of the uncertainty in measured data.

  7. 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.

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

    PubMed

    Moser, Elke; Grass, Dieter; Tragler, Gernot

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

  9. An Inventory Model for Special Display Goods with Seasonal Demand

    NASA Astrophysics Data System (ADS)

    Kawakatsu, Hidefumi

    2010-10-01

    The present study discusses the retailer's optimal replenishment policy for seasonal products. The demand rate of seasonal merchandise such as clothes, sporting goods, children's toys and electrical home appearances tends to decrease with time after reaching its maximum value. In this study, we focus on "Special Display Goods", which are heaped up in end displays or special areas at retail stores. They are sold at a fast velocity when their quantity displayed is large, but are sold at a low velocity if the quantity becomes small. We develop the model with a finite time horizon (selling period) to determine the optimal replenishment policy, which maximizes the retailer's total profit. Numerical examples are presented to illustrate the theoretical underpinnings of the proposed model.

  10. 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

  11. 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.

  12. An Extended Production and Inspection Model with Nonrigid Demand

    PubMed Central

    Shih, Neng-Hui; Wang, Chih-Hsiung

    2013-01-01

    This paper extends a previous production and inspection (PI) model in relation to market demand that is nonrigid to consider an imperfect process that has a general hazard rate instead of a constant failure rate. Products are produced by an imperfect process that may shift randomly from the IN state to the OUT state. When the process is in the OUT state, it has a higher probability of producing a nonconforming product than when it is in the IN state. To achieve the zero defects policy, all products before delivery to the market should be inspected and the inspection order follows their production sequence. Furthermore, the inspection information from all previous products is used to decide either that the next candidate product should be inspected or that the inspection procedure for the current production lot should be terminated. When the inspection procedure is terminated, the remaining unmet demand is regarded as a shortage. An algorithm is developed to determine an optimal PI policy that minimizes the expected total cost, which includes the cost of inspection, of shortage, and of production. PMID:24396302

  13. 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.

  14. A double exponential model for biochemical oxygen demand.

    PubMed

    Mason, Ian G; McLachlan, Robert I; Gérard, Daniel T

    2006-01-01

    Biochemical oxygen demand (BOD) exertion patterns in anaerobically treated farm dairy wastewater were investigated on a laboratory scale. Oxygen uptake was typically characterised by a period of rapid oxygen exertion, a transitional "shoulder" phase and a period of slower activity. A multi-species model, involving rapidly degradable and slowly degradable material, was developed, leading to a double exponential model of BOD exertion as follows:where t is time, BOD(u1)(') and BOD(u2)(') are apparent ultimate BOD (BOD(u)) values, and k(1) and k(2) are rate constants. The model provided an improved description of BOD exertion patterns in anaerobically treated farm dairy wastewater in comparison to a conventional single exponential model, with rapidly degradable rate constant values (k(1)) ranging from 2.74 to 17.36d(-1), whilst slowly degradable rate constant values (k(2)) averaged 0.25d(-1) (range 0.20-0.29). Rapidly and slowly degradable apparent BOD(u) estimates ranged from 20 to 140g/m(3) and 225 to 500g/m(3), respectively, giving total BOD(u) levels of 265-620g/m(3). The mean square error in the curve fitting procedure ranged between 20 and 60g(2)/m(6), with values on average 70% lower (range 31-91%) than those obtained for the single exponential model. When applied to existing data for a range of other wastewaters, the double exponential model demonstrated a superior fit to the conventional single exponential model and provided a marginally better fit than a mixed order model. It is proposed that the presence of rapidly degradable material may be indicated from the value of the first rate constant (k1) and the time to 95% saturation of the first exponential function. Further model development is required to describe observed transitional and lag phases.

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. 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

  20. Reconciling reinforcement learning models with behavioral extinction and renewal: implications for addiction, relapse, and problem gambling.

    PubMed

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

    2007-07-01

    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 models are based on the hypothesis that dopamine carries a reward prediction error signal; these models predict reward by driving that reward error to zero. The authors construct a TDRL model that can accommodate extinction and renewal through two simple processes: (a) a TDRL process that learns the value of situation-action pairs and (b) a situation recognition process that categorizes the observed cues into situations. This model has implications for dysfunctional states, including relapse after addiction and problem gambling.

  1. 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…

  2. 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…

  3. Improving the Model for Energy Consumption Load Demand Forecasting

    NASA Astrophysics Data System (ADS)

    Bunnoon, Pituk; Chalermyanont, Kusumal; Limsakul, Chusak

    This paper proposes an application of a filter method in preprocessing stage for mid-term load demand forecasting to improve electricity load forecasting and to guarantee satisfactory forecasting accuracy. Case study employs the historical electricity consumption demand data in Thailand which were recorded in the 12 years of 1997 through to 2007. The load demand forecasted value is used for unit commitment and fuel reserve planning in the power system. This method consists of a trend component and a cyclical component decomposed from the original load demand using the Hodrick-Prescott (HP) filter in the preprocessing stage and the forecasting of each component using Double Neural Networks (DNNs) in the forecasting stage. Experimental results show that with preprocessing before forecasting can predict the load demand better than that without preprocessing.

  4. 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.

  5. 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

  6. Demand-control-person: integrating the demand-control and conservation of resources models to test an expanded stressor-strain model.

    PubMed

    Rubino, Cristina; Perry, Sara Jansen; Milam, Alex C; Spitzmueller, Christiane; Zapf, Dieter

    2012-10-01

    We propose an expanded stressor-strain model that explicitly incorporates person characteristics, the Demand-Control-Person model. This model integrates Karasek's traditional Demand-Control model with Hobfoll's (1989) Conservation of Resources theory. With participants from two organizations, we tested the moderating role of emotional stability in conjunction with two job demands (i.e., uncertainty and time pressure) and control (i.e., decision latitude) in predicting two forms of strain (i.e., job dissatisfaction and disengagement). Our findings support the expanded Demand-Control-Person model, such that a significant three-way interaction emerged for uncertainty and time pressure. As predicted, the traditional Demand-Control model only held among individuals high in emotional stability, such that low-emotional stability individuals did either not benefit as readily from decision latitude or were more susceptible to job demands when they had decision latitude. Thus, the Demand-Control-Person model may provide a more comprehensive model and consistent prediction of the effect of stressors on strain as determined by individual characteristics.

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

    ERIC Educational Resources Information Center

    CAMPBELL, ROBERT; SIEGEL, BARRY N.

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

  8. Program Demand Cost Model for Alaskan Schools. 6th Edition. Revised.

    ERIC Educational Resources Information Center

    Alaska State Dept. of Education, Juneau.

    The Program Demand Cost Model for Alaskan Schools (Cost Model) is a tool for use by school districts and their consultants in estimating school construction costs in the planning phase of a project. This document sets out the sixth edition of the demand-cost model, a rewrite of the whole system. The model can be used to establish a complete budget…

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

    PubMed

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

    2009-02-01

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

  10. 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.

  11. 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.

  12. 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

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  15. 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.

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

    PubMed

    Bi, Ya

    2015-01-01

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

  18. Localization of a demand for nursing model at the grassroots level.

    PubMed

    Terry, Allison J

    2008-01-01

    A major obstacle to the development of a usable demand model for nursing is the standardization of the definition for "demand." The lack of standardization of economic terms which are utilized in the state demand models is contributing to the failure of the long-range forecasting process for nursing nationwide. Any state that chooses to utilize U.S. Department of Health and Human Services' Health Resources and Services Administration data has selected a model which is invalid due to failure to include all members of the nursing population since this definition excludes LPNs completely. Likewise, state nursing demand models in California, Pennsylvania, North Dakota, New Jersey, and the District of Columbia have similar disadvantages. Only at a localized county-by-county grassroots level can a nursing demand model be translated into an equation which would actually calculate demand for nursing.

  19. Alternative models of recreational off-highway vehicle site demand

    Treesearch

    Jeffrey Englin; Thomas Holmes; Rebecca Niell

    2006-01-01

    A controversial recreation activity is off-highway vehicle use. Off-highway vehicle use is controversial because it is incompatible with most other activities and is extremely hard on natural eco-systems. This study estimates utility theoretic incomplete demand systems for four off-highway vehicle sites. Since two sets of restrictions are equally consistent with...

  20. 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...

  1. 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.

  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. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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.

  8. A Modeling Study of Deep Water Renewal in the Red Sea

    NASA Astrophysics Data System (ADS)

    Yao, F.; Hoteit, I.

    2016-02-01

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

  9. 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…

  10. Job demands, job resources and individual innovation at work: going beyond Karasek's model?

    PubMed

    Martín, Pilar; Salanova, Marisa; Peiró, José María

    2007-11-01

    The job demands-control model is one of the most recognized models in occupational stress research. It has, however, provided contradictory results, and the active learning hypothesis derived from this model has been under-researched in comparison with research on the stress hypothesis. The main aim of this study is to test the Job Demands Resources Model in the prediction of individual innovation at work as an active coping strategy. Results with hierarchical multiple regression analyses provide empirical support for this model. We found a positive relationship between job demands and individual innovation in situations characterized by high job resources. Finally, we discuss the limitations and practical implications of this study.

  11. Incorporating home demands into models of job strain: Findings from the Work, Family & Health Network

    PubMed Central

    Koenen, KC; Berkman, LF

    2009-01-01

    Objective To integrate home demands with the Demand-Control-Support model to test if home demands interact with job strain to increase depressive symptoms. Methods Data were from 431 employees in four extended care facilities. Presence of a child under age 18 in the household signified home demands. The outcome was depressive symptoms based on a shortened version of the Center for Epidemiologic Studies Depression Scale. Results The association between job strain and depressive symptoms was moderated by social support (SS) and presence of a child in the household (child). There was no association among participants with high SS and no child, but a positive one among participants with low SS and a child. Conclusions Job strain may be a particularly important determinant of depressive symptoms among employees with family demands. Models of job strain should expand to incorporate family demands. PMID:19001950

  12. An Analysis of Economic Retention Models for Excess Stock in a Stochastic Demand Environment

    DTIC Science & Technology

    1994-03-01

    Postgraduate School studying Operations Research. x For each demand scenario four retention scenarios were analyzed using the simulation. The four retention...of seed selection and unique demand stream generation is contained in Section IV.B.2. Because the internal execution of the Supply/Demand Review...IONS There are three areas related to this research which merit further study . First, because all of the models’ actual retention quantities are

  13. 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.

  14. 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.

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

    PubMed

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

    2016-11-09

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

  16. 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

  17. 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.

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

    PubMed Central

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

    2010-01-01

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

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

    PubMed

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

    2010-11-06

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

  20. 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

  1. 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

  2. Models and Solution for On-Demand Data Delivery Problems

    DTIC Science & Technology

    1999-01-01

    servers. We will describe motivation and format of the basic model, and several enhancements to the model formulation and solution process that are necessary to solve the problem within reasonable time limits.

  3. 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…

  4. 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…

  5. 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…

  6. 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…

  7. 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…

  8. 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…

  9. 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…

  10. 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…

  11. Essential value of cocaine and food in rats: tests of the exponential model of demand.

    PubMed

    Christensen, Chesley J; Silberberg, Alan; Hursh, Steven R; Huntsberry, Mary E; Riley, Anthony L

    2008-06-01

    To provide a prospective test of the predictive adequacy of the exponential model of demand (Hursh and Silberberg, Psych Rev 115(1):186-198, 2008). In Experiment 1, to measure the 'essential value' (the propensity to defend consumption with changes in price) of cocaine and food in a demand analysis (functional relation between price and consumption) by means of the exponential model; in Experiment 2, to test whether the model's systematic underestimation of cocaine consumption in Experiment 1 was due to weight loss; and in Experiment 3, to evaluate the effects of cocaine on the essential value of food. In Experiment 1, demand curves for food and cocaine were determined by measuring consumption of these goods in a multiple schedule over a range of fixed ratios; in Experiment 2, a demand curve for only cocaine was determined; and in Experiment 3, demand for food was determined in the absence of cocaine. In Experiment 1, the exponential equation accommodated high portions of variance for both curves, but systematically underestimated cocaine demand; in Experiment 2, this predictive underestimation of the equation was eliminated; and in Experiment 3, the essential value of food was greater than in Experiment 1. The exponential model of demand accommodated the data variance for all cocaine and food demand curves. Compared to food, cocaine is a good of lower essential value.

  12. 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.

  13. Generalized network flow model with application to power supply-demand problems

    SciTech Connect

    Liu, C.

    1982-08-01

    A generalization of the conventional network flow model to a very general F-flow model is provided. The max-flow-min-cut theorem is then generalized. The theorem is used to derive a necessary and sufficient condition for feasibility of the multi-terminal supply-demand problem based on the F-flow model. As an application, the electric power supply-demand problem is discussed from the F-flow point of view.

  14. 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.

  15. 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.

  16. Modeling and Optimization of Renewable and Hybrid Fuel Cell Systems for Space Power and Propulsion

    DTIC Science & Technology

    2010-11-14

    For that the project achieved: the optimization of SOFC and PEMFC internal structure and external shape under a volume constraint; an initial set of...subcomponent models for regenerative, renewable fuel cell system (RFC); the integration of PEMFC into RFC systems were developed; power electronic...with the same objectives and goals but using a PEMFC regenerative system instead. This research group studied and published on the optimization and

  17. 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..

  18. 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.

  19. 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.

  20. Determinants of orthodontic treatment need and demand: a cross-sectional path model study.

    PubMed

    Taghavi Bayat, Jari; Huggare, Jan; Mohlin, Bengt; Akrami, Nazar

    2017-02-01

    To put forward a model predicting orthodontic treatment need and demand. Furthermore, to explore how much of the variance in treatment demand could be explained by a set of self-assessed measures, and how these measures relate to professionally assessed treatment need. One hundred and fifty adolescents, aged 13 years, completed a questionnaire which included a set of self-assessed measures dealing with self-esteem, such as dental and global self-esteem, various aspects of malocclusion, such as perceived malocclusion and perceived functional limitation, and treatment demand. Treatment need was assessed by Dental Health Component of the Index of Orthodontic Treatment Need grading. Path analysis was used to examine the relations between the measures and if they could predict treatment need and demand. The measures proved to be reliable and inter-correlated. Path analysis revealed that the proposed model had good fit to the data, providing a test of the unique effect of all included measures on treatment need and demand. The model explained 33% of the variance in treatment demand and 22% of the variance in treatment need. The specific age group could affect the generalizability of the findings. Moreover, although showing good fit to data, the final model is based on a combination of theoretical reasoning and semi-explorative approach. The proposed model displays the unique effect of each included measure on treatment need and demand, explaining a large proportion of the variance in perceived treatment demand and professionally assessed treatment need. The model would hopefully lead to improved and more cost-efficient predictions of treatment need and demand. © The Author 2016. Published by Oxford University Press on behalf of the European Orthodontic Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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

    NASA Astrophysics Data System (ADS)

    Alyamani, Talal M.

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

  2. Wilderness Recreation Demand: A Comparison of Travel Cost and On-Site Cost Models

    Treesearch

    J.M. Bowker; A. Askew; L. Seymour; J.P. Zhu; D. English; C.M. Starbuck

    2009-01-01

    This study used travel cost and on-site day cost models, coupled with the Forest Service’s National Visitor Use Monitoring data, to examine the demand for and value of recreation access to designated Wilderness.

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

    NASA Astrophysics Data System (ADS)

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

    2011-08-01

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

  4. [Demand-Control model and occupational stress among nursing professionals: integrative review].

    PubMed

    Schmidt, Denise Rodrigues Costa

    2013-01-01

    The Demand Control model aims to evaluate the occupational stress. This study aimed to know, through an integrative review of the literature, the scientific production about the Demand Control Model to investigation occupational stress among nursing professionals from 2000 to 2011.Of the 16 selected studies, five were published in 2009. Of these studies, 56.25% assessed the Demand and Control dimensions and their correlations with workers' health problems; 37.5% of these studies were related with mental health. The results showed a lack of national publications. We recommend that authors conduct experimental studies to reduce the occupational stress for better conditions of workers' mental health.

  5. 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.

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

    SciTech Connect

    Gallo, Giulia

    2016-01-08

    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.

  7. 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

  8. Energy demand forecasting by means of Statistical Modelling: Assessing Benefits of Climate Information

    NASA Astrophysics Data System (ADS)

    De Felice, M.; Alessandri, A.; Ruti, P. M.

    2012-04-01

    Energy demand forecasting is a critical task and it allows to anticipate any problems that might affect power systems operators, especially during periods with high demand peaks. The difficulties of this task are due to the complexity of the systems involved: energy usage patterns are particularly variable and influenced by many factors, such as weather conditions, social, economic and political aspects (i.e. national regulations, international relations). The strong influence of weather on electricity demand in Italy is due to the wide use of residential air-conditioning devices and, more in general, refrigeration and ventilation equipments. For this reasons, accurate climate information may help in obtaining precise energy demand forecasts, usually performed with statistical methods which show their effectiveness particularly where large amount of data is available. We present a study with the aim of assess the effects of the quality of weather data on statistical modelling performance on energy demand forecasting, using data provided by national transmission grid operator.

  9. Application of short-term water demand prediction model to Seoul.

    PubMed

    Joo, C N; Koo, J Y; Yu, M J

    2002-01-01

    To predict daily water demand for Seoul, Korea, the artificial neural network (ANN) was used. For the cross correlation, the factors affecting water demand such as maximum temperature, humidity, and wind speed as natural factors, holidays as a social factor and daily demand 1 day before were used. From the results of learning using various hidden layers and units in order to establish the structure of optimal ANN, the case of 3 hidden layers and numbers of unit with the same number of input factors showed the best result and, therefore, it was applied to seasonal water demand prediction. The performance of ANN was compared with a multiple regression method. We discuss the representation ability of the model building process and the applicability of the ANN approach for the daily water demand prediction. ANN provided reasonable results for time series prediction.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

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

    PubMed Central

    Mondal, Chanchal

    2017-01-01

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

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

    PubMed

    Mondal, Chanchal; Chatterjee, Siddharth G

    2017-07-01

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

  16. 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.

  17. System dynamics modeling for municipal water demand estimation in an urban region under uncertain economic impacts.

    PubMed

    Qi, Cheng; Chang, Ni-Bin

    2011-06-01

    Accurate prediction of municipal water demand is critically important to water utilities in fast-growing urban regions for drinking water system planning, design, and water utility asset management. Achieving the desired prediction accuracy is challenging, however, because the forecasting model must simultaneously consider a variety of factors associated with climate changes, economic development, population growth and migration, and even consumer behavioral patterns. Traditional forecasting models such as multivariate regression and time series analysis, as well as advanced modeling techniques (e.g., expert systems and artificial neural networks), are often applied for either short- or long-term water demand projections, yet few can adequately manage the dynamics of a water supply system because of the limitations in modeling structures. Potential challenges also arise from a lack of long and continuous historical records of water demand and its dependent variables. The objectives of this study were to (1) thoroughly review water demand forecasting models over the past five decades, and (2) propose a new system dynamics model to reflect the intrinsic relationship between water demand and macroeconomic environment using out-of-sample estimation for long-term municipal water demand forecasts in a fast-growing urban region. This system dynamics model is based on a coupled modeling structure that takes into account the interactions among economic and social dimensions, offering a realistic platform for practical use. Practical implementation of this water demand forecasting tool was assessed by using a case study under the most recent alternate fluctuations of economic boom and downturn environments. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

    PubMed

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

    2016-12-01

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

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

    PubMed

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

    2003-02-27

    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. 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. 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. Future work should explore the combined effects of these two models of psychosocial stress at work on health more thoroughly.

  20. Reliability modelling of redundant safety systems without automatic diagnostics incorporating common cause failures and process demand.

    PubMed

    Alizadeh, Siamak; Sriramula, Srinivas

    2017-09-16

    Redundant safety systems are commonly used in the process industry to respond to hazardous events. In redundant systems composed of identical units, Common Cause Failures (CCFs) can significantly influence system performance with regards to reliability and safety. However, their impact has been overlooked due to the inherent complexity of modelling common cause induced failures. This article develops a reliability model for a redundant safety system using Markov analysis approach. The proposed model incorporates process demands in conjunction with CCF for the first time and evaluates their impacts on the reliability quantification of safety systems without automatic diagnostics. The reliability of the Markov model is quantified by considering the Probability of Failure on Demand (PFD) as a measure for low demand systems. The safety performance of the model is analysed using Hazardous Event Frequency (HEF) to evaluate the frequency of entering a hazardous state that will lead to an accident if the situation is not controlled. The utilisation of Markov model for a simple case study of a pressure protection system is demonstrated and it is shown that the proposed approach gives a sufficiently accurate result for all demand rates, durations, component failure rates and corresponding repair rates for low demand mode of operation. The Markov model proposed in this paper assumes the absence of automatic diagnostics, along with multiple stage repair strategy for CCFs and restoration of the system from hazardous state to the "as good as new" state. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

    Chen, H.; Yang, Z. F.

    2009-05-01

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

  2. Process-based modelling of regional water demand for electricity, industry and municipal sectors in Integrated Assessment Models.

    NASA Astrophysics Data System (ADS)

    Bijl, David L.; Bogaart, Patrick W.; Kram, Tom; De Vries, Bert J. M.; Van Vuuren, Detlef P.

    2014-05-01

    Integrated Assessment Models (IAMs) are a prime tool for studying global scale interactions between the human and natural earth systems. Our research contributes to this field by modelling water, food and energy demand as outcomes of more physical processes and by adding links between them. As part of this ambition, we here describe a model for water demand in the electricity generation, industrial and municipal sectors, going beyond previous modelling efforts. For instance, by coupling water demand to energy inputs, the model directly couples water efficiency to fuel efficiency of power plants. We present electricity, industry and municipal water demand models and develop water demand projections for the new Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) for climate research. Our regional-level demand models contribute to understanding the extent of crossing planetary boundaries and the scope for solutions such as virtual water trade or efficiency improvements. We also discuss how we plan to link demand and supply models, and how the usefulness for policy makers can be increased.

  3. Validating HRSA's nurse supply and demand models: a state-level perspective.

    PubMed

    Nooney, Jennifer G; Lacey, Linda M

    2007-01-01

    In addition to federal initiatives, solutions to the nursing shortage must also be devised at the state level. Understanding the timing and severity of the nursing shortage in a particular state is paramount to devising appropriate solutions In 2005, the Health Resources and Services Administration released new versions of the Nurse Supply Model and Nurse Demand Model designed to project the supply of RNs and demand for RNs, LPNs, and nurse aides in the United States through the year 2020. The process used by two state-level analysts to project nurse supply and demand in North Carolina using the HRSA models is described. The authors conclude that the models work well for state-level forecasting but that users should carefully assess the default data provided with the model against independent data sources specific to their states.

  4. 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.

  5. 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

  6. 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

  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. 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.

  9. 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

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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.)

  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. 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.)

  18. 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.

  19. Residential electricity demand in Mexico: a model distinguishing access from consumption

    SciTech Connect

    Berndt, E.R.; Samaniego, R.

    1984-08-01

    Electricity access-consumption data of households by region and over time are the empirical basis for this paper. Following a brief background on residential electricity and energy consumption in Mexico, the authors discuss important demographic phenomena, the goals of electrification programs, and features of the electricity tariff schedules. They extend typical residential demand models to include separately the demand for electricity hook-ups. A principal finding is that a developing country like Mexico experiences a double whammy impact on electricity consumption with increases in income because of the demand for new hook-ups and the increased consumption by those who already have access. Policy implications are that pricing policy has a statistically significant impact on demand; that government-sponsored rural electrification programs have a major impact on consumption; and that the growth rates of consumption will level off as access becomes universal by 1990. 30 references 2 tables.

  20. Transformation of potential medical demand in China: A system dynamics simulation model.

    PubMed

    Yu, Wenya; Li, Meina; Ge, Yang; Li, Ling; Zhang, Yi; Liu, Yuan; Zhang, Lulu

    2015-10-01

    The increasing of potential medical demand in China has threatened the health of the population, the medical equity, accessibility to medical services, and has impeded the development of Chinese health delivery system. This study aims to understand the mechanism of the increasing potential medical demand and find some solutions. We constructed a system dynamics model to analyze and simulate this problem, to predict the influences of health policies on the actual percentage of patients not seeking medical care (adjusting the quantity structure of hospitals and community health systems (CHSs), adjusting outpatient prices, and adjusting the level of health insurance). Decreasing the number of hospitals, increasing the number of CHSs, and raising the proportion of health insurance compensation would effectively increase the transformation of potential medical demand. But currently, changes of the outpatient prices didn't play a role in the transformation of potential medical demand. Combined with validation analysis and model simulation, we suggest some possible solutions. The main factors causing potential medical demand are accessibility to medical services and proportion of health insurance compensation. Thus, adjusting the number of hospitals and CHSs and increasing the proportion of health insurance compensation should decrease the actual percentage of patients not seeking medical care and accelerate the transformation of potential medical demand, which deserved being concerned in policymaking. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  1. 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…

  2. 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…

  3. The Demand-Driven Learning Model: A Framework for Web-Based Learning.

    ERIC Educational Resources Information Center

    MacDonald, Colla J.; Stodel, Emma J.; Farres, Laura G.; Breithaupt, Krista; Gabriel, Martha A.

    2001-01-01

    Reviews recent philosophical debate surrounding the future role and activities of universities in a technological society; discusses the need for new learning models to meet the needs of working adult students; and presents the demand-driven learning model, a collaborative effort between academics and experts from private and public industries…

  4. 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…

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

    PubMed

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

    2016-04-01

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

  6. 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.

  7. 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.

  8. A single period inventory model with a truncated normally distributed fuzzy random variable demand

    NASA Astrophysics Data System (ADS)

    Dey, Oshmita; Chakraborty, Debjani

    2012-03-01

    In this article, a single period inventory model has been considered in the mixed fuzzy random environment by assuming the annual customer demand to be a fuzzy random variable. Since assuming demand to be normally distributed implies that some amount of demand information is being automatically taken to be negative, the model has been developed for two cases, using the non-truncated and the truncated normal distributions. The problem has been developed to represent scenarios where the aim of the decision-maker is to determine the optimal order quantity such that the expected profit is greater than or equal to a predetermined target. This 'greater than or equal to' inequality has been modelled as a fuzzy inequality and a methodology has been developed to this effect. This methodology has been illustrated through a numerical example.

  9. Development and application of econometric demand and supply models for selected Chesapeake Bay seafood products

    SciTech Connect

    Nieves, L.A.; Moe, R.J.

    1984-12-01

    Five models were developed to forecast future Chesapeake seafood product prices, harvest quantities, and resulting income. Annual econometric models are documented for oysters, hard and soft blue crabs, and hard and soft clams. To the degree that data permit, these models represent demand and supply at the retail, wholesale, and harvest levels. The resulting models have broad applications in environmental policy issues and regulatory analyses for the Chesapeake Bay. 37 references, 10 figures, 99 tables.

  10. Modeling the Demand for Spare Parts: Estimating the Variance-to-Mean Ratio and other Issues

    DTIC Science & Technology

    1985-05-01

    REPORT & PERIOD COVERED Modeling the Demand for Spare Parts: Interin stimatinq .the Variance-to-Mean Ratio and Other issues 6. PERFORMING ORG. REPORT...repair systems. Butaccurate evaluations of supply policies arenot possible without accurate models of thesupPly system, and models that understate the...variability in the supply system wilibias evaluations in favor of policies thatrely on accurate predictions of part failures. This Note examines the model

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. Modeling the demand for long-term care services under uncertain information.

    PubMed

    Cardoso, Teresa; Oliveira, Mónica Duarte; Barbosa-Póvoa, Ana; Nickel, Stefan

    2012-12-01

    Developing a network of long-term care (LTC) services is currently a health policy priority in many countries, in particular in countries with a health system based on a National Health Service (NHS) structure. Developing such a network requires proper planning and basic information on future demand and utilization of LTC services. Unfortunately, this information is often not available and the development of methods to properly predict demand is therefore essential. The current study proposes a simulation model based on a Markov cycle tree structure to predict annual demand for LTC services so as to inform the planning of these services at the small-area level in the coming years. The simulation model is multiservice, as it allows for predicting the annual number of individuals in need of each type of LTC service (formal and informal home-based, ambulatory and institutional services), the resources/services that are required to satisfy those needs (informal caregivers, domiciliary visits, consultations and beds) and the associated costs. The model developed was validated using past data and key international figures and applied to Portugal at the Lisbon borough level for the 2010-2015 period. Given data imperfections and uncertainties related to predicting future LTC demand, uncertainty was modeled through an integrated approach that combines scenario analysis with probabilistic sensitivity analysis using Monte Carlo simulation. Results show that the model provides information critical for informing the planning and financing of LTC networks.

  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. 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

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

    PubMed

    Potocka, Adrianna; Waszkowska, Małgorzata

    2013-01-01

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

  19. Demand, Supply, and Shortage of Bilingual and ESL Teachers: Models, Data, and Policy Issues.

    ERIC Educational Resources Information Center

    Boe, Erling E.

    A comprehensive teacher demand, supply, and shortage (TDSS) model is proposed as a conceptual framework for analyzing and determining the teaching force in bilingual and English-as-a-Second-Language (ESL) education. Available data on the shortage of bilingual education teachers are reviewed, and new national data on their characteristics are…

  20. 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…

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

    PubMed Central

    Duan, Jinli; Jiao, Feng; Zhang, Qishan

    2017-01-01

    The sharp increase of the aging population has raised the pressure on the current limited medical resources in China. To better allocate resources, a more accurate prediction on medical service demand is very urgently needed. This study aims to improve the prediction on medical services demand in China. To achieve this aim, the study combines Taylor Approximation into the Grey Markov Chain model, and develops a new model named Taylor-Markov Chain GM (1,1) (T-MCGM (1,1)). The new model has been tested by adopting the historical data, which includes the medical service on treatment of diabetes, heart disease, and cerebrovascular disease from 1997 to 2015 in China. The model provides a predication on medical service demand of these three types of disease up to 2022. The results reveal an enormous growth of urban medical service demand in the future. The findings provide practical implications for the Health Administrative Department to allocate medical resources, and help hospitals to manage investments on medical facilities. PMID:28783088

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

    PubMed

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

    2017-08-06

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

  3. 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…

  4. 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...

  5. An analysis of dynamics of discrete demand-inventory model with bifurcation diagrams and phase portraits

    NASA Astrophysics Data System (ADS)

    Hachuła, Piotr; Nockowska-Rosiak, Magdalena; Schmeidel, Ewa

    2017-07-01

    An analysis of dynamics of demand-inventory model formulated with a system of three first order difference equations with three parameters. The origin, rules, assumptions and example of application are presented. The numerical analysis is performed using bifurcation diagrams and phase portraits. Graphical observation of evolution of trajectories suggests chaotic behaviour occurrence.

  6. 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.

  7. 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

  8. 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

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

    PubMed

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

    2012-01-01

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

  10. Supply-demand 3D dynamic model in water resources evaluation: taking Lebanon as an example

    NASA Astrophysics Data System (ADS)

    Fang, Hong; Hou, Zhimin

    2017-05-01

    In this paper, supply-demand 3D dynamic model is adopted to create a measurement of a region’s capacity to provide available water to meet the needs of its population. First of all, we draw a diagram between supply and demand. Then taking the main dynamic factors into account, we establish an index to evaluate the balance of supply and demand. The three dimension vector reflects the scarcity of industrial, agricultural and residential water. Lebanon is chosen as the object of case study, and we do quantitative analysis of its current situation. After data collecting and processing, we calculate the 3D vector in 2012, which reveals that agriculture is susceptible to water scarcity. Water resources of Lebanon are “physical rich” but “economic scarcity” according to the correlation chart and other statistical analysis.

  11. Physicians' perception of demand-induced supply in the information age: a latent class model analysis.

    PubMed

    Shih, Ya-Chen Tina; Tai-Seale, Ming

    2012-03-01

    This paper introduces a concept called 'demand-induced supply' that reflects the excess supply of services due to an increase in demand initiated by patients. We examine its association with the proportion of information-savvy patients in physicians' practice. Using data from a national representative physician survey, we apply latent class models to analyze this association. Our analyses categorize physicians into three 'types' according to the frequency with which they provided additional medical services at their patients' requests: frequent, occasional, and rare. The proportion of information-savvy patients is significantly and positively correlated with demand-induced supply for the frequent or occasional type, but not among physicians in the rare type. Efforts to contain healthcare costs through utilization control need to recognize the pattern of responses from physicians who treat an increasing number of information-savvy patients.

  12. 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.

  13. 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.…

  14. 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.…

  15. 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

  16. Burnout in medical residents: a study based on the job demands-resources model.

    PubMed

    Zis, Panagiotis; Anagnostopoulos, Fotios; Sykioti, Panagiota

    2014-01-01

    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). 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. 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. Burnout among medical residents is associated with home-work interface, autonomy, professional development, and resident to specialist ratio.

  17. 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.

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

    PubMed

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

    2017-09-29

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

  19. 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

  20. 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.

  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.

  2. 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.

  3. An Innovative Interactive Modeling Tool to Analyze Scenario-Based Physician Workforce Supply and Demand

    PubMed Central

    Gupta, Saurabh; Black-Schaffer, W. Stephen; Crawford, James M.; Gross, David; Karcher, Donald S.; Kaufman, Jill; Knapman, Doug; Prystowsky, Michael B.; Wheeler, Thomas M.; Bean, Sarah; Kumar, Paramhans; Sharma, Raghav; Chamoli, Vaibhav; Ghai, Vikrant; Gogia, Vineet; Weintraub, Sally; Cohen, Michael B.

    2015-01-01

    Effective physician workforce management requires that the various organizations comprising the House of Medicine be able to assess their current and future workforce supply. This information has direct relevance to funding of graduate medical education. We describe a dynamic modeling tool that examines how individual factors and practice variables can be used to measure and forecast the supply and demand for existing and new physician services. The system we describe, while built to analyze the pathologist workforce, is sufficiently broad and robust for use in any medical specialty. Our design provides a computer-based software model populated with data from surveys and best estimates by specialty experts about current and new activities in the scope of practice. The model describes the steps needed and data required for analysis of supply and demand. Our modeling tool allows educators and policy makers, in addition to physician specialty organizations, to assess how various factors may affect demand (and supply) of current and emerging services. Examples of factors evaluated include types of professional services (3 categories with 16 subcategories), service locations, elements related to the Patient Protection and Affordable Care Act, new technologies, aging population, and changing roles in capitated, value-based, and team-based systems of care. The model also helps identify where physicians in a given specialty will likely need to assume new roles, develop new expertise, and become more efficient in practice to accommodate new value-based payment models. PMID:28725751

  4. Modeling a drip irrigation system powered by a renewable energy source

    NASA Astrophysics Data System (ADS)

    Al-Zoheiry, Ahmed M.

    Food production is a problem in many of the regions in the world. Today, the process of producing food is very dependent on energy. The dependency on fossil fuels causes the cost of producing crops to increase as the prices of fuel increases. Using a renewable energy sources to power an irrigation system is a mean of decreasing the dependency of food products on the prices of fuel and minimize the impact of the irrigation system on the environment. A model was developed to simulate and predict the performance of an irrigation system powered by a renewable energy source. Both solar energy and wind energy were considered for the modeling of the system. The solar energy was simulated using the difference between the maximum and the minimum daily temperatures as an indicator of the amount of clouds in the atmosphere. The model is a modification of earlier models and has the advantage of not needing to be calibrated for each new site. Results showed that a model that calibrates it self for the upper and the lower expected values of the solar radiation can be developed using metrological data such as the location of the site, the daily temperatures, and the minimum relative humidity. The wind energy was predicted using the power coefficient of the turbine and statistical representation of the daily wind speeds. The average hourly values of the wind speed were used for finding the distribution constants for the Weibull distribution and Rayleigh distribution. The results showed that the Weibull distribution is more accurate in predicting the expected power output of the turbine when the daily wind speed coefficient of variation (Cv) was less than 0.5. When the Cv is greater than 0.5 the Rayleigh distribution gives better results. A computer model was developed using Visual Basic to model the system and the resulting model was tested and used in comparing the economics of a traditional irrigation system and an irrigation system powered by solar panels. The system powered by

  5. The Cycle of Renewal.

    ERIC Educational Resources Information Center

    Farrell, Edmund J.

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

  6. 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.

  7. 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

  8. Modeling and Analysis of Commercial Building Electrical Loads for Demand Side Management

    NASA Astrophysics Data System (ADS)

    Berardino, Jonathan

    In recent years there has been a push in the electric power industry for more customer involvement in the electricity markets. Traditionally the end user has played a passive role in the planning and operation of the power grid. However, many energy markets have begun opening up opportunities to consumers who wish to commit a certain amount of their electrical load under various demand side management programs. The potential benefits of more demand participation include reduced operating costs and new revenue opportunities for the consumer, as well as more reliable and secure operations for the utilities. The management of these load resources creates challenges and opportunities to the end user that were not present in previous market structures. This work examines the behavior of commercial-type building electrical loads and their capacity for supporting demand side management actions. This work is motivated by the need for accurate and dynamic tools to aid in the advancement of demand side operations. A dynamic load model is proposed for capturing the response of controllable building loads. Building-specific load forecasting techniques are developed, with particular focus paid to the integration of building management system (BMS) information. These approaches are tested using Drexel University building data. The application of building-specific load forecasts and dynamic load modeling to the optimal scheduling of multi-building systems in the energy market is proposed. Sources of potential load uncertainty are introduced in the proposed energy management problem formulation in order to investigate the impact on the resulting load schedule.

  9. 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.

  10. A Mathematical Model of Demand-Supply Dynamics with Collectability and Saturation Factors

    NASA Astrophysics Data System (ADS)

    Li, Y. Charles; Yang, Hong

    We introduce a mathematical model on the dynamics of demand and supply incorporating collectability and saturation factors. Our analysis shows that when the fluctuation of the determinants of demand and supply is strong enough, there is chaos in the demand-supply dynamics. Our numerical simulation shows that such a chaos is not an attractor (i.e. dynamics is not approaching the chaos), instead a periodic attractor (of period-3 under the Poincaré period map) exists near the chaos, and coexists with another periodic attractor (of period-1 under the Poincaré period map) near the market equilibrium. Outside the basins of attraction of the two periodic attractors, the dynamics approaches infinity indicating market irrational exuberance or flash crash. The period-3 attractor represents the product’s market cycle of growth and recession, while period-1 attractor near the market equilibrium represents the regular fluctuation of the product’s market. Thus our model captures more market phenomena besides Marshall’s market equilibrium. When the fluctuation of the determinants of demand and supply is strong enough, a three leaf danger zone exists where the basins of attraction of all attractors intertwine and fractal basin boundaries are formed. Small perturbations in the danger zone can lead to very different attractors. That is, small perturbations in the danger zone can cause the market to experience oscillation near market equilibrium, large growth and recession cycle, and irrational exuberance or flash crash.

  11. 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....

  12. 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....

  13. 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.

  14. 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).

  15. Regime switches induced by supply-demand equilibrium: a model for power-price dynamics

    NASA Astrophysics Data System (ADS)

    Mari, Carlo; Tondini, Daniela

    2010-11-01

    Regime-switching models can be used to describe stochastic movements of electricity prices in deregulated markets. This paper shows that regime-switching dynamics arise quite naturally in an equilibrium context in which the functional form of the supply curve is described by a two-state Markov process. This mechanism is responsible for random switches between regimes and it allows one to describe the main features of the price-formation process. With the interplay between demand and supply, the proposed methodology can be used to capture shortages in electricity generation, forced outages, and peaks in electricity demand. As an example of application, a two-regime model specification is proposed, and it will be shown that the empirical analysis, performed by estimating using the model on the California power market, offers an interesting agreement with observed data.

  16. Increasing secondary and renewable material use: a chance constrained modeling approach to manage feedstock quality variation.

    PubMed

    Olivetti, Elsa A; Gaustad, Gabrielle G; Field, Frank R; Kirchain, Randolph E

    2011-05-01

    The increased use of secondary (i.e., recycled) and renewable resources will likely be key toward achieving sustainable materials use. Unfortunately, these strategies share a common barrier to economical implementation - increased quality variation compared to their primary and synthetic counterparts. Current deterministic process-planning models overestimate the economic impact of this increased variation. This paper shows that for a range of industries from biomaterials to inorganics, managing variation through a chance-constrained (CC) model enables increased use of such variable raw materials, or heterogeneous feedstocks (hF), over conventional, deterministic models. An abstract, analytical model and a quantitative model applied to an industrial case of aluminum recycling were used to explore the limits and benefits of the CC formulation. The results indicate that the CC solution can reduce cost and increase potential hF use across a broad range of production conditions through raw materials diversification. These benefits increase where the hFs exhibit mean quality performance close to that of the more homogeneous feedstocks (often the primary and synthetic materials) or have large quality variability. In terms of operational context, the relative performance grows as intolerance for batch error increases and as the opportunity to diversify the raw material portfolio increases.

  17. 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.

  18. 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.

  19. Measuring welfare changes and modeling demand systems: Theory and applications to energy efficiency and environmental externalities in New York state residential energy demand

    SciTech Connect

    Dumagan, J.C.

    1991-01-01

    This study implements a generalized logit model of consumer demand. The generalized logit model conforms to the theory of consumer behavior better than the standard flexible functional form demand systems. This generalized logit was estimated using New York state-level and company-level data on residential consumption of electricity, natural gas, and fuel oil, including a composite good to complete the demand system. Results show that the estimated model satisfies the theoretical conditions of a well-behaved demand system for every data point in the sample and for a range of hypothetical households distinctly different from the sample. Results demonstrate that the generalized logit embodies utility-maximizing behavior over a much wider range of observations than standard flexible functional forms. The estimated generalized logit and money metric were combined to measure the money-metric welfare effects of (a) a variety of specific electricity-conservation options in the residential sector of New York state, and of (b) carbon taxes on electricity and fuels and an emissions penalty only on electricity.

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

    PubMed

    Iguchi, Aya

    2016-01-01

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

  1. 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

  2. Measuring public acceptance on renewable energy (RE) development in Malaysia using ordered probit model

    NASA Astrophysics Data System (ADS)

    Zainudin, W. N. R. A.; Ishak, W. W. M.

    2017-09-01

    In 2009, government of Malaysia has announced a National Renewable Energy Policy and Action Plan as part of their commitment to accelerate the growth in renewable energies (RE). However, an adoption of RE as a main source of energy is still at an early stage due to lack of public awareness and acceptance on RE. Up to date, there are insufficient studies done on the reasons behind this lack of awareness and acceptance. Therefore, this paper is interested to investigate the public acceptance towards development of RE by measuring their willingness to pay slightly more for energy generated from RE sources, denote as willingness level and whether the importance for the electricity to be supplied at absolute lowest possible cost regardless of source and environmental impact, denote as importance level and other socio-economic factors could improve their willingness level. Both qualitative and quantitative research methods are used to achieve the research objectives. A total of 164 respondents from local universities in Malaysia participated in a survey to collect this relevant information. Using Ordered Probit model, the study shows that among the relevant socio-economic factors, age seems to be an important factor to influence the willingness level of the respondents. This paper concludes that younger generation are more willing to pay slightly more for energy generated from RE sources as compared to older generation. One of the possible reason may due to better information access by the younger generation on the RE issues and its positive implication to the world. Finding from this paper is useful to help policy maker in designing RE advocacy programs that would be able to secure public participation. These efforts are important to ensure future success of the RE policy.

  3. An Integrated Urban Land Use and Transportation Demand Model Based on Lowry Linage

    NASA Astrophysics Data System (ADS)

    Zargari, Shahriar A.; Araghi, Morteza

    Here, we concentrate on the equilibrium modeling of Integrated Land Use and Transportation Demand Model (ILUTDM). We propose two combined sub models to involve in the ILUTDM: 1- residential activity location choices, trip distribution, mode choices and route choices, 2-employment location choices, trip distribution, mode choices and route choices. In the both combined sub models is assumed each individual minimize his or her travel cost and maximize his or her living or service utility. The joint choice of the residential or the employment location and transportation destination and mode of the two sub models is formulated as a nested multinomial logit model. We reformulate the combined sub models as an Equivalent Minimization Problem (EMP). The Evans algorithm may be applied to the EMP, in purpose of a realistic application within a reasonable time period. Finally, we develop an ILUTDM that contains the economic-base mechanism, the proposed combined sub models and the constraint procedure and their interactions.

  4. A Longitudinal Study of Teachers' Occupational Well-Being: Applying the Job Demands-Resources Model.

    PubMed

    Dicke, Theresa; Stebner, Ferdinand; Linninger, Christina; Kunter, Mareike; Leutner, Detlev

    2017-02-02

    The job demands-resources model (JD-R model; Bakker & Demerouti, 2014) is well established in occupational research, and the proposed processes it posits have been replicated numerous times. Thus, the JD-R model provides an excellent framework for explaining the occupational well-being of beginning teachers-an occupation associated with particularly high levels of strain and consequently, high attrition rates. However, the model's assumptions have to date mostly been tested piecewise, and seldom on the basis of longitudinal models. With a series of longitudinal autoregressive SEM models (N = 1,700) we tested all assumptions of the JD-R model simultaneously in one model with an applied focus on beginning teachers. We assessed self-reports of beginning teachers at three time waves: at the beginning and end (one and a half to two years later) of their preservice period, and again, one year later. Results revealed significant direct effects of resources (self-efficacy) on engagement, of demands (classroom disturbances) on strain (emotional exhaustion), and a significant reverse path of engagement on self-efficacy. Additionally, the results showed two moderation effects: Self-efficacy buffered the demands-strain relationship, while self-efficacy also predicted engagement, especially when disturbances were high. Thus, self-efficacy in classroom management plays an important role in the teachers' stress development process, as it will, in case of high classroom disturbances, not only buffer the strain-enhancing effects, but also boost engagement. Commitment was predicted directly by emotional exhaustion and engagement, but indirectly only by self-efficacy (via engagement). Thus, we provide strong empirical support for the JD-R model. (PsycINFO Database Record

  5. 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.

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

    PubMed

    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.

  7. Two-warehouse inventory model with ramp-type demand and partially backlogged shortages

    NASA Astrophysics Data System (ADS)

    Agrawal, Swati; Banerjee, Snigdha

    2011-07-01

    In this article, we consider an inventory model for items that are stored in two-warehouses when demand is a general ramp-type function of time. Shortages are allowed and a constant fraction of shortages is backlogged. The existence and uniqueness of optimal solution is proved for both - the single-warehouse and the two-warehouse models. An algorithm is developed to facilitate the choice between the two-warehouse and the single-warehouse systems and hence to obtain the optimal replenishment policy. Numerical examples are presented. Sensitivity analysis with respect to the parameters of the model is performed.

  8. 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…

  9. 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.

  10. Combined Task and Physical Demands Analyses towards a Comprehensive Human Work Model

    DTIC Science & Technology

    2014-09-01

    the task hierarchy) that exert forces and moments on neck joints along with any head -borne mass. These low level tasks clearly overlap with the...and whole missions. The result is a comprehensive model of tasks and associated physical demands from which one can estimate the accumulative neck ...Griffon Helicopter aircrew (Pilots and Flight Engineers) reported neck pain particularly when wearing Night Vision Goggles (NVGs) (Forde et al. , 2011

  11. Mixture Distributions for Modeling Lead Time Demand in Coordinated Supply Chains

    DTIC Science & Technology

    2014-05-01

    different sets of assump- tions, e.g. a vendor - managed inventory model; improving the efficiency of the solution algorithm. 33 ...Institute of Technology AFCEA Acquisition Research Symposium — May 2014 ∗Support from grant N00244-13-1-0014 to VMI Research Laboratories, Inc. from the...size Q from the supplier when its inventory level drops below reorder point R. Supplier Buyer Inventory Order Demand (Random) • The supplier receives

  12. Modelling the energy demands of aerobic and anaerobic membrane bioreactors for wastewater treatment.

    PubMed

    Martin, I; Pidou, M; Soares, A; Judd, S; Jefferson, B

    2011-07-01

    A modelling study has been developed in which the energy requirements of aerobic and anaerobic membrane bioreactors (MBRs) are assessed in order to compare these two wastewater treatment technologies. The model took into consideration the aeration required for biological oxidation in aerobic MBRs (AeMBRs), the energy recovery from methane production in anaerobic MBRs (AnMBRs) and the energy demands of operating submerged and sidestream membrane configurations. Aeration and membrane energy demands were estimated based on previously developed modelling studies populated with operational data from the literature. Given the difference in sludge production between aerobic and anaerobic systems, the model was benchmarked by assuming high sludge retention times or complete retention of solids in both AeMBRs and AnMBRs. Analysis of biogas production in AnMBRs revealed that the heat required to achieve mesophilic temperatures (35 degrees C) in the reactor was only possible with influent wastewater strengths above 4-5 g COD L(-1). The general trend of the submerged configuration, which is less energy intensive than the sidestream configuration in aerobic systems, was not observed in AnMBRs, mainly due to the wide variation in gas demand utilized in anaerobic systems. Compared to AeMBRs, for which the energy requirements were estimated to approach 2 kWh m(-3) (influent up to 1 g COD L(-1)), the energy demands associated with fouling control in AnMBRs were lower (0.80 kWh m(-3) for influent of 1.14 g COD L(-1)), although due to the low fluxes reported in the literature capital costs associated with membrane material would be three times higher than this.

  13. 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.

  14. 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.

  15. 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.

  16. Longitudinal Mediation Modeling of Unhealthy Behaviors as Mediators between Workplace Demands/Support and Depressive Symptoms

    PubMed Central

    Magnusson Hanson, Linda L.; Peristera, Paraskevi; Chungkham, Holendro Singh; Westerlund, Hugo

    2016-01-01

    Lifestyle has been regarded as a key pathway through which adverse psychosocial working characteristics can give rise to long-term health problems. The purpose of this study was to estimate the indirect/mediated effect of health behaviors in the longitudinal work characteristics-depression relationship. The analyses were based on the Swedish Longitudinal Occupational Survey of Health, including 3706 working participants with repeat survey measures on four occasions (2008, 2010, 2012 and 2014). Psychosocial work characteristics including demands and social support were analyzed in relation to depressive symptoms. Autoregressive longitudinal mediation models using structural equation modeling were used to estimate the intermediate effects of unhealthy behaviors including current smoking, excessive alcohol consumption, unhealthy diet and physical inactivity. Both workplace demands and social support were related to later depressive symptoms. In bivariate models we found no significant paths from workplace demands to health behaviors, but two out of three significant time-specific paths from workplace support to excessive drinking and from excessive drinking to depressive symptoms. Social support was also associated with subsequent unhealthy diet, and one path from unhealthy diet to depressive symptoms was found. However, despite indications of certain longitudinal relationships between psychosocial working conditions and health behaviors as well as between health behaviors and depressive symptoms, no significant intermediate effects were found (p>0.05). We conclude that changes in unhealthy behaviors over a period of two years are unlikely to act as strong intermediaries in the longitudinal relationship between job demands and depressive symptoms and between social support and depressive symptoms. PMID:28036376

  17. Longitudinal Mediation Modeling of Unhealthy Behaviors as Mediators between Workplace Demands/Support and Depressive Symptoms.

    PubMed

    Magnusson Hanson, Linda L; Peristera, Paraskevi; Chungkham, Holendro Singh; Westerlund, Hugo

    2016-01-01

    Lifestyle has been regarded as a key pathway through which adverse psychosocial working characteristics can give rise to long-term health problems. The purpose of this study was to estimate the indirect/mediated effect of health behaviors in the longitudinal work characteristics-depression relationship. The analyses were based on the Swedish Longitudinal Occupational Survey of Health, including 3706 working participants with repeat survey measures on four occasions (2008, 2010, 2012 and 2014). Psychosocial work characteristics including demands and social support were analyzed in relation to depressive symptoms. Autoregressive longitudinal mediation models using structural equation modeling were used to estimate the intermediate effects of unhealthy behaviors including current smoking, excessive alcohol consumption, unhealthy diet and physical inactivity. Both workplace demands and social support were related to later depressive symptoms. In bivariate models we found no significant paths from workplace demands to health behaviors, but two out of three significant time-specific paths from workplace support to excessive drinking and from excessive drinking to depressive symptoms. Social support was also associated with subsequent unhealthy diet, and one path from unhealthy diet to depressive symptoms was found. However, despite indications of certain longitudinal relationships between psychosocial working conditions and health behaviors as well as between health behaviors and depressive symptoms, no significant intermediate effects were found (p>0.05). We conclude that changes in unhealthy behaviors over a period of two years are unlikely to act as strong intermediaries in the longitudinal relationship between job demands and depressive symptoms and between social support and depressive symptoms.

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

    PubMed

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

    2016-09-01

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

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

    PubMed

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

    2013-11-01

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

  20. 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.

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

    PubMed

    Wang, Jining; Chen, Tingqiang

    2016-01-01

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

  2. 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.

  3. 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.

  4. Renewables for Sustainable Village Power

    SciTech Connect

    Flowers, L.; Baring-Gould, I.; Bianchi, J.; Corbus, D.; Drouilhet, S.; Elliott, D.; Gevorgian, V.; Jimenez, A.; Lilienthal, P.; Newcomb, C.; Taylor, R.

    2000-11-06

    This paper describes the efforts of NREL's Renewables for Sustainable Village Power team to match renewable energy technologies with rural energy needs in the international market. The paper describes the team's activities, updates the lessons learned, and proposes an integrated approach as a model for rural electrification with renewables.

  5. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

    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.

  7. 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.

  8. 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.

  9. Influence of road network and population demand assumptions in evacuation modeling for distant tsunamis

    USGS Publications Warehouse

    Henry, Kevin; Wood, Nathan J.; Frazier, Tim G.

    2017-01-01

    Tsunami evacuation planning in coastal communities is typically focused on local events where at-risk individuals must move on foot in a matter of minutes to safety. Less attention has been placed on distant tsunamis, where evacuations unfold over several hours, are often dominated by vehicle use and are managed by public safety officials. Traditional traffic simulation models focus on estimating clearance times but often overlook the influence of varying population demand, alternative modes, background traffic, shadow evacuation, and traffic management alternatives. These factors are especially important for island communities with limited egress options to safety. We use the coastal community of Balboa Island, California (USA), as a case study to explore the range of potential clearance times prior to wave arrival for a distant tsunami scenario. We use a first-in–first-out queuing simulation environment to estimate variations in clearance times, given varying assumptions of the evacuating population (demand) and the road network over which they evacuate (supply). Results suggest clearance times are less than wave arrival times for a distant tsunami, except when we assume maximum vehicle usage for residents, employees, and tourists for a weekend scenario. A two-lane bridge to the mainland was the primary traffic bottleneck, thereby minimizing the effect of departure times, shadow evacuations, background traffic, boat-based evacuations, and traffic light timing on overall community clearance time. Reducing vehicular demand generally reduced clearance time, whereas improvements to road capacity had mixed results. Finally, failure to recognize non-residential employee and tourist populations in the vehicle demand substantially underestimated clearance time.

  10. 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.

  11. 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.

  12. 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

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

    PubMed Central

    Segal, Leonie; Bolton, Tom

    2009-01-01

    historical 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

  14. 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…

  15. 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…

  16. A Daily Diary Study of Coping in the Context of the Job Demands-Control-Support Model

    ERIC Educational Resources Information Center

    Daniels, Kevin; Harris, Claire

    2005-01-01

    We examined one of the processes thought to underpin Karasek and Theorell's job demands-control-support model (1990). This is that control and support accentuate better well-being by fostering problem-focused coping with work demands. We also examined whether other forms of coping implemented through control and support are related to indicators…

  17. 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.

  18. 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

  19. Modeling the Capacity and Emissions Impacts of Reduced Electricity Demand. Part 1. Methodology and Preliminary Results

    SciTech Connect

    Coughlin, Katie; Shen, Hongxia; Chan, Peter; McDevitt, Brian; Sturges, Andrew

    2013-02-07

    Policies aimed at energy conservation and efficiency have broad environmental and economic impacts. Even if these impacts are relatively small, they may be significant compared to the cost of implementing the policy. Methodologies that quantify the marginal impacts of reduced demand for energy have an important role to play in developing accurate measures of both the benefits and costs of a given policy choice. This report presents a methodology for estimating the impacts of reduced demand for electricity on the electric power sector as a whole. The approach uses the National Energy Modeling System (NEMS), a mid-range energy forecast model developed and maintained by the U.S. Department of Energy, Energy Information Administration (EIA)(DOE EIA 2013). The report is organized as follows: In the rest of this section the traditional NEMS-BT approach is reviewed and an outline of the new reduced form NEMS methodology is presented. Section 2 provides an overview of how the NEMS model works, and describes the set of NEMS-BT runs that are used as input to the reduced form approach. Section 3 presents our NEMS-BT simulation results and post-processing methods. In Section 4 we show how the NEMS-BT output can be generalized to apply to a broader set of end-uses. In Section 5 we disuss the application of this approach to policy analysis, and summarize some of the issues that will be further investigated in Part 2 of this study.

  20. A Method for Formulizing Disaster Evacuation Demand Curves Based on SI Model

    PubMed Central

    Song, Yulei; Yan, Xuedong

    2016-01-01

    The prediction of evacuation demand curves is a crucial step in the disaster evacuation plan making, which directly affects the performance of the disaster evacuation. In this paper, we discuss the factors influencing individual evacuation decision making (whether and when to leave) and summarize them into four kinds: individual characteristics, social influence, geographic location, and warning degree. In the view of social contagion of decision making, a method based on Susceptible-Infective (SI) model is proposed to formulize the disaster evacuation demand curves to address both social influence and other factors’ effects. The disaster event of the “Tianjin Explosions” is used as a case study to illustrate the modeling results influenced by the four factors and perform the sensitivity analyses of the key parameters of the model. Some interesting phenomena are found and discussed, which is meaningful for authorities to make specific evacuation plans. For example, due to the lower social influence in isolated communities, extra actions might be taken to accelerate evacuation process in those communities. PMID:27735875

  1. [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…

  2. 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.

  3. Modeling factors influencing the demand for emergency department services in ontario: a comparison of methods

    PubMed Central

    2011-01-01

    Background Emergency departments are medical treatment facilities, designed to provide episodic care to patients suffering from acute injuries and illnesses as well as patients who are experiencing sporadic flare-ups of underlying chronic medical conditions which require immediate attention. Supply and demand for emergency department services varies across geographic regions and time. Some persons do not rely on the service at all whereas; others use the service on repeated occasions. Issues regarding increased wait times for services and crowding illustrate the need to investigate which factors are associated with increased frequency of emergency department utilization. The evidence from this study can help inform policy makers on the appropriate mix of supply and demand targeted health care policies necessary to ensure that patients receive appropriate health care delivery in an efficient and cost-effective manner. The purpose of this report is to assess those factors resulting in increased demand for emergency department services in Ontario. We assess how utilization rates vary according to the severity of patient presentation in the emergency department. We are specifically interested in the impact that access to primary care physicians has on the demand for emergency department services. Additionally, we wish to investigate these trends using a series of novel regression models for count outcomes which have yet to be employed in the domain of emergency medical research. Methods Data regarding the frequency of emergency department visits for the respondents of Canadian Community Health Survey (CCHS) during our study interval (2003-2005) are obtained from the National Ambulatory Care Reporting System (NACRS). Patients' emergency department utilizations were linked with information from the Canadian Community Health Survey (CCHS) which provides individual level medical, socio-demographic, psychological and behavioral information for investigating predictors of

  4. Evaluation of a static granular bed reactor using a chemical oxygen demand balance and mathematical modeling.

    PubMed

    Lim, Seung Joo; Fox, Peter; Ellis, Timothy G

    2011-06-01

    In order to evaluate the static granular bed reactor (SGBR), a chemical oxygen demand (COD) balance was used along with a mathematical model. The SGBR was operated with an organic loading rate (OLR) ranging from 0.8 to 5.5 kg/m(3) day at 24°C. The average COD removal efficiency was 87.4%, and the removal efficiencies of COD, carbohydrates, and proteins increased with an OLR, while the lipids removal efficiency was not a function of an OLR. From the results of the COD balance, the yield of biomass increased with an OLR. The SGBR was modeled using the general transport equation considering advection, diffusion, and degradation by microorganisms, and the first-order reaction rate constant was 0.0166/day. The simulation results were in excellent agreement with experimental data. In addition, the SGBR model provided mechanistic insight into why the COD removal efficiency in the SGBR is proportional to an OLR.

  5. 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.

  6. Development of a model for activated sludge aeration systems: linking air supply, distribution, and demand.

    PubMed

    Schraa, Oliver; Rieger, Leiv; Alex, Jens

    2017-02-01

    During the design of a water resource recovery facility, it is becoming industry practice to use simulation software to assist with process design. Aeration is one of the key components of the activated sludge process, and is one of the most important aspects of modelling wastewater treatment systems. However, aeration systems are typically not modelled in detail in most wastewater treatment process modelling studies. A comprehensive dynamic aeration system model has been developed that captures both air supply and demand. The model includes sub-models for blowers, pipes, fittings, and valves. An extended diffuser model predicts both oxygen transfer efficiency within an aeration basin and pressure drop across the diffusers. The aeration system model allows engineers to analyse aeration systems as a whole to determine biological air requirements, blower performance, air distribution, control valve impacts, controller design and tuning, and energy costs. This enables engineers to trouble-shoot the entire aeration system including process, equipment and controls. It also allows much more realistic design of these highly complex systems.

  7. Projecting and attributing future changes of evaporative demand over China in CMIP5 climate models

    NASA Astrophysics Data System (ADS)

    Liu, Wenbin; Sun, Fubao

    2017-04-01

    Atmospheric evaporative demand plays a pivotal role in global water and energy budgets and its change is very important for drought monitoring, irrigation scheduling and water resource management under a changing environment. Here, we first projected and attributed future changes of pan evaporation (E_pan), a measurable indictor for atmospheric evaporative demand, over China through a physical- based approach, namely PenPan model, forced with outputs form twelve state-of-the-art Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. An equidistant quantile mapping method was also used to correct the biases in GCMs outputs to reduce uncertainty in〖 E〗_pan projection. The results indicated that the E_panwould increase during the periods 2021-2050 and 2071-2100 relative to the baseline period 1971-2000 under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios, which can mainly be attributed to the projected increase in air temperature and vapour pressure deficit over China. The percentage increase of E_pan is relatively larger in eastern China than that in western China, which is due to the spatially inconsistent increases in air temperature, net radiation, wind speed and vapour pressure deficit over China. The widely reported "pan evaporation paradox" was not well reproduced for the period 1961-2000 in the climate models, before or after bias correction, suggesting discrepancy between observed and modeled trends. With that caveat, we found that the pan evaporation has been projected to increase at a rate of 117 167 mm/yr per K (72 80 mm/yr per K) over China using the multiple GCMs under the RCP4.5 (RCP8.5) scenario with increased greenhouse gases and the associated warming of the climate system. References: Liu W, and Sun F, 2017. Projecting and attributing future changes of evaporative demand over China in CMIP5 climate models, Journal of Hydrometeorology, doi: 10.1175/JHM-D-16-0204.1

  8. 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.

  9. Multi-model projections and uncertainties of irrigation water demand under climate change (Invited)

    NASA Astrophysics Data System (ADS)

    Wada, Y.; Wisser, D.; Eisner, S.; Flörke, M.; Gerten, D.; Haddeland, I.; Hanasaki, N.; Masaki, Y.; Portmann, F. T.; Stacke, T.; Tessler, Z. D.; Schewe, J.

    2013-12-01

    Crop irrigation is responsible for 70% of humanity's water demand. Since the late 1990s, the expansion of irrigated areas has been tapering off, and this trend is expected to continue in the future. Future irrigation water demand (IWD) is, however, subject to large uncertainties due to anticipated climate change. Here, we used a set of seven global hydrological models (GHMs) to quantify the impact of projected global climate change on IWD on currently irrigated areas by the end of this century, and to assess the resulting uncertainties arising from both the GHMs and climate projections. The resulting ensemble projections generally show an increasing trend in future IWD, but the increase varies substantially depending on the degree of global warming and associated regional precipitation changes. Under the highest greenhouse gas emission scenario (RCP8.5), IWD will considerably increase during the summer in the Northern Hemisphere (>20% by 2100) and the present peak IWD is projected to shift one month or more over regions where ≥80% of the global irrigated areas exist and 4 billion people currently live. Uncertainties arising from GHMs and global climate models (GCMs) are large, with GHM uncertainty dominating throughout the century and with GCM uncertainty substantially increasing from the mid-century, indicating the choice of GHM outweighing by far the uncertainty arising from the choice of GCM and associated emission scenario.

  10. 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.

  11. Aggregate supply and demand modeling using GIS methods for the front range urban corridor, Colorado

    NASA Astrophysics Data System (ADS)

    Karakas, Ahmet; Turner, Keith

    2004-07-01

    The combined use of allocation modeling and geographical information system (GIS) technologies for providing quantitative assessments of aggregate supply and demand is evaluated using representative data for the Front Range Urban Corridor (FRUC) in Colorado. The FRUC extends from the Colorado-Wyoming border to south of Colorado Springs, and includes Denver and the major urban growth regions of Colorado. In this area, aggregate demand is high and is increasing in response to population growth. Neighborhood opposition to the establishment of new pits and quarries and the depletion of many deposits are limiting aggregate supplies. Many sources are already covered by urban development or eliminated from production by zoning. Transport of aggregate by rail from distant resources may be required in the future. Two allocation-modeling procedures are tested in this study. Network analysis procedures provided within the ARC/INFO software, are unsatisfactory. Further aggregate allocation modeling used a model specifically designed for this task; a modified version of an existing Colorado School of Mines allocation model allows for more realistic market analyses. This study evaluated four scenarios. The entire region was evaluated with a scenario reflecting the current market and by a second scenario in which some existing suppliers were closed down and new potential suppliers were activated. The conditions within the Denver metropolitan area were studied before and after the introduction of three possible rail-to-truck aggregate distribution centers. GIS techniques are helpful in developing the required database to describe the Front Range Urban Corridor aggregate market conditions. GIS methods allow the digital representation of the regional road network, and the development of a distance matrix relating all suppliers and purchasers.

  12. 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.

  13. 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.

  14. Determination of the periodicity and synchronization of anticipative agent based supply-demand model

    NASA Astrophysics Data System (ADS)

    Škraba, A.; Bren, M.; Kofjač, D.

    2017-02-01

    The paper presents the transformation of cobweb model by including the anticipation about the supply and demand. Developed transformation leads to oscillatory behaviour. The periodic conditions of the model have been analytically determined by the application of z-transform. Periodic solutions of the system are presented in the form of an inverse Farey tree, where the Golden Ratio path could be observed. The table of periodic conditions is given up to period 8. The agent-based system was developed in order to show the possibility of controlling the system by varying the key parameter, which determines the frequency response of agents and their interaction. A note on application in the stock market has been provided.

  15. Effects of Variable Inflationary Conditions on AN Inventory Model with Inflation-Proportional Demand Rate

    NASA Astrophysics Data System (ADS)

    Mirzazadeh, Abolfazl

    2009-08-01

    The inflation rate in the most of the previous researches has been considered constant and well-known over the time horizon, although the future rate of inflation is inherently uncertain and unstable, and is difficult to predict it accurately. Therefore, A time varying inventory model for deteriorating items with allowable shortages is developed in this paper. The inflation rates (internal and external) are time-dependent and demand rate is inflation-proportional. The inventory level is described by differential equations over the time horizon and present value method is used. The numerical example is given to explain the results. Some particular cases, which follow the main problem, will discuss and the results will compare with the main model by using the numerical examples. It has been achieved which shortages increases considerably in comparison with the case of without variable inflationary conditions.

  16. 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

  17. 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

  18. 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

  19. 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

  20. Inbound Call Centers and Emotional Dissonance in the Job Demands - Resources Model.

    PubMed

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

    2016-01-01

    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. 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. 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. 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. 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 practical implications useful both to support

  1. Design of demand side response model in energy internet demonstration park

    NASA Astrophysics Data System (ADS)

    Zhang, Q.; Liu, D. N.

    2017-08-01

    The implementation of demand side response can bring a lot of benefits to the power system, users and society, but there are still many problems in the actual operation. Firstly, this paper analyses the current situation and problems of demand side response. On this basis, this paper analyses the advantages of implementing demand side response in the energy Internet demonstration park. Finally, the paper designs three kinds of feasible demand side response modes in the energy Internet demonstration park.

  2. Model-on-Demand Predictive Control for Nonlinear Hybrid Systems With Application to Adaptive Behavioral Interventions

    PubMed Central

    Nandola, Naresh N.; Rivera, Daniel E.

    2011-01-01

    This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem because model parameters depend on the mode or operating point of the system. The proposed algorithm applies Model-on-Demand (MoD) estimation to generate a local linear approximation of the nonlinear hybrid system at each time step, using a small subset of data selected by an adaptive bandwidth selector. The appeal of the MoD approach lies in the fact that model parameters are estimated based on a current operating point; hence estimation of locations or modes governed by autonomous discrete events is achieved automatically. The local MoD model is then converted into a mixed logical dynamical (MLD) system representation which can be used directly in a model predictive control (MPC) law for hybrid systems using multiple-degree-of-freedom tuning. The effectiveness of the proposed MoD predictive control algorithm for nonlinear hybrid systems is demonstrated on a hypothetical adaptive behavioral intervention problem inspired by Fast Track, a real-life preventive intervention for improving parental function and reducing conduct disorder in at-risk children. Simulation results demonstrate that the proposed algorithm can be useful for adaptive intervention problems exhibiting both nonlinear and hybrid character. PMID:21874087

  3. Analyzing hydrotreated renewable jet fuel (HRJ) feedstock availability using crop simulation modeling

    USDA-ARS?s Scientific Manuscript database

    While hydrotreated renewable jet fuel (HRJ) has been demonstrated for use in commercial and military aviation, a challenge to large-scale adoption is availability of cost competitive feedstocks. Brassica oilseed crops like Brassica napus, B. rapa, B. juncea, B. carinata, Sinapis alba, and Camelina s...

  4. Enzyme catalysis: tool to make and break amygdalin hydrogelators from renewable resources: a delivery model for hydrophobic drugs.

    PubMed

    Vemula, Praveen Kumar; Li, Jun; John, George

    2006-07-12

    We report a novel approach for the controlled delivery of an antiinflammatory, chemopreventive drug by an enzyme-triggered drug release mechanism via the degradation of encapsulated hydrogels. The hydro- and organogelators are synthesized in high yields from renewable resources by using regioselective enzyme catalysis, and a known chemopreventive and antiinflammatory drug, i.e., curcumin, is used for the model study. The release of the drug occurred at physiological temperature, and control of the drug release rate is achieved by manipulating the enzyme concentration and/or temperature. The byproducts formed after the gel degradation were characterized and clearly demonstrated the site specificity of degradation of the gelator by enzyme catalysis. The present approach could have applications in developing cost-effective controlled drug delivery vehicles from renewable resources, with a potential impact on pharmaceutical research and molecular design and delivery strategies.

  5. 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

  6. 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.

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

    PubMed

    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.

  8. 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.

  9. Renewable energy.

    PubMed

    Destouni, Georgia; Frank, Harry

    2010-01-01

    The Energy Committee of the Royal Swedish Academy of Sciences has in a series of projects gathered information and knowledge on renewable energy from various sources, both within and outside the academic world. In this article, we synthesize and summarize some of the main points on renewable energy from the various Energy Committee projects and the Committee's Energy 2050 symposium, regarding energy from water and wind, bioenergy, and solar energy. We further summarize the Energy Committee's scenario estimates of future renewable energy contributions to the global energy system, and other presentations given at the Energy 2050 symposium. In general, international coordination and investment in energy research and development is crucial to enable future reliance on renewable energy sources with minimal fossil fuel use.

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

    NASA Astrophysics Data System (ADS)

    Kanta, L.

    2016-12-01

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

  11. Assessing estimates of evaporative demand in climate models using observed pan evaporation over China

    NASA Astrophysics Data System (ADS)

    Liu, Wenbin; Sun, Fubao

    2016-07-01

    Here we assess estimates of atmospheric evaporative demand over China in 12 state-of-the-art global climate models (GCMs) against observed D20 pan evaporation (Epan) over the period of 1961-2000. To do that, we use an energy-relevant and physical-based approach, namely, PenPan model, to comprehensively evaluate GCM performance with respect to their ability to simulate annual, seasonal, and monthly statistics of Epan (and its radiative and aerodynamic components, Ep,R and Ep,A). The results indicated that most GCMs generally captured the spatial pattern and seasonal cycle of Epan, Ep,R, and Ep,A. However, regional means of annual and monthly Epan, Ep,R, and Ep,A were underestimated by most GCMs mainly due to negatively biased surface air temperature (Ta) and vapor pressure deficit (vpd) outputted/simulated by the GCMs. Overall, the discrepancies among GCMs in estimating the regional statistics (regional means and seasonal cycles) of Ep,A were relatively larger than that of Ep,R, which indicates considerable uncertainties in the calculation of the aerodynamic component of evaporation based on the GCM outputs. Moreover, a few GCMs captured negative trends of regional mean annual and seasonal Epan, Ep,R, and Ep,A well over the period of 1961- 2000, but most showed positive trends. The underestimation of net radiation (Rn) and overestimation of wind speed at 2 m (u2) in most GCMs may, to some extent, accentuate/compensate the negative biases in GCM-estimated annual and seasonal Epan, Ep,R, and Ep,A. The results demonstrate the importance of incorporating observation of pan evaporation and well-validated PenPan model to evaluate GCM performance on atmospheric evaporative demand that is relevant to projections of future drought and regional water-energy budgets.

  12. 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.

  13. An inventory model for deteriorating items with time-dependent demand and time-varying holding cost under partial backlogging

    NASA Astrophysics Data System (ADS)

    Mishra, Vinod Kumar; Singh, Lal Sahab; Kumar, Rakesh

    2013-04-01

    In this paper, we considered a deterministic inventory model with time-dependent demand and time-varying holding cost where deterioration is time proportional. The model considered here allows for shortages, and the demand is partially backlogged. The model is solved analytically by minimizing the total inventory cost. The result is illustrated with numerical example for the model. The model can be applied to optimize the total inventory cost for the business enterprises where both the holding cost and deterioration rate are time dependent.

  14. Watershed modeling of dissolved oxygen and biochemical oxygen demand using a hydrological simulation Fortran program.

    PubMed

    Liu, Zhijun; Kieffer, Janna M; Kingery, William L; Huddleston, David H; Hossain, Faisal

    2007-11-01

    Several inland water bodies in the St. Louis Bay watershed have been identified as being potentially impaired due to low level of dissolved oxygen (DO). In order to calculate the total maximum daily loads (TMDL), a standard watershed model supported by U.S. Environmental Protection Agency, Hydrological Simulation Program Fortran (HSPF), was used to simulate water temperature, DO, and bio-chemical oxygen demand (BOD). Both point and non-point sources of BOD were included in watershed modeling. The developed model was calibrated at two time periods: 1978 to 1986 and 2000 to 2001 with simulated DO closely matched the observed data and captured the seasonal variations. The model represented the general trend and average condition of observed BOD. Water temperature and BOD decay are the major factors that affect DO simulation, whereas nutrient processes, including nitrification, denitrification, and phytoplankton cycle, have slight impacts. The calibrated water quality model provides a representative linkage between the sources of BOD and in-stream DO\\BOD concentrations. The developed input parameters in this research could be extended to similar coastal watersheds for TMDL determination and Best Management Practice (BMP) evaluation.

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  17. 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.

  18. The effect of alternative work arrangements on women's well-being: a demand-control model.

    PubMed

    Kelloway, E K; Gottlieb, B H

    1998-01-01

    The growth of women's participation in the labor force and evidence of the conflict they experience between job and family demands have spurred many employers to introduce alternative work arrangements such as flextime, job sharing, and telecommuting. Drawing on data gained from a sample of women (N = 998) in two large Canadian organizations, this study evaluates two mediational models of the impact of alternative work arrangements on women's stress and family role competence. Specifically, it tests and finds support for the hypotheses that (a) work arrangements involving scheduling flexibility (telecommuting and flextime) promote these aspects of women's well-being by increasing their perceived control over their time, and (b) arrangements involving reduced hours of employment (part-time employment and job sharing) promote well-being by reducing perceived job overload. Discussion of these findings centers on their implications for employed women, their employers, and future research.

  19. Renewal of explosive activity at Vesuvius: models for the expected tephra fallout

    NASA Astrophysics Data System (ADS)

    Macedonio, Giovanni; Pareschi, M. Teresa; Santacroce, Roberto

    1990-06-01

    One of the major problems concerning the assessment of volcanic hazard at Vesuvius is to determine the type and size of the eruptive event that will characterize the volcano when it becomes active once again. During its history, Somma-Vesuvius has exhibited different types of activity, ranging from quiet lava emission to moderate strombolian activity, to catastrophic plinian eruptions. Available data support a behavior model characterized by the increasing size and explosiveness of the eruptions with increasing repose time, as a consequence of a roughly constant periodic supply of deep basic magma to a shallow magma chamber and differentiation and mixing in the chamber. After the A.D. 79 eruption, a homogeneous HK (high potassium) nature of erupted products was reflected by a magma alimentation rate roughly estimated at 1.5-2.0 millions of cubic meters per year. Assuming no major changes have occurred in the feeding system of the volcano after its last eruption in 1944, a volume of 40-70 × 10 6 m 3 magma could be considered presently available for a renewal of activity at Vesuvius. The emission of such a mass of magma during a single eruption would result into the largest event since the highly disruptive 1631 subplinian eruption. Presently, no possibility exists to forecast the eruptive character of such an eruption, and either a "ultrastrombolian" or a "subplinian" case appear equally possible. The latter possibility implies the highest potential hazard. This paper provides the numerical simulations of the main eruptive phenomenon that probably will occur during this "maximum expected event": the fallout of tephra from a high, sustained eruption column. After the initial explosive opening of the vent, the scenario consists of the formation of a high convective column with lee-side fallout of pumice and lithic fragments, accompanied and followed by column collapses generating pyroclastic flows and surges. The column behavior was numerically simulated by using the

  20. Creating pharmacy staffing-to-demand models: predictive tools used at two institutions.

    PubMed

    Krogh, Paul; Ernster, Jason; Knoer, Scott

    2012-09-15

    The creation and implementation of data-driven staffing-to-demand models at two institutions are described. Predictive workload tools provide a guideline for pharmacy managers to adjust staffing needs based on hospital volume metrics. At Abbott Northwestern Hospital, management worked with the department's staff and labor management committee to clearly outline the productivity monitoring system and the process for reducing hours. Reference charts describing the process for reducing hours and a form to track the hours of involuntary reductions for each employee were created to further enhance communication, explain the rationale behind the new process, and promote transparency. The University of Minnesota Medical Center-Fairview, found a strong correlation between measured pharmacy workload and an adjusted census formula. If the daily census and admission report indicate that the adjusted census will provide enough workload for the fully staffed department, no further action is needed. If the census report indicates the adjusted census is less than the breakeven point, staff members are asked to leave work, either voluntarily or involuntarily. The opposite holds true for days when the adjusted census is higher than the breakeven point, at which time additional staff are required to synchronize worked hours with predicted workload. Successful staffing-to- demand models were implemented in two hospital pharmacies. Financial savings, as indicated by decreased labor costs secondary to reduction of staffed shifts, were approximately $42,000 and $45,500 over a three-month period for Abbott Northwestern Hospital and the University of Minnesota Medical Center-Fairview, respectively. Maintenance of 100% productively allowed the departments to continue to replace vacant positions and avoid permanent staff reductions.

  1. The Gamma renewal process as an output of the diffusion leaky integrate-and-fire neuronal model.

    PubMed

    Lansky, Petr; Sacerdote, Laura; Zucca, Cristina

    2016-06-01

    Statistical properties of spike trains as well as other neurophysiological data suggest a number of mathematical models of neurons. These models range from entirely descriptive ones to those deduced from the properties of the real neurons. One of them, the diffusion leaky integrate-and-fire neuronal model, which is based on the Ornstein-Uhlenbeck (OU) stochastic process that is restricted by an absorbing barrier, can describe a wide range of neuronal activity in terms of its parameters. These parameters are readily associated with known physiological mechanisms. The other model is descriptive, Gamma renewal process, and its parameters only reflect the observed experimental data or assumed theoretical properties. Both of these commonly used models are related here. We show under which conditions the Gamma model is an output from the diffusion OU model. In some cases, we can see that the Gamma distribution is unrealistic to be achieved for the employed parameters of the OU process.

  2. 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

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

    PubMed

    Dinh, Thanh; Kim, Younghan

    2016-06-28

    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.

  4. Sensitivity Analysis of the Capacity of Battery and Photovoltaic Generation and Contracted Demand of Purchased Power in a Microgrid

    NASA Astrophysics Data System (ADS)

    Bando, Shigeru; Asano, Hiroshi; Tokumoto, Tsutomu; Tsukada, Tatsuya; Ogata, Takao

    The microgrid concept is being seriously considered as a solution to growing electricity demand. And to increase renewable energy near the demand side, a microgrid that utilizes controllable prime movers such as gas engines to compensate fluctuating demand and output of renewable energy is proposed here. We model the optimal operation planning of a microgrid system for the day ahead based on 30-minute demand data, and we conduct the sensitivity analysis of the battery capacity, contracted electric power demand from a utility grid, and PV capacity on costs. It is effective for annual cost reduction to make the contracted demand as small as possible. And the benefit of combination of PV and gas engine can be gained the most in the case that PV capacity is between 20% and 30% of the peak demand of the microgrid.

  5. 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

    2015-01-01

    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.

  6. 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

  7. 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)

  8. 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).

  9. 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)

  10. 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

  11. [Analysis of burnout and job satisfaction among nurses based on the Job Demand-Resource Model].

    PubMed

    Yom, Young-Hee

    2013-02-01

    The purpose of this study was to examine burnout and job satisfaction among nurses based on Job Demand-Resource Model. A survey using a structured questionnaire was conducted with 464 hospital nurses. Analysis of data was done with both SPSS Win 17.0 for descriptive statistics and AMOS 18.0 for the structural equation model. The hypothetical model yielded the following Chi-square=34.13 (p = <.001), df=6, GFI=.98, AGFI=.92, CFI=.94, RMSR=.02, NFI=.93, IFI=.94 and showed good fit indices. Workload had a direct effect on emotional exhaustion (β = 0.39), whereas supervisor support had direct effects on emotional exhaustion (β = -0.24), depersonalization (β = -0.11), and low personal accomplishment (β = -0.22). Emotional exhaustion (β = -0.42), depersonalization (β = -0.11) and low personal accomplishment (β = -0.36) had significant direct effects on job satisfaction. The results suggest that nurses' workload should be decreased and supervisor's support should be increased in order to retain nurses. Further study with a longitudinal design is necessary.

  12. 77 FR 40404 - Agency Information Collection Activities: Requests for Comments; Clearance of Renewed Approval of...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-09

    ... of Renewed Approval of Information Collection: Operating Requirements: Commuter and On Demand... . SUPPLEMENTARY INFORMATION: OMB Control Number: 2120-0039. Title: Operating Requirements: Commuter and On Demand...

  13. 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... INFORMATION: OMB Control Number: 2120-0039. Title: Operating Requirements: Commuter and On Demand Operations...

  14. Field Testing and Modeling of Supermarket Refrigeration Systems as a Demand Response Resource

    SciTech Connect

    Deru, Michael; Hirsch, Adam; Clark, Jordan; Anthony, Jamie

    2016-08-26

    Supermarkets offer a substantial demand response (DR) resource because of their high energy intensity and use patterns; however, refrigeration as the largest load has been challenging to access. Previous work has analyzed supermarket DR using heating, ventilating, and air conditioning; lighting; and anti-sweat heaters. This project evaluated and quantified the DR potential inherent in supermarket refrigeration systems in the Bonneville Power Administration service territory. DR events were carried out and results measured in an operational 45,590-ft2 supermarket located in Hillsboro, Oregon. Key results from the project include the rate of temperature increase in freezer reach-in cases and walk-ins when refrigeration is suspended, the load shed amount for DR tests, and the development of calibrated models to quantify available DR resources. Simulations showed that demand savings of 15 to 20 kilowatts (kW) are available for 1.5 hours for a typical store without precooling and for about 2.5 hours with precooling using only the low-temperature, non-ice cream cases. This represents an aggregated potential of 20 megawatts within BPA's service territory. Inability to shed loads for medium-temperature (MT) products because of the tighter temperature requirements is a significant barrier to realizing larger DR for supermarkets. Store owners are reluctant to allow MT case set point changes, and laboratory tests of MT case DR strategies are needed so that owners become comfortable testing, and implementing, MT case DR. The next-largest barrier is the lack of proper controls in most supermarket displays over ancillary equipment, such as anti-sweat heaters, lights, and fans.

  15. 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.

  16. 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.

  17. 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

  18. Gender differences in a resources-demands model in the general population.

    PubMed

    Kocalevent, Rüya-Daniela; Klapp, Burghard F; Albani, Cornelia; Brähler, Elmar

    2014-09-01

    The population-based study examined postulated effects, derived from a resources-demands-model about gender-related aspects of self-efficacy, optimism, chronic stress, and exhaustion. Data acquisition was carried out by a market research institute with a multi-topic questionnaire in the general population (N = 2,552). Instruments administered were the Questionnaire for Self-Efficacy and Optimism, the Trier Inventory for Chronic Stress, and the Chalder-Fatigue-Scale. Households and target persons were selected randomly. The analyses focused on structural equation modeling. There were significant differences in structural relations among the resource paths. In particular, significant gender differences were found with respect to self-efficacy, and among the exhaustion paths, namely in the mental dimension of exhaustion. The observed measures of chronic stress were found to be operating equivalently for both genders. Results suggest that resources play an important role in the understanding of how chronic stress is preceded and may lead to exhaustion in both genders. Personal resources seem to be more expressed by men than by woman, for whom the relation of resources to health is of greater importance than for men.

  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. Community Biological Ammonium Demand: A Conceptual Model for Cyanobacteria Blooms in Eutrophic Lakes.

    PubMed

    Gardner, Wayne S; Newell, Silvia E; McCarthy, Mark J; Hoffman, Daniel K; Lu, Kaijun; Lavrentyev, Peter J; Hellweger, Ferdi L; Wilhelm, Steven W; Liu, Zhanfei; Bruesewitz, Denise A; Paerl, Hans W

    2017-07-18

    Cyanobacterial harmful algal blooms (CyanoHABs) are enhanced by anthropogenic pressures, including excessive nutrient (nitrogen, N, and phosphorus, P) inputs and a warming climate. Severe eutrophication in aquatic systems is often manifested as non-N2-fixing CyanoHABs (e.g., Microcystis spp.), but the biogeochemical relationship between N inputs/dynamics and CyanoHABs needs definition. Community biological ammonium (NH4(+)) demand (CBAD) relates N dynamics to total microbial productivity and NH4(+) deprivation in aquatic systems. A mechanistic conceptual model was constructed by combining nutrient cycling and CBAD observations from a spectrum of lakes to assess N cycling interactions with CyanoHABs. Model predictions were supported with CBAD data from a Microcystis bloom in Maumee Bay, Lake Erie, during summer 2015. Nitrogen compounds are transformed to reduced, more bioavailable forms (e.g., NH4(+) and urea) favored by CyanoHABs. During blooms, algal biomass increases faster than internal NH4(+) regeneration rates, causing high CBAD values. High turnover rates from cell death and remineralization of labile organic matter consume oxygen and enhance denitrification. These processes drive eutrophic systems to NH4(+) limitation or colimitation under warm, shallow conditions and support the need for dual nutrient (N and P) control.

  1. 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…

  2. 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…

  3. 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.

  4. 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

  5. A modeling framework for estimating energy demand and CO{sub 2} emissions from energy intensive industries in India

    SciTech Connect

    Das, A.; Kandpal, T.C.

    1999-08-01

    This paper presents a modeling framework for estimating energy demand and CO{sub 2} emissions from process industries. The model has been used to project the same for four energy-intensive industries--steel, cement, fertilizer, and aluminum--in India, which account for nearly 50% of the energy consumed in the industrial sector.

  6. 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.

  7. The Effect of Job Demand-Control-Social Support Model on Nurses' Job Satisfaction in Specialized Teaching Hospitals, Ethiopia.

    PubMed

    Negussie, Nebiat; Kaur, Geetinder

    2016-07-01

    The job demand-control-social support model has been widely studied in western countries but has not been theoretically addressed on health workers of sub-Saharan African countries. Therefore, this study investigates the relationship between Job Demand-Control-Support Model and job satisfaction in specialized teaching hospitals in Ethiopia. A cross-sectional survey was conducted from September 2014 to May 2015 in three public specialized teaching hospitals in Ethiopia. Among 1371 nurses, 360 were selected as sample. Data was collected using Job Content Questionnaire and Job Satisfaction Survey Questionnaire. After the data was collected, it was analyzed using SPSS version16.0 statistical software. The results were analyzed using of descriptive statistics followed by inferential statistics on the variables. The result revealed that control variables (gender, age, educational qualification, and work experience) accounted for a significant increment explaining 2.1 percent of the variance in job satisfaction. Job demand and social support together explained 24.5 percent of job satisfaction. Job demand(β=-0.152; p<0.01) had significant but negative relationship with job satisfaction and social support (β=0.458; p<0.01) had significant and positive relationship with job satisfaction. On the other hand, job control (β=0.042; p>0.05) did not have a significant relationship with job satisfaction. Furthermore, there was no straight three-way interaction effect among job demand, job control and social support (β=0.05, p>0.05). Job demand and social support are related to nurses' job satisfaction, but job control neither related to nor moderated the relationship between job demands and job satisfaction. Furthermore, there was no joint three-way interaction effect among job demand, job control and social support.

  8. A PLANNING MODEL USING FUZZY LINEAR PROGRAMMING FOR REPLACEMENT OF WATER DISTRIBUTION SYSTEM CONSIDERING UNCERTAINTY OF FUTURE WATER DEMAND

    NASA Astrophysics Data System (ADS)

    Mori, Masayuki; Inakazu, Toyono; Koizumi, Akira; Watanabe, Haruhiko; Arai, Yasuhiro; Nishizawa, Tsunehiko

    The purpose of this study is to propose an economical and steady planning model of long-term replacement project on water distribution system to co nsider uncertainty of water demand in future. For economical efficiency as the first objective, the model deals with minimization of expected value of total cost in a planning period. Assuming that uncertainty of future water demand appears as width of estimated cost variation, the second objective is minimization of total cost width. Two LP (Linear Programming) models are defined for the first and the second objectives respectively. Successively, we propose a Fuzzy LP model with two objectives combining each characteristic of the two models. Case study demonstrates that the proposed model has advantage achieving balance of these two objectives well over the two models, and usefulness of the proposed one is confirmed. Furthermore, through comparison of produced plans by the three models, meanings of both economic efficiency and steadiness in the pipeline replacement planning are considered.

  9. 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.

  10. 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

  11. Self-adaptive prediction of cloud resource demands using ensemble model and subtractive-fuzzy clustering based fuzzy neural network.

    PubMed

    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.

  12. 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.

  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. 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…

  15. Modeling and clustering water demand patterns from real-world smart meter data

    NASA Astrophysics Data System (ADS)

    Cheifetz, Nicolas; Noumir, Zineb; Samé, Allou; Sandraz, Anne-Claire; Féliers, Cédric; Heim, Véronique

    2017-08-01

    Nowadays, drinking water utilities need an acute comprehension of the water demand on their distribution network, in order to efficiently operate the optimization of resources, manage billing and propose new customer services. With the emergence of smart grids, based on automated meter reading (AMR), a better understanding of the consumption modes is now accessible for smart cities with more granularities. In this context, this paper evaluates a novel methodology for identifying relevant usage profiles from the water consumption data produced by smart meters. The methodology is fully data-driven using the consumption time series which are seen as functions or curves observed with an hourly time step. First, a Fourier-based additive time series decomposition model is introduced to extract seasonal patterns from time series. These patterns are intended to represent the customer habits in terms of water consumption. Two functional clustering approaches are then used to classify the extracted seasonal patterns: the functional version of K-means, and the Fourier REgression Mixture (FReMix) model. The K-means approach produces a hard segmentation and K representative prototypes. On the other hand, the FReMix is a generative model and also produces K profiles as well as a soft segmentation based on the posterior probabilities. The proposed approach is applied to a smart grid deployed on the largest water distribution network (WDN) in France. The two clustering strategies are evaluated and compared. Finally, a realistic interpretation of the consumption habits is given for each cluster. The extensive experiments and the qualitative interpretation of the resulting clusters allow one to highlight the effectiveness of the proposed methodology.

  16. Workforce Projections 2010-2020: Annual Supply and Demand Forecasting Models for Physical Therapists Across the United States.

    PubMed

    Landry, Michel D; Hack, Laurita M; Coulson, Elizabeth; Freburger, Janet; Johnson, Michael P; Katz, Richard; Kerwin, Joanne; Smith, Megan H; Wessman, Henry C Bud; Venskus, Diana G; Sinnott, Patricia L; Goldstein, Marc

    2016-01-01

    Health human resources continue to emerge as a critical health policy issue across the United States. The purpose of this study was to develop a strategy for modeling future workforce projections to serve as a basis for analyzing annual supply of and demand for physical therapists across the United States into 2020. A traditional stock-and-flow methodology or model was developed and populated with publicly available data to produce estimates of supply and demand for physical therapists by 2020. Supply was determined by adding the estimated number of physical therapists and the approximation of new graduates to the number of physical therapists who immigrated, minus US graduates who never passed the licensure examination, and an estimated attrition rate in any given year. Demand was determined by using projected US population with health care insurance multiplied by a demand ratio in any given year. The difference between projected supply and demand represented a shortage or surplus of physical therapists. Three separate projection models were developed based on best available data in the years 2011, 2012, and 2013, respectively. Based on these projections, demand for physical therapists in the United States outstrips supply under most assumptions. Workforce projection methodology research is based on assumptions using imperfect data; therefore, the results must be interpreted in terms of overall trends rather than as precise actuarial data-generated absolute numbers from specified forecasting. Outcomes of this projection study provide a foundation for discussion and debate regarding the most effective and efficient ways to influence supply-side variables so as to position physical therapists to meet current and future population demand. Attrition rates or permanent exits out of the profession can have important supply-side effects and appear to have an effect on predicting future shortage or surplus of physical therapists. © 2016 American Physical Therapy

  17. 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…

  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. 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

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

    Treesearch

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

    2010-01-01

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

  1. 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

  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. 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.

  4. 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.

  5. 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

  6. 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.

  7. [Work-related stress according to the Demand-Control Model and Minor Psychic Disorder in nursing workers].

    PubMed

    Urbanetto, Janete de Souza; Magalhães, Maria Cristina Cademartori; Maciel, Vanessa Oreda; Sant'Anna, Viviane Massena; Gustavo, Andréia da Silva; Poli-de-Figueiredo, Carlos Eduardo; Magnago, Tânia Solange Bosi de Souza

    2013-10-01

    This was a cross-sectional study that aimed to assess the association between work-related stress according to the Demand-Control Model, and the occurrence of Minor Psychic Disorder (MPD) in nursing workers. The participants were 335 professionals, out of which 245 were nursing technicians, aged predominantly between 20 and 40 years. Data were collected using the Job Stress Scale and the Self-Reporting Questionnaire-20. The analysis was performed using descriptive and analytical statistics. The prevalence of suspected MPD was 20.6%. Workers classified in the quadrants active job and high strain of the Demand-Control Model presented higher potential for developing MPD compared with those classified in the quadrant low strain. In conclusion, stress affects the mental health of workers and the aspects related to high psychological demands and high control still require further insight in order to understand their influence on the disease processes of nursing workers.

  8. Application of a hurdle negative binomial count data model to demand for bass fishing in the southeastern United States.

    PubMed

    Bilgic, Abdulbaki; Florkowski, Wojciech J

    2007-06-01

    This paper identifies factors that influence the demand for a bass fishing trip taken in the southeastern United States using a hurdle negative binomial count data model. The probability of fishing for a bass is estimated in the first stage and the fishing trip frequency is estimated in the second stage for individuals reporting bass fishing trips in the Southeast. The applied approach allows the decomposition of the effects of factors responsible for the decision to take a trip and the trip number. Calculated partial and total elasticities indicate a highly inelastic demand for the number of fishing trips as trip costs increase. However, the demand can be expected to increase if anglers experience a success measured by the number of caught fish or their size. Benefit estimates based on alternative estimation methods differ substantially, suggesting the need for testing each modeling approach applied in empirical studies.

  9. Endocrinological and psychological responses to job stressors: an experimental test of the job demand--control model.

    PubMed

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

    2011-08-01

    The buffer hypothesis of the Job Demand-Control Model predicts that high levels of job control compensate for the negative effects of high job demands on well-being and health. Several studies have tested this hypothesis, but the results are far from consistent. The objective of this study was to test the buffer hypothesis with respect to psychological (subjective well-being) and physiological (salivary cortisol) indicators of job strain, using an experimental study design. Seventy-seven men and women worked at a simulated computer workplace for more than two hours. Job demands and job control were manipulated in a 2 (job demands: high vs. low)×2 (job control: high vs. low)×7 (time of measurement) study design. Demands were operationalized in terms of workload, and pacing control (self-paced vs. machine-paced) was used as a job control manipulation. As dependent variables, subjective well-being and salivary cortisol were measured at seven time points during the experiment (T1-T7). In line with the buffer hypothesis, high control eliminated the impact of high demands on salivary cortisol responses. The hypothesis was supported by a predicted significant three-way interaction of demands, control and time of measurement (p<.001), qualified by the absence of significant effects of the independent variables at T1 and T2 due to lagged cortisol reactions, and significant two-way interactions of demands and control, as predicted by the model, at the five remaining times of measurement (T3-T7): high demands led to increased cortisol reactions only in the low control condition. In contrast, no main or interaction effects of the independent variables were found for subjective well-being. This discrepancy between physiological and psychological stress reactions might be due to the lack of specificity inherent in measures of subjective well-being, due to lagged psychological reactions, or due to self-report biases in the subjective measures. In sum, this study provides the

  10. 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…

  11. Consequences of increasing bioenergy demand on wood and forests: an application of the global forest products model

    Treesearch

    Joseph Buongiorno; Ronald Raunikar; Shushuai Zhu

    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...

  12. 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…

  13. 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…

  14. 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.

  15. 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.

  16. Extension of the Job Demands-Resources model in the prediction of burnout and engagement among teachers over time.

    PubMed

    Lorente Prieto, Laura; Salanova Soria, Marisa; Martínez Martínez, Isabel; Schaufeli, Wilmar

    2008-08-01

    Our purpose was to extend the Job Demand-Resources Model (Schaufeli & Bakker, 2004) by including personal resources, job demands and job resources to predict burnout (exhaustion, cynicism, depersonalization) and work engagement (vigour and dedication). The sample comprised 274 teachers from 23 secondary schools of the Valencian Community (Spain). Hierarchical multiple regression analyses have revealed: (1) the predictor effect of quantitative overload on exhaustion and dedication at T2, (2) role conflict on cynicism and (3) role ambiguity on dedication. Lastly, the mediating role of burnout and engagement at T2. Practical implications and directions of future research are discussed.

  17. Oxygenate Supply/Demand Balances in the Short-Term Integrated Forecasting Model (Released in the STEO March 1998)

    EIA Publications

    1998-01-01

    The blending of oxygenates, such as fuel ethanol and methyl tertiary butyl ether (MTBE), into motor gasoline has increased dramatically in the last few years because of the oxygenated and reformulated gasoline programs. Because of the significant role oxygenates now have in petroleum product markets, the Short-Term Integrated Forecasting System (STIFS) was revised to include supply and demand balances for fuel ethanol and MTBE. The STIFS model is used for producing forecasts in the Short-Term Energy Outlook. A review of the historical data sources and forecasting methodology for oxygenate production, imports, inventories, and demand is presented in this report.

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

    PubMed

    Baka, Łukasz

    2015-01-01

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

  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. Eastern Renewable Generation Integration Study

    SciTech Connect

    Bloom, Aaron; Townsend, Aaron; Palchak, David; Novacheck, Joshua; King, Jack; Barrows, Clayton; Ibanez, Eduardo; O'Connell, Matthew; Jordan, Gary; Roberts, Billy; Draxl, Caroline; Gruchalla, Kenny

    2016-08-01

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

  1. 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.

  2. 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.

  3. 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.

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

    Treesearch

    H. Ken Cordell; John C. Bergstrom

    1989-01-01

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

  5. 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.

  6. Modeling the current and future capacity of water resources to meet water demands in the Ebro basin

    NASA Astrophysics Data System (ADS)

    Milano, Marianne; Ruelland, Denis; Dezetter, Alain; Fabre, Julie; Ardoin-Bardin, Sandra; Servat, Eric

    2013-09-01

    Worldwide studies have shown that the Mediterranean region is one of the most vulnerable areas to water crisis. The region is characterized by limited and unequally distributed water resources and increasing water demands. The Ebro catchment (85,000 km2, Spain) is representative of this context. Since the late 1970s, a negative trend in river discharge has been observed, attributed to a decrease in mean precipitation, and a rise in mean temperature and in water consumption. Finally, over 230 storage dams regulate river discharge. In this context, an integrated water resources modeling framework was developed to evaluate the current and future capacity of water resources to meet domestic and agricultural water demands as well as environmental flow requirements. The approach was driven by a conceptual rainfall-runoff model generating water supplies and by a demand driven storage dam model. The approach defines current pressures on water resources and evaluates future changes in water allocation in the medium term under climatic and water use scenarios, considering changes in population and in irrigated areas. Currently, water demands in the Ebro catchment are satisfied. In 2050, water resources are projected to decrease by 15-35% during spring and summer, leading to growing competition among users and severe water shortages for irrigated agriculture. This study provides an original approach to identify the most vulnerable regions to water use conflicts. It also highlights the interest of integrated modeling for complete analysis of the ability of water resources to meet water demands in complex change scenarios as a support for decision making.

  7. 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.

  8. 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).

  9. 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…

  10. A Model to Support Synchronization in Multimedia On-Demand Systems.

    ERIC Educational Resources Information Center

    Saiedina, Hossein; Awad, Mahmoud

    1994-01-01

    Describes a proposed Multimedia On-Demand (MMOD) system architecture that will support MMOD network services and will have the ability to solve presentation synchronization problems caused by either transmission line delay or any mismatch between the data transmission rates or the different parts of the system. (Contains nine references.)…

  11. 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…

  12. Handling Demands of Success among Girls and Boys in Primary School: A Conceptual Model

    ERIC Educational Resources Information Center

    Wilhsson, Marie; Svedberg, Petra; Carlsson, Ing-Marie; Högdin, Sara; Nygren, Jens M.

    2017-01-01

    Stress among adolescents in Western societies is becoming an issue of increasing concern, and the global trend of adolescents' health shows a gradual deterioration that is independent of national differences and increases with age. The aim of this study was to explore the main concern of adolescents and about how they cope with demands in everyday…

  13. Mixture Distributions for Modeling Lead Time Demand in Coordinated Supply Chains

    DTIC Science & Technology

    2014-04-30

    Demand in Coordinated Supply Chains Barry R. Cobb—is a professor in the Department of Economics and Business at the Virginia Military Institute ( VMI ...Production Economics, 115, 248–259. Acknowledgements Support from Grant N00244-13-1-0014 to VMI Research Laboratories, Inc. from the Office of the

  14. 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…

  15. 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…

  16. Evaluation of Online, On-Demand Science Professional Development Material Involving Two Different Implementation Models

    ERIC Educational Resources Information Center

    Sherman, Greg; Byers, Al; Rapp, Steve

    2008-01-01

    This report presents pilot-test results for a science professional development program featuring online, on-demand materials developed by the National Science Teachers Association. During the spring 2006 semester, 45 middle school teachers from three different school districts across the United States participated in a professional development…

  17. 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…

  18. 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…

  19. Emotional Demands, Emotional Labour and Occupational Outcomes in School Principals: Modelling the Relationships

    ERIC Educational Resources Information Center

    Maxwell, Aimee; Riley, Philip

    2017-01-01

    Most research into emotional labour is focussed on front-line service staff and health professionals, in short-term interactions. Little exists exploring the emotional labour involved in repeated on-going interactions by educational leaders with key stakeholders. This study explored the relationships between emotional demands, three emotional…

  20. 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…

  1. 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…

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Describing high-dimensional dynamics with low-dimensional piecewise affine models: applications to renewable energy.

    PubMed

    Hirata, Yoshito; Aihara, Kazuyuki

    2012-06-01

    We introduce a low-dimensional description for a high-dimensional system, which is a piecewise affine model whose state space is divided by permutations. We show that the proposed model tends to predict wind speeds and photovoltaic outputs for the time scales from seconds to 100 s better than by global affine models. In addition, computations using the piecewise affine model are much faster than those of usual nonlinear models such as radial basis function models.

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

    PubMed

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

    2015-06-01

    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. 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. 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. 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. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  8. 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.

  9. 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.

  10. 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

  11. An eco-environmental water demand based model for optimising water resources using hybrid genetic simulated annealing algorithms. Part I. Model development.

    PubMed

    Wang, Xiaoling; Sun, Yuefeng; Song, Lingguang; Mei, Chuanshu

    2009-06-01

    We propose here an improved multi-objective optimisation model that considers eco-environmental water demand (EWD) for allocating water resources in a river basin over the long term. The model considers economic, social, and environmental objectives, and it improves on traditional optimisation methods by emphasizing not only the water demand of the artificial ecosystem but also that of the natural ecosystem. Water resource constraints are considered. The hybrid genetic simulated annealing algorithms (HGSAA) technique incorporates a genetic algorithm (GA) and a simulated annealing (SA) algorithm, which have strong local and global searching abilities, in order to solve the highly non-linear model and avoid local and pre-mature convergence. In the method, the water demands of users in the planning year serve as the basis for long-term optimisation using a forecasting procedure. In this study, the combined forecasting method based on the principle of optimal combination is built to forecast domestic and industrial water demands. The proposed model and method are subsequently used in a companion paper to optimise water allocation in the Haihe River basin in China [An eco-environmental water demand based model for optimising water resources using hybrid genetic simulated annealing algorithms. Part II. Model application and results 90 (8), 2612-2619].

  12. 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.

  13. 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. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

  14. Demand Forecasts Using Process Models and Item Class Parameters: Application of Ancillary Variables

    DTIC Science & Technology

    1976-04-01

    the algorithm is identical but with different k-values.^ Projected savings, over the current Army method of forecasting demands on the wholesale...Objectives PI Investigate untried but theoretically rigorous forecast techniques including methods applicable to items for which a program factor is not...n+1 (2) (3) * . ■ i ii ■ n where - observed value in period (QTR) n In our context, sub-optimal refers to methods which also can "fit" the

  15. POLARIS: Agent-Based Modeling Framework Development and Implementation for Integrated Travel Demand and Network and Operations Simulations

    SciTech Connect

    Auld, Joshua; Hope, Michael; Ley, Hubert; Sokolov, Vadim; Xu, Bo; Zhang, Kuilin

    2016-03-01

    This paper discusses the development of an agent-based modelling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typically done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Initial tests with case studies involving traffic management center impacts on various network events such as accidents, congestion and weather events, show the potential of the system.

  16. 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.

  17. ROS-responsive microspheres for on demand antioxidant therapy in a model of diabetic peripheral arterial disease.

    PubMed

    Poole, Kristin M; Nelson, Christopher E; Joshi, Rucha V; Martin, John R; Gupta, Mukesh K; Haws, Skylar C; Kavanaugh, Taylor E; Skala, Melissa C; Duvall, Craig L

    2015-02-01

    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.

  18. The relationship of the job demands-control-support model with vigor across time: testing for reciprocality.

    PubMed

    Armon, Galit; Shmuel, Samuel; Shirom, Arie

    2012-11-01

    We used a longitudinal design to investigate the hypotheses that the components of the Job Demands-Control-Support model and changes in their levels over time predict subsequent changes in levels of positive affect of vigor over time, and vice versa. Our study was conducted on a sample of adults working in a variety of occupations (N = 909, 68% men) at three points in time (T1, T2, and T3), over a period of about four years, controlling for neuroticism and other potential confounding variables. Job control at T1 and increase in its levels from T1 to T2 predicted an increase from T2 to T3 in the levels of vigor, whereas for social support, only its level at T1 predicted an increase from T2 to T3 in levels of vigor. An increase from T1 to T2 in levels of job demands predicted an increase from T2 to T3 in levels of vigor only for those rated low on neuroticism. Vigor at T1 predicted an increase from T2 to T3 in levels of job control and social support, but not changes from T2 to T3 in levels of job demands. The reciprocal causal relationship between job resources and vigor exists regardless of the demands of the work environment.

  19. 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.

  20. 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…

  1. 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.

  2. 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.

  3. Data Driven Models to Forecast Groundwater Level in Response to Hydro-climatological Conditions and Agricultural Water Demand

    NASA Astrophysics Data System (ADS)

    Amaranto, Alessandro; Corzo Perez, Gerald; Solomatine, Dimitri; Meyer, George; Munoz-Arriola, Francisco

    2017-04-01

    Water table forecasts are important for development of water management plans, especially in areas where groundwater is the main resource for irrigation. This study aims to investigate the capability of different data-driven models to forecast water table levels from one to five months ahead. Five different models (Random Forest, Support Vector Machines, Artificial Neural Networks, Deep Neural Networks and Genetic Programming) are developed to predict the water table level in response to hydro-climatological variables (precipitation, snowmelt and evapotranspiration) in an intensively corn-cultivated area in the Platte River Basin (Nebraska, USA). Corn water demand and precipitation forecasts are also considered as possible inputs to the model. Four error statistics (root mean squared error, coefficient of determination, percent bias and Nash-Sutcliffe index) and two baseline references models (autoregressive and naïve) are used to compare the accuracy of the different models. Results for the case under investigation show that all considered data-driven models predict water table depth with high accuracy up to two months ahead. When the prediction horizon increases, a model using genetic programming is showing better results than the other modelling techniques, in particular when the corn water demand and the forecasted precipitation are included as inputs.

  4. 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).

  5. Modelling supply and demand influences on the use of health care: implications for deriving a needs-based capitation formula.

    PubMed

    Gravelle, Hugh; Sutton, Matthew; Morris, Stephen; Windmeijer, Frank; Leyland, Alastair; Dibben, Chris; Muirhead, Mike

    2003-12-01

    Many health-care systems allocate funding according to measures of need. The utilisation approach for measuring need rests on the assumptions that use of health care is determined by demand and supply and that need is an important element of demand. By estimating utilisation models which allow for supply it is possible to isolate the socio-economic and health characteristics which affect demand. A subset of these variables can then be identified by a combination of judgement and further analysis as needs variables to inform funding allocations. We estimate utilisation models using newly assembled data on admissions to acute hospitals, measures of supply, morbidity and socio-economic characteristics for 8414 small geographical areas in England. We make a number of methodological innovations including deriving additional measures of specific morbidities at small area level from individual level survey data. We compare models with different specifications for the effect of waiting times and provider characteristics, with total, planned and unplanned hospital admissions, and estimated at small area (ward) and primary care organisation (general practice) level. After allowing for waiting times, distance, capacity and the availability of private health care, measures of mortality, self-reported morbidity, low education and low income increase the use of health care. We find evidence of horizontal inequity with respect to ethnicity and employment and suggest a method for reducing its effects when deriving a needs-based allocation formula.

  6. Managerial leadership is associated with employee stress, health, and sickness absence independently of the demand-control-support model.

    PubMed

    Westerlund, Hugo; Nyberg, Anna; Bernin, Peggy; Hyde, Martin; Oxenstierna, Gabriel; Jäppinen, Paavo; Väänänen, Ari; Theorell, Töres

    2010-01-01

    Research on health effects of managerial leadership has only taken established work environment factors into account to a limited extent. We therefore investigated the associations between a measure of Attentive Managerial Leadership (AML), and perceived stress, age-relative self-rated health, and sickness absence due to overstrain/fatigue, adjusting for the dimensions of the Demand-Control-Support model. Blue- and white-collar workers from Finland, Germany and Sweden employed in a multi-national forest industry company (N=12,622). Cross-sectional data on leadership and health from a company-wide survey analysed with logistic regression in different subgroups. AML was associated with perceived stress, age-relative self-rated health, and sickness absence due to overstrain/fatigue after controlling for the Demand-Control-Support model. Lack of AML was significantly associated with a high stress level in all subgroups (OR=1.68-2.67). Associations with age-relative self-rated health and sickness absence due to overstrain/fatigue were weaker, but still significant, and in the expected direction for several of the subgroups studied, suggesting an association between lack of AML and negative health consequences. The study indicates that managerial leadership is associated with employee stress, health, and sickness absence independently of the Demand-Control-Support model and should be considered in future studies of health consequences for employees, and in work environment interventions.

  7. Temporal Resolution in Time Series and Probabilistic Models of Renewable Power Systems

    NASA Astrophysics Data System (ADS)

    Hoevenaars, Eric

    There are two main types of logistical models used for long-term performance prediction of autonomous power systems: time series and probabilistic. Time series models are more common and are more accurate for sizing storage systems because they are able to track the state of charge. However, the computational time is usually greater than for probabilistic models. It is common for time series models to perform 1-year simulations with a 1-hour time step. This is likely because of the limited availability of high resolution data and the increase in computation time with a shorter time step. Computation time is particularly important because these types of models are often used for component size optimization which requires many model runs. This thesis includes a sensitivity analysis examining the effect of the time step on these simulations. The results show that it can be significant, though it depends on the system configuration and site characteristics. Two probabilistic models are developed to estimate the temporal resolution error of a 1-hour simulation: a time series/probabilistic model and a fully probabilistic model. To demonstrate the application of and evaluate the performance of these models, two case studies are analyzed. One is for a typical residential system and one is for a system designed to provide on-site power at an aquaculture site. The results show that the time series/probabilistic model would be a useful tool if accurate distributions of the sub-hour data can be determined. Additionally, the method of cumulant arithmetic is demonstrated to be a useful technique for incorporating multiple non-Gaussian random variables into a probabilistic model, a feature other models such as Hybrid2 currently do not have. The results from the fully probabilistic model showed that some form of autocorrelation is required to account for seasonal and diurnal trends.

  8. Personal renewal.

    PubMed

    Gardner, J W

    1992-10-01

    After John Gardner's presentation on "Self-Renewal" to THE WESTERN JOURNAL OF MEDICINE Editors' Meeting, (*) Joseph Murphy, MD, Special Editor for Wyoming, asked the former Secretary of Health, Education, and Welfare, "Where are you in your life's cycle?" Dr Gardner, who is 80 years old, answered, "When Chief Justice Oliver Wendell Holmes, Jr, was in his 90s, he was asked a similar question and said, ;I'm like a race horse cantering along after the race is over, cooling down.' Well, I'm nowhere near cantering! I'm still in the race, pushing the world." race, pushing the world."John Gardner, who received his undergraduate degree from Stanford and PhD from the University of California, Berkeley, taught at the college level for several years before he joined the Carnegie Foundation. As president of Carnegie Corporation and Carnegie Foundation for the Advancement of Teaching, he began to "push the world" toward education and in 1964 received the country's highest civilian honor, the Presidential Medal of Freedom. He has also pushed it toward political reform by founding Common Cause, toward grass-roots political action by founding the Urban Coalition, toward leadership training by founding the White House Fellows program, and toward volunteerism by founding the Independent Sector (a coalition of for-profit and not-for-profit organizations and foundations). His books, including Excellence, Self-Renewal, No Easy Victories, and On Leadership, have pushed readers to new understanding of themselves and of organizations to higher levels of creativity and energy to get important work done. His current research focuses on discovering and defining the characteristics of healthy, vital communities. His call to "keep on keeping on," indeed, to push the world, leads to constructive change. Active people become effective people, infused with the energy and optimism that good hard work inspires. I think you will find this paper as invigorating to read as it was to hear.

  9. Renewable Fuels Module - NEMS Documentation

    EIA Publications

    2017-01-01

    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.

  10. 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.

  11. Demand Response Availability Profiles for California in the Year 2020

    SciTech Connect

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

    2014-11-01

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

  12. Sustainable use of renewable resources in a stylized social-ecological network model under heterogeneous resource distribution

    NASA Astrophysics Data System (ADS)

    Barfuss, Wolfram; Donges, Jonathan F.; Wiedermann, Marc; Lucht, Wolfgang

    2017-04-01

    Human societies depend on the resources ecosystems provide. Particularly since the last century, human activities have transformed the relationship between nature and society at a global scale. We study this coevolutionary relationship by utilizing a stylized model of private resource use and social learning on an adaptive network. The latter process is based on two social key dynamics beyond economic paradigms: boundedly rational imitation of resource use strategies and homophily in the formation of social network ties. The private and logistically growing resources are harvested with either a sustainable (small) or non-sustainable (large) effort. We show that these social processes can have a profound influence on the environmental state, such as determining whether the private renewable resources collapse from overuse or not. Additionally, we demonstrate that heterogeneously distributed regional resource capacities shift the critical social parameters where this resource extraction system collapses. We make these points to argue that, in more advanced coevolutionary models of the planetary social-ecological system, such socio-cultural phenomena as well as regional resource heterogeneities should receive attention in addition to the processes represented in established Earth system and integrated assessment models.

  13. A Renewable Tissue Resource of Phenotypically Stable, Biologically and Ethnically Diverse, Patient-derived Human Breast Cancer Xenograft (PDX) Models

    PubMed Central

    Zhang, Xiaomei; Claerhout, Sofie; Pratt, Aleix; Dobrolecki, Lacey E.; Petrovic, Ivana; Lai, Qing; Landis, Melissa D.; Wiechmann, Lisa; Schiff, Rachel; Giuliano, Mario; Wong, Helen; Fuqua, Suzanne W.; Contreras, Alejandro; Gutierrez, Carolina; Huang, Jian; Mao, Sufeng; Pavlick, Anne C.; Froehlich, Amber M.; Wu, Meng-Fen; Tsimelzon, Anna; Hilsenbeck, Susan G.; Chen, Edward S.; Zuloaga, Pavel; Shaw, Chad A.; Rimawi, Mothaffar F.; Perou, Charles M.; Mills, Gordon B.; Chang, Jenny C.; Lewis, Michael T.

    2013-01-01

    Breast cancer research is hampered by difficulties in obtaining and studying primary human breast tissue, and by the lack of in vivo preclinical models that reflect patient tumor biology accurately. To overcome these limitations, we propagated a cohort of human breast tumors grown in the epithelium-free mammary fat pad of SCID/Beige and NOD/SCID/IL2γ-receptor null (NSG) mice, under a series of transplant conditions. Both models yielded stably transplantable xenografts at comparably high rates (~21% and ~19%, respectively). Of the conditions tested, xenograft take rate was highest in the presence of a low-dose estradiol pellet. Overall, 32 stably transplantable xenograft lines were established, representing 25 unique patients. Most tumors yielding xenografts were “triple-negative” (ER-PR-HER2+) (n=19). However, we established lines from three ER-PR-HER2+ tumors, one ER+PR-HER2−, one ER+PR+HER2− and one “triple-positive” (ER+PR+HER2+) tumor. Serially passaged xenografts show biological consistency with the tumor of origin, are phenotypically stable across multiple transplant generations at the histologic, transcriptomic, proteomic, and genomic levels, and show comparable treatment responses as those observed clinically. Xenografts representing 12 patients, including two ER+ lines, showed metastasis to the mouse lung. These models thus serve as a renewable, quality-controlled tissue resource for preclinical studies investigating treatment response and metastasis. PMID:23737486

  14. 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

  15. 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.

  16. 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…

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  18. 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.

  19. 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. Copyright © 2013 Elsevier B.V. All rights reserved.

  20. 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.