National Library of Energy BETA

Sample records for demand module forecasts

  1. Commercial Demand Module - NEMS Documentation

    Reports and Publications (EIA)

    2014-01-01

    Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

  2. Module 6 - Metrics, Performance Measurements and Forecasting...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    6 - Metrics, Performance Measurements and Forecasting Module 6 - Metrics, Performance Measurements and Forecasting This module focuses on the metrics and performance measurement ...

  3. Industrial Demand Module - NEMS Documentation

    Reports and Publications (EIA)

    2014-01-01

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

  4. Residential Demand Module - NEMS Documentation

    Reports and Publications (EIA)

    2014-01-01

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

  5. Expert Panel: Forecast Future Demand for Medical Isotopes | Department of

    Energy Savers [EERE]

    Energy Expert Panel: Forecast Future Demand for Medical Isotopes Expert Panel: Forecast Future Demand for Medical Isotopes The Expert Panel has concluded that the Department of Energy and National Institutes of Health must develop the capability to produce a diverse supply of radioisotopes for medical use in quantities sufficient to support research and clinical activities. Such a capability would prevent shortages of isotopes, reduce American dependence on foreign radionuclide sources and

  6. U.S. Regional Demand Forecasts Using NEMS and GIS

    SciTech Connect (OSTI)

    Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

    2005-07-01

    The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

  7. Forecast of transportation energy demand through the year 2010

    SciTech Connect (OSTI)

    Mintz, M.M.; Vyas, A.D.

    1991-04-01

    Since 1979, the Center for Transportation Research (CTR) at Argonne National Laboratory (ANL) has produced baseline projections of US transportation activity and energy demand. These projections and the methodologies used to compute them are documented in a series of reports and research papers. As the lastest in this series of projections, this report documents the assumptions, methodologies, and results of the most recent projection -- termed ANL-90N -- and compares those results with other forecasts from the current literature, as well as with the selection of earlier Argonne forecasts. This current forecast may be used as a baseline against which to analyze trends and evaluate existing and proposed energy conservation programs and as an illustration of how the Transportation Energy and Emission Modeling System (TEEMS) works. (TEEMS links disaggregate models to produce an aggregate forecast of transportation activity, energy use, and emissions). This report and the projections it contains were developed for the US Department of Energy's Office of Transportation Technologies (OTT). The projections are not completely comprehensive. Time and modeling effort have been focused on the major energy consumers -- automobiles, trucks, commercial aircraft, rail and waterborne freight carriers, and pipelines. Because buses, rail passengers services, and general aviation consume relatively little energy, they are projected in the aggregate, as other'' modes, and used primarily as scaling factors. These projections are also limited to direct energy consumption. Projections of indirect energy consumption, such as energy consumed in vehicle and equipment manufacturing, infrastructure, fuel refining, etc., were judged outside the scope of this effort. The document is organized into two complementary sections -- one discussing passenger transportation modes, and the other discussing freight transportation modes. 99 refs., 10 figs., 43 tabs.

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

    SciTech Connect (OSTI)

    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.

  9. Residential Demand Module of the National Energy Modeling System: Model Documentation 2014

    U.S. Energy Information Administration (EIA) Indexed Site

    Residential Demand Module of the National Energy Modeling System: Model Documentation 2014 August 2014 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | NEMS Residential Demand Module Documentation Report 2014 ii This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts

  10. Global GPS Phones Market Size, Segmentation, Demand Forecast...

    Open Energy Info (EERE)

    we deeply analyzed the world's main region market conditions that including the product price, profit, capacity, production, capacity utilization, supply, demand and industry...

  11. Optimization Based Data Mining Approah for Forecasting Real-Time Energy Demand

    SciTech Connect (OSTI)

    Omitaomu, Olufemi A; Li, Xueping; Zhou, Shengchao

    2015-01-01

    The worldwide concern over environmental degradation, increasing pressure on electric utility companies to meet peak energy demand, and the requirement to avoid purchasing power from the real-time energy market are motivating the utility companies to explore new approaches for forecasting energy demand. Until now, most approaches for forecasting energy demand rely on monthly electrical consumption data. The emergence of smart meters data is changing the data space for electric utility companies, and creating opportunities for utility companies to collect and analyze energy consumption data at a much finer temporal resolution of at least 15-minutes interval. While the data granularity provided by smart meters is important, there are still other challenges in forecasting energy demand; these challenges include lack of information about appliances usage and occupants behavior. Consequently, in this paper, we develop an optimization based data mining approach for forecasting real-time energy demand using smart meters data. The objective of our approach is to develop a robust estimation of energy demand without access to these other building and behavior data. Specifically, the forecasting problem is formulated as a quadratic programming problem and solved using the so-called support vector machine (SVM) technique in an online setting. The parameters of the SVM technique are optimized using simulated annealing approach. The proposed approach is applied to hourly smart meters data for several residential customers over several days.

  12. Module 6- Metrics, Performance Measurements and Forecasting

    Broader source: Energy.gov [DOE]

    This module reviews metrics such as cost and schedule variance along with cost and schedule performance indices.

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

    SciTech Connect (OSTI)

    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.

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

    Reports and Publications (EIA)

    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.

  15. Demand forecasting and revenue requirements, with implications for consideration in British Columbia

    SciTech Connect (OSTI)

    Acton, J.P.

    1983-05-01

    This paper was filed as an exhibit on behalf of The Consumers' Association of Canada (B.C. Branch), The Federated Anti-Poverty Groups of B.C., The Sierra Club of Western Canada, and the B.C. Old Age Pensioners' Organization. It was subjected to cross-examination on October 29, 1982, during Phase I of the hearings. The Utilities Commission had designated Phase I for consideration of (1) demand, (2) assets in service, (3) revenue requirements excluding return, and (4) financing and capital requirements. This paper presents a general discussion of the elements of a rate structure and their relationship to the demand for electricity, a systematic review of some 50 empirical studies of the demand for electricity as a function of price and other factors by the three principal classes of customers, and a discussion of the notion of revenue requirements. The paper should be of interest to utility regulators, rate specialists, and forecasters for its review of demand models and to academics concerned with the study of energy demand.

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

    SciTech Connect (OSTI)

    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.

  17. Model Documentation Report: Residential Demand Module of the...

    Gasoline and Diesel Fuel Update (EIA)

    (conditioned square footage) based on current Census Bureau data. * Revision of the benchmarking process that incorporates historical and near-term forecasted values. December 2012...

  18. Residential Demand Module of the National Energy Modeling System...

    Gasoline and Diesel Fuel Update (EIA)

    (conditioned square footage) based on current Census Bureau data. * Revision of the benchmarking process that incorporates historical and near-term forecasted values. * Revision of...

  19. Coal supply/demand, 1980 to 2000. Task 3. Resource applications industrialization system data base. Final review draft. [USA; forecasting 1980 to 2000; sector and regional analysis

    SciTech Connect (OSTI)

    Fournier, W.M.; Hasson, V.

    1980-10-10

    This report is a compilation of data and forecasts resulting from an analysis of the coal market and the factors influencing supply and demand. The analyses performed for the forecasts were made on an end-use-sector basis. The sectors analyzed are electric utility, industry demand for steam coal, industry demand for metallurgical coal, residential/commercial, coal demand for synfuel production, and exports. The purpose is to provide coal production and consumption forecasts that can be used to perform detailed, railroad company-specific coal transportation analyses. To make the data applicable for the subsequent transportation analyses, the forecasts have been made for each end-use sector on a regional basis. The supply regions are: Appalachia, East Interior, West Interior and Gulf, Northern Great Plains, and Mountain. The demand regions are the same as the nine Census Bureau regions. Coal production and consumption in the United States are projected to increase dramatically in the next 20 years due to increasing requirements for energy and the unavailability of other sources of energy to supply a substantial portion of this increase. Coal comprises 85 percent of the US recoverable fossil energy reserves and could be mined to supply the increasing energy demands of the US. The NTPSC study found that the additional traffic demands by 1985 may be met by the railways by the way of improved signalization, shorter block sections, centralized traffic control, and other modernization methods without providing for heavy line capacity works. But by 2000 the incremental traffic on some of the major corridors was projected to increase very significantly and is likely to call for special line capacity works involving heavy investment.

  20. EIA projections of coal supply and demand

    SciTech Connect (OSTI)

    Klein, D.E.

    1989-10-23

    Contents of this report include: EIA projections of coal supply and demand which covers forecasted coal supply and transportation, forecasted coal demand by consuming sector, and forecasted coal demand by the electric utility sector; and policy discussion.

  1. 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 (OSTI)

    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.

  2. 1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    1994-02-01

    This publication documents the load forecast scenarios and assumptions used to prepare BPA`s Whitebook. It is divided into: intoduction, summary of 1993 Whitebook electricity demand forecast, conservation in the load forecast, projection of medium case electricity sales and underlying drivers, residential sector forecast, commercial sector forecast, industrial sector forecast, non-DSI industrial forecast, direct service industry forecast, and irrigation forecast. Four appendices are included: long-term forecasts, LTOUT forecast, rates and fuel price forecasts, and forecast ranges-calculations.

  3. Hawaii demand-side management resource assessment. Final report, Reference Volume 5: The DOETRAN user`s manual; The DOE-2/DBEDT DSM forecasting model interface

    SciTech Connect (OSTI)

    1995-04-01

    The DOETRAN model is a DSM database manager, developed to act as an intermediary between the whole building energy simulation model, DOE-2, and the DBEDT DSM Forecasting Model. DOETRAN accepts output data from DOE-2 and TRANslates that into the format required by the forecasting model. DOETRAN operates in the Windows environment and was developed using the relational database management software, Paradox 5.0 for Windows. It is not necessary to have any knowledge of Paradox to use DOETRAN. DOETRAN utilizes the powerful database manager capabilities of Paradox through a series of customized user-friendly windows displaying buttons and menus with simple and clear functions. The DOETRAN model performs three basic functions, with an optional fourth. The first function is to configure the user`s computer for DOETRAN. The second function is to import DOE-2 files with energy and loadshape data for each building type. The third main function is to then process the data into the forecasting model format. As DOETRAN processes the DOE-2 data, graphs of the total electric monthly impacts for each DSM measure appear, providing the user with a visual means of inspecting DOE-2 data, as well as following program execution. DOETRAN provides three tables for each building type for the forecasting model, one for electric measures, gas measures, and basecases. The optional fourth function provided by DOETRAN is to view graphs of total electric annual impacts by measure. This last option allows a comparative view of how one measure rates against another. A section in this manual is devoted to each of the four functions mentioned above, as well as computer requirements and exiting DOETRAN.

  4. Commercial Sector Demand Module

    Gasoline and Diesel Fuel Update (EIA)

    the State Energy Data System (SEDS) historical commercial sector consumption, applying an additive correction term to ensure that simulated model results correspond to published...

  5. Residential Sector Demand Module

    Gasoline and Diesel Fuel Update (EIA)

    Stoves Geothermal Heat Pump Natural Gas Heat Pump Variables: HSYSSHR 2002-5,eg,b,r Benchmarking Data from Short-Term Energy Outlook Definition: Household energy consumption by...

  6. Solar Forecasting

    Broader source: Energy.gov [DOE]

    On December 7, 2012, DOE announced $8 million to fund two solar projects that are helping utilities and grid operators better forecast when, where, and how much solar power will be produced at U.S....

  7. Demand Reduction

    Broader source: Energy.gov [DOE]

    Grantees may use funds to coordinate with electricity supply companies and utilities to reduce energy demands on their power systems. These demand reduction programs are usually coordinated through...

  8. Heat wave contributes to higher summer electricity demand in...

    U.S. Energy Information Administration (EIA) Indexed Site

    Heat wave contributes to higher summer electricity demand in the Northeast In its new energy forecast, the U.S. Energy Information Administration expects summer retail electricity ...

  9. Modules

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    it's recommended to use the full version number, i.e. instead of doing "module load python" do "module load python2.7.6". This will preserve a record of the software version...

  10. Forecast Change

    U.S. Energy Information Administration (EIA) Indexed Site

    Forecast Change 2011 2012 2013 2014 2015 2016 from 2015 United States Usage (kWh) 3,444 3,354 3,129 3,037 3,153 3,143 -0.3% Price (centskWh) 12.06 12.09 12.58 13.04 12.95 12.96 ...

  11. A Buildings Module for the Stochastic Energy Deployment System

    SciTech Connect (OSTI)

    Lacommare, Kristina S H; Marnay, Chris; Stadler, Michael; Borgeson, Sam; Coffey, Brian; Komiyama, Ryoichi; Lai, Judy

    2008-05-15

    The U.S. Department of Energy (USDOE) is building a new long-range (to 2050) forecasting model for use in budgetary and management applications called the Stochastic Energy Deployment System (SEDS), which explicitly incorporates uncertainty through its development within the Analytica(R) platform of Lumina Decision Systems. SEDS is designed to be a fast running (a few minutes), user-friendly model that analysts can readily run and modify in its entirety through a visual programming interface. Lawrence Berkeley National Laboratory is responsible for implementing the SEDS Buildings Module. The initial Lite version of the module is complete and integrated with a shared code library for modeling demand-side technology choice developed by the National Renewable Energy Laboratory (NREL) and Lumina. The module covers both commercial and residential buildings at the U.S. national level using an econometric forecast of floorspace requirement and a model of building stock turnover as the basis for forecasting overall demand for building services. Although the module is fundamentally an engineering-economic model with technology adoption decisions based on cost and energy performance characteristics of competing technologies, it differs from standard energy forecasting models by including considerations of passive building systems, interactions between technologies (such as internal heat gains), and on-site power generation.

  12. Chinese Oil Demand: Steep Incline Ahead

    U.S. Energy Information Administration (EIA) Indexed Site

    Chinese Oil Demand: Steep Incline Ahead Malcolm Shealy Alacritas, Inc. April 7, 2008 Oil Demand: China, India, Japan, South Korea 0 2 4 6 8 1995 2000 2005 2010 Million Barrels/Day China South Korea Japan India IEA China Oil Forecast 0 2 4 6 8 10 12 14 16 18 2000 2005 2010 2015 2020 2025 2030 Million Barrels/Day WEO 2007 16.3 mbd 12.7 mbd IEA China Oil Forecasts 0 2 4 6 8 10 12 14 16 18 2000 2005 2010 2015 2020 2025 2030 Million Barrels/Day WEO 2007 WEO 2006 WEO 2004 WEO 2002 Vehicle Sales in

  13. Demand Response

    Energy Savers [EERE]

    Demand Response Assessment for Eastern Interconnection Youngsun Baek, Stanton W. Hadley, Rocio Martinez, Gbadebo Oladosu, Alexander M. Smith, Fran Li, Paul Leiby and Russell Lee Prepared for FY12 DOE-CERTS Transmission Reliability R&D Internal Program Review September 20, 2012 2 Managed by UT-Battelle for the U.S. Department of Energy DOE National Laboratory Studies Funded to Support FOA 63 * DOE set aside $20 million from transmission funding for national laboratory studies. * DOE

  14. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01

    This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

  15. travel-demand-modeling

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Demand Modeler, Cambridge Systematics, Tallahassee, FL Abstract ... Travel demand ... Ahmed Mohideen Travel Demand Modeler Cambridge Systematics, Tallahassee, FL Transportation ...

  16. Commercial & Industrial Demand Response

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    & Events Skip navigation links Smart Grid Demand Response Agricultural Residential Demand Response Commercial & Industrial Demand Response Cross-sector Demand Response...

  17. International Oil Supplies and Demands

    SciTech Connect (OSTI)

    Not Available

    1992-04-01

    The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--1990 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

  18. International Oil Supplies and Demands

    SciTech Connect (OSTI)

    Not Available

    1991-09-01

    The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--90 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

  19. Demand for oil and energy in developing countries

    SciTech Connect (OSTI)

    Wolf, C. Jr.; Relles, D.A.; Navarro, J.

    1980-05-01

    How much of the world's oil and energy supply will the non-OPEC less-developed countries (NOLDCs) demand in the next decade. Will their requirements be small and thus fairly insignificant compared with world demand, or large and relatively important. How will world demand be affected by the economic growth of the NOLDCs. In this report, we try to develop some reasonable forecasts of NOLDC energy demands in the next 10 years. Our focus is mainly on the demand for oil, but we also give some attention to the total commercial energy requirements of these countries. We have tried to be explicit about the uncertainties associated with our forecasts, and with the income and price elasticities on which they are based. Finally, we consider the forecasts in terms of their implications for US policies concerning the NOLDCs and suggest areas of future research on NOLDC energy issues.

  20. Short-Term Energy Outlook Model Documentation: Coal Supply, Demand, and Prices

    Reports and Publications (EIA)

    2016-01-01

    The coal module of the Short-Term Energy Outlook (STEO) model is designed to provide forecasts of U.S. production, consumption, imports, exports, inventories, and prices.

  1. Wind Power Forecasting Data

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Operations Call 2012 Retrospective Reports 2012 Retrospective Reports 2011 Smart Grid Wind Integration Wind Integration Initiatives Wind Power Forecasting Wind Projects Email...

  2. Forecasting Water Quality & Biodiversity

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Forecasting Water Quality & Biodiversity March 25, 2015 Cross-cutting Sustainability ... that measure feedstock production, water quality, water quantity, and biodiversity. ...

  3. probabilistic energy production forecasts

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    energy production forecasts - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary ...

  4. Wind Power Forecasting

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    data Presentations BPA Super Forecast Methodology Related Links Near Real-time Wind Animation Meteorological Data Customer Supplied Generation Imbalance Dynamic Transfer Limits...

  5. Using Wikipedia to forecast disease

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Using Wikipedia to forecast disease Using Wikipedia to forecast disease Scientists can now monitor and forecast diseases around the globe more effectively by analyzing views of Wikipedia articles. December 22, 2014 Using Wikipedia to forecast disease Scientists can now monitor and forecast diseases around the globe more effectively by analyzing views of Wikipedia articles. Contact Nancy Ambrosiano Communications Office (505) 667-0471 Email "A global disease-forecasting system will improve

  6. NREL: Transmission Grid Integration - Forecasting

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Forecasting NREL researchers use solar and wind resource assessment and forecasting techniques to develop models that better characterize the potential benefits and impacts of ...

  7. Model documentation, Coal Market Module of the National Energy Modeling System

    SciTech Connect (OSTI)

    1998-01-01

    This report documents the objectives and the conceptual and methodological approach used in the development of the National Energy Modeling System`s (NEMS) Coal Market Module (CMM) used to develop the Annual Energy Outlook 1998 (AEO98). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of CMM`s two submodules. These are the Coal Production Submodule (CPS) and the Coal Distribution Submodule (CDS). CMM provides annual forecasts of prices, production, and consumption of coal for NEMS. In general, the CDS integrates the supply inputs from the CPS to satisfy demands for coal from exogenous demand models. The international area of the CDS forecasts annual world coal trade flows from major supply to major demand regions and provides annual forecasts of US coal exports for input to NEMS. Specifically, the CDS receives minemouth prices produced by the CPS, demand and other exogenous inputs from other NEMS components, and provides delivered coal prices and quantities to the NEMS economic sectors and regions.

  8. Model Documentation Report: Commercial Sector Demand Module...

    Gasoline and Diesel Fuel Update (EIA)

    the State Energy Data System (SEDS) historical commercial sector consumption, applying an additive correction term to ensure that simulated model results correspond to published...

  9. Model Documentation Report: Industrial Sector Demand Module...

    Gasoline and Diesel Fuel Update (EIA)

    factors are multiplicative for all fuels which have values greater than zero and are additive otherwise. The equation for total industrial electricity consumption is below....

  10. Model Documentation Report: Residential Sector Demand Module...

    Gasoline and Diesel Fuel Update (EIA)

    Stoves Geothermal Heat Pump Natural Gas Heat Pump Variables: HSYSSHR 2006,eg,b,r Benchmarking Data from Short-Term Energy Outlook Definition: Household energy consumption by...

  11. Model Documentation Report: Residential Sector Demand Module...

    Gasoline and Diesel Fuel Update (EIA)

    Stoves Geothermal Heat Pump Natural Gas Heat Pump Variables: HSYSSHR 2001,eg,b,r Benchmarking Data from Short-Term Energy Outlook Definition: Household energy consumption by...

  12. Model Documentation Report: Residential Sector Demand Module...

    Gasoline and Diesel Fuel Update (EIA)

    The penetration rate for central air-conditioning is estimated by means of time series analysis of RECS survey data. Water Heating: Solar Water Heaters Market shares for solar...

  13. Renewable Fuels Module - NEMS Documentation

    Reports and Publications (EIA)

    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.

  14. Acquisition Forecast | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Acquisition Forecast Acquisition Forecast Acquisition Forecast It is the policy of the U.S. Department of Energy (DOE) to provide timely information to the public regarding DOE's forecast of future prime contracting opportunities and subcontracting opportunities which are available via the Department's major site and facilities management contractors. This forecast has been expanded to also provide timely status information for ongoing prime contracting actions that are valued in excess of the

  15. The forecast calls for flu

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    The forecast calls for flu Science on the Hill: The forecast calls for flu Using mathematics, computer programs, statistics and information about how disease develops and spreads, a research team at Los Alamos National Laboratory found a way to forecast the flu season and even next week's sickness trends. January 15, 2016 Forecasting flu A team from Los Alamos has developed a method to predict flu outbreaks based in part on influenza-related searches of Wikipedia. The forecast calls for flu

  16. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    1998-07-01

    Issues in Midterm Analysis and Forecasting 1998 (Issues) presents a series of nine papers covering topics in analysis and modeling that underlie the Annual Energy Outlook 1998 (AEO98), as well as other significant issues in midterm energy markets. AEO98, DOE/EIA-0383(98), published in December 1997, presents national forecasts of energy production, demand, imports, and prices through the year 2020 for five cases -- a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The forecasts were prepared by the Energy Information Administration (EIA), using EIA`s National Energy Modeling System (NEMS). The papers included in Issues describe underlying analyses for the projections in AEO98 and the forthcoming Annual Energy Outlook 1999 and for other products of EIA`s Office of Integrated Analysis and Forecasting. Their purpose is to provide public access to analytical work done in preparation for the midterm projections and other unpublished analyses. Specific topics were chosen for their relevance to current energy issues or to highlight modeling activities in NEMS. 59 figs., 44 tabs.

  17. Cross-sector Demand Response

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    & Events Skip navigation links Smart Grid Demand Response Agricultural Residential Demand Response Commercial & Industrial Demand Response Cross-sector Demand Response...

  18. International Oil Supplies and Demands. Volume 2

    SciTech Connect (OSTI)

    Not Available

    1992-04-01

    The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--1990 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world`s dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group`s thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

  19. International Oil Supplies and Demands. Volume 1

    SciTech Connect (OSTI)

    Not Available

    1991-09-01

    The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--90 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world`s dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group`s thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

  20. Residential Demand Sector Data, Commercial Demand Sector Data, Industrial Demand Sector Data - Annual Energy Outlook 2006

    SciTech Connect (OSTI)

    2009-01-18

    Tables describing consumption and prices by sector and census division for 2006 - includes residential demand, commercial demand, and industrial demand

  1. East Coast blizzard cuts into gasoline demand, but home electricity demand rises

    U.S. Energy Information Administration (EIA) Indexed Site

    East Coast blizzard cuts into gasoline demand, but home electricity demand rises U.S. monthly gasoline consumption declined in January, as the big winter storm that shut down many East Coast cities kept people in their homes and off the road. In its new monthly forecast, the U.S. Energy Information Administration said monthly gasoline consumption dropped 230,000 barrels per day in January compared to year-ago levels and that marked the first year-over-year decline in monthly gasoline use since

  2. Behavioral Economics Applied to Energy Demand Analysis: A Foundation

    U.S. Energy Information Administration (EIA) Indexed Site

    Behavioral Economics Applied to Energy Demand Analysis: A Foundation October 2014 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Behavioral Economics Applied to Energy Demand Analysis i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of

  3. Demand Response Analysis Tool

    SciTech Connect (OSTI)

    2012-03-01

    Demand Response Analysis Tool is a software developed at the Lawrence Berkeley National Laboratory. It is initially funded by Southern California Edison. Our goal in developing this tool is to provide an online, useable, with standardized methods, an analysis tool to evaluate demand and demand response performance of commercial and industrial facilities. The tool provides load variability and weather sensitivity analysis capabilities as well as development of various types of baselines. It can be used by researchers, real estate management firms, utilities, or any individuals who are interested in analyzing their demand and demand response capabilities.

  4. Demand Response Analysis Tool

    Energy Science and Technology Software Center (OSTI)

    2012-03-01

    Demand Response Analysis Tool is a software developed at the Lawrence Berkeley National Laboratory. It is initially funded by Southern California Edison. Our goal in developing this tool is to provide an online, useable, with standardized methods, an analysis tool to evaluate demand and demand response performance of commercial and industrial facilities. The tool provides load variability and weather sensitivity analysis capabilities as well as development of various types of baselines. It can be usedmore » by researchers, real estate management firms, utilities, or any individuals who are interested in analyzing their demand and demand response capabilities.« less

  5. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

    Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.

    2010-05-01

    Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.

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

    Reports and Publications (EIA)

    2015-01-01

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

  7. Managing Increased Charging Demand

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Managing Increased Charging Demand Carrie Giles ICF International, Supporting the Workplace Charging Challenge Workplace Charging Challenge Do you already own an EV? Are you ...

  8. Residential Demand Response

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    in-home displays with controllable home area network capabilities and thermal storage devices for home heating. Goals and objectives: Reduce the City's NCP demand above...

  9. Managing Increased Charging Demand

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Managing Increased Charging Demand Carrie Giles ICF International, Supporting the Workplace Charging Challenge Workplace Charging Challenge Do you already own an EV? Are you...

  10. Using Wikipedia to forecast diseases

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Using Wikipedia to forecast diseases Using Wikipedia to forecast diseases Scientists can now monitor and forecast diseases around the globe more effectively by analyzing views of Wikipedia articles. November 13, 2014 Del Valle and her team observe findings from their research on disease patterns from analyzing Wikipedia articles. Del Valle and her team observe findings from their research on disease patterns from analyzing Wikipedia articles. Contact Nancy Ambrosiano Communications Office (505)

  11. Supply Forecast and Analysis (SFA)

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Science Team Leader Oak Ridge National Laboratory DOE Bioenergy Technologies Office (BETO) 2015 Project Peer Review Supply Forecast and Analysis (SFA) 2 | Bioenergy Technologies ...

  12. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01

    This presentation describes the importance of good forecasting for variable generation, the different approaches used by industry, and the importance of validated high-quality data.

  13. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

    Zip: 94965 Region: Bay Area Sector: Services Product: Intelligent Monitoring and Forecasting Services Year Founded: 2010 Website: www.forecastenergy.net Coordinates:...

  14. Energy technologies and their impact on demand

    SciTech Connect (OSTI)

    Drucker, H.

    1995-06-01

    Despite the uncertainties, energy demand forecasts must be made to guide government policies and public and private-sector capital investment programs. Three principles can be identified in considering long-term energy prospects. First energy demand will continue to grow, driven by population growth, economic development, and the current low per capita energy consumption in developing countries. Second, energy technology advancements alone will not solve the problem. Energy-efficient technologies, renewable resource technologies, and advanced electric power technologies will all play a major role but will not be able to keep up with the growth in world energy demand. Third, environmental concerns will limit the energy technology choices. Increasing concern for environmental protection around the world will restrict primarily large, centralized energy supply facilities. The conclusion is that energy system diversity is the only solution. The energy system must be planned with consideration of both supply and demand technologies, must not rely on a single source of energy, must take advantage of all available technologies that are specially suited to unique local conditions, must be built with long-term perspectives, and must be able to adapt to change.

  15. Demand Response Dispatch Tool

    SciTech Connect (OSTI)

    2012-08-31

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

  16. Demand Dispatch-Intelligent

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Demand Dispatch-Intelligent Demand for a More Efficient Grid 10 August 2011 DOE/NETL- DE-FE0004001 U.S. Department of Energy Office of Electricity Delivery and Energy Reliability Prepared by: National Energy Technology Laboratory Disclaimer This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal

  17. Solar Energy Market Forecast | Open Energy Information

    Open Energy Info (EERE)

    Market Forecast Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar Energy Market Forecast AgencyCompany Organization: United States Department of Energy Sector:...

  18. Intermediate future forecasting system

    SciTech Connect (OSTI)

    Gass, S.I.; Murphy, F.H.; Shaw, S.H.

    1983-12-01

    The purposes of the Symposium on the Department of Energy's Intermediate Future Forecasting System (IFFS) were: (1) to present to the energy community details of DOE's new energy market model IFFS; and (2) to have an open forum in which IFFS and its major elements could be reviewed and critiqued by external experts. DOE speakers discussed the total system, its software design, and the modeling aspects of oil and gas supply, refineries, electric utilities, coal, and the energy economy. Invited experts critiqued each of these topics and offered suggestions for modifications and improvement. This volume documents the proceedings (papers and discussion) of the Symposium. Separate abstracts have been prepared for each presentation for inclusion in the Energy Data Base.

  19. Investigating the Correlation Between Wind and Solar Power Forecast Errors in the Western Interconnection: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.; Florita, A.

    2013-05-01

    Wind and solar power generations differ from conventional energy generation because of the variable and uncertain nature of their power output. This variability and uncertainty can have significant impacts on grid operations. Thus, short-term forecasting of wind and solar generation is uniquely helpful for power system operations to balance supply and demand in an electricity system. This paper investigates the correlation between wind and solar power forecasting errors.

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

    Broader source: Energy.gov [DOE]

    Renewable integration studies have evaluated many challenges associated with deploying large amounts of variable wind and solar generation technologies. These studies can evaluate operational impacts associated with variable generation, benefits of improved wind and solar resource forecasting, and trade-offs between institutional changes, including increasing balancing area cooperation and technical changes such as installing new flexible generation. Demand response (DR) resources present a potentially important source of grid flexibility and can aid in integrating variable generation; however, integration analyses have not yet incorporated these resources explicitly into grid simulation models as part of a standard toolkit for resource planners.

  1. Assessment of the possibility of forecasting future natural gas curtailments

    SciTech Connect (OSTI)

    Lemont, S.

    1980-01-01

    This study provides a preliminary assessment of the potential for determining probabilities of future natural-gas-supply interruptions by combining long-range weather forecasts and natural-gas supply/demand projections. An illustrative example which measures the probability of occurrence of heating-season natural-gas curtailments for industrial users in the southeastern US is analyzed. Based on the information on existing long-range weather forecasting techniques and natural gas supply/demand projections enumerated above, especially the high uncertainties involved in weather forecasting and the unavailability of adequate, reliable natural-gas projections that take account of seasonal weather variations and uncertainties in the nation's energy-economic system, it must be concluded that there is little possibility, at the present time, of combining the two to yield useful, believable probabilities of heating-season gas curtailments in a form useful for corporate and government decision makers and planners. Possible remedial actions are suggested that might render such data more useful for the desired purpose in the future. The task may simply require the adequate incorporation of uncertainty and seasonal weather trends into modeling systems and the courage to report projected data, so that realistic natural gas supply/demand scenarios and the probabilities of their occurrence will be available to decision makers during a time when such information is greatly needed.

  2. Science on Tap - Forecasting illness

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Science on Tap - Forecasting illness Science on Tap - Forecasting illness WHEN: Mar 17, 2016 5:30 PM - 7:00 PM WHERE: UnQuarked Wine Room 145 Central Park Square, Los Alamos, New Mexico 87544 USA CONTACT: Linda Anderman (505) 665-9196 CATEGORY: Bradbury INTERNAL: Calendar Login Event Description Mark your calendars for this event held every third Thursday from 5:30 to 7 p.m. A short presentation is followed by a lively discussion on a different subject each month. Forecasting the flu (and other

  3. Demand Response Dispatch Tool

    Energy Science and Technology Software Center (OSTI)

    2012-08-31

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

  4. Residential Electricity Demand in China -- Can Efficiency Reverse the Growth?

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.; Zhou, Nan

    2009-05-18

    The time when energy-related carbon emissions come overwhelmingly from developed countries is coming to a close. China has already overtaken the United States as the world's leading emitter of greenhouse gas emissions. The economic growth that China has experienced is not expected to slow down significantly in the long term, which implies continued massive growth in energy demand. This paper draws on the extensive expertise from the China Energy Group at LBNL on forecasting energy consumption in China, but adds to it by exploring the dynamics of demand growth for electricity in the residential sector -- and the realistic potential for coping with it through efficiency. This paper forecasts ownership growth of each product using econometric modeling, in combination with historical trends in China. The products considered (refrigerators, air conditioners, fans, washing machines, lighting, standby power, space heaters, and water heating) account for 90percent of household electricity consumption in China. Using this method, we determine the trend and dynamics of demandgrowth and its dependence on macroeconomic drivers at a level of detail not accessible by models of a more aggregate nature. In addition, we present scenarios for reducing residential consumption through efficiency measures defined at the product level. The research takes advantage of an analytical framework developed by LBNL (BUENAS) which integrates end use technology parameters into demand forecasting and stock accounting to produce detailed efficiency scenarios, thus allowing for a technologically realistic assessment of efficiency opportunities specifically in the Chinese context.

  5. Acquisition Forecast Download | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Acquisition Forecast Download Acquisition Forecast Download Click on the link to download a copy of the DOE HQ Acquisition Forecast. File Acquisition-Forecast-2016-05-06.xlsx More Documents & Publications Small Business Program Manager Directory EA-1900: Notice of Availability of a Draft Environmental Assessment Small Business Program Manager Directory

  6. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

    Lew, D.; Milligan, M.; Jordan, G.; Piwko, R.

    2011-04-01

    This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.

  7. Demand Response | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Demand Response Demand Response Demand Response Demand response provides an opportunity for consumers to play a significant role in the operation of the electric grid by reducing or shifting their electricity usage during peak periods in response to time-based rates or other forms of financial incentives. Demand response programs are being used by electric system planners and operators as resource options for balancing supply and demand. Such programs can lower the cost of electricity in

  8. Demand Charges | Open Energy Information

    Open Energy Info (EERE)

    Demand Charges Jump to: navigation, search Retrieved from "http:en.openei.orgwindex.php?titleDemandCharges&oldid488967" Feedback Contact needs updating Image needs...

  9. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

    Botterud, A.; Zhi, Z.; Wang, J.; Bessa, R.J.; Keko, H.; Mendes, J.; Sumaili, J.; Miranda, V.

    2011-11-29

    The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supply and demand in ths system. In this report, we analyze how wind power forecasting can serve as an efficient tool toward this end. We discuss the current status of wind power forecasting in U.S. electricity markets and develop several methodologies and modeling tools for the use of wind power forecasting in operational decisions, from the perspectives of the system operator as well as the wind power producer. In particular, we focus on the use of probabilistic forecasts in operational decisions. Driven by increasing prices for fossil fuels and concerns about greenhouse gas (GHG) emissions, wind power, as a renewable and clean source of energy, is rapidly being introduced into the existing electricity supply portfolio in many parts of the world. The U.S. Department of Energy (DOE) has analyzed a scenario in which wind power meets 20% of the U.S. electricity demand by 2030, which means that the U.S. wind power capacity would have to reach more than 300 gigawatts (GW). The European Union is pursuing a target of 20/20/20, which aims to reduce greenhouse gas (GHG) emissions by 20%, increase the amount of renewable energy to 20% of the energy supply, and improve energy efficiency by 20% by 2020 as compared to 1990. Meanwhile, China is the leading country in terms of installed wind capacity, and had 45 GW of installed wind power capacity out of about 200 GW on a global level at the end of 2010. The rapid increase in the penetration of wind power into power systems introduces more variability and uncertainty in the electricity generation portfolio, and these factors are the key challenges when it comes to integrating wind power into the electric power grid. Wind power forecasting (WPF) is an important tool to help efficiently address this challenge, and significant efforts have been invested in developing more accurate wind power forecasts. In this report, we document our work on the use of wind power forecasting in operational decisions.

  10. The Future of U.S. Natural Gas: Supply, Demand & Infrastructure Developments

    Broader source: Energy.gov [DOE]

    This analysis forecasts natural gas supply, demand, and infrastructure developments through 2030 using an inventory and cell model. After introduction of methodology and market approach, the analysis describes expectations of production and supply and demand. This includes how production shifts in North America have shifted Midstream needs, trends in drilling that are leading to more wells with fewer rigs, and processing capacity considerations. Finally, the analysis describing the regionally driven infrastructure requirements and the impact on natural gas price forecasts and regional basis and volatility is presented.

  11. Uncertainty Reduction in Power Generation Forecast Using Coupled...

    Office of Scientific and Technical Information (OSTI)

    quantify the forecast uncertainty by reducing prediction intervals of forecasts. ... means, e.g., using weather-based models, and reduce forecast errors prediction intervals. ...

  12. Wind Forecast Improvement Project Southern Study Area Final Report...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report PDF icon Wind Forecast Improvement Project ...

  13. Picture of the Week: Forecasting Flu

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    3 Forecasting Flu What if we could forecast infectious diseases the same way we forecast the weather, and predict how diseases like Dengue, Typhus or Zika were going to spread? March 6, 2016 flu epidemics modellled using social media Watch the video on YouTube. Forecasting Flu What if we could forecast infectious diseases the same way we forecast the weather, and predict how diseases like Dengue, Typhus or Zika were going to spread? Using real-time data from Wikipedia and social media, Sara del

  14. Economic Rebalancing and Electricity Demand in China

    SciTech Connect (OSTI)

    He, Gang; Lin, Jiang; Yuan, Alexandria

    2015-11-01

    Understanding the relationship between economic growth and electricity use is essential for power systems planning. This need is particularly acute now in China, as the Chinese economy is going through a transition to a more consumption and service oriented economy. This study uses 20 years of provincial data on gross domestic product (GDP) and electricity consumption to examine the relationship between these two factors. We observe a plateauing effect of electricity consumption in the richest provinces, as the electricity demand saturates and the economy develops and moves to a more service-based economy. There is a wide range of forecasts for electricity use in 2030, ranging from 5,308 to 8,292 kWh per capita, using different estimating functions, as well as in existing studies. It is therefore critical to examine more carefully the relationship between electricity use and economic development, as China transitions to a new growth phase that is likely to be less energy and resource intensive. The results of this study suggest that policymakers and power system planners in China should seriously re-evaluate power demand projections and the need for new generation capacity to avoid over-investment that could lead to stranded generation assets.

  15. Expectations models of electric utilities' forecasts: a case study of econometric estimation with influential data points

    SciTech Connect (OSTI)

    Vellutini, R. de A.S.; Mount, T.D.

    1983-01-01

    This study develops an econometric model for explaining how electric utilities revise their forecasts of future electricity demand each year. The model specification is developed from the adaptive expectations hypothesis and it relates forecasted growth rates to actual lagged growth rates of electricity demand. Unlike other studies of the expectation phenomenon, expectations of future demand levels constitute an observable variable and thus can be incorporated explicitly into the model. The data used for the analysis were derived from the published forecasts of the nine National Electric Reliability Councils in the US for the years 1974 to 1980. Three alternative statistical methods are used for estimation purposes: ordinary least-squares, robust regression and a diagnostic analysis to identify influential observations. The results obtained with the first two methods are very similar, but are both inconsistent with the underlying economic logic of the model. The estimated model obtained from the diagnostics approach after deleting two aberrant observations is consistent with economic logic, and supports the hypothesis that the low growth demand experienced immediately following the oil embargo in 1973 were disregarded by the industry for forecasting purposes. The model includes transitory effects associated with the oil embargo that gradually disappear over time, the estimated coefficients for the lagged values of actual growth approach a structure with declining positive weights. The general shape of this asymptotic structure is similar to the findings in many economic applications using distributed lag models.

  16. EIA lowers forecast for summer gasoline prices

    U.S. Energy Information Administration (EIA) Indexed Site

    EIA lowers forecast for summer gasoline prices U.S. gasoline prices are expected to be ... according to the new monthly forecast from the U.S. Energy Information Administration. ...

  17. Demand Response Quick Assessment Tool

    Energy Science and Technology Software Center (OSTI)

    2008-12-01

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

  18. Wind Forecasting Improvement Project | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Forecasting Improvement Project Wind Forecasting Improvement Project October 3, 2011 - 12:12pm Addthis This is an excerpt from the Third Quarter 2011 edition of the Wind Program R&D Newsletter. In July, the Department of Energy launched a $6 million project with the National Oceanic and Atmospheric Administration (NOAA) and private partners to improve wind forecasting. Wind power forecasting allows system operators to anticipate the electrical output of wind plants and adjust the electrical

  19. Taxonomy for Modeling Demand Response Resources

    SciTech Connect (OSTI)

    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.

  20. Irrigation and the demand for electricity. Progress report

    SciTech Connect (OSTI)

    Maddigan, R. J.; Chern, W. S.; Gallagher, C. A.

    1980-03-01

    In order to anticipate the need for generating capacity, utility planners must estimate the future growth in electricity demand. The need for demand forecasts is no less important for the nation's Rural Electric Cooperatives (RECs) than it is for the investor-owned utilities. The RECs serve an historically agrarian region; therefore, the irrigation sector accounts for a significant portion of the western RECs' total demand. A model is developed of the RECs' demand for electricity used in irrigation. The model is a simultaneous equation system which focuses on both the short-run utilization of electricity in irrigation and the long-run determination of the number of irrigators using electricity. Irrigation demand is described by a set of equations in which the quantity of electricity demanded, the average electricity price, the number of irrigation customers, and the ratio of electricity to total energy used for irrigation are endogenous. The structural equations are estimated using pooled state-level data for the period 1961-1977. In light of the model's results, the impact of changes in relative energy prices on irrigation can be examined.

  1. NREL: Resource Assessment and Forecasting Home Page

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    NREL's resource assessment and forecasting research supports industry, government, and academia by providing renewable energy resource measurements, models, maps, and support services. These resources are used to plan and develop renewable energy technologies and support climate change research. Learn more about NREL's resource assessment and forecasting research: Capabilities Facilities Research staff Data and resources. Resource assessment and forecasting research is primarily performed at

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

    SciTech Connect (OSTI)

    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.

  3. Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future

    Broader source: Energy.gov [DOE]

    Freight transportation demand is projected to grow to 27.5 billion tons in 2040, and by extrapolation, to nearly 30.2 billion tons in 2050, requiring ever-greater amounts of energy. This report describes the current and future demand for freight transportation in terms of tons and ton-miles of commodities moved by truck, rail, water, pipeline, and air freight carriers. It outlines the economic, logistics, transportation, and policy and regulatory factors that shape freight demand; the possible trends and 2050 outlook for these factors, and their anticipated effect on freight demand and related energy use.After describing federal policy actions that could influence freight demand, the report then summarizes the available analytical models for forecasting freight demand, and identifies possible areas for future action.

  4. Demand Response Programs, 6. edition

    SciTech Connect (OSTI)

    2007-10-15

    The report provides a look at the past, present, and future state of the market for demand/load response based upon market price signals. It is intended to provide significant value to individuals and companies who are considering participating in demand response programs, energy providers and ISOs interested in offering demand response programs, and consultants and analysts looking for detailed information on demand response technology, applications, and participants. The report offers a look at the current Demand Response environment in the energy industry by: defining what demand response programs are; detailing the evolution of program types over the last 30 years; discussing the key drivers of current initiatives; identifying barriers and keys to success for the programs; discussing the argument against subsidization of demand response; describing the different types of programs that exist including:direct load control, interruptible load, curtailable load, time-of-use, real time pricing, and demand bidding/buyback; providing examples of the different types of programs; examining the enablers of demand response programs; and, providing a look at major demand response programs.

  5. LPG export growth will exceed demand by 2000

    SciTech Connect (OSTI)

    True, W.R.

    1994-08-08

    LPG supplies for international trade will increase sharply through 2000 and begin to outstrip demand by 1997 or 1998. This outlook depends on several production projects proceeding as planned. Leading the way to increased volumes are projects in Algeria, Nigeria, and Australia, among others. Purvin and Gertz, Dallas, projected this trend earlier this year at an international LPG seminar near Houston. Representatives from LPG-supplying countries also presented information to support this view and subsequently supplied more specifics to OGJ in response to questions. This paper discusses this information. Trends in Africa, Australia, North America, and South America are forecast.

  6. Demand Response Technology Roadmap A

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    meetings and workshops convened to develop content for the Demand Response Technology Roadmap. The project team has developed this companion document in the interest of providing...

  7. DemandDirect | Open Energy Information

    Open Energy Info (EERE)

    DemandDirect Place: Woodbury, Connecticut Zip: 6798 Sector: Efficiency, Renewable Energy, Services Product: DemandDirect provides demand response, energy efficiency, load...

  8. Market and energy demand analysis of a US maglev system

    SciTech Connect (OSTI)

    Vyas, A.D.; Rote, D.M.

    1993-06-01

    High-speed magnetically levitated (maglev) vehicles can provide an alternative mode of transportation for intercity travel, particularly for short- and medium-distance trips between 100 to 600 mi (160 and 960 km). The patterns of growth and the underlying factors affecting that growth In the year 2010 are evaluated to determine the magnitude of US Intercity travel that would become the basis for maglev demand. A methodology that is sensitive to the travelers` socioeconomic attributes was developed to Forecast intercity travel. Travel between 78 major metropolitan areas by air and highway modes is projected, and 12 high-density travel corridors are Identified and selected. The potential for a maglev system to substitute for part or that travel is calculated by using a model that estimates the extent of diversion from highway and air to maglev. Energy demand is estimated on the basis of energy usage during acceleration and cruise phases for each corridor and corridor connections.

  9. Market and energy demand analysis of a US maglev system

    SciTech Connect (OSTI)

    Vyas, A.D.; Rote, D.M.

    1993-01-01

    High-speed magnetically levitated (maglev) vehicles can provide an alternative mode of transportation for intercity travel, particularly for short- and medium-distance trips between 100 to 600 mi (160 and 960 km). The patterns of growth and the underlying factors affecting that growth In the year 2010 are evaluated to determine the magnitude of US Intercity travel that would become the basis for maglev demand. A methodology that is sensitive to the travelers' socioeconomic attributes was developed to Forecast intercity travel. Travel between 78 major metropolitan areas by air and highway modes is projected, and 12 high-density travel corridors are Identified and selected. The potential for a maglev system to substitute for part or that travel is calculated by using a model that estimates the extent of diversion from highway and air to maglev. Energy demand is estimated on the basis of energy usage during acceleration and cruise phases for each corridor and corridor connections.

  10. China, India demand cushions prices

    SciTech Connect (OSTI)

    Boyle, M.

    2006-11-15

    Despite the hopes of coal consumers, coal prices did not plummet in 2006 as demand stayed firm. China and India's growing economies, coupled with solid supply-demand fundamentals in North America and Europe, and highly volatile prices for alternatives are likely to keep physical coal prices from wide swings in the coming year.

  11. VERDE Analytic Modules

    Energy Science and Technology Software Center (OSTI)

    2008-01-15

    The Verde Analytic Modules permit the user to ingest openly available data feeds about phenomenology (storm tracks, wind, precipitation, earthquake, wildfires, and similar natural and manmade power grid disruptions and forecast power outages, restoration times, customers outaged, and key facilities that will lose power. Damage areas are predicted using historic damage criteria of the affected area. The modules use a cellular automata approach to estimating the distribution circuits assigned to geo-located substations. Population estimates servedmore » within the service areas are located within 1 km grid cells and converted to customer counts by conversion through demographic estimation of households and commercial firms within the population cells. Restoration times are estimated by agent-based simulation of restoration crews working according to utility published prioritization calibrated by historic performance.« less

  12. Model Documentation Report: Industrial Demand Module of the National...

    Gasoline and Diesel Fuel Update (EIA)

    are multiplicative for all fuels that have consumption values greater than zero and are additive otherwise. The equation for total industrial electricity consumption is below....

  13. Commercial Demand Module of the National Energy Modeling System...

    Gasoline and Diesel Fuel Update (EIA)

    the State Energy Data System (SEDS) historical commercial sector consumption, applying an additive correction term to ensure that simulated model results correspond to published...

  14. Commercial Sector Demand Module of the National Energy Modeling...

    Gasoline and Diesel Fuel Update (EIA)

    the State Energy Data System (SEDS) historical commercial sector consumption, applying an additive correction term to ensure that simulated model results correspond to published...

  15. Transportation Sector Demand Module of the National Energy Modeling...

    Gasoline and Diesel Fuel Update (EIA)

    and historic yearly values for car prices at different production levels by applying an additive adjustment to the price of a gasoline-fueled vehicle. a) Car and Light Truck at...

  16. Model Documentation Report: Industrial Demand Module of the National...

    Gasoline and Diesel Fuel Update (EIA)

    are multiplicative for all fuels that have consumption values greater than zero and are additive otherwise. September 2013 U.S. Energy Information Administration | Model...

  17. Industrial Sector Demand Module of the National Energy Modeling...

    Gasoline and Diesel Fuel Update (EIA)

    factors are multiplicative for all fuels which have values greater than zero and are additive otherwise. ( ) ( ) ( ) ( ) ( ) ( ) - - - fg...

  18. Residential Sector Demand Module of the National Energy Modeling...

    Gasoline and Diesel Fuel Update (EIA)

    Stoves Geothermal Heat Pump Natural Gas Heat Pump Variables: HSYSSHR 2001,eg,b,r Benchmarking Data from Short-Term Energy Outlook Definition: Household energy consumption by...

  19. Commercial Demand Module of the National Energy Modeling System...

    Gasoline and Diesel Fuel Update (EIA)

    - non-PC Wood Renewables 10 Warehouse Misc. End-Use Loads (MELs) Municipal Solid Waste (MSW) 11 U.S. Total Other Hydro 12 Waste Hear Other 13 Other Gaseous Fuels (OGF)...

  20. ARM - CARES - Tracer Forecast for CARES

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    CampaignsCarbonaceous Aerosols and Radiative Effects Study (CARES)Tracer Forecast for CARES Related Links CARES Home AAF Home ARM Data Discovery Browse Data Post-Campaign Data Sets Field Updates CARES Wiki Campaign Images Experiment Planning Proposal Abstract and Related Campaigns Science Plan Operations Plan Measurements Forecasts News News & Press Backgrounder (PDF, 1.45MB) G-1 Aircraft Fact Sheet (PDF, 1.3MB) Contacts Rahul Zaveri, Lead Scientist Tracer Forecasts for CARES This webpage

  1. Demand Response for Ancillary Services

    SciTech Connect (OSTI)

    Alkadi, Nasr E; Starke, Michael R

    2013-01-01

    Many demand response resources are technically capable of providing ancillary services. In some cases, they can provide superior response to generators, as the curtailment of load is typically much faster than ramping thermal and hydropower plants. Analysis and quantification of demand response resources providing ancillary services is necessary to understand the resources economic value and impact on the power system. Methodologies used to study grid integration of variable generation can be adapted to the study of demand response. In the present work, we describe and illustrate a methodology to construct detailed temporal and spatial representations of the demand response resource and to examine how to incorporate those resources into power system models. In addition, the paper outlines ways to evaluate barriers to implementation. We demonstrate how the combination of these three analyses can be used to translate the technical potential for demand response providing ancillary services into a realizable potential.

  2. Automated Demand Response and Commissioning

    SciTech Connect (OSTI)

    Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Bourassa, Norman

    2005-04-01

    This paper describes the results from the second season of research to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve the electric grid reliability and manage electricity costs. Fully-Automated Demand Response does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. We refer to this as Auto-DR. The evaluation of the control and communications must be properly configured and pass through a set of test stages: Readiness, Approval, Price Client/Price Server Communication, Internet Gateway/Internet Relay Communication, Control of Equipment, and DR Shed Effectiveness. New commissioning tests are needed for such systems to improve connecting demand responsive building systems to the electric grid demand response systems.

  3. Solar Forecast Improvement Project | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    NOAA also will provide advanced satellite products. INNOVATIONS NOAA is providing numerical weather prediction (NWP) modeling with new information that will help solar forecasts. ...

  4. Development and Demonstration of Advanced Forecasting, Power...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Management Tools and Best Practices Development and Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices Development ...

  5. NREL: Resource Assessment and Forecasting - Webmaster

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    email address: Your message: Send Message Printable Version Resource Assessment & Forecasting Home Capabilities Facilities Working with Us Research Staff Data & Resources Did...

  6. Forecast and Funding Arrangements - Hanford Site

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Annual Waste Forecast and Funding Arrangements About Us Hanford Site Solid Waste Acceptance Program What's New Acceptance Criteria Acceptance Process Becoming a new Hanford...

  7. Honeywell Demonstrates Automated Demand Response Benefits for...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Honeywell Demonstrates Automated Demand Response Benefits for Utility, Commercial, and Industrial Customers Honeywell Demonstrates Automated Demand Response Benefits for Utility, ...

  8. Demand Response for Ancillary Services

    Broader source: Energy.gov [DOE]

    Methodologies used to study grid integration of variable generation can be adapted to the study of demand response. In the present work, we describe and implement a methodology to construct detailed temporal and spatial representations of demand response resources and to incorporate those resources into power system models. In addition, the paper outlines ways to evaluate barriers to implementation. We demonstrate how the combination of these three analyses can be used to assess economic value of the realizable potential of demand response for ancillary services.

  9. Drivers of Future Energy Demand

    U.S. Energy Information Administration (EIA) Indexed Site

    Drivers of Future Energy Demand in China Asian Energy Demand Outlook 2014 EIA Energy Conference July 14, 2014 Valerie J. Karplus MIT Sloan School of Management 2 www.china.org.cn www.flickr.com www.wikimedia.org globalchange.mit.edu Global Climate Change Human Development Local Pollution Industrial Development & Resource Needs How to balance? 0 500 1000 1500 2000 2500 3000 3500 4000 1981 1991 2001 2011 Non-material Sectors/Other Construction Commercial consumption Residential consumption

  10. Data Collection and Comparison with Forecasted Unit Sales of...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Data Collection and Comparison with Forecasted Unit Sales of Five Lamp Types Data Collection and Comparison with Forecasted Unit Sales of Five Lamp Types PDF icon Data Collection ...

  11. Study forecasts disappearance of conifers due to climate change

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Study forecasts disappearance of conifers due to climate change Study forecasts disappearance of conifers due to climate change New results, reported in a paper released today in ...

  12. The Wind Forecast Improvement Project (WFIP): A Public/Private...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits ... Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits ...

  13. Modeling and forecasting the distribution of Vibrio vulnificus...

    Office of Scientific and Technical Information (OSTI)

    Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay Citation Details In-Document Search Title: Modeling and forecasting the distribution of Vibrio ...

  14. Improving the Accuracy of Solar Forecasting Funding Opportunity...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Improving the Accuracy of Solar Forecasting Funding Opportunity Improving the Accuracy of Solar Forecasting Funding Opportunity Through the Improving the Accuracy of Solar ...

  15. AVLIS: a technical and economic forecast

    SciTech Connect (OSTI)

    Davis, J.I.; Spaeth, M.L.

    1986-01-01

    The AVLIS process has intrinsically large isotopic selectivity and hence high separative capacity per module. The critical components essential to achieving the high production rates represent a small fraction (approx.10%) of the total capital cost of a production facility, and the reference production designs are based on frequent replacement of these components. The specifications for replacement frequencies in a plant are conservative with respect to our expectations; it is reasonable to expect that, as the plant is operated, the specifications will be exceeded and production costs will continue to fall. Major improvements in separator production rates and laser system efficiencies (approx.power) are expected to occur as a natural evolution in component improvements. With respect to the reference design, such improvements have only marginal economic value, but given the exigencies of moving from engineering demonstration to production operations, we continue to pursue these improvements in order to offset any unforeseen cost increases. Thus, our technical and economic forecasts for the AVLIS process remain very positive. The near-term challenge is to obtain stable funding and a commitment to bring the process to full production conditions within the next five years. If the funding and commitment are not maintained, the team will disperse and the know-how will be lost before it can be translated into production operations. The motivation to preserve the option for low-cost AVLIS SWU production is integrally tied to the motivation to maintain a competitive nuclear option. The US industry can certainly survive without AVLIS, but our tradition as technology leader in the industry will certainly be lost.

  16. NREL: Energy Analysis - dGen: Distributed Generation Market Demand Model

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    The Distributed Generation Market Demand (dGen) model 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 dGen model builds on and provides significant advances over NREL's deprecated Solar Deployment System (SolarDS) model. The dGen model can help develop deployment forecasts for distributed resources,

  17. Short-Term Energy Outlook Model Documentation: Petroleum Product Prices Module

    Reports and Publications (EIA)

    2015-01-01

    The petroleum products price module of the Short-Term Energy Outlook (STEO) model is designed to provide U.S. average wholesale and retail price forecasts for motor gasoline, diesel fuel, heating oil, and jet fuel.

  18. Transportation Energy Futures Series: Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future

    SciTech Connect (OSTI)

    Grenzeback, L. R.; Brown, A.; Fischer, M. J.; Hutson, N.; Lamm, C. R.; Pei, Y. L.; Vimmerstedt, L.; Vyas, A. D.; Winebrake, J. J.

    2013-03-01

    Freight transportation demand is projected to grow to 27.5 billion tons in 2040, and to nearly 30.2 billion tons in 2050. This report describes the current and future demand for freight transportation in terms of tons and ton-miles of commodities moved by truck, rail, water, pipeline, and air freight carriers. It outlines the economic, logistics, transportation, and policy and regulatory factors that shape freight demand, the trends and 2050 outlook for these factors, and their anticipated effect on freight demand. After describing federal policy actions that could influence future freight demand, the report then summarizes the capabilities of available analytical models for forecasting freight demand. This is one in a series of reports produced as a result of the Transportation Energy Futures project, a Department of Energy-sponsored multi-agency effort to pinpoint underexplored strategies for reducing GHGs and petroleum dependence related to transportation.

  19. U.S. Coal Supply and Demand

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Coal > U.S. Coal Supply and Demand > U.S. Coal Supply and Demand U.S. Coal Supply and Demand 2010 Review (entire report also available in printer-friendly format ) Previous ...

  20. Projecting Electricity Demand in 2050

    SciTech Connect (OSTI)

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

    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.

  1. Promising Technology: Demand Control Ventilation

    Broader source: Energy.gov [DOE]

    Demand control ventilation (DCV) measures carbon dioxide concentrations in return air or other strategies to measure occupancy, and accurately matches the ventilation requirement. This system reduces ventilation when spaces are vacant or at lower than peak occupancy. When ventilation is reduced, energy savings are accrued because it is not necessary to heat, cool, or dehumidify as much outside air.

  2. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

    Offshore Lubricants Market Forecast Home There are currently no posts in this category. Syndicate...

  3. Metrics for Evaluating the Accuracy of Solar Power Forecasting (Presentation)

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B.; Florita, A.; Lu, S.; Hamann, H.; Banunarayanan, V.

    2013-10-01

    This presentation proposes a suite of metrics for evaluating the performance of solar power forecasting.

  4. Coal Fired Power Generation Market Forecast | OpenEI Community

    Open Energy Info (EERE)

    Coal Fired Power Generation Market Forecast Home There are currently no posts in this category. Syndicate...

  5. Distribution of Wind Power Forecasting Errors from Operational Systems (Presentation)

    SciTech Connect (OSTI)

    Hodge, B. M.; Ela, E.; Milligan, M.

    2011-10-01

    This presentation offers new data and statistical analysis of wind power forecasting errors in operational systems.

  6. Marketing & Driving Demand: Social Media Tools & Strategies ...

    Office of Environmental Management (EM)

    Marketing & Driving Demand: Social Media Tools & Strategies - January 16, 2011 (Text Version) Marketing & Driving Demand: Social Media Tools & Strategies - January 16, 2011 (Text...

  7. Demand Response - Policy | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Demand Response - Policy Demand Response - Policy Since its inception, the Office of Electricity Delivery and Energy Reliability (OE) has been committed to modernizing the nation's ...

  8. Demand Management Institute (DMI) | Open Energy Information

    Open Energy Info (EERE)

    Demand Management Institute (DMI) Jump to: navigation, search Name: Demand Management Institute (DMI) Address: 35 Walnut Street Place: Wellesley, Massachusetts Zip: 02481 Region:...

  9. Generating Demand for Multifamily Building Upgrades | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Generating Demand for Multifamily Building Upgrades Generating Demand for Multifamily Building Upgrades Better Buildings Residential Network Peer Exchange Call Series: Generating...

  10. Text-Alternative Version LED Lighting Forecast

    Office of Energy Efficiency and Renewable Energy (EERE)

    The DOE report Energy Savings Forecast of Solid-State Lighting in General Illumination Applications estimates the energy savings of LED white-light sources over the analysis period of 2013 to 2030....

  11. energy data + forecasting | OpenEI Community

    Open Energy Info (EERE)

    energy data + forecasting Home FRED Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in...

  12. NREL: Resource Assessment and Forecasting - Research Staff

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Research Staff NREL's resource assessment and forecasting research staff provides expertise in renewable energy measurement and instrumentation through NREL's Power Systems Engineering Center. Photo not available Linda Crow - Administrative Associate B.S. Environmental Studies, The Evergreen State College Linda currently works for the Resource Assessment and Forecasting group as their administrative support. She has worked with scientists at the Office of Science at the Air Force Academy and at

  13. The alchemy of demand response: turning demand into supply

    SciTech Connect (OSTI)

    Rochlin, Cliff

    2009-11-15

    Paying customers to refrain from purchasing products they want seems to run counter to the normal operation of markets. Demand response should be interpreted not as a supply-side resource but as a secondary market that attempts to correct the misallocation of electricity among electric users caused by regulated average rate tariffs. In a world with costless metering, the DR solution results in inefficiency as measured by deadweight losses. (author)

  14. Addressing Energy Demand through Demand Response. International Experiences and Practices

    SciTech Connect (OSTI)

    Shen, Bo; Ghatikar, Girish; Ni, Chun Chun; Dudley, Junqiao; Martin, Phil; Wikler, Greg

    2012-06-01

    Demand response (DR) is a load management tool which provides a cost-effective alternative to traditional supply-side solutions to address the growing demand during times of peak electrical load. According to the US Department of Energy (DOE), demand response reflects “changes in electric usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity over time, or to incentive payments designed to induce lower electricity use at times of high wholesale market prices or when system reliability is jeopardized.” 1 The California Energy Commission (CEC) defines DR as “a reduction in customers’ electricity consumption over a given time interval relative to what would otherwise occur in response to a price signal, other financial incentives, or a reliability signal.” 2 This latter definition is perhaps most reflective of how DR is understood and implemented today in countries such as the US, Canada, and Australia where DR is primarily a dispatchable resource responding to signals from utilities, grid operators, and/or load aggregators (or DR providers).

  15. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-01-01

    Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

  16. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-12-31

    Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

  17. Demand for petrochem feedstock to buoy world LPG industry

    SciTech Connect (OSTI)

    Not Available

    1992-05-18

    This paper reports that use of liquefied petroleum gas as petrochemical feedstock will increase worldwide, providing major growth opportunities for LPG producers. World exports of liquefied petroleum gas will increase more slowly than production as producers choose to use LPG locally as chemical feedstock and export in value added forms such as polyethylene. So predicts Poten and Partners Inc., New York. Poten forecasts LPG production in exporting countries will jump to 95 million tons in 2010 from 45 million tons in 1990. However, local and regional demand will climb to 60 million tons/year from 23 million tons/year during the same period. So supplies available for export will rise to 35 million tons in 2010 from 22 million tons in 1990.

  18. NEMS integrating module documentation report

    SciTech Connect (OSTI)

    Not Available

    1993-12-14

    The National Energy Modeling System (NEMS) is a computer modeling system that produces a general equilibrium solution for energy supply and demand in the US energy markets. The model achieves a supply and demand balance in the end-use demand regions, defined as the nine Census Divisions, by solving for the prices of each energy type such that the quantities producers are willing to supply equal the quantities consumers wish to consume. The system reflects market economics, industry structure, and energy policies and regulations that influence market behavior. The NEMS Integrating Module is the central integrating component of a complex modeling system. As such, a thorough understanding of its role in the modeling process can only be achieved by placing it in the proper context with respect to the other modules. To that end, this document provides an overview of the complete NEMS model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

  19. Sensor-based demand controlled ventilation

    SciTech Connect (OSTI)

    De Almeida, A.T.; Fisk, W.J.

    1997-07-01

    In most buildings, occupancy and indoor pollutant emission rates vary with time. With sensor-based demand-controlled ventilation (SBDCV), the rate of ventilation (i.e., rate of outside air supply) also varies with time to compensate for the changes in pollutant generation. In other words, SBDCV involves the application of sensing, feedback and control to modulate ventilation. Compared to ventilation without feedback, SBDCV offers two potential advantages: (1) better control of indoor pollutant concentrations; and (2) lower energy use and peak energy demand. SBDCV has the potential to improve indoor air quality by increasing the rate of ventilation when indoor pollutant generation rates are high and occupants are present. SBDCV can also save energy by decreasing the rate of ventilation when indoor pollutant generation rates are low or occupants are absent. After providing background information on indoor air quality and ventilation, this report provides a relatively comprehensive discussion of SBDCV. Topics covered in the report include basic principles of SBDCV, sensor technologies, technologies for controlling air flow rates, case studies of SBDCV, application of SBDCV to laboratory buildings, and research needs. SBDCV appears to be an increasingly attractive technology option. Based on the review of literature and theoretical considerations, the application of SBDCV has the potential to be cost-effective in applications with the following characteristics: (a) a single or small number of dominant pollutants, so that ventilation sufficient to control the concentration of the dominant pollutants provides effective control of all other pollutants; (b) large buildings or rooms with unpredictable temporally variable occupancy or pollutant emission; and (c) climates with high heating or cooling loads or locations with expensive energy.

  20. Ramp Forecasting Performance from Improved Short-Term Wind Power Forecasting: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Florita, A.; Hodge, B. M.; Freedman, J.

    2014-05-01

    The variable and uncertain nature of wind generation presents a new concern to power system operators. One of the biggest concerns associated with integrating a large amount of wind power into the grid is the ability to handle large ramps in wind power output. Large ramps can significantly influence system economics and reliability, on which power system operators place primary emphasis. The Wind Forecasting Improvement Project (WFIP) was performed to improve wind power forecasts and determine the value of these improvements to grid operators. This paper evaluates the performance of improved short-term wind power ramp forecasting. The study is performed for the Electric Reliability Council of Texas (ERCOT) by comparing the experimental WFIP forecast to the current short-term wind power forecast (STWPF). Four types of significant wind power ramps are employed in the study; these are based on the power change magnitude, direction, and duration. The swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental short-term wind power forecasts improve the accuracy of the wind power ramp forecasting, especially during the summer.

  1. 1994 Solid waste forecast container volume summary

    SciTech Connect (OSTI)

    Templeton, K.J.; Clary, J.L.

    1994-09-01

    This report describes a 30-year forecast of the solid waste volumes by container type. The volumes described are low-level mixed waste (LLMW) and transuranic/transuranic mixed (TRU/TRUM) waste. These volumes and their associated container types will be generated or received at the US Department of Energy Hanford Site for storage, treatment, and disposal at Westinghouse Hanford Company`s Solid Waste Operations Complex (SWOC) during a 30-year period from FY 1994 through FY 2023. The forecast data for the 30-year period indicates that approximately 307,150 m{sup 3} of LLMW and TRU/TRUM waste will be managed by the SWOC. The main container type for this waste is 55-gallon drums, which will be used to ship 36% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of 55-gallon drums is Past Practice Remediation. This waste will be generated by the Environmental Restoration Program during remediation of Hanford`s past practice sites. Although Past Practice Remediation is the primary generator of 55-gallon drums, most waste generators are planning to ship some percentage of their waste in 55-gallon drums. Long-length equipment containers (LECs) are forecasted to contain 32% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of LECs is the Long-Length Equipment waste generator, which is responsible for retrieving contaminated long-length equipment from the tank farms. Boxes are forecasted to contain 21% of the waste. These containers are primarily forecasted for use by the Environmental Restoration Operations--D&D of Surplus Facilities waste generator. This waste generator is responsible for the solid waste generated during decontamination and decommissioning (D&D) of the facilities currently on the Surplus Facilities Program Plan. The remaining LLMW and TRU/TRUM waste volume is planned to be shipped in casks and other miscellaneous containers.

  2. Module Configuration

    DOE Patents [OSTI]

    Oweis, Salah; D'Ussel, Louis; Chagnon, Guy; Zuhowski, Michael; Sack, Tim; Laucournet, Gaullume; Jackson, Edward J.

    2002-06-04

    A stand alone battery module including: (a) a mechanical configuration; (b) a thermal management configuration; (c) an electrical connection configuration; and (d) an electronics configuration. Such a module is fully interchangeable in a battery pack assembly, mechanically, from the thermal management point of view, and electrically. With the same hardware, the module can accommodate different cell sizes and, therefore, can easily have different capacities. The module structure is designed to accommodate the electronics monitoring, protection, and printed wiring assembly boards (PWAs), as well as to allow airflow through the module. A plurality of modules may easily be connected together to form a battery pack. The parts of the module are designed to facilitate their manufacture and assembly.

  3. Industrial end-use forecasting that incorporates DSM and air quality

    SciTech Connect (OSTI)

    Tutt, T.; Flory, J.

    1995-05-01

    The California Energy Commission (CEC) and major enregy utilities in California have generally depended on simple aggregate intensity or economic models to forecast energy use in the process industry sector (which covers large industries employing basic processes to transform raw materials, such as paper mills, glass plants, and cement plants). Two recent trends suggests that the time has come to develop a more disaggregate process industry forecasting model. First, recent efforts to improve air quality, especially by the South Coast Air Quality Management District (SCAQMD), could significantly affect energy use by the process industry by altering the technologies and processes employed in order to reduce emissions. Second, there is a renewed interest in Demand-Side Management (DSM), not only for utility least-cost planning, but also for improving the economic competitiveness and environmental compliance of the pro{minus}cess industries. A disaggregate forecasting model is critical to help the CEC and utilities evaluate both the air quality and DSM impacts on energy use. A crucial obstacle to the development and use of these detailed process industry forecasting models is the lack of good data about disaggregate energy use in the sector. The CEC is nearing completion of a project to begin to overcome this lack of data. The project is testing methds of developing detailed energy use data, collecting an initial database for a large portion of southern California, and providing recommendations and direction for further data collection efforts.

  4. National forecast for geothermal resource exploration and development with techniques for policy analysis and resource assessment

    SciTech Connect (OSTI)

    Cassel, T.A.V.; Shimamoto, G.T.; Amundsen, C.B.; Blair, P.D.; Finan, W.F.; Smith, M.R.; Edeistein, R.H.

    1982-03-31

    The backgrund, structure and use of modern forecasting methods for estimating the future development of geothermal energy in the United States are documented. The forecasting instrument may be divided into two sequential submodels. The first predicts the timing and quality of future geothermal resource discoveries from an underlying resource base. This resource base represents an expansion of the widely-publicized USGS Circular 790. The second submodel forecasts the rate and extent of utilization of geothermal resource discoveries. It is based on the joint investment behavior of resource developers and potential users as statistically determined from extensive industry interviews. It is concluded that geothermal resource development, especially for electric power development, will play an increasingly significant role in meeting US energy demands over the next 2 decades. Depending on the extent of R and D achievements in related areas of geosciences and technology, expected geothermal power development will reach between 7700 and 17300 Mwe by the year 2000. This represents between 8 and 18% of the expected electric energy demand (GWh) in western and northwestern states.

  5. Demand Response - Policy | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Demand Response - Policy Demand Response - Policy Since its inception, the Office of Electricity Delivery and Energy Reliability (OE) has been committed to modernizing the nation's electricity delivery infrastructure to assure consumers a robust, reliable electric power system that meets their increasing demand for energy. OE's mission includes assisting states and regions in developing policies that decrease demand on existing energy infrastructure. Appropriate cost-effective demand response

  6. Forecasting longitudinal changes in oropharyngeal tumor morphology throughout the course of head and neck radiation therapy

    SciTech Connect (OSTI)

    Yock, Adam D.; Kudchadker, Rajat J.; Rao, Arvind; Dong, Lei; Beadle, Beth M.; Garden, Adam S.; Court, Laurence E.

    2014-08-15

    Purpose: To create models that forecast longitudinal trends in changing tumor morphology and to evaluate and compare their predictive potential throughout the course of radiation therapy. Methods: Two morphology feature vectors were used to describe 35 gross tumor volumes (GTVs) throughout the course of intensity-modulated radiation therapy for oropharyngeal tumors. The feature vectors comprised the coordinates of the GTV centroids and a description of GTV shape using either interlandmark distances or a spherical harmonic decomposition of these distances. The change in the morphology feature vector observed at 33 time points throughout the course of treatment was described using static, linear, and mean models. Models were adjusted at 0, 1, 2, 3, or 5 different time points (adjustment points) to improve prediction accuracy. The potential of these models to forecast GTV morphology was evaluated using leave-one-out cross-validation, and the accuracy of the models was compared using Wilcoxon signed-rank tests. Results: Adding a single adjustment point to the static model without any adjustment points decreased the median error in forecasting the position of GTV surface landmarks by the largest amount (1.2 mm). Additional adjustment points further decreased the forecast error by about 0.4 mm each. Selection of the linear model decreased the forecast error for both the distance-based and spherical harmonic morphology descriptors (0.2 mm), while the mean model decreased the forecast error for the distance-based descriptor only (0.2 mm). The magnitude and statistical significance of these improvements decreased with each additional adjustment point, and the effect from model selection was not as large as that from adding the initial points. Conclusions: The authors present models that anticipate longitudinal changes in tumor morphology using various models and model adjustment schemes. The accuracy of these models depended on their form, and the utility of these models includes the characterization of patient-specific response with implications for treatment management and research study design.

  7. Crude oil and alternate energy production forecasts for the twenty-first century: The end of the hydrocarbon era

    SciTech Connect (OSTI)

    Edwards, J.D.

    1997-08-01

    Predictions of production rates and ultimate recovery of crude oil are needed for intelligent planning and timely action to ensure the continuous flow of energy required by the world`s increasing population and expanding economies. Crude oil will be able to supply increasing demand until peak world production is reached. The energy gap caused by declining conventional oil production must then be filled by expanding production of coal, heavy oil and oil shales, nuclear and hydroelectric power, and renewable energy sources (solar, wind, and geothermal). Declining oil production forecasts are based on current estimated ultimate recoverable conventional crude oil resources of 329 billion barrels for the United States and close to 3 trillion barrels for the world. Peak world crude oil production is forecast to occur in 2020 at 90 million barrels per day. Conventional crude oil production in the United States is forecast to terminate by about 2090, and world production will be close to exhaustion by 2100.

  8. Demand Response Valuation Frameworks Paper

    SciTech Connect (OSTI)

    Heffner, Grayson

    2009-02-01

    While there is general agreement that demand response (DR) is a valued component in a utility resource plan, there is a lack of consensus regarding how to value DR. Establishing the value of DR is a prerequisite to determining how much and what types of DR should be implemented, to which customers DR should be targeted, and a key determinant that drives the development of economically viable DR consumer technology. Most approaches for quantifying the value of DR focus on changes in utility system revenue requirements based on resource plans with and without DR. This ''utility centric'' approach does not assign any value to DR impacts that lower energy and capacity prices, improve reliability, lower system and network operating costs, produce better air quality, and provide improved customer choice and control. Proper valuation of these benefits requires a different basis for monetization. The review concludes that no single methodology today adequately captures the wide range of benefits and value potentially attributed to DR. To provide a more comprehensive valuation approach, current methods such as the Standard Practice Method (SPM) will most likely have to be supplemented with one or more alternative benefit-valuation approaches. This report provides an updated perspective on the DR valuation framework. It includes an introduction and four chapters that address the key elements of demand response valuation, a comprehensive literature review, and specific research recommendations.

  9. Solar Photovoltaic Cell/Module Shipments Report

    U.S. Energy Information Administration (EIA) Indexed Site

    Solar Photovoltaic Cell/Module Shipments Report February 2016 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Improving the Quality and Scope of EIA Data i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or

  10. Solar Forecasting Gets a Boost from Watson, Accuracy Improved...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% October 27, 2015 - 11:48am Addthis IBM ...

  11. PBL FY 2003 Second Quarter Review Forecast of Generation Accumulated...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    the rate period (i.e., FY 2002-2006), a forecast of that end-of-year Accumulated Net Revenue (ANR) will be completed. If the ANR at the end of the forecast year falls below the...

  12. Energy demand and population changes

    SciTech Connect (OSTI)

    Allen, E.L.; Edmonds, J.A.

    1980-12-01

    Since World War II, US energy demand has grown more rapidly than population, so that per capita consumption of energy was about 60% higher in 1978 than in 1947. Population growth and the expansion of per capita real incomes have led to a greater use of energy. The aging of the US population is expected to increase per capita energy consumption, despite the increase in the proportion of persons over 65, who consume less energy than employed persons. The sharp decline in the population under 18 has led to an expansion in the relative proportion of population in the prime-labor-force age groups. Employed persons are heavy users of energy. The growth of the work force and GNP is largely attributable to the growing participation of females. Another important consequence of female employment is the growth in ownership of personal automobiles. A third factor pushing up labor-force growth is the steady influx of illegal aliens.

  13. Coordination of Energy Efficiency and Demand Response

    SciTech Connect (OSTI)

    none,

    2010-01-01

    Summarizes existing research and discusses current practices, opportunities, and barriers to coordinating energy efficiency and demand response programs.

  14. Wind Power Forecasting Error Distributions over Multiple Timescales (Presentation)

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01

    This presentation presents some statistical analysis of wind power forecast errors and error distributions, with examples using ERCOT data.

  15. Wind power forecasting in U.S. electricity markets.

    SciTech Connect (OSTI)

    Botterud, A.; Wang, J.; Miranda, V.; Bessa, R. J.; Decision and Information Sciences; INESC Porto

    2010-04-01

    Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts.

  16. Wind power forecasting in U.S. Electricity markets

    SciTech Connect (OSTI)

    Botterud, Audun; Wang, Jianhui; Miranda, Vladimiro; Bessa, Ricardo J.

    2010-04-15

    Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts. (author)

  17. Combined Heat And Power Installation Market Forecast | OpenEI...

    Open Energy Info (EERE)

    Combined Heat And Power Installation Market Forecast Home There are currently no posts in this category. Syndicate...

  18. DOE Taking Wind Forecasting to New Heights | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Taking Wind Forecasting to New Heights DOE Taking Wind Forecasting to New Heights May 18, 2015 - 3:24pm Addthis A 2013 study conducted for the U.S. Department of Energy (DOE) by the National Oceanic and Atmospheric Administration (NOAA), AWS Truepower, and WindLogics in the Great Plains and Western Texas, demonstrated that wind power forecasts can be improved substantially using data collected from tall towers, remote sensors, and other devices, and incorporated into improved forecasting models

  19. Uncertainty Reduction in Power Generation Forecast Using Coupled

    Office of Scientific and Technical Information (OSTI)

    Wavelet-ARIMA (Conference) | SciTech Connect Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA Citation Details In-Document Search Title: Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA In this paper, we introduce a new approach without implying normal distributions and stationarity of power generation forecast errors. In addition, it is desired to more accurately quantify the forecast uncertainty by reducing prediction intervals of

  20. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    1996-08-01

    This document consists of papers which cover topics in analysis and modeling that underlie the Annual Energy Outlook 1996. Topics include: The Potential Impact of Technological Progress on U.S. Energy Markets; The Outlook for U.S. Import Dependence; Fuel Economy, Vehicle Choice, and Changing Demographics, and Annual Energy Outlook Forecast Evaluation.

  1. Model documentation: Electricity Market Module, Electricity Fuel Dispatch Submodule

    SciTech Connect (OSTI)

    Not Available

    1994-04-08

    This report documents the objectives, analytical approach and development of the National Energy Modeling System Electricity Fuel Dispatch Submodule (EFD), a submodule of the Electricity Market Module (EMM). 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.

  2. The Wind Forecast Improvement Project (WFIP). A Public-Private Partnership Addressing Wind Energy Forecast Needs

    SciTech Connect (OSTI)

    Wilczak, James M.; Finley, Cathy; Freedman, Jeff; Cline, Joel; Bianco, L.; Olson, J.; Djalaova, I.; Sheridan, L.; Ahlstrom, M.; Manobianco, J.; Zack, J.; Carley, J.; Benjamin, S.; Coulter, R. L.; Berg, Larry K.; Mirocha, Jeff D.; Clawson, K.; Natenberg, E.; Marquis, M.

    2015-10-30

    The Wind Forecast Improvement Project (WFIP) is a public-private research program, the goals of which are to improve the accuracy of short-term (0-6 hr) wind power forecasts for the wind energy industry and then to quantify the economic savings that accrue from more efficient integration of wind energy into the electrical grid. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that include the National Oceanic and Atmospheric Administration (NOAA), private forecasting companies (WindLogics and AWS Truepower), DOE national laboratories, grid operators, and universities. WFIP employed two avenues for improving wind power forecasts: first, through the collection of special observations to be assimilated into forecast models to improve model initial conditions; and second, by upgrading NWP forecast models and ensembles. The new observations were collected during concurrent year-long field campaigns in two high wind energy resource areas of the U.S. (the upper Great Plains, and Texas), and included 12 wind profiling radars, 12 sodars, 184 instrumented tall towers and over 400 nacelle anemometers (provided by private industry), lidar, and several surface flux stations. Results demonstrate that a substantial improvement of up to 14% relative reduction in power root mean square error (RMSE) was achieved from the combination of improved NOAA numerical weather prediction (NWP) models and assimilation of the new observations. Data denial experiments run over select periods of time demonstrate that up to a 6% relative improvement came from the new observations. The use of ensemble forecasts produced even larger forecast improvements. Based on the success of WFIP, DOE is planning follow-on field programs.

  3. Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting: Preprint

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting Preprint Jie Zhang 1 , Bri-Mathias Hodge 1 , Siyuan Lu 2 , Hendrik F. Hamann 2 , Brad Lehman 3 , Joseph Simmons 4 , Edwin Campos 5 , and Venkat Banunarayanan 6 1 National Renewable Energy Laboratory 2 IBM TJ Watson Research Center 3 Northeastern University 4 University of Arizona 5 Argonne National Laboratory 6 U.S. Department of Energy Presented at the IEEE Power and Energy Society General Meeting Denver,

  4. Operational forecasting based on a modified Weather Research and Forecasting model

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

    Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

  5. Year Modules

    U.S. Energy Information Administration (EIA) Indexed Site

    Annual photovoltaic module shipments, 2003-2013 (peak kilowatts) Year Modules 2003 80,062 2004 143,274 2005 204,996 2006 320,208 2007 494,148 2008 920,693 2009 1,188,879 2010 2,644,498 2011 3,772,075 2012 4,655,005 2013 4,984,881 Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report.' Note: Includes both U.S. Shipments and Exports.

  6. Year Modules

    U.S. Energy Information Administration (EIA) Indexed Site

    dollars per peak watt) Year Modules 2003 $3.17 2004 $2.99 2005 $3.19 2006 $3.50 2007 $3.37 2008 $3.49 2009 $2.79 2010 $1.96 2011 $1.59 2012 $1.15 2013 $0.75 Table 4. Average value of photovoltaic modules, 2003-2013 Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report.' Note: Dollars are not adjusted for inflation.

  7. Forecastability as a Design Criterion in Wind Resource Assessment: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01

    This paper proposes a methodology to include the wind power forecasting ability, or 'forecastability,' of a site as a design criterion in wind resource assessment and wind power plant design stages. The Unrestricted Wind Farm Layout Optimization (UWFLO) methodology is adopted to maximize the capacity factor of a wind power plant. The 1-hour-ahead persistence wind power forecasting method is used to characterize the forecastability of a potential wind power plant, thereby partially quantifying the integration cost. A trade-off between the maximum capacity factor and the forecastability is investigated.

  8. Hawaii demand-side management resource assessment. Final report: DSM opportunity report

    SciTech Connect (OSTI)

    1995-08-01

    The Hawaii Demand-Side Management Resource Assessment was the fourth of seven projects in the Hawaii Energy Strategy (HES) program. HES was designed by the Department of Business, Economic Development, and Tourism (DBEDT) to produce an integrated energy strategy for the State of Hawaii. The purpose of Project 4 was to develop a comprehensive assessment of Hawaii`s demand-side management (DSM) resources. To meet this objective, the project was divided into two phases. The first phase included development of a DSM technology database and the identification of Hawaii commercial building characteristics through on-site audits. These Phase 1 products were then used in Phase 2 to identify expected energy impacts from DSM measures in typical residential and commercial buildings in Hawaii. The building energy simulation model DOE-2.1E was utilized to identify the DSM energy impacts. More detailed information on the typical buildings and the DOE-2.1E modeling effort is available in Reference Volume 1, ``Building Prototype Analysis``. In addition to the DOE-2.1E analysis, estimates of residential and commercial sector gas and electric DSM potential for the four counties of Honolulu, Hawaii, Maui, and Kauai through 2014 were forecasted by the new DBEDT DSM Assessment Model. Results from DBEDTs energy forecasting model, ENERGY 2020, were linked with results from DOE-2.1E building energy simulation runs and estimates of DSM measure impacts, costs, lifetime, and anticipated market penetration rates in the DBEDT DSM Model. Through its algorithms, estimates of DSM potential for each forecast year were developed. Using the load shape information from the DOE-2.1E simulation runs, estimates of electric peak demand impacts were developed. 10 figs., 55 tabs.

  9. Outlook for Biomass Ethanol Production and Demand

    Reports and Publications (EIA)

    2000-01-01

    This paper presents a midterm forecast for biomass ethanol production under three different technology cases for the period 2000 to 2020, based on projections developed from the Energy Information Administration's National Energy Modeling System. An overview of cellulose conversion technology and various feedstock options and a brief history of ethanol usage in the United States are also presented.

  10. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

    Maciejewski, Ross; Hafen, Ryan; Rudolph, Stephen; Cleveland, William; Ebert, David

    2014-12-30

    A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.

  11. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect (OSTI)

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y.; Priedhorsky, Reid; Salathé, Marcel

    2014-11-13

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: access logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.

  12. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

    Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J.

    2011-02-23

    The increasing use of wind power as a source of electricity poses new challenges with regard to both power production and load balance in the electricity grid. This new source of energy is volatile and highly variable. The only way to integrate such power into the grid is to develop reliable and accurate wind power forecasting systems. Electricity generated from wind power can be highly variable at several different timescales: sub-hourly, hourly, daily, and seasonally. Wind energy, like other electricity sources, must be scheduled. Although wind power forecasting methods are used, the ability to predict wind plant output remains relatively low for short-term operation. Because instantaneous electrical generation and consumption must remain in balance to maintain grid stability, wind power's variability can present substantial challenges when large amounts of wind power are incorporated into a grid system. A critical issue is ramp events, which are sudden and large changes (increases or decreases) in wind power. This report presents an overview of current ramp definitions and state-of-the-art approaches in ramp event forecasting.

  13. Global disease monitoring and forecasting with Wikipedia

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y.; Priedhorsky, Reid; Salathé, Marcel

    2014-11-13

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: accessmore » logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.« less

  14. NCEP_Demand_Response_Draft_111208.indd

    Energy Savers [EERE]

    National Council on Electricity Policy: Electric Transmission Series for State Offi cials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials Prepared by the U.S. Demand Response Coordinating Committee for The National Council on Electricity Policy Fall 2008 i National Council on Electricity Policy: Electric

  15. Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting: Preprint

    SciTech Connect (OSTI)

    Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Lehman, Brad; Simmons, Joseph; Campos, Edwin; Banunarayanan, Venkat

    2015-08-05

    Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output. forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.

  16. Fabricate-on-Demand Vacuum Insulating Glazings

    Broader source: Energy.gov [DOE]

    PPG is working to design a fabricate-on-demand process to overcome the cost and supply chain issues preventing widespread adoption of vacuum insulating glazings (VIGs).

  17. BPA, Energy Northwest launch demand response pilot

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    BPA-Energy-Northwest-launch-demand-response-pilot Sign In About | Careers | Contact | Investors | bpa.gov Search News & Us Expand News & Us Projects & Initiatives Expand...

  18. Integration of Demand Side Management, Distributed Generation...

    Open Energy Info (EERE)

    various aspects of demand response, distributed generation, smart grid and energy storage. Annex 9 is a list of pilot programs and case studies, with links to those...

  19. Demand Response and Energy Storage Integration Study

    Broader source: Energy.gov [DOE]

    Demand response and energy storage resources present potentially important sources of bulk power system services that can aid in integrating variable renewable generation. While renewable...

  20. Demand Response (transactional control) - Energy Innovation Portal

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Energy Analysis Energy Analysis Electricity Transmission Electricity Transmission Find More Like This Return to Search Demand Response (transactional control) Pacific Northwest ...

  1. Distributed Automated Demand Response - Energy Innovation Portal

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Energy Analysis Energy Analysis Electricity Transmission Electricity Transmission Find More Like This Return to Search Distributed Automated Demand Response Lawrence Livermore ...

  2. Energy Efficiency, Demand Response, and Volttron

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    ENERGY EFFICIENCY, DEMAND RESPONSE, AND VOLTTRON Presented by Justin Sipe SEEMINGLY SIMPLE STATEMENTS Utilities need more capacity to handle growth on the grid ...

  3. Demand Response in the ERCOT Markets

    SciTech Connect (OSTI)

    Patterson, Mark

    2011-10-25

    ERCOT grid serves 85% of Texas load over 40K+ miles transmission line. Demand response: voluntary load response, load resources, controllable load resources, and emergency interruptible load service.

  4. Reducing Logistics Footprints and Replenishment Demands: Nano...

    Office of Scientific and Technical Information (OSTI)

    Water Treatment Citation Details In-Document Search Title: Reducing Logistics Footprints and Replenishment Demands: Nano-engineered Silica Aerogels a Proven Method for Water ...

  5. Geographically Based Hydrogen Demand and Infrastructure Rollout...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Rollout Scenario Analysis Geographically Based Hydrogen Demand and Infrastructure Rollout Scenario Analysis Presentation by Margo Melendez at the 2010-2025 Scenario Analysis for ...

  6. Marketing & Driving Demand Collaborative - Social Media Tools...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Marketing & Driving Demand Collaborative - Social Media Tools & Strategies Presentation slides from the Better Buildings webinar on January 6, 2011. PDF icon Marketing & Driving ...

  7. Geographically Based Hydrogen Consumer Demand and Infrastructure...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Geographically Based Hydrogen Consumer Demand and Infrastructure Analysis Final Report M. Melendez and A. Milbrandt Technical Report NRELTP-540-40373 October 2006 NREL is operated...

  8. Thermionic modules

    DOE Patents [OSTI]

    King, Donald B.; Sadwick, Laurence P.; Wernsman, Bernard R.

    2002-06-18

    Modules of assembled microminiature thermionic converters (MTCs) having high energy-conversion efficiencies and variable operating temperatures manufactured using MEMS manufacturing techniques including chemical vapor deposition. The MTCs incorporate cathode to anode spacing of about 1 micron or less and use cathode and anode materials having work functions ranging from about 1 eV to about 3 eV. The MTCs also exhibit maximum efficiencies of just under 30%, and thousands of the devices and modules can be fabricated at modest costs.

  9. Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.; Florita, A.; Lu, S.; Hamann, H. F.; Banunarayanan, V.

    2013-10-01

    Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The results show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.

  10. Coordination of Energy Efficiency and Demand Response

    SciTech Connect (OSTI)

    Goldman, Charles; Reid, Michael; Levy, Roger; Silverstein, Alison

    2010-01-29

    This paper reviews the relationship between energy efficiency and demand response and discusses approaches and barriers to coordinating energy efficiency and demand response. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025. Improving energy efficiency in our homes, businesses, schools, governments, and industries - which consume more than 70 percent of the nation's natural gas and electricity - is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demand response is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demand response resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demand response potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that 'the combination of demand response and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW' by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demand response programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

  11. Strategies for Demand Response in Commercial Buildings

    SciTech Connect (OSTI)

    Watson, David S.; Kiliccote, Sila; Motegi, Naoya; Piette, Mary Ann

    2006-06-20

    This paper describes strategies that can be used in commercial buildings to temporarily reduce electric load in response to electric grid emergencies in which supplies are limited or in response to high prices that would be incurred if these strategies were not employed. The demand response strategies discussed herein are based on the results of three years of automated demand response field tests in which 28 commercial facilities with an occupied area totaling over 11 million ft{sup 2} were tested. Although the demand response events in the field tests were initiated remotely and performed automatically, the strategies used could also be initiated by on-site building operators and performed manually, if desired. While energy efficiency measures can be used during normal building operations, demand response measures are transient; they are employed to produce a temporary reduction in demand. Demand response strategies achieve reductions in electric demand by temporarily reducing the level of service in facilities. Heating ventilating and air conditioning (HVAC) and lighting are the systems most commonly adjusted for demand response in commercial buildings. The goal of demand response strategies is to meet the electric shed savings targets while minimizing any negative impacts on the occupants of the buildings or the processes that they perform. Occupant complaints were minimal in the field tests. In some cases, ''reductions'' in service level actually improved occupant comfort or productivity. In other cases, permanent improvements in efficiency were discovered through the planning and implementation of ''temporary'' demand response strategies. The DR strategies that are available to a given facility are based on factors such as the type of HVAC, lighting and energy management and control systems (EMCS) installed at the site.

  12. Effects of the Financial Crisis on Photovoltaics: An Analysis of Changes in Market Forecasts from 2008 to 2009

    SciTech Connect (OSTI)

    Bartlett, J. E.; Margolis, R. M.; Jennings, C. E.

    2009-09-01

    To examine how the financial crisis has impacted expectations of photovoltaic production, demand and pricing over the next several years, we surveyed the market forecasts of industry analysts that had issued projections in 2008 and 2009. We find that the financial crisis has had a significant impact on the PV industry, primarily through increasing the cost and reducing the availability of investment into the sector. These effects have been more immediately experienced by PV installations than by production facilities, due to the different types and duration of investments, and thus PV demand has been reduced by a greater proportion than PV production. By reducing demand more than production, the financial crisis has accelerated previously expected PV overcapacity and resulting price declines.

  13. Residential sector end-use forecasting with EPRI-Reeps 2.1: Summary input assumptions and results

    SciTech Connect (OSTI)

    Koomey, J.G.; Brown, R.E.; Richey, R.

    1995-12-01

    This paper describes current and projected future energy use by end-use and fuel for the U.S. residential sector, and assesses which end-uses are growing most rapidly over time. The inputs to this forecast are based on a multi-year data compilation effort funded by the U.S. Department of Energy. We use the Electric Power Research Institute`s (EPRI`s) REEPS model, as reconfigured to reflect the latest end-use technology data. Residential primary energy use is expected to grow 0.3% per year between 1995 and 2010, while electricity demand is projected to grow at about 0.7% per year over this period. The number of households is expected to grow at about 0.8% per year, which implies that the overall primary energy intensity per household of the residential sector is declining, and the electricity intensity per household is remaining roughly constant over the forecast period. These relatively low growth rates are dependent on the assumed growth rate for miscellaneous electricity, which is the single largest contributor to demand growth in many recent forecasts.

  14. Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical

    Office of Scientific and Technical Information (OSTI)

    Modelling Approach (Journal Article) | SciTech Connect Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach Citation Details In-Document Search Title: Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates daily nowcasts and three-day forecasts of several environmental variables, such as sea-surface temperature and salinity, the

  15. Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory

    Office of Scientific and Technical Information (OSTI)

    (BNL) Field Campaign Report (Technical Report) | SciTech Connect SciTech Connect Search Results Technical Report: Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report Citation Details In-Document Search Title: Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report The Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) [http://www.arm.gov/campaigns/osc2013rwpcf]

  16. Energy Conservation Program: Data Collection and Comparison with Forecasted

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Unit Sales for Five Lamp Types, Notice of Data Availability | Department of Energy Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability This document is the notice of data availability for Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types. PDF icon

  17. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Complex Terrain | Department of Energy for Wind Forecasting Improvement Project in Complex Terrain Upcoming Funding Opportunity for Wind Forecasting Improvement Project in Complex Terrain February 12, 2014 - 10:47am Addthis On February 11, 2014 the Wind Program announced a Notice of Intent to issue a funding opportunity entitled "Wind Forecasting Improvement Project in Complex Terrain." By researching the physical processes that take place in complex terrain, this funding would

  18. DOE Benefits Forecasts: Report of the External Peer Review Panel |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy Benefits Forecasts: Report of the External Peer Review Panel DOE Benefits Forecasts: Report of the External Peer Review Panel A report for the FY 2007 GPRA methodology review, highlighting the views of an external expert peer review panel on DOE benefits forecasts. PDF icon Report of the External Peer Review Panel More Documents & Publications Industrial Technologies Funding Profile by Subprogram Survey of Emissions Models for Distributed Combined Heat and Power

  19. 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

    Title: 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory When considering the amount of shortwave radiation incident on a photovoltaic solar array and, ...

  20. Improving the Accuracy of Solar Forecasting Funding Opportunity...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    These projects aim to improve the accuracy of solar forecasting that could increase penetration of solar power by enabling more certainty in power prediction from solar power ...

  1. Ecological Forecasting in Chesapeake Bay: Using a Mechanistic...

    Office of Scientific and Technical Information (OSTI)

    Title: Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates ...

  2. Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint

    SciTech Connect (OSTI)

    Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad

    2015-12-08

    Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.

  3. DOE Announces Webinars on Solar Forecasting Metrics, the DOE...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    DOE Announces Webinars on Solar Forecasting Metrics, the DOE ... from adopting the latest energy efficiency and renewable ... to liquids technology, advantages of using natural gas, ...

  4. FY 2004 Second Quarter Review Forecast of Generation Accumulated...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Bonneville Power Administration Power Business Line Generation (PBL) Accumulated Net Revenue Forecast for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) and Safety-Net...

  5. PBL FY 2003 Third Quarter Review Forecast of Generation Accumulated...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    2003 Bonneville Power Administration Power Business Line Generation Accumulated Net Revenue Forecast for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) and Safety-Net...

  6. Wind Power Forecasting Error Distributions: An International Comparison; Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Lew, D.; Milligan, M.; Holttinen, H.; Sillanpaa, S.; Gomez-Lazaro, E.; Scharff, R.; Soder, L.; Larsen, X. G.; Giebel, G.; Flynn, D.; Dobschinski, J.

    2012-09-01

    Wind power forecasting is expected to be an important enabler for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that do occur can be critical to system operation functions, such as the setting of operating reserve levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations.

  7. Selected papers on fuel forecasting and analysis

    SciTech Connect (OSTI)

    Gordon, R.L.; Prast, W.G.

    1983-05-01

    Of the 19 presentations at this seminar, covering coal, uranium, oil, and gas issues as well as related EPRI research projects, eleven papers are published in this volume. Nine of the papers primarily address coal-market analysis, coal transportation, and uranium supply. Two additional papers provide an evaluation and perspective on the art and use of coal-supply forecasting models and on the relationship between coal and oil prices. The authors are energy analysts and EPRI research contractors from academia, the consulting profession, and the coal industry. A separate abstract was prepared for each of the 11 papers.

  8. Autonomous Demand Response for Primary Frequency Regulation

    SciTech Connect (OSTI)

    Donnelly, Matt; Trudnowski, Daniel J.; Mattix, S.; Dagle, Jeffery E.

    2012-02-28

    The research documented within this report examines the use of autonomous demand response to provide primary frequency response in an interconnected power grid. The work builds on previous studies in several key areas: it uses a large realistic model (i.e., the interconnection of the western United States and Canada); it establishes a set of metrics that can be used to assess the effectiveness of autonomous demand response; and it independently adjusts various parameters associated with using autonomous demand response to assess effectiveness and to examine possible threats or vulnerabilities associated with the technology.

  9. FERC sees huge potential for demand response

    SciTech Connect (OSTI)

    2010-04-15

    The FERC study concludes that U.S. peak demand can be reduced by as much as 188 GW -- roughly 20 percent -- under the most aggressive scenario. More moderate -- and realistic -- scenarios produce smaller but still significant reductions in peak demand. The FERC report is quick to point out that these are estimates of the potential, not projections of what could actually be achieved. The main varieties of demand response programs include interruptible tariffs, direct load control (DLC), and a number of pricing schemes.

  10. Electricity demand in a developing country. [Paraguay

    SciTech Connect (OSTI)

    Westley, G.D.

    1984-08-01

    This study analyzes the residential and commercial demand for electricity in ten regions in Paraguay for 1970-1977. Models that are both linear and nonlinear in the parameters are estimated. The nonlinear model takes advantage of prior information on the nature of the appliances being utilized and simultaneously deals with the demand discontinuities caused by appliance indivisibility. Three dynamic equations, including a novel cumulative adjustment model, all indicate rapid adjustment to desired appliance stock levels. Finally, the multiproduct surplus loss obtained from an estimated demand equation is used to measure the welfare cost of power outages. 15 references.

  11. Thermoelectric module

    DOE Patents [OSTI]

    Kortier, William E.; Mueller, John J.; Eggers, Philip E.

    1980-07-08

    A thermoelectric module containing lead telluride as the thermoelectric mrial is encapsulated as tightly as possible in a stainless steel canister to provide minimum void volume in the canister. The lead telluride thermoelectric elements are pressure-contacted to a tungsten hot strap and metallurgically bonded at the cold junction to iron shoes with a barrier layer of tin telluride between the iron shoe and the p-type lead telluride element.

  12. Next Update: December 2011 Net Internal Demand

    U.S. Energy Information Administration (EIA) Indexed Site

    Net Internal Demand (MW) Capacity Resources (MW) Capacity Margin (percent) Net Internal Demand (MW) Capacity Resources (MW) Capacity Margin (percent) Net Internal Demand (MW) Capacity Resources (MW) Capacity Margin (percent) Net Internal Demand (MW) Capacity Resources (MW) Capacity Margin (percent) 2005 746,470 882,125 15.4 45,950 50,200 8.5 38,266 46,792 18.2 57,402 72,258 20.6 2006 760,108 906,155 16.1 43,824 53,171 17.6 41,754 49,792 16.1 59,727 70,607 15.4 2007 768,061 946,631 18.9 46,434

  13. SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY

    Broader source: Energy.gov [DOE]

    As a city that experiences seasonal spikes in energy demand and accompanying energy bills, San Antonio, Texas, wanted to help homeowners and businesses reduce their energy use and save on energy...

  14. Solar in Demand | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    In case you missed it... This week, the Wall Street Journal published an article, "U.S. Solar-Panel Demand Expected to Double," highlighting the successes of the U.S. solar ...

  15. Demand Response and Energy Storage Integration Study

    Broader source: Energy.gov [DOE]

    This study is a multi-national laboratory effort to assess the potential value of demand response and energy storage to electricity systems with different penetration levels of variable renewable...

  16. Global Energy: Supply, Demand, Consequences, Opportunities

    ScienceCinema (OSTI)

    Majumdar, Arun

    2010-01-08

    July 29, 2008 Berkeley Lab lecture: Arun Majumdar, Director of the Environmental Energy Technologies Division, discusses current and future projections of economic growth, population, and global energy demand and supply, and explores the implications of these trends for the environment.

  17. Climate policy implications for agricultural water demand

    SciTech Connect (OSTI)

    Chaturvedi, Vaibhav; Hejazi, Mohamad I.; Edmonds, James A.; Clarke, Leon E.; Kyle, G. Page; Davies, Evan; Wise, Marshall A.; Calvin, Katherine V.

    2013-03-28

    Energy, water and land are scarce resources, critical to humans. Developments in each affect the availability and cost of the others, and consequently human prosperity. Measures to limit greenhouse gas concentrations will inevitably exact dramatic changes on energy and land systems and in turn alter the character, magnitude and geographic distribution of human claims on water resources. We employ the Global Change Assessment Model (GCAM), an integrated assessment model to explore the interactions of energy, land and water systems in the context of alternative policies to limit climate change to three alternative levels: 2.5 Wm-2 (445 ppm CO2-e), 3.5 Wm-2 (535 ppm CO2-e) and 4.5 Wm-2 (645 ppm CO2-e). We explore the effects of two alternative land-use emissions mitigation policy options—one which taxes terrestrial carbon emissions equally with fossil fuel and industrial emissions, and an alternative which only taxes fossil fuel and industrial emissions but places no penalty on land-use change emissions. We find that increasing populations and economic growth could be anticipated to almost triple demand for water for agricultural systems across the century even in the absence of climate policy. In general policies to mitigate climate change increase agricultural demands for water still further, though the largest changes occur in the second half of the century, under both policy regimes. The two policies examined profoundly affected both the sources and magnitudes of the increase in irrigation water demands. The largest increases in agricultural irrigation water demand occurred in scenarios where only fossil fuel emissions were priced (but not land-use change emission) and were primarily driven by rapid expansion in bioenergy production. In these scenarios water demands were large relative to present-day total available water, calling into question whether it would be physically possible to produce the associated biomass energy. We explored the potential of improved water delivery and irrigation system efficiencies. These could potentially reduce demands substantially. However, overall demands remained high under our fossil-fuel-only tax policy. In contrast, when all carbon was priced, increases in agricultural water demands were smaller than under the fossil-fuel-only policy and were driven primarily by increased demands for water by non-biomass crops such as rice. Finally we estimate the geospatial pattern of water demands and find that regions such as China, India and other countries in south and east Asia might be expected to experience greatest increases in water demands. 

  18. Measuring the capacity impacts of demand response

    SciTech Connect (OSTI)

    Earle, Robert; Kahn, Edward P.; Macan, Edo

    2009-07-15

    Critical peak pricing and peak time rebate programs offer benefits by increasing system reliability, and therefore, reducing capacity needs of the electric power system. These benefits, however, decrease substantially as the size of the programs grows relative to the system size. More flexible schemes for deployment of demand response can help address the decreasing returns to scale in capacity value, but more flexible demand response has decreasing returns to scale as well. (author)

  19. Photovoltaic module and module arrays

    DOE Patents [OSTI]

    Botkin, Jonathan; Graves, Simon; Lenox, Carl J. S.; Culligan, Matthew; Danning, Matt

    2013-08-27

    A photovoltaic (PV) module including a PV device and a frame, The PV device has a PV laminate defining a perimeter and a major plane. The frame is assembled to and encases the laminate perimeter, and includes leading, trailing, and side frame members, and an arm that forms a support face opposite the laminate. The support face is adapted for placement against a horizontal installation surface, to support and orient the laminate in a non-parallel or tilted arrangement. Upon final assembly, the laminate and the frame combine to define a unitary structure. The frame can orient the laminate at an angle in the range of 3.degree.-7.degree. from horizontal, and can be entirely formed of a polymeric material. Optionally, the arm incorporates integral feature(s) that facilitate interconnection with corresponding features of a second, identically formed PV module.

  20. Photovoltaic module and module arrays

    DOE Patents [OSTI]

    Botkin, Jonathan; Graves, Simon; Lenox, Carl J. S.; Culligan, Matthew; Danning, Matt

    2012-07-17

    A photovoltaic (PV) module including a PV device and a frame. The PV device has a PV laminate defining a perimeter and a major plane. The frame is assembled to and encases the laminate perimeter, and includes leading, trailing, and side frame members, and an arm that forms a support face opposite the laminate. The support face is adapted for placement against a horizontal installation surface, to support and orient the laminate in a non-parallel or tilted arrangement. Upon final assembly, the laminate and the frame combine to define a unitary structure. The frame can orient the laminate at an angle in the range of 3.degree.-7.degree. from horizontal, and can be entirely formed of a polymeric material. Optionally, the arm incorporates integral feature(s) that facilitate interconnection with corresponding features of a second, identically formed PV module.

  1. Ethanol Demand in United States Gasoline Production

    SciTech Connect (OSTI)

    Hadder, G.R.

    1998-11-24

    The Oak Ridge National Laboratory (OWL) Refinery Yield Model (RYM) has been used to estimate the demand for ethanol in U.S. gasoline production in year 2010. Study cases examine ethanol demand with variations in world oil price, cost of competing oxygenate, ethanol value, and gasoline specifications. For combined-regions outside California summer ethanol demand is dominated by conventional gasoline (CG) because the premised share of reformulated gasoline (RFG) production is relatively low and because CG offers greater flexibility for blending high vapor pressure components like ethanol. Vapor pressure advantages disappear for winter CG, but total ethanol used in winter RFG remains low because of the low RFG production share. In California, relatively less ethanol is used in CG because the RFG production share is very high. During the winter in California, there is a significant increase in use of ethanol in RFG, as ethanol displaces lower-vapor-pressure ethers. Estimated U.S. ethanol demand is a function of the refiner value of ethanol. For example, ethanol demand for reference conditions in year 2010 is 2 billion gallons per year (BGY) at a refiner value of $1.00 per gallon (1996 dollars), and 9 BGY at a refiner value of $0.60 per gallon. Ethanol demand could be increased with higher oil prices, or by changes in gasoline specifications for oxygen content, sulfur content, emissions of volatile organic compounds (VOCS), and octane numbers.

  2. Opportunities for Automated Demand Response in Wastewater Treatment Facilities in California - Southeast Water Pollution Control Plant Case Study

    SciTech Connect (OSTI)

    Olsen, Daniel; Goli, Sasank; Faulkner, David; McKane, Aimee

    2012-12-20

    This report details a study into the demand response potential of a large wastewater treatment facility in San Francisco. Previous research had identified wastewater treatment facilities as good candidates for demand response and automated demand response, and this study was conducted to investigate facility attributes that are conducive to demand response or which hinder its implementation. One years' worth of operational data were collected from the facility's control system, submetered process equipment, utility electricity demand records, and governmental weather stations. These data were analyzed to determine factors which affected facility power demand and demand response capabilities The average baseline demand at the Southeast facility was approximately 4 MW. During the rainy season (October-March) the facility treated 40% more wastewater than the dry season, but demand only increased by 4%. Submetering of the facility's lift pumps and centrifuges predicted load shifts capabilities of 154 kW and 86 kW, respectively, with large lift pump shifts in the rainy season. Analysis of demand data during maintenance events confirmed the magnitude of these possible load shifts, and indicated other areas of the facility with demand response potential. Load sheds were seen to be possible by shutting down a portion of the facility's aeration trains (average shed of 132 kW). Load shifts were seen to be possible by shifting operation of centrifuges, the gravity belt thickener, lift pumps, and external pump stations These load shifts were made possible by the storage capabilities of the facility and of the city's sewer system. Large load reductions (an average of 2,065 kW) were seen from operating the cogeneration unit, but normal practice is continuous operation, precluding its use for demand response. The study also identified potential demand response opportunities that warrant further study: modulating variable-demand aeration loads, shifting operation of sludge-processing equipment besides centrifuges, and utilizing schedulable self-generation.

  3. Comparison of Wind Power and Load Forecasting Error Distributions: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Florita, A.; Orwig, K.; Lew, D.; Milligan, M.

    2012-07-01

    The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent System Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.

  4. The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations | Department of Energy The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The Wind Forecast Improvement

  5. Refrigerated Warehouse Demand Response Strategy Guide

    SciTech Connect (OSTI)

    Scott, Doug; Castillo, Rafael; Larson, Kyle; Dobbs, Brian; Olsen, Daniel

    2015-11-01

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

  6. Short-Term Energy Outlook Model Documentation: Macro Bridge Procedure to Update Regional Macroeconomic Forecasts with National Macroeconomic Forecasts

    Reports and Publications (EIA)

    2010-01-01

    The Regional Short-Term Energy Model (RSTEM) uses macroeconomic variables such as income, employment, industrial production and consumer prices at both the national and regional1 levels as explanatory variables in the generation of the Short-Term Energy Outlook (STEO). This documentation explains how national macroeconomic forecasts are used to update regional macroeconomic forecasts through the RSTEM Macro Bridge procedure.

  7. 3TIER Environmental Forecast Group Inc 3TIER | Open Energy Information

    Open Energy Info (EERE)

    TIER Environmental Forecast Group Inc 3TIER Jump to: navigation, search Name: 3TIER Environmental Forecast Group Inc (3TIER) Place: Seattle, Washington Zip: 98121 Sector: Renewable...

  8. Material World: Forecasting Household Appliance Ownership in a Growing Global Economy

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

    Over the past years the Lawrence Berkeley National Laboratory (LBNL) has developed an econometric model that predicts appliance ownership at the household level based on macroeconomic variables such as household income (corrected for purchase power parity), electrification, urbanization and climate variables. Hundreds of data points from around the world were collected in order to understand trends in acquisition of new appliances by households, especially in developing countries. The appliances covered by this model are refrigerators, lighting fixtures, air conditioners, washing machines and televisions. The approach followed allows the modeler to construct a bottom-up analysis based at the end use and the household level. It captures the appliance uptake and the saturation effect which will affect the energy demand growth in the residential sector. With this approach, the modeler can also account for stock changes in technology and efficiency as a function of time. This serves two important functions with regard to evaluation of the impact of energy efficiency policies. First, it provides insight into which end uses will be responsible for the largest share of demand growth, and therefore should be policy priorities. Second, it provides a characterization of the rate at which policies affecting new equipment penetrate the appliance stock. Over the past 3 years, this method has been used to support the development of energy demand forecasts at the country, region or global level.

  9. Centralized and Decentralized Control for Demand Response

    SciTech Connect (OSTI)

    Lu, Shuai; Samaan, Nader A.; Diao, Ruisheng; Elizondo, Marcelo A.; Jin, Chunlian; Mayhorn, Ebony T.; Zhang, Yu; Kirkham, Harold

    2011-04-29

    Demand response has been recognized as an essential element of the smart grid. Frequency response, regulation and contingency reserve functions performed traditionally by generation resources are now starting to involve demand side resources. Additional benefits from demand response include peak reduction and load shifting, which will defer new infrastructure investment and improve generator operation efficiency. Technical approaches designed to realize these functionalities can be categorized into centralized control and decentralized control, depending on where the response decision is made. This paper discusses these two control philosophies and compares their relative advantages and disadvantages in terms of delay time, predictability, complexity, and reliability. A distribution system model with detailed household loads and controls is built to demonstrate the characteristics of the two approaches. The conclusion is that the promptness and reliability of decentralized control should be combined with the predictability and simplicity of centralized control to achieve the best performance of the smart grid.

  10. Utility Sector Impacts of Reduced Electricity Demand

    SciTech Connect (OSTI)

    Coughlin, Katie

    2014-12-01

    This report presents a new approach to estimating the marginal utility sector impacts associated with electricity demand reductions. The method uses publicly available data and provides results in the form of time series of impact factors. The input data are taken from the Energy Information Agency's Annual Energy Outlook (AEO) projections of how the electric system might evolve in the reference case, and in a number of side cases that incorporate different effciency and other policy assumptions. The data published with the AEO are used to define quantitative relationships between demand-side electricity reductions by end use and supply-side changes to capacity by plant type, generation by fuel type and emissions of CO2, Hg, NOx and SO2. The impact factors define the change in each of these quantities per unit reduction in site electricity demand. We find that the relative variation in these impacts by end use is small, but the time variation can be significant.

  11. China's Coal: Demand, Constraints, and Externalities

    SciTech Connect (OSTI)

    Aden, Nathaniel; Fridley, David; Zheng, Nina

    2009-07-01

    This study analyzes China's coal industry by focusing on four related areas. First, data are reviewed to identify the major drivers of historical and future coal demand. Second, resource constraints and transport bottlenecks are analyzed to evaluate demand and growth scenarios. The third area assesses the physical requirements of substituting coal demand growth with other primary energy forms. Finally, the study examines the carbon- and environmental implications of China's past and future coal consumption. There are three sections that address these areas by identifying particular characteristics of China's coal industry, quantifying factors driving demand, and analyzing supply scenarios: (1) reviews the range of Chinese and international estimates of remaining coal reserves and resources as well as key characteristics of China's coal industry including historical production, resource requirements, and prices; (2) quantifies the largest drivers of coal usage to produce a bottom-up reference projection of 2025 coal demand; and (3) analyzes coal supply constraints, substitution options, and environmental externalities. Finally, the last section presents conclusions on the role of coal in China's ongoing energy and economic development. China has been, is, and will continue to be a coal-powered economy. In 2007 Chinese coal production contained more energy than total Middle Eastern oil production. The rapid growth of coal demand after 2001 created supply strains and bottlenecks that raise questions about sustainability. Urbanization, heavy industrial growth, and increasing per-capita income are the primary interrelated drivers of rising coal usage. In 2007, the power sector, iron and steel, and cement production accounted for 66% of coal consumption. Power generation is becoming more efficient, but even extensive roll-out of the highest efficiency units would save only 14% of projected 2025 coal demand for the power sector. A new wedge of future coal consumption is likely to come from the burgeoning coal-liquefaction and chemicals industries. If coal to chemicals capacity reaches 70 million tonnes and coal-to-liquids capacity reaches 60 million tonnes, coal feedstock requirements would add an additional 450 million tonnes by 2025. Even with more efficient growth among these drivers, China's annual coal demand is expected to reach 3.9 to 4.3 billion tonnes by 2025. Central government support for nuclear and renewable energy has not reversed China's growing dependence on coal for primary energy. Substitution is a matter of scale: offsetting one year of recent coal demand growth of 200 million tonnes would require 107 billion cubic meters of natural gas (compared to 2007 growth of 13 BCM), 48 GW of nuclear (compared to 2007 growth of 2 GW), or 86 GW of hydropower capacity (compared to 2007 growth of 16 GW). Ongoing dependence on coal reduces China's ability to mitigate carbon dioxide emissions growth. If coal demand remains on a high growth path, carbon dioxide emissions from coal combustion alone would exceed total US energy-related carbon emissions by 2010. Within China's coal-dominated energy system, domestic transportation has emerged as the largest bottleneck for coal industry growth and is likely to remain a constraint to further expansion. China has a low proportion of high-quality reserves, but is producing its best coal first. Declining quality will further strain production and transport capacity. Furthermore, transporting coal to users has overloaded the train system and dramatically increased truck use, raising transportation oil demand. Growing international imports have helped to offset domestic transport bottlenecks. In the long term, import demand is likely to exceed 200 million tonnes by 2025, significantly impacting regional markets.

  12. Wireless Demand Response Controls for HVAC Systems

    SciTech Connect (OSTI)

    Federspiel, Clifford

    2009-06-30

    The objectives of this scoping study were to develop and test control software and wireless hardware that could enable closed-loop, zone-temperature-based demand response in buildings that have either pneumatic controls or legacy digital controls that cannot be used as part of a demand response automation system. We designed a SOAP client that is compatible with the Demand Response Automation Server (DRAS) being used by the IOUs in California for their CPP program, design the DR control software, investigated the use of cellular routers for connecting to the DRAS, and tested the wireless DR system with an emulator running a calibrated model of a working building. The results show that the wireless DR system can shed approximately 1.5 Watts per design CFM on the design day in a hot, inland climate in California while keeping temperatures within the limits of ASHRAE Standard 55: Thermal Environmental Conditions for Human Occupancy.

  13. Development and testing of improved statistical wind power forecasting methods.

    SciTech Connect (OSTI)

    Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J.

    2011-12-06

    Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.

  14. DEMAND CONTROLLED VENTILATION AND CLASSROOM VENTILATION

    SciTech Connect (OSTI)

    Fisk, William J.; Mendell, Mark J.; Davies, Molly; Eliseeva, Ekaterina; Faulkner, David; Hong, Tienzen; Sullivan, Douglas P.

    2014-01-06

    This document summarizes a research effort on demand controlled ventilation and classroom ventilation. The research on demand controlled ventilation included field studies and building energy modeling. Major findings included: ? The single-location carbon dioxide sensors widely used for demand controlled ventilation frequently have large errors and will fail to effectively control ventilation rates (VRs).? Multi-location carbon dioxide measurement systems with more expensive sensors connected to multi-location sampling systems may measure carbon dioxide more accurately.? Currently-available optical people counting systems work well much of the time but have large counting errors in some situations. ? In meeting rooms, measurements of carbon dioxide at return-air grilles appear to be a better choice than wall-mounted sensors.? In California, demand controlled ventilation in general office spaces is projected to save significant energy and be cost effective only if typical VRs without demand controlled ventilation are very high relative to VRs in codes. Based on the research, several recommendations were developed for demand controlled ventilation specifications in the California Title 24 Building Energy Efficiency Standards.The research on classroom ventilation collected data over two years on California elementary school classrooms to investigate associations between VRs and student illness absence (IA). Major findings included: ? Median classroom VRs in all studied climate zones were below the California guideline, and 40percent lower in portable than permanent buildings.? Overall, one additional L/s per person of VR was associated with 1.6percent less IA. ? Increasing average VRs in California K-12 classrooms from the current average to the required level is estimated to decrease IA by 3.4percent, increasing State attendance-based funding to school districts by $33M, with $6.2 M in increased energy costs. Further VR increases would provide additional benefits.? Confirming these findings in intervention studies is recommended. ? Energy costs of heating/cooling unoccupied classrooms statewide are modest, but a large portion occurs in relatively few classrooms.

  15. Demand Responsive Lighting: A Scoping Study

    SciTech Connect (OSTI)

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-03

    The objective of this scoping study is: (1) to identify current market drivers and technology trends that can improve the demand responsiveness of commercial building lighting systems and (2) to quantify the energy, demand and environmental benefits of implementing lighting demand response and energy-saving controls strategies Statewide. Lighting systems in California commercial buildings consume 30 GWh. Lighting systems in commercial buildings often waste energy and unnecessarily stress the electrical grid because lighting controls, especially dimming, are not widely used. But dimmable lighting equipment, especially the dimming ballast, costs more than non-dimming lighting and is expensive to retrofit into existing buildings because of the cost of adding control wiring. Advances in lighting industry capabilities coupled with the pervasiveness of the Internet and wireless technologies have led to new opportunities to realize significant energy saving and reliable demand reduction using intelligent lighting controls. Manufacturers are starting to produce electronic equipment--lighting-application specific controllers (LAS controllers)--that are wirelessly accessible and can control dimmable or multilevel lighting systems obeying different industry-accepted protocols. Some companies make controllers that are inexpensive to install in existing buildings and allow the power consumed by bi-level lighting circuits to be selectively reduced during demand response curtailments. By intelligently limiting the demand from bi-level lighting in California commercial buildings, the utilities would now have an enormous 1 GW demand shed capability at hand. By adding occupancy and light sensors to the remotely controllable lighting circuits, automatic controls could harvest an additional 1 BkWh/yr savings above and beyond the savings that have already been achieved. The lighting industry's adoption of DALI as the principal wired digital control protocol for dimming ballasts and increased awareness of the need to standardize on emerging wireless technologies are evidence of this transformation. In addition to increased standardization of digital control protocols controller capabilities, the lighting industry has improved the performance of dimming lighting systems over the last two years. The system efficacy of today's current dimming ballasts is approaching that of non-dimming program start ballasts. The study finds that the benefits of applying digital controls technologies to California's unique commercial buildings market are enormous. If California were to embark on an concerted 20 year program to improve the demand responsiveness and energy efficiency of commercial building lighting systems, the State could avoid adding generation capacity, improve the elasticity of the grid, save Californians billion of dollars in avoided energy charges and significantly reduce greenhouse gas emissions.

  16. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema (OSTI)

    Gonzalez, Frank

    2010-01-08

    After a review of tsunami statistics and the destruction caused by tsunamis, a means of forecasting tsunamis is discussed as part of an overall program of reducing fatalities through hazard assessment, education, training, mitigation, and a tsunami warning system. The forecast is accomplished via a concept called Deep Ocean Assessment and Reporting of Tsunamis (DART). Small changes of pressure at the sea floor are measured and relayed to warning centers. Under development is an international modeling network to transfer, maintain, and improve tsunami forecast models.

  17. Tankless Demand Water Heater Basics | Department of Energy

    Energy Savers [EERE]

    Water Heating Tankless Demand Water Heater Basics Tankless Demand Water Heater Basics August 19, 2013 - 2:57pm Addthis Illustration of an electric demand water heater. At the ...

  18. Washington: Sustainability Training for Realtors in High Demand...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Sustainability Training for Realtors in High Demand Washington: Sustainability Training for Realtors in High Demand March 6, 2014 - 5:50pm Addthis Demand has been high for a free ...

  19. Final Scientific Technical Report: INTEGRATED PREDICTIVE DEMAND RESPONSE CONTROLLER FOR COMMERCIAL BUILDINGS

    SciTech Connect (OSTI)

    Wenzel, Mike

    2013-10-14

    This project provides algorithms to perform demand response using the thermal mass of a building. Using the thermal mass of the building is an attractive method for performing demand response because there is no need for capital expenditure. The algorithms rely on the thermal capacitance inherent in the building?s construction materials. A near-optimal ?day ahead? predictive approach is developed that is meant to keep the building?s electrical demand constant during the high cost periods. This type of approach is appropriate for both time-of-use and critical peak pricing utility rate structures. The approach uses the past days data in order to determine the best temperature setpoints for the building during the high price periods on the next day. A second ?model predictive approach? (MPC) uses a thermal model of the building to determine the best temperature for the next sample period. The approach uses constant feedback from the building and is capable of appropriately handling real time pricing. Both approaches are capable of using weather forecasts to improve performance.

  20. Supported PV module assembly

    DOE Patents [OSTI]

    Mascolo, Gianluigi; Taggart, David F.; Botkin, Jonathan D.; Edgett, Christopher S.

    2013-10-15

    A supported PV assembly may include a PV module comprising a PV panel and PV module supports including module supports having a support surface supporting the module, a module registration member engaging the PV module to properly position the PV module on the module support, and a mounting element. In some embodiments the PV module registration members engage only the external surfaces of the PV modules at the corners. In some embodiments the assembly includes a wind deflector with ballast secured to a least one of the PV module supports and the wind deflector. An array of the assemblies can be secured to one another at their corners to prevent horizontal separation of the adjacent corners while permitting the PV modules to flex relative to one another so to permit the array of PV modules to follow a contour of the support surface.

  1. Wind power forecasting : state-of-the-art 2009.

    SciTech Connect (OSTI)

    Monteiro, C.; Bessa, R.; Miranda, V.; Botterud, A.; Wang, J.; Conzelmann, G.; Decision and Information Sciences; INESC Porto

    2009-11-20

    Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and uncertainty in wind power and to more efficiently operate power systems with large wind power penetrations. Moreover, in a market environment, the wind power contribution to the generation portofolio becomes important in determining the daily and hourly prices, as variations in the estimated wind power will influence the clearing prices for both energy and operating reserves. With the increasing penetration of wind power, WPF is quickly becoming an important topic for the electric power industry. System operators (SOs), generating companies (GENCOs), and regulators all support efforts to develop better, more reliable and accurate forecasting models. Wind farm owners and operators also benefit from better wind power prediction to support competitive participation in electricity markets against more stable and dispatchable energy sources. In general, WPF can be used for a number of purposes, such as: generation and transmission maintenance planning, determination of operating reserve requirements, unit commitment, economic dispatch, energy storage optimization (e.g., pumped hydro storage), and energy trading. The objective of this report is to review and analyze state-of-the-art WPF models and their application to power systems operations. We first give a detailed description of the methodologies underlying state-of-the-art WPF models. We then look at how WPF can be integrated into power system operations, with specific focus on the unit commitment problem.

  2. Indianapolis Offers a Lesson on Driving Demand

    Broader source: Energy.gov [DOE]

    Successful program managers know that understanding the factors that drive homeowners to make upgrades is critical to the widespread adoption of energy efficiency. What better place to learn about driving demand for upgrades than in Indianapolis, America's most famous driving city?

  3. Energy Demand (released in AEO2010)

    Reports and Publications (EIA)

    2010-01-01

    Growth in U.S. energy use is linked to population growth through increases in demand for housing, commercial floorspace, transportation, manufacturing, and services. This affects not only the level of energy use, but also the mix of fuels and consumption by sector.

  4. Demand Response and Energy Storage Integration Study - Past Workshops...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Demand Response and Energy Storage Integration Study - Past Workshops Demand Response and Energy Storage Integration Study - Past Workshops The project was initiated and informed...

  5. Draft Chapter 3: Demand-Side Resources | Department of Energy

    Office of Environmental Management (EM)

    Demand-Side Resources Draft Chapter 3: Demand-Side Resources Utilities in many states have been implementing energy efficiency and load management programs (collectively called ...

  6. Agreement Template for Energy Conservation and Demand Side Management...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Agreement Template for Energy Conservation and Demand Side Management Services Agreement Template for Energy Conservation and Demand Side Management Services Template agreement ...

  7. Estimating Costs and Efficiency of Storage, Demand, and Heat...

    Energy Savers [EERE]

    Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters A water heater's energy ...

  8. Estimating Costs and Efficiency of Storage, Demand, and Heat...

    Energy Savers [EERE]

    Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters A water heater's ...

  9. Tool Improves Electricity Demand Predictions to Make More Room...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Tool Improves Electricity Demand Predictions to Make More Room for Renewables Tool Improves Electricity Demand Predictions to Make More Room for Renewables October 3, 2011 - ...

  10. Reducing Energy Demand in Buildings Through State Energy Codes...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Reducing Energy Demand in Buildings Through State Energy Codes Reducing Energy Demand in ... More Documents & Publications Technology Performance Exchange - 2013 BTO Peer Review ...

  11. Estimating Costs and Efficiency of Storage, Demand, and Heat...

    Office of Environmental Management (EM)

    Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters A water heater's...

  12. Can Automotive Battery Recycling Help Meet Lithium Demand? |...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Can Automotive Battery Recycling Help Meet Lithium Demand? Title Can Automotive Battery Recycling Help Meet Lithium Demand? Publication Type Presentation Year of Publication 2013...

  13. SGDP Report Now Available: Interoperability of Demand Response...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    SGDP Report Now Available: Interoperability of Demand Response Resources Demonstration in NY (February 2015) SGDP Report Now Available: Interoperability of Demand Response ...

  14. SGDP Report: Interoperability of Demand Response Resources Demonstrati...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    SGDP Report: Interoperability of Demand Response Resources Demonstration in NY (February 2015) SGDP Report: Interoperability of Demand Response Resources Demonstration in NY ...

  15. FERC Presendation: Demand Response as Power System Resources...

    Office of Environmental Management (EM)

    FERC Presendation: Demand Response as Power System Resources, October 29, 2010 FERC Presendation: Demand Response as Power System Resources, October 29, 2010 Federal Energy ...

  16. Implementation Proposal for the National Action Plan on Demand...

    Energy Savers [EERE]

    Implementation Proposal for the National Action Plan on DemandResponse - July 2011 Implementation Proposal for the National Action Plan on Demand Response - July 2011 Report to ...

  17. Sustainable Energy Resources for Consumers (SERC) - On-Demand...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    On-Demand Tankless Water Heaters Sustainable Energy Resources for Consumers (SERC) - On-Demand Tankless Water Heaters This presentation, aimed at Sustainable Energy Resources for ...

  18. High-Performance with Solar Electric Reduced Peak Demand: Premier...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    with Solar Electric Reduced Peak Demand: Premier Homes Rancho Cordoba, CA - Building America Top Innovation High-Performance with Solar Electric Reduced Peak Demand: Premier Homes ...

  19. Structuring Rebate and Incentive Programs for Sustainable Demand...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Structuring Rebate and Incentive Programs for Sustainable Demand Structuring Rebate and ... Loan Rates and Demand Peer Exchange Call on Financing and Revenue: Bond Funding Marketing ...

  20. Structuring Rebate and Incentive Programs for Sustainable Demand...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Structuring Rebate and Incentive Programs for Sustainable Demand Structuring Rebate and Incentive Programs for Sustainable Demand Better Buildings Neighborhood Program Peer...

  1. Using Mobile Applications to Generate Customer Demand | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Using Mobile Applications to Generate Customer Demand Using Mobile Applications to Generate Customer Demand Better Buildings Residential Network Peer Exchange Call Series: Using...

  2. Strategies for Marketing and Driving Demand for Commercial Financing...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Marketing and Driving Demand for Commercial Financing Products Strategies for Marketing and Driving Demand for Commercial Financing Products Better Buildings Neighborhood Program ...

  3. Model documentation coal market module of the National Energy Modeling System

    SciTech Connect (OSTI)

    1997-02-01

    This report documents the objectives and the conceptual and methodological approach used in the development of the Coal Production Submodule (CPS). It provides a description of the CPS for model analysts and the public. The Coal Market Module provides annual forecasts of prices, production, and consumption of coal.

  4. Short-Term Energy Outlook Model Documentation: Petroleum Products Supply Module

    Reports and Publications (EIA)

    2013-01-01

    The Petroleum Products Supply Module of the Short-Term Energy Outlook (STEO) model provides forecasts of petroleum refinery inputs (crude oil, unfinished oils, pentanes plus, liquefied petroleum gas, motor gasoline blending components, and aviation gasoline blending components) and refinery outputs (motor gasoline, jet fuel, distillate fuel, residual fuel, liquefied petroleum gas, and other petroleum products).

  5. Development and Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices

    Broader source: Energy.gov [DOE]

    Development and Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices

  6. Recently released EIA report presents international forecasting data

    SciTech Connect (OSTI)

    1995-05-01

    This report presents information from the Energy Information Administration (EIA). Articles are included on international energy forecasting data, data on the use of home appliances, gasoline prices, household energy use, and EIA information products and dissemination avenues.

  7. Value of Improved Short-Term Wind Power Forecasting

    SciTech Connect (OSTI)

    Hodge, B. M.; Florita, A.; Sharp, J.; Margulis, M.; Mcreavy, D.

    2015-02-01

    This report summarizes an assessment of improved short-term wind power forecasting in the California Independent System Operator (CAISO) market and provides a quantification of its potential value.

  8. Summer gasoline price forecast slightly higher, but drivers still...

    U.S. Energy Information Administration (EIA) Indexed Site

    In its new monthly forecast, the U.S. Energy Information Administration said the retail price for regular grade gasoline will average 2.21 per gallon this summer. While that's 17 ...

  9. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

    With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

  10. Radar Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

    1) To provide profiles of the horizontal wind to be used to test and validate short-term cloud advection forecasts for solar-energy applications and 2) to provide vertical ...

  11. PBL FY 2002 Second Quarter Review Forecast of Generation Accumulated...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Slice true-ups, and actual expense levels. Any variation of these can change the net revenue situation. FY 2002 Forecasted Second Quarter Results 170 (418) FY 2002 Unaudited...

  12. Forecasting the oil-gasoline price relationship: should we care...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    (2007, EE) obtain similar results on a panel of 15 OECD countries, with annual data ... Results Point forecasts of the N.Y. gasoline price 26 Panel (a): daily data Model MSFE ...

  13. New Forecasting Tools Enhance Wind Energy Integration In Idaho...

    Office of Environmental Management (EM)

    New Forecasting Tools Enhance Wind Energy Integration in Idaho and Oregon Page 1 Under the ... (RIT) that enables grid operators to use wind energy more cost-effectively to serve ...

  14. Solar Trackers Market Forecast | OpenEI Community

    Open Energy Info (EERE)

    Solar Trackers Market Forecast Home John55364's picture Submitted by John55364(100) Contributor 12 May, 2015 - 03:54 Solar Trackers Market - Global Industry Analysis, Size, Share,...

  15. Energy Forecasting Framework and Emissions Consensus Tool (EFFECT...

    Open Energy Info (EERE)

    Tool (EFFECT) EFFECT is an open, Excel-based modeling tool used to forecast greenhouse gas emissions from a range of development scenarios at the regional and national levels....

  16. Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory Levels

    Reports and Publications (EIA)

    2003-01-01

    This paper presents a short-term monthly forecasting model of West Texas Intermediate crude oil spot price using Organization for Economic Cooperation and Development (OECD) petroleum inventory levels.

  17. ARM - PI Product - CCPP-ARM Parameterization Testbed Model Forecast...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : CCPP-ARM Parameterization Testbed Model Forecast Data Dataset contains the NCAR...

  18. Forecasting neutrino masses from combining KATRIN and the CMB observations:

    Office of Scientific and Technical Information (OSTI)

    Frequentist and Bayesian analyses (Journal Article) | SciTech Connect SciTech Connect Search Results Journal Article: Forecasting neutrino masses from combining KATRIN and the CMB observations: Frequentist and Bayesian analyses Citation Details In-Document Search Title: Forecasting neutrino masses from combining KATRIN and the CMB observations: Frequentist and Bayesian analyses We present a showcase for deriving bounds on the neutrino masses from laboratory experiments and cosmological

  19. 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National

    Office of Scientific and Technical Information (OSTI)

    Laboratory (Technical Report) | SciTech Connect 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory Citation Details In-Document Search Title: 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory When considering the amount of shortwave radiation incident on a photovoltaic solar array and, therefore, the amount and stability of the energy output from the system, clouds represent the greatest source of short-term (i.e., scale of minutes to

  20. Modeling and forecasting the distribution of Vibrio vulnificus in

    Office of Scientific and Technical Information (OSTI)

    Chesapeake Bay (Journal Article) | SciTech Connect Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay Citation Details In-Document Search Title: Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters

  1. Study forecasts disappearance of conifers due to climate change

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Study forecasts disappearance of conifers due to climate change Study forecasts disappearance of conifers due to climate change New results, reported in a paper released today in the journal Nature Climate Change, suggest that global models may underestimate predictions of forest death. December 21, 2015 Los Alamos scientist Nate McDowell discusses how climate change is killing trees with PBS NewsHour reporter Miles O'Brien. Los Alamos scientist Nate McDowell discusses how climate change is

  2. Demand Side Management in the Smart Grid: Information Processing for the Power Switch

    SciTech Connect (OSTI)

    Alizadeh, Mahnoosh; LI, Xiao; Wang, Zhifang; Scagilone, Anna; Melton, Ronald B.

    2012-09-01

    In this article we discuss the most recent developments in the area of load management, and consider possible interaction schemes of novel architectures with distributed energy resources (DER). In order to handle the challenges faced by tomorrow’s smart grid, which are caused by volatile load and generation profiles (from the large number of plug-in EVs and from renewable integration), the conventional grid operating principle of load-following needs to be changed into load-shaping or generation-following. Demand Side Management will be a most promising and powerful solution to the above challenges. However, many other issues such as load forecasting, pricing structure, market policy, renewable integration interface, and even the AC/DC implementation at the distribution side, need to be taken into the design in order to search for the most effective and applicable solution.

  3. NERSC Python Modules

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    NERSC Python Modules NERSC Python Modules Python Interpreter Modules To use the NERSC-built installation, type: module load python This loads the default version of the following useful core modules: python_base: Python 2.7.x module. numpy: Defines the numerical array and matrix type and basic operations on them. scipy: Uses numpy to do advanced math, signal processing, optimization, statistics and much more. matplotlib: Plotting/visualization library. ipython: Interactive python shell offering

  4. National Oceanic and Atmospheric Administration Provides Forecasting Support for CLASIC and CHAPS 2007

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    NOAA Provides Forecasting Support for CLASIC and CHAPS 2007 Forecasting Challenge While weather experiments in the heart of Tornado Alley typically focus on severe weather, the CLASIC and CHAPS programs will have different emphases. Forecasters from the National Oceanic and Atmospheric Administration in Norman, Okla. will provide weather forecasting support to these two Department of Energy experiments based in the state. Forecasting support for meteorological research field programs usually

  5. Home Network Technologies and Automating Demand Response

    SciTech Connect (OSTI)

    McParland, Charles

    2009-12-01

    Over the past several years, interest in large-scale control of peak energy demand and total consumption has increased. While motivated by a number of factors, this interest has primarily been spurred on the demand side by the increasing cost of energy and, on the supply side by the limited ability of utilities to build sufficient electricity generation capacity to meet unrestrained future demand. To address peak electricity use Demand Response (DR) systems are being proposed to motivate reductions in electricity use through the use of price incentives. DR systems are also be design to shift or curtail energy demand at critical times when the generation, transmission, and distribution systems (i.e. the 'grid') are threatened with instabilities. To be effectively deployed on a large-scale, these proposed DR systems need to be automated. Automation will require robust and efficient data communications infrastructures across geographically dispersed markets. The present availability of widespread Internet connectivity and inexpensive, reliable computing hardware combined with the growing confidence in the capabilities of distributed, application-level communications protocols suggests that now is the time for designing and deploying practical systems. Centralized computer systems that are capable of providing continuous signals to automate customers reduction of power demand, are known as Demand Response Automation Servers (DRAS). The deployment of prototype DRAS systems has already begun - with most initial deployments targeting large commercial and industrial (C & I) customers. An examination of the current overall energy consumption by economic sector shows that the C & I market is responsible for roughly half of all energy consumption in the US. On a per customer basis, large C & I customers clearly have the most to offer - and to gain - by participating in DR programs to reduce peak demand. And, by concentrating on a small number of relatively sophisticated energy consumers, it has been possible to improve the DR 'state of the art' with a manageable commitment of technical resources on both the utility and consumer side. Although numerous C & I DR applications of a DRAS infrastructure are still in either prototype or early production phases, these early attempts at automating DR have been notably successful for both utilities and C & I customers. Several factors have strongly contributed to this success and will be discussed below. These successes have motivated utilities and regulators to look closely at how DR programs can be expanded to encompass the remaining (roughly) half of the state's energy load - the light commercial and, in numerical terms, the more important residential customer market. This survey examines technical issues facing the implementation of automated DR in the residential environment. In particular, we will look at the potential role of home automation networks in implementing wide-scale DR systems that communicate directly to individual residences.

  6. Demand for superpremium needle cokes on upswing

    SciTech Connect (OSTI)

    Acciarri, J.A.; Stockman, G.H. )

    1989-12-01

    The authors discuss how recent supply shortages of super-premium quality needle cokes, plus the expectation of increased shortfalls in the future, indicate that refiners should consider upgrading their operations to fill these demands. Calcined, super-premium needle cokes are currently selling for as much as $550/metric ton, fob producer, and increasing demand will continue the upward push of the past year. Needle coke, in its calcined form, is the major raw material in the manufacture of graphite electrodes. Used in steelmaking, graphite electrodes are the electrical conductors that supply the heat source, through arcing electrode column tips, to electric arc steel furnaces. Needle coke is commercially available in three grades - super premium, premium, and intermediate. Super premium is used to produce electrodes for the most severe electric arc furnace steelmaking applications, premium for electrodes destined to less severe operations, and intermediate for even less critical needs.

  7. What is a High Electric Demand Day?

    Broader source: Energy.gov [DOE]

    This presentation by T. McNevin of the New Jersey Bureau of Air Quality Planning was part of the July 2008 Webcast sponsored by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Weatherization and Intergovernmental Program Clean Energy and Air Quality Integration Initiative that was titled Role of Energy Efficiency and Renewable Energy in Improving Air Quality and Addressing Greenhouse Gas Reduction Goals on High Electric Demand Days.

  8. Retail Demand Response in Southwest Power Pool

    Energy Savers [EERE]

    LBNL-1470E Retail Demand Response in Southwest Power Pool Ranjit Bharvirkar, Grayson Heffner and Charles Goldman Lawrence Berkeley National Laboratory Environmental Energy Technologies Division January 2009 The work described in this report was funded by the Office of Electricity Delivery and Energy Reliability, Permitting, Siting and Analysis of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY Disclaimer This document was

  9. Price-responsive demand management for a smart grid world

    SciTech Connect (OSTI)

    Chao, Hung-po

    2010-01-15

    Price-responsive demand is essential for the success of a smart grid. However, existing demand-response programs run the risk of causing inefficient price formation. This problem can be solved if each retail customer could establish a contract-based baseline through demand subscription before joining a demand-response program. (author)

  10. Ballasted photovoltaic module and module arrays

    DOE Patents [OSTI]

    Botkin, Jonathan; Graves, Simon; Danning, Matt

    2011-11-29

    A photovoltaic (PV) module assembly including a PV module and a ballast tray. The PV module includes a PV device and a frame. A PV laminate is assembled to the frame, and the frame includes an arm. The ballast tray is adapted for containing ballast and is removably associated with the PV module in a ballasting state where the tray is vertically under the PV laminate and vertically over the arm to impede overt displacement of the PV module. The PV module assembly can be installed to a flat commercial rooftop, with the PV module and the ballast tray both resting upon the rooftop. In some embodiments, the ballasting state includes corresponding surfaces of the arm and the tray being spaced from one another under normal (low or no wind) conditions, such that the frame is not continuously subjected to a weight of the tray.

  11. A hybrid inventory management system respondingto regular demand and surge demand

    SciTech Connect (OSTI)

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

    2014-06-01

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

  12. Dramatic Demand Reduction In The Desert Southwest

    SciTech Connect (OSTI)

    Boehm, Robert; Hsieh, Sean; Lee, Joon; Baghzouz, Yahia; Cross, Andrew; Chatterjee, Sarah

    2015-07-06

    This report summarizes a project that was funded to the University of Nevada Las Vegas (UNLV), with subcontractors Pulte Homes and NV Energy. The project was motivated by the fact that locations in the Desert Southwest portion of the US demonstrate very high peak electrical demands, typically in the late afternoons in the summer. These high demands often require high priced power to supply the needs, and the large loads can cause grid supply problems. An approach was proposed through this contact that would reduce the peak electrical demands to an anticipated 65% of what code-built houses of the similar size would have. It was proposed to achieve energy reduction through four approaches applied to a development of 185 homes in northwest part of Las Vegas named Villa Trieste. First, the homes would all be highly energy efficient. Secondly, each house would have a PV array installed on it. Third, an advanced demand response technique would be developed to allow the resident to have some control over the energy used. Finally, some type of battery storage would be used in the project. Pulte Homes designed the houses. The company considered initial cost vs. long-term savings and chose options that had relatively short paybacks. HERS (Home Energy Rating Service) ratings for the homes are approximately 43 on this scale. On this scale, code-built homes rate at 100, zero energy homes rate a 0, and Energy Star homes are 85. In addition a 1.764 Wp (peak Watt) rated PV array was used on each house. This was made up of solar shakes that were in visual harmony with the roofing material used. A demand response tool was developed to control the amount of electricity used during times of peak demand. While demand response techniques have been used in the utility industry for some time, this particular approach is designed to allow the customer to decide the degree of participation in the response activity. The temperature change in the residence can be decided by the residents by adjusting settings. In a sense the customer can choose between greater comfort and greater money savings during demand response circumstances. Finally a battery application was to be considered. Initially it was thought that a large battery (probably a sodium-sulfur type) would be installed. However, after the contract was awarded, it was determined that a single, centrally-located battery system would not be appropriate for many reasons, including that with the build out plan there would not be any location to put it. The price had risen substantially since the budget for the project was put together. Also, that type of battery has to be kept hot all the time, but its use was only sought for summer operation. Hence, individual house batteries would be used, and these are discussed at the end of this report. Many aspects of the energy use for climate control in selected houses were monitored before residents moved in. This was done both to understand the magnitude of the energy flows but also to have data that could be compared to the computer simulations. The latter would be used to evaluate various aspects of our plan. It was found that good agreement existed between actual energy use and computed energy use. Hence, various studies were performed via simulations. Performance simulations showed the impact on peak energy usage between a code built house of same size and shape compared to the Villa Trieste homes with and without the PV arrays on the latter. Computations were also used to understand the effect of varying orientations of the houses in this typical housing development, including the effect of PV electrical generation. Energy conservation features of the Villa Trieste homes decreased the energy use during peak times (as well as all others), but the resulting decreased peak occurred at about the same time as the code-built houses. Consideration of the PV generation decreases the grid energy use further during daylight hours, but did not extend long enough many days to decrease the peak. Hence, a demand response approach, as planned, was needed. With participation of the residents in the demand response program developed does enable the houses to reduce the peak demand between 66% and 72%, depending on the built years. This was addressed fully in the latter part the study and is described in the latter part of this report.

  13. Demand Response - Policy: More Information | Department of Energy

    Energy Savers [EERE]

    Demand Response - Policy: More Information Demand Response - Policy: More Information OE's commitment to ensuring non-wires options to modernize the nation's electricity delivery system includes ongoing support of a number of national and regional activities in support of demand response. The New England Demand Response Initiative (NEDRI), OE's initial endeavor to assist states with non-wire solutions, was created to develop a comprehensive, coordinated set of demand response programs for the

  14. Forecasting the 2013–2014 influenza season using Wikipedia

    SciTech Connect (OSTI)

    Hickmann, Kyle S.; Fairchild, Geoffrey; Priedhorsky, Reid; Generous, Nicholas; Hyman, James M.; Deshpande, Alina; Del Valle, Sara Y.; Salathé, Marcel

    2015-05-14

    Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are applied to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.

  15. Forecasting the 2013–2014 influenza season using Wikipedia

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Hickmann, Kyle S.; Fairchild, Geoffrey; Priedhorsky, Reid; Generous, Nicholas; Hyman, James M.; Deshpande, Alina; Del Valle, Sara Y.; Salathé, Marcel

    2015-05-14

    Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are appliedmore » to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.« less

  16. Module 4- Budgeting

    Broader source: Energy.gov [DOE]

    This module outlines basic costing concepts such as control accounts, work packages and planning packages.

  17. Modules Software Environment

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Environment » Modules Environment Modules Software Environment NERSC uses the module utility to manage nearly all software. There are two huge advantages of the module approach: NERSC can provide many different versions and/or installations of a single software package on a given machine, including a default version as well as several older and newer versions; and Users can easily switch to different versions or installations without having to explicitly specify different paths. With modules,

  18. LNG demand, shipping will expand through 2010

    SciTech Connect (OSTI)

    True, W.R.

    1998-02-09

    The 1990s, especially the middle years, have witnessed a dramatic turnaround in the growth of liquefied-natural-gas demand which has tracked equally strong natural-gas demand growth. This trend was underscored late last year by several annual studies of world LNG demand and shipping. As 1998 began, however, economic turmoil in Asian financial markets has clouded near-term prospects for LNG in particular and all energy in general. But the extent of damage to energy markets is so far unclear. A study by US-based Institute of Gas Technology, Des Plaines, IL, reveals that LNG imports worldwide have climbed nearly 8%/year since 1980 and account for 25% of all natural gas traded internationally. In the mid-1970s, the share was only 5%. In 1996, the most recent year for which complete data are available, world LNG trade rose 7.7% to a record 92 billion cu m, outpacing the overall consumption for natural gas which increased 4.7% in 1996. By 2015, says the IGT study, natural-gas use would surpass coal as the world`s second most widely used fuel, after petroleum. Much of this growth will occur in the developing countries of Asia where gas use, before the current economic crisis began, was projected to grow 8%/year through 2015. Similar trends are reflected in another study of LNG trade released at year end 1997, this from Ocean Shipping Consultants Ltd., Surrey, U.K. The study was done too early, however, to consider the effects of the financial problems roiling Asia.

  19. Demand-Side Response from Industrial Loads

    SciTech Connect (OSTI)

    Starke, Michael R; Alkadi, Nasr E; Letto, Daryl; Johnson, Brandon; Dowling, Kevin; George, Raoule; Khan, Saqib

    2013-01-01

    Through a research study funded by the Department of Energy, Smart Grid solutions company ENBALA Power Networks along with the Oak Ridge National Laboratory (ORNL) have geospatially quantified the potential flexibility within industrial loads to leverage their inherent process storage to help support the management of the electricity grid. The study found that there is an excess of 12 GW of demand-side load flexibility available in a select list of top industrial facilities in the United States. Future studies will expand on this quantity of flexibility as more in-depth analysis of different industries is conducted and demonstrations are completed.

  20. Survey of Variable Generation Forecasting in the West: August 2011 - June 2012

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2012-04-01

    This report surveyed Western Interconnection Balancing Authorities regarding their implementation of variable generation forecasting, the lessons learned to date, and recommendations they would offer to other Balancing Authorities who are considering variable generation forecasting. Our survey found that variable generation forecasting is at an early implementation stage in the West. Eight of the eleven Balancing Authorities interviewed began forecasting in 2008 or later. It also appears that less than one-half of the Balancing Authorities in the West are currently utilizing variable generation forecasting, suggesting that more Balancing Authorities in the West will engage in variable generation forecasting should more variable generation capacity be added.

  1. 1980 annual report to Congress: Volume three, Forecasts: Summary

    SciTech Connect (OSTI)

    Not Available

    1981-05-27

    This report presents an overview of forecasts of domestic energy consumption, production, and prices for the year 1990. These results are selected from more detailed projections prepared and published in Volume 3 of the Energy Information Administration 1980 Annual Report to Congress. This report focuses specifically upon the 1980's and concentrates upon similarities and differences in the domestic energy system, as forecast, compared to the national experience in the years immediately following the 1973--1974 oil embargo. Interest in the 1980's stems not only from its immediacy in time, but also from its importance as a time in which certain adjustments to higher energy prices are expected to take place. The forecasts presented do not attempt to account for all of this wide range of potentially important forces that could conceivably alter the energy situation. Instead, the projections are based on a particular set of assumptions that seems reasonable in light of what is currently known. 9 figs., 25 tabs.

  2. DOE/EIA-M066(2010) Commercial Sector Demand Module

    Gasoline and Diesel Fuel Update (EIA)

    the State Energy Data System (SEDS) historical commercial sector consumption, applying an additive correction term to ensure that simulated model results correspond to published...

  3. DOE/EIA-M066(2009) Commercial Sector Demand Module

    Gasoline and Diesel Fuel Update (EIA)

    the State Energy Data System (SEDS) historical commercial sector consumption, applying an additive correction term to ensure that simulated model results correspond to published...

  4. CCPP-ARM Parameterization Testbed Model Forecast Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Klein, Stephen

    Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).

  5. CCPP-ARM Parameterization Testbed Model Forecast Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Klein, Stephen

    2008-01-15

    Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).

  6. California: Geothermal Plant to Help Meet High Lithium Demand...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Geothermal Plant to Help Meet High Lithium Demand California: Geothermal Plant to Help Meet High Lithium Demand May 21, 2013 - 5:54pm Addthis Through funding provided by the...

  7. Tankless or Demand-Type Water Heaters | Department of Energy

    Energy Savers [EERE]

    or Demand-Type Water Heaters Tankless or Demand-Type Water Heaters Diagram of a tankless water heater. Diagram of a tankless water heater. Tankless water heaters, also known as ...

  8. Demand Response: Lessons Learned with an Eye to the Future |...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Demand Response: Lessons Learned with an Eye to the Future Demand Response: Lessons Learned with an Eye to the Future July 11, 2013 - 11:56am Addthis Patricia A. Hoffman Patricia...

  9. A National Forum on Demand Response: Results on What Remains...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Part of the July 2011 Implementation Proposal called for a "National Forum" on demand response to be conducted by DOE and FERC. Given the rapid development of the demand response ...

  10. California Geothermal Power Plant to Help Meet High Lithium Demand...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    California Geothermal Power Plant to Help Meet High Lithium Demand California Geothermal Power Plant to Help Meet High Lithium Demand September 20, 2012 - 1:15pm Addthis Ever ...

  11. Tankless or Demand-Type Water Heaters | Department of Energy

    Office of Environmental Management (EM)

    Tankless or Demand-Type Water Heaters Tankless or Demand-Type Water Heaters Diagram of a tankless water heater. Diagram of a tankless water heater. Tankless water heaters, also...

  12. A Hierarchical Framework for Demand-Side Frequency Control (Conference...

    Office of Scientific and Technical Information (OSTI)

    A Hierarchical Framework for Demand-Side Frequency Control Citation Details In-Document Search Title: A Hierarchical Framework for Demand-Side Frequency Control With large-scale ...

  13. Industrial demand side management: A status report

    SciTech Connect (OSTI)

    Hopkins, M.F.; Conger, R.L.; Foley, T.J.

    1995-05-01

    This report provides an overview of and rationale for industrial demand side management (DSM) programs. Benefits and barriers are described, and data from the Manufacturing Energy Consumption Survey are used to estimate potential energy savings in kilowatt hours. The report presents types and examples of programs and explores elements of successful programs. Two in-depth case studies (from Boise Cascade and Eli Lilly and Company) illustrate two types of effective DSM programs. Interviews with staff from state public utility commissions indicate the current thinking about the status and future of industrial DSM programs. A comprehensive bibliography is included, technical assistance programs are listed and described, and a methodology for evaluating potential or actual savings from projects is delineated.

  14. International Transportation Energy Demand Determinants (ITEDD): Prototype Results for China

    U.S. Energy Information Administration (EIA) Indexed Site

    Jim Turnure, Director Office of Energy Consumption & Efficiency Analysis, EIA EIA Conference: Asian Energy Demand July 14, 2014 | Washington, DC International Transportation Energy Demand Determinants (ITEDD): Prototype Results for China Dawn of new global oil market paradigm? 2 Jim Turnure, EIA Conference July 14, 2014 * Conventional wisdom has centered around $100-120/barrel oil and 110-115 million b/d global liquid fuel demand in the long term (2030-2040) * Demand in non-OECD may push

  15. FERC Presendation: Demand Response as Power System Resources, October 29,

    Energy Savers [EERE]

    2010 | Department of Energy FERC Presendation: Demand Response as Power System Resources, October 29, 2010 FERC Presendation: Demand Response as Power System Resources, October 29, 2010 Federal Energy Regulatory Commission (FERC) presentation on demand response as power system resources before the Electicity Advisory Committee, October 29, 2010 PDF icon Demand Response as Power System Resources More Documents & Publications Ancillary Service Revenue Potential for Geothermal Generators in

  16. Marketing & Driving Demand Collaborative - Social Media Tools & Strategies

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    | Department of Energy & Driving Demand Collaborative - Social Media Tools & Strategies Marketing & Driving Demand Collaborative - Social Media Tools & Strategies Presentation slides from the Better Buildings webinar on January 6, 2011. PDF icon Marketing & Driving Demand Collaborative More Documents & Publications Using Social Media for Long-Term Branding Marketing & Driving Demand: Social Media Tools & Strategies - January 16, 2011 (Text Version) Generating

  17. Using Partnerships to Drive Demand and Provide Services in Communities |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy Partnerships to Drive Demand and Provide Services in Communities Using Partnerships to Drive Demand and Provide Services in Communities Better Buildings Neighborhood Program Multifamily and Low-Income Peer Exchange Call: Using Partnerships to Drive Demand and Provide Services in Communities, February 2, 2012. PDF icon Call Slides and Discussion Summary More Documents & Publications Strategies for Marketing and Driving Demand for Commercial Financing Products

  18. 2010 Assessment of Demand Response and Advanced Metering - Staff Report |

    Energy Savers [EERE]

    Department of Energy Assessment of Demand Response and Advanced Metering - Staff Report 2010 Assessment of Demand Response and Advanced Metering - Staff Report 2010 Assessment of Demand Response and Advanced Metering - Staff Report. The Federal Energy Regulatory Commission's 2010 Demand Response and Advanced Metering Survey (2010 FERC Survey, covering calendar year 2009) indicates that advanced metering penetration (i.e., the fraction of all installed meters that are advanced meters) reached

  19. Hawaii demand-side management resource assessment. Final report, Reference Volume 1: Building prototype analysis

    SciTech Connect (OSTI)

    1995-04-01

    This report provides a detailed description of, and the baseline assumptions and simulation results for, the building prototype simulations conducted for the building types designated in the Work Plan for Demand-side Management Assessment of Hawaii`s Demand-Side Resources (HES-4, Phase 2). This report represents the second revision to the initial building prototype description report provided to DBEDT early in the project. Modifications and revisions to the prototypes, based on further calibration efforts and on comments received from DBEDT Staff have been incorporated into this final version. These baseline prototypes form the basis upon which the DSM measure impact estimates and the DSM measure data base were developed for this project. This report presents detailed information for each of the 17 different building prototypes developed for use with the DOE-21E program (23 buildings in total, including resorts and hotels defined separately for each island) to estimate the impact of the building technologies and measures included in this project. The remainder of this section presents some nomenclature and terminology utilized in the reports, tables, and data bases developed from this project to denote building type and vintage. Section 2 contains a more detailed discussion of the data sources, the definition of the residential sector building prototypes, and results of the DOE-2 analysis. Section 3 provides a similar discussion for the commercial sector. The prototype and baseline simulation results are presented in a separate section for each building type. Where possible, comparison of the baseline simulation results with benchmark data from the ENERGY 2020 model or other demand forecasting models specific to Hawaii is included for each building. Appendix A contains a detailed listing of the commercial sector baseline indoor lighting technologies included in the existing and new prototypes by building type.

  20. Lessons learned in implementing a demand side management contract at the Presidio of San Francisco

    SciTech Connect (OSTI)

    Sartor, D.; Munn, M.

    1998-06-01

    The National Park Service (NSP) recently completed the implementation phase of its Power Saving Partners (PSP) Demand Side Management (DSM) contract with the local utility, Pacific Gas and Electric (PG&E). Through the DSM contract, NPS will receive approximately $4.1 million over eight years in payment for saving 61 kW of electrical demand, 179,000 km of electricity per year, and 1.1 million therms of natural gas per year. These payments are for two projects: the installation of high-efficiency lighting systems at the Thoreau Center for Sustainability and the replacement of an old central boiler plant with new, distributed boilers. Although these savings and payments are substantial, the electrical savings and contract payments fall well short of the projected 1,700 kW of electrical demand, 8 million kwh of annual electricity savings, and $11 million in payments, anticipated at the project's onset. Natural gas savings exceeded the initial forecast of 800,000 therms per year. The DSM contract payments did not meet expectations for a variety of reasons which fall into two broad categories: first, many anticipated projects were not constructed, and second, some of the projects that were constructed were not included in the program because the cost of implementing the DSM program's measurement and verification (M&V) requirements outweighed anticipated payments. This paper discusses the projects implemented, and examines the decisions made to withdraw some of them from the DSM contract. It also presents the savings that were realized and documented through M&V efforts. Finally, it makes suggestions relative to M&V protocols to encourage all efficiency measures, not just those that are easy to measure.

  1. Impacts of Improved Day-Ahead Wind Forecasts on Power Grid Operations: September 2011

    SciTech Connect (OSTI)

    Piwko, R.; Jordan, G.

    2011-11-01

    This study analyzed the potential benefits of improving the accuracy (reducing the error) of day-ahead wind forecasts on power system operations, assuming that wind forecasts were used for day ahead security constrained unit commitment.

  2. Status of Centralized Wind Power Forecasting in North America: May 2009-May 2010

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2010-04-01

    Report surveys grid wind power forecasts for all wind generators, which are administered by utilities or regional transmission organizations (RTOs), typically with the assistance of one or more wind power forecasting companies.

  3. DOE Releases Latest Report on Energy Savings Forecast of Solid-State Lighting

    Broader source: Energy.gov [DOE]

    DOE has published a new report forecasting the energy savings of LED white-light sources compared with conventional white-light sources. The sixth iteration of the Energy Savings Forecast of Solid...

  4. Module 8- Reporting

    Broader source: Energy.gov [DOE]

    This module illustrates and defines the different cost performance reports (CPR) available for reporting earned value information.

  5. Data Collection and Comparison with Forecasted Unit Sales of Five Lamp

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Types | Department of Energy Collection and Comparison with Forecasted Unit Sales of Five Lamp Types Data Collection and Comparison with Forecasted Unit Sales of Five Lamp Types PDF icon Data Collection and Comparison with Forecasted Unit Sales of Five Lamp Types More Documents & Publications Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability CX-100584 Categorical Exclusion Determination ISSUANCE

  6. Central Wind Power Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2009-12-01

    The report addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America.

  7. Beyond "Partly Sunny": A Better Solar Forecast | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Beyond "Partly Sunny": A Better Solar Forecast Beyond "Partly Sunny": A Better Solar Forecast December 7, 2012 - 10:00am Addthis The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods of cloud coverage. | Photo by Dennis Schroeder/NREL. The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during

  8. A Public-Private-Academic Partnership to Advance Solar Power Forecasting |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy A Public-Private-Academic Partnership to Advance Solar Power Forecasting A Public-Private-Academic Partnership to Advance Solar Power Forecasting UCAR logo2.jpg The University Corporation for Atmospheric Research (UCAR) will develop a solar power forecasting system that advances the state of the science through cutting-edge research. APPROACH UCAR value chain.png The team will develop a solar power forecasting system that advances the state of the science through

  9. Modulating lignin in plants

    DOE Patents [OSTI]

    Apuya, Nestor; Bobzin, Steven Craig; Okamuro, Jack; Zhang, Ke

    2013-01-29

    Materials and methods for modulating (e.g., increasing or decreasing) lignin content in plants are disclosed. For example, nucleic acids encoding lignin-modulating polypeptides are disclosed as well as methods for using such nucleic acids to generate transgenic plants having a modulated lignin content.

  10. Integrating Module - NEMS Documentation

    Reports and Publications (EIA)

    2014-01-01

    Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

  11. Weather forecast-based optimization of integrated energy systems.

    SciTech Connect (OSTI)

    Zavala, V. M.; Constantinescu, E. M.; Krause, T.; Anitescu, M.

    2009-03-01

    In this work, we establish an on-line optimization framework to exploit detailed weather forecast information in the operation of integrated energy systems, such as buildings and photovoltaic/wind hybrid systems. We first discuss how the use of traditional reactive operation strategies that neglect the future evolution of the ambient conditions can translate in high operating costs. To overcome this problem, we propose the use of a supervisory dynamic optimization strategy that can lead to more proactive and cost-effective operations. The strategy is based on the solution of a receding-horizon stochastic dynamic optimization problem. This permits the direct incorporation of economic objectives, statistical forecast information, and operational constraints. To obtain the weather forecast information, we employ a state-of-the-art forecasting model initialized with real meteorological data. The statistical ambient information is obtained from a set of realizations generated by the weather model executed in an operational setting. We present proof-of-concept simulation studies to demonstrate that the proposed framework can lead to significant savings (more than 18% reduction) in operating costs.

  12. Weather Research and Forecasting Model with the Immersed Boundary Method

    Energy Science and Technology Software Center (OSTI)

    2012-05-01

    The Weather Research and Forecasting (WRF) Model with the immersed boundary method is an extension of the open-source WRF Model available for wwww.wrf-model.org. The new code modifies the gridding procedure and boundary conditions in the WRF model to improve WRF's ability to simutate the atmosphere in environments with steep terrain and additionally at high-resolutions.

  13. Review of Wind Energy Forecasting Methods for Modeling Ramping Events

    SciTech Connect (OSTI)

    Wharton, S; Lundquist, J K; Marjanovic, N; Williams, J L; Rhodes, M; Chow, T K; Maxwell, R

    2011-03-28

    Tall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved. In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or 'ramping events' at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument. Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF.WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.

  14. Navy mobility fuels forecasting system report: World petroleum trade forecasts for the year 2000

    SciTech Connect (OSTI)

    Das, S.

    1991-12-01

    The Middle East will continue to play the dominant role of a petroleum supplier in the world oil market in the year 2000, according to business-as-usual forecasts published by the US Department of Energy. However, interesting trade patterns will emerge as a result of the democratization in the Soviet Union and Eastern Europe. US petroleum imports will increase from 46% in 1989 to 49% in 2000. A significantly higher level of US petroleum imports (principally products) will be coming from Japan, the Soviet Union, and Eastern Europe. Several regions, the Far East, Japan, Latin American, and Africa will import more petroleum. Much uncertainty remains about of the level future Soviet crude oil production. USSR net petroleum exports will decrease; however, the United States and Canada will receive some of their imports from the Soviet Union due to changes in the world trade patterns. The Soviet Union can avoid becoming a net petroleum importer as long as it (1) maintains enough crude oil production to meet its own consumption and (2) maintains its existing refining capacities. Eastern Europe will import approximately 50% of its crude oil from the Middle East.

  15. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.; Gomez-Lazaro, E.; Lovholm, A. L.; Berge, E.; Miettinen, J.; Holttinen, H.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Dobschinski, J.

    2013-10-01

    One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer.

  16. Final Report- Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations

    Broader source: Energy.gov [DOE]

    Four major research objectives were completed over the course of this study. Three of the objectives were to evaluate three, new, state-of-the-art solar irradiance forecasting models. The fourth objective was to improve the California independent system operator’s load forecasts by integrating behind-the-meter photovoltaic forecasts.

  17. Automated Demand Response Opportunities in Wastewater Treatment Facilities

    SciTech Connect (OSTI)

    Thompson, Lisa; Song, Katherine; Lekov, Alex; McKane, Aimee

    2008-11-19

    Wastewater treatment is an energy intensive process which, together with water treatment, comprises about three percent of U.S. annual energy use. Yet, since wastewater treatment facilities are often peripheral to major electricity-using industries, they are frequently an overlooked area for automated demand response opportunities. Demand response is a set of actions taken to reduce electric loads when contingencies, such as emergencies or congestion, occur that threaten supply-demand balance, and/or market conditions occur that raise electric supply costs. Demand response programs are designed to improve the reliability of the electric grid and to lower the use of electricity during peak times to reduce the total system costs. Open automated demand response is a set of continuous, open communication signals and systems provided over the Internet to allow facilities to automate their demand response activities without the need for manual actions. Automated demand response strategies can be implemented as an enhanced use of upgraded equipment and facility control strategies installed as energy efficiency measures. Conversely, installation of controls to support automated demand response may result in improved energy efficiency through real-time access to operational data. This paper argues that the implementation of energy efficiency opportunities in wastewater treatment facilities creates a base for achieving successful demand reductions. This paper characterizes energy use and the state of demand response readiness in wastewater treatment facilities and outlines automated demand response opportunities.

  18. Measurement and evaluation techniques for automated demand response demonstration

    SciTech Connect (OSTI)

    Motegi, Naoya; Piette, Mary Ann; Watson, David S.; Sezgen, Osman; ten Hope, Laurie

    2004-08-01

    The recent electricity crisis in California and elsewhere has prompted new research to evaluate demand response strategies in large facilities. This paper describes an evaluation of fully automated demand response technologies (Auto-DR) in five large facilities. Auto-DR does not involve human intervention, but is initiated at a facility through receipt of an external communications signal. This paper summarizes the measurement and evaluation of the performance of demand response technologies and strategies in five large facilities. All the sites have data trending systems such as energy management and control systems (EMCS) and/or energy information systems (EIS). Additional sub-metering was applied where necessary to evaluate the facility's demand response performance. This paper reviews the control responses during the test period, and analyzes demand savings achieved at each site. Occupant comfort issues are investigated where data are available. This paper discusses methods to estimate demand savings and results from demand response strategies at five large facilities.

  19. Research Study - Global Enterprise VoIP Equipment Market Forecasts...

    Open Energy Info (EERE)

    we deeply analyzed the world's main region market conditions that including the product price, profit, capacity, production, capacity utilization, supply, demand and industry...

  20. Incentives for demand-side management

    SciTech Connect (OSTI)

    Reid, M.W.; Brown, J.B.

    1992-01-01

    This report is the first product of an ongoing project to monitor the efforts of states to remove regulatory barriers to, and provide financial incentives for, utility investment in demand-side management (DSM) resources. The project was commissioned by the National Association of Regulatory Utility Commissioners (NARUC) in response to growing interest among regulators for a comprehensive survey of developments in this area. Each state report beings with an overview of the state`s progress toward removing regulatory barriers and providing incentives for DSM. Information is organized under five headings: status; IRP regulations and practice; current treatment of DSM, directions and trends; commission contact person. Where applicable, each overview is followed by one or more sections that report on specific incentive proposals or mechanisms within the state. Information on each proposal or mechanism is organized under eight headings. A notation on each page identifies the utility or other group associated with the proposal or mechanism. The eight headings are as follows: status; background; treatment of cost recovery; treatment of lost revenues/decoupling; treatment of profitability; other features; issues, and additional observations.

  1. Incentives for demand-side management

    SciTech Connect (OSTI)

    Reid, M.W.; Brown, J.B. )

    1992-01-01

    This report is the first product of an ongoing project to monitor the efforts of states to remove regulatory barriers to, and provide financial incentives for, utility investment in demand-side management (DSM) resources. The project was commissioned by the National Association of Regulatory Utility Commissioners (NARUC) in response to growing interest among regulators for a comprehensive survey of developments in this area. Each state report beings with an overview of the state's progress toward removing regulatory barriers and providing incentives for DSM. Information is organized under five headings: status; IRP regulations and practice; current treatment of DSM, directions and trends; commission contact person. Where applicable, each overview is followed by one or more sections that report on specific incentive proposals or mechanisms within the state. Information on each proposal or mechanism is organized under eight headings. A notation on each page identifies the utility or other group associated with the proposal or mechanism. The eight headings are as follows: status; background; treatment of cost recovery; treatment of lost revenues/decoupling; treatment of profitability; other features; issues, and additional observations.

  2. CO2 MONITORING FOR DEMAND CONTROLLED VENTILATION IN COMMERCIAL BUILDINGS

    SciTech Connect (OSTI)

    Fisk, William J.; Sullivan, Douglas P.; Faulkner, David; Eliseeva, Ekaterina

    2010-03-17

    Carbon dioxide (CO{sub 2}) sensors are often deployed in commercial buildings to obtain CO{sub 2} data that are used, in a process called demand-controlled ventilation, to automatically modulate rates of outdoor air ventilation. The objective is to keep ventilation rates at or above design specifications and code requirements and also to save energy by avoiding excessive ventilation rates. Demand controlled ventilation is most often used in spaces with highly variable and sometime dense occupancy. Reasonably accurate CO{sub 2} measurements are needed for successful demand controlled ventilation; however, prior research has suggested substantial measurement errors. Accordingly, this study evaluated: (a) the accuracy of 208 CO{sub 2} single-location sensors located in 34 commercial buildings, (b) the accuracy of four multi-location CO{sub 2} measurement systems that utilize tubing, valves, and pumps to measure at multiple locations with single CO{sub 2} sensors, and (c) the spatial variability of CO{sub 2} concentrations within meeting rooms. The field studies of the accuracy of single-location CO{sub 2} sensors included multi-concentration calibration checks of 90 sensors in which sensor accuracy was checked at multiple CO{sub 2} concentrations using primary standard calibration gases. From these evaluations, average errors were small, -26 ppm and -9 ppm at 760 and 1010 ppm, respectively; however, the averages of the absolute values of error were 118 ppm (16%) and 138 ppm (14%), at concentrations of 760 and 1010 ppm, respectively. The calibration data are generally well fit by a straight line as indicated by high values of R{sup 2}. The Title 24 standard specifies that sensor error must be certified as no greater than 75 ppm for a period of five years after sensor installation. At 1010 ppm, 40% of sensors had errors greater than {+-}75 ppm and 31% of sensors has errors greater than {+-}100 ppm. At 760 ppm, 47% of sensors had errors greater than {+-}75 ppm and 37% of sensors had errors greater than {+-}100 ppm. A significant fraction of sensors had errors substantially larger than 100 ppm. For example, at 1010 ppm, 19% of sensors had an error greater than 200 ppm and 13% of sensors had errors greater than 300 ppm. The field studies also included single-concentration calibration checks of 118 sensors at the concentrations encountered in the buildings, which were normally less than 500 ppm during the testing. For analyses, these data were combined with data from the calibration challenges at 510 ppm obtained during the multi-concentration calibration checks. For the resulting data set, the average error was 60 ppm and the average of the absolute value of error was 154 ppm. Statistical analyses indicated that there were statistically significant differences between the average accuracies of sensors from different manufacturers. Sensors with a 'single lamp single wavelength' design tended to have a statistically significantly smaller average error than sensors with other designs except for 'single lamp dual wavelength' sensors, which did not have a statistically significantly lower accuracy. Sensor age was not consistently a statistically significant predictor of error.

  3. Thermoelectrics Partnership: Automotive Thermoelectric Modules...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Solution for Automotive Thermoelectric Modules Application Thermoelectrics Partnership: Automotive Thermoelectric Modules with Scalable Thermo- and Electro-Mechanical Interfaces

  4. Investigation of structural changes in residential electricity demand

    SciTech Connect (OSTI)

    Chern, W.S.; Bouis, H.E.

    1982-09-23

    The purpose of this study was to investigate the stability of aggregate national residential electricity demand coefficients over time. The hypothesis is maintained that the aggregate residential demand is the sum of various end-use demand components. Since the end-use composition changes over time, the demand relationship may change as well. Since the end-use composition differs among regions, the results obtained from this study can be used for making inferences about regional differences in electricity demand relationships. There are two additional sources for a possible structural change. One is that consumers may react differently to declining and rising prices, secondly, the impact of the 1973 oil embargo may have shifted demand preferences. The electricity demand model used for this study is presented. A moving regression method was employed to investigate changes in residential electricity demand over time. The statistical results show a strikingly consistent pattern of change for most of the structural variables. The most important finding of this study is that the estimated structure of residential electricity demand changes systematically over time as a result of changes in the characteristics (both durability and saturation level) of the stock of appliances. Furthermore, there is not strong evidence that the structural changes in demand occurred due to either the reversal of the declining trend of electricity prices or the impact of the 1973 oil embarge. (LCL)

  5. Opportunities for Automated Demand Response in California Agricultural Irrigation

    SciTech Connect (OSTI)

    Olsen, Daniel; Aghajanzadeh, Arian; McKane, Aimee

    2015-08-01

    Pumping water for agricultural irrigation represents a significant share of California’s annual electricity use and peak demand. It also represents a large source of potential flexibility, as farms possess a form of storage in their wetted soil. By carefully modifying their irrigation schedules, growers can participate in demand response without adverse effects on their crops. This report describes the potential for participation in demand response and automated demand response by agricultural irrigators in California, as well as barriers to widespread participation. The report first describes the magnitude, timing, location, purpose, and manner of energy use in California. Typical on-­farm controls are discussed, as well as common impediments to participation in demand response and automated demand response programs. Case studies of demand response programs in California and across the country are reviewed, and their results along with overall California demand estimates are used to estimate statewide demand response potential. Finally, recommendations are made for future research that can enhance the understanding of demand response potential in this industry.

  6. EIA model documentation: Electricity market module - electricity fuel dispatch

    SciTech Connect (OSTI)

    1997-01-01

    This report documents the National Energy Modeling System Electricity Fuel Dispatch Submodule (EFD), a submodule of the Electricity Market Module (EMM) as it was used for EIA`s Annual Energy Outlook 1997. It replaces previous documentation dated March 1994 and subsequent yearly update revisions. 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 document serves four purposes. First, it is a reference document providing a detailed description of the model for reviewers and potential users of the EFD including energy experts at the Energy Information Administration (EIA), other Federal agencies, state energy agencies, private firms such as utilities and consulting firms, and non-profit groups such as consumer and environmental groups. 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. Third, it facilitates continuity in model development by providing documentation which details model enhancements that were undertaken for AE097 and since the previous documentation. Last, because the major use of the EFD is to develop forecasts, this documentation explains the calculations, major inputs and assumptions which were used to generate the AE097.

  7. Report: Natural Gas Infrastructure Implications of Increased Demand from

    Energy Savers [EERE]

    the Electric Power Sector | Department of Energy Natural Gas Infrastructure Implications of Increased Demand from the Electric Power Sector Report: Natural Gas Infrastructure Implications of Increased Demand from the Electric Power Sector This report examines the potential infrastructure needs of the U.S. interstate natural gas pipeline transmission system across a range of future natural gas demand scenarios that drive increased electric power sector natural gas use. To perform this

  8. Retail Demand Response in Southwest Power Pool | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Retail Demand Response in Southwest Power Pool Retail Demand Response in Southwest Power Pool In 2007, the Southwest Power Pool (SPP) formed the Customer Response Task Force (CRTF) to identify barriers to deploying demand response (DR) resources in wholesale markets and develop policies to overcome these barriers. One of the initiatives of this Task Force was to develop more detailed information on existing retail DR programs and dynamic pricing tariffs, program rules, and utility operating

  9. SGDP Report Now Available: Interoperability of Demand Response Resources

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Demonstration in NY (February 2015) | Department of Energy SGDP Report Now Available: Interoperability of Demand Response Resources Demonstration in NY (February 2015) SGDP Report Now Available: Interoperability of Demand Response Resources Demonstration in NY (February 2015) March 20, 2015 - 4:42pm Addthis The Interoperability of Demand Response Resources Demonstration in NY was awarded to Con Edison in 2009 as part of DOE's Smart Grid Demonstration Project (SGDP) grants funded by the

  10. SGDP Report: Interoperability of Demand Response Resources Demonstration in

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    NY (February 2015) | Department of Energy SGDP Report: Interoperability of Demand Response Resources Demonstration in NY (February 2015) SGDP Report: Interoperability of Demand Response Resources Demonstration in NY (February 2015) The Interoperability of Demand Response Resources Demonstration in NY was awarded to Con Edison in 2009 as part of DOE's Smart Grid Demonstration Project (SGDP) grants funded by the Recovery Act. The objective of the project was to develop and demonstrate

  11. Generating Demand for Multifamily Building Upgrades | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Demand for Multifamily Building Upgrades Generating Demand for Multifamily Building Upgrades Better Buildings Residential Network Peer Exchange Call Series: Generating Demand for Multifamily Building Upgrades, call slides and discussion summary, May 14, 2015. PDF icon Call Slides and Discussion Summary More Documents & Publications Strategies to Address Split Incentives in Multifamily Buildings Outreach to Multifamily Landlords and Tenants Trends in Multifamily Programs: What's Working and

  12. Honeywell Demonstrates Automated Demand Response Benefits for Utility,

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Commercial, and Industrial Customers | Department of Energy Honeywell Demonstrates Automated Demand Response Benefits for Utility, Commercial, and Industrial Customers Honeywell Demonstrates Automated Demand Response Benefits for Utility, Commercial, and Industrial Customers September 22, 2014 - 5:59pm Addthis Honeywell's Smart Grid Investment Grant (SGIG) project demonstrates utility-scale performance of a hardware/software platform for automated demand response (ADR). This project stands

  13. Regulation Services with Demand Response - Energy Innovation Portal

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Regulation Services with Demand Response Pacific Northwest National Laboratory Contact PNNL About This Technology Using grid frequency information, researchers have created algorithms that intelligently control power demand while meeting consumer objectives (i.e. target pricing). Using grid frequency information, researchers have created algorithms that intelligently control power demand while meeting consumer objectives (i.e. target pricing). Technology Marketing Summary Grid Friendly(tm)

  14. Demand Response National Trends: Implications for the West? | Department of

    Energy Savers [EERE]

    Energy National Trends: Implications for the West? Demand Response National Trends: Implications for the West? Committee on Regional Electric Power Cooperation. San Francisco, CA. March 25, 2004 PDF icon Demand Response National Trends: Implications for the West? More Documents & Publications Demand Response in U.S. Electricity Markets: Empirical Evidence Technical Assistance to ISO's and Grid Operators For Loads Providing Ancillary Services To Enhance Grid Reliability Transmission

  15. Demand and Price Outlook for Phase 2 Reformulated Gasoline, 2000

    Gasoline and Diesel Fuel Update (EIA)

    Demand and Price Outlook for Phase 2 Reformulated Gasoline, 2000 Tancred Lidderdale and Aileen Bohn (1) Contents * Summary * Introduction * Reformulated Gasoline Demand * Oxygenate Demand * Logistics o Interstate Movements and Storage o Local Distribution o Phase 2 RFG Logistics o Possible Opt-Ins to the RFG Program o State Low Sulfur, Low RVP Gasoline Initiatives o NAAQS o Tier 2 Gasoline * RFG Production Options o Toxic Air Pollutants (TAP) Reduction o Nitrogen Oxides (NOx) Reduction o

  16. Agreement Template for Energy Conservation and Demand Side Management

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Services | Department of Energy Agreement Template for Energy Conservation and Demand Side Management Services Agreement Template for Energy Conservation and Demand Side Management Services Template agreement between a federal agency and a utility company for the implementation of energy conservation measures and demand side management services. A detailed description of the template is also available below. PDF icon Download the template agreement. PDF icon Download the model agreement

  17. Using Mobile Applications to Generate Customer Demand | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Energy Mobile Applications to Generate Customer Demand Using Mobile Applications to Generate Customer Demand Better Buildings Residential Network Peer Exchange Call Series: Using Mobile Applications to Generate Customer Demand, Call Slides and Discussion Summary, March 12, 2015. PDF icon Call Slides and Discussion Summary More Documents & Publications Better Buildings Network View | October 2014 Incorporating Behavior Change Efforts Into Energy Efficiency Programs Outreach to Multifamily

  18. Executive Order 13693 Training Now Available On Demand | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Energy Executive Order 13693 Training Now Available On Demand Executive Order 13693 Training Now Available On Demand January 4, 2016 - 8:00am Addthis Executive Order (E.O.) 13693: Recent Developments, Implementation Updates, and Opportunities Training is now available on-demand. The seminar covers the major goals of E. O. 13693 and offers examples of technologies and concepts the U.S. Department of Energy and other federal agencies are using to meet these goals. Addthis Related Articles

  19. Monitoring SERC Technologies: On-Demand Tankless Water Heaters | Department

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    of Energy Weatherization Assistance Program » Pilot Projects » Monitoring SERC Technologies: On-Demand Tankless Water Heaters Monitoring SERC Technologies: On-Demand Tankless Water Heaters On Oct. 4, 2011, Ethan MacCormick, VP for Services to Energy Businesses at Performance Systems Development, presented a Webinar about On-Demand Tankless Water Heaters and how to properly monitor their installation. View the webinar presentation. More Information Some resources and tools mentioned in the

  20. Sustainable Energy Resources for Consumers (SERC) - On-Demand Tankless

    Energy Savers [EERE]

    Water Heaters | Department of Energy On-Demand Tankless Water Heaters Sustainable Energy Resources for Consumers (SERC) - On-Demand Tankless Water Heaters This presentation, aimed at Sustainable Energy Resources for Consumers (SERC) grantees, provides information on Monitoring Checklists for the installation of On-Demand Tankless Water Heaters. PDF icon serc_webinar_presentation_20111004.pdf More Documents & Publications Sustainable Energy Resources for Consumers (SERC) - Solar Hot

  1. Cavity enhanced terahertz modulation

    SciTech Connect (OSTI)

    Born, N.; Scheller, M.; Moloney, J. V.; Koch, M.

    2014-03-10

    We present a versatile concept for all optical terahertz (THz) amplitude modulators based on a Fabry-Prot semiconductor cavity design. Employing the high reflectivity of two parallel meta-surfaces allows for trapping selected THz photons within the cavity and thus only a weak optical modulation of the semiconductor absorbance is required to significantly damp the field within the cavity. The optical switching yields to modulation depths of more than 90% with insertion efficiencies of 80%.

  2. Roel Neggers European Centre for Medium-range Weather Forecasts

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    transition from shallow to deep convection using a dual mass flux boundary layer scheme Roel Neggers European Centre for Medium-range Weather Forecasts Introduction ! " #" $ % % & # % " " " ' % ' ( ) * + " % ( , - . / 0 / " 0 . * 0 . * . . " 0 References A short model description Sensitivity tests Results Tropospheric humidity # " humidity 1 % 2 % ' 3 " % + 1 % 2 % % 3 % Updraft entrainment ' + % " 3 % 4 # " + %' 5 6)( . % ' 1 % .7

  3. NREL: Resource Assessment and Forecasting - Data and Resources

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Data and Resources National Solar Radiation Database NREL resource assessment and forecasting research information is available from the following sources. Renewable Resource Data Center (RReDC) Provides information about biomass, geothermal, solar, and wind energy resources. Measurement and Instrumentation Data Center Provides irradiance and meteorological data from stations throughout the United States. Baseline Measurement System (BMS) Provides live solar radiation data from approximately 70

  4. NREL: Energy Analysis - Energy Forecasting and Modeling Staff

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Energy Forecasting and Modeling The following includes summary bios of staff expertise and interests in analysis relating to energy economics, energy system planning, risk and uncertainty modeling, and energy infrastructure planning. Team Lead: Nate Blair Administrative Support: Elizabeth Torres Clayton Barrows Dave Bielen Aaron Bloom Greg Brinkman Brian W Bush Stuart Cohen Wesley Cole Paul Denholm Nicholas DiOrio Aron Dobos Kelly Eurek Janine Freeman Bethany Frew Pieter Gagnon Elaine Hale

  5. Bracket for photovoltaic modules

    DOE Patents [OSTI]

    Ciasulli, John; Jones, Jason

    2014-06-24

    Brackets for photovoltaic ("PV") modules are described. In one embodiment, a saddle bracket has a mounting surface to support one or more PV modules over a tube, a gusset coupled to the mounting surface, and a mounting feature coupled to the gusset to couple to the tube. The gusset can have a first leg and a second leg extending at an angle relative to the mounting surface. Saddle brackets can be coupled to a torque tube at predetermined locations. PV modules can be coupled to the saddle brackets. The mounting feature can be coupled to the first gusset and configured to stand the one or more PV modules off the tube.

  6. Module 3- Project Scheduling

    Broader source: Energy.gov [DOE]

    This module differentiates between planning and scheduling and outlines basic scheduling concepts, the logic relationships and critical path, and different schedule formats.

  7. PV modules modelling

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Energy PVsyst Summary Losses in a PV system simulation may be: - Determined by specific models (shadings) - Interpretations of models (PV module behaviour) - User's parameter...

  8. Using Partnerships to Drive Demand and Provide Services in Communities...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Using Partnerships to Drive Demand and Provide Services in Communities Better Buildings Neighborhood Program Multifamily and Low-Income Peer Exchange Call: Using Partnerships to ...

  9. Optical People Counting for Demand Controlled Ventilation: A...

    Office of Scientific and Technical Information (OSTI)

    of Counter Performance Citation Details In-Document Search Title: Optical People Counting for Demand Controlled Ventilation: A Pilot Study of Counter Performance This pilot ...

  10. Optical People Counting for Demand Controlled Ventilation: A...

    Office of Scientific and Technical Information (OSTI)

    of Counter Performance Citation Details In-Document Search Title: Optical People Counting for Demand Controlled Ventilation: A Pilot Study of Counter Performance You are ...

  11. China-Transportation Demand Management in Beijing: Mitigation...

    Open Energy Info (EERE)

    demand management (TDM) in Beijing in order to manage the steadily increasing traffic density. The project provides capacity building for decision-makers and transport planners in...

  12. South Korea-ANL Distributed Energy Resources and Demand Side...

    Open Energy Info (EERE)

    is part of a team that assists the Korean government in analyzing the economic and environmental benefits of distributed resources and demand side management (DSM). DSM has...

  13. Amplified Demand for Solar Trackers to Boost Market Growth in...

    Open Energy Info (EERE)

    Amplified Demand for Solar Trackers to Boost Market Growth in Middle East and Africa Home > Groups > Solar Permitting Roadmap Development Wayne31jan's picture Submitted by...

  14. Network-Driven Demand Side Management Website | Open Energy Informatio...

    Open Energy Info (EERE)

    URI: cleanenergysolutions.orgcontentnetwork-driven-demand-side-management Language: English Policies: "Deployment Programs,Regulations" is not in the list of possible...

  15. Estimating Demand Response Market Potential | Open Energy Information

    Open Energy Info (EERE)

    URI: cleanenergysolutions.orgcontentestimating-demand-response-market-pot Language: English Policies: "Deployment Programs,Regulations" is not in the list of possible...

  16. Demand Response Energy Consulting LLC | Open Energy Information

    Open Energy Info (EERE)

    Response Energy Consulting LLC Jump to: navigation, search Name: Demand Response & Energy Consulting LLC Place: Delanson, New York Zip: NY 12053 Sector: Efficiency Product:...

  17. Coordination of Energy Efficiency and Demand Response: A Resource...

    Open Energy Info (EERE)

    Coordination of Energy Efficiency and Demand Response: A Resource of the National Action Plan for Energy Efficiency Jump to: navigation, search Tool Summary LAUNCH TOOL Name:...

  18. Benefits of Demand Response in Electricity Markets and Recommendations...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Demand Response in Electricity Markets and Recommendations for Achieving Them. A report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005 ...

  19. Chapter 3 Demand-Side Resources | Department of Energy

    Energy Savers [EERE]

    Typically, these resources result from one of two methods of reducing load: energy efficiency or demand response load management. The energy efficiency method designs and deploys ...

  20. Reducing Peak Demand to Defer Power Plant Construction in Oklahoma

    Office of Environmental Management (EM)

    To better control costs and manage electric reliability under these conditions, OG&E is pursuing demand response strategies made possible by implementation of smart grid ...

  1. Electricity demand as frequency controlled reserves, ForskEL...

    Open Energy Info (EERE)

    ForskEL (Smart Grid Project) Jump to: navigation, search Project Name Electricity demand as frequency controlled reserves, ForskEL Country Denmark Coordinates 56.26392,...

  2. Electricity demand as frequency controlled reserves, ENS (Smart...

    Open Energy Info (EERE)

    ENS (Smart Grid Project) Jump to: navigation, search Project Name Electricity demand as frequency controlled reserves, ENS Country Denmark Coordinates 56.26392, 9.501785...

  3. U.S. Electric Utility Demand-Side Management

    Reports and Publications (EIA)

    2002-01-01

    Final issue of this report. - Presents comprehensive information on electric power industry demand side management (DSM) activities in the United States at the national, regional, and utility levels.

  4. Opportunities for Mass Market Demand Response to Provide Ancillary Services

    SciTech Connect (OSTI)

    Pratt, Rob; Najewicz, Dave

    2011-10-01

    Discusses what is meant by mass market demand response to provide ancillary services and outlines opportunities for adoption, and barriers to adoption.

  5. Structuring Rebate and Incentive Programs for Sustainable Demand

    Broader source: Energy.gov [DOE]

    Better Buildings Neighborhood Program Peer Exchange Call: Structuring Rebate and Incentive Programs for Sustainable Demand, call slides and discussion summary, August 18, 2011.

  6. Hydrogen Demand and Resource Analysis (HyDRA) Model

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    users to view, download, and analyze hydrogen demand, resource, and infrastructure ... HyDRA contains more than 100 datasets, including resource cost and availability, hydrogen ...

  7. Oil, gas tanker industry responding to demand, contract changes

    SciTech Connect (OSTI)

    True, W.R.

    1998-03-02

    Steady if slower growth in demand for crude oil and natural gas, low levels of scrapping, and a moderate newbuilding pace bode well for the world`s petroleum and natural-gas shipping industries. At year-end 1997, several studies of worldwide demand patterns and shipping fleets expressed short and medium-term optimism for seaborne oil and gas trade and fleet growth. The paper discusses steady demand and shifting patterns, the aging fleet, the slowing products traffic, the world`s fleet, gas carriers, LPG demand, and LPG vessels.

  8. Strategies for Aligning Program Demand with Contractor's Seasonal...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Strategies for Aligning Program Demand with Contractor's Seasonal Fluctuations Better Buildings Neighborhood Program Workforce Peer Exchange Call: Strategies for Aligning Program ...

  9. Strategies for Marketing and Driving Demand for Commercial Financing Products

    Broader source: Energy.gov [DOE]

    Better Buildings Neighborhood Program Financing and Commercial Peer Exchange Call: Strategies for Marketing and Driving Demand for Commercial Financing Products, Call Slides and Discussion Summary, February 2, 2012.

  10. Assessment of Energy Savings Potential from the Use of Demand...

    Office of Scientific and Technical Information (OSTI)

    Energy Savings Potential from the Use of Demand Controlled Ventilation in General Office Spaces in California Citation Details In-Document Search Title: Assessment of Energy ...

  11. Calculating impacts of energy standards on energy demand in U...

    Office of Scientific and Technical Information (OSTI)

    Calculating impacts of energy standards on energy demand in U.S. buildings with uncertainty in an integrated assessment model Citation Details In-Document Search Title: Calculating ...

  12. Table A19. Components of Total Electricity Demand by Census...

    U.S. Energy Information Administration (EIA) Indexed Site

    Components of Total Electricity Demand by Census Region and" " Economic Characteristics of ...ansfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)",...

  13. Strategies for Aligning Program Demand with Contractor's Seasonal Fluctuations

    Broader source: Energy.gov [DOE]

    Better Buildings Neighborhood Program Workforce Peer Exchange Call: Strategies for Aligning Program Demand with Contractor’s Seasonal Fluctuations, Call Slides and Discussion Summary, June 7, 2012.

  14. EnergySolve Demand Response | Open Energy Information

    Open Energy Info (EERE)

    Demand Response Place: Somerset, New Jersey Product: Somerset-based utility bill outsourcing company that provides electronic utility bill auditing, tariff analysis, late fee...

  15. Hydrogen Demand and Resource Assessment Tool | Open Energy Information

    Open Energy Info (EERE)

    Resource Assessment Tool Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Hydrogen Demand and Resource Assessment Tool AgencyCompany Organization: National Renewable...

  16. Table 11.2 Electricity: Components of Net Demand, 2010;

    U.S. Energy Information Administration (EIA) Indexed Site

    Electricity: Components of Net Demand, 2010; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Electricity Components; Unit: Million ...

  17. Assumption to the Annual Energy Outlook 2014 - Commercial Demand...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    chosen to meet the projected service demands for the seven major end uses. Once technologies are chosen, the energy consumed by the equipment stock (both existing and purchased...

  18. Towards a Science of Tumor Forecast for Clinical Oncology

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

    We propose that the quantitative cancer biology community make a concerted effort to apply the methods of weather forecasting to develop an analogous theory for predicting tumor growth and treatment response. Currently, the time course of response is not predicted, but rather assessed post hoc by physical exam or imaging methods. This fundamental limitation of clinical oncology makes it extraordinarily difficult to select an optimal treatment regimen for a particular tumor of an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoplymore » of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. With a successful theory of tumor forecasting, it should be possible to integrate large tumor specific datasets of varied types, and effectively defeat cancer one patient at a time.« less

  19. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect (OSTI)

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

    We propose that the quantitative cancer biology community make a concerted effort to apply the methods of weather forecasting to develop an analogous theory for predicting tumor growth and treatment response. Currently, the time course of response is not predicted, but rather assessed post hoc by physical exam or imaging methods. This fundamental limitation of clinical oncology makes it extraordinarily difficult to select an optimal treatment regimen for a particular tumor of an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. With a successful theory of tumor forecasting, it should be possible to integrate large tumor specific datasets of varied types, and effectively defeat cancer one patient at a time.

  20. Silicon photonic heater-modulator

    DOE Patents [OSTI]

    Zortman, William A.; Trotter, Douglas Chandler; Watts, Michael R.

    2015-07-14

    Photonic modulators, methods of forming photonic modulators and methods of modulating an input optical signal are provided. A photonic modulator includes a disk resonator having a central axis extending along a thickness direction of the disk resonator. The disk resonator includes a modulator portion and a heater portion. The modulator portion extends in an arc around the central axis. A PN junction of the modulator portion is substantially normal to the central axis.

  1. Opportunities for Automated Demand Response in California Wastewater Treatment Facilities

    SciTech Connect (OSTI)

    Aghajanzadeh, Arian; Wray, Craig; McKane, Aimee

    2015-08-30

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

  2. The Boom of Electricity Demand in the Residential Sector in the Developing World and the Potential for Energy Efficiency

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2008-05-13

    With the emergence of China as the world's largest energy consumer, the awareness of developing country energy consumption has risen. According to common economic scenarios, the rest of the developing world will probably see an economic expansion as well. With this growth will surely come continued rapid growth in energy demand. This paper explores the dynamics of that demand growth for electricity in the residential sector and the realistic potential for coping with it through efficiency. In 2000, only 66% of developing world households had access to electricity. Appliance ownership rates remain low, but with better access to electricity and a higher income one can expect that households will see their electricity consumption rise significantly. This paper forecasts developing country appliance growth using econometric modeling. Products considered explicitly - refrigerators, air conditioners, lighting, washing machines, fans, televisions, stand-by power, water heating and space heating - represent the bulk of household electricity consumption in developing countries. The resulting diffusion model determines the trend and dynamics of demand growth at a level of detail not accessible by models of a more aggregate nature. In addition, the paper presents scenarios for reducing residential consumption through cost-effective and/or best practice efficiency measures defined at the product level. The research takes advantage of an analytical framework developed by LBNL (BUENAS) which integrates end use technology parameters into demand forecasting and stock accounting to produce detailed efficiency scenarios, which allows for a realistic assessment of efficiency opportunities at the national or regional level. The past decades have seen some of the developing world moving towards a standard of living previously reserved for industrialized countries. Rapid economic development, combined with large populations has led to first China and now India to emerging as 'energy giants', a phenomenon that is expected to continue, accelerate and spread to other countries. This paper explores the potential for slowing energy consumption and greenhouse gas emissions in the residential sector in developing countries and evaluates the potential of energy savings and emissions mitigation through market transformation programs such as, but not limited to Energy Efficiency Standards and Labeling (EES&L). The bottom-up methodology used allows one to identify which end uses and regions have the greatest potential for savings.

  3. Membrane module assembly

    DOE Patents [OSTI]

    Kaschemekat, J.

    1994-03-15

    A membrane module assembly is described which is adapted to provide a flow path for the incoming feed stream that forces it into prolonged heat-exchanging contact with a heating or cooling mechanism. Membrane separation processes employing the module assembly are also disclosed. The assembly is particularly useful for gas separation or pervaporation. 2 figures.

  4. Logs Perl Module

    Energy Science and Technology Software Center (OSTI)

    2007-04-04

    A perl module designed to read and parse the voluminous set of event or accounting log files produced by a Portable Batch System (PBS) server. This module can filter on date-time and/or record type. The data can be returned in a variety of formats.

  5. Module Safety Issues (Presentation)

    SciTech Connect (OSTI)

    Wohlgemuth, J.

    2012-02-01

    Description of how to make PV modules so that they are less likely to turn into safety hazards. Making modules inherently safer with minimum additional cost is the preferred approach for PV. Safety starts with module design to ensure redundancy within the electrical circuitry to minimize open circuits and proper mounting instructions to prevent installation related ground faults. Module manufacturers must control the raw materials and processes to ensure that that every module is built like those qualified through the safety tests. This is the reason behind the QA task force effort to develop a 'Guideline for PV Module Manufacturing QA'. Periodic accelerated stress testing of production products is critical to validate the safety of the product. Combining safer PV modules with better systems designs is the ultimate goal. This should be especially true for PV arrays on buildings. Use of lower voltage dc circuits - AC modules, DC-DC converters. Use of arc detectors and interrupters to detect arcs and open the circuits to extinguish the arcs.

  6. Membrane module assembly

    DOE Patents [OSTI]

    Kaschemekat, Jurgen

    1994-01-01

    A membrane module assembly adapted to provide a flow path for the incoming feed stream that forces it into prolonged heat-exchanging contact with a heating or cooling mechanism. Membrane separation processes employing the module assembly are also disclosed. The assembly is particularly useful for gas separation or pervaporation.

  7. Availability of Canadian imports to meet U.S. demand for ethane, propane and butane

    SciTech Connect (OSTI)

    Hawkins, D.J.

    1996-12-31

    Historically, Canada has had a surplus of ethane, propane and butane. Almost all of the available propane and butane in Canadian natural gas streams is recovered. While there is significant ethane recovery in Canada, ethane that cannot be economically sold is left in the gas streams. All of the surplus Canadian ethane and most of the Canadian surplus propane and butane is exported to the US. Some volumes of Canadian propane and butane have been moved offshore by marine exports to the Asia-Pacific region or South America, or directly to Mexico by rail. Essentially all of the Canadian ethane, 86% of the propane and 74% of the butane are recovered by gas processing. Canadian natural gas production has increased significantly over the last 10 years. Canadian gas resources in the Western Canadian Sedimentary Basin should permit further expansion of gas exports, and several gas pipeline projects are pending to expand the markets for Canadian gas in the US. The prospective increase in Canadian gas production will yield higher volumes of ethane, propane and butane. While there is a potential to expand domestic markets for ethane, propane and butane, a significant part of the incremental production will move to export markets. This paper provides a forecast of the expected level of ethane, propane and butane exports from Canada and discusses the supply, demand and logistical developments which may affect export availability from Canada.

  8. Open Automated Demand Response for Small Commerical Buildings

    SciTech Connect (OSTI)

    Dudley, June Han; Piette, Mary Ann; Koch, Ed; Hennage, Dan

    2009-05-01

    This report characterizes small commercial buildings by market segments, systems and end-uses; develops a framework for identifying demand response (DR) enabling technologies and communication means; and reports on the design and development of a low-cost OpenADR enabling technology that delivers demand reductions as a percentage of the total predicted building peak electric demand. The results show that small offices, restaurants and retail buildings are the major contributors making up over one third of the small commercial peak demand. The majority of the small commercial buildings in California are located in southern inland areas and the central valley. Single-zone packaged units with manual and programmable thermostat controls make up the majority of heating ventilation and air conditioning (HVAC) systems for small commercial buildings with less than 200 kW peak electric demand. Fluorescent tubes with magnetic ballast and manual controls dominate this customer group's lighting systems. There are various ways, each with its pros and cons for a particular application, to communicate with these systems and three methods to enable automated DR in small commercial buildings using the Open Automated Demand Response (or OpenADR) communications infrastructure. Development of DR strategies must consider building characteristics, such as weather sensitivity and load variability, as well as system design (i.e. under-sizing, under-lighting, over-sizing, etc). Finally, field tests show that requesting demand reductions as a percentage of the total building predicted peak electric demand is feasible using the OpenADR infrastructure.

  9. Progress toward Producing Demand-Response-Ready Appliances

    SciTech Connect (OSTI)

    Hammerstrom, Donald J.; Sastry, Chellury

    2009-12-01

    This report summarizes several historical and ongoing efforts to make small electrical demand-side devices like home appliances more responsive to the dynamic needs of electric power grids. Whereas the utility community often reserves the word demand response for infrequent 2 to 6 hour curtailments that reduce total electrical system peak load, other beneficial responses and ancillary services that may be provided by responsive electrical demand are of interest. Historically, demand responses from the demand side have been obtained by applying external, retrofitted, controlled switches to existing electrical demand. This report is directed instead toward those manufactured products, including appliances, that are able to provide demand responses as soon as they are purchased and that require few, or no, after-market modifications to make them responsive to needs of power grids. Efforts to be summarized include Open Automated Demand Response, the Association of Home Appliance Manufacturer standard CHA 1, a simple interface being developed by the U-SNAP Alliance, various emerging autonomous responses, and the recent PinBus interface that was developed at Pacific Northwest National Laboratory.

  10. Reducing Energy Demand in Buildings Through State Energy Codes | Department

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    of Energy Reducing Energy Demand in Buildings Through State Energy Codes Reducing Energy Demand in Buildings Through State Energy Codes Building Codes Project for the 2013 Building Technologies Office's Program Peer Review PDF icon bldgcodes03_guttman_040213.pdf More Documents & Publications Technology Performance Exchange - 2013 BTO Peer Review Atmospheric Pressure Deposition for Electrochromic Windows Building America System Research

  11. Interoperability of Demand Response Resources Demonstration in NY

    SciTech Connect (OSTI)

    Wellington, Andre

    2014-03-31

    The Interoperability of Demand Response Resources Demonstration in NY (Interoperability Project) was awarded to Con Edison in 2009. The objective of the project was to develop and demonstrate methodologies to enhance the ability of customer sited Demand Response resources to integrate more effectively with electric delivery companies and regional transmission organizations.

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

    SciTech Connect (OSTI)

    Author: Denholm, Paul

    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.

  13. Transportation Sector Module - NEMS Documentation

    Reports and Publications (EIA)

    2014-01-01

    Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

  14. Economic Evaluation of Short-Term Wind Power Forecasts in ERCOT: Preliminary Results; Preprint

    SciTech Connect (OSTI)

    Orwig, K.; Hodge, B. M.; Brinkman, G.; Ela, E.; Milligan, M.; Banunarayanan, V.; Nasir, S.; Freedman, J.

    2012-09-01

    Historically, a number of wind energy integration studies have investigated the value of using day-ahead wind power forecasts for grid operational decisions. These studies have shown that there could be large cost savings gained by grid operators implementing the forecasts in their system operations. To date, none of these studies have investigated the value of shorter-term (0 to 6-hour-ahead) wind power forecasts. In 2010, the Department of Energy and National Oceanic and Atmospheric Administration partnered to fund improvements in short-term wind forecasts and to determine the economic value of these improvements to grid operators, hereafter referred to as the Wind Forecasting Improvement Project (WFIP). In this work, we discuss the preliminary results of the economic benefit analysis portion of the WFIP for the Electric Reliability Council of Texas. The improvements seen in the wind forecasts are examined, then the economic results of a production cost model simulation are analyzed.

  15. Photovoltaic module and interlocked stack of photovoltaic modules

    DOE Patents [OSTI]

    Wares, Brian S.

    2014-09-02

    One embodiment relates to an arrangement of photovoltaic modules configured for transportation. The arrangement includes a plurality of photovoltaic modules, each photovoltaic module including a frame. A plurality of individual male alignment features and a plurality of individual female alignment features are included on each frame. Adjacent photovoltaic modules are interlocked by multiple individual male alignment features on a first module of the adjacent photovoltaic modules fitting into and being surrounded by corresponding individual female alignment features on a second module of the adjacent photovoltaic modules. Other embodiments, features and aspects are also disclosed.

  16. module 4 | Department of Energy

    Energy Savers [EERE]

    module 4 module 4 HR5 TRANSITION BRIEFING PDF icon module 4 More Documents & Publications Microsoft Word - Rev5functionalaccountabilityimplementationplan..doc High Risk Plan Department of Energy (DOE) Acquisition Guide

  17. Central Wind Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities: Revised Edition

    SciTech Connect (OSTI)

    Rogers, J.; Porter, K.

    2011-03-01

    The report and accompanying table addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America. The first part of the table focuses on electric utilities and regional transmission organizations that have central wind power forecasting in place; the second part focuses on electric utilities and regional transmission organizations that plan to adopt central wind power forecasting in 2010. This is an update of the December 2009 report, NREL/SR-550-46763.

  18. Photovoltaic module with removable wind deflector (Patent) |...

    Office of Scientific and Technical Information (OSTI)

    Photovoltaic module with removable wind deflector Title: Photovoltaic module with removable wind deflector A photovoltaic (PV) module assembly including a PV module, a deflector, ...

  19. Sonication standard laboratory module

    DOE Patents [OSTI]

    Beugelsdijk, Tony; Hollen, Robert M.; Erkkila, Tracy H.; Bronisz, Lawrence E.; Roybal, Jeffrey E.; Clark, Michael Leon

    1999-01-01

    A standard laboratory module for automatically producing a solution of cominants from a soil sample. A sonication tip agitates a solution containing the soil sample in a beaker while a stepper motor rotates the sample. An aspirator tube, connected to a vacuum, draws the upper layer of solution from the beaker through a filter and into another beaker. This beaker can thereafter be removed for analysis of the solution. The standard laboratory module encloses an embedded controller providing process control, status feedback information and maintenance procedures for the equipment and operations within the standard laboratory module.

  20. Water heater control module

    DOE Patents [OSTI]

    Hammerstrom, Donald J

    2013-11-26

    An advanced electric water heater control system that interfaces with a high temperature cut-off thermostat and an upper regulating thermostat. The system includes a control module that is electrically connected to the high-temperature cut-off thermostat and the upper regulating thermostat. The control module includes a switch to open or close the high-temperature cut-off thermostat and the upper regulating thermostat. The control module further includes circuitry configured to control said switch in response to a signal selected from the group of an autonomous signal, a communicated signal, and combinations thereof.

  1. Analysis of Residential Demand Response and Double-Auction Markets

    SciTech Connect (OSTI)

    Fuller, Jason C.; Schneider, Kevin P.; Chassin, David P.

    2011-10-10

    Demand response and dynamic pricing programs are expected to play increasing roles in the modern Smart Grid environment. While direct load control of end-use loads has existed for decades, price driven response programs are only beginning to be explored at the distribution level. These programs utilize a price signal as a means to control demand. Active markets allow customers to respond to fluctuations in wholesale electrical costs, but may not allow the utility to control demand. Transactive markets, utilizing distributed controllers and a centralized auction can be used to create an interactive system which can limit demand at key times on a distribution system, decreasing congestion. With the current proliferation of computing and communication resources, the ability now exists to create transactive demand response programs at the residential level. With the combination of automated bidding and response strategies coupled with education programs and customer response, emerging demand response programs have the ability to reduce utility demand and congestion in a more controlled manner. This paper will explore the effects of a residential double-auction market, utilizing transactive controllers, on the operation of an electric power distribution system.

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

    SciTech Connect (OSTI)

    Hadley, Stanton W.; Sanstad, Alan H.

    2015-01-01

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

  3. Open Automated Demand Response Communications Specification (Version 1.0)

    SciTech Connect (OSTI)

    Piette, Mary Ann; Ghatikar, Girish; Kiliccote, Sila; Koch, Ed; Hennage, Dan; Palensky, Peter; McParland, Charles

    2009-02-28

    The development of the Open Automated Demand Response Communications Specification, also known as OpenADR or Open Auto-DR, began in 2002 following the California electricity crisis. The work has been carried out by the Demand Response Research Center (DRRC), which is managed by Lawrence Berkeley National Laboratory. This specification describes an open standards-based communications data model designed to facilitate sending and receiving demand response price and reliability signals from a utility or Independent System Operator to electric customers. OpenADR is one element of the Smart Grid information and communications technologies that are being developed to improve optimization between electric supply and demand. The intention of the open automated demand response communications data model is to provide interoperable signals to building and industrial control systems that are preprogrammed to take action based on a demand response signal, enabling a demand response event to be fully automated, with no manual intervention. The OpenADR specification is a flexible infrastructure to facilitate common information exchange between the utility or Independent System Operator and end-use participants. The concept of an open specification is intended to allow anyone to implement the signaling systems, the automation server or the automation clients.

  4. Assessment of Industrial Load for Demand Response across Western Interconnect

    SciTech Connect (OSTI)

    Alkadi, Nasr E; Starke, Michael R; Ma, Ookie

    2013-11-01

    Demand response (DR) has the ability to both increase power grid reliability and potentially reduce operating system costs. Understanding the role of demand response in grid modeling has been difficult due to complex nature of the load characteristics compared to the modeled generation and the variation in load types. This is particularly true of industrial loads, where hundreds of different industries exist with varying availability for demand response. We present a framework considering industrial loads for the development of availability profiles that can provide more regional understanding and can be inserted into analysis software for further study. The developed framework utilizes a number of different informational resources, algorithms, and real-world measurements to perform a bottom-up approach in the development of a new database with representation of the potential demand response resource in the industrial sector across the U.S. This tool houses statistical values of energy and demand response (DR) potential by industrial plant and geospatially locates the information for aggregation for different territories without proprietary information. This report will discuss this framework and the analyzed quantities of demand response for Western Interconnect (WI) in support of evaluation of the cost production modeling with power grid modeling efforts of demand response.

  5. Introduction to the Buildings Sector Module of SEDS

    SciTech Connect (OSTI)

    DeForest, Nicholas; Bonnet, Florence; Stadler, Michael; Marnay, Chris

    2010-12-31

    SEDS is a stochastic engineering-economics model that forecasts economy-wide energy consumption in the U.S. to 2050. It is the product of multi-laboratory collaboration among the National Renewable Energy Laboratory (NREL), Pacific Northwest National Laboratory (PNNL), Argonne National Laboratory (ANL), Lawrence Berkeley National Laboratory (LBNL), and Lumina Decision Systems. Among national energy models, SEDS is unique, as it is the only model written to explicitly incorporate uncertainty in its inputs and outputs. The primary purpose of SEDS is to estimate the impact of various US Department of Energy (DOE)R&D and policy programs on the performance and subsequent adoption rates of technologies relating to every energy consuming sector of the economy (shown below). It has previously been used to assist DOE in complying with the Government Performance and Results Act of 1993 (GPRA). The focus of LBNL research has been exclusively on develop the buildings model (SBEAM), which is capable of running as a stand-alone forecasting model, or as a part of SEDS as a whole. The full version of SEDS, containing all sectors and interaction is also called the 'integrated' version and is managed by NREL. Forecasts from SEDS are often compared to those coming from National Energy Modeling System (NEMS). The intention of this document is to present new users and developers with a general description of the purpose, functionality and structure of the buildings module within the Stochastic Energy Deployment System (SEDS). The Buildings module, which is capable of running as a standalone model, is also called the Stochastic Buildings Energy and Adoption Model (SBEAM). This document will focus exclusively on SBEAM and its interaction with other major sector modules present within SEDS. The methodologies and major assumptions employed in SBEAM will also be discussed. The organization of this report will parallel the organization of the model itself, being divided into major submodules. As the description progresses, the nature of modules will change from broad, easily understood concepts to lower-level data manipulation. Because SBEAM contains dozens of submodules and hundreds of variables, it would not be relevant or useful to describe each and every one. Rather, the investigation will focus more generally on the operations performed throughout the model. This manual is by no means a complete description of SBEAM; however it should provide the foundation for an introductory understanding of the model. The manual assumes a basic level of understating of Analytica{reg_sign}, the platform on which SEDS and SBEAM have been developed.

  6. Value of Improved Wind Power Forecasting in the Western Interconnection (Poster)

    SciTech Connect (OSTI)

    Hodge, B.

    2013-12-01

    Wind power forecasting is a necessary and important technology for incorporating wind power into the unit commitment and dispatch process. It is expected to become increasingly important with higher renewable energy penetration rates and progress toward the smart grid. There is consensus that wind power forecasting can help utility operations with increasing wind power penetration; however, there is far from a consensus about the economic value of improved forecasts. This work explores the value of improved wind power forecasting in the Western Interconnection of the United States.

  7. Report of the external expert peer review panel: DOE benefits forecasts

    SciTech Connect (OSTI)

    None, None

    2006-12-20

    A report for the FY 2007 GPRA methodology review, highlighting the views of an external expert peer review panel on DOE benefits forecasts.

  8. The Value of Improved Short-Term Wind Power Forecasting

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    The Value of Improved Short- Term Wind Power Forecasting B.-M. Hodge and A. Florita National Renewable Energy Laboratory J. Sharp Sharply Focused, LLC M. Margulis and D. Mcreavy Lockheed Martin Technical Report NREL/TP-5D00-63175 February 2015 NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency & Renewable Energy Operated by the Alliance for Sustainable Energy, LLC This report is available at no cost from the National Renewable Energy Laboratory (NREL)

  9. A Look Ahead at Demand Response in New England

    SciTech Connect (OSTI)

    Burke, Robert B.; Henderson, Michael I.; Widergren, Steven E.

    2008-08-01

    The paper describes the demand response programs developed and in operation in New England, and the revised designs for participation in the forward capacity market. This description will include how energy efficiency, demand-side resources, and distributed generation are eligible to participate in this new forward capacity market. The paper will also discuss various methods that can be used to configure and communicate with demand response resources and important concerns in specifying interfaces that accommodate multiple technologies and allow technology choice and evolution.

  10. Demand response compensation, net Benefits and cost allocation: comments

    SciTech Connect (OSTI)

    Hogan, William W.

    2010-11-15

    FERC's Supplemental Notice of Public Rulemaking addresses the question of proper compensation for demand response in organized wholesale electricity markets. Assuming that the Commission would proceed with the proposal ''to require tariff provisions allowing demand response resources to participate in wholesale energy markets by reducing consumption of electricity from expected levels in response to price signals, to pay those demand response resources, in all hours, the market price of energy for such reductions,'' the Commission posed questions about applying a net benefits test and rules for cost allocation. This article summarizes critical points and poses implications for the issues of net benefit tests and cost allocation. (author)

  11. Assumption to the Annual Energy Outlook 2014 - Residential Demand...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    oil, liquefied petroleum gas, natural gas, kerosene, electricity, wood, geothermal, and solar energy. The module's output includes number of households, equipment stock, average...

  12. International Energy Module

    Gasoline and Diesel Fuel Update (EIA)

    self-contained units which are linked by an integrating mechanism. The NEMS International Energy Module (IEM) computes world oil prices, provides a set of crude oil and refined...

  13. NEMS International Energy Module

    Gasoline and Diesel Fuel Update (EIA)

    EIA NEMS International Energy Module Model Documentation Report vii Mr. G. Daniel Butler U.S. Department of Energy EI-812 1000 Independence Ave., SW Washington, DC 20585 Tel:...

  14. International Energy Module

    Gasoline and Diesel Fuel Update (EIA)

    EIA NEMS International Energy Module Model Documentation Report vii Mr. G. Daniel Butler U.S. Department of Energy EI-812 1000 Independence Ave., SW Washington, DC 20585 Tel:...

  15. GREET Pretreatment Module

    SciTech Connect (OSTI)

    Adom, Felix K.; Dunn, Jennifer B.; Han, Jeongwoo

    2014-09-01

    A wide range of biofuels and biochemicals can be produced from biomass via different pretreatment technologies that yield sugars. This report documents the material and energy flows that occur when fermentable sugars from four lignocellulosic feedstocks (corn stover, miscanthus, switchgrass, and poplar) are produced via dilute acid pretreatment and ammonia fiber expansion. These flows are documented for inclusion in the pretreatment module of the Greenhouses Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model. Process simulations of each pretreatment technology were developed in Aspen Plus. Material and energy consumption data from Aspen Plus were then compiled in the GREET pretreatment module. The module estimates the cradle-to-gate fossil energy consumption (FEC) and greenhouse gas (GHG) emissions associated with producing fermentable sugars. This report documents the data and methodology used to develop this module and the cradle-to-gate FEC and GHG emissions that result from producing fermentable sugars.

  16. Digital optical conversion module

    DOE Patents [OSTI]

    Kotter, D.K.; Rankin, R.A.

    1988-07-19

    A digital optical conversion module used to convert an analog signal to a computer compatible digital signal including a voltage-to-frequency converter, frequency offset response circuitry, and an electrical-to-optical converter. Also used in conjunction with the digital optical conversion module is an optical link and an interface at the computer for converting the optical signal back to an electrical signal. Suitable for use in hostile environments having high levels of electromagnetic interference, the conversion module retains high resolution of the analog signal while eliminating the potential for errors due to noise and interference. The module can be used to link analog output scientific equipment such as an electrometer used with a mass spectrometer to a computer. 2 figs.

  17. Digital optical conversion module

    DOE Patents [OSTI]

    Kotter, Dale K.; Rankin, Richard A.

    1991-02-26

    A digital optical conversion module used to convert an analog signal to a computer compatible digital signal including a voltage-to-frequency converter, frequency offset response circuitry, and an electrical-to-optical converter. Also used in conjunction with the digital optical conversion module is an optical link and an interface at the computer for converting the optical signal back to an electrical signal. Suitable for use in hostile environments having high levels of electromagnetic interference, the conversion module retains high resolution of the analog signal while eliminating the potential for errors due to noise and interference. The module can be used to link analog output scientific equipment such as an electrometer used with a mass spectrometer to a computer.

  18. Hawaii demand-side management resource assessment. Final report, Reference Volume 3 -- Residential and commercial sector DSM analyses: Detailed results from the DBEDT DSM assessment model; Part 1, Technical potential

    SciTech Connect (OSTI)

    1995-04-01

    The Hawaii Demand-Side Management Resource Assessment was the fourth of seven projects in the Hawaii Energy Strategy (HES) program. HES was designed by the Department of Business, Economic Development, and Tourism (DBEDT) to produce an integrated energy strategy for the State of Hawaii. The purpose of Project 4 was to develop a comprehensive assessment of Hawaii`s demand-side management (DSM) resources. To meet this objective, the project was divided into two phases. The first phase included development of a DSM technology database and the identification of Hawaii commercial building characteristics through on-site audits. These Phase 1 products were then used in Phase 2 to identify expected energy impacts from DSM measures in typical residential and commercial buildings in Hawaii. The building energy simulation model DOE-2.1E was utilized to identify the DSM energy impacts. More detailed information on the typical buildings and the DOE-2.1E modeling effort is available in Reference Volume 1, ``Building Prototype Analysis``. In addition to the DOE-2.1E analysis, estimates of residential and commercial sector gas and electric DSM potential for the four counties of Honolulu, Hawaii, Maui, and Kauai through 2014 were forecasted by the new DBEDT DSM Assessment Model. Results from DBEDTs energy forecasting model, ENERGY 2020, were linked with results from DOE-2.1E building energy simulation runs and estimates of DSM measure impacts, costs, lifetime, and anticipated market penetration rates in the DBEDT DSM Model. Through its algorithms, estimates of DSM potential for each forecast year were developed. Using the load shape information from the DOE-2.1E simulation runs, estimates of electric peak demand impacts were developed. Numerous tables and figures illustrating the technical potential for demand-side management are included.

  19. Photovoltaic module reliability workshop

    SciTech Connect (OSTI)

    Mrig, L.

    1990-01-01

    The paper and presentations compiled in this volume form the Proceedings of the fourth in a series of Workshops sponsored by Solar Energy Research Institute (SERI/DOE) under the general theme of photovoltaic module reliability during the period 1986--1990. The reliability Photo Voltaic (PV) modules/systems is exceedingly important along with the initial cost and efficiency of modules if the PV technology has to make a major impact in the power generation market, and for it to compete with the conventional electricity producing technologies. The reliability of photovoltaic modules has progressed significantly in the last few years as evidenced by warranties available on commercial modules of as long as 12 years. However, there is still need for substantial research and testing required to improve module field reliability to levels of 30 years or more. Several small groups of researchers are involved in this research, development, and monitoring activity around the world. In the US, PV manufacturers, DOE laboratories, electric utilities and others are engaged in the photovoltaic reliability research and testing. This group of researchers and others interested in this field were brought together under SERI/DOE sponsorship to exchange the technical knowledge and field experience as related to current information in this important field. The papers presented here reflect this effort.

  20. Detailed Modeling and Response of Demand Response Enabled Appliances

    SciTech Connect (OSTI)

    Vyakaranam, Bharat; Fuller, Jason C.

    2014-04-14

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

  1. MODELING THE DEMAND FOR E85 IN THE UNITED STATES

    SciTech Connect (OSTI)

    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.

  2. Tankless or Demand-Type Water Heaters | Department of Energy

    Broader source: Energy.gov (indexed) [DOE]

    a demand water heater at each hot water outlet. ENERGY STAR estimates that a typical family can save 100 or more per year with an ENERGY STAR qualified tankless water heater....

  3. Chapter 3: Demand-Side Resources | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    According to one source, U.S. electric utilities spent 14.7 billion on DSM programs between 1989 and 1999, an average of 1.3 billion per year. PDF icon Chapter 3: Demand-Side ...

  4. Demand charge schedule data | OpenEI Community

    Open Energy Info (EERE)

    Demand charge schedule data Home > Groups > Utility Rate Hi, I'm a new user of this database,so first, thanks for creating it, and apologies if this question is answered in...

  5. Response to several FOIA requests - Renewable Energy. Demand...

    Broader source: Energy.gov (indexed) [DOE]

    Demand for fossil fuels surely will overrun supply sooner or later, as indeed it already has in the casc of United States domestic oil drilling. Recognition also is growing that ...

  6. U.S. electric utility demand-side management 1993

    SciTech Connect (OSTI)

    1995-07-01

    This report presents comprehensive information on electric power industry demand-side management activities in the United States at the national, regional, and utility levels. Data is included for energy savings, peakload reductions, and costs.

  7. Demand response medium sized industry consumers (Smart Grid Project...

    Open Energy Info (EERE)

    demand and regulation power in Danish Industry consumers via a price and control signal from the supplier of electricity. The aim is to develop a valuable solution for the...

  8. Global Energy: Supply, Demand, Consequences, Opportunities (LBNL Summer Lecture Series)

    ScienceCinema (OSTI)

    Majumdar, Arun

    2011-04-28

    Summer Lecture Series 2009: Arun Majumdar, Director of the Environmental Energy Technologies Division, discusses current and future projections of economic growth, population, and global energy demand and supply, and explores the implications of these trends for the environment.

  9. Global Energy: Supply, Demand, Consequences, Opportunities (LBNL Summer Lecture Series)

    SciTech Connect (OSTI)

    Majumdar, Arun

    2008-07-29

    Summer Lecture Series 2009: Arun Majumdar, Director of the Environmental Energy Technologies Division, discusses current and future projections of economic growth, population, and global energy demand and supply, and explores the implications of these trends for the environment.

  10. Demand Response and Open Automated Demand Response Opportunities for Data Centers

    SciTech Connect (OSTI)

    Ghatikar, Girish; Piette, Mary Ann; Fujita, Sydny; McKane, Aimee; Dudley, Junqiao Han; Radspieler, Anthony; Mares, K.C.; Shroyer, Dave

    2009-12-30

    This study examines data center characteristics, loads, control systems, and technologies to identify demand response (DR) and automated DR (Open Auto-DR) opportunities and challenges. The study was performed in collaboration with technology experts, industrial partners, and data center facility managers and existing research on commercial and industrial DR was collected and analyzed. The results suggest that data centers, with significant and rapidly growing energy use, have significant DR potential. Because data centers are highly automated, they are excellent candidates for Open Auto-DR. 'Non-mission-critical' data centers are the most likely candidates for early adoption of DR. Data center site infrastructure DR strategies have been well studied for other commercial buildings; however, DR strategies for information technology (IT) infrastructure have not been studied extensively. The largest opportunity for DR or load reduction in data centers is in the use of virtualization to reduce IT equipment energy use, which correspondingly reduces facility cooling loads. DR strategies could also be deployed for data center lighting, and heating, ventilation, and air conditioning. Additional studies and demonstrations are needed to quantify benefits to data centers of participating in DR and to address concerns about DR's possible impact on data center performance or quality of service and equipment life span.

  11. Light-Duty Vehicle Energy Demand, Demographics, and Travel Behavior

    U.S. Energy Information Administration (EIA) Indexed Site

    EIA Conference July 15, 2014 | Washington, DC By Trisha Hutchins, Office of Energy Consumption and Efficiency Analysis Light-duty vehicle energy demand, demographics, and travel behavior Examining changes in light-duty vehicle travel trends 2 EIA Conference: Light-duty vehicle energy demand, demographics, and travel behavior July 15, 2014 * Recent data indicate possible structural shift in travel behavior, measured as vehicle miles traveled (VMT) - VMT per licensed driver, vehicles per capita,

  12. Reducing Peak Demand to Defer Power Plant Construction in Oklahoma

    Energy Savers [EERE]

    Reducing Peak Demand to Defer Power Plant Construction in Oklahoma Located in the heart of "Tornado Alley," Oklahoma Gas & Electric Company's (OG&E) electric grid faces significant challenges from severe weather, hot summers, and about 2% annual load growth. To better control costs and manage electric reliability under these conditions, OG&E is pursuing demand response strategies made possible by implementation of smart grid technologies, tools, and techniques from

  13. Reducing Logistics Footprints and Replenishment Demands: Nano-engineered

    Office of Scientific and Technical Information (OSTI)

    Silica Aerogels a Proven Method for Water Treatment (Technical Report) | SciTech Connect Technical Report: Reducing Logistics Footprints and Replenishment Demands: Nano-engineered Silica Aerogels a Proven Method for Water Treatment Citation Details In-Document Search Title: Reducing Logistics Footprints and Replenishment Demands: Nano-engineered Silica Aerogels a Proven Method for Water Treatment Rapid deployment and the use of objective force aggressively reduce logistic footprints and

  14. International Energy Outlook 2016-World energy demand and economc outlook -

    Gasoline and Diesel Fuel Update (EIA)

    Energy Information Administration Analysis & Projections International Energy Outlook 2016 Release Date: May 11, 2016 | Next Release Date: September 2017 | Complete PDF anticipated May 23 Chapter 1. World energy demand and economic outlook Overview The International Energy Outlook 2016 (IEO2016) Reference case projects significant growth in worldwide energy demand over the 28-year period from 2012 to 2040. Total world consumption of marketed energy expands from 549 quadrillion British

  15. California Geothermal Power Plant to Help Meet High Lithium Demand |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy California Geothermal Power Plant to Help Meet High Lithium Demand California Geothermal Power Plant to Help Meet High Lithium Demand September 20, 2012 - 1:15pm Addthis Ever wonder how we get the materials for the advanced batteries that power our cell phones, laptops, and even some electric vehicles? The U.S. Department of Energy's Geothermal Technologies Program (GTP) is working with California's Simbol Materials to develop technologies that extract battery materials

  16. Benefits of Demand Response in Electricity Markets and Recommendations for

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Achieving Them. A report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005 (February 2006) | Department of Energy Demand Response in Electricity Markets and Recommendations for Achieving Them. A report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005 (February 2006) Benefits of Demand Response in Electricity Markets and Recommendations for Achieving Them. A report to the United States Congress Pursuant to Section

  17. Determination of Thermoelectric Module Efficiency A Survey

    SciTech Connect (OSTI)

    Wang, Hsin; McCarty, Robin; Salvador, James R.; Yamamoto, Atsushi; Konig, Jan

    2014-01-01

    The development of thermoelectrics (TE) for energy conversion is in the transition phase from laboratory research to device development. There is an increasing demand to accurately determine the module efficiency, especially for the power generation mode. For many thermoelectrics, the figure of merit, ZT, of the material sometimes cannot be fully realized at the device level. Reliable efficiency testing of thermoelectric modules is important to assess the device ZT and provide the end-users with realistic values on how much power can be generated under specific conditions. We conducted a general survey of efficiency testing devices and their performance. The results indicated the lack of industry standards and test procedures. This study included a commercial test system and several laboratory systems. Most systems are based on the heat flow meter method and some are based on the Harman method. They are usually reproducible in evaluating thermoelectric modules. However, cross-checking among different systems often showed large errors that are likely caused by unaccounted heat loss and thermal resistance. Efficiency testing is an important area for the thermoelectric community to focus on. A follow-up international standardization effort is planned.

  18. Load Reduction, Demand Response and Energy Efficient Technologies and Strategies

    SciTech Connect (OSTI)

    Boyd, Paul A.; Parker, Graham B.; Hatley, Darrel D.

    2008-11-19

    The Department of Energys (DOEs) Pacific Northwest National Laboratory (PNNL) was tasked by the DOE Office of Electricity (OE) to recommend load reduction and grid integration strategies, and identify additional demand response (energy efficiency/conservation opportunities) and strategies at the Forest City Housing (FCH) redevelopment at Pearl Harbor and the Marine Corps Base Hawaii (MCBH) at Kaneohe Bay. The goal was to provide FCH staff a path forward to manage their electricity load and thus reduce costs at these FCH family housing developments. The initial focus of the work was at the MCBH given the MCBH has a demand-ratchet tariff, relatively high demand (~18 MW) and a commensurate high blended electricity rate (26 cents/kWh). The peak demand for MCBH occurs in July-August. And, on average, family housing at MCBH contributes ~36% to the MCBH total energy consumption. Thus, a significant load reduction in family housing can have a considerable impact on the overall site load. Based on a site visit to the MCBH and meetings with MCBH installation, FCH, and Hawaiian Electric Company (HECO) staff, recommended actions (including a "smart grid" recommendation) that can be undertaken by FCH to manage and reduce peak-demand in family housing are made. Recommendations are also made to reduce overall energy consumption, and thus reduce demand in FCH family housing.

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

    SciTech Connect (OSTI)

    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 timeframesincentivizing 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.

  20. The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area

    SciTech Connect (OSTI)

    Finley, Cathy

    2014-04-30

    This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times.

  1. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison (Presentation)

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B.; Miettinen, J.; Holttinen, H.; Gomez-Lozaro, E.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Lovholm, A.; Berge, E.; Dobschinski, J.

    2013-10-01

    This presentation summarizes the work to investigate the uncertainty in wind forecasting at different times of year and compare wind forecast errors in different power systems using large-scale wind power prediction data from six countries: the United States, Finland, Spain, Denmark, Norway, and Germany.

  2. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect (OSTI)

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together into larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

  3. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

  4. How much will low prices stimulate oil demand?

    Gasoline and Diesel Fuel Update (EIA)

    Household heating bills expected to be lower this winter U.S. consumers are expected to pay less this winter on their home heating bills because of lower oil and natural gas prices and projected milder temperatures than last winter. In its new forecast, the U.S. Energy Information Administration said households that rely on heating oil which are mainly located in the Northeast will pay the lowest heating expenditures in 9 years down 25% from last winter as consumers are expected to save about

  5. Power module assembly

    DOE Patents [OSTI]

    Campbell, Jeremy B.; Newson, Steve

    2011-11-15

    A power module assembly of the type suitable for deployment in a vehicular power inverter, wherein the power inverter has a grounded chassis, is provided. The power module assembly comprises a conductive base layer electrically coupled to the chassis, an insulating layer disposed on the conductive base layer, a first conductive node disposed on the insulating layer, a second conductive node disposed on the insulating layer, wherein the first and second conductive nodes are electrically isolated from each other. The power module assembly also comprises a first capacitor having a first electrode electrically connected to the conductive base layer, and a second electrode electrically connected to the first conductive node, and further comprises a second capacitor having a first electrode electrically connected to the conductive base layer, and a second electrode electrically connected to the second conductive node.

  6. Printed Module Interconnects

    SciTech Connect (OSTI)

    Stockert, Talysa R.; Fields, Jeremy D.; Pach, Gregory F.; Mauger, Scott A.; van Hest, Maikel F. A. M.

    2015-06-14

    Monolithic interconnects in photovoltaic modules connect adjacent cells in series, and are typically formed sequentially involving multiple deposition and scribing steps. Interconnect widths of 500 um every 10 mm result in 5% dead area, which does not contribute to power generation in an interconnected solar panel. This work expands on previous work that introduced an alternative interconnection method capable of producing interconnect widths less than 100 um. The interconnect is added to the module in a single step after deposition of the photovoltaic stack, eliminating the need for scribe alignment. This alternative method can be used for all types of thin film photovoltaic modules. Voltage addition with copper-indium-gallium-diselenide (CIGS) solar cells using a 2-scribe printed interconnect approach is demonstrated. Additionally, interconnect widths of 250 um are shown.

  7. Thirty-Year Solid Waste Generation Maximum and Minimum Forecast for SRS

    SciTech Connect (OSTI)

    Thomas, L.C.

    1994-10-01

    This report is the third phase (Phase III) of the Thirty-Year Solid Waste Generation Forecast for Facilities at the Savannah River Site (SRS). Phase I of the forecast, Thirty-Year Solid Waste Generation Forecast for Facilities at SRS, forecasts the yearly quantities of low-level waste (LLW), hazardous waste, mixed waste, and transuranic (TRU) wastes generated over the next 30 years by operations, decontamination and decommissioning and environmental restoration (ER) activities at the Savannah River Site. The Phase II report, Thirty-Year Solid Waste Generation Forecast by Treatability Group (U), provides a 30-year forecast by waste treatability group for operations, decontamination and decommissioning, and ER activities. In addition, a 30-year forecast by waste stream has been provided for operations in Appendix A of the Phase II report. The solid wastes stored or generated at SRS must be treated and disposed of in accordance with federal, state, and local laws and regulations. To evaluate, select, and justify the use of promising treatment technologies and to evaluate the potential impact to the environment, the generic waste categories described in the Phase I report were divided into smaller classifications with similar physical, chemical, and radiological characteristics. These smaller classifications, defined within the Phase II report as treatability groups, can then be used in the Waste Management Environmental Impact Statement process to evaluate treatment options. The waste generation forecasts in the Phase II report includes existing waste inventories. Existing waste inventories, which include waste streams from continuing operations and stored wastes from discontinued operations, were not included in the Phase I report. Maximum and minimum forecasts serve as upper and lower boundaries for waste generation. This report provides the maximum and minimum forecast by waste treatability group for operation, decontamination and decommissioning, and ER activities.

  8. Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets

    SciTech Connect (OSTI)

    Wong-Parodi, Gabrielle; Lekov, Alex; Dale, Larry

    2005-02-09

    This paper evaluates the accuracy of two methods to forecast natural gas prices: using the Energy Information Administration's ''Annual Energy Outlook'' forecasted price (AEO) and the ''Henry Hub'' compared to U.S. Wellhead futures price. A statistical analysis is performed to determine the relative accuracy of the two measures in the recent past. A statistical analysis suggests that the Henry Hub futures price provides a more accurate average forecast of natural gas prices than the AEO. For example, the Henry Hub futures price underestimated the natural gas price by 35 cents per thousand cubic feet (11.5 percent) between 1996 and 2003 and the AEO underestimated by 71 cents per thousand cubic feet (23.4 percent). Upon closer inspection, a liner regression analysis reveals that two distinct time periods exist, the period between 1996 to 1999 and the period between 2000 to 2003. For the time period between 1996 to 1999, AEO showed a weak negative correlation (R-square = 0.19) between forecast price by actual U.S. Wellhead natural gas price versus the Henry Hub with a weak positive correlation (R-square = 0.20) between forecasted price and U.S. Wellhead natural gas price. During the time period between 2000 to 2003, AEO shows a moderate positive correlation (R-square = 0.37) between forecasted natural gas price and U.S. Wellhead natural gas price versus the Henry Hub that show a moderate positive correlation (R-square = 0.36) between forecast price and U.S. Wellhead natural gas price. These results suggest that agencies forecasting natural gas prices should consider incorporating the Henry Hub natural gas futures price into their forecasting models along with the AEO forecast. Our analysis is very preliminary and is based on a very small data set. Naturally the results of the analysis may change, as more data is made available.

  9. Climate Mitigation Policy Implications for Global Irrigation Water Demand

    SciTech Connect (OSTI)

    Chaturvedi, Vaibhav; Hejazi, Mohamad I.; Edmonds, James A.; Clarke, Leon E.; Kyle, G. Page; Davies, Evan; Wise, Marshall A.

    2013-08-22

    Energy, water and land are scarce resources, critical to humans. Developments in each affect the availability and cost of the others, and consequently human prosperity. Measures to limit greenhouse gas concentrations will inevitably exact dramatic changes on energy and land systems and in turn alter the character, magnitude and geographic distribution of human claims on water resources. We employ the Global Change Assessment Model (GCAM), an integrated assessment model to explore the interactions of energy, land and water systems in the context of alternative policies to limit climate change to three alternative levels: 2.5 Wm-2 (445 ppm CO2-e), 3.5 Wm-2 (535 ppm CO2-e) and 4.5 Wm-2 (645 ppm CO2-e). We explore the effects of alternative land-use emissions mitigation policy options—one which values terrestrial carbon emissions equally with fossil fuel and industrial emissions, and an alternative which places no penalty on land-use change emissions. We find that increasing populations and economic growth could be anticipated to lead to increased demand for water for agricultural systems (+200%), even in the absence of climate change. In general policies to mitigate climate change will increase agricultural demands for water, regardless of whether or not terrestrial carbon is valued or not. Burgeoning demands for water are driven by the demand for bioenergy in response to emissions mitigation policies. We also find that the policy matters. Increases in the demand for water when terrestrial carbon emissions go un-prices are vastly larger than when terrestrial system carbon emissions are prices at the same rate as fossil fuel and industrial emissions. Our estimates for increased water demands when terrestrial carbon systems go un-priced are larger than earlier studies. We find that the deployment of improved irrigation delivery systems could mitigate some of the increase in water demands, but cannot reverse the increases in water demands when terrestrial carbon emissions go un-priced. Finally we estimates that the geospatial pattern of water demands could stress some parts of the world, e.g. China, India and other countries in south and east Asia, earlier and more intensely than in other parts of the world, e.g. North America.

  10. Flexible programmable logic module

    DOE Patents [OSTI]

    Robertson, Perry J.; Hutchinson, Robert L.; Pierson, Lyndon G.

    2001-01-01

    The circuit module of this invention is a VME board containing a plurality of programmable logic devices (PLDs), a controlled impedance clock tree, and interconnecting buses. The PLDs are arranged to permit systolic processing of a problem by offering wide data buses and a plurality of processing nodes. The board contains a clock reference and clock distribution tree that can drive each of the PLDs with two critically timed clock references. External clock references can be used to drive additional circuit modules all operating from the same synchronous clock reference.

  11. Weather Research and Forecasting Model with Vertical Nesting Capability

    Energy Science and Technology Software Center (OSTI)

    2014-08-01

    The Weather Research and Forecasting (WRF) model with vertical nesting capability is an extension of the WRF model, which is available in the public domain, from www.wrf-model.org. The new code modifies the nesting procedure, which passes lateral boundary conditions between computational domains in the WRF model. Previously, the same vertical grid was required on all domains, while the new code allows different vertical grids to be used on concurrently run domains. This new functionality improvesmore » WRF's ability to produce high-resolution simulations of the atmosphere by allowing a wider range of scales to be efficiently resolved and more accurate lateral boundary conditions to be provided through the nesting procedure.« less

  12. Providing Reliability Services through Demand Response: A Prelimnary Evaluation of the Demand Response Capabilities of Alcoa Inc.

    SciTech Connect (OSTI)

    Starke, Michael R; Kirby, Brendan J; Kueck, John D; Todd, Duane; Caulfield, Michael; Helms, Brian

    2009-02-01

    Demand response is the largest underutilized reliability resource in North America. Historic demand response programs have focused on reducing overall electricity consumption (increasing efficiency) and shaving peaks but have not typically been used for immediate reliability response. Many of these programs have been successful but demand response remains a limited resource. The Federal Energy Regulatory Commission (FERC) report, 'Assessment of Demand Response and Advanced Metering' (FERC 2006) found that only five percent of customers are on some form of demand response program. Collectively they represent an estimated 37,000 MW of response potential. These programs reduce overall energy consumption, lower green house gas emissions by allowing fossil fuel generators to operate at increased efficiency and reduce stress on the power system during periods of peak loading. As the country continues to restructure energy markets with sophisticated marginal cost models that attempt to minimize total energy costs, the ability of demand response to create meaningful shifts in the supply and demand equations is critical to creating a sustainable and balanced economic response to energy issues. Restructured energy market prices are set by the cost of the next incremental unit of energy, so that as additional generation is brought into the market, the cost for the entire market increases. The benefit of demand response is that it reduces overall demand and shifts the entire market to a lower pricing level. This can be very effective in mitigating price volatility or scarcity pricing as the power system responds to changing demand schedules, loss of large generators, or loss of transmission. As a global producer of alumina, primary aluminum, and fabricated aluminum products, Alcoa Inc., has the capability to provide demand response services through its manufacturing facilities and uniquely through its aluminum smelting facilities. For a typical aluminum smelter, electric power accounts for 30% to 40% of the factory cost of producing primary aluminum. In the continental United States, Alcoa Inc. currently owns and/or operates ten aluminum smelters and many associated fabricating facilities with a combined average load of over 2,600 MW. This presents Alcoa Inc. with a significant opportunity to respond in areas where economic opportunities exist to help mitigate rising energy costs by supplying demand response services into the energy system. This report is organized into seven chapters. The first chapter is the introduction and discusses the intention of this report. The second chapter contains the background. In this chapter, topics include: the motivation for Alcoa to provide demand response; ancillary service definitions; the basics behind aluminum smelting; and a discussion of suggested ancillary services that would be particularly useful for Alcoa to supply. Chapter 3 is concerned with the independent system operator, the Midwest ISO. Here the discussion examines the evolving Midwest ISO market structure including specific definitions, requirements, and necessary components to provide ancillary services. This section is followed by information concerning the Midwest ISO's classifications of demand response parties. Chapter 4 investigates the available opportunities at Alcoa's Warrick facility. Chapter 5 involves an in-depth discussion of the regulation service that Alcoa's Warrick facility can provide and the current interactions with Midwest ISO. Chapter 6 reviews future plans and expectations for Alcoa providing ancillary services into the market. Last, chapter 7, details the conclusion and recommendations of this paper.

  13. Photovoltaic module and interlocked stack of photovoltaic modules

    DOE Patents [OSTI]

    Wares, Brian S.

    2012-09-04

    One embodiment relates to an arrangement of photovoltaic modules configured for transportation. The arrangement includes a plurality of photovoltaic modules, each photovoltaic module including a frame having at least a top member and a bottom member. A plurality of alignment features are included on the top member of each frame, and a plurality of alignment features are included on the bottom member of each frame. Adjacent photovoltaic modules are interlocked by the alignment features on the top member of a lower module fitting together with the alignment features on the bottom member of an upper module. Other embodiments, features and aspects are also disclosed.

  14. Energy Forecast, ForskEL (Smart Grid Project) | Open Energy Informatio...

    Open Energy Info (EERE)

    meeting both the clients' demand for cost stability and at the same time encourages a demand response. 2. Lack of information and awareness about the possibilities and...

  15. Using Utility Load Data to Estimate Demand for Space Cooling and Potential for Shiftable Loads

    SciTech Connect (OSTI)

    Denholm, P.; Ong, S.; Booten, C.

    2012-05-01

    This paper describes a simple method to estimate hourly cooling demand from historical utility load data. It compares total hourly demand to demand on cool days and compares these estimates of total cooling demand to previous regional and national estimates. Load profiles generated from this method may be used to estimate the potential for aggregated demand response or load shifting via cold storage.

  16. U.S. electric utility demand-side management 1996

    SciTech Connect (OSTI)

    1997-12-01

    The US Electric Utility Demand-Side Management report presents comprehensive information on electric power industry demand-side management (DSM) activities in the US at the national, regional, and utility levels. The objective of the publication is to provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it related to the US electric power industry. The first chapter, ``Profile: U.S. Electric Utility Demand-Side Management,`` presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions and costs attributable to DSM. 9 figs., 24 tabs.

  17. Formed photovoltaic module busbars

    SciTech Connect (OSTI)

    Rose, Douglas; Daroczi, Shan; Phu, Thomas

    2015-11-10

    A cell connection piece for a photovoltaic module is disclosed herein. The cell connection piece includes an interconnect bus, a plurality of bus tabs unitarily formed with the interconnect bus, and a terminal bus coupled with the interconnect bus. The plurality of bus tabs extend from the interconnect bus. The terminal bus includes a non-linear portion.

  18. Demand Response in U.S. Electricity Markets: Empirical Evidence |

    Energy Savers [EERE]

    Department of Energy in U.S. Electricity Markets: Empirical Evidence Demand Response in U.S. Electricity Markets: Empirical Evidence The work described in this paper was funded by the Office of Electricity Delivery and Energy Reliability, Permitting, Siting and Analysis of the U.S. Department of Energy under contract No. DE-AC02-05CH11231. The authors are solely responsible for any omissions or errors contained herein. PDF icon Demand Response in U.S. Electricity Markets: Empirical Evidence

  19. Evaluation of Representative Smart Grid Investment Project Technologies: Demand Response

    SciTech Connect (OSTI)

    Fuller, Jason C.; Prakash Kumar, Nirupama; Bonebrake, Christopher A.

    2012-02-14

    This document is one of a series of reports estimating the benefits of deploying technologies similar to those implemented on the Smart Grid Investment Grant (SGIG) projects. Four technical reports cover the various types of technologies deployed in the SGIG projects, distribution automation, demand response, energy storage, and renewables integration. A fifth report in the series examines the benefits of deploying these technologies on a national level. This technical report examines the impacts of a limited number of demand response technologies and implementations deployed in the SGIG projects.

  20. Fabricate-on-Demand Vacuum Insulating Glazings | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Fabricate-on-Demand Vacuum Insulating Glazings Fabricate-on-Demand Vacuum Insulating Glazings 1 of 3 PPG developed and commercialized the Intercept® Spacer System that revolutionized the manufacture of double-pane insulated glazing units (IGUs) 25 years ago. Over 125 PPG-licensed Intercept® Spacer System lines are in operation in the US. Currently in use in more than 600 million residential windows, the Intercept® Spacer System is the top-selling product of its kind in North America. Image: