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Sample records for forecast integration william

  1. 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 ...

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

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

    ... RIT forecasting is saving costs and improving operational practices for IPC and helping integrate wind power more efficiently and cost effectively. Figure 3 shows how the ...

  3. Final Report - Integration of Behind-the-Meter PV Fleet Forecasts...

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

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

  4. 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.

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

    Office of Energy Efficiency and Renewable Energy (EERE)

    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.

  6. Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System

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

    Operations | Department of Energy Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Clean Power Research logo.jpg This project will address the need for a more accurate approach to forecasting net utility load by taking into consideration the contribution of customer-sited PV energy generation. Tasks within the project are designed to integrate novel PV power

  7. Integration of Behind-the-Meter PV Fleet Forecasts into Utility...

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

    Forecasting behind-the-meter distributed PV generation power production within a region ... This project is expected to reduce the costs of integrating higher penetrations of PV into ...

  8. William Tang

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

    William Tang William Tang FES Requirements Worksheet 1.1. Project Information - Title Document Prepared By William Tang Project Title Title Principal Investigator William Tang Participating Organizations Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project Summary & Scientific Objectives for the Next 5 Years Please give a brief description of your project - highlighting its computational aspect - and outline its scientific objectives for the next 3-5 years. Please list one or two

  9. William Weaver

    Broader source: Energy.gov [DOE]

    William W. Weaver is a Nuclear Facilities and Tritium Risk Specialist in the Office of Chief Nuclear Safety, experienced with operation and decommissioning of nuclear facilities and tritium...

  10. Resource Information and Forecasting Group; Electricity, Resources, & Building Systems Integration (ERBSI) (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2009-11-01

    Researchers in the Resource Information and Forecasting group at NREL provide scientific, engineering, and analytical expertise to help characterize renewable energy resources and facilitate the integration of these clean energy sources into the electricity grid.

  11. Ramping Effect on Forecast Use: Integrated Ramping as a Mitigation Strategy; NREL (National Renewable Energy Laboratory)

    SciTech Connect (OSTI)

    Diakov, Victor; Barrows, Clayton; Brinkman, Gregory; Bloom, Aaron; Denholm, Paul

    2015-06-23

    Power generation ramping between forecasted (net) load set-points shift the generation (MWh) from its scheduled values. The Integrated Ramping is described as a method that mitigates this problem.

  12. Short-Term Load Forecasting Error Distributions and Implications for Renewable Integration Studies: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Lew, D.; Milligan, M.

    2013-01-01

    Load forecasting in the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process or with suitable reserves. An understanding of that load forecasting errors that may be expected in this process can lead to better decisions about the amount of reserves necessary to compensate errors. In this work, we performed a statistical analysis of the day-ahead (and two-day-ahead) load forecasting errors observed in two independent system operators for a one-year period. Comparisons were made with the normal distribution commonly assumed in power system operation simulations used for renewable power integration studies. Further analysis identified time periods when the load is more likely to be under- or overforecast.

  13. William F. Hederman, Jr. | Department of Energy

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

    William F. Hederman, Jr. About Us William F. Hederman, Jr. - Counselor to the Director and Senior Advisor to the Secretary William F. Hederman, Jr. William F. Hederman is the Deputy Director for Systems Integration and Senior Advisor to the Secretary. Mr. Hederman is a trained electrical engineer and public policy analyst with decades of executive experience in the private and public sectors. He began his professional career as a systems integration engineer at Bell Labs in the directorate that

  14. Ben Williams

    Broader source: Energy.gov [DOE]

    In October 2015, Ben Williams began serving as the interim senior communications specialist for the Office of Technology Transitions for the Department of Energy.Prior to his detail in the office,...

  15. Analysis and Synthesis of Load Forecasting Data for Renewable Integration Studies: Preprint

    SciTech Connect (OSTI)

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

    2013-11-01

    As renewable energy constitutes greater portions of the generation fleet, the importance of modeling uncertainty as part of integration studies also increases. In pursuit of optimal system operations, it is important to capture not only the definitive behavior of power plants, but also the risks associated with systemwide interactions. This research examines the dependence of load forecast errors on external predictor variables such as temperature, day type, and time of day. The analysis was utilized to create statistically relevant instances of sequential load forecasts with only a time series of historic, measured load available. The creation of such load forecasts relies on Bayesian techniques for informing and updating the model, thus providing a basis for networked and adaptive load forecast models in future operational applications.

  16. Williams named ASA Fellow

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

    Williams named ASA Fellow May 27, 2015 The American Statistical Association (ASA) has honored Brian Williams of LANL's Statistical Sciences group with the title of Fellow. Williams...

  17. Signature of William H. Goldstein Signature of William H. Goldstein

    National Nuclear Security Administration (NNSA)

    William H. Goldstein Signature of William H. Goldstein Signature of William H. Goldstein Signature of William H. Goldstein Signature of N. Nicole Nelson - Jean Signature of N. ...

  18. Williams named ASA Fellow

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

    May » Williams named ASA Fellow Williams named ASA Fellow The American Statistical Association (ASA) has honored Brian Williams with the title of Fellow. May 27, 2015 Brian Williams Brian Williams Communications Office (505) 667-7000 His research includes experimental design, computer experiments, Bayesian inference, spatial statistics, and statistical computing. The American Statistical Association (ASA) has honored Brian Williams of LANL's Statistical Sciences group with the title of Fellow.

  19. Unit commitment with wind power generation: integrating wind forecast uncertainty and stochastic programming.

    SciTech Connect (OSTI)

    Constantinescu, E. M.; Zavala, V. M.; Rocklin, M.; Lee, S.; Anitescu, M.

    2009-10-09

    We present a computational framework for integrating the state-of-the-art Weather Research and Forecasting (WRF) model in stochastic unit commitment/energy dispatch formulations that account for wind power uncertainty. We first enhance the WRF model with adjoint sensitivity analysis capabilities and a sampling technique implemented in a distributed-memory parallel computing architecture. We use these capabilities through an ensemble approach to model the uncertainty of the forecast errors. The wind power realizations are exploited through a closed-loop stochastic unit commitment/energy dispatch formulation. We discuss computational issues arising in the implementation of the framework. In addition, we validate the framework using real wind speed data obtained from a set of meteorological stations. We also build a simulated power system to demonstrate the developments.

  20. FY 1996 solid waste integrated life-cycle forecast characteristics summary. Volumes 1 and 2

    SciTech Connect (OSTI)

    Templeton, K.J.

    1996-05-23

    For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the physical waste forms, hazardous waste constituents, and radionuclides of the waste expected to be shipped to the CWC from 1996 through the remaining life cycle of the Hanford Site (assumed to extend to 2070). In previous years, forecast data has been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to two previous reports: the more detailed report on waste volumes, WHC-EP-0900, FY1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary and the report on expected containers, WHC-EP-0903, FY1996 Solid Waste Integrated Life-Cycle Forecast Container Summary. All three documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on two main characteristics: the physical waste forms and hazardous waste constituents of low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major generators for each waste category and waste characteristic are also discussed. The characteristics of low-level waste (LLW) are described in Appendix A. In addition, information on radionuclides present in the waste is provided in Appendix B. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste is expected to be received at the CWC over the remaining life cycle of the site. Based on

  1. 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.

  2. Tommy Williams | Open Energy Information

    Open Energy Info (EERE)

    Tommy Williams Jump to: navigation, search Name: Tommy Williams Place: Gainesville, FL Website: www.tommywilliams.com References: Tommy Williams1 Information About Partnership...

  3. NREL: Photovoltaics Research - William Nemeth

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

    Photo of William Nemeth William Nemeth Research Engineer On staff since: 2008 Phone number: 303-384-7801 Email William Nemeth Primary Research Interests Silicon solar cell...

  4. FY 1996 solid waste integrated life-cycle forecast container summary volume 1 and 2

    SciTech Connect (OSTI)

    Valero, O.J.

    1996-04-23

    For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the containers expected to be used for these waste shipments from 1996 through the remaining life cycle of the Hanford Site. In previous years, forecast data have been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to the more detailed report on waste volumes: WHC-EP0900, FY 1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary. Both of these documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on the types of containers that will be used for packaging low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major waste generators for each waste category and container type are also discussed. Containers used for low-level waste (LLW) are described in Appendix A, since LLW requires minimal treatment and storage prior to onsite disposal in the LLW burial grounds. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste are expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters.

  5. 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...

  6. Trish Williams | Department of Energy

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

    Trish Williams About Us Trish Williams - Communications Specialist, EERE Communications Office Most Recent Energy Department Dream Team Opens Students' Eyes to Limitless STEM ...

  7. Wind Energy Management System Integration Project Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

    2010-09-01

    features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. In this report, a new methodology to predict the uncertainty ranges for the required balancing capacity, ramping capability and ramp duration is presented. Uncertainties created by system load forecast errors, wind and solar forecast errors, generation forced outages are taken into account. The uncertainty ranges are evaluated for different confidence levels of having the actual generation requirements within the corresponding limits. The methodology helps to identify system balancing reserve requirement based on a desired system performance levels, identify system “breaking points”, where the generation system becomes unable to follow the generation requirement curve with the user-specified probability level, and determine the time remaining to these potential events. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (California ISO) real life data have shown the effectiveness of the proposed approach. A tool developed based on the new methodology described in this report will be integrated with the California ISO systems. Contractual work is currently in place to integrate the tool with the AREVA EMS system.

  8. William Brocker | Argonne National Laboratory

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

    William Brocker ESH/QA Coordinator - EGS E-mail wbrocker

  9. Melvin G. Williams, Jr.

    Broader source: Energy.gov [DOE]

    Melvin G. Williams Jr., Vice Admiral, U.S. Navy (retired), served as the Associate Deputy Secretary of Energy until February 2013.   As a Presidential Appointee at the U.S. Department of...

  10. William E. Murphie

    Broader source: Energy.gov [DOE]

    William Murphie was appointed in 2003 to manage the activities of the U.S. Department of Energy's newly created Portsmouth/Paducah Project Office (PPPO) in Lexington, Kentucky to provide...

  11. Williams, Joel F Jr

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

    ... that vou will be accompanying her at this meeting and to Put you on emails to Ms. ... Thanks Joel for both infG emails. From*. William, Joel F Jr rnvifto:Joel F Jr ...

  12. Integration of Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Chakrabarti, Bhujanga B.; Subbarao, Krishnappa; Loutan, Clyde; Guttromson, Ross T.

    2010-04-20

    In this paper, a new approach to evaluate the uncertainty ranges for the required generation performance envelope, including the balancing capacity, ramping capability and ramp duration is presented. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (CAISO) real life data have shown the effectiveness and efficiency of the proposed approach.

  13. Roy Williams as recalled by Margaret Morrow ? Or: Roy Williams...

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

    Margaret Morrow - Or: Roy Williams, a man with great presence and leadership (title as it appeared in The Oak Ridger) The series on Roy Williams has created a great response from...

  14. Solid waste integrated forecast technical (SWIFT) report: FY1997 to FY 2070, Revision 1

    SciTech Connect (OSTI)

    Valero, O.J.; Templeton, K.J.; Morgan, J.

    1997-01-07

    This web site provides an up-to-date report on the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: an overview of Hanford-wide solid waste to be managed by the WM Project; program-level and waste class-specific estimates; background information on waste sources; and comparisons with previous forecasts and with other national data sources. This web site does not include: liquid waste (current or future generation); waste to be managed by the Environmental Restoration (EM-40) contractor (i.e., waste that will be disposed of at the Environmental Restoration Disposal Facility (ERDF)); or waste that has been received by the WM Project to date (i.e., inventory waste). The focus of this web site is on low-level mixed waste (LLMW), and transuranic waste (both non-mixed and mixed) (TRU(M)). Some details on low-level waste and hazardous waste are also provided. Currently, this web site is reporting data th at was requested on 10/14/96 and submitted on 10/25/96. The data represent a life cycle forecast covering all reported activities from FY97 through the end of each program's life cycle. Therefore, these data represent revisions from the previous FY97.0 Data Version, due primarily to revised estimates from PNNL. There is some useful information about the structure of this report in the SWIFT Report Web Site Overview.

  15. Solid Waste Integrated Forecast Technical (SWIFT) Report FY2001 to FY2046 Volume 1

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2000-08-31

    This report provides up-to-date life cycle information about the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: an overview of Hanford-wide solid waste to be managed by the WM Project; program-level and waste class-specific estimates; background information on waste sources; and comparisons to previous forecasts and other national data sources. This report does not include: waste to be managed by the Environmental Restoration (EM-40) contractor (i.e., waste that will be disposed of at the Environmental Restoration Disposal Facility (ERDF)); waste that has been received by the WM Project to date (i.e., inventory waste); mixed low-level waste that will be processed and disposed by the River Protection Program; and liquid waste (current or future generation). Although this report currently does not include liquid wastes, they may be added as information becomes available.

  16. Mr. William Steuteville

    Office of Legacy Management (LM)

    45 DEC 18 13% Mr. William Steuteville 3 HW 33 EPA Region III 841 Chestnut Street Philadelphia, Pennsylvania 19107 Dear Mr. Steuteville: I am enclosing for your information a copy of the radiological survey report for the former Aeroprojects Facility in West Chester, Pennsylvania. The survey was performed for the U.S. Department of Energy (DOE) by Oak Ridge National Laboratory. Only background levels of radioactivity were found during the course of the survey. A copy of the survey has been

  17. Bradley Williams | Department of Energy

    Broader source: Energy.gov (indexed) [DOE]

    Bradley Williams - Team Lead, Nuclear Energy University Programs Most Recent New Nuclear Energy Awards Give Students Hands-On Research Experience September 28...

  18. William T. Freeman

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

    A big world of tiny motions William T. Freeman Massachusetts Institute of Technology (MIT) June 3, 2015 4:00 p.m. (coffee @ 3:30) We have developed a "motion microscope" to visualize small motions by synthesizing a video with the desired motions amplified. The project began as an algorithm to amplify small color changes in videos, allowing color changes from blood flow to be visualized. Modifications to this algorithm allow small motions to be amplified in a video. I'll describe the

  19. 2016 Solar Forecasting Workshop

    Office of Energy Efficiency and Renewable Energy (EERE)

    On August 3, 2016, the SunShot Initiative's systems integration subprogram hosted the Solar Forecasting Workshop to convene experts in the areas of bulk power system operations, distribution system operations, weather and solar irradiance forecasting, and photovoltaic system operation and modeling. The goal was to identify the technical challenges and opportunities in solar forecasting as a capability that can significantly reduce the integration cost of high levels of solar energy into the electricity grid. This will help SunShot to assess current technology and practices in this field and identify the gaps and needs for further research.

  20. Williams Energy Services | Open Energy Information

    Open Energy Info (EERE)

    Energy Services Jump to: navigation, search Name: Williams Energy Services Place: Tulsa, OK Website: www.williamsenergyservices.com References: Williams Energy Services1...

  1. Williams Stone Wind Turbine | Open Energy Information

    Open Energy Info (EERE)

    Stone Wind Turbine Jump to: navigation, search Name Williams Stone Wind Turbine Facility Williams Stone Wind Turbine Sector Wind energy Facility Type Community Wind Facility Status...

  2. William Alexander | Department of Energy

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

    William Alexander Mr. Alexander is a graduate of New Mexico Mining and Technology Institute, in Socorro New Mexico. He has been working in the Los Alamos area since 2007, where he ...

  3. Federal Energy and Water Management Award Winners William Kuster...

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

    William Kuster, John McDuffie, Dennis Svalstad, William Turnbull and Steven White Federal Energy and Water Management Award Winners William Kuster, John McDuffie, Dennis Svalstad, ...

  4. EA-208 Williams Energy Marketing and Trading Company | Department...

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

    8 Williams Energy Marketing and Trading Company EA-208 Williams Energy Marketing and Trading Company Order authorizing Williams Energy Marketing and Trading Company to export ...

  5. Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

    2010-01-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter

  6. William N. Haberichter | Argonne National Laboratory

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

    William N. Haberichter Argonne Associate Telephone (630) 252-7525 E-mail wnh@hep.anl

  7. 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.

  8. SOLID WASTE INTEGRATED FORECAST TECHNICAL (SWIFT) REPORT FY2005 THRU FY2035 2005.0 VOLUME 2

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2005-08-17

    This report provides up-to-date life cycle information about the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: (1) an overview of Hanford-wide solid waste to be managed by the WM Project; (2) multi-level and waste class-specific estimates; (3) background information on waste sources; and (4) comparisons to previous forecasts and other national data sources. The focus of this report is low-level waste (LLW), mixed low-level waste (MLLW), and transuranic waste, both non-mixed and mixed (TRU(M)). Some details on hazardous waste are also provided, however, this information is not considered comprehensive. This report includes data requested in December, 2004 with updates through March 31,2005. The data represent a life cycle forecast covering all reported activities from FY2005 through the end of each program's life cycle and are an update of the previous FY2004.1 data version.

  9. 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....

  10. SOLID WASTE INTEGRATED FORECAST TECHNICAL (SWIFT) REPORT FY2003 THRU FY2046 VERSION 2003.1 VOLUME 2 [SEC 1 & 2

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2003-12-01

    This report includes data requested on September 10, 2002 and includes radioactive solid waste forecasting updates through December 31, 2002. The FY2003.0 request is the primary forecast for fiscal year FY 2003.

  11. The .Hoiorable William S. Cohen'

    Office of Legacy Management (LM)

    Secretary of Energy' Washington, bC 20585 October 10, 1997 ' . , :. . The .Hoiorable William S. Cohen' Secretary of' eefense Washing+, D.C. 203Oi .' Dear Mr. Se&etm: ,_ -_ . . ' ,I. ' . a- / 4 ' . \ ' . The Congr&s recently se$ tp the President for signature the' Energy and Water Development Appropriations Act, 1998. Among other provi$ions, this bill would immediately transfer responsibility forthe Formerly:U&zed Sites Remedial Action . Program (FUSRAP) from the Department of Energy

  12. The Honorable, William S . Cohen

    Office of Legacy Management (LM)

    c - . .' 0 -- .' . . - . . The Honorable, William S . Cohen . : Secretary ofDefense Washington, D.C. 20301 -. , 1. .' .- - I &karMr. Secretary: . ' The Congress recently sent to the President for signature the Energy and Water Development Appropriations Act, 1998. Among other provisions, this bill would immediately transfer responsibility for the Formerly Utilized Sites Remedial Action Program @USRAP) from the Department of Energy to the United States Army Corps of Engineers. Assuming that

  13. William A. Goddard III - JCAP

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

    william a. goddard iii Principal Investigator Email: wag@wag.caltech.edu Dr. Goddard is a pioneer in developing methods for quantum mechanics (QM), force fields, molecular dynamics (MD), and Monte Carlo predictions on chemical and materials systems and is actively involved in applying these methods to ceramics, semiconductors, superconductors, thermoelectrics, metal alloys, polymers, proteins, nuclei acids, Pharma ligands, nanotechnology, and energetic materials. He uses QM methods to determine

  14. Timothy Williams | Argonne Leadership Computing Facility

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

    Timothy Williams Deputy Director of Science Timothy Williams Argonne National Laboratory 9700 South Cass Avenue Building 240 - Rm. 2129 Argonne, IL 60439 630-252-1154 tjwilliams@anl.gov http://alcf.anl.gov/~zippy Tim Williams is a computational scientist at the Argonne Leadership Computing Facility (ALCF), where he serves as Deputy Director of Science. He is manager of the Early Science Program, which prepares scientific applications for early use of the facility's next-generation

  15. William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) | U.S.

    Office of Science (SC) Website

    DOE Office of Science (SC) William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) Biological and Environmental Research (BER) BER Home About Research Biological Systems Science Division (BSSD) Climate and Environmental Sciences Division (CESD) ARM Climate Research Facility Atmospheric System Research (ASR) Program Data Management Earth System Modeling (ESM) Program William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) Integrated Assessment of Global Climate Change

  16. Kumar, Jitendra; Hoffman, Forrest; Hargrove, William; Mills,...

    Office of Scientific and Technical Information (OSTI)

    based Sampling Network Design for the State of Alaska Kumar, Jitendra; Hoffman, Forrest; Hargrove, William; Mills, Richard 54 Environmental Sciences Ecoregions; Representativeness;...

  17. Williams Biomass Facility | Open Energy Information

    Open Energy Info (EERE)

    USA Biomass National Map Retrieved from "http:en.openei.orgwindex.php?titleWilliamsBiomassFacility&oldid398342" Feedback Contact needs updating Image needs updating...

  18. Williams, Arizona: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Williams, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.2494566, -112.1910031 Show Map Loading map... "minzoom":false,"mappingser...

  19. Bicycle Generator Lightbar Indicator ----- Inventors William...

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

    ----- Inventors William Evans (Princeton University), Andrew Zwicker, and Shana Weber (Princeton University) This invention is a series of incandescent light bulbs that...

  20. William R. Harvey | Department of Energy

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

    William R. Harvey About Us William R. Harvey, Ph.D. - President, Hampton University Dr. William R. Harvey Dr. William R. Harvey is President of Hampton University and 100% owner of the Pepsi Cola Bottling Company of Houghton, Michigan. Since 1978, he has served with distinction as President of Hampton University and created a monumental legacy during his thirty year tenure-one of the longest tenures of any sitting president of a college or university in the country. Dr. Harvey is described as

  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. William E. and Diane M. Spicer Young Investigator Award | Stanford...

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

    William E. and Diane M. Spicer Young Investigator Award William E. and Diane M. Spicer Young Investigator Award William E. Spicer (1929-2004) was an esteemed member of the...

  3. Sherwin-Williams' Richmond, Kentucky, Facility Achieves 26% Energy...

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

    Sherwin-Williams' Richmond, Kentucky, Facility Achieves 26% Energy Intensity Reduction; Leads to Corporate Adoption of Save Energy Now LEADER Sherwin-Williams' Richmond, Kentucky, ...

  4. DOE - Office of Legacy Management -- Baker and Williams Co -...

    Office of Legacy Management (LM)

    Baker and Williams Co - NJ 13 FUSRAP Considered Sites Site: Baker and Williams Co (NJ 13) Eliminated from consideration under FUSRAP Designated Name: Not Designated Alternate Name:...

  5. Mountrail-Williams Elec Coop | Open Energy Information

    Open Energy Info (EERE)

    Mountrail-Williams Elec Coop Jump to: navigation, search Name: Mountrail-Williams Elec Coop Place: North Dakota Phone Number: Williston Office- 701-577-3765 -- Stanley Office-...

  6. City of Williams - AZ, Arizona (Utility Company) | Open Energy...

    Open Energy Info (EERE)

    Williams - AZ, Arizona (Utility Company) Jump to: navigation, search Name: City of Williams - AZ Place: Arizona Phone Number: 928-635-2667 or 928-635-4451 Website:...

  7. W&M, JLab Host International Neutrino Workshop (William & Mary...

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

    W&M, JLab Host International Neutrino Workshop (William & Mary News & Events) External Link: http:www.wm.edunewsstories2012william--mary-hosts-international-neutrino-w... By ...

  8. EA-158 Williams Energy Services Company | Department of Energy

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

    8 Williams Energy Services Company EA-158 Williams Energy Services Company Order authorizing Williams Energy Services Company to export electric energy to Canada. EA-158 Williams Energy Services Company (45.04 KB) More Documents & Publications EA-162 PP&L, Inc EA-164 Constellation Power Source

  9. Dianne Williams Wilburn-Creating her

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

    Dianne Williams Wilburn-Creating her own destiny March 11, 2014 Creating her own destiny Dianne Williams Wilburn does not have an ounce of pretension or narcissism. Nominated by multiple Los Alamos colleagues as an inspirational woman, the always- smiling Wilburn deflects attention. When asked about challenges she has overcome or how courage has touched her life, she does not mention the fact that she recently battled breast cancer. Instead, she focuses on the positive, focuses on the

  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 3,151 3,302 4.8% Price (cents/kWh) 12.06 12.09 12.58 13.04 12.95 12.84 -0.9% Expenditures $415 $405 $393 $396 $408 $424 3.9% New England Usage (kWh) 2,122 2,188 2,173 1,930 1,992 2,082 4.5% Price (cents/kWh) 15.85 15.50 16.04 17.63 18.64 18.37 -1.5% Expenditures $336 $339 $348 $340 $371 $382 3.0% Mid-Atlantic Usage (kWh) 2,531 2,548 2,447 2,234 2,371 2,497 5.3% Price (cents/kWh) 16.39 15.63

  11. Buildng America Whole-House Solutions for New Homes: William...

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

    Buildng America Whole-House Solutions for New Homes: William Ryan Homes, Tampa, Florida Buildng America Whole-House Solutions for New Homes: William Ryan Homes, Tampa, Florida Case ...

  12. William & Mary Undergrad Receives JSA Research Assistantship | Jefferson

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

    Lab William & Mary Undergrad Receives JSA Research Assistantship William & Mary Undergrad Receives JSA Research Assistantship Alice Perrin, a senior physics major at The College of William and Mary Alice Perrin, a senior physics major at The College of William and Mary is the recipient of the 2014-15 Jefferson Science Associates Minority/Female Undergraduate Research Assistantship (JSA MFURA) at Jefferson Lab. Her assistantship project involves setting up a testing facility to

  13. Anderson-Cook wins William G. Hunter Award

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

    Anderson-Cook Wins William G. Hunter Award Anderson-Cook wins William G. Hunter Award The award is named and presented annually in honor of the Statistics Division's founding chair, William G. Hunter. November 6, 2012 Christine Anderson-Cook Christine Anderson-Cook Christine Anderson-Cook of LANL's Statistical Sciences group has received the 2012 William G. Hunter Award from the American Society for Quality-Statistics Division. The award is named and presented annually in honor of the Statistics

  14. Geothermal Literature Review At General Us Region (Williams ...

    Open Energy Info (EERE)

    navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermal Literature Review At General Us Region (Williams & Reed, 2005) Exploration Activity Details...

  15. Builders Challenge High Performance Builder Spotlight Tommy Williams Homes

    SciTech Connect (OSTI)

    2010-02-05

    Builders Challenge fact sheet highlighting performance and energy-efficiency features of Tommy Williams Homes, Longleaf case study, Gainesville, FL

  16. Solid waste integrated forecast technical (SWEFT) report: FY1997 to FY 2070 - Document number changed to HNF-0918 at revision 1 - 1/7/97

    SciTech Connect (OSTI)

    Valero, O.J.

    1996-10-03

    This web site provides an up-to-date report on the radioactive solid waste expected to be managed at Hanford`s Solid Waste (SW) Program from onsite and offsite generators. It includes: an overview of Hanford-wide solid waste to be managed by the SW Program; program- level and waste class-specific estimates; background information on waste sources; and Li comparisons with previous forecasts and with other national data sources. The focus of this web site is on low- level mixed waste (LLMW), and transuranic waste (both non-mixed and mixed) (TRU(M)). Some details on low-level waste and hazardous waste are also provided. Currently, this site is reporting data current as of 9/96. The data represent a life cycle forecast covering all reported activities from FY97 through the end of each program`s life cycle.

  17. Roy Williams as recalled by his son and family ? Or: Roy Williams...

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

    his son and family - Or: Roy Williams: A leader among many (title at it appeared The Oak Ridger) The rewards for writing stories about Y-12 history come in many and varied formsl...

  18. 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.

  19. Federal Energy and Water Management Award Winners William Kuster, John

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

    McDuffie, Dennis Svalstad, William Turnbull and Steven White | Department of Energy William Kuster, John McDuffie, Dennis Svalstad, William Turnbull and Steven White Federal Energy and Water Management Award Winners William Kuster, John McDuffie, Dennis Svalstad, William Turnbull and Steven White fewm13_acclangley_highres.pdf (3.11 MB) fewm13_acclangley.pdf (2.8 MB) More Documents & Publications October 2009 Seismic Lessons-Learned panel Meeting Implementation of DOE NPH Requirements at

  20. John J. MacWilliams | Department of Energy

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

    J. MacWilliams About Us John J. MacWilliams - Associate Deputy Secretary John J. MacWilliams John J. MacWilliams was appointed in August 2015 as Associate Deputy Secretary of the U.S. Department of Energy. He also serves as the Department's Chief Risk Officer and advances Secretarial priorities of enterprise-wide approaches to innovative finance, risk management, project management, nuclear and cyber security. Mr. MacWilliams joined the Department in May 2013 as a Senior Advisor to the

  1. The HonorableZ William S. Cohen

    Office of Legacy Management (LM)

    .- . ) p. .' *-. , * . . _ The Secretary of Energy d ' -- ,. Washington. s>C 20585 October 10, 199' 7 ' ./ .- ~ * The HonorableZ William S. Cohen : Secretary ofDefense Washington, D.C. 20301 -' Jkar Mr. Secretary: /' . " _,.. .- - z ' The Congress recently sent to the President for signature the Energy and Water . Development Appropriations Act,' 1998. Among other provisions, this bill would immediately transfer responsibility for the Formerly' Utilized Sites Remedial Action Program

  2. 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 ...

  3. 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...

  4. Forecasting Water Quality & Biodiversity

    Broader source: Energy.gov (indexed) [DOE]

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

  5. 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.

  6. William E. and Diane M. Spicer Young Investigator Award | Stanford

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

    Synchrotron Radiation Lightsource William E. and Diane M. Spicer Young Investigator Award William E. and Diane M. Spicer Young Investigator Award William E. Spicer (1929-2004) was an esteemed member of the international scientific community as a teacher and researcher in electrical engineering, applied physics and materials science. Bill spent the past 40 years as a professor at Stanford where he pioneered the technique ofultraviolet photoemission spectroscopy and its subsequent expansion

  7. Anderson-Cook wins William G. Hunter Award

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

    Anderson-Cook wins William G. Hunter Award November 6, 2012 Christine Anderson-Cook of LANL's Statistical Sciences group has received the 2012 William G. Hunter Award from the American Society for Quality-Statistics Division. The award is named and presented annually in honor of the Statistics Division's founding chair, William G. Hunter. The award is presented to a person whose qualities mirror those of Hunter. These include substantial contributions to statistical consulting, education for

  8. Replace Fossil Fuels, Final Technical Report Roberts, William...

    Office of Scientific and Technical Information (OSTI)

    Crude Glycerol as Cost-Effective Fuel for Combined Heat and Power to Replace Fossil Fuels, Final Technical Report Roberts, William L 09 BIOMASS FUELS biofuels, glycerin, glycerol,...

  9. Buildng America Whole-House Solutions for New Homes: William...

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

    More Documents & Publications Building America Whole-House Solutions for New Homes: Tommy Williams Homes, Gainesville, Florida Building America Best Practices Series Volume 15: 40% ...

  10. Static Temperature Survey At San Andreas Region (Williams, Et...

    Open Energy Info (EERE)

    San Andreas Region (Williams, Et Al., 2004) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Static Temperature Survey At San Andreas Region...

  11. Geographic Information System At U.S. West Region (Williams ...

    Open Energy Info (EERE)

    U.S. West Region (Williams & Deangelo, 2008) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geographic Information System At U.S. West Region...

  12. MHK Projects/Williams Point Project | Open Energy Information

    Open Energy Info (EERE)

    Williams Point Project < MHK Projects Jump to: navigation, search << Return to the MHK database homepage Loading map... "minzoom":false,"mappingservice":"googlemaps3","type":"ROAD...

  13. Barnes, Cris William [Los Alamos National Laboratory]; Kippen...

    Office of Scientific and Technical Information (OSTI)

    MaRIE: A facility for time-dependent materials science at the mesoscale Barnes, Cris William Los Alamos National Laboratory; Kippen, Karen Elizabeth Los Alamos National...

  14. Challenge of Dynamic Mesoscale Imaging Barnes, Cris William ...

    Office of Scientific and Technical Information (OSTI)

    The Matter-Radiation Interactions in Extremes Project, and the Challenge of Dynamic Mesoscale Imaging Barnes, Cris William Los Alamos National Laboratory; Barber, John L. Los...

  15. Anderson-Cook wins William G. Hunter Award

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

    Christine Anderson-Cook Christine Anderson-Cook Christine Anderson-Cook of LANL's Statistical Sciences group has received the 2012 William G. Hunter Award from the American...

  16. William S. Maharay: Before the Subcommittee on Government Management...

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

    Organization and Procurement Committee on Oversight and Government Reform U.S. House William S. Maharay: Before the Subcommittee on Government Management, Organization and ...

  17. Williams To Head Livermore Site Office | National Nuclear Security...

    National Nuclear Security Administration (NNSA)

    Williams To Head Livermore Site Office August 14, 2008 WASHINGTON, D.C. - Alice C. ... and environment, has been named the new Livermore Site Office manager, effective November ...

  18. Albert "Al" J. Williams | Department of Energy

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

    Albert "Al" J. Williams About Us Albert "Al" J. Williams - President, Chevron Pipe Line Company (CPL) Albert “Al” J. Williams Albert (Al) J. Williams is president of Chevron Pipe Line Company (CPL), a wholly-owned subsidiary of Chevron Corporation, a role he assumed in May 2014. He is responsible for managing an extensive network of crude oil, natural gas and refined product pipelines, as well as storage facilities in North America. CPL also provides technical,

  19. Two NNSA Awards for LSO's Alice Williams | National Nuclear Security...

    National Nuclear Security Administration (NNSA)

    NNSA Blog Livermore Site Office Manager Alice Williams yesterday received the NNSA Gold Medal for distinguished service in the national security of the United States and the...

  20. Microsoft PowerPoint - Briefings_Williams [Compatibility Mode...

    Office of Environmental Management (EM)

    Jeff Williams Project Director National Transportation Stakeholders Forum Bloomington, Minnesota May 13-15, 2014 NFST Established to Plan for Interim Storage and Transportation ...

  1. William Herschel, the First Observational Cosmologist

    ScienceCinema (OSTI)

    Lemonick, Michael [Princeton University and Time Magazine, Princeton, New Jersey, United States

    2010-01-08

    In the late 1700s, a composer, orchestra director and soloist named William Herschel became fascinated with astronomy, and, having built his own reflecting telescope, went out in his garden in Bath, England, one night and discovered Uranus?the first planet in human history ever found by an individual. The feat earned him a lifetime pension from King George III. But Herschel considered the discovery to be relatively unimportant in comparison to his real work: understanding the composition, structure and evolution of the universe. In pursuing that work, he became the first observational cosmologist.

  2. Data Acquisition-Manipulation At U.S. West Region (Williams ...

    Open Energy Info (EERE)

    Williams & Deangelo, 2008) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Data Acquisition-Manipulation At U.S. West Region (Williams &...

  3. Camp William Utah National Guard Wind Farm II | Open Energy Informatio...

    Open Energy Info (EERE)

    II Jump to: navigation, search Name Camp William Utah National Guard Wind Farm II Facility Camp William Utah National Guard Sector Wind energy Facility Type Community Wind Facility...

  4. Today's Forecast: Improved Wind Predictions

    Broader source: Energy.gov [DOE]

    Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable.

  5. Solar Forecast Improvement Project

    Office of Energy Efficiency and Renewable Energy (EERE)

    For the Solar Forecast Improvement Project (SFIP), the Earth System Research Laboratory (ESRL) is partnering with the National Center for Atmospheric Research (NCAR) and IBM to develop more...

  6. 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

  7. 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.

  8. The Honorable Robert E. Williams 44 W. Washington Street

    Office of Legacy Management (LM)

    If you have any questions, please feel free to call me at 301-427-1721 or Dr. W. Alexander Williams (301-427-1719) oi my staff. Sincerely, 7 4 I T- 2L ( &.&&& LAJ- ...

  9. John William (Bill) Ebert Jr. ? Longtime Y-12 Maintenance Manager

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

    John William (Bill) Ebert Jr. - Longtime Y-12 Maintenance Manager I knew him as "Mr. Ebert" when his office was in Building 9734. I used to park my bicycle in the hallway just...

  10. Dr. Ellen Williams Confirmed as Director of ARPA-E

    Broader source: Energy.gov [DOE]

    WASHINGTON – Dr. Ellen Williams was confirmed by the United States Senate on Monday, December 8, 2014 as the Director of the Department of Energy’s Advanced Research Projects Agency – Energy (ARPA-E).

  11. VBH-0079- In the Matter of William Cor

    Broader source: Energy.gov [DOE]

    This Decision involves a whistleblower complaint filed by William Cor under the Department of Energy's (DOE) Contractor Employee Protection Program. From August 1998 to September 2001, Mr. Cor was...

  12. TBU-0045- In the Matter of William Cor

    Broader source: Energy.gov [DOE]

    William Cor (the complainant or the employee), appeals the dismissal of his complaint of retaliation filed under 10 C.F.R. Part 708, the Department of Energy (DOE) Contractor Employee Protection...

  13. Roy Williams as recalled by Bill Wilcox and others

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

    worked for Roy, calling him a "wonderful boss that everyone liked." I also asked Ken Brady to comment on Roy Williams. I believe his insight is helpful to demonstrate a...

  14. From: Miller, William [mailto:wmiller@McCarter.com

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

    ... If you have any questions regarding this email or our questions, please contact me or Rick Murphy at AGA. Thank you - Bud William T. Miller | Partner McCARTER & ENGLISH, LLP 1015 ...

  15. From: Miller, William [mailto:wmiller@McCarter.com

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

    ... Bud William T. Miller | Partner McCARTER & ENGLISH, LLP 1015 15th Street, NW, 12th Floor | ... message from the law firm of McCarter & English, LLP is for the sole use of the intended ...

  16. From: Miller, William [mailto:wmiller@McCarter.com

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

    ... whether DOE intends to heed this request. Bud William T. Miller | Partner McCARTER & ENGLISH, LLP 1015 15th Street, NW, 12th Floor | Washington DC, 20005 T: 202-753-3420 F: ...

  17. TO: Alexander Williams FROM: Ed MitchelfiM

    Office of Legacy Management (LM)

    420 OTS NOTE . DATE: September 13, 1990 TO: Alexander Williams FROM: Ed MitchelfiM NY 463 fusrap7 SUBJECT: Elimination Recommendation for American Machine and Foundry in Buffalo...

  18. Williams County, Ohio: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Hide Map This article is a stub. You can help OpenEI by expanding it. Williams County is a county in Ohio. Its FIPS County Code is 171. It is classified as ASHRAE...

  19. Williams Creek, Indiana: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Hide Map This article is a stub. You can help OpenEI by expanding it. Williams Creek is a town in Marion County, Indiana. It falls under Indiana's 5th congressional...

  20. Williams County, North Dakota: Energy Resources | Open Energy...

    Open Energy Info (EERE)

    Hide Map This article is a stub. You can help OpenEI by expanding it. Williams County is a county in North Dakota. Its FIPS County Code is 105. It is classified as...

  1. Y-12s Moon Rocks and Jim Williams

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

    Moon Rocks and Jim Williams Often I am stopped and given suggestions about what would be good information to include in the history of Y-12 being published weekly in The Oak...

  2. King William County, Virginia: Energy Resources | Open Energy...

    Open Energy Info (EERE)

    Hide Map This article is a stub. You can help OpenEI by expanding it. King William County is a county in Virginia. Its FIPS County Code is 101. It is classified...

  3. 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.

  4. William S. Maharay: Before the Subcommittee on Government Management,

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

    Organization and Procurement Committee on Oversight and Government Reform U.S. House | Department of Energy William S. Maharay: Before the Subcommittee on Government Management, Organization and Procurement Committee on Oversight and Government Reform U.S. House William S. Maharay: Before the Subcommittee on Government Management, Organization and Procurement Committee on Oversight and Government Reform U.S. House March 20, 2007 Before the Subcommittee on Government Management, Organization

  5. Principal Deputy Chief William A. Eckroade's Written Testimony Before the

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

    Subcommittee on Financial and Contracting Oversight Committee on Homeland Security and Governmental Affairs (March 11, 2014) | Department of Energy Principal Deputy Chief William A. Eckroade's Written Testimony Before the Subcommittee on Financial and Contracting Oversight Committee on Homeland Security and Governmental Affairs (March 11, 2014) Principal Deputy Chief William A. Eckroade's Written Testimony Before the Subcommittee on Financial and Contracting Oversight Committee on Homeland

  6. William Fowler and Elements in the Stars

    Office of Scientific and Technical Information (OSTI)

    ... Integrated Flux Distributions in Neutron Capture in Stars, DOE Technical Report, September 23, 1965 Helium (3) Rich Solar Flares, DOE Technical Report, May 3, 1977 Top Additional ...

  7. 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.

  8. QER- Comment of William Smith III

    Broader source: Energy.gov [DOE]

    ://www.rmi.org/Knowledge-Center/Library/E05-14_NuclearPowerEconomics.... If you have not yet done so, I strongly urge you to contact the Rocky Mountain Institute and contract with them for their advice in consulting on the Quadrennial Energy Review. Sincerely, William Wharton Smith III

  9. 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.

  10. February 8, 2014: Prof. William C. Jones, Princeton University: Uncovering

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

    our Cosmic Origins: What We Know, What We Can Know, and What Limits We May Face. | Princeton Plasma Physics Lab February 8, 2014, 9:30am to 11:00am Science On Saturday MBG Auditorium February 8, 2014: Prof. William C. Jones, Princeton University: Uncovering our Cosmic Origins: What We Know, What We Can Know, and What Limits We May Face. Professor William Jones, Assistant Professor of Physics Princeton University, Department of Physics Presentation: PDF icon Presentation Abstract: PDF icon 05

  11. KST Coatings, A Business Unit of The Sherwin-Williams Company...

    Open Energy Info (EERE)

    KST Coatings, A Business Unit of The Sherwin-Williams Company Jump to: navigation, search Name: KST Coatings, A Business Unit of The Sherwin-Williams Company Address: 101Prospect...

  12. 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)

  13. Baseline and Target Values for PV Forecasts: Toward Improved...

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

  14. Comprehensive Solutions for Integration of Solar Resources into...

    Broader source: Energy.gov (indexed) [DOE]

    tool by incorporating accurate forecasting of solar generation, and then integrate ... and hence the costs of system integration of solar generation into the bulk power system. ...

  15. Watt-Sun: A Multi-Scale, Multi-Model, Machine-Learning Solar Forecasting

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

    Technology | Department of Energy Watt-Sun: A Multi-Scale, Multi-Model, Machine-Learning Solar Forecasting Technology Watt-Sun: A Multi-Scale, Multi-Model, Machine-Learning Solar Forecasting Technology IBM logo.png As part of this project, new solar forecasting technology will be developed that leverages big data processing, deep machine learning, and cloud modeling integrated in a universal platform with an open architecture. Similar to the Watson computer system, this proposed technology

  16. 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.

  17. The forecast calls for flu

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

    Science on the Hill: The forecast calls for flu Using mathematics, computer programs, ... We're getting close. Using mathematics, computer programs, statistics and information ...

  18. 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:...

  19. 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.

  20. Best Practices Case Study: Tommy Williams Homes -Gainesville, FL

    SciTech Connect (OSTI)

    none,

    2011-04-01

    Case study of Tommy Williams Homes who has continued to outsell the competition with sales increasing despite the recession thanks to a systems-engineering approach developed with DOE’s Building America that yields high energy efficiency, comfort, and indoor air quality. The company offers to pay buyers’ energy bills for the first year.

  1. NREL: Transmission Grid Integration - Issues Affecting Renewable...

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

    Variability of renewable energy sources Integration costs Frequency response Emissions System balancing Energy storage Transmission Solar and wind forecasting High-penetration ...

  2. 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.

  3. Upcoming Funding Opportunity for Wind Forecasting Improvement...

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

    Wind Forecasting Improvement Project in Complex Terrain Upcoming Funding Opportunity for Wind Forecasting Improvement Project in Complex Terrain February 12, 2014 - 10:47am ...

  4. 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:...

  5. Project Profile: Forecasting and Influencing Technological Progress...

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

    Soft Costs Project Profile: Forecasting and Influencing Technological Progress in Solar Energy Project Profile: Forecasting and Influencing Technological Progress in Solar ...

  6. National Oceanic and Atmospheric Administration Provides Forecasting...

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

    ... will share their expertise with CLASIC and CHAPS forecasters and project leaders as they consult on the forecast that will determine the day's operations plan. -- Storm Prediction ...

  7. 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.

  8. 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.

  9. Mr. William E. Mott, Acting Director Environmental Control Technology Division

    Office of Legacy Management (LM)

    7, I979 Mr. William E. Mott, Acting Director Environmental Control Technology Division Department of Energy Washington, D. C. 2Q545 Dear Mr. Mott: In response to your March 13, 1979 inquiry soliciting additional information regarding facilities involved in the feed materials program of MED/AEC, the following supplementary information is provided with respect to the Hood Building located at 155 Massachusetts Avenue, Cambridge, Massachusetts. The facility known as the Hood Building was built about

  10. Designation Survey - Palmerton, Pa. Ore Storage Site William Bibb

    Office of Legacy Management (LM)

    Designation Survey - Palmerton, Pa. Ore Storage Site William Bibb Oak Ridge Operations Office Based on the information furnished in Aerospace's Review of the.subject site (Attachment 1) and the ORKL/RASA (Attachment 2), it Is requested that designation survey of the Palmerton Ore Storage Pennsylvania. The survey should be detailed to and subsurface data to make up for the lack of the previous AEC surveys and in keeping with ORNL/RASA group should furnish a draft survey approval prior to

  11. Microsoft PowerPoint - Williams_Profilers.ppt

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

    0-MHz Profiler Rain Gauges Joss Waldvogel Disdrometers 2835-MHz Profiler Status of Profiler and Surface Data Sets for TWPICE Christopher.R.Williams@noaa.gov - University of Colorado at Boulder and NOAA Earth Science Research Laboratory Funding is from the NASA TRMM & GPM Programs through the former NOAA Aeronomy Laboratory and from the Australian Bureau of Meteorology Research Centre (BMRC) Approximately 8 km between ARM and Profiler sites The profiler and surface observations deployed at

  12. 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

  13. 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. Acquisition-Forecast-2016-07-20.xlsx (72.85 KB) More Documents & Publications Small Business Program Manager Directory EA-1900: Notice of Availability of a Draft Environmental Assessment Assessment Report: OAS-V-15-01

  14. Little Boy weaponeer William "Deak" Parsons, wartime Los Alamos

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

    division leader, focus of next 70th anniversary lecture 70th anniversary lecture Little Boy weaponeer William "Deak" Parsons, wartime Los Alamos division leader, focus of next 70th anniversary lecture Former Laboratory historian Roger Meade to present lecture. August 8, 2013 William S. "Deak" Parsons William S. "Deak" Parsons Contact Steve Sandoval Communications Office (505) 665-9206 Email Josh Dolin Communications Office (505) 665-4803 Email Meade said Los

  15. Buildng America Whole-House Solutions for New Homes: William Ryan Homes,

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

    Tampa, Florida | Department of Energy Buildng America Whole-House Solutions for New Homes: William Ryan Homes, Tampa, Florida Buildng America Whole-House Solutions for New Homes: William Ryan Homes, Tampa, Florida Case study of William Ryan Homes, who worked with Building America research partner CARB to design HERS-65 homes with energy-efficient heat pumps and programmable thermostats with humidity controls, foam-filled concrete block walls, draining house wrap, and airsealed kneewalls.

  16. Building America Whole-House Solutions for New Homes: Tommy Williams...

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

    of 2.7 ACH50. PDF icon Tommy Williams Homes: Longleaf Village & Belmont - Gainesville, FL More Documents & Publications Building America Efficient Solutions for New Homes Case ...

  17. Modeling-Computer Simulations At U.S. West Region (Williams ...

    Open Energy Info (EERE)

    navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Modeling-Computer Simulations At U.S. West Region (Williams & Deangelo, 2008) Exploration Activity...

  18. Building America Whole-House Solutions for New Homes: Tommy Williams Homes,

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

    Gainesville, Florida | Department of Energy Tommy Williams Homes, Gainesville, Florida Building America Whole-House Solutions for New Homes: Tommy Williams Homes, Gainesville, Florida Case study of Tommy Williams Homes who partnered with Building America to build HERS-58 homes with foam gaskets at sill and top plates, fresh air intakes, SEER 16/HSPF 9.5 heat pumps, and tight air sealing of 2.7 ACH50. Tommy Williams Homes: Longleaf Village & Belmont - Gainesville, FL (671.55 KB) More

  19. 10 CFR 850, Request for Information- Docket Number: HS-RM-10-CBDPP- William R. Kleem

    Broader source: Energy.gov [DOE]

    Commenter: William R. Kleem 10 CFR 850 - Request for Information Docket Number: HS-RM-10-CBDPP Comment Close Date: 2/22/2011

  20. VERIFICATION SURVEY OF THE BAKER AND WILLIAMS WAREHOUSES

    Office of Legacy Management (LM)

    ~ *-,-' .r_~, VERIFICATION SURVEY OF THE BAKER AND WILLIAMS WAREHOUSES BUILDING 513-519 NEW YORK, NEW YORK Prepared by W. C. Adams Environmental Survey and Site Assessment Program Energy/Environment Systems Division Oak Ridge Institute for Science and Education Oak Ridge, Tennessee 37831-0117 Prepared for the Office of Environmental Restoration U.S. Department of Energy FINAL REPORT JUNE 1994 This report is based on work performed under contract number DE-AC05-760R00033 with the U.S. Department

  1. Mr. William R. Augustine Deputy Chief Programs Management Division

    Office of Legacy Management (LM)

    h :.:, \ i 5 , Department of Energy Washington, DC 20585 t 7-c I-..._ .' , Mr. William R. Augustine Deputy Chief Programs Management Division U.S. Army Corps of Engineers Department of the Army Washington. D.C. 203 14- 1000 Dear Mr. Augustine: I am writing to you as a follow-up to discussions our staffs have had regarding two former Department of the Army facilities in the Formerly Used Defense Sites (FUDS) program where the former Atomic Energy Commission (AEC) also conducted activities. These

  2. 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 Wind Forecast Improvement Project Southern ...

  3. 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

  4. W&M, JLab Host International Neutrino Workshop (William & Mary News &

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

    Events) | Jefferson Lab W&M, JLab Host International Neutrino Workshop (William & Mary News & Events) External Link: http://www.wm.edu/news/stories/2012/william--mary-hosts-international-neutrino-w... By jlab_admin on Thu, 2012-07-19

  5. The Value of Wind Power Forecasting

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

    ... day-ahead wind generation forecasts yields an average of 195M savings in annual operating costs. Figure 6 shows how operating cost savings vary with improvements in forecasting. ...

  6. 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. ...

  7. Western Wind and Solar Integration Study: Executive Summary,...

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

    ... benefit of integrating wind and solar forecasting into grid operations? * How can hydro ... different interstate transmission build-outs and in- cluded these costs in the scenarios. ...

  8. UPF Forecast | Y-12 National Security Complex

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

    Subcontracting / Subcontracting Forecasts / UPF Forecast UPF Forecast UPF Procurement provides the following forecast of subcontracting opportunities. Keep in mind that these requirements may be revised or cancelled, depending on program budget funding or departmental needs. If you have questions or would like to express an interest in any of the opportunities listed below, contact UPF Procurement. Descriptiona Methodb NAICS Est. Dollar Range RFP release/ Award datec Buyer/ Phone Commodities

  9. 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

  10. Recent Trends in Variable Generation Forecasting and Its Value to the Power System

    SciTech Connect (OSTI)

    Orwig, Kirsten D.; Ahlstrom, Mark L.; Banunarayanan, Venkat; Sharp, Justin; Wilczak, James M.; Freedman, Jeffrey; Haupt, Sue Ellen; Cline, Joel; Bartholomy, Obadiah; Hamann, Hendrik F.; Hodge, Bri-Mathias; Finley, Catherine; Nakafuji, Dora; Peterson, Jack L.; Maggio, David; Marquis, Melinda

    2014-12-23

    We report that the rapid deployment of wind and solar energy generation systems has resulted in a need to better understand, predict, and manage variable generation. The uncertainty around wind and solar power forecasts is still viewed by the power industry as being quite high, and many barriers to forecast adoption by power system operators still remain. In response, the U.S. Department of Energy has sponsored, in partnership with the National Oceanic and Atmospheric Administration, public, private, and academic organizations, two projects to advance wind and solar power forecasts. Additionally, several utilities and grid operators have recognized the value of adopting variable generation forecasting and have taken great strides to enhance their usage of forecasting. In parallel, power system markets and operations are evolving to integrate greater amounts of variable generation. This paper will discuss the recent trends in wind and solar power forecasting technologies in the U.S., the role of forecasting in an evolving power system framework, and the benefits to intended forecast users.

  11. Recent Trends in Variable Generation Forecasting and Its Value to the Power System

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

    Orwig, Kirsten D.; Ahlstrom, Mark L.; Banunarayanan, Venkat; Sharp, Justin; Wilczak, James M.; Freedman, Jeffrey; Haupt, Sue Ellen; Cline, Joel; Bartholomy, Obadiah; Hamann, Hendrik F.; et al

    2014-12-23

    We report that the rapid deployment of wind and solar energy generation systems has resulted in a need to better understand, predict, and manage variable generation. The uncertainty around wind and solar power forecasts is still viewed by the power industry as being quite high, and many barriers to forecast adoption by power system operators still remain. In response, the U.S. Department of Energy has sponsored, in partnership with the National Oceanic and Atmospheric Administration, public, private, and academic organizations, two projects to advance wind and solar power forecasts. Additionally, several utilities and grid operators have recognized the value ofmore » adopting variable generation forecasting and have taken great strides to enhance their usage of forecasting. In parallel, power system markets and operations are evolving to integrate greater amounts of variable generation. This paper will discuss the recent trends in wind and solar power forecasting technologies in the U.S., the role of forecasting in an evolving power system framework, and the benefits to intended forecast users.« less

  12. Forecasting Wind and Solar Generation: Improving System Operations, Greening the Grid

    SciTech Connect (OSTI)

    Tian; Tian; Chernyakhovskiy, Ilya

    2016-01-01

    This document discusses improving system operations with forecasting and solar generation. By integrating variable renewable energy (VRE) forecasts into system operations, power system operators can anticipate up- and down-ramps in VRE generation in order to cost-effectively balance load and generation in intra-day and day-ahead scheduling. This leads to reduced fuel costs, improved system reliability, and maximum use of renewable resources.

  13. ALCF Future Systems Tim Williams, Argonne Leadership Computing Facility

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

    Future Systems Tim Williams, Argonne Leadership Computing Facility DOE Exascale Requirements Review: High Energy Physics June 11, 2015 Production Systems (ALCF-2) 2 Mira - IBM Blue Gene/Q ¥ 49,152 nodes ¡ PowerPC A2 cpu - 16 cores, 4 HW threads/core ¡ 16 GB RAM ¥ Aggregate ¡ 768 TB RAM, 768K cores ¡ Peak 10 PetaFLOPS ¥ 5D torus interconnect Cooley - Viz/Analysis cluster ¥ 126 nodes: ¡ Two 2.4 GHz Intel Haswell 6-core - 384 GB RAM ¡ NVIDIA Tesla K80 (two

  14. Plant improvements extend life of McWilliams Station

    SciTech Connect (OSTI)

    Meyer, R.; Balsbaugh, R.; Korinek, K.

    1995-12-31

    A combined-cycle conversion project at Alabama Electric Cooperative (AEC) will extend the life of its gas- and coal-fired McWilliams Station. The conversion will allow the plant to generate power for the next 30 years and boost its system intermediate and peaking capacity. Station capacity will increase from 42 MW to 151 MW (net), and the heat rate will improve from 15,000 to 9,000 Btu/kW-hr (HHV). Thanks to AEC`s preventive maintenance program, overhauls to the equipment remaining in service were unnecessary. Except for slight modifications, most systems will remain as they have for the last 40 years. This paper will describe the plant`s original construction and the changes made to sustain it.

  15. Grid Integration

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

    ... Named PRESCIENT, the software produces probabilistic forecasts automatically from deterministic historical forecasts for load, solar, andor wind power production and their ...

  16. Supply Forecast and Analysis (SFA)

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

    Matthew Langholtz Science Team Leader Oak Ridge National Laboratory DOE Bioenergy Technologies Office (BETO) 2015 Project Peer Review Supply Forecast and Analysis (SFA) 2 | Bioenergy Technologies Office Goal Statement * Provide timely and credible estimates of feedstock supplies and prices to support - the development of a bioeconomy; feedstock demand analysis of EISA, RFS2, and RPS mandates - the data and analysis of other projects in Analysis and Sustainability, Feedstock Supply and Logistics,

  17. An Optimized Autoregressive Forecast Error Generator for Wind and Load Uncertainty Study

    SciTech Connect (OSTI)

    De Mello, Phillip; Lu, Ning; Makarov, Yuri V.

    2011-01-17

    This paper presents a first-order autoregressive algorithm to generate real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast errors. The methodology aims at producing random wind and load forecast time series reflecting the autocorrelation and cross-correlation of historical forecast data sets. Five statistical characteristics are considered: the means, standard deviations, autocorrelations, and cross-correlations. A stochastic optimization routine is developed to minimize the differences between the statistical characteristics of the generated time series and the targeted ones. An optimal set of parameters are obtained and used to produce the RT, HA, and DA forecasts in due order of succession. This method, although implemented as the first-order regressive random forecast error generator, can be extended to higher-order. Results show that the methodology produces random series with desired statistics derived from real data sets provided by the California Independent System Operator (CAISO). The wind and load forecast error generator is currently used in wind integration studies to generate wind and load inputs for stochastic planning processes. Our future studies will focus on reflecting the diurnal and seasonal differences of the wind and load statistics and implementing them in the random forecast generator.

  18. 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

  19. Why Did the Electron Cross the Solar Cell? William Tisdale Knows...

    Office of Science (SC) Website

    Why Did the Electron Cross the Solar Cell? William Tisdale Knows News News Home Featured ... Contact Information Office of Science U.S. Department of Energy 1000 Independence Ave., SW ...

  20. Roy Williams and others ? keys to Y-12s success Or: People...

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

    in The Oak Ridger) Gordon Fee sent me an e-mail on December 23, 2009, noting that Roy Williams had just died. He went on to say that he sure hoped the history of Y-12 would include...

  1. Best Practices Case Study: William Ryan House - Tampa Division, Tampa, FL

    SciTech Connect (OSTI)

    none,

    2011-04-01

    Case study of William Ryan Homes, who cut energy use to achieve HERS scores of 65 to 70 on nine floor plans that will be featured in 277 homes in central Florida.

  2. FIA-12-0049- In the Matter of William B. Ray

    Broader source: Energy.gov [DOE]

    On October 1, 2012, OHA denied an Appeal filed by William B. Ray under the Freedom of Information and Privacy Act.  Mr. Ray was appealing from a determination issued by the DOE’s Oak Ridge Office ...

  3. Redelegation/Designation Order No. 00-022.02A to William C. Gibson...

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

    No. 00-022.02A to William C. Gibson, Jr as Head of Contracting Activity (HCA) for the Strategic Petroleum Reserve Project Management Office by johnsonmd Functional areas:...

  4. Wind Power Forecasting Error Frequency Analyses for Operational Power System Studies: Preprint

    SciTech Connect (OSTI)

    Florita, A.; Hodge, B. M.; Milligan, M.

    2012-08-01

    The examination of wind power forecasting errors is crucial for optimal unit commitment and economic dispatch of power systems with significant wind power penetrations. This scheduling process includes both renewable and nonrenewable generators, and the incorporation of wind power forecasts will become increasingly important as wind fleets constitute a larger portion of generation portfolios. This research considers the Western Wind and Solar Integration Study database of wind power forecasts and numerical actualizations. This database comprises more than 30,000 locations spread over the western United States, with a total wind power capacity of 960 GW. Error analyses for individual sites and for specific balancing areas are performed using the database, quantifying the fit to theoretical distributions through goodness-of-fit metrics. Insights into wind-power forecasting error distributions are established for various levels of temporal and spatial resolution, contrasts made among the frequency distribution alternatives, and recommendations put forth for harnessing the results. Empirical data are used to produce more realistic site-level forecasts than previously employed, such that higher resolution operational studies are possible. This research feeds into a larger work of renewable integration through the links wind power forecasting has with various operational issues, such as stochastic unit commitment and flexible reserve level determination.

  5. L3:VUQ.VVDA.P2-2.03 William Rider SNL

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

    3 William Rider SNL Completed: 3/28/11 CASL-U-2011-0060-000 1 SAND2010-234P Unlimited Release December 2010 Verification, Validation and Uncertainty Quantification Workflow in CASL William J. Rider Computational Shock and MultiPhysics Department James R. Kamm and V. Gregory Weirs Optimization and Uncertainty Quantification Department Sandia National Laboratories P.O. Box 5800 Albuquerque, New Mexico 87185 Dan G. Cacui Department of Nuclear Engineering North Carolina State University Raleigh, NC

  6. 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

  7. LED Lighting Forecast | Department of Energy

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

    Publications » Market Studies » LED Lighting Forecast LED Lighting Forecast 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. With declining costs and improving performance, LED products have been seeing increased adoption for general illumination applications. This is a positive development in terms of energy consumption, as LEDs use significantly

  8. NREL: Resource Assessment and Forecasting Home Page

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

    are used to plan and develop renewable energy technologies and support climate change research. Learn more about NREL's resource assessment and forecasting research:...

  9. Funding Opportunity Announcement for Wind Forecasting Improvement...

    Broader source: Energy.gov (indexed) [DOE]

    There is no cost to participate and all applicants are encouraged to attend. To join the ... Related Articles Upcoming Funding Opportunity for Wind Forecasting Improvement Project in ...

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

    Broader source: Energy.gov (indexed) [DOE]

    This module reviews metrics such as cost and schedule variance along with cost and schedule performance indices. In addition, this module will outline forecasting tools such as ...

  11. 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...

  12. 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...

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

    Broader source: Energy.gov (indexed) [DOE]

    and Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices 63wateruseoptimizationprojectanlgasper.ppt (7.72 MB) More ...

  14. Sensing, Measurement, and Forecasting | Grid Modernization | NREL

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

    Sensing, Measurement, and Forecasting NREL measures weather resources and power systems, forecasts renewable resources and grid conditions, and converts measurements into operational intelligence to support a modern grid. Photo of solar resource monitoring equipment Modernizing the grid involves assessing its health in real time, predicting its behavior and potential disruptions, and quickly responding to events-which requires understanding vital parameters throughout the electric

  15. 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

  16. 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.

  17. Toward a science of tumor forecasting for clinical oncology

    SciTech Connect (OSTI)

    Yankeelov, Thomas E.; Quaranta, Vito; Evans, Katherine J.; Rericha, Erin C.

    2015-03-15

    We propose that the quantitative cancer biology community makes a concerted effort to apply lessons from weather forecasting to develop an analogous methodology for predicting and evaluating tumor growth and treatment response. Currently, the time course of tumor response is not predicted; instead, response is only assessed post hoc by physical examination or imaging methods. This fundamental practice within clinical oncology limits optimization of a treatment regimen for 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. Furthermore, with a successful methodology toward tumor forecasting, it should be possible to integrate large tumor-specific datasets of varied types and effectively defeat one cancer patient at a time.

  18. Toward a science of tumor forecasting for clinical oncology

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

    Yankeelov, Thomas E.; Quaranta, Vito; Evans, Katherine J.; Rericha, Erin C.

    2015-03-15

    We propose that the quantitative cancer biology community makes a concerted effort to apply lessons from weather forecasting to develop an analogous methodology for predicting and evaluating tumor growth and treatment response. Currently, the time course of tumor response is not predicted; instead, response is only assessed post hoc by physical examination or imaging methods. This fundamental practice within clinical oncology limits optimization of a treatment regimen for 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 therapiesmore » 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. Furthermore, with a successful methodology toward tumor forecasting, it should be possible to integrate large tumor-specific datasets of varied types and effectively defeat one cancer patient at a time.« less

  19. 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 ...

  20. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

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

    Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen MJ ... Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen, ...

  1. 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 ...

  2. Systems Integration | Department of Energy

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

    Systems Integration Systems Integration Hawaii DREAMS of New Solar Technologies Hawaii DREAMS of New Solar Technologies Read more Plug and Play Solar PV for American Homes Plug and Play Solar PV for American Homes Read more Watt-Sun: A Multi-Scale, Multi-Modal, Machine-Learning Solar Forecasting Technology Watt-Sun: A Multi-Scale, Multi-Modal, Machine-Learning Solar Forecasting Technology Read more High PV Penetration with Energy Storage in Flagstaff, AZ High PV Penetration with Energy Storage

  3. 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.

  4. Integration of Novel Flux Coupling Motor and Current Source Inverter |

    Broader source: Energy.gov (indexed) [DOE]

    Operations | Department of Energy Clean Power Research logo.jpg This project will address the need for a more accurate approach to forecasting net utility load by taking into consideration the contribution of customer-sited PV energy generation. Tasks within the project are designed to integrate novel PV power forecasting techniques into the operational tools used by the California Independent System Operator (CAISO) to forecast customer load, and then validate their efficacy at enabling

  5. A parable of oil and water: Revisiting Prince William Sound, four years after

    SciTech Connect (OSTI)

    Keeble, J.

    1993-12-31

    On Good Friday, March 24, 1989, the Exxon oil tanker Valdez foundered on Bligh Reef, spilling 11 million gallons of crude oil into Alaska`s Prince William Sound. To Alaskans, especially fishing people, this was a shocking but not entirely unanticipated event, as there had been several near misses in the twelve years since the opening of oil shipping from Valdez, Alaska. This article revisits Prince William sound to evaluate both the lingering environmental effects and the socio-economic effects of the spill and the huge monetary settlement from the spills.

  6. William A. Lokke, 1975 | U.S. DOE Office of Science (SC)

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

    William A. Lokke, 1975 The Ernest Orlando Lawrence Award Lawrence Award Home Nomination & Selection Guidelines Award Laureates 2010's 2000's 1990's 1980's 1970's 1960's Ceremony The Life of Ernest Orlando Lawrence Contact Information The Ernest Orlando Lawrence Award U.S. Department of Energy SC-2/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-2411 E: Email Us 1970's William A. Lokke, 1975 Print Text Size: A A A FeedbackShare Page Weapons: For original and

  7. William Dorland, 2009 | U.S. DOE Office of Science (SC)

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

    William Dorland, 2009 The Ernest Orlando Lawrence Award Lawrence Award Home Nomination & Selection Guidelines Award Laureates 2010's 2000's 1990's 1980's 1970's 1960's Ceremony The Life of Ernest Orlando Lawrence Contact Information The Ernest Orlando Lawrence Award U.S. Department of Energy SC-2/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-2411 E: Email Us 2000's William Dorland, 2009 Print Text Size: A A A FeedbackShare Page Nuclear Technologies (Fission

  8. William H. Miller, 1985 | U.S. DOE Office of Science (SC)

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

    William H. Miller, 1985 The Ernest Orlando Lawrence Award Lawrence Award Home Nomination & Selection Guidelines Award Laureates 2010's 2000's 1990's 1980's 1970's 1960's Ceremony The Life of Ernest Orlando Lawrence Contact Information The Ernest Orlando Lawrence Award U.S. Department of Energy SC-2/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-2411 E: Email Us 1980's William H. Miller, 1985 Print Text Size: A A A FeedbackShare Page Chemistry: For the

  9. William J. Bair, 1970 | U.S. DOE Office of Science (SC)

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

    William J. Bair, 1970 The Ernest Orlando Lawrence Award Lawrence Award Home Nomination & Selection Guidelines Award Laureates 2010's 2000's 1990's 1980's 1970's 1960's Ceremony The Life of Ernest Orlando Lawrence Contact Information The Ernest Orlando Lawrence Award U.S. Department of Energy SC-2/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-2411 E: Email Us 1970's William J. Bair, 1970 Print Text Size: A A A FeedbackShare Page Life Sciences: For his

  10. OSTIblog Posts by Dr. William Watson | OSTI, US Dept of Energy Office of

    Office of Scientific and Technical Information (OSTI)

    Scientific and Technical Information Dr. William Watson Dr. William Watson's picture Physicist Mars Science Laboratory Curiosity - ChemCam 4265 Caltech.png Mars Science Laboratory Curiosity - ChemCam Read more about 4265 Science Communications Published on Sep 12, 2012 How do you run chemical tests at a geologic site millions of miles away from you to see what the rocks and soil are made of? Curiosity's new instrument ChemCam, developed at Los Alamos National Laboratory, is designed to

  11. Largest On-Campus Solar Facility Being Installed at William Paterson |

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

    Department of Energy Largest On-Campus Solar Facility Being Installed at William Paterson Largest On-Campus Solar Facility Being Installed at William Paterson March 29, 2010 - 10:57am Addthis Paul Lester Paul Lester Digital Content Specialist, Office of Public Affairs What does this project do? Solar arrays at parking lots and photovoltaic cells on the rooftops of campus buildings should provide about 15 to 20 percent of our energy needs on the campus. Cranes place solar panels on roofs and

  12. F. William Studier, 1977 | U.S. DOE Office of Science (SC)

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

    F. William Studier, 1977 The Ernest Orlando Lawrence Award Lawrence Award Home Nomination & Selection Guidelines Award Laureates 2010's 2000's 1990's 1980's 1970's 1960's Ceremony The Life of Ernest Orlando Lawrence Contact Information The Ernest Orlando Lawrence Award U.S. Department of Energy SC-2/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-2411 E: Email Us 1970's F. William Studier, 1977 Print Text Size: A A A FeedbackShare Page Life Sciences: For

  13. L3:VUQ.VVDA.P2-2.05 William Rider SNL

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

    5 William Rider SNL Completed: 7/31/11 CASL-U-2011-0192-000 Solution V erification f or G TRF---CFD 1 Solution V erification A pplied t o D rekar and Fuego Calculations using of Grid---to---Rod---Fretting (GTRF) William J. Rider Sandia National Laboratories, Albuquerque With c ontributions b y WEC (CASL AMA): R. L u, A . M andour, F uego/Sierra (CASL VRI/SNL): D . T urner, S . R odriguez, R . B ond, R . S ummers D rekar ( CASL, T HM/SNL): P . Weber (UNM student), T . S mith, J. Shadid, R. P

  14. 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...

  15. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

  16. 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.

  17. 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.

  18. Flood Forecasting in River System Using ANFIS

    SciTech Connect (OSTI)

    Ullah, Nazrin; Choudhury, P.

    2010-10-26

    The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in forecasting flood flow in a river system. The proposed technique combines the learning ability of neural network with the transparent linguistic representation of fuzzy system. The technique is applied to forecast discharge at a downstream station using flow information at various upstream stations. A total of three years data has been selected for the implementation of this model. ANFIS models with various input structures and membership functions are constructed, trained and tested to evaluate efficiency of the models. Statistical indices such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and Coefficient of Efficiency (CE) are used to evaluate performance of the ANFIS models in forecasting river flood. The values of the indices show that ANFIS model can accurately and reliably be used to forecast flood in a river system.

  19. 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....

  20. 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...

  1. 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.

  2. 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.

  3. Science on the Hill: The forecast calls for flu

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

    The forecast calls for flu 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 Beyond the familiar flu,

  4. Key Neutrino behavior observed at Daya Bay (The College of William and

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

    Mary) | Jefferson Lab Key Neutrino behavior observed at Daya Bay (The College of William and Mary) External Link: http://www.wm.edu/news/stories/2012/key-neutrino-behavior-observed-at-daya-bay-1... By jlab_admin on Thu, 2012-03-08

  5. Eastern Renewable Generation Integration Study Solar Dataset (Presentation)

    SciTech Connect (OSTI)

    Hummon, M.

    2014-04-01

    The National Renewable Energy Laboratory produced solar power production data for the Eastern Renewable Generation Integration Study (ERGIS) including "real time" 5-minute interval data, "four hour ahead forecast" 60-minute interval data, and "day-ahead forecast" 60-minute interval data for the year 2006. This presentation provides a brief overview of the three solar power datasets.

  6. 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.

  7. Advanced variable speed air-source integrated heat pump (AS-IHP...

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

    ... are difficult to forecast 10 Project Integration: The project is bas ed on a collaborative R&D Project Integration and Collaboration agreement (CRADA) with Nordyne (US HVAC OEM). ...

  8. Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

    SciTech Connect (OSTI)

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

    2015-11-10

    Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was 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 in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.

  9. Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

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

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

    2015-11-10

    Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based onmore » state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.« less

  10. Western Wind and Solar Integration Study | Grid Modernization...

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

    The Western Wind and Solar Integration Study Value of Wind Power Forecasting Impact of ... Phase 2 of WWSIS was initiated to determine the wear-and-tear costs and emissions impacts ...

  11. Wind Integration

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

    Wind Generation - ScheduledActual Balancing Reserves - Deployed Near Real-time Wind Animation Wind Projects under Review Growth Forecast Fact Sheets Working together to address...

  12. The Value of Improved Short-Term Wind Power Forecasting

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

    ... up-ramp reserves c down cost in MWh of down-ramp reserves R down MW range for ... power forecasting and the increased gas usage that comes with less-accurate forecasting. ...

  13. 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...

  14. 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 ...

  15. Regional four-dimensional variational data assimilation in a quasi-operational forecasting environment

    SciTech Connect (OSTI)

    Zupanski, M. )

    1993-08-01

    Four-dimensional variational data assimilation is applied to a regional forecast model as part of the development of a new data assimilation system at the National Meteorological Center (NMC). The assimilation employs an operational version of the NMC's new regional forecast model defined in eta vertical coordinates, and data used are operationally produced optimal interpolation (OI) analyses (using the first guess from the NMC's global spectral model), available every 3 h. Humidity and parameterized processes are not included in the adjoint model integration. The calculation of gradients by the adjoint model is approximate since the forecast model is used in its full-physics operational form. All experiments are over a 12-h assimilation period with subsequent 48-h forecast. Three different types of assimilation experiments are performed: (a) adjustment of initial conditions only (standard [open quotes]adjoint[close quotes] approach), (b) adjustment of a correction to the model equations only (variational continuous assimilation), and (c) simultaneous or sequential adjustment of both initial conditions and the correction term. Results indicate significantly better results when the correction term is included in the assimilation. It is shown, for a single case, that the new technique [experiment (c)] is able to produce a forecast better than the current conventional OI assimilation. It is very important to note that these results are obtained with an approximate gradient, calculated from a simplified adjoint model. Thus, it may be possible to perform an operational four-dimensional variational data assimilation of realistic forecast models, even before more complex adjoint models are developed. Also, the results suggest that it may be possible to reduce the large computational cost of assimilation by using only a few iterations of the minimization algorithm. This fast convergence is encouraging from the prospective of operational use. 37 refs., 10 figs., 1 tab.

  16. New Whole-House Solutions Case Study: Tommy Williams Homes Initial Performance of Two Zero Energy Homes, Gainesville, Florida

    SciTech Connect (OSTI)

    none,

    2011-11-01

    Tommy Williams Homes worked with PNNL, Florida HERO, Energy Smart Home Plans, and Florida Solar Energy Center to design and test two zero energy homes. Energy use was 30% lower in one home and 60% lower in the other.

  17. M E M O R A N D U M To: DOE Office of General Counsel From: William...

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

    Present for APGA were Dave Schryver and Dan Lapato and its General Counsel, William T. Miller of McCarter & English, LLP. Present for DOE were John Cymbalski and Dan Cohen. The ...

  18. 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.

  19. 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...

  20. 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.

  1. 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)

  2. 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

  3. 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.

  4. Essential Role in Modern Science William E. Johnston, ESnet Adviser and Senior Scientist

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

    Evolution of Research and Education Networks and their Essential Role in Modern Science William E. Johnston, ESnet Adviser and Senior Scientist Chin Guok, Evangelos Chaniotakis, Kevin Oberman, Eli Dart, Joe Metzger and Mike O'Conner, Core Engineering, Brian Tierney, Advanced Development, Mike Helm and Dhiva Muruganantham, Federated Trust Steve Cotter, Department Head wej@es.net, this talk is available at www.es.net Energy Sciences Network Lawrence Berkeley National Laboratory Networking for the

  5. TESTIMONY OF WILLIAM S. MAHARAY DEPUTY INSPECTOR GENERAL FOR AUDIT SERVICES

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

    TESTIMONY OF WILLIAM S. MAHARAY DEPUTY INSPECTOR GENERAL FOR AUDIT SERVICES U.S. DEPARTMENT OF ENERGY WASHINGTON D.C. BEFORE THE SUBCOMMITTEE ON GOVERNMENT MANAGEMENT, ORGANIZATION AND PROCUREMENT COMMITTEE ON OVERSIGHT AND GOVERNMENT REFORM U.S. HOUSE OF REPRESENTATIVES MARCH 20,2007 Mr. Chairman and members of the Subcommittee, I am pleased to be here at your request to testify on issues associated with the FY 2005 and 2006 Audits of the Department of Energy's Financial Statements. Over the

  6. OSTIblog Articles in the William Watson Topic | OSTI, US Dept of Energy

    Office of Scientific and Technical Information (OSTI)

    Office of Scientific and Technical Information William Watson Topic Plasmas - The Greatest Show on Earth by Kathy Chambers 24 Jun, 2013 in Products and Content Perhaps the most beautiful and eerie displays of light in our sky are a phenomenon known as the auroras. This natural glow of light in the sky in high latitude regions usually displays ribbons of colors from a fluorescent green to brilliant purple to a vivid crimson somewhat like an unexpected beautiful sunrise or sunset. Observers

  7. Speakers: Eric M. Lightner, U.S. Department of Energy William M. Gausman, Pepco Holdings, Inc.

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

    8: "Smart Grid: Impacts on Electric Power Supply and Demand" Speakers: Eric M. Lightner, U.S. Department of Energy William M. Gausman, Pepco Holdings, Inc. Christian Grant, Booz & Company, Inc. F. Michael Valocchi, IBM Global Business Services [Note: Recorders did not pick up introduction of panel (see biographies for details on the panelists) or introduction of session.] Eric Lightner: Well, good morning, everybody. My name is Eric Lightner. I work at the U.S. Department of

  8. Wind Forecast Improvement Project Southern Study Area Final Report |

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

    Department of Energy Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report.pdf (15.76 MB) More Documents & Publications QER - Comment of Edison Electric Institute (EEI) 1 QER - Comment of Canadian Hydropower Association QER - Comment of Edison Electric Institute (EEI) 2

  9. Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach

    SciTech Connect (OSTI)

    Brown, C. W.; Hood, Raleigh R.; Long, Wen; Jacobs, John M.; Ramers, D. L.; Wazniak, C.; Wiggert, J. D.; Wood, R.; Xu, J.

    2013-09-01

    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 concentrations of chlorophyll, nitrate, and dissolved oxygen, and the likelihood of encountering several noxious species, including harmful algal blooms and water-borne pathogens, for the purpose of monitoring the Bay's ecosystem. While the physical and biogeochemical variables are forecast mechanistically using the Regional Ocean Modeling System configured for the Chesapeake Bay, the species predictions are generated using a novel mechanistic empirical approach, whereby real-time output from the coupled physical biogeochemical model drives multivariate empirical habitat models of the target species. The predictions, in the form of digital images, are available via the World Wide Web to interested groups to guide recreational, management, and research activities. Though full validation of the integrated forecasts for all species is still a work in progress, we argue that the mechanisticempirical approach can be used to generate a wide variety of short-term ecological forecasts, and that it can be applied in any marine system where sufficient data exist to develop empirical habitat models. This paper provides an overview of this system, its predictions, and the approach taken.

  10. Enhanced Short-Term Wind Power Forecasting and Value to Grid Operations: Preprint

    SciTech Connect (OSTI)

    Orwig, K.; Clark, C.; Cline, J.; Benjamin, S.; Wilczak, J.; Marquis, M.; Finley, C.; Stern, A.; Freedman, J.

    2012-09-01

    The current state of the art of wind power forecasting in the 0- to 6-hour time frame has levels of uncertainty that are adding increased costs and risk on the U.S. electrical grid. It is widely recognized within the electrical grid community that improvements to these forecasts could greatly reduce the costs and risks associated with integrating higher penetrations of wind energy. The U.S. Department of Energy has sponsored a research campaign in partnership with the National Oceanic and Atmospheric Administration (NOAA) and private industry to foster improvements in wind power forecasting. The research campaign involves a three-pronged approach: 1) a 1-year field measurement campaign within two regions; 2) enhancement of NOAA's experimental 3-km High-Resolution Rapid Refresh (HRRR) model by assimilating the data from the field campaign; and 3) evaluation of the economic and reliability benefits of improved forecasts to grid operators. This paper and presentation provides an overview of the regions selected, instrumentation deployed, data quality and control, assimilation of data into HRRR, and preliminary results of HRRR performance analysis.