National Library of Energy BETA

Sample records for focus macroeconomic forecasting

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

    Reports and Publications (EIA)

    2010-01-01

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

  2. Methodology for the Assessment of the Macroeconomic Impacts of Stricter CAFE Standards - Addendum

    Reports and Publications (EIA)

    2002-01-01

    This assessment of the economic impacts of Corporate Average Fuel Economy (CAFÉ) standards marks the first time the Energy Information Administration has used the new direct linkage of the DRI-WEFA Macroeconomic Model to the National Energy Modeling System (NEMS) in a policy setting. This methodology assures an internally consistent solution between the energy market concepts forecast by NEMS and the aggregate economy as forecast by the DRI-WEFA Macroeconomic Model of the U.S. Economy.

  3. AEO2017 Preliminary Macroeconomic Results

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

    AEO2017 Preliminary Macroeconomic Results For Macroeconomic Working Group July 28, 2016 | Washington, DC By Vipin Arora, Elizabeth Sendich, and Russ Tarver Macroeconomic Analysis Team Economic growth in major trading partners slows over the projection period while the dollar gradually depreciates Macroeconomic Working Group, Washington DC, July 28, 2016 2 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 1989 1994 1999 2004 2009 2014 2019 2024 2029 2034 2039 real trade-weighted GDP of major trading

  4. Macroeconomic Activity Module - NEMS Documentation

    Reports and Publications (EIA)

    2016-01-01

    Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Macroeconomic Activity Module (MAM) used to develop the Annual Energy Outlook for 2016 (AEO2016). The report catalogues and describes the module assumptions, computations, methodology, parameter estimation techniques, and mainframe source code

  5. Macroeconomic Activity Module - NEMS Documentation

    Reports and Publications (EIA)

    2014-01-01

    Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Macroeconomic Activity Module (MAM) used to develop the Annual Energy Outlook for 2014 (AEO2014). The report catalogues and describes the module assumptions, computations, methodology, parameter estimation techniques, and mainframe source code

  6. Macroeconomic aspects of a petroleum boom: Ecuador, 1972-1980

    SciTech Connect (OSTI)

    de la Torre, A.P.

    1987-01-01

    This dissertation analyzes Ecuador's macroeconomic experience during the period of petroleum bonanza (1972-1980). The first chapter describes salient adjustments to a booming-sector phenomenon in the context of a formal, two-sector model of a small open economy, adapted to the stylized facts of the Ecuadorean case. The remainder of the dissertation is a historical case study that reviews actual macroeconomic developments and policies in Ecuador. The review of Ecuador's experience is organized as follows. Chapter 2 analyzes the adjustments in income, absorption, and the current account to the oil boom. Chapter 3 examines the monetary implications of the sudden influx of foreign exchange and the nature of the policy responses to it. Chapter 4 turns to the fiscal and credit areas, focusing on how the boom gave rise to, on the one hand, a significant increase in the State's allocative and developmental roles and, on the other, a relaxation of domestic resource-mobilization efforts. Chapter 5 emphasizes the distinction between exposed (or traded) and sheltered (or nontraded) sectors in order to clarify the nature of the linkages between the oil boom, the real exchange-rate appreciation, and the observed pattern of change in sectoral output and employment during the 1970s.

  7. Alternative Measures of Welfare in Macroeconomic Models

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

    ... To the extent that policy changes require forecasting, a CGE model may not be the ... it can incorporate the direct and indirect costs and benefits of different policies. ...

  8. Assumption to the Annual Energy Outlook 2014 - Macroeconomic...

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

    in this module. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy...

  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. Petroleum Data, Natural Gas Data, Coal Data, Macroeconomic Data, Petroleum Import Data

    SciTech Connect (OSTI)

    2009-01-18

    Supplemental tables to the Annual Energy Outlook (AEO) 2006 for petroleum, natural gas, coal, macroeconomic, and import data

  11. 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

  12. Energy Production and Trade: An Overview of Some Macroeconomic Issues

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

    Energy Production and Trade: An Overview of Some Macroeconomic Issues Vipin Arora November 2014 Independent Statistics & Analysis www.eia.gov U.S. Energy Information Administration Washington, DC 20585 This paper is released to encourage discussion and critical comment. The analysis and conclusions expressed here are those of the authors and not necessarily those of the U.S. Energy Information Administration. WORKING PAPER SERIES November 2014 Vipin Arora | U.S. Energy Information

  13. 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...

  14. 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 ...

  15. 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...

  16. 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. ...

  17. Bringing Clouds into Focus

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

    Bringing Clouds into Focus Bringing Clouds into Focus A New Global Climate Model May Reduce the Uncertainty of Climate Forecasting May 11, 2010 Contact: John Hules, JAHules@lbl.gov , +1 510 486 6008 Randall-fig4.png The large data sets generated by the GCRM require new analysis and visualization capabilities. This 3D plot of vorticity isosurfaces was developed using VisIt, a 3D visualization tool with a parallel distributed architecture, which is being extended to support the geodesic grid used

  18. Macroeconomic consequences of energy supply shocks in Ukraine. Discussion paper

    SciTech Connect (OSTI)

    Chu, H.Q.; Grais, W.

    1994-07-01

    In exploring the short-term macroeconomic effects of energy-supply shocks in Ukraine, the paper relies on the simplifying assumption that enterprises face economic regulation but not ownership uncertainty that would adversely affect their behavior. In a sense, it assumes that Ukraine's economy is already at the second stage of reform, when ownership and contract-enforcement questions are less of an issue. Under these assumptions and if real wages are protected, the analysis yields clear messages. The conclusion is that Ukraine must clarify ownership and contract-enforcement issues as rapidly as possible, liberalize nonenergy prices at a minimum, and begin adjusting domestic energy prices to reflect the opportunity cost of these resources.

  19. 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 ...

  20. Technical analysis in short-term uranium price forecasting

    SciTech Connect (OSTI)

    Schramm, D.S.

    1990-03-01

    As market participants anticipate the end of the current uranium price decline and its subsequent reversal, increased attention will be focused upon forecasting future price movements. Although uranium is economically similar to other mineral commodities, it is questionable whether methodologies used to forecast price movements of such commodities may be successfully applied to uranium.

  1. Evaluation of the St. Lucia geothermal resource: macroeconomic models

    SciTech Connect (OSTI)

    Burris, A.E.; Trocki, L.K.; Yeamans, M.K.; Kolstad, C.D.

    1984-08-01

    A macroeconometric model describing the St. Lucian economy was developed using 1970 to 1982 economic data. Results of macroeconometric forecasts for the period 1983 through 1985 show an increase in gross domestic product (GDP) for 1983 and 1984 with a decline in 1985. The rate of population growth is expected to exceed GDP growth so that a small decline in per capita GDP will occur. We forecast that garment exports will increase, providing needed employment and foreign exchange. To obtain a longer-term but more general outlook on St. Lucia's economy, and to evaluate the benefit of geothermal energy development, we applied a nonlinear programming model. The model maximizes discounted cumulative consumption.

  2. 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.

  3. Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System

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

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

  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. Central Wind Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities: Revised Edition

    SciTech Connect (OSTI)

    Rogers, J.; Porter, K.

    2011-03-01

    The report and accompanying table addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America. The first part of the table focuses on electric utilities and regional transmission organizations that have central wind power forecasting in place; the second part focuses on electric utilities and regional transmission organizations that plan to adopt central wind power forecasting in 2010. This is an update of the December 2009 report, NREL/SR-550-46763.

  8. In Focus

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

    In Focus Our Vision National User Facilities Research Areas In Focus Global Solutions ⇒ Navigate Section Our Vision National User Facilities Research Areas In Focus Global Solutions Amazing Science Images Take a look at some incredible images from the science we conduct at Berkeley Lab. 10 On the Way At Berkeley Lab, our goal is to bring science solutions to the world. Here are 10 entries in our 2015 "On the Way" list that are either starting up, moving along, or getting ready to

  9. Ion focusing

    DOE Patents [OSTI]

    Cooks, Robert Graham; Baird, Zane; Peng, Wen-Ping

    2015-11-10

    The invention generally relates to apparatuses for focusing ions at or above ambient pressure and methods of use thereof. In certain embodiments, the invention provides an apparatus for focusing ions that includes an electrode having a cavity, at least one inlet within the electrode configured to operatively couple with an ionization source, such that discharge generated by the ionization source is injected into the cavity of the electrode, and an outlet. The cavity in the electrode is shaped such that upon application of voltage to the electrode, ions within the cavity are focused and directed to the outlet, which is positioned such that a proximal end of the outlet receives the focused ions and a distal end of the outlet is open to ambient pressure.

  10. LANSCE Focus

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

    Focus Nuclear science observations and opportunities at the Los Alamos Neutron Science Center Colleagues, This special Focus issue highlights a set of nuclear physics capabilities at the Los Alamos Neutron Science Center (LANSCE) serving Los Alamos National Laboratory's national security mis- sion and the global scientific user community. With a total of 10 flight paths, LANSCE pro- vides the opportunity to perform experiments with low- to high-energy neutron sources and high-energy proton

  11. 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)

  12. 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 ...

  13. 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.

  14. 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 ...

  15. 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:...

  16. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect (OSTI)

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

    2014-11-13

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

  17. Global disease monitoring and forecasting with Wikipedia

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

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

    2014-11-13

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

  18. 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 ...

  19. 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:...

  20. 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 ...

  1. 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 ...

  2. Macroeconomic consequences of energy supply shocks in Ukraine. Studies of Economies in Transformation 12

    SciTech Connect (OSTI)

    Chu, H.Q.; Grais, W.

    1994-08-01

    Analyzes the macroeconomic implications of the economic shock the Ukraine has experienced in its transition to a market economy. This study analyzes the short-term macroeconomic implications of the energy crisis for Ukraine, the largest energy-dependent successor state of the former Soviet Union. The framework assumes, for the sake of analysis, that Ukraine`s economy is already at the second stage of reform, in which ownership and contract enforcement are an increasingly minor issue. The authors point out that the synergy between economic liberalization and adjustment to the shock allows a recovery of activity. They conclude that Ukraine should clarify as rapidly as possible ownership and contract enforcement issues, liberalize nonenergy prices, and adjust domestic energy prices to reflect the opportunity cost of using these resources elsewhere.

  3. 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.

  4. 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

  5. Acquisition Forecast Download | Department of Energy

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

    Acquisition Forecast Download Acquisition Forecast Download Click on the link to download a copy of the DOE HQ Acquisition Forecast. 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

  6. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01

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

  7. 1980 annual report to Congress: Volume three, Forecasts: Summary

    SciTech Connect (OSTI)

    Not Available

    1981-05-27

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

  8. Model developer`s appendix to the model documentation report: NEMS macroeconomic activity module

    SciTech Connect (OSTI)

    1994-07-15

    The NEMS Macroeconomic Activity Module (MAM) tested here was used to generate the Annual Energy Outlook 1994 (AEO94). MAM is a response surface model, not a structural model, composed of three submodules: the National Submodule, the Interindustry Submodule, and the Regional Submodule. Contents of this report are as follows: properties of the mathematical solution; NEMS MAM empirical basis; and scenario analysis. Scenario analysis covers: expectations for scenario analysis; historical world oil price scenario; AEO94 high world oil price scenario; AEO94 low world oil price scenario; and immediate increase world oil price scenario.

  9. 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 ...

  10. 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

  11. 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. ...

  12. 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. ...

  13. 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

  14. 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

  15. Model documentation report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System

    SciTech Connect (OSTI)

    Not Available

    1994-02-07

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Macroeconomic Activity Module (MAM) used to develop the Annual Energy Outlook for 1994 (AEO94). The report catalogues and describes the module assumptions, computations, methodology, parameter estimation techniques, and mainframe source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS MAM used for the AEO 1994 production runs for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models (Public Law 94-385, section 57.b.2). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

  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. The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations. The Southern Study Area, Final Report

    SciTech Connect (OSTI)

    Freedman, Jeffrey M.; Manobianco, John; Schroeder, John; Ancell, Brian; Brewster, Keith; Basu, Sukanta; Banunarayanan, Venkat; Hodge, Bri-Mathias; Flores, Isabel

    2014-04-30

    This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP) -- Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute - 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10 - 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems’ ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 - 3 hours.

  19. 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

  20. ARM - CARES - Tracer Forecast for CARES

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

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

  1. 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

  2. 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:...

  3. 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 ...

  4. 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 ...

  5. 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...

  6. 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...

  7. 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 ...

  8. Strong focus space charge

    DOE Patents [OSTI]

    Booth, Rex

    1981-01-01

    Strong focus space charge lens wherein a combination of current-carrying coils and charged electrodes form crossed magnetic and electric fields to focus charged particle beams.

  9. Strategic Focus Areas

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

    Strategic Focus Areas Lockheed Martin on behalf of Sandia National Laboratories will consider grant requests that best support the Corporation's strategic focus areas and reflect ...

  10. 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

  11. Study forecasts disappearance of conifers due to climate change

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

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

  12. 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, ...

  13. 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 ...

  14. Forecast of transportation energy demand through the year 2010

    SciTech Connect (OSTI)

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

    1991-04-01

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

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

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

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

  16. 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.

  17. HASQARD Focus Group

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

    17, 2012 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:05 PM on July 17, 2012 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Glen Clark, Robert Elkins, Scot Fitzgerald, Larry Markel, Cindy Taylor, Sam Vega, Rich Weiss and Eric Wyse. I. Huei Meznarich requested comments on the minutes from the June 12, 2012 meeting. No HASQARD Focus Group members present stated any

  18. HASQARD Focus Group

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

    8, 2013 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:05 PM on June 18, 2013 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Glen Clark, Scot Fitzgerald, Joan Kessner, Larry Markel, Karl Pool, Chris Sutton, Amanda Tuttle, Rich Weiss and Eric Wyse. I. Huei Meznarich requested comments on the minutes from the May 21, 2013 meeting. No HASQARD Focus Group members present

  19. Tritium Focus Group- INEL

    Broader source: Energy.gov [DOE]

    Presentation from the 34th Tritium Focus Group Meeting held in Idaho Falls, Idaho on September 23-25, 2014.

  20. Alternating phase focused linacs

    DOE Patents [OSTI]

    Swenson, Donald A. (Los Alamos, NM)

    1980-01-01

    A heavy particle linear accelerator employing rf fields for transverse and ongitudinal focusing as well as acceleration. Drift tube length and gap positions in a standing wave drift tube loaded structure are arranged so that particles are subject to acceleration and succession of focusing and defocusing forces which contain the beam without additional magnetic or electric focusing fields.

  1. 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...

  2. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  4. 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.

  5. 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.

  6. 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....

  7. 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...

  8. 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.

  9. 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,

  10. HASQARD Focus Group

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

    January 15, 2013 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:02 PM on January 15, 2013 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Glen Clark, Scot Fitzgerald, Larry Markel, Karl Pool, Dave St. John, Chris Sutton, Chris Thompson, Steve Trent, Amanda Tuttle and Eric Wyse. I. Huei Meznarich requested comments on the minutes from the December 18, 2012 meeting. One issue

  11. HASQARD Focus Group

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

    7, 2013 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:09 PM on December 17, 2013 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Taffy Almeida, Joe Archuleta, Jeff Cheadle, Glen Clark, Robert Elkins, Scot Fitzgerald, Joan Kessner, Karl Pool, Chris Sutton, Amanda Tuttle, Rich Weiss and Eric Wyse. I. Huei Meznarich asked if there were any comments on the minutes from the

  12. HASQARD Focus Group

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

    22, 2015 The meeting was called to order by Cliff Watkins, HASQARD Focus Group Secretary at 2:05 PM on October 22, 2015 in Conference Room 328 at 2420 Stevens. Those attending were: Jonathan Sanwald (Mission Support Alliance (MSA), Focus Group Chair), Cliff Watkins (Corporate Allocation Services, DOE-RL Support Contractor, Focus Group Secretary), Glen Clark (Washington River Protection Solution (WRPS)), Fred Dunhour (DOE-ORP), Joan Kessner (Washington Closure Hanford (WCH)), Karl Pool (Pacific

  13. HASQARD Focus Group

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

    6, 2016 The meeting was called to order by Jonathan Sanwald, HASQARD Focus Group Chair at 2:05 PM on January 26, 2016 in Conference Room 308 at 2420 Stevens. Those attending were: Jonathan Sanwald (Mission Support Alliance (MSA), Focus Group Chair), Cliff Watkins (Corporate Allocation Services, DOE-RL Support Contractor, Focus Group Secretary), Taffy Almeida (Pacific Northwest National Laboratory (PNNL)), Jeff Cheadle (DOE-ORP), Glen Clark (Washington River Protection Solution (WRPS)), Fred

  14. HASQARD Focus Group

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

    6 The meeting was called to order by Jonathan Sanwald, HASQARD Focus Group Chair at 2:10 PM on April 19, 2016 in Conference Room 308 at 2420 Stevens. Those attending were: Jonathan Sanwald (Mission Support Alliance (Mission Support Alliance (MSA)), Focus Group Chair), Cliff Watkins (Corporate Allocation Services, DOE-RL Support Contractor, Focus Group Secretary), Marcus Aranda (Wastren Advantage Inc. Wastren Hanford Laboratory (WHL)), Joe Archuleta (CH2M HILL Plateau Remediation Company

  15. Tritium Focus Group Meeting

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

    Meeting Information Tritium Focus Group Charter (pdf) Hotel Information Classified Session Information Los Alamos Restaurants (pdf) LANL Information Visiting Los Alamos Area Map ...

  16. FEMP Focus - June 2001

    SciTech Connect (OSTI)

    2001-06-01

    FEMP Focus is FEMP's bimonthly newsletter that promotes energy awareness, recognizes successes, and communicates information about saving energy and dollars to the federal community.

  17. HASQARD Focus Group

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

    6, 2012 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:04 PM on October 16, 2012 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Jeff Cheadle, Glen Clark, Robert Elkins, Larry Markel, Mary McCormick-Barger, Karl Pool, Noe'l Smith-Jackson, Chris Sutton, Steve Trent, Amanda Tuttle, Sam Vega, Rich Weiss and Eric Wyse. New personnel have joined the Focus Group since the last

  18. HASQARD Focus Group

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

    27, 2012 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:09 PM on November 27, 2012 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Glen Clark, Robert Elkins, Joan Kessner, Larry Markel, Mary McCormick-Barger, Steve Trent, and Rich Weiss. I. Huei Meznarich requested comments on the minutes from the October 16, 2012 meeting. No HASQARD Focus Group members present stated any

  19. HASQARD Focus Group

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

    0, 2013 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:05 PM on August 20, 2013 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Taffy Almeida, Glen Clark, Robert Elkins, Scot Fitzgerald, Joan Kessner, Steve Smith, Rich Weiss and Eric Wyse. I. Huei Meznarich asked if there were any comments on the minutes from the July 23, 2013 meeting. No Focus Group members stated they had

  20. HASQARD Focus Group

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

    5, 2014 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:10 PM on April 15, 2014 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Glen Clark, Robert Elkins, Scot Fitzgerald, Mary McCormick-Barger, Karl Pool, Noe'l Smith-Jackson, and Eric Wyse. I. Huei Meznarich asked if there were any comments on the minutes from the March 18, 2014 meeting. No Focus Group members stated they

  1. Focus on Energy Program

    Broader source: Energy.gov [DOE]

    Focus on Energy provides information, financial assistance, technical assistance and other services to residents, businesses, schools, institutions and local governments on energy efficiency and...

  2. 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.

  3. 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.

  4. Microfabricated particle focusing device

    DOE Patents [OSTI]

    Ravula, Surendra K.; Arrington, Christian L.; Sigman, Jennifer K.; Branch, Darren W.; Brener, Igal; Clem, Paul G.; James, Conrad D.; Hill, Martyn; Boltryk, Rosemary June

    2013-04-23

    A microfabricated particle focusing device comprises an acoustic portion to preconcentrate particles over large spatial dimensions into particle streams and a dielectrophoretic portion for finer particle focusing into single-file columns. The device can be used for high throughput assays for which it is necessary to isolate and investigate small bundles of particles and single particles.

  5. HASQARD Focus Group

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

    2 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:06 PM on June 12, 2012 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Jeff Cheadle, Glen Clark, Shannan Johnson, Joan Kessner, Larry Markel, Karl Pool, Steve Smith, Noe'l Smith-Jackson, Chris Sutton, Cindy Taylor, Chris Thomson, Amanda Tuttle, Sam Vega, Rick Warriner and Eric Wyse. I. Huei Meznarich requested comments on the

  6. HASQARD Focus Group

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

    1, 2012 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:10 PM on August 21, 2012 in an alternate Conference Room in 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Lynn Albin, Glen Clark, Robert Elkins, Scot Fitzgerald, Joan Kessner, Larry Markel, Steve Smith, Chris Sutton. Chris Thompson, Amanda Tuttle, and Rich Weiss. I. Because the meeting was scheduled to take place in Room 308 and a glitch in

  7. HASQARD Focus Group

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

    6, 2013 The beginning of the meeting was delayed due to an unannounced loss of the conference room scheduled for the meeting. After securing another meeting location, the meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:18 PM on April 16, 2013 in Conference Room 156 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Jeff Cheadle, Glen Clark, Joan Kessner, Larry Markel, Mary McCormick-Barger, Karl Pool,

  8. HASQARD Focus Group

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

    19, 2013 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:05 PM on November 19, 2013 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Taffy Almeida, Joe Archuleta, Mike Barnes, Jeff Cheadle, Glen Clark, Robert Elkins, Scot Fitzgerald, Joan Kessner, Mary McCormick-Barger, Noe'l Smith-Jackson, Chris Sutton, Amanda Tuttle, Rich Weiss and Eric Wyse. I. Huei Meznarich asked if

  9. HASQARD Focus Group

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

    January 28, 2014 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:04 PM on January 28, 2014 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Joe Archuleta, Glen Clark, Robert Elkins, Scot Fitzgerald, Joan Kessner, Mary McCormick-Barger, Karl Pool, Noe'l Smith-Jackson, Chris Sutton, Chris Thompson, Rich Weiss and Eric Wyse. I. Huei Meznarich asked if there were any comments on

  10. HASQARD Focus Group

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

    5, 2014 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:07 PM on February 25, 2014 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Lynn Albin, Taffy Almeida, Joe Archuleta, Glen Clark, Robert Elkins, Scot Fitzgerald, Joan Kessner, Mary McCormick-Barger, Karl Pool, Noe'l Smith-Jackson, Chris Sutton, Chris Thompson, and Eric Wyse. I. Huei Meznarich asked if there were any

  11. HASQARD Focus Group

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

    8, 2014 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:05 PM on March 18, 2014 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Joe Archuleta, Glen Clark, Robert Elkins, Scot Fitzgerald, Joan Kessner, Mary McCormick-Barger, Karl Pool, Noe'l Smith-Jackson, Rich Weiss, and Eric Wyse. I. Huei Meznarich asked if there were any comments on the minutes from the February 25, 2014

  12. HASQARD Focus Group

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

    0, 2014 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:05 PM on May 20, 2014 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Lynn Albin, Taffy Almeida, Joe Archuleta, Glen Clark, Robert Elkins, Scot Fitzgerald, Shannan Johnson, Joan Kessner, Mary McCormick-Barger, Craig Perkins, Karl Pool, Noe'l Smith-Jackson, Chris Sutton, Chris Thompson and Eric Wyse. I. Acknowledging the

  13. HASQARD Focus Group

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

    4 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:07 PM on June 12, 2014 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Joe Archuleta, Sara Champoux, Glen Clark, Jim Douglas, Robert Elkins, Scot Fitzgerald, Joan Kessner, Jan McCallum, Mary McCormick-Barger, Karl Pool, Noe'l Smith-Jackson, Rich Weiss and Eric Wyse. I. Acknowledging the presence of new and/or infrequent

  14. HASQARD Focus Group

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

    7, 2014 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:10 PM on June 17, 2014 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Focus Group Chair), Cliff Watkins (Focus Group Secretary), Robert Elkins, Shannan Johnson, Joan Kessner, Jan McCallum, Craig Perkins, Karl Pool, Chris Sutton and Rich Weiss. I. Because of the short time since the last meeting, Huei Meznarich stated that the minutes from the June 12, 2014 meeting have not yet

  15. Tritium Focus Group

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

    matters related to tritium. Contacts Mike Rogers (505) 665-2513 Email Chandra Savage Marsden (505) 664-0183 Email The Tritium Focus Group consists of participants from member...

  16. Focusing corner cube

    DOE Patents [OSTI]

    Monjes, J.A.

    1985-09-12

    This invention retortreflects and focuses a beam of light. The invention comprises a modified corner cube reflector wherein one reflective surface is planar, a second reflective surface is spherical, and the third reflective surface may be planar or convex cylindrical.

  17. HASQARD Focus Group

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

    been distributed to the Focus Group prior to the meeting. The comments that required editorial changes to the document were made in the working electronic version. b. At the June...

  18. HASQARD Focus Group

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

    Elkins, Mary McCormick-Barger, Noe'l Smith-Jackson, Chris Sutton, Amanda Tuttle, Rick ... Noe'l Smith-Jackson stated that the HASQARD document is the work of the Focus Group not ...

  19. HASQARD Focus Group

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

    6, 2010 The meeting was called to order by Dave Crawford, Focus Group Chairman at 2:03 PM on November 16, 2010 in Conference Room 208 at 2425 Stevens. Those attending were: Dave Crawford (Chair), Cliff Watkins (Secretary), Lynn Albin, Heather Anastos, Paula Ciszak, Glen Clark, Doug Duvon, Kathi Dunbar, Robert Elkins, Scot Fitzgerald, Joan Kessner, Larry Markel, Huei Meznarich, Steve Smith, Chris Sutton, Noe'l Smith-Jackson, Chris Thompson, Eric Wyse. New members to the Focus Group were

  20. Planar-focusing cathodes.

    SciTech Connect (OSTI)

    Lewellen, J. W.; Noonan, J.; Accelerator Systems Division

    2005-01-01

    Conventional {pi}-mode rf photoinjectors typically use magnetic solenoids for emittance compensation. This provides independent focusing strength but can complicate rf power feed placement, introduce asymmetries (due to coil crossovers), and greatly increase the cost of the photoinjector. Cathode-region focusing can also provide for a form of emittance compensation. Typically this method strongly couples focusing strength to the field gradient on the cathode, however, and usually requires altering the longitudinal position of the cathode to change the focusing. We propose a new method for achieving cathode-region variable-strength focusing for emittance compensation. The new method reduces the coupling to the gradient on the cathode and does not require a change in the longitudinal position of the cathode. Expected performance for an S-band system is similar to conventional solenoid-based designs. This paper presents the results of rf cavity and beam dynamics simulations of the new design. We have proposed a method for performing emittance compensation using a cathode-region focusing scheme. This technique allows the focusing strength to be adjusted somewhat independently of the on-axis field strength. Beam dynamics calculations indicate performance should be comparable to presently in-use emittance compensation schemes, with a simpler configuration and fewer possibilities for emittance degradation due to the focusing optics. There are several potential difficulties with this approach, including cathode material selection, cathode heating, and peak fields in the gun. We hope to begin experimenting with a cathode of this type in the near future, and several possibilities exist for reducing the peak gradients to more acceptable levels.

  1. Plutonium focus area

    SciTech Connect (OSTI)

    1996-08-01

    To ensure research and development programs focus on the most pressing environmental restoration and waste management problems at the U.S. Department of Energy (DOE), the Assistant Secretary for the Office of Environmental Management (EM) established a working group in August 1993 to implement a new approach to research and technology development. As part of this new approach, EM developed a management structure and principles that led to the creation of specific Focus Areas. These organizations were designed to focus the scientific and technical talent throughout DOE and the national scientific community on the major environmental restoration and waste management problems facing DOE. The Focus Area approach provides the framework for intersite cooperation and leveraging of resources on common problems. After the original establishment of five major Focus Areas within the Office of Technology Development (EM-50, now called the Office of Science and Technology), the Nuclear Materials Stabilization Task Group (EM-66) followed the structure already in place in EM-50 and chartered the Plutonium Focus Area (PFA). The following information outlines the scope and mission of the EM, EM-60, and EM-66 organizations as related to the PFA organizational structure.

  2. 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.

  3. 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

  4. 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. ...

  5. 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...

  6. 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 ...

  7. Decontamination & decommissioning focus area

    SciTech Connect (OSTI)

    1996-08-01

    In January 1994, the US Department of Energy Office of Environmental Management (DOE EM) formally introduced its new approach to managing DOE`s environmental research and technology development activities. The goal of the new approach is to conduct research and development in critical areas of interest to DOE, utilizing the best talent in the Department and in the national science community. To facilitate this solutions-oriented approach, the Office of Science and Technology (EM-50, formerly the Office of Technology Development) formed five Focus AReas to stimulate the required basic research, development, and demonstration efforts to seek new, innovative cleanup methods. In February 1995, EM-50 selected the DOE Morgantown Energy Technology Center (METC) to lead implementation of one of these Focus Areas: the Decontamination and Decommissioning (D & D) Focus Area.

  8. Sagittal focusing Laue monochromator

    DOE Patents [OSTI]

    Zhong; Zhong , Hanson; Jonathan , Hastings; Jerome , Kao; Chi-Chang , Lenhard; Anthony , Siddons; David Peter , Zhong; Hui

    2009-03-24

    An x-ray focusing device generally includes a slide pivotable about a pivot point defined at a forward end thereof, a rail unit fixed with respect to the pivotable slide, a forward crystal for focusing x-rays disposed at the forward end of the pivotable slide and a rearward crystal for focusing x-rays movably coupled to the pivotable slide and the fixed rail unit at a distance rearward from the forward crystal. The forward and rearward crystals define reciprocal angles of incidence with respect to the pivot point, wherein pivoting of the slide about the pivot point changes the incidence angles of the forward and rearward crystals while simultaneously changing the distance between the forward and rearward crystals.

  9. HASQARD Focus Group

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

    20, 2012 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:05 PM on March 20, 2012 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Chair), Cliff Watkins (Secretary), Jeff Cheadle, Glen Clark, Scot Fitzgerald, Larry Markel, Noe'l Smith-Jackson, Chris Sutton, Amanda Tuttle, Sam Vega, Rick Warriner and Eric Wyse. I. Huei Meznarich requested comments on the minutes from the February 21, 2012 meeting. No HASQARD Focus Group members present

  10. Final Report on California Regional Wind Energy Forecasting Project:Application of NARAC Wind Prediction System

    SciTech Connect (OSTI)

    Chin, H S

    2005-07-26

    direction, using its wind tunnel facility at the windmill farm at the Altamont Pass. The main objective of LLNL's involvement is to provide UC-Davis with improved wind forecasts to drive the parameterization scheme of turbine power curves developed from the wind tunnel facility. Another objective of LLNL's effort is to support the windmill farm operation with real-time wind forecasts for the effective energy management. The forecast skill in capturing the situation to meet the cut-in and cutout speed of given turbines would help reduce the operation cost in low and strong wind scenarios, respectively. The main focus of this report is to evaluate the wind forecast errors of LLNL's three-dimensional real-time weather forecast model at the location with the complex terrain. The assessment of weather forecast accuracy would help quantify the source of wind energy forecast errors from the atmospheric forecast model and/or wind-tunnel module for further improvement in the wind energy forecasting system.

  11. 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.

  12. 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...

  13. 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.

  14. 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)

  15. 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

  16. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    1998-07-01

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

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. Focused ion beam system

    DOE Patents [OSTI]

    Leung, K.; Gough, R.A.; Ji, Q.; Lee, Y.Y.

    1999-08-31

    A focused ion beam (FIB) system produces a final beam spot size down to 0.1 {mu}m or less and an ion beam output current on the order of microamps. The FIB system increases ion source brightness by properly configuring the first (plasma) and second (extraction) electrodes. The first electrode is configured to have a high aperture diameter to electrode thickness aspect ratio. Additional accelerator and focusing electrodes are used to produce the final beam. As few as five electrodes can be used, providing a very compact FIB system with a length down to only 20 mm. Multibeamlet arrangements with a single ion source can be produced to increase throughput. The FIB system can be used for nanolithography and doping applications for fabrication of semiconductor devices with minimum feature sizes of 0.1 m or less. 13 figs.

  2. Focused ion beam system

    DOE Patents [OSTI]

    Leung, Ka-Ngo; Gough, Richard A.; Ji, Qing; Lee, Yung-Hee Yvette

    1999-01-01

    A focused ion beam (FIB) system produces a final beam spot size down to 0.1 .mu.m or less and an ion beam output current on the order of microamps. The FIB system increases ion source brightness by properly configuring the first (plasma) and second (extraction) electrodes. The first electrode is configured to have a high aperture diameter to electrode thickness aspect ratio. Additional accelerator and focusing electrodes are used to produce the final beam. As few as five electrodes can be used, providing a very compact FIB system with a length down to only 20 mm. Multibeamlet arrangements with a single ion source can be produced to increase throughput. The FIB system can be used for nanolithography and doping applications for fabrication of semiconductor devices with minimum feature sizes of 0.1 .mu.m or less.

  3. NETL Focused Standards List

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

    1/6/14 Contact: Janet Lambert Reviewed: 3/5/14 Page 1 of 17 The National Energy Technology Laboratory (NETL) Focused Standards List is primarily derived from standard references contained in the requirements section of NETL's environment, safety, security, and health (ESS&H) and cyber security directives. All standards shall reference the most current edition/version of that standard. 1. DEPARTMENT OF ENERGY (DOE) AND OTHER GOVERNMENT STANDARDS AND REQUIREMENTS a. DOE Directives The

  4. HASQARD Focus Group

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

    8, 2011 The meeting was called to order by Dave Crawford, Focus Group Chairman at 2:08 PM on January 18, 2011 in Conference Room 208 at 2425 Stevens. Those attending were: Dave Crawford (Chair), Cliff Watkins (Secretary), Heather Anastos, Paula Ciszak, Jim Conca, Scott Conley, Glen Clark, Scott Conley, Jim Douglas, Scot Fitzgerald, Stewart Huggins, Jim Jewett, Joan Kessner, Larry Markel, Huei Meznarich, Karl Pool, Dave Shea, Steve Smith, Chris Sutton, Amanda Tuttle, Rich Weiss, Eric Wyse. Dave

  5. HASQARD Focus Group

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

    1 The meeting was called to order by Huei Meznarich who was acting for the absent Dave Crawford, Focus Group Chairman at 2:04 PM on April 19, 2011 in Conference Room 208 at 2425 Stevens. Those attending were: Huei Meznarich (Acting Chair), Cliff Watkins (Secretary), Taffy Almeida, Heather Anastos, Courtney Blanchard, Jeff Cheadle, Glen Clark, Kathie Dunbar, Robert Elkins, Scot Fitzgerald, Greg Holte, Joan Kessner, Noe'l Smith- Jackson, Chris Sutton, Cindy Taylor, Chris Thompson, Amanda Tuttle,

  6. HASQARD Focus Group

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

    7, 2011 The meeting was called to order by Dave Crawford, Focus Group Chairman at 2:03 PM on May 17, 2011 in Conference Room 208 at 2425 Stevens. Those attending were: Dave Crawford (Chair), Cliff Watkins (Secretary), Taffy Almeida, Courtney Blanchard, Jeff Cheadle, Glen Clark, Robert Elkins, Scot Fitzgerald, Al Hawkins, Greg Holte, Kris Kuhl-Klinger, Larry Markel, Huei Meznarich, Noe'l Smith-Jackson, Chris Sutton, Cindy Taylor, Chris Thompson, Amanda Tuttle, Eric Wyse. I. Dave Crawford

  7. HASQARD Focus Group

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

    8, 2011 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:04 PM on November 8, 2011 in Conference Room 126 at 2420 Stevens. Those attending were: Huei Meznarich (Chair), Cliff Watkins (Secretary), Lynn Albin, Heather Anastos, Courtney Blanchard, Jeff Cheadle, Scot Fitzgerald, Jim Jewett, Shannan Johnson, Kris Kuhl-Klinger, Joan Kessner, Larry Markel, Karl Pool, Noe'l Smith-Jackson, Steve Smith, Chris Sutton, Cindy Taylor, Chris Thompson, Amanda Tuttle and Eric

  8. HASQARD Focus Group

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

    7, 2012 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:04 PM on January 17, 2012 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Chair), Cliff Watkins (Secretary), Mike Barnes, Jeff Cheadle, Glen Clark, Scot Fitzgerald, Shannan Johnson, Joan Kessner, Larry Markel, Cindy Taylor, Chris Thompson, Amanda Tuttle, Sam Vega, Rich Weiss and Eric Wyse. I. Huei Meznarich requested comments on the minutes from the December 13, 2011 meeting.

  9. HASQARD Focus Group

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

    1, 2012 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:02 PM on February 21, 2012 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Chair), Cliff Watkins (Secretary), Lynn Albin, Taffy Almeida, Courtney Blanchard, Glen Clark, Scot Fitzgerald, Shannan Johnson, Kris Kuhl-Klinger, Larry Markel, Karl Pool, Steve Smith, Cindy Taylor, Amanda Tuttle, Sam Vega, Rick Warriner, Rich Weiss and Eric Wyse. I. Huei Meznarich requested comments on

  10. Strategic Focus Points

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

    Focus Points June 2011 1. Establish the human capital and organizational foundation to create a high-performing organization. 2. Implement a cyber risk-management and incident response program that ensures effective security of Federal and M&O networks, provides appropriate flexibility, and meets legal requirements and OMB expectations. 3. Improve IT Services (EITS) into a best-in-class provider from both a technical and business perspective. 4. Implement and institutionalize a reformed,

  11. Tritium Focus Group Meeting:

    Office of Environmental Management (EM)

    32 nd Tritium Focus Group Meeting: Tritium research activities in Safety and Tritium Applied Research (STAR) facility, Idaho National Laboratory Masashi Shimada Fusion Safety Program, Idaho National Laboratory April 25 th 2013, Germantown, MD STI #: INL/MIS-13-28975 Outlines 1. Motivation of tritium research activity in STAR facility 2. Unique capabilities in STAR facility 3. Research highlights from tritium retention in HFIR neutron- irradiated tungsten April 25th 2013 Germantown, MD STAR

  12. Subsurface contaminants focus area

    SciTech Connect (OSTI)

    1996-08-01

    The US Department of Enregy (DOE) Subsurface Contaminants Focus Area is developing technologies to address environmental problems associated with hazardous and radioactive contaminants in soil and groundwater that exist throughout the DOE complex, including radionuclides, heavy metals; and dense non-aqueous phase liquids (DNAPLs). More than 5,700 known DOE groundwater plumes have contaminated over 600 billion gallons of water and 200 million cubic meters of soil. Migration of these plumes threatens local and regional water sources, and in some cases has already adversely impacted off-site rsources. In addition, the Subsurface Contaminants Focus Area is responsible for supplying technologies for the remediation of numerous landfills at DOE facilities. These landfills are estimated to contain over 3 million cubic meters of radioactive and hazardous buried Technology developed within this specialty area will provide efective methods to contain contaminant plumes and new or alternative technologies for development of in situ technologies to minimize waste disposal costs and potential worker exposure by treating plumes in place. While addressing contaminant plumes emanating from DOE landfills, the Subsurface Contaminants Focus Area is also working to develop new or alternative technologies for the in situ stabilization, and nonintrusive characterization of these disposal sites.

  13. 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.

  14. NETL Focused Standards List

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

    6/12 Contact: Janet Lambert Reviewed: 10/4/12 Page 1 of 17 This Focused Standards List has been primarily derived from selected standard references contained in NETL issued directives. All standards shall reference the most current edition/ version of that standard. DOE and other Government Standards and Requirements DOE DIRECTIVES Note: The following DOE directives can be found at http://www.directives.doe.gov: DOE Policy 141.1, DOE Management of Cultural Resources DOE Order 142.1, Classified

  15. HASQARD Focus Group

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

    18, 2010 The meeting was called to order by Don Hart, Focus Group Chairman, at 2:00 PM on February 18, 2010 in Conference Room 199 at 2430 Stevens. Those attending were: Lynn Albin, Taffy Almeida, Heather Anastos, Glen Clark, Doug Duvon, Kathi Dunbar, Robert Elkins, Cindy English, Kris Kuhl-Klinger, Joan Kessner, Larry Markel, Huei Meznarich, Karl Pool, Steve Smith, Noe'l Smith-Jackson, Andrew Stevens, Chris Sutton, Chris Thompson, Wendy Thompson, Rich Weis, and Cliff Watkins. I. Because new

  16. HASQARD Focus Group

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

    0 The meeting was called to order by Dave Crawford, Focus Group Chairman at 2:10 PM on December 13, 2010 in Conference Room 199 at 2430 Stevens. Those attending were: Dave Crawford (Chair), Cliff Watkins (Secretary), Jeff Cheadle, Glen Clark, Robert Elkins, Scot Fitzgerald, Kris Kuhl-Klinger, Larry Markel, Huei Meznarich, Noe'l Smith-Jackson, Dave Shea, Chris Sutton, Cindy Taylor, Chris Thompson, Rich Weiss, Eric Wyse. I. Dave Crawford requested approval of the minutes from the November 16

  17. HASQARD Focus Group

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

    16, 2011 The meeting was called to order by Dave Crawford, HASQARD Focus Group Chairman at 2:07 PM on August 16, 2011 in Conference Room 208 at 2425 Stevens. Those attending were: (Chair), Cliff Watkins (Secretary), Lynn Albin, Heather Anastos, Jeff Cheadle, Kathi Dunbar, Robert Elkins, Scot Fitzgerald, Jim Jewett, Kris Kuhl-Klinger, Joan Kessner, Larry Markel, Huei Meznarich, Noe'l Smith-Jackson, Cindy Taylor, Amanda Tuttle, Rich Weiss and Eric Wyse. I. Dave Crawford requested comments on the

  18. HASQARD Focus Group

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

    4, 2011 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:04 PM on October 4, 2011 in Conference Room 208 at 2425 Stevens. Those attending were: Huei Meznarich (Chair), Cliff Watkins (Secretary), Lynn Albin, Heather Anastos, Jeff Cheadle, Glen Clark, Scot Fitzgerald, Shannan Johnson, Kris Kuhl-Klinger, Joan Kessner, Larry Markel, Karl Pool, Noe'l Smith-Jackson, Dave Shea, Cindy Taylor, Amanda Tuttle, Mary Ryan, Rich Weiss and Eric Wyse. I. Huei Meznarich requested

  19. HASQARD Focus Group

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

    1 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:04 PM on December 13, 2011 in Conference Room 126 at 2420 Stevens. Those attending were: Huei Meznarich (Chair), Cliff Watkins (Secretary), Lynn Albin, Heather Anastos, Jeff Cheadle, Glen Clark, Scot Fitzgerald, Shannan Johnson, Kris Kuhl-Klinger, Joan Kessner, Karl Pool, Dave St. John, Noe'l Smith-Jackson, Chris Sutton, Cindy Taylor, Amanda Tuttle, Rich Weiss and Eric Wyse. I. Huei Meznarich requested comments

  20. HASQARD Focus Group

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

    7, 2012 The meeting was called to order by Huei Meznarich, HASQARD Focus Group Chair at 2:06 PM on April 17, 2012 in Conference Room 308 at 2420 Stevens. Those attending were: Huei Meznarich (Chair), Cliff Watkins (Secretary), Lynn Albin, Taffy Almeida, Jeff Cheadle, Glen Clark, Scot Fitzgerald, Kris Kuhl-Klinger, Joan Kessner, Larry Markel, Noe'l Smith-Jackson, Cindy Taylor, Amanda Tuttle, Rich Weiss and Eric Wyse. I. Huei Meznarich requested comments on the minutes from the March 20, 2012

  1. Transverse field focused system

    DOE Patents [OSTI]

    Anderson, Oscar A.

    1986-01-01

    A transverse field focused (TFF) system for transport or acceleration of an intense sheet beam of negative ions in which a serial arrangement of a plurality of pairs of concentric cylindrical-arc electrodes is provided. Acceleration of the sheet beam can be achieved by progressively increasing the mean electrode voltage of successive electrode pairs. Because the beam is curved by the electrodes, the system can be designed to transport the beam through a maze passage which is baffled to prevent line of sight therethrough. Edge containment of the beam can be achieved by shaping the side edges of the electrodes to produce an electric force vector directed inwardly from the electrode edges.

  2. Dielectrophoretic columnar focusing device

    DOE Patents [OSTI]

    James, Conrad D. (Albuquerque, NM); Galambos, Paul C. (Albuquerque, NM); Derzon, Mark S. (Tijeras, NM)

    2010-05-11

    A dielectrophoretic columnar focusing device uses interdigitated microelectrodes to provide a spatially non-uniform electric field in a fluid that generates a dipole within particles in the fluid. The electric field causes the particles to either be attracted to or repelled from regions where the electric field gradient is large, depending on whether the particles are more or less polarizable than the fluid. The particles can thereby be forced into well defined stable paths along the interdigitated microelectrodes. The device can be used for flow cytometry, particle control, and other process applications, including cell counting or other types of particle counting, and for separations in material control.

  3. Forecasting hotspots using predictive visual analytics approach

    SciTech Connect (OSTI)

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

    2014-12-30

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

  4. 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.

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

    SciTech Connect (OSTI)

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

    2015-08-05

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

  6. Process Intensification - Chemical Sector Focus

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

    Process Intensification - Chemical Sector Focus 1 Technology Assessment 2 Contents 3 1. Introduction ..................................................................................................................................................................... 1 4 2. Technology Assessment and Potential ................................................................................................................. 5 5 2.1 Chemical Industry Focus

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  8. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

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

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

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

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

    transition from shallow to deep convection using a dual mass flux boundary layer scheme Roel Neggers European Centre for Medium-range Weather Forecasts Introduction " " % % &...

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

    Office of Scientific and Technical Information (OSTI)

    forecasts for solar-energy applications and 2) to provide vertical profiling capabilities for the study of dynamics (i.e., vertical velocity) and hydrometeors in winter storms. ...

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

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

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

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

    SciTech Connect (OSTI)

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

    2015-12-08

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

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

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

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

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

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

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

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

    Energy Savers [EERE]

    Through the Improving the Accuracy of Solar Forecasting Funding Opportunity, DOE is funding solar projects that are helping utilities, grid operators, solar power plant owners, and ...

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

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

    Data and Resources National Solar Radiation Database NREL resource assessment and forecasting research information is available from the following sources. Renewable Resource Data ...

  17. 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 ...

  18. A Review of Variable Generation Forecasting in the West: July...

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

    ... Cost Assignment - Only a few respondents partly or fully recover forecasting costs from variable generators. Many simply absorb the costs, possibly viewing them as relatively ...

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

  20. ANL Software Improves Wind Power Forecasting | Department of...

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

    ... The licensing arrangement helps to facilitate transfer of the statistical learning algorithms developed in the project to industry use. A leading forecast provider in the United ...

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

    Office of Energy Efficiency and Renewable Energy (EERE)

    A report for the FY 2007 GPRA methodology review, highlighting the views of an external expert peer review panel on DOE benefits forecasts.

  2. Selected papers on fuel forecasting and analysis

    SciTech Connect (OSTI)

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

    1983-05-01

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

  3. Focus Group | Department of Energy

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

    Outreach Forums » Focus Group and Work Group Activities » Focus Group Focus Group The Focus Group was formed in March 2007 to initiate dialogue and interface with labor unions, DOE Program Secretarial Offices, and stakeholders in areas of mutual interest and concern related to health, safety, security, and the environment. Meeting Documents Available for Download November 13, 2012 Work Group Leadership Meetings: Transition Elements This Focus Group Work Group telecom was held with the Work

  4. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

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

    2010-05-01

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

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

    SciTech Connect (OSTI)

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

    2012-07-01

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

  6. Focus Areas | Critical Materials Institute

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

    Focus Areas FA 1: Diversifying Supply FA 2: Developing Substitutes FA 3: Improving Reuse and Recycling FA 4: Crosscutting Research

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

    Open Energy Info (EERE)

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

  8. Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy

    SciTech Connect (OSTI)

    Parks, K.; Wan, Y. H.; Wiener, G.; Liu, Y.

    2011-10-01

    The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span three operating companies1, serving customers in eight states2, and three market structures3. The great majority of the wind energy is contracted through power purchase agreements (PPAs). The remainder is utility owned, Qualifying Facilities (QF), distributed resources (i.e., 'behind the meter'), or merchant entities within Xcel Energy's Balancing Authority footprints. Regardless of the contractual or ownership arrangements, the output of the wind energy is balanced by Xcel Energy's generation resources that include fossil, nuclear, and hydro based facilities that are owned or contracted via PPAs. These facilities are committed and dispatched or bid into day-ahead and real-time markets by Xcel Energy's Commercial Operations department. Wind energy complicates the short and long-term planning goals of least-cost, reliable operations. Due to the uncertainty of wind energy production, inherent suboptimal commitment and dispatch associated with imperfect wind forecasts drives up costs. For example, a gas combined cycle unit may be turned on, or committed, in anticipation of low winds. The reality is winds stayed high, forcing this unit and others to run, or be dispatched, to sub-optimal loading positions. In addition, commitment decisions are frequently irreversible due to minimum up and down time constraints. That is, a dispatcher lives with inefficient decisions made in prior periods. In general, uncertainty contributes to conservative operations - committing more units and keeping them on longer than may have been necessary for purposes of maintaining reliability. The downside is costs are

  9. Incorporating Forecast Uncertainty in Utility Control Center

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian

    2014-07-09

    Uncertainties in forecasting the output of intermittent resources such as wind and solar generation, as well as system loads are not adequately reflected in existing industry-grade tools used for transmission system management, generation commitment, dispatch and market operation. There are other sources of uncertainty such as uninstructed deviations of conventional generators from their dispatch set points, generator forced outages and failures to start up, load drops, losses of major transmission facilities and frequency variation. These uncertainties can cause deviations from the system balance, which sometimes require inefficient and costly last minute solutions in the near real-time timeframe. This Chapter considers sources of uncertainty and variability, overall system uncertainty model, a possible plan for transition from deterministic to probabilistic methods in planning and operations, and two examples of uncertainty-based fools for grid operations.This chapter is based on work conducted at the Pacific Northwest National Laboratory (PNNL)

  10. FOCUS

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

    (given the uncertainties we are likely to face in coming years, such as the evolving electricity market, changes in the electricity policy landscape and technology...

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

    SciTech Connect (OSTI)

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

    2011-12-06

    Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios

  12. 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.

  13. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema (OSTI)

    Gonzalez, Frank

    2010-01-08

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

  14. Focus Areas | Department of Energy

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

    Focus Areas Focus Areas Safety With this focus on cleanup completion and risk reducing results, safety still remains the utmost priority. EM will continue to maintain and demand the highest safety performance. All workers deserve to go home as healthy as they were when they came to the job in the morning. There is no schedule or milestone worth any injury to the work force. Project Management EM is increasing its concentration on project management to improve its overall performance toward

  15. HASQARD Focus Group - Hanford Site

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

    Contracting Wastren Advantage, Inc. HASQARD Focus Group Contracting ORP Contracts and Procurements RL Contracts and Procurements CH2M HILL Plateau Remediation Company Mission Support Alliance Washington Closure Hanford HPM Corporation (HPMC) Wastren Advantage, Inc. Analytical Services HASQARD Focus Group Bechtel National, Inc. Washington River Protection Solutions HASQARD Focus Group Email Email Page | Print Print Page | Text Increase Font Size Decrease Font Size HASQARD Document HASQARD

  16. Sector trends and driving forces of global energy use and greenhouse gas emissions: focus in industry and buildings

    SciTech Connect (OSTI)

    Price, Lynn; Worrell, Ernst; Khrushch, Marta

    1999-09-01

    Disaggregation of sectoral energy use and greenhouse gas emissions trends reveals striking differences between sectors and regions of the world. Understanding key driving forces in the energy end-use sectors provides insights for development of projections of future greenhouse gas emissions. This report examines global and regional historical trends in energy use and carbon emissions in the industrial, buildings, transport, and agriculture sectors, with a more detailed focus on industry and buildings. Activity and economic drivers as well as trends in energy and carbon intensity are evaluated. The authors show that macro-economic indicators, such as GDP, are insufficient for comprehending trends and driving forces at the sectoral level. These indicators need to be supplemented with sector-specific information for a more complete understanding of future energy use and greenhouse gas emissions.

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

    Office of Energy Efficiency and Renewable Energy (EERE)

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

  18. Wind Energy Technology Trends: Comparing and Contrasting Recent Cost and Performance Forecasts (Poster)

    SciTech Connect (OSTI)

    Lantz, E.; Hand, M.

    2010-05-01

    Poster depicts wind energy technology trends, comparing and contrasting recent cost and performance forecasts.

  19. Macroeconomic Activity Module

    Gasoline and Diesel Fuel Update (EIA)

    of employment by industry is industrial output. Both current and lagged output values enter in the employment specification, reflecting the tendency of firms to hire employees in...

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

    Office of Scientific and Technical Information (OSTI)

    U.S. DEPARTMENT OF HP IENERGY Office of Science DOESC-ARM-15-024 915-MHz Wind Profiler ... M Jensen et al., March 2016, DOESC-ARM-15-024 915-MHz Wind Profiler for Cloud Forecasting ...

  1. World oil inventories forecast to grow significantly in 2016...

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

    World oil inventories forecast to grow significantly in 2016 and 2017 Global oil inventories are expected to continue strong growth over the next two years which should keep oil ...

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

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

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

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

    Reports and Publications (EIA)

    2003-01-01

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

  4. Improving the Accuracy of Solar Forecasting Funding Opportunity

    Broader source: Energy.gov [DOE]

    Through the Improving the Accuracy of Solar Forecasting Funding Opportunity, DOE is funding solar projects that are helping utilities, grid operators, solar power plant owners, and other...

  5. DOE Publishes New Forecast of Energy Savings from LED Lighting

    Broader source: Energy.gov [DOE]

    The U.S. Department of Energy has just published the latest edition of its biannual report, Energy Savings Forecast of Solid-State Lighting in General Illumination Applications, which models the...

  6. Value of Improved Short-Term Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2015-02-01

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

  7. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

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

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

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

    The Wind Forecast Improvement Project (WFIP) is a U. S. Department of Energy (DOE) sponsored research project whose overarching goals are to improve the accuracy of short-term wind ...

  9. Recently released EIA report presents international forecasting data

    SciTech Connect (OSTI)

    1995-05-01

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

  10. Solar Trackers Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

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

  12. Meanwhile, much attention will focus on model evaluation results at Frenchman Fl

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

    Meanwhile, much attention will focus on model evaluation results at Frenchman Flat. "We are optimistic the results will be reasonably consistent with our model forecasts," explained Wilborn. "If model evaluation results are approved by the State of Nevada, we can move toward closure and long-term monitoring - the final stage in our strategy." All components of the Nevada Site Office groundwater program will be discussed at an upcoming Groundwater Open House on September 18,

  13. New Climate Research Centers Forecast Changes and Challenges | Department

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

    of Energy Climate Research Centers Forecast Changes and Challenges New Climate Research Centers Forecast Changes and Challenges October 25, 2013 - 12:24pm Addthis This artist's rendering illustrates the full site installation, including a new aerosol observing system (far left) and a precipitation radar (far right, with 20-ft tower). The site is located near the Graciosa Island aiport terminal, hidden by the image inset. | Image courtesy of ARM Climate Research Facility. This artist's

  14. Study forecasts disappearance of conifers due to climate change

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

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

  15. Energy Department Forecasts Geothermal Achievements in 2015 | Department of

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

    Energy Forecasts Geothermal Achievements in 2015 Energy Department Forecasts Geothermal Achievements in 2015 The 40th annual Stanford Geothermal Workshop in January featured speakers in the geothermal sector, including Jay Nathwani, Acting Director of the Energy Department's Geothermal Technologies Office. Nathwani shared achievements and challenges in the program's technical portfolio. The 40th annual Stanford Geothermal Workshop in January featured speakers in the geothermal sector,

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

    SciTech Connect (OSTI)

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

    2009-11-20

    Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and

  17. 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

  18. Compact electron beam focusing column

    SciTech Connect (OSTI)

    Persaud, Arun; Leung, Ka-Ngo; Reijonen, Jani

    2001-07-13

    A novel design for an electron beam focusing column has been developed at LBNL. The design is based on a low-energy spread multicusp plasma source which is used as a cathode for electron beam production. The focusing column is 10 mm in length. The electron beam is focused by means of electrostatic fields. The column is designed for a maximum voltage of 50 kV. Simulations of the electron trajectories have been performed by using the 2-D simulation code IGUN and EGUN. The electron temperature has also been incorporated into the simulations. The electron beam simulations, column design and fabrication will be discussed in this presentation.

  19. E&P Focus Newsletter

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

    ... Winter 2011 Issue PDF-1.83MB In this issue read about NETL research focusing on R&D in the Bakken Shale. Included are an overview of activity levels in the Bakken and its ...

  20. Simulations of neutralized final focus

    SciTech Connect (OSTI)

    Welch, D.R.; Rose, D.V.; Genoni, T.C.; Yu, S.S.; Barnard, J.J.

    2005-01-18

    In order to drive an inertial fusion target or study high energy density physics with heavy ion beams, the beam radius must be focused to < 3 mm and the pulse length must be compressed to < 10 ns. The conventional scheme for temporal pulse compression makes use of an increasing ion velocity to compress the beam as it drifts and beam space charge to stagnate the compression before final focus. Beam compression in a neutralizing plasma does not require stagnation of the compression, enabling a more robust method. The final pulse shape at the target can be programmed by an applied velocity tilt. In this paper, neutralized drift compression is investigated. The sensitivity of the compression and focusing to beam momentum spread, plasma, and magnetic field conditions is studied with realistic driver examples. Using the 3D particle-in-cell code, we examine issues associated with self-field generation, stability, and vacuum-neutralized transport transition and focusing.

  1. Focus Series | Department of Energy

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

    Focus Series Focus Series On-Bill Financing Brings Lenders and Homeowners on Board Photo of a man, woman, and small child standing in front of a house. Read how Clean Energy Works' partnership with a nonprofit community development financial institution resulted in an unprecedented number of upgrades in a short period of time. July 2014 Energy Advisors Help Homeowners Go the Extra Mile Advertisement for the Denver Energy Challenge, with a female smiling at the camera -- with something wrong with

  2. 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.

  3. Forecasting the 2013–2014 influenza season using Wikipedia

    SciTech Connect (OSTI)

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

    2015-05-14

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

  4. Forecasting the 2013–2014 influenza season using Wikipedia

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

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

    2015-05-14

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

  5. Use of Data Denial Experiments to Evaluate ESA Forecast Sensitivity Patterns

    SciTech Connect (OSTI)

    Zack, J; Natenberg, E J; Knowe, G V; Manobianco, J; Waight, K; Hanley, D; Kamath, C

    2011-09-13

    The overall goal of this multi-phased research project known as WindSENSE is to develop an observation system deployment strategy that would improve wind power generation forecasts. The objective of the deployment strategy is to produce the maximum benefit for 1- to 6-hour ahead forecasts of wind speed at hub-height ({approx}80 m). In this phase of the project the focus is on the Mid-Columbia Basin region which encompasses the Bonneville Power Administration (BPA) wind generation area shown in Figure 1 that includes Klondike, Stateline, and Hopkins Ridge wind plants. The Ensemble Sensitivity Analysis (ESA) approach uses data generated by a set (ensemble) of perturbed numerical weather prediction (NWP) simulations for a sample time period to statistically diagnose the sensitivity of a specified forecast variable (metric) for a target location to parameters at other locations and prior times referred to as the initial condition (IC) or state variables. The ESA approach was tested on the large-scale atmospheric prediction problem by Ancell and Hakim 2007 and Torn and Hakim 2008. ESA was adapted and applied at the mesoscale by Zack et al. (2010a, b, and c) to the Tehachapi Pass, CA (warm and cools seasons) and Mid-Colombia Basin (warm season only) wind generation regions. In order to apply the ESA approach at the resolution needed at the mesoscale, Zack et al. (2010a, b, and c) developed the Multiple Observation Optimization Algorithm (MOOA). MOOA uses a multivariate regression on a few select IC parameters at one location to determine the incremental improvement of measuring multiple variables (representative of the IC parameters) at various locations. MOOA also determines how much information from each IC parameter contributes to the change in the metric variable at the target location. The Zack et al. studies (2010a, b, and c), demonstrated that forecast sensitivity can be characterized by well-defined, localized patterns for a number of IC variables such as 80-m

  6. Magnetically focused liquid drop radiator

    DOE Patents [OSTI]

    Botts, Thomas E. (Fairfax, VA); Powell, James R. (Shoreham, NY); Lenard, Roger (Redondo Beach, CA)

    1986-01-01

    A magnetically focused liquid drop radiator for application in rejecting rgy from a spacecraft, characterized by a magnetizable liquid or slurry disposed in operative relationship within the liquid droplet generator and its fluid delivery system, in combination with magnetic means disposed in operative relationship around a liquid droplet collector of the LDR. The magnetic means are effective to focus streams of droplets directed from the generator toward the collector, thereby to assure that essentially all of the droplets are directed into the collector, even though some of the streams may be misdirected as they leave the generator. The magnetic focusing means is also effective to suppress splashing of liquid when the droplets impinge on the collector.

  7. Magnetically focused liquid drop radiator

    DOE Patents [OSTI]

    Botts, T.E.; Powell, J.R.; Lenard, R.

    1984-12-10

    A magnetically focused liquid drop radiator for application in rejecting energy from a spacecraft, characterized by a magnetizable liquid or slurry disposed in operative relationship within the liquid droplet generator and its fluid delivery system, in combination with magnetic means disposed in operative relationship around a liquid droplet collector of the LDR. The magnetic means are effective to focus streams of droplets directed from the generator toward the collector, thereby to assure that essentially all of the droplets are directed into the collector, even though some of the streams may be misdirected as they leave the generator. The magnetic focusing means is also effective to suppress splashing of liquid when the droplets impinge on the collector.

  8. New charm results from FOCUS

    SciTech Connect (OSTI)

    Bianco, Stefano; /Frascati

    2004-12-01

    New results from the photoproduction experiment FOCUS are reported: Dalitz plot analysis, semileptonic form factor ratios and excited meson spectroscopy. The author reports on three new results from the photoproduction experiment FOCUS: the first Dalitz plot analysis of charm meson decays using the K-matrix approach[ 1], new measurements of the D{sub s}{sup +} {yields} {delta}(1020) {mu}{sup +}{nu} form factor ratios [2], and new measurements on L=1 excited meson spectroscopy [3], i.e., precise measurements of the masses and widths of the D*{sub 2}{sup +} and D*{sub 2}{sup 0} mesons, and evidence for broad states decaying to D{sup +}{pi}{sup -}, D{sup 0}{pi}{sup +} (the first such evidence in D{sup 0}{pi}{sup +}). The data for this paper were collected in the Wideband photoproduction experiment FOCUS during the Fermilab 1996-1997 fixed-target run.

  9. Focused X-ray source

    DOE Patents [OSTI]

    Piestrup, M.A.; Boyers, D.G.; Pincus, C.I.; Maccagno, P.

    1990-08-21

    Disclosed is an intense, relatively inexpensive X-ray source (as compared to a synchrotron emitter) for technological, scientific, and spectroscopic purposes. A conical radiation pattern produced by a single foil or stack of foils is focused by optics to increase the intensity of the radiation at a distance from the conical radiator. 8 figs.

  10. Focused X-ray source

    DOE Patents [OSTI]

    Piestrup, Melvin A.; Boyers, David G.; Pincus, Cary I.; Maccagno, Pierre

    1990-01-01

    An intense, relatively inexpensive X-ray source (as compared to a synchrotron emitter) for technological, scientific, and spectroscopic purposes. A conical radiation pattern produced by a single foil or stack of foils is focused by optics to increase the intensity of the radiation at a distance from the conical radiator.

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2012-04-01

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

  12. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

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

  13. Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts |

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

    Department of Energy Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts May 11, 2016 - 6:48pm Addthis Balancing the power grid is an art-or at least a scientific study in chaos-and the Energy Department is hoping wind energy can take a greater role in the act. Yet, the intermittency of wind-sometimes it's blowing, sometimes it's not-makes adding it smoothly to the nation's electrical grid a challenge.

  14. Forecast of contracting and subcontracting opportunities. Fiscal year 1996

    SciTech Connect (OSTI)

    1996-02-01

    This forecast of prime and subcontracting opportunities with the U.S. Department of Energy and its MAO contractors and environmental restoration and waste management contractors, is the Department`s best estimate of small, small disadvantaged and women-owned small business procurement opportunities for fiscal year 1996. The information contained in the forecast is published in accordance with Public Law 100-656. It is not an invitation for bids, a request for proposals, or a commitment by DOE to purchase products or services. Each procurement opportunity is based on the best information available at the time of publication and may be revised or cancelled.

  15. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

    2008-01-15

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

  16. 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.

  17. Central focus solar energy system

    SciTech Connect (OSTI)

    Findell, M.

    1982-02-23

    A central focus solar energy system consists of one or more arrays of mirrors, a receiver for each array, a sun tracker, a sun tracker sun acquisition device and a control unit. Mirrors of the arrays are subjected to two-axis control by electromechanical devices actuated by sun-tracking error signals generated by the sun tracker. Mirrors are thus oriented so as to cause reflections of the direct rays of the sun from all mirrors in an array to converge on a receiver at a common focus. Fixed (Principal) axes of mirror rotation are parallel to the fixed (Principal) axis of rotation of the sun tracker sensor making orientation of the system independent of the earth's spin axis. The system includes a ''vernier'' or fine adjustment control for positioning mirrors that supplements sun tracker controls.

  18. Presentation: FracFocus | Department of Energy

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

    FracFocus Presentation: FracFocus Mike Paque, Gerry Baker, and Stan Belieu reported on the work of FracFocus and the improvements made in FracFocus 2.0 as well as their connection ...

  19. 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.

  20. Cost-Effective, Customer-Focused, and Contractor-Focused Data...

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

    Effective, Customer-Focused, and Contractor-Focused Data Tracking Systems Cost-Effective, Customer-Focused, and Contractor-Focused Data Tracking Systems Better Buildings ...

  1. EIA revises up forecast for U.S. 2013 crude oil production by...

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

    EIA revises up forecast for U.S. 2013 crude oil production by 70,000 barrels per day The forecast for U.S. crude oil production keeps going higher. The U.S. Energy Information ...

  2. 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 ...

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

    SciTech Connect (OSTI)

    Piwko, R.; Jordan, G.

    2011-11-01

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

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

    Broader source: Energy.gov [DOE]

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

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2010-04-01

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

  6. Combining multi-objective optimization and bayesian model averaging to calibrate forecast ensembles of soil hydraulic models

    SciTech Connect (OSTI)

    Vrugt, Jasper A; Wohling, Thomas

    2008-01-01

    Most studies in vadose zone hydrology use a single conceptual model for predictive inference and analysis. Focusing on the outcome of a single model is prone to statistical bias and underestimation of uncertainty. In this study, we combine multi-objective optimization and Bayesian Model Averaging (BMA) to generate forecast ensembles of soil hydraulic models. To illustrate our method, we use observed tensiometric pressure head data at three different depths in a layered vadose zone of volcanic origin in New Zealand. A set of seven different soil hydraulic models is calibrated using a multi-objective formulation with three different objective functions that each measure the mismatch between observed and predicted soil water pressure head at one specific depth. The Pareto solution space corresponding to these three objectives is estimated with AMALGAM, and used to generate four different model ensembles. These ensembles are post-processed with BMA and used for predictive analysis and uncertainty estimation. Our most important conclusions for the vadose zone under consideration are: (1) the mean BMA forecast exhibits similar predictive capabilities as the best individual performing soil hydraulic model, (2) the size of the BMA uncertainty ranges increase with increasing depth and dryness in the soil profile, (3) the best performing ensemble corresponds to the compromise (or balanced) solution of the three-objective Pareto surface, and (4) the combined multi-objective optimization and BMA framework proposed in this paper is very useful to generate forecast ensembles of soil hydraulic models.

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

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

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

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2009-12-01

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

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

    SciTech Connect (OSTI)

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

    2011-03-28

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

  10. 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.