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Sample records for reference case forecast

  1. Appendix A: Reference case

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

    4 Reference case Table A2. Energy consumption by sector and source (quadrillion Btu per year, unless otherwise noted) Energy Information Administration Annual Energy Outlook 2014...

  2. Appendix A: Reference case

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

    Reference case Energy Information Administration Annual Energy Outlook 2014 Table A17. Renewable energy consumption by sector and source (quadrillion Btu) Sector and source...

  3. Appendix A: Reference case projections

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

    Reference case projections Table A1. World total primary energy consumption by region, Reference case, 2011-40 (quadrillion Btu) Region History Projections Average annual percent ...

  4. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    G Projections of petroleum and other liquids production in three cases * Reference * High Oil Price * Low Oil Price This page inTenTionally lefT blank 85 U.S. Energy Information Administration | International Energy Outlook 2016 Projections of petroleum and other liquid fuels production in three cases Table G1. World petroleum and other liquids production by region and country, Reference case, 2011-40 (million barrels per day, unless otherwise noted) Region/country History (estimates)

  5. Appendix A: Reference case projections

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

    Reference case projections by end-use sector and country grouping Table F1. Total world delivered energy consumption by end-use sector and fuel, 2011-40 (quadrillion Btu) Sector...

  6. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    9 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections Table A14. World population by region, Reference case, 2011-40 (millions) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 484 489 523 544 564 581 597 0.7 United States a 312 315 334 347 359 370 380 0.7 Canada 34 35 38 39 41 43 44 0.8 Mexico and Chile 137 139 151 158 164 169 173 0.8 OECD Europe 548 550 565 571 576 579 581

  7. Appendix A: Reference case projections

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

    U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections Table A1. World total primary energy consumption by region, Reference case, 2011-40 (quadrillion Btu) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 120.6 118.1 125.7 128.1 130.7 133.8 138.1 0.6 United States a 96.8 94.4 100.8 102.0 102.9 103.8 105.7 0.4 Canada 14.5 14.5 15.1 15.6 16.3 17.1 18.1 0.8 Mexico and Chile 9.3

  8. Appendix A: Reference case projections

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

    International Energy Outlook 2016 Reference case projections Table A4. World gross domestic product (GDP) by region expressed in market exchange rates, Reference case, 2011-40 (billion 2010 dollars) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 18,006 18,440 22,566 25,585 28,757 32,166 36,120 2.4 United States a 15,021 15,369 18,801 21,295 23,894 26,659 29,898 2.4 Canada 1,662 1,694 2,024 2,240 2,470 2,730 3,012 2.1 Mexico

  9. Appendix A: Reference case projections

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

    U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections Table A6. World natural gas consumption by region, Reference case, 2011-40 (trillion cubic feet) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 30.8 31.8 32.8 34.3 36.5 38.2 40.1 0.8 United States a 24.5 25.5 26.1 26.9 28.1 28.8 29.7 0.5 Canada 3.7 3.7 3.9 4.2 4.7 5.2 5.6 1.5 Mexico and Chile 2.6 2.6 2.8 3.2 3.6 4.2 4.8

  10. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    1 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for natural gas production Table I1. World total natural gas production by region, Reference case, 2012-40 (trillion cubic feet) Region/country Projections Average annual percent change, 2012-40 2012 2020 2025 2030 2035 2040 OECD OECD Americas 31.8 35.7 38.6 42.1 44.6 47.3 1.4 United States a 24.0 28.7 30.4 32.9 34.0 35.3 1.4 Canada 6.1 5.8 6.6 7.2 7.9 8.6 1.2 Mexico 1.7 1.2 1.5 2.0 2.6 3.3

  11. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    J Kaya Identity factor projections * Carbon dioxide intensity * Energy intensity * GDP per capita * Population This page inTenTionally lefT blank 127 U.S. Energy Information Administration | International Energy Outlook 2016 Kaya Identity factor projections Table J1. World carbon dioxide intensity of energy use by region, Reference case, 2011-40 (metric tons per billion Btu) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas

  12. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    7 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for electricity capacity and generation by fuel Table H1. World total installed generating capacity by region and country, 2011-40 (gigawatts) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 1,258 1,278 1,330 1,371 1,436 1,517 1,622 0.9 United States a 1,046 1,063 1,079 1,091 1,133 1,187 1,261 0.6 Canada 133 135

  13. Appendix A: Reference case projections

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

    8 Appendix A Table A3. World gross domestic product (GDP) by region expressed in purchasing power parity, Reference case, 2011-40 (billion 2010 dollars) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 18,616 19,080 23,390 26,577 29,942 33,569 37,770 2.5 United States a 15,021 15,369 18,801 21,295 23,894 26,659 29,898 2.4 Canada 1,396 1,422 1,700 1,881 2,074 2,293 2,529 2.1 Mexico and Chile 2,200 2,288 2,890 3,400 3,974 4,618

  14. Appendix A: Reference case projections

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

    6 Appendix A Table A2. World total energy consumption by region and fuel, Reference case, 2011-40 (quadrillion Btu) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas Liquids 45.3 44.6 46.4 46.1 46.0 46.2 46.7 0.2 Natural gas 31.8 32.8 33.9 35.5 37.7 39.5 41.4 0.8 Coal 21.0 18.7 20.3 20.5 20.1 20.0 20.0 0.2 Nuclear 9.4 9.2 9.5 9.4 9.5 9.5 9.7 0.2 Other 13.1 12.9 15.6 16.6 17.5 18.6 20.3 1.6 Total 120.6 118.1 125.7 128.1 130.7

  15. Appendix A: Reference case projections

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

    30 Appendix A Table A5. World liquids consumption by region, Reference case, 2011-40 (million barrels per day) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 23.6 23.2 24.4 24.4 24.3 24.4 24.6 0.2 United States a 18.9 18.5 19.6 19.6 19.4 19.3 19.3 0.2 Canada 2.3 2.4 2.4 2.4 2.4 2.4 2.5 0.2 Mexico and Chile 2.4 2.4 2.4 2.4 2.5 2.7 2.9 0.6 OECD Europe 14.5 14.1 13.7 13.6 13.7 13.8 14.0 0.0 OECD Asia 7.9 8.2 7.7 7.5 7.5 7.5

  16. Appendix A. Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    by region and country, Low Oil Price case, 2009-40 (million barrels per day) Region History Projections Average annual percent change, 2010-40 2009 2010 2011 2020 2025 2030...

  17. Appendix A. Reference case projections

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

    by region and end-use sector, High Oil Price case, 2010-40 (quadrillion Btu) Region History Projections Average annual percent change, 2010-40 2010 2020 2025 2030 2035 2040 OECD...

  18. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    E Low Oil Price case projections This page inTenTionally lefT blank 57 U.S. Energy Information Administration | International Energy Outlook 2016 Low Oil Price case projections Table E1. World total primary energy consumption by region, Low Oil Price case, 2011-40 (quadrillion Btu) Region History Projections Average annual percent change, 2012-s40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 120.6 118.1 126.5 129.2 131.8 135.0 138.9 0.6 United States a 96.8 94.4 101.2 102.7 103.6 104.6

  19. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    7 U.S. Energy Information Administration | International Energy Outlook 2016 Low Economic Growth case projections Table C1. World total primary energy consumption by region, Low Economic Growth case, 2011-40 (quadrillion Btu) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 120.6 118.1 123.3 123.9 124.7 126.3 128.8 0.3 United States a 96.8 94.4 98.7 98.1 97.5 97.4 98.0 0.1 Canada 14.5 14.5 15.0 15.4 15.9 16.6 17.3 0.6 Mexico

  20. Annual Energy Outlook 2011 Reference Case

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

    October 9, 2012 | Washington, DC Annual Energy Outlook 2013: Modeling Updates in the Transportation Sector WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE Overview 2 * Modeling updates made to the Annual Energy Outlook 2013 Reference case * Light-duty vehicle technology updates * Heavy-duty natural gas vehicles * Preliminary results (Working group presentation for discussion purposes. Do not quote or cite as results are subject to change)

  1. Generic Argillite/Shale Disposal Reference Case

    SciTech Connect (OSTI)

    Zheng, Liange; Colon, Carlos Jové; Bianchi, Marco; Birkholzer, Jens

    2014-08-08

    Radioactive waste disposal in a deep subsurface repository hosted in clay/shale/argillite is a subject of widespread interest given the desirable isolation properties, geochemically reduced conditions, and widespread geologic occurrence of this rock type (Hansen 2010; Bianchi et al. 2013). Bianchi et al. (2013) provides a description of diffusion in a clay-hosted repository based on single-phase flow and full saturation using parametric data from documented studies in Europe (e.g., ANDRA 2005). The predominance of diffusive transport and sorption phenomena in this clay media are key attributes to impede radionuclide mobility making clay rock formations target sites for disposal of high-level radioactive waste. The reports by Hansen et al. (2010) and those from numerous studies in clay-hosted underground research laboratories (URLs) in Belgium, France and Switzerland outline the extensive scientific knowledge obtained to assess long-term clay/shale/argillite repository isolation performance of nuclear waste. In the past several years under the UFDC, various kinds of models have been developed for argillite repository to demonstrate the model capability, understand the spatial and temporal alteration of the repository, and evaluate different scenarios. These models include the coupled Thermal-Hydrological-Mechanical (THM) and Thermal-Hydrological-Mechanical-Chemical (THMC) models (e.g. Liu et al. 2013; Rutqvist et al. 2014a, Zheng et al. 2014a) that focus on THMC processes in the Engineered Barrier System (EBS) bentonite and argillite host hock, the large scale hydrogeologic model (Bianchi et al. 2014) that investigates the hydraulic connection between an emplacement drift and surrounding hydrogeological units, and Disposal Systems Evaluation Framework (DSEF) models (Greenberg et al. 2013) that evaluate thermal evolution in the host rock approximated as a thermal conduction process to facilitate the analysis of design options. However, the assumptions and the properties (parameters) used in these models are different, which not only make inter-model comparisons difficult, but also compromise the applicability of the lessons learned from one model to another model. The establishment of a reference case would therefore be helpful to set up a baseline for model development. A generic salt repository reference case was developed in Freeze et al. (2013) and the generic argillite repository reference case is presented in this report. The definition of a reference case requires the characterization of the waste inventory, waste form, waste package, repository layout, EBS backfill, host rock, and biosphere. This report mainly documents the processes in EBS bentonite and host rock that are potentially important for performance assessment and properties that are needed to describe these processes, with brief description other components such as waste inventory, waste form, waste package, repository layout, aquifer, and biosphere. A thorough description of the generic argillite repository reference case will be given in Jové Colon et al. (2014).

  2. Annual Energy Outlook 2011 Reference Case

    Gasoline and Diesel Fuel Update (EIA)

    April 2016 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 Annual Coal Distribution Report 2014 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as

  3. Annual Energy Outlook 2013 Early Release Reference Case

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

    emission intensity index, 20051 Source: EIA, Annual Energy Outlook 2015 Reference case History Projections 2013 Carbon dioxide emissions per 2009 dollar GDP Energy use per 2009...

  4. REFERENCE CASES FOR USE IN THE CEMENTITOUS PARTNERSHIP PROJECT

    SciTech Connect (OSTI)

    Langton, C.; Kosson, D.; Garrabrants, A.

    2010-08-31

    The Cementitious Barriers Partnership Project (CBP) is a multi-disciplinary, multi-institution cross cutting collaborative effort supported by the US Department of Energy (DOE) to develop a reasonable and credible set of tools to improve understanding and prediction of the structural, hydraulic and chemical performance of cementitious barriers used in nuclear applications. The period of performance is >100 years for operating facilities and > 1000 years for waste management. The CBP has defined a set of reference cases to provide the following functions: (i) a common set of system configurations to illustrate the methods and tools developed by the CBP, (ii) a common basis for evaluating methodology for uncertainty characterization, (iii) a common set of cases to develop a complete set of parameter and changes in parameters as a function of time and changing conditions, (iv) a basis for experiments and model validation, and (v) a basis for improving conceptual models and reducing model uncertainties. These reference cases include the following two reference disposal units and a reference storage unit: (i) a cementitious low activity waste form in a reinforced concrete disposal vault, (ii) a concrete vault containing a steel high-level waste tank filled with grout (closed high-level waste tank), and (iii) a spent nuclear fuel basin during operation. Each case provides a different set of desired performance characteristics and interfaces between materials and with the environment. Examples of concretes, grout fills and a cementitious waste form are identified for the relevant reference case configurations.

  5. Preliminary Reference Case Results for Oil and Natural Gas

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

    Preliminary Reference Case Results for Oil and Natural Gas AEO2014 Oil and Gas Supply Working Group Meeting Office of Petroleum, Gas, and Biofuels Analysis September 26, 2013 | Washington, DC WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE AEO2014P uses ref2014.d092413a AEO2013 uses ref2013.d102312a Changes for AEO2014 2 * Revised shale & tight play resources (EURs, type curves) * Updated classification of shale gas, tight gas, &

  6. Coal-by-Rail: A Business-as-Usual Reference Case | Argonne National...

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

    Coal-by-Rail: A Business-as-Usual Reference Case Title Coal-by-Rail: A Business-as-Usual Reference Case Publication Type Report Year of Publication 2015 Authors Mintz, MM, Saricks,...

  7. Coal-by-Rail Business-as-Usual Reference Case

    Broader source: Energy.gov [DOE]

    As proposed carbon emission standards reduce domestic coal use, the role of coal in the U.S. energy mix may be expected to decline. If such a decline were to occur, how would it affect rail traffic? Today, coal represents a major share of rail tonnage and gross revenue. While growth in other traffic―most notably, crude oil―may offset some of any potential decline in coal shipments, would it be sufficient? This paper explores trends in coal production volumes and use, rail tonnage and revenue, and the distribution of traffic origins and destinations in order to consider the impact of potential changes in future coal traffic. Rather than modeling discrete flows, it draws on historical data and forecasts maintained by the U.S. Department of Energy’s Energy Information Administration (EIA), industry studies and analyses, and background knowledge of the rail industry, specific routes and service territories, and commodity-level traffic volumes.

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

    SciTech Connect (OSTI)

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

    1983-01-01

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

  9. 2007 Wholesale Power Rate Case Final Proposal : Market Price Forecast Study.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    2006-07-01

    This study presents BPA's market price forecasts for the Final Proposal, which are based on AURORA modeling. AURORA calculates the variable cost of the marginal resource in a competitively priced energy market. In competitive market pricing, the marginal cost of production is equivalent to the market-clearing price. Market-clearing prices are important factors for informing BPA's power rates. AURORA was used as the primary tool for (a) estimating the forward price for the IOU REP Settlement benefits calculation for fiscal years (FY) 2008 and 2009, (b) estimating the uncertainty surrounding DSI payments and IOU REP Settlements benefits, (c) informing the secondary revenue forecast and (d) providing a price input used for the risk analysis. For information about the calculation of the secondary revenues, uncertainty regarding the IOU REP Settlement benefits and DSI payment uncertainty, and the risk run, see Risk Analysis Study WP-07-FS-BPA-04.

  10. 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.

  11. 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.

  12. Annual Energy Outlook Retrospective Review: Evaluation of 2014 and Prior Reference Case Projections

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

    Annual Energy Outlook Retrospective Review: Evaluation of 2014 and Prior Reference Case Projections March 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | AEO Retrospective Review: Evaluation of 2014 and Prior Reference Case Projections 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

  13. Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices

    SciTech Connect (OSTI)

    Bolinger, Mark A.; Wiser, Ryan H.

    2010-01-04

    On December 14, 2009, the reference-case projections from Annual Energy Outlook 2010 were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in itigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings.

  14. Simulations of Clouds and Sensitivity Study by Weather Research and Forecast Model for Atmospheric Radiation Measurement Case 4

    SciTech Connect (OSTI)

    Wu, J.; Zhang, M.

    2005-03-18

    One of the large errors in general circulation models (GCMs) cloud simulations is from the mid-latitude, synoptic-scale frontal cloud systems. Now, with the availability of the cloud observations from Atmospheric Radiation Measurement (ARM) 2000 cloud Intensive Operational Period (IOP) and other observational datasets, the community is able to document the model biases in comparison with the observations and make progress in development of better cloud schemes in models. Xie et al. (2004) documented the errors in midlatitude frontal cloud simulations for ARM Case 4 by single-column models (SCMs) and cloud resolving models (CRMs). According to them, the errors in the model simulated cloud field might be caused by following reasons: (1) lacking of sub-grid scale variability; (2) lacking of organized mesoscale cyclonic advection of hydrometeors behind a moving cyclone which may play important role to generate the clouds there. Mesoscale model, however, can be used to better under stand these controls on the subgrid variability of clouds. Few studies have focused on applying mesoscale models to the forecasting of cloud properties. Weaver et al. (2004) used a mesoscale model RAMS to study the frontal clouds for ARM Case 4 and documented the dynamical controls on the sub-GCM-grid-scale cloud variability.

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

    SciTech Connect (OSTI)

    1995-04-01

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

  16. 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....

  17. Forecast Change

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

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

  18. Reference Materials

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

    Reference Materials Reference Materials Large Scale Computing and Storage Requirements for Advanced Scientific Computing Research January 5-6, 2011 Official DOE Invitation Workshop Invitation Letter from DOE Associate Directors NERSC Documents NERSC science requirements home page NERSC science requirements workshop page NERSC science requirements case study FAQ Previous NERSC Requirements Workshops Biological and Environmental Research (BER) Basic Energy Sciences (BES) Fusion Energy Sciences

  19. An Updated Annual Energy Outlook 2009 Reference Case Reflecting Provisions of the American Recovery and Reinvestment Act and Recent Changes in the Economic Outlook

    Reports and Publications (EIA)

    2009-01-01

    This report updates the Reference Case presented in the Annual Energy Outlook 2009 based on recently enacted legislation and the changing macroeconomic environment.

  20. Technical basis for cases N-629 and N-631 as an alternative for RTNDT reference temperature

    SciTech Connect (OSTI)

    Merkle, John Graham; Server, W. L.

    2007-01-01

    ASME Code Cases N-629/N-631, published in 1999, provided an important new approach to allow material specific, measured fracture toughness curves for ferritic steels in the code applications. This has enabled some of the nuclear power plants whose reactor pressure vessel materials reached a certain threshold level based on overly conservative rules to use an alternative RTNDT to justify continued operation of their plants. These code cases have been approved by the US Nuclear Regulatory Commission and these have been proposed to be codified in Appendix A and Appendix G of the ASME Boiler and Pressure Vessel Code. This paper summarizes the basis of this approach for the record.

  1. Reference Materials

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

    Reference Materials Reference Materials Large Scale Computing and Storage Requirements for Fusion Energy Sciences August 3-4, 2010 Official DOE Invitation Workshop Invitation Letter from DOE Associate Directors [not available] NERSC Documents NERSC science requirements home page NERSC science requirements workshop page NERSC science requirements case study FAQ Workshop Agenda Previous NERSC Requirements Workshops Biological and Environmental Research (BER) Basic Energy Sciences (BES) Fusion

  2. Reference Materials

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

    Reference Materials Reference Materials Large Scale Computing and Storage Requirements for High Energy Physics November 12-13, 2009 Official DOE Invitation Workshop Invitation Letter from DOE Associate Directors NERSC Documents NERSC science requirements home page NERSC science requirements workshop page NERSC science requirements case study FAQ Workshop Agenda Previous NERSC Requirements Workshops Biological and Environmental Research (BER) Basic Energy Sciences (BES) Fusion Energy Sciences

  3. Mechanism reduction for multicomponent surrogates: A case study using toluene reference fuels

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

    Niemeyer, Kyle E.; Sung, Chih-Jen

    2014-11-01

    Strategies and recommendations for performing skeletal reductions of multicomponent surrogate fuels are presented, through the generation and validation of skeletal mechanisms for a three-component toluene reference fuel. Using the directed relation graph with error propagation and sensitivity analysis method followed by a further unimportant reaction elimination stage, skeletal mechanisms valid over comprehensive and high-temperature ranges of conditions were developed at varying levels of detail. These skeletal mechanisms were generated based on autoignition simulations, and validation using ignition delay predictions showed good agreement with the detailed mechanism in the target range of conditions. When validated using phenomena other than autoignition, suchmore » as perfectly stirred reactor and laminar flame propagation, tight error control or more restrictions on the reduction during the sensitivity analysis stage were needed to ensure good agreement. In addition, tight error limits were needed for close prediction of ignition delay when varying the mixture composition away from that used for the reduction. In homogeneous compression-ignition engine simulations, the skeletal mechanisms closely matched the point of ignition and accurately predicted species profiles for lean to stoichiometric conditions. Furthermore, the efficacy of generating a multicomponent skeletal mechanism was compared to combining skeletal mechanisms produced separately for neat fuel components; using the same error limits, the latter resulted in a larger skeletal mechanism size that also lacked important cross reactions between fuel components. Based on the present results, general guidelines for reducing detailed mechanisms for multicomponent fuels are discussed.« less

  4. Mechanism reduction for multicomponent surrogates: A case study using toluene reference fuels

    SciTech Connect (OSTI)

    Niemeyer, Kyle E.; Sung, Chih-Jen

    2014-11-01

    Strategies and recommendations for performing skeletal reductions of multicomponent surrogate fuels are presented, through the generation and validation of skeletal mechanisms for a three-component toluene reference fuel. Using the directed relation graph with error propagation and sensitivity analysis method followed by a further unimportant reaction elimination stage, skeletal mechanisms valid over comprehensive and high-temperature ranges of conditions were developed at varying levels of detail. These skeletal mechanisms were generated based on autoignition simulations, and validation using ignition delay predictions showed good agreement with the detailed mechanism in the target range of conditions. When validated using phenomena other than autoignition, such as perfectly stirred reactor and laminar flame propagation, tight error control or more restrictions on the reduction during the sensitivity analysis stage were needed to ensure good agreement. In addition, tight error limits were needed for close prediction of ignition delay when varying the mixture composition away from that used for the reduction. In homogeneous compression-ignition engine simulations, the skeletal mechanisms closely matched the point of ignition and accurately predicted species profiles for lean to stoichiometric conditions. Furthermore, the efficacy of generating a multicomponent skeletal mechanism was compared to combining skeletal mechanisms produced separately for neat fuel components; using the same error limits, the latter resulted in a larger skeletal mechanism size that also lacked important cross reactions between fuel components. Based on the present results, general guidelines for reducing detailed mechanisms for multicomponent fuels are discussed.

  5. Comparison of AEO 2005 natural gas price forecast to NYMEX futures prices

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13

    On December 9, the reference case projections from ''Annual Energy Outlook 2005 (AEO 2005)'' were posted on the Energy Information Administration's (EIA) web site. As some of you may be aware, we at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk. As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past four years, forward natural gas contracts (e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past four years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation (presuming that long-term price stability is valued). In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2005. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or, more recently (and briefly), http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past four AEO releases (AEO 2001-AE0 2004), we once again find that the AEO 2005 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. In fact, the NYMEXAEO 2005 reference case comparison yields by far the largest premium--$1.11/MMBtu levelized over six years--that we have seen over the last five years. In other words, on average, one would have to pay $1.11/MMBtu more than the AEO 2005 reference case natural gas price forecast in order to lock in natural gas prices over the coming six years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation. Fixed-price renewables obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of six years.

  6. Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX FuturesPrices

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19

    On December 12, 2005, the reference case projections from ''Annual Energy Outlook 2006'' (AEO 2006) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past five years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past five years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2006. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past five AEO releases (AEO 2001-AEO 2005), we once again find that the AEO 2006 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. In fact, the NYMEX-AEO 2006 reference case comparison yields by far the largest premium--$2.3/MMBtu levelized over five years--that we have seen over the last six years. In other words, on average, one would have had to pay $2.3/MMBtu more than the AEO 2006 reference case natural gas price forecast in order to lock in natural gas prices over the coming five years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation (or other forms of generation whose costs are not tied to the price of natural gas). Fixed-price generation (like certain forms of renewable generation) obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of five years.

  7. 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 ...

  8. 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...

  9. Forecasting Water Quality & Biodiversity

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

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

  10. 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...

  11. Appendix A: Reference case

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

    and related equipment 2 ... 0.33 0.33 0.33 0.33 0.35 0.37 0.39 0.5% Computers and related equipment 3 ... 0.13 0.12 0.10 0.08 0.07 0.06 0.05...

  12. Appendix A: Reference case

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

    DC, September 2013). 2011 and 2012 natural gas spot price at Henry Hub: Thomson Reuters. 2011 and 2012 electric power prices: EIA, Electric Power Monthly, DOEEIA-0226,...

  13. Appendix A: Reference case

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

    2011 and 2012 Brent and West Texas Intermediate crude oil spot prices: Thomson Reuters. 2011 and 2012 average imported crude oil cost: U.S. Energy Information...

  14. Appendix A: Reference case

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

    ... 9,429 9,603 11,592 12,773 14,220 15,828 17,635 2.2% Real investment ... 1,744 1,914 2,876 3,269 3,740...

  15. Appendix A: Reference case

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

    523.3 1.5% 1 Does not include water heating portion of load. 2 Includes televisions, set-top boxes, home theater systems, DVD players, and video game consoles. 3 Includes desktop...

  16. Appendix A: Reference case

    Gasoline and Diesel Fuel Update (EIA)

    ... 29.52 28.85 29.72 29.67 30.56 31.49 32.63 0.4% Non-renewable energy expenditures by sector (billion 2012 dollars) Residential...

  17. Appendix A: Reference case

    Gasoline and Diesel Fuel Update (EIA)

    ... 4,370 4,525 5,735 6,467 7,148 7,784 8,443 2.3% Agriculture, mining, and construction ... 1,556 1,623 2,226 2,311 2,389 2,457...

  18. Appendix A: Reference case

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

    supplies. 2 Includes lease condensate. 3 Tight oil represents resources in low-permeability reservoirs, including shale and chalk formations. The specific plays included in...

  19. Appendix A: Reference case

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

    2012-2040 (percent) 2011 2012 2020 2025 2030 2035 2040 Energy consumption Residential Propane ... 0.51 0.51 0.42 0.40...

  20. Appendix A: Reference case

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

    district services. 2 Includes (but is not limited to) miscellaneous uses such as transformers, medical imaging and other medical equipment, elevators, escalators, off-road...

  1. Appendix A: Reference case

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

    12.92 12.90 13.09 -0.2% 1 Commercial trucks 8,501 to 10,000 pounds gross vehicle weight rating. 2 CAFE standard based on projected new vehicle sales. 3 Includes CAFE credits for...

  2. Appendix A: Reference case

    Gasoline and Diesel Fuel Update (EIA)

    Sources: 2011 and 2012 interregional firm electricity trade data: 2012 seasonal reliability assessments from North American Electric Reliability Council regional entities and...

  3. Appendix A: Reference case

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

    ... 1,096 1,016 1,077 1,114 1,127 1,126 1,121 0.3% Waste coal supplied 2 ... 13 11 14 14 15 17 19...

  4. Appendix A: Reference case

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

    Information Administration Annual Energy Outlook 2014 Table A18. Energy-related carbon dioxide emissions by sector and source (million metric tons, unless otherwise noted)...

  5. Appendix A: Reference case

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

    Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, and the United Kingdom. 3 Other Europe and Eurasia Albania, Armenia, Azerbaijan,...

  6. Appendix A: Reference case

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

    road oil, still gas, special naphthas, petroleum coke, crude oil product supplied, methanol, and miscellaneous petroleum products. 14 Includes energy for combined heat and...

  7. Appendix A: Reference case

    Gasoline and Diesel Fuel Update (EIA)

    energy. See Table A17 for selected nonmarketed residential and commercial renewable energy data. 5 Includes non-biogenic municipal waste, liquid hydrogen, methanol, and some...

  8. Appendix A: Reference case

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

    ... 133.0 147.6 173.1 175.0 178.2 184.2 199.2 1.1% Distributed generation (natural gas) 7 ... 0.0 0.0 1.6 3.3 4.6 6.2 8.9 - -...

  9. Appendix A: Reference case

    Gasoline and Diesel Fuel Update (EIA)

    sources 5 ... 476 459 600 634 660 686 735 1.7% Distributed generation (natural gas) ... 0 0 1 2 2 3 4 - - Total...

  10. Using Wikipedia to forecast disease

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

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

  11. 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 ...

  12. Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX FuturesPrices

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06

    On December 5, 2006, the reference case projections from 'Annual Energy Outlook 2007' (AEO 2007) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past six years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past six years at least, levelized cost comparisons of fixed-price renewable generation with variable-price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are 'biased' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2007. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past six AEO releases (AEO 2001-AEO 2006), we once again find that the AEO 2007 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. Specifically, the NYMEX-AEO 2007 premium is $0.73/MMBtu levelized over five years. In other words, on average, one would have had to pay $0.73/MMBtu more than the AEO 2007 reference case natural gas price forecast in order to lock in natural gas prices over the coming five years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation (or other forms of generation whose costs are not tied to the price of natural gas). Fixed-price generation (like certain forms of renewable generation) obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of five years.

  13. 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

  14. The forecast calls for flu

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

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

  15. Reference Materials

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

    Reference Materials Reference Materials Large Scale Computing and Storage Requirements for Biological and Environmental Research May 7-8, 2009 Invitation Workshop Invitation Letter...

  16. Reference Materials

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

    Reference Materials Reference Materials Large Scale Computing and Storage Requirements for Basic Energy Sciences February 9-10, 2010 Official DOE Invitation Workshop Invitation...

  17. A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part 1. Wind and Turbulence

    SciTech Connect (OSTI)

    Nelson, Matthew A.; Brown, Michael J.; Halverson, Scot A.; Bieringer, Paul E.; Annunzio, Andrew; Bieberbach, George; Meech, Scott

    2015-09-25

    We found that numerical-weather-prediction models are often used to supply the mean wind and turbulence fields for atmospheric transport and dispersion plume models as they provide dense horizontally- and vertically-resolved geographic coverage in comparison to typically sparse monitoring networks. Here, the Weather Research and Forecasting (WRF) model was run over the month-long period of the Joint Urban 2003 field campaign conducted in Oklahoma City and the simulated fields important to transport and dispersion models were compared to measurements from a number of sodars, tower-based sonic anemometers, and balloon soundings located in the greater metropolitan area. Time histories of computed wind speed, wind direction, turbulent kinetic energy (e), friction velocity (u* ), and reciprocal Obukhov length (1 / L) were compared to measurements over the 1-month field campaign. Vertical profiles of wind speed, potential temperature (θ ), and e were compared during short intensive operating periods. The WRF model was typically able to replicate the measured diurnal variation of the wind fields, but with an average absolute wind direction and speed difference of 35° and 1.9 m s-1 , respectively. Then, using the Mellor-Yamada-Janjic (MYJ) surface-layer scheme, the WRF model was found to generally underpredict surface-layer TKE but overpredict u* that was observed above a suburban region of Oklahoma City. The TKE-threshold method used by the WRF model’s MYJ surface-layer scheme to compute the boundary-layer height (h) consistently overestimated h derived from a θ gradient method whether using observed or modelled θ profiles.

  18. A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part 1. Wind and Turbulence

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

    Nelson, Matthew A.; Brown, Michael J.; Halverson, Scot A.; Bieringer, Paul E.; Annunzio, Andrew; Bieberbach, George; Meech, Scott

    2015-09-25

    We found that numerical-weather-prediction models are often used to supply the mean wind and turbulence fields for atmospheric transport and dispersion plume models as they provide dense horizontally- and vertically-resolved geographic coverage in comparison to typically sparse monitoring networks. Here, the Weather Research and Forecasting (WRF) model was run over the month-long period of the Joint Urban 2003 field campaign conducted in Oklahoma City and the simulated fields important to transport and dispersion models were compared to measurements from a number of sodars, tower-based sonic anemometers, and balloon soundings located in the greater metropolitan area. Time histories of computed windmore » speed, wind direction, turbulent kinetic energy (e), friction velocity (u* ), and reciprocal Obukhov length (1 / L) were compared to measurements over the 1-month field campaign. Vertical profiles of wind speed, potential temperature (θ ), and e were compared during short intensive operating periods. The WRF model was typically able to replicate the measured diurnal variation of the wind fields, but with an average absolute wind direction and speed difference of 35° and 1.9 m s-1 , respectively. Then, using the Mellor-Yamada-Janjic (MYJ) surface-layer scheme, the WRF model was found to generally underpredict surface-layer TKE but overpredict u* that was observed above a suburban region of Oklahoma City. The TKE-threshold method used by the WRF model’s MYJ surface-layer scheme to compute the boundary-layer height (h) consistently overestimated h derived from a θ gradient method whether using observed or modelled θ profiles.« less

  19. Reference Materials

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

    Reference Materials Reference Materials Large Scale Computing and Storage Requirements for Basic Energy Sciences February 9-10, 2010 Official DOE Invitation Workshop Invitation Letter from DOE Associate Directors Last edited: 2016-04-29 11:35:05

  20. 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)

  1. Supply Forecast and Analysis (SFA)

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

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

  2. 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.

  3. 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:...

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

    SciTech Connect (OSTI)

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

    2011-12-06

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

  5. Reference Materials

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

    Reference Materials Reference Materials Large Scale Computing and Storage Requirements for Biological and Environmental Research May 7-8, 2009 Invitation Workshop Invitation Letter from DOE Associate Directors Workshop Invitation Letter from DOE ASCR Program Manager Yukiko Sekine Last edited: 2016-04-29 11:34:54

  6. Economic Evaluation of Short-Term Wind Power Forecasts in ERCOT: Preliminary Results; Preprint

    SciTech Connect (OSTI)

    Orwig, K.; Hodge, B. M.; Brinkman, G.; Ela, E.; Milligan, M.; Banunarayanan, V.; Nasir, S.; Freedman, J.

    2012-09-01

    Historically, a number of wind energy integration studies have investigated the value of using day-ahead wind power forecasts for grid operational decisions. These studies have shown that there could be large cost savings gained by grid operators implementing the forecasts in their system operations. To date, none of these studies have investigated the value of shorter-term (0 to 6-hour-ahead) wind power forecasts. In 2010, the Department of Energy and National Oceanic and Atmospheric Administration partnered to fund improvements in short-term wind forecasts and to determine the economic value of these improvements to grid operators, hereafter referred to as the Wind Forecasting Improvement Project (WFIP). In this work, we discuss the preliminary results of the economic benefit analysis portion of the WFIP for the Electric Reliability Council of Texas. The improvements seen in the wind forecasts are examined, then the economic results of a production cost model simulation are analyzed.

  7. 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:...

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

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

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

  9. 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.

  10. Quick Reference

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

    Reference 2015 Annual Planning Summary (APS) User's Guide 1, 2 PART 1 OFFICE Enter the office preparing this APS. NEPA REVIEWS Select one of two responses. SITE-WIDE EISs Select...

  11. 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

  12. Appendix A. Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    Persian Gulf Share of World Production 29% 29% 31% 32% 35% 38% 40% 42% a Crude and lease condensate includes tight oil, shale oil, extra-heavy oil, field condensate, and bitumen. b ...

  13. Appendix A. Reference case projections

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

    Persian Gulf Share of World Production 29% 29% 31% 24% 24% 26% 27% 28% a Crude and lease condensate includes tight oil, shale oil, extra-heavy oil, field condensate, and bitumen. b ...

  14. Appendix A. Reference case projections

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

    Non-OECD Asia 18.4 19.8 26.0 30.4 35.8 41.6 47.4 3.0 China 8.5 9.3 13.0 15.1 18.2 21.3 ... 2025 2030 2035 2040 Non-OECD (continued) China Residential 1.2 1.1 1.0 1.0 1.0 0.9 -1.0 ...

  15. Appendix A. Reference case projections

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

    9.7 15.3 15.2 14.2 13.8 13.5 1.2 Canada 3.4 3.6 3.7 5.4 6.4 7.3 7.8 8.0 2.7 Mexico and Chile 3.0 3.0 3.0 3.1 3.4 3.7 3.9 4.2 1.1 OECD Europe 4.9 4.6 4.3 3.3 3.2 3.2 3.2 3.4 -1.0...

  16. Appendix A. Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    9.7 13.6 12.9 11.7 11.2 10.6 0.4 Canada 3.4 3.6 3.7 4.7 5.1 5.5 5.7 5.8 1.6 Mexico and Chile 3.0 3.0 3.0 2.4 2.0 2.0 2.1 2.2 -1.0 OECD Europe 4.9 4.6 4.3 3.1 2.9 2.5 2.4 2.5 -2.0...

  17. Appendix A: Reference case projections

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

    6 Appendix H Table H10. World installed solar generating capacity by region and country, 2011-40 (gigawatts) Regioncountry History Projections Average annual percent change, ...

  18. Appendix A. Reference case projections

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

    4.3 4.5 4.8 5.1 5.0 1.4 Natural gas plant liquids 3.1 3.3 3.4 4.0 4.2 4.4 4.8 4.7 1.2 Biofuels c 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - Coal-to-liquids 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -...

  19. Appendix A. Reference case projections

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

    4.6 4.9 5.3 5.8 5.9 1.9 Natural gas plant liquids 3.1 3.3 3.4 4.3 4.6 4.9 5.3 5.3 1.6 Biofuels c 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - Coal-to-liquids 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -...

  20. Appendix A: Reference case projections

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

    Japan 251 260 288 316 321 332 337 0.9 South Korea 98 105 126 131 140 160 177 1.9 Australia and New Zealand 86 80 92 109 127 149 177 2.9 Total OECD 3,117 3,131 3,317 3,527 3,771 ...

  1. Appendix A: Reference case projections

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

    41 43 0.5 Japan 22 22 23 23 23 23 23 0.1 South Korea 2 2 2 2 2 2 2 0.3 Australia and New Zealand 13 13 13 14 15 17 19 1.2 Total OECD 361 364 389 400 405 413 436 0.6 Non-OECD ...

  2. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    0.8 1.0 1.0 1.0 1.1 1.1 1.0 OECD Asia 0.8 0.8 0.9 1.1 1.2 1.5 1.7 2.9 Australia and New Zealand 0.6 0.6 0.7 0.9 1.1 1.3 1.5 3.6 Other 0.2 0.2 0.2 0.2 0.2 0.2 0.2 -0.4 Non-OECD ...

  3. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    Japan 33,771 34,382 37,500 39,720 41,754 43,805 45,297 1.0 South Korea 31,272 31,813 38,529 41,320 44,559 48,357 52,905 1.8 Australia and New Zealand 39,986 40,699 44,228 46,433 ...

  4. Appendix A: Reference case projections

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

    Japan 156 17 167 180 175 169 146 7.9 South Korea 148 144 214 258 281 281 281 2.4 Australia and New Zealand 0 0 0 0 0 0 0 - Total OECD 2,053 1,865 2,128 2,208 2,287 2,298 2,246 0.7 ...

  5. Appendix A: Reference case projections

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

    0.1 0.1 0.1 0.1 0.1 0.1 -1.4 South Korea 0.0 0.0 0.0 0.0 0.0 0.0 - Australia and New Zealand 1.8 2.2 2.4 2.6 2.9 3.1 1.9 Total OECD 24.2 20.3 19.5 20.3 19.9 19.9 Non-OECD ...

  6. Appendix A: Reference case projections

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

    270 260 251 242 233 -0.7 South Korea 211 225 235 228 227 236 251 0.4 Australia and New Zealand 165 164 157 154 150 146 146 -0.4 Total OECD 3,369 3,234 3,392 3,404 3,329 3,290 ...

  7. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    Japan 55.9 60.1 53.7 52.6 51.9 51.6 51.8 -0.5 South Korea 56.7 56.1 52.8 50.6 49.5 49.9 50.3 -0.4 Australia and New Zealand 63.8 63.8 59.4 58.4 57.2 55.9 54.6 -0.6 Total OECD 53.4 ...

  8. Appendix A: Reference case projections

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

    0.5 0.4 0.3 0.2 0.2 0.2 -3.0 OECD Asia 0.5 0.5 0.6 0.8 1.0 1.2 1.4 4.1 Australia and New Zealand 0.5 0.5 0.6 0.8 1.0 1.2 1.4 4.1 Other 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -1.2 Non-OECD ...

  9. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    Japan 21.2 20.8 21.7 22.0 21.8 21.6 20.8 0.0 South Korea 11.3 11.4 13.7 14.4 15.0 15.5 15.9 1.2 Australia and New Zealand 6.9 6.8 7.5 7.9 8.3 8.9 9.6 1.2 Total OECD 242.0 238.4 ...

  10. Appendix A: Reference case projections

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

    Japan 127 127 125 123 120 117 114 -0.4 South Korea 49 49 51 52 52 52 52 0.2 Australia and New Zealand 27 27 31 33 36 38 40 1.3 Total OECD 1,235 1,243 1,295 1,323 1,348 1,368 1,384 ...

  11. Appendix A: Reference case projections

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

    1 1 2 2 3 3 3 3.6 Japan 1 1 1 1 1 1 1 0.0 South Korea 0 0 0 0 0 0 0 - Australia and New Zealand 1 1 2 2 2 2 3 4.5 Total OECD 6 6 10 12 14 16 18 3.8 Non-OECD Non-OECD Europe and ...

  12. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    4.3 5.0 5.4 5.5 5.7 5.8 1.1 South Korea 1.7 2.1 2.2 2.4 2.7 3.0 2.1 Australia and New Zealand -0.7 -1.7 -2.2 -2.7 -3.2 -3.8 6.3 Total OECD 13.4 13.7 13.3 12.5 12.1 12.0 -0.4 ...

  13. Appendix A: Reference case projections

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

    1.0 1.0 1.1 1.2 1.0 Liquids from coal 0.2 0.2 0.3 0.4 0.9 1.4 1.9 8.5 Australia and New Zealand 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - China 0.0 0.0 0.1 0.3 0.6 0.9 1.2 13.7 Germany 0.0 ...

  14. Appendix A: Reference case projections

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

    3.1 Japan 23 33 38 44 50 51 51 1.5 South Korea 1 1 17 21 24 26 28 12.0 Australia and New Zealand 4 3 6 6 7 7 9 3.9 Total OECD 270 281 385 432 460 485 522 2.2 Non-OECD Non-OECD ...

  15. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    Japan 537 568 473 452 442 430 411 -1.1 South Korea 248 253 263 264 267 272 280 0.4 Australia and New Zealand 157 160 176 181 184 189 199 0.8 Total OECD 5,792 5,721 5,595 5,513 ...

  16. Appendix A: Reference case projections

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

    Japan 4.9 4.7 4.7 4.6 4.4 4.3 4.1 -0.5 South Korea 7.4 7.3 7.1 6.9 6.6 6.4 6.1 -0.6 Australia and New Zealand 6.4 6.1 5.5 5.2 4.9 4.6 4.5 -1.1 Total OECD 5.5 5.3 4.8 4.4 4.1 3.9 ...

  17. Appendix A: Reference case projections

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

    1,124 1,149 1,149 0.6 South Korea 491 501 628 680 735 794 856 1.9 Australia and New Zealand 284 279 328 364 402 455 530 2.3 Total OECD 10,334 10,248 11,321 11,956 12,625 ...

  18. Appendix A: Reference case projections

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

    Japan 83 86 89 96 97 101 104 0.7 South Korea 26 30 37 37 39 44 49 1.8 Australia and New Zealand 20 21 22 25 29 34 41 2.4 Total OECD 777 799 848 895 963 1,040 1,142 1.3 Non-OECD ...

  19. Appendix A: Reference case projections

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

    17 18 20 22 25 3.9 Japan 3 3 3 3 3 3 3 0.1 South Korea 0 0 1 1 2 2 2 - Australia and New Zealand 6 6 13 14 16 18 20 4.4 Total OECD 42 42 74 90 107 121 135 4.2 Non-OECD Non-OECD ...

  20. Appendix A: Reference case projections

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

    Japan 0.0 0.0 0.0 0.0 0.0 0.0 - South Korea 0.0 0.0 0.0 0.0 0.0 0.0 - Australia and New Zealand 0.3 1.1 1.7 2.3 3.1 4.0 9.6 Total OECD 20.2 27.6 32.5 37.0 42.0 46.5 3.0 Non-OECD ...

  1. Appendix A: Reference case projections

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

    Japan 21.2 20.8 22.1 22.6 22.7 22.6 21.8 0.2 South Korea 11.3 11.4 14.1 14.9 15.6 16.4 17.0 1.4 Australia and New Zealand 6.9 6.8 7.6 8.1 8.5 9.2 10.1 1.4 Total OECD 242.0 238.4 ...

  2. Appendix A: Reference case projections

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

    267 282 295 299 300 295 0.4 South Korea 80 90 124 132 142 150 159 2.1 Australia and New Zealand 71 72 84 89 95 103 115 1.7 Total OECD 2,614 2,691 2,949 3,035 3,152 3,297 3,467 0.9 ...

  3. Appendix A: Reference case projections

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

    Japan 44 44 28 31 30 29 25 -2.0 South Korea 19 21 27 33 36 36 36 2.0 Australia and New Zealand 0 0 0 0 0 0 0 - Total OECD 301 304 287 297 306 306 298 -0.1 Non-OECD Non-OECD ...

  4. Appendix A: Reference case projections

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

    0.8 1.0 1.0 1.0 1.0 1.0 0.7 OECD Asia 0.8 0.8 0.8 0.8 0.7 0.7 0.7 -0.4 Australia and New Zealand 0.6 0.6 0.6 0.6 0.6 0.6 0.5 -0.1 Other 0.2 0.2 0.2 0.2 0.2 0.2 0.2 -1.0 Non-OECD ...

  5. Appendix A: Reference case projections

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

    40 44 7.2 Japan 2 3 3 5 8 8 8 4.1 South Korea 0 0 9 12 16 17 18 13.9 Australia and New Zealand 3 3 11 12 13 15 17 6.2 Total OECD 153 180 320 350 386 444 480 3.6 Non-OECD Non-OECD ...

  6. Appendix A: Reference case projections

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

    Japan 4,299 4,373 4,625 4,761 4,846 4,920 4,896 0.4 South Korea 1,528 1,563 1,934 2,081 2,239 2,405 2,555 1.8 Australia and New Zealand 1,077 1,115 1,365 1,521 1,683 1,884 2,127 ...

  7. Appendix A: Reference case projections

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

    Japan 142 170 49 2 1 1 1 -18.3 South Korea 16 20 17 16 15 14 13 -1.4 Australia and New Zealand 4 4 4 4 4 3 3 -0.6 Total OECD 315 357 208 126 120 115 111 -4.1 Non-OECD Non-OECD ...

  8. Appendix A: Reference case projections

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

    Japan 21.2 20.8 21.3 21.9 21.9 22.0 21.5 0.1 South Korea 11.3 11.4 13.5 14.3 15.1 15.9 16.8 1.4 Australia and New Zealand 6.9 6.8 7.5 8.0 8.4 9.1 10.1 1.4 Total OECD 242.0 238.4 ...

  9. Appendix A: Reference case projections

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

    0.8 1.0 1.0 1.0 1.0 1.1 0.9 OECD Asia 0.8 0.8 0.8 0.8 0.8 0.9 1.0 0.8 Australia and New Zealand 0.6 0.6 0.7 0.6 0.6 0.7 0.8 1.0 Other 0.2 0.2 0.2 0.2 0.2 0.2 0.2 -0.2 Non-OECD ...

  10. Appendix A: Reference case projections

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

    Japan 4.4 4.7 4.0 3.9 3.8 3.7 3.6 -0.9 South Korea 2.3 2.3 2.5 2.5 2.5 2.6 2.7 0.5 Australia and New Zealand 1.2 1.2 1.4 1.4 1.4 1.5 1.5 0.8 Total OECD 46.0 45.5 46.8 46.7 46.9 ...

  11. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    0.1 0.1 0.1 0.1 0.1 0.2 0.1 South Korea 0.0 0.0 0.0 0.0 0.0 0.0 2.2 Australia and New Zealand 2.1 3.3 4.2 5.0 5.9 7.0 4.4 Total OECD 44.4 47.9 52.0 57.4 61.9 66.4 1.4 Non-OECD ...

  12. Appendix A: Reference case projections

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

    0.4 0.3 0.2 0.2 0.2 -3.0 OECD Asia 0.5 0.5 0.5 0.5 0.5 0.4 0.4 -0.3 Australia and New Zealand 0.5 0.5 0.5 0.5 0.5 0.4 0.4 -0.3 Other 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -1.2 Non-OECD ...

  13. Appendix A: Reference case projections

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

    Japan 397 419 415 407 396 382 363 -0.5 South Korea 296 281 345 347 355 371 394 1.2 Australia and New Zealand 199 196 183 180 177 174 176 -0.4 Total OECD 4,100 3,926 4,102 4,126 ...

  14. Appendix A: Reference case projections

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

    118 122 185 205 226 231 231 2.3 South Korea 8 7 52 67 83 90 97 9.8 Australia and New Zealand 60 55 98 106 117 133 155 3.7 Total OECD 2,081 2,168 2,976 3,210 3,412 3,687 3,987 ...

  15. Appendix A: Reference case projections

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

    1.0 1.0 1.0 1.1 0.7 Liquids from coal 0.2 0.2 0.3 0.2 0.3 0.4 0.5 3.4 Australia and New Zealand 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - China 0.0 0.0 0.1 0.2 0.3 0.4 0.5 10.2 Germany 0.0 ...

  16. Appendix A: Reference case projections

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

    153 1.0 Japan 82 75 83 83 83 85 85 0.5 South Korea 5 4 4 4 4 4 5 0.7 Australia and New Zealand 41 37 39 43 47 54 63 1.9 Total OECD 1,374 1,375 1,482 1,532 1,558 1,592 1,696 0.8 ...

  17. Appendix A: Reference case projections

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

    8.2 Japan 4 5 6 13 20 21 21 5.4 South Korea 1 1 27 35 47 51 55 15.8 Australia and New Zealand 8 8 33 35 38 44 51 6.7 Total OECD 334 379 806 910 1,017 1,198 1,310 4.5 Non-OECD ...

  18. Appendix A: Reference case projections

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

    Japan 4.3 4.6 4.5 4.4 4.3 4.2 4.0 -0.5 South Korea 3.2 3.0 3.7 3.8 3.8 4.0 4.3 1.2 Australia and New Zealand 2.1 2.1 2.0 1.9 1.9 1.9 1.9 -0.4 Total OECD 43.6 41.8 43.7 44.0 43.3 ...

  19. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    3.8 Japan 32 33 66 74 82 84 84 3.3 South Korea 3 4 16 21 26 28 30 7.8 Australia and New Zealand 19 20 32 34 37 41 47 3.2 Total OECD 664 721 1,001 1,059 1,122 1,207 1,294 2.1 ...

  20. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    17 167 180 175 169 146 7.9 South Korea 148 144 214 258 281 281 281 2.4 Australia and New Zealand 0 0 0 0 0 0 0 - Total OECD 2,053 1,865 2,127 2,208 2,287 2,298 2,246 0.7 Non-OECD ...

  1. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    89 91 8.4 Japan 5 7 55 62 69 71 71 8.6 South Korea 1 1 4 6 6 7 7 7.0 Australia and New Zealand 1 1 8 8 9 11 12 7.8 Total OECD 61 92 228 247 270 291 324 4.6 Non-OECD Non-OECD ...

  2. Appendix A: Reference case projections

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

    Japan 50 50 49 47 46 44 43 -0.6 South Korea 28 31 39 38 38 39 41 1.0 Australia and New Zealand 31 30 29 28 27 26 26 -0.5 Total OECD 639 637 603 590 577 570 564 -0.4 Non-OECD ...

  3. Appendix A: Reference case projections

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

    45 -1.0 Japan 52 52 49 46 44 42 40 -1.0 South Korea 4 5 4 4 4 4 4 -1.0 Australia and New Zealand 1 2 2 1 1 1 1 -0.6 Total OECD 234 229 210 195 184 175 169 -1.1 Non-OECD Non-OECD ...

  4. Appendix A: Reference case projections

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

    8 10 10 11 4.9 Japan 2 2 2 3 4 4 4 3.5 South Korea 0 0 3 4 4 5 5 10.3 Australia and New Zealand 1 1 1 1 1 2 2 2.2 Total OECD 80 83 112 117 123 128 135 1.7 Non-OECD Non-OECD Europe ...

  5. Appendix A: Reference case projections

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

    387 450 471 507 539 1.3 South Korea 109 105 111 112 128 172 213 2.5 Australia and New Zealand 55 55 69 100 132 173 227 5.2 Total OECD 2,516 2,624 2,618 3,008 3,477 3,957 4,537 ...

  6. Appendix A: Reference case projections

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

    0.5 0.4 0.3 0.2 0.2 0.2 -3.0 OECD Asia 0.5 0.5 0.5 0.5 0.5 0.6 0.6 1.2 Australia and New Zealand 0.5 0.5 0.5 0.5 0.5 0.6 0.6 1.2 Other 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -1.2 Non-OECD ...

  7. Appendix A: Reference case projections

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

    1.0 1.0 1.0 1.0 0.4 Liquids from coal 0.2 0.2 0.3 0.1 0.0 0.0 0.0 - Australia and New Zealand 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - China 0.0 0.0 0.1 0.1 0.0 0.0 0.0 - Germany 0.0 0.0 ...

  8. Appendix A: Reference case projections

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

    Japan 1.6 1.6 2.3 2.5 2.7 2.8 2.7 2.0 South Korea 0.2 0.2 0.7 0.8 1.0 1.1 1.2 7.1 Australia and New Zealand 0.7 0.7 1.2 1.2 1.4 1.5 1.8 3.2 Total OECD 26.3 27.0 35.5 37.9 39.8 42.5 ...

  9. Appendix A: Reference case projections

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

    Japan 4,299 4,373 4,697 4,890 5,032 5,151 5,159 0.6 South Korea 1,528 1,563 1,961 2,134 2,324 2,527 2,703 2.0 Australia and New Zealand 1,077 1,115 1,379 1,552 1,737 1,966 2,247 ...

  10. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    Japan 1,185 1,247 1,176 1,175 1,159 1,144 1,111 -0.4 South Korea 642 639 734 742 761 803 850 1.0 Australia and New Zealand 442 436 451 470 487 513 552 0.8 Total OECD 13,021 12,790 ...

  11. The NEPA reference guide

    SciTech Connect (OSTI)

    Swartz, L.L.; Reinke, D.C.

    1999-10-01

    The NEPA Reference Guide conveniently organizes and indexes National Environmental Policy Act (NEPA) and Council on Environmental Quality (CEQ) regulations and guidance, along with relevant federal case law, all in one place. It allows the user to quickly learn the statutory, regulatory, and case law authority for a large number of NEPA subjects. A unique feature of The NEPA Reference Guide is its detailed index that includes a large number of diverse NEPA subjects. The index enables users to find and compile any statutory, regulatory (including CEQ guidance), and case law original source material and references on virtually any NEPA subject. This will be an especially useful tool for new NEPA practitioners who need to become immersed in a particular subject quickly.

  12. Acquisition Forecast Download | Department of Energy

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

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

  13. Reference Material

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

    Reference Materials There are a variety of reference materials the NSSAB utilizes and have been made available on its website. Documents Fact Sheets - links to Department of Energy Nevada Field Office webpage Public Reading Room NTA Public Reading Facility Open Monday through Friday, 7:30 am to 4:30 pm (except holidays) 755C East Flamingo Road Las Vegas, Nevada 89119 Phone (702) 794-5106 http://www.nv.doe.gov/library/testingarchive.aspx DOE Electronic Database Also available to the public is an

  14. 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.

  15. Poroelastic references

    SciTech Connect (OSTI)

    Christina Morency

    2014-12-12

    This file contains a list of relevant references on the Biot theory (forward and inverse approaches), the double-porosity and dual-permeability theory, and seismic wave propagation in fracture porous media, in RIS format, to approach seismic monitoring in a complex fractured porous medium such as Brady?s Geothermal Field.

  16. Poroelastic references

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

    Christina Morency

    This file contains a list of relevant references on the Biot theory (forward and inverse approaches), the double-porosity and dual-permeability theory, and seismic wave propagation in fracture porous media, in RIS format, to approach seismic monitoring in a complex fractured porous medium such as Brady?s Geothermal Field.

  17. Reference Materials

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

    home page NERSC science requirements workshop page NERSC science requirements case study FAQ Workshop Agenda Previous NERSC Requirements Workshops Biological and...

  18. Reference Materials

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

    home page NERSC science requirements workshop page NERSC science requirements case study FAQ Previous NERSC Requirements Workshops Biological and Environmental Research...

  19. Reference Materials

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

    ID 412- 11/16/2012 - Page 1 Log No 2012-263 Reference Materials * Transporting Radioactive Waste to the Nevada National Security Site fact sheet (ww.nv.energy.gov/library/factsheets/DOENV_990.pdf) - Generators contract with commercial carriers - U.S. Department of Transportation regulations require carriers to select routes which minimize radiological risk * Drivers Route and Shipment Information Questionnaire completed by drivers to document routes taken to the NNSS upon entry into Nevada -

  20. Tracking stochastic resonance curves using an assisted reference model

    SciTech Connect (OSTI)

    Caldern Ramrez, Mario; Rico Martnez, Ramiro; Parmananda, P.

    2015-06-15

    The optimal noise amplitude for Stochastic Resonance (SR) is located employing an Artificial Neural Network (ANN) reference model with a nonlinear predictive capability. A modified Kalman Filter (KF) was coupled to this reference model in order to compensate for semi-quantitative forecast errors. Three manifestations of stochastic resonance, namely, Periodic Stochastic Resonance (PSR), Aperiodic Stochastic Resonance (ASR), and finally Coherence Resonance (CR) were considered. Using noise amplitude as the control parameter, for the case of PSR and ASR, the cross-correlation curve between the sub-threshold input signal and the system response is tracked. However, using the same parameter the Normalized Variance curve is tracked for the case of CR. The goal of the present work is to track these curves and converge to their respective extremal points. The ANN reference model strategy captures and subsequently predicts the nonlinear features of the model system while the KF compensates for the perturbations inherent to the superimposed noise. This technique, implemented in the FitzHugh-Nagumo model, enabled us to track the resonance curves and eventually locate their optimal (extremal) values. This would yield the optimal value of noise for the three manifestations of the SR phenomena.

  1. 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.

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

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

  4. Quick Reference

    Energy Savers [EERE]

    Quick Reference 2016 Annual Planning Summary (APS) User's Guide 1, 2 PART 1 OFFICE Enter the office preparing this APS. NEPA REVIEWS Select one of two responses. SITE-WIDE Select one of three responses. DOCUMENT NUMBER & TITLE Enter the DOE NEPA identification number if available, e.g., DOE/EIS-XXXX. If no document number has been assigned, enter N/A. Also enter the document title. Text is limited to 350 characters. PART 2 TYPE Select the type of document using the dropdown menu. STATUS

  5. 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

  6. 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.

  7. 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

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

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

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

  9. Energy reference handbook. Third edition

    SciTech Connect (OSTI)

    Not Available

    1985-01-01

    The energy field has exploded since the OPEC oil embargo of 1973. Terms that did not even exist several years ago are now being used. In addition, many words have developed interpretations somewhat different from their commonly accepted meanings. The 3rd Edition of the Energy Reference Handbook records and standardizes these terms in a comprehensive glossary. Special emphasis is placed on providing terms and definitions in the area of alternative fuels-synthetics from coal and oil shale; solar; wind; biomass; geothermal; and more - as well as traditional fossil fuels. In total, more than 3,500 terms, key words, and phrases used daily in energy literature are referenced. In addition to these definitions, conversion tables, diagrams, maps, tables, and charts on various aspects of energy which forecast the reserves of fuel resources, plus other information relevant to energy resources and technologies are found in this reference.

  10. Aluminum reference electrode

    DOE Patents [OSTI]

    Sadoway, D.R.

    1988-08-16

    A stable reference electrode is described for use in monitoring and controlling the process of electrolytic reduction of a metal. In the case of Hall cell reduction of aluminum, the reference electrode comprises a pool of molten aluminum and a solution of molten cryolite, Na[sub 3]AlF[sub 6], wherein the electrical connection to the molten aluminum does not contact the highly corrosive molten salt solution. This is accomplished by altering the density of either the aluminum (decreasing the density) or the electrolyte (increasing the density) so that the aluminum floats on top of the molten salt solution. 1 fig.

  11. Aluminum reference electrode

    DOE Patents [OSTI]

    Sadoway, Donald R. (Belmont, MA)

    1988-01-01

    A stable reference electrode for use in monitoring and controlling the process of electrolytic reduction of a metal. In the case of Hall cell reduction of aluminum, the reference electrode comprises a pool of molten aluminum and a solution of molten cryolite, Na.sub.3 AlF.sub.6, wherein the electrical connection to the molten aluminum does not contact the highly corrosive molten salt solution. This is accomplished by altering the density of either the aluminum (decreasing the density) or the electrolyte (increasing the density) so that the aluminum floats on top of the molten salt solution.

  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. 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

  14. NREL: Resource Assessment and Forecasting Home Page

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

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

  15. Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28

    On December 17, 2008, the reference-case projections from Annual Energy Outlook 2009 (AEO 2009) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in mitigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. Note that this memo pertains only to natural gas fuel price risk (i.e., the risk that natural gas prices might differ over the life of a gas-fired generation asset from what was expected when the decision to build the gas-fired unit was made). We do not take into consideration any of the other distinct attributes of gas-fired and renewable generation, such as dispatchability (or lack thereof), differences in capital costs and O&M expenses, or environmental externalities. A comprehensive comparison of different resource types--which is well beyond the scope of this memo--would need to account for differences in all such attributes, including fuel price risk. Furthermore, our analysis focuses solely on natural-gas-fired generation (as opposed to coal-fired or nuclear generation, for example), for several reasons: (1) price volatility has been more of a concern for natural gas than for other fuels used to generate power; (2) for environmental and other reasons, natural gas has, in recent years, been the fuel of choice among power plant developers; and (3) natural gas-fired generators often set the market clearing price in competitive wholesale power markets throughout the United States. That said, a more-complete analysis of how renewables mitigate fuel price risk would also need to consider coal, uranium, and other fuel prices. Finally, we caution readers about drawing inferences or conclusions based solely on this memo in isolation: to place the information contained herein within its proper context, we strongly encourage readers interested in this issue to read through our previous, more-detailed studies, available at http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf.

  16. Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices

    SciTech Connect (OSTI)

    Bolinger, Mark A; Bolinger, Mark; Wiser, Ryan

    2008-01-07

    On December 12, 2007, the reference-case projections from Annual Energy Outlook 2008 (AEO 2008) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in mitigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. Note that this memo pertains only to natural gas fuel price risk (i.e., the risk that natural gas prices might differ over the life of a gas-fired generation asset from what was expected when the decision to build the gas-fired unit was made). We do not take into consideration any of the other distinct attributes of gas-fired and renewable generation, such as dispatchability (or lack thereof) or environmental externalities. A comprehensive comparison of different resource types--which is well beyond the scope of this memo--would need to account for differences in all such attributes, including fuel price risk. Furthermore, our analysis focuses solely on natural-gas-fired generation (as opposed to coal-fired generation, for example), for several reasons: (1) price volatility has been more of a concern for natural gas than for other fuels used to generate power; (2) for environmental and other reasons, natural gas has, in recent years, been the fuel of choice among power plant developers (though its appeal has diminished somewhat as prices have increased); and (3) natural gas-fired generators often set the market clearing price in competitive wholesale power markets throughout the United States. That said, a more-complete analysis of how renewables mitigate fuel price risk would also need to consider coal and other fuel prices. Finally, we caution readers about drawing inferences or conclusions based solely on this memo in isolation: to place the information contained herein within its proper context, we strongly encourage readers interested in this issue to read through our previous, more-detailed studies, available at http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf.

  17. Accounting for fuel price risk: Using forward natural gas prices instead of gas price forecasts to compare renewable to natural gas-fired generation

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-08-13

    Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projected costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards < forecasts) or natural gas-fired generation (if forwards > forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e.g., futures, swaps, and fixed-price physical supply contracts) to contemporaneous forecasts of spot natural gas prices, with the purpose of identifying any systematic differences between the two. Although our data set is quite limited, we find that over the past three years, forward gas prices for durations of 2-10 years have been considerably higher than most natural gas spot price forecasts, including the reference case forecasts developed by the Energy Information Administration (EIA). This difference is striking, and implies that resource planning and modeling exercises based on these forecasts over the past three years have yielded results that are biased in favor of gas-fired generation (again, presuming that long-term stability is desirable). As discussed later, these findings have important ramifications for resource planners, energy modelers, and policy-makers.

  18. 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

  19. Solar Forecast Improvement Project | Department of Energy

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

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

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

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

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

  1. 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...

  2. 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...

  3. 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.

  4. 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 ...

  5. 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 ...

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

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

  9. A Comparison of Model Short-Range Forecasts and the ARM Microbase Data

    Office of Scientific and Technical Information (OSTI)

    Fourth Quarter ARM Science Metric (Technical Report) | SciTech Connect Model Short-Range Forecasts and the ARM Microbase Data Fourth Quarter ARM Science Metric Citation Details In-Document Search Title: A Comparison of Model Short-Range Forecasts and the ARM Microbase Data Fourth Quarter ARM Science Metric For the fourth quarter ARM metric we will make use of new liquid water data that has become available, and called the "Microbase" value added product (referred to as OBS, within

  10. 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.

  11. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

  12. 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.

  13. 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...

  14. 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....

  15. 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...

  16. NREL: Resource Assessment and Forecasting - Research Staff

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

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

  17. 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.

  18. 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.

  19. 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.

  20. Fallout forecasting: 1945-1962

    SciTech Connect (OSTI)

    Kennedy, W.R. Jr.

    1986-03-01

    The delayed hazards of fallout from the detonations of nuclear devices in the atmosphere have always been the concern of those involved in the Test Program. Even before the Trinity Shot (TR-2) of July 16, 1945, many very competent, intelligent scientists and others from all fields of expertise tried their hand at the prediction problems. This resume and collection of parts from reports, memoranda, references, etc., endeavor to chronologically outline prediction methods used operationally in the field during Test Operations of nuclear devices fired into the atmosphere.

  1. Annual Energy Outlook 2011 Reference Case

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

    : Electricity Working Group Meeting 2 October 11, 2012 Electricity Working Group Office of Electricity, Coal, Nuclear, and Renewables Analysis Office of Energy Analysis WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE Key changes from AEO 2012 * Projection extended to 2040 * Representation of Clean Air Interstate Rule (CAIR) after U.S. Court of Appeals vacated Cross-State Air Pollution Rule (CSAPR) * Continued to coordinate with Survey Team

  2. Annual Energy Outlook 2011 Reference Case

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

    Liquid Fuels Markets Working Group Meeting Office of Petroleum, Natural Gas & Biofuels Analysis October 4, 2012 | Washington, DC Preliminary AEO2013: Biofuels and Petroleum WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE Overview 2 Office of Petroleum, Natural Gas, & Biofuels Analysis Working Group Presentation for Discussion Purposes Washington DC, October 4, 2012 DO NOT QUOTE OR CITE as results are subject to change * World oil

  3. Annual Energy Outlook 2011 Reference Case

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

    August 14, 2012 | Washington, DC Annual Energy Outlook 2013: Modeling Updates in the Transportation Sector WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE Overview 2 AEO2013 Transportation Model Updates Washington, D.C., August 2012 Discussion purposes only - Do not cite or circulate * Light-duty vehicle - Light-duty vehicle technology update based on EPA/NHTSA Notice of Proposed Rule for model years 2017 through 2025 * Heavy-duty vehicle

  4. Annual Energy Outlook 2011 Reference Case

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

    Outlook for U.S. Coal and Nuclear Electricity Generation for 2013 EIA Energy Conference June 18, 2013 | Washington, DC by Jim Diefenderfer, Office of Electricity, Coal, Nuclear & Renewables Analysis U. S. Energy Information Administration Over time the electricity mix gradually shifts to lower-carbon options, led by growth in natural gas and renewable generation 2 U.S. electricity net generation trillion kilowatthours Source: EIA, Annual Energy Outlook 2013 25% 19% 42% 13% 1% Nuclear Oil and

  5. High frequency reference electrode

    DOE Patents [OSTI]

    Kronberg, James W.

    1994-01-01

    A high frequency reference electrode for electrochemical experiments comprises a mercury-calomel or silver-silver chloride reference electrode with a layer of platinum around it and a layer of a chemically and electrically resistant material such as TEFLON around the platinum covering all but a small ring or "halo" at the tip of the reference electrode, adjacent to the active portion of the reference electrode. The voltage output of the platinum layer, which serves as a redox electrode, and that of the reference electrode are coupled by a capacitor or a set of capacitors and the coupled output transmitted to a standard laboratory potentiostat. The platinum may be applied by thermal decomposition to the surface of the reference electrode. The electrode provides superior high-frequency response over conventional electrodes.

  6. High frequency reference electrode

    DOE Patents [OSTI]

    Kronberg, J.W.

    1994-05-31

    A high frequency reference electrode for electrochemical experiments comprises a mercury-calomel or silver-silver chloride reference electrode with a layer of platinum around it and a layer of a chemically and electrically resistant material such as TEFLON around the platinum covering all but a small ring or halo' at the tip of the reference electrode, adjacent to the active portion of the reference electrode. The voltage output of the platinum layer, which serves as a redox electrode, and that of the reference electrode are coupled by a capacitor or a set of capacitors and the coupled output transmitted to a standard laboratory potentiostat. The platinum may be applied by thermal decomposition to the surface of the reference electrode. The electrode provides superior high-frequency response over conventional electrodes. 4 figs.

  7. 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 ...

  8. 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...

  9. Optical voltage reference

    DOE Patents [OSTI]

    Rankin, R.; Kotter, D.

    1994-04-26

    An optical voltage reference for providing an alternative to a battery source is described. The optical reference apparatus provides a temperature stable, high precision, isolated voltage reference through the use of optical isolation techniques to eliminate current and impedance coupling errors. Pulse rate frequency modulation is employed to eliminate errors in the optical transmission link while phase-lock feedback is employed to stabilize the frequency to voltage transfer function. 2 figures.

  10. Optical voltage reference

    DOE Patents [OSTI]

    Rankin, Richard; Kotter, Dale

    1994-01-01

    An optical voltage reference for providing an alternative to a battery source. The optical reference apparatus provides a temperature stable, high precision, isolated voltage reference through the use of optical isolation techniques to eliminate current and impedance coupling errors. Pulse rate frequency modulation is employed to eliminate errors in the optical transmission link while phase-lock feedback is employed to stabilize the frequency to voltage transfer function.

  11. 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...

  12. 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

  13. 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.

  14. 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.

  15. 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)

  16. Uncertainty Reduction in Power Generation Forecast Using Coupled

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

  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. Reference Documents | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    Reference Documents Summary References Main Draft SEIS References Additional SEIS References Appendix C References Appendix D References Appendix E References Appendix F References Learn More Summary References Main Draft SEIS References Appendix C References Appendix D References Appendix E References Appendix F References Additional SEIS references

  2. Sandia Energy - Reference Model Documents

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

    Documents Home Stationary Power Energy Conversion Efficiency Water Power Reference Model Project (RMP) Reference Model Documents Reference Model DocumentsTara Camacho-Lopez2015-05-...

  3. Multifunctional reference electrode (Patent) | DOEPatents

    Office of Scientific and Technical Information (OSTI)

    Multifunctional reference electrode Title: Multifunctional reference electrode A multifunctional, low mass reference electrode of a nickel tube, thermocouple means inside the ...

  4. reference | OpenEI Community

    Open Energy Info (EERE)

    reference Home Jweers's picture Submitted by Jweers(88) Contributor 7 August, 2013 - 18:23 New Robust References citation citing developer formatting reference Semantic Mediawiki...

  5. 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.

  6. Value of Information References

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

    Morency, Christina

    This file contains a list of relevant references on value of information (VOI) in RIS format. VOI provides a quantitative analysis to evaluate the outcome of the combined technologies (seismology, hydrology, geodesy) used to monitor Brady's Geothermal Field.

  7. Value of Information References

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

    Morency, Christina

    2014-12-12

    This file contains a list of relevant references on value of information (VOI) in RIS format. VOI provides a quantitative analysis to evaluate the outcome of the combined technologies (seismology, hydrology, geodesy) used to monitor Brady's Geothermal Field.

  8. Precision displacement reference system

    DOE Patents [OSTI]

    Bieg, Lothar F.; Dubois, Robert R.; Strother, Jerry D.

    2000-02-22

    A precision displacement reference system is described, which enables real time accountability over the applied displacement feedback system to precision machine tools, positioning mechanisms, motion devices, and related operations. As independent measurements of tool location is taken by a displacement feedback system, a rotating reference disk compares feedback counts with performed motion. These measurements are compared to characterize and analyze real time mechanical and control performance during operation.

  9. Membrane reference electrode

    DOE Patents [OSTI]

    Redey, Laszlo; Bloom, Ira D.

    1989-01-01

    A reference electrode utilizes a small thin, flat membrane of a highly conductive glass placed on a small diameter insulator tube having a reference material inside in contact with an internal voltage lead. When the sensor is placed in a non-aqueous ionic electrolytic solution, the concentration difference across the glass membrane generates a low voltage signal in precise relationship to the concentration of the species to be measured with high spatial resolution.

  10. Membrane reference electrode

    DOE Patents [OSTI]

    Redey, L.; Bloom, I.D.

    1988-01-21

    A reference electrode utilizes a small thin, flat membrane of a highly conductive glass placed on a small diameter insulator tube having a reference material inside in contact with an internal voltage lead. When the sensor is placed in a non-aqueous ionic electrolytic solution, the concentration difference across the glass membrane generates a low voltage signal in precise relationship to the concentration of the species to be measured, with high spatial resolution. 2 figs.

  11. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

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

    2014-12-30

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

  12. 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

  13. 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.

  14. 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.

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

    SciTech Connect (OSTI)

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

    2015-08-05

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

  16. Multifunctional reference electrode

    DOE Patents [OSTI]

    Redey, Laszlo; Vissers, Donald R.

    1983-01-01

    A multifunctional, low mass reference electrode of a nickel tube, thermocouple means inside the nickel tube electrically insulated therefrom for measuring the temperature thereof, a housing surrounding the nickel tube, an electrolyte having a fixed sulfide ion activity between the housing and the outer surface of the nickel tube forming the nickel/nickel sulfide/sulfide half-cell. An ion diffusion barrier is associated with the housing in contact with the electrolyte. Also disclosed is a cell using the reference electrode to measure characteristics of a working electrode.

  17. Multifunctional reference electrode

    DOE Patents [OSTI]

    Redey, L.; Vissers, D.R.

    1981-12-30

    A multifunctional, low mass reference electrode of a nickel tube, thermocouple means inside the nickel tube electrically insulated therefrom for measuring the temperature thereof, a housing surrounding the nickel tube, an electrolyte having a fixed sulfide ion activity between the housing and the outer surface of the nickel tube forming the nickel/nickel sulfide/sulfide half-cell are described. An ion diffusion barrier is associated with the housing in contact with the electrolyte. Also disclosed is a cell using the reference electrode to measure characteristics of a working electrode.

  18. 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.

  19. Reference Model Development

    SciTech Connect (OSTI)

    Jepsen, Richard

    2011-11-02

    Presentation from the 2011 Water Peer Review in which principal investigator discusses project progress to develop a representative set of Reference Models (RM) for the MHK industry to develop baseline cost of energy (COE) and evaluate key cost component/system reduction pathways.

  20. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

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

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

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

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

  5. 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.

  6. 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

  9. 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.

  10. 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, ...

  11. 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...

  12. 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...

  13. 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.

  14. OSH technical reference manual

    SciTech Connect (OSTI)

    Not Available

    1993-11-01

    In an evaluation of the Department of Energy (DOE) Occupational Safety and Health programs for government-owned contractor-operated (GOCO) activities, the Department of Labor`s Occupational Safety and Health Administration (OSHA) recommended a technical information exchange program. The intent was to share written safety and health programs, plans, training manuals, and materials within the entire DOE community. The OSH Technical Reference (OTR) helps support the secretary`s response to the OSHA finding by providing a one-stop resource and referral for technical information that relates to safe operations and practice. It also serves as a technical information exchange tool to reference DOE-wide materials pertinent to specific safety topics and, with some modification, as a training aid. The OTR bridges the gap between general safety documents and very specific requirements documents. It is tailored to the DOE community and incorporates DOE field experience.

  15. EFRC Management Reference Document

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

    EFRC management reference document Energy Frontier Research Centers Acknowledgments of Support (v.1, October 2009) Office of Basic Energy Sciences Office of Science US Department of Energy How to Acknowledge Basic Energy Sciences-Energy Frontier Research Center (BES-EFRC) funding in papers, presentations, and other materials: For a publication on work supported wholly under your EFRC, the acknowledgement should at a minimum state that "This material is based upon work supported as part of

  16. Alignment reference device

    DOE Patents [OSTI]

    Patton, Gail Y.; Torgerson, Darrel D.

    1987-01-01

    An alignment reference device provides a collimated laser beam that minimizes angular deviations therein. A laser beam source outputs the beam into a single mode optical fiber. The output end of the optical fiber acts as a source of radiant energy and is positioned at the focal point of a lens system where the focal point is positioned within the lens. The output beam reflects off a mirror back to the lens that produces a collimated beam.

  17. Reference Model Project (RMP)

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

    Reference Model Project (RMP) - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Fuel Cycle Defense Waste Management Programs

  18. Coal Data: A reference

    SciTech Connect (OSTI)

    Not Available

    1991-11-26

    The purpose of Coal Data: A Reference is to provide basic information on the mining and use of coal, an important source of energy in the United States. The report is written for a general audience. The goal is to cover basic material and strike a reasonable compromise between overly generalized statements and detailed analyses. The section ``Coal Terminology and Related Information`` provides additional information about terms mentioned in the text and introduces new terms. Topics covered are US coal deposits, resources and reserves, mining, production, employment and productivity, health and safety, preparation, transportation, supply and stocks, use, coal, the environment, and more. (VC)

  19. STEP Intern Reference Check Sheet

    Broader source: Energy.gov [DOE]

    STEP Intern Reference Check Sheet, from the Tool Kit Framework: Small Town University Energy Program (STEP).

  20. 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.

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

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

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

  2. Coal data: A reference

    SciTech Connect (OSTI)

    Not Available

    1995-02-01

    This report, Coal Data: A Reference, summarizes basic information on the mining and use of coal, an important source of energy in the US. This report is written for a general audience. The goal is to cover basic material and strike a reasonable compromise between overly generalized statements and detailed analyses. The section ``Supplemental Figures and Tables`` contains statistics, graphs, maps, and other illustrations that show trends, patterns, geographic locations, and similar coal-related information. The section ``Coal Terminology and Related Information`` provides additional information about terms mentioned in the text and introduces some new terms. The last edition of Coal Data: A Reference was published in 1991. The present edition contains updated data as well as expanded reviews and additional information. Added to the text are discussions of coal quality, coal prices, unions, and strikes. The appendix has been expanded to provide statistics on a variety of additional topics, such as: trends in coal production and royalties from Federal and Indian coal leases, hours worked and earnings for coal mine employment, railroad coal shipments and revenues, waterborne coal traffic, coal export loading terminals, utility coal combustion byproducts, and trace elements in coal. The information in this report has been gleaned mainly from the sources in the bibliography. The reader interested in going beyond the scope of this report should consult these sources. The statistics are largely from reports published by the Energy Information Administration.

  3. 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.

  4. 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...

  5. Long life reference electrode

    DOE Patents [OSTI]

    Yonco, R.M.; Nagy, Z.

    1989-04-04

    An external, reference electrode is provided for long term use with a high temperature, high pressure system. The electrode is arranged in a vertical, electrically insulative tube with an upper portion serving as an electrolyte reservoir and a lower portion in electrolytic communication with the system to be monitored. The lower end portion includes a flow restriction such as a porous plug to limit the electrolyte release into the system. A piston equalized to the system pressure is fitted into the upper portion of the tube to impart a small incremental pressure to the electrolyte. The piston is selected of suitable size and weight to cause only a slight flow of electrolyte through the porous plug into the high pressure system. This prevents contamination of the electrolyte but is of such small flow rate that operating intervals of a month or more can be achieved. 2 figs.

  6. Long life reference electrode

    DOE Patents [OSTI]

    Yonco, Robert M.; Nagy, Zoltan

    1989-01-01

    An external, reference electrode is provided for long term use with a high temperature, high pressure system. The electrode is arranged in a vertical, electrically insulative tube with an upper portion serving as an electrolyte reservior and a lower portion in electrolytic communication with the system to be monitored. The lower end portion includes a flow restriction such as a porous plug to limit the electrolyte release into the system. A piston equalized to the system pressure is fitted into the upper portion of the tube to impart a small incremental pressure to the electrolyte. The piston is selected of suitable size and weight to cause only a slight flow of electrolyte through the porous plug into the high pressure system. This prevents contamination of the electrolyte but is of such small flow rate that operating intervals of a month or more can be achieved.

  7. Long life reference electrode

    DOE Patents [OSTI]

    Yonco, R.M.; Nagy, Z.

    1987-07-30

    An external, reference electrode is provided for long term use with a high temperature, high pressure system. The electrode is arranged in a vertical, electrically insulative tube with an upper portion serving as an electrolyte reservoir and a lower portion in electrolytic communication with the system to be monitored. The lower end portion includes a flow restriction such as a porous plug to limit the electrolyte release into the system. A piston equalized to the system pressure is fitted into the upper portion of the tube to impart a small incremental pressure to the electrolyte. The piston is selected of suitable size and weight to cause only a slight flow of electrolyte through the porous plug into the high pressure system. This prevents contamination of the electrolyte but is of such small flow rate that operating intervals of a month or more can be achieved. 2 figs.

  8. 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.

  9. 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.

  10. 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 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. The range is primarily due to uncertainties associated with the Tank Waste Remediation System (TWRS) program, including uncertainties regarding retrieval of long-length equipment, scheduling, and tank retrieval technologies.

  11. Sensor Characteristics Reference Guide

    SciTech Connect (OSTI)

    Cree, Johnathan V.; Dansu, A.; Fuhr, P.; Lanzisera, Steven M.; McIntyre, T.; Muehleisen, Ralph T.; Starke, M.; Banerjee, Pranab; Kuruganti, T.; Castello, C.

    2013-04-01

    The Buildings Technologies Office (BTO), within the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), is initiating a new program in Sensor and Controls. The vision of this program is: • Buildings operating automatically and continuously at peak energy efficiency over their lifetimes and interoperating effectively with the electric power grid. • Buildings that are self-configuring, self-commissioning, self-learning, self-diagnosing, self-healing, and self-transacting to enable continuous peak performance. • Lower overall building operating costs and higher asset valuation. The overarching goal is to capture 30% energy savings by enhanced management of energy consuming assets and systems through development of cost-effective sensors and controls. One step in achieving this vision is the publication of this Sensor Characteristics Reference Guide. The purpose of the guide is to inform building owners and operators of the current status, capabilities, and limitations of sensor technologies. It is hoped that this guide will aid in the design and procurement process and result in successful implementation of building sensor and control systems. DOE will also use this guide to identify research priorities, develop future specifications for potential market adoption, and provide market clarity through unbiased information

  12. Attachment F- Bibliography and References

    Broader source: Energy.gov [DOE]

    These documents are listed in Attachment F - Bibliography and References section of the Phase 2 Radiological Release Accident Investigation Report.

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

    Broader source: Energy.gov [DOE]

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

  14. Solar Trackers Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

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

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

    Reports and Publications (EIA)

    2003-01-01

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

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

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

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

  18. 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.

  19. 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.

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

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

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

  1. 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.

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

    Office of Scientific and Technical Information (OSTI)

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

  3. 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...

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

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

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

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

    Office of Environmental Management (EM)

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

  6. Modeling and forecasting the distribution of Vibrio vulnificus in

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Energy Savers [EERE]

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

  9. 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National

    Office of Scientific and Technical Information (OSTI)

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

  10. 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

  11. Capillary reference half-cell

    DOE Patents [OSTI]

    Hall, Stephen H.

    1996-01-01

    The present invention is a reference half-cell electrode wherein intermingling of test fluid with reference fluid does not affect the performance of the reference half-cell over a long time. This intermingling reference half-cell may be used as a single or double junction submersible or surface reference electrode. The intermingling reference half-cell relies on a capillary tube having a first end open to reference fluid and a second end open to test fluid wherein the small diameter of the capillary tube limits free motion of fluid within the capillary to diffusion. The electrode is placed near the first end of the capillary in contact with the reference fluid. The method of operation of the present invention begins with filling the capillary tube with a reference solution. After closing the first end of the capillary, the capillary tube may be fully submerged or partially submerged with the second open end inserted into test fluid. Since the electrode is placed near the first end of the capillary, and since the test fluid may intermingle with the reference fluid through the second open end only by diffusion, this intermingling capillary reference half-cell provides a stable voltage potential for long time periods.

  12. Capillary reference half-cell

    DOE Patents [OSTI]

    Hall, S.H.

    1996-02-13

    The present invention is a reference half-cell electrode wherein intermingling of test fluid with reference fluid does not affect the performance of the reference half-cell over a long time. This intermingling reference half-cell may be used as a single or double junction submersible or surface reference electrode. The intermingling reference half-cell relies on a capillary tube having a first end open to reference fluid and a second end open to test fluid wherein the small diameter of the capillary tube limits free motion of fluid within the capillary to diffusion. The electrode is placed near the first end of the capillary in contact with the reference fluid. The method of operation of the present invention begins with filling the capillary tube with a reference solution. After closing the first end of the capillary, the capillary tube may be fully submerged or partially submerged with the second open end inserted into test fluid. Since the electrode is placed near the first end of the capillary, and since the test fluid may intermingle with the reference fluid through the second open end only by diffusion, this intermingling capillary reference half-cell provides a stable voltage potential for long time periods. 11 figs.

  13. Introduction to the BTO Goals Framework

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

    uses - EUI trends regularly reported and forecast by EIA * Tiered Goals: - Building Sector ... All numbers are relative to the 2015 AEO Reference Case Forecast. 11 Are BTO's Goals ...

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

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

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

  15. Climatic Forecasting of Net Infiltration at Yucca Montain Using Analogue Meteororological Data

    SciTech Connect (OSTI)

    B. Faybishenko

    2006-09-11

    At Yucca Mountain, Nevada, future changes in climatic conditions will most likely alter net infiltration, or the drainage below the bottom of the evapotranspiration zone within the soil profile or flow across the interface between soil and the densely welded part of the Tiva Canyon Tuff. The objectives of this paper are to: (a) develop a semi-empirical model and forecast average net infiltration rates, using the limited meteorological data from analogue meteorological stations, for interglacial (present day), and future monsoon, glacial transition, and glacial climates over the Yucca Mountain region, and (b) corroborate the computed net-infiltration rates by comparing them with the empirically and numerically determined groundwater recharge and percolation rates through the unsaturated zone from published data. In this paper, the author presents an approach for calculations of net infiltration, aridity, and precipitation-effectiveness indices, using a modified Budyko's water-balance model, with reference-surface potential evapotranspiration determined from the radiation-based Penman (1948) formula. Results of calculations show that net infiltration rates are expected to generally increase from the present-day climate to monsoon climate, to glacial transition climate, and then to the glacial climate. The forecasting results indicate the overlap between the ranges of net infiltration for different climates. For example, the mean glacial net-infiltration rate corresponds to the upper-bound glacial transition net infiltration, and the lower-bound glacial net infiltration corresponds to the glacial transition mean net infiltration. Forecasting of net infiltration for different climate states is subject to numerous uncertainties-associated with selecting climate analogue sites, using relatively short analogue meteorological records, neglecting the effects of vegetation and surface runoff and runon on a local scale, as well as possible anthropogenic climate changes.

  16. A 24-h forecast of solar irradiance using artificial neural network: Application for performance prediction of a grid-connected PV plant at Trieste, Italy

    SciTech Connect (OSTI)

    Mellit, Adel; Pavan, Alessandro Massi

    2010-05-15

    Forecasting of solar irradiance is in general significant for planning the operations of power plants which convert renewable energies into electricity. In particular, the possibility to predict the solar irradiance (up to 24 h or even more) can became - with reference to the Grid Connected Photovoltaic Plants (GCPV) - fundamental in making power dispatching plans and - with reference to stand alone and hybrid systems - also a useful reference for improving the control algorithms of charge controllers. In this paper, a practical method for solar irradiance forecast using artificial neural network (ANN) is presented. The proposed Multilayer Perceptron MLP-model makes it possible to forecast the solar irradiance on a base of 24 h using the present values of the mean daily solar irradiance and air temperature. An experimental database of solar irradiance and air temperature data (from July 1st 2008 to May 23rd 2009 and from November 23rd 2009 to January 24th 2010) has been used. The database has been collected in Trieste (latitude 45 40'N, longitude 13 46'E), Italy. In order to check the generalization capability of the MLP-forecaster, a K-fold cross-validation was carried out. The results indicate that the proposed model performs well, while the correlation coefficient is in the range 98-99% for sunny days and 94-96% for cloudy days. As an application, the comparison between the forecasted one and the energy produced by the GCPV plant installed on the rooftop of the municipality of Trieste shows the goodness of the proposed model. (author)

  17. Optical probe with reference fiber

    DOE Patents [OSTI]

    Da Silva, Luiz B.; Chase, Charles L.

    2006-03-14

    A system for characterizing tissue includes the steps of generating an emission signal, generating a reference signal, directing the emission signal to and from the tissue, directing the reference signal in a predetermined manner relative to the emission signal, and using the reference signal to compensate the emission signal. In one embodiment compensation is provided for fluctuations in light delivery to the tip of the probe due to cable motion.

  18. Reference Documents | Department of Energy

    Energy Savers [EERE]

    Reference Documents Reference Documents The following are reference documents utilized by CNS staff to perform its functions. Understanding Process Plant Schedule Slippage and Startup Costs A Review of Cost Estimation in New Technologies - Implications for Energy Process Plants Understanding Cost Growth and Performance Shortfalls in Pioneer Process Plants Pioneer Plants Study User's Manual The Formation of Pioneer Plant Projects in Chemical Processing Firms Industry Information Practices and the

  19. References | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    References U.S. Department of Energy / U.S. Nuclear Regulatory Commission Nuclear Materials Management & Safeguards System References Additional information related to the NMMSS may be located in the publications listed below. By referencing these documents, a more extensive understanding of the system may be gained. Other references extracted from DOE M 470.4-6 and used within the industry have also been included. "Agreement between the United States of America and the IAEA for the

  20. Desk Reference | Department of Energy

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

    forms of compensation for overtime work and to assist in advising and training ... Operational Plan and Desktop Reference for the Disability Employment Program The ...

  1. FAQS Reference Guide- Chemical Processing

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the February 2010 edition of DOE-STD-1176-2010, Chemical Processing Functional Area Qualification Standard.

  2. Archived Reference Building Type: Warehouse

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  3. Archived Reference Building Type: Warehouse

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  4. Archived Reference Building Type: Hospital

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  5. Archived Reference Building Type: Hospital

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  6. 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.

  7. Forecasting the response of Earth's surface to future climatic and land use changes: A review of methods and research needs

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

    Pelletier, Jon D.; Murray, A. Brad; Pierce, Jennifer L.; Bierman, Paul R.; Breshears, David D.; Crosby, Benjamin T.; Ellis, Michael; Foufoula-Georgiou, Efi; Heimsath, Arjun M.; Houser, Chris; et al

    2015-07-14

    In the future, Earth will be warmer, precipitation events will be more extreme, global mean sea level will rise, and many arid and semiarid regions will be drier. Human modifications of landscapes will also occur at an accelerated rate as developed areas increase in size and population density. We now have gridded global forecasts, being continually improved, of the climatic and land use changes (C&LUC) that are likely to occur in the coming decades. However, besides a few exceptions, consensus forecasts do not exist for how these C&LUC will likely impact Earth-surface processes and hazards. In some cases, we havemore » the tools to forecast the geomorphic responses to likely future C&LUC. Fully exploiting these models and utilizing these tools will require close collaboration among Earth-surface scientists and Earth-system modelers. This paper assesses the state-of-the-art tools and data that are being used or could be used to forecast changes in the state of Earth's surface as a result of likely future C&LUC. We also propose strategies for filling key knowledge gaps, emphasizing where additional basic research and/or collaboration across disciplines are necessary. The main body of the paper addresses cross-cutting issues, including the importance of nonlinear/threshold-dominated interactions among topography, vegetation, and sediment transport, as well as the importance of alternate stable states and extreme, rare events for understanding and forecasting Earth-surface response to C&LUC. Five supplements delve into different scales or process zones (global-scale assessments and fluvial, aeolian, glacial/periglacial, and coastal process zones) in detail.« less

  8. Forecasting the response of Earth's surface to future climatic and land use changes: A review of methods and research needs

    SciTech Connect (OSTI)

    Pelletier, Jon D.; Murray, A. Brad; Pierce, Jennifer L.; Bierman, Paul R.; Breshears, David D.; Crosby, Benjamin T.; Ellis, Michael; Foufoula-Georgiou, Efi; Heimsath, Arjun M.; Houser, Chris; Lancaster, Nick; Marani, Marco; Merritts, Dorothy J.; Moore, Laura J.; Pederson, Joel L.; Poulos, Michael J.; Rittenour, Tammy M.; Rowland, Joel C.; Ruggiero, Peter; Ward, Dylan J.; Wickert, Andrew D.; Yager, Elowyn M.

    2015-07-14

    In the future, Earth will be warmer, precipitation events will be more extreme, global mean sea level will rise, and many arid and semiarid regions will be drier. Human modifications of landscapes will also occur at an accelerated rate as developed areas increase in size and population density. We now have gridded global forecasts, being continually improved, of the climatic and land use changes (C&LUC) that are likely to occur in the coming decades. However, besides a few exceptions, consensus forecasts do not exist for how these C&LUC will likely impact Earth-surface processes and hazards. In some cases, we have the tools to forecast the geomorphic responses to likely future C&LUC. Fully exploiting these models and utilizing these tools will require close collaboration among Earth-surface scientists and Earth-system modelers. This paper assesses the state-of-the-art tools and data that are being used or could be used to forecast changes in the state of Earth's surface as a result of likely future C&LUC. We also propose strategies for filling key knowledge gaps, emphasizing where additional basic research and/or collaboration across disciplines are necessary. The main body of the paper addresses cross-cutting issues, including the importance of nonlinear/threshold-dominated interactions among topography, vegetation, and sediment transport, as well as the importance of alternate stable states and extreme, rare events for understanding and forecasting Earth-surface response to C&LUC. Five supplements delve into different scales or process zones (global-scale assessments and fluvial, aeolian, glacial/periglacial, and coastal process zones) in detail.

  9. 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.

  10. 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.

  11. 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 wind speed and vertical temperature difference. Ideally, the data assimilation scheme used in the experiments would have been based upon an ensemble Kalman filter (EnKF) that was similar to the ESA method used to diagnose the Mid-Colombia Basin sensitivity patterns in the previous studies. However, the use of an EnKF system at high resolution is impractical because of the very high computational cost. Thus, it was decided to use the three-dimensional variational analysis data assimilation that is less computationally intensive and more economically practical for generating operational forecasts. There are two tasks in the current project effort designed to validate the ESA observational system deployment approach in order to move closer to the overall goal: (1) Perform an Observing System Experiment (OSE) using a data denial approach which is the focus of this task and report; and (2) Conduct a set of Observing System Simulation Experiments (OSSE) for the Mid-Colombia basin region. The results of this task are presented in a separate report. The objective of the OSE task involves validating the ESA-MOOA results from the previous sensitivity studies for the Mid-Columbia Basin by testing the impact of existing meteorological tower measurements on the 0- to 6-hour ahead 80-m wind forecasts at the target locations. The testing of the ESA-MOOA method used a combination of data assimilation techniques and data denial experiments to accomplish the task objective.

  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. 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).

  14. REFERENCES

    Energy Savers [EERE]

    OFFICE OF MANAGEMENT AND BUDGET (OMB) CIRCULARS. Located ...ombmemorandadefault 5. DOE ORDERS, MANUALS, NOTICES, ... 5-8-01. 6. OTHER a. 32 CFR 2001.23, Classification Marking ...

  15. NPS Quick Reference Guide | Open Energy Information

    Open Energy Info (EERE)

    Quick Reference Guide Jump to: navigation, search OpenEI Reference LibraryAdd to library Legal Document- OtherOther: NPS Quick Reference GuideLegal Abstract NPS Quick Reference...

  16. Safeguards and Security Program References

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    2005-08-26

    The manual establishes definitions for terms related to the Department of Energy Safeguards and Security (S&S) Program and includes lists of references and acronyms/abbreviations applicable to S&S Program directives. Cancels the Safeguards and Security Glossary of Terms, dated 12-18-95. Current Safeguards and Security Program References can also be found at Safeguards and Security Policy Information Resource (http://pir.pnl.gov/)

  17. 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...

  18. 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.

  19. 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.

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

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

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

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

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

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

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

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

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

  3. 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.

  4. 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.

  5. 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.

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

    Energy Science and Technology Software Center (OSTI)

    2012-05-01

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

  7. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

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

    2011-11-29

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

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

    SciTech Connect (OSTI)

    Das, S.

    1991-12-01

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

  9. A hybrid procedure for MSW generation forecasting at multiple time scales in Xiamen City, China

    SciTech Connect (OSTI)

    Xu, Lilai; Gao, Peiqing; Cui, Shenghui; Liu, Chun

    2013-06-15

    Highlights: ► We propose a hybrid model that combines seasonal SARIMA model and grey system theory. ► The model is robust at multiple time scales with the anticipated accuracy. ► At month-scale, the SARIMA model shows good representation for monthly MSW generation. ► At medium-term time scale, grey relational analysis could yield the MSW generation. ► At long-term time scale, GM (1, 1) provides a basic scenario of MSW generation. - Abstract: Accurate forecasting of municipal solid waste (MSW) generation is crucial and fundamental for the planning, operation and optimization of any MSW management system. Comprehensive information on waste generation for month-scale, medium-term and long-term time scales is especially needed, considering the necessity of MSW management upgrade facing many developing countries. Several existing models are available but of little use in forecasting MSW generation at multiple time scales. The goal of this study is to propose a hybrid model that combines the seasonal autoregressive integrated moving average (SARIMA) model and grey system theory to forecast MSW generation at multiple time scales without needing to consider other variables such as demographics and socioeconomic factors. To demonstrate its applicability, a case study of Xiamen City, China was performed. Results show that the model is robust enough to fit and forecast seasonal and annual dynamics of MSW generation at month-scale, medium- and long-term time scales with the desired accuracy. In the month-scale, MSW generation in Xiamen City will peak at 132.2 thousand tonnes in July 2015 – 1.5 times the volume in July 2010. In the medium term, annual MSW generation will increase to 1518.1 thousand tonnes by 2015 at an average growth rate of 10%. In the long term, a large volume of MSW will be output annually and will increase to 2486.3 thousand tonnes by 2020 – 2.5 times the value for 2010. The hybrid model proposed in this paper can enable decision makers to develop integrated policies and measures for waste management over the long term.

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

    Broader source: Energy.gov [DOE]

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  12. CASE Design/Remodeling | Open Energy Information

    Open Energy Info (EERE)

    DesignRemodeling Jump to: navigation, search Name: CASE DesignRemodeling Place: Bethesda, MD Website: www.casedesignremodeling.com References: CASE DesignRemodeling1...

  13. Document Number Q0029500 References

    Office of Legacy Management (LM)

    References 7.0 References 10 CFR 1021. U.S. Department of Energy, "National Environmental Policy Act Implementing Procedures," Code of Federal Regzilations, January 1,2003. 10 CFR 1022. U.S. Department of Energy, "Compliance with Floodplain/Wetlands Environmental Review Requirements," Code ofFederal Regulations, January 1,2003. 33 CFR 323. Corps of Engineers, Department of the Army, "Permits for Discharges of Dredged or Fill Material Into Waters of the United

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

    SciTech Connect (OSTI)

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

    2010-01-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. Currently, uncertainties associated with wind and load forecasts, as well as uncertainties associated with random generator outages and unexpected disconnection of supply lines, are not taken into account in power grid operation. Thus, operators have little means to weigh the likelihood and magnitude of upcoming events of power imbalance. In this project, funded by the U.S. Department of Energy (DOE), a framework has been developed for incorporating uncertainties associated with wind and load forecast errors, unpredicted ramps, and forced generation disconnections into the energy management system (EMS) as well as generation dispatch and commitment applications. A new approach to evaluate the uncertainty ranges for the required generation performance envelope including balancing capacity, ramping capability, and ramp duration has been proposed. The approach includes three stages: forecast and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence levels. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis, incorporating all sources of uncertainties of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the flying brick technique has been developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation algorithm has been developed to validate the accuracy of the confidence intervals.

  15. Draft SPD Supplemental EIS Master Reference List | National Nuclear

    National Nuclear Security Administration (NNSA)

    Security Administration Draft SPD Supplemental EIS Master Reference List References for Chapters 1 - 5 References for Appendix A References for Appendix B References for Appendix C References for Appendix D References for Appendix E References for Appendix F References for Appendix G References for Appendix H References for Appendix I References for Appendix J References for Summary Learn More SPD SEIS References for Appendix J SPD SEIS Summary References SPD SEIS References for Chapters 1 -

  16. Annual Energy Outlook 2013 Early Release Reference Case

    Gasoline and Diesel Fuel Update (EIA)

    : Electricity Working Group Meeting 2 October 11, 2012 Electricity Working Group Office of Electricity, Coal, Nuclear, and Renewables Analysis Office of Energy Analysis WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE Key changes from AEO 2012 * Projection extended to 2040 * Representation of Clean Air Interstate Rule (CAIR) after U.S. Court of Appeals vacated Cross-State Air Pollution Rule (CSAPR) * Continued to coordinate with Survey Team

  17. Annual Energy Outlook 2013 Early Release Reference Case

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

    energy markets For Cheung Kong Graduate School of Business July 29, 2015 | Beijing, China by Adam Sieminski, Administrator U.S. Energy Information Administration International...

  18. Annual Energy Outlook 2013 Early Release Reference Case

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

    : Focus on the Electricity Supply Mix for Natural Gas Power Generation US May 18, 2015 | Philadelphia, Pennsylvania by Howard Gruenspecht, Deputy Administrator U.S. Energy...

  19. Annual Energy Outlook 2013 Early Release Reference Case

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

    (CO, WY) Haynesville Utica (OH, PA & WV) Marcellus (PA,WV,OH & NY) Woodford (OK) Granite Wash (OK & TX) Austin Chalk (LA & TX) Monterey (CA) U.S. tight oil production...

  20. Annual Energy Outlook 2013 Early Release Reference Case

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

    price per barrel (real 2010 dollars) Sources: U.S. Energy Information Administration, Thomson Reuters Prices shown are quarterly averages: dashed lines are EIA projections...

  1. Annual Energy Outlook 2013 Early Release Reference Case

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

    resource and technology scenario (a key driver of domestic gas prices); global energy market prices (which along with domestic prices defines the "gap" that determines the...

  2. Annual Energy Outlook 2013 Early Release Reference Case

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

    Gov't deficits, high reliance on oil revenue, and asset coverage of gov't spending are indicators of geopolitical stress exposure more risk less risk more risk less risk 7...

  3. Appendix E References | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    E References Crosswalk of Appendix E References to Main DSEIS Reference File name (Main DSEIS) or file name in Appendix E folder DOE (U.S. Department of Energy) 1999. Final ...

  4. Category:Buildings References | Open Energy Information

    Open Energy Info (EERE)

    Buildings References Jump to: navigation, search Add a new Reference Pages in category "Buildings References" The following 16 pages are in this category, out of 16 total. B Bureau...

  5. Category:Water References | Open Energy Information

    Open Energy Info (EERE)

    Water References Jump to: navigation, search Add a new Reference Pages in category "Water References" The following 22 pages are in this category, out of 22 total. A Alaska AS...

  6. Category:Hydrogen References | Open Energy Information

    Open Energy Info (EERE)

    Hydrogen References Jump to: navigation, search Add a new Reference Pages in category "Hydrogen References" The following 6 pages are in this category, out of 6 total. F FERC Order...

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

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

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

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

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

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

  9. 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.

  10. Towards a Science of Tumor Forecast for Clinical Oncology

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

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

    We propose that the quantitative cancer biology community make a concerted effort to apply the methods of weather forecasting to develop an analogous theory for predicting tumor growth and treatment response. Currently, the time course of response is not predicted, but rather assessed post hoc by physical exam or imaging methods. This fundamental limitation of clinical oncology makes it extraordinarily difficult to select an optimal treatment regimen for a particular tumor of an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoplymore » of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. With a successful theory of tumor forecasting, it should be possible to integrate large tumor specific datasets of varied types, and effectively defeat cancer one patient at a time.« less

  11. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect (OSTI)

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

    We propose that the quantitative cancer biology community make a concerted effort to apply the methods of weather forecasting to develop an analogous theory for predicting tumor growth and treatment response. Currently, the time course of response is not predicted, but rather assessed post hoc by physical exam or imaging methods. This fundamental limitation of clinical oncology makes it extraordinarily difficult to select an optimal treatment regimen for a particular tumor of an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. With a successful theory of tumor forecasting, it should be possible to integrate large tumor specific datasets of varied types, and effectively defeat cancer one patient at a time.

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

    SciTech Connect (OSTI)

    Lemont, S.

    1980-01-01

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

  13. HANFORD WASTE MINERALOGY REFERENCE REPORT

    SciTech Connect (OSTI)

    DISSELKAMP RS

    2010-06-29

    This report lists the observed mineral phases present in the Hanford tanks. This task was accomplished by performing a review of numerous reports that used experimental techniques including, but not limited to: x-ray diffraction, polarized light microscopy, scanning electron microscopy, transmission electron microscopy, energy dispersive spectroscopy, electron energy loss spectroscopy, and particle size distribution analyses. This report contains tables that can be used as a quick reference to identify the crystal phases observed in Hanford waste.

  14. HANFORD WASTE MINEROLOGY REFERENCE REPORT

    SciTech Connect (OSTI)

    DISSELKAMP RS

    2010-06-18

    This report lists the observed mineral phase phases present in the Hanford tanks. This task was accomplished by performing a review of numerous reports using experimental techniques including, but not limited to: x-ray diffraction, polarized light microscopy, scanning electron microscopy, transmission electron microscopy, energy dispersive spectroscopy, electron energy loss spectroscopy, and particle size distribution analyses. This report contains tables that can be used as a quick reference to identify the crystal phases present observed in Hanford waste.

  15. Microgrid cyber security reference architecture.

    SciTech Connect (OSTI)

    Veitch, Cynthia K.; Henry, Jordan M.; Richardson, Bryan T.; Hart, Derek H.

    2013-07-01

    This document describes a microgrid cyber security reference architecture. First, we present a high-level concept of operations for a microgrid, including operational modes, necessary power actors, and the communication protocols typically employed. We then describe our motivation for designing a secure microgrid; in particular, we provide general network and industrial control system (ICS)-speci c vulnerabilities, a threat model, information assurance compliance concerns, and design criteria for a microgrid control system network. Our design approach addresses these concerns by segmenting the microgrid control system network into enclaves, grouping enclaves into functional domains, and describing actor communication using data exchange attributes. We describe cyber actors that can help mitigate potential vulnerabilities, in addition to performance bene ts and vulnerability mitigation that may be realized using this reference architecture. To illustrate our design approach, we present a notional a microgrid control system network implementation, including types of communica- tion occurring on that network, example data exchange attributes for actors in the network, an example of how the network can be segmented to create enclaves and functional domains, and how cyber actors can be used to enforce network segmentation and provide the neces- sary level of security. Finally, we describe areas of focus for the further development of the reference architecture.

  16. Subsurface Knowledge Reference Page | Department of Energy

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

    The below listing provides additional references related to Subsurface & Groundwater Remediation. The references are categorized by documents types (e.g., Strategic Plans, ...

  17. A New Solar Irradiance Reference Spectrum

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

    A New Solar Irradiance Reference Spectrum Pilewskie, Peter University of Colorado ... We describe the development of a new solar reference spectrum for radiation and climate ...

  18. Template:ReferenceMaterial | Open Energy Information

    Open Energy Info (EERE)

    - The type of reference material (allowable values include: Journal article, Book, Report, etc.) Documentnumber - The reference material document number or DOI...

  19. Reference Inflow Characterization for River Resource Reference Model (RM2)

    SciTech Connect (OSTI)

    Neary, Vincent S [ORNL

    2011-12-01

    Sandia National Laboratory (SNL) is leading an effort to develop reference models for marine and hydrokinetic technologies and wave and current energy resources. This effort will allow the refinement of technology design tools, accurate estimates of a baseline levelized cost of energy (LCoE), and the identification of the main cost drivers that need to be addressed to achieve a competitive LCoE. As part of this effort, Oak Ridge National Laboratory was charged with examining and reporting reference river inflow characteristics for reference model 2 (RM2). Published turbulent flow data from large rivers, a water supply canal and laboratory flumes, are reviewed to determine the range of velocities, turbulence intensities and turbulent stresses acting on hydrokinetic technologies, and also to evaluate the validity of classical models that describe the depth variation of the time-mean velocity and turbulent normal Reynolds stresses. The classical models are found to generally perform well in describing river inflow characteristics. A potential challenge in river inflow characterization, however, is the high variability of depth and flow over the design life of a hydrokinetic device. This variation can have significant effects on the inflow mean velocity and turbulence intensity experienced by stationary and bottom mounted hydrokinetic energy conversion devices, which requires further investigation, but are expected to have minimal effects on surface mounted devices like the vertical axis turbine device designed for RM2. A simple methodology for obtaining an approximate inflow characterization for surface deployed devices is developed using the relation umax=(7/6)V where V is the bulk velocity and umax is assumed to be the near-surface velocity. The application of this expression is recommended for deriving the local inflow velocity acting on the energy extraction planes of the RM2 vertical axis rotors, where V=Q/A can be calculated given a USGS gage flow time-series and stage vs. cross-section area rating relationship.

  20. Energy consumption and expenditure projections by population group on the basis of the annual energy outlook 1999 forecast

    SciTech Connect (OSTI)

    Poyer, D.A.; Balsley, J.H.

    2000-01-07

    This report presents an analysis of the relative impact of the base-case scenario used in Annual Energy Outlook 1999 on different population groups. Projections of energy consumption and expenditures, as well as energy expenditure as a share of income, from 1996 to 2020 are given. The projected consumption of electricty, natural gas, distillate fuel, and liquefied petroleum gas during this period is also reported for each population group. In addition, this report compares the findings of the Annual Energy Outlook 1999 report with the 1998 report. Changes in certain indicators and information affect energy use forecasts, and these effects are analyzed and discussed.

  1. PVWatts Version 1 Technical Reference

    SciTech Connect (OSTI)

    Dobos, A. P.

    2013-10-01

    The NREL PVWatts(TM) calculator is a web application developed by the National Renewable Energy Laboratory (NREL) that estimates the electricity production of a grid-connected photovoltaic system based on a few simple inputs. PVWatts combines a number of sub-models to predict overall system performance, and makes several hidden assumptions about performance parameters. This technical reference details the individual sub-models, documents assumptions and hidden parameters, and explains the sequence of calculations that yield the final system performance estimation.

  2. Reference electrode for electrolytic cell

    DOE Patents [OSTI]

    Kessie, R.W.

    1988-07-28

    A reference electrode device is provided for a high temperature electrolytic cell used to electrolytically recover uranium from spent reactor fuel dissolved in an anode pool, the device having a glass tube to enclose the electrode and electrolyte and serve as a conductive membrane with the cell electrolyte, and an outer metal tube about the glass tube to serve as a shield and basket for any glass sections broken by handling of the tube to prevent their contact with the anode pool, the metal tube having perforations to provide access between the bulk of the cell electrolyte and glass membrane. 4 figs.

  3. Emergency Responder Radioactive Material Quick Reference Sheet

    Broader source: Energy.gov [DOE]

    Transportation Emergency Preparedness Program (TEPP) Emergency Responder Radioactive Material Quick Reference Sheet

  4. High stability wavefront reference source

    DOE Patents [OSTI]

    Feldman, M.; Mockler, D.J.

    1994-05-03

    A thermally and mechanically stable wavefront reference source which produces a collimated output laser beam is disclosed. The output beam comprises substantially planar reference wavefronts which are useful for aligning and testing optical interferometers. The invention receives coherent radiation from an input optical fiber, directs a diverging input beam of the coherent radiation to a beam folding mirror (to produce a reflected diverging beam), and collimates the reflected diverging beam using a collimating lens. In a class of preferred embodiments, the invention includes a thermally and mechanically stable frame comprising rod members connected between a front end plate and a back end plate. The beam folding mirror is mounted on the back end plate, and the collimating lens mounted to the rods between the end plates. The end plates and rods are preferably made of thermally stable metal alloy. Preferably, the input optical fiber is a single mode fiber coupled to an input end of a second single mode optical fiber that is wound around a mandrel fixedly attached to the frame of the apparatus. The output end of the second fiber is cleaved so as to be optically flat, so that the input beam emerging therefrom is a nearly perfect diverging spherical wave. 7 figures.

  5. High stability wavefront reference source

    DOE Patents [OSTI]

    Feldman, Mark; Mockler, Daniel J.

    1994-01-01

    A thermally and mechanically stable wavefront reference source which produces a collimated output laser beam. The output beam comprises substantially planar reference wavefronts which are useful for aligning and testing optical interferometers. The invention receives coherent radiation from an input optical fiber, directs a diverging input beam of the coherent radiation to a beam folding mirror (to produce a reflected diverging beam), and collimates the reflected diverging beam using a collimating lens. In a class of preferred embodiments, the invention includes a thermally and mechanically stable frame comprising rod members connected between a front end plate and a back end plate. The beam folding mirror is mounted on the back end plate, and the collimating lens mounted to the rods between the end plates. The end plates and rods are preferably made of thermally stable metal alloy. Preferably, the input optical fiber is a single mode fiber coupled to an input end of a second single mode optical fiber that is wound around a mandrel fixedly attached to the frame of the apparatus. The output end of the second fiber is cleaved so as to be optically flat, so that the input beam emerging therefrom is a nearly perfect diverging spherical wave.

  6. 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.

  7. Report of the external expert peer review panel: DOE benefits forecasts

    SciTech Connect (OSTI)

    None, None

    2006-12-20

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

  8. Value of Improved Wind Power Forecasting in the Western Interconnection (Poster)

    SciTech Connect (OSTI)

    Hodge, B.

    2013-12-01

    Wind power forecasting is a necessary and important technology for incorporating wind power into the unit commitment and dispatch process. It is expected to become increasingly important with higher renewable energy penetration rates and progress toward the smart grid. There is consensus that wind power forecasting can help utility operations with increasing wind power penetration; however, there is far from a consensus about the economic value of improved forecasts. This work explores the value of improved wind power forecasting in the Western Interconnection of the United States.

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

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

    The Value of Improved Short- Term Wind Power Forecasting B.-M. Hodge and A. Florita National Renewable Energy Laboratory J. Sharp Sharply Focused, LLC M. Margulis and D. Mcreavy Lockheed Martin Technical Report NREL/TP-5D00-63175 February 2015 NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency & Renewable Energy Operated by the Alliance for Sustainable Energy, LLC This report is available at no cost from the National Renewable Energy Laboratory (NREL)

  10. Waste Generation Forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1994--FY 2001. Environmental Restoration Program, September 1993 Revision

    SciTech Connect (OSTI)

    Not Available

    1993-12-01

    This Waste Generation Forecast for DOE-ORO`s Environmental Restoration OR-1 Project. FY 1994--FY 2001 is the third in a series of documents that report current estimates of the waste volumes expected to be generated as a result of Environmental Restoration activities at Department of Energy, Oak Ridge Operations Office (DOE-ORO), sites. Considered in the scope of this document are volumes of waste expected to be generated as a result of remedial action and decontamination and decommissioning activities taking place at these sites. Sites contributing to the total estimates make up the DOE-ORO Environmental Restoration OR-1 Project: the Oak Ridge K-25 Site, the Oak Ridge National Laboratory, the Y-12 Plant, the Paducah Gaseous Diffusion Plant, the Portsmouth Gaseous Diffusion Plant, and the off-site contaminated areas adjacent to the Oak Ridge facilities (collectively referred to as the Oak Ridge Reservation Off-Site area). Estimates are available for the entire fife of all waste generating activities. This document summarizes waste estimates forecasted for the 8-year period of FY 1994-FY 2001. Updates with varying degrees of change are expected throughout the refinement of restoration strategies currently in progress at each of the sites. Waste forecast data are relatively fluid, and this document represents remediation plans only as reported through September 1993.

  11. Analysis of Restricted Natural Gas Supply Cases

    Reports and Publications (EIA)

    2004-01-01

    The four cases examined in this study have progressively greater impacts on overall natural gas consumption, prices, and supply. Compared to the Annual Energy Outlook 2004 reference case, the no Alaska pipeline case has the least impact; the low liquefied natural gas case has more impact; the low unconventional gas recovery case has even more impact; and the combined case has the most impact.

  12. Form:Reference | Open Energy Information

    Open Energy Info (EERE)

    The reference title should match the book title. e.g.- Where the Wild Things Are Book Review Used when citing a review of a book. The reference title should include "Review of the...

  13. Research Notes and Information References

    Energy Science and Technology Software Center (OSTI)

    1994-12-01

    The RNS (Research Notes System) is a set of programs and databases designed to aid the research worker in gathering, maintaining, and using notes taken from the literature. The sources for the notes can be books, journal articles, reports, private conversations, conference papers, audiovisuals, etc. The system ties the databases together in a relational structure, thus eliminating data redundancy while providing full access to all the information. The programs provide the means for access andmore » data entry in a way that reduces the key-entry burden for the user. Each note has several data fields. Included are the text of the note, the subject classification (for retrieval), and the reference identification data. These data are divided into four databases: Document data - title, author, publisher, etc., fields to identify the article within the document; Note data - text and page of the note; Sublect data - subject categories to ensure uniform spelling for searches. Additionally, there are subsidiary files used by the system, including database index and temporary work files. The system provides multiple access routes to the notes, both structurally (access method) and topically (through cross-indexing). Output may be directed to a printer or saved as a file for input to word processing software.« less

  14. The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area

    SciTech Connect (OSTI)

    Finley, Cathy

    2014-04-30

    This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times.

  15. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect (OSTI)

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together into larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

  16. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

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

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

  17. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison (Presentation)

    SciTech Connect (OSTI)

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

    2013-10-01

    This presentation summarizes the work to investigate the uncertainty in wind forecasting at different times of year and compare wind forecast errors in different power systems using large-scale wind power prediction data from six countries: the United States, Finland, Spain, Denmark, Norway, and Germany.

  18. World Business Council for Sustainable Development-Case Studies...

    Open Energy Info (EERE)

    Efficiency, Renewable Energy, Buildings, Industry Topics Implementation Resource Type Lessons learnedbest practices Website http:www.wbcsd.orgtemplates References Case...

  19. Geothermal Exploration Techniques a Case Study. Final Report...

    Open Energy Info (EERE)

    Techniques a Case Study. Final Report Jump to: navigation, search OpenEI Reference LibraryAdd to library Report: Geothermal Exploration Techniques a Case Study. Final Report...

  20. Thirty-Year Solid Waste Generation Maximum and Minimum Forecast for SRS

    SciTech Connect (OSTI)

    Thomas, L.C.

    1994-10-01

    This report is the third phase (Phase III) of the Thirty-Year Solid Waste Generation Forecast for Facilities at the Savannah River Site (SRS). Phase I of the forecast, Thirty-Year Solid Waste Generation Forecast for Facilities at SRS, forecasts the yearly quantities of low-level waste (LLW), hazardous waste, mixed waste, and transuranic (TRU) wastes generated over the next 30 years by operations, decontamination and decommissioning and environmental restoration (ER) activities at the Savannah River Site. The Phase II report, Thirty-Year Solid Waste Generation Forecast by Treatability Group (U), provides a 30-year forecast by waste treatability group for operations, decontamination and decommissioning, and ER activities. In addition, a 30-year forecast by waste stream has been provided for operations in Appendix A of the Phase II report. The solid wastes stored or generated at SRS must be treated and disposed of in accordance with federal, state, and local laws and regulations. To evaluate, select, and justify the use of promising treatment technologies and to evaluate the potential impact to the environment, the generic waste categories described in the Phase I report were divided into smaller classifications with similar physical, chemical, and radiological characteristics. These smaller classifications, defined within the Phase II report as treatability groups, can then be used in the Waste Management Environmental Impact Statement process to evaluate treatment options. The waste generation forecasts in the Phase II report includes existing waste inventories. Existing waste inventories, which include waste streams from continuing operations and stored wastes from discontinued operations, were not included in the Phase I report. Maximum and minimum forecasts serve as upper and lower boundaries for waste generation. This report provides the maximum and minimum forecast by waste treatability group for operation, decontamination and decommissioning, and ER activities.

  1. Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets

    SciTech Connect (OSTI)

    Wong-Parodi, Gabrielle; Lekov, Alex; Dale, Larry

    2005-02-09

    This paper evaluates the accuracy of two methods to forecast natural gas prices: using the Energy Information Administration's ''Annual Energy Outlook'' forecasted price (AEO) and the ''Henry Hub'' compared to U.S. Wellhead futures price. A statistical analysis is performed to determine the relative accuracy of the two measures in the recent past. A statistical analysis suggests that the Henry Hub futures price provides a more accurate average forecast of natural gas prices than the AEO. For example, the Henry Hub futures price underestimated the natural gas price by 35 cents per thousand cubic feet (11.5 percent) between 1996 and 2003 and the AEO underestimated by 71 cents per thousand cubic feet (23.4 percent). Upon closer inspection, a liner regression analysis reveals that two distinct time periods exist, the period between 1996 to 1999 and the period between 2000 to 2003. For the time period between 1996 to 1999, AEO showed a weak negative correlation (R-square = 0.19) between forecast price by actual U.S. Wellhead natural gas price versus the Henry Hub with a weak positive correlation (R-square = 0.20) between forecasted price and U.S. Wellhead natural gas price. During the time period between 2000 to 2003, AEO shows a moderate positive correlation (R-square = 0.37) between forecasted natural gas price and U.S. Wellhead natural gas price versus the Henry Hub that show a moderate positive correlation (R-square = 0.36) between forecast price and U.S. Wellhead natural gas price. These results suggest that agencies forecasting natural gas prices should consider incorporating the Henry Hub natural gas futures price into their forecasting models along with the AEO forecast. Our analysis is very preliminary and is based on a very small data set. Naturally the results of the analysis may change, as more data is made available.

  2. Weather Research and Forecasting Model with Vertical Nesting Capability

    Energy Science and Technology Software Center (OSTI)

    2014-08-01

    The Weather Research and Forecasting (WRF) model with vertical nesting capability is an extension of the WRF model, which is available in the public domain, from www.wrf-model.org. The new code modifies the nesting procedure, which passes lateral boundary conditions between computational domains in the WRF model. Previously, the same vertical grid was required on all domains, while the new code allows different vertical grids to be used on concurrently run domains. This new functionality improvesmore » WRF's ability to produce high-resolution simulations of the atmosphere by allowing a wider range of scales to be efficiently resolved and more accurate lateral boundary conditions to be provided through the nesting procedure.« less

  3. 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.

  4. NREL: Measurements and Characterization - Reference Cell Calibration

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

    Reference Cell Calibration The National Renewable Energy Laboratory (NREL) calibrates primary reference cells for in-house use and for use by other national laboratories. We also do so to provide our clients and partners with a path for traceability to standards. Our laboratory is one of only four facilities in the world certified to calibrate reference cells in accordance with the world photovoltaic scale, and these measurements are accredited to International Organization for Standardization

  5. FAQS Reference Guide – Industrial Hygiene

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the November 2007 edition of DOE-STD-1138-2007, Industrial Hygiene Functional Area Qualification Standard.

  6. FAQS Reference Guide – Mechanical Systems

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the June 2008 edition of DOE-STD-1161-2008, Mechanical Systems Functional Area Qualification Standard.

  7. FAQS Reference Guide – Facility Maintenance Management

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the April 2014 edition of DOE Standard DOE-STD-1181-2014, Facility Maintenance Management Functional Area Qualification Standard.

  8. FAQS Reference Guide – Criticality Safety (NNSA)

    Broader source: Energy.gov [DOE]

    This reference guide has been developed to address the competency statements in DOE-STD-1173-2009, Criticality Safety Functional Area Qualification Standard.

  9. AVIATION MANAGER QUALIFICATION STANDARD REFERENCE GUIDE

    Energy Savers [EERE]

    Manager Qualification Standard Reference Guide MARCH 2010 i This page is intentionally blank. Table of Contents ii LIST OF FIGURES ..................................................................................................................... iii LIST OF TABLES ....................................................................................................................... iii ACRONYMS

  10. AVIATION SAFETY OFFICER QUALIFICATION STANDARD REFERENCE GUIDE

    Energy Savers [EERE]

    Safety Officer Qualification Standard Reference Guide MARCH 2010 i This page is intentionally blank. Table of Contents ii LIST OF FIGURES ..................................................................................................................... iii LIST OF TABLES ....................................................................................................................... iii ACRONYMS

  11. FAQS Reference Guide – Environmental Compliance

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the June 2011 edition of DOE-STD-1156-2011, Environmental Compliance Functional Area Qualification Standard.

  12. Reference Designs for Hydrogen Fueling Stations Webinar

    Broader source: Energy.gov [DOE]

    Access the recording and download the presentation slides from the Fuel Cell Technologies Office webinar "Reference Designs for Hydrogen Fueling Stations" held on October 13, 2015.

  13. FAQS Reference Guide – Criticality Safety

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the April 2009 edition of DOE-STD-1173-2009, Criticality Safety Functional Area Qualification Standard.

  14. FAQS Reference Guide – Emergency Management

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the January 2004 edition of DOE-STD-1177-2004, Emergency Management Functional Area Qualification Standard.

  15. FAQS Reference Guide – Safeguards and Security

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the May 2009 edition of DOE-STD-1171-2009, Safeguards and Security Functional Area Qualification Standard.

  16. FAQS Reference Guide – Fire Protection Engineering

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the December 2007 edition of DOE-STD-1137-2007, Fire Protection Engineering Functional Area Qualification Standard.

  17. Property:ReferenceGenre | Open Energy Information

    Open Energy Info (EERE)

    Property Type Text Description The genre or subcategory label of reference material. Allows Values Buildings;Bulk Transmission;Geothermal;Hydrogen;Hydropower;Smart...

  18. FAQS Reference Guide – Facility Representative

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the October 2010 edition of DOE-STD-1151-2010, Facility Representative Functional Area Qualification Standard.

  19. Commercial Reference Buildings | Open Energy Information

    Open Energy Info (EERE)

    Reference Building Types1 , which represent approximately 70% of the commercial buildings in the U.S. 2. Whole building energy analysis data (developed using EnergyPlus...

  20. FAQS Reference Guide – Construction Management

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the March 2004 edition of DOE-STD-1180-2004, Construction Management Functional Area Qualification Standard.

  1. FAQS Reference Guide – General Technical Base

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the December 2007 edition of DOE-STD-1146-2007, General Technical Base Functional Area Qualification Standard.

  2. Template:Reference | Open Energy Information

    Open Energy Info (EERE)

    for references that may not require listed authors such as technical reports or web referenced material (Report & Web Site) GraphicAuthor - List of authors or map...

  3. Manufacturing Energy and Carbon Footprint References

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

    References AMO (Advanced Manufacturing Office), EERE (Energy Efficiency and Renewable Energy). 2012. Consider Installing High-Pressure Boilers with Backpressure Turbine-Generators. ...

  4. FAQS Reference Guide – Environmental Restoration

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the November 2002 edition of DOE-STD-1157-2002, Environmental Restoration Functional Area Qualification Standard.

  5. Reference Form | SREL REU in Radioecology

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

    to highlight specific examples that illustrate the candidate's strengths or suitability to the program. Therefore, we also require references to also upload a letter of...

  6. IBM References | Argonne Leadership Computing Facility

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

    Feedback Form IBM References Contents IBM Redbooks A2 Processor Manual QPX Vector Instruction Set Architecture XL Compiler Documentation MASS Documentation Back to top IBM...

  7. Review of Variable Generation Forecasting in the West: July 2013 - March 2014

    SciTech Connect (OSTI)

    Widiss, R.; Porter, K.

    2014-03-01

    This report interviews 13 operating entities (OEs) in the Western Interconnection about their implementation of wind and solar forecasting. The report updates and expands upon one issued by NREL in 2012. As in the 2012 report, the OEs interviewed vary in size and character; the group includes independent system operators, balancing authorities, utilities, and other entities. Respondents' advice for other utilities includes starting sooner rather than later as it can take time to plan, prepare, and train a forecast; setting realistic expectations; using multiple forecasts; and incorporating several performance metrics.

  8. World oil inventories forecast to grow significantly in 2016 and 2017

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

    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 prices low. In its new monthly forecast, the U.S. Energy Information Administration said world oil stocks are likely to increase by 1.6 million barrels per day this year and by 600,000 barrels per day next year. The higher forecast for inventory builds are the result of both higher global oil production and less oil

  9. Archived Reference Climate Zone: 7 Duluth, Minnesota

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  10. Archived Reference Climate Zone: 7 Duluth, Minnesota

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  11. References - DOE Directives, Delegations, and Requirements

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

    References by Website Administrator This page provides information and links to references. Technical Standards Technical Standards Program Technical Standards Home RevCom for Technical Standards Review Process for Technical Standards of Interest to the Directives Program Technical Standards Crosswalk NNSA Directives National Nuclear Security Administration (NNSA) Supplemental Directives NNSA Policies (NAPs) FAR Federal Acquisition Regulations Federal Acquisition Regulations (FAR) DOE

  12. Archived Reference Building Type: Outpatient health care

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  13. Archived Reference Climate Zone: 8 Fairbanks, Alaska

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zonesis available for reference.Current versionsare also available.

  14. Archived Reference Climate Zone: 8 Fairbanks, Alaska

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  15. Archived Reference Building Type: Quick service restaurant

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  16. Archived Reference Building Type: Full service restaurant

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  17. Archived Reference Building Type: Quick service restaurant

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  18. Archived Reference Building Type: Full service restaurant

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  19. Archived Reference Building Type: Primary school

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  20. Archived Reference Building Type: Primary school

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  1. Archived Reference Building Type: Medium office

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  2. Archived Reference Building Type: Medium office

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  3. Archived Reference Building Type: Secondary school

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  4. Archived Reference Building Type: Secondary school

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  5. Archived Reference Building Type: Large Hotel

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  6. Archived Reference Building Type: Small Hotel

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  7. Archived Reference Building Type: Small Hotel

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  8. Archived Reference Building Type: Large Hotel

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  9. Archived Reference Building Type: Outpatient health care

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  10. Archived Reference Building Type: Strip mall

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zonesis available for reference.Current versionsare also available.

  11. Archived Reference Building Type: Strip mall

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  12. Archived Reference Building Type: Midrise Apartment

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zonesis available for reference.Current versionsare also available.

  13. Archived Reference Building Type: Midrise Apartment

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

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

    Broader source: Energy.gov [DOE]

    This project will address the need for a more accurate approach to forecasting net utility load by taking into consideration the contribution of customer-sited PV energy generation. Tasks within...

  15. Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex Terrain

    Broader source: Energy.gov [DOE]

    On April 4, 2014 the U.S. Department of Energy announced a $2.5 million funding opportunity entitled “Wind Forecasting Improvement Project in Complex Terrain.” By researching the physical processes...

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

    SciTech Connect (OSTI)

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

    2015-06-23

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

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

    Broader source: Energy.gov [DOE]

    As part of this project, new solar forecasting technology will be developed that leverages big data processing, deep machine learning, and cloud modeling integrated in a universal platform with an...

  18. U.S. diesel fuel price forecast to be 1 penny lower this summer...

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

    That's down 12 percent from last summer's record exports. Biodiesel production, which averaged 68,000 barrels a day last summer, is forecast to jump to 82,000 barrels a day this ...

  19. A comparison of model short-range forecasts and the ARM Microbase...

    Office of Scientific and Technical Information (OSTI)

    the text) at three sites: the North Slope of Alaska (NSA), Tropical West Pacific (TWP) and the Southern Great Plains (SGP) and compare these observations to model forecast data. ...

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

    SciTech Connect (OSTI)

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

    2013-01-01

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

  1. Examining Information Entropy Approaches as Wind Power Forecasting Performance Metrics: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Orwig, K.; Milligan, M.

    2012-06-01

    In this paper, we examine the parameters associated with the calculation of the Renyi entropy in order to further the understanding of its application to assessing wind power forecasting errors.

  2. U.S. oil production forecast update reflects lower rig count

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

    U.S. oil production forecast update reflects lower rig count Lower oil prices and fewer rigs drilling for crude oil are expected to slow U.S. oil production growth this year and in ...

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

    SciTech Connect (OSTI)

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

    2013-11-01

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

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

    SciTech Connect (OSTI)

    Not Available

    2009-11-01

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

  5. U.S. Crude Oil Production Forecast-Analysis of Crude Types

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

    of Energy Washington, DC 20585 U.S. Energy Information Administration | U.S. Crude Oil Production Forecast-Analysis of Crude Types i This report was prepared by the U.S....

  6. U.S. Department of Energy Workshop Report: Solar Resources and Forecasting

    SciTech Connect (OSTI)

    Stoffel, T.

    2012-06-01

    This report summarizes the technical presentations, outlines the core research recommendations, and augments the information of the Solar Resources and Forecasting Workshop held June 20-22, 2011, in Golden, Colorado. The workshop brought together notable specialists in atmospheric science, solar resource assessment, solar energy conversion, and various stakeholders from industry and academia to review recent developments and provide input for planning future research in solar resource characterization, including measurement, modeling, and forecasting.

  7. A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and

    Office of Scientific and Technical Information (OSTI)

    ARM Observations (Technical Report) | SciTech Connect Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations Citation Details In-Document Search Title: A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations (in English; Croatian) Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was

  8. Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE (Presentation)

    SciTech Connect (OSTI)

    Brancucci Martinez-Anido, C.; Florita, A.; Hodge, B.M.

    2014-11-01

    The diurnal nature of solar power is made uncertain by variable cloud cover and the influence of atmospheric conditions on irradiance scattering processes. Its forecasting has become increasingly important to the unit commitment and dispatch process for efficient scheduling of generators in power system operations. This presentation is an overview of a study that examines the value of improved solar forecasts on Bulk Power System Operations.

  9. Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE: Preprint

    SciTech Connect (OSTI)

    Brancucci Martinez-Anido, C.; Florita, A.; Hodge, B. M.

    2014-09-01

    The diurnal nature of solar power is made uncertain by variable cloud cover and the influence of atmospheric conditions on irradiance scattering processes. Its forecasting has become increasingly important to the unit commitment and dispatch process for efficient scheduling of generators in power system operations. This study examines the value of improved solar power forecasting for the Independent System Operator-New England system. The results show how 25% solar power penetration reduces net electricity generation costs by 22.9%.

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

    SciTech Connect (OSTI)

    Tian; Tian; Chernyakhovskiy, Ilya

    2016-01-01

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

  11. Solar energy conversion: Technological forecasting. (Latest citations from the Aerospace database). Published Search

    SciTech Connect (OSTI)

    Not Available

    1993-12-01

    The bibliography contains citations concerning current forecasting of Earth surface-bound solar energy conversion technology. Topics consider research, development and utilization of this technology in relation to electric power generation, heat pumps, bioconversion, process heat and the production of renewable gaseous, liquid, and solid fuels for industrial, commercial, and domestic applications. Some citations concern forecasts which compare solar technology with other energy technologies. (Contains 250 citations and includes a subject term index and title list.)

  12. Solar energy conversion: Technological forecasting. (Latest citations from the Aerospace database). Published Search

    SciTech Connect (OSTI)

    1995-01-01

    The bibliography contains citations concerning current forecasting of Earth surface-bound solar energy conversion technology. Topics consider research, development and utilization of this technology in relation to electric power generation, heat pumps, bioconversion, process heat and the production of renewable gaseous, liquid, and solid fuels for industrial, commercial, and domestic applications. Some citations concern forecasts which compare solar technology with other energy technologies. (Contains 250 citations and includes a subject term index and title list.)

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

    SciTech Connect (OSTI)

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

    2013-05-01

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

  14. FAQS Reference Guide - Aviation Manager | Department of Energy

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

    FAQS Reference Guide - Aviation Manager FAQS Reference Guide - Aviation Manager This reference guide addresses the competency statements in the January 2010 edition of...

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

    SciTech Connect (OSTI)

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

    2012-08-01

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

  16. FAQS Reference Guide – Nuclear Safety Specialist

    Broader source: Energy.gov [DOE]

    This reference guide has been developed to address the competency statements in the November 2007 edition of DOE Standard DOE-STD-1183-2007, Nuclear Safety Specialist Functional Area Qualification Standard.

  17. Archive Reference Buildings by Building Type: Warehouse

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the reference buildings for new construction commercial buildings, organized by building type and location. A summary of building types and climate zones is...

  18. FAQS Reference Guide – Occupational Safety

    Broader source: Energy.gov [DOE]

    This reference guide has been developed to address the competency statements in the July 2011 version of DOE-STD-1160-2011, Occupational Safety Functional Area Qualification Standard.

  19. New Construction Commercial Reference Buildings — Archive

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the reference buildings for new construction commercial buildings, organized by building type and location. A summary of building types and climate zones is...

  20. FAQS Reference Guide –Radiation Protection

    Broader source: Energy.gov [DOE]

    This reference guide has been developed to address the competency statements in the December 2003 edition of DOE-STD-1174-2003, Radiation Protection Functional Area Qualification Standard.

  1. FAQS Reference Guide – Instrumentation and Control

    Broader source: Energy.gov [DOE]

    This reference guide has been developed to address the competency statements in the June 2013 edition of DOE-Standard (STD)-1162-2013, Instrumentation and Control Functional Area Qualification Standard.

  2. Webinar: Reference Designs for Hydrogen Fueling Stations

    Broader source: Energy.gov [DOE]

    The Fuel Cell Technologies Office will present a live webinar titled "Reference Designs for Hydrogen Fueling Stations" on Tuesday, October 13, from 12 to 1 p.m. Eastern Daylight Time (EDT).

  3. FAQS Reference Guide – Civil/ Structural Engineering

    Broader source: Energy.gov [DOE]

    This reference guide has been developed to address the competency statements in the March 2004 edition of DOE-STD-1182-2004, Civil/Structural Engineering Functional Area Qualification Standard.

  4. New Robust References! | OpenEI Community

    Open Energy Info (EERE)

    provided document type If I,Robot doesn't exist yet, the template will return a red link specially coded to open in the Reference form so that it can be easily added...

  5. Emergency Responder Radioactive Material Quick Reference Sheet

    Broader source: Energy.gov [DOE]

    This job aid is a quick reference to assist emergency responders in identifying preliminary safety precautions that should be taken during the initial response phase after arrival at the scene of...

  6. Template:ReferenceHeader | Open Energy Information

    Open Energy Info (EERE)

    Reference Library banner, typically across the top of the page, which features a unique color scheme and simple menu. Parameters none Usage It should be called in the following...

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

    SciTech Connect (OSTI)

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

    2009-11-20

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

  8. No Sunset and Extended Policies Cases (released in AEO2010)

    Reports and Publications (EIA)

    2010-01-01

    The Annual Energy Outlook 2010 Reference case is best described as a current laws and regulations case, because it generally assumes that existing laws and fully promulgated regulations will remain unchanged throughout the projection period, unless the legislation establishing them specifically calls for them to end or change. The Reference case often serves as a starting point for the analysis of proposed legislative or regulatory changes, a task that would be difficult if the Reference case included projected legislative or regulatory changes.

  9. "Analysis of SOFCs using reference electrodes?

    SciTech Connect (OSTI)

    Finklea, Harry; Chen,Xiaoke; Gerdes,Kirk; Pakalapati, Suryanarayana; Celik, Ismail

    2013-07-01

    Reference electrodes are frequently applied to isolate the performance of one electrode in a solid oxide fuel cell. However, reference electrode simulations raise doubt to veracity of data collected using reference electrodes. The simulations predict that the reported performance for the one electrode will frequently contain performance of both electrodes. Nonetheless, recent reports persistently treat data so collected as ideally isolated. This work confirms the predictions of the reference electrode simulations on two SOFC designs, and to provides a method of validating the data measured in the 3-electrode configuration. Validation is based on the assumption that a change in gas composition to one electrode does not affect the impedance of the other electrode at open circuit voltage. This assumption is supported by a full physics simulation of the SOFC. Three configurations of reference electrode and cell design are experimentally examined using various gas flows and two temperatures. Impedance data are subjected to deconvolution analysis and equivalent circuit fitting and approximate polarization resistances of the cathode and anode are determined. The results demonstrate that the utility of reference electrodes is limited and often wholly inappropriate. Reported impedances and single electrode polarization values must be scrutinized on this basis.

  10. 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.

  11. The Value of Improved Wind Power Forecasting in the Western Interconnection (Poster), NREL (National Renewable Energy Laboratory)

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

    outcome of this research will facilitate a better functional understanding of wind forecasting accuracy and power system operations at various spatial and temporal scales.* Of particular interest are: 1. Correlated behavior among variables (e.g., changes in dispatch stacks, production costs, or generation by type as a function of forecasting accuracy); 2. The relative reduction in wind curtailment with improved forecasting accuracy; and 3. The value of information (e.g., which subset of

  12. Development of solid radium-226 reference materials

    SciTech Connect (OSTI)

    Chessmore, R.B.; Engelder, P.R.; Sill, C.W.

    1983-11-01

    Radium-226 reference materials having a matrix similar to soil or tailings samples are not available in sufficient quantity for use by remedial-action contractors to calibrate their laboratory gamma-ray spectrometers. Such reference materials are needed to provide uniform standardization among measurements made by remedial-action contractors. A task, therefore, was undertaken to prepare about 200 pounds each of three different concentrations of radium-226 reference materials by diluting tailings with high-purity silica. Target values for radium-226 content were 50, 15, and 5 pCi/g. The radium-226 content of the reference materials was measured by C.W. Sill of EG and G Idaho, Inc., Idaho Falls, using a high- resolution alpha spectrometry technique standardized with National Bureau of Standards (NBS) standard 4961. A summary of this technique is provided in Appendix A of this report. An independent measurement of the radium-226 content was conducted by Bendix Field Engineering Corporation (Bendix), Grand Junction, Colorado, using a high-resolution Ge(Li) detector, which was calibrated using the New Brunswick Laboratory (NBL) 100-A Series standards. The Ge(Li) detector has also been used to determine the radium-226 content in the calibration models at the Grand Junction facility; these models are used by remedial-action contractors for calibration of borehole logging gamma-ray probes. 8 references, 12 tables.

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

    SciTech Connect (OSTI)

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

    2015-01-01

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

  14. Case Studies

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

    OSCARS Case Studies Science DMZ Case Studies Multi-facility Workflow Case Study News & Publications ESnet News Publications and Presentations Galleries ESnet Awards and Honors Blog...

  15. TriBITS Developers Guide and Reference

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

    TriBITS Developers Guide and Reference Ross Bartlett Oak Ridge National Laboratory March 31, 2014 CASL-U-2014-0075-000-E CASL-U-2014-0075-000-b TriBITS Developers Guide and Reference Author: Roscoe A. Bartlett (bartlettra@ornl.gov) Abstract This document describes the usage of TriBITS to build, test, and deploy complex software. The primary audience are those individuals who develop on a software project which uses TriBITS. The overall structure of a TriBITS project is described including all of

  16. Annual Energy Outlook 2016 Early Release: Annotated Summary of Two Cases

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

    Early Release: Annotated Summary of Two Cases May 17, 2016 The Annual Energy Outlook 2016 (AEO2016) Early Release features two cases: the Reference case and a case excluding implementation of the Clean Power Plan (CPP) Reference case: A business-as-usual trend estimate, given known technology and technological and demographic trends. The Reference case assumes CPP compliance through mass-based standards that establish caps on CO2 emissions from fossil-fired generators covered by the CPP. The

  17. Baseline data for the residential sector and development of a residential forecasting database

    SciTech Connect (OSTI)

    Hanford, J.W.; Koomey, J.G.; Stewart, L.E.; Lecar, M.E.; Brown, R.E.; Johnson, F.X.; Hwang, R.J.; Price, L.K.

    1994-05-01

    This report describes the Lawrence Berkeley Laboratory (LBL) residential forecasting database. It provides a description of the methodology used to develop the database and describes the data used for heating and cooling end-uses as well as for typical household appliances. This report provides information on end-use unit energy consumption (UEC) values of appliances and equipment historical and current appliance and equipment market shares, appliance and equipment efficiency and sales trends, cost vs efficiency data for appliances and equipment, product lifetime estimates, thermal shell characteristics of buildings, heating and cooling loads, shell measure cost data for new and retrofit buildings, baseline housing stocks, forecasts of housing starts, and forecasts of energy prices and other economic drivers. Model inputs and outputs, as well as all other information in the database, are fully documented with the source and an explanation of how they were derived.

  18. Positional reference system for ultraprecision machining

    DOE Patents [OSTI]

    Arnold, Jones B.; Burleson, Robert R.; Pardue, Robert M.

    1982-01-01

    A stable positional reference system for use in improving the cutting tool-to-part contour position in numerical controlled-multiaxis metal turning machines is provided. The reference system employs a plurality of interferometers referenced to orthogonally disposed metering bars which are substantially isolated from machine strain induced position errors for monitoring the part and tool positions relative to the metering bars. A microprocessor-based control system is employed in conjunction with the plurality of position interferometers and part contour description data inputs to calculate error components for each axis of movement and output them to corresponding axis drives with appropriate scaling and error compensation. Real-time position control, operating in combination with the reference system, makes possible the positioning of the cutting points of a tool along a part locus with a substantially greater degree of accuracy than has been attained previously in the art by referencing and then monitoring only the tool motion relative to a reference position located on the machine base.

  19. Positional reference system for ultraprecision machining

    DOE Patents [OSTI]

    Arnold, J.B.; Burleson, R.R.; Pardue, R.M.

    1980-09-12

    A stable positional reference system for use in improving the cutting tool-to-part contour position in numerical controlled-multiaxis metal turning machines is provided. The reference system employs a plurality of interferometers referenced to orthogonally disposed metering bars which are substantially isolated from machine strain induced position errors for monitoring the part and tool positions relative to the metering bars. A microprocessor-based control system is employed in conjunction with the plurality of positions interferometers and part contour description data input to calculate error components for each axis of movement and output them to corresponding axis driven with appropriate scaling and error compensation. Real-time position control, operating in combination with the reference system, makes possible the positioning of the cutting points of a tool along a part locus with a substantially greater degree of accuracy than has been attained previously in the art by referencing and then monitoring only the tool motion relative to a reference position located on the machine base.

  20. Xyce parallel electronic simulator : reference guide.

    SciTech Connect (OSTI)

    Mei, Ting; Rankin, Eric Lamont; Thornquist, Heidi K.; Santarelli, Keith R.; Fixel, Deborah A.; Coffey, Todd Stirling; Russo, Thomas V.; Schiek, Richard Louis; Warrender, Christina E.; Keiter, Eric Richard; Pawlowski, Roger Patrick

    2011-05-01

    This document is a reference guide to the Xyce Parallel Electronic Simulator, and is a companion document to the Xyce Users Guide. The focus of this document is (to the extent possible) exhaustively list device parameters, solver options, parser options, and other usage details of Xyce. This document is not intended to be a tutorial. Users who are new to circuit simulation are better served by the Xyce Users Guide. The Xyce Parallel Electronic Simulator has been written to support, in a rigorous manner, the simulation needs of the Sandia National Laboratories electrical designers. It is targeted specifically to run on large-scale parallel computing platforms but also runs well on a variety of architectures including single processor workstations. It also aims to support a variety of devices and models specific to Sandia needs. This document is intended to complement the Xyce Users Guide. It contains comprehensive, detailed information about a number of topics pertinent to the usage of Xyce. Included in this document is a netlist reference for the input-file commands and elements supported within Xyce; a command line reference, which describes the available command line arguments for Xyce; and quick-references for users of other circuit codes, such as Orcad's PSpice and Sandia's ChileSPICE.

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

    SciTech Connect (OSTI)

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

    2014-08-15

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

  2. Gasoline price forecast to stay below 3 dollar a gallon in 2015

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

    Gasoline price forecast to stay below $3 a gallon in 2015 The national average pump price of gasoline is expected to stay below $3 per gallon during 2015. In its new monthly forecast, the U.S. Energy Information Administration said the retail price for regular gasoline should average $2.33 per gallon this year. The price of gasoline increased in early February after falling for 17 weeks in a row. But gasoline prices will continue to remain low in 2015 when compared with pump prices in recent

  3. EERE Success Story-Solar Forecasting Gets a Boost from Watson, Accuracy

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

    Improved by 30% | Department of Energy Forecasting Gets a Boost from Watson, Accuracy Improved by 30% EERE Success Story-Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% October 27, 2015 - 11:48am Addthis IBM Youtube Video | Courtesy of IBM Remember when IBM's super computer Watson defeated Jeopardy! champions Ken Jennings and Brad Rutter? With funding from the U.S. Department of Energy SunShot Initiative, IBM researchers are using Watson-like technology to improve solar

  4. Updated Buildings Sector Appliance and Equipment Costs and Efficiency

    Gasoline and Diesel Fuel Update (EIA)

    Full report (4.1 mb) Heating, cooling, & water heating equipment Appendix A - Technology Forecast Updates - Residential and Commercial Building Technologies - Reference Case (1.9...

  5. Category:Smart Grid References | Open Energy Information

    Open Energy Info (EERE)

    Category Edit History Category:Smart Grid References Jump to: navigation, search Add a new Reference Pages in category "Smart Grid References" The following 11 pages are in this...

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

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2003-12-01

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

  7. Reference electrode for strong oxidizing acid solutions

    DOE Patents [OSTI]

    Rigdon, Lester P.; Harrar, Jackson E.; Bullock, Sr., Jack C.; McGuire, Raymond R.

    1990-01-01

    A reference electrode for the measurement of the oxidation-reduction potentials of solutions is especially suitable for oxidizing solutions such as highly concentrated and fuming nitric acids, the solutions of nitrogen oxides, N.sub.2 O.sub.4 and N.sub.2 O.sub.5, in nitric acids. The reference electrode is fabricated of entirely inert materials, has a half cell of Pt/Ce(IV)/Ce(III)/70 wt. % HNO.sub.3, and includes a double-junction design with an intermediate solution of 70 wt. % HNO.sub.3. The liquid junctions are made from Corning No. 7930 glass for low resistance and negligible solution leakage.

  8. Natural Gas Business Case (Webinar) | Open Energy Information

    Open Energy Info (EERE)

    future market outlook. References Retrieved from "http:en.openei.orgwindex.php?titleNaturalGasBusinessCase(Webinar)&oldid514498" Feedback Contact needs updating Image...

  9. References & Links | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    References & Links 48CFR Chapter 9, Acquisition Regulation (DEAR) Department of Energy Acquisition Requirements (DEAR) DOE Order 470.4B, Safeguards and Security Program DOE Order 472.2, Personnel Security DOE Order 206.2 DOE Order 470.4B Executive Order 10865 Executive Order 12968 Federal Acquisition Regulation (FAR) Federal Bureau of Investigations FIPS PUB 201-2, Personal Identity Verification (PIV) of Federal Employees and Contractors Intelligence Reform and Terrorism Prevention Act of

  10. Floating Oscillating Water Column Reference Model Completed

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

    Floating Oscillating Water Column Reference Model Completed - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Fuel Cycle Defense

  11. Technical Reference for Hydrogen Compatibility of Materials

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

    15/2008 Technical Reference on Hydrogen Compatibility of Materials Austenitc Steels: 300-Series Stainless Alloys Stabilized Alloys, Types 321 and 347 (code 2104) Prepared by: B.P. Somerday, Sandia National Laboratories, Livermore CA Editors C. San Marchi B.P. Somerday Sandia National Laboratories This report may be updated and revised periodically in response to the needs of the technical community; up-to-date versions can be requested from the editors at the address given below or downloaded at

  12. Technical Reference on Hydrogen Compatibility of Materials

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

    Type 316 (code 2103) Prepared by: C. San Marchi, Sandia National Laboratories Editors C. San Marchi B.P. Somerday Sandia National Laboratories This report may be updated and revised periodically in response to the needs of the technical community; up-to-date versions can be requested from the editors at the address given below. The success of this reference depends upon feedback from the technical community; please forward your comments, suggestions, criticisms and relevant public- domain data

  13. Technical Reference on Hydrogen Compatibility of Materials

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

    321 Unlimited Release Printed September 2012 Technical Reference for Hydrogen Compatibility of Materials C. San Marchi B.P. Somerday Prepared by Sandia National Laboratories Albuquerque, New Mexico 87185 and Livermore, California 94550 Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract

  14. The Hydrogen Laboratory and The Brazilian Reference Center for...

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

    The Hydrogen Laboratory and The Brazilian Reference Center for Hydrogen Energy The Hydrogen Laboratory and The Brazilian Reference Center for Hydrogen Energy Presentation given by ...

  15. NPS Reference Manual 53: Special Park Uses | Open Energy Information

    Open Energy Info (EERE)

    search OpenEI Reference LibraryAdd to library PermittingRegulatory Guidance - Inner-Office Memorandum: NPS Reference Manual 53: Special Park UsesPermittingRegulatory...

  16. Biomass Scenario Model Documentation: Data and References Lin...

    Office of Scientific and Technical Information (OSTI)

    Documentation: Data and References Lin, Y.; Newes, E.; Bush, B.; Peterson, S.; Stright, D. 09 BIOMASS FUELS BIOMASS SCENARIO MODEL; BSM; BIOMASS; BIOFUEL; MODEL; DATA; REFERENCES;...

  17. Terms of Reference for the International Partnership for the...

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

    Terms of Reference for the International Partnership for the Hydrogen Economy Terms of Reference for the International Partnership for the Hydrogen Economy Updated version (October ...

  18. Detailed HCCI Exhaust Speciation - ORNL Reference Fuel Blends...

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

    HCCI Exhaust Speciation - ORNL Reference Fuel Blends Detailed HCCI Exhaust Speciation - ORNL Reference Fuel Blends *Accurately measure exhaust profile from an HCCI engine with a ...

  19. Archive Reference Buildings by Climate Zone: 3A Atlanta, Georgia...

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

    More Documents & Publications Archive Reference Buildings by Climate Zone: 3B Los Angeles, California Archive Reference Buildings by Climate Zone: 3B Las Vegas, Nevada Archive ...

  20. Plutonium Certified Reference Materials Price List | U.S. DOE...

    Office of Science (SC) Website

    NBL Program Office Home About Programs Certified Reference Materials (CRMs) Prices and ... Prices and Certificates Plutonium Certified Reference Materials Price List Print Text ...