National Library of Energy BETA

Sample records for year forecast 2

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

    SciTech Connect (OSTI)

    1996-02-01

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

  2. 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.

  3. 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.

  4. 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.

  5. HONEYWELL - KANSAS CITY PLANT FISCAL YEARS 2009 THRU 2015 SMALL BUSINESS PROGRAM RESULTS & FORECAST

    National Nuclear Security Administration (NNSA)

    HONEYWELL - KANSAS CITY PLANT FISCAL YEARS 2009 THRU 2015 SMALL BUSINESS PROGRAM RESULTS & FORECAST CATEGORY Total Procurement Total SB Small Disad. Bus Woman-Owned SB Hub-Zone SB Veteran-Owned SB Service Disabled Vet. SB FY 2009 Dollars Goal (projected) $183,949,920 $82,690,000 $4,550,000 $8,829,596 $3,370,000 $5,025,000 $460,000 FY 2009 Dollars Accomplished $143,846,731 $68,174,398 $9,247,214 $11,333,905 $4,979,858 $6,713,791 $1,612,136 FY 2009 % Goal 45.0% 2.5% 4.8% 1.8% 2.7% 0.25% FY

  6. Summer gasoline price forecast slightly higher, but drivers still pay less than last year

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

    Summer gasoline price forecast slightly higher, but drivers still pay less than last year Rising crude oil prices are likely to be passed on to consumers at the pump, but U.S. drivers are still expected to pay the lowest summer gasoline prices since 2004, and for all of 2016 the average household will spend $900 less on gasoline than it did two years ago." In its new monthly forecast, the U.S. Energy Information Administration said the retail price for regular grade gasoline will average

  7. Regional forecasting with global atmospheric models; Third year report

    SciTech Connect (OSTI)

    Crowley, T.J.; North, G.R.; Smith, N.R.

    1994-05-01

    This report was prepared by the Applied Research Corporation (ARC), College Station, Texas, under subcontract to Pacific Northwest Laboratory (PNL) as part of a global climate studies task. The task supports site characterization work required for the selection of a potential high-level nuclear waste repository and is part of the Performance Assessment Scientific Support (PASS) Program at PNL. The work is under the overall direction of the Office of Civilian Radioactive Waste Management (OCRWM), US Department of Energy Headquarters, Washington, DC. The scope of the report is to present the results of the third year`s work on the atmospheric modeling part of the global climate studies task. The development testing of computer models and initial results are discussed. The appendices contain several studies that provide supporting information and guidance to the modeling work and further details on computer model development. Complete documentation of the models, including user information, will be prepared under separate reports and manuals.

  8. Validation of a 20-year forecast of US childhood lead poisoning: Updated prospects for 2010

    SciTech Connect (OSTI)

    Jacobs, David E. . E-mail: dejacobs@starpower.net; Nevin, Rick

    2006-11-15

    We forecast childhood lead poisoning and residential lead paint hazard prevalence for 1990-2010, based on a previously unvalidated model that combines national blood lead data with three different housing data sets. The housing data sets, which describe trends in housing demolition, rehabilitation, window replacement, and lead paint, are the American Housing Survey, the Residential Energy Consumption Survey, and the National Lead Paint Survey. Blood lead data are principally from the National Health and Nutrition Examination Survey. New data now make it possible to validate the midpoint of the forecast time period. For the year 2000, the model predicted 23.3 million pre-1960 housing units with lead paint hazards, compared to an empirical HUD estimate of 20.6 million units. Further, the model predicted 498,000 children with elevated blood lead levels (EBL) in 2000, compared to a CDC empirical estimate of 434,000. The model predictions were well within 95% confidence intervals of empirical estimates for both residential lead paint hazard and blood lead outcome measures. The model shows that window replacement explains a large part of the dramatic reduction in lead poisoning that occurred from 1990 to 2000. Here, the construction of the model is described and updated through 2010 using new data. Further declines in childhood lead poisoning are achievable, but the goal of eliminating children's blood lead levels {>=}10 {mu}g/dL by 2010 is unlikely to be achieved without additional action. A window replacement policy will yield multiple benefits of lead poisoning prevention, increased home energy efficiency, decreased power plant emissions, improved housing affordability, and other previously unrecognized benefits. Finally, combining housing and health data could be applied to forecasting other housing-related diseases and injuries.

  9. Navy Mobility Fuels Forecasting System report: Navy fuel production in the year 2000

    SciTech Connect (OSTI)

    Hadder, G.R.; Davis, R.M.

    1991-09-01

    The Refinery Yield Model of the Navy Mobility Fuels Forecasting System has been used to study the feasibility and quality of Navy JP-5 jet fuel and F-76 marine diesel fuel for two scenarios in the year 2000. Both scenarios account for environmental regulations for fuels produced in the US and assume that Eastern Europe, the USSR, and the People`s Republic of China have free market economies. One scenario is based on business-as-usual market conditions for the year 2000. The second scenario is similar to first except that USSR crude oil production is 24 percent lower. During lower oil production in the USSR., there are no adverse effects on Navy fuel availability, but JP-5 is generally a poorer quality fuel relative to business-as-usual in the year 2000. In comparison with 1990, there are two potential problems areas for future Navy fuel quality. The first problem is increased aromaticity of domestically produced Navy fuels. Higher percentages of aromatics could have adverse effects on storage, handling, and combustion characteristics of both JP-5 and F-76. The second, and related, problem is that highly aromatic light cycle oils are blended into F-76 at percentages which promote fuel instability. It is recommended that the Navy continue to monitor the projected trend toward increased aromaticity in JP-5 and F-76 and high percentages of light cycle oils in F-76. These potential problems should be important considerations in research and development for future Navy engines.

  10. Navy Mobility Fuels Forecasting System report: Navy fuel production in the year 2000

    SciTech Connect (OSTI)

    Hadder, G.R.; Davis, R.M.

    1991-09-01

    The Refinery Yield Model of the Navy Mobility Fuels Forecasting System has been used to study the feasibility and quality of Navy JP-5 jet fuel and F-76 marine diesel fuel for two scenarios in the year 2000. Both scenarios account for environmental regulations for fuels produced in the US and assume that Eastern Europe, the USSR, and the People's Republic of China have free market economies. One scenario is based on business-as-usual market conditions for the year 2000. The second scenario is similar to first except that USSR crude oil production is 24 percent lower. During lower oil production in the USSR., there are no adverse effects on Navy fuel availability, but JP-5 is generally a poorer quality fuel relative to business-as-usual in the year 2000. In comparison with 1990, there are two potential problems areas for future Navy fuel quality. The first problem is increased aromaticity of domestically produced Navy fuels. Higher percentages of aromatics could have adverse effects on storage, handling, and combustion characteristics of both JP-5 and F-76. The second, and related, problem is that highly aromatic light cycle oils are blended into F-76 at percentages which promote fuel instability. It is recommended that the Navy continue to monitor the projected trend toward increased aromaticity in JP-5 and F-76 and high percentages of light cycle oils in F-76. These potential problems should be important considerations in research and development for future Navy engines.

  11. YEAR 2 BIOMASS UTILIZATION

    SciTech Connect (OSTI)

    Christopher J. Zygarlicke

    2004-11-01

    This Energy & Environmental Research Center (EERC) Year 2 Biomass Utilization Final Technical Report summarizes multiple projects in biopower or bioenergy, transportation biofuels, and bioproducts. A prototype of a novel advanced power system, termed the high-temperature air furnace (HITAF), was tested for performance while converting biomass and coal blends to energy. Three biomass fuels--wood residue or hog fuel, corn stover, and switchgrass--and Wyoming subbituminous coal were acquired for combustion tests in the 3-million-Btu/hr system. Blend levels were 20% biomass--80% coal on a heat basis. Hog fuel was prepared for the upcoming combustion test by air-drying and processing through a hammer mill and screen. A K-Tron biomass feeder capable of operating in both gravimetric and volumetric modes was selected as the HITAF feed system. Two oxide dispersion-strengthened (ODS) alloys that would be used in the HITAF high-temperature heat exchanger were tested for slag corrosion rates. An alumina layer formed on one particular alloy, which was more corrosion-resistant than a chromia layer that formed on the other alloy. Research activities were completed in the development of an atmospheric pressure, fluidized-bed pyrolysis-type system called the controlled spontaneous reactor (CSR), which is used to process and condition biomass. Tree trimmings were physically and chemically altered by the CSR process, resulting in a fuel that was very suitable for feeding into a coal combustion or gasification system with little or no feed system modifications required. Experimental procedures were successful for producing hydrogen from biomass using the bacteria Thermotoga, a deep-ocean thermal vent organism. Analytical procedures for hydrogen were evaluated, a gas chromatography (GC) method was derived for measuring hydrogen yields, and adaptation culturing and protocols for mutagenesis were initiated to better develop strains that can use biomass cellulose. Fly ash derived from

  12. 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.

  13. 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

  14. 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.

  15. Energy Department Announces $2.5 Million to Improve Wind Forecasting...

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

    turbines operate closer to maximum capacity, leading to lower energy costs for consumers. ... for the Weather Research and Forecasting model, a widely used weather prediction system. ...

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

    SciTech Connect (OSTI)

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

    1995-12-01

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

  17. 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:...

  18. Gasoline price to average below $2 in 2016 for first time in 12 years

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

    Gasoline price to average below $2 in 2016 for first time in 12 years The annual average price for U.S. regular-grade gasoline is expected to fall below $2 per gallon this year for the first time since 2004. In its new monthly forecast, the U.S. Energy Information Administration said drivers will pay on average $1.98 per gallon to fill up at the pump with regular-grade gasoline. EIA expects the monthly average price of gasoline to reach a seven-year low of $1.82 per gallon in February, before

  19. Forecast Change

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

    Forecast Change 2011 2012 2013 2014 2015 2016 from 2015 United States Usage (kWh) 3,444 3,354 3,129 3,037 3,151 3,302 4.8% Price (cents/kWh) 12.06 12.09 12.58 13.04 12.95 12.84 -0.9% Expenditures $415 $405 $393 $396 $408 $424 3.9% New England Usage (kWh) 2,122 2,188 2,173 1,930 1,992 2,082 4.5% Price (cents/kWh) 15.85 15.50 16.04 17.63 18.64 18.37 -1.5% Expenditures $336 $339 $348 $340 $371 $382 3.0% Mid-Atlantic Usage (kWh) 2,531 2,548 2,447 2,234 2,371 2,497 5.3% Price (cents/kWh) 16.39 15.63

  20. 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....

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    National Nuclear Security Administration (NNSA)

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    National Nuclear Security Administration (NNSA)

    of Employees 14 GENDER YEAR 2012 Males 9 Females 5 YEAR 2012 SES 2 EJEK 2 NN (Engineering) 4 NQ (ProfTechAdmin) 6 YEAR 2012 American Indian Male 0 American Indian Female 0...

  5. Why Models Don%3CU%2B2019%3Et Forecast.

    SciTech Connect (OSTI)

    McNamara, Laura A.

    2010-08-01

    The title of this paper, Why Models Don't Forecast, has a deceptively simple answer: models don't forecast because people forecast. Yet this statement has significant implications for computational social modeling and simulation in national security decision making. Specifically, it points to the need for robust approaches to the problem of how people and organizations develop, deploy, and use computational modeling and simulation technologies. In the next twenty or so pages, I argue that the challenge of evaluating computational social modeling and simulation technologies extends far beyond verification and validation, and should include the relationship between a simulation technology and the people and organizations using it. This challenge of evaluation is not just one of usability and usefulness for technologies, but extends to the assessment of how new modeling and simulation technologies shape human and organizational judgment. The robust and systematic evaluation of organizational decision making processes, and the role of computational modeling and simulation technologies therein, is a critical problem for the organizations who promote, fund, develop, and seek to use computational social science tools, methods, and techniques in high-consequence decision making.

  6. Year 2 Report: Protein Function Prediction Platform

    SciTech Connect (OSTI)

    Zhou, C E

    2012-04-27

    Upon completion of our second year of development in a 3-year development cycle, we have completed a prototype protein structure-function annotation and function prediction system: Protein Function Prediction (PFP) platform (v.0.5). We have met our milestones for Years 1 and 2 and are positioned to continue development in completion of our original statement of work, or a reasonable modification thereof, in service to DTRA Programs involved in diagnostics and medical countermeasures research and development. The PFP platform is a multi-scale computational modeling system for protein structure-function annotation and function prediction. As of this writing, PFP is the only existing fully automated, high-throughput, multi-scale modeling, whole-proteome annotation platform, and represents a significant advance in the field of genome annotation (Fig. 1). PFP modules perform protein functional annotations at the sequence, systems biology, protein structure, and atomistic levels of biological complexity (Fig. 2). Because these approaches provide orthogonal means of characterizing proteins and suggesting protein function, PFP processing maximizes the protein functional information that can currently be gained by computational means. Comprehensive annotation of pathogen genomes is essential for bio-defense applications in pathogen characterization, threat assessment, and medical countermeasure design and development in that it can short-cut the time and effort required to select and characterize protein biomarkers.

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    National Nuclear Security Administration (NNSA)

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  16. U.S. gasoline price expected to average less than $2 a gallon both this year and next

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

    U.S. gasoline price expected to average less than $2 a gallon both this year and next U.S. drivers are now expected to see back-to-back years of annual average gasoline prices below $2 per gallon for the first time in more than a decade. In its latest monthly forecast, the U.S. Energy Information Administration said low oil prices will keep the average annual price for a gallon of regular-grade gasoline at $1.89 this year and at $1.97 in 2017. The last time gasoline averaged less than $2 for two

  17. Residential applliance data, assumptions and methodology for end-use forecasting with EPRI-REEPS 2.1

    SciTech Connect (OSTI)

    Hwang, R.J,; Johnson, F.X.; Brown, R.E.; Hanford, J.W.; Kommey, J.G.

    1994-05-01

    This report details the data, assumptions and methodology for end-use forecasting of appliance energy use in the US residential sector. Our analysis uses the modeling framework provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which was developed by the Electric Power Research Institute. In this modeling framework, appliances include essentially all residential end-uses other than space conditioning end-uses. We have defined a distinct appliance model for each end-use based on a common modeling framework provided in the REEPS software. This report details our development of the following appliance models: refrigerator, freezer, dryer, water heater, clothes washer, dishwasher, lighting, cooking and miscellaneous. Taken together, appliances account for approximately 70% of electricity consumption and 30% of natural gas consumption in the US residential sector. Appliances are thus important to those residential sector policies or programs aimed at improving the efficiency of electricity and natural gas consumption. This report is primarily methodological in nature, taking the reader through the entire process of developing the baseline for residential appliance end-uses. Analysis steps documented in this report include: gathering technology and market data for each appliance end-use and specific technologies within those end-uses, developing cost data for the various technologies, and specifying decision models to forecast future purchase decisions by households. Our implementation of the REEPS 2.1 modeling framework draws on the extensive technology, cost and market data assembled by LBL for the purpose of analyzing federal energy conservation standards. The resulting residential appliance forecasting model offers a flexible and accurate tool for analyzing the effect of policies at the national level.

  18. 2013 2nd Qtr Package

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

    FY 2013 through March 31, 2013 Agency * The end-of-year (EOY) Agency adjusted net revenue forecast for the 2 nd Quarter Review is 21 million. o This forecast is 44 million...

  19. Forecasting the market for SO sub 2 emission allowances under uncertainty

    SciTech Connect (OSTI)

    Hanson, D.; Molburg, J.; Fisher, R.; Boyd, G.; Pandola, G.; Lurie, G.; Taxon, T.

    1991-01-01

    This paper deals with the effects of uncertainty and risk aversion on market outcomes for SO{sub 2} emission allowance prices and on electric utility compliance choices. The 1990 Clean Air Act Amendments (CAAA), which are briefly reviewed here, provide for about twice as many SO{sub 2} allowances to be issued per year in Phase 1 (1995--1999) than in Phase 2. Considering the scrubber incentives in Phase 1, there is likely to be substantial emission banking for use in Phase 2. Allowance prices are expected to increase over time at a rate less than the return on alternative investments, so utilities which are risk neutral, or potential speculators in the allowance market, are not expected to bank allowances. The allowances will be banked by utilities that are risk averse. The Argonne Utility Simulation Model (ARGUS2) is being revised to incorporate the provisions of the CAAA acid rain title and to simulate SO{sub 2} allowance prices, compliance choices, capacity expansion, system dispatch, fuel use, and emissions using a unit level data base and alternative scenario assumptions. 1 fig.

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    563 YEAR 2012 Males 518 Females 45 YEAR 2012 SES 1 EJEK 2 EN 04 1 EN 03 1 NN (Engineering) 12 NQ (ProfTechAdmin) 209 NU (TechAdmin Support) 2 NV (Nuc Mat Courier) 335 YEAR 2012...

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    National Nuclear Security Administration (NNSA)

    78 YEAR 2012 Males 57 Females 21 YEAR 2012 SES 2 SL 1 EJEK 12 EN 04 21 EN 03 2 NN (Engineering) 12 NQ (ProfTechAdmin) 24 NU (TechAdmin Support) 4 YEAR 2012 American Indian Male...

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

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2005-08-17

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

  4. YEAR

    National Nuclear Security Administration (NNSA)

    Males 139 Females 88 YEAR 2012 SES 13 EX 1 EJEK 8 EN 05 23 EN 04 20 EN 03 2 NN (Engineering) 91 NQ (ProfTechAdmin) 62 NU (TechAdmin Support) 7 YEAR 2012 American Indian...

  5. Property:Building/YearConstruction2 | Open Energy Information

    Open Energy Info (EERE)

    to: navigation, search This is a property of type Date. Year of construction 2 (Year of construction) Pages using the property "BuildingYearConstruction2" Showing 25 pages using...

  6. 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...

  7. YEAR

    National Nuclear Security Administration (NNSA)

    26 YEAR 2014 Males 81 Females 45 PAY PLAN YEAR 2014 SES 1 SL1 EJEK 25 EN 04 26 EN 03 2 NN (Engineering) 23 NQ (ProfTechAdmin) 44 NU (TechAdmin Support) 4 YEAR 2014 American ...

  8. YEAR

    National Nuclear Security Administration (NNSA)

    4 YEAR 2012 Males 37 Females 7 YEAR 2012 SES 1 EJEK 6 EN 05 5 EN 04 7 EN 03 1 NN (Engineering) 17 NQ (ProfTechAdmin) 6 NU (TechAdmin Support) 1 YEAR 2012 American Indian Male 2...

  9. YEAR

    National Nuclear Security Administration (NNSA)

    7 YEAR 2011 Males 38 Females 9 YEAR 2011 SES 1 EJEK 6 EN 05 5 EN 04 7 EN 03 1 NN (Engineering) 19 NQ (ProfTechAdmin) 7 NU (TechAdmin Support) 1 YEAR 2011 American Indian Male 2...

  10. YEAR

    National Nuclear Security Administration (NNSA)

    8 YEAR 2013 Males 62 Females 26 YEAR 2013 SES 1 EJEK 3 EN 05 1 EN 04 28 EN 03 1 NN (Engineering) 25 NQ (ProfTechAdmin) 27 NU (TechAdmin Support) 2 YEAR 2013 American Indian...

  11. 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).

  12. 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).

  13. YEAR

    National Nuclear Security Administration (NNSA)

    563 YEAR 2014 Males 517 Females 46 PAY PLAN YEAR 2014 SES 2 EJ/EK 2 EN 04 1 NN (Engineering) 11 NQ (Prof/Tech/Admin) 218 NU (Tech/Admin Support) 2 NV (Nuc Mat Courier) 327 YEAR 2014 American Indian Alaska Native Male (AIAN M) 14 American Indian Alaskan Native Female (AIAN F) 2 African American Male (AA M) 18 African American Female (AA F) 1 Asian American Pacific Islander Male (AAPI M) 8 Asian American Pacific Islander Female (AAPI F) 2 Hispanic Male (H M) 76 Hispanic Female (H F) 21 White Male

  14. YEAR

    National Nuclear Security Administration (NNSA)

    2012 Males 149 Females 115 YEAR 2012 SES 17 EX 1 EJEK 7 EN 05 2 EN 04 9 EN 03 2 NN (Engineering) 56 NQ (ProfTechAdmin) 165 NU (TechAdmin Support) 4 GS 13 1 YEAR 2012 American...

  15. Onboarding Year 2 | Argonne National Laboratory

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

    2 Performance Evaluation Process For Postdoctoral Appointments to be extended, all postdocs are required to complete a Postdoctoral Performance Evaluation Form in collaboration...

  16. YEAR

    National Nuclear Security Administration (NNSA)

    446 YEAR 2014 Males 1626 Females 820 YEAR 2014 SES 97 EX 2 ED 1 SL 1 EJ/EK 84 EN 05 38 EN 04 162 EN 03 18 NN (Engineering) 427 NQ (Prof/Tech/Admin) 1216 NU (Tech/Admin Support) 66 NV (Nuc Mat Courier) 327 GS 15 2 GS 14 2 GS 13 2 GS 10 1 YEAR 2014 American Indian Alaska Native Male (AIAN M) 27 American Indian Alaskan Native Female (AIAN F) 24 African American Male (AA M) 90 African American Female (AA F) 141 Asian American Pacific Islander Male (AAPI M) 63 Asian American Pacific Islander Female

  17. YEAR

    National Nuclear Security Administration (NNSA)

    2 YEAR 2014 Males 57 Females 25 PAY PLAN YEAR 2014 SES 3 EJ/EK 4 EN 04 2 NN (Engineering) 20 NQ (Prof/Tech/Admin) 53 YEAR 2014 American Indian Alaska Native Male (AIAN M) 0 American Indian Alaskan Native Female (AIAN F) 0 African American Male (AA M) 9 African American Female (AA F) 9 Asian American Pacific Islander Male (AAPI M) 2 Asian American Pacific Islander Female (AAPI F) 1 Hispanic Male (H M) 3 Hispanic Female (H F) 5 White Male (W M) 43 White Female (W F) 10 DIVERSITY TOTAL WORKFORCE

  18. YEAR

    National Nuclear Security Administration (NNSA)

    YEAR 2014 Males 11 Females 2 PAY PLAN YEAR 2014 SES 2 EJ/EK 1 EN 04 1 NN (Engineering) 5 NQ (Prof/Tech/Admin) 4 YEAR 2014 American Indian Alaska Native Male (AIAN M) 0 American Indian Alaskan Native Female (AIAN F) 0 African American Male (AA M) 0 African American Female (AA F) 0 Asian American Pacific Islander Male (AAPI M) 1 Asian American Pacific Islander Female (AAPI F) 0 Hispanic Male (H M) 0 Hispanic Female (H F) 0 White Male (W M) 10 White Female (W F) 2 DIVERSITY TOTAL WORKFORCE GENDER

  19. YEAR

    National Nuclear Security Administration (NNSA)

    4 YEAR 2014 Males 7 Females 7 PAY PLAN YEAR 2014 SES 1 NQ (Prof/Tech/Admin) 7 GS 15 1 GS 14 2 GS 13 2 GS 10 1 YEAR 2014 American Indian Alaska Native Male (AIAN M) 0 American Indian Alaskan Native Female (AIAN F) 0 African American Male (AA M) 3 African American Female (AA F) 2 Asian American Pacific Islander Male (AAPI M) 0 Asian American Pacific Islander Female (AAPI F) 0 Hispanic Male (H M) 0 Hispanic Female (H F) 0 White Male (W M) 4 White Female (W F) 5 DIVERSITY TOTAL WORKFORCE GENDER

  20. YEAR

    National Nuclear Security Administration (NNSA)

    5 YEAR 2014 Males 92 Females 43 YEAR 2014 SES 8 EX 1 EJ/EK 4 EN 05 9 EN 04 12 EN 03 2 NN (Engineering) 57 NQ (Prof/Tech/Admin) 42 YEAR 2014 American Indian Alaska Native Male (AIAN M) 1 American Indian Alaskan Native Female (AIAN F) 1 African American Male (AA M) 9 African American Female (AA F) 11 Asian American Pacific Islander Male (AAPI M) 4 Asian American Pacific Islander Female (AAPI F) 2 Hispanic Male (H M) 12 Hispanic Female (H F) 7 White Male (W M) 66 White Female (W F) 22 PAY PLAN

  1. YEAR

    National Nuclear Security Administration (NNSA)

    16 YEAR 2014 Males 72 Females 144 PAY PLAN YEAR 2014 SES 8 EJ/EK 1 NQ (Prof/Tech/Admin) 198 NU (Tech/Admin Support) 9 YEAR 2014 American Indian Alaska Native Male (AIAN M) 2 American Indian Alaskan Native Female (AIAN F) 2 African American Male (AA M) 10 African American Female (AA F) 38 Asian American Pacific Islander Male (AAPI M) 1 Asian American Pacific Islander Female (AAPI F) 3 Hispanic Male (H M) 15 Hispanic Female (H F) 33 White Male (W M) 44 White Female (W F) 68 DIVERSITY TOTAL

  2. YEAR

    National Nuclear Security Administration (NNSA)

    1 YEAR 2014 Males 48 Females 33 PAY PLAN YEAR 2014 SES 1 EJ/EK 8 EN 04 10 EN 03 1 NN (Engineering) 27 NQ (Prof/Tech/Admin) 29 NU (Tech/Admin Support) 5 YEAR 2014 American Indian Alaska Native Male (AIAN M) 0 American Indian Alaskan Native Female (AIAN F) 3 African American Male (AA M) 0 African American Female (AA F) 2 Asian American Pacific Islander Male (AAPI M) 2 Asian American Pacific Islander Female (AAPI F) 0 Hispanic Male (H M) 12 Hispanic Female (H F) 12 White Male (W M) 34 White Female

  3. YEAR

    National Nuclear Security Administration (NNSA)

    9 Females 24 PAY PLAN YEAR 2014 SES 1 EJ/EK 4 EN 05 3 EN 04 22 EN 03 8 NN (Engineering) 15 NQ (Prof/Tech/Admin) 27 NU (Tech/Admin Support) 3 YEAR 2014 American Indian Alaska Native Male (AIAN M) 2 American Indian Alaskan Native Female (AIAN F) 1 African American Male (AA M) 5 African American Female (AA F) 2 Asian American Pacific Islander Male (AAPI M) 21 Asian American Pacific Islander Female (AAPI F) 2 Hispanic Male (H M) 5 Hispanic Female (H F) 3 White Male (W M) 26 White Female (W F) 16

  4. YEAR

    National Nuclear Security Administration (NNSA)

    8 Females 25 PAY PLAN YEAR 2014 SES 1 EJ/EK 3 EN 05 1 EN 04 25 EN 03 1 NN (Engineering) 25 NQ (Prof/Tech/Admin) 25 NU (Tech/Admin Support) 2 YEAR 2014 American Indian Alaska Native Male (AIAN M) 1 American Indian Alaskan Native Female (AIAN F) 1 African American Male (AA M) 3 African American Female (AA F) 3 Asian American Pacific Islander Male (AAPI M) 2 Asian American Pacific Islander Female (AAPI F) 2 Hispanic Male (H M) 6 Hispanic Female (H F) 6 White Male (W M) 46 White Female (W F) 13

  5. YEAR

    National Nuclear Security Administration (NNSA)

    -9.09% YEAR 2012 2013 SES 1 1 0.00% EN 05 1 1 0.00% EN 04 11 11 0.00% NN (Engineering) 8 8 0.00% NQ (ProfTechAdmin) 17 14 -17.65% NU (TechAdmin Support) 2 2...

  6. YEAR

    National Nuclear Security Administration (NNSA)

    5 YEAR 2014 Males 61 Females 24 PAY PLAN YEAR 2014 SES 1 EJ/EK 8 EN 04 22 NN (Engineering) 23 NQ (Prof/Tech/Admin) 28 NU (Tech/Admin Support) 3 YEAR 2014 American Indian Alaska Native Male (AIAN M) 2 American Indian Alaskan Native Female (AIAN F) 3 African American Male (AA M) 0 African American Female (AA F) 0 Asian American Pacific Islander Male (AAPI M) 3 Asian American Pacific Islander Female (AAPI F) 0 Hispanic Male (H M) 13 Hispanic Female (H F) 10 White Male (W M) 43 White Female (W F) 11

  7. YEAR

    National Nuclear Security Administration (NNSA)

    93 YEAR 2014 Males 50 Females 43 PAY PLAN YEAR 2014 EJ/EK 3 NN (Engineering) 13 NQ (Prof/Tech/Admin) 74 NU (Tech/Admin Support) 3 YEAR 2014 American Indian Alaska Native Male (AIAN M) 0 American Indian Alaskan Native Female (AIAN F) 2 African American Male (AA M) 5 African American Female (AA F) 6 Asian American Pacific Islander Male (AAPI M) 0 Asian American Pacific Islander Female (AAPI F) 0 Hispanic Male (H M) 6 Hispanic Female (H F) 14 White Male (W M) 39 White Female (W F) 21 DIVERSITY

  8. YEAR

    National Nuclear Security Administration (NNSA)

    89 YEAR 2014 Males 98 Females 91 PAY PLAN YEAR 2014 SES 14 EX 1 EJ/EK 3 EN 05 1 EN 04 4 EN 03 1 NN (Engineering) 32 NQ (Prof/Tech/Admin) 130 NU (Tech/Admin Support) 2 GS 15 1 YEAR 2014 American Indian Alaska Native Male (AIAN M) 1 American Indian Alaskan Native Female (AIAN F) 0 African American Male (AA M) 5 African American Female (AA F) 14 Asian American Pacific Islander Male (AAPI M) 3 Asian American Pacific Islander Female (AAPI F) 7 Hispanic Male (H M) 7 Hispanic Female (H F) 10 White Male

  9. YEAR

    National Nuclear Security Administration (NNSA)

    3 YEAR 2014 Males 162 Females 81 PAY PLAN YEAR 2014 SES 26 EJ/EK 3 EN 05 7 NN (Engineering) 77 NQ (Prof/Tech/Admin) 108 NU (Tech/Admin Support) 22 YEAR 2014 American Indian Alaska Native Male (AIAN M) 0 American Indian Alaskan Native Female (AIAN F) 1 African American Male (AA M) 5 African American Female (AA F) 9 Asian American Pacific Islander Male (AAPI M) 1 Asian American Pacific Islander Female (AAPI F) 0 Hispanic Male (H M) 2 Hispanic Female (H F) 0 White Male (W M) 154 White Female (W F)

  10. YEAR

    National Nuclear Security Administration (NNSA)

    74 YEAR 2014 Males 96 Females 78 PAY PLAN YEAR 2014 SES 8 EJ/EK 4 EN 04 11 EN 03 1 NN (Engineering) 34 NQ (Prof/Tech/Admin) 113 NU (Tech/Admin Support) 3 YEAR 2014 American Indian Alaska Native Male (AIAN M) 2 American Indian Alaskan Native Female (AIAN F) 1 African American Male (AA M) 3 African American Female (AA F) 11 Asian American Pacific Islander Male (AAPI M) 5 Asian American Pacific Islander Female (AAPI F) 0 Hispanic Male (H M) 25 Hispanic Female (H F) 25 White Male (W M) 61 White

  11. YEAR

    National Nuclear Security Administration (NNSA)

    26 YEAR 2014 Males 81 Females 45 PAY PLAN YEAR 2014 SES 1 SL 1 EJ/EK 25 EN 04 26 EN 03 2 NN (Engineering) 23 NQ (Prof/Tech/Admin) 44 NU (Tech/Admin Support) 4 YEAR 2014 American Indian Alaska Native Male (AIAN M) 0 American Indian Alaskan Native Female (AIAN F) 1 African American Male (AA M) 3 African American Female (AA F) 7 Asian American Pacific Islander Male (AAPI M) 4 Asian American Pacific Islander Female (AAPI F) 1 Hispanic Male (H M) 6 Hispanic Female (H F) 6 White Male (W M) 68 White

  12. YEAR

    National Nuclear Security Administration (NNSA)

    8 YEAR 2014 Males 18 Females 20 PAY PLAN YEAR 2014 SES 3 EJ/EK 1 EN 03 1 NN (Engineering) 3 NQ (Prof/Tech/Admin) 28 NU (Tech/Admin Support) 2 YEAR 2014 American Indian Alaska Native Male (AIAN M) 0 American Indian Alaskan Native Female (AIAN F) 0 African American Male (AA M) 1 African American Female (AA F) 1 Asian American Pacific Islander Male (AAPI M) 0 Asian American Pacific Islander Female (AAPI F) 1 Hispanic Male (H M) 4 Hispanic Female (H F) 7 White Male (W M) 13 White Female (W F) 11

  13. Simulations of arctic mixed-phase clouds in forecasts with CAM3 and AM2 for M-PACE

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

    Xie, Shaocheng; Boyle, James; Klein, Stephen A.; Liu, Xiaohong; Ghan, Steven

    2008-02-27

    [1] Simulations of mixed-phase clouds in forecasts with the NCAR Atmosphere Model version 3 (CAM3) and the GFDL Atmospheric Model version 2 (AM2) for the Mixed-Phase Arctic Cloud Experiment (M-PACE) are performed using analysis data from numerical weather prediction centers. CAM3 significantly underestimates the observed boundary layer mixed-phase cloud fraction and cannot realistically simulate the variations of liquid water fraction with temperature and cloud height due to its oversimplified cloud microphysical scheme. In contrast, AM2 reasonably reproduces the observed boundary layer cloud fraction while its clouds contain much less cloud condensate than CAM3 and the observations. The simulation of themore » boundary layer mixed-phase clouds and their microphysical properties is considerably improved in CAM3 when a new physically based cloud microphysical scheme is used (CAM3LIU). The new scheme also leads to an improved simulation of the surface and top of the atmosphere longwave radiative fluxes. Sensitivity tests show that these results are not sensitive to the analysis data used for model initialization. Increasing model horizontal resolution helps capture the subgrid-scale features in Arctic frontal clouds but does not help improve the simulation of the single-layer boundary layer clouds. AM2 simulated cloud fraction and LWP are sensitive to the change in cloud ice number concentrations used in the Wegener-Bergeron-Findeisen process while CAM3LIU only shows moderate sensitivity in its cloud fields to this change. Furthermore, this paper shows that the Wegener-Bergeron-Findeisen process is important for these models to correctly simulate the observed features of mixed-phase clouds.« less

  14. YEAR

    National Nuclear Security Administration (NNSA)

    17 Females 18 PAY PLAN YEAR 2014 SES 1 EJ/EK 3 NQ (Prof/Tech/Admin) 30 NU (Tech/Admin Support) 1 YEAR 2014 American Indian Alaska Native Male (AIAN M) 1 American Indian Alaskan Native Female (AIAN F) 2 African American Male (AA M) 3 African American Female (AA F) 7 Asian American Pacific Islander Male (AAPI M) 1 Asian American Pacific Islander Female (AAPI F) 0 Hispanic Male (H M) 2 Hispanic Female (H F) 6 White Male (W M) 10 White Female (W F) 3 DIVERSITY TOTAL WORKFORCE GENDER Associate

  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. YEAR

    National Nuclear Security Administration (NNSA)

    YEAR 2012 2013 SES 2 1 -50.00% EN 05 0 1 100.00% EN 04 4 4 0.00% NN (Engineering) 13 12 -7.69% NQ (ProfTechAdmin) 13 9 -30.77% NU (TechAdmin Support) 1 1...

  17. YEAR

    National Nuclear Security Administration (NNSA)

    25 Females 10 YEAR 2014 SES 1 EN 04 11 NN (Engineering) 8 NQ (Prof/Tech/Admin) 13 NU (Tech/Admin Support) 2 YEAR 2014 American Indian Alaska Native Male (AIAN M) 0 American Indian Alaskan Native Female (AIAN F) 1 African American Male (AA M) 1 African American Female (AA F) 3 Asian American Pacific Islander Male (AAPI M) 0 Asian American Pacific Islander Female (AAPI F) 0 Hispanic Male (H M) 0 Hispanic Female (H F) 0 White Male (W M) 24 White Female (W F) 6 TOTAL WORKFORCE GENDER Kansas City

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

    SciTech Connect (OSTI)

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

    2014-04-30

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

  19. RACORO Forecasting

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

    7a. Space Heating by Census Region and Climate Zone, Million U.S. Households, 1993 Space Heating Characteristics RSE Column Factor: Total Census Region Climate Zone RSE Row Factors Northeast Midwest South West Fewer than 2,000 CDD and -- More than 2,000 CDD and Few- er than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Few- er than 4,000 HDD 0.5 0.9 1.1 0.8 0.8 1.6 1.3 1.2 1.2 1.1 Total ................................................. 96.6 19.5 23.3 33.5 20.4 8.7 26.5

  20. WPN 16-2: Program Year 2016 Grantee Allocations

    Broader source: Energy.gov [DOE]

    To provide Grantee allocations for the preparation and submission of applications for funding of the Weatherization Assistance Program (WAP) for Program Year (PY) 2016. Archived 01/08/16, Superseded by WPN 16-2A

  1. YEAR

    National Nuclear Security Administration (NNSA)

    69 YEAR 2014 Males 34 Females 35 YEAR 2014 SES 5 EJEK 1 EN 05 8 EN 04 5 NN (Engineering) 27 NQ (ProfTechAdmin) 22 NU (TechAdmin Support) 1 YEAR 2014 American Indian Alaska...

  2. YEAR

    National Nuclear Security Administration (NNSA)

    4 YEAR 2012 Males 65 Females 29 YEAR 2012 SES 3 EJEK 5 EN 04 3 NN (Engineering) 21 NQ (ProfTechAdmin) 61 NU (TechAdmin Support) 1 YEAR 2012 American Indian Male 0 American...

  3. YEAR

    National Nuclear Security Administration (NNSA)

    4 YEAR 2011 Males 21 Females 23 YEAR 2011 SES 3 EJEK 1 EN 03 1 NN (Engineering) 3 NQ (ProfTechAdmin) 31 NU (TechAdmin Support) 5 YEAR 2011 American Indian Male 0 American...

  4. YEAR

    National Nuclear Security Administration (NNSA)

    92 YEAR 2012 Males 52 Females 40 YEAR 2012 SES 1 EJEK 7 EN 04 13 EN 03 1 NN (Engineering) 27 NQ (ProfTechAdmin) 38 NU (TechAdmin Support) 5 YEAR 2012 American Indian Male 0...

  5. YEAR

    National Nuclear Security Administration (NNSA)

    02 YEAR 2011 Males 48 Females 54 YEAR 2011 SES 5 EJEK 1 NN (Engineering) 13 NQ (ProfTechAdmin) 80 NU (TechAdmin Support) 3 YEAR 2011 American Indian Male 0 American Indian...

  6. YEAR

    National Nuclear Security Administration (NNSA)

    86 YEAR 2012 Males 103 Females 183 YEAR 2012 SES 7 EJEK 1 NN (Engineering) 1 NQ (ProfTechAdmin) 202 NU (TechAdmin Support) 30 NF (Future Ldrs) 45 YEAR 2012 American Indian Male...

  7. YEAR

    National Nuclear Security Administration (NNSA)

    80 YEAR 2012 Males 51 Females 29 YEAR 2012 SES 1 EJEK 22 EN 04 21 NN (Engineering) 14 NQ (ProfTechAdmin) 21 NU (TechAdmin Support) 1 YEAR 2012 American Indian Male 0 American...

  8. YEAR

    National Nuclear Security Administration (NNSA)

    96 YEAR 2013 Males 69 Females 27 YEAR 2013 SES 1 EJEK 9 EN 04 27 NN (Engineering) 26 NQ (ProfTechAdmin) 30 NU (TechAdmin Support) 3 YEAR 2013 American Indian Alaska Native Male...

  9. YEAR

    National Nuclear Security Administration (NNSA)

    40 YEAR 2011 Males 68 Females 72 YEAR 2011 SES 5 EJEK 1 NN (Engineering) 16 NQ (ProfTechAdmin) 115 NU (TechAdmin Support) 3 YEAR 2011 American Indian Male 1 American Indian...

  10. YEAR

    National Nuclear Security Administration (NNSA)

    00 YEAR 2012 Males 48 Females 52 YEAR 2012 SES 5 EJEK 1 NN (Engineering) 11 NQ (ProfTechAdmin) 80 NU (TechAdmin Support) 3 YEAR 2012 American Indian Male 0 American Indian...

  11. YEAR

    National Nuclear Security Administration (NNSA)

    3 YEAR 2012 Males 21 Females 22 YEAR 2012 SES 3 EJEK 1 EN 03 1 NN (Engineering) 3 NQ (ProfTechAdmin) 30 NU (TechAdmin Support) 5 YEAR 2012 American Indian Male 0 American...

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

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

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

  13. YEAR

    National Nuclear Security Administration (NNSA)

    6 YEAR 2012 Males 64 Females 32 YEAR 2012 SES 1 EJEK 5 EN 05 3 EN 04 23 EN 03 9 NN (Engineering) 18 NQ (ProfTechAdmin) 33 NU (TechAdmin Support) 4 YEAR 2012 American Indian...

  14. YEAR

    National Nuclear Security Administration (NNSA)

    5 YEAR 2013 Males 58 Females 27 YEAR 2013 SES 1 EJEK 4 EN 05 3 EN 04 21 EN 03 8 NN (Engineering) 16 NQ (ProfTechAdmin) 28 NU (TechAdmin Support) 4 YEAR 2013 American Indian...

  15. 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...

  16. 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 ...

  17. 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...

  18. Forecasting Water Quality & Biodiversity

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

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

  19. 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.

  20. YEAR

    National Nuclear Security Administration (NNSA)

    9 YEAR 2014 Males 9 Females 10 YEAR 2014 SES 7 ED 1 EJ/EK 1 EN 05 1 NQ (Prof/Tech/Admin) 8 NU (Tech/Admin Support) 1 YEAR 2014 American Indian Alaska Native Male (AIAN M) 0 American Indian Alaskan Native Female (AIAN F) 1 African American Male (AA M) 1 African American Female (AA F) 5 Asian American Pacific Islander Male (AAPI M) 1 Asian American Pacific Islander Female (AAPI F) 0 Hispanic Male (H M) 0 Hispanic Female (H F) 3 White Male (W M) 7 White Female (W F) 1 PAY PLAN DIVERSITY TOTAL

  1. YEAR

    National Nuclear Security Administration (NNSA)

    8 YEAR 2014 Males 18 Females 10 PAY PLAN YEAR 2014 SES 1 EN 05 1 EN 04 4 NN (Engineering) 12 NQ (Prof/Tech/Admin) 9 NU (Tech/Admin Support) 1 YEAR 2014 American Indian Alaska Native Male (AIAN M) 0 American Indian Alaskan Native Female (AIAN F) 1 African American Male (AA M) 4 African American Female (AA F) 4 Asian American Pacific Islander Male (AAPI M) 1 Asian American Pacific Islander Female (AAPI F) 0 Hispanic Male (H M) 0 Hispanic Female (H F) 0 White Male (W M) 13 White Female (W F) 5

  2. 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 ...

  3. YEAR

    National Nuclear Security Administration (NNSA)

    White Male (W M) 26 White Female (W F) 16 DIVERSITY TOTAL WORKFORCE GENDER Livermore Field ... YEARS OF FEDERAL SERVICE SUPERVISOR RATIO AGE Livermore Field Office As of March 22, 2014 ...

  4. Flood Forecasting in River System Using ANFIS

    SciTech Connect (OSTI)

    Ullah, Nazrin; Choudhury, P.

    2010-10-26

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

  5. Supply Forecast and Analysis (SFA)

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

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

  6. YEAR

    National Nuclear Security Administration (NNSA)

    SES 1 2 100.00% EJEK 2 2 0.00% EN 04 1 1 0.00% EN 03 1 0 -100.00% NN (Engineering) 12 11 -8.33% NQ (ProfTechAdmin) 216 218 0.93% NU (TechAdmin Support) 2...

  7. YEAR

    National Nuclear Security Administration (NNSA)

    Females 863 YEAR 2013 SES 102 EX 3 SL 1 EJEK 89 EN 05 41 EN 04 170 EN 03 18 NN (Engineering) 448 NQ (ProfTechAdmin) 1249 NU (TechAdmin Support) 76 NV (Nuc Mat Courier) 321...

  8. YEAR

    National Nuclear Security Administration (NNSA)

    Females 942 YEAR 2012 SES 108 EX 4 SL 1 EJEK 96 EN 05 45 EN 04 196 EN 03 20 NN (Engineering) 452 NQ (ProfTechAdmin) 1291 NU (TechAdmin Support) 106 NV (Nuc Mat Courier) 335...

  9. 2016 Solar Forecasting Workshop

    Office of Energy Efficiency and Renewable Energy (EERE)

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

  10. YEAR

    National Nuclear Security Administration (NNSA)

    2013 SES 2 2 0.00% EJEK 7 8 14.29% EN 04 11 11 0.00% EN 03 1 1 0.00% NN (Engineering) 23 24 4.35% NQ (ProfTechAdmin) 35 32 -8.57% NU (TechAdmin Support) 3 2...

  11. Today's Forecast: Improved Wind Predictions

    Broader source: Energy.gov [DOE]

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

  12. Solar Forecast Improvement Project

    Office of Energy Efficiency and Renewable Energy (EERE)

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

  13. 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.

  14. Acquisition Forecast | Department of Energy

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

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

  15. YEAR

    National Nuclear Security Administration (NNSA)

    Asian American Pacific Islander Female (AAPI F) 2 Hispanic Male (H M) 6 Hispanic Female (H F) 6 White Male (W M) 46 White Female (W F) 13 DIVERSITY TOTAL WORKFORCE GENDER Nevada ...

  16. Year

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

    Note: Total may not equal sum of components because of independent rounding. Source: U.S. Department of Labor, Mine Safety and Health Administration, Form 7000-2, 'Quarterly Mine ...

  17. YEAR

    National Nuclear Security Administration (NNSA)

    Asian American Pacific Islander Male (AAPI M) 2 Asian American Pacific Islander Female (AAPI F) 0 Hispanic Male (H M) 12 Hispanic Female (H F) 12 White Male (W M) 34 White Female ...

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

    Office of Scientific and Technical Information (OSTI)

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

  19. YEAR

    National Nuclear Security Administration (NNSA)

    2012 2013 SES 2 1 -50.00% EJEK 10 9 -10.00% EN 04 27 24 -11.11% NN (Engineering) 28 24 -14.29% NQ (ProfTechAdmin) 31 29 -6.45% NU (TechAdmin Support) 4...

  20. 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.

  1. WPN 07-2: Program Year 2007 State Allocations

    Broader source: Energy.gov [DOE]

    To provide final State allocations for preparation and submission of applications for funding of the Low-Income Weatherization Assistance Program for Program Year (PY) 2007.

  2. WPN 05-2: Program Year 2005 State Allocations

    Broader source: Energy.gov [DOE]

    To provide final state allocations for preparation and submission of applications for funding of the low-income Weatherization Assistance Program for Program Year 2005.

  3. WPN 14-2: Program Year 2014 Grantee Allocations

    Broader source: Energy.gov [DOE]

    To provide final Grantee allocations for the preparation and submission of applications for funding of the Weatherization Assistance Program (WAP) for Program Year (PY) 2014.

  4. WPN 12-2: Program Year 2012 Grantee Allocations

    Broader source: Energy.gov [DOE]

    To provide final Grantee allocations for the preparation and submission of applications for funding for the Weatherization Assistance Program (WAP) for Program Year (PY) 2012.

  5. WPN 13-2: Program Year 2013 Grantee Allocations

    Broader source: Energy.gov [DOE]

    To provide Grantee allocations for the preparation and submission of applications for funding for the Weatherization Assistance Program (WAP) for Program Year (PY) 2013.

  6. WPN 04-2a: Program Year 2004 Final Allocations

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide final state allocations to the states for their preparation and submission of applications for funding of the low-income Weatherization Assistance Program for Program Year 2004.

  7. 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.

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

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

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  10. EMSL Quarterly Highlights Report: 2nd Quarter, Fiscal Year 2009

    SciTech Connect (OSTI)

    Showalter, Mary Ann; Kathmann, Loel E.; Manke, Kristin L.

    2009-05-04

    This report outlines the highlights, staff and user accomplishments, and publications that occured during FY09, 2nd quarter at EMSL.

  11. 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.

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

    SciTech Connect (OSTI)

    Chin, H S

    2005-07-26

    Wind power is the fastest growing renewable energy technology and electric power source (AWEA, 2004a). This renewable energy has demonstrated its readiness to become a more significant contributor to the electricity supply in the western U.S. and help ease the power shortage (AWEA, 2000). The practical exercise of this alternative energy supply also showed its function in stabilizing electricity prices and reducing the emissions of pollution and greenhouse gases from other natural gas-fired power plants. According to the U.S. Department of Energy (DOE), the world's winds could theoretically supply the equivalent of 5800 quadrillion BTUs of energy each year, which is 15 times current world energy demand (AWEA, 2004b). Archer and Jacobson (2005) also reported an estimation of the global wind energy potential with the magnitude near half of DOE's quote. Wind energy has been widely used in Europe; it currently supplies 20% and 6% of Denmark's and Germany's electric power, respectively, while less than 1% of U.S. electricity is generated from wind (AWEA, 2004a). The production of wind energy in California ({approx}1.2% of total power) is slightly higher than the national average (CEC & EPRI, 2003). With the recently enacted Renewable Portfolio Standards calling for 20% of renewables in California's power generation mix by 2010, the growth of wind energy would become an important resource on the electricity network. Based on recent wind energy research (Roulston et al., 2003), accurate weather forecasting has been recognized as an important factor to further improve the wind energy forecast for effective power management. To this end, UC-Davis (UCD) and LLNL proposed a joint effort through the use of UCD's wind tunnel facility and LLNL's real-time weather forecasting capability to develop an improved regional wind energy forecasting system. The current effort of UC-Davis is aimed at developing a database of wind turbine power curves as a function of wind speed and

  13. 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.

  14. 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)

  15. WPN 09-2: Program Year 2009 Grantee Allocations | Department of Energy

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

    2: Program Year 2009 Grantee Allocations WPN 09-2: Program Year 2009 Grantee Allocations Archived 12/08/09, Superseded by WPN 10-2 To provide final Grantee allocations for preparation and submission of applications for funding of the Low-Income Weatherization Assistance Program for Program Year (PY) 2009. WPN 09-2: Program Year 2009 Grantee Allocations (142.09 KB) More Documents & Publications WPN 08-2: Program Year 2008 State Allocations WPN 09-1A: Grant Guidance for Program Years 2008 and

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

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

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

  17. 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.

  18. The forecast calls for flu

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

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

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

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

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

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

  1. 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:...

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

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

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

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

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

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

  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

  5. 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

  6. Carbon Storage Partner Completes First Year of CO2 Injection Operations in

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

    Illinois | Department of Energy Carbon Storage Partner Completes First Year of CO2 Injection Operations in Illinois Carbon Storage Partner Completes First Year of CO2 Injection Operations in Illinois November 19, 2012 - 12:00pm Addthis Washington, DC - A project important to demonstrating the commercial viability of carbon capture, utilization and storage (CCUS) technology has completed the first year of injecting carbon dioxide (CO2) from an industrial plant at a large-scale test site in

  7. 15 Years of Successful H2S Abatement | Open Energy Information

    Open Energy Info (EERE)

    to library Journal Article: 15 Years of Successful H2S Abatement Abstract NA Author Gary J. Nagl Published Journal Geothermal Resources Council Bulletin, 2009 DOI Not Provided...

  8. Acquisition Forecast Download | Department of Energy

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

    Acquisition Forecast Download Acquisition Forecast Download Click on the link to download a copy of the DOE HQ Acquisition Forecast. Acquisition-Forecast-2016-07-20.xlsx (72.85 KB) More Documents & Publications Small Business Program Manager Directory EA-1900: Notice of Availability of a Draft Environmental Assessment Assessment Report: OAS-V-15-01

  9. 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.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19

    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.

  11. OPEC: 10 years after the Arab oil boycott

    SciTech Connect (OSTI)

    Cooper, M.H.

    1983-09-23

    OPEC's dominance over world oil markets is waning 10 years after precipitating world-wide energy and economic crises. The 1979 revolution in Iran and the start of the Iranian-Iraqi war in 1980 introduced a second shock that caused oil importers to seek non-OPEC supplies and emphasize conservation. No breakup of the cartel is anticipated, however, despite internal disagreements over production and price levels. Forecasters see OPEC as the major price setter as an improved economy increases world demand for oil. Long-term forecasts are even more optimistic. 24 references, 2 figures, 2 tables. (DCK)

  12. 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

    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.

  13. 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.

  14. EcoCAR 2 Competition Announces Year Two Winner: Penn State University |

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

    Department of Energy Competition Announces Year Two Winner: Penn State University EcoCAR 2 Competition Announces Year Two Winner: Penn State University May 24, 2013 - 2:14pm Addthis News Media Contact (202) 586-4940 SAN DIEGO, Calif. - EcoCAR 2: Plugging In to the Future today named Pennsylvania State University its Year Two winner at the EcoCAR 2013 Competition in San Diego. The 15 universities competing in EcoCAR 2 gathered in Yuma, Arizona last week for six days of rigorous vehicle

  15. 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.

  16. 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.

  17. EcoCAR 2 Announces Year One Winner: Mississippi State University |

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

    Department of Energy Announces Year One Winner: Mississippi State University EcoCAR 2 Announces Year One Winner: Mississippi State University May 24, 2012 - 10:40am Addthis NEWS MEDIA CONTACT (202) 586-4940 Los Angeles, Calif. - EcoCAR 2: Plugging In to the Future today named Mississippi State University its Year One winner at the EcoCAR 2012 Competition in Los Angeles. The 15 universities competing in EcoCAR 2 gathered for six days of judged competition this week with $100,000 in prize

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

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

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

  19. 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

  20. ARM - PI Product - CCPP-ARM Parameterization Testbed Model Forecast Data

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

    ProductsCCPP-ARM Parameterization Testbed Model Forecast Data ARM Data Discovery Browse Data Comments? We would 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 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

  1. Assessing middle school students` understanding of science relationships and processes: Year 2 - instrument validation. Final report

    SciTech Connect (OSTI)

    Schau, C.; Mattern, N.; Weber, R.; Minnick, K.

    1997-01-01

    Our overall purpose for this multi-year project was to develop an alternative assessment format measuring rural middle school students understanding of science concepts and processes and the interrelationships among them. This kind of understanding is called structural knowledge. We had 3 major interrelated goals: (1) Synthesize the existing literature and critically evaluate the actual and potential use of measures of structural knowledge in science education. (2) Develop a structural knowledge alternative assessment format. (3) Examine the validity of our structural knowledge format. We accomplished the first two goals during year 1. The structural knowledge assessment we identified and developed further was a select-and-fill-in concept map format. The goal for our year 2 work was to begin to validate this assessment approach. This final report summarizes our year 2 work.

  2. The Value of Wind Power Forecasting

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

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

  3. 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. ...

  4. Solid Waste Program Fiscal Year 1996 Multi-Year Program Plan WBS 1.2.1, Revision 1

    SciTech Connect (OSTI)

    1995-09-01

    This document contains the Fiscal Year 1996 Multi-Year Program Plan for the Solid Waste Program at the Hanford Reservation in Richland, Washington. The Solid Waste Program treats, stores, and disposes of a wide variety of solid wastes consisting of radioactive, nonradioactive and hazardous material types. Solid waste types are typically classified as transuranic waste, low-level radioactive waste, low-level mixed waste, and non-radioactive hazardous waste. This report describes the mission, goals and program strategies for the Solid Waste Program for fiscal year 1996 and beyond.

  5. UPF Forecast | Y-12 National Security Complex

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

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

  6. 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

  7. Table HC1-2a. Housing Unit Characteristics by Year of Construction,

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

    2a. Housing Unit Characteristics by Year of Construction, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.5 1.6 1.2 1.0 1.1 1.1 0.8 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.3 Census Region and Division Northeast ...................................... 20.3 1.5 2.4 2.1 2.8 3.0 8.5 8.8 New

  8. EcoCAR 2 Year 1 Winners Announced! | Department of Energy

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

    Year 1 Winners Announced! EcoCAR 2 Year 1 Winners Announced! May 25, 2012 - 1:21pm Addthis EcoCAR 2: Pluggin in to the Future challenges 15 universities across North America to reduce the environmental impact of a 2013 Chevrolet Malibu by minimizing the vehicles' fuel consumption and reducing its emissions while retaining the vehicle's performance, safety, and consumer appeal. | Photo by Myles Regan. EcoCAR 2: Pluggin in to the Future challenges 15 universities across North America to reduce the

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

    SciTech Connect (OSTI)

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

    1982-03-31

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

  10. Table 2.10 Commercial Buildings Energy Consumption and Expenditure Indicators, Selected Years, 1979-2003

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

    0 Commercial Buildings Energy Consumption and Expenditure Indicators, Selected Years, 1979-2003 Energy Source and Year Building Characteristics Energy Consumption Energy Expenditures Number of Buildings Total Square Feet Square Feet per Building Total Per Building Per Square Foot Per Employee Total Per Building Per Square Foot Per Million Btu Thousands Millions Thousands Trillion Btu Million Btu Thousand Btu Million Btu Million Dollars 1 Thousand Dollars 1 Dollars 1 Dollars 1 Major Sources 2

  11. Enclosure - FY 2016 Q2 Metrics Report 2016-05-03.xlsx

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

    FY 2016 Target 95% 95% 90% 85% 90% 90% FY 2016 2nd Qtr Actual Comment FY 2016 Forecast ... Schedule Compliance, Projects Less Than 5 Years Duration: Projects will meet the project ...

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

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

    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 ...

  13. EcoCAR 2 Teams Cruise Forward with Second Year Finals | Department of

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

    Energy Teams Cruise Forward with Second Year Finals EcoCAR 2 Teams Cruise Forward with Second Year Finals May 20, 2013 - 5:44pm Addthis The University of Washington team works on their vehicle while lifted on a hoist. Teams are working in a garage that is fully equipped with tools that will help them make the most of their time this week. | Photo courtesy of EcoCAR 2. The University of Washington team works on their vehicle while lifted on a hoist. Teams are working in a garage that is fully

  14. New Carbon Storage Atlas Shows Hundreds of Years of CO2 Storage Potential |

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

    Department of Energy Carbon Storage Atlas Shows Hundreds of Years of CO2 Storage Potential New Carbon Storage Atlas Shows Hundreds of Years of CO2 Storage Potential December 21, 2012 - 9:58am Addthis Atlas IV was created by the National Energy Technology Laboratory (NETL), and includes input from the more than 400 organizations in 43 states and four Canadian provinces that make up the Department’s seven Regional Carbon Sequestration Partnerships (as shown above). <a

  15. Environmental support FY 1995 multi-year program plan/fiscal year work plan WBS 1.5.2/7.4.11

    SciTech Connect (OSTI)

    Moore, D.A.

    1994-09-01

    The multi-Year Program Plan (MYPP) is the programmatic planning baseline document for technical, schedule, and cost data. The MYPP contains data by which all work is managed, performed and controlled. The integrated planning process, defined by RL, is redicted on establishment of detailed data in the MYPP. The MYPP includes detailed information for the data elements including Level II critical path schedules, cost estimate detail, and updated technical data to be done annually. There will be baseline execution year and out year approval with work authorization for execution. The MYPP will concentrate on definition of the scope, schedule, cost and program element level critical path schedules that show the relationship of planned activities. The Fiscal Year Work Plan (FYWP) is prepared for each program to provide the basis for authorizing fiscal year work. The MYPP/FYWP will be structured into three main areas: (1) Program Overview; (2) Program Baselines; (3) Fiscal Year Work Plan.

  16. 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.

  17. 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

  18. LED Lighting Forecast | Department of Energy

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

    Publications » Market Studies » LED Lighting Forecast LED Lighting Forecast The DOE report Energy Savings Forecast of Solid-State Lighting in General Illumination Applications estimates the energy savings of LED white-light sources over the analysis period of 2013 to 2030. With declining costs and improving performance, LED products have been seeing increased adoption for general illumination applications. This is a positive development in terms of energy consumption, as LEDs use significantly

  19. NREL: Resource Assessment and Forecasting Home Page

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

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

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

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

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

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

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

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

  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. 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...

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

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

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

  5. 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 systems 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.

  6. 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.

  7. 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

  8. 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

    .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.

  9. Forecast of contracting and subcontracting opportunities: Fiscal year 1998

    SciTech Connect (OSTI)

    1998-01-01

    This report describes procurement procedures and opportunities for small businesses with the Department of Energy (DOE). It describes both prime and subcontracting opportunities of $100,000 and above which are being set aside for 8(a) and other small business concerns. The report contains sections on: SIC codes; procurement opportunities with headquarters offices; procurement opportunities with field offices; subcontracting opportunities with major contractors; 8(a) contracts expiring in FY 1998; other opportunities to do business with DOE; management and operating contractors--expiration dates; Office of Small and Disadvantaged Business Utilization (OSDBU) staff directory; and small business survey. This document will be updated quarterly on the home page.

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

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

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

  11. Study forecasts disappearance of conifers due to climate change

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

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

  12. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

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

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

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

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

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

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

    Office of Energy Efficiency and Renewable Energy (EERE)

    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...

  15. 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.

  16. U.S. gasoline consumption highest in 8 years

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

    U.S. gasoline consumption highest in 8 years U.S. gasoline consumption this year is expected to be at the highest level since the record fuel demand seen back in 2007 as lower gasoline prices and more people finding jobs means more sales at the gasoline pump. In its new monthly forecast, the U.S. Energy Information Administration said gasoline consumption increased by 2.7% during the first eight months of 2015 and should rise by an average of 190,000 barrels per day this year to 9.1 million

  17. 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.

  18. Biomass Commercialization Prospects the Next 2 to 5 Years; BIOMASS COLLOQUIES 2000

    SciTech Connect (OSTI)

    Hettenhaus, J. R.; Wooley, R.; Wiselogel, A.

    2000-10-12

    A series of four colloquies held in the first quarter of 2000 examined the expected development of biomass commercialization in the next 2 to 5 years. Each colloquy included seven to ten representatives from key industries that can contribute to biomass commercialization and who are in positions to influence the future direction. They represented: Corn Growers, Biomass Suppliers, Plant Science Companies, Process Engineering Companies, Chemical Processors, Agri-pulp Suppliers, Current Ethanol Producers, Agricultural Machinery Manufacturers, and Enzyme Suppliers. Others attending included representatives from the National Renewable Energy Lab., Oak Ridge National Laboratory, the U.S. Department of Energy's Office of Fuels Development, the U.S. Department of Agriculture, environmental groups, grower organizations, and members of the financial and economic development community. The informal discussions resulted in improved awareness of the current state, future possibilit ies, and actions that can accelerate commercialization. Biomass commercialization on a large scale has four common issues: (1) Feedstock availability from growers; (2) Large-scale collection and storage; (3) An economic process; (4) Market demand for the product.

  19. 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...

  20. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

  1. 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.

  2. 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.

  3. 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....

  4. 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...

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

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

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

  6. WPN 16-2A: Program Year 2016 Grantee Allocations- Revised

    Broader source: Energy.gov [DOE]

    To provide revised Grantee allocations for the preparation and submission of applications for funding of the Weatherization Assistance Program (WAP) for Program Year (PY) 2016.

  7. WPN 03-2: Revised Weatherization Program Year 2003 Tentative Allocations

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide tentative allocations to the states for their preparation and submission of applications for funding of the low-income Weatherization Assistance Program for Program Year 2003.

  8. WPN 02-2: Revised Weatherization Program Year 2002 Tentative Allocations

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide tentative allocations to the states for their preparation and submission of applications for funding of the low-income Weatherization Assistance Program for Program Year 2002.

  9. Microsoft PowerPoint - ECOLOGY HAB PPT 11_03_11 v2.pptx

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

    Jane Hedges, Manager Jane Hedges, Manager Update for Hanford Advisory Board November 3, 2011 State Budget Update September 15: Report finds state budget $1.4 billion short (despite $10 billion in cuts over last 3 years). Sept./Oct.: State agencies submit proposed budget cuts of up to 15 percent. November 17: Next revenue forecast (not expected to be pretty) November 17: Next revenue forecast (not expected to be pretty). Governor to finish preparing budget plan that cuts $2 billion in state

  10. A Distributed Modeling System for Short-Term to Seasonal Ensemble Streamflow Forecasting in Snowmelt Dominated Basins

    SciTech Connect (OSTI)

    Wigmosta, Mark S.; Gill, Muhammad K.; Coleman, Andre M.; Prasad, Rajiv; Vail, Lance W.

    2007-12-01

    This paper describes a distributed modeling system for short-term to seasonal water supply forecasts with the ability to utilize remotely-sensed snow cover products and real-time streamflow measurements. Spatial variability in basin characteristics and meteorology is represented using a raster-based computational grid. Canopy interception, snow accumulation and melt, and simplified soil water movement are simulated in each computational unit. The model is run at a daily time step with surface runoff and subsurface flow aggregated at the basin scale. This approach allows the model to be updated with spatial snow cover and measured streamflow using an Ensemble Kalman-based data assimilation strategy that accounts for uncertainty in weather forecasts, model parameters, and observations used for updating. Model inflow forecasts for the Dworshak Reservoir in northern Idaho are compared to observations and to April-July volumetric forecasts issued by the Natural Resource Conservation Service (NRCS) for Water Years 2000 2006. October 1 volumetric forecasts are superior to those issued by the NRCS, while March 1 forecasts are comparable. The ensemble spread brackets the observed April-July volumetric inflows in all years. Short-term (one and three day) forecasts also show excellent agreement with observations.

  11. Geek-Up[3.4.2011]: 3,000+ MW and 2,500 Year-Old Greek Pottery

    Broader source: Energy.gov [DOE]

    Bonneville Power Administration celebrates big windy milestone and researchers SLAC National Accelerator Laboratory study the surfaces of 2,500 year old Greek pottery -- all in this week's Geek-Up.

  12. 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.

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

    Reports and Publications (EIA)

    1998-01-01

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

  14. Y YEAR

    National Nuclear Security Administration (NNSA)

    2 40 -4.76% YEAR 2013 2014 Males 37 35 -5.41% Females 5 5 0% YEAR 2013 2014 SES 2 2 0% EJEK 5 4 -20.00% EN 05 5 7 40.00% EN 04 6 6 0% EN 03 1 1 0% NN...

  15. WPN 00-2a- Revised Program Year 2000 Tentative Allocations

    Broader source: Energy.gov [DOE]

    To provide revised tentative allocations to the states for their preparation and submission of applications for funding of the low-income Weatherization Assistance Program for Program Year 2000.

  16. WPN 06-2a: Program Year 2006 Final State Allocations

    Broader source: Energy.gov [DOE]

    To provide final state allocations to the states for their preparation and submission of applications for funding of the low-income Weatherization Assistance Program for Program Year (PY) 2006.

  17. Midwest Has Potential to Store Hundreds of Years of CO2 Emissions

    Broader source: Energy.gov [DOE]

    Geologic capacity exists to permanently store hundreds of years of regional carbon dioxide emissions in nine states stretching from Indiana to New Jersey, according to injection field tests conducted by the Midwest Regional Carbon Sequestration Partnership.

  18. Options in the Eleventh Year for Interim Standard Offer Number Four Contracts

    SciTech Connect (OSTI)

    Hinrichs, Thomas C.

    1992-03-24

    The Interim Standard Offer Number Four Contracts (ISM), under which most of the geothermal industry is selling power (outside of The Geysers), has an initial ten year period of known fixed energy payments. In the eleventh year, the price goes to the Avoided Cost of the buying utility. The specific contract language is ''Seller will be paid at a rate equal to the utilities' published avoided cost of energy as updated and authorized by the Commission (CPUC)''. The first geothermal contract will reach the end of the initial 10 year period in early 1994, a few will end in 1995 and 1996, and the majority will end in the 1997-2000 period. This is beginning to be focused upon by the utilities, lenders and, of course, the operators themselves. The prime reason for focusing on the issue is that avoided costs of the utilities directly track the delivered cost of the natural gas, and most forecasts are showing that the price of gas in the eleventh year of the contracts will be significantly lower than the last year of the fixed period of energy payments. There are many forums in which the predication of natural gas prices are discussed. In the State of California, the agency responsible for the official forecast is the California Energy Commission. Every two years, the CEC holds hearings for input into its biennial Fuels Report (FR) which establishes the forecast of natural gas prices in addition to other parameters which are used in the planning process. The attached Exhibit I is an excerpt out of the 1991 Fuels Report (FR91). Figure 1 compares the forecast of FR89 and FR91 for the Utility Electric Generation (UEG) in PG&E's service area, and Figure 2, the forecast in the SOCAL service area. The FR91 SOCAL service area forecast indicates a bottoming of the gas price in 1994 at $2.50/mmbtu. Recent prices in 1992 are already at these levels. Converting this to an avoided energy cost brings about a price of 2 to 2-1/2 Cents/kWh. The 1992 energy price in the IS04 contract is 9

  19. 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.

  20. Planning for Pre-Exascale Platform Environment (Fiscal Year 2015 Level 2 Milestone 5216)

    SciTech Connect (OSTI)

    Springmeyer, R.; Lang, M.; Noe, J.

    2015-09-28

    This Plan for ASC Pre-Exascale Platform Environments document constitutes the deliverable for the fiscal year 2015 (FY15) Advanced Simulation and Computing (ASC) Program Level 2 milestone Planning for Pre-Exascale Platform Environment. It acknowledges and quantifies challenges and recognized gaps for moving the ASC Program towards effective use of exascale platforms and recommends strategies to address these gaps. This document also presents an update to the concerns, strategies, and plans presented in the FY08 predecessor document that dealt with the upcoming (at the time) petascale high performance computing (HPC) platforms. With the looming push towards exascale systems, a review of the earlier document was appropriate in light of the myriad architectural choices currently under consideration. The ASC Program believes the platforms to be fielded in the 2020s will be fundamentally different systems that stress ASC’s ability to modify codes to take full advantage of new or unique features. In addition, the scale of components will increase the difficulty of maintaining an errorfree system, thus driving new approaches to resilience and error detection/correction. The code revamps of the past, from serial- to vector-centric code to distributed memory to threaded implementations, will be revisited as codes adapt to a new message passing interface (MPI) plus “x” or more advanced and dynamic programming models based on architectural specifics. Development efforts are already underway in some cases, and more difficult or uncertain aspects of the new architectures will require research and analysis that may inform future directions for program choices. In addition, the potential diversity of system architectures may require parallel if not duplicative efforts to analyze and modify environments, codes, subsystems, libraries, debugging tools, and performance analysis techniques as well as exploring new monitoring methodologies. It is difficult if not impossible to

  1. Uranium Mill Tailings Remedial Action Project Annual Environmental Monitoring Report calendar year 1992: Volume 2

    SciTech Connect (OSTI)

    1993-12-31

    This report contains environmental monitoring information for the following UMTRA sites for the 1992 Calendar Year: Lakeview, OR; Lowman, ID; Mexican Hat, UT; Monument Valley, AZ; Rifle, CO; Riverton, WY; Shiprock, NM; Spook, WY; Tuba City, AZ. Each site report contains a site description, compliance summary, environmental program information, environmental radiological and non-radiological program information, water resources protection, and quality assurance information.

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

    SciTech Connect (OSTI)

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

    2015-11-10

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

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

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

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

    2015-11-10

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

  4. Electric-utility DSM programs: 1990 data and forecasts to 2000

    SciTech Connect (OSTI)

    Hirst, E.

    1992-06-01

    In April 1992, the Energy Information Administration (EIA) released data on 1989 and 1990 electric-utility demand-site management (DMS) programs. These data represent a census of US utility DSM programs, with reports of utility expenditures, energy savings, and load reductions caused by these programs. In addition, EIA published utility estimates of the costs and effects of these programs from 1991 to 2000. These data provide the first comprehensive picture of what utilities are spending and accomplishing by utility, state, and region. This report presents, summarizes, and interprets the 1990 data and the utility forecasts of their DSM-program expenditures and impacts to the year 2000. Only utilities with annual sales greater than 120 GWh were required to report data on their DSM programs to EIA. Of the 1194 such utilities, 363 reported having a DSM program that year. These 363 electric utilities spent $1.2 billion on their DSM programs in 1990, up from $0.9 billion in 1989. Estimates of energy savings (17,100 GWh in 1990 and 14,800 GWh in 1989) and potential reductions in peak demand (24,400 MW in 1990 and about 19,400 MW in 1989) also showed substantial increases. Overall, utility DSM expenditures accounted for 0.7% of total US electric revenues, while the reductions in energy and demand accounted for 0.6% and 4.9% of their respective 1990 national totals. The investor-owned utilities accounted for 70 to 90% of the totals for DSM costs, energy savings, and demand reductions. The public utilities reported larger percentage reductions in peak demand and energy smaller percentage DSM expenditures. These averages hide tremendous variations across utilities. Utility forecasts of DSM expenditures and effects show substantial growth in both absolute and relative terms.

  5. Deepwater royalty relief product of 3 1/2 year U.S. political effort

    SciTech Connect (OSTI)

    Davis, R.E.; Neff, S.

    1996-04-01

    Against the backdrop of more than 20 years of increasingly stringent environmental regulation, ever-expanding exploration and development moratoria on the Outer Continental Shelf (OCS), and reductions in producer tax incentives, oil and natural gas exploration companies active in deep waters of the Gulf of Mexico recently won a significant legislative victory. On Nov. 28, 1995, President Clinton signed into law S.395, the Alaska Power Administration Sale Act. Title 3 of S.395 embodies the Outer Continental Shelf Deep Water Royalty Relief Act. This landmark legislation provides substantial incentives for oil and natural gas production in the gulf of Mexico by temporarily eliminating royalties on certain deepwater leases. It is the first direct incentive for oil and gas production enacted at the federal level in many years. This paper reviews the elements used to arrive at this successful legislation including the congressional leadership. It describes debates, cabinet level discussions, and use of parlimentary procedures.

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

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

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

  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. Section 2, Bioenergy Technologies Office Multi-Year Program Plan, March 2016

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

    2-1 Last revised: March 2016 Section 2: Office Technology Research, Development, and Demonstration Plan The Bioenergy Technologies Office's research, development, and demonstration efforts are organized around four key technical and three key crosscutting program areas (see Figure 2-1). The first three technical program areas-Terrestrial Feedstock Supply and Logistics R&D, Advanced Algal Systems R&D, and Conversion R&D-focus on research and development (R&D). The fourth

  9. Table 2.9 Commercial Buildings Consumption by Energy Source, Selected Years, 1979-2003 (Trillion Btu)

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

    9 Commercial Buildings Consumption by Energy Source, Selected Years, 1979-2003 (Trillion Btu) Energy Source and Year Square Footage Category Principal Building Activity Census Region 1 All Buildings 1,001 to 10,000 10,001 to 100,000 Over 100,000 Education Food Sales Food Service Health Care Lodging Mercantile and Service Office All Other Northeast Midwest South West Major Sources 2 1979 1,255 2,202 1,508 511 [3] 336 469 278 894 861 1,616 1,217 1,826 1,395 526 4,965 1983 1,242 1,935 1,646 480 [3]

  10. Integrating High Penetrations of PV into Southern California: Year 2 Project Update; Preprint

    SciTech Connect (OSTI)

    Mather, B.; Neal, R.

    2012-08-01

    Southern California Edison (SCE) is well into a five-year project to install a total of 500 MW of distributed photovoltaic (PV) energy within its utility service territory. Typical installations to date are 1-3 MW peak rooftop PV systems that interconnect to medium-voltage urban distribution circuits or larger (5 MW peak) ground-mounted systems that connect to medium-voltage rural distribution circuits. Some of the PV system interconnections have resulted in distribution circuits that have a significant amount of PV generation compared to customer load, resulting in high-penetration PV integration scenarios. The National Renewable Energy Laboratory (NREL) and SCE have assembled a team of distribution modeling, resource assessment, and PV inverter technology experts in order to investigate a few of the high-penetration PV distribution circuits. Currently, the distribution circuits being studied include an urban circuit with a PV penetration of approximately 46% and a rural circuit with a PV penetration of approximately 60%. In both cases, power flow on the circuit reverses direction, compared to traditional circuit operation, during periods of high PV power production and low circuit loading. Research efforts during year two of the five-year project were focused on modeling the distribution system level impacts of high-penetration PV integrations, the development and installation of distribution circuit data acquisition equipment appropriate for quantifying the impacts of high-penetration PV integrations, and investigating high-penetration PV impact mitigation strategies. This paper outlines these research efforts and discusses the following activities in more detail: the development of a quasi-static time-series test feeder for evaluating high-penetration PV integration modeling tools; the advanced inverter functions being investigated for deployment in the project's field demonstration and a power hardware-in-loop test of a 500-kW PV inverter implementing a

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

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01

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

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

    Open Energy Info (EERE)

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

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

    SciTech Connect (OSTI)

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

    2010-04-01

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

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

    SciTech Connect (OSTI)

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

    2010-04-15

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

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

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

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

  16. Y YEAR

    National Nuclear Security Administration (NNSA)

    563 560 -0.53% ↓ YEAR 2013 2014 Males 518 514 -0.77% ↓ Females 45 46 2.22% ↑ YEAR 2013 2014 SES 2 2 0% / EJ/EK 2 2 0% / EN 04 1 1 0% / NN (Engineering) 11 11 0% / NQ (Prof/Tech/Admin) 218 221 1.38% ↑ NU (Tech/Admin Support) 1 2 100% ↑ NV (Nuc Mat Courier) 328 321 -2.13% ↓ YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 15 15 0% / American Indian Alaskan Native Female (AIAN,F) 2 2 0% / African American Male (AA,M) 19 18 -5.26% ↓ African American Female (AA,F) 1 1 0% /

  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. A detailed 2,000-year late holocene pollen record from lower Pahranagat Lake, Southern Nevada, USA

    SciTech Connect (OSTI)

    Hemphill, M.L.; Wigand, P.E.

    1995-09-01

    Preliminary analysis of 128 pollen samples and seven radiocarbon dates from a 5-meter long, 10-cm diameter sediment core retrieved from Lower Pahranagat Lake (elevation - 975 in), Lincoln County, Nevada, gives us a rare, continuous, record of vegetation change at an interval of every 14 years over the last 2,000 years. During this period increasing Pinus (pine) pollen values with respect to Juniperus Ouniper pollen values reflect the increasing dominance of pinyon in southern Nevada woodlands during the last 2,000 years. Today Pinus pollen values indicate that pinyon pine is more frequent in the southern Great Basin since the end of the Neoglacial 2,000 years ago. During the same time frame, a general decrease in Poaceae (grass) pollen values with respect to Artemisia (sagebrush) pollen values reflect the general trend of increasing dominance of steppe and desert scrub species with respect to grasses. Variations in these two species reflect not only the generally more xeric nature of climate during the last 2,000 years, but also periods of summer shifted rainfall - 1,500 years ago that encouraged both a period of grass and pinyon expansion. The ratio of aquatic to littoral pollen types indicates generally deeper water conditions 2 to 1 ka and more variable, but predominately more marshy, conditions at the site during most of the last 1 ka. Investigation of ostracodes from the same record being conducted by Dr. R. Forester at the USGS corroborate the pollen record by evidencing shifts between open and closed hydrologic systems including lake, marsh and even stream habitats. Analysis of an additional 10 meters of core recovered in the summer of 1994 with a basal date of 5.6 ka promises to provide the best record of middle through late Holocene vegetation and climate history for southern Nevada.

  19. Fact #806: December 2, 2013 Light Vehicle Market Shares, Model Years 1975–2012

    Broader source: Energy.gov [DOE]

    In 1975, cars were by far the dominant vehicle style among new light vehicle sales, with a few vans and pickup trucks. Sport Utility Vehicles (SUVs) accounted for less than 2% of the market at that...

  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. Projections of motor vehicle growth, fuel consumption and CO{sub 2} emissions for the next thirty years in China.

    SciTech Connect (OSTI)

    He, D.; Wang, M.

    2000-12-12

    Since the early 1990s, China's motor vehicles have entered a period of fast growth resultant from the rapid economic expansion. As the largest developing country, the fast growth of China's motor vehicles will have tremendous effects on the world's automotive and fuel market and on global CO{sub 2} emissions. In this study, we projected Chinese vehicle stocks for different vehicle types on the provincial level. First, we reviewed the historical data of China's vehicle growth in the past 10 years and the correlations between vehicle growth and economic growth in China. Second, we investigated historical vehicle growth trends in selected developed countries over the past 50 or so years. Third, we established a vehicle growth scenario based on the historical trends in several developed nations. Fourth, we estimated fuel economy, annual mileage and other vehicle usage parameters for Chinese vehicles. Finally, we projected vehicle stocks and estimated motor fuel use and CO{sub 2} emissions in each Chinese province from 2000 to 2030. Our results show that China will continue the rapid vehicle growth, increase gasoline and diesel consumption and increased CO{sub 2} emissions in the next 30 years. We estimated that by year 2030, Chinese motor vehicle fuel consumption and CO{sub 2} emissions could reach the current US levels.

  2. Fuel Cell Technologies Office Multi-Year Research, Development, and Demonstration Plan - Section 3.2 Hydrogen Delivery

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

    Delivery Multi-Year Research, Development and Demonstration Plan Page 3.2 - 1 3.2 Hydrogen Delivery Delivery is an essential component of any future hydrogen infrastructure. It encompasses those processes needed to transport hydrogen from a central or semi-central production facility to the final point of use and those required to load the energy carrier directly onto a given fuel cell system. Successful commercialization of hydrogen-fueled fuel cell systems, including those used in vehicles,

  3. Fuel Cell Technologies Program Multi-Year Research, Development and Demonstration (MYRDD) Plan - Section 2.0: Program Benefits

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

    Benefits Multi-Year Research, Development and Demonstration Plan Page 2 - 1 2.0 Program Benefits Fuel cells provide power and heat cleanly and efficiently, using diverse domestic fuels, including hydrogen produced from renewable resources and biomass-based fuels. Fuel cells can be used in a wide range of stationary, transportation, and portable-power applications. Hydrogen can also function as an energy storage medium for renewable electricity. Hydrogen and fuel cell technologies are being

  4. Stellar Astrophysics Requirements NERSC Forecast

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

    (Copernicus Center, Warsaw). Computing cycles: DOE NERSC. 14 May 26, 2011 FLASHWDM Parallel Performance strong peak weak 15 May 26, 2011 Example 2: Core-Collapse SN...

  5. Geothermal energy program summary: Volume 2, Research summaries, fiscal year 1988

    SciTech Connect (OSTI)

    Not Available

    1989-03-01

    The Geothermal Technology Division (GTD) of the US Department of Energy (DOE) is charged with the lead federal role in the research and development (R&D) of technologies that will assist industry in economically exploiting the nation`s vast geothermal resources. The GTD R&D program represents a comprehensive, balanced approach to establishing all forms of geothermal energy as significant contributors to the nation`s energy supply. It is structured both to maintain momentum in the growth of the existing hydrothermal industry and to develop long-term options offering the greatest promise for practical applications. The Geothermal Energy Program Summary for Fiscal Year 1988 is a two-volume set designed to be an easily accessible reference to inform the US geothermal industry and other interested parties of the technological advances and progress achieved in the DOE geothermal program as well as to describe the thrust of the current R&D effort and future R&D directions. This volume, Volume II, contains a detailed compilation of each GTD-funded R&D activity performed by national laboratories or under contract to industrial, academic, and nonprofit research institutions. The Program Summary is intended as an important technology transfer vehicle to assure the wide and timely dissemination of information concerning the department`s geothermal research.

  6. 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.

  7. Table 2.6 Household End Uses: Fuel Types, Appliances, and Electronics, Selected Years, 1978-2009

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

    6 Household End Uses: Fuel Types, Appliances, and Electronics, Selected Years, 1978-2009 Appliance Year Change 1978 1979 1980 1981 1982 1984 1987 1990 1993 1997 2001 2005 2009 1980 to 2009 Total Households (millions) 77 78 82 83 84 86 91 94 97 101 107 111 114 32 Percent of Households<//td> Space Heating - Main Fuel 1 Natural Gas 55 55 55 56 57 55 55 55 53 52 55 52 50 -5 Electricity 2 16 17 18 17 16 17 20 23 26 29 29 30 35 17 Liquefied Petroleum Gases 4 5 5 4 5 5 5 5 5 5 5 5 5 0 Distillate

  8. Evaluation of an Experimental Re-introduction of Sockeye Salmon into Skaha Lake; Year 2 of 3, 2001 Technical Report.

    SciTech Connect (OSTI)

    Fisher, Christopher; Machin, Deanna; Wright, Howie

    2002-04-01

    This report summarizes the findings from YEAR 2 of a three-year disease risk assessment. The Okanagan Nation Fisheries Commission (ONFC) and the Colville Confederated Tribes (CCT) are investigating the risks involved in re-introducing sockeye salmon into Skaha Lake, part of their historical range (Ernst and Vedan 2000). The disease risk assessment compares the disease and infection status of fish above and below McIntyre Dam (the present limit of sockeye migration). The disease agents identified that are of a particular concern are: infectious pancreatic necrosis virus (IPNV), infectious haematopoietic necrosis virus type 2 (IHNV type2), erythrocytic inclusion body syndrome virus (EIBSV), the whirling disease agent (Myxobolus cerebralis), and the ceratomyxosis agent (Ceratomyxa shasta).

  9. Y YEAR

    National Nuclear Security Administration (NNSA)

    502 2381 -4.84% ↓ YEAR 2013 2014 Males 1663 1593 -4.21% ↓ Females 839 788 -6.08% ↓ YEAR 2013 2014 SES 104 90 -13.46% ↓ EX 2 4 100% ↑ SL 1 0 -100% ↓ EJ/EK 88 73 -17.05% ↓ EN 05 40 41 2.50% ↑ EN 04 169 157 -7.10% ↓ EN 03 18 21 100% ↑ EN 00 0 6 100% ↑ NN (Engineering) 441 416 -5.67% ↓ NQ (Prof/Tech/Admin) 1239 1190 -3.95% ↓ NU (Tech/Admin Support) 66 57 -13.64% ↓ NV (Nuc Mat Courier) 328 321 -2.13% ↓ GS 15 1 2 100% ↑ GS 13 2 2 0% / GS 10 3 1 -66.67% ↓ YEAR 2013

  10. Fuel Cell Technologies Office Multi-Year Research, Development, and Demonstration Plan - Section 3.2 Hydrogen Delivery

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

    Brayton cycle, and a Joule-Thompson cycle) and are energy intensive, consuming energy in amounts corresponding to ~⅓ of the energy in the hydrogen. 2015 DELIVERY SECTION Multi-Year Research, Development, and Demonstration Plan Page 3.2 - 7 Table 3.2.1 Hydrogen Delivery Infrastructure Components Delivery Component Current Status Gas cooling systems 70-MPa (700-bar) dispensing of gaseous H 2 into Type IV tanks at a fill rate of 1.6 kg/min currently requires pre-cooling of the gas to overcome the