National Library of Energy BETA

Sample records for year forecast 4

  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. 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:...

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

    SciTech Connect (OSTI)

    Wu, J.; Zhang, M.

    2005-03-18

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

  13. 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

  14. 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...

  15. 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...

  16. YEAR

    National Nuclear Security Administration (NNSA)

    31 YEAR 2013 Males 20 Females 11 YEAR 2013 SES 2 EN 04 4 NN (Engineering) 12 NQ (ProfTechAdmin) 12 NU (TechAdmin Support) 1 YEAR 2013 American Indian Alaska Native Male (AIAN,...

  17. YEAR

    National Nuclear Security Administration (NNSA)

    31 YEAR 2012 Males 19 Females 12 YEAR 2012 SES 2 EN 04 4 NN (Engineering) 12 NQ (ProfTechAdmin) 12 NU (TechAdmin Support) 1 YEAR 2012 American Indian Male 0 American Indian...

  18. YEAR

    National Nuclear Security Administration (NNSA)

    137 YEAR 2013 Males 90 Females 47 YEAR 2013 SES 2 SL 1 EJEK 30 EN 04 30 EN 03 2 NN (Engineering) 23 NQ (ProfTechAdmin) 45 NU (TechAdmin Support) 4 YEAR 2013 American Indian...

  19. YEAR

    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...

  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....

  1. 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...

  2. 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...

  3. 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...

  4. YEAR

    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...

  5. 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 ...

  6. 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

  7. 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...

  8. 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...

  9. 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

  10. 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

  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)

    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...

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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...

  19. 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

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

  1. 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

  2. Taking a Look at 4.57 Billion Year Old Space Objects | Department of Energy

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

    a Look at 4.57 Billion Year Old Space Objects Taking a Look at 4.57 Billion Year Old Space Objects March 23, 2011 - 3:29pm Addthis Compositional X-ray image of the rim and margin of a ~4.6 billion year old calcium aluminum refractory inclusion (CAI)
from the Allende carbonaceous chondrite. | Courtesy of Lawrence Livermore National Laboratory Compositional X-ray image of the rim and margin of a ~4.6 billion year old calcium aluminum refractory inclusion (CAI)
from the Allende carbonaceous

  3. Microsoft PowerPoint - NEAC CASL @ 3.5 Years Report v4

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

    ... Reactor System Multiphysics Integrator 4 CASL @3.5 Years Mesh Motion Quality Improvement Geometry Management Mesh Motion Quality Improvement Geometry Management Virtual ...

  4. 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...

  5. YEAR

    National Nuclear Security Administration (NNSA)

    42 YEAR 2014 Males 36 Females 6 PAY PLAN YEAR 2014 SES 2 EJEK 5 EN 05 7 EN 04 6 EN 03 1 NN (Engineering) 15 NQ (ProfTechAdmin) 6 YEAR 2014 American Indian Alaska Native Male...

  6. 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...

  7. YEAR

    National Nuclear Security Administration (NNSA)

    558 YEAR 2013 Males 512 Females 46 YEAR 2013 SES 2 EJEK 2 EN 04 1 NN (Engineering) 11 NQ (ProfTechAdmin) 220 NU (TechAdmin Support) 1 NV (Nuc Mat Courier) 321 YEAR 2013...

  8. YEAR

    National Nuclear Security Administration (NNSA)

    11 YEAR 2012 Males 78 Females 33 YEAR 2012 SES 2 EJEK 9 EN 05 1 EN 04 33 NN (Engineering) 32 NQ (ProfTechAdmin) 31 NU (TechAdmin Support) 3 YEAR 2012 American Indian Male 2...

  9. YEAR

    National Nuclear Security Administration (NNSA)

    300 YEAR 2011 Males 109 Females 191 YEAR 2011 SES 9 EJEK 1 NN (Engineering) 2 NQ (ProfTechAdmin) 203 NU (TechAdmin Support) 38 NF (Future Ldrs) 47 YEAR 2011 American Indian...

  10. 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...

  11. YEAR

    National Nuclear Security Administration (NNSA)

    8 YEAR 2013 Males 27 Females 11 YEAR 2013 SES 1 EN 05 1 EN 04 11 NN (Engineering) 8 NQ (ProfTechAdmin) 15 NU (TechAdmin Support) 2 YEAR 2013 American Indian Alaska Native Male...

  12. YEAR

    National Nuclear Security Administration (NNSA)

    16 YEAR 2012 Males 84 Females 32 YEAR 2012 SES 26 EJEK 2 EN 05 9 NN (Engineering) 39 NQ (ProfTechAdmin) 30 NU (TechAdmin Support) 10 YEAR 2012 American Indian Male 0 American...

  13. YEAR

    National Nuclear Security Administration (NNSA)

    34 YEAR 2012 Males 66 Females 68 YEAR 2012 SES 6 NN (Engineering) 15 NQ (ProfTechAdmin) 110 NU (TechAdmin Support) 3 YEAR 2012 American Indian Male 1 American Indian Female 2...

  14. 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...

  15. 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...

  16. YEAR

    National Nuclear Security Administration (NNSA)

    1 YEAR 2012 Males 30 Females 11 YEAR 2012 SES 1 EN 05 1 EN 04 11 NN (Engineering) 9 NQ (ProfTechAdmin) 17 NU (TechAdmin Support) 2 YEAR 2012 American Indian Male 0 American...

  17. 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...

  18. YEAR

    National Nuclear Security Administration (NNSA)

    0 YEAR 2013 Males 48 Females 32 YEAR 2013 SES 2 EJEK 7 EN 04 11 EN 03 1 NN (Engineering) 23 NQ (ProfTechAdmin) 33 NU (TechAdmin Support) 3 YEAR 2013 American Indian Alaska...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. YEAR

    National Nuclear Security Administration (NNSA)

    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...

  4. YEAR

    National Nuclear Security Administration (NNSA)

    7 YEAR 2012 Males 64 Females 33 YEAR 2012 SES 2 EJEK 3 EN 05 1 EN 04 30 EN 03 1 NN (Engineering) 26 NQ (ProfTechAdmin) 32 NU (TechAdmin Support) 2 YEAR 2012 American Indian...

  5. 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...

  6. 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...

  7. probabilistic energy production forecasts

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

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

  8. Wind Power Forecasting Data

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

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

  9. Forecasting Water Quality & Biodiversity

    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. ...

  10. Wind Power Forecasting

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

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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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)

  16. 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

  17. 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

  18. 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

  19. NREL: Transmission Grid Integration - Forecasting

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

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

  20. 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 ...

  1. 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.

  2. 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

  3. 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

  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)

    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...

  7. 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.

  8. 300 Area D4 Project Fiscal Year 2009 Building Completion Report

    SciTech Connect (OSTI)

    B. J. Skwarek

    2010-01-27

    This report summarizes the deactivation, decontamination, decommissioning, and demolition activities of seven facilities in the 300 Area of the Hanford Site in fiscal year 2009. The D4 of these facilities included characterization; engineering; removal of hazardous and radiologically contaminated materials; equipment removal; utility disconnection; deactivation, decontamination, demolition of the structure; and stabilization or removal of slabs and foundations. This report also summarizes the nine below-grade slabs/foundations removed in FY09 of buildings demolished in previous fiscal years.

  9. 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.

  10. 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...

  11. 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...

  12. 300 Area D4 Project Fiscal Year 2008 Building Completion Report

    SciTech Connect (OSTI)

    R. A. Westberg

    2009-01-15

    This report documents the deactivation, decontamination, decommissioning, and demolition (D4) of eighteen buildings in the 300 Area of the Hanford Site that were demolished in Fiscal Year 2008. The D4 of these facilties included characterization, engineering, removal of hazardous and radiologically contaminated materials, equipment removal, utility disconnection, deactivation, decontamination, demolition of the structure, and stabilization or removal of the remaining slab and foundation, as appropriate.

  13. 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...

  14. 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.

  15. 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

  16. National radon database documentation. Volume 4. The EPA/state residential radon surveys: Year 4. Final report 1986-1992

    SciTech Connect (OSTI)

    Not Available

    1993-01-01

    The National Radon Database has been developed by the U.S. Environmental Protection Agency (EPA) to distribute information collected in two recently completed radon surveys: the EPA/State Residential Radon Surveys, Years 1 to 6; and The National Residential Radon Survey. The goals of the state radon surveys were twofold. Some measure of the distribution of radon levels among residences was desired for major geographic areas within each state and for each state as a whole. In addition, it was desired that each state survey would be able to identify areas of potentially high residential radon concentrations (hot spots) in the state, enabling the state to focus its attention on areas where indoor radon concentrations might pose a greater health threat. The document discusses year 4, 1989-90. The areas surveyed are: California; Hawaii; Idaho; Louisiana; Nebraska; Billings, MT IHS Area; Nevada; North Carolina; Oklahoma; South Carolina; and Navajo Nation.

  17. Potentially biogenic carbon preserved in a 4.1 billion-year-old zircon

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

    Bell, Elizabeth A.; Boehnke, Patrick; Harrison, T. Mark; Mao, Wendy L.

    2015-10-19

    Here, evidence of life on Earth is manifestly preserved in the rock record. However, the microfossil record only extends to ~3.5 billion years (Ga), the chemofossil record arguably to ~3.8 Ga, and the rock record to 4.0 Ga. Detrital zircons from Jack Hills, Western Australia range in age up to nearly 4.4 Ga. From a population of over 10,000 Jack Hills zircons, we identified one >3.8-Ga zircon that contains primary graphite inclusions. Here, we report carbon isotopic measurements on these inclusions in a concordant, 4.10 ± 0.01-Ga zircon. We interpret these inclusions as primary due to their enclosure in amore » crack-free host as shown by transmission X-ray microscopy and their crystal habit. Their δ13CPDB of –24 ± 5‰ is consistent with a biogenic origin and may be evidence that a terrestrial biosphere had emerged by 4.1 Ga, or ~300 My earlier than has been previously proposed.« less

  18. Potentially biogenic carbon preserved in a 4.1 billion-year-old zircon

    SciTech Connect (OSTI)

    Bell, Elizabeth A.; Boehnke, Patrick; Harrison, T. Mark; Mao, Wendy L.

    2015-10-19

    Here, evidence of life on Earth is manifestly preserved in the rock record. However, the microfossil record only extends to ~3.5 billion years (Ga), the chemofossil record arguably to ~3.8 Ga, and the rock record to 4.0 Ga. Detrital zircons from Jack Hills, Western Australia range in age up to nearly 4.4 Ga. From a population of over 10,000 Jack Hills zircons, we identified one >3.8-Ga zircon that contains primary graphite inclusions. Here, we report carbon isotopic measurements on these inclusions in a concordant, 4.10 ± 0.01-Ga zircon. We interpret these inclusions as primary due to their enclosure in a crack-free host as shown by transmission X-ray microscopy and their crystal habit. Their δ13CPDB of –24 ± 5‰ is consistent with a biogenic origin and may be evidence that a terrestrial biosphere had emerged by 4.1 Ga, or ~300 My earlier than has been previously proposed.

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

    SciTech Connect (OSTI)

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

    2015-10-30

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

  20. 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 ...

  1. Tennessee health studies agreement. Annual report for year 4, January 1--December 31, 1995

    SciTech Connect (OSTI)

    1996-04-01

    The Tennessee Department of Health (TDH) has completed the fourth full year of the Oak Ridge Health Studies Agreement grant. This report summarizes the accomplishments and concerns of the State for the period January 1, 1995, to December 31, 1995. The focus of work during the fourth grant year was the actual work on the dose reconstruction. The final work plan for Task 5, Plan to Perform a Systematic Document Search was received in November 1994. Final work plans for Task 1, Investigation of Radioiodine from Radioactive Lanthanum Processing; Task 2, Investigation of Mercury Releases from Lithium Enrichment; Task 3, Investigation of Releases of PCBs from Oak Ridge Facilities; and Task 4, Investigation of Releases of Radionuclides from White Oak Creek to the Clinch River, were received in February 1995. Final work plans for Task 6, Investigation of the Quality of Historical Uranium Effluent Monitoring at Oak Ridge Facilities; and Task 7, Additional Screening of Materials Not Evaluated in the Dose Reconstruction Feasibility Study, were received in April 1995. ChemRisk`s 4th Quarterly Report, for October through December 1995, is included in Attachment 1. Attachment 2 contains a study which developed a quality improvement program for data imported to the Tennessee Cancer Reporting System and Birth Defects Verification Program.

  2. 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.

  3. 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.

  4. 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.

  5. 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 ...

  6. 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)

  7. 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.

  8. 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 ...

  9. 300 Area D4 Project Fiscal Year 2010 Building Completion Report

    SciTech Connect (OSTI)

    Skwarek, B. J.

    2011-01-27

    This report summarizes the deactiviation, decontamination, decommissioning, and demolition activities of facilities in the 300 Area of the Hanford Site in fiscal year 2010.

  10. 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 ...

  11. 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:...

  12. 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 ...

  13. 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 ...

  14. 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.

  15. 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

    (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.

  16. Diagnosis of the Marine Low Cloud Simulation in the NCAR Community Earth System Model (CESM) and the NCEP Global Forecast System (GFS)-Modular Ocean Model v4 (MOM4) coupled model

    SciTech Connect (OSTI)

    Xiao, Heng; Mechoso, C. R.; Sun, Rui; Han, J.; Pan, H. L.; Park, S.; Hannay, Cecile; Bretherton, Christopher S.; Teixeira, J.

    2014-07-25

    We present a diagnostic analysis of the marine low cloud climatology simulated by two state-of-the-art coupled atmosphere-ocean models: the NCAR Community Earth System Model (CESM) and the NCEP Global Forecasting System (GFS). In both models, the shallow convection and boundary layer turbulence parameterizations have been recently updated: both models now use a mass-flux scheme for the parameterization of shallow convection, and a turbulence parameterization capable of handling Stratocumulus (Sc)-topped Planetary Boundary Layers (PBLs). For shallow convection, both models employ a convective trigger function based on the concept of convective inhibition and both include explicit convective overshooting/penetrative entrainment formulation. For Sc-topped PBL, both models treat explicitly turbulence mixing and cloud-top entrainment driven by cloud-top radiative cooling. Our focus is on the climatological transition from Sc to shallow Cumulus (Cu)-topped PBL in the subtropical eastern oceans. We show that in the CESM the coastal Sc-topped PBLs in the subtropical Eastern Pacific are well-simulated but the climatological transition from Sc to shallow Cu is too abrupt and happens too close to the coast. By contrast, in the GFS coupled simulation the coastal Sc amount and PBL depth are severely underestimated while the transition from Sc to shallow Cu is delayed and offshore Sc cover is too extensive in the subtropical Eastern Pacific. We discuss the possible connections between such differences in the simulations and differences in the parameterizations of shallow convection and boundary layer turbulence in the two models.

  17. Fact #765: February 4, 2013 EPA's Top 10 Conventionally-Fueled Vehicles for Model Year 2013

    Broader source: Energy.gov [DOE]

    For the 2013 model year, the Toyota Prius and smaller Prius c took the top spot with a combined average of 50 mpg. All vehicles making this list are hybrid vehicles, and six of the ten cars making...

  18. 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

  19. 300 Area D4 Project Fiscal Year 2007 Building Completion Report

    SciTech Connect (OSTI)

    R. A. Westberg

    2009-01-15

    This report documents the deactivation, decontamination, decommissioning, and demolition (D4) of twenty buildings in the 300 Area of the Hanford Site. The D4 of these facilties included characterization, engineering, removal of hazardous and radiologically contaminated materials, equipment removal, utility disconnection, deactivation, decontamination, demolition of the structure, and stabilization or removal of the remaining slab and foundation, as appropriate.

  20. Arrow Lakes Reservoir Fertilization Experiment; Years 4 and 5, Technical Report 2002-2003.

    SciTech Connect (OSTI)

    Schindler, E.

    2007-02-01

    This report presents the fourth and fifth year (2002 and 2003, respectively) of a five-year fertilization experiment on the Arrow Lakes Reservoir. The goal of the experiment was to increase kokanee populations impacted from hydroelectric development on the Arrow Lakes Reservoir. The impacts resulted in declining stocks of kokanee, a native land-locked sockeye salmon (Oncorhynchus nerka), a key species of the ecosystem. Arrow Lakes Reservoir, located in southeastern British Columbia, has undergone experimental fertilization since 1999. It is modeled after the successful Kootenay Lake fertilization experiment. The amount of fertilizer added in 2002 and 2003 was similar to the previous three years. Phosphorus loading from fertilizer was 52.8 metric tons and nitrogen loading from fertilizer was 268 metric tons. As in previous years, fertilizer additions occurred between the end of April and the beginning of September. Surface temperatures were generally warmer in 2003 than in 2002 in the Arrow Lakes Reservoir from May to September. Local tributary flows to Arrow Lakes Reservoir in 2002 and 2003 were generally less than average, however not as low as had occurred in 2001. Water chemistry parameters in select rivers and streams were similar to previous years results, except for dissolved inorganic nitrogen (DIN) concentrations which were significantly less in 2001, 2002 and 2003. The reduced snow pack in 2001 and 2003 would explain the lower concentrations of DIN. The natural load of DIN to the Arrow system ranged from 7200 tonnes in 1997 to 4500 tonnes in 2003; these results coincide with the decrease in DIN measurements from water samples taken in the reservoir during this period. Water chemistry parameters in the reservoir were similar to previous years of study except for a few exceptions. Seasonal averages of total phosphorus ranged from 2.11 to 7.42 {micro}g/L from 1997 through 2003 in the entire reservoir which were indicative of oligo-mesotrophic conditions

  1. 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

  2. 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.

  3. 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.

  4. Fuel Cell Technologies Office Multi-Year Research, Development, and Demonstration Plan - Section 3.4 Fuel Cells

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

    FUEL CELLS SECTION Multi-Year Research, Development, and Demonstration Plan Page 3.4 - 1 3.4 Fuel Cells Fuel cells efficiently convert diverse fuels directly into electricity without combustion, and they are key elements of a broad portfolio for building a competitive, secure, and sustainable clean energy economy. They offer a broad range of benefits, including reduced greenhouse gas emissions; reduced oil consumption; expanded use of renewable power (through the use of hydrogen derived from

  5. Fuel Cell Technologies Office Multi-Year Research, Development, and Demonstration Plan - Section 4.0 Systems Analysis

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

    ANALYSIS SECTION Multi-Year Research, Development, and Demonstration Plan Page 4.0 - 1 4.0 Systems Analysis The Fuel Cell Technologies Office (The Office) conducts a coordinated, comprehensive effort in modeling and analysis to clarify where hydrogen and fuel cells can be most effective from an economic, environmental, and energy security standpoint, as well as to guide RD&D priorities and set program goals. These activities support the Office's decision-making process by evaluating

  6. 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).

  7. 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).

  8. 300 Area D4 Project 3rd Quarter Fiscal Year 2006 Building Completion Report

    SciTech Connect (OSTI)

    D. S. Smith

    2006-09-25

    This report documents the deactivation, decontamination, decommissioning, and demolition of five buildings in the 300 Area of the Hanford Site. The D4 of these facilities included characterization, engineering, removal of hazardous and radiologically contaminated materials, equipment removal, utility disconnection, deactivation, decontamination, demolition of the structure, and stabilization or removal of the remaining slab and foundation as appropriate.

  9. 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.

  10. Table 2.4 Household Energy Consumption by Census Region, Selected Years, 1978-2009 (Quadrillion Btu, Except as Noted)

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

    Household 1 Energy Consumption by Census Region, Selected Years, 1978-2009 (Quadrillion Btu, Except as Noted) Census Region 2 1978 1979 1980 1981 1982 1984 1987 1990 1993 1997 2001 2005 2009 United States Total (does not include wood) 10.56 9.74 9.32 9.29 8.58 9.04 9.13 9.22 10.01 10.25 9.86 10.55 10.18 Natural Gas 5.58 5.31 4.97 5.27 4.74 4.98 4.83 4.86 5.27 5.28 4.84 4.79 4.69 Electricity 3 2.47 2.42 2.48 2.42 2.35 2.48 2.76 3.03 3.28 3.54 3.89 4.35 4.39 Distillate Fuel Oil and Kerosene 2.19

  11. 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.

  12. Black liquor combustion validated recovery boiler modeling: Final year report. Volume 4 (Appendix IV)

    SciTech Connect (OSTI)

    Grace, T.M.; Frederick, W.J.; Salcudean, M.; Wessel, R.A.

    1998-08-01

    This project was initiated in October 1990, with the objective of developing and validating a new computer model of a recovery boiler furnace using a computational fluid dynamics (CFD) code specifically tailored to the requirements for solving recovery boiler flows, and using improved submodels for black liquor combustion based on continued laboratory fundamental studies. The key tasks to be accomplished were as follows: (1) Complete the development of enhanced furnace models that have the capability to accurately predict carryover, emissions behavior, dust concentrations, gas temperatures, and wall heat fluxes. (2) Validate the enhanced furnace models, so that users can have confidence in the predicted results. (3) Obtain fundamental information on aerosol formation, deposition, and hardening so as to develop the knowledge base needed to relate furnace model outputs to plugging and fouling in the convective sections of the boiler. (4) Facilitate the transfer of codes, black liquid submodels, and fundamental knowledge to the US kraft pulp industry. Volume 4 contains the following appendix sections: Radiative heat transfer properties for black liquor combustion -- Facilities and techniques and Spectral absorbance and emittance data; and Radiate heat transfer determination of the optical constants of ash samples from kraft recovery boilers -- Calculation procedure; Computation program; Density determination; Particle diameter determination; Optical constant data; and Uncertainty analysis.

  13. 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.

  14. Six-year optical monitoring of the BL Lacertae object 1ES 0806+52.4

    SciTech Connect (OSTI)

    Man, Zhongyi; Zhang, Xiaoyuan; Wu, Jianghua; Zhou, Xu; Yuan, Qirong

    2014-12-01

    We present the results of the first systematic long-term multicolor optical monitoring of the BL Lacertae object 1ES 0806+52.4. The monitoring was performed in multiple passbands with a 60/90 cm Schmidt telescope from 2005 December to 2011 February. The overall brightness of this object decreased from 2005 December to 2008 December but was regained after that. A sharp outburst probably occurred around the end of our monitoring program. Overlapping the long-term trend are some short-term small-amplitude oscillations. No intranight variability was found in the object, which is in accordance with the historical observations before 2005. By investigating the color behavior, we found a strong bluer-when-brighter chromatism for the long-term variability of 1ES 0806+52.4. The total amplitudes at the c, i, and o bands are 1.18, 1.12, and 1.02 mag, respectively. The amplitudes tend to increase toward shorter wavelengths, which may be a major cause of the bluer-when-brighter chromatism. Such bluer-when-brighter chromatisms are also found in other blazars, such as S5 0716+714, OJ 287. The hard-X-ray data collected from the Swift/BAT archive was correlated with our optical data. No positive result was found, the reason for which may be that the hard-X-ray flux is a combination of the synchrotron and inverse Compton emission, but with different timescales and cadences under the leptonic synchrotron self-Compton model.

  15. 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 ...

  16. 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

  17. 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. ...

  18. 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. ...

  19. 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

  20. 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

  1. 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 ...

  2. 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.

  3. EnPI V4.0 Algorithm

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

    ... period is summed to determine the annual cost savings. ... SEnPI (unitless) Forecasting (Model year baseline year) Calculation for the model year: ...

  4. 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,

  5. 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...

  6. ARM - CARES - Tracer Forecast for CARES

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

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

  7. LED Lighting Forecast | Department of Energy

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

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

  8. NREL: Resource Assessment and Forecasting Home Page

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

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

  9. 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 ...

  10. 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...

  11. 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...

  12. 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 ...

  13. 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 ...

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

    SciTech Connect (OSTI)

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

    2005-02-09

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

  15. 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.

  16. 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

  17. 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, ...

  18. 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 ...

  19. 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 ...

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

    SciTech Connect (OSTI)

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

    2013-01-01

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

  1. 4

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

    -4 -3 -2 -1 0 1 2 3 4 -4 -3 -2 -1 0 1 2 3 4 px x -0.006 -0.004 -0.002 0 0.002 0.004 0.006 -0.02 -0.015 -0.01 -0.005 0 0.005 0.01 0.015 0.02 px x(m) 50 100 50 100 0 10000 20000 30000 50 10

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

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    1994-02-01

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

  3. WPN 00-4- Estimated 25% State Cost Share Requirement for the Weatherization Assistance Program for Program Year 2001

    Broader source: Energy.gov [DOE]

    To provide estimated figures for the states to begin their planning for the enacted 25% cost share requirement for funding of the low-income Weatherization Assistance Program beginning with Program Year 2001.

  4. Fact #871: May 4, 2015 Most Manufacturers Have Positive CAFE Credit Balances at the End of Model Year 2013

    Office of Energy Efficiency and Renewable Energy (EERE)

    At the end of the 2013 model year (MY), Toyota, which neither bought nor sold credits between 2010 and 2013, had by far the highest balance of Corporate Average Fuel Economy (CAFE) credits at more...

  5. 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.

  6. 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...

  7. 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...

  8. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

  9. 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.

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

    SciTech Connect (OSTI)

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

    2011-10-01

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

  11. energy data + forecasting | OpenEI Community

    Open Energy Info (EERE)

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

  12. 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....

  13. Oak Ridge National Laboratory [ORNL] Review, Vol. 25, Nos. 3 and 4, 1992 [The First Fifty Years

    DOE R&D Accomplishments [OSTI]

    Krause, C.(ed.)

    1992-01-01

    In observation of the 50th anniversary of Oak Ridge National Laboratory, this special double issue of the Review contains a history of the Laboratory, complete with photographs, drawings, and short accompanying articles. Table of contents include: Wartime Laboratory; High-flux Years; Accelerating Projects; Olympian Feats; Balancing Act; Responding to Social Needs; Energy Technologies; Diversity and Sharing; Global Outreach; Epilogue

  14. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01

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

  15. 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,

  16. 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.

  17. 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.

  18. 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.

  19. Spent nuclear fuels project: FY 1995 multi-year program plan, WBS {number_sign}1.4

    SciTech Connect (OSTI)

    Denning, J.L.

    1994-09-01

    The mission of the Spent Nuclear Fuel (SNF) program is to safely, reliably, and efficiently manage, condition, transport, and store Department of Energy (DOE)-owned SNF, so that it meets acceptance criteria for disposal in a permanent repository. The Hanford Site Spent Nuclear Fuel strategic plan for accomplishing the project mission is: Establish near-term safe storage in the 105-K Basins; Complete national Environmental Policy Act (NEPA) process to obtain a decision on how and where spent nuclear fuel will be managed on the site; Define and establish alternative interim storage on site or transport off site to support implementation of the NEPA decision; and Define and establish a waste package qualified for final disposition. This report contains descriptions of the following: Work Breakdown Structure; WBS Dictionary; Responsibility Assignment Matrix; Program Logic Diagrams; Program Master Baseline Schedule; Program Performance Baseline Schedule; Milestone List; Milestone Description Sheets; Cost Baseline Summary by Year; Basis of Estimate; Waste Type Data; Planned Staffing; and Fiscal Year Work Plan.

  20. 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.

  1. 4

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

    1663 July 2016 work in parallel on other aspects of fusion power. In addition to the U.S. Department of Energy's earlier commitment to ITER, its Advanced Research Projects Agency-Energy (ARPA-E) last year announced nine research grants "to create... new, lower-cost pathways to fusion power and to enable more rapid progress in fusion research and development." The largest of these grants, awarded jointly to Los Alamos National Laboratory and HyperV Technologies Corp., comes in at about

  2. Spent nuclear fuel project multi-year work plan WBS {number_sign}1.4.1

    SciTech Connect (OSTI)

    Wells, J.L.

    1997-03-01

    The Spent Nuclear Fuel (SNF) Project Multi-Year Work Plan (MYWP) is a controlled living document that contains the current SNF Project Technical, Schedule and Cost Baselines. These baselines reflect the current Project execution strategies and are controlled via the change control process. Other changes to the MYWP document will be controlled using the document control process. These changes will be processed as they are approved to keep the MYWP a living document. The MYWP will be maintained continuously as the project baseline through the life of the project and not revised annually. The MYWP is the one document which summarizes and links these three baselines in one place. Supporting documentation for each baseline referred to herein may be impacted by changes to the MYWP, and must also be revised through change control to maintain consistency.

  3. AVLIS: a technical and economic forecast

    SciTech Connect (OSTI)

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

    1986-01-01

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

  4. Y YEAR

    National Nuclear Security Administration (NNSA)

    79 67 -15.19% YEAR 2013 2014 Males 44 34 -22.73% Females 35 33 -5.71% YEAR 2013 2014 SES 6 4 -33.33% EJEK 1 1 0% EN 05 9 8 -11.11% EN 04 6 5 -16.67% NN...

  5. SITE-LEVEL SUMMARY (4Q) of FINAL-4TH-QUARTER-FY-2014-SCORECARD...

    Office of Environmental Management (EM)

    ... FORECAST DATE ACTUAL DATE EA DATE STATUS NARRATIVE VARIANCE NARRATIVE REGULATORY AGREEMENT NAME DESIGNATIONS GREEN SHADED DATES ARE 4TH QUARTER FY 2014 MILESTONES ARRA Project: ...

  6. Builds in U.S. natural gas storage running above five-year average

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

    Builds in U.S. natural gas storage running above five-year average The amount of natural gas put into underground storage since the beginning of the so-called "injection season" in April has been above the five-year average by a wide margin. In its new forecast, the U.S. Energy Information Administration said natural gas inventories, which are running more than 50% above year ago levels, are on track to reach almost 4 trillion cubic feet by the end of October which marks the start of

  7. 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.

  8. 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

  9. Y YEAR

    National Nuclear Security Administration (NNSA)

    4 79 -5.95% ↓ YEAR 2013 2014 Males 59 55 -6.78% ↓ Females 25 24 -4.00% ↓ YEAR 2013 2014 SES 3 3 0% / EJ/EK 4 4 0% / EN 04 2 1 -50.00% ↓ NN (Engineering) 20 20 0% / NQ (Prof/Tech/Admin) 55 51 -7.27% ↓ YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 0 0 0% / American Indian Alaskan Native Female (AIAN,F) 0 0 0% / African American Male (AA,M) 10 10 0% / African American Female (AA,F) 9 8 -11.11% ↓ Asian American Pacific Islander Male (AAPI,M) 2 2 0% / Asian American Pacific

  10. Y YEAR

    National Nuclear Security Administration (NNSA)

    8 27 -3.57% ↓ YEAR 2013 2014 Males 18 17 -5.56% ↓ Females 10 10 0% / YEAR 2013 2014 SES 1 1 0% / EN 05 1 1 0% / EN 04 4 3 -25.00% ↓ NN (Engineering) 12 12 0% / NQ (Prof/Tech/Admin) 9 9 0% / NU (Tech/Admin Support) 1 1 0% / YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 0 0 0% / American Indian Alaskan Native Female (AIAN,F) 1 1 0% / African American Male (AA,M) 4 4 0% / African American Female (AA,F) 3 4 33.33% ↑ Asian American Pacific Islander Male (AAPI,M) 1 1 0% / Asian

  11. 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. ...

  12. 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 ...

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

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01

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

  14. 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

  15. 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...

  16. 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.

  17. 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)

  18. 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.

  19. 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

  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. 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

  2. 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

  3. 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.

  4. Analysis of LaNi{sub 4.25}Al{sub 0.75} (LANA.75) tritide after five years of tritium exposure

    SciTech Connect (OSTI)

    Wermer, J.R.; Holder, J.S.; Mosley, W.C.

    1993-09-01

    Tritium aging studies have shown that LaNi{sub 4.25}Al{sub 0.75} (LANA .75) tritide storage material undergoes significant degradation with tritium aging. After 5.4 years of dormant storage at full stoichiometry, which is considered a worst-case condition for this material, the performance is still acceptable for SRS tritium processing applications. The isotherms change, decreasing the desorption pressures, increasing the isotherm plateau slopes, and decreasing the total storage capacity. Eventually, the material will degrade with time to the point where it may no longer be useful for tritium processing applications. At the end of life, the tritium heel can be exchanged with protium or deuterium to produce a final material containing very little tritium.

  5. HONEYWELL - KANSAS CITY PLANT FISCAL YEARS 2009 THRU 2015 SMALL...

    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 ...

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

    SciTech Connect (OSTI)

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

    1983-01-01

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

  7. Y YEAR

    National Nuclear Security Administration (NNSA)

    5 79 -7.06% ↓ YEAR 2013 2014 Males 59 57 -3.39% ↓ Females 26 22 -15.38% ↓ YEAR 2013 2014 SES 1 0 -100% ↓ EJ/EK 4 3 -25.00% ↓ EN 05 3 2 -33.33% ↓ EN 04 22 22 0% / EN 03 8 8 0% / NN (Engineering) 16 15 -6.25% ↓ NQ (Prof/Tech/Admin) 28 26 -7.14% ↓ NU (Tech/Admin Support) 3 3 0% / YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 2 2 0% / American Indian Alaskan Native Female (AIAN,F) 1 1 0% / African American Male (AA,M) 5 4 -20.00% ↓ African American Female (AA,F) 3 2

  8. Y YEAR

    National Nuclear Security Administration (NNSA)

    21 -4.55% ↓ YEAR 2013 2014 Males 10 8 -20.00% ↓ Females 12 13 8.33% ↑ YEAR 2013 2014 SES 10 7 -30.00% ↓ EX 0 2 100% ↑ EJ/EK 1 1 0% / EN 05 0 1 100% ↑ EN 04 0 1 100% ↑ NQ (Prof/Tech/Admin) 9 8 -11.11% ↓ NU (Tech/Admin Support) 1 1 0% / ED 00 1 0 -100% ↓ YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 0 0 0% / American Indian Alaskan Native Female (AIAN,F) 2 1 -50.00% ↓ African American Male (AA,M) 1 1 0% / African American Female (AA,F) 5 4 -20.00% ↓ Asian

  9. Y YEAR

    National Nuclear Security Administration (NNSA)

    41 155 9.93% ↑ YEAR 2013 2014 Males 92 106 15.22% ↑ Females 49 49 0% / YEAR 2013 2014 SES 8 8 0% / EX 1 1 0% / EJ/EK 4 4 0% / EN 05 11 10 -9.09% ↓ EN 04 11 14 27.27% ↑ EN 03 2 5 150% ↑ NN (Engineering) 60 63 5.00% ↑ NQ (Prof/Tech/Admin) 44 50 13.64% ↑ YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 1 1 0% / American Indian Alaskan Native Female (AIAN,F) 1 1 0% / African American Male (AA,M) 7 10 42.86% ↑ African American Female (AA,F) 13 11 -15.38% ↓ Asian American

  10. Y YEAR

    National Nuclear Security Administration (NNSA)

    79 164 -8.38% ↓ YEAR 2013 2014 Males 100 92 -8.00% ↓ Females 79 72 -8.86% ↓ YEAR 2013 2014 SES 8 8 0% / EJ/EK 4 3 -25.00% ↓ EN 04 11 11 0% / EN 03 1 1 0% / EN 00 0 2 100% ↑ NN (Engineering) 39 32 -17.95% ↓ NQ (Prof/Tech/Admin) 111 104 -6.31% ↓ NU (Tech/Admin Support) 5 3 -40.00% ↓ YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 1 2 100% ↑ American Indian Alaskan Native Female (AIAN,F) 2 1 -50.00% ↓ African American Male (AA,M) 4 3 -25.00% ↓ African American

  11. Forecasting hotspots using predictive visual analytics approach

    SciTech Connect (OSTI)

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

    2014-12-30

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

  12. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

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

    2011-02-23

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

  13. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect (OSTI)

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

    2014-11-13

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

  14. Global disease monitoring and forecasting with Wikipedia

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

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

    2014-11-13

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

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

    SciTech Connect (OSTI)

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

    2015-08-05

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

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

    SciTech Connect (OSTI)

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

    2014-08-15

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  18. 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.

  19. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

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

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

  20. Year Modules

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

    Annual photovoltaic module shipments, 2004-2014 (peak kilowatts) Year Modules 2004 143,274 2005 204,996 2006 320,208 2007 494,148 2008 920,693 2009 1,188,879 2010 2,644,498 2011 3,772,075 2012 4,655,005 2013 4,984,881 2014 6,237,524 Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report.' Note: Includes both U.S. Shipments and Exports.

  1. Y YEAR

    National Nuclear Security Administration (NNSA)

    91 81 -10.99% ↓ YEAR 2013 2014 Males 67 56 -16.42% ↓ Females 24 25 4.17% ↑ YEAR 2013 2014 SES 1 2 100% ↑ EJ/EK 9 8 -11.11% ↓ EN 04 25 22 -12.00% ↓ NN (Engineering) 24 20 -16.67% ↓ NQ (Prof/Tech/Admin) 29 26 -10.34% ↓ NU (Tech/Admin Support) 3 3 0% / YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 2 2 0% / American Indian Alaskan Native Female (AIAN,F) 3 3 0% / African American Male (AA,M) 0 0 0% / African American Female (AA,F) 0 0 0% / Asian American Pacific Islander

  2. Y YEAR

    National Nuclear Security Administration (NNSA)

    97 180 -8.63% ↓ YEAR 2013 2014 Males 105 89 -15.24% ↓ Females 92 91 -1.09% ↓ YEAR 2013 2014 SES 14 13 -7.14% ↓ EX 1 1 0% / EJ/EK 3 3 0% / EN 05 1 1 0% / EN 04 4 2 -50.00% ↓ EN 03 1 1 0% / EN 00 0 3 100% ↑ NN (Engineering) 35 27 -22.86% ↓ NQ (Prof/Tech/Admin) 135 126 -6.67% ↓ NU (Tech/Admin Support) 2 2 0% / GS 15 0 1 100% ↑ GS 13 1 0 -100% ↓ YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 2 1 -50.00% ↓ American Indian Alaskan Native Female (AIAN,F) 0 0 0% /

  3. Y YEAR

    National Nuclear Security Administration (NNSA)

    8 87 -1.14% ↓ YEAR 2013 2014 Males 46 46 0% / Females 42 41 -2.38% ↓ YEAR 2013 2014 SES 1 0 -100% ↓ EJ/EK 4 2 -50.00% ↓ NN (Engineering) 12 12 0% / NQ (Prof/Tech/Admin) 68 70 2.94% ↑ NU (Tech/Admin Support) 3 3 0% / YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 0 0 0% / American Indian Alaskan Native Female (AIAN,F) 2 2 0% / African American Male (AA,M) 5 5 0% / African American Female (AA,F) 5 6 20.00% ↑ Asian American Pacific Islander Male (AAPI,M) 0 0 0% / Asian

  4. Y YEAR

    National Nuclear Security Administration (NNSA)

    1 14 27.27% ↑ YEAR 2013 2014 Males 9 12 33.33% ↑ Females 2 2 0% / YEAR 2013 2014 SES 2 2 0% / EJ/EK 1 1 0% / EN 04 0 1 100% ↑ EN 00 0 1 100% ↑ NN (Engineering) 5 5 0% / NQ (Prof/Tech/Admin) 3 4 33.33% ↑ YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 0 0 0% / American Indian Alaskan Native Female (AIAN,F) 0 0 0% / African American Male (AA,M) 0 0 0% / African American Female (AA,F) 0 0 0% / Asian American Pacific Islander Male (AAPI,M) 1 1 0% / Asian American Pacific

  5. Y YEAR

    National Nuclear Security Administration (NNSA)

    4 30 -11.76% ↓ YEAR 2013 2014 Males 16 14 -12.50% ↓ Females 18 16 -11.11% ↓ YEAR 2013 2014 SES 1 1 0% / EJ/EK 3 1 -66.67% ↓ NQ (Prof/Tech/Admin) 29 27 -6.90% ↓ NU (Tech/Admin Support) 1 1 0% / YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 1 1 0% / American Indian Alaskan Native Female (AIAN,F) 2 2 0% / African American Male (AA,M) 3 3 0% / African American Female (AA,F) 7 6 -14.29% ↓ Asian American Pacific Islander Male (AAPI,M) 1 1 0% / Asian American Pacific Islander

  6. Y YEAR

    National Nuclear Security Administration (NNSA)

    80 83 3.75% ↑ YEAR 2013 2014 Males 48 50 4.17% ↑ Females 32 33 3.13% ↑ YEAR 2013 2014 SES 2 1 -50.00% ↓ EJ/EK 8 7 -12.50% ↓ EN 04 11 9 -18.18% ↓ EN 03 1 1 0% / NN (Engineering) 24 27 12.50% ↑ NQ (Prof/Tech/Admin) 32 33 3.13% ↑ NU (Tech/Admin Support) 2 5 150% ↑ YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 0 0 0% / American Indian Alaskan Native Female (AIAN,F) 3 3 0% / African American Male (AA,M) 0 0 0% / African American Female (AA,F) 2 2 0% / Asian American

  7. The impact of forecasted energy price increases on low-income consumers

    SciTech Connect (OSTI)

    Eisenberg, Joel F.

    2005-10-31

    The Department of Energy’s Energy Information Administration (EIA) recently released its short term forecast for residential energy prices for the winter of 2005-2006. The forecast indicates significant increases in fuel costs, particularly for natural gas, propane, and home heating oil, for the year ahead. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation’s low-income households by primary heating fuel type, nationally and by Census Region. The statistics are intended for the use of policymakers in the Department of Energy’s Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2006 fiscal year.

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

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

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

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

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

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

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

    Energy Savers [EERE]

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

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

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

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

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

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

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

  13. 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. ...

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

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

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

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

    SciTech Connect (OSTI)

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

    2015-12-08

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

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

    Office of Energy Efficiency and Renewable Energy (EERE)

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

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

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

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

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

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

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

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

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

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

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

  1. Selected papers on fuel forecasting and analysis

    SciTech Connect (OSTI)

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

    1983-05-01

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

  2. Twenty years after '95: What climate change means for heat waves...

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

    Twenty years after '95: What climate change means for heat waves, cities and forecasting ... "In the last few years, there's been a big push to get instruments into urban areas." ...

  3. 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.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19

    On December 12, 2005, the reference case projections from ''Annual Energy Outlook 2006'' (AEO 2006) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past five years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past five years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2006. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past five AEO releases (AEO 2001-AEO

  6. Technical analysis in short-term uranium price forecasting

    SciTech Connect (OSTI)

    Schramm, D.S.

    1990-03-01

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06

    On December 5, 2006, the reference case projections from 'Annual Energy Outlook 2007' (AEO 2007) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past six years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past six years at least, levelized cost comparisons of fixed-price renewable generation with variable-price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are 'biased' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2007. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past six AEO releases (AEO 2001-AEO 2006), we

  8. Fact #871: May 4, 2015 Most Manufacturers Have Positive CAFE Credit Balances at the End of Model Year 2013 – Dataset

    Broader source: Energy.gov [DOE]

    Excel file and dataset for Most Manufacturers Have Positive CAFE Credit Balances at the End of Model Year 2013

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

    SciTech Connect (OSTI)

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

    2012-07-01

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

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

    SciTech Connect (OSTI)

    Templeton, K.J.

    1996-05-23

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

  11. Year Modules

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

    dollars per peak watt) Year Modules 2004 $2.99 2005 $3.19 2006 $3.50 2007 $3.37 2008 $3.49 2009 $2.79 2010 $1.96 2011 $1.59 2012 $1.15 2013 $0.75 2014 $0.87 Table 4. Average value of photovoltaic modules, 2004-2014 Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report.' Note: Dollars are not adjusted for inflation.

  12. 3TIER Environmental Forecast Group Inc 3TIER | Open Energy Information

    Open Energy Info (EERE)

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

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

    Reports and Publications (EIA)

    2010-01-01

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

  14. Incorporating Forecast Uncertainty in Utility Control Center

    SciTech Connect (OSTI)

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

    2014-07-09

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

  15. 2007 Wholesale Power Rate Case Final Proposal : Market Price Forecast Study.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    2006-07-01

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

  16. Guide for the preparation of proposals for faculty development projects in energy education, 1980. I. Summer workshops: 4-year college, community college, and 2-year postsecondary technical education teachers. II. Summer workshops: high school teachers. III. In-service workshops: elementary teachers

    SciTech Connect (OSTI)

    Not Available

    1980-01-01

    A program announcement to support Faculty Development Projects in Energy is presented. The project supported will include summer or in-service workshops for groups of teachers conducted by the grantee institution and staffed by faculty or others selected for their appropriate expertise. Eligible organizations include any accredited 4-year college, university, community college, or 2-year postsecondary technical institution.

  17. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema (OSTI)

    Gonzalez, Frank

    2010-01-08

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

  18. 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.

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

    Office of Energy Efficiency and Renewable Energy (EERE)

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

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

    SciTech Connect (OSTI)

    Lantz, E.; Hand, M.

    2010-05-01

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

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

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

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

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

    Reports and Publications (EIA)

    2003-01-01

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

  3. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

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

  4. Improving the Accuracy of Solar Forecasting Funding Opportunity

    Broader source: Energy.gov [DOE]

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

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

    Broader source: Energy.gov [DOE]

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

  6. Value of Improved Short-Term Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2015-02-01

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

  7. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

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

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

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

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

  9. Solar Trackers Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

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

  11. Recently released EIA report presents international forecasting data

    SciTech Connect (OSTI)

    1995-05-01

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

  12. Forecasting of municipal solid waste quantity in a developing country using multivariate grey models

    SciTech Connect (OSTI)

    Intharathirat, Rotchana; Abdul Salam, P.; Kumar, S.; Untong, Akarapong

    2015-05-15

    Highlights: • Grey model can be used to forecast MSW quantity accurately with the limited data. • Prediction interval overcomes the uncertainty of MSW forecast effectively. • A multivariate model gives accuracy associated with factors affecting MSW quantity. • Population, urbanization, employment and household size play role for MSW quantity. - Abstract: In order to plan, manage and use municipal solid waste (MSW) in a sustainable way, accurate forecasting of MSW generation and composition plays a key role. It is difficult to carry out the reliable estimates using the existing models due to the limited data available in the developing countries. This study aims to forecast MSW collected in Thailand with prediction interval in long term period by using the optimized multivariate grey model which is the mathematical approach. For multivariate models, the representative factors of residential and commercial sectors affecting waste collected are identified, classified and quantified based on statistics and mathematics of grey system theory. Results show that GMC (1, 5), the grey model with convolution integral, is the most accurate with the least error of 1.16% MAPE. MSW collected would increase 1.40% per year from 43,435–44,994 tonnes per day in 2013 to 55,177–56,735 tonnes per day in 2030. This model also illustrates that population density is the most important factor affecting MSW collected, followed by urbanization, proportion employment and household size, respectively. These mean that the representative factors of commercial sector may affect more MSW collected than that of residential sector. Results can help decision makers to develop the measures and policies of waste management in long term period.

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

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

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

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

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

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

  15. Study forecasts disappearance of conifers due to climate change

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

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

  16. Application of Ensemble Sensitivity Analysis to Observation Targeting for Short-term Wind Speed Forecasting

    SciTech Connect (OSTI)

    Zack, J; Natenberg, E; Young, S; Manobianco, J; Kamath, C

    2010-02-21

    The operators of electrical grids, sometimes referred to as Balancing Authorities (BA), typically make critical decisions on how to most reliably and economically balance electrical load and generation in time frames ranging from a few minutes to six hours ahead. At higher levels of wind power generation, there is an increasing need to improve the accuracy of 0- to 6-hour ahead wind power forecasts. Forecasts on this time scale have typically been strongly dependent on short-term trends indicated by the time series of power production and meteorological data from a wind farm. Additional input information is often available from the output of Numerical Weather Prediction (NWP) models and occasionally from off-site meteorological towers in the region surrounding the wind generation facility. A widely proposed approach to improve short-term forecasts is the deployment of off-site meteorological towers at locations upstream from the wind generation facility in order to sense approaching wind perturbations. While conceptually appealing, it turns out that, in practice, it is often very difficult to derive significant benefit in forecast performance from this approach. The difficulty is rooted in the fact that the type, scale, and amplitude of the processes controlling wind variability at a site change from day to day if not from hour to hour. Thus, a location that provides some useful forecast information for one time may not be a useful predictor a few hours later. Indeed, some processes that cause significant changes in wind power production operate predominantly in the vertical direction and thus cannot be monitored by employing a network of sensors at off-site locations. Hence, it is very challenging to determine the type of sensors and deployment locations to get the most benefit for a specific short-term forecast application. Two tools recently developed in the meteorological research community have the potential to help determine the locations and parameters to

  17. 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.

  18. LNG to the year 2000

    SciTech Connect (OSTI)

    Davenport, S.T.

    1984-04-01

    By 2000, about 190 MM metric-tpy of LNG will be moving in world trade, with Asia-Pacific as the dominant producer By the year 2000, approximately 190 million metric tons per year of LNG will be moving in worldwide trade. Production of LNG will be spread throughout most of the world, with Asia-Pacific as the dominant producer. LNG will be delivered only to the heavily industrialized areas of North America, Europe and Asia-Pacific. The success of any LNG project will be dependent on its individual economics, market needs, financial planning, and governmental permit processes. We hope industry will be able to put together the LNG projects required to meet the quanitities of production forecast here for the year 2000.

  19. 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.

  20. Forecasting the 2013–2014 influenza season using Wikipedia

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

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

    2015-05-14

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

  1. Forecasting the 2013–2014 influenza season using Wikipedia

    SciTech Connect (OSTI)

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

    2015-05-14

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

  2. Solid waste 30-year volume summary

    SciTech Connect (OSTI)

    Valero, O.J.; Armacost, L.L.; DeForest, T.J.; Templeton, K.J.; Williams, N.C.

    1994-06-01

    A 30-year forecast of the solid waste volumes to be generated or received at the US Department of Energy Hanford Site is described in this report. The volumes described are low-level mixed waste (LLMW) and transuranic/transuranic mixed (TRU/TRUM) waste that will require treatment, storage, and disposal at Hanford`s Solid Waste Operations Complex (SWOC) during the 30-year period from FY 1994 through FY 2023. The data used to complete this document were collected from onsite and offsite waste generators who currently, or are planning to, ship solid wastes to the Hanford Site. An analysis of the data suggests that over 300,000 m{sup 3} of LLMW and TRU/TRUM waste will be managed at Hanford`s SWOC over the next 30 years. An extensive effort was made this year to collect this information. The 1993 solid waste forecast was used as a starting point, which identified approximately 100,000 m{sup 3} of LLMW and TRU/TRUM waste to be sent to the SWOC. After analyzing the forecast waste volume, it was determined that additional waste was expected from the tank waste remediation system (TWRS), onsite decontamination and decommissioning (D&D) activities, and onsite remedial action (RA) activities. Data presented in this report establish a starting point for solid waste management planning. It is recognized that forecast estimates will vary (typically increasing) as facility planning and missions continue to change and become better defined, but the information presented still provides useful insight into Hanford`s future solid waste management requirements.

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2012-04-01

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

  4. Black liquor combustion validated recovery boiler modeling: Final year report. Volume 1 (Main text and Appendix I, sections 1--4)

    SciTech Connect (OSTI)

    Grace, T.M.; Frederick, W.J.; Salcudean, M.; Wessel, R.A.

    1998-08-01

    This project was initiated in October 1990, with the objective of developing and validating a new computer model of a recovery boiler furnace using a computational fluid dynamics (CFD) code specifically tailored to the requirements for solving recovery boiler flows, and using improved submodels for black liquor combustion based on continued laboratory fundamental studies. The key tasks to be accomplished were as follows: (1) Complete the development of enhanced furnace models that have the capability to accurately predict carryover, emissions behavior, dust concentrations, gas temperatures, and wall heat fluxes. (2) Validate the enhanced furnace models, so that users can have confidence in the predicted results. (3) Obtain fundamental information on aerosol formation, deposition, and hardening so as to develop the knowledge base needed to relate furnace model outputs to plugging and fouling in the convective sections of the boiler. (4) Facilitate the transfer of codes, black liquid submodels, and fundamental knowledge to the US kraft pulp industry. Volume 1 contains the main body of the report and the first 4 sections of Appendix 1: Modeling of black liquor recovery boilers -- summary report; Flow and heat transfer modeling in the upper furnace of a kraft recovery boiler; Numerical simulation of black liquor combustion; and Investigation of turbulence models and prediction of swirling flows for kraft recovery furnaces.

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

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

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

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

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

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

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

    SciTech Connect (OSTI)

    Piwko, R.; Jordan, G.

    2011-11-01

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

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

    Broader source: Energy.gov [DOE]

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

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2010-04-01

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

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

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

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

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

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

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

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2009-12-01

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

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

    SciTech Connect (OSTI)

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

    2011-03-28

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

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

    Energy Science and Technology Software Center (OSTI)

    2012-05-01

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

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

    SciTech Connect (OSTI)

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

    2009-03-01

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

  16. 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)

  17. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

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

    2011-11-29

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

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

    Office of Energy Efficiency and Renewable Energy (EERE)

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

  19. Y YEAR

    National Nuclear Security Administration (NNSA)

    7 35 -5.41% ↓ YEAR 2013 2014 Males 27 25 -7.41% ↓ Females 10 10 0% / YEAR 2013 2014 SES 1 1 0% / EN 05 1 1 0% / EN 04 11 10 -9.09% ↓ NN (Engineering) 8 8 0% / NQ (Prof/Tech/Admin) 14 15 7.14% ↑ NU (Tech/Admin Support) 2 0 -100% ↓ YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 0 0 0% / American Indian Alaskan Native Female (AIAN,F) 1 1 0% / African American Male (AA,M) 1 1 0% / African American Female (AA,F) 3 3 0% / Asian American Pacific Islander Male (AAPI,M) 0 0 0% /

  20. 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% /

  1. Y YEAR

    National Nuclear Security Administration (NNSA)

    *Total number of Employees 122 112 -8.20% ↓ YEAR 2013 2014 Males 90 84 -6.67% ↓ Females 32 28 -12.50% ↓ YEAR 2013 2014 SES 26 24 -7.69% ↓ EJ/EK 3 3 0% / EN 05 8 9 12.50% ↑ NN (Engineering) 48 47 -2.08% ↓ NQ (Prof/Tech/Admin) 30 26 -13.33% ↓ NU (Tech/Admin Support) 7 3 -57.14% ↓ YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 0 0 0% / American Indian Alaskan Native Female (AIAN,F) 1 1 0% / African American Male (AA,M) 3 3 0% / African American Female (AA,F) 7 6 -14.29%

  2. Y YEAR

    National Nuclear Security Administration (NNSA)

    40 36 -10.00% ↓ YEAR 2013 2014 Males 18 18 0% / Females 22 18 -18.18% ↓ YEAR 2013 2014 SES 3 2 -33.33% ↓ EJ/EK 1 1 0% / EN 03 1 1 0% / NN (Engineering) 3 3 0% / NQ (Prof/Tech/Admin) 30 27 -10.00% ↓ NU (Tech/Admin Support) 2 2 0% / YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 0 0 0% / American Indian Alaskan Native Female (AIAN,F) 0 0 0% / African American Male (AA,M) 1 1 0% / African American Female (AA,F) 1 1 0% / Asian American Pacific Islander Male (AAPI,M) 0 0 0% /

  3. Y YEAR

    National Nuclear Security Administration (NNSA)

    9 209 -8.73% ↓ YEAR 2013 2014 Males 76 76 0% / Females 153 133 -13.07% ↓ YEAR 2013 2014 SES 9 6 -33.33% ↓ EJ/EK 1 1 0% / NQ (Prof/Tech/Admin) 208 194 -6.73% ↓ NU (Tech/Admin Support) 11 8 -27.27% ↓ YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 2 2 0% / American Indian Alaskan Native Female (AIAN,F) 3 2 -33.33% ↓ African American Male (AA,M) 10 10 0% / African American Female (AA,F) 39 36 -7.69% ↓ Asian American Pacific Islander Male (AAPI,M) 1 1 0% / Asian American

  4. Y YEAR

    National Nuclear Security Administration (NNSA)

    7 80 -8.05% ↓ YEAR 2013 2014 Males 62 57 -8.06% ↓ Females 25 23 -8.00% ↓ YEAR 2013 2014 SES 1 1 0% / EJ/EK 3 3 0% / EN 05 1 1 0% / EN 04 27 24 -11.11% ↓ EN 03 1 0 -100% ↓ NN (Engineering) 26 25 -3.85% ↓ NQ (Prof/Tech/Admin) 26 24 -7.69% ↓ NU (Tech/Admin Support) 2 2 0% / YEAR 2013 2014 American Indian Alaska Native Male (AIAN,M) 1 1 0% / American Indian Alaskan Native Female (AIAN,F) 1 1 0% / African American Male (AA,M) 3 2 -33.33% ↓ African American Female (AA,F) 3 3 0% / Asian

  5. 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.

  6. Microsoft Word - Documentation - Price Forecast Uncertainty.doc

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

    October 2009 1 October 2009 Short-Term Energy Outlook Supplement: Energy Price Volatility and Forecast Uncertainty 1 Summary It is often noted that energy prices are quite volatile, reflecting market participants' adjustments to new information from physical energy markets and/or markets in energy- related financial derivatives. Price volatility is an indication of the level of uncertainty, or risk, in the market. This paper describes how markets price risk and how the market- clearing process

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

    SciTech Connect (OSTI)

    Lemont, S.

    1980-01-01

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

  8. Towards a Science of Tumor Forecast for Clinical Oncology

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

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

    2015-01-01

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

  9. Toward a science of tumor forecasting for clinical oncology

    SciTech Connect (OSTI)

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

    2015-03-15

    We propose that the quantitative cancer biology community makes a concerted effort to apply lessons from weather forecasting to develop an analogous methodology for predicting and evaluating tumor growth and treatment response. Currently, the time course of tumor response is not predicted; instead, response is only assessed post hoc by physical examination or imaging methods. This fundamental practice within clinical oncology limits optimization of a treatment regimen for an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. Furthermore, with a successful methodology toward tumor forecasting, it should be possible to integrate large tumor-specific datasets of varied types and effectively defeat one cancer patient at a time.

  10. Toward a science of tumor forecasting for clinical oncology

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

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

    2015-03-15

    We propose that the quantitative cancer biology community makes a concerted effort to apply lessons from weather forecasting to develop an analogous methodology for predicting and evaluating tumor growth and treatment response. Currently, the time course of tumor response is not predicted; instead, response is only assessed post hoc by physical examination or imaging methods. This fundamental practice within clinical oncology limits optimization of a treatment regimen for an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapiesmore » is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. Furthermore, with a successful methodology toward tumor forecasting, it should be possible to integrate large tumor-specific datasets of varied types and effectively defeat one cancer patient at a time.« less

  11. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect (OSTI)

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

    2015-01-01

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

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

    Broader source: Energy.gov [DOE]

    The Wind Forecast Improvement Project (WFIP) is a U. S. Department of Energy (DOE) sponsored research project whose overarching goals are to improve the accuracy of short-term wind energy forecasts, and to demonstrate the economic value of these improvements.

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

    SciTech Connect (OSTI)

    Vrugt, Jasper A; Wohling, Thomas

    2008-01-01

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

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

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

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

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

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

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

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

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

    SciTech Connect (OSTI)

    Rogers, J.; Porter, K.

    2011-03-01

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

  18. 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

  19. The Value of Improved Wind Power Forecasting in the Western Interconne...

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

    of this research will facilitate a better functional understanding of wind forecasting accuracy and power system operations at various spatial and temporal scales.* Of particular ...

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

    SciTech Connect (OSTI)

    None, None

    2006-12-20

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

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

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

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

  2. 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. ...

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

    SciTech Connect (OSTI)

    Hodge, B.

    2013-12-01

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

  4. EERE Success Story-Solar Forecasting Gets a Boost from Watson...

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

    electric system operators, and solar project owners better predict when and how much ... production varies, an accurate solar forecast is needed in order to maintain an ...

  5. YEAR IN REVIEW

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

    Amped Up Newsletter Volume 1, No. 1 | February 2015 2014 ANNUAL REPORT 2014 YEAR IN REVIEW Volume 1, No. 1, January/February 2015 What's Happening @ EERE IN THIS ISSUE A Message from Dave.......................................... 2 EERE All Hands Meeting ..................................... 3 Staffing Update ..................................................... 4 2014 Success Stories .......................................... 6 Sustainable Transportation ............................ 6 Renewable

  6. Waste Information Management System: One Year After Web Deployment

    SciTech Connect (OSTI)

    Shoffner, P.A.; Geisler, T.J.; Upadhyay, H.; Quintero, W.

    2008-07-01

    The implementation of the Department of Energy (DOE) mandated accelerated cleanup program created significant potential technical impediments. The schedule compression required close coordination and a comprehensive review and prioritization of the barriers that impeded treatment and disposition of the waste streams at each site. Many issues related to site waste treatment and disposal were potential critical path issues under the accelerated schedules. In order to facilitate accelerated cleanup initiatives, waste managers at DOE field sites and at DOE Headquarters in Washington, D.C., needed timely waste forecast information regarding the volumes and types of waste that would be generated by DOE sites over the next 30 years. Each local DOE site has historically collected, organized, and displayed site waste forecast information in separate and unique systems. However, waste information from all sites needed a common application to allow interested parties to understand and view the complete complex-wide picture. A common application allows identification of total waste volumes, material classes, disposition sites, choke points, and technological or regulatory barriers to treatment and disposal. The Applied Research Center (ARC) at Florida International University (FIU) in Miami, Florida, has completed the deployment of this fully operational, web-based forecast system. New functional modules and annual waste forecast data updates have been added to ensure the long-term viability and value of this system. In conclusion: WIMS continues to successfully accomplish the goals and objectives set forth by DOE for this project. WIMS has replaced the historic process of each DOE site gathering, organizing, and reporting their waste forecast information utilizing different database and display technologies. In addition, WIMS meets DOE's objective to have the complex-wide waste forecast information available to all stakeholders and the public in one easy-to-navigate system

  7. Short and Long-Term Perspectives: The Impact on Low-Income Consumers of Forecasted Energy Price Increases in 2008 and A Cap & Trade Carbon Policy in 2030

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred

    2008-01-01

    The Department of Energy's Energy Information Administration (EIA) recently released its short-term forecast for residential energy prices for the winter of 2007-2008. The forecast indicates increases in costs for low-income consumers in the year ahead, particularly for those using fuel oil to heat their homes. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation's low-income households by primary heating fuel type, nationally and by Census Region. The report provides an update of bill estimates provided in a previous study, "The Impact Of Forecasted Energy Price Increases On Low-Income Consumers" (Eisenberg, 2005). The statistics are intended for use by policymakers in the Department of Energy's Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2008 fiscal year. In addition to providing expenditure forecasts for the year immediately ahead, this analysis uses a similar methodology to give policy makers some insight into one of the major policy debates that will impact low-income energy expenditures well into the middle decades of this century and beyond. There is now considerable discussion of employing a cap-and-trade mechanism to first limit and then reduce U.S. emissions of carbon into the atmosphere in order to combat the long-range threat of human-induced climate change. The Energy Information Administration has provided an analysis of projected energy prices in the years 2020 and 2030 for one such cap-and-trade carbon reduction proposal that, when integrated with the RECS 2001 database, provides estimates of how low-income households will be impacted over the long term by such a carbon reduction policy.

  8. 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.

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

    SciTech Connect (OSTI)

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

    2014-12-23

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

  10. 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.

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

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

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

    2014-12-23

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

  12. 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

  13. 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

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

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

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

  15. Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability

    Broader source: Energy.gov [DOE]

    Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability

  16. After 5 Years, NERSC's Franklin Retires

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

    After 5 Years, NERSC's Franklin Retires After 5 Years, NERSC's Franklin Retires May 4, 2012 Linda Vu, lvu@lbl.gov, +1 510 495 2402 Franklin Cray XT4 supercomputer: Franklin Cray ...

  17. Weather Research and Forecasting Model with Vertical Nesting Capability

    Energy Science and Technology Software Center (OSTI)

    2014-08-01

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

  18. ON THE IMPACT OF SUPER RESOLUTION WSR-88D DOPPLER RADAR DATA ASSIMILATION ON HIGH RESOLUTION NUMERICAL MODEL FORECASTS

    SciTech Connect (OSTI)

    Chiswell, S

    2009-01-11

    Assimilation of radar velocity and precipitation fields into high-resolution model simulations can improve precipitation forecasts with decreased 'spin-up' time and improve short-term simulation of boundary layer winds (Benjamin, 2004 & 2007; Xiao, 2008) which is critical to improving plume transport forecasts. Accurate description of wind and turbulence fields is essential to useful atmospheric transport and dispersion results, and any improvement in the accuracy of these fields will make consequence assessment more valuable during both routine operation as well as potential emergency situations. During 2008, the United States National Weather Service (NWS) radars implemented a significant upgrade which increased the real-time level II data resolution to 8 times their previous 'legacy' resolution, from 1 km range gate and 1.0 degree azimuthal resolution to 'super resolution' 250 m range gate and 0.5 degree azimuthal resolution (Fig 1). These radar observations provide reflectivity, velocity and returned power spectra measurements at a range of up to 300 km (460 km for reflectivity) at a frequency of 4-5 minutes and yield up to 13.5 million point observations per level in super-resolution mode. The migration of National Weather Service (NWS) WSR-88D radars to super resolution is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current operational mesoscale model domains utilize grid spacing several times larger than the legacy data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of super resolution reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution is investigated here to determine the impact of the improved data resolution on model predictions.

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

    SciTech Connect (OSTI)

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

    2011-01-17

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

  20. 4-j, 4

    Office of Legacy Management (LM)

    +4-j, 4 ' 1 The Oak Ridge Institute for Science and Education (ORISE) carries out ... were performed using the computer capabilities inherent in the analyzer system. ...

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

    SciTech Connect (OSTI)

    Widiss, R.; Porter, K.

    2014-03-01

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

  2. Comparing Price Forecast Accuracy of Natural Gas Models andFutures Markets

    SciTech Connect (OSTI)

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

    2005-06-30

    The purpose of this article is to compare the accuracy of forecasts for natural gas prices as reported by the Energy Information Administration's Short-Term Energy Outlook (STEO) and the futures market for the period from 1998 to 2003. The analysis tabulates the existing data and develops a statistical comparison of the error between STEO and U.S. wellhead natural gas prices and between Henry Hub and U.S. wellhead spot prices. The results indicate that, on average, Henry Hub is a better predictor of natural gas prices with an average error of 0.23 and a standard deviation of 1.22 than STEO with an average error of -0.52 and a standard deviation of 1.36. This analysis suggests that as the futures market continues to report longer forward prices (currently out to five years), it may be of interest to economic modelers to compare the accuracy of their models to the futures market. The authors would especially like to thank Doug Hale of the Energy Information Administration for supporting and reviewing this work.

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

    SciTech Connect (OSTI)

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

    2008-01-07

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28

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

  5. 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.

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

    SciTech Connect (OSTI)

    Not Available

    1993-12-01

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

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

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

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

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

    SciTech Connect (OSTI)

    Not Available

    2009-11-01

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

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

    Broader source: Energy.gov [DOE]

    The University Corporation for Atmospheric  Research (UCAR) will develop a solar power forecasting system that advances the state of the science through cutting-edge research.

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

    SciTech Connect (OSTI)

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

    2015-06-23

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

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

    SciTech Connect (OSTI)

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

    2012-06-01

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

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

    SciTech Connect (OSTI)

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

    2013-11-01

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

  13. Energy Savings Forecast of Solid-State Lighting in General Illumination Applications

    Broader source: Energy.gov [DOE]

    Report forecasting the U.S. energy savings of LED white-light sources compared to conventional white-light sources (i.e., incandescent, halogen, fluorescent, and high-intensity discharge) over the...

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

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

    Gasoline price forecast to stay below 3 a gallon in 2015 The national average pump price of gasoline is expected to stay below 3 per gallon during 2015. In its new monthly ...

  15. Year's End 2012 | Jefferson Lab

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

    Annual photovoltaic module shipments, 2004-2014 (peak kilowatts) Year Modules 2004 143,274 2005 204,996 2006 320,208 2007 494,148 2008 920,693 2009 1,188,879 2010 2,644,498 2011 3,772,075 2012 4,655,005 2013 4,984,881 2014 6,237,524 Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report.' Note: Includes both U.S. Shipments and Exports.

    Year's End 2012 Year's End 2012 September 27, 2012 Throughout history, civilizations have developed

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

    SciTech Connect (OSTI)

    Fournier, W.M.; Hasson, V.

    1980-10-10

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

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

    SciTech Connect (OSTI)

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

    2014-09-01

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

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

    SciTech Connect (OSTI)

    Stoffel, T.

    2012-06-01

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

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

    SciTech Connect (OSTI)

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

    2013-05-01

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

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

    SciTech Connect (OSTI)

    Not Available

    1993-12-01

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

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

    SciTech Connect (OSTI)

    1995-01-01

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

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

    SciTech Connect (OSTI)

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

    2014-11-01

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

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

    SciTech Connect (OSTI)

    Tian; Tian; Chernyakhovskiy, Ilya

    2016-01-01

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

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

    SciTech Connect (OSTI)

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

    2012-08-01

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

  5. HPSS Yearly Network Traffic

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

    HPSS Yearly Network Traffic HPSS Yearly Network Traffic Yearly Summary of IO Traffic Between Storage and Network Destinations These bar charts show the total transfer traffic for...

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

    SciTech Connect (OSTI)

    Acton, J.P.

    1983-05-01

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

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

    SciTech Connect (OSTI)

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

    2009-09-01

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

  8. Calendar Year 2009 Program Benefits for ENERGY STAR Labeled Products

    SciTech Connect (OSTI)

    Homan, Gregory K; Sanchez, Marla C.; Brown, Richard E.

    2010-11-15

    ENERGY STAR is a voluntary energy efficiency labeling program operated jointly by the Environmental Protection Agency (US EPA) and the U.S. Department of Energy (US DOE), designed to identify and promote energy-efficient products, buildings and practices. Since the program inception in 1992, ENERGY STAR has become a leading international brand for energy efficient products, and currently labels more than thirty products, spanning office equipment, heating, cooling and ventilation equipment, commercial and residential lighting, home electronics, and major appliances. ENERGY STAR's central role in the development of regional, national and international energy programs necessitates an open process whereby its program achievements to date as well as projected future savings are shared with stakeholders. This report presents savings estimates from the use ENERGY STAR labeled products. We present estimates of energy, dollar, and carbon savings achieved by the program in the year 2009, annual forecasts for 2010 and 2011, and cumulative savings estimates for the period 1993 through 2009 and cumulative forecasts for the period 2010 through 2015. Through 2009 the program saved 9.5 Quads of primary energy and avoided the equivalent of 170 million metric tons carbon (MMTC). The forecast for the period 2009-2015 is 11.5 Quads or primary energy saved and 202 MMTC emissions avoided. The sensitivity analysis bounds the best estimate of carbon avoided between 110 MMTC and 231 MMTC (1993 to 2009) and between 130 MMTC and 285 MMTC (2010 to 2015).

  9. Mercury emissions from municipal solid waste combustors. An assessment of the current situation in the United States and forecast of future emissions

    SciTech Connect (OSTI)

    1993-05-01

    This report examines emissions of mercury (Hg) from municipal solid waste (MSW) combustion in the United States (US). It is projected that total annual nationwide MSW combustor emissions of mercury could decrease from about 97 tonnes (1989 baseline uncontrolled emissions) to less than about 4 tonnes in the year 2000. This represents approximately a 95 percent reduction in the amount of mercury emitted from combusted MSW compared to the 1989 mercury emissions baseline. The likelihood that routinely achievable mercury emissions removal efficiencies of about 80 percent or more can be assured; it is estimated that MSW combustors in the US could prove to be a comparatively minor source of mercury emissions after about 1995. This forecast assumes that diligent measures to control mercury emissions, such as via use of supplemental control technologies (e.g., carbon adsorption), are generally employed at that time. However, no present consensus was found that such emissions control measures can be implemented industry-wide in the US within this time frame. Although the availability of technology is apparently not a limiting factor, practical implementation of necessary control technology may be limited by administrative constraints and other considerations (e.g., planning, budgeting, regulatory compliance requirements, etc.). These projections assume that: (a) about 80 percent mercury emissions reduction control efficiency is achieved with air pollution control equipment likely to be employed by that time; (b) most cylinder-shaped mercury-zinc (CSMZ) batteries used in hospital applications can be prevented from being disposed into the MSW stream or are replaced with alternative batteries that do not contain mercury; and (c) either the amount of mercury used in fluorescent lamps is decreased to an industry-wide average of about 27 milligrams of mercury per lamp or extensive diversion from the MSW stream of fluorescent lamps that contain mercury is accomplished.

  10. Financial Management Committee

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

    is negative 4 million for the end of FY 2011. The 2nd Quarter Review end-of-year net revenue forecast is 25 million. The current Northwest River Forecasting Center forecast puts...

  11. HPSS Yearly Network Traffic

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

    HPSS Yearly Network Traffic HPSS Yearly Network Traffic Yearly Summary of I/O Traffic Between Storage and Network Destinations These bar charts show the total transfer traffic for each year between storage and network destinations (systems within and outside of NERSC). Traffic for the current year is an estimate derived by scaling the known months traffic up to 12 months. The years shown are calendar years. The first graph shows the overall growth in network traffic to storage over the years.

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

    SciTech Connect (OSTI)

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

    2009-11-20

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

  13. H. R. 4926: a bill to authorize appropriations to the Department of Energy for civilian energy programs for fiscal year 1987. Introduced in the House of Representatives, Ninety-Ninth Congress, Second Session, June 4, 1986

    SciTech Connect (OSTI)

    Not Available

    1986-01-01

    The DOE Civilian Energy Programs Authorization Act for Fiscal Year 1987 authorizes appropriations for the operating costs of non-nuclear energy programs, nuclear energy and electric programs, plant and capital equipment, and both prior year and new construction. The bill reduces supporting research and technical analysis budgets by $66,303,000 for a total of $474,711,000. The authorization for general science and research totals $633,671,000, a reduction of $131,729,000. Title II authorizes funds for other activities, such as energy conservation and solar and nuclear energy research and development. Title III establishes a research and development program in advanced steel manufacturing technologies.

  14. Making appropriations for energy and water development for the fiscal year ending September 30, 1995, and for other purposes. Introduced in the House of Representatives, One Hundred Third Congress, Second Session, August 4, 1994

    SciTech Connect (OSTI)

    1994-12-31

    The report addresses H.R. 4506 a bill making appropriations for energy and water development for the fiscal year ending September 30, 1995. The bill supplies funds for water resources development programs and related activities of the Dept. of Army, Civil Functions - U.S. Army Corps of Engineers Civil Works Program, the Department of Interior`s Bureau of Reclamation, and for certain Department of Energy`s energy research activities. The report includes comments on various programs.

  15. US TG 4 Activities of QA Forum | Department of Energy

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

    US TG 4 Activities of QA Forum US TG 4 Activities of QA Forum Presented at the PV Module Reliability Workshop, February 26 - 27 2013, Golden, Colorado pvmrw13_diodes_solaria_whitfield.pdf (3.42 MB) More Documents & Publications On the Occurrence of Thermal Runaway in Diode in the J-Box US & Japan TG 4 Activities of QA Forum Wind Forecast Improvement Project Southern Study Area Final Report

  16. Energy Level Diagrams A=4

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

    4 Available in the following year: (1992) A=4 Energy Level Diagrams from (1992TI02) GIF (Graphic Interchange Format): 4H (38 KB) 4He (90 KB) 4Li (36 KB) Isobar diagram (60 KB) PDF (Portable Document Format): 4H (26 KB) 4He (47 KB) 4Li (24 KB) Isobar diagram (36 KB) EPS (Encapsulated Postscript): 4H (1.32 MB) 4He (1.79 MB) 4Li (1.13 MB) Isobar diagram (1.54 MB

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

    SciTech Connect (OSTI)

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

    2015-01-01

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

  18. Demand forecasting for automotive sector in Malaysia by system dynamics approach

    SciTech Connect (OSTI)

    Zulkepli, Jafri Abidin, Norhaslinda Zainal; Fong, Chan Hwa

    2015-12-11

    In general, Proton as an automotive company needs to forecast future demand of the car to assist in decision making related to capacity expansion planning. One of the forecasting approaches that based on judgemental or subjective factors is normally used to forecast the demand. As a result, demand could be overstock that eventually will increase the operation cost; or the company will face understock, which resulted losing their customers. Due to automotive industry is very challenging process because of high level of complexity and uncertainty involved in the system, an accurate tool to forecast the future of automotive demand from the modelling perspective is required. Hence, the main objective of this paper is to forecast the demand of automotive Proton car industry in Malaysia using system dynamics approach. Two types of intervention namely optimistic and pessimistic experiments scenarios have been tested to determine the capacity expansion that can prevent the company from overstocking. Finding from this study highlighted that the management needs to expand their production for optimistic scenario, whilst pessimistic give results that would otherwise. Finally, this study could help Proton Edar Sdn. Bhd (PESB) to manage the long-term capacity planning in order to meet the future demand of the Proton cars.

  19. Idaho National Laboratory Emergency Readiness Assurance Plan - Fiscal Year 2015

    SciTech Connect (OSTI)

    Farmer, Carl J.

    2015-09-01

    Department of Energy Order 151.1C, Comprehensive Emergency Management System requires that each Department of Energy field element documents readiness assurance activities, addressing emergency response planning and preparedness. Battelle Energy Alliance, LLC, as prime contractor at the Idaho National Laboratory (INL), has compiled this Emergency Readiness Assurance Plan to provide this assurance to the Department of Energy Idaho Operations Office. Stated emergency capabilities at the INL are sufficient to implement emergency plans. Summary tables augment descriptive paragraphs to provide easy access to data. Additionally, the plan furnishes budgeting, personnel, and planning forecasts for the next 5 years.

  20. Technology data characterizing water heating in commercial buildings: Application to end-use forecasting

    SciTech Connect (OSTI)

    Sezgen, O.; Koomey, J.G.

    1995-12-01

    Commercial-sector conservation analyses have traditionally focused on lighting and space conditioning because of their relatively-large shares of electricity and fuel consumption in commercial buildings. In this report we focus on water heating, which is one of the neglected end uses in the commercial sector. The share of the water-heating end use in commercial-sector electricity consumption is 3%, which corresponds to 0.3 quadrillion Btu (quads) of primary energy consumption. Water heating accounts for 15% of commercial-sector fuel use, which corresponds to 1.6 quads of primary energy consumption. Although smaller in absolute size than the savings associated with lighting and space conditioning, the potential cost-effective energy savings from water heaters are large enough in percentage terms to warrant closer attention. In addition, water heating is much more important in particular building types than in the commercial sector as a whole. Fuel consumption for water heating is highest in lodging establishments, hospitals, and restaurants (0.27, 0.22, and 0.19 quads, respectively); water heating`s share of fuel consumption for these building types is 35%, 18% and 32%, respectively. At the Lawrence Berkeley National Laboratory, we have developed and refined a base-year data set characterizing water heating technologies in commercial buildings as well as a modeling framework. We present the data and modeling framework in this report. The present commercial floorstock is characterized in terms of water heating requirements and technology saturations. Cost-efficiency data for water heating technologies are also developed. These data are intended to support models used for forecasting energy use of water heating in the commercial sector.

  1. 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

  2. Sandia's Cooperative Monitoring Center celebrates 20 years |...

    National Nuclear Security Administration (NNSA)

    Cooperative Monitoring Center celebrates 20 years Tuesday, November 18, 2014 - 4:10pm Sandia National Laboratories' Cooperative Monitoring Center is celebrating its 20th ...

  3. 50 Years of Space

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

    50 Years of Space science-innovationassetsimagesicon-science.jpg 50 Years of Space Since 1943, some of the world's smartest and most dedicated technical people have ...

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

    SciTech Connect (OSTI)

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

    1994-05-01

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

  5. PBL FY 2002 Third Quarter Review Forecast of Generation Accumulated...

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

    Revenue Basis. The FB CRAC Revenue Basis is the total generation revenue (not including LB CRAC) for the loads subject to FB CRAC plus Slice loads, for the year in which the FB...

  6. After 5 Years, NERSC's Franklin Retires

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

    After 5 Years, NERSC's Franklin Retires After 5 Years, NERSC's Franklin Retires May 4, 2012 Linda Vu, lvu@lbl.gov, +1 510 495 2402 Franklin Cray XT4 supercomputer: Franklin Cray XT4 supercomputer -- a massively parallel processor (MPP) system. Photo: Roy Kaltschmidt/LBNL. This week, the Department of Energy's National Energy Research Scientific Computing Center (NERSC) retired one of its most scientifically prolific supercomputers to date-a Cray XT4 named Franklin, in honor of the United States'

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

    SciTech Connect (OSTI)

    Zupanski, M. )

    1993-08-01

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

  8. ARM - Field Campaign - 915 MHz Wind Profiler for Cloud Forecasting at BNL

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

    govCampaigns915 MHz Wind Profiler for Cloud Forecasting at BNL Campaign Links Field Campaign Report 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 Campaign : 915 MHz Wind Profiler for Cloud Forecasting at BNL 2011.05.31 - 2012.05.31 Lead Scientist : Michael Jensen For data sets, see below. Abstract In support of the installation of a 37 MW solar array on the grounds of Brookhaven National Laboratory (BNL), a study

  9. ARM - Field Campaign - Radar Wind Profiler for Cloud Forecasting at BNL

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

    govCampaignsRadar Wind Profiler for Cloud Forecasting at BNL Campaign Links Field Campaign Report 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 Campaign : Radar Wind Profiler for Cloud Forecasting at BNL 2013.07.15 - 2015.08.06 Lead Scientist : Michael Jensen For data sets, see below. Abstract In support of recent activities funded by the DOE Energy Efficiency and Renewable Energy (EERE) to produce short-term

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

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

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark A.; Wiser, Ryan H.

    2010-01-04

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

  12. Projects of the year

    SciTech Connect (OSTI)

    Hansen, T.

    2007-01-15

    The Peabody Hotel, Orlando, Florida was the site of Power Engineering magazine's 2006 Projects of the Year Awards Banquet, which kicked-off the Power-Gen International conference and exhibition. The Best Coal-fired Project was awarded to Tri-State Generation and Transmission Association Inc., owner of Springenville Unit 3. This is a 400 MW pulverized coal plant in Springeville, AZ, sited with two existing coal-fired units. Designed to fire Powder River Basin coal, it has low NOx burners and selective catalytic reduction for NOx control, dry flue gas desulfurization for SO{sub 2} control and a pulse jet baghouse for particulate control. It has a seven-stage feedwater heater and condensers to ensure maximum performance. Progress Energy-Carolinas' Asheville Power Station FGD and SCR Project was awarded the 2006 coal-fired Project Honorable Mention. This plant in Skyland, NC was required to significantly reduce NOx emissions. When completed, the improvements will reduce NOx by 93% compared to 1996 levels and SO{sub 2} by 93% compared to 2001 levels. Awards for best gas-fired, nuclear, and renewable/sustainable energy projects are recorded. The Sasyadko Coal-Mine Methane Cogeneration Plant near Donezk, Ukraine, was given the 2006 Honorable Mention for Best Renewable/Sustainable Energy Project. In November 2004, Ukraine was among 14 nations to launch the Methane to Markets partnership. The award-winning plant is fuelled by methane released during coal extraction. It generates 42 MW of power. 4 photos.

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

    SciTech Connect (OSTI)

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

    2013-09-01

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

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

    SciTech Connect (OSTI)

    Tutt, T.; Flory, J.

    1995-05-01

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

  15. Stan Watkins Named Department of Energy Facility Representative of the Year

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

    Stan Calvert About Us Stan Calvert - Wind Systems Integration Team Lead, Wind & Water Power Program Stan Calvert is the Wind Systems Integration Team Lead for the Wind and Water Power Program. Most Recent Today's Forecast: Improved Wind Predictions July 20 | National Nuclear Security Administration | (NNSA)

    Stan Watkins Named Department of Energy Facility Representative of the Year May 15, 2009 Microsoft Office document icon R-09-02

  16. 70 years after Trinity

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

    70 years after Trinity 70 years after Trinity Though the world has seen many changes since Trinity, one thing has remained constant: Los Alamos remains essential to our nation's ...

  17. Secretary Moniz's First Year

    Broader source: Energy.gov [DOE]

    We're looking back at some of the biggest moments from Energy Secretary Ernest Moniz's first year in office.

  18. Optimal observation time window for forecasting the next earthquake

    SciTech Connect (OSTI)

    Omi, Takahiro; Shinomoto, Shigeru; Kanter, Ido

    2011-02-15

    We report that the accuracy of predicting the occurrence time of the next earthquake is significantly enhanced by observing the latest rate of earthquake occurrences. The observation period that minimizes the temporal uncertainty of the next occurrence is on the order of 10 hours. This result is independent of the threshold magnitude and is consistent across different geographic areas. This time scale is much shorter than the months or years that have previously been considered characteristic of seismic activities.

  19. 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

  20. Calendar Year 2008 Program Benefits for ENERGY STAR Labeled Products

    SciTech Connect (OSTI)

    Homan, GregoryK; Sanchez, Marla; Brown, RichardE; Lai, Judy

    2010-08-24

    This paper presents current and projected savings for ENERGY STAR labeled products, and details the status of the model as implemented in the September 2009 spreadsheets. ENERGY STAR is a voluntary energy efficiency labeling program operated jointly by the Environmental Protection Agency (US EPA) and the U.S. Department of Energy (US DOE), designed to identify and promote energy-efficient products, buildings and practices. Since the program inception in 1992, ENERGY STAR has become a leading international brand for energy efficient products, and currently labels more than thirty products, spanning office equipment, heating, cooling and ventilation equipment, commercial and residential lighting, home electronics, and major appliances. ENERGY STAR's central role in the development of regional, national and international energy programs necessitates an open process whereby its program achievements to date as well as projected future savings are shared with stakeholders. This report presents savings estimates for ENERGY STAR labeled products. We present estimates of energy, dollar, and carbon savings achieved by the program in the year 2008, annual forecasts for 2009 and 2010, and cumulative savings estimates for the period 1993 through 2008 and cumulative forecasts for the period 2009 through 2015. Through 2008 the program saved 8.8 Quads of primary energy and avoided the equivalent of 158 metric tones carbon (MtC). The forecast for the period 2009-2015 is 18.1 Quads or primary energy saved and 316 MtC emissions avoided. The sensitivity analysis bounds the best estimate of carbon avoided between 104 MtC and 213 MtC (1993 to 2008) and between 206 MtC and 444 MtC (2009 to 2015). In this report we address the following questions for ENERGY STAR labeled products: (1) How are ENERGY STAR impacts quantified; (2) What are the ENERGY STAR achievements; and (3) What are the limitations to our method?

  1. Agent-based model forecasts aging of the population of people who inject drugs in metropolitan Chicago and changing prevalence of hepatitis C infections

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

    Gutfraind, Alexander; Boodram, Basmattee; Prachand, Nikhil; Hailegiorgis, Atesmachew; Dahari, Harel; Major, Marian E.; Kaderali, Lars

    2015-09-30

    People who inject drugs (PWID) are at high risk for blood-borne pathogens transmitted during the sharing of contaminated injection equipment, particularly hepatitis C virus (HCV). HCV prevalence is influenced by a complex interplay of drug-use behaviors, social networks, and geography, as well as the availability of interventions, such as needle exchange programs. To adequately address this complexity in HCV epidemic forecasting, we have developed a computational model, the Agent-based Pathogen Kinetics model (APK). APK simulates the PWID population in metropolitan Chicago, including the social interactions that result in HCV infection. We used multiple empirical data sources on Chicago PWID tomore » build a spatial distribution of an in silico PWID population and modeled networks among the PWID by considering the geography of the city and its suburbs. APK was validated against 2012 empirical data (the latest available) and shown to agree with network and epidemiological surveys to within 1%. For the period 2010–2020, APK forecasts a decline in HCV prevalence of 0.8% per year from 44(±2)% to 36(±5)%, although some sub-populations would continue to have relatively high prevalence, including Non-Hispanic Blacks, 48(±5)%. The rate of decline will be lowest in Non-Hispanic Whites and we find, in a reversal of historical trends, that incidence among non-Hispanic Whites would exceed incidence among Non-Hispanic Blacks (0.66 per 100 per years vs 0.17 per 100 person years). APK also forecasts an increase in PWID mean age from 35(±1) to 40(±2) with a corresponding increase from 59(±2)% to 80(±6)% in the proportion of the population >30 years old. Our research highlight the importance of analyzing sub-populations in disease predictions, the utility of computer simulation for analyzing demographic and health trends among PWID and serve as a tool for guiding intervention and prevention strategies in Chicago, and other major cities.« less

  2. Agent-based model forecasts aging of the population of people who inject drugs in metropolitan Chicago and changing prevalence of hepatitis C infections

    SciTech Connect (OSTI)

    Gutfraind, Alexander; Boodram, Basmattee; Prachand, Nikhil; Hailegiorgis, Atesmachew; Dahari, Harel; Major, Marian E.; Kaderali, Lars

    2015-09-30

    People who inject drugs (PWID) are at high risk for blood-borne pathogens transmitted during the sharing of contaminated injection equipment, particularly hepatitis C virus (HCV). HCV prevalence is influenced by a complex interplay of drug-use behaviors, social networks, and geography, as well as the availability of interventions, such as needle exchange programs. To adequately address this complexity in HCV epidemic forecasting, we have developed a computational model, the Agent-based Pathogen Kinetics model (APK). APK simulates the PWID population in metropolitan Chicago, including the social interactions that result in HCV infection. We used multiple empirical data sources on Chicago PWID to build a spatial distribution of an in silico PWID population and modeled networks among the PWID by considering the geography of the city and its suburbs. APK was validated against 2012 empirical data (the latest available) and shown to agree with network and epidemiological surveys to within 1%. For the period 2010–2020, APK forecasts a decline in HCV prevalence of 0.8% per year from 44(±2)% to 36(±5)%, although some sub-populations would continue to have relatively high prevalence, including Non-Hispanic Blacks, 48(±5)%. The rate of decline will be lowest in Non-Hispanic Whites and we find, in a reversal of historical trends, that incidence among non-Hispanic Whites would exceed incidence among Non-Hispanic Blacks (0.66 per 100 per years vs 0.17 per 100 person years). APK also forecasts an increase in PWID mean age from 35(±1) to 40(±2) with a corresponding increase from 59(±2)% to 80(±6)% in the proportion of the population >30 years old. Our research highlight the importance of analyzing sub-populations in disease predictions, the utility of computer simulation for analyzing demographic and health trends among PWID and serve as a tool for guiding intervention and prevention strategies in Chicago, and other major cities.

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

    SciTech Connect (OSTI)

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

    2011-10-01

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

  4. Fiscal Year Ended

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

    Fiscal Year Ended September 30, 2014 Report to Congress July 2016 United States Department of Energy Washington, DC 20585 Department of Energy | July 2016 Report on Uncosted Balances for Fiscal Year Ended 2014| Page iii Executive Summary As required by the Energy Policy Act of 1992 (Public Law 102-486), the Department of Energy is submitting a Report on Uncosted Balances for Fiscal Year Ended 2014. This report presents the results of the Department's annual analysis of uncosted obligation

  5. 2013 Year in Review

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

    3 Year in Review i 2013 YIR May 2014 Year-in-Review: 2013 Energy Infrastructure Events and Expansions Infrastructure Security and Energy Restoration Office of Electricity Delivery and Energy Reliability U.S. Department of Energy DOE / 2013 Year in Review ii 2013 YIR For Further Information This report was prepared by the Office of Electricity Delivery and Energy Reliability under the direction of Patricia Hoffman, Assistant Secretary, and William Bryan, Deputy Assistant Secretary. Specific

  6. Agency Improvement Plan For Fiscal Year 2006 and Fiscal Year...

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

    Agency Improvement Plan For Fiscal Year 2006 and Fiscal Year 2007 Agency Improvement Plan For Fiscal Year 2006 and Fiscal Year 2007 Department of Energy Report and Agency ...

  7. New Tools for Forecasting Old Physics at the LHC

    ScienceCinema (OSTI)

    None

    2011-10-06

    For the LHC to uncover many types of new physics, the "old physics" produced by the Standard Model must be understood very well. For decades, the central theoretical tool for this job was the Feynman diagram expansion. However, Feynman diagrams are just too slow, even on fast computers, to allow adequate precision for complicated LHC events with many jets in the final state. Such events are already visible in the initial LHC data. Over the past few years, alternative methods to Feynman diagrams have come to fruition. These new "on-shell" methods are based on the old principles of unitarity and factorization. They can be much more efficient because they exploit the underlying simplicity of scattering amplitudes, and recycle lower-loop information. I will describe how and why these methods work, and present some of the recent state-of-the-art results that have been obtained with them.

  8. b)(4

    National Nuclear Security Administration (NNSA)

    (b)(4) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(4) (b)(4) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(4) (b)(4) (b)(4) (b)(4) (b)(6)

  9. Final Year Project Report

    SciTech Connect (OSTI)

    Hubsch, Tristan

    2013-06-20

    In the last years of this eighteen-year grant project, the research efforts have focused mostly on the study of off-shell representations of supersymmetry, both on the worldline and on the world- sheet, i.e., both in supersymmetric quantum mechanics and in supersymmetric field theory in 1+1-dimensional spacetime.

  10. EM Contractors' Donations Support 4-Year Engineering Degree at...

    Office of Environmental Management (EM)

    USC Aiken Chancellor Sandra Jordan, and SRR President and Project Manager Ken Rueter. ... USC Aiken Chancellor Sandra Jordan, and SRR President and Project Manager Ken Rueter. ...

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

    SciTech Connect (OSTI)

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

    2009-10-09

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

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

    SciTech Connect (OSTI)

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

    2010-04-20

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

  13. Validation of Global Weather Forecast and Climate Models Over the North

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

    Slope of Alaska Validation of Global Weather Forecast and Climate Models Over the North Slope of Alaska Xie, Shaocheng Lawrence Livermore National Laboratory Klein, Stephen Lawrence Livermore National Laboratory Boyle, Jim Lawrence Livermore National Laboratory Fiorino, Michael DOE/Lawrence Livermore National Laboratory Hnilo, Justin DOE/Lawrence Livermore National Laboratory Phillips, Thomas PCMDI/LLNL Potter, Gerald Lawrence Livermore National Laboratory Beljaars, Anton ECMWF Category:

  14. Are there Gains from Pooling Real-Time Oil Price Forecasts?

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

    Are there Gains from Pooling Real- Time Oil Price Forecasts? Christiane Baumeister, Bank of Canada Lutz Kilian, University of Michigan Thomas K. Lee, U.S. Energy Information Administration February 12, 2014 Independent Statistics & Analysis www.eia.gov U.S. Energy Information Administration Washington, DC 20585 This paper is released to encourage discussion and critical comment. The analysis and conclusions expressed here are those of the authors and not necessarily those of the U.S. Energy

  15. Allocation Year Rollover process

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

    Allocatio Year Rollover process Allocation Year Rollover process December 23, 2013 by Francesca Verdier Allocation Year 2013 (AY13) ends at 23:59:59 on Monday, January 13, 2014. AY14 runs from Tuesday, January 14, 2014 through Monday, January 12, 2015. The major features of the rollover are: charging acroess the AY boundary: All batch jobs will continue running during the rollover. Time accrued before midnight will be charged to AY13 repos; time accrued after midnight will be charged to AY14

  16. Forecasting the Magnitude of Sustainable Biofeedstock Supplies: the Challenges and the Rewards

    SciTech Connect (OSTI)

    Graham, Robin Lambert

    2007-01-01

    Forecasting the magnitude of sustainable biofeedstock supplies is challenging because of 1) the myriad of potential feedstock types and their management 2) the need to account for the spatial variation of both the supplies and their environmental and economic consequences, and 3) the inherent challenges of optimizing across economic and environmental considerations. Over the last two decades U.S. biomass forecasts have become increasingly complex and sensitive to environmental and economic considerations. More model development and research is needed however, to capture the landscape and regional tradeoffs of differing biofeedstock supplies especially with regards water quality concerns and wildlife/biodiversity. Forecasts need to be done in the context of the direction of change and what the probable land use and attendant environmental and economic outcomes would be if biofeedstocks were not being produced. To evaluate sustainability, process-oriented models need to be coupled or used to inform sector models and more work needs to be done on developing environmental metrics that are useful for evaluating economic and environmental tradeoffs. These challenges are exciting and worthwhile as they will enable the bioenergy industry to capture environmental and social benefits of biofeedstock production and reduce risks.

  17. Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay

    SciTech Connect (OSTI)

    Jacobs, John M.; Rhodes, M.; Brown, C. W.; Hood, Raleigh R.; Leight, A.; Long, Wen; Wood, R.

    2014-11-01

    The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions: Environmental parameters such as temperature, salinity and turbidity are capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions.

  18. Turbulence-driven coronal heating and improvements to empirical forecasting of the solar wind

    SciTech Connect (OSTI)

    Woolsey, Lauren N.; Cranmer, Steven R.

    2014-06-01

    Forecasting models of the solar wind often rely on simple parameterizations of the magnetic field that ignore the effects of the full magnetic field geometry. In this paper, we present the results of two solar wind prediction models that consider the full magnetic field profile and include the effects of Alfvn waves on coronal heating and wind acceleration. The one-dimensional magnetohydrodynamic code ZEPHYR self-consistently finds solar wind solutions without the need for empirical heating functions. Another one-dimensional code, introduced in this paper (The Efficient Modified-Parker-Equation-Solving Tool, TEMPEST), can act as a smaller, stand-alone code for use in forecasting pipelines. TEMPEST is written in Python and will become a publicly available library of functions that is easy to adapt and expand. We discuss important relations between the magnetic field profile and properties of the solar wind that can be used to independently validate prediction models. ZEPHYR provides the foundation and calibration for TEMPEST, and ultimately we will use these models to predict observations and explain space weather created by the bulk solar wind. We are able to reproduce with both models the general anticorrelation seen in comparisons of observed wind speed at 1 AU and the flux tube expansion factor. There is significantly less spread than comparing the results of the two models than between ZEPHYR and a traditional flux tube expansion relation. We suggest that the new code, TEMPEST, will become a valuable tool in the forecasting of space weather.

  19. Evaluation of Forecasted Southeast Pacific Stratocumulus in the NCAR, GFDL and ECMWF Models

    SciTech Connect (OSTI)

    Hannay, C; Williamson, D L; Hack, J J; Kiehl, J T; Olson, J G; Klein, S A; Bretherton, C S; K?hler, M

    2008-01-24

    We examine forecasts of Southeast Pacific stratocumulus at 20S and 85W during the East Pacific Investigation of Climate (EPIC) cruise of October 2001 with the ECMWF model, the Atmospheric Model (AM) from GFDL, the Community Atmosphere Model (CAM) from NCAR, and the CAM with a revised atmospheric boundary layer formulation from the University of Washington (CAM-UW). The forecasts are initialized from ECMWF analyses and each model is run for 3 days to determine the differences with the EPIC field data. Observations during the EPIC cruise show a stable and well-mixed boundary layer under a sharp inversion. The inversion height and the cloud layer have a strong and regular diurnal cycle. A key problem common to the four models is that the forecasted planetary boundary layer (PBL) height is too low when compared to EPIC observations. All the models produce a strong diurnal cycle in the Liquid Water Path (LWP) but there are large differences in the amplitude and the phase compared to the EPIC observations. This, in turn, affects the radiative fluxes at the surface. There is a large spread in the surface energy budget terms amongst the models and large discrepancies with observational estimates. Single Column Model (SCM) experiments with the CAM show that the vertical pressure velocity has a large impact on the PBL height and LWP. Both the amplitude of the vertical pressure velocity field and its vertical structure play a significant role in the collapse or the maintenance of the PBL.

  20. 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.

  1. Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting

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

    Carlberg, Kevin; Ray, Jaideep; van Bloemen Waanders, Bart

    2015-02-14

    Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-like method, which incurs a sequence of linear-system solves. Most model-reduction techniques for nonlinear ODEs exploit knowledge of system's spatial behavior to reduce the computational complexity of each linear-system solve. However, the number of linear-system solves for the reduced-order simulation often remains roughly the same as that for the full-order simulation. We propose exploiting knowledge of the model's temporal behavior to (1) forecast the unknown variable of the reduced-order system of nonlinear equationsmore » at future time steps, and (2) use this forecast as an initial guess for the Newton-like solver during the reduced-order-model simulation. To compute the forecast, we propose using the Gappy POD technique. As a result, the goal is to generate an accurate initial guess so that the Newton solver requires many fewer iterations to converge, thereby decreasing the number of linear-system solves in the reduced-order-model simulation.« less

  2. Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting

    SciTech Connect (OSTI)

    Carlberg, Kevin; Ray, Jaideep; van Bloemen Waanders, Bart

    2015-02-14

    Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-like method, which incurs a sequence of linear-system solves. Most model-reduction techniques for nonlinear ODEs exploit knowledge of system's spatial behavior to reduce the computational complexity of each linear-system solve. However, the number of linear-system solves for the reduced-order simulation often remains roughly the same as that for the full-order simulation. We propose exploiting knowledge of the model's temporal behavior to (1) forecast the unknown variable of the reduced-order system of nonlinear equations at future time steps, and (2) use this forecast as an initial guess for the Newton-like solver during the reduced-order-model simulation. To compute the forecast, we propose using the Gappy POD technique. As a result, the goal is to generate an accurate initial guess so that the Newton solver requires many fewer iterations to converge, thereby decreasing the number of linear-system solves in the reduced-order-model simulation.

  3. Fiscal Year 2013 Budget Request Briefing

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

    ... FY12 Phase I 22 Application in review 2-4 awards expected Phase II MagiQ Technologies Downhole High Temperature Seismic Sensor (Year 2) Physical Optics Corporation Fiber Optic High ...

  4. Welcome Year in Review

    National Nuclear Security Administration (NNSA)

    Training Meeting Orlando, Florida-May 23-25, 2006 Sponsored by the U.S. Department of Energy & the U.S. Nuclear Regulatory Commission Welcome & Year In Review Peter Dessaules...

  5. Year 2000 awareness

    SciTech Connect (OSTI)

    Holmes, C.

    1997-11-01

    This report contains viewgraphs on the challenges business face with the year 2000 software problem. Estimates, roadmaps, virtual factory software, current awareness, and world wide web references are given.

  6. Natural Gas Futures Contract 4 (Dollars per Million Btu)

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

    Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 1.906 2.054 1.746 2.270 2.363 2.332 2.418 2000's 4.045 4.103 3.539 5.401 6.534 9.185 8.238 7.811 9.254 4.882 2010's 4.658 4.227 3.109 3.854 4.218 2.792

  7. U.S. natural gas exports to exceed imports for first time in 60 years

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

    U.S. natural gas exports to exceed imports for first time in 60 years The United States is on track during the second half of 2017 to export more natural gas than it imports for the first time since 1957. In its new monthly forecast, the U.S. Energy Information Administration said the United States will become a net exporter after years of steadily increasing its natural gas production and building the terminals necessary to ship super-cooled liquefied natural gas to overseas markets. Just last

  8. Texas--RRC District 4 Onshore Coalbed Methane Proved Reserves...

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

    4 Onshore Coalbed Methane Proved Reserves (Billion Cubic Feet) Texas--RRC District 4 Onshore Coalbed Methane Proved Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 ...

  9. 4Li

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

    Li Ground-State Decay Evaluated Data Measured Ground-State Γcm(T1/2) for 4Li Adopted value: 91 ± 9 ys (2003AU02) Measured Mass Excess for 4Li Adopted value: 25320 ± 210 keV (2003AU02) Measurements 1960BR05: 4Li; measured not abstracted; deduced nuclear properties. 1960BR10: 4Li; measured not abstracted; deduced nuclear properties. 1960BR19: 4Li; measured not abstracted; deduced nuclear properties. 1960RO11: 4Li; measured not abstracted; deduced nuclear properties. 1963WE10: 4Li; measured not

  10. Beamline 1.4.4

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

    Beamline 1.4.4 Print Infrared spectromicroscopy Scientific disciplines: Biology, correlated electron systems, environmental science, geology, chemistry, polymers, soft materials...

  11. EMERGENCY READINESS ASSURANCE PLAN (ERAP) FOR FISCAL YEAR (FY) 2014

    SciTech Connect (OSTI)

    Bush, Shane

    2014-09-01

    This Emergency Readiness Assurance Plan (ERAP) for Fiscal Year (FY) 2014 in accordance with DOE O 151.1C, “Comprehensive Emergency Management System.” The ERAP documents the readiness of the INL Emergency Management Program using emergency response planning and preparedness activities as the basis. It describes emergency response planning and preparedness activities, and where applicable, summarizes and/or provides supporting information in tabular form for easy access to data. The ERAP also provides budget, personnel, and planning forecasts for FY-15. Specifically, the ERAP assures the Department of Energy Idaho Operations Office that stated emergency capabilities at INL are sufficient to implement PLN-114, “INL Emergency Plan/RCRA Contingency Plan.

  12. Coal operators prepare for a prosperous new year

    SciTech Connect (OSTI)

    Fiscor, S.

    2008-01-15

    Results are given of the Coal Age 2008 annual Forecast Survey of 17 coal mining executives which reinforces that 2008 could be a very good year. Coal operators are planning to invest in new equipment, development and new coal mine start-ups, based on a number of demand- and supply-side fundamentals. 71% of those surveyed thought coal production in 2008 would increase from 2007 levels and US exports are expected to climb due to the weak dollar. If the tax credit on synfuels expires on 31 December 2007 production of coal synfuel will likely cease. Asked about expensive planned purchases, companies answers ranged from $80,000 for an underground scoop to $500 m for a new mine installation. However, most producers admit they will not be able to operate at full capacity. 7 figs.

  13. HDF4

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

    table . Using HDF Load the appropriate modulefile and then you can use the HDF C or Fortran wrappers: module load hdf h4cc ... ... h4fc ... ... Documentation For a full...

  14. b)(4

    National Nuclear Security Administration (NNSA)

    (b)(4) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(4) (b)(4) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6) (b)(6)...

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

    SciTech Connect (OSTI)

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

    2011-09-13

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

  16. ch_4

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

    1998, INEEL contracts paid $1.4 million to the State of Idaho in Idaho sales taxes and an additional $0.9 million in Idaho franchise tax. 4.4 Cultural Resources 4.4.1 CULTURAL RESOURCE MANAGEMENT AND CONSULTATION AT INEEL Cultural resources at INEEL include archaeolog- ical and historic resources, such as prehistoric camp sites and historic buildings and trails, as well as the plants, animals, physical locations, and other features of INEEL environment impor- tant to the culture of the

  17. 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

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

    SciTech Connect (OSTI)

    B. Faybishenko

    2006-09-11

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

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

    SciTech Connect (OSTI)

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

    2013-06-15

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

  20. Energy Savings Forecast of Solid-State Lighting in General Illumination Applications

    SciTech Connect (OSTI)

    none,

    2014-08-29

    With declining production costs and increasing technical capabilities, LED adoption has recently gained momentum in general illumination applications. This is a positive development for our energy infrastructure, as LEDs use significantly less electricity per lumen produced than many traditional lighting technologies. The U.S. Department of Energy’s Energy Savings Forecast of Solid-State Lighting in General Illumination Applications examines the expected market penetration and resulting energy savings of light-emitting diode, or LED, lamps and luminaires from today through 2030.

  1. Waste generation forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1995-FY 2002, September 1994 revision

    SciTech Connect (OSTI)

    Not Available

    1994-12-01

    A comprehensive waste-forecasting task was initiated in FY 1991 to provide a consistent, documented estimate of the volumes of waste expected to be generated as a result of U.S. Department of Energy-Oak Ridge Operations (DOE-ORO) Environmental Restoration (ER) OR-1 Project activities. Continual changes in the scope and schedules for remedial action (RA) and decontamination and decommissioning (D&D) activities have required that an integrated data base system be developed that can be easily revised to keep pace with changes and provide appropriate tabular and graphical output. The output can then be analyzed and used to drive planning assumptions for treatment, storage, and disposal (TSD) facilities. The results of this forecasting effort and a description of the data base developed to support it are provided herein. The initial waste-generation forecast results were compiled in November 1991. Since the initial forecast report, the forecast data have been revised annually. This report reflects revisions as of September 1994.

  2. Beamline 1.4.4

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

    4 Print Infrared spectromicroscopy Scientific disciplines: Biology, correlated electron systems, environmental science, geology, chemistry, polymers, soft materials GENERAL...

  3. Table 4

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

    ... 17.2 12.5 14.0 17.4 19.1 14.3 19.7 16.1 17.5 21.3 8.46 Automatic Control... 18.8 9.7 7.4 11.9 17.3 17.5 17.9 22.4 27.3 31.6 8.59 High...

  4. ESnet4:

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

    ESnet4: Networking for the Future of DOE Science William E. Johnston ESnet Department Head ... Laboratory Networking for the Future of Science Office of Science, Science Programs ...

  5. Office of Energy Efficiency and Renewable Energy Fiscal Year...

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

    ... optimization studies for wind systems and operational forecasting tool development to understand and reduce costs associated with integrating variable wind energy into the ...

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

    SciTech Connect (OSTI)

    Edwards, J.D.

    1997-08-01

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

  7. Two Years Later, Greensburg is Officially Green - with NREL's...

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

    Two Years Later, Greensburg is Officially Green - with NREL's Help May 8, 2009 Photo of a ... A tornado on May 4, 2007 destroyed 90 percent of Greensburg, Kan. Two years later, with ...

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

    SciTech Connect (OSTI)

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

    1997-01-07

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

  9. Incorporating Uncertainty of Wind Power Generation Forecast into Power System Operation, Dispatch, and Unit Commitment Procedures

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian; Huang, Zhenyu; Subbarao, Krishnappa

    2011-06-23

    An approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. An assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty - both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures). A new method called the 'flying-brick' technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through EMS integration illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems in control rooms.

  10. Incorporating Wind Generation Forecast Uncertainty into Power System Operation, Dispatch, and Unit Commitment Procedures

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Subbarao, Krishnappa

    2010-10-19

    In this paper, an approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the "flying-brick" technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through integration with an EMS system illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems from other vendors.

  11. Table 4

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

    Night... 16.6 3.4 5.1 3.1 2.9 1.3 0.8 7.89 Automatic Control... 18.2 3.1 6.9 3.4 3.2 1.1 0.5 7.89 High...

  12. Table 4

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

    ... 17.2 14.7 16.1 18.5 19.6 19.7 21.7 7.32 Automatic Control... 18.8 13.3 21.7 20.4 21.7 16.8 14.4 7.21 High...

  13. Table 4

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

    ... 17.2 8.7 15.2 18.5 20.6 17.6 18.9 17.8 8.25 Automatic Control... 18.8 4.4 10.1 17.0 26.2 25.9 28.2 31.2 8.37 High...

  14. Beamline 1.4.4

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

    for 4.2-730 K Scientific disciplines Biology, correlated electron systems, environmental science, geology, chemistry, polymers, soft materials Scientific applications Biological...

  15. Developing an industrial end-use forecast: A case study at the Los Angeles department of water and power

    SciTech Connect (OSTI)

    Mureau, T.H.; Francis, D.M.

    1995-05-01

    The Los Angeles Department of Water and Power (LADWP) uses INFORM 1.0 to forecast industrial sector energy. INFORM 1.0 provides an end-use framework that can be used to forecast electricity, natural gas or other fuels consumption. Included with INFORM 1.0 is a default date set including the input data and equations necessary to solve each model. LADWP has substituted service area specific data for the default data wherever possible. This paper briefly describes the steps LADWP follows in developing those inputs and application in INFORM 1.0.

  16. ,"Projected Year Base","Year","Summer",,,"Eastern Power Grid...

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

    2008 " ,"(Megawatts and Percent)" ,"Projected Year Base","Year","Summer",,,"Eastern Power Grid",,,"Texas Power Grid",,,"Western Power Grid" ,,,"Contiguous...

  17. ,"Projected Year Base","Year","Summer",,,"Eastern Power Grid...

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

    2009 " ,"(Megawatts and Percent)" ,"Projected Year Base","Year","Summer",,,"Eastern Power Grid",,,"Texas Power Grid",,,"Western Power Grid" ,,,"Contiguous...

  18. ch_4

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

    0 4.0 Aff Aff ected ected E E nvir nvir onment onment 4-1 DOE/EIS-0287 4.1 Introduction This chapter describes the environment of the Idaho National Engineering and Environmental Laboratory (INEEL) and surrounding area that could be affected by the alternatives analyzed in this environ- mental impact statement (EIS). One of the alternatives under consideration, the Minimum INEEL Processing Alternative, would involve treatment of INEEL high- level waste (HLW) at the Hanford Site. Appendix C.8

  19. January 4

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

    4 January 4 PDSF users meeting 1/4/11 Attending: Eric, Katie and Jay from NERSC and users Jeff P., Thomas, Art and possibly an an unknown person on the phone (?). Cluster Status/Utilization: Quite full over the break and stable. Only issue was that at one point there were 26k jobs running or pending but that didn't cause any major problems. Outages: None. Upcoming downtimes: Need to do some work on rack 22 - clean up and rearrange some things. This will affect STAR db and will take ~5 hours.

  20. Calendar Year 2016 | Department of Energy

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

    Calendar Year 2016 Calendar Year 2016 August 4, 2016 Inspection Report: OAI-L-16-13 Technetium-99 Incident at Los Alamos National Laboratory July 29, 2016 Assessment Report: OAI-V-16-11 Audit Coverage of Cost Allowability for UT-Battelle LLC During Fiscal Year 2014 Under Department of Energy Contract No. DE-AC05-00OR22725 July 27, 2016 Audit Report: OAI-M-16-14 Battelle's Pacific Northwest National Laboratory Procurement Activities July 14, 2016 Audit Report: DOE-OIG-16-13 Enriched Uranium

  1. 4H

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

    spectrum. 1980SE08: 7Li(-, nt), E at rest; measured tt-coin. 4H deduced possible ... 1985DO19: 6Li(-, 2p), (-, nt), E at rest; measured (particle)(particle)-coin ...

  2. ch_4

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

    47 DOEEIS-0287 Idaho HLW & FD EIS 4.8.2 SUBSURFACE WATER Subsurface water at INEEL occurs in the under- lying Snake River Plain Aquifer and the vadose zone (area of unsaturated ...

  3. Table 4

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

    4. Light Usage by Total Number of Rooms, Percent of U.S. Households, 1993 Total Number of Rooms Housing Unit and Household Characteristics Total 1 or 2 3 to 5 6 to 8 9 or More RSE...

  4. ch_4

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

    58 Affected Environment 4.9.1 PLANT COMMUNITIES AND ASSOCIATIONS INEEL lies within a cool desert ecosystem dom- inated by shrub-steppe vegetation. The area is relatively undisturbed, providing important habi- tat for species native to the region. Vegetation and habitat on INEEL can be grouped into six types: shrub-steppe, juniper woodlands, native grasslands, modified ephemeral playas, lava, and wetland-like areas. Figure 4-16 shows these areas. More than 90 percent of INEEL falls within the

  5. Table 4

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

    ... 16.6 0.5 1.5 1.9 1.8 1.3 2.8 2.8 2.2 1.8 9.27 Automatic Control... 18.2 0.4 0.8 1.3 1.7 1.5 2.5 3.9 3.4 2.6 9.51 High...

  6. Concurrent Transfers Historical Yearly Peak

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

    the graph for current year shows the data for the year-to-date peak. Daily Storage Concurrency Daily Storage Concurrency Daily Storage Concurrency Daily Storage Concurrency Daily...

  7. Planning for Years to Come

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

    Planning for Years to Come Planning for Years to Come LANL's Governing Policy on the Environment August 1, 2013 Water sampling tour for the Association of Experiential Education ...

  8. CHAPTER 4

    National Nuclear Security Administration (NNSA)

    mber 2009 . mber 2009 . December 2009 . "Defense Programs performs a vital mission and is a true national asset. Our job cannot be done unless our core program is adequately supported through fiscal year 2014:  to maintain the stockpile as the President and the nation demand,  to sustain our infrastructure capabilities, especially those addressing plutonium and highly enriched uranium - needed not just for the stockpile but also for a myriad of national needs, and finally  to

  9. Machine Learning Based Multi-Physical-Model Blending for Enhancing Renewable Energy Forecast -- Improvement via Situation Dependent Error Correction

    SciTech Connect (OSTI)

    Lu, Siyuan; Hwang, Youngdeok; Khabibrakhmanov, Ildar; Marianno, Fernando J.; Shao, Xiaoyan; Zhang, Jie; Hodge, Bri-Mathias; Hamann, Hendrik F.

    2015-07-15

    With increasing penetration of solar and wind energy to the total energy supply mix, the pressing need for accurate energy forecasting has become well-recognized. Here we report the development of a machine-learning based model blending approach for statistically combining multiple meteorological models for improving the accuracy of solar/wind power forecast. Importantly, we demonstrate that in addition to parameters to be predicted (such as solar irradiance and power), including additional atmospheric state parameters which collectively define weather situations as machine learning input provides further enhanced accuracy for the blended result. Functional analysis of variance shows that the error of individual model has substantial dependence on the weather situation. The machine-learning approach effectively reduces such situation dependent error thus produces more accurate results compared to conventional multi-model ensemble approaches based on simplistic equally or unequally weighted model averaging. Validation over an extended period of time results show over 30% improvement in solar irradiance/power forecast accuracy compared to forecasts based on the best individual model.

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

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2000-08-31

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

  11. Department of Energy award DE-SC0004164 Climate and National Security: Securing Better Forecasts

    SciTech Connect (OSTI)

    Reno Harnish

    2011-08-16

    The Climate and National Security: Securing Better Forecasts symposium was attended by senior policy makers and distinguished scientists. The juxtaposition of these communities was creative and fruitful. They acknowledged they were speaking past each other. Scientists were urged to tell policy makers about even improbable outcomes while articulating clearly the uncertainties around the outcomes. As one policy maker put it, we are accustomed to making these types of decisions. These points were captured clearly in an article that appeared on the New York Times website and can be found with other conference materials most easily on our website, www.scripps.ucsd.edu/cens/. The symposium, generously supported by the NOAA/JIMO, benefitted the public by promoting scientifically informed decision making and by the transmission of objective information regarding climate change and national security.

  12. Updated Eastern Interconnect Wind Power Output and Forecasts for ERGIS: July 2012

    SciTech Connect (OSTI)

    Pennock, K.

    2012-10-01

    AWS Truepower, LLC (AWST) was retained by the National Renewable Energy Laboratory (NREL) to update wind resource, plant output, and wind power forecasts originally produced by the Eastern Wind Integration and Transmission Study (EWITS). The new data set was to incorporate AWST's updated 200-m wind speed map, additional tall towers that were not included in the original study, and new turbine power curves. Additionally, a primary objective of this new study was to employ new data synthesis techniques developed for the PJM Renewable Integration Study (PRIS) to eliminate diurnal discontinuities resulting from the assimilation of observations into mesoscale model runs. The updated data set covers the same geographic area, 10-minute time resolution, and 2004?2006 study period for the same onshore and offshore (Great Lakes and Atlantic coast) sites as the original EWITS data set.

  13. A comparison of water vapor quantities from model short-range forecasts and ARM observations

    SciTech Connect (OSTI)

    Hnilo, J J

    2006-03-17

    Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the 'Merged-sounding' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output.

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

    SciTech Connect (OSTI)

    Hnilo, J J

    2006-09-22

    For the fourth quarter ARM metric we will make use of new liquid water data that has become available, and called the 'Microbase' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Tropical West Pacific (TWP) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both TWP and NSA. The Microbase data have been averaged to 35 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3hourly data for direct comparison to our model output.

  15. A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations

    SciTech Connect (OSTI)

    Hnilo, J.

    2006-03-17

    Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the “Mergedsounding” value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output.

  16. Forecasting the northern African dust outbreak towards Europe in April 2011: A model intercomparison

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

    Huneeus, N.; Basart, S.; Fiedler, S.; Morcrette, J. -J.; Benedetti, A.; Mulcahy, J.; Terradellas, E.; Garcia-Pando, C. Perez; Pejanovic, G.; Nickovic, S.; et al

    2016-04-21

    In the framework of the World Meteorological Organisation's Sand and Dust Storm Warning Advisory and Assessment System, we evaluated the predictions of five state-of-the-art dust forecast models during an intense Saharan dust outbreak affecting western and northern Europe in April 2011. We assessed the capacity of the models to predict the evolution of the dust cloud with lead times of up to 72 h using observations of aerosol optical depth (AOD) from the AErosol RObotic NETwork (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) and dust surface concentrations from a ground-based measurement network. In addition, the predicted vertical dust distributionmore » was evaluated with vertical extinction profiles from the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP). To assess the diversity in forecast capability among the models, the analysis was extended to wind field (both surface and profile), synoptic conditions, emissions and deposition fluxes. Models predict the onset and evolution of the AOD for all analysed lead times. On average, differences among the models are larger than differences among lead times for each individual model. In spite of large differences in emission and deposition, the models present comparable skill for AOD. In general, models are better in predicting AOD than near-surface dust concentration over the Iberian Peninsula. Models tend to underestimate the long-range transport towards northern Europe. In this paper, our analysis suggests that this is partly due to difficulties in simulating the vertical distribution dust and horizontal wind. Differences in the size distribution and wet scavenging efficiency may also account for model diversity in long-range transport.« less

  17. Table 4

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

    ght... 16.6 0.7 3.3 5.1 2.6 1.7 1.6 1.7 8.87 Automatic Control... 18.2 0.3 2.2 4.7 3.3 2.5 2.3 2.9 8.90 High...

  18. Table 4

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

    10.8 0.3 0.8 1.6 2.0 2.2 4.0 11.94 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  19. Table 4

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

    0.6 0.8 0.6 1.4 2.3 1.9 2.5 12.69 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  20. Aggregate Transfers Historical Yearly Peak

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

    Transfers Historical Yearly Peak Aggregate Transfers Historical Yearly Peak These plots show the yearly peak days from 2000 to the present. BE CAREFUL because the graphs are autoscaling - check the scales on each axis before you compare graphs. Note that the graph for current year shows the data for the year-to-date peak. Daily Aggregate Bandwidth Daily Aggregate Bandwidth Daily Aggregate Bandwidth Daily Aggregate Bandwidth Daily Aggregate Bandwidth Daily Aggregate Bandwidth Daily Aggregate

  1. Concurrent Transfers Historical Yearly Peak

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

    Transfers Historical Yearly Peak Concurrent Transfers Historical Yearly Peak These plots show the yearly peak days from 2000 to present. BE CAREFUL because the graphs are autoscaling - check the scales on each axis before you compare graphs. Note that the graph for current year shows the data for the year-to-date peak. Daily Storage Concurrency Daily Storage Concurrency Daily Storage Concurrency Daily Storage Concurrency Daily Storage Concurrency Daily Storage Concurrency Daily Storage

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

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

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

    2015-07-14

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

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

    SciTech Connect (OSTI)

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

    2015-07-14

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

  4. 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

  5. 60 Years of Computing | Department of Energy

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

    60 Years of Computing 60 Years of Computing

  6. Characteristics RSE Column Factor: All Model Years Model Year

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

    ... 19.1 1.4 2.0 2.2 5.0 4.4 2.1 0.6 Q 0.9 14.3 Below Poverty Line 100 Percent ... 12.4 Q Q 0.6 2.1 2.1 2.4 1.7...

  7. Joint Analysis of Galaxy-Galaxy Lensing and Galaxy Clustering: Methodology and Forecasts for DES

    SciTech Connect (OSTI)

    Park, Y.

    2015-07-19

    The joint analysis of galaxy-galaxy lensing and galaxy clustering is a promising method for inferring the growth function of large scale structure. Our analysis will be carried out on data from the Dark Energy Survey (DES), with its measurements of both the distribution of galaxies and the tangential shears of background galaxies induced by these foreground lenses. We develop a practical approach to modeling the assumptions and systematic effects affecting small scale lensing, which provides halo masses, and large scale galaxy clustering. Introducing parameters that characterize the halo occupation distribution (HOD), photometric redshift uncertainties, and shear measurement errors, we study how external priors on different subsets of these parameters affect our growth constraints. Degeneracies within the HOD model, as well as between the HOD and the growth function, are identified as the dominant source of complication, with other systematic effects sub-dominant. The impact of HOD parameters and their degeneracies necessitate the detailed joint modeling of the galaxy sample that we employ. Finally, we conclude that DES data will provide powerful constraints on the evolution of structure growth in the universe, conservatively/optimistically constraining the growth function to 7.9%/4.8% with its first-year data that covered over 1000 square degrees, and to 3.9%/2.3% with its full five-year data that will survey 5000 square degrees, including both statistical and systematic uncertainties.

  8. Federal Real Property Council Guidance

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

    ... best practices 3. Employ life-cycle cost-benefit analysis 4. Promote full and appropriate ... development of a 5-year capital forecasting and investment outlook, (4) ...

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

    SciTech Connect (OSTI)

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

    2010-09-01

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

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

    SciTech Connect (OSTI)

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

    2010-01-01

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

  11. ch_4

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

    40 Affected Environment playas 15 to 20 miles northeast of INTEC, where the water infiltrates. The water in Birch Creek and the Little Lost River is diverted in summer months for irriga- tion prior to reaching INEEL. During periods of unusually high precipitation or rapid snow melt, water from Birch Creek and the Little Lost River may enter INEEL from the northwest and infil- trate the ground, recharging the underlying aquifer. 4.8.1.2 Local Drainage INTEC is located on an alluvial plain

  12. 2013 Director's New Year Address

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

    has in store for the ALS. An immediate answer is - a celebration - as the ALS marks its 20th year of operation. We'll spend some time this year looking back at what we've...

  13. WIPP_Marks_12_Years

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

    Marks 12 Years of Operations CARLSBAD, N.M., March 28, 2011 - On Saturday, March 26, 2011, ... It has now been 12 years since WIPP received its first shipment of transuranic (TRU) ...

  14. Beamline 1.4.4

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

    4 Print Infrared spectromicroscopy Scientific disciplines: Biology, correlated electron systems, environmental science, geology, chemistry, polymers, soft materials GENERAL BEAMLINE INFORMATION Operational Yes Source characteristics Bend magnet Energy range 0.05-1.5 eV Frequency range 800 - 10,000 cm-1 Interferometer resolution up to 0.125 cm-1 Endstations Thermo Nicolet Nexus 870 FTIR, Continuum XL IR microscope (N2 purged) Characteristics Computerized sample stage, 0.1-micron resolution;

  15. Calendar Year 2014 | Department of Energy

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

    4 Calendar Year 2014 December 17, 2014 Audit Report: OAS-FS-15-05 Federal Energy Regulatory Commission's Fiscal Year 2014 Financial Statement Audit December 16, 2014 Inspection Report: DOE/IG-0929 Allegations Regarding the Consolidation of Central Alarm Stations at the Oak Ridge Reservation December 16, 2014 Audit Report: DOE/IG-0930 Follow-up on the Los Alamos National Laboratory Hydrodynamic Test Program December 15, 2014 Audit Report: OAS-FS-15-04 Management Letter on the Western Federal

  16. Transfer Activity Historical Yearly Peak

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

    Activity Historical Yearly Peak Transfer Activity Historical Yearly Peak The plots below show the yearly peak days from 2000 to the present. BE CAREFUL because the graphs are autoscaling - check the scales on each axis before you compare graphs. Note that the graph for the current year shows the data for the year-to-date peak. Transfers Started/In Progress Transfers Started/In Progress Transfers Started/In Progress Transfers Started/In Progress Transfers Started/In Progress Transfers Started/In

  17. YEAR

    National Nuclear Security Administration (NNSA)

    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 DIVERSITY TOTAL WORKFORCE GENDER Savannah ...

  18. YEAR

    National Nuclear Security Administration (NNSA)

    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 Field ...

  19. 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 ...

  20. YEAR

    National Nuclear Security Administration (NNSA)

    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 DIVERSITY TOTAL WORKFORCE GENDER Los ...