Sample records for year forecast 2

  1. 1992 five year battery forecast

    SciTech Connect (OSTI)

    Amistadi, D.

    1992-12-01T23:59:59.000Z

    Five-year trends for automotive and industrial batteries are projected. Topic covered include: SLI shipments; lead consumption; automotive batteries (5-year annual growth rates); industrial batteries (standby power and motive power); estimated average battery life by area/country for 1989; US motor vehicle registrations; replacement battery shipments; potential lead consumption in electric vehicles; BCI recycling rates for lead-acid batteries; US average car/light truck battery life; channels of distribution; replacement battery inventory end July; 2nd US battery shipment forecast.

  2. 1995 shipment review & five year forecast

    SciTech Connect (OSTI)

    Fetherolf, D.J. Jr. [East Penn Manufacturing Co., Inc., Lyon Station, PA (United States)

    1996-01-01T23:59:59.000Z

    This report describes the 1995 battery shipment review and five year forecast for the battery market. Historical data is discussed.

  3. 1994 battery shipment review and five-year forecast report

    SciTech Connect (OSTI)

    Fetherolf, D. [East Penn Manufacturing Co., Lyon Station, PA (United States)

    1995-12-31T23:59:59.000Z

    This paper presents a 1994 battery shipment review and five year forecast report. Data is presented on replacement battery shipments, battery shipments, car and truck production, truck sales, original equipment, shipments for passenger cars and light commercial vehicles, and ten year battery service life trend.

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

    SciTech Connect (OSTI)

    NONE

    1996-02-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Das, S.

    1991-12-01T23:59:59.000Z

    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.

  6. J2.6 A SPATIAL DATA MINING APPROACH FOR VERIFICATION AND UNDERSTANDING OF ENSEMBLE PRECIPITATION FORECASTING

    E-Print Network [OSTI]

    Gruenwald, Le

    FORECASTING Xuechao Yu* 1,2 and Ming Xue 2,3 1 NOAA/NWS/WDTB Cooperative Institute for Mesoscale is placed on meso- scale ensemble forecasting in recent years [e.g., the Storm and Mesoscale Ensemble complicated for mesoscale quantitative precipitation forecast (QPF), since QPF is a discontinuous field. Em

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

    SciTech Connect (OSTI)

    Thomas, L.C.

    1994-10-01T23:59:59.000Z

    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.

  8. FAA (federal Aviation Administration) aviation forecasts - fiscal years 1983-1994

    SciTech Connect (OSTI)

    Not Available

    1983-02-01T23:59:59.000Z

    This report contains the Fiscal Years 1983-1994 Federal Aviation Administration (FAA) forecasts of aviation activity at FAA facilities. These include airports with FAA control towers, air route traffic control centers, and flight service stations. Detailed forecasts were made for the four major users of the national aviation system: air carriers, air taxi/commuters, general aviation and the military. The forecasts have been prepared to meet the budget and planning needs of the constituent units of the FAA and to provide information that can be used by state and local authorities, by the aviation industry and the general public. The overall outlook for the forecast period is for moderate economic growth, relatively stable real fuel prices, and decreasing inflation. Based upon these assumptions, aviation activity is forecast to increase by Fiscal Year 1994 by 97 percent at towered airports, 50 percent at air route traffic control centers, and 54 percent in flight services performed. Hours flown by general aviation is forecast to increase 56 percent and helicopter hours flown 80 percent. Scheduled domestic revenue passenger miles (RPM's) are forecast to increase 81 percent, with scheduled international RPM's forecast to increase by 80 percent and commuter RPM's forecast to increase by 220 percent.

  9. What constrains spread growth in forecasts ini2alized from

    E-Print Network [OSTI]

    Hamill, Tom

    1 What constrains spread growth in forecasts ini2alized from ensemble Kalman filters? Tom from manner in which ini2al condi2ons are generated, some due to the model (e.g., stochas2c physics as error; part of spread growth from manner in which ini2al condi2ons are generated, some due

  10. Thirty-year solid waste generation forecast for facilities at SRS

    SciTech Connect (OSTI)

    Not Available

    1994-07-01T23:59:59.000Z

    The information supplied by this 30-year solid waste forecast has been compiled as a source document to the Waste Management Environmental Impact Statement (WMEIS). The WMEIS will help to select a sitewide strategic approach to managing present and future Savannah River Site (SRS) waste generated from ongoing operations, environmental restoration (ER) activities, transition from nuclear production to other missions, and decontamination and decommissioning (D&D) programs. The EIS will support project-level decisions on the operation of specific treatment, storage, and disposal facilities within the near term (10 years or less). In addition, the EIS will provide a baseline for analysis of future waste management activities and a basis for the evaluation of the specific waste management alternatives. This 30-year solid waste forecast will be used as the initial basis for the EIS decision-making process. The Site generates and manages many types and categories of waste. With a few exceptions, waste types are divided into two broad groups-high-level waste and solid waste. High-level waste consists primarily of liquid radioactive waste, which is addressed in a separate forecast and is not discussed further in this document. The waste types discussed in this solid waste forecast are sanitary waste, hazardous waste, low-level mixed waste, low-level radioactive waste, and transuranic waste. As activities at SRS change from primarily production to primarily decontamination and decommissioning and environmental restoration, the volume of each waste s being managed will change significantly. This report acknowledges the changes in Site Missions when developing the 30-year solid waste forecast.

  11. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 2 AUGUST 15, 2013

    E-Print Network [OSTI]

    Gray, William

    that we are trying to predict with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index This is the fifth year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting for ACE using three categories as defined in Table 1. Table 1: ACE forecast definition. Parameter

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

    SciTech Connect (OSTI)

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

    1991-09-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    1991-09-01T23:59:59.000Z

    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.

  14. Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results

    E-Print Network [OSTI]

    Koomey, Jonathan G.

    2010-01-01T23:59:59.000Z

    End-Use Forecasting with EPRI-REEPS 2.1. Lawrence BerkeleyEnd-Use Forecasting with EPRI-REEPS 2.1. Lawrence BerkeleyPower Research Institute. EPRI Research Project Meier, Alan

  15. YEAR 2 BIOMASS UTILIZATION

    SciTech Connect (OSTI)

    Christopher J. Zygarlicke

    2004-11-01T23:59:59.000Z

    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 cofiring coal with waste paper, sunflower hulls, and wood waste showed a broad spectrum of chemical and physical characteristics, according to American Society for Testing and Materials (ASTM) C618 procedures. Higher-than-normal levels of magnesium, sodium, and potassium oxide were observed for the biomass-coal fly ash, which may impact utilization in cement replacement in concrete under ASTM requirements. Other niche markets for biomass-derived fly ash were explored. Research was conducted to develop/optimize a catalytic partial oxidation-based concept for a simple, low-cost fuel processor (reformer). Work progressed to evaluate the effects of temperature and denaturant on ethanol catalytic partial oxidation. A catalyst was isolated that had a yield of 24 mole percent, with catalyst coking limited to less than 15% over a period of 2 hours. In biodiesel research, conversion of vegetable oils to biodiesel using an alternative alkaline catalyst was demonstrated without the need for subsequent water washing. In work related to biorefinery technologies, a continuous-flow reactor was used to react ethanol with lactic acid prepared from an ammonium lactate concentrate produced in fermentations conducted at the EERC. Good yields of ester were obtained even though the concentration of lactic acid in the feed was low with respect to the amount of water present. Esterification gave lower yields of ester, owing to the lowered lactic acid content of the feed. All lactic acid fermentation from amylose hydrolysate test trials was completed. Management activities included a decision to extend several projects to December 31, 2003, because of delays in receiving biomass feedstocks for testing and acquisition of commercial matching funds. In strategic studies, methods for producing acetate esters for high-value fibers, fuel additives, solvents, and chemical intermediates were discussed with several commercial entities. Commercial industries have an interest in efficient biomass gasification designs but are waiting for economic incentives. Utility, biorefinery, pulp and paper, or o

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

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2003-12-01T23:59:59.000Z

    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.

  17. Weather Research and Forecasting Model 2.2 Documentation

    E-Print Network [OSTI]

    Sadjadi, S. Masoud

    : Javier Munoz, Diego Lopez, and David Villegas Undergraduate REU Students: Javier Figueroa, Xabriel J International University (FIU) 11200 SW 8th St., Miami, Florida 33199, USA #12;2 Contents Project Motivation

  18. III.C. 2. Plastics and Competing Materials by 1985: A Delphi Forecasting Study

    E-Print Network [OSTI]

    Bieber, Michael

    189 III.C. 2. Plastics and Competing Materials by 1985: A Delphi Forecasting Study SELWYN ENZER The application of Delphi to the identification and assessment of possible developments in plastics and competing. The ability to tailor-make plastics for various applications, enhanced by growth in understanding of organic

  19. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

    2.1.2 European Solar Radiation Atlas (ESRA)2.4 Evaluation of Solar Forecasting . . . . . . . . .2.4.1 Solar Variability . . . . . . . . . . . . .

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

    SciTech Connect (OSTI)

    Templeton, K.J.

    1996-05-23T23:59:59.000Z

    For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the physical waste forms, hazardous waste constituents, and radionuclides of the waste expected to be shipped to the CWC from 1996 through the remaining life cycle of the Hanford Site (assumed to extend to 2070). In previous years, forecast data has been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to two previous reports: the more detailed report on waste volumes, WHC-EP-0900, FY1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary and the report on expected containers, WHC-EP-0903, FY1996 Solid Waste Integrated Life-Cycle Forecast Container Summary. All three documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on two main characteristics: the physical waste forms and hazardous waste constituents of low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major generators for each waste category and waste characteristic are also discussed. The characteristics of low-level waste (LLW) are described in Appendix A. In addition, information on radionuclides present in the waste is provided in Appendix B. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste is expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters. The range is primarily due to uncertainties associated with the Tank Waste Remediation System (TWRS) program, including uncertainties regarding retrieval of long-length equipment, scheduling, and tank retrieval technologies.

  1. CSUF Economic Outlook and Forecasts Mid-Year Update -April 2012

    E-Print Network [OSTI]

    de Lijser, Peter

    . Second, oil prices have risen steadily during this year, posing a significant risk to the world economy at a moderate pace -- a notch below the U.S. long-run potential growth and well below the historical rates in the first half by higher energy prices and a "soft-landing" of emerging market economies. Developments

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

    SciTech Connect (OSTI)

    Valero, O.J.

    1996-04-23T23:59:59.000Z

    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.

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

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilA Approved:AdministrationAnalysisDarby/%2AO 474.2Y-12NevadaPROCEEDINGS, R e s

  4. Page 1 of 2 2005-2006 MLOG Thesis Proposal 10/2/2005 Working Title Improved New Product Forecasting through Visualization of Spatial Diffusion

    E-Print Network [OSTI]

    Brock, David

    Page 1 of 2 2005-2006 MLOG Thesis Proposal 10/2/2005 Working Title Improved New Product Forecasting. Schuster, Stuart J. Allen, and David L. Brock Company Contact Several companies are interested in this area to implement an operational system for improving new product forecasting in practice. Is · Innovative thinking

  5. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

    electricity demand forecast means that the region's electricity needs would grow by 5,343 average megawattsDemand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required in electricity demand is, of course, crucial to determining the need for new electricity resources and helping

  6. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    Energy Commission's final forecasts for 2012­2022 electricity consumption, peak, and natural gas demand Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand

  7. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    Energy Commission staff's revised forecasts for 2012­2022 electricity consumption, peak, and natural Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility

  8. AN APPLICATION OF URBANSIM TO THE AUSTIN, TEXAS REGION: INTEGRATED-MODEL FORECASTS FOR THE YEAR 2030

    E-Print Network [OSTI]

    Kockelman, Kara M.

    , as well as energy consumption and greenhouse gas emissions. This work describes the modeling of year-2030 policies significantly impact the region's future land use patterns, traffic conditions, greenhouse gas (emitting over 6 billion metric tons of CO2-equivalents annually, and accounting for 22.2% of the world

  9. Technology Forecasting Scenario Development

    E-Print Network [OSTI]

    Technology Forecasting and Scenario Development Newsletter No. 2 October 1998 Systems Analysis was initiated on the establishment of a new research programme entitled Technology Forecasting and Scenario and commercial applica- tion of new technology. An international Scientific Advisory Panel has been set up

  10. Rainfall-River Forecasting

    E-Print Network [OSTI]

    US Army Corps of Engineers

    ;2Rainfall-River Forecasting Joint Summit II NOAA Integrated Water Forecasting Program · Minimize losses due management and enhance America's coastal assets · Expand information for managing America's Water Resources, Precipitation and Water Quality Observations · USACE Reservoir Operation Information, Streamflow, Snowpack

  11. Consensus Coal Production Forecast for

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    Consensus Coal Production Forecast for West Virginia 2009-2030 Prepared for the West Virginia Summary 1 Recent Developments 2 Consensus Coal Production Forecast for West Virginia 10 Risks References 27 #12;W.Va. Consensus Coal Forecast Update 2009 iii List of Tables 1. W.Va. Coal Production

  12. Forecasting of Solar Radiation Detlev Heinemann, Elke Lorenz, Marco Girodo

    E-Print Network [OSTI]

    Heinemann, Detlev

    Forecasting of Solar Radiation Detlev Heinemann, Elke Lorenz, Marco Girodo Oldenburg University have been presented more than twenty years ago (Jensenius, 1981), when daily solar radiation forecasts

  13. 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. [and others

    1995-12-01T23:59:59.000Z

    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.

  14. 9A.2 FORECAST CHALLENGES AT THE NWS STORM PREDICTION CENTER RELATING TO THE FREQUENCY OF FAVORABLE SEVERE STORM ENVIRONMENTS

    E-Print Network [OSTI]

    to the performance of convective watches issued by the NOAA Storm Prediction Center (SPC layer bulk wind shear, are linked to SPC convective watches and verification metrics forecast performance. 2. SPC CONVECTIVE WATCHES A convective watch is issued by the SPC

  15. 13.2 A REPORT AND FEATURE-BASED VERIFICATION STUDY OF THE CAPS 2008 STORM-SCALE ENSEMBLE FORECASTS FOR SEVERE CONVECTIVE WEATHER

    E-Print Network [OSTI]

    of computing power, innovative numerical systems, and assimilation of observations at high spatial and temporal system as a means by which model error and uncertainty can be quantified in the forecast. Employing13.2 A REPORT AND FEATURE-BASED VERIFICATION STUDY OF THE CAPS 2008 STORM-SCALE ENSEMBLE FORECASTS

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  19. Postdoctoral Researcher, Materials Chemistry (2 year contract)

    E-Print Network [OSTI]

    Humphrys, Mark

    Postdoctoral Researcher, Materials Chemistry (2 year contract) Adaptive Sensors Group Dublin City Foundation Ireland through the CLARITY CSET (www.clarity- centre.org), supplemented by significant project partners. The group's research strategy in materials chemistry research is to closely align activity

  20. Benchmarking of different approaches to forecast solar irradiance Elke Lorenz1, Wolfgang Traunmller2, Gerald Steinmaurer2, Christian Kurz3,

    E-Print Network [OSTI]

    Heinemann, Detlev

    Benchmarking of different approaches to forecast solar irradiance Elke Lorenz1, Wolfgang and operation strategies. Due to the strong increase of solar power generation the prediction of solar yields and companies have been developing different methods to forecast irradiance as a basis for respective power

  1. Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast Role of the Economic Forecast..................................................................................................................................... 2 Economic Growth Assumptions

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    National Nuclear Security Administration (NNSA)

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  4. Accountability report. Fiscal Year 1996, Volume 2

    SciTech Connect (OSTI)

    NONE

    1997-05-01T23:59:59.000Z

    This report consolidates several performance-related reports into a single financial management report. Information in this report includes information previously reported in the following documents: (1) US Nuclear Regulatory Commission`s (NRC`s) annual financial statement, (2) NRC Chairman`s annual report to the President and the Congress, and (3) NRC Chairman`s semiannual report to Congress on management decisions and final actions on Office of Inspector General audit recommendations. This report also contains performance measures. The report is organized into the following subtopics: information about the US NRC, program performance, management accountability, and the audited financial statement for Fiscal Year 1996. 19 figs., 4 tabs.

  5. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand The California Energy Demand 2014 ­ 2024 Revised Forecast, Volume 2: Electricity Demand by Utility Planning Area Energy Policy Report. The forecast includes three full scenarios: a high energy demand case, a low

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

    SciTech Connect (OSTI)

    McNamara, Laura A.

    2010-08-01T23:59:59.000Z

    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.

  8. 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...

  9. Web 2.0, Cloud Computing, and Earthquake Forecasting Geoffrey Fox1,2

    E-Print Network [OSTI]

    ) introduces several important parallel programming models relevant to data-mining. Web 2.0 provides's EC2 and S3 online services, the Google App Engine, and Microsoft's SkyDrive) outsources basic technologies such as VMWare, Xen, and OpenVZ. Programming models for clouds such as MapReduce-based Hadoop

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

    SciTech Connect (OSTI)

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

    1994-05-01T23:59:59.000Z

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

  11. YEAR

    National Nuclear Security Administration (NNSA)

    8 Females 25 PAY PLAN YEAR 2014 SES 1 EJEK 3 EN 05 1 EN 04 25 EN 03 1 NN (Engineering) 25 NQ (ProfTechAdmin) 25 NU (TechAdmin Support) 2 YEAR 2014 American Indian Alaska Native...

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

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2005-08-17T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    1991-01-01T23:59:59.000Z

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

  14. Adams, JM (Dr) TUTORIAL (YEAR 2) -UG

    E-Print Network [OSTI]

    Stevenson, Paul

    (YEA JMA 48 AZ 04 TUTX-PH00-GM1 Sem1: 01-06,08-14 SGT-Grp A1 TUTORIAL (YEAR 3) - UG SP, AL, JLK, PJM BB 03 Sem1: 09,11,13 UCAS JSA, JA, DB, WNC, AD, OH, JLK, PJM, BNM, PHR, RPS, PDS, JAT, PMW, AL, SP LTL EXAMPHY1022mm Sem1: 07, 15 Test TUTORIAL (YEAR 3) SP, AL, JLK, PJM, BNM, JM Room to be advised

  15. architecture 2-year master of architecture option deadlinesmaster of architecture 3-year master of architecture option

    E-Print Network [OSTI]

    Papalambros, Panos

    master of architecture (M.Arch.) #12;2-year master of architecture option deadlinesmaster of architecture 3-year master of architecture option Taubman College's 2-year master of architecture option is for applicants who hold a bachelor of science degree in architecture or its equivalent. This 60 credit

  16. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

    and forecasting of solar radiation data: a review,”forecasting of solar- radiation data,” Solar Energy, vol.sequences of global solar radiation data for isolated sites:

  17. Geothermal wells: a forecast of drilling activity

    SciTech Connect (OSTI)

    Brown, G.L.; Mansure, A.J.; Miewald, J.N.

    1981-07-01T23:59:59.000Z

    Numbers and problems for geothermal wells expected to be drilled in the United States between 1981 and 2000 AD are forecasted. The 3800 wells forecasted for major electric power projects (totaling 6 GWe of capacity) are categorized by type (production, etc.), and by location (The Geysers, etc.). 6000 wells are forecasted for direct heat projects (totaling 0.02 Quads per year). Equations are developed for forecasting the number of wells, and data is presented. Drilling and completion problems in The Geysers, The Imperial Valley, Roosevelt Hot Springs, the Valles Caldera, northern Nevada, Klamath Falls, Reno, Alaska, and Pagosa Springs are discussed. Likely areas for near term direct heat projects are identified.

  18. 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...

  19. 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

    SciTech Connect (OSTI)

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

    2014-04-30T23:59:59.000Z

    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.

  20. Year in Review Letter from the President 2

    E-Print Network [OSTI]

    Year in Review 2010 #12;#12;Contents Letter from the President 2 Open for Business 4 Community one filled with success and promise for Old Dominion University. As you'll see in this Year in Review

  1. Solid low-level waste forecasting guide

    SciTech Connect (OSTI)

    Templeton, K.J.; Dirks, L.L.

    1995-03-01T23:59:59.000Z

    Guidance for forecasting solid low-level waste (LLW) on a site-wide basis is described in this document. Forecasting is defined as an approach for collecting information about future waste receipts. The forecasting approach discussed in this document is based solely on hanford`s experience within the last six years. Hanford`s forecasting technique is not a statistical forecast based upon past receipts. Due to waste generator mission changes, startup of new facilities, and waste generator uncertainties, statistical methods have proven to be inadequate for the site. It is recommended that an approach similar to Hanford`s annual forecasting strategy be implemented at each US Department of Energy (DOE) installation to ensure that forecast data are collected in a consistent manner across the DOE complex. Hanford`s forecasting strategy consists of a forecast cycle that can take 12 to 30 months to complete. The duration of the cycle depends on the number of LLW generators and staff experience; however, the duration has been reduced with each new cycle. Several uncertainties are associated with collecting data about future waste receipts. Volume, shipping schedule, and characterization data are often reported as estimates with some level of uncertainty. At Hanford, several methods have been implemented to capture the level of uncertainty. Collection of a maximum and minimum volume range has been implemented as well as questionnaires to assess the relative certainty in the requested data.

  2. A Feasibility Study for Probabilistic Convection Initiation Forecasts Based on Explicit Numerical Guidance2

    E-Print Network [OSTI]

    Lakshmanan, Valliappa

    , Steven J. Weiss2 , Fanyou Kong4,5 , Ming Xue4,5 , Ryan A. Sobash1,4 , Andrew R. Dean2 , Israel L. Jirak2 ,6 and Christopher J. Melick2,3 8 1 NOAA/National Severe Storms Laboratory, Norman, OK10 2 NOAA/Storm Prediction Center, Norman, OK 3 Cooperative Institute for Mesoscale Meteorological Studies, Norman, OK12 4

  3. Online Forecast Combination for Dependent Heterogeneous Data

    E-Print Network [OSTI]

    Sancetta, Alessio

    the single individual forecasts. Several studies have shown that combining forecasts can be a useful hedge against structural breaks, and forecast combinations are often more stable than single forecasts (e.g. Hendry and Clements, 2004, Stock and Watson, 2004... in expectations. Hence, we have the following. Corollary 4 Suppose maxt?T kl (Yt, hwt,Xti)kr ? A taking expectation on the left hand side, adding 2A ? T and setting ? = 0 in mT (?), i.e. TX t=1 E [lt (wt)? lt (ut...

  4. California's Electricity Supply and Demand Balance Over the Next Five Years

    E-Print Network [OSTI]

    and Northwest over the past two years by about 8,000 megawatts. Natural gas prices have declined from the high the resources of the system. The Commission's 2003 Baseline Demand forecast assumes the following assumptions September October 1 CEC 2003 Baseline Demand Forecast (1-in-2 Weather)1, 2 3

  5. 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...

  6. YEAR

    National Nuclear Security Administration (NNSA)

    1 YEAR 2014 Males 48 Females 33 PAY PLAN YEAR 2014 SES 1 EJEK 8 EN 04 10 EN 03 1 NN (Engineering) 27 NQ (ProfTechAdmin) 29 NU (TechAdmin Support) 5 YEAR 2014 American Indian...

  7. 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 (ProfTechAdmin) 9 NU (TechAdmin Support) 1 YEAR 2014 American Indian Alaska...

  8. YEAR

    National Nuclear Security Administration (NNSA)

    5 YEAR 2014 Males 61 Females 24 PAY PLAN YEAR 2014 SES 1 EJEK 8 EN 04 22 NN (Engineering) 23 NQ (ProfTechAdmin) 28 NU (TechAdmin Support) 3 YEAR 2014 American Indian Alaska...

  9. Simulations of Arctic Mixed-Phase Clouds in Forecasts with CAM3 and AM2 for M-PACE

    SciTech Connect (OSTI)

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

    2008-02-29T23:59:59.000Z

    Simulations of mixed-phase clouds in short-range forecasts with the National Center for Atmospheric Research Community Atmosphere Model version 3 (CAM3) and the Geophysical Fluid Dynamics Laboratory (GFDL) climate model (AM2) for the Mixed-Phase Arctic Cloud Experiment (M-PACE) are performed under the DOE CCPP-ARM Parameterization Testbed (CAPT), which initializes the climate models with analysis data produced from numerical weather prediction (NWP) centers. It is shown that CAM3 significantly underestimates the observed boundary layer mixed-phase clouds and cannot realistically simulate the variations with temperature and cloud height of liquid water fraction in the total cloud condensate based an oversimplified cloud microphysical scheme. In contrast, AM2 reasonably reproduces the observed boundary layer clouds while its clouds contain much less cloud condensate than CAM3 and the observations. Both models underestimate the observed cloud top and base for the boundary layer clouds. The simulation of the boundary layer mixed-phase clouds and their microphysical properties is considerably improved in CAM3 when a new physically based cloud microphysical scheme is used. The new scheme also leads to an improved simulation of the surface and top of the atmosphere longwave radiative fluxes in CAM3. It is shown that the Bergeron-Findeisen process, i.e., the ice crystal growth by vapor deposition at the expense of coexisting liquid water, is important for the models to correctly simulate the characteristics of the observed microphysical properties in mixed-phase clouds. Sensitivity tests show that these results are not sensitive to the analysis data used for model initializations. Increasing model horizontal resolution helps capture the subgrid-scale features in Arctic frontal clouds but does not help improve the simulation of the single-layer boundary layer clouds. Ice crystal number density has large impact on the model simulated mixed-phase clouds and their microphysical properties and needs to be accurately represented in climate models.

  10. Table of Contents Page 2National High Magnetic Field Laboratory and Its Forecasted Impact on the Florida Economy

    E-Print Network [OSTI]

    Weston, Ken

    Impact on the Florida Economy History and Evaluation of the Economic Impact of the Magnet Lab Forecasted Impact on the Florida Economy The National Science Foundation (NSF) awarded the National High generated by Magnet Lab activities across the broader statewide economy. Since 1990, the Magnet Lab has

  11. Lost : 2,938 miles and 42 years away

    E-Print Network [OSTI]

    Oring, Sheryl

    2011-01-01T23:59:59.000Z

    and Port-au-Prince, Haiti. 42 years April 7, 1968 to Junes devastating earthquake in Haiti. While San Diego is 2,938that would deliver it to Haiti. At first, this was not meant

  12. YEAR

    National Nuclear Security Administration (NNSA)

    3 YEAR 2014 Males 59 Females 24 PAY PLAN YEAR 2014 SES 1 EJEK 4 EN 05 3 EN 04 22 EN 03 8 NN (Engineering) 15 NQ (ProfTechAdmin) 27 NU (TechAdmin Support) 3 YEAR 2014 American...

  13. 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...

  14. 1993 Solid Waste Reference Forecast Summary

    SciTech Connect (OSTI)

    Valero, O.J.; Blackburn, C.L. [Westinghouse Hanford Co., Richland, WA (United States); Kaae, P.S.; Armacost, L.L.; Garrett, S.M.K. [Pacific Northwest Lab., Richland, WA (United States)

    1993-08-01T23:59:59.000Z

    This report, which updates WHC-EP-0567, 1992 Solid Waste Reference Forecast Summary, (WHC 1992) forecasts the volumes of solid wastes to be generated or received at the US Department of Energy Hanford Site during the 30-year period from FY 1993 through FY 2022. The data used in this document were collected from Westinghouse Hanford Company forecasts as well as from surveys of waste generators at other US Department of Energy sites who are now shipping or plan to ship solid wastes to the Hanford Site for disposal. These wastes include low-level and low-level mixed waste, transuranic and transuranic mixed waste, and nonradioactive hazardous waste.

  15. The Valley Fever Corridor Year 2 Fundraising Status

    E-Print Network [OSTI]

    Arizona, University of

    Marianne Stephens Ray Thurston Valley of the Sun Boston Terrier Club Mark Whitaker Nickel $500The Valley Fever Corridor Year 2 Fundraising Status Goal = $85,000 Updated: 2/15/2011 *The Valley Fever Clinic Titanium $5,000 or more: Anonymous Shirley and Ken Cole Heller Foundation

  16. ASSESSING THE QUALITY AND ECONOMIC VALUE OF WEATHER AND CLIMATE FORECASTS

    E-Print Network [OSTI]

    Katz, Richard

    INFORMATION SYSTEM · Forecast -- Conditional probability distribution for event Z = z indicates forecast tornado #12;(1.2) FRAMEWORK · Joint Distribution of Observations & Forecasts Observed Weather = Forecast probability p (e.g., induced by Z) · Reliability Diagram Observed weather: = 1 (Adverse weather occurs) = 0

  17. Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price.................................................................................................................................. 27 INTRODUCTION The Council prepares and periodically updates a 20-year forecast of wholesale to forecast wholesale power prices. AURORAxmp® provides the ability to inco

  18. Price forecasting for U.S. cattle feeders: which technique to apply?

    E-Print Network [OSTI]

    Hicks, Geoff Cody

    1997-01-01T23:59:59.000Z

    both feeder cattle costs and corn costs, and maximizing fed cattle prices. This research strives to evaluate the accuracy of six distinct price forecasting techniques over an eleven year period. The forecast techniques selected for this analysisare...

  19. Growing Up in Scotland: Sweep 2 - Summary of Findings from Year 2 

    E-Print Network [OSTI]

    Government, Scottish

    2008-02-01T23:59:59.000Z

    Research findings (of four) accompanying the full research report on Sweep 2 findings of the Growing Up in Scotland Study Year 2...

  20. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 200874 YEAR4 YEAR

  1. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 200874 YEAR4 YEAR7

  2. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 200874 YEAR43 YEAR

  3. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR 20144 YEAR

  4. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR8 YEAR 2013

  5. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR8 YEAR 20138

  6. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR8 YEAR 201387

  7. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR8 YEAR

  8. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR8 YEAR558

  9. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR8 YEAR558563

  10. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR85573380 YEAR

  11. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 2008 A794826 YEAR

  12. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 200874 YEAR 2014

  13. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 200874 YEAR 201434

  14. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 200874 YEAR

  15. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 200874 YEAR4

  16. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 200874 YEAR43

  17. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 200874 YEAR434

  18. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 200874 YEAR43417

  19. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 200874 YEAR434170

  20. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 20087486 YEAR 2012

  1. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 20087486 YEAR

  2. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 20087486 YEAR42

  3. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 20087486 YEAR424

  4. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 20087486 YEAR4247

  5. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 20087486 YEAR42478

  6. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 200874861 YEAR

  7. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 200874861 YEAR40

  8. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 200874861 YEAR4096

  9. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 20087486111 YEAR

  10. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 20087486111 YEAR17

  11. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S. 2008748611196 YEAR

  12. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR 2014 Males

  13. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR 2014 Males16

  14. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR 2014

  15. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR 20144

  16. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR 20144707

  17. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR 201447072540

  18. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR

  19. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR8

  20. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR8557 563

  1. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR8557 56378

  2. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR8557 5637831

  3. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR8557 56378318

  4. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR8557

  5. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR855733 28

  6. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR855733 280

  7. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR855733 2801

  8. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR855733 280192

  9. YEAR

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. Hirsch SNLMaythe Interior U.S.3 YEAR855733

  10. Year

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline prices4 Oil demand Motor444 U.S.Working and.

  11. 1994 Solid waste forecast container volume summary

    SciTech Connect (OSTI)

    Templeton, K.J.; Clary, J.L.

    1994-09-01T23:59:59.000Z

    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.

  12. 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...

  13. Weather Forecast Data an Important Input into Building Management Systems

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01T23:59:59.000Z

    it can generate as much or more energy that it needs ? Building activities need N kWhrs per day (solar panels, heating, etc) ? Harvested from solar panels & passive solar. Amount depends on weather ? NWP models forecast DSWRF @ surface (MJ/m2...://collaboration.cmc.ec.gc.ca/cmc/cmoi/SolarScribe/SolarScribe/ CMC NWP datasets for Day 2 Forecasts ? Regional Deterministic Prediction System (RDPS) ? RDPS raw model data ? 10 km resolution, North America, 000-054 forecasts ? Data at: http...

  14. The Climate of the McMurdo, Antarctica, Region as Represented by One Year of Forecasts from the Antarctic Mesoscale Prediction System*

    E-Print Network [OSTI]

    Howat, Ian M.

    System (AMPS) was implemented in October 2000. AMPS employs a limited-area model, the Polar fifth-generation and seasonal distributions of wind direction and speed, 2-m temperature, mean sea level pressure, precipitation influence on the near-surface winds. Time-mean vortices occur in the lee of Ross Island, perhaps a factor

  15. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 15 SEPTEMBER 28, 2010

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the second year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  16. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 27 OCTOBER 10, 2013

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fifth year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  17. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 16 AUGUST 29, 2013

    E-Print Network [OSTI]

    that we are trying to predict with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index This is the fifth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early for ACE using three categories as defined in Table 1. Table 1: ACE forecast definition. Parameter

  18. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 3 AUGUST 16, 2012

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fourth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  19. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM OCTOBER 12 OCTOBER 25, 2012

    E-Print Network [OSTI]

    Gray, William

    to predict with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined This is the fourth year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting for individual event parameters such as named storms and hurricanes. We issue forecasts for ACE using three

  20. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 28 OCTOBER 11, 2012

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fourth year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  1. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 13 SEPTEMBER 26, 2013

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fifth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  2. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 18 AUGUST 31, 2010

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the second year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  3. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM OCTOBER 11 OCTOBER 24, 2013

    E-Print Network [OSTI]

    Gray, William

    to predict with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined This is the fifth year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting for individual event parameters such as named storms and hurricanes. We issue forecasts for ACE using three

  4. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 31 SEPTEMBER 13, 2012

    E-Print Network [OSTI]

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fourth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  5. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 17 AUGUST 30, 2012

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fourth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  6. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 4 AUGUST 17, 2010

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the second year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  7. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 29 OCTOBER 12, 2010

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the second year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  8. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 11 SEPTEMBER 24, 2014

    E-Print Network [OSTI]

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the sixth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  9. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 30 SEPTEMBER 12, 2013

    E-Print Network [OSTI]

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fifth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  10. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 31 SEPTEMBER 13, 2011

    E-Print Network [OSTI]

    Birner, Thomas

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the third year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  11. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 28 SEPTEMBER 10, 2014

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the sixth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  12. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM OCTOBER 13 OCTOBER 26, 2010

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the second year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  13. Probabilistic manpower forecasting

    E-Print Network [OSTI]

    Koonce, James Fitzhugh

    1966-01-01T23:59:59.000Z

    PROBABILISTIC MANPOWER FORECASTING A Thesis JAMES FITZHUGH KOONCE Submitted to the Graduate College of the Texas ASSAM University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May, 1966 Major Subject...: Computer Science and Statistics PROBABILISTIC MANPOWER FORECASTING A Thesis By JAMES FITZHUGH KOONCE Submitted to the Graduate College of the Texas A@M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May...

  14. Table 2. Percent of Households with Vehicles, Selected Survey Years

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear Jan FebDecadeDecade21752 2,616 January 1996 January1996Percent

  15. UPF Forecast | Y-12 National Security Complex

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

    Uranium Processing Facility UPF Forecast UPF Forecast UPF Procurement provides the following forecast of subcontracting opportunities. Keep in mind that these requirements may be...

  16. Long Term Forecast ofLong Term Forecast of TsunamisTsunamis

    E-Print Network [OSTI]

    : ImproveImprove NOAANOAA''ss understandingunderstanding and forecast capabilityand forecast capability inin

  17. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01T23:59:59.000Z

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

  18. Solid waste program fiscal year 1997 multi-year work plan WBS 1.2.1

    SciTech Connect (OSTI)

    Riddelle, J.G.

    1996-09-30T23:59:59.000Z

    This document provides the technical baseline, work breakdown structure, schedule baseline, cost baseline, and execution year for the solid waste program.

  19. An econometric analysis and forecasting of Seoul office market

    E-Print Network [OSTI]

    Kim, Kyungmin

    2011-01-01T23:59:59.000Z

    This study examines and forecasts the Seoul office market, which is going to face a big supply in the next few years. After reviewing several previous studies on the Dynamic model and the Seoul Office market, this thesis ...

  20. Wind Power Forecasting: State-of-the-Art 2009

    E-Print Network [OSTI]

    Kemner, Ken

    Wind Power Forecasting: State-of-the-Art 2009 ANL/DIS-10-1 Decision and Information Sciences about Argonne and its pioneering science and technology programs, see www.anl.gov. #12;Wind Power................................................ 14 2.2.3 Critical Processes for Wind Forecast

  1. 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.

    2013-10-01T23:59:59.000Z

    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.

  2. Steam System Forecasting and Management

    E-Print Network [OSTI]

    Mongrue, D. M.; Wittke, D. O.

    1982-01-01T23:59:59.000Z

    '. This and the complex and integrated nature of the plants energy balance makes steam system forecasting and management essential for optimum use of the plant's energy. This paper discusses the method used by Union carbide to accomplish effective forecasting...

  3. Improving Inventory Control Using Forecasting

    E-Print Network [OSTI]

    Balandran, Juan

    2005-12-16T23:59:59.000Z

    EMGT 835 FIELD PROJECT: Improving Inventory Control Using Forecasting By Juan Mario Balandran jmbg@hotmail.com Master of Science The University of Kansas Fall Semester, 2005 An EMGT Field Project report submitted...............................................................................................................................................10 Current Inventory Forecast Process ...........................................................................................10 Development of Alternative Forecast Process...

  4. timber quality Modelling and forecasting

    E-Print Network [OSTI]

    Forest and timber quality in Europe Modelling and forecasting yield and quality in Europe Forest and timber quality in Europe Modelling and forecasting yield and quality in Europe M E F Y Q U E #12;Valuing and the UK ­ are working closely together to develop a model to help forecast timber growth, yield, quality

  5. RESERVOIR INFLOW FORECASTING USING NEURAL NETWORKS CHANDRASHEKAR SUBRAMANIAN

    E-Print Network [OSTI]

    Manry, Michael

    a mixture of hydroelectric and non- hydroelectric power, the economics of the hydroelectric plants depend, and to economically allocate the load between various non-hydroelectric plants. Neural networks provide an attractive technology for inflow forecasting, because of (1) their success in power load forecasting 1- 6 , and (2

  6. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST, and utilities. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption STAFFFINALREPORT NOVEMBER 2007 CEC-200-2007-015-SF2 Arnold Schwarzenegger, Governor #12;CALIFORNIA ENERGY

  7. I strongly urge that the forecasts recognize the high oil prices and gas prices experienced in 2008 and not treat them as an unusual occurrence in the next 20 years. In the long term with cap and

    E-Print Network [OSTI]

    I strongly urge that the forecasts recognize the high oil prices and gas prices experienced in 2008 and the development of carbon capture and storage applied to new coal fired generating stations, gas prices will only go up. Gas from the Rockies will move east as quickly as transport is available. To the extent

  8. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    AMERICAN METEOROLOGICAL SOCIETY Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary and interpretation of information from National Weather Service watches and warnings by10 decision makers such an outlier to the regional severe weather climatology. An analysis of the synoptic and13 mesoscale

  9. Fuel Price Forecasts INTRODUCTION

    E-Print Network [OSTI]

    Fuel Price Forecasts INTRODUCTION Fuel prices affect electricity planning in two primary ways and water heating, and other end-uses as well. Fuel prices also influence electricity supply and price because oil, coal, and natural gas are potential fuels for electricity generation. Natural gas

  10. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

    Quantifying PV power output variability,” Solar Energy, vol.each solar sen at node i, P(t) the total power output of theSolar Forecasting Historically, traditional power generation technologies such as fossil and nu- clear power which were designed to run in stable output

  11. Evaluation of Mixed-Phase Cloud Parameterizations in Short-Range Weather Forecasts with CAM3 and AM2 for Mixed-Phase Arctic Cloud Experiment

    SciTech Connect (OSTI)

    Xie, S; Boyle, J; Klein, S; Liu, X; Ghan, S

    2007-06-01T23:59:59.000Z

    By making use of the in-situ data collected from the recent Atmospheric Radiation Measurement Mixed-Phase Arctic Cloud Experiment, we have tested the mixed-phase cloud parameterizations used in the two major U.S. climate models, the National Center for Atmospheric Research Community Atmosphere Model version 3 (CAM3) and the Geophysical Fluid Dynamics Laboratory climate model (AM2), under both the single-column modeling framework and the U.S. Department of Energy Climate Change Prediction Program-Atmospheric Radiation Measurement Parameterization Testbed. An improved and more physically based cloud microphysical scheme for CAM3 has been also tested. The single-column modeling tests were summarized in the second quarter 2007 Atmospheric Radiation Measurement metric report. In the current report, we document the performance of these microphysical schemes in short-range weather forecasts using the Climate Chagne Prediction Program Atmospheric Radiation Measurement Parameterizaiton Testbest strategy, in which we initialize CAM3 and AM2 with realistic atmospheric states from numerical weather prediction analyses for the period when Mixed-Phase Arctic Cloud Experiment was conducted.

  12. U.S. Regional Demand Forecasts Using NEMS and GIS

    SciTech Connect (OSTI)

    Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

    2005-07-01T23:59:59.000Z

    The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

  13. Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01T23:59:59.000Z

    Forecasting and Resource Assessment, 1 st Edition, Editors:Forecasting and Resource Assessment, 1 st Edition, Editors:Forecasting and Resource Assessment, 1 st Ed.. Editor: Jan

  14. Site systems engineering fiscal year 1999 multi-year work plan (MYWP) update for WBS 1.8.2.2

    SciTech Connect (OSTI)

    GRYGIEL, M.L.

    1998-10-08T23:59:59.000Z

    Manage the Site Systems Engineering process to provide a traceable integrated requirements-driven, and technically defensible baseline. Through the Site Integration Group(SIG), Systems Engineering ensures integration of technical activities across all site projects. Systems Engineering's primary interfaces are with the RL Project Managers, the Project Direction Office and with the Project Major Subcontractors, as well as with the Site Planning organization. Systems Implementation: (1) Develops, maintains, and controls the site integrated technical baseline, ensures the Systems Engineering interfaces between projects are documented, and maintain the Site Environmental Management Specification. (2) Develops and uses dynamic simulation models for verification of the baseline and analysis of alternatives. (3) Performs and documents fictional and requirements analyses. (4) Works with projects, technology management, and the SIG to identify and resolve technical issues. (5) Supports technical baseline information for the planning and budgeting of the Accelerated Cleanup Plan, Multi-Year Work Plans, Project Baseline Summaries as well as performance measure reporting. (6) Works with projects to ensure the quality of data in the technical baseline. (7) Develops, maintains and implements the site configuration management system.

  15. P2.3 DEVELOPMENT OF A COMPREHENSIVE SEVERE WEATHER FORECAST VERIFICATION SYSTEM AT THE STORM PREDICTION CENTER

    E-Print Network [OSTI]

    : Andrew R. Dean, CIMMS, Univ. of Oklahoma, National Weather Center, Suite 2300, Norman, OK 73072-7268; e PREDICTION CENTER Andrew R. Dean*1,2 , Russell S. Schneider 2 , and Joseph T. Schaefer 2 1 Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, OK 2 NOAA/NWS Storm

  16. Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results

    E-Print Network [OSTI]

    Koomey, Jonathan G.

    2010-01-01T23:59:59.000Z

    Natural Gas Oil Lighting 0-1 hrs 1-2 his 2-3 hrs Usage levelNatural gas Oil Dishwasher End-Use Lighting 0-1 hrs 1-2 hrs UsageNatural gas Oil Dishwasher End-Use Lighting 0-1 hrs 1-2 hrs Usage

  17. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    NONE

    1998-07-01T23:59:59.000Z

    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.

  18. Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1

    E-Print Network [OSTI]

    Johnson, F.X.

    2010-01-01T23:59:59.000Z

    Administration. April. EPRI. 1982. Residential End-UseInstitute. EA-2512. July. EPRI. 1990. REEPS 2.0 HVAC ModelInstitute. October 11. EPRI, Electric Power Research

  19. SIMULATION AND FORECASTING IN INTERMODAL CONTAINER TERMINAL

    E-Print Network [OSTI]

    Gambardella, Luca Maria

    SIMULATION AND FORECASTING IN INTERMODAL CONTAINER TERMINAL Luca Maria Gambardella1 , Gianluca@idsia.ch 2 LCST, La Spezia Container Terminal, La Spezia (IT) 3 DSP, Data System & Planning sa, Manno (CH working in intermodal container terminals. INTRODUCTION The amount of work a container terminal deals

  20. Forecasting oilfield economic performance

    SciTech Connect (OSTI)

    Bradley, M.E. (Univ. of Chicago, IL (United States)); Wood, A.R.O. (BP Exploration, Anchorage, AK (United States))

    1994-11-01T23:59:59.000Z

    This paper presents a general method for forecasting oilfield economic performance that integrates cost data with operational, reservoir, and financial information. Practices are developed for determining economic limits for an oil field and its components. The economic limits of marginal wells and the role of underground competition receive special attention. Also examined is the influence of oil prices on operating costs. Examples illustrate application of these concepts. Categorization of costs for historical tracking and projections is recommended.

  1. Taking out 1 billion tons of CO2: The magic of China's 11th Five-Year Plan?

    E-Print Network [OSTI]

    Lin, Jiang

    2008-01-01T23:59:59.000Z

    E. I.. 1996. China's Energy A forecast to 2015, U.S. DOEChina’s energy/GDP elasticity remains at 1 and economic growth unfolds as forecast,

  2. 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.

    2012-09-01T23:59:59.000Z

    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.

  3. RESIDENTIAL SECTOR END-USE FORECASTING WITH EPRI-REEPS 2.1: SUMMARY INPUT ASSUMPTIONS AND RESULTS

    E-Print Network [OSTI]

    of Energy. We use the Electric Power Research Institute's (EPRI's) REEPS model, as reconfigured to reflect was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Building ....................................................................................................1 2. OVERVIEW OF THE REEPS MODEL..............................................................1

  4. Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1

    E-Print Network [OSTI]

    Johnson, F.X.

    2010-01-01T23:59:59.000Z

    Efficiency Choice 6.3 New Home HVAC System Choice 6.4. NewJuly. EPRI. 1990. REEPS 2.0 HVAC Model Logic, prepared by1990. Review of Equipment HVAC Choice Parameters. Cambridge

  5. Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1

    E-Print Network [OSTI]

    Johnson, F.X.

    2010-01-01T23:59:59.000Z

    A H A M . 1991. Room Air Conditioner Data. Association of7. FUTURE WORK 7.1 Room Air Conditioners 7.2. Common heatingShipments of Unitary Air Conditioners and Heat Pumps. Air-

  6. Characterization and Simulation of ECBM: History Matching of Forecasting CO2 Sequestration in Marshal County, West Virginia.

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    . Bromhal, National Energy Technology Laboratory Copyright 2010, Society of Petroleum Engineers This paper injection. Introduction Sustain economic growth by providing sufficient energy and controlling the CO2 emissions as byproduct of producing Energy from fossil fuels is one of the most challenging tasks

  7. Property:Building/YearConstruction2 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation,Pillar GroupInformationInformationYearConstruction1 Jump to:

  8. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01T23:59:59.000Z

    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.

  9. ELECTRICITY DEMAND FORECAST COMPARISON REPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005.................................................................................................................................3 PACIFIC GAS & ELECTRIC PLANNING AREA ........................................................................................9 Commercial Sector

  10. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

    Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN Manager Joseph O' Hagan Project Manager Kelly Birkinshaw Program Area Manager ENERGY-RELATED ENVIRONMENTAL

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

    SciTech Connect (OSTI)

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

    2009-05-04T23:59:59.000Z

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

  12. Verification of hourly forecasts of wind turbine power output

    SciTech Connect (OSTI)

    Wegley, H.L.

    1984-08-01T23:59:59.000Z

    A verification of hourly average wind speed forecasts in terms of hourly average power output of a MOD-2 was performed for four sites. Site-specific probabilistic transformation models were developed to transform the forecast and observed hourly average speeds to the percent probability of exceedance of an hourly average power output. (This transformation model also appears to have value in predicting annual energy production for use in wind energy feasibility studies.) The transformed forecasts were verified in a deterministic sense (i.e., as continuous values) and in a probabilistic sense (based upon the probability of power output falling in a specified category). Since the smoothing effects of time averaging are very pronounced, the 90% probability of exceedance was built into the transformation models. Semiobjective and objective (model output statistics) forecasts were made compared for the four sites. The verification results indicate that the correct category can be forecast an average of 75% of the time over a 24-hour period. Accuracy generally decreases with projection time out to approx. 18 hours and then may increase due to the fairly regular diurnal wind patterns that occur at many sites. The ability to forecast the correct power output category increases with increasing power output because occurrences of high hourly average power output (near rated) are relatively rare and are generally not forecast. The semiobjective forecasts proved superior to model output statistics in forecasting high values of power output and in the shorter time frames (1 to 6 hours). However, model output statistics were slightly more accurate at other power output levels and times. Noticeable differences were observed between deterministic and probabilistic (categorical) forecast verification results.

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

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    2 2. Annual Energy Outlook (Administration’s Annual Energy Outlook forecasted price (of Energy, Annual Energy Outlook 2004 with Projections to

  14. Stretched Exponential Decline Model as a Probabilistic and Deterministic Tool for Production Forecasting and Reserve Estimation in Oil and Gas Shales

    E-Print Network [OSTI]

    Akbarnejad Nesheli, Babak

    2012-07-16T23:59:59.000Z

    stabilized production forecast than traditional DCA models and in this work it is shown that it produces unchanging EUR forecasts after only two-three years of production data are available in selected reservoirs, notably the Barnett Shale...

  15. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    the California Energy Commission staff's revised forecasts for 2012­2022 electricity consumption, peak Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand

  16. NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    · NATIONAL AND GLOBAL FORECASTS · WEST VIRGINIA PROFILES AND FORECASTS · ENERGY · HEALTHCARE Research West Virginia University College of Business and Economics P.O. Box 6527, Morgantown, WV 26506 EXPERT OPINION PROVIDED BY Keith Burdette Cabinet Secretary West Virginia Department of Commerce

  17. Conservation The Northwest ForecastThe Northwest Forecast

    E-Print Network [OSTI]

    & Resources Creating Mr. Toad's Wild Ride for the PNW's Energy Efficiency InCreating Mr. Toad's Wild RideNorthwest Power and Conservation Council The Northwest ForecastThe Northwest Forecast ­­ Energy EfficiencyEnergy Efficiency Dominates ResourceDominates Resource DevelopmentDevelopment Tom EckmanTom Eckman

  18. A methodology for forecasting carbon dioxide flooding performance

    E-Print Network [OSTI]

    Marroquin Cabrera, Juan Carlos

    1998-01-01T23:59:59.000Z

    A methodology was developed for forecasting carbon dioxide (CO2) flooding performance quickly and reliably. The feasibility of carbon dioxide flooding in the Dollarhide Clearfork "AB" Unit was evaluated using the methodology. This technique is very...

  19. Post-Construction Evaluation of Forecast Accuracy Pavithra Parthasarathi1

    E-Print Network [OSTI]

    Levinson, David M.

    Post-Construction Evaluation of Forecast Accuracy Pavithra Parthasarathi1 David Levinson 2 February, the assumed networks to the actual in-place networks and other travel behavior assumptions that went

  20. Figure 2. Energy Consumption of Vehicles, Selected Survey Years

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803 Table A1.Gas Proved Reserves, WetGasCubic Feet)Gas2

  1. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400. Hall Deputy Director Energy Efficiency and Demand Analysis Division Scott W. Matthews Acting Executive

  2. Mathematical Forecasting Donald I. Good

    E-Print Network [OSTI]

    Boyer, Robert Stephen

    Mathematical Forecasting Donald I. Good Technical Report 47 September 1989 Computational Logic Inc the physical behavior of computer programs can reduce these risks for software engineering in the same way that it does for aerospace and other fields of engineering. Present forecasting capabilities for computer

  3. Regional-seasonal weather forecasting

    SciTech Connect (OSTI)

    Abarbanel, H.; Foley, H.; MacDonald, G.; Rothaus, O.; Rudermann, M.; Vesecky, J.

    1980-08-01T23:59:59.000Z

    In the interest of allocating heating fuels optimally, the state-of-the-art for seasonal weather forecasting is reviewed. A model using an enormous data base of past weather data is contemplated to improve seasonal forecasts, but present skills do not make that practicable. 90 references. (PSB)

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19T23:59:59.000Z

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

  5. Weather Forecast Data an Important Input into Building Management Systems 

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01T23:59:59.000Z

    GEPS 21 members ? Provides probabilistic forecasts ? Can give useful outlooks for longer term weather forecasts ? Scribe matrix from GDPS ? includes UMOS post processed model data ? Variables like Temperature, humidity post processed by UMOS ? See...://collaboration.cmc.ec.gc.ca/cmc/cmoi/cmc-prob-products/ ? Link to experimental 3-day outlook of REPS quilts ? http://collaboration.cmc.ec.gc.ca/cmc/cmoi/cmc-prob-products.reps Users can also make their own products from ensemble forecast data? Sample ascii matrix of 2m temperature could be fed...

  6. Natural Priors, CMSSM Fits and LHC Weather Forecasts

    E-Print Network [OSTI]

    Allanach, B C; Cranmer, Kyle; Lester, Christopher G; Weber, Arne M

    2007-08-07T23:59:59.000Z

    ar X iv :0 70 5. 04 87 v3 [ he p- ph ] 5 J ul 20 07 Preprint typeset in JHEP style - HYPER VERSION DAMTP-2007-18 Cavendish-HEP-2007-03 MPP-2007-36 Natural Priors, CMSSM Fits and LHC Weather Forecasts Benjamin C Allanach1, Kyle Cranmer2... ’s likely discoveries. There are big differences between nature of the questions answered by a forecast, and the ques- tions that will be answered by the experiments themselves when they have acquired compelling data. A weather forecast predicting “severe...

  7. 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. (Decision and Information Sciences); (INESC Porto)

    2011-12-06T23:59:59.000Z

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

  8. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 1 SEPTEMBER 14, 2010

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all are not developing any new tropical cyclones after Earl and Fiona. We expect Earl to generate large amounts of ACE This is the second year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting

  9. Short Term Hourly Load Forecasting Using Abductive Networks R. E. Abdel-Aal

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Physical Sciences, Research Institute, King Fahd University of Petroleum and Minerals, Dhahran, Saudi for forecasting next-day hourly loads have been developed. Evaluated on data for the 6th year, the models give. INTRODUCTION Accurate load forecasting is a key requirement for the planning and economic and secure operation

  10. 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.

    2013-10-01T23:59:59.000Z

    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.

  11. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07T23:59:59.000Z

    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.

  12. FEBRUARY 1999 119O ' C O N N O R E T A L . Forecast Verification for Eta Model Winds Using Lake Erie

    E-Print Network [OSTI]

    FEBRUARY 1999 119O ' C O N N O R E T A L . Forecast Verification for Eta Model Winds Using Lake. The in- crease in computer power in recent years and advances in numerical mesoscale models of both ocean Forecasting System (GLCFS) can be used to validate wind forecasts for the Great Lakes using observed

  13. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

    Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN with primary contributions in the area of decision support for reservoir planning and management Commission Energy-Related Environmental Research Joseph O' Hagan Contract Manager Joseph O' Hagan Project

  14. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

    Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN: California Energy Commission Energy-Related Environmental Research Joseph O' Hagan Contract Manager Joseph O' Hagan Project Manager Kelly Birkinshaw Program Area Manager ENERGY-RELATED ENVIRONMENTAL RESEARCH Martha

  15. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01T23:59:59.000Z

    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.

  16. Value of medium range weather forecasts in the improvement of seasonal hydrologic prediction skill

    SciTech Connect (OSTI)

    Shukla, Shraddhanand; Voisin, Nathalie; Lettenmaier, D. P.

    2012-08-15T23:59:59.000Z

    We investigated the contribution of medium range weather forecasts with lead times up to 14 days to seasonal hydrologic prediction skill over the Conterminous United States (CONUS). Three different Ensemble Streamflow Prediction (ESP)-based experiments were performed for the period 1980-2003 using the Variable Infiltration Capacity (VIC) hydrology model to generate forecasts of monthly runoff and soil moisture (SM) at lead-1 (first month of the forecast period) to lead-3. The first experiment (ESP) used a resampling from the retrospective period 1980-2003 and represented full climatological uncertainty for the entire forecast period. In the second and third experiments, the first 14 days of each ESP ensemble member were replaced by either observations (perfect 14-day forecast) or by a deterministic 14-day weather forecast. We used Spearman rank correlations of forecasts and observations as the forecast skill score. We estimated the potential and actual improvement in baseline skill as the difference between the skill of experiments 2 and 3 relative to ESP, respectively. We found that useful runoff and SM forecast skill at lead-1 to -3 months can be obtained by exploiting medium range weather forecast skill in conjunction with the skill derived by the knowledge of initial hydrologic conditions. Potential improvement in baseline skill by using medium range weather forecasts, for runoff (SM) forecasts generally varies from 0 to 0.8 (0 to 0.5) as measured by differences in correlations, with actual improvement generally from 0 to 0.8 of the potential improvement. With some exceptions, most of the improvement in runoff is for lead-1 forecasts, although some improvement in SM was achieved at lead-2.

  17. Weather forecasting : the next generation : the potential use and implementation of ensemble forecasting

    E-Print Network [OSTI]

    Goto, Susumu

    2007-01-01T23:59:59.000Z

    This thesis discusses ensemble forecasting, a promising new weather forecasting technique, from various viewpoints relating not only to its meteorological aspects but also to its user and policy aspects. Ensemble forecasting ...

  18. Optimal combined wind power forecasts using exogeneous variables

    E-Print Network [OSTI]

    Optimal combined wind power forecasts using exogeneous variables Fannar ¨Orn Thordarson Kongens of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

  19. CSUF ECONOMIC OUTLOOK AND FORECASTS MIDYEAR UPDATE -APRIL 2014

    E-Print Network [OSTI]

    de Lijser, Peter

    CSUF ECONOMIC OUTLOOK AND FORECASTS MIDYEAR UPDATE - APRIL 2014 Anil Puri, Ph.D. -- Director-year increase in the debt ceiling -- both of which proceeded without the usual drama. Second, the private sector, corporate coffers are flush with cash, and low US energy prices have dramatically improved the global

  20. The Galactic Center Weather Forecast M. Moscibrodzka1

    E-Print Network [OSTI]

    Gammie, Charles F.

    The Galactic Center Weather Forecast M. Mo´scibrodzka1 , H. Shiokawa2 , C. F. Gammie2,3 , J*. The > 3M cloud will #12;­ 2 ­ interact strongly with gas near nominal pericenter at rp 300AU 8000GM/c2 transient phase while the flow circularizes-- accompanied by transient emission--it is natural to think

  1. On-Road Remote Sensing of Automobile Emissions in the Phoenix Area: Year 2

    E-Print Network [OSTI]

    Denver, University of

    On-Road Remote Sensing of Automobile Emissions in the Phoenix Area: Year 2 Sajal S. Pokharel, Gary Alpharetta, Georgia 30022 Contract No. E-23-4 #12;On-Road Remote Sensing of Automobile Emissions when the measurements were binned by model year. #12;On-Road Remote Sensing of Automobile Emissions

  2. On-Road Remote Sensing of Automobile Emissions in the Chicago Area: Year 2

    E-Print Network [OSTI]

    Denver, University of

    On-Road Remote Sensing of Automobile Emissions in the Chicago Area: Year 2 Peter J. Popp, Gary A from automobiles are at a maximum when the air/fuel ratio is rich of stoichiometric, and are caused

  3. Forecasting consumer products using prediction markets

    E-Print Network [OSTI]

    Trepte, Kai

    2009-01-01T23:59:59.000Z

    Prediction Markets hold the promise of improving the forecasting process. Research has shown that Prediction Markets can develop more accurate forecasts than polls or experts. Our research concentrated on analyzing Prediction ...

  4. Massachusetts state airport system plan forecasts.

    E-Print Network [OSTI]

    Mathaisel, Dennis F. X.

    This report is a first step toward updating the forecasts contained in the 1973 Massachusetts State System Plan. It begins with a presentation of the forecasting techniques currently available; it surveys and appraises the ...

  5. Management Forecast Quality and Capital Investment Decisions

    E-Print Network [OSTI]

    Goodman, Theodore H.

    Corporate investment decisions require managers to forecast expected future cash flows from potential investments. Although these forecasts are a critical component of successful investing, they are not directly observable ...

  6. Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations

    E-Print Network [OSTI]

    Kemner, Ken

    forecasting methods and better integration of advanced wind power forecasts into system and plant operations and wind power plants) ­ Review and assess current practices Propose and test new and improved approachesWind Power Forecasting andWind Power Forecasting and Electricity Market Operations Audun Botterud

  7. Consensus Coal Production And Price Forecast For

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    Consensus Coal Production And Price Forecast For West Virginia: 2011 Update Prepared for the West December 2011 © Copyright 2011 WVU Research Corporation #12;#12;W.Va. Consensus Coal Forecast Update 2011 i Table of Contents Executive Summary 1 Recent Developments 3 Consensus Coal Production And Price Forecast

  8. 2 million tons per year: A performing biofuels supply chain for

    E-Print Network [OSTI]

    1 2 million tons per year: A performing biofuels supply chain for EU aviation NOTE It is understood that in the context of this text the term "biofuel(s) use in aviation" categorically implies "sustainably produced biofuel(s)" according to the EU legislation. June 2011 #12;2 This technical paper was drafted

  9. Growing Up in Scotland: Year 2 - Results from the second year of a study following the lives of Scotland's children 

    E-Print Network [OSTI]

    Bradshaw, Paul; Cunningham-Burley, Sarah; Dobie, Fiona; MacGregor, Andy; Marryat, Louise; Ormston, Rachel; Wasoff, Fran

    2008-02-18T23:59:59.000Z

    The Growing Up in Scotland study (GUS) is an important longitudinal research project aimed at tracking the lives of a cohort of Scottish children from the early years, through childhood and beyond. Its principal aim is ...

  10. Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime-Switching

    E-Print Network [OSTI]

    Genton, Marc G.

    Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at a wind energy site and fits a conditional predictive model for each regime. Geographically dispersed was applied to 2-hour-ahead forecasts of hourly average wind speed near the Stateline wind energy center

  11. Improvements in wind speed forecasts for wind power prediction purposes using Kalman filtering

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Improvements in wind speed forecasts for wind power prediction purposes using Kalman filtering P : 10.1016/j.jweia.2008.03.013 #12;2 Abstract This paper studies the application of Kalman filtering forecasts. The application of Kalman filter to these data leads to the elimination of any possible

  12. Model bias correction for dust storm forecast using ensemble Kalman filter

    E-Print Network [OSTI]

    Model bias correction for dust storm forecast using ensemble Kalman filter Caiyan Lin,1,2 Jiang Zhu Kalman filter (EnKF) assimilation targeting heavy dust episodes during the period of 15­24 March 2002. Wang (2008), Model bias correction for dust storm forecast using ensemble Kalman filter, J. Geophys

  13. Advanced statistical methods for shortterm wind power forecasting Research proposal draft

    E-Print Network [OSTI]

    Barnett, Alex

    Barnett July 2001 1 Background Over the last decade wind power has become a cost­effective alternative at a turbine) using linear or nonlinear time­series analysis (Alex­ iadis 1999), or 2) forecasting windAdvanced statistical methods for short­term wind power forecasting Research proposal draft Alex

  14. LOAD FORECASTING Eugene A. Feinberg

    E-Print Network [OSTI]

    Feinberg, Eugene A.

    , regression, artificial intelligence. 1. Introduction Accurate models for electric power load forecasting to make important decisions including decisions on pur- chasing and generating electric power, load for different operations within a utility company. The natures 269 #12;270 APPLIED MATHEMATICS FOR POWER SYSTEMS

  15. Calculator simplifies field production forecasting

    SciTech Connect (OSTI)

    Bixler, B.

    1982-05-01T23:59:59.000Z

    A method of forecasting future field production from an assumed average well production schedule and drilling schedule has been programmed for the HP-41C hand-held programmable computer. No longer must tedious row summations be made by hand for staggered well production schedules. Details of the program are provided.

  16. 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 [WindLogics

    2014-04-30T23:59:59.000Z

    This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times. A comprehensive analysis of wind energy forecast errors for the various model-based power forecasts was presented for a suite of wind energy ramp definitions. The results compiled over the year-long study period showed that the power forecasts based on the research models (ESRL_RAP, HRRR) more accurately predict wind energy ramp events than the current operational forecast models, both at the system aggregate level and at the local wind plant level. At the system level, the ESRL_RAP-based forecasts most accurately predict both the total number of ramp events and the occurrence of the events themselves, but the HRRR-based forecasts more accurately predict the ramp rate. At the individual site level, the HRRR-based forecasts most accurately predicted the actual ramp occurrence, the total number of ramps and the ramp rates (40-60% improvement in ramp rates over the coarser resolution forecast

  17. GenForecast(26yr)(avg).PDF

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

    SLCAIP Historical & Forecast Generation at Plant Total Range of Hydrology 0 2,000,000,000 4,000,000,000 6,000,000,000 8,000,000,000 10,000,000,000 12,000,000,000 1 9 7 0 1 9 7 2 1...

  18. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

    2.1.2 European Solar Radiation Atlas (ESRA)for supplementing solar radiation network data,” FinalEstimating incident solar radiation at the surface from geo-

  19. 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.

    1994-09-01T23:59:59.000Z

    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.

  20. 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

    2003-08-13T23:59:59.000Z

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

  1. TOWSON'S PHYSTEC COURSE IMPROVEMENT PROJECT, YEARS 1 AND 2: RESULTS AND LESSONS LEARNED

    E-Print Network [OSTI]

    Sandifer, Cody

    TOWSON'S PHYSTEC COURSE IMPROVEMENT PROJECT, YEARS 1 AND 2: RESULTS AND LESSONS LEARNED Cody. Lastly, the project team has learned numerous lessons about large-scale course reform with respect to include lessons learned by the project team about effective course structure, different forms of inquiry

  2. On-Road Remote Sensing of Automobile Emissions in the LaBrea Area: Year 2

    E-Print Network [OSTI]

    Denver, University of

    On-Road Remote Sensing of Automobile Emissions in the LaBrea Area: Year 2 Mitchell J. Williams 140 Alpharetta, Georgia 30022 Contract No. E-23-4 #12;On-Road Remote Sensing of Automobile Emissions compared to the standard error of the mean measurements. #12;On-Road Remote Sensing of Automobile Emissions

  3. Risk Forecasting with GARCH, Skewed t Distributions, and Multiple Timescales

    E-Print Network [OSTI]

    Risk Forecasting with GARCH, Skewed t Distributions, and Multiple Timescales Alec N. Kercheval describe how the histori- cal data can first be GARCH filtered and then used to calibrate parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.2 Data and Stylized Facts . . . . . . . . . . . . . . . . . . . . . . . 16 3.3 GARCH Filter

  4. Development and Deployment of an Advanced Wind Forecasting Technique

    E-Print Network [OSTI]

    Kemner, Ken

    findings. Part 2 addresses how operators of wind power plants and power systems can incorporate advanced the output of advanced wind energy forecasts into decision support models for wind power plant and power and applications of power market simulation models around the world. Argonne's software tools are used extensively

  5. air pollution forecast: Topics by E-print Network

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

    air pollution forecast First Page Previous Page 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 1 ENVIRONMENTAL INFORMATION SYSTEM...

  6. NREL: Transmission Grid Integration - Forecasting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's Possible for Renewable Energy: Grid IntegrationReport AvailableForecasting NREL researchers use

  7. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

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

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

    2015-08-01T23:59:59.000Z

    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. This information is then applied to stitch images together into largermore »views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

  8. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

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

    2010-05-01T23:59:59.000Z

    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.

  9. Radical irradiation and misonidazole for T2 grade III and T3 bladder cancer: 2 year follow-up

    SciTech Connect (OSTI)

    Abratt, R.P.; Barnes, D.R.; Hammond, J.A.; Sarembok, L.A.; Tucker, R.D.; Williams, A.M.

    1984-09-01T23:59:59.000Z

    Patients with T2 grade III and T3 bladder cancer were treated in a Phase II trial of radical irradiation plus Misonidazole (MISO). Twenty-two patients were treated and the results compared with historical controls. The cystoscopic complete tumor response between 6 and 12 months post therapy were 73 and 43%, respectively. The patient two year survival was 81 and 51%, respectively, and the patient 2 year survival with bladder preservation was 61 and 48%, respectively - 4 patients in the MISO study having undergone salvage cystectomy. Complications that may be radiation related in the MISO study are would sepsis after salvage cystectomy in 2 patients, rectal stenosis requiriing colostomy 16 months after salvage cystecomy in 1 patient and the development of a contracted bladder in 1 patient with a history of prior extensive endoscopic therapy. No misonidazole neurotoxicity seen. These findings are being further evaluated in a prospective radomized trial.

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

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

    collects data on a variety of physical processes that impact the wind forecasts used by wind farms, system operators and other industry professionals. By having access to...

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

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

    collects data on a variety of physical processes that impact the wind forecasts used by wind farms, system operators and other industry professionals. By having access to...

  12. The Value of Wind Power Forecasting

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

    Wind Power Forecasting Preprint Debra Lew and Michael Milligan National Renewable Energy Laboratory Gary Jordan and Richard Piwko GE Energy Presented at the 91 st American...

  13. U-M Construction Forecast December 15, 2011 U-M Construction Forecast

    E-Print Network [OSTI]

    Kamat, Vineet R.

    U-M Construction Forecast December 15, 2011 U-M Construction Forecast Spring ­ Fall 2012 As of December 15, 2011 Prepared by AEC Preliminary & Advisory #12;U-M Construction Forecast December 15, 2011 Overview · Campus by campus · Snapshot in time ­ Not all projects · Construction coordination efforts

  14. HAMMER FY 1996 Multi-Year Program Plan: WBS {number_sign}8.2

    SciTech Connect (OSTI)

    NONE

    1995-09-01T23:59:59.000Z

    The Hazardous Material Management and Emergency Response Training and Education Center -- known simply as HAMMER -- is being developed to assist the US Department of Energy (DOE) and others dedicated to improving worker health, safety and productivity. HAMMER is a training and education program for hazardous material, waste management, and emergency response workers. HAMMER is managed by the DOE Richland Operations Office under Work Breakdown Structure (8.2). The 1996 Multi-Year Program Plan (MYPP) includes the Execution Year data and provides the information for Programmatic Fiscal Year Site Management System Execution Baseline, as well as the detailed work plan for performance evaluation of the authorized work. The MYPP incorporates various planning methodologies to define the program and provides essential program integration, and a fully developed technical, cost, and schedule baseline. The MYPP will be utilized by WHC Program and Department Managers as the baseline management tool for status and progress monitoring, performance enhancement, impact analysis studies, and as the basis for detailed fiscal year and near-term planning.

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

    SciTech Connect (OSTI)

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

    2013-01-01T23:59:59.000Z

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

  16. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    has developed longterm forecasts of transportation energy demand as well as projected ranges of transportation fuel and crude oil import requirements. The transportation energy demand forecasts makeCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY

  17. Dynamic Filtering and Mining Triggers in Mesoscale Meteorology Forecasting

    E-Print Network [OSTI]

    Plale, Beth

    Dynamic Filtering and Mining Triggers in Mesoscale Meteorology Forecasting Nithya N. Vijayakumar {rramachandran, xli}@itsc.uah.edu Abstract-- Mesoscale meteorology forecasting as a data driven application Triggers, Data Mining, Stream Processing, Meteorology Forecasting I. INTRODUCTION Mesoscale meteorologists

  18. Growing Up in Scotland: Sweep 2 - Issues of Child Health and Development at Ages 1-2 and 3-4 Years 

    E-Print Network [OSTI]

    Government, Scottish

    2008-02-18T23:59:59.000Z

    Research findings (of four) accompanying the full research report on Sweep 2 findings of the Growing Up in Scotland study Year 2....

  19. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual SiteofEvaluating A PotentialJumpGermanFife Energy Park atFisiaFlorida:Forecast Energy Jump to:

  20. Water resources data, Ohio: Water year 1991. Volume 2, St. Lawrence River Basin: Statewide project data

    SciTech Connect (OSTI)

    Shindel, H.L.; Klingler, J.H.; Mangus, J.P.; Trimble, L.E.

    1992-03-01T23:59:59.000Z

    The Water Resources Division of the US Geological Survey (USGS), in cooperation with State agencies, obtains a large amount of data pertaining to the water resources of Ohio each water year. These data, accumulated during many years, constitute a valuable data base for developing an improved understanding of the water resources of the State. To make these data readily available to interested parties outside the USGS, the data are published annually in this report series entitled ``Water Resources Data--Ohio.`` This report (in two volumes) includes records on surface water and ground water in the State. Specifically, it contains: (1) Discharge records for 131 streamflow-gaging stations, 95 miscellaneous sites; (2) stage and content records for 5 streams, lakes, and reservoirs; (3) water-quality for 40 streamflow-gaging stations, 378 wells, and 74 partial-record sites; and (4) water levels for 431 observation wells.

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

    Office of Environmental Management (EM)

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

  2. Alternative methods for forecasting GDP Dominique Gugan

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    analysis. Better forecast performance for macroeconomic variables will lead to Paris School of Economics the speed of computers that can develop search algorithms from appropriate selection criteria, Devroye. 1 Introduction Forecasting macroeconomic variables such as GDP and inflation play an important role

  3. A NEW APPROACH FOR EVALUATING ECONOMIC FORECASTS

    E-Print Network [OSTI]

    Vertes, Akos

    APPROACH FOR EVALUATING ECONOMIC FORECASTS Tara M. Sinclair , H.O. Stekler, and Warren Carnow Department of Economics The George Washington University Monroe Hall #340 2115 G Street NW Washington, DC 20052 JEL Codes, Mahalanobis Distance Abstract This paper presents a new approach to evaluating multiple economic forecasts

  4. 2013 Midyear Economic Forecast Sponsorship Opportunity

    E-Print Network [OSTI]

    de Lijser, Peter

    2013 Midyear Economic Forecast Sponsorship Opportunity Thursday, April 18, 2013, ­ Hyatt Regency Irvine 11:30 a.m. ­ 1:30 p.m. Dr. Anil Puri presents his annual Midyear Economic Forecast addressing and Economics at California State University, Fullerton, the largest accredited business school in California

  5. Dynamic Algorithm for Space Weather Forecasting System

    E-Print Network [OSTI]

    Fischer, Luke D.

    2011-08-08T23:59:59.000Z

    /effective forecasts, and we have performed preliminary benchmarks on this algorithm. The preliminary benchmarks yield surprisingly effective results thus far?forecasts have been made 8-16 hours into the future with significant magnitude and trend accuracy, which is a...

  6. Nonparametric models for electricity load forecasting

    E-Print Network [OSTI]

    Genève, Université de

    Electricity consumption is constantly evolving due to changes in people habits, technological innovations1 Nonparametric models for electricity load forecasting JANUARY 23, 2015 Yannig Goude, Vincent at University Paris-Sud 11 Orsay. His research interests are electricity load forecasting, more generally time

  7. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand, EndUser Natural Gas Demand, and Energy Efficiency SEPTEMBER 2013 CEC2002013004SDV1REV CALIFORNIA The California Energy Demand 2014 ­ 2024 Revised Forecast, Volume 1: Statewide Electricity Demand and Methods

  8. 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.

    1994-02-01T23:59:59.000Z

    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.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny:RevisedAdvisory Board Contributions EMEMEnergyEarlyDepartment ofEcoCAR 2 Year 1

  10. Pressure Normalization of Production Rates Improves Forecasting Results

    E-Print Network [OSTI]

    Lacayo Ortiz, Juan Manuel

    2013-08-07T23:59:59.000Z

    reservoir conditions, psi 2/cp ?wf Pseudopressure at flowing conditions, psi 2/cp ? Characteristic time parameter for SEPD model, D ?g Gas viscosity, cp ?o Oil viscosity, cp Acronyms BDF Boundary-Dominated Flow DCA Decline Curve Analysis EUR..., as the advanced analytical and numerical models depend on copious inputs, there is a high probability that different combinations of those parameters could generate equivalent and acceptable history matches, but different production forecasts and EUR...

  11. Leap Year 2012: Why We Need February 291 by Brian Handwerk for National Geographic News2

    E-Print Network [OSTI]

    South Bohemia, University of

    for tracking time needed to use it, too?6 7 Leap Year Needed to Correct Calendar Drift8 We observe the modern the Babylonians--23 were among the first to determine the true length of the solar year. Egypt adopted a leap in the actual solar year. This seemingly small difference made the solar year about 11 minutes too long,30

  12. Hybrid methodology for hourly global radiation forecasting in Mediterranean area

    E-Print Network [OSTI]

    Voyant, Cyril; Paoli, Christophe; Nivet, Marie Laure

    2012-01-01T23:59:59.000Z

    The renewable energies prediction and particularly global radiation forecasting is a challenge studied by a growing number of research teams. This paper proposes an original technique to model the insolation time series based on combining Artificial Neural Network (ANN) and Auto-Regressive and Moving Average (ARMA) model. While ANN by its non-linear nature is effective to predict cloudy days, ARMA techniques are more dedicated to sunny days without cloud occurrences. Thus, three hybrids models are suggested: the first proposes simply to use ARMA for 6 months in spring and summer and to use an optimized ANN for the other part of the year; the second model is equivalent to the first but with a seasonal learning; the last model depends on the error occurred the previous hour. These models were used to forecast the hourly global radiation for five places in Mediterranean area. The forecasting performance was compared among several models: the 3 above mentioned models, the best ANN and ARMA for each location. In t...

  13. P9.137 The SPC Storm-Scale Ensemble of Opportunity: Overview and Results from the 2012 Hazardous Weather Testbed Spring Forecasting Experiment

    E-Print Network [OSTI]

    P9.137 The SPC Storm-Scale Ensemble of Opportunity: Overview and Results from the 2012 Hazardous) available to forecasters at the Storm Prediction Center (SPC) has been increasing over the past few years to examine and scrutinize the data in creating a forecast has not changed. Thus, the concept of the SPC Storm

  14. Constraint on inflation model from BICEP2 and WMAP 9-year data

    E-Print Network [OSTI]

    Cheng Cheng; Qing-Guo Huang

    2014-04-08T23:59:59.000Z

    Even though Planck data released in 2013 (P13) is not compatible with Background Imaging of Cosmic Extragalactic Polarization (B2) and some local cosmological observations, including Supernova Legacy Survey (SNLS) samples and $H_0$ prior from Hubble Space Telescope (HST) etc, Wilkinson Microwaves Anisotropy Probe 9-year data (W9) is consistent with all of them in the base six-parameter $\\Lambda$CDM+tensor cosmology quite well. In this letter, we adopt the combinations of B2+W9 and B2+W9+SNLS+BAO+HST to constrain the cosmological parameters in the base six-parameter $\\Lambda$CDM+tensor model with $n_t=-r/8$, where r and $n_t$ are the tensor-to-scalar ratio and the tilt of relic gravitational wave spectrum, and BAO denotes Baryon Acoustic Oscillation. We find that the Harrison-Zel'dovich (HZ) scale invariant scalar power spectrum is consistent with both data combinations, chaotic inflation is marginally disfavored by the data at around $2\\sigma$ level, but the power-law inflation model and the inflation model with inverse power-law potential can fit the data nicely.

  15. 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.

    2007-12-01T23:59:59.000Z

    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.

  16. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST

    E-Print Network [OSTI]

    procurement process at the California Public Utilities Commission. This forecast was produced with the Energy Commission demand forecast models. Both the staff draft energy consumption and peak forecasts are slightly and commercial sectors. Keywords Electricity demand, electricity consumption, demand forecast, weather

  17. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    and water pumping sectors. Mark Ciminelli forecasted energy for transportation, communication and utilities. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data at the California Public Utilities Commission. This forecast was produced with the Energy Commission demand forecast

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

    SciTech Connect (OSTI)

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

    2011-10-01T23:59:59.000Z

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

  19. 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.

    2013-10-01T23:59:59.000Z

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

  20. Solar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting Questionnaire As someone who is familiar with solar energy issues, we hope that you will tak

    E-Print Network [OSTI]

    Islam, M. Saif

    Page 1 Solar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting Questionnaire As someone who is familiar with solar energy issues, we hope that you will take a few moments to answer this short survey

  1. PSO (FU 2101) Ensemble-forecasts for wind power

    E-Print Network [OSTI]

    PSO (FU 2101) Ensemble-forecasts for wind power Analysis of the Results of an On-line Wind Power Ensemble- forecasts for wind power (FU2101) a demo-application producing quantile forecasts of wind power correct) quantile forecasts of the wind power production are generated by the application. However

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

    Reports and Publications (EIA)

    1998-01-01T23:59:59.000Z

    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.

  3. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    supervised data preparation. Steven Mac and Keith O'Brien prepared the historical energy consumption data. Nahid Movassagh forecasted consumption for the agriculture and water pumping sectors. Cynthia Rogers generation, conservation, energy efficiency, climate zone, investorowned, public, utilities, additional

  4. Wind Speed Forecasting for Power System Operation 

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22T23:59:59.000Z

    In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system...

  5. STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES 2005 TO 2018 Mignon Marks Principal Author Mignon Marks Project Manager David Ashuckian Manager ELECTRICITY ANALYSIS OFFICE Sylvia Bender Acting Deputy Director ELECTRICITY SUPPLY DIVISION B.B. Blevins Executive Director

  6. Wind Speed Forecasting for Power System Operation

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22T23:59:59.000Z

    In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system...

  7. Potential Economic Value of Seasonal Hurricane Forecasts

    E-Print Network [OSTI]

    Emanuel, Kerry Andrew

    This paper explores the potential utility of seasonal Atlantic hurricane forecasts to a hypothetical property insurance firm whose insured properties are broadly distributed along the U.S. Gulf and East Coasts. Using a ...

  8. Text-Alternative Version LED Lighting Forecast

    Broader source: Energy.gov [DOE]

    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....

  9. Essays in International Macroeconomics and Forecasting

    E-Print Network [OSTI]

    Bejarano Rojas, Jesus Antonio

    2012-10-19T23:59:59.000Z

    This dissertation contains three essays in international macroeconomics and financial time series forecasting. In the first essay, I show, numerically, that a two-country New-Keynesian Sticky Prices model, driven by monetary and productivity shocks...

  10. California climate change, hydrologic response, and flood forecasting

    SciTech Connect (OSTI)

    Miller, Norman L.

    2003-11-11T23:59:59.000Z

    There is strong evidence that the lower atmosphere has been warming at an unprecedented rate during the last 50 years, and it is expected to further increase at least for the next 100 years. Warmer air mass implies a higher capacity to hold water vapor and an increased likelihood of an acceleration of the global water cycle. This acceleration is not validated and considerable new research has gone into understanding aspects of the water cycle (e.g. Miller et al. 2003). Several significant findings on the hydrologic response to climate change can be reported. It is well understood that the observed and expected warming is related to sea level rise. In a recent seminar at Lawrence Berkeley National Laboratory, James Hansen (Director of the Institute for Space Studies, National Aeronautics and Space Administration) stressed that a 1.25 Wm{sup -2} increase in radiative forcing will lead to an increase in the near surface air temperature by 1 C. This small increase in temperature from 2000 levels is enough to cause very significant impacts to coasts. Maury Roos (Chief Hydrologist, California Department of Water Resources) has shown that a 0.3 m rise in sea level shifts the San Francisco Bay 100-year storm surge flood event to a 10-year event. Related coastal protection costs for California based on sea level rise are shown. In addition to rising sea level, snowmelt-related streamflow represents a particular problem in California. Model studies have indicated that there will be approximately a 50% decrease in snow pack by 2100. This potential deficit must be fully recognized and plans need to be put in place well in advance. In addition, the warmer atmosphere can hold more water vapor and result in more intense warm winter-time precipitation events that result in flooding. During anticipated high flow, reservoirs need to release water to maintain their structural integrity. California is at risk of water shortages, floods, and related ecosystem stresses. More research needs to be done to further improve our ability to forecast weather events at longer time scales. Seasonal predictions have been statistical and only recently have studies begun to use ensemble simulations and historical observations to constrain such predictions. Understanding the mechanisms of large-scale atmospheric dynamics and its local impacts remain topics of intensive research. The ability to predict extreme events and provide policy makers with this information, along with climate change and hydrologic response information, will help to guide planning to form a more resilient infrastructure in the future.

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01T23:59:59.000Z

    gas price forecasts with contemporaneous natural gas pricesreference-case natural gas price forecast, and that have notof AEO 2009 Natural Gas Price Forecast to NYMEX Futures

  12. Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01T23:59:59.000Z

    Gas Price Forecast W ith natural gas prices significantlyof AEO 2006 Natural Gas Price Forecast to NYMEX Futurescase long-term natural gas price forecasts from the AEO

  13. Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    to accurately forecast natural gas prices. Many policyseek alternative methods to forecast natural gas prices. Thethe accuracy of forecasts for natural gas prices as reported

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

    gas price forecasts with contemporaneous natural gas pricesreference-case natural gas price forecast, and that have notof AEO 2008 Natural Gas Price Forecast to NYMEX Futures

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01T23:59:59.000Z

    the base-case natural gas price forecast, but to alsogas price forecasts with contemporaneous natural gas pricesof AEO 2010 Natural Gas Price Forecast to NYMEX Futures

  16. Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01T23:59:59.000Z

    Natural Gas Price Forecast Although natural gas prices areof AEO 2007 Natural Gas Price Forecast to NYMEX Futurescase long-term natural gas price forecasts from the AEO

  17. 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.

  18. Bivariate Splines for Hurricane Path Forecasting Bree Ettinger and Ming-Jun Lai

    E-Print Network [OSTI]

    Lai, Ming-Jun

    Bivariate Splines for Hurricane Path Forecasting Bree Ettinger and Ming-Jun Lai 1 Introduction Every year, hurricanes cause a lot of damage, especially, when they hit cities along the coast line. A notorious example is Hurricane Katrina in 2005 which hit New Orleans and damaged the city significantly

  19. Forecasting of preprocessed daily solar radiation time series using neural networks

    E-Print Network [OSTI]

    Boyer, Edmond

    Forecasting of preprocessed daily solar radiation time series using neural networks Christophe prediction of global solar radiation on a horizontal surface. First results are promising with nRMSE ~ 21 t or at day d and year y d H0 Extraterrestrial solar radiation coefficient for day d [MJ/m²] xt, xd,y Time

  20. Ramp Forecasting Performance from Improved Short-Term Wind Power Forecasting: Preprint

    SciTech Connect (OSTI)

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

    2014-05-01T23:59:59.000Z

    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.

  1. 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...

  2. A Novel Approach to Material Development for Advanced Reactor Systems. Quarterly progress report, Year 1 - Quarter 2

    SciTech Connect (OSTI)

    None

    2000-03-27T23:59:59.000Z

    OAK B188 A Novel Approach to Material Development for Advanced Reactor Systems. Quarterly progress report, Year 1--Quarter 2. Year one of this project had three major goals. First, to specify, order and install a new high current ion source for more rapid and stable proton irradiation. Second, to assess the use low temperature irradiation and chromium pre-enrichment in an effort to isolate a radiation damage microstructure in stainless steels without the effects of RIS. Third, to prepare for the irradiation of reactor pressure vessel steel and Zircaloy. Program goals for Second Quarter, Year One: In year 1 quarter 2, the project goal was to complete an irradiation of an RPV steel sample and begin sample characterization. We also planned to identify sources of Zircaloy for irradiation and characterization.

  3. Rev. sci. tech. Off. int. Epiz., 2008, 27 (2), 00-00 Predicted climate changes for the years to come

    E-Print Network [OSTI]

    Rev. sci. tech. Off. int. Epiz., 2008, 27 (2), 00-00 Predicted climate changes for the years 3PU, United Kingdom. E-mail: stoned@atm.ox.ac.uk (2) Tyndall Centre for Climate Change Research community to produce predictions of future climate change. Predictions for the next few decades

  4. Total soil C and N sequestration in a grassland following 10 years of free air CO2 enrichment

    E-Print Network [OSTI]

    van Kessel, Chris

    Total soil C and N sequestration in a grassland following 10 years of free air CO2 enrichment C H R, Laboratory of Soil Science and Geology, Wageningen University and Research Centre, PO Box 37, 6700 AA Abstract Soil C sequestration may mitigate rising levels of atmospheric CO2. However, it has yet

  5. Radar-Derived Forecasts of Cloud-to-Ground Lightning Over Houston, Texas

    E-Print Network [OSTI]

    Mosier, Richard Matthew

    2011-02-22T23:59:59.000Z

    .1.6 Comparison to Previous Studies......................................................................59 3.2 VII Forecast Method...............................................................................................61 3.2.1 Percentile Value...) percentile values for the entire dataset (1997-2006) when considering only cells with a minimum track count of 2.......................................................................... 117 3.5 Same as Figure 3.4 for the POD values...

  6. Forecasting project progress and early warning of project overruns with probabilistic methods

    E-Print Network [OSTI]

    Kim, Byung Cheol

    2008-10-10T23:59:59.000Z

    , the critical path method (CPM) and earned value management (EVM) are deterministic and fail to account for the inherent uncertainty in forecasting and project performance. The objective of this dissertation is to improve the predictive capabilities....4.1 Earned Value Management ................................................... 14 2.4.2 CPM ...................................................................................... 20 2.4.3 Monte Carlo Simulation...

  7. Viability, Development, and Reliability Assessment of Coupled Coastal Forecasting Systems

    E-Print Network [OSTI]

    Singhal, Gaurav

    2012-10-19T23:59:59.000Z

    disaster, Cook Inlet (CI) and Prince William Sound (PWS) are regions that suffer from a lack of accurate wave forecast information. This dissertation develops high- resolution integrated wave forecasting schemes for these regions in order to meet...

  8. Potential to Improve Forecasting Accuracy: Advances in Supply Chain Management

    E-Print Network [OSTI]

    Datta, Shoumen

    2008-07-31T23:59:59.000Z

    Forecasting is a necessity almost in any operation. However, the tools of forecasting are still primitive in view of the great strides made by research and the increasing abundance of data made possible by automatic ...

  9. Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output Perturbation

    E-Print Network [OSTI]

    Washington at Seattle, University of

    Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output. This is typically not feasible for mesoscale weather prediction carried out locally by organizations without by simulating realizations of the geostatistical model. The method is applied to 48-hour mesoscale forecasts

  10. The effect of multinationality on management earnings forecasts

    E-Print Network [OSTI]

    Runyan, Bruce Wayne

    2005-08-29T23:59:59.000Z

    This study examines the relationship between a firm??s degree of multinationality and its managers?? earnings forecasts. Firms with a high degree of multinationality are subject to greater uncertainty regarding earnings forecasts due...

  11. Mathematics Module options 2013/14 for years 1, 2 and 3 Full name Maths BSc Maths MSci

    E-Print Network [OSTI]

    Applebaum, David

    Mathematics Module options 2013/14 for years 1, 2 and 3 Full name Maths BSc Maths MSci 4CCM111A CALCULUS I 1 4CCM112A CALCULUS II 2 4CCM113A LINEAR METHODS 1 4CCM115A NUMBERS AND FUNCTIONS 1 x 5CCM115B NUMBERS AND FUNCTIONS FOR JOINT HONOURS 1 x x x x x 4CCM121A INTRODUCTION TO ABSTRACT ALGEBRA 2 x x x 5CCM

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

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01T23:59:59.000Z

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

  13. Cooperative Extension of Schoharie County Slashes Energy Bills by $2,400 per Year

    E-Print Network [OSTI]

    Keinan, Alon

    and Investment Yield Big Savings in One-Floor Office Building Cobleskill, New York--Cornell Cooperative Extension had an energy audit performed on its building several years ago, but the staff knew it was time building. Proposing an energy assessment Don Smyers, executive director of the Schoharie and Otsego

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

    SciTech Connect (OSTI)

    none,

    1993-12-31T23:59:59.000Z

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

  15. Weighted Parametric Operational Hydrology Forecasting Thomas E. Croley II1

    E-Print Network [OSTI]

    1 Weighted Parametric Operational Hydrology Forecasting Thomas E. Croley II1 1 Great Lakes forecasts in operational hydrology builds a sample of possibilities for the future, of climate series from-parametric method can be extended into a new weighted parametric hydrological forecasting technique to allow

  16. A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION

    E-Print Network [OSTI]

    Boyer, Edmond

    1 A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION in the realm of solar radiation forecasting. In this work, two forecasting models: Autoregressive Moving. The very first results show an improvement brought by this approach. 1. INTRODUCTION Solar radiation

  17. FORECASTING SOLAR RADIATION PRELIMINARY EVALUATION OF AN APPROACH

    E-Print Network [OSTI]

    Perez, Richard R.

    FORECASTING SOLAR RADIATION -- PRELIMINARY EVALUATION OF AN APPROACH BASED UPON THE NATIONAL, and undertake a preliminary evaluation of, a simple solar radiation forecast model using sky cover predictions forecasts is 0.05o in latitude and longitude. Solar Radiation model: The model presented in this paper

  18. AUTOMATION OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S.

    E-Print Network [OSTI]

    Povinelli, Richard J.

    AUTOMATION OF ENERGY DEMAND FORECASTING by Sanzad Siddique, B.S. A Thesis submitted to the Faculty OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S. Marquette University, 2013 Automation of energy demand of the energy demand forecasting are achieved by integrating nonlinear transformations within the models

  19. Univariate Modeling and Forecasting of Monthly Energy Demand Time Series

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Univariate Modeling and Forecasting of Monthly Energy Demand Time Series Using Abductive and Neural dedicated models to forecast the 12 individual months directly. Results indicate better performance is superior to naïve forecasts based on persistence and seasonality, and is better than results quoted

  20. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    requirements. The transportation energy demand forecasts make assumptions about fuel price forecastsCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY ENERGY COMMISSION Gordon Schremp, Jim Page, and Malachi Weng-Gutierrez Principal Authors Jim Page Project

  1. PSO (FU 2101) Ensemble-forecasts for wind power

    E-Print Network [OSTI]

    PSO (FU 2101) Ensemble-forecasts for wind power Wind Power Ensemble Forecasting Using Wind Speed the problems of (i) transforming the meteorological ensembles to wind power ensembles and, (ii) correcting) data. However, quite often the actual wind power production is outside the range of ensemble forecast

  2. Savings at the pump help push U.S. gasoline demand to 8-year...

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    U.S. gasoline demand to 8-year high U.S. gasoline consumption this year is expected to top 9 million barrels per day for the first time since 2007. In its new monthly forecast,...

  3. Forecasting the Market Penetration of Energy Conservation Technologies: The Decision Criteria for Choosing a Forecasting Model

    E-Print Network [OSTI]

    Lang, K.

    1982-01-01T23:59:59.000Z

    capital requirements and research and development programs in the alum inum industry. : CONCLUSIONS Forecasting the use of conservation techndlo gies with a market penetration model provides la more accountable method of projecting aggrega...

  4. A first large-scale flood inundation forecasting model

    SciTech Connect (OSTI)

    Schumann, Guy J-P; Neal, Jeffrey C.; Voisin, Nathalie; Andreadis, Konstantinos M.; Pappenberger, Florian; Phanthuwongpakdee, Kay; Hall, Amanda C.; Bates, Paul D.

    2013-11-04T23:59:59.000Z

    At present continental to global scale flood forecasting focusses on predicting at a point discharge, with little attention to the detail and accuracy of local scale inundation predictions. Yet, inundation is actually the variable of interest and all flood impacts are inherently local in nature. This paper proposes a first large scale flood inundation ensemble forecasting model that uses best available data and modeling approaches in data scarce areas and at continental scales. The model was built for the Lower Zambezi River in southeast Africa to demonstrate current flood inundation forecasting capabilities in large data-scarce regions. The inundation model domain has a surface area of approximately 170k km2. ECMWF meteorological data were used to force the VIC (Variable Infiltration Capacity) macro-scale hydrological model which simulated and routed daily flows to the input boundary locations of the 2-D hydrodynamic model. Efficient hydrodynamic modeling over large areas still requires model grid resolutions that are typically larger than the width of many river channels that play a key a role in flood wave propagation. We therefore employed a novel sub-grid channel scheme to describe the river network in detail whilst at the same time representing the floodplain at an appropriate and efficient scale. The modeling system was first calibrated using water levels on the main channel from the ICESat (Ice, Cloud, and land Elevation Satellite) laser altimeter and then applied to predict the February 2007 Mozambique floods. Model evaluation showed that simulated flood edge cells were within a distance of about 1 km (one model resolution) compared to an observed flood edge of the event. Our study highlights that physically plausible parameter values and satisfactory performance can be achieved at spatial scales ranging from tens to several hundreds of thousands of km2 and at model grid resolutions up to several km2. However, initial model test runs in forecast mode revealed that it is crucial to account for basin-wide hydrological response time when assessing lead time performances notwithstanding structural limitations in the hydrological model and possibly large inaccuracies in precipitation data.

  5. Navy Mobility Fuels Forecasting System Phase 4 report

    SciTech Connect (OSTI)

    Das, S.; Hadder, G.R.; Leiby, P.N.; Lee, R.; Davis, R.M.

    1988-09-01T23:59:59.000Z

    The Department of Navy's Maritime Strategy is designed to maintain military readiness and the ability to operate in all major theaters of the world. Mobility fuels required for sea, air, and land operations are vital components of the Navy's peacetime and wartime strategies. The purpose of the Navy's Mobility Fuels Technology Program is to understand fuel supply and fuel property impacts on Navy equipment performance and fleet readiness and operations. Oak Ridge National Laboratory (ORNL) has assisted the Department of Navy in developing and testing a methodology for forecasting mobility fuel availability, quality, and relative price, as well as evaluating options to increase fuel supplies during world oil supply disruptions. Publicly available models developed by the Energy Information Administration of the Department of Energy were selected as the foundation of the Navy Mobility Fuels Forecasting System (NMFFS). The NMFFS was enhanced as ORNL reviewed data on world oil reserves, production and prices, trends in crude oil and refined product quality, and changes in refinery process technology. The system was used to analyze the availability, quality, and relative price of military fuels that could be produced in several domestic and foreign refining regions under Business-As-Usual (BAU) and two hypothetical world crude oil disruption scenarios in the year 1995. 25 refs., 11 figs., 29 tabs.

  6. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    , Gary Occhiuzzo, and Keith O'Brien prepared the historical energy consumption data. Nahid Movassagh forecasted consumption for the agriculture and water pumping sectors. Don Schultz and Doug Kemmer developed. California Energy Commission, Electricity Supply Analysis Division. Publication Number: CEC2002012001CMFVI

  7. Facebook IPO updated valuation and user forecasting

    E-Print Network [OSTI]

    Facebook IPO ­ updated valuation and user forecasting Based on: Amendment No. 6 to Form S-1 (May 9. Peter Cauwels and Didier Sornette, Quis pendit ipsa pretia: facebook valuation and diagnostic Extreme Growth JPMPaper Cauwels and Sornette 840 1110 1820 S1- filing- May 9 2012 1006 1105 1371 Facebook

  8. Modeling of Uncertainty in Wind Energy Forecast

    E-Print Network [OSTI]

    regression and splines are combined to model the prediction error from Tunø Knob wind power plant. This data of the thesis is quantile regression and splines in the context of wind power modeling. Lyngby, February 2006Modeling of Uncertainty in Wind Energy Forecast Jan Kloppenborg Møller Kongens Lyngby 2006 IMM-2006

  9. Segmenting Time Series for Weather Forecasting

    E-Print Network [OSTI]

    Sripada, Yaji

    for generating textual summaries. Our algorithm has been implemented in a weather forecast generation system. 1 presentation, aid human understanding of the underlying data sets. SUMTIME is a research project aiming turbines. In the domain of meteorology, time series data produced by numerical weather prediction (NWP

  10. Forecasting sudden changes in environmental pollution patterns

    E-Print Network [OSTI]

    Olascoaga, Maria Josefina

    Forecasting sudden changes in environmental pollution patterns María J. Olascoagaa,1 and George of Mexico in 2010. We present a methodology to predict major short-term changes in en- vironmental River's mouth in the Gulf of Mexico. The resulting fire could not be extinguished and the drilling rig

  11. New Concepts in Wind Power Forecasting Models

    E-Print Network [OSTI]

    Kemner, Ken

    New Concepts in Wind Power Forecasting Models Vladimiro Miranda, Ricardo Bessa, João Gama, Guenter to the training of mappers such as neural networks to perform wind power prediction as a function of wind characteristics (mainly speed and direction) in wind parks connected to a power grid. Renyi's Entropy is combined

  12. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand, EndUser Natural Gas Demand, and Energy Efficiency DECEMBER 2013 CEC2002013004SFV1 CALIFORNIA and expertise of numerous California Energy Commission staff members in the Demand Analysis Office. In addition

  13. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    NONE

    1996-08-01T23:59:59.000Z

    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.

  14. Forecast Technical Document Felling and Removals

    E-Print Network [OSTI]

    of local investment and business planning. Timber volume production will be estimated at sub. Planning of operations. Control of the growing stock. Wider reporting (under UKWAS). The calculation fellings and removals are handled in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan

  15. Forecasting Turbulent Modes with Nonparametric Diffusion Models

    E-Print Network [OSTI]

    Tyrus Berry; John Harlim

    2015-01-27T23:59:59.000Z

    This paper presents a nonparametric diffusion modeling approach for forecasting partially observed noisy turbulent modes. The proposed forecast model uses a basis of smooth functions (constructed with the diffusion maps algorithm) to represent probability densities, so that the forecast model becomes a linear map in this basis. We estimate this linear map by exploiting a previously established rigorous connection between the discrete time shift map and the semi-group solution associated to the backward Kolmogorov equation. In order to smooth the noisy data, we apply diffusion maps to a delay embedding of the noisy data, which also helps to account for the interactions between the observed and unobserved modes. We show that this delay embedding biases the geometry of the data in a way which extracts the most predictable component of the dynamics. The resulting model approximates the semigroup solutions of the generator of the underlying dynamics in the limit of large data and in the observation noise limit. We will show numerical examples on a wide-range of well-studied turbulent modes, including the Fourier modes of the energy conserving Truncated Burgers-Hopf (TBH) model, the Lorenz-96 model in weakly chaotic to fully turbulent regimes, and the barotropic modes of a quasi-geostrophic model with baroclinic instabilities. In these examples, forecasting skills of the nonparametric diffusion model are compared to a wide-range of stochastic parametric modeling approaches, which account for the nonlinear interactions between the observed and unobserved modes with white and colored noises.

  16. Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price forecast of the Fifth Northwest Power

    E-Print Network [OSTI]

    Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price as traded on the wholesale, short-term (spot) market at the Mid-Columbia trading hub. This price represents noted. BASE CASE FORECAST The base case wholesale electricity price forecast uses the Council's medium

  17. Ris Energy Report 5 Wind 2 In the past 20 years wind energy has proved itself as a

    E-Print Network [OSTI]

    Risø Energy Report 5 Wind 2 6.1 Status In the past 20 years wind energy has proved itself all these achievements, wind energy remains on the fringes of power generation. For people working ignorance and emo- tional opposition. Wind energy is far from having been proved to lay people, large

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

    SciTech Connect (OSTI)

    He, D.; Wang, M.

    2000-12-12T23:59:59.000Z

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

  19. On-Road Remote Sensing of Automobile Emissions in the Denver Area: Year 2

    E-Print Network [OSTI]

    Denver, University of

    oxygen not involved in combustion. Mass emissions per mass or volume of fuel can also be determined and NO to CO2 in motor vehicle exhaust. From these ratios, we calculate the percent concentrations of CO, CO2 valid measurements for at least CO and CO2, and 22,867 records contained valid measurements for HC

  20. Operational forecasting based on a modified Weather Research and Forecasting model

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18T23:59:59.000Z

    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. Forecastability as a Design Criterion in Wind Resource Assessment: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Mather, B.; Neal, R.

    2012-08-01T23:59:59.000Z

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

  3. Energy Department's Texas Pantex Plant to Save Over $2 Million Per Year

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011AT&T,OfficeEnd of Year 2010 SNFEnergy Policy Act of 2005and Money | Department

  4. Fiscal Year 2013 Phase II (Release 2) Awardee List | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page onYouTube YouTube Note: Since the YouTube|6721Energy 3_adv_battery.pdfFerrinMarketAugustShipmentFiscal Year 2013 Phase

  5. Steam System Forecasting and Management 

    E-Print Network [OSTI]

    Mongrue, D. M.; Wittke, D. O.

    1982-01-01T23:59:59.000Z

    process unit is not operating (down) is specified. If the process will be operating for the entire period, the word "LP" is displayed. PRODUCTION SCHEDULE 2/20/92 - 5/20/82 UNIT 1 A UP 2 B UP D 2./20-3./15 D 4.19. TO- 3 C D 2./20-3./15 D 4..../9. TO- 4 D 5 E D 4./15 TO- UP 6 F D 2./20-2./21 7 G UP 9 I UP 8 H D 2./20-3./13 D 3./27 TO- 10 J 11 K D 2./20 TO- 12 L UP 13 M UP UP 15 0 14 N UP D 2./20-2./24 D 3./7.-3./17 D 3./28 TO- 16 P 17 G D 4./1. TO- 19 R II 3...

  6. Solar buildings program summary: Volume 2: Research summaries, fiscal year 1988

    SciTech Connect (OSTI)

    Not Available

    1989-04-01T23:59:59.000Z

    The US Department of Energy's (DOE) Solar Buildings Technology Program was initiated in 1975 to provide focus, direction, and funding for the development of solar technologies for buildings as an energy option for the United States. The program's progress has been impressive: active solar water and passive space heating systems are now widely available and have operated reliably throughout the United States. The efficiency of flat-plate collectors has increased 35%, and the incidence of system problems has decreased markedly. Whereas design tools for passive solar homes were once unavailable. DOE-sponsored research has led to the development of widely accepted guidelines, suitable for designing passive solar homes for any region of the country. Under DOE sponsorship, researchers have developed new window glazing materials such as low-emissivity films that significantly reduce heat loss over standard windows. Proven strategies also have been developed for using daylight to provide 50% of the lighting needs for small nonresidential buildings, substantially reducing electricity and cooling requirements. The Solar Buildings Technology Program Summary, Fiscal Year 1988 is a two-volume reference set describing the technological advances and future research and development (R and D) directions of the Solar Buildings Technology Program for the Fiscal Year 1988 (October 1, 1987 through September 30, 1988).

  7. Engineering Tripos Part IB SECOND YEAR Part IB Paper 8: -ELECTIVE (2)

    E-Print Network [OSTI]

    Talbot, James P.

    FOR RENEWABLE ENERGY SYSTEMS Examples Paper 2 ­ Wind Turbines: Materials, Mechanics and Electrical Power All noise issues can affect wind turbine installations. Materials 2. (a) Discuss the importance of materials choice in wind turbine blade and tower design. (b) Consider a series of self-similar blades in which

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

    SciTech Connect (OSTI)

    Fisher, Christopher (Colville Confederated Tribes, Omak Community Center, Omak, WA); Machin, Deanna; Wright, Howie (Okanagan National Fisheries Commission, Westbank, BC, Canada)

    2002-04-01T23:59:59.000Z

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

  9. Traffic congestion forecasting model for the INFORM System. Final report

    SciTech Connect (OSTI)

    Azarm, A.; Mughabghab, S.; Stock, D.

    1995-05-01T23:59:59.000Z

    This report describes a computerized traffic forecasting model, developed by Brookhaven National Laboratory (BNL) for a portion of the Long Island INFORM Traffic Corridor. The model has gone through a testing phase, and currently is able to make accurate traffic predictions up to one hour forward in time. The model will eventually take on-line traffic data from the INFORM system roadway sensors and make projections as to future traffic patterns, thus allowing operators at the New York State Department of Transportation (D.O.T.) INFORM Traffic Management Center to more optimally manage traffic. It can also form the basis of a travel information system. The BNL computer model developed for this project is called ATOP for Advanced Traffic Occupancy Prediction. The various modules of the ATOP computer code are currently written in Fortran and run on PC computers (pentium machine) faster than real time for the section of the INFORM corridor under study. The following summarizes the various routines currently contained in the ATOP code: Statistical forecasting of traffic flow and occupancy using historical data for similar days and time (long term knowledge), and the recent information from the past hour (short term knowledge). Estimation of the empirical relationships between traffic flow and occupancy using long and short term information. Mechanistic interpolation using macroscopic traffic models and based on the traffic flow and occupancy forecasted (item-1), and the empirical relationships (item-2) for the specific highway configuration at the time of simulation (construction, lane closure, etc.). Statistical routine for detection and classification of anomalies and their impact on the highway capacity which are fed back to previous items.

  10. Wadter Resources Data Ohio: Water year 1994. Volume 2, St. Lawrence River Basin and Statewide Project Data

    SciTech Connect (OSTI)

    NONE

    1994-12-31T23:59:59.000Z

    The Water Resources Division of the US Geological Survey (USGS), in cooperation with State agencies, obtains a large amount of data each water year (a water year is the 12-month period from October 1 through September 30 and is identified by the calendar year in which it ends) pertaining to the water resources of Ohio. These data, accumulated during many years, constitute a valuable data base for developing an improved understanding of the water resources of the State. To make these data readily available to interested parties outside the USGS, they are published annually in this report series entitled ``Water Resources Data--Ohio.`` This report (in two volumes) includes records on surface water and ground water in the State. Specifically, it contains: (1) Discharge records for streamflow-gaging stations, miscellaneous sites, and crest-stage stations; (2) stage and content records for streams, lakes, and reservoirs; (3) water-quality data for streamflow-gaging stations, wells, synaptic sites, and partial-record sites; and (4) water-level data for observation wells. Locations of lake- and streamflow-gaging stations, water-quality stations, and observation wells for which data are presented in this volume are shown in figures ga through 8b. The data in this report represent that part of the National Water Data System collected by the USGS and cooperating State and Federal agencies in Ohio. This series of annual reports for Ohio began with the 1961 water year with a report that contained only data relating to the quantities of surface water. For the 1964 water year, a similar report was introduced that contained only data relating to water quality. Beginning with the 1975 water year, the report was changed to present (in two to three volumes) data on quantities of surface water, quality of surface and ground water, and ground-water levels.

  11. Union Carbides Last 20 Years in Oak Ridge ? part 2

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

    until finally shut down in 1987. (Rosenthal). 1962. A chemical explosion at the Paducah Gaseous Diffusion Plant resulted in a fire with damages estimated at 2 million. 1963. The...

  12. Engineering Tripos Part IB SECOND YEAR Part IB Paper 8: -ELECTIVE (2)

    E-Print Network [OSTI]

    Talbot, James P.

    .5 ­ 70.2 1440 Aluminium alloy 184 ­ 203 2700 Silicone rubber 152 ­ 168 1550 Table 1: Data from CES (a) Estimate the total mass of glass, PVC, aluminium alloy and silicone rubber in the complete set of double

  13. Test application of a semi-objective approach to wind forecasting for wind energy applications

    SciTech Connect (OSTI)

    Wegley, H.L.; Formica, W.J.

    1983-07-01T23:59:59.000Z

    The test application of the semi-objective (S-O) wind forecasting technique at three locations is described. The forecasting sites are described as well as site-specific forecasting procedures. Verification of the S-O wind forecasts is presented, and the observed verification results are interpreted. Comparisons are made between S-O wind forecasting accuracy and that of two previous forecasting efforts that used subjective wind forecasts and model output statistics. (LEW)

  14. Effects of compensatory growth on muscle characteristics in 2 year-old beef steers

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    3700 pm2 vs 4868 pm2). At slaughter at the end of finishing period, animals of C and CG groups (415, in metabolic activities (138 and 133 nkat/g for LDH ; 0.155 and 0.147 nkat/g for ICDH in ST), in percentages of fiber types (15 and 16 % type 1, 29 and 30 % type IIA, 56 and 54 % type IIB) and in fiber areas (4906 pm

  15. CO2 stimulation of photosynthesis is not sustained during long-term (12 years) FACE treatments in Liquidambar styraciflua

    SciTech Connect (OSTI)

    Warren, Jeffrey [ORNL; Jensen, Anna M [ORNL; Medlyn, Belinda [Macquarie University; Norby, Richard J [ORNL; Tissue, David Thomas [ORNL

    2015-01-01T23:59:59.000Z

    Elevated atmospheric CO2 (eCO2) often increases photosynthetic CO2 assimilation (A) in field studies of temperate tree species, although there is evidence that the increases may decline through time due to biochemical and morphological acclimation, and environmental constraints. Indeed, at the free air CO2 enrichment (FACE) study in Oak Ridge, Tennessee, A was increased in 12-year-old sweetgum trees following two years of ~40% enhancement of CO2. A was re-assessed a decade later to determine if initial enhancement of CO2 was sustained through time. Measurements were conducted at prevailing CO2 and temperature on detached, re-hydrated branches using a portable gas exchange system. Photosynthetic CO2 response curves (A-Ci curves) were contrasted with earlier measurements using consistent leaf photosynthesis model equations. Relationships between maximum electron transport rate (Jmax), maximum Rubisco activity (Vcmax) and foliar nitrogen (N) and chlorophyll content were assessed. In 1999, light-saturated photosynthesis (Asat) for eCO2 treatments was 15.4 0.8 mol m-2 s-1, 22% higher than aCO2 treatments (P<0.01). By 2009, Asat declined to <50% of 1999 values, and there was no longer a significant effect of eCO2 (Asat = 6.9 or 5.7 0.7 mol m-2 s-1 for eCO2 or aCO2, respectively). In 1999, there was no treatment effect on area-based foliar N; however, by 2008, N content in eCO2 foliage was 17% less than in aCO2 foliage. Photosynthetic N use efficiency (Asat:N) was greater in eCO2 in 1999 resulting in greater Asat despite similar N content, but the enhanced efficiency in eCO2 trees was lost as foliar N declined to sub-optimal levels. There was no treatment difference in the declining linear relationships between Jmax or Vcmax with declining N, or in the ratio of Jmax:Vcmax through time. Results suggest that initial enhancement of photosynthesis to elevated CO2 will not be sustained through time if nitrogen becomes limited.

  16. SN 2009ip at late times - an interacting transient at +2 years

    E-Print Network [OSTI]

    Fraser, Morgan; Pastorello, Andrea; Jerkstrand, Anders; Smartt, Stephen J; Chen, Ting-Wan; Childress, Michael; Gilmore, Gerard; Inserra, Cosimo; Kankare, Erkki; Margheim, Steve; Mattila, Seppo; Valenti, Stefano; Ashall, Christopher; Benetti, Stefano; Botticella, Maria Teresa; Bauer, Franz Erik; Campbell, Heather; Elias-Rosa, Nancy; Fleury, Mathilde; Gal-Yam, Avishay; Hachinger, Stephan; Howell, D Andrew; Guillou, Laurent Le; Léget, Pierre-François; Morales-Garoffolo, Antonia; Polshaw, Joe; Spiro, Susanna; Sullivan, Mark; Taubenberger, Stefan; Turatto, Massimo; Walker, Emma S; Young, David R; Zhang, Bonnie

    2015-01-01T23:59:59.000Z

    We present photometric and spectroscopic observations of the interacting transient SN 2009ip taken during the 2013 and 2014 observing seasons. We characterise the photometric evolution as a steady and smooth decline in all bands, with a decline rate that is slower than expected for a solely $^{56}$Co-powered supernova at late phases. No further outbursts or eruptions were seen over a two year period from 2012 December until 2014 December. SN 2009ip remains brighter than its historic minimum from pre-discovery images. Spectroscopically, SN 2009ip continues to be dominated by strong, narrow ($\\lesssim$2000 km~s$^{-1}$) emission lines of H, He, Ca, and Fe. While we make tenuous detections of [Fe~{\\sc ii}] $\\lambda$7155 and [O~{\\sc i}] $\\lambda\\lambda$6300,6364 lines at the end of 2013 June and the start of 2013 October respectively, we see no strong broad nebular emission lines that could point to a core-collapse origin. In general, the lines appear relatively symmetric, with the exception of our final spectrum ...

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

    SciTech Connect (OSTI)

    Eisenberg, Joel F. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2005-10-31T23:59:59.000Z

    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.

  18. European Wind Energy Conference -Brussels, Belgium, April 2008 Data mining for wind power forecasting

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    European Wind Energy Conference - Brussels, Belgium, April 2008 Data mining for wind power-term forecasting of wind energy produc- tion up to 2-3 days ahead is recognized as a major contribution the improvement of predic- tion systems performance is recognised as one of the priorities in wind energy research

  19. Multiagent Bayesian Forecasting of Structural Time-Invariant Dynamic Systems with

    E-Print Network [OSTI]

    Xiang, Yang

    . Alternatively, time series are represented by state-space models, also referred to as multivariate dynamic and science. We study forecasting of stochastic, dynamic systems based on observations from multivariate time to a discrete time, multivariate time series [1, 2]. The primary inference that we address is one- step

  20. Time series modeling and large scale global solar radiation forecasting from geostationary satellites data

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Time series modeling and large scale global solar radiation forecasting from geostationary global solar radiation. In this paper, we use geostationary satellites data to generate 2-D time series of solar radiation for the next hour. The results presented in this paper relate to a particular territory

  1. Gaussian Processes for Short-Horizon Wind Power Forecasting Joseph Bockhorst, Chris Barber

    E-Print Network [OSTI]

    Bockhorst, Joseph

    on this task, and attention has shifted to statistical and machine learning approaches. Among the challenges of wind energy into electrical trans- mission systems. The importance of wind forecasts for wind energy throughout a power system must be nearly in balance at all times, 2) because it depends strongly on wind

  2. Short-term Wind Power Forecasting Using Advanced Statistical T.S. Nielsen1

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    , in order to be able to absorb a large fraction of wind power in the electrical systems reliable short from refer- ence MET forecasts to the actual wind farm, wind farm power curve models, dynamical models of art wind power prediction system is outlined in Section 2. Numerical Weather Prediction (NWP

  3. Forecasting U.S. Hurricanes 6 Months in Advance James B. Elsner,1

    E-Print Network [OSTI]

    Elsner, James B.

    . A hurricane can make more than one landfall as hurricane Andrew did in striking southeast FloridaForecasting U.S. Hurricanes 6 Months in Advance James B. Elsner,1 Richard J. Murnane,2 Thomas H correspondence should be addressed; E-mail: jelsner@garnet.fsu.edu. [1] Hurricanes are a serious social

  4. Forecasting U.S. hurricanes 6 months in advance J. B. Elsner,1

    E-Print Network [OSTI]

    Elsner, James B.

    . A hurricane can make more than one landfall as hurricane Andrew did in striking southeast FloridaForecasting U.S. hurricanes 6 months in advance J. B. Elsner,1 R. J. Murnane,2 and T. H. Jagger1 is a grim reminder of the serious social and economic threat that hurricanes pose to the United States

  5. Using multi-layer models to forecast gas flow rates in tight gas reservoirs 

    E-Print Network [OSTI]

    Jerez Vera, Sergio Armando

    2007-04-25T23:59:59.000Z

    , and (2) to use the single-layer match to demonstrate the error that can occur when forecasting long-term gas production for such complex gas reservoirs. A finite-difference reservoir simulator was used to simulate gas production from various layered tight...

  6. Solar Power Forecasting at UC San Diego Jan Kleissl, Dept of Mechanical & Aerospace Engineering, UCSD

    E-Print Network [OSTI]

    Fainman, Yeshaiahu

    show 2 cloud layers. Vaisala Fig. 4: Observed solar power output (black line) and simulation (Fig. 4). Tier 3: Power output forecast As cloud related solar radiation reductions are observed algorithm to determine actual expected solar power output at each PV array over the hour ahead. #12;

  7. PHYSICAL REVIEW E 85, 056220 (2012) Forecasting synchronizability of complex networks from data

    E-Print Network [OSTI]

    Lai, Ying-Cheng

    2012-01-01T23:59:59.000Z

    PHYSICAL REVIEW E 85, 056220 (2012) Forecasting synchronizability of complex networks from data Ri-Qi Su,1 Xuan Ni,1 Wen-Xu Wang,1,2 and Ying-Cheng Lai1,3 1 School of Electrical, Computer, and Energy of Management and Center for Complexity Research, Beijing Normal University, Beijing 100875, China 3 Department

  8. Addressing model bias and uncertainty in three dimensional groundwater transport forecasts for a physical aquifer experiment

    E-Print Network [OSTI]

    Vermont, University of

    Addressing model bias and uncertainty in three dimensional groundwater transport forecasts, and D. M. Rizzo (2008), Addressing model bias and uncertainty in three dimensional groundwater transport. Introduction [2] Eigbe et al. [1998] provide an excellent review of groundwater applications of the linear

  9. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

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

    2014-12-30T23:59:59.000Z

    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.

  10. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

    Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J. (Decision and Information Sciences); (INESC Porto)

    2011-02-23T23:59:59.000Z

    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.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33Frequently20,000 Russian NuclearandJunetrack graphics4DimitriJune 30, 2015Vehicles|EcoCAR 2:

  12. 15 Years of Successful H2S Abatement | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcat 1 Wind Projectsource HistorykV remotea Responsible00260H2S

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742Energy Chinaof EnergyImpactOn July 2, 2014 in theGroup Report |ofM A N A G EAnticipation

  14. Forecasting Water Quality & Biodiversity

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't YourTransport inEnergy0.pdf Flash2010-60.pdf2 DOE Hydrogen andMeetingonup onFood7,2

  15. Making Fusion Power Work: Materials Blanket: 150 dpa/5 years, 2.5 MW/m2

    E-Print Network [OSTI]

    of nanometre scale Y2O3 particles: act as He, H sinks, strengthen, reduce creep. Currently only small ­ 2045? Full design and materials ­ 2030 ? ITER could act as test-bed from ~2025... It is nearly 2013 particles: act as He, H sinks, strengthen, reduce creep. Currently only small experimental batches made

  16. 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.

    2013-10-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13T23:59:59.000Z

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

  18. Forecasting model of the PEPCO service area economy. Volume 3

    SciTech Connect (OSTI)

    Not Available

    1984-03-01T23:59:59.000Z

    Volume III describes and documents the regional economic model of the PEPCO service area which was relied upon to develop many of the assumptions of future values of economic and demographic variables used in the forecast. The PEPCO area model is mathematically linked to the Wharton long-term forecast of the U.S. Volume III contains a technical discussion of the structure of the regional model and presents the regional economic forecast.

  19. Emissions Inventory Report Summary: Reporting Requirements for the New Mexico Administrative Code, Title 20, Chapter 2, Part 73 (20 NMAC 2.73) for Calendar Year 2001

    SciTech Connect (OSTI)

    Margorie Stockton

    2003-04-01T23:59:59.000Z

    Los Alamos National Laboratory is subject to annual emissions-reporting requirements for regulated air contaminants under Title 20 of the New Mexico Administrative Code, Chapter 2, Part 73 (20.2.73 NMAC), Notice of Intent and Emissions Inventory Requirements. The applicability of the requirements is based on the Laboratory's potential to emit 100 tons per year of suspended particulate matter, nitrogen oxides, carbon monoxide, sulfur oxides, or volatile organic compounds. For calendar year 2001, the Technical Area 3 steam plant was the primary source of criteria air pollutants from the Laboratory, while research and development activities were the primary source of volatile organic compounds. Emissions of beryllium and aluminum were reported for activities permitted under 20.2.72 NMAC. Hazardous air pollutant emissions from chemical use for research and development activities were also reported.

  20. Randomized Controlled Trial of Forward-Planned Intensity Modulated Radiotherapy for Early Breast Cancer: Interim Results at 2 Years

    SciTech Connect (OSTI)

    Barnett, Gillian C. [Department of Oncology, University of Cambridge, Cambridge University Hospitals, National Health Service Foundation Trust, Cambridge (United Kingdom); Wilkinson, Jennifer S.; Moody, Anne M.; Wilson, Charles B.; Twyman, Nicola [Oncology Centre, Cambridge University Hospitals, National Health Services Foundation Trust, Cambridge (United Kingdom); Wishart, Gordon C. [Cambridge Breast Unit, Addenbrooke's Hospital, Cambridge (United Kingdom); Burnet, Neil G. [Department of Oncology, University of Cambridge, Cambridge University Hospitals, National Health Service Foundation Trust, Cambridge (United Kingdom); Coles, Charlotte E., E-mail: charlotte.coles@addenbrookes.nhs.uk [Oncology Centre, Cambridge University Hospitals, National Health Services Foundation Trust, Cambridge (United Kingdom)

    2012-02-01T23:59:59.000Z

    Purpose: This single-center randomized trial was designed to investigate whether intensity-modulated radiotherapy (IMRT) reduces late toxicity in patients with early-stage breast cancer. Methods and Materials: The standard tangential plans of 1,145 nonselected patients were analyzed. The patients with inhomogeneous plans were randomized to a simple method of forward-planned IMRT or standard radiotherapy (RT). The primary endpoint was serial photographic assessment of breast shrinkage. Results: At 2 years, no significant difference was found in the development of any photographically assessed breast shrinkage between the patients randomized to the interventional or control group (odds ratio, 1.51; 95% confidence interval, 0.83-1.58; p = .41). The patients in the control group were more likely to develop telangiectasia than those in the IMRT group (odds ratio, 1.68; 95% confidence interval 1.13-2.40; p = .009). Poor baseline surgical cosmesis resulted in poor overall cosmesis at 2 years after RT. In patients who had good surgical cosmesis, those randomized to IMRT were less likely to deteriorate to a moderate or poor overall cosmesis than those in the control group (odds ratio, 0.63; 95% confidence interval, 0.39-1.03, p = .061). Conclusions: IMRT can lead to a significant reduction in telangiectasia at comparatively early follow-up of only 2 years after RT completion. An important component of breast induration and shrinkage will actually result from the surgery and not from the RT. Surgical cosmesis is an important determinant of overall cosmesis and could partially mask the longer term benefits of IMRT at this early stage.

  1. 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.

    2012-09-01T23:59:59.000Z

    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.

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

    Office of Environmental Management (EM)

    Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report.pdf More Documents & Publications Computational Advances in Applied...

  3. Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures

    E-Print Network [OSTI]

    Richard A. Berk; Brian Kriegler; Jong-Ho Baek

    2011-01-01T23:59:59.000Z

    Forecasting Dangerous Inmate Misconduct: An Applications ofof Term Length more dangerous than other inmates servingIV beds or moving less dangerous Level IV inmates to Level

  4. Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures

    E-Print Network [OSTI]

    Berk, Richard; Kriegler, Brian; Baek, Jong-Ho

    2005-01-01T23:59:59.000Z

    Forecasting Dangerous Inmate Misconduct: An Applications ofof Term Length more dangerous than other inmates servingIV beds or moving less dangerous Level IV inmates to Level

  5. Forecasting the underlying potential governing climatic time series

    E-Print Network [OSTI]

    Livina, V N; Mudelsee, M; Lenton, T M

    2012-01-01T23:59:59.000Z

    We introduce a technique of time series analysis, potential forecasting, which is based on dynamical propagation of the probability density of time series. We employ polynomial coefficients of the orthogonal approximation of the empirical probability distribution and extrapolate them in order to forecast the future probability distribution of data. The method is tested on artificial data, used for hindcasting observed climate data, and then applied to forecast Arctic sea-ice time series. The proposed methodology completes a framework for `potential analysis' of climatic tipping points which altogether serves anticipating, detecting and forecasting climate transitions and bifurcations using several independent techniques of time series analysis.

  6. Sandia National Laboratories: Solar Energy Forecasting and Resource...

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

    & Events, Partnership, Photovoltaic, Renewable Energy, Solar, Systems Analysis The book, Solar Energy Forecasting and Resource Assessment, provides an authoritative voice on the...

  7. analytical energy forecasting: Topics by E-print Network

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

    COMMISSION Tom Gorin Lynn Marshall Principal Author Tom Gorin Project 11 Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Computer Technologies and...

  8. Econometric model and futures markets commodity price forecasting

    E-Print Network [OSTI]

    Just, Richard E.; Rausser, Gordon C.

    1979-01-01T23:59:59.000Z

    Versus CCll1rnercial Econometric M:ldels." Uni- versity ofWorking Paper No. 72 ECONOMETRIC ! 'econometric forecasts with the futures

  9. Optimization Online - Data Assimilation in Weather Forecasting: A ...

    E-Print Network [OSTI]

    M. Fisher

    2007-02-14T23:59:59.000Z

    Feb 14, 2007 ... Data Assimilation in Weather Forecasting: A Case Study in PDE-Constrained Optimization. M. Fisher(Mike.Fisher ***at*** ecmwf.int)

  10. Weather-based yield forecasts developed for 12 California crops

    E-Print Network [OSTI]

    Lobell, David; Cahill, Kimberly Nicholas; Field, Christopher

    2006-01-01T23:59:59.000Z

    RESEARCH ARTICLE Weather-based yield forecasts developed fordepend largely on the weather, measurements from existingpredictions. We developed weather-based models of statewide

  11. Using Customers' Reported Forecasts to Predict Future Sales

    E-Print Network [OSTI]

    Gordon, Geoffrey J.

    Using Customers' Reported Forecasts to Predict Future Sales Nihat Altintas , Alan Montgomery , Michael Trick Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA 15213. nihat

  12. IMPROVED ANTIFOAM AGENT STUDY END OF YEAR REPORT, EM PROJECT 3.2.3

    SciTech Connect (OSTI)

    Lambert, D.; Koopman, D.; Newell, J.

    2011-09-30T23:59:59.000Z

    Antifoam 747 is added to minimize foam produced by process gases and water vapor during chemical processing of sludge in the Defense Waste Processing Facility (DWPF). This allows DWPF to maximize acid addition and evaporation rates to minimize the cycle time in the Chemical Processing Cell (CPC). Improvements in DWPF melt rate due to the addition of bubblers in the melter have resulted in the need for further reductions in cycle time in the CPC. This can only be accomplished with an effective antifoam agent. DWPF production was suspended on March 22, 2011 as the result of a Flammable Gas New Information/(NI) Potential Inadequacy in the Safety Analysis (PISA). The issue was that the DWPF melter offgas flammability strategy did not take into account the H and C in the antifoam, potentially flammable components, in the melter feed. It was also determined the DWPF was using much more antifoam than anticipated due to a combination of longer processing in the CPC due to high Hg, longer processing due to Actinide Removal Process (ARP)/Modular Caustic Side Solvent Extraction Unit (MCU) additions, and adding more antifoam than recommended. The resolution to the PISA involved and assessment of the impact of the antifoam on melter flammability and the implementation of a strategy to control additions within acceptable levels. This led to the need to minimize the use of Antifoam 747 in processing beginning in May 2011. DWPF has had limited success in using Antifoam 747 in caustic processing. Since starting up the ARP facility, the ARP product (similar chemically to caustic sludge) is added to the Sludge Receipt and Adjustment Tank (SRAT) at boiling and evaporated to maintain a constant SRAT volume. Although there is very little offgas generated during caustic boiling, there is a large volume of water vapor produced which can lead to foaming. High additions and more frequent use of antifoam are used to mitigate the foaming during caustic boiling. The result of these three issues above is that DWPF had three antifoam needs in FY2011: (1) Determine the cause of the poor Antifoam 747 performance during caustic boiling; (2) Determine the decomposition products of Antifoam 747 during CPC processing; and (3) Improve the effectiveness of Antifoam 747, in order to minimize the amount used. Testing was completed by Illinois Institute of Technology (IIT) and Savannah River National Laboratory (SRNL) researchers to address these questions. The testing results reported were funded by both DWPF and DOE/EM 31. Both sets of results are reported in this document for completeness. The results of this research are summarized: (1) The cause for the poor Antifoam 747 performance during caustic boiling was the high hydrolysis rate, cleaving the antifoam molecule in two, leading to poor antifoam performance. In testing with pH solutions from 1 to 13, the antifoam degraded quickly at a pH < 4 and pH > 10. As the antifoam decomposed it lost its spreading ability (wetting agent performance), which is crucial to its antifoaming performance. During testing of a caustic sludge simulants, there was more foam in tests with added Antifoam 747 than in tests without added antifoam. (2) Analyses were completed to determine the composition of the two antifoam components and Antifoam 747. In addition, the decomposition products of Antifoam 747 were determined during CPC processing of sludge simulants. The main decomposition products were identified primarily as Long Chain Siloxanes, boiling point > 400 C. Total antifoam recovery was 33% by mass. In a subsequent study, various compounds potentially related to antifoam were found using semi-volatile organic analysis and volatile organic analysis on the hexane extractions and hexane rinses. These included siloxanes, trimethyl silanol, methoxy trimethyl silane, hexamethyl disiloxane, aliphatic hydrocarbons, dioctyl phthalate, and emulsifiers. Cumulatively, these species amounted to less than 3% of the antifoam mass. The majority of the antifoam was identified using carbon analysis of the SRAT product (40-80% by ma

  13. Fallout forecasting: 1945-1962

    SciTech Connect (OSTI)

    Kennedy, W.R. Jr.

    1986-03-01T23:59:59.000Z

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

  14. Solar Forecasting | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn'tOriginEducationVideo »UsageSecretary ofSmallConfidential,2 Solar BackgroundWakePowersSystems

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06T23:59:59.000Z

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

  16. Reducing the demand forecast error due to the bullwhip effect in the computer processor industry

    E-Print Network [OSTI]

    Smith, Emily (Emily C.)

    2010-01-01T23:59:59.000Z

    Intel's current demand-forecasting processes rely on customers' demand forecasts. Customers do not revise demand forecasts as demand decreases until the last minute. Intel's current demand models provide little guidance ...

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

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    of two methods to forecast natural gas prices: using theof two methods to forecast natural gas prices is performed:accurate average forecast of natural gas prices than the

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01T23:59:59.000Z

    Gas Price Forecast With natural gas prices significantlyto the EIA’s natural gas price forecasts in AEO 2004 and AEOon the AEO 2005 natural gas price forecasts will likely once

  19. Evaluation of forecasting techniques for short-term demand of air transportation

    E-Print Network [OSTI]

    Wickham, Richard Robert

    1995-01-01T23:59:59.000Z

    Forecasting is arguably the most critical component of airline management. Essentially, airlines forecast demand to plan the supply of services to respond to that demand. Forecasts of short-term demand facilitate tactical ...

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01T23:59:59.000Z

    revisions to the EIA’s natural gas price forecasts in AEOsolely on the AEO 2005 natural gas price forecasts willComparison of AEO 2005 Natural Gas Price Forecast to NYMEX

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01T23:59:59.000Z

    to estimate the base-case natural gas price forecast, but toComparison of AEO 2010 Natural Gas Price Forecast to NYMEXs reference-case long-term natural gas price forecasts from

  2. LANL JOWOG 31 2012 Forecast

    SciTech Connect (OSTI)

    Vidlak, Anton J. II [Los Alamos National Laboratory

    2012-08-08T23:59:59.000Z

    Joint Working Group (JOWOG) 31, Nuclear Weapons Engineering, has a particularly broad scope of activities within its charter which emphasizes systems engineering. JOWOG 31 brings together experts from AWE and the national laboratories to address engineering issues associated with warhead design and certification. Some of the key areas of interaction, as addressed by the HOCWOGs are: (1) Engineering Analysis, (2) Hydrodynamic Testing, (3) Environmental Testing, and (4) Model Based Integrated Toolkit (MBIT). Gas Transfer Systems and Condition Monitoring interaction has been moved back to JOWOG 31. The regularly scheduled JOWOG 31 activities are the General Sessions, Executive Sessions, Focused Exchanges and HOCWOGs. General Sessions are scheduled every 12-18 months and are supported by the four design laboratories (AWE, LANL, LLNL, and SNL). Beneficial in educating the next generation of weapons engineers and establishing contacts between AWE and the US laboratory personnel. General Sessions are based on a blend of presentations and workshops centered on various themed subjects directly related to Stockpile Stewardship. HOCWOG meetings are more narrowly focused than the General Sessions. They feature presentations by experts in the field with a greater emphasis on round table discussions. Typically about 20 people attend. Focused exchanges are generally the result of interactions within JOWOG general sessions or HOCWOG meetings. They generally span a very specific topic of current interest within the US and UK.

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

    SciTech Connect (OSTI)

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

    2010-08-24T23:59:59.000Z

    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?

  4. Renewable Forecast Min-Max2020.xls

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's PossibleRadiation Protection Technical s o Freiberge s 3 c/)RenewableRenewable EnergyForecast of

  5. Forecast and Funding Arrangements - Hanford Site

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC) Environmental Assessments (EA)Budget(DANCE) Target 1Annual Waste Forecast and Funding

  6. Make Model SPECS ACURA ILX (Model Year 2013) 2.0L 4, auto stk [P] ULEV II / Bin 5 45

    E-Print Network [OSTI]

    II / Bin 5 42 BMW 328i (Model Year 2013) 2.0L 4, auto stk [P] Bin 5 / ULEV II 42 BMW 328i (Model Year 2013) 2.0L 4, manual [P] ULEV II / Bin 5 43 BMW 328i XDRIVE (Model Year 2013) 2.0L 4, auto stk Awd [P] ULEV II / Bin 5 41 BMW 335i (Model Year 2013) 3.0L 6, auto stk [P] ULEV II / Bin 5 41 BMW 528i (Model

  7. 2007 Wholesale Power Rate Case Final Proposal : Market Price Forecast Study.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    2006-07-01T23:59:59.000Z

    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.

  8. 2007 Wholesale Power Rate Case Initial Proposal : Market Price Forecast Study.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    2005-11-01T23:59:59.000Z

    This chapter presents BPA's market price forecasts, 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 rates. AURORA is used as the primary tool for (a) calculation of the demand rate, (b) shaping the PF rate, (c) estimating the forward price for the IOU REP settlement benefits calculation for fiscal years 2008 and 2009, (d) estimating the uncertainty surrounding DSI payments, (e) informing the secondary revenue forecast and (f) providing a price input used for the risk analysis.

  9. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

    to  predict daily solar radiation.   Agriculture and Forest and Chuo, S.   2008.  Solar radiation forecasting using Short?term forecasting of solar radiation:   A statistical 

  10. Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA

    SciTech Connect (OSTI)

    Hou, Zhangshuan; Etingov, Pavel V.; Makarov, Yuri V.; Samaan, Nader A.

    2014-10-27T23:59:59.000Z

    In this paper, we introduce a new approach without implying normal distributions and stationarity of power generation forecast errors. In addition, it is desired to more accurately quantify the forecast uncertainty by reducing prediction intervals of forecasts. We use automatically coupled wavelet transform and autoregressive integrated moving-average (ARIMA) forecasting to reflect multi-scale variability of forecast errors. The proposed analysis reveals slow-changing “quasi-deterministic” components of forecast errors. This helps improve forecasts produced by other means, e.g., using weather-based models, and reduce forecast errors prediction intervals.

  11. Table HIST002R_2. Death rates for 113 selected causes by 5-year age groups, race and sex: United States, 1979-98

    E-Print Network [OSTI]

    Hunter, David

    _2. Death rates for 113 selected causes, by 5-year age groups, race and sex: United States, 1979Table HIST002R_2. Death rates for 113 selected causes by 5-year age groups, race and sex: United though the cause-of-death titles may be the same. Deaths rates are per 100,000 population in specified

  12. Short term forecasting of solar radiation based on satellite data

    E-Print Network [OSTI]

    Heinemann, Detlev

    Short term forecasting of solar radiation based on satellite data Elke Lorenz, Annette Hammer University, D-26111 Oldenburg Forecasting of solar irradiance will become a major issue in the future integration of solar energy resources into existing energy supply structures. Fluctuations of solar irradiance

  13. Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center

    E-Print Network [OSTI]

    Washington at Seattle, University of

    Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime meteorological data from sites upwind of wind farms can be efficiently used to improve short-term forecasts acknowledges the support of PPM Energy, Inc. The data used in this work were obtained from Oregon State

  14. Revised 1997 Retail Electricity Price Forecast Principal Author: Ben Arikawa

    E-Print Network [OSTI]

    Revised 1997 Retail Electricity Price Forecast March 1998 Principal Author: Ben Arikawa Electricity 1997 FORE08.DOC Page 1 CALIFORNIA ENERGY COMMISSION ELECTRICITY ANALYSIS OFFICE REVISED 1997 RETAIL ELECTRICITY PRICE FORECAST Introduction The Electricity Analysis Office of the California Energy Commission

  15. A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size

    E-Print Network [OSTI]

    Hansens, Jim

    A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size Andrew. R.Lawrence@ecmwf.int #12;Abstract An ensemble-based data assimilation approach is used to transform old en- semble. The impact of the transformations are propagated for- ward in time over the ensemble's forecast period

  16. Introducing the Canadian Crop Yield Forecaster Aston Chipanshi1

    E-Print Network [OSTI]

    Miami, University of

    for crop yield forecasting and risk analysis. Using the Census Agriculture Region (CAR) as the unit Climate Decision Support and Adaptation, Agriculture and Agri-Food Canada, 1011, Innovation Blvd, Saskatoon, SK S7V 1B7, Canada The Canadian Crop Yield Forecaster (CCYF) is a statistical modelling tool

  17. Wind-Wave Probabilistic Forecasting based on Ensemble

    E-Print Network [OSTI]

    have to be jointly taken into account in some decision-making problems, e.g. offshore wind farmWind-Wave Probabilistic Forecasting based on Ensemble Predictions Maxime FORTIN Kongens Lyngby 2012.imm.dtu.dk IMM-PhD-2012-86 #12;Summary Wind and wave forecasts are of a crucial importance for a number

  18. PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022

    E-Print Network [OSTI]

    PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022 AUGUST 2011 CEC-200-2011-011-SD CALIFORNIA for electric vehicles. #12;ii #12;iii ABSTRACT The Preliminary California Energy Demand Forecast 2012 includes three full scenarios: a high energy demand case, a low energy demand case, and a mid energy demand

  19. CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST Manager Kae Lewis Acting Manager Demand Analysis Office Valerie T. Hall Deputy Director Energy Efficiency Demand Forecast report is the product of the efforts of many current and former California Energy

  20. Distribution Based Data Filtering for Financial Time Series Forecasting

    E-Print Network [OSTI]

    Bailey, James

    recent past. In this paper, we address the challenge of forecasting the behavior of time series using@unimelb.edu.au Abstract. Changes in the distribution of financial time series, particularly stock market prices, can of stock prices, which aims to forecast the future values of the price of a stock, in order to obtain

  1. Managing Wind Power Forecast Uncertainty in Electric Brandon Keith Mauch

    E-Print Network [OSTI]

    i Managing Wind Power Forecast Uncertainty in Electric Grids Brandon Keith Mauch Co for the modeled wind- CAES system would not cover annualized capital costs. We also estimate market prices-ahead market is roughly $100, with large variability due to electric power prices. Wind power forecast errors

  2. Draft for Public Comment Appendix A. Demand Forecast

    E-Print Network [OSTI]

    in the planning process. Electricity demand is forecast to grow from 20,080 average megawatts in 2000 to 25 forecast of electricity demand is a required component of the Council's Northwest Regional Conservation and Electric Power Plan.1 Understanding growth in electricity demand is, of course, crucial to determining

  3. FORECASTING WATER DEMAND USING CLUSTER AND REGRESSION ANALYSIS

    E-Print Network [OSTI]

    Keller, Arturo A.

    resources resulting in water stress. Effective water management ­ a solution Supply side management Demand side management #12;Developing a regression equation based on cluster analysis for forecasting waterFORECASTING WATER DEMAND USING CLUSTER AND REGRESSION ANALYSIS by Bruce Bishop Professor of Civil

  4. Forecasting Uncertainty Related to Ramps of Wind Power Production

    E-Print Network [OSTI]

    Boyer, Edmond

    - namic reserve quantification [8], for the optimal oper- ation of combined wind-hydro power plants [5, 1Forecasting Uncertainty Related to Ramps of Wind Power Production Arthur Bossavy, Robin Girard - The continuous improvement of the accuracy of wind power forecasts is motivated by the increasing wind power

  5. Impact of PV forecasts uncertainty in batteries management in microgrids

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    -- Photovoltaic systems, Batteries, Forecasting I. INTRODUCTION This paper presents first results of a study Energies and Energy Systems Sophia Antipolis, France andrea.michiorri@mines-paristech.fr Abstract production forecast algorithm is used in combination with a battery schedule optimisation algorithm. The size

  6. Forecasting Building Occupancy Using Sensor Network James Howard

    E-Print Network [OSTI]

    Hoff, William A.

    of the forecasting algorithm for the different conditions. 1. INTRODUCTION According to the U.S. Department of Energy could take advantage of times when electricity cost is lower, to chill a cold water storage tankForecasting Building Occupancy Using Sensor Network Data James Howard Colorado School of Mines

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

    SciTech Connect (OSTI)

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

    2012-07-01T23:59:59.000Z

    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.

  8. 010-2 s0-2 s2 012 Two Year Course Schedule for Graduate Program012 Two Year Course Schedule for Graduate Program 2010-11GRADUATE PROGRAM

    E-Print Network [OSTI]

    Carter, John

    558/FBI Practicum (FBI Representatives) (E) F 9:00-5:00PM (2 sessions only -- Jan 21 and Jan 28) CRJS

  9. Emissions Inventory Report Summary: Reporting Requirements for the New Mexico Administrative Code, Title 20, Chapter 2, Part 73 (20.2.73 NMAC) for Calendar Year 2003

    SciTech Connect (OSTI)

    M. Stockton

    2005-01-01T23:59:59.000Z

    Los Alamos National Laboratory is subject to annual emissions-reporting requirements for regulated air pollutants under Title 20 of the New Mexico Administrative Code, Chapter 2, Part 73 (20.2.73 NMAC), Notice of Intent and Emissions Inventory Requirements. The applicability of the requirements is based on the Laboratory's potential to emit 100 tons per year of suspended particulate matter, nitrogen oxides, carbon monoxide, sulfur oxides, or volatile organic compounds. For calendar year 2003, the Technical Area 3 steam plant and the air curtain destructors were the primary sources of criteria air pollutants from the Laboratory, while the air curtain destructors and chemical use associated with research and development activities were the primary sources of volatile organic compounds and hazardous air pollutants. Emissions of beryllium and aluminum were reported for activities permitted under 20.2.72 NMAC. Hazardous air pollutant emissions were reported from chemical use as well as from all combustion sources. In addition, estimates of particulate matter with diameter less than 2.5 micrometers and ammonia were provided as requested by the New Mexico Environment Department, Air Quality Bureau.

  10. NatioNal aNd Global Forecasts West VirGiNia ProFiles aNd Forecasts

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    · NatioNal aNd Global Forecasts · West VirGiNia ProFiles aNd Forecasts · eNerGy · Healt Global Insight, paid for by the West Virginia Department of Revenue. 2013 WEST VIRGINIA ECONOMIC OUTLOOKWest Virginia Economic Outlook 2013 is published by: Bureau of Business & Economic Research West

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2008-01-07T23:59:59.000Z

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

  13. Taking out 1 billion tons of CO2: The magic of China's 11th Five-Year Plan?

    SciTech Connect (OSTI)

    Zhou, Nan; Lin, Jiang; Zhou, Nan; Levine, Mark; Fridley, David

    2007-07-01T23:59:59.000Z

    China's 11th Five-Year Plan (FYP) sets an ambitious target for energy-efficiency improvement: energy intensity of the country's gross domestic product (GDP) should be reduced by 20% from 2005 to 2010 (NDRC, 2006). This is the first time that a quantitative and binding target has been set for energy efficiency, and signals a major shift in China's strategic thinking about its long-term economic and energy development. The 20% energy intensity target also translates into an annual reduction of over 1.5 billion tons of CO2 by 2010, making the Chinese effort one of most significant carbon mitigation effort in the world today. While it is still too early to tell whether China will achieve this target, this paper attempts to understand the trend in energy intensity in China and to explore a variety of options toward meeting the 20% target using a detailed end-use energy model.

  14. Emissions Inventory Report Summary: Reporting Requirements for the New Mexico Administrative code, Title 20, Chapter 2, Part 73 (20 NMAC 2.73) for Calendar Year 1997

    SciTech Connect (OSTI)

    NONE

    1999-01-01T23:59:59.000Z

    Los Alamos National Laboratory (the Laboratory) is subject to emissions reporting requirements for regulated air contaminants under Title 20 of the New Mexico Administrative Code, Chapter 2, Part 73, (20 NMAC 2.73), Notice of Intent and Emissions Inventory Requirements. The Laboratory has the potential to emit 100 tons per year of suspended particulate matter (PM), nitrogen oxides (NO{sub x}), carbon monoxide (CO), and volatile organic compounds (VOCs). For 1997, combustion products from the industrial sources contributed the greatest amount of regulated air emissions from the Laboratory. Research and development activities contributed the greatest amount of VOCs. Emissions of beryllium and aluminum were reported for activities permitted under 20 NMAC 2.72, Construction Permits.

  15. Emissions Inventory Report Summary Reporting Requirements for the New Mexico Administrative Code, Title 20, Chapter 2, Part 73 (20 NMAC 2.73) for Calendar Year 1998

    SciTech Connect (OSTI)

    Air Quality Group, ESH-17

    1999-09-01T23:59:59.000Z

    Los Alamos National Laboratory (the Laboratory) is subject to emissions reporting requirements for regulated air contaminants under Title 20 of the New Mexico Administrative Code, Chapter 2, Part 73 (20 NMAC 2.73), Notice of Intent and Emissions Inventory Requirements. The Laboratory has the potential to emit 100 tons per year of suspended particulate matter, nitrogen oxides, carbon monoxide, sulfur oxides, and volatile organic compounds. For 1998, combustion products from the industrial sources contributed the greatest amount of criteria air pollutants from the Laboratory. Research and development activities contributed the greatest amount of volatile organic compounds. Emissions of beryllium and aluminum were reported for activities permitted under 20 NMAC 2.72 Construction Permits.

  16. Infall Motions in Massive Star-Forming Regions: Results from Years 1 & 2 of the MALT90 Survey

    E-Print Network [OSTI]

    He, Yu-Xin; Esimbek, Jarken; Ji, Wei-Guang; Wu, Gang; Tang, Xin-Di; Yuan, Ye; Li, Da-Lei; Baan,; A, W

    2015-01-01T23:59:59.000Z

    Massive star-forming regions with observed infall motions are good sites for studying the birth of massive stars. In this paper, 405 compact sources have been extracted from the APEX Telescope Large Area Survey of the Galaxy (ATLASGAL) compact sources that also have been observed in the Millimetre Astronomy Legacy Team 90 GHz (MALT90) survey during Years 1 and 2. These observations are complemented with Spitzer GLIMPSE/MIPSGAL mid-IR survey data to help classify the elected star-forming clumps into three evolutionary stages: pre-stellar, proto-stellar and UCHII regions. The results suggest that 0.05 g cm$^{-2}$ is a reliable empirical lower bound for the clump surface densities required for massive-star formation to occur. The optically thick HCO$^{+}$(1-0) and HNC(1-0) lines, as well as the optically thin N$_{2}$H$^{+}$(1-0) line were used to search for infall motions toward these sources. By analyzing the asymmetries of the optically thick HCO$^{+}$(1-0) and HNC(1-0) lines and the mapping observations of HC...

  17. LNG to the year 2000

    SciTech Connect (OSTI)

    Davenport, S.T.

    1984-04-01T23:59:59.000Z

    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.

  18. Fiscal Year 2008 Phased Construction Completion Report for EU Z2-33 in Zone 2, East Tennessee Technology Park, Oak Ridge, Tennessee

    SciTech Connect (OSTI)

    Bechtel Jacobs

    2008-09-11T23:59:59.000Z

    The Record of Decision for Soil, Buried Waste, and Subsurface Structure Actions in Zone 2, East Tennessee Technology Park, Oak Ridge, Tennessee (DOE/OR/01-2161&D2) (Zone 2 ROD) acknowledged that most of the 800 acres in Zone 2 were contaminated, but that sufficient data to confirm the levels of contamination were lacking. The Zone 2 ROD further specified that a sampling strategy for filling the data gaps would be developed. The Remedial Design Report/Remedial Action Work Plan for Zone 2 Soils, Slabs, and Subsurface Structures, East Tennessee Technology Park, Oak Ridge, Tennessee (DOE/OR/01-2224&D3) (Zone 2 RDR/RAWP) defined the sampling strategy as the Dynamic Verification Strategy (DVS), generally following the approach used for characterization of the Zone 1 exposure units (EUs). The Zone 2 ROD divided the Zone 2 area into seven geographic areas and 44 EUs. To facilitate the data quality objectives (DQOs) of the DVS process, the Zone 2 RDR/RAWP regrouped the 44 EUs into 12 DQO scoping EU groups. These groups facilitated the DQO process by placing similar facilities and their support facilities together and allowing identification of data gaps. The EU groups were no longer pertinent after DQO planning was completed and characterization was conducted as areas became accessible. As the opportunity to complete characterization became available, the planned DVS program and remedial actions (RAs) were completed for EU Z2-33. Remedial action was also performed at two additional areas in adjacent EU Z2-42 because of their close proximity and similar nature to a small surface soil RA in EU Z2-33. Remedial actions for building slabs performed in EU Z2-33 during fiscal year (FY) 2007 were reported in the Fiscal Year 2007 Phased Construction Completion Report for the Zone 2 Soils, Slabs, and Subsurface Structures at East Tennessee Technology Park, Oak Ridge, Tennessee (DOE/OR/01-2723&D1). Recommended RAs for EU Z2-42 were described in the Fiscal Year 2006 Phased Construction Completion Report for the Zone 2 Soils, Slabs, and Subsurface Structures at East Tennessee Technology Park, Oak Ridge, Tennessee (DOE/OR/01-2317&D2). Remedial actions performed in the Balance of Site (BOS) Laboratory Area of EU Z2-33 and two small areas in EU Z2-42 are described in Sects. 5 through 10 of this Phased Construction Completion Report (PCCR). The purpose of this PCCR is to address the following: (1) Document DVS characterization results for EU Z2-33; (2) Describe and document the risk evaluation and determine if the EU meets the Zone 2 ROD requirements for unrestricted industrial use to 10 ft bgs; (3) Identify additional areas not defined in the Zone 2 ROD that require remediation based on the DVS evaluation results; and (4) Describe RAs performed in the EU Z2-33 BOS Laboratory Area and two small areas in EU Z2-42. Approximately 18 acres in EU Z2-33 are addressed in this PCCR. Based on the results of the DVS evaluation and RAs performed, all 18 acres are recommended for unrestricted industrial use to 10 ft bgs. Three Federal Facility Agreement sites are addressed and recommended for no further action within this acreage, including: (1) K-1004-L Recirculating Cooling Water Lines Leak Sites; (2) K-1044 Heavy Equipment Repair Shop; and (3) K-1015-A Laundry Pit. Remedial actions for EU Z2-33 were developed in response to DVS characterization results described in the EU Z2-33 Technical Memorandum (Appendix A) and to support reindustrialization of the East Tennessee Technology Park as a commercial industrial park. Remediation criteria were designed for the protection of a future industrial worker who normally would not have the potential for exposure to soil below 10ft bgs. Accordingly, the Zone 2 ROD required land use controls to prevent disturbance of soils below 10 ft deep and to restrict future land use to industrial/commercial activities. In response to stakeholder comments, the U.S. Department of Energy agreed to re-evaluate the need for such land use restrictions. This document includes a screening evaluation to determine the likel

  19. Incorporating Forecast Uncertainty in Utility Control Center

    SciTech Connect (OSTI)

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

    2014-07-09T23:59:59.000Z

    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)

  20. November 14, 2000 A Quarterly Forecast of U.S. Trade

    E-Print Network [OSTI]

    Shyy, Wei

    November 14, 2000 A Quarterly Forecast of U.S. Trade in Services and the Current Account, 2000 of Forecast*** We forecast that the services trade surplus, which declined from 1997 to 1998 and edged upward. That is, from a level of $80.6 billion in 1999, we forecast that the services trade surplus will be $80

  1. Smard Grid Software Applications for Distribution Network Load Forecasting Eugene A. Feinberg, Jun Fei

    E-Print Network [OSTI]

    Feinberg, Eugene A.

    of the distribution network. Keywords: load forecasting, feeder, transformer, load pocket, SmartGrid I. INTRODUCTION

  2. Solar irradiance forecasting at multiple time horizons and novel methods to evaluate uncertainty

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01T23:59:59.000Z

    Solar irradiance data . . . . . . . . . . . . .Accuracy . . . . . . . . . . . . . . . . . Solar Resourcev Uncertainty In Solar Resource: Forecasting

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

    SciTech Connect (OSTI)

    Lantz, E.; Hand, M.

    2010-05-01T23:59:59.000Z

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

  4. USING BOX-JENKINS MODELS TO FORECAST FISHERY DYNAMICS: IDENTIFICATION, ESTIMATION, AND CHECKING

    E-Print Network [OSTI]

    ~ is illustrated by developing a model that makes monthly forecasts of skipjack tuna, Katsuwonus pelamis, catches

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

    Broader source: Energy.gov [DOE]

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

  6. Dragon Year

    E-Print Network [OSTI]

    Hacker, Randi

    2012-01-11T23:59:59.000Z

    Broadcast Transcript: Can you believe it? It's New Year again. It seems like only yesterday we were celebrating the advent of the year of the Rabbit and now, here it is, the year of the Dragon. January 22nd is New Year's ...

  7. Solid waste 30-year volume summary

    SciTech Connect (OSTI)

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

    1994-06-01T23:59:59.000Z

    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.

  8. Analysis and forecasting of gas well performanc: a rigorous approach using decline curve analysis

    E-Print Network [OSTI]

    Palacio Uran, Juan Carlos

    1993-01-01T23:59:59.000Z

    . . . . . . . . . . . . 146 Normalized Flow Rate Profile versus Material Balance Pseudotimes for Well C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 138 139 6. 35 6, 36 6. 37 A-1 A-2 A-3 149 186 Type Curve Match...ANALYSIS AND FORECASTING OF GAS WELL PERFORMANCE A RIGOROUS APPROACH USING DECLINE CURVE ANALYSIS A Thesis by JUAN CARLOS PALACIO URAN Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment...

  9. Visualizing the Surface Infrastructure Used to Move 2 MtCO2/year from the Dakota Gasification Company to the Weyburn CO2 Enhanced Oil Recovery Project: Version of July 1, 2009

    SciTech Connect (OSTI)

    Dooley, James J.

    2009-07-09T23:59:59.000Z

    Google Earth Pro has been employed to create an interactive flyover of the world’s largest operational carbon dioxide capture and storage project. The visualization focuses on the transport and storage of 2 MtCO2/year which is captured from the Dakota Gasification Facility (Beula, North Dakota) and transported 205 miles and injected into the Weyburn oil field in Southeastern Saskatchewan.

  10. 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.

    2011-10-01T23:59:59.000Z

    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 higher. In organized electricity markets, units that are committed for reliability reasons are paid their offer price even when prevailing market prices are lower. Often, these uplift charges are allocated to market participants that caused the inefficient dispatch in the first place. Thus, wind energy facilities are burdened with their share of costs proportional to their forecast errors. For Xcel Energy, wind energy uncertainty costs manifest depending on specific market structures. In the Public Service of Colorado (PSCo), inefficient commitment and dispatch caused by wind uncertainty increases fuel costs. Wind resources participating in the Midwest Independent System Operator (MISO) footprint make substantial payments in the real-time markets to true-up their day-ahead positions and are additionally burdened with deviation charges called a Revenue Sufficiency Guarantee (RSG) to cover out of market costs associated with operations. Southwest Public Service (SPS) wind plants cause both commitment inefficiencies and are charged Southwest Power Pool (SPP) imbalance payments due to wind uncertainty and variability. Wind energy forecasting helps mitigate these costs. Wind integration studies for the PSCo and Northern States Power (NSP) operating companies have projected increasing costs as more wind is installed on the system due to forecast error. It follows that reducing forecast error would reduce these costs. This is echoed by large scale studies in neighboring regions and states that have recommended adoption of state-of-the-art wind forecasting tools in day-ahead and real-time planning and operations. Further, Xcel Energy concluded reduction of the normalized mean absolute error by one percent would have reduced costs in 2008 by over $1 million annually in PSCo alone. The value of reducing forecast error prompted Xcel Energy to make substantial investments in wind energy forecasting research and development.

  11. 24 Fall 2011 Year 2 Year 3

    E-Print Network [OSTI]

    Guo, Jing

    of south america, bahiagrass can be thought of as kudzu without the bad rap. since 1938, when a variety

  12. Assessment of Non-traditional Isotopic Ratios by Mass Spectrometry for Analysis of Nuclear Activities: Annual Report Year 2

    SciTech Connect (OSTI)

    Biegalski, S; Buchholz, B

    2009-08-26T23:59:59.000Z

    The objective of this work is to identify isotopic ratios suitable for analysis via mass spectrometry that distinguish between commercial nuclear reactor fuel cycles, fuel cycles for weapons grade plutonium, and products from nuclear weapons explosions. Methods will also be determined to distinguish the above from medical and industrial radionuclide sources. Mass spectrometry systems will be identified that are suitable for field measurement of such isotopes in an expedient manner. Significant progress has been made with this project within the past year: (1) Isotope production from commercial nuclear fuel cycles and nuclear weapons fuel cycles have been modeled with the ORIGEN and MCNPX codes. (2) MCNPX has been utilized to calculate isotopic inventories produced in a short burst fast bare sphere reactor (to approximate the signature of a nuclear weapon). (3) Isotopic ratios have been identified that are good for distinguishing between commercial and military fuel cycles as well as between nuclear weapons and commercial nuclear fuel cycles. (4) Mass spectrometry systems have been assessed for analysis of the fission products of interest. (5) A short-list of forensic ratios have been identified that are well suited for use in portable mass spectrometry systems.

  13. Temporal properties of GX 301-2 over a year-long observation with SuperAGILE

    E-Print Network [OSTI]

    Evangelista, Y; Costa, E; Del Monte, E; Donnarumma, I; Lapshov, I; Lazzarotto, F; Pacciani, L; Rapisarda, M; Soffitta, P; Argan, A; Barbiellini, G; Boffelli, F; Bulgarelli, A; Caraveo, P; Cattaneo, P W; Chen, A; D'Ammando, F; Di Cocco, G; Fuschino, F; Galli, M; Gianotti, F; Giuliani, A; Labanti, C; Lipari, P; Longo, F; Marisaldi, M; Mereghetti, S; Moretti, E; Morselli, A; Pellizzoni, A; Perotti, F; Piano, G; Picozza, P; Pilia, M; Prest, M; Pucella, G; Rappoldi, A; Sabatini, S; Striani, E; Tavani, M; Trifoglio, M; Trois, A; Vallazza, E; Vercellone, S; Vittorini, V; Zambra, A; Antonelli, L A; Cutini, S; Pittori, C; Preger, B; Santolamazza, P; Verrecchia, F; Giommi, P; Salotti, L

    2009-01-01T23:59:59.000Z

    We present the long-term monitoring of the High Mass X-ray Binary GX 301-2 performed with the SuperAGILE instrument on-board the AGILE mission. The source was monitored in the 20-60 keV energy band during the first year of the mission from 2007 July 17 to 2008 August 31, covering about one whole orbital period and three more pre-periastron passages for a total net observation time of about 3.7 Ms. The SuperAGILE dataset represents one of the most continuous and complete monitoring at hard X-ray energies of the 41.5 day long binary period available to date. The source behaviour was characterized at all orbital phases in terms of hard X-ray flux, spectral hardness, spin period history, pulsed fraction and pulse shape profile. We also complemented the SuperAGILE observations with the soft X-ray data of the RossiXTE/ASM. Our analysis shows a clear orbital modulation of the spectral hardness, with peaks in correspondence of the pre-periastron flare and near phase 0.25. The hardness peaks we found could be related ...

  14. Optimally controlling hybrid electric vehicles using path forecasting

    E-Print Network [OSTI]

    Katsargyri, Georgia-Evangelina

    2008-01-01T23:59:59.000Z

    Hybrid Electric Vehicles (HEVs) with path-forecasting belong to the class of fuel efficient vehicles, which use external sensory information and powertrains with multiple operating modes in order to increase fuel economy. ...

  15. Recently released EIA report presents international forecasting data

    SciTech Connect (OSTI)

    NONE

    1995-05-01T23:59:59.000Z

    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.

  16. Grid-scale Fluctuations and Forecast Error in Wind Power

    E-Print Network [OSTI]

    G. Bel; C. P. Connaughton; M. Toots; M. M. Bandi

    2015-03-29T23:59:59.000Z

    The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

  17. OCTOBER-NOVEMBER FORECAST FOR 2014 CARIBBEAN BASIN HURRICANE ACTIVITY

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    and hurricanes, but instead predicts both hurricane days and Accumulated Cyclone Energy (ACE). Typically, while) tropical cyclone (TC) activity. We have decided to issue this forecast, because Klotzbach (2011) has

  18. The Rationality of EIA Forecasts under Symmetric and Asymmetric Loss

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01T23:59:59.000Z

    Agency: 1982-2005a, Annual Energy Outlook, EIA, Washington,Agency: 2004, Annual Energy Outlook Forecast Evaluation,Agency: 2005b, Annual Energy Outlook, EIA, Washington, D.C.

  19. The Rationality of EIA Forecasts under Symmetric and Asymmetric Loss

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01T23:59:59.000Z

    2005a, Annual Energy Outlook, EIA, Washington, D.C. Energy2005b, Annual Energy Outlook, EIA, Washington, D.C. Granger,Paper ???? The Rationality of EIA Forecasts under Symmetric

  20. Forecasting and strategic inventory placement for gas turbine aftermarket spares

    E-Print Network [OSTI]

    Simmons, Joshua T. (Joshua Thomas)

    2007-01-01T23:59:59.000Z

    This thesis addresses the problem of forecasting demand for Life Limited Parts (LLPs) in the gas turbine engine aftermarket industry. It is based on work performed at Pratt & Whitney, a major producer of turbine engines. ...

  1. Optimally Controlling Hybrid Electric Vehicles using Path Forecasting

    E-Print Network [OSTI]

    Kolmanovsky, Ilya V.

    The paper examines path-dependent control of Hybrid Electric Vehicles (HEVs). In this approach we seek to improve HEV fuel economy by optimizing charging and discharging of the vehicle battery depending on the forecasted ...

  2. africa conditional forecasts: Topics by E-print Network

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

    forecasts had the potential to improve resource management but instead played only a marginal role in real-world decision making. 1 A widespread perception that the quality of the...

  3. accident risk forecasting: Topics by E-print Network

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

    forecasts had the potential to improve resource management but instead played only a marginal role in real-world decision making. 1 A widespread perception that the quality of the...

  4. Forecasting Volatility in Stock Market Using GARCH Models

    E-Print Network [OSTI]

    Yang, Xiaorong

    2008-01-01T23:59:59.000Z

    Forecasting volatility has held the attention of academics and practitioners all over the world. The objective for this master's thesis is to predict the volatility in stock market by using generalized autoregressive conditional heteroscedasticity(GARCH...

  5. Forecasting Returns and Volatilities in GARCH Processes Using the Bootstrap

    E-Print Network [OSTI]

    Romo, Juan

    Forecasting Returns and Volatilities in GARCH Processes Using the Bootstrap Lorenzo Pascual, Juan generated by GARCH processes. The main advantage over other bootstrap methods previously proposed for GARCH by having conditional heteroscedasticity. Generalized Autoregressive Conditionally Heteroscedastic (GARCH

  6. Adaptive sampling and forecasting with mobile sensor networks

    E-Print Network [OSTI]

    Choi, Han-Lim

    2009-01-01T23:59:59.000Z

    This thesis addresses planning of mobile sensor networks to extract the best information possible out of the environment to improve the (ensemble) forecast at some verification region in the future. To define the information ...

  7. Dispersion in analysts' forecasts: does it make a difference? 

    E-Print Network [OSTI]

    Adut, Davit

    2004-09-30T23:59:59.000Z

    Financial analysts are an important group of information intermediaries in the capital markets. Their reports, including both earnings forecasts and stock recommendations, are widely transmitted and have a significant impact on stock prices (Womack...

  8. FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007

    E-Print Network [OSTI]

    ......................................................................... 11 3. Demand Side Management (DSM) Program Impacts................................... 13 4. Demand Sylvia Bender Manager DEMAND ANALYSIS OFFICE Scott W. Matthews Chief Deputy Director B.B. Blevins Forecast Methods and Models ....................................................... 14 5. Demand-Side

  9. 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...

  10. Variable Selection and Inference for Multi-period Forecasting Problems

    E-Print Network [OSTI]

    Pesaran, M Hashem; Pick, Andreas; Timmermann, Allan

    Variable Selection and Inference for Multi-period Forecasting Problems? M. Hashem Pesaran Cambridge University and USC Andreas Pick De Nederlandsche Bank and Cambridge University, CIMF Allan Timmermann UC San Diego and CREATES January 26, 2009...

  11. Grid-scale Fluctuations and Forecast Error in Wind Power

    E-Print Network [OSTI]

    Bel, G; Toots, M; Bandi, M M

    2015-01-01T23:59:59.000Z

    The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

  12. Dispersion in analysts' forecasts: does it make a difference?

    E-Print Network [OSTI]

    Adut, Davit

    2004-09-30T23:59:59.000Z

    Financial analysts are an important group of information intermediaries in the capital markets. Their reports, including both earnings forecasts and stock recommendations, are widely transmitted and have a significant impact on stock prices (Womack...

  13. Mesoscale predictability and background error convariance estimation through ensemble forecasting

    E-Print Network [OSTI]

    Ham, Joy L

    2002-01-01T23:59:59.000Z

    Over the past decade, ensemble forecasting has emerged as a powerful tool for numerical weather prediction. Not only does it produce the best estimate of the state of the atmosphere, it also could quantify the uncertainties associated with the best...

  14. Subhourly wind forecasting techniques for wind turbine operations

    SciTech Connect (OSTI)

    Wegley, H.L.; Kosorok, M.R.; Formica, W.J.

    1984-08-01T23:59:59.000Z

    Three models for making automated forecasts of subhourly wind and wind power fluctuations were examined to determine the models' appropriateness, accuracy, and reliability in wind forecasting for wind turbine operation. Such automated forecasts appear to have value not only in wind turbine control and operating strategies, but also in improving individual wind turbine control and operating strategies, but also in improving individual wind turbine operating strategies (such as determining when to attempt startup). A simple persistence model, an autoregressive model, and a generalized equivalent Markhov (GEM) model were developed and tested using spring season data from the WKY television tower located near Oklahoma City, Oklahoma. The three models represent a pure measurement approach, a pure statistical method and a statistical-dynamical model, respectively. Forecasting models of wind speed means and measures of deviations about the mean were developed and tested for all three forecasting techniques for the 45-meter level and for the 10-, 30- and 60-minute time intervals. The results of this exploratory study indicate that a persistence-based approach, using onsite measurements, will probably be superior in the 10-minute time frame. The GEM model appears to have the most potential in 30-minute and longer time frames, particularly when forecasting wind speed fluctuations. However, several improvements to the GEM model are suggested. In comparison to the other models, the autoregressive model performed poorly at all time frames; but, it is recommended that this model be upgraded to an autoregressive moving average (ARMA or ARIMA) model. The primary constraint in adapting the forecasting models to the production of wind turbine cluster power output forecasts is the lack of either actual data, or suitable models, for simulating wind turbine cluster performance.

  15. Streamflow forecasting for large-scale hydrologic systems

    E-Print Network [OSTI]

    Awwad, Haitham Munir

    1991-01-01T23:59:59.000Z

    STREAMFLOW FORECASTING FOR LARGE-SCALE HYDROLOGIC SYSTEMS A Thesis by HAITHAM MUNIR AWWAD Submitted to the Office of Graduate Studies of Texas AkM University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May... 1991 Major Subject: Civil Engineering STREAMFLOW FORECASTING FOR LARGE-SCALE HYDROLOGIC SYSTEMS A Thesis by HAITHAM MUNIR AWWAD Approved as to style and content by: uan B. Valdes (Chair of Committee) alph A. Wurbs (Member) Marshall J. Mc...

  16. A model for short term electric load forecasting

    E-Print Network [OSTI]

    Tigue, John Robert

    1975-01-01T23:59:59.000Z

    A MODEL FOR SHORT TERM ELECTRIC LOAD FORECASTING A Thesis by JOHN ROBERT TIGUE, III Submitted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE May 1975 Major... Subject: Electrical Engineering A MODEL FOR SHORT TERM ELECTRIC LOAD FORECASTING A Thesis by JOHN ROBERT TIGUE& III Approved as to style and content by: (Chairman of Committee) (Head Depart t) (Member) ;(Me r (Member) (Member) May 1975 ABSTRACT...

  17. 11.1 DEVELOPMENT OF AN IMMERSED BOUNDARY METHOD TO RESOLVE COMPLEX TERRAIN IN THE WEATHER RESEARCH AND FORECASTING MODEL

    E-Print Network [OSTI]

    Chow, Fotini Katopodes

    11.1 DEVELOPMENT OF AN IMMERSED BOUNDARY METHOD TO RESOLVE COMPLEX TERRAIN IN THE WEATHER RESEARCH AND FORECASTING MODEL Katherine A. Lundquist1 , Fotini K. Chow 2 , Julie K. Lundquist 3 , and Jeffery D. Mirocha 3 in urban areas are profoundly influenced by the presence of build- ings which divert mean flow, affect

  18. Improved water allocation utilizing probabilistic climate forecasts: Short-term water contracts in a risk management framework

    E-Print Network [OSTI]

    Arumugam, Sankar

    . Thus, integrated supply and demand management can be achieved. In this paper, a single period multiuser, forecast consumers, water managers and reservoir operators, have difficulty interpreting such products in a risk management framework A. Sankarasubramanian,1 Upmanu Lall,2 Francisco Assis Souza Filho,3

  19. Comparison of Bottom-Up and Top-Down Forecasts: Vision Industry Energy Forecasts with ITEMS and NEMS

    E-Print Network [OSTI]

    Roop, J. M.; Dahowski, R. T

    Comparisons are made of energy forecasts using results from the Industrial module of the National Energy Modeling System (NEMS) and an industrial economic-engineering model called the Industrial Technology and Energy Modeling System (ITEMS), a model...

  20. Black Liquor Combustion Validated Recovery Boiler Modeling, Final Year Report, Volume 3: Appendix II, Sections 2 & 3 and Appendix III

    SciTech Connect (OSTI)

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

    1998-08-01T23:59:59.000Z

    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. Many of these objectives were accomplished at the end of the first five years and documented in a comprehensive report on that work (DOE/CE/40936-T3, 1996). A critical review of recovery boiler modeling, carried out in 1995, concluded that further enhancements of the model were needed to make reliable predictions of key output variables. In addition, there was a need for sufficient understanding of fouling and plugging processes to allow model outputs to be interpreted in terms of the effect on plugging and fouling. As a result, the project was restructured and reinitiated at the end of October 1995, and was completed in June 1997. The entire project is now complete and this report summarizes all of the work done on the project since it was restructured. The key tasks to be accomplished under the restructured project were to (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 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; and (4) Facilitate the transfer of codes, black liquor submodels, and fundamental knowledge to the U.S. kraft pulp industry.

  1. Probabilistic wind power forecasting -European Wind Energy Conference -Milan, Italy, 7-10 May 2007 Probabilistic short-term wind power forecasting

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Probabilistic wind power forecasting - European Wind Energy Conference - Milan, Italy, 7-10 May 2007 Probabilistic short-term wind power forecasting based on kernel density estimators J´er´emie Juban jeremie.juban@ensmp.fr; georges.kariniotakis@ensmp.fr Abstract Short-term wind power forecasting tools

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-01-01T23:59:59.000Z

    vs. AEO 2001 Price Forecast Natural Gas Price (nominal $/if forwards forecasts) or natural gas-fired generation (ifs reference case forecast of natural gas prices delivered to

  3. A Breakout Year Propels New Jersey Economy into 2005

    E-Print Network [OSTI]

    A Breakout Year Propels New Jersey Economy into 2005 A t the end of 2003, we tiptoed out on the forecasting limb and asserted that if the 2004 national economy were a movie, it would be titled "Showtime." We also opined that if the 2004 New Jersey economy were a movie, it would be titled "The Sweet Smell

  4. 2, 921942, 2002 Global ozone

    E-Print Network [OSTI]

    Boyer, Edmond

    ACPD 2, 921­942, 2002 Global ozone forecasting H. J. Eskes et al. Title Page Abstract Introduction Geophysical Society 2002 Atmospheric Chemistry and Physics Discussions Global ozone forecasting based on ERS-2 July 2002 Correspondence to: H. J. Eskes (eskes@knmi.nl) 921 #12;ACPD 2, 921­942, 2002 Global ozone

  5. Long-Term Outcome of a Hepatocellular Carcinoma 71/2 Years After Surgery and Repeated Radiofrequency Ablation: Case Report and Review of the Literature

    SciTech Connect (OSTI)

    Thanos, L., E-mail: loutharad@yahoo.com; Mylona, S.; Nikita, A.; Ptohis, N.; Kelekis, D.A. [University of Athens, 2nd Radiology Department (Greece)

    2007-04-15T23:59:59.000Z

    An interesting case is presented of a 78-year-old patient with cirrhosis who was managed with combined treatment (surgery and radiofrequency (RF) ablation) for hepatocellular carcinoma (HCC) and has survived for 71/2 years. Elevation of the {alpha}-FP (alpha-fetoprotein) levels was noted 2 years after surgery. CT demonstrated two lesions: one central at the remaining right liver lobe, and the other at the excision site. Biopsy of the lesions confirmed the diagnosis of HCC for both of them. RF ablation of these two lesions was performed in one session with technical success. Four and a half years after the first RF ablation a new recurrence was demonstrated at the CT follow-up control. RF ablation was again applied successfully. The imaging findings and the therapeutic percutaneous management of this patient along with the natural course of HCC and its recurrence are discussed, and the literature concerning risk factors is reviewed.

  6. Mars in the glacial ages of the past millions of years: modeling a planet partially mantled by dust and ice J.-B. Madeleine 1,2

    E-Print Network [OSTI]

    Madeleine, Jean-Baptiste

    and ice J.-B. Madeleine 1,2 (jean-baptiste.madeleine@upmc.fr), F. For- get 1 , J. W. Head 2 , T. Navarro 1 recent ice ages, reflected in the latitude dependent mantle, were more enigmatic, and their origin was more difficult to explain. In recent years, Mars GCMs underwent a new phase of development al- lowed

  7. The first 2.5 years of the HETE : toward an understanding of the nature of short and long duration gamma-ray bursts

    E-Print Network [OSTI]

    Butler, Nathaniel Richard, 1976-

    2003-01-01T23:59:59.000Z

    The HETE satellite became operational on the 2nd of February, 2001. In the first 2.5 years of the mission prior to July 1 of 2003, 42 Gamma-ray bursts (GRBs) were promptly localized and publicized over the GRB Coordinates ...

  8. Forecasting Model for Crude Oil Price Using Artificial Neural Networks and Commodity Futures Prices

    E-Print Network [OSTI]

    Kulkarni, Siddhivinayak

    2009-01-01T23:59:59.000Z

    This paper presents a model based on multilayer feedforward neural network to forecast crude oil spot price direction in the short-term, up to three days ahead. A great deal of attention was paid on finding the optimal ANN model structure. In addition, several methods of data pre-processing were tested. Our approach is to create a benchmark based on lagged value of pre-processed spot price, then add pre-processed futures prices for 1, 2, 3,and four months to maturity, one by one and also altogether. The results on the benchmark suggest that a dynamic model of 13 lags is the optimal to forecast spot price direction for the short-term. Further, the forecast accuracy of the direction of the market was 78%, 66%, and 53% for one, two, and three days in future conclusively. For all the experiments, that include futures data as an input, the results show that on the short-term, futures prices do hold new information on the spot price direction. The results obtained will generate comprehensive understanding of the cr...

  9. Regulatory Assistance, Stakeholder Outreach, and Coastal and Marine Spatial Planning Activities In Support Marine and Hydrokinetic Energy Deployment: Task 2.1.7 Permitting and Planning Fiscal Year 2012 Year-End Report

    SciTech Connect (OSTI)

    Geerlofs, Simon H.; Hanna, Luke A.; Judd, Chaeli R.; Blake, Kara M.

    2012-09-01T23:59:59.000Z

    This fiscal year 2012 year-end report summarizes activities carried out under DOE Water Power task 2.1.7, Permitting and Planning. Activities under Task 2.1.7 address the concerns of a wide range of stakeholders with an interest in the development of the MHK industry, including regulatory and resource management agencies, tribes, NGOs, and industry. Objectives for 2.1.7 are the following: • To work with stakeholders to streamline the MHK regulatory permitting process. • To work with stakeholders to gather information on needs and priorities for environmental assessment of MHK development. • To communicate research findings and directions to the MHK industry and stakeholders. • To engage in spatial planning processes in order to further the development of the MHK industry. These objectives are met through three subtasks, each of which are described in this report: • 2.1.7.1—Regulatory Assistance • 2.1.7.2—Stakeholder Outreach • 2.1.7.3—Coastal and Marine Spatial Planning As the MHK industry works with the regulatory community and stakeholders to plan, site, permit and license MHK technologies they have an interest in a predictable, efficient, and transparent process. Stakeholders and regulators have an interest in processes that result in sustainable use of ocean space with minimal effects to existing ocean users. Both stakeholders and regulators have an interest in avoiding legal challenges by meeting the intent of federal, state, and local laws that govern siting and operation of MHK technologies. The intention of work under 2.1.7 is to understand these varied interests, explore mechanisms to reduce conflict, identify efficiencies, and ultimately identify pathways to reduce the regulatory costs, time, and potential environmental impacts associated with developing, siting, permitting, and deploying MHK systems.

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2012-04-01T23:59:59.000Z

    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.

  11. Summary of Research through Phase II/Year 2 of Initially Approved 3 Phase/3 Year Project - Establishing the Relationship between Fracture-Related Dolomite and Primary Rock Fabric on the Distribution of Reservoirs in the Michigan Basin

    SciTech Connect (OSTI)

    G. Grammer

    2007-09-30T23:59:59.000Z

    This final scientific/technical report covers the first 2 years (Phases I and II of an originally planned 3 Year/3 Phase program). The project was focused on evaluating the relationship between fracture-related dolomite and dolomite constrained by primary rock fabric in the 3 most prolific reservoir intervals in the Michigan Basin. The characterization of select dolomite reservoirs was the major focus of our efforts in Phases I and II of the project. Structural mapping and log analysis in the Dundee (Devonian) and Trenton/Black River (Ordovician) suggest a close spatial relationship among gross dolomite distribution and regional-scale, wrench fault-related NW-SE and NE-SW structural trends. A high temperature origin for much of the dolomite in these 2 studied intervals (based upon fluid inclusion homogenization temperatures and stable isotopic analyses,) coupled with persistent association of this dolomite in reservoirs coincident with wrench fault-related features, is strong evidence for these reservoirs being influenced by hydrothermal dolomitization. In the Niagaran (Silurian), there is a general trend of increasing dolomitization shelfward, with limestone predominant in more basinward positions. A major finding is that facies types, when analyzed at a detailed level, are directly related to reservoir porosity and permeability in these dolomites which increases the predictability of reservoir quality in these units. This pattern is consistent with our original hypothesis of primary facies control on dolomitization and resulting reservoir quality at some level. The identification of distinct and predictable vertical stacking patterns within a hierarchical sequence and cycle framework provides a high degree of confidence at this point that the results should be exportable throughout the basin. Much of the data synthesis and modeling for the project was scheduled to be part of Year 3/Phase III, but the discontinuation of funding after Year 2 precluded those efforts. Therefore, the results presented in this document are not final, and in many cases represent a report of 'progress to date' as numerous tasks were scheduled to extend into Year 3.

  12. Update On The Wholesale Electricity Price Forecast & Modeling Results

    E-Print Network [OSTI]

    ,877 Replacement #12;CO2 Emission Modeling § The AURORAxmp® electric market model calculates CO2 emission) Assumptions § CO2 emission modeling § Base Case Results § Scenario/Sensitivities § Emission Projections Database ­ eGRID 2012 Year 2009 ­ Emissions, including CO2, are estimated using information from various

  13. 8. Neural Networks Over the years, linear regression models have attempted to characterise the 0.2% proof stress and

    E-Print Network [OSTI]

    Cambridge, University of

    30 8. Neural Networks Over the years, linear regression models have attempted to characterise the 0 interact. A more powerful alternative is the use of neural networks [40,42], a non-linear modelling prediction uncertainties. #12;31 In linear regression, the sum of each input xi multiplied with a weight wi

  14. 2008 Year in Review 1 2008 Year in Review

    E-Print Network [OSTI]

    Hickman, Mark

    2008 Year in Review 1 2008 Year in Review The Science of Communication Disorders Departmental Research Committee. #12;2 2008 Year in Review Billinghurst, M., Moran, C., Gostomski, P., Basu, A

  15. Short-term planning and forecasting for petroleum. Master's thesis

    SciTech Connect (OSTI)

    Elkins, R.D.

    1988-06-01T23:59:59.000Z

    The Defense Fuel Supply Center (DFSC) has, in recent past, been unable to adequately forecast for short-term petroleum requirements. This has resulted in inaccurate replenishment quantities and required short-notice corrections, which interrupted planned resupply methods. The relationship between the annual CINCLANTFLT DFM budget and sales from the the Norfolk Defense Fuel Support Point (DFSP) is developed and the past sales data from the Norfolk DFSP is used to construct seasonality indices. Finally, the budget/sales relationship is combined with the seasonality indices to provide a new forecasting model. The model is then compared with the current one for FY-88 monthly forecasts. The comparison suggests that the new model can provide accurate, timely requirements data and improve resupply of the Norfolk Defense Fuel Support Point.

  16. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

    and validation.   Solar Energy.   73:5, 307? Perez, R. , forecast database.   Solar Energy.   81:6, 809?812.  forecasts in the US.   Solar Energy.   84:12, 2161?2172.  

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

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

    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...

  18. Application of the Stretched Exponential Production Decline Model to Forecast Production in Shale Gas Reservoirs

    E-Print Network [OSTI]

    Statton, James Cody

    2012-07-16T23:59:59.000Z

    . This study suggests a type curve is most useful when 24 months or less is available to forecast. The SEPD model generally provides more conservative forecasts and EUR estimates than Arps' model with a minimum decline rate of 5%....

  19. SHORT-TERM FORECASTING OF SOLAR RADIATION BASED ON SATELLITE DATA WITH STATISTICAL METHODS

    E-Print Network [OSTI]

    Heinemann, Detlev

    SHORT-TERM FORECASTING OF SOLAR RADIATION BASED ON SATELLITE DATA WITH STATISTICAL METHODS Annette governing the insolation, forecasting of solar radiation makes the description of development of the cloud

  20. Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast

    E-Print Network [OSTI]

    ............................................................................................................................... 12 Oil Price Forecast Range. The price of crude oil was $25 a barrel in January of 2000. In July 2008 it averaged $127, even approachingSixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast Introduction