National Library of Energy BETA

Sample records for forecasting wa id

  1. CRICOS Provider Code 00301J (WA) 02637B (NSW) Application for Student ID card External students

    E-Print Network [OSTI]

    Mucina, Ladislav

    institution Health Care, Social Security or Pension card Public Service employee ID card Other licence issued these requirements. Information about your new Curtin ID card Your Curtin ID card has a number of functions. First of buildings including Abacus Labs, print services and Library facilities. Your card also has a Curtin sticker

  2. 'EAITLE, WA bruary 1972

    E-Print Network [OSTI]

    · tions that review in con id rable d tail and at a high technical 11'\\"f'1 c daill "nlad an'as flf r lU70, pp., (j fig'. !J!l. ,'almon r · arch at Ice Harbor Dam. By Wesley J. Eb 1. prill 70, pp.. 4

  3. RAPID/Roadmap/9-WA-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa <NV-b <Roadmap/9-CA-bl <ID-a9-WA-a

  4. Solar Forecasting

    Broader source: Energy.gov [DOE]

    On December 7, 2012, DOE announced $8 million to fund two solar projects that are helping utilities and grid operators better forecast when, where, and how much solar power will be produced at U.S....

  5. WA_05_022_DOW_CHEMICAL_COMPANY_Waiver_of_domestic_and_Foreig...

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

    5022DOWCHEMICALCOMPANYWaiverofdomesticandForeig.pdf WA05022DOWCHEMICALCOMPANYWaiverofdomesticandForeig.pdf WA05022DOWCHEMICALCOMPANYWaiverofdomesticand...

  6. WA_96_016_AIR_PRODUCTS_AND_CHEMICALS_INC_Waiver_of_Domestic_...

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

    16AIRPRODUCTSANDCHEMICALSINCWaiverofDomestic.pdf WA96016AIRPRODUCTSANDCHEMICALSINCWaiverofDomestic.pdf WA96016AIRPRODUCTSANDCHEMICALSINCWaiverofDomest...

  7. Badging, Real ID Act

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

    employees, or subcontractors needing to access LANL facilities may be impacted by new access control procedures Only driver's licenses or ID cards from states that meet federal...

  8. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

    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:

  9. WA_96_012_ALLIEDSIGNAL_INC_CERAMIC_COMPONENTS_Waiver_of_Dome...

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

    ALLIEDSIGNALINCCERAMICCOMPONENTSWaiverofDome.pdf WA96011ALLIEDSIGNALWaiverofDomesticandForeignRight.pdf WA1993021ALLIEDSIGNALINCWaiverofDomesticandForeign...

  10. WA_98_001_REYNOLDS_METALS_COMPANY_Waiver_of_Domestic_and_For...

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

    01REYNOLDSMETALSCOMPANYWaiverofDomesticandFor.pdf WA98001REYNOLDSMETALSCOMPANYWaiverofDomesticandFor.pdf WA98001REYNOLDSMETALSCOMPANYWaiverofDomesticand...

  11. WA_02_034_BP_SOLAR_INTERNATIONAL_LLC_Waiver_of_Domestic_and_...

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

    BPSOLARINTERNATIONALWaiverofDomesticandFore.pdf WA06016BPSOLARINTERNATIONALWaiverofPatentRightsUnd.pdf WA03032RWESCHOTTSOLARINCWaiverofPatentRightsUnder...

  12. 4-ID-D optics

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

    4-ID-D Beamline Optics A schetch of the major optical components for beam line 4-ID-D are shown above. All these components located in the B-station upstream from the D...

  13. BayWa Group | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EAandAmminexInformationArkansas: Energy ResourcesPoint,View,BayWa Group

  14. waTer economics. environmenTand Policy

    E-Print Network [OSTI]

    Botea, Adi

    41 cenTre for waTer economics. environmenTand Policy "Men and nature must work hand in hand and public policy insights for the supply, demand, management, and governance of water CWEEP pronounced `sweep' as in to survey so as to obtain a whole and continuous view of the world #12;42 waTer is a cri

  15. WA_98_023_McDERMOTT_TECHNOLOGY_INC_Waiver_of_Domestic_and_Fo...

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

    23McDERMOTTTECHNOLOGYINCWaiverofDomesticandFo.pdf WA98023McDERMOTTTECHNOLOGYINCWaiverofDomesticandFo.pdf WA98023McDERMOTTTECHNOLOGYINCWaiverofDomesticand...

  16. WA_06_016_BP_SOLAR_INTERNATIONAL_Waiver_of_Patent_Rights_Und...

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

    6016BPSOLARINTERNATIONALWaiverofPatentRightsUnd.pdf WA06016BPSOLARINTERNATIONALWaiverofPatentRightsUnd.pdf WA06016BPSOLARINTERNATIONALWaiverofPatentRigh...

  17. Wind Power Forecasting Data

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

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

  18. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

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

  19. Forecasting Water Quality & Biodiversity

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

    Forecasting Water Quality & Biodiversity March 25, 2015 Cross-cutting Sustainability Platform Review Principle Investigator: Dr. Henriette I. Jager Organization: Oak Ridge National...

  20. 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 turbines. This second effect is the primary use of the fuel price forecast for the Council's Fifth Power

  1. Weather Forecasting Spring 2014

    E-Print Network [OSTI]

    Hennon, Christopher C.

    ATMS 350 Weather Forecasting Spring 2014 Professor : Dr. Chris Hennon Office : RRO 236C Phone : 232 of atmospheric physics and the ability to include this understanding into modern numerical weather prediction agencies, forecast tools, numerical weather prediction models, model output statistics, ensemble

  2. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

    ....................................................................................................1-16 Energy Consumption Data...............................................1-15 Data Sources for Energy Demand Forecasting ModelsCALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report

  3. APS Beamline 6-ID-B,C

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

    6-ID-B,C Home Recent Publications Beamline Info Optics Instrumentation Software User Info Beamline 6-ID-B,C Beamline 6-ID-B,C is operated by the Magnetic Materials Group in the...

  4. Beamline 29-ID

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B L O OLaura| National2.1 Print National Center 29-ID - IEX

  5. Beamline 29-ID

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B L O OLaura| National2.1 Print National Center 29-ID - IEX IEX

  6. Beamline 29-ID

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B L O OLaura| National2.1 Print National Center 29-ID - IEX

  7. Beamline 29-ID

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B L O OLaura| National2.1 Print National Center 29-ID - IEXResonant

  8. Data ID Service

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformation Current HAB Packet HanfordDOEDaniel Shechtman andDarkID Service First DOI for a

  9. FITCH RATES ENERGY NORTHWEST, WA'S ELECTRIC REV RFDG BONDS 'AA...

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

    FITCH RATES ENERGY NORTHWEST, WA'S ELECTRIC REV RFDG BONDS 'AA'; OUTLOOK STABLE Fitch Ratings-Austin-22 September 2015: Fitch Ratings assigns its 'AA' rating to the following bonds...

  10. New Mexico State University ID Card Services

    E-Print Network [OSTI]

    Johnson, Eric E.

    New Mexico State University ID Card Services Aggie Cash Payroll Deduction Authorization IDS account? Yes No AUTHORIZATION FOR PAYROLL DEDUCTION: I hereby authorize New Mexico State University

  11. Solar Forecast Improvement Project

    Office of Energy Efficiency and Renewable Energy (EERE)

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

  12. Beamline 4-ID-D

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

    intense interest because they offer a pollution-free source of electricity and a vibration free source of refrigeration. Research at beamline 4-ID-D examined how the magnetism...

  13. Bull Test ID 1181 2013 Florida Bull Test

    E-Print Network [OSTI]

    Jawitz, James W.

    Bull Test ID 1181 2013 Florida Bull Test #12;Bull Test ID 1182 2013 Florida Bull Test #12;Bull Test ID 1183 2013 Florida Bull Test #12;Bull Test ID 1184 2013 Florida Bull Test #12;Bull Test ID 1185 2013 Florida Bull Test #12;Bull Test ID 1186 2013 Florida Bull Test #12;Bull Test ID 1187 2013 Florida

  14. Bull Test ID 1140 2013 Florida Bull Test

    E-Print Network [OSTI]

    Jawitz, James W.

    Bull Test ID 1140 2013 Florida Bull Test #12;Bull Test ID 1141 2013 Florida Bull Test #12;Bull Test ID 1142 2013 Florida Bull Test #12;Bull Test ID 1143 2013 Florida Bull Test #12;Bull Test ID 1144 2013 Florida Bull Test #12;Bull Test ID 1145 2013 Florida Bull Test #12;Bull Test ID 1146 2013 Florida

  15. Bull Test ID 1098 2013 Florida Bull Test

    E-Print Network [OSTI]

    Jawitz, James W.

    Bull Test ID 1098 2013 Florida Bull Test #12;Bull Test ID 1099 2013 Florida Bull Test #12;Bull Test ID 1100 2013 Florida Bull Test #12;Bull Test ID 1101 2013 Florida Bull Test #12;Bull Test ID 1102 2013 Florida Bull Test #12;Bull Test ID 1103 2013 Florida Bull Test #12;Bull Test ID 1104 2013 Florida

  16. Bull Test ID 1118 2013 Florida Bull Test

    E-Print Network [OSTI]

    Jawitz, James W.

    Bull Test ID 1118 2013 Florida Bull Test #12;Bull Test ID 1119 2013 Florida Bull Test #12;Bull Test ID 1120 2013 Florida Bull Test #12;Bull Test ID 1121 2013 Florida Bull Test #12;Bull Test ID 1122 2013 Florida Bull Test #12;Bull Test ID 1123 2013 Florida Bull Test #12;Bull Test ID 1124 2013 Florida

  17. Bull Test ID 1160 2013 Florida Bull Test

    E-Print Network [OSTI]

    Jawitz, James W.

    Bull Test ID 1160 2013 Florida Bull Test #12;Bull Test ID 1161 2013 Florida Bull Test #12;Bull Test ID 1162 2013 Florida Bull Test #12;Bull Test ID 1163 2013 Florida Bull Test #12;Bull Test ID 1164 2013 Florida Bull Test #12;Bull Test ID 1165 2013 Florida Bull Test #12;Bull Test ID 1166 2013 Florida

  18. RAPID/Roadmap/8-WA-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa <NV-b < RAPID‎WA-aFD-bUT-a8-WA-a

  19. Improving automotive battery sales forecast

    E-Print Network [OSTI]

    Bulusu, Vinod

    2015-01-01

    Improvement in sales forecasting allows firms not only to respond quickly to customers' needs but also to reduce inventory costs, ultimately increasing their profits. Sales forecasts have been studied extensively to improve ...

  20. Appendix A: Fuel Price Forecast Introduction..................................................................................................................................... 1

    E-Print Network [OSTI]

    Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts ............................................................................................................................ 5 U.S. Natural Gas Commodity Prices

  1. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

    Demand 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 of any forecast of electricity demand and developing ways to reduce the risk of planning errors

  2. 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

  3. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    Rutledge, Steven

    AMERICAN METEOROLOGICAL SOCIETY Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary microbursts than in many previously documented microbursts. Alignment of Doppler radar data to reports of wind-related damage to electrical power infrastructure in Phoenix allowed a comparison of microburst wind damage

  4. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    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

  5. Computer Science & Engineering Box 352350 Seattle, WA 98195-2350

    E-Print Network [OSTI]

    Borenstein, Elhanan

    Computer Science & Engineering #12;Box 352350 Seattle, WA 98195-2350 Nonprofit Org US Postage PAID in the Computer Science Department. He is a superb researcher in the design of interactive, visual data, Carnegie Mellon University's Finmeccanica Associate Professor in the School of Computer Science, is widely

  6. EIS-0397: Lyle Falls Fish Passage Project, WA

    Broader source: Energy.gov [DOE]

    This EIS analyzes BPA's decision to modify funding to the existing Lyle Falls Fishway on the lower Klickitat River in Klickitat County, WA. The proposed project would help BPA meet its off-site mitigation responsibilities for anadromous fish affected by the development of the Federal Columbia River Power System and increase overall fish production in the Columbia Basin.

  7. WA S C2 0 01 Handbook of

    E-Print Network [OSTI]

    California at Santa Cruz, University of

    WA S C2 0 01 Handbook of Accreditation #12;The Western Association of Schools and Colleges be terminated, or when the Commission formally acts to terminate accreditation. This Handbook of Accreditation associations and related bodies, see pages 118­119. #12;HANDBOOK OF ACCREDITATION Standards Addressing Core

  8. Gaseous Detonation-Driven Fracture of Tubes Tong Wa Chao

    E-Print Network [OSTI]

    Barr, Al

    Gaseous Detonation-Driven Fracture of Tubes Thesis by Tong Wa Chao In Partial Fulfillment An experimental investigation of fracture response of aluminum 6061-T6 tubes under internal gaseous detonation of this particular traveling load and tube geometry produced fracture data not available before in the open

  9. Data ID Service | DOE Data Explorer

    Office of Scientific and Technical Information (OSTI)

    DOE Data ID Service DOE Data ID Service Note 1: This section pertains to datasets, dataset records, and Digital Object Identifiers (DOIs). It is not related to the collection...

  10. Copyright 2004 Auto-ID Labs, All Rights Reserved Auto-ID Labs

    E-Print Network [OSTI]

    Brock, David

    E. Grosvenor Plowman Award given by the Council of Logistics Management for the "paper judged©Copyright 2004 Auto-ID Labs, All Rights Reserved Auto-ID Labs Massachusetts Institute-ID Labs Massachusetts Institute of Technology #12;©Copyright 2004 Auto-ID Labs, All Rights Reserved

  11. Bull Test ID 1077 2013 Florida Bull Test

    E-Print Network [OSTI]

    Jawitz, James W.

    14th Annual Florida Bull Test #12;Bull Test ID 1077 2013 Florida Bull Test #12;Bull Test ID 1078 2013 Florida Bull Test #12;Bull Test ID 1079 2013 Florida Bull Test #12;Bull Test ID 1080 2013 Florida Bull Test #12;Bull Test ID 1081 2013 Florida Bull Test #12;Bull Test ID 1082 2013 Florida Bull Test #12

  12. ID SYSTEM DEBIT ACCOUNT Payroll Deduction Form

    E-Print Network [OSTI]

    Karsai, Istvan

    ID SYSTEM DEBIT ACCOUNT Payroll Deduction Form This is my authorization for the ETSU Payroll Department to make a monthly deduction from my paycheck to be deposited to my ETSU ID System Debit Card 37614-0611 PHONE: 423/439-8316 http://www.etsu.edu/students/univcent/id.htm e-mail ­ IDBUCS@etsu.edu #12;

  13. New Mexico State University ID Card Services

    E-Print Network [OSTI]

    Johnson, Eric E.

    New Mexico State University ID Card Services Aggie Cash Application IDS: This form constitutes application and agreement to open the following account with New Mexico State when it is in the possession of others. New Mexico State University ID Card Services Aggie Cash

  14. , 1. CONTRACT ID CODE IPAG~ O F PAGES

    E-Print Network [OSTI]

    .S. Department of Energy Pacific Northwest Site Office Post Office Box 350 Richland, WA 99352 8. NAME AND ADDRESS

  15. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01

    This presentation describes the importance of good forecasting for variable generation, the different approaches used by industry, and the importance of validated high-quality data.

  16. Wind Power 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking WithTelecentricNCubicthe FOIA?ResourceMeasurement BuoyForecasting Sign

  17. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

    s economy. Demand Forecasts The three energy futures wereto meet the forecast demand in each energy futurE2. e e1Ł~energy saved through improved appliance efficiencies. Also icit in our demand forecasts

  18. Price forecasting for notebook computers 

    E-Print Network [OSTI]

    Rutherford, Derek Paul

    1997-01-01

    of individual features are estimated. A time series analysis is used to forecast and can be used, for example, to forecast (1) notebook computer price at introduction, and (2) rate of price erosion for a notebook's life cycle. Results indicate that this approach...

  19. Multivariate Forecast Evaluation And Rationality Testing

    E-Print Network [OSTI]

    Komunjer, Ivana; OWYANG, MICHAEL

    2007-01-01

    Economy, 95(5), 1062—1088. MULTIVARIATE FORECASTS Chaudhuri,Notion of Quantiles for Multivariate Data,” Journal of thePress, United Kingdom. MULTIVARIATE FORECASTS Kirchgässner,

  20. VA VT CT RI MT WY CO ID UT OR NV CA AZ NM WA TN WV NC AR OK

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

    2 1 Locations of Smart Grid Demonstration and Large-Scale Energy Storage Projects NH 32 Awards Support Projects in 24 States 6 11 MA...

  1. VA VT CT RI MT WY CO ID UT OR NV CA AZ NM WA TN WV NC AR OK

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirley Ann Jackson About1996HowFOAShowing YouNeedofDepartment ofDeploymentDepartmentService2 1

  2. VA VT CT RI MT WY CO ID UT OR NV CA AZ NM WA TN WV NC AR OK

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirley Ann Jackson About1996HowFOAShowing YouNeedofDepartment ofDeploymentDepartmentService2 1 2 1

  3. VA VT CT RI MT WY CO ID UT OR NV CA AZ NM WA TN WV NC AR OK

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirley Ann Jackson About1996HowFOAShowing YouNeedofDepartment ofDeploymentDepartmentService2 1 2 1 7

  4. ID Ecoregion name ID Ecoregion name 103 Alaska & Canada Pacific Coastal 140 East Texas Gulf

    E-Print Network [OSTI]

    Sprott, Julien Clinton

    ID Ecoregion name ID Ecoregion name 103 Alaska & Canada Pacific Coastal 140 East Texas Gulf 107 California 135 Lower Rio Grande - Bravo 160 Sonora 139 West Texas Gulf 161 Guzman - Samalayuca #12;

  5. Graduate Assistant Commitment Form Eagle ID:________________________

    E-Print Network [OSTI]

    Hutcheon, James M.

    Graduate Assistant Commitment Form 1 Eagle ID:________________________ Name:_____________________________________________ Supervisor:______________________________________Dept./Unit unites within the University. Research Assistant (RA) ­ primary responsibility

  6. RAPID/Roadmap/1-WA-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevada <UtahMontanasourceWA-a < RAPID‎ |

  7. RAPID/Roadmap/11-WA-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevada <UtahMontanasourceWA-a <aaTX-a <bca

  8. RAPID/Roadmap/11-WA-b | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevada <UtahMontanasourceWA-a <aaTX-a

  9. RAPID/Roadmap/11-WA-c | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevada <UtahMontanasourceWA-a <aaTX-ac <

  10. RAPID/Roadmap/13-WA-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎ | Roadmap JumpfWA-a <

  11. RAPID/Roadmap/14-WA-c | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎ | RoadmapCO-ce <cdeWA-c

  12. RAPID/Roadmap/14-WA-e | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎ | RoadmapCO-ceWA-e <

  13. RAPID/Roadmap/18-WA-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎ |a <-AK-bNV-a <bb8-WA-a

  14. RAPID/Roadmap/19-WA-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎f < RAPID‎19-WA-a <

  15. RAPID/Roadmap/19-WA-b | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎f < RAPID‎19-WA-a <b

  16. RAPID/Roadmap/19-WA-c | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎f < RAPID‎19-WA-a <bc

  17. RAPID/Roadmap/19-WA-d | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎f < RAPID‎19-WA-a <bcd

  18. RAPID/Roadmap/19-WA-e | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎f < RAPID‎19-WA-a

  19. RAPID/Roadmap/19-WA-f | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎f < RAPID‎19-WA-af <

  20. RAPID/Roadmap/7-WA-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa <NV-b < RAPID‎WA-a < RAPID‎ |

  1. RAPID/Roadmap/5-WA-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EIS Report UrlNM-b < RAPID‎ | RoadmapAK-a <CA-aeNV-aUT-a <WA-a

  2. BayWa Sunways JV | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LIST OFAMERICA'S FUTURE.EnergyWoodenDateSAEngineering LLCBarner InvestmentBayWa

  3. DOE-ID Twitter 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would like submit theCovalent Bonding Low-Cost2 DOE HQSite toDOE, StateResearchers111DOE-ID

  4. DOE-ID Operations Summary

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformation Current HAB Packet HanfordDOE Project TapsofofDoubleReading Room10, 2013 DOE-ID

  5. DOE-ID Operations Summary

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformation Current HAB Packet HanfordDOE Project TapsofofDoubleReading1, 2015 DOE-ID

  6. DOE-ID Operations Summary

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformation Current HAB Packet HanfordDOE Project TapsofofDoubleReading1, 2015 DOE-ID4,

  7. DOE-ID Operations Summary

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformation Current HAB Packet HanfordDOE Project TapsofofDoubleReading1, 2015 DOE-ID4,25,

  8. ID BUC$ EQUIPMENT REQUEST FORM CAMPUS EVENT PAYMENT OPTION

    E-Print Network [OSTI]

    Karsai, Istvan

    ID BUC$ EQUIPMENT REQUEST FORM CAMPUS EVENT PAYMENT OPTION FOR ETSU ORGANIZATIONS Name ID BUC$. ETSU account transfer or a check requested? o ETSU Account

  9. U.S. NUclear WaSte techNical revieW Board

    E-Print Network [OSTI]

    , packaging, and transporting spent nuclear fuel and high-level radioactive waste is presented. The technical-level radioactive waste. Sincerely, B. John Garrick Chairman #12;NUclear WaSte techNical revieW Board 2005 Dr. BU.S. NUclear WaSte techNical revieW Board Report to The U.S. Congress and The Secretary

  10. The real costs of housing in WA BANKWEST CURTIN ECONOMICS CENTRE

    E-Print Network [OSTI]

    Mucina, Ladislav

    The real costs of housing in WA BANKWEST CURTIN ECONOMICS CENTRE Focus on Western Australia Report Series, No.2 April 2014 HOUSING AFFORDABILITY #12;About the Centre The Bankwest Curtin Economics Centre, public and not-for-profit sectors. #12;Contents HOUSING AFFORDABILITY The real costs of housing in WA

  11. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01

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

  12. Downscaling Extended Weather Forecasts for Hydrologic Prediction

    SciTech Connect (OSTI)

    Leung, Lai-Yung R.; Qian, Yun

    2005-03-01

    Weather and climate forecasts are critical inputs to hydrologic forecasting systems. The National Center for Environmental Prediction (NCEP) issues 8-15 days outlook daily for the U.S. based on the Medium Range Forecast (MRF) model, which is a global model applied at about 2? spatial resolution. Because of the relatively coarse spatial resolution, weather forecasts produced by the MRF model cannot be applied directly to hydrologic forecasting models that require high spatial resolution to represent land surface hydrology. A mesoscale atmospheric model was used to dynamically downscale the 1-8 day extended global weather forecasts to test the feasibility of hydrologic forecasting through this model nesting approach. Atmospheric conditions of each 8-day forecast during the period 1990-2000 were used to provide initial and boundary conditions for the mesoscale model to produce an 8-day atmospheric forecast for the western U.S. at 30 km spatial resolution. To examine the impact of initialization of the land surface state on forecast skill, two sets of simulations were performed with the land surface state initialized based on the global forecasts versus land surface conditions from a continuous mesoscale simulation driven by the NCEP reanalysis. Comparison of the skill of the global and downscaled precipitation forecasts in the western U.S. showed higher skill for the downscaled forecasts at all precipitation thresholds and increasingly larger differences at the larger thresholds. Analyses of the surface temperature forecasts show that the mesoscale forecasts generally reduced the root-mean-square error by about 1.5 C compared to the global forecasts, because of the much better resolved topography at 30 km spatial resolution. In addition, initialization of the land surface states has large impacts on the temperature forecasts, but not the precipitation forecasts. The improvements in forecast skill using downscaling could be potentially significant for improving hydrologic forecasts for managing river basins.

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

    E-Print Network [OSTI]

    Goto, Susumu

    2007-01-01

    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 ...

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

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

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

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    weather prediction solar irradiance forecasts in the US.2013: Review of solar irradiance forecasting methods and asatellite-derived irradiances: Description and validation.

  16. Id-1 and Id-2 genes and products as markers of epithelial cancer

    SciTech Connect (OSTI)

    Desprez, Pierre-Yves; Campisi, Judith

    2011-10-04

    A method for detection and prognosis of breast cancer and other types of cancer. The method comprises detecting expression, if any, for both an Id-1 and an Id-2 genes, or the ratio thereof, of gene products in samples of breast tissue obtained from a patient. When expressed, Id-1 gene is a prognostic indicator that breast cancer cells are invasive and metastatic, whereas Id-2 gene is a prognostic indicator that breast cancer cells are localized and noninvasive in the breast tissue.

  17. Id-1 and Id-2 genes and products as markers of epithelial cancer

    DOE Patents [OSTI]

    Desprez, Pierre-Yves (El Cerrito, CA); Campisi, Judith (Berkeley, CA)

    2008-09-30

    A method for detection and prognosis of breast cancer and other types of cancer. The method comprises detecting expression, if any, for both an Id-1 and an Id-2 genes, or the ratio thereof, of gene products in samples of breast tissue obtained from a patient. When expressed, Id-1 gene is a prognostic indicator that breast cancer cells are invasive and metastatic, whereas Id-2 gene is a prognostic indicator that breast cancer cells are localized and noninvasive in the breast tissue.

  18. SLAC Dosimeter / ID Request Form A

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

    Feb 2009 (updated 13 May 2010) SLAC-I-760-0A07J-006-R010 1 of 2 SLAC Dosimeter ID Request Form A (For applicants who have completed SLAC Environment, Safety, and Health Training)...

  19. Student ID (R) Number ________________________ Semester/Year______ ________________________

    E-Print Network [OSTI]

    Rock, Chris

    Student ID (R) Number ________________________ Semester/Year______ ________________________ THIRD: ______________________________________________________ CHECK ALL THAT APPLY: _____First-time Third Party Student _____TTU Campus Student _____Non sponsor and the Third Party Sponsor Agreement prior to the due date to ensure timely posting of third

  20. Kentucky WRI Pilot Test Universal ID

    E-Print Network [OSTI]

    screening deployment experience · Significant cost savings to FMCSA ·Enabling technology already deployedKentucky WRI Pilot Test ­ Universal ID Commercial Motor Vehicle Roadside Technology Corridor Safety Technology Showcase October 14, 2010 #12;·Utilizes existing automated screening system ·Uses assorted

  1. 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 ...

  2. 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 ...

  3. Forecasting consumer products using prediction markets

    E-Print Network [OSTI]

    Trepte, Kai

    2009-01-01

    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. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

    FORECASTING THE ROLE OF RENEWABLES IN HAWAII Jayant SathayeFORECASTING THE ROLF OF RENEWABLES IN HAWAII J Sa and Henrythe Conservation Role of Renewables November 18, 1980 Page 2

  5. NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    income 7 Figure 1.14: United States inflation Rate 8 Figure 1.15: Select United States interest Rates 8 2014 TABLE OF CONTENTS EXECUTiVE SUMMARY 1 CHAPTER 1: THE UNiTED STATES ECONOMY 3 Recent Trends Forecast Summary 2 CHAPTER 1: THE UNiTED STATES ECONOMY Figure 1.1: United States Real GDP Growth 3 Figure

  6. Advance Patent Waiver W(A)2009-016 | Department of Energy

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

    16 Advance Patent Waiver W(A)2009-016 This document waives certain patent rights the Department of Energy (DOE) has to inventions conceived or first actually reduced to practice by...

  7. Advance Patent Waiver W(A)2009-058 | Department of Energy

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

    09-058 Advance Patent Waiver W(A)2009-058 This document waives certain patent rights the Department of Energy (DOE) has to inventions conceived or first actually reduced to...

  8. Best Practices Case Study: Devoted Builders, LLC, Mediterrtanean Villas, Pasco,WA

    SciTech Connect (OSTI)

    2010-12-01

    Devoted Builders of Kennewick, WA worked with Building America's BIRA team to achieve the 50% Federal tax credit level energy savings on 81 homes at its Mediterranean Villas community in eastern Washington.

  9. Modeling and Forecasting Electric Daily Peak Loads

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    for the same data. Two methods are described for forecasting daily peak loads up to one week ahead through, including generator unit commitment, hydro-thermal coordination, short-term maintenance, fuel allocation forecasting accuracies. STLF forecasting covers the daily peak load, total daily energy, and daily load curve

  10. 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

  11. SHIELDING STUDIES FOR IDS80f-IDS120f NICHOLAS SOUCHLAS (BNL)

    E-Print Network [OSTI]

    McDonald, Kirk

    GEOMETRY 8 #12;IDS120f GEOMETRY:Hg POOL AREA DETAIL 8 #12;IDS120f GEOMETRY:PROTON TRAJECTORY WITHOUT Hg JET/POOL 9 Hg Pool free surface at y=-14 cm and -8pool>72.2 cm or >5

  12. Forecasting phenology under global warming

    E-Print Network [OSTI]

    Silander Jr., John A.

    Forecasting phenology under global warming Ine´s Iba´n~ez1,*, Richard B. Primack2, Abraham J in phenology. Keywords: climate change; East Asia, global warming; growing season, hierarchical Bayes; plant is shifting, and these shifts have been linked to recent global warming (Parmesan & Yohe 2003; Root et al

  13. 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

  14. $J$ functions for the process ud$\\to$WA

    E-Print Network [OSTI]

    D. Bardin; L. Kalinovskaya; E. Uglov; W. von Schlippe

    2014-12-29

    In this paper we present a description of the universal approach for analytic calculations for a certain class of $J$ functions for six topologies of the boxes for process $ud\\rightarrow WA$. These functions $J$ arise at the reduction of infrared divergent box diagrams. The standard Passarino--Veltman reduction of four-point box diagram with an internal photon line connecting two external lines on the mass shell leads to infrared-divergent and mass-singular $D_0$ functions. In the system SANC a systematic procedure is adopted to separate both types of singularities into the simplest objects, namely $C_0$ functions. The functions $J$, in turn, are represented as certain linear combinations of the standard $D_0$ and $C_0$ functions. The subtracted $J$ functions are free of both types of singularities and are expressed as explicit and compact linear combinations of dilogarithm functions. We present extensive comparisons of numerical results of SANC with those obtained with the aid of the LoopTools package.

  15. CHANGE IN ACCEPTABLE ID DOCUMENTS FOR JLAB ACCESS:

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

    JLAB ACCESS: The REAL ID Act (Public Law 109-13) now determines which state driver's license can be presented and accepted as a valid ID document for access to Jefferson Lab. The...

  16. 8-ID Home Page | Advanced Photon Source

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfateSciTechtail.TheoryTuesday, August 10, 20102016 News Below are4B Drawings 4B618-108-ID 8-ID Home

  17. Data ID Service | DOE Data Explorer

    Office of Scientific and Technical Information (OSTI)

    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01TechnicalScientific andScientificDOE Data ID Service DOE Data ID

  18. Forecasting wind speed financial return

    E-Print Network [OSTI]

    D'Amico, Guglielmo; Prattico, Flavio

    2013-01-01

    The prediction of wind speed is very important when dealing with the production of energy through wind turbines. In this paper, we show a new nonparametric model, based on semi-Markov chains, to predict wind speed. Particularly we use an indexed semi-Markov model that has been shown to be able to reproduce accurately the statistical behavior of wind speed. The model is used to forecast, one step ahead, wind speed. In order to check the validity of the model we show, as indicator of goodness, the root mean square error and mean absolute error between real data and predicted ones. We also compare our forecasting results with those of a persistence model. At last, we show an application of the model to predict financial indicators like the Internal Rate of Return, Duration and Convexity.

  19. Improving Inventory Control Using Forecasting

    E-Print Network [OSTI]

    Balandran, Juan

    2005-12-16

    and encouragement. I am very grateful to Lucille and Michael Hobbs for their friendship, understanding and financial support. Finally, thank you to Tom Decker, Pat Jackson and Brian Zellar for all their contributions and hard work on this project... below: 1. Na?ve 2. Linear Regression 3. Moving Average 4. Exponential 5. Double exponential The na?ve forecasting method assumes that more recent data values are the best predictors of future values. The model is ? t+1 = Y t . Where ? t...

  20. Grant ID#: 71316 South Carolina SIP 2 Workplan

    E-Print Network [OSTI]

    Grant ID#: 71316 South Carolina SIP 2 Workplan NPO Accepted Revision on 2/5/2015 1 South Carolina Complete #12;Grant ID#: 71316 South Carolina SIP 2 Workplan NPO Accepted Revision on 2/5/2015 2 Objectives grant success / challenges. May not meet On target to meet Complete #12;Grant ID#: 71316 South Carolina

  1. Comment on "d id0 Chiral Superconductivity

    E-Print Network [OSTI]

    Wu, Zhigang

    Comment on "d ţ id0 Chiral Superconductivity in Bilayer Silicene" In Ref. [1], Liu et al, their random-phase-approximation analysis sug- gests that the system is superconducting with the Cooper pairs, they claim that a high superconducting critical temperature is possible due to the tunable Fermi pocket via

  2. Study Abroad Agreement Student's Name: MSU ID

    E-Print Network [OSTI]

    Barge, Marcy

    Study Abroad Agreement Student's Name: MSU ID: Name of Institution: Country: Date Classes Begin University study abroad program. If you enroll in a study abroad program sponsored by other organizations and attach a signed copy of the Study Abroad Budget Form. Return both documents to the Office of Financial

  3. Optimal combined wind power forecasts using exogeneous variables

    E-Print Network [OSTI]

    Optimal combined wind power forecasts using exogeneous variables Fannar ¨Orn Thordarson Kongens to the Klim wind farm using three WPPT forecasts based on different weather forecasting systems. It is shown of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

  4. LAYNE, HOSPEDALES, GONG: RE-ID: HUNTING ATTRIBUTES IN THE WILD 1 Re-id: Hunting Attributes in the Wild

    E-Print Network [OSTI]

    Gong, Shaogang

    LAYNE, HOSPEDALES, GONG: RE-ID: HUNTING ATTRIBUTES IN THE WILD 1 Re-id: Hunting Attributes in the Wild Ryan Layne r.d.c.layne@qmul.ac.uk Timothy M. Hospedales t.hospedales@qmul.ac.uk Shaogang Gong s.gong, HOSPEDALES, GONG: RE-ID: HUNTING ATTRIBUTES IN THE WILD Much re-identification research breaks down into two

  5. Weather Forecasts are for Wimps: Why Water Resource Managers Do Not Use Climate Forecasts

    E-Print Network [OSTI]

    Rayner, Steve; Lach, Denise; Ingram, Helen

    2005-01-01

    and Winter, S. G. : 1960, Weather Information and EconomicThe ENSO Signal 7, 4–6. WEATHER FORECASTS ARE FOR WIMPSWEATHER FORECASTS ARE FOR WIMPS ? : WHY WATER RESOURCE

  6. The Preservation of Physical Fashion Forecasts

    E-Print Network [OSTI]

    Kosztowny, Alexander John

    2015-01-01

    schools and their libraries, which use trend forecastingin archives and libraries would be that the trend forecastsin a library or archive, not exclusively to trend forecasts.

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

    Energy Savers [EERE]

    R&D translates into improved performance and reduced costs for energy technologies. Motivation Technological forecasts, which plot the anticipated performance and costs of...

  8. Promotional forecasting in the grocery retail business

    E-Print Network [OSTI]

    Koottatep, Pakawkul

    2006-01-01

    Predicting customer demand in the highly competitive grocery retail business has become extremely difficult, especially for promotional items. The difficulty in promotional forecasting has resulted from numerous internal ...

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

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

    that take place in complex terrain, this funding opportunity will improve foundational weather models by developing short-term wind forecasts for use by industry professionals,...

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

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

    processes that take place in complex terrain, this funding would improve foundational weather models by developing short-term wind forecasts for use by industry professionals,...

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

    E-Print Network [OSTI]

    to the electricity price forecast. This resource mix is used to forecast the fuel consumption and carbon dioxide (CO2Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price forecast of the Fifth Northwest Power Plan. This forecast is an estimate of the future price of electricity

  12. 1Bureau of Meteorology | Water Information > INFORMATION SHEET 6 > Flood Forecasting and Warning Services Flood Forecasting

    E-Print Network [OSTI]

    Greenslade, Diana

    SHEET 6 1Bureau of Meteorology | Water Information > INFORMATION SHEET 6 > Flood Forecasting and Warning Services Flood Forecasting and Warning Services The Bureau of Meteorology (the Bureau) is responsible for providing an effective flood forecasting and warning service in each Australian state

  13. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines lightGeospatial ToolkitSMARTS -BeingFuture forForecasting NREL researchers

  14. 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar2-0057-EA Jump to:ofEnia SpAFlex Fuels Energy JumpVyncke Jump to:Forecast

  15. Forecasting Market Demand for New Telecommunications Services: An Introduction

    E-Print Network [OSTI]

    Parsons, Simon

    Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc in demand forecasting for new communication services. Acknowledgments: The writing of this paper commenced employers or consultancy clients. KEYWORDS: Demand Forecasting, New Product Marketing, Telecommunica- tions

  16. 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

  17. Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts

    E-Print Network [OSTI]

    Raftery, Adrian

    Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts VERONICA ensembles that generates calibrated probabilistic forecast products for weather quantities at indi- vidual perturbation (GOP) method, and extends BMA to generate calibrated probabilistic forecasts of whole weather

  18. AMENDMENT OF SOLIC ITATION/MODIFICATION OF CONTRACT 11. CONTRACT ID CODE

    E-Print Network [OSTI]

    ) ICODE CODE U.S. Department of Energy Pacific Northwest Site Office Post Office Box 350 Richland, WA

  19. AMENDMENT OF SOLICITATION/MODIFICATION OF CONTRACT 1. CONTRACT ID CODE

    E-Print Network [OSTI]

    .S. Department of Energy Pacific Northwest Site Office Post Office Box 350 Richland, WA 99352 8. NAM E

  20. Nonparametric models for electricity load forecasting

    E-Print Network [OSTI]

    Genčve, 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

  1. INTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev

    E-Print Network [OSTI]

    , discourse and semantic. They are based on a conceptual model underlying weather forecasts as well situations represented in the form of texts in NL, weather maps, data tables or combined information objectsINTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev I n s t i t u t e of Mathematics Acad

  2. Smooth Calibration, Leaky Forecasts, and Finite Recall

    E-Print Network [OSTI]

    Hart, Sergiu

    Smooth Calibration, Leaky Forecasts, and Finite Recall Sergiu Hart October 2015 SERGIU HART c 2015 ­ p. #12;Smooth Calibration, Leaky Forecasts, and Finite Recall Sergiu Hart Center for the Study of Rationality Dept of Mathematics Dept of Economics The Hebrew University of Jerusalem hart@huji.ac.il http://www.ma.huji.ac.il/hart

  3. Multivariate Time Series Forecasting in Incomplete Environments

    E-Print Network [OSTI]

    Roberts, Stephen

    Multivariate Time Series Forecasting in Incomplete Environments Technical Report PARG 08-03 Seung of Oxford December 2008 #12;Seung Min Lee and Stephen J. Roberts Technical Report PARG 08-03 Multivariate missing observations and forecasting future values in incomplete multivariate time series data. We study

  4. Weather and Forecasting EARLY ONLINE RELEASE

    E-Print Network [OSTI]

    Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary PDF of the author, Guangzhou 510301, China9 2. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological10, China20 21 22 23 24 Submitted to Weather and Forecasting25 2014. 12. 2826 27 Corresponding author: Dr

  5. Weather and Forecasting EARLY ONLINE RELEASE

    E-Print Network [OSTI]

    Johnson, Richard H.

    Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary PDF of the author Fort Collins, Colorado7 October 20128 (submitted to Weather and Forecasting)9 1 Corresponding author address: Rebecca D. Adams-Selin, HQ Air Force Weather Agency 16th Weather Squadron, 101 Nelson Dr., Offutt

  6. 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...

  7. Electrical impedance tomography and Calderon's Department of Mathematics, University of Washington, Seattle, WA 98195, USA

    E-Print Network [OSTI]

    Uhlmann, Gunther

    Electrical impedance tomography and Calder´on's problem G Uhlmann Department of Mathematics, University of Washington, Seattle, WA 98195, USA E-mail: gunther@math.washington.edu Abstract. We survey mathematical developments in the inverse method of Electrical Impedance Tomography which consists

  8. Proceedings of the Western Protective Relay Conference, Spokane, WA, 2006 New wide-area algorithms for

    E-Print Network [OSTI]

    " Venkatasubramanian School of Electrical Engineering and Computer Science Washington State University, Pullman, WA will discuss the new algorithms along with illustrative examples on standard IEEE test systems. #12;- 2 - 1 that heavy power-flows across long transmission lines weakens the operational security of the power system

  9. Local Stability of the Median LMS Filter W.A. Sethares // J.A. Bucklew

    E-Print Network [OSTI]

    Bucklew, James Antonio

    Local Stability of the Median LMS Filter W.A. Sethares // J.A. Bucklew November 17, 2000 1 #12; Abstract Local stability properties of the recently proposed median LMS adaptive filter are investigated. This will help delineate those applications for which the median LMS is an appropriate adaptive al­ gorithm

  10. An International Pellet Ablation Database L.R. Baylor, A. Geraud*, W.A. Houlberg,

    E-Print Network [OSTI]

    An International Pellet Ablation Database L.R. Baylor, A. Geraud*, W.A. Houlberg, D. Frigione+, M of an international pellet ablation database (IPADBASE) that has been assembled to enable studies of pellet ablation theories that are used to describe the physics of an ablating fuel pellet in a tokamak plasma. The database

  11. Proceedings ASCE International Water Resources Engineering Conference August 8-12, 1999, Seattle, WA

    E-Print Network [OSTI]

    Wells, Scott A.

    , WA #12;2 River Basin Modeling Using CE-QUAL-W2 Version 3 Scott A. Wells1 Introduction CE-QUAL-W2 hydraulic and water quality models in common use for unsteady flow include the 1-D dynamic EPA model DYNHYD the ability to characterize adequately the hydraulics or water quality of deeper reservoir systems or deep

  12. Earthquake Forecast via Neutrino Tomography

    E-Print Network [OSTI]

    Bin Wang; Ya-Zheng Chen; Xue-Qian Li

    2011-03-29

    We discuss the possibility of forecasting earthquakes by means of (anti)neutrino tomography. Antineutrinos emitted from reactors are used as a probe. As the antineutrinos traverse through a region prone to earthquakes, observable variations in the matter effect on the antineutrino oscillation would provide a tomography of the vicinity of the region. In this preliminary work, we adopt a simplified model for the geometrical profile and matter density in a fault zone. We calculate the survival probability of electron antineutrinos for cases without and with an anomalous accumulation of electrons which can be considered as a clear signal of the coming earthquake, at the geological region with a fault zone, and find that the variation may reach as much as 3% for $\\bar \

  13. Perl ASP Servlet JSP ID cookie encodeURL

    E-Print Network [OSTI]

    Chiba, Shigeru

    14 Servlet 99-2270-6 15 2 28 #12;1 Web Web Perl ASP Servlet JSP HTML Web ID Web ID ID cookie encode Servlet JSP 1.1 1963 70 1991 93 HTML #12;1 9 1.1.1 TCP/IP WWW(World Wide Web) · WWW WWW 1989 CERN(European Particle Physics Laboratory) Http Web / WWW HTML(Hyper Text Markup Language) HTML WWW WWW 1.2 Web · Java

  14. Property:RAPID/Contact/ID9/Name | Open Energy Information

    Open Energy Info (EERE)

    page using this property. U Utah Department of Environmental Quality + Doug Hansen + Retrieved from "http:en.openei.orgwindex.php?titleProperty:RAPIDContactID9...

  15. Forecasting Random Walks Under Drift Instability

    E-Print Network [OSTI]

    Pesaran, M Hashem; Pick, Andreas

    will yield a biased forecast but will continue to have the least variance. On the other hand a forecast based on the sub-sample {yTi , yTi+1, . . . , yT }, where Ti > 1 is likely to have a lower bias but could be inefficient due to a higher variance... approach considered in Pesaran and Timmermann (2007) is to use different sub-windows to forecast and then average the outcomes, either by means of cross-validated weights or by simply using equal weights. To this end consider the sample {yTi , yTi+1...

  16. 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)

    1993-08-01

    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.

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

    SciTech Connect (OSTI)

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

    2011-10-01

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

  18. Wind-Wave Probabilistic Forecasting based on Ensemble

    E-Print Network [OSTI]

    Wind-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 weather forecasts and do not take any possible correlation into ac- count. Since wind and wave forecasts

  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.

    2013-10-01

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

  20. 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 networks, Neural networks, Modeling, Forecasting, Energy demand, Time series forecasting, Power system demand time series based only on data for six years to forecast the demand for the seventh year. Both

  1. Id-1 and Id-2 genes and products as therapeutic targets for treatment of breast cancer and other types of carcinoma

    DOE Patents [OSTI]

    Desprez, Pierre-Yves; Campisi, Judith

    2014-09-30

    A method for treatment and amelioration of breast, cervical, ovarian, endometrial, squamous cells, prostate cancer and melanoma in a patient comprising targeting Id-1 or Id-2 gene expression with a delivery vehicle comprising a product which modulates Id-1 or Id-2 expression.

  2. Airless drying -- Developments since IDS'94

    SciTech Connect (OSTI)

    Stubbing, T.J.

    1999-09-01

    Since its introduction to IDS'94 delegates, significant progress has been made with the development of airless drying technology. The ceramic industry internationally is beginning to benefit from both the energy use and drying time reductions it achieves, while on the basis of further theoretical work carried out since 1993 other industries, including the bioenergy sector, should also soon begin to exploit its advantages. As global warming becomes a reality and oil reserves decline, superheated steam drying and gasification of biomass will contribute to the mitigation of those problems.

  3. 7-ID Home Page | Advanced Photon Source

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-InspiredAtmosphericdevicesPPONeApril351APPLICATION OF kVProposedLIST of77-ID

  4. 1. CONTRACT ID CODE PAGE OF PAGES

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-InspiredAtmosphericdevicesPPO Retirees with Medicare PlanCONTRACT ID CODE PAGE

  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. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand Bill Junker Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS

  7. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P

  8. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    /demographic growth, relatively low electricity and natural gas rates, and relatively low efficiency program CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity Manager Bill Junker Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY

  9. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    incorporates relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P. Oglesby Executive

  10. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    high economic/demographic growth, relatively low electricity and natural gas rates, and relatively low CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION

  11. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    incorporates relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P

  12. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand Gough Office Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS

  13. 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....

  14. Load Forecast For use in Resource Adequacy

    E-Print Network [OSTI]

    forecast of 4) Calculate Hourly Load Allocation Factor s for each day for 2019 For use in RA analysis as a function ofthe load for electricity in the region as a function of cyclical, weather and economic variables

  15. Wind Speed Forecasting for Power System Operation 

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22

    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...

  16. Testing Competing High-Resolution Precipitation Forecasts

    E-Print Network [OSTI]

    Gilleland, Eric

    Testing Competing High-Resolution Precipitation Forecasts Eric Gilleland Research Prediction Comparison Test D1 D2 D = D1 ­ D2 copyright NCAR 2013 Loss Differential Field #12;Spatial Prediction Comparison Test Introduced by Hering and Genton

  17. New product forecasting in volatile markets

    E-Print Network [OSTI]

    Baldwin, Alexander (Alexander Lee)

    2014-01-01

    Forecasting demand for limited-life cycle products is essentially projecting an arc trend of demand growth and decline over a relatively short time horizon. When planning for a new limited-life product, many marketing and ...

  18. 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 ...

  19. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01

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

  20. NO FISHING REPORTING FORM Vessel ID. NO. Vessel Name

    E-Print Network [OSTI]

    NO FISHING REPORTING FORM Vessel ID. NO. Vessel Name: During the entire month of , year this vessel fishery if your vessel does not have a permit for it > Use Black Ink NMFS Use Only: Opened: Atlantic King Mackerel Spanish Mackerel Schedule # NO FISHING REPORTING FORM Vessel ID. NO. Vessel Name: During

  1. IDS120h GEOMETRY WITH SHIELDING VESSELS ENERGY FLOW ANALYSIS

    E-Print Network [OSTI]

    McDonald, Kirk

    IDS120h GEOMETRY WITH SHIELDING VESSELS ENERGY FLOW ANALYSIS SHIELDING MATERIAL: 60% W + 40% He vs SHIELDING Nicholas Souchlas, PBL (10/18/2011) 1 #12;IDS120h with shielding vessels. # Different cases ENERGY CUTOFF >SHIELDING: 60% W + 40% He , 80% W + 20% He, 88% W + 12% He ( WITH W VESSELS) >4 MW proton

  2. ASPE -Instructor Led Class Vendor Item ID Class Cost

    E-Print Network [OSTI]

    Dennis, Robert G.

    ASPE - Instructor Led Class Vendor Item ID Class Cost 26500 Data Modeling - Onsite Session for up Day Course 1,871.00$ #12;ASPE - Virtual Class Vendor Item ID Class Cost 26500V Data Modeling - Onsite Session for up to 20 Students 9,500.00$ 26500PV Data Modeling - Public Course (price per student) 1

  3. Testing Buda-Lund hydro model on particle correlations and spectra in NA44, WA93 and WA98 heavy ion experiments

    E-Print Network [OSTI]

    A. Ster; T. Csorgo; B. Lorstad

    1998-09-28

    Analytic and numerical approximations to a hydrodynamical model describing longitudinally expanding, cylindrically symmetric, finite systems are fitted to preliminary NA44 data measured in 200 AGeV central $S + Pb$ reactions. The model describes the measured spectra and HBT radii of pions, kaons and protons, simultaneously. The source is characterized by a central freeze-out temperature of T_0 = 154 +/- 8 +/- 11 MeV, a "surface" temperature of T_r = 107 +/- 28 +/- 18 MeV and by a well-developed transverse flow, = 0.53 +/- 0.17 +/- 0.11. The transverse geometrical radius and the mean freeze-out time are found to be R_G = 5.4 +/- 0.9 +/- 0.7 fm and tau_0 = 5.1 +/- 0.3 +/- 0.3 fm/c, respectively. Fits to preliminary WA93 200 AGeV S + Au and WA98 158 AGeV Pb + Pb data dominated by pions indicate similar model parameters. The absolute normalization of the measured particle spectra together with the experimental determination of both the statistical and the systematic errors were needed to obtain successful fits.

  4. Intra-hour Direct Normal Irradiance solar forecasting using genetic programming

    E-Print Network [OSTI]

    Queener, Benjamin Daniel

    2012-01-01

    guideline for Solar Power Forecasting Performance . . 46 viof forecasting techniques for solar power production with noand A. Pavlovski, “Solar power forecasting performance

  5. A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

    of the WRF model solar irradiance forecasts in Andalusia (Beyer, H. , 2009.    Irradiance forecasting for the power dependent probabilistic irradiance  forecasts for coastal 

  6. Mathematics Of Ice To Aid Global Warming Forecasts Mathematics Of Ice To Aid Global Warming Forecasts

    E-Print Network [OSTI]

    Golden, Kenneth M.

    Mathematics Of Ice To Aid Global Warming Forecasts Mathematics Of Ice To Aid Global Warming forecasts of how global warming will affect polar icepacks. See also: Earth & Climate q Global Warming q the effects of climate warming, and its presence greatly reduces solar heating of the polar oceans." "Sea ice

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

    SciTech Connect (OSTI)

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

    2014-05-01

    The variable and uncertain nature of wind generation presents a new concern to power system operators. One of the biggest concerns associated with integrating a large amount of wind power into the grid is the ability to handle large ramps in wind power output. Large ramps can significantly influence system economics and reliability, on which power system operators place primary emphasis. The Wind Forecasting Improvement Project (WFIP) was performed to improve wind power forecasts and determine the value of these improvements to grid operators. This paper evaluates the performance of improved short-term wind power ramp forecasting. The study is performed for the Electric Reliability Council of Texas (ERCOT) by comparing the experimental WFIP forecast to the current short-term wind power forecast (STWPF). Four types of significant wind power ramps are employed in the study; these are based on the power change magnitude, direction, and duration. The swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental short-term wind power forecasts improve the accuracy of the wind power ramp forecasting, especially during the summer.

  8. Forecasting Prices andForecasting Prices and Congestion forCongestion for

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    Goal: Design nodal price and grid congestion forecasting tools for market operators and market Traders To facilitate scenario-conditioned planning Price forecasting for Market Participants (MPs) To manage short for portfolio management by power market participants Conclusion #12;Project OverviewProject Overview Project

  9. 1994 Solid waste forecast container volume summary

    SciTech Connect (OSTI)

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

    1994-09-01

    This report describes a 30-year forecast of the solid waste volumes by container type. The volumes described are low-level mixed waste (LLMW) and transuranic/transuranic mixed (TRU/TRUM) waste. These volumes and their associated container types will be generated or received at the US Department of Energy Hanford Site for storage, treatment, and disposal at Westinghouse Hanford Company`s Solid Waste Operations Complex (SWOC) during a 30-year period from FY 1994 through FY 2023. The forecast data for the 30-year period indicates that approximately 307,150 m{sup 3} of LLMW and TRU/TRUM waste will be managed by the SWOC. The main container type for this waste is 55-gallon drums, which will be used to ship 36% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of 55-gallon drums is Past Practice Remediation. This waste will be generated by the Environmental Restoration Program during remediation of Hanford`s past practice sites. Although Past Practice Remediation is the primary generator of 55-gallon drums, most waste generators are planning to ship some percentage of their waste in 55-gallon drums. Long-length equipment containers (LECs) are forecasted to contain 32% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of LECs is the Long-Length Equipment waste generator, which is responsible for retrieving contaminated long-length equipment from the tank farms. Boxes are forecasted to contain 21% of the waste. These containers are primarily forecasted for use by the Environmental Restoration Operations--D&D of Surplus Facilities waste generator. This waste generator is responsible for the solid waste generated during decontamination and decommissioning (D&D) of the facilities currently on the Surplus Facilities Program Plan. The remaining LLMW and TRU/TRUM waste volume is planned to be shipped in casks and other miscellaneous containers.

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

    E-Print Network [OSTI]

    Raftery, Adrian

    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

  11. New directions for forecasting air travel passenger demand

    E-Print Network [OSTI]

    Garvett, Donald Stephen

    1974-01-01

    While few will disagree that sound forecasts are an essential prerequisite to rational transportation planning and analysis, the making of these forecasts has become a complex problem with the broadening of the scope and ...

  12. Generalized Cost Function Based Forecasting for Periodically Measured Nonstationary Traffic

    E-Print Network [OSTI]

    Zeng, Yong - Department of Mathematics and Statistics, University of Missouri

    1 Generalized Cost Function Based Forecasting for Periodically Measured Nonstationary Traffic true value. However, such a forecast- ing function is not directly applicable for applications potentially result in insufficient allocation of bandwidth leading to short term data loss. To facilitate

  13. The effect of multinationality on management earnings forecasts 

    E-Print Network [OSTI]

    Runyan, Bruce Wayne

    2005-08-29

    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...

  14. Market perceptions of efficiency and news in analyst forecast errors 

    E-Print Network [OSTI]

    Chevis, Gia Marie

    2004-11-15

    Financial analysts are considered inefficient when they do not fully incorporate relevant information into their forecasts. In this dissertation, I investigate differences in the observable efficiency of analysts' earnings forecasts between firms...

  15. DOE Releases Latest Report on Energy Savings Forecast of Solid...

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

    Latest Report on Energy Savings Forecast of Solid-State Lighting DOE Releases Latest Report on Energy Savings Forecast of Solid-State Lighting September 12, 2014 - 2:06pm Addthis...

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

    E-Print Network [OSTI]

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

    2005-01-01

    Forecasts Using NEMS and GIS National Climatic Data Center.with Changing Boundaries." Use of GIS to Understand Socio-Forecasts Using NEMS and GIS Appendix A. Map Results Gallery

  17. OPERATIONAL EARTHQUAKE FORECASTING State of Knowledge and Guidelines for Utilization

    E-Print Network [OSTI]

    .................................................................................................................................... 323 II. SCIENCE OF EARTHQUAKE FORECASTING AND PREDICTION 325 A. Definitions and Concepts....................................................................................................................................... 325 B. Research on Earthquake PredictabilityOPERATIONAL EARTHQUAKE FORECASTING State of Knowledge and Guidelines for Utilization Report

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

    SciTech Connect (OSTI)

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

    2010-04-01

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

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

    SciTech Connect (OSTI)

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

    2010-04-15

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

  20. Property:RAPID/Contact/ID9/Website | Open Energy Information

    Open Energy Info (EERE)

    page using this property. U Utah Department of Environmental Quality + http:www.deq.utah.gov + Retrieved from "http:en.openei.orgwindex.php?titleProperty:RAPIDContactID9...

  1. Economics, Quantitative Emphasis BA, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Economics, Quantitative Emphasis BA, 2015-2016 Name ID# Date Course Number and Title Credits Quantitative Methods in Economics 3 FF ECON 422 Econometrics 3 Upper-division economics courses 16 MATH 175

  2. MINOR IN WEATHER AND CLIMATE (1913F) NAME___________________________________ ID# _______________________________

    E-Print Network [OSTI]

    Droegemeier, Kelvin K.

    MINOR IN WEATHER AND CLIMATE (1913F) NAME___________________________________ ID _______________ DATE_____________________________ A MINOR IN WEATHER AND CLIMATE REQUIRES A MINIMUM OF 15 HOURS IS REQUIRED. A MINOR IN WEATHER AND CLIMATE REQUIRES: A MINIMUM OF SIX HOURS FROM: METR 1014 WEATHER

  3. Managerial Career Concerns and Earnings Forecasts SARAH SHAIKH

    E-Print Network [OSTI]

    Tipple, Brett

    's aversion to risk, I find that a CEO is less likely to issue an earnings forecast in periods of stricter non is more pronounced for a CEO who has greater concern for his reputation, faces more risk in forecasting the provision of earnings forecasts. Literature has long recognized that the labor market provides distinct

  4. Forecasting Market Demand for New Telecommunications Services: An Introduction

    E-Print Network [OSTI]

    McBurney, Peter

    Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc to redress this situation by presenting a discussion of the issues involved in demand forecasting for new or consultancy clients. KEYWORDS: Demand Forecasting, New Product Marketing, Telecommunica­ tions Services. 1 #12

  5. Neural Network forecasts of the tropical Pacific sea surface temperatures

    E-Print Network [OSTI]

    Hsieh, William

    Neural Network forecasts of the tropical Pacific sea surface temperatures Aiming Wu, William W Tang Jet Propulsion Laboratory, Pasadena, CA, USA Neural Networks (in press) December 11, 2005 title: Forecast of sea surface temperature 1 #12;Neural Network forecasts of the tropical Pacific sea

  6. 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 Paulina Jaramillo Doctor Paul Fischbeck 2012 #12;ii #12;iii Managing Wind Power Forecast Uncertainty generated from wind power is both variable and uncertain. Wind forecasts provide valuable information

  7. Forecasting Uncertainty Related to Ramps of Wind Power Production

    E-Print Network [OSTI]

    Boyer, Edmond

    Forecasting 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. This paper presents two methods focusing on forecasting large and sharp variations in power output of a wind

  8. SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS

    E-Print Network [OSTI]

    Heinemann, Detlev

    SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS Detlev Heinemann Oldenburg in irradiance forecasting have been presented more than twenty years ago (Jensenius and Cotton, 1981), when or progress with respect to the development of solar irradiance forecasting methods. Heck and Takle (1987

  9. Choosing Words in Computer-Generated Weather Forecasts

    E-Print Network [OSTI]

    Reiter, Ehud

    to communicate numeric weather data. A corpus-based analysis of how humans write forecasts showed that there wereTime- Mousam weather-forecast generator to use consistent data-to-word rules, which avoided words which were weather forecast texts from numerical weather pre- diction data (SumTime-Mousam in fact is used

  10. Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging

    E-Print Network [OSTI]

    Raftery, Adrian

    Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging J. MCLEAN 2011, in final form 26 May 2012) ABSTRACT Probabilistic forecasts of wind vectors are becoming critical with univariate quantities, statistical approaches to wind vector forecasting must be based on bivariate

  11. Accuracy of near real time updates in wind power forecasting

    E-Print Network [OSTI]

    Heinemann, Detlev

    Accuracy of near real time updates in wind power forecasting with regard to different weather October 2007 #12;EMS/ECAM 2007 ­ Nadja Saleck Outline · Study site · Wind power forecasting - method #12;EMS/ECAM 2007 ­ Nadja Saleck Wind power forecast data observed wind power input (2004 ­ 2006

  12. Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging

    E-Print Network [OSTI]

    Raftery, Adrian

    Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging J. Mc in the context of wind power, where under- forecasting and overforecasting carry different financial penal- ties, calibrated and sharp probabilistic forecasts can help to make wind power a more financially competitive alter

  13. Forecasting Building Occupancy Using Sensor Network James Howard

    E-Print Network [OSTI]

    Hoff, William A.

    Forecasting Building Occupancy Using Sensor Network Data James Howard Colorado School of Mines@mines.edu ABSTRACT Forecasting the occupancy of buildings can lead to signif- icant improvement of smart heating throughout a building, we perform data mining to forecast occupancy a short time (i.e., up to 60 minutes

  14. Weather Forecasting -Predicting Performance for Streaming Video over Wireless LANs

    E-Print Network [OSTI]

    Claypool, Mark

    Weather Forecasting - Predicting Performance for Streaming Video over Wireless LANs Mingzhe Li, "weather forecasts" are created such that selected wireless LAN performance indicators might be used to evaluate the effec- tiveness of individual weather forecasts. The paper evaluates six distinct weather

  15. Weather Forecasting Predicting Performance for Streaming Video over Wireless LANs

    E-Print Network [OSTI]

    Claypool, Mark

    Weather Forecasting ­ Predicting Performance for Streaming Video over Wireless LANs Mingzhe Li, ``weather forecasts'' are created such that selected wireless LAN performance indicators might be used to evaluate the e#ec­ tiveness of individual weather forecasts. The paper evaluates six distinct weather

  16. 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

  17. Preprints, 15th AMS Conference on Weather Analysis and Forecasting

    E-Print Network [OSTI]

    Doswell III, Charles A.

    ) models have substantially improved forecast skill. Recent and planned changes along these lines (e to delivering two kinds of weather products. The first is a day-to-day forecast of weather elements, e by the private sector. Improvements in automated techniques for the forecasting of basic weather elements

  18. Influences of soil moisture and vegetation on convective precipitation forecasts

    E-Print Network [OSTI]

    Robock, Alan

    Influences of soil moisture and vegetation on convective precipitation forecasts over the United and vegetation on 30 h convective precipitation forecasts using the Weather Research and Forecasting model over, the complete removal of vegetation produced substantially less precipitation, while conversion to forest led

  19. DOE Zero Energy Ready Home Case Study: Dwell Development, Seattle, WA,

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n c i pStateDOE FederalTheofHeyeck, AEP, Sr.EnergyWA |

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    of Solar 2011, American Solar Energy Society, Raleigh, NC.Description and validation. Solar Energy, 73 (5), 307-317.forecast database. Solar Energy, Perez, R. , S. Kivalov, J.

  1. Online short-term solar power forecasting

    SciTech Connect (OSTI)

    Bacher, Peder; Madsen, Henrik [Informatics and Mathematical Modelling, Richard Pedersens Plads, Technical University of Denmark, Building 321, DK-2800 Lyngby (Denmark); Nielsen, Henrik Aalborg [ENFOR A/S, Lyngsoe Alle 3, DK-2970 Hoersholm (Denmark)

    2009-10-15

    This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h. The data used is 15-min observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques. Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to 2 h ahead the most important input is the available observations of solar power, while for longer horizons NWPs are the most important input. A root mean square error improvement of around 35% is achieved by the ARX model compared to a proposed reference model. (author)

  2. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    1998-07-01

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

  3. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    1996-08-01

    This document consists of papers which cover topics in analysis and modeling that underlie the Annual Energy Outlook 1996. Topics include: The Potential Impact of Technological Progress on U.S. Energy Markets; The Outlook for U.S. Import Dependence; Fuel Economy, Vehicle Choice, and Changing Demographics, and Annual Energy Outlook Forecast Evaluation.

  4. Forecasting Hot Water Consumption in Residential Houses

    E-Print Network [OSTI]

    MacDonald, Mark

    and technological advancement in energy-intensive applications are causing fast electric energy consumption growth and consumption of electricity [8], as long as there is no significant correlation between intermittent energyArticle Forecasting Hot Water Consumption in Residential Houses Linas Gelazanskas * and Kelum A

  5. GENETIC ALGORITHM FORECASTING FOR TELECOMMUNICATIONS PRODUCTS

    E-Print Network [OSTI]

    Havlicek, Joebob

    available economic indicators such as Disposable Personal Income and New Housing Starts as independent exhibiting maximal fitness achieved RMS forecast errors below the the average two-week sales figure. 1 (Holland, 1975), (Packard, 1990), (Koza, 1992), (Bäck, et al., 1997), (Mitchell, 1998). For example, Meyer

  6. GOES Aviation Products Aviation Weather Forecasting

    E-Print Network [OSTI]

    Kuligowski, Bob

    GOES Aviation Products · The GOES aviation forecast products are based on energy measured in different characteristics #12;GOES Aviation Products Quiz · What is a geostationary satellite? · What generates energy received by the satellite in the visible band? · What generates energy received by the satellite

  7. Solar Forecasting System and Irradiance Variability Characterization

    E-Print Network [OSTI]

    solar forecasting system based on numerical weather prediction plus satellite and ground-based data.1 Photovoltaic Systems: Report 3 Development of data base allowing managed access to statewide PV and insolation Based Data 13 Summary 14 References 14 #12;List of Figures Figure Number and Title Page # 1. Topography

  8. Segmenting Time Series for Weather Forecasting

    E-Print Network [OSTI]

    Reiter, Ehud

    summarisation. We found three alternative ways in which we could model data summarisation. One approach is based turbines. In the domain of meteorology, time series data produced by numerical weather prediction (NWP) models is summarised as weather forecast texts. In the domain of gas turbines, sensor data from

  9. "FLIGHT PLAN" FORECASTS SEATTLE/TACOMA AND

    E-Print Network [OSTI]

    ASSESSMENT OF THE "FLIGHT PLAN" FORECASTS FOR SEATTLE/TACOMA AND REGIONAL AIRPORTS TOGETHER 1. Introduction 5 2. Airport Planning Process 7 Traditional Master Planning Application to Seattle/Tacoma. Uncertainty about Capacity 27 A Fuzzy Concept Assessment Factors Application to Seattle/Tacoma 7. Assessment

  10. 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

  11. Forecasting Turbulent Modes with Nonparametric Diffusion Models

    E-Print Network [OSTI]

    Tyrus Berry; John Harlim

    2015-01-27

    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.

  12. Stochastic Weather Generator Based Ensemble Streamflow Forecasting

    E-Print Network [OSTI]

    Stochastic Weather Generator Based Ensemble Streamflow Forecasting by Nina Marie Caraway B of Civil Engineering 2012 #12;This thesis entitled: Stochastic Weather Generator Based Ensemble Streamflow mentioned discipline. #12;iii Caraway, Nina Marie (M.S., Civil Engineering) Stochastic Weather Generator

  13. A 110-Day Ensemble Forecasting Scheme for the Major River Basins of Bangladesh: Forecasting Severe Floods of 200307*

    E-Print Network [OSTI]

    Webster, Peter J.

    A 1­10-Day Ensemble Forecasting Scheme for the Major River Basins of Bangladesh: Forecasting Severe of the Brahmaputra and Ganges Rivers as they flow into Bangladesh; it has been operational since 2003. The Bangladesh points of the Ganges and Brahmaputra into Bangladesh. Forecasts with 1­10-day horizons are presented

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

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

    Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

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

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01

    This paper proposes a methodology to include the wind power forecasting ability, or 'forecastability,' of a site as a design criterion in wind resource assessment and wind power plant design stages. The Unrestricted Wind Farm Layout Optimization (UWFLO) methodology is adopted to maximize the capacity factor of a wind power plant. The 1-hour-ahead persistence wind power forecasting method is used to characterize the forecastability of a potential wind power plant, thereby partially quantifying the integration cost. A trade-off between the maximum capacity factor and the forecastability is investigated.

  16. Combinatorial Evolution and Forecasting of Communication Protocol ZigBee

    E-Print Network [OSTI]

    Levin, Mark Sh; Kistler, Rolf; Klapproth, Alexander

    2012-01-01

    The article addresses combinatorial evolution and forecasting of communication protocol for wireless sensor networks (ZigBee). Morphological tree structure (a version of and-or tree) is used as a hierarchical model for the protocol. Three generations of ZigBee protocol are examined. A set of protocol change operations is generated and described. The change operations are used as items for forecasting based on combinatorial problems (e.g., clustering, knapsack problem, multiple choice knapsack problem). Two kinds of preliminary forecasts for the examined communication protocol are considered: (i) direct expert (expert judgment) based forecast, (ii) computation of the forecast(s) (usage of multicriteria decision making and combinatorial optimization problems). Finally, aggregation of the obtained preliminary forecasts is considered (two aggregation strategies are used).

  17. Transit Vehicles as Traffic Probe Sensors F.W. Cathey, University of Washington, Dept. of Electrical Engineering, Box 352500, Seattle, WA, 98195-2500,

    E-Print Network [OSTI]

    TRB 02-2228 Transit Vehicles as Traffic Probe Sensors F.W. Cathey, University of Washington, Dept. of Electrical Engineering, Box 352500, Seattle, WA, 98195-2500, phone 206-616-3185, fax 206-616-1787, fritz@its.washington.edu D.J. Dailey, University of Washington, Dept. of Electrical Engineering, Box 352500, Seattle, WA

  18. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

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

    2014-12-30

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

  19. Two techniques for forecasting clear air turbulence 

    E-Print Network [OSTI]

    Arbeiter, Randolph George

    1977-01-01

    result in only mild annoyance or discomfort (air sickness) to crew and passengers. As it becomes moderate, difficulty may be experienced in moving about inside the airplane and the crew may momentarily lose control. Severe CAT can result in injury... successfully used by the Air Force Clobal Heather Central (Barnett, 1970) for oper" tional forecasting on a day-to-day basis. Furthermore, its usefulness 1' or supersonic aircraft in the stratosphere v;as successfully demonstrated by Scoggins et H. (1975...

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

    SciTech Connect (OSTI)

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

    2015-08-05

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

  1. Solar Wind Forecasting with Coronal Holes

    E-Print Network [OSTI]

    S. Robbins; C. J. Henney; J. W. Harvey

    2007-01-09

    An empirical model for forecasting solar wind speed related geomagnetic events is presented here. The model is based on the estimated location and size of solar coronal holes. This method differs from models that are based on photospheric magnetograms (e.g., Wang-Sheeley model) to estimate the open field line configuration. Rather than requiring the use of a full magnetic synoptic map, the method presented here can be used to forecast solar wind velocities and magnetic polarity from a single coronal hole image, along with a single magnetic full-disk image. The coronal hole parameters used in this study are estimated with Kitt Peak Vacuum Telescope He I 1083 nm spectrograms and photospheric magnetograms. Solar wind and coronal hole data for the period between May 1992 and September 2003 are investigated. The new model is found to be accurate to within 10% of observed solar wind measurements for its best one-month periods, and it has a linear correlation coefficient of ~0.38 for the full 11 years studied. Using a single estimated coronal hole map, the model can forecast the Earth directed solar wind velocity up to 8.5 days in advance. In addition, this method can be used with any source of coronal hole area and location data.

  2. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

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

    2011-02-23

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

  3. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect (OSTI)

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

    2014-11-13

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

  4. Global disease monitoring and forecasting with Wikipedia

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

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

    2014-11-13

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

  5. W.A. SERDIJN: "A CLASSIFICATION OF ELECTRONIC SIGNAL-PROCESSING FUNCTIONS" 1 A classification of electronic signal-processing

    E-Print Network [OSTI]

    Serdijn, Wouter A.

    W.A. SERDIJN: "A CLASSIFICATION OF ELECTRONIC SIGNAL-PROCESSING FUNCTIONS" 1 A classification classification of electronic signal-processing functions is proposed. Electronic signals can either be 1 sources, wave- shaping circuits, digital logic functions, digital memories, power supplies, and converters

  6. TWRIa n n u a l r e p o r t The Texas waTer

    E-Print Network [OSTI]

    Mukhtar, Saqib

    The sole designaTed waTer resources insTiTuTe in Texas since 1952. Securing and managing sufficient three programmatic areas: · Water Quality Improvement · Water Sustainability and Security · Water Resources Research Act of 1964. That act established water resources institutes in each state and provided

  7. "I'd Like to Check Out Two Books, One DVD, and One Electrical...

    Energy Savers [EERE]

    "I'd Like to Check Out Two Books, One DVD, and One Electrical Meter, Please." "I'd Like to Check Out Two Books, One DVD, and One Electrical Meter, Please." December 8, 2009 -...

  8. MA 261 EXAM II Fall 2001 Page 1/6 NAME STUDENT ID ...

    E-Print Network [OSTI]

    1910-20-20

    I.D.# is your 9 digit ID (probably your social security number). Also write your name at the top of ... information about the nature of f(1, -1). D. fxx(1, -1)fyy(1, -1) < 0.

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  10. RAPID/Roadmap/14-ID-c | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EIS Report UrlNM-b < RAPID‎ | Roadmap JumpNV-a <CA-cID-a <ID-c

  11. The Commission Forecast 1992 Report: Important Resource Planning Issues 

    E-Print Network [OSTI]

    Adib, P.

    1992-01-01

    FORECAST 1992 REPORT: IMPORTANT RESOURCE PLANNING ISSUES PARVIZ ADIB MANAGER, ECONOMIC ANALYSIS SECTION ELECTRIC DIVISION PUBLIC UTILITY COMMISSION OF TEXAS ABSTRACT There is a general agreement among experts in the electric utility industry... there are many important issues in the preparation of a utility's electric resource plan, the Commission staff will address a few important ones in the next Commission Forecast Report (Forecast '92). In particular, the Commission staff will insure...

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

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

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01

    function. The forecasts of oil, coal and gas prices as wellforecasts for natural gas consumption, electricity sales, coal and electricity prices,

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

    E-Print Network [OSTI]

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

    2011-01-01

    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

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

    E-Print Network [OSTI]

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

    2005-01-01

    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

  16. Electric Grid - Forecasting system licensed | ornl.gov

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

    Electric Grid - Forecasting system licensed Location Based Technologies has signed an agreement to integrate and market an Oak Ridge National Laboratory technology that provides...

  17. Ramping Effect on Forecast Use: Integrated Ramping (Presentation...

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

    the shift from ramping. * the benefits - better use of forecast values (load or net load) - reduce the amount of variability that the regulation reserve must accommodate...

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

    SciTech Connect (OSTI)

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

    2015-12-08

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

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

    E-Print Network [OSTI]

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

    2006-01-01

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

  20. Nuclear Theory Helps Forecast Neutron Star Temperatures | U.S...

    Office of Science (SC) Website

    Nuclear Theory Helps Forecast Neutron Star Temperatures Nuclear Physics (NP) NP Home About Research Facilities Science Highlights Benefits of NP Funding Opportunities Nuclear...

  1. TASD Update 2Alan Bross IDS Plenary Meeting Mumbai October 12-14, 2009

    E-Print Network [OSTI]

    McDonald, Kirk

    TASD Update #12;2Alan Bross IDS Plenary Meeting ­ Mumbai October 12-14, 2009 Fine Plenary Meeting ­ Mumbai October 12-14, 2009 TASD Performance Event Reconstruction Efficiency Muon charge mis-ID rate #12;4Alan Bross IDS Plenary Meeting ­ Mumbai October 12-14, 2009 TASD Performance II

  2. APPLICATION to TEACHER EDUCATION PROGRAM(S) NAME: STUDENT ID#

    E-Print Network [OSTI]

    Minnesota, University of

    APPLICATION to TEACHER EDUCATION PROGRAM(S) NAME: STUDENT ID#: CAMPUS ADDRESS: CAMPUS EMAIL applying to enter the following teacher licensure program(s): Early Childhood Education (Birth through Grade 3) Elementary Education (Kindergarten through Grade 6) I understand the following admission

  3. SENIOR HONORS THESIS CONTRACT Honors Student Name: Student ID

    E-Print Network [OSTI]

    Lawrence, Rick L.

    SENIOR HONORS THESIS CONTRACT HONR 490 Honors Student Name: Student ID: Date Submitted: The Senior Honors Thesis is an independent research/creativity project that enables Honors students to synthesize. At the completion of the Senior Honors Thesis, a public presentation of your work is required. A copy of the thesis

  4. Bachelor of Science, Geophysics, 2013-2014 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Bachelor of Science, Geophysics, 2013-2014 Name ID# Date General Degree Requirements Residency with Lab 4 COMPSCI 115 Introduction to C 2 GEOPH 201 Seeing the Unseen: an Introduction to Geophysics 4 GEOPH 300 Physics of the Earth 3 GEOPH 305 Applied Geophysics 3 GEOPH 420 Geophysical Applications

  5. History BA, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    History BA, 2015-2016 Name ID# Date Course Number and Title Credits Completed InProgress Future Government (recommended) 3 DLS Social Sciences course in a second field other than history 3 One year of college level foreign language in sequence Language equivalency required by the history department

  6. History, Secondary Education BA, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    History, Secondary Education BA, 2015-2016 Name ID# Date Course Number and Title Credits Completed equivalency required by the history department will be determined by the department of modern languages or the history department. 8 HIST 111/211 United States History 3 HIST 112/212 United States History 3 CID HIST

  7. Mathematics BS, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Mathematics BS, 2015-2016 Name ID# Date Course Number and Title Credits Completed In Progress and Foundational Mathematics I 3 MATH 275 Multivariable and Vector Calculus 4 CID MATH 287 Communication in the Mathematical Sciences 3 MATH 305 Intro to Abstract Algebra & Number Theory 3 MATH 314 Foundations of Analysis 3

  8. Applied Mathematics BS, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Applied Mathematics BS, 2015-2016 Name ID# Date Course Number and Title Credits Completed Mathematics I 3 MATH 275 Multivariable and Vector Calculus 4 CID MATH 287 Communication in the Mathematical To Computational Mathematics 3 FF MATH 401 Senior Thesis in the Mathematical Sciences 1 MATH 465 Numerical Analysis

  9. IDS120h GEOMETRY SHIELDING VESSELS: STAINLESS STEEL vs. TUNGSTEN

    E-Print Network [OSTI]

    McDonald, Kirk

    IDS120h GEOMETRY SHIELDING VESSELS: STAINLESS STEEL vs. TUNGSTEN SHIELDING MATERIAL: 60%WC+40%H2 O shielding vessels (STST OR W) Different cases of shielding material. >mars1510/MCNP >10-11 MeV NEUTRON ENERGY CUTOFF >SHIELDING:60%WC+40%H2 O (STST or W VESSELS), 80%WC+20%He, 80%W+20%He (W VESSELS) >4 MW

  10. Article ID: Query Translation on the Fly in Deep Web

    E-Print Network [OSTI]

    Article ID: Query Translation on the Fly in Deep Web Integration Jiang Fangjiao, Jia Linlin, Meng users to access the desired information, many researches have dedicated to the Deep Web (i.e. Web databases) integration. We focus on query translation which is an important part of the Deep Web integration

  11. CONTROL ID: 1187959 TITLE: Climate destabilization on tidally locked exoplanets

    E-Print Network [OSTI]

    CONTROL ID: 1187959 TITLE: Climate destabilization on tidally locked exoplanets PRESENTATION TYPE-zone rocky planets, should be tidally locked. We will discuss two different feedbacks that can destabilize cause a runaway climate shift. We use an idealized energy balance model to illustrate the scope

  12. ORNL 2010-G01074/jcn UT-B ID 200301298

    E-Print Network [OSTI]

    of the hybrid phase change material in the heat pump cycle. The material combines Group I and II halides Keith Rice, Super Energy Saver Heat Pump with Dynamic Hybrid Phase Change Material, U.S. Patent 7ORNL 2010-G01074/jcn UT-B ID 200301298 Super Energy Saver Heat Pump Technology Summary ORNL

  13. Marketing BBA, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Marketing BBA, 2015-2016 Name ID# Date Course Number and Title Credits Completed In Progress Future MGMT 301 Leadership Skills 3 MKTG 301 Principles of Marketing 3 MKTG 307 Customer Behavior 3 MKTG 315 Marketing Research 3 MKTG 321 Professional Selling 3 MKTG 425 Marketing Planning Applications 3 PSYC 101

  14. Visual Art BA, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Visual Art BA, 2015-2016 Name ID# Date Course Number and Title Credits Completed InProgress Future Survey of Western Art I 3 DLL Literature and Humanities 3-4 DLS Social Sciences course in a first field 3 DLS Social Sciences course in a second field 3 ART 107, 108 Art Foundations I and II 6 ART 109

  15. Photo ID Form 2014-15 Queen's University at Kingston

    E-Print Network [OSTI]

    Fletcher, Robin

    Photo ID Form 2014-15 Queen's University at Kingston Office of the University Registrar The personal information on the `Photo Identification Student Card' form is collected under the authority of the University Registrar to create your photo identification student card. Your photo will be made available

  16. Physics BS, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Physics BS, 2015-2016 Name ID# Date Physics BS Credits Completed In Progress Future ENGL 101 Foundations 3 UF 200 Civic and Ethical Foundations 3 DLM MATH 170 Calculus I 4 DLN PHYS 211, 211L Physics I with Calculus & Lab 5 DLN PHYS 212, 212L Physics II with Calculus & Lab 5 DLV Visual and Performing Arts 3 DLL

  17. Physics BS, Astrophysics Emphasis, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Physics BS, Astrophysics Emphasis, 2015-2016 Name ID# Date Course Number and Title Credits 4 DLN PHYS 211, 211L Physics I with Calculus & Lab 5 DLN PHYS 212, 212L Physics II with Calculus Electronics 4 PHYS 309, 309L Introductory Quantum Physics & Lab 4 PHYS 311 Modern Physics 3 PHYS 325

  18. Biomedical Engineering Minor, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Biomedical Engineering Minor, 2015-2016 Name ID# Date Course Number and Title Credits Completed InProgress Future BIOL 191 General Biology I 4 BIOL/ME/MSE 477 Biomaterials 3 ENGR 210 Engineering Statics* 3 ME 112 Introduction to Biomedical Engineering 1 ME 356 Introduction to Solid Biomechanics 3 One of the following

  19. Civil Engineering BS, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Civil Engineering BS, 2015-2016 Name ID# Date Course Number and Title Credits Completed In course in a second field* 3 CE 210, 211 Engineering Surveying and Lab 3 CE 280 Civil Engineering Case Studies 2 CE 282 Engineering Practice 3 CE 284 Computational Methods 2 CE 320 Principles of Environmental

  20. Mechanical Engineering BS, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Mechanical Engineering BS, 2015-2016 Name ID# Date Course Number and Title Credits Completed Mechanical Engineering Graphics 3 ME 271 Introduction to Computation for Engineers 3 ME 302 or ENGR 320 or ENGR 330, 331 Fluid Mechanics and Lab 4 ME 350 or CE 350 or ENGR 350 Engineering Mechanics of Materials

  1. Music, Composition BM, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Music, Composition BM, 2015-2016 Name ID# Date Course Number and Title Credits Completed 3-4 DLV MUS 100 Introduction to Music 3 DLL Literature and Humanities 3-4 DLS Social Sciences course in a first field 3 DLS Social Sciences course in a second field 3 MUS 119, 120, 219, 220 Materials of Music

  2. Music Education BM, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Music Education BM, 2015-2016 Name ID# Date Course Number and Title Credits Completed In Progress Introduction to Music 3 DLL Literature and Humanities 3-4 DLS ED-CIFS 201 Foundations of Education 3 DLS Social 119*, 120, 219, 220 Materials of Music (*with grade of C or higher this course satisfies

  3. Music BA, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Music BA, 2015-2016 Name ID# Date Course Number and Title Credits Completed In Progress Future ENGL Introduction to Music 3 DLL Literature and Humanities 3-4 DLS Social Sciences course in a first field 3 DLS Social Sciences course in a second field 3 MUS 119, 120, 219, 220 Materials of Music 12 MUS 121, 122 221

  4. ORNL 2010-G00967/jcn UT-B ID 200802057

    E-Print Network [OSTI]

    ORNL 2010-G00967/jcn UT-B ID 200802057 Treatment of Fuel Process Wastewater Using Fuel Cells Technology Summary ORNL researchers invented a method using microbial fuel cells for cleansing fuel processing water of hydrocarbon by-products and metal salts. This cost efficient method can be used on

  5. Biology BS, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Biology BS, 2015-2016 Name ID# Date Course Number and Title Credits Completed InProgress Future General Biology I 4 DLN CHEM 111, 111L General Chemistry I with Lab 4 DLV Visual and Performing Arts 3 DLL in a second field 3 BIOL 192 General Biology II 4 BIOL 301 Cell Biology 3 CID BIOL 323 Ecology 4 BIOL 343

  6. Biology BS, Microbiology Emphasis, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Biology BS, Microbiology Emphasis, 2015-2016 Name ID# Date Course Number and Title Credits 170 4 DLN BIOL 191 General Biology I 4 DLN CHEM 111, 111L General Chemistry I with Lab 4 DLV Visual Sciences course in a second field 3 BIOL 192 General Biology II 4 BIOL 301 Cell Biology 3 CID BIOL 323

  7. Biology BS, Ecology Emphasis, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Biology BS, Ecology Emphasis, 2015-2016 Name ID# Date Course Number and Title Credits Completed DLN BIOL 191 General Biology I 4 DLN CHEM 111, 111L General Chemistry I with Lab 4 DLV Visual Sciences course in a second field 3 BIOL 192 General Biology II 4 BIOL 301 Cell Biology 3 CID BIOL 323

  8. Biology BS, Botany Emphasis, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Biology BS, Botany Emphasis, 2015-2016 Name ID# Date Course Number and Title Credits Completed DLN BIOL 191 General Biology I 4 DLN CHEM 111, 111L General Chemistry I with Lab 4 DLV Visual Sciences course in a second field 3 BIOL 192 General Biology II 4 BIOL 301 Cell Biology 3 CID BIOL 323

  9. Biology BS, Zoology Emphasis, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Biology BS, Zoology Emphasis, 2015-2016 Name ID# Date Course Number and Title Credits Completed In General Biology I 4 DLN CHEM 111, 111L General Chemistry I with Lab 4 DLV Visual and Performing Arts 3 DLL in a second field 3 BIOL 192 General Biology II 4 BIOL 301 Cell Biology 3 CID BIOL 323 Ecology 4 BIOL 343

  10. Communication BA, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Communication BA, 2015-2016 Name ID# Date Course Number and Title Credits Completed In and Performing Arts 3 DLL Literature and Humanities 3-4 DLS COMM 101 Fundamentals of Communication 3 DLS Social Sciences course in a second field 3 Communication Arts - choose one from the following: COMM 131, COMM 211

  11. Psychology BS, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Psychology BS, 2015-2016 Name ID# Date Course Number and Title Credits Completed InProgress Future Sciences course in a second field 3 BIOL 228 Human Anatomy and Physiology 4 PSYC 101 General Psychology 3 PSYC 120 Introduction to the Psychology Major 2 PSYC 295 Statistical Methods 3 CID PSYC 321 Research

  12. Psychology Taster Days in Schools and FE Colleges (ID:317)

    E-Print Network [OSTI]

    Martin, Ralph R.

    Psychology Taster Days in Schools and FE Colleges (ID:317) Outline The University's Psychology department brings its students and staff to local schools and colleges to discuss studying psychology Psychology at Higher Education level. A pre-planned programme of events will focus on Psychology as a Science

  13. Electrical Engineering BS, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Electrical Engineering BS, 2015-2016 Name ID# Date Course Number and Title Credits Completed In, 121L Computer Science I and lab 4 CS 221 Computer Science II 3 ECE 210 Introduction to Electric ECE 380, 380L Electrical Engineering Practice and Lab 3 ECE 480 Senior Design Project I 3 FF ECE 482

  14. Kinesiology BS, Biomechanics Emphasis, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Kinesiology BS, Biomechanics Emphasis, 2015-2016 Name ID# Date Course Number and Title Credits, 331 Exercise Physiology and Lab 4 KINES 363 Exercise Psychology 3 KINES 370, 371 Biomechanics and Lab Biomechanics 3 #12;PHYS 211, 211L Physics I with Calculus and Lab 5 PHYS 212, 212L Physics II with Calculus

  15. Social Science AA, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Social Science AA, 2015-2016 Name ID# Date Course Number and Title Credits Completed In, & Applied Sciences course with lab 4 DLN Natural, Physical, and Applied Sciences course 3-4 DLV Visual and Performing Arts 3 DLL Literature and Humanities 3-4 DLS COMM 101 or COMM 112 3 DLS Social Sciences course

  16. Social Science BS, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Social Science BS, 2015-2016 Name ID# Date Course Number and Title Credits Completed In, & Applied Sciences course with lab 4 DLN Natural, Physical, and Applied Sciences course 3-4 DLV Visual and Performing Arts 3 DLL Literature and Humanities 3-4 DLS Social Sciences course in a first field 3 DLS Social

  17. Residency Pre-Screening Form (pre) Name ____________________________ ID#____________________________

    E-Print Network [OSTI]

    Maxwell, Bruce D.

    much more quickly. COMPLETED RESIDENCY QUESTIONNAIRE YES MONTANA DRIVER'S LICENSE OR STATE ID YES N/A ISSUE DATE _________ If you do not have a copy of your MT Driver's License contact the local Department-TO-DATE YES NO YTD AMOUNT _________ MONTANA STATE INCOME TAX RETURN YES NO N/A FINANCIAL AID: AWARD LETTER

  18. https://doyouliveunited.org 1. Enter you user ID

    E-Print Network [OSTI]

    Search' button. 7. Enter you search terms for the agency of your choice and click on `Search'. #12;httpshttps://doyouliveunited.org 1. Enter you user ID: your email address Enter your password: welcome be different then the options listed here. 5. For a payroll pledge, enter the amount per pay or the total

  19. Computer Science BS, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Computer Science BS, 2015-2016 Name ID# Date Course Number and Title Credits Completed In DLS ENGL 202 Technical Communication 3 CS 121, 121L Computer Science I and Lab 4 CS 221 Computer Science II 3 CID CS 230 Ethical Issues in Computing 3 CS 253 Introduction to Systems Programming 3 CS 321

  20. Chemistry BS, Forensics Emphasis, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Chemistry BS, Forensics Emphasis, 2015-2016 Name ID# Date Course Number and Title Credits Completed 4 DLN CHEM 111, 111L General Chemistry I with Lab 4 DLN PHYS 211, 211L Physics I with Calculus & Lab and Justice 3 DLS Social Sciences course in a second field 3 CHEM 112, 112L General Chemistry II & Lab 4 CHEM

  1. Chemistry BS, Biochemistry Emphasis, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Chemistry BS, Biochemistry Emphasis, 2015-2016 Name ID# Date Course Number and Title Credits 4 DLN CHEM 111, 111L General Chemistry I with Lab 4 DLN PHYS 211, 211L Physics I with Calculus & Lab in a first field 3 DLS Social Sciences course in a second field 3 CHEM 112, 112L General Chemistry II & Lab 4

  2. Economics BA, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Economics BA, 2015-2016 Name ID# Date Course Number and Title Credits Completed InProgress Future Intermediate Macroeconomics 3 CID ECON 421 Quantitative Methods in Economics 3 FF ECON 422 Econometrics 3 Upper-division economics courses 15 Upper-division mathematics, business, or environmental studies courses or social

  3. Business Economics BBA, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Business Economics BBA, 2015-2016 Name ID# Date Course Number and Title Credits Completed 305 Intermediate Macroeconomics 3 ECON 421 Quantitative Methods in Economics 3 ECON 422 Econometrics 3 Upper-division economics electives 15 FINAN 303 Principles of Finance 3 GENBUS 101 Business for the New

  4. IST Taguspark lana Programa Escola 2.0 Id: 40472638

    E-Print Network [OSTI]

    Instituto de Sistemas e Robotica

    .php?option=com_content&task=view&id=105828&pop=1&page=0&Itemid=302 Texto: Escrito por CienciaPT 28-Feb-2012 O Campus do Taguspark do Instituto Superior Técnico celebrou hoje, dia 28 de Fevereiro, ŕs 12h00

  5. Environmental Studies Minor, 2015-2016 Name ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Environmental Studies Minor, 2015-2016 Name ID# Date Course Number and Title Credits Completed InProgress Future ENVSTD 121 Introduction to Environmental Studies 3 GEOG 100 Introduction to Geography 3 *ANTH 314 Environmental Anthropology or *BIOL 323 Ecology or *GEOG 321 Conservation of Natural Resources 3-4 *ECON 333

  6. Environmental Studies Major Checklist 2013-2014 Name: ID# Date

    E-Print Network [OSTI]

    Barrash, Warren

    Environmental Studies Major Checklist 2013-2014 Name: ID# Date: Course Number and Title Credits DLN GEOS 101 Global environmental science PREREQ: Math 108 or higher 4 DLV Visual and Performing Arts to Environmental studies 3 CID ENVSTD 221 People and Nature PREREQ: ENSTD 121 and ENG 102 4 ENVSTD 491 Project

  7. Exam 1 Phys 105 Section______Fall 2002 Name__________________________________ ID

    E-Print Network [OSTI]

    Gary, Dale E.

    Exam 1 Phys 105 Section______Fall 2002 Name__________________________________ ID: Closed book exam each. Work out problems are 4 points each. Passing of the exam requires at least 50% of the maximum an expression, a t2 /2 where a is acceleration and t is time. The dimension of this expression in the SI system

  8. UT-B ID 200701930 ORNL 2010-G00649/jcn

    E-Print Network [OSTI]

    UT-B ID 200701930 ORNL 2010-G00649/jcn Skin-Like Prosthetic Polymer Surfaces Technology Summary, 2009. Inventors John T. Simpson1 and Ilia N. Ivanov2 1 Engineering Science and Technology Division 2 Materials Science and Technology Division Oak Ridge National Laboratory Licensing Contact Gregory C

  9. EIA lowers forecast for summer gasoline prices

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural GasNatural GasEIA lowers forecast for summer gasoline prices

  10. RAPID/Roadmap/11-ID-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevada <UtahMontanasourceWA-a <a

  11. RAPID/Roadmap/12-ID-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevada <UtahMontanasourceWA-aCA-a

  12. RAPID/Roadmap/15-ID-b | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎ | RoadmapCO-ceWA-eb <

  13. RAPID/Roadmap/8-ID-c | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa <NV-b < RAPID‎WA-aFD-b <a <c

  14. Motivation Methods Model configuration Results Forecasting Summary & Outlook Retrieving direct and diffuse radiation with the

    E-Print Network [OSTI]

    Heinemann, Detlev

    Motivation Methods Model configuration Results Forecasting Summary & Outlook 1/ 14 Retrieving. 17, 2015 #12;Motivation Methods Model configuration Results Forecasting Summary & Outlook 2/ 14 Motivation Sky Imager based shortest-term solar irradiance forecasts for local solar energy applications

  15. ECMWF analyses and forecasts of 500 mb synoptic-scale activity during wintertime blocking 

    E-Print Network [OSTI]

    Matson, David Michael

    1993-01-01

    An observational study of 500 mb atmospheric blocking is conducted based on an European Centre for Medium-Range Weather Forecasts (ECMWF) wintertime analysis and forecast dataset during dynamic extended range forecasting ...

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01

    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

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01

    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

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

    E-Print Network [OSTI]

    Smith, Emily (Emily C.)

    2010-01-01

    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 ...

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01

    revisions to the EIA’s natural gas price forecasts in AEOon the AEO 2005 natural gas price forecasts will likely onceComparison of AEO 2005 Natural Gas Price Forecast to NYMEX

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01

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

  1. HOW ACCURATE ARE WEATHER MODELS IN ASSISTING AVALANCHE FORECASTERS? M. Schirmer, B. Jamieson

    E-Print Network [OSTI]

    Jamieson, Bruce

    HOW ACCURATE ARE WEATHER MODELS IN ASSISTING AVALANCHE FORECASTERS? M. Schirmer, B. Jamieson and decision makers strongly rely on Numerical Weather Prediction (NWP) models, for example on the forecasted on forecasted precipitation. KEYWORDS: Numerical weather prediction models, validation, precipitation 1

  2. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

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

    2010-05-01

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

  3. 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

  4. Using Neural Networks to Forecast Stock Market Prices Ramon Lawrence

    E-Print Network [OSTI]

    Lawrence, Ramon

    Using Neural Networks to Forecast Stock Market Prices Ramon Lawrence Department of Computer Science on the application of neural networks in forecasting stock market prices. With their ability to discover patterns in nonlinear and chaotic systems, neural networks offer the ability to predict market directions more

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Impact of PV forecasts uncertainty in batteries management in microgrids Andrea Michiorri Arthur-based battery schedule optimisation in microgrids in presence of network constraints. We examine a specific case production forecast algorithm is used in combination with a battery schedule optimisation algorithm. The size

  6. Forecasting Hot Water Consumption in Dwellings Using Artifitial Neural Networks

    E-Print Network [OSTI]

    MacDonald, Mark

    electricity consumption in time. This paper investigates the ability on Artificial Neural Networks to predict shift electric energy. Keywords--Hot Water Consumption; Forecasting; Artifitial Neural Networks; SmartForecasting Hot Water Consumption in Dwellings Using Artifitial Neural Networks Linas Gelazanskas

  7. Draft for Public Comment Appendix A. Demand Forecast

    E-Print Network [OSTI]

    in the forecast of electricity consumption for those years has been less than one half of a percent. Figure A-1 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

  8. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    of transportation fuel and crude oil import requirements. The transportation energy demand forecasts make. The transportation fuel and crude oil import requirement assessments build on assumptions about California crude oil forecasts, transportation energy, gasoline, diesel, jet fuel, crude oil production, fuel imports, crude oil

  9. A Deep Hybrid Model for Weather Forecasting Aditya Grover

    E-Print Network [OSTI]

    Horvitz, Eric

    @microsoft.com ABSTRACT Weather forecasting is a canonical predictive challenge that has depended primarily on model-based methods. We ex- plore new directions with forecasting weather as a data- intensive challenge that involves the joint statistics of a set of weather-related vari- ables. We show how the base model can be enhanced

  10. Hydrological Forecasting Improvements Primary Investigator: Thomas Croley -NOAA GLERL (Emeritus)

    E-Print Network [OSTI]

    multiple data streams in a near-real-time manner and incorporate them into the AHPS data base, run for matching weather forecasts with historical data, and prepare extensive forecasts of hydrology probabilities maximum use of all available information and be based on efficient and true hydrological process models

  11. DEEP COMPREHENSION, GENERATION AND TRANSLATION OF WEATHER FORECASTS (WEATHRA)

    E-Print Network [OSTI]

    in a data base and graphic representation with tile standard meteorological icons on a map, e.g. iconsDEEP COMPREHENSION, GENERATION AND TRANSLATION OF WEATHER FORECASTS (WEATHRA) by BENGT SIGURD, Sweden E-mail: linglund@gemini.ldc.lu.se FAX:46-(0)46 104210 Introduction and abstract Weather forecasts

  12. Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    markets could aid in the design of appropriate price forecasting tools for such markets. Scenario1 Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets Qun Zhou, restructured wholesale power markets, scenario generation, ARMA model, moment-matching method I. INTRODUCTION

  13. Probabilistic forecasting of solar flares from vector magnetogram data

    E-Print Network [OSTI]

    Barnes, Graham

    Probabilistic forecasting of solar flares from vector magnetogram data G. Barnes,1 K. D. Leka,1 E to solar flare forecasting, adapted to provide the probability that a measurement belongs to either group, the groups in this case being solar active regions which produced a flare within 24 hours and those

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

    E-Print Network [OSTI]

    Singhal, Gaurav

    2012-10-19

    Real-time wave forecasts are critical to a variety of coastal and offshore opera- tions. NOAA’s global wave forecasts, at present, do not extend into many coastal regions of interest. Even after more than two decades of the historical Exxon Valdez...

  15. Human Trajectory Forecasting In Indoor Environments Using Geometric Context

    E-Print Network [OSTI]

    . In addressing this problem, we have built a model to estimate the occupancy behavior of humans based enhancement in the accuracy of trajectory forecasting by incorporating the occupancy behavior model. Keywords Trajectory forecasting, human occupancy behavior, 3D ge- ometric context 1. INTRODUCTION Given a human

  16. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    . Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data Office. Andrea Gough ran the summary energy model and supervised data preparation. Glen Sharp prepared models. Both the staff revised energy consumption and peak forecasts are slightly higher than

  17. 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 at wind energy sites are becoming paramount. Regime-switching space-time (RST) models merge meteorological forecast regimes at the wind energy site and fits a conditional predictive model for each regime

  18. MAINTENANCE, UPGRADE AND VERIFICATION OF OPERATIONAL FORECASTS OF

    E-Print Network [OSTI]

    MAINTENANCE, UPGRADE AND VERIFICATION OF OPERATIONAL FORECASTS OF CLOUD COVER AND WATER VAPOUR Purchase Order 58311/ODG/99/8362/GWI/LET #12;i PREFACE Starting in August 1998, operational forecasts satellite imagery from the Co-operative Institute for Research in the Atmosphere (CIRA) and upper

  19. Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids

    E-Print Network [OSTI]

    Hwang, Kai

    1 Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids Yogesh Simmhan. One of the characteristic applications of Smart Grids is demand response optimization (DR). The goal of DR is to use the power consumption time series data to reliable forecast the future consumption

  20. THE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD

    E-Print Network [OSTI]

    THE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD ENERGY SERVICES by Steven Groves BASc of Research Project: The Desire to Acquire: Forecasting the Evolution of Household Energy Services Report No, and gasoline. A fixed effects panel model was used to examine the relationship of demand for energy

  1. Airplanes Aloft as a Sensor Network for Wind Forecasting

    E-Print Network [OSTI]

    Horvitz, Eric

    Airplanes Aloft as a Sensor Network for Wind Forecasting Ashish Kapoor, Zachary Horvitz, Spencer for observing weather phenomena at a continental scale. We focus specifically on the problem of wind forecasting with the sensed winds. The experiments show the promise of using airplane in flight as a large-scale sensor

  2. Classification of Commodity Price Forecast With Random Forests and Bayesian

    E-Print Network [OSTI]

    Freitas, Nando de

    on the sentiment of price39 forecasts and reports for commodities such as gold, natural gas or most commonly oil or natural gas can impact everything from the21 critical business decisions made within nationsClassification of Commodity Price Forecast Sentiment With Random Forests and Bayesian Optimization

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

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

    114 Solar Irradiance And Power Output Variabilityand L. Bangyin. Online 24-h solar power forecasting based onNielsen. Online short-term solar power forecasting. Solar

  4. A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

    of numerical weather prediction solar irradiance forecasts numerical weather prediction model for solar irradiance weather prediction for intra?day solar  forecasting in the 

  5. Building Electricity Load Forecasting via Stacking Ensemble Learning Method with Moving Horizon Optimization

    E-Print Network [OSTI]

    Burger, Eric M.; Moura, Scott J.

    2015-01-01

    K. W. Yau, “Predicting electricity energy con- sumption: Afor building-level electricity load forecasts,” Energy andannealing algorithms in electricity load forecasting,”

  6. Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts ............................................................................................................................ 5 U.S. Natural Gas Commodity Prices

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

    SciTech Connect (OSTI)

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

    2014-10-27

    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.

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01

    Comparison of AEO 2009 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01

    Comparison of AEO 2008 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01

    Comparison of AEO 2006 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01

    Comparison of AEO 2007 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

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

  13. IDS120h GEOMETRY WITH MODIFIED Hg POOL VESSEL SIMULATIONS FOR 60% W + 40% He SHIELDING (P12 'POINT') WITH

    E-Print Network [OSTI]

    McDonald, Kirk

    IDS120h GEOMETRY WITH MODIFIED Hg POOL VESSEL SIMULATIONS FOR 60% W + 40% He SHIELDING (P12 'POINT POWER DISTRIBUTION. Nicholas Souchlas, PBL (1/24/2012) 1 #12;IDS120hm: (m IS FOR) modified Hg pool 'POINT'). >GAUSSIAN PROFILE: x = y = 0.12 cm. 2 #12;3 IDS120hm GEOMETRY = IDS120h WITH MODIFIED Hg POOL

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

    SciTech Connect (OSTI)

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

    2012-07-01

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

  15. EIS-0473: W.A. Parish Post-Combustion CO2 Capture and Sequestration Project (PCCS), Fort Bend County, TX

    Broader source: Energy.gov [DOE]

    This EIS evaluates the environmental impacts of a proposal to provide financial assistance for a project proposed by NRG Energy, Inc (NRG). DOE selected NRG’s proposed W.A. Parish Post-Combustion CO2 Capture and Sequestration Project for a financial assistance award through a competitive process under the Clean Coal Power Initiative Program. NRG would design, construct and operate a commercial-scale carbon dioxide (CO2) capture facility at its existing W.A. Parish Generating Station in Fort Bend County, Texas; deliver the CO2 via a new pipeline to the existing West Ranch oil field in Jackson County, Texas, for use in enhanced oil recovery operations; and demonstrate monitoring techniques to verify the permanence of geologic CO2 storage.

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

    Reports and Publications (EIA)

    2010-01-01

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

  17. Leverhulme research network: ID20060104 EUROBRISA Page 1 of 6

    E-Print Network [OSTI]

    periods). For example, seasonal forecasts of rainfall are used for decision-making in hydropower electricity production in South America. Hydropower accounts for the major source of electricity production management, hydropower production, and agriculture). B Description of the institutions involved The proposed

  18. Leverhulme research network: ID20060104 EUROBRISA Page 1 of 6

    E-Print Network [OSTI]

    decision- making in several key areas such as energy production, agriculture, and water resources planning in several South American countries: 60% in Bolivia, Brazil, Colombia, Paraguay and Uruguay; and 40/northeast Brazil, northeast Argentina, Paraguay, Uruguay and south of Brazil. Forecast skill heavily depends

  19. 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)

    2011-12-06

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

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

    SciTech Connect (OSTI)

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

    2005-07-01

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

  1. Science and Engineering of an Operational Tsunami Forecasting System

    SciTech Connect (OSTI)

    Gonzalez, Frank

    2009-04-06

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

  2. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema (OSTI)

    Gonzalez, Frank

    2010-01-08

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

  3. CloudCast: Cloud Computing for Short-term Mobile Weather Forecasts

    E-Print Network [OSTI]

    Shenoy, Prashant

    of Massachusetts Amherst Abstract--Since today's weather forecasts only cover large regions every few hours algorithm for generating accurate short-term weather forecasts. We study CloudCast's design space, which One useful application is mobile weather forecasting, which provides hour-to-hour forecasts

  4. 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

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

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

    Solar irradiance data . . . . . . . . . . . . .Irradiance . . . . . . . . . . . . . . . . . . . . . . . . . . .4 Forecasting Solar Irradiance With GOES-West Satellite

  6. Ensemble Kalman Filter Data Assimilation in a 1D Numerical Model Used for Fog Forecasting

    E-Print Network [OSTI]

    Ensemble Kalman Filter Data Assimilation in a 1D Numerical Model Used for Fog Forecasting SAMUEL RE, a need exists for accurate and updated fog and low-cloud forecasts. Couche Brouillard Eau Liquide (COBEL for the very short-term forecast of fog and low clouds. This forecast system assimilates local observations

  7. Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction

    E-Print Network [OSTI]

    Raftery, Adrian

    Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction LE proposes an effective bias correction technique for wind direction forecasts from numerical weather forecasts. These techniques are applied to 48-h forecasts of surface wind direction over the Pacific

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

    Office of Energy Efficiency and Renewable Energy (EERE)

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

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

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

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

  10. 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

  11. Improved forecasts of extreme weather events by future space borne Doppler wind lidar

    E-Print Network [OSTI]

    Marseille, Gert-Jan

    of forecast failures, in particular those with large socio economic impact. Forecast failures of high- impact on their ability to improve meteorological analyses and subsequently reduce the probability of forecast failures true atmospheric state. This was generated by the European Centre for Medium-Range Weather Forecasts

  12. Solar Trackers Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

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

    E-Print Network [OSTI]

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

    2015-03-29

    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 ($e_{\\zeta}$).

  14. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

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

  15. Forecasting and Risk Analysis in Supply Chain Management

    E-Print Network [OSTI]

    Hilmola, Olli-Pekka

    Forecasting is an underestimated field of research in supply chain management. Recently advanced methods are coming into use. Initial results are encouraging, but often require changes in policies for collaboration and ...

  16. 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...

  17. PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022

    E-Print Network [OSTI]

    low electricity and natural gas rates, and relatively low efficiency program and self Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert Oglesby Executive Director DISCLAIMER Staff for electric vehicles. #12;ii #12;iii ABSTRACT The Preliminary California Energy Demand Forecast 2012

  18. 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 ...

  19. Multidimensional approaches to performance evaluation of competing forecasting models 

    E-Print Network [OSTI]

    Xu, Bing

    2009-01-01

    The purpose of my research is to contribute to the field of forecasting from a methodological perspective as well as to the field of crude oil as an application area to test the performance of my methodological contributions ...

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

    E-Print Network [OSTI]

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

    2015-01-01

    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 ($e_{\\zeta}$).

  1. Optimally controlling hybrid electric vehicles using path forecasting

    E-Print Network [OSTI]

    Katsargyri, Georgia-Evangelina

    2008-01-01

    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. ...

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

    E-Print Network [OSTI]

    Ham, Joy L

    2002-01-01

    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 ...

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

    E-Print Network [OSTI]

    Simmons, Joshua T. (Joshua Thomas)

    2007-01-01

    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. ...

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

    E-Print Network [OSTI]

    Adut, Davit

    2004-09-30

    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...

  5. Radiation fog forecasting using a 1-dimensional model 

    E-Print Network [OSTI]

    Peyraud, Lionel

    2001-01-01

    weather patterns known to be favorable for producing fog and once it has formed, to state that it will persist unless the pattern changes. Unfortunately, while such methods have shown some success, many times they have led weather forecasters astray...

  6. Pressure Normalization of Production Rates Improves Forecasting Results 

    E-Print Network [OSTI]

    Lacayo Ortiz, Juan Manuel

    2013-08-07

    reliable production forecasting technique suited to interpret unconventional wells in specific situations such as unstable operating conditions, limited availability of production data (short production history) and high-pressure, rate-restricted wells...

  7. Forecasting Stock Market Volatility: Evidence from Fourteen Countries. 

    E-Print Network [OSTI]

    Balaban, Ercan; Bayar, Asli; Faff, Robert

    2002-01-01

    This paper evaluates the out-of-sample forecasting accuracy of eleven models for weekly and monthly volatility in fourteen stock markets. Volatility is defined as within-week (within-month) standard deviation of continuously ...

  8. Adaptive sampling and forecasting with mobile sensor networks

    E-Print Network [OSTI]

    Choi, Han-Lim

    2009-01-01

    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 ...

  9. 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

  10. Forecasting the probability of forest fires in Northeast Texas 

    E-Print Network [OSTI]

    Wadleigh, Stuart Allen

    1972-01-01

    FORECASTING THE PROBABILITY OF FOREST FIRES IN NORTHEAST TEXAS A Thesis by STUART ALLEN WADLEIGH Submit ted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE... December 1972 Major Subject: Meteorology FORECASTING THE PROBABILITY OF FOREST FIRES IN NORTHEAST TEXAS A Thesis by STUART ALLEN WADLEIGH Approved as to style and content by: ( irman of ee) (Head of Depar nt) (Member) (Member) December 1972 c...

  11. Forecasting potential project risks through leading indicators to project outcome 

    E-Print Network [OSTI]

    Choi, Ji Won

    2007-09-17

    for the degree of MASTER OF SCIENCE May 2007 Major Subject: Civil Engineering FORECASTING POTENTIAL PROJECT RISKS THROUGH LEADING INDICATORS TO PROJECT OUTCOME A Thesis by JI WON CHOI... Guikema Head of Department, David Rosowsky May 2007 Major Subject: Civil Engineering iii ABSTRACT Forecasting Potential Project Risks through Leading Indicators to Project Outcome. (May 2007) Ji Won Choi, B.S., Han-Yang University...

  12. Point-trained models in a grid environment: Transforming a potato late blight risk forecast for use with the National Digital Forecast Database

    E-Print Network [OSTI]

    Douches, David S.

    Point-trained models in a grid environment: Transforming a potato late blight risk forecast for use with the National Digital Forecast Database Kathleen Baker a, , Paul Roehsner a , Thomas Lake b , Douglas Rivet

  13. Weather-based forecasts of California crop yields

    SciTech Connect (OSTI)

    Lobell, D B; Cahill, K N; Field, C B

    2005-09-26

    Crop yield forecasts provide useful information to a range of users. Yields for several crops in California are currently forecast based on field surveys and farmer interviews, while for many crops official forecasts do not exist. As broad-scale crop yields are largely dependent on weather, measurements from existing meteorological stations have the potential to provide a reliable, timely, and cost-effective means to anticipate crop yields. We developed weather-based models of state-wide yields for 12 major California crops (wine grapes, lettuce, almonds, strawberries, table grapes, hay, oranges, cotton, tomatoes, walnuts, avocados, and pistachios), and tested their accuracy using cross-validation over the 1980-2003 period. Many crops were forecast with high accuracy, as judged by the percent of yield variation explained by the forecast, the number of yields with correctly predicted direction of yield change, or the number of yields with correctly predicted extreme yields. The most successfully modeled crop was almonds, with 81% of yield variance captured by the forecast. Predictions for most crops relied on weather measurements well before harvest time, allowing for lead times that were longer than existing procedures in many cases.

  14. 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

    2000-01-01

    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...

  15. Value of Probabilistic Weather Forecasts: Assessment by Real-Time Optimization of Irrigation Scheduling

    SciTech Connect (OSTI)

    Cai, Ximing; Hejazi, Mohamad I.; Wang, Dingbao

    2011-09-29

    This paper presents a modeling framework for real-time decision support for irrigation scheduling using the National Oceanic and Atmospheric Administration's (NOAA's) probabilistic rainfall forecasts. The forecasts and their probability distributions are incorporated into a simulation-optimization modeling framework. In this study, modeling irrigation is determined by a stochastic optimization program based on the simulated soil moisture and crop water-stress status and the forecasted rainfall for the next 1-7 days. The modeling framework is applied to irrigated corn in Mason County, Illinois. It is found that there is ample potential to improve current farmers practices by simply using the proposed simulation-optimization framework, which uses the present soil moisture and crop evapotranspiration information even without any forecasts. It is found that the values of the forecasts vary across dry, normal, and wet years. More significant economic gains are found in normal and wet years than in dry years under the various forecast horizons. To mitigate drought effect on crop yield through irrigation, medium- or long-term climate predictions likely play a more important role than short-term forecasts. NOAA's imperfect 1-week forecast is still valuable in terms of both profit gain and water saving. Compared with the no-rain forecast case, the short-term imperfect forecasts could lead to additional 2.4-8.5% gain in profit and 11.0-26.9% water saving. However, the performance of the imperfect forecast is only slightly better than the ensemble weather forecast based on historical data and slightly inferior to the perfect forecast. It seems that the 1-week forecast horizon is too limited to evaluate the role of the various forecast scenarios for irrigation scheduling, which is actually a seasonal decision issue. For irrigation scheduling, both the forecast quality and the length of forecast time horizon matter. Thus, longer forecasts might be necessary to evaluate the role of forecasts for irrigation scheduling in a more effective way.

  16. Results from the Second Forum on the Future Role of the Human in the Forecast Process. Part II: Cognitive Psychological Aspects of Expert Weather Forecasters

    E-Print Network [OSTI]

    Schultz, David

    : Cognitive Psychological Aspects of Expert Weather Forecasters NEIL A. STUART* NOAA/National Weather Service of Applied Research Associates, Fairborn, Ohio In Preparation for Submission to Forecasters Forum, Weather and Forecasting 30 June 2006 Corresponding author address: Neil A. Stuart, National Weather Service, 10009 General

  17. DOE-ID Procurement Services ďż˝ the action team

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would like submit theCovalent Bonding Low-Cost2 DOE HQSite toDOE, StateResearchers111DOE-ID

  18. File:INL-geothermal-id.pdf | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History View New Pages Recent Changes AllApschem.pdfgasp 03.pdf JumpGerak.pdf Jump to:hi.pdf Jump to:id.pdf

  19. Property:HPBD/ProjectId | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 Jump to: navigation, search This isGeothermalArraAwardeeCostShareProjectId

  20. RAPID/Roadmap/13-ID-a | Open Energy Information

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    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 onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎ | Roadmap Jumpf <ID-a <

  1. RAPID/Roadmap/14-ID-d | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎ | RoadmapCO-c <FD-cID-d

  2. RAPID/Roadmap/19-ID-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎f < RAPID‎ | RoadmaphID-a

  3. RAPID/Roadmap/20-ID-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa < RAPID‎f <CA-a < RAPID‎ID-a

  4. RAPID/Roadmap/9-ID-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onRAPID/Geothermal/Exploration/Colorado <RAPID/Geothermal/Water Use/Nevadaa <NV-b <Roadmap/9-CA-bl <ID-a <

  5. RAPID/Roadmap/14-ID-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EIS Report UrlNM-b < RAPID‎ | Roadmap JumpNV-a <CA-cID-a <

  6. RAPID/Roadmap/14-ID-f | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EIS Report UrlNM-b < RAPID‎ | Roadmap JumpNV-a <CA-cID-a

  7. RAPID/Roadmap/5-ID-a | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EIS Report UrlNM-b < RAPID‎ | RoadmapAK-a <CA-ae <cCA-aID-a

  8. RAPID/Roadmap/8-ID-e | 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EIS Report UrlNM-b < RAPID‎ | RoadmapAK-abFD-a < RAPID‎ID-e

  9. Department of Energy Idaho - Inside DOE-ID

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfateSciTechtail.Theory ofDid you not find what you were looking for?DelegationsInside ID Inside Idaho

  10. Microsoft Word - 140602DOE-ID_OperationsSummary.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete and realistic microscopic calculations Mr., 2014 DOE-ID

  11. Microsoft Word - DOE-ID-INL-10-020.doc

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based Femtosecond65611 DOE-ID-INL-10-020

  12. Microsoft Word - DOE-ID-INL-10-021.doc

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based Femtosecond65611 DOE-ID-INL-10-02021

  13. Microsoft Word - DOE-ID-INL-14-046.docx

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  14. Microsoft Word - DOE-ID-INL-14-048.docx

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  15. Microsoft Word - DOE-ID-INL-14-049.docx

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  16. Microsoft Word - DOE-ID-INL-14-050.docx

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  17. Microsoft Word - DOE-ID-INL-14-051.docx

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  18. Microsoft Word - DOE-ID-INL-14-052.docx

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  19. Microsoft Word - DOE-ID-INL-14-053.docx

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  20. Microsoft Word - DOE-ID-INL-14-054.docx

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  1. Microsoft Word - DOE-ID-INL-14-055.docx

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  2. Microsoft Word - DOE-ID-INL-14-056.docx

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  3. Microsoft Word - DOE-ID-INL-14-057.docx

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  4. Microsoft Word - DOE-ID-INL-14-058.docx

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  5. Microsoft Word - DOE-ID-INL-15-001.docx

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  6. Microsoft Word - DOE-ID-INL-15-002.docx

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  7. Microsoft Word - DOE-ID-INL-15-003.docx

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  8. Microsoft Word - DOE-ID-INL-15-004.docx

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  9. Microsoft Word - DOE-ID-INL-15-005.docx

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  10. Microsoft Word - DOE-ID-INL-15-006.docx

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  11. Microsoft Word - DOE-ID-INL-15-007.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4 SECTION

  12. Microsoft Word - DOE-ID-INL-15-008.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4 SECTION8

  13. Microsoft Word - DOE-ID-INL-15-009.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4 SECTION82 CS

  14. Microsoft Word - DOE-ID-INL-15-010.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4 SECTION82

  15. Microsoft Word - DOE-ID-INL-15-011.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4 SECTION8211

  16. Microsoft Word - DOE-ID-INL-15-012.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4 SECTION82112

  17. Microsoft Word - DOE-ID-INL-15-014.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R1 SECTION

  18. Microsoft Word - DOE-ID-INL-15-015.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R1 SECTION5

  19. Microsoft Word - DOE-ID-INL-15-016.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R1 SECTION56

  20. Microsoft Word - DOE-ID-INL-15-017.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R1 SECTION567

  1. Microsoft Word - DOE-ID-INL-15-018.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R1

  2. Microsoft Word - DOE-ID-INL-15-019.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R19 SECTION

  3. Microsoft Word - DOE-ID-INL-15-020.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R19 SECTION0

  4. Microsoft Word - DOE-ID-INL-15-021.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R19

  5. Microsoft Word - DOE-ID-INL-15-022.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R192 SECTION

  6. Microsoft Word - DOE-ID-INL-15-023.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R192

  7. Microsoft Word - DOE-ID-INL-15-024.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R1924 SECTION

  8. Microsoft Word - DOE-ID-INL-15-025.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R1924

  9. Microsoft Word - DOE-ID-INL-15-026.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R19246

  10. Microsoft Word - DOE-ID-INL-15-027.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R192467

  11. Microsoft Word - DOE-ID-INL-15-028.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R1924678

  12. Microsoft Word - DOE-ID-INL-15-029.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R19246789

  13. Microsoft Word - DOE-ID-INL-15-030.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R1924678930

  14. Microsoft Word - DOE-ID-INL-15-031.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R19246789301

  15. Microsoft Word - DOE-ID-INL-15-032.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID NEPA4R192467893012

  16. Microsoft Word - DOE-ID-INL-15-034.docx

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    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID

  17. Microsoft Word - DOE-ID-INL-15-035.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION A.

  18. Microsoft Word - DOE-ID-INL-15-036.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION A.6

  19. Microsoft Word - DOE-ID-INL-15-037.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION A.67

  20. Microsoft Word - DOE-ID-INL-15-038.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION A.678

  1. Microsoft Word - DOE-ID-INL-15-039.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION A.6789

  2. Microsoft Word - DOE-ID-INL-15-040.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION A.67890

  3. Microsoft Word - DOE-ID-INL-15-041.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION A.678901

  4. Microsoft Word - DOE-ID-INL-15-042.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION A.6789012

  5. Microsoft Word - DOE-ID-INL-15-043.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION

  6. Microsoft Word - DOE-ID-INL-15-044.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION4 SECTION

  7. Microsoft Word - DOE-ID-INL-15-045.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION4 SECTION7

  8. Microsoft Word - DOE-ID-INL-15-046.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION4

  9. Microsoft Word - DOE-ID-INL-15-048.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION48 SECTION

  10. Microsoft Word - DOE-ID-INL-15-049.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION48

  11. Microsoft Word - DOE-ID-INL-15-050.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION480

  12. Microsoft Word - DOE-ID-INL-15-051.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION4801

  13. Microsoft Word - DOE-ID-INL-15-052.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION48012

  14. Microsoft Word - DOE-ID-INL-15-053.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5 SECTION4801253

  15. Microsoft Word - DOE-ID-INL-15-054.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID5

  16. Microsoft Word - DOE-ID-INL-15-055.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID55 SECTION A.

  17. Microsoft Word - DOE-ID-INL-15-056.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID55 SECTION A.6

  18. Microsoft Word - DOE-ID-INL-15-057.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID55 SECTION A.67

  19. Microsoft Word - DOE-ID-INL-15-058.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID55 SECTION A.678

  20. Microsoft Word - DOE-ID-INL-15-059.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID55 SECTION A.6789

  1. Microsoft Word - DOE-ID-INL-15-061.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID55 SECTION A.678961

  2. Microsoft Word - DOE-ID-INL-15-062.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID55 SECTION

  3. Microsoft Word - DOE-ID-INL-15-063.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID55 SECTION3 SECTION

  4. Microsoft Word - DOE-ID-INL-15-064.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID55 SECTION3

  5. Microsoft Word - DOE-ID-INL-15-065.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID55 SECTION35

  6. Microsoft Word - DOE-ID-INL-15-066.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID55 SECTION356

  7. Microsoft Word - DOE-ID-INL-15-067.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID55 SECTION3567

  8. Microsoft Word - DOE-ID-INL-15-068.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID55 SECTION35678

  9. Microsoft Word - DOE-ID-INL-15-069.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID55

  10. Microsoft Word - DOE-ID-INL-15-070.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID550 SECTION A.

  11. Microsoft Word - DOE-ID-INL-15-071.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID550 SECTION A.1

  12. Microsoft Word - DOE-ID-INL-15-072.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID550 SECTION A.12

  13. Microsoft Word - DOE-ID-INL-15-073.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID550 SECTION

  14. Microsoft Word - DOE-ID-INL-15-074.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID550 SECTION4

  15. Microsoft Word - DOE-ID-INL-15-075.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID550 SECTION475

  16. Microsoft Word - DOE-ID-INL-15-076.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID550 SECTION4756

  17. Microsoft Word - DOE-ID-INL-15-077.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID550 SECTION47567

  18. Microsoft Word - DOE-ID-INL-15-078.docx

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID550 SECTION475678

  19. Microsoft Word - DOE-ID_INL-13-010.doc

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete andGoniometer-based3 SECTION A.DOE0ID550 SECTION4756780

  20. Forecasting the 2013–2014 influenza season using Wikipedia

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

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

    2015-05-14

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