National Library of Energy BETA

Sample records for text forecast tables

  1. 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....

  2. Forecasting Flu

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

    Forecasting Flu March 6, 2016 Forecasting Flu What if we could forecast infectious diseases the same way we forecast the weather, and predict how diseases like Dengue, Typhus or Zika were going to spread? Using real-time data from Wikipedia and social media, Sara del Valle and her team from Los Alamos National Laboratory have developed a global disease-forecasting system that will improve the way we respond to epidemics. Using this model, individuals and public health officials can monitor

  3. RACORO Forecasting

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

    Hartsock CIMMS, University of Oklahoma  ARM AAF Wiki page  Weather Briefings  Observed Weather  Cloud forecasting models  BUFKIT forecast soundings + guidance from Norman NWS enhanced pages and discussions NAM-WRF updated twice/day (12Z and 00Z) Forecast out to 84-hours RUC (updated every 3 hours) Operational RUC forecast only goes out 12 hours (developmental out 24 hours)

  4. Q3 1996 STEO TEXT/TABLES

    Gasoline and Diesel Fuel Update (EIA)

    DOE/EIA-0202(96/3Q) Distribution Category UC-950 Short-Term Energy Outlook Quarterly Projections Third Quarter 1996 Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the Department of Energy. The information contained herein should not be construed as advocating or reflecting any policy position of the

  5. Acquisition Forecast

    Broader source: Energy.gov [DOE]

    It is the policy of the Department of Energy (DOE) and the National Nuclear Security Administration (NNSA) to provide timely information to the public regarding DOE/NNSA’s forecast of future prime contracting opportunities and subcontracting opportunities which are available via the Department’s major site and facilities management contractors.

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

    SciTech Connect (OSTI)

    Rogers, J.; Porter, K.

    2011-03-01

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

  7. General Tables

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

    General Tables The General Tables for the most recent TUNL evaluation of "Energy Levels of Light Nuclei, A = 8, 9, 10" published in Nuclear Physics A745 (2004) p.155 and "Energy Levels of Light Nuclei, A = 5, 6, 7" published in Nuclear Physics A708 (2002) p.3 are available below. Beginning with the A = 5, 6, 7 nuclei, the General Tables will no longer be included in the publications of "Energy Levels of Light Nuclei" in Nuclear Physics A. The tables will be placed

  8. Table 4

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

    112 70 83 98 99 117 150 5.89 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  9. Table 4

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

    125 43 101 95 99 130 149 8.25 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  10. Table 4

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

    125 69 112 131 137 158 7.36 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  11. Wind Power Forecasting

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

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

  12. 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...

  13. Table 4

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

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

  14. Table 4

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

    10.8 0.9 2.9 1.9 2.8 2.3 9.84 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  15. Table 4

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

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

  16. A = 5 General Tables

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

    5 General Tables The General Table for 5H is subdivided into the following categories: Cluster Model Hypernuclei Model Calculations Photodisintegration Pions The General Table for...

  17. NREL: Transmission Grid Integration - Forecasting

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

    generation output by using forecasts that incorporate meteorological data to predict production. Such systems typically provide forecasts at a number of timescales, ranging from...

  18. Table 7

    Gasoline and Diesel Fuel Update (EIA)

    1 Table 7 Created on: 2/24/2016 8:11:36 AM Table 7. Marketed production of natural gas in selected states and the Federal Gulf of Mexico, 2010-2015 (million cubic feet) Year and Month Alaska Arkansas California Colorado Kansas Louisiana Montana New Mexico North Dakota Ohio 2010 Total 374,226 926,639 286,841 1,578,379 324,720 2,210,099 87,539 1,292,185 81,837 78,122 2011 Total 356,225 1,072,212 250,177 1,637,576 309,124 3,029,206 74,624 1,237,303 97,102 78,858 2012 Total 351,259 1,146,168 246,822

  19. 8C General Tables

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

    C General Tables The General Table for 8C is subdivided into the following categories: Reviews Other Theoretical Work

  20. 1999 CBECS Detailed Tables

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

    Commercial Buildings Energy Consumption Survey (CBECS) > Detailed Tables 1999 CBECS Detailed Tables Building Characteristics | Consumption & Expenditures Data from the 1999...

  1. 6Be General Tables

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

    6Be General Table The General Table for 6Be is subdivided into the following categories: Cluster Model Model Calculations...

  2. A=18 Tables

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

    (1959) Adobe Reader Download Tables from (1995TI07): Introductory Table 3 in PS or PDF. Table 18.1 in PS or PDF. Table 18.2 in PS or PDF. Table 18.3 in PS or PDF. Table 18.4...

  3. A=19 Tables

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

    (1959) Adobe Reader Download Tables from (1995TI07): Introductory Table 3 in PS or PDF. Table 19.1 in PS or PDF. Table 19.2 in PS or PDF. Table 19.3 in PS or PDF. Table 19.4...

  4. A=20 Tables

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

    (1959) Adobe Reader Download Tables from (1998TI06): Introductory Table 3 in PS or PDF. Table 20.1 in PS or PDF. Table 20.2 in PS or PDF. Table 20.3 in PS or PDF. Table 20.4...

  5. TABLE 1

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

    ATTACHMENT 1 - FEHB PROGRAM TABLE 1 PLANS LEAVING THE FEHB PROGRAM Enrollees in the terminating FEHB plans who do not change their health plan by enrolling in another FEHB plan during Open Season will not have health benefits for 2016. State FEHB Plan Name 2015 Enrollment Codes General Location Florida Coventry Health Plan of Florida 5E1, 5E2, 5E4, 5E5, J41, J42 South Florida Indiana Physicians Health Plan of Northern Indiana DQ1, DQ2, DQ4, DQ5 Northeast Indiana Louisiana Coventry Health Care

  6. LED Lighting Forecast | Department of Energy

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

    Publications Market Studies LED Lighting Forecast LED Lighting Forecast The DOE report Energy Savings Forecast of Solid-State Lighting in General Illumination Applications ...

  7. 7He General Tables

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

    He General Table The General Table for 7He is subdivided into the following categories: Experimental Theoretical Model Calculations Hypernuclei and Mesons Pions

  8. 9He General Tables

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

    He General Table The General Table for 9He is subdivided into the following categories: Shell Model Other Model Calculations Theoretical

  9. 5He General Tables

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

    He General Table The General Table for 5He is subdivided into the following categories: Ground State Properties Theoretical Special States Model Discussions Shell Model Cluster...

  10. 6He General Tables

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

    He General Table The General Table for 6He is subdivided into the following categories: Ground State Properties Theoretical Special States Shell Model Cluster and alpha-particle...

  11. A = 10 General Tables

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

    Table for 10He is subdivided into the following categories: Theoretical Shell Model Cluster Model Other Models Special States Electromagnetic Transitions The General Table for...

  12. 5H General Tables

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

    H General Table The General Table for 5H is subdivided into the following categories: Cluster Model Hypernuclei Model Calculations Photodisintegration Pions...

  13. 10He General Tables

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

    General Table The General Table for 10He is subdivided into the following categories: Theoretical Shell Model Cluster Model Other Models Special States Electromagnetic Transitions...

  14. 1995 Detailed Tables

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

    Households, Buildings & Industry > Commercial Buildings Energy Consumption Survey > Detailed Tables 1995 Detailed Tables Data from the 1995 Commercial Buildings Energy Consumption...

  15. FY 2005 Statistical Table

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

    Statistical Table by Appropriation (dollars in thousands - OMB Scoring) Table of Contents Summary...................................................................................................... 1 Mandatory Funding....................................................................................... 3 Energy Supply.............................................................................................. 4 Non-Defense site acceleration

  16. The forecast calls for flu

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

    Laboratory found a way to forecast the flu season and even next week's sickness trends. ... Laboratory found a way to forecast the flu season and even next week's sickness trends. ...

  17. Solar Forecasting | Department of Energy

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

    Systems Integration » Solar Forecasting Solar Forecasting 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. solar energy plants. Part of the SunShot Systems Integration efforts, the Solar Forecasting projects will allow power system operators to integrate more solar energy into the electricity grid, and ensure the economic and reliable delivery of

  18. probabilistic energy production forecasts

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

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

  19. CBECS Buildings Characteristics --Revised Tables

    Gasoline and Diesel Fuel Update (EIA)

    Energy Sources and End Use Tables (27 pages, 152 kb) CONTENTS PAGES Table 18. Energy Sources, Number of Buildings, 1995 Table 19. Energy Sources, Floorspace, 1995 Table 20. Energy End Uses, Number of Buildings and Floorspace, 1995 Table 21. Space-Heating Energy Sources, Number of Buildings, 1995 Table 22. Space-Heating Energy Sources, Floorspace, 1995 Table 23. Primary Space-Heating Energy Sources, Number of Buildings, 1995 Table 24. Primary Space-Heating Energy Sources, Floorspace, 1995 Table

  20. CBECS Buildings Characteristics --Revised Tables

    Gasoline and Diesel Fuel Update (EIA)

    End-Use Equipment Tables (27 pages, 151 kb) CONTENTS PAGES Table 33. Heating Equipment, Number of Buildings, 1995 Table 34. Heating Equipment, Floorspace, 1995 Table 35. Cooling Equipment,Number of Buildings, 1995 Table 36. Cooling Equipment, Floorspace, 1995 Table 37. Refrigeration Equipment, Number of Buildings and Floorspace, 1995 Table 38. Water-Heating Equipment, Number of Buildings and Floorspace, 1995 Table 39. Lighting Equipment, Number of Buildings, 1995 Table 40. Lighting Equipment,

  1. Using Wikipedia to forecast diseases

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

    Using Wikipedia to forecast diseases Using Wikipedia to forecast diseases Scientists can now monitor and forecast diseases around the globe more effectively by analyzing views of Wikipedia articles. November 13, 2014 Del Valle and her team observe findings from their research on disease patterns from analyzing Wikipedia articles. Del Valle and her team observe findings from their research on disease patterns from analyzing Wikipedia articles. Contact Nancy Ambrosiano Communications Office (505)

  2. 8Be General Tables

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

    Be General Tables The General Table for 8Be is subdivided into the following categories: Reviews Ground State Properties Shell Model Cluster Model Other Models Photodisintegration Fission and Fusion Astrophysical b-decay Hypernuclei

  3. 9B General Tables

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

    B General Table The General Table for 9B is subdivided into the following categories: Shell Model Cluster Model Theoretical Other Model Calculations Complex Reactions Beta-Decay Pions Light-ion and Neutron Induced Reactions Hypernuclei

  4. 9C General Tables

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

    C General Table The General Table for 9C is subdivided into the following categories: Shell Model Cluster Model Other Models Theoretical Beta-Decay Light-ion and Neutron Induced Reactions Astrophysical

  5. 6Li General Tables

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

    Li General Table The General Table for 6Li is subdivided into the following categories: Ground State Properties of 6Li Special States Theoretical Shell Model Cluster Models Complex...

  6. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

    Zip: 94965 Region: Bay Area Sector: Services Product: Intelligent Monitoring and Forecasting Services Year Founded: 2010 Website: www.forecastenergy.net Coordinates:...

  7. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01

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

  8. Using Wikipedia to forecast diseases

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

    based on today's forecast." Del Valle and her team were able to successfully monitor influenza in the United States, Poland, Japan and Thailand, dengue fever in Brazil and...

  9. FY 2005 Laboratory Table

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

    Congressional Budget Request Laboratory Tables Preliminary Department of Energy FY 2005 Congressional Budget Request Office of Management, Budget and Evaluation/CFO February 2004 Laboratory Tables Preliminary Department of Energy Department of Energy FY 2005 Congressional Budget FY 2005 Congressional Budget Request Request Office of Management, Budget and Evaluation/CFO February 2004 Laboratory Tables Laboratory Tables Printed with soy ink on recycled paper Preliminary Preliminary The numbers

  10. FY 2005 State Table

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

    Office of Management, Budget and Evaluation/CFO February 2004 State Tables State Tables Preliminary Preliminary Department of Energy Department of Energy FY 2005 Congressional Budget FY 2005 Congressional Budget Request Request Office of Management, Budget and Evaluation/CFO February 2004 State Tables State Tables Printed with soy ink on recycled paper Preliminary Preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The

  11. A = 7 General Tables

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

    7 General Tables The General Table for 7He is subdivided into the following categories: Experimental Theoretical Model Calculations Hypernuclei and Mesons Pions The General Table for 7Li is subdivided into the following categories: Reviews Ground State Properties Shell Model Cluster Model Other Theoretical Work Model Calculations Photodisintegration Polarization Fission and Fusion Elastic and Inelastic Scattering Projectile Fragmentation and Multifragmentation Astrophysical Hyperfine Structure

  12. Hot cell examination table

    DOE Patents [OSTI]

    Gaal, Peter S. (Monroeville, PA); Ebejer, Lino P. (Weston, MA); Kareis, James H. (Slickville, PA); Schlegel, Gary L. (McKeesport, PA)

    1991-01-01

    A table for use in a hot cell or similar controlled environment for use in examining specimens. The table has a movable table top that can be moved relative to a table frame. A shaft is fixedly mounted to the frame for axial rotation. A shaft traveler having a plurality of tilted rollers biased against the shaft is connected to the table top such that rotation of the shaft causes the shaft traveler to roll along the shaft. An electromagnetic drive is connected to the shaft and the frame for controllably rotating the shaft.

  13. Intermediate future forecasting system

    SciTech Connect (OSTI)

    Gass, S.I.; Murphy, F.H.; Shaw, S.H.

    1983-12-01

    The purposes of the Symposium on the Department of Energy's Intermediate Future Forecasting System (IFFS) were: (1) to present to the energy community details of DOE's new energy market model IFFS; and (2) to have an open forum in which IFFS and its major elements could be reviewed and critiqued by external experts. DOE speakers discussed the total system, its software design, and the modeling aspects of oil and gas supply, refineries, electric utilities, coal, and the energy economy. Invited experts critiqued each of these topics and offered suggestions for modifications and improvement. This volume documents the proceedings (papers and discussion) of the Symposium. Separate abstracts have been prepared for each presentation for inclusion in the Energy Data Base.

  14. Solar Energy Market Forecast | Open Energy Information

    Open Energy Info (EERE)

    Market Forecast Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar Energy Market Forecast AgencyCompany Organization: United States Department of Energy Sector:...

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

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

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

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

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

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

  17. Solar Webinar Text Version

    Broader source: Energy.gov [DOE]

    Download the text version of the audio from the DOE Office of Indian Energy webinar on solar renewable energy.

  18. Wind Webinar Text Version

    Broader source: Energy.gov [DOE]

    Download the text version of the audio from the DOE Office of Indian Energy webinar on wind renewable energy.

  19. 10Li General Tables

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

    Li General Table The General Table for 10Li is subdivided into the following categories: Reviews Theoretical Ground State Properties Shell Model Cluster Model Other Models Special States Astrophysical Electromagnetic Transitions Hypernuclei Photodisintegration Light-Ion and Neutron Induced Reactions These General Tables correspond to the 2003 preliminary evaluation of ``Energy Levels of Light Nuclei, A = 10''. The prepublication version of A = 10 is available on this website in PDF format: A =

  20. Science on Tap - Forecasting illness

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

    Science on Tap - Forecasting illness Science on Tap - Forecasting illness WHEN: Mar 17, 2016 5:30 PM - 7:00 PM WHERE: UnQuarked Wine Room 145 Central Park Square, Los Alamos, New Mexico 87544 USA CONTACT: Linda Anderman (505) 665-9196 CATEGORY: Bradbury INTERNAL: Calendar Login Event Description Mark your calendars for this event held every third Thursday from 5:30 to 7 p.m. A short presentation is followed by a lively discussion on a different subject each month. Forecasting the flu (and other

  1. CBECS Buildings Characteristics --Revised Tables

    Gasoline and Diesel Fuel Update (EIA)

    Buildings Use Tables (24 pages, 129 kb) CONTENTS PAGES Table 12. Employment Size Category, Number of Buildings, 1995 Table 13. Employment Size Category, Floorspace, 1995 Table 14. Weekly Operating Hours, Number of Buildings, 1995 Table 15. Weekly Operating Hours, Floorspace, 1995 Table 16. Occupancy of Nongovernment-Owned and Government-Owned Buildings, Number of Buildings, 1995 Table 17. Occupancy of Nongovernment-Owned and Government-Owned Buildings, Floorspace, 1995 These data are from the

  2. Description of Detailed Tables

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

    for the 1999 Commercial Buildings Energy Consumption Survey (CBECS) consists of building characteristics tables B1 through B39, which contain the number of buildings and...

  3. TABLE OF CONTENTS

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

    ... Table 1 Waste Surface Level Decrease Trends for Tanks B-203 and B-204 ... These two SSTs with decreasing waste surface level (SL) data trends were recommended for ...

  4. TABLE OF CONTENTS

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

    ... Table 1 Waste Surface Level Decrease Trends for Tank TY-105 ......and interstitial liquid level (ILL) data trends and was recommended for level decrease ...

  5. TABLE OF CONTENTS

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

    ... Table 1 Waste Surface Level Decrease Trends for Tanks T-203 and T-204 ... These two SSTs with decreasing waste surface level (SL) data trends were recommended for ...

  6. Table of Contents

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

    TABLE OF CONTENTS INTRODUCTION J. B. Natowitz, Director SECTION I: NUCLEAR STRUCTURE, FUNDAMENTAL INTERACTIONS AND ASTROPHYSICS SECTION II: HEAVY ION REACTIONS SECTION III: NUCLEAR...

  7. A = 9 General Tables

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

    The General Table for 9Li is subdivided into the following categories: Shell Model Cluster Model Theoretical Ground State Properties Special States Other Model Calculations...

  8. 5Li General Tables

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

    Table for 5Li is subdivided into the folowing categories: Ground State Properties Cluster Model Shell Model Special States Model Calculations Model Discussions Complex...

  9. 10N General Tables

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

    subdivided into the following categories: Reviews Ground-State Properties Shell Model Cluster Model Other Theoretical Work These General Tables correspond to "Energy Levels of...

  10. SEP Program Transition Tables

    Broader source: Energy.gov [DOE]

    The Program Transition Tables provide information concerning the level of effort required to move from a traditional, industrial incentive program to Strategic Energy Management, ISO 50001, or SEP.

  11. MDF Overview (Text Version)

    Broader source: Energy.gov [DOE]

    This is a text version of the Manufacturing Demonstration Facilities (MDF) overview video, originally presented on March 12, 2012 at the MDF Workshop held in Chicago, Illinois.

  12. 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.

  13. 7Be General Tables

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

    Be General Table The General Table for 7Be is subdivided into the following categories: Reviews Experimental Work Shell Model Cluster Model Other Theoretical Work Model Calculations Projectile Fragmentation and Multifragmentation Astrophysical b Decay Astrophysical Neutrinos Hypernuclei, Mesons and Other Exotic Particles Applications

  14. Solar Forecast Improvement Project | Department of Energy

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

    Solar Forecast Improvement Project Solar Forecast Improvement Project NOAA.png 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 accurate methods for solar forecasts using their state-of-the-art weather models. APPROACH NOAA solar.png SFIP has three main goals: 1) to develop solar forecasting metrics tailored to the utility sector; 2) to improve solar

  15. 1995 CECS C&E Tables

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

    Fuel Oil Tables (10 pages, 58 kb) CONTENTS PAGES Table 26. Total Fuel Oil Consumption and Expenditures, 1995 Table 27. Fuel Oil Consumption and Expenditure Intensities, 1995 Table...

  16. 2013 User Survey Text

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

    2013 User Survey Text 2013 User Survey Text Section 1: Overall Satisfaction with NERSC For each item you use, please indicate both your satisfaction and its importance to you. Please rate: How satisfied are you? How important is this to you? Overall satisfaction with NERSC Not Answered Very Satisfied Mostly Satisfied Somewhat Sat. Neutral Somewhat Dissat. Mostly Dissat. Very Dissatisfied I Do Not Use This Not Answered Very Important Somewhat Important Not Important I Do Not Use This NERSC

  17. All Consumption Tables.vp

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

    4) June 2007 State Energy Consumption Estimates 1960 Through 2004 2004 Consumption Summary Tables Table S1. Energy Consumption Estimates by Source and End-Use Sector, 2004...

  18. table11.xls

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

    ... 14.1 NA 17.9 18.3 19.6 20.1 Table 11. Fuel Economy, Selected Survey Years (Miles Per Gallon) Survey Years Page A-1 of A-5 1983 1985 1988...

  19. 8He General Tables

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

    Table for 8He is subdivided into the following categories: Reviews Ground-state Properties Shell Model Cluster Model Other Theoretical Work Elastic and Inelastic Scattering b-decay...

  20. TABLE OF CONTENTS

    Energy Savers [EERE]

    008 High Temperature Superconductivity for Electric Systems Peer Review Final Report i TABLE OF CONTENTS High Temperature Superconductivity for Electric Systems Program Overview ...... 1 The Peer Review................................................................................................................ 3 Review Criteria ................................................................................................................. 5 Guidelines

  1. Table_of_Contents

    Energy Savers [EERE]

    Table of Contents 1. Physical Security .............................................................................................................................. 1-1 101. Headquarters Security Badges ........................................................................................ 101-1 102. HSPD-12 Badges and the PIV Process ........................................................................... 102-1 103. Prohibited Articles

  2. Tables of Energy Levels

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

    of Energy Levels The Image Map below will direct you to the table of energy levels PDF format only for that particular nuclide from the most recent publication found within...

  3. Picture of the Week: Forecasting Flu

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

    3 Forecasting Flu What if we could forecast infectious diseases the same way we forecast the weather, and predict how diseases like Dengue, Typhus or Zika were going to spread? March 6, 2016 flu epidemics modellled using social media Watch the video on YouTube. Forecasting Flu What if we could forecast infectious diseases the same way we forecast the weather, and predict how diseases like Dengue, Typhus or Zika were going to spread? Using real-time data from Wikipedia and social media, Sara del

  4. FY 2006 Laboratory Table

    Energy Savers [EERE]

    Laboratory Tables Preliminary Department of Energy FY 2006 Congressional Budget Request Office of Management, Budget and Evaluation/CFO February 2005 Laboratory Tables Preliminary Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals,

  5. FY 2006 State Table

    Energy Savers [EERE]

    State Tables Preliminary Department of Energy FY 2006 Congressional Budget Request Office of Management, Budget and Evaluation/CFO February 2005 State Tables Preliminary Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals, rescissions, or

  6. FY 2008 Laboratory Table

    Energy Savers [EERE]

    Laboratory Table Preliminary Department of Energy FY 2008 Congressional Budget Request February 2007 Office of Chief Financial Officer Laboratory Table Preliminary Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals, rescissions, or other

  7. FY 2008 State Table

    Energy Savers [EERE]

    State Table Preliminary Department of Energy FY 2008 Congressional Budget Request February 2007 Office of Chief Financial Officer State Table Preliminary Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals, rescissions, or other adjustments

  8. FY 2009 State Table

    Energy Savers [EERE]

    State Tables Preliminary February 2008 Office of Chief Financial Officer Department of Energy FY 2009 Congressional Budget Request State Tables Preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, use of prior year balances, deferrals, rescissions, or other adjustments appropriated as offsets to the DOE

  9. FY 2011 Laboratory Table

    Energy Savers [EERE]

    Laboratory Tables Department of Energy FY 2011 Congressional Budget Request DOE/CF-0055 March 2010 Office of Chief Financial Officer Laboratory Tables Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, use of prior year balances, deferrals, rescissions, or other adjustments

  10. FY 2011 State Table

    Energy Savers [EERE]

    State Tables Department of Energy FY 2011 Congressional Budget Request DOE/CF-0054 March 2010 Office of Chief Financial Officer State Tables Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, use of prior year balances, deferrals, rescissions, or other adjustments appropriated

  11. FY 2012 State Table

    Energy Savers [EERE]

    6 Department of Energy FY 2012 Congressional Budget Request State Tables P li i Preliminary February 2012 Office of Chief Financial Officer DOE/CF-0066 Department of Energy FY 2012 Congressional Budget Request State Tables P li i Preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They displayed. The figures include both the discretionary and

  12. ARM - Instrument Location Table

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

    govInstrumentsLocation Table Instruments Location Table Contacts Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Instrument Locations Site abbreviations explained in the key. Instrument Name Abbreviation ENA NSA SGP AMF C1 C1 EF BF CF EF IF Aerosol Chemical Speciation Monitor ACSM Atmospheric Emitted Radiance Interferometer AERI Aethalometer AETH Ameriflux Measurement Component AMC Aerosol Observing System AOS Meteorological Measurements

  13. FY 2013 State Table

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

    9 Department of Energy FY 2013 Congressional Budget Request State Tables P li i Preliminary February 2012 Office of Chief Financial Officer DOE/CF-0079 Department of Energy FY 2013 Congressional Budget Request State Tables P li i Preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They displayed. The figures include both the discretionary and

  14. CPMS Tables | Department of Energy

    Energy Savers [EERE]

    Program Management » Quality Assurance » CPMS Tables CPMS Tables EM Quality Assurance Corporate Performance Metrics table. PDF icon CPMS Tables More Documents & Publications EM Corporate QA Performance Metrics QA Corporate Board Meeting - July 2008 QA Corporate Board Meeting - November 2008

  15. CBECS Buildings Characteristics --Revised Tables

    Gasoline and Diesel Fuel Update (EIA)

    Structure Tables (16 pages, 93 kb) CONTENTS PAGES Table 8. Building Size, Number of Buildings, 1995 Table 9. Building Size, Floorspace, 1995 Table 10. Year Constructed, Number of Buildings, 1995 Table 11. Year Constructed, Floorspace, 1995 These data are from the 1995 Commercial Buildings Energy Consumption Survey (CBECS), a national probability sample survey of commercial buildings sponsored by the Energy Information Administration, that provides information on the use of energy in commercial

  16. 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 Laboratory This presentation does not contain any proprietary, confidential, or otherwise restricted information 2015 DOE Bioenergy Technologies Office (BETO) Project Peer Review Goal Statement Addresses the following MYPP BETO goals:  Advance scientific methods and models for measuring and understanding

  17. Wind Forecasting Improvement Project | Department of Energy

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

    Forecasting Improvement Project Wind Forecasting Improvement Project October 3, 2011 - 12:12pm Addthis This is an excerpt from the Third Quarter 2011 edition of the Wind Program R&D Newsletter. In July, the Department of Energy launched a $6 million project with the National Oceanic and Atmospheric Administration (NOAA) and private partners to improve wind forecasting. Wind power forecasting allows system operators to anticipate the electrical output of wind plants and adjust the electrical

  18. Microsoft Word - table_01

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

    U.S. Energy Information Administration | Natural Gas Monthly 3 Table 1 Table 1. Summary of natural gas supply and disposition in the United States, 2010-2015 (billion cubic feet) Year and Month Gross Withdrawals Marketed Production NGPL Production a Dry Gas Production b Supplemental Gaseous Fuels c Net Imports Net Storage Withdrawals d Balancing Item e Consumption f 2010 Total 26,816 22,382 1,066 21,316 65 2,604 -13 115 24,087 2011 Total 28,479 24,036 1,134 22,902 60 1,963 -354 -94 24,477 2012

  19. FY 2012 Laboratory Table

    Energy Savers [EERE]

    5 Department of Energy FY 2012 Congressional Budget Request Laboratory Tables y Preliminary February 2012 Office of Chief Financial Officer DOE/CF-0065 Department of Energy FY 2012 Congressional Budget Request Laboratory Tables P li i Preliminary h b d i d i hi d h l l f b d h i f h The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider

  20. FY 2013 Laboratory Table

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

    8 Department of Energy FY 2013 Congressional Budget Request Laboratory Tables y Preliminary February 2012 Office of Chief Financial Officer DOE/CF-0078 Department of Energy FY 2013 Congressional Budget Request Laboratory Tables P li i Preliminary h b d i d i hi d h l l f b d h i f h The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider

  1. FY 2006 Statistical Table

    Energy Savers [EERE]

    Statistical Table by Appropriation (dollars in thousands - OMB Scoring) FY 2004 FY 2005 FY 2006 Comparable Comparable Request to FY 2006 vs. FY 2005 Approp Approp Congress Discretionary Summary By Appropriation Energy And Water Development Appropriation Summary: Energy Programs Energy supply Operation and maintenance................................................. 787,941 909,903 862,499 -47,404 -5.2% Construction......................................................................... 6,956

  2. FY 2007 Statistical Table

    Energy Savers [EERE]

    Statistical Table by Appropriation (dollars in thousands - OMB Scoring) FY 2005 FY 2006 FY 2007 Current Current Congressional Approp. Approp. Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy supply and conservation Operation and maintenance............................................ 1,779,399 1,791,372 1,917,331 +125,959 +7.0%

  3. FY 2008 Statistical Table

    Energy Savers [EERE]

    Statistical Table by Appropriation (dollars in thousands - OMB Scoring) FY 2006 FY 2007 FY 2008 Current Congressional Congressional Approp. Request Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy supply and conservation Operation and maintenance........................................... 1,781,242 1,917,331 2,187,943 +270,612 +14.1%

  4. Table of Contents

    Energy Savers [EERE]

    COMMUNICATIONS REQUIREMENTS OF SMART GRID TECHNOLOGIES October 5, 2010 i Table of Contents I. Introduction and Executive Summary.......................................................... 1 a. Overview of Smart Grid Benefits and Communications Needs................. 2 b. Summary of Recommendations .................................................................... 5 II. Federal Government Smart Grid Initiatives ................................................ 7 a. DOE Request for Information

  5. FY 2013 Statistical Table

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

    Statistical Table by Appropriation (dollars in thousands - OMB Scoring) FY 2011 FY 2012 FY 2013 Current Enacted Congressional Approp. Approp. * Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy efficiency and renewable energy........................................ 1,771,721 1,809,638 2,337,000 +527,362 +29.1% Electricity delivery and energy reliability.........................................

  6. TABLE OF CONTENTS

    National Nuclear Security Administration (NNSA)

    AC05-00OR22800 TABLE OF CONTENTS Contents Page # TOC - i SECTION A - SOLICITATION/OFFER AND AWARD ......................................................................... A-i SECTION B - SUPPLIES OR SERVICES AND PRICES/COSTS ........................................................ B-i B.1 SERVICES BEING ACQUIRED ....................................................................................B-2 B.2 TRANSITION COST, ESTIMATED COST, MAXIMUM AVAILABLE FEE, AND AVAILABLE FEE (Modification 295,

  7. Supply Forecast and Analysis (SFA)

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

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

  8. 1995 CECS C&E Tables

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

    Electricity Tables (35 pages, 218 kb) CONTENTS PAGES Table 9. Total Electricity Consumption and Expenditures, 1995 Table 10. Electricity Consumption and Expenditure Intensities,...

  9. 1995 CECS C&E Tables

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

    kb) CONTENTS PAGES Table 1. Total Energy Consumption by Major Fuel, 1995 Table 9. Total Electricity Consumption and Expenditures, 1995 Table 20. Total Natural Gas Consumption and...

  10. 1995 CECS C&E Tables

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

    pages, 95 kb) CONTENTS PAGES Table 3. Consumption for Sum of Major Fuels, 1995 Table 10. Electricity Consumption and Expenditure Intensities, 1995 Table 21. Natural Gas...

  11. 1995 CECS C&E Tables

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

    kb) CONTENTS PAGES Table 2. Total Energy Expenditures by Major Fuel, 1995 Table 9. Total Electricity Consumption and Expenditures, 1995 Table 20. Total Natural Gas Consumption and...

  12. 1995 CECS C&E Tables

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

    pages, 95 kb) CONTENTS PAGES Table 4. Expenditures for Sum of Major Fuels, 1995 Table10. Electricity Consumption and Expenditure Intensities, 1995 Table 21. Natural Gas...

  13. Continuous Learning Points Credit Assignment Table | Department...

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

    Continuous Learning Points Credit Assignment Table Continuous Learning Points Credit Assignment Table PDF icon Microsoft Word - CLPCreditAssignmentTable More Documents &...

  14. Usage by Job Size Table

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

    Usage by Job Size Table Usage by Job Size Table page loading animation Usage Query Interface System All Hopper Edison Cori Carver Planck Matgen Franklin Hopper 1 Magellan Dirac...

  15. Energy.gov Data Tables

    Broader source: Energy.gov [DOE]

    Follow these guidelines for creating Section 508-compliant data tables in the Energy.gov Drupal environment.

  16. Advanced Vehicle Technologies Awards Table

    Broader source: Energy.gov [DOE]

    The table contains a listing of the applicants, their locations, the amounts of the awards, and description of each project.

  17. 2003 CBECS Detailed Tables: Summary

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

    c32.pdf c32.xls c32.html Fuel Oil (Tables C33-C36) set12-pdf Table C33. Total Fuel Oil Consumption and Expenditures c33-pdf c33.xls c33.html Table C34. Fuel Oil Consumption...

  18. Description of Energy Intensity Tables (12)

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

    3. Description of Energy Intensity Data Tables There are 12 data tables used as references for this report. Specifically, these tables are categorized as tables 1 and 2 present...

  19. FY 2009 Statistical Table

    Energy Savers [EERE]

    Statistical Table by Appropriation (dollars in thousands - OMB Scoring) FY 2007 FY 2008 FY 2009 Current Current Congressional Op. Plan Approp. Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy efficiency and renewable energy.......................... -- 1,722,407 1,255,393 -467,014 -27.1% Electricity delivery and energy reliability........................... -- 138,556 134,000 -4,556 -3.3% Nuclear

  20. ARM - CARES - Tracer Forecast for CARES

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

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

  1. UPF Forecast | Y-12 National Security Complex

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

    UPF Forecast UPF Forecast UPF Procurement provides the following forecast of subcontracting opportunities. Keep in mind that these requirements may be revised or cancelled, depending on program budget funding or departmental needs. If you have questions or would like to express an interest in any of the opportunities listed below, contact UPF Procurement. Descriptiona Methodb NAICS Est. Dollar Range RFP release/ Award datec Buyer/ Phone Commodities Equipment Rental FOC 238910 TBD 3Q FY15/ 3Q

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

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

    Influencing Technological Progress in Solar Energy Project Profile: Forecasting and ... energy technologies based on estimates of future rates of progress and adoption. ...

  3. NREL: Resource Assessment and Forecasting Home Page

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

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

  4. Forecast and Funding Arrangements - Hanford Site

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

    Annual Waste Forecast and Funding Arrangements About Us Hanford Site Solid Waste Acceptance Program What's New Acceptance Criteria Acceptance Process Becoming a new Hanford...

  5. QTR table of respondents | Department of Energy

    Energy Savers [EERE]

    table of respondents QTR table of respondents PDF icon QTR_RFI_Comments_Table _V2.pdf More Documents & Publications Table of QTR comments in response to Federal Register RFI Table of QTR comments in response to Federal Register RFI Table of QTR comments in response to Federal Register RFI

  6. Table G3

    Gasoline and Diesel Fuel Update (EIA)

    1905-0194 Expiration Date: 07/31/2013 May 28, 2010 Voluntary Reporting of Greenhouse Gases 14 Table G3. Decision Chart for a Start Year Report for a Large Emitter Intending To Register Reductions Report Characteristics Reporting Requirements Schedule I Schedule II (For Each Subentity) Schedule III Schedule IV Sec. 1 Sec. 2 Sec. 3 Sec. 4 Sec. 1 Sec. 2 & Add. A Sec. 3 Sec. 1 Sec. 2 Sec. 1 Sec. 2 Part A Part B Part C Part D Part E Part A Part B Part C Independent Verification? All A- or

  7. Text analysis methods, text analysis apparatuses, and articles of manufacture

    DOE Patents [OSTI]

    Whitney, Paul D; Willse, Alan R; Lopresti, Charles A; White, Amanda M

    2014-10-28

    Text analysis methods, text analysis apparatuses, and articles of manufacture are described according to some aspects. In one aspect, a text analysis method includes accessing information indicative of data content of a collection of text comprising a plurality of different topics, using a computing device, analyzing the information indicative of the data content, and using results of the analysis, identifying a presence of a new topic in the collection of text.

  8. CBECS Buildings Characteristics --Revised Tables

    Gasoline and Diesel Fuel Update (EIA)

    Summary Tables (12 pages, 59 kb) CONTENTS PAGES 1. Summary Table: Totals and Means of Floorspace, Number of Workers, and Hours of Operation, 1995 2. Summary Table: Totals and Medians of Floorspace, Number of Workers, Hours of Operation, and Age of Building, 1995 These data are from the 1995 Commercial Buildings Energy Consumption Survey (CBECS), a national probability sample survey of commercial buildings sponsored by the Energy Information Administration, that provides information on the use of

  9. MECS 1991 Publications and Tables

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

    Capability To Switch Fuels Appendices Appendix A. Detailed Tables Appendix B. Survey Design, Implementation, and Estimates (file size 141,211 bytes) pages: 22. Appendix C....

  10. Table 1. Crude Oil Prices

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

    from Table 24. Refiner acquisition costs -- Energy Information Administration, Form FEA-P110-M-1, "Refiners' Monthly Cost Allocation Report," January 1978 through June 1978;...

  11. Health Care Buildings: Subcategories Table

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

    Subcategories Table Selected Data by Type of Health Care Building Number of Buildings (thousand) Percent of Buildings Floorspace (million square feet) Percent of Floorspace Square...

  12. Health Care Buildings: Equipment Table

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

    Equipment Table Buildings, Size and Age Data by Equipment Types for Health Care Buildings Number of Buildings (thousand) Percent of Buildings Floorspace (million square feet)...

  13. Text analysis devices, articles of manufacture, and text analysis methods

    DOE Patents [OSTI]

    Turner, Alan E; Hetzler, Elizabeth G; Nakamura, Grant C

    2013-05-28

    Text analysis devices, articles of manufacture, and text analysis methods are described according to some aspects. In one aspect, a text analysis device includes processing circuitry configured to analyze initial text to generate a measurement basis usable in analysis of subsequent text, wherein the measurement basis comprises a plurality of measurement features from the initial text, a plurality of dimension anchors from the initial text and a plurality of associations of the measurement features with the dimension anchors, and wherein the processing circuitry is configured to access a viewpoint indicative of a perspective of interest of a user with respect to the analysis of the subsequent text, and wherein the processing circuitry is configured to use the viewpoint to generate the measurement basis.

  14. Table of Contents

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

    U U . . S S . . D D E E P P A A R R T T M M E E N N T T O O F F E E N N E E R R G G Y Y O O F F F F I I C C E E O O F F I I N N S S P P E E C C T T O O R R G G E E N N E E R R A A L L Semiannual Report toCongress DOE/IG-0065 April 1 - September 30, 2013 TABLE OF CONTENTS From the Desk of the Inspector General ..................................................... 2 Impacts Key Accomplishments ............................................................................................... 3

  15. CEMI Industrial Efficiency (text version)

    Broader source: Energy.gov [DOE]

    Below is the text version for the Clean Energy Manufacturing Initiative Industrial Efficiency and Energy Productivity Video.

  16. EIA lowers forecast for summer gasoline prices

    Gasoline and Diesel Fuel Update (EIA)

    EIA lowers forecast for summer gasoline prices U.S. gasoline prices are expected to be lower this summer than previously thought. The price for regular gasoline this summer is now expected to average $3.53 a gallon, according to the new monthly forecast from the U.S. Energy Information Administration. That's down 10 cents from last month's forecast and 16 cents cheaper than last summer. After reaching a weekly peak of $3.78 a gallon in late February, pump prices fell nine weeks in a row to $3.52

  17. 1999 Commercial Building Characteristics--Detailed Tables--Principal...

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

    Principal Building Activities > Detailed Tables-Principal Building Activities Complete Set of 1999 CBECS Detailed Tables Detailed Tables-Principal Building Activities Table B1....

  18. 1999 Commercial Building Characteristics--Detailed Tables--Year...

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

    Year Constructed > Detailed Tables-Year Constructed Complete Set of 1999 CBECS Detailed Tables Detailed Tables-Year Constructed Table B8. Year Constructed, Number of Buildings...

  19. Text analysis devices, articles of manufacture, and text analysis methods

    DOE Patents [OSTI]

    Turner, Alan E; Hetzler, Elizabeth G; Nakamura, Grant C

    2015-03-31

    Text analysis devices, articles of manufacture, and text analysis methods are described according to some aspects. In one aspect, a text analysis device includes a display configured to depict visible images, and processing circuitry coupled with the display and wherein the processing circuitry is configured to access a first vector of a text item and which comprises a plurality of components, to access a second vector of the text item and which comprises a plurality of components, to weight the components of the first vector providing a plurality of weighted values, to weight the components of the second vector providing a plurality of weighted values, and to combine the weighted values of the first vector with the weighted values of the second vector to provide a third vector.

  20. energy data + forecasting | OpenEI Community

    Open Energy Info (EERE)

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

  1. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

  2. Coal Fired Power Generation Market Forecast | OpenEI Community

    Open Energy Info (EERE)

    Coal Fired Power Generation Market Forecast Home There are currently no posts in this category. Syndicate...

  3. 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.

  4. 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.

  5. 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.

  6. Commerial Buildings Characteristics, 1995 (Table of Contents...

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

    Number of Buildings and Relative Standard Errors, 1995 Table I.2. Participation in Energy Conservation Programs, Floorspace and Relative Standard Errors, 1995 Table J.1....

  7. Trends in Commercial Buildings--Table

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

    Home > Trends in Commercial Buildings > Energy Consumption - Part 1> Site Energy Consumption Tables Table 1. Total site energy consumption, relative standard errors, and 95%...

  8. 1995 CECS C&E Tables

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

    Category (6 pages, 36 kb) CONTENTS PAGES Table 17. Peak Electricity Demand Category, Number of Buildings, 1995 Table 18. Peak Electricity Demand Category, Floorspace, 1995 These...

  9. 1995 CECS C&E Tables

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

    Building Level Intensities (percentile) (6 pages, 39 kb) CONTENTS PAGES Table 10. Electricity Consumption and Expenditure Intensities, 1995 Table 21. Natural Gas Consumption and...

  10. 1995 CECS C&E Tables

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

    and Gross Energy Intensity by Census Region for Sum of Major Fuels, 1995 Table 11. Electricity Consumption and Conditional Energy Intensity by Census Region, 1995 Table 22....

  11. 1995 CECS C&E Tables

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

    and Gross Energy Intensity by Year Constructed for Sum of Major Fuels, 1995 Table 14. Electricity Consumption and Conditional Energy Intensity by Year Constructed, 1995 Table...

  12. 1995 CECS C&E Tables

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

    and Gross Energy Intensity by Building Size for Sum of Major Fuels, 1995 Table13. Electricity Consumption and Conditional Energy Intensity by Building Size, 1995 Table 24....

  13. Appendix B: Technical Projection Tables, Bioenergy Technologies...

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

    Tables B-2 Last updated: November 2014 Table B-2: Terrestrial Feedstock Supply and Logistics Costs to Supply Feedstock to a Pyrolysis Conversion Process Processing Area Cost...

  14. Precision Flow Table | Open Energy Information

    Open Energy Info (EERE)

    Table Jump to: navigation, search Basic Specifications Facility Name Flow Table Overseeing Organization United States Army Corp of Engineers (ERDC) Hydrodynamic Testing Facility...

  15. Annual Energy Outlook (AEO) 2006 - Supplemental Tables - All Tables

    SciTech Connect (OSTI)

    2009-01-18

    Tables describing regional energy consumption and prices by sector; residential, commercial, and industrial demand sector data; transportation demand sector; electricity and renewable fuel; and petroleum, natural gas, and coal data.

  16. Table of tables: A database design tool for SYBASE

    SciTech Connect (OSTI)

    Brown, B.C.; Coulter, K.; Glass, H.D.; Glosson, R.; Hanft, R.W.; Harding, D.J.; Trombly-Freytag, K.; Walbridge, D.G.C.; Wallis, D.B. ); Allen, M.E. )

    1991-01-04

    The Table of Tables' application system captures in a set of SYBASE tables the basic design specification for a database schema. Specification of tables, columns (including the related defaults and rules for the stored values) and keys is provided. The feature which makes this application specifically useful for SYBASE is the ability to automatically generate SYBASE triggers. A description field is provided for each database object. Based on the data stored, SQL scripts for creating complete schema including the tables, their defaults and rules, their indexes, and their SYBASE triggers, are written by TOT. Insert, update and delete triggers are generated from TOT to guarantee integrity of data relations when tables are connected by single column foreign keys. The application is written in SYBASE's APT-SQL and includes a forms based data entry system. Using the features of TOT we can create a complete database schema for which the data integrity specified by our design is guaranteed by the SYBASE triggers generated by TOT. 3 refs.

  17. Microsoft Word - table_26.doc

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

    Fueled Vehicles"; state agencies; Form EIA-23, "Annual Survey of Domestic Oil and Gas Reserves"; PointLogic Energy; DI; Ventyz; and EIA estimates based on historical data. Table 27...

  18. Microsoft Word - table_19.doc

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

    7 Table 19. Natural gas delivered to industrial consumers for the account of others by state, 2010-2014 (volumes in million cubic feet) Alabama 109,031 75.2 117,277 76.5 133,765...

  19. Health Care Buildings: Consumption Tables

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

    Consumption Tables Sum of Major Fuel Consumption by Size and Type of Health Care Building Total (trillion Btu) per Building (million Btu) per Square Foot (thousand Btu) Dollars per...

  20. text | OpenEI Community

    Open Energy Info (EERE)

    Contributor 17 September, 2013 - 12:39 Are you willing to reply to a text message once a day with information about your comfort level at your indoor location? building...

  1. 2012 NISE Awards Summary Table

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

    Awards » 2012 NISE Summary Table 2012 NISE Awards Summary Table Investigator NERSC repo Hours awarded DOE Office Project Title Gilbert Compo, University of Colorado at Boulder m958 10,000,000 BER Climate Research Ocean-Atmosphere Reanalysis for Climate Applications (OARCA) 1850-2013 Silvia Crivelli, Lawrence Berkeley National Laboratory m1532 1,550,000 BER Biological Systems Science WeFold: A collaborative effort for protein structure prediction Thomas Hamill, National Oceanic & Atmospheric

  2. 2013 NISE Awards Summary Table

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

    Awards » 2013 NISE Summary Table 2013 NISE Awards Summary Table Investigator NERSC repo Hours awarded DOE Office Project Title Katie Antypas, Lawrence Berkeley National Laboratory m1759 250,000 ASCR Applied Mathematical Sciences NERSC Application Readiness for Future Architectures Inez Fung, University of California Berkeley m189 750,000 BER Climate and Environmental Sciences Carbon Data Assimilation with a Coupled Ensemble Kalman Filter Thomas Hamill, National Oceanic & Atmospheric

  3. 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.

  4. 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.

  5. NREL: Biomass Research - Video Text

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

    NREL Fermentation Laboratory Video (Text Version) This is the text version for the NREL Fermentation Laboratory video. The video opens with a collage of researchers. Music plays in the background. The video shows cars/traffic on a highway. Nancy Dowe: "We need a different fuel." (Voiceover) The cars and trucks that clog our roads... Nancy Dowe: "We need to get away from oil." The video shows a fuel nozzle in a car's gas tank then shows a fuel pump sale price window.

  6. 2012 NERSC User Survey Text

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

    2012 User Survey Text 2010/2011 User Survey Results 2009/2010 User Survey Results 2008/2009 User Survey Results 2007/2008 User Survey Results 2006 User Survey Results 2005 User Survey Results 2004 User Survey Results 2003 User Survey Results 2002 User Survey Results 2001 User Survey Results 2000 User Survey Results 1999 User Survey Results 1998 User Survey Results HPC Requirements for Science HPC Workshop Reports NERSC Staff Publications & Presentations Journal Cover Stories Galleries

  7. 2011 NISE Awards Summary Table

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

    Awards » 2011 NISE Summary Table 2011 NISE Awards Summary Table Investigator NERSC Repo Hours Awarded DOE Office Project Title Dmitri Babikov, Marquette University m409 1,450,000 BES Chemistry New potential energy surface for ozone molecule Connor Balance, Auburn University m41 600,000 Fusion Energy Hybrid OpenMP/MPI approach to R-matrix scattering Amitava Bhattacharjee, University of New Hampshire m148 1,000,000 Fusion Energy Global Effects on the Dynamics of Plasmoids and Flux Ropes during

  8. Solar Forecasting Gets a Boost from Watson, Accuracy Improved...

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

    Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% October 27, 2015 - 11:48am Addthis IBM ...

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

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

    rely on an array of VG forecasts suited to different purposes. Some of the most common types of VG forecasts are defined below: 2 This report is available at no cost from the...

  10. PBL FY 2003 Second Quarter Review Forecast of Generation Accumulated...

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

    the rate period (i.e., FY 2002-2006), a forecast of that end-of-year Accumulated Net Revenue (ANR) will be completed. If the ANR at the end of the forecast year falls below the...

  11. 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.

  12. NREL: Resource Assessment and Forecasting - Capabilities

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

    Capabilities Best Practices Handbook Helps Industry Collect and Interpret Solar Resource Data Read about this new comprehensive resource for the solar industry. NREL's resource assessment and forecasting research staff provides expertise in renewable energy measurement and instrumentation. Major capabilities include solar resource measurement, instrument calibration, instrument characterization, solar monitoring training, and standards development and information dissemination. Solar Resource

  13. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    1998-07-01

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

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

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01

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

  15. 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.

  16. 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)

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

    Open Energy Info (EERE)

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

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

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

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

  19. Uncertainty Reduction in Power Generation Forecast Using Coupled

    Office of Scientific and Technical Information (OSTI)

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

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

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

    ANL Software Improves Wind Power Forecasting ANL Software Improves Wind Power Forecasting May 1, 2012 - 3:19pm Addthis This is an excerpt from the Second Quarter 2012 edition of the Wind Program R&D Newsletter. Since 2008, Argonne National Laboratory and INESC TEC (formerly INESC Porto) have conducted a research project to improve wind power forecasting and better use of forecasting in electricity markets. One of the main results from the project is ARGUS PRIMA (PRediction Intelligent

  1. Today's Forecast: Improved Wind Predictions | Department of Energy

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

    Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical

  2. "RSE Table N13.1. Relative Standard Errors for Table N13.1;...

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

    "Energy Consumption Survey.'" X-Input-Content-Type: applicationvnd.ms-excel X-Translator-Status: translating "RSE Table N13.1. Relative Standard Errors for Table...

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

    SciTech Connect (OSTI)

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

    2015-10-11

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

  4. Microsoft Word - table_23.doc

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

    6 Table 23. Average citygate price of natural gas in the United States, 2010- 2014 (dollars per thousand cubic feet) Alabama 6.46 5.80 5.18 4.65 4.93 Alaska 6.67 6.53 6.14 6.02...

  5. 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.

  6. Table 2a. Electricity Consumption and Electricity Intensities...

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

    Administration Home Page Home > Commercial Buildings Home > Sq Ft Tables > Table 2a. Electricity Consumption per Sq Ft Table 2a. Electricity Consumption and Electricity...

  7. CBECS 1992 - Building Characteristics, Detailed Tables

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

    major topics of each table. Directions for calculating an approximate relative standard error (RSE) for each estimate in the tables are presented in Figure A1, "Use of RSE Row...

  8. TableHC2.11.xls

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

    ... Below Poverty Line Eligible for Federal Assistance 1 Table HC7.11 Home Electronics ... Below Poverty Line Eligible for Federal Assistance 1 Table HC7.11 Home Electronics ...

  9. 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.

  10. National Targets Table | Department of Energy

    Energy Savers [EERE]

    National Targets Table National Targets Table PDF icon National Targets Table More Documents & Publications Commercial Building Energy Asset Rating Workshop Fossil Fuel-Generated Energy Consumption Reduction for New Federal Buildings and Major Renovations of Federal Buildings OIRA Comparison Document Fossil Fuel-Generated Energy Consumption Reduction for New Federal Buildings and Major Renovations of Federal Buildings

  11. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

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

    2014-12-30

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

  12. Prod_Tables_2013.indd

    Gasoline and Diesel Fuel Update (EIA)

    State Energy Production Estimates 1960 Through 2013 2013 Summary Tables U.S. Energy Information Administration | State Energy Data 2013: Production 1 Table P1. Energy Production Estimates in Physical Units, 2013 Alabama 18,628 196,326 10,391 0 Alaska 1,632 338,182 187,954 0 Arizona 7,603 72 60 0 Arkansas 59 1,139,654 6,640 0 California 0 252,310 198,928 3,997 Colorado 24,236 1,604,860 65,394 3,042 Connecticut 0 0 0 0 Delaware 0 0 0 0 District of Columbia 0 0 0 0 Florida 0 292 2,174 0 Georgia 0 0

  13. 1999 Commercial Building Characteristics--Detailed Tables--Census...

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

    Census Region > Detailed Tables-Census Region Complete Set of 1999 CBECS Detailed Tables Detailed Tables-Census Region Table B3. Census Region, Number of Buildings and Floorspace...

  14. FY 2014 Budget Request Laboratory Table | Department of Energy

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

    Laboratory Table FY 2014 Budget Request Laboratory Table PDF icon Lab Table FY2014.pdf More Documents & Publications FY 2014 Budget Request State Table Fiscal Year 2013 President's Budget Request Fiscal Year 2013 President's

  15. FY 2014 Budget Request State Table | Department of Energy

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

    State Table FY 2014 Budget Request State Table PDF icon State Table FY2014.pdf More Documents & Publications FY 2014 Budget Request Laboratory Table FY 2007 Congressional Budget Request FY 2007 Congressional

  16. 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.

  17. 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.

  18. 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

  19. COST AND QUALITY TABLES 95

    Gasoline and Diesel Fuel Update (EIA)

    5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear, Electric and Alternate Fuels U.S. Department of Energy Washington DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the Department of Energy. The information contained herein should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. Contacts The annual publication Cost

  20. SECTION J - TABLE OF CONTENTS

    National Nuclear Security Administration (NNSA)

    Conformed to Mod 0108 DE-NA0000622 Section J Page i PART III - LIST OF DOCUMENTS, EXHIBITS, AND OTHER ATTACHMENTS SECTION J LIST OF APPENDICES TABLE OF CONTENTS Appendix A Statement of Work (Replaced by Mod 002; Modified Mod 016; Replaced Mod 029) Appendix B Performance Evaluation Plan (Replaced by Mods 002, 016, 020, 029, 0084) Appendix C Contractor's Transition Plan Appendix D Sensitive Foreign Nations Control Appendix E Performance Guarantee Agreement(s) Appendix F National Work Breakdown

  1. 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.

  2. TableBuster V1.0

    Energy Science and Technology Software Center (OSTI)

    2003-06-06

    Brief Description:TableBuster enables Telelogic DOORS users to export tables with split merged cells from Microsoft Word into DOORS. Practical Application: Users of Telelogic DOORS will be more easily able to track and manage requirements that are initally defined in Microsoft Word tables containing split or merged cells. Method of Solution: TableSplitter contains two procedures. The Setup subroutine unlinks all Word fields in the active Word document. It next counts all the tables in the documentmore » and then calls the SplitCells subroutine. SplitCells splits the appropriate cells for each table, so a n row by m column table actually has n by m cells that DOORS can import.« less

  3. 1999 Commercial Buildings Energy Consumption Survey Detailed Tables

    Gasoline and Diesel Fuel Update (EIA)

    Consumption and Expenditures Tables Table C1. Total Energy Consumption by Major Fuel ............................................... 124 Table C2. Total Energy Expenditures by Major Fuel................................................ 130 Table C3. Consumption for Sum of Major Fuels ...................................................... 135 Table C4. Expenditures for Sum of Major Fuels....................................................... 140 Table C5. Consumption and Gross Energy Intensity by

  4. NREL: Resource Assessment and Forecasting - Metrology Laboratory

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

    Metrology Laboratory Photo of Solar Radiation Research Laboratory researchers inspecting radiometers mounted to calibration tables at the outside test site. Researchers at the Solar Radiation Research Laboratory use pyranometers, pyrheliometers, pyrgeometers, photometers, and spectroradiometers to provide the solar resource information necessary for renewable energy research and development. Metrology, the science of measurement, is a critical part of providing accurate and repeatable data.

  5. Table

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

    from (2012KE01): Energy Levels of 11 Li E x (MeV ± keV) J π ; T T 1 2 or Γ Decay Reactions g.s. 3 2 - ; 5 2 T 1 2 = 8.75 ± 0.14 ms β - 1, 2, 4, 5, 6, 8, 9 1.220 ± 40 Γ = 0.53 ± 0.15 MeV n 2, 6, 7, 9, 10 2.420 ± 50 Γ = 1.26 ± 0.30 MeV n 2, 4, 6, 7, 9, 10 3.700 ± 130 Γ < 200 keV n 7 4.860 ± 60 Γ < 100 keV n 2, 4, 9 6.230 ± 60 Γ < 100 keV n 2, 4, 9 11.300 n 2 1

  6. Table

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

    4 from (2012KE01): Energy levels of 11 Be E x (MeV ± keV) J π ; T T 1 2 or Γ c.m. (keV) Decay Reactions 0 1 2 + ; 3 2 T 1 2 = 13.76 ± 0.07 s β - 1, 3, 4, 5, 6, 8, 9, 10, 12, 14, 16, 17, 19, 23, 24, 25, 26, 27, 28, 30, 31, 32 0.32004 ± 0.1 1 2 - T 1 2 = 115 ± 10 fs γ 4, 5, 6, 8, 9, 10, 14, 15, 16, 17, 19, 21, 22, 23, 26, 28, 29, 30, 33 1.783 ± 4 5 2 + Γ = 100 ± 10 n 4, 5, 6, 9, 10, 14, 23, 26, 28 2.654 ± 10 3 2 - a 206 ± 8 n 5, 6, 9, 10, 15, 16, 21, 22, 23, 28, 29 3.40 ± 6 ( 3 2 - ,

  7. Table

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

    8 from (2012KE01): Energy levels of 11 B E x J π ; T Γ cm (keV) Decay Reactions (MeV ± keV) 0 3 2 - ; 1 2 stable 2, 3, 7, 8, 11, 15, 16, 17, 18, 19, 22, 26, 27, 28, 29, 30, 32, 33, 34, 35, 36, 37, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 51, 53, 54, 55, 56, 57, 58, 59, 60, 61, 63, 67, 68, 69, 70, 71, 72, 73, 74 2.124693 ± 0.027 1 2 - 0.117 ± 0.004 eV γ 2, 7, 8, 11, 15, 16, 17, 18, 19, 26, 27, 28, 30, 32, 33, 35, 36, 37, 39, 40, 42, 44, 51, 53, 54, 55, 56, 57, 58, 59, 60, 61, 63, 67, 68, 69,

  8. Table

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

    5 from (2012KE01): Energy levels of 11 N E res (MeV ± keV) E x (MeV ± keV) J π ; T Γ (keV) Decay Reactions 1.49 ± 60 0 1 2 + ; 3 2 830 ± 30 p 1, 2, 3, 6 2.22 ± 30 0.73 ± 70 1 2 - 600 ± 100 p 1, 2, 3, 5, 6 3.06 ± 80 (1.57 ± 80) < 100 p 3 3.69 ± 30 2.20 ± 70 5 2 + 540 ± 40 p 1, 3, 5, 6 4.35 ± 30 2.86 ± 70 3 2 - 340 ± 40 p 1, 3, 5, 6 5.12 ± 80 (3.63 ± 100) ( 5 2 - ) < 220 p 5 5.91 ± 30 4.42 ± 70 ( 5 2 - ) p 3, 5, 6 6.57 ± 100 5.08 ± 120 ( 3 2 - ) 100 ± 60 p 3, 6 1

  9. Table

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

    1.0 fs 5, 7, 9, 14, 15, 19, 20, 23, 24, 25 5.2409 0.3 5 2 + 3.25 0.30 ps 4, 5, 6, 7, 9, 14, 15, 18, 19, 20, 23, 24, 25, 27 g +0.248 0.026 6.1763 1.7 3 2 -...

  10. Table

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

    transitions in A 18-19 nuclei a Nucleus E xi E xf J i J f b Mult. S (MeV) (eV) (W.u.) 18 O c 1.98 0 2 + 0 + (2.35 0.06) 10 -4 E2 3.32 ...

  11. Table

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

    - 17 a Nucleus E xi E xf J i (T i ) J f (T f ) (eV) Branching ratio Mult. S (W.u.) (MeV) (%) 16 N b 0.12 0 0 - (1) 2 - (1) (8.7 0.1) 10 -11 100 E2...

  12. Table

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

    transitions in A 5 - 10 a Nucleus E xi E xf (MeV) J i J f b (eV) Mult. S (W.u.) 5 He 16.75 0 3 2 + 3 2 - 2.1 0.4 E1 (2.3 0.4) 10 -3 5 Li...

  13. Table

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

    transitions in A 11 - 12 a Nucleus E xi E xf J i J f b Mult. S (MeV) (eV) (W.u.) 11 Be 0.32 0 1 2 - 1 2 + (3.97 0.36) 10 -3 E1 0.360...

  14. Table

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

    transitions in A 20 nuclei a Nucleus E xi E xf J i J f b Mult. S (MeV) (eV) (W.u.) 20 O c 1.67 0 2 + 0 + (6.28 0.24) 10 -5 E2 1.80 ...

  15. Table

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

    transitions in A 5 - 7 Nucleus E xi E xf J i J f a (eV) Mult. S (W.u.) b (MeV) 5 He 16.84 0 3 2 + 3 2 - 2.1 0.4 E1 (2.2 0.4) 10 -3...

  16. Table

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

    in A 13 - 15 a Nucleus E xi E xf J i (T i ) J i (T f ) Mult. S (MeV) (eV) (W.u.) 13 C b 3.09 0 1 2 + 1 2 - 0.43 0.04 E1 (3.9 0.4) ...

  17. Table

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

    transitions in A 18 - 20 a Nucleus E xi E xf J i J f b Mult. S (MeV) (eV) (W.u.) 18 O c 1.98 0 2 + 0 + (2.35 0.06) 10 -4 E2 3.32 ...

  18. Table

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

    electromagnetic transitions in A 11 Nucleus E xi E xf J i J f Mult. W (MeV) (eV) (W.u.) 11 Be 0.32 0 1 2 - 1 2 + (3.97 0.35) 10 -3...

  19. Table

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

    5.4 from (1991AJ01): Energy levels of 15 N a E x J ; T m or Decay Reactions (MeV keV) c.m. (keV) 0 1 2 - ; 1 2 - stable 3, 4, 5, 6, 13, 14, 16, 17, 18, 19, 20, 24, 25,...

  20. Table

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

    or m (keV) Decay Reactions 0 0 + ; 0 stable 5, 7, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 24, 30, 32, 33, 34, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,...

  1. Table

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

    keV) 0 3 2 - ; 1 2 T 1 2 20.364 0.014 min + 1, 2, 6, 7, 10, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 43, 44 2.0000 ...

  2. 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.

  3. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

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

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

  4. Module 6 - Metrics, Performance Measurements and Forecasting | Department

    Energy Savers [EERE]

    of Energy 6 - Metrics, Performance Measurements and Forecasting Module 6 - Metrics, Performance Measurements and Forecasting This module focuses on the metrics and performance measurement tools used in Earned Value. This module reviews metrics such as cost and schedule variance along with cost and schedule performance indices. In addition, this module will outline forecasting tools such as estimate to complete (ETC) and estimate at completion (EAC)

  5. Funding Opportunity Announcement for Wind Forecasting Improvement Project

    Office of Environmental Management (EM)

    in Complex Terrain | Department of Energy Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex Terrain Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex Terrain April 4, 2014 - 9:47am Addthis On April 4, 2014 the U.S. Department of Energy announced a $2.5 million funding opportunity entitled "Wind Forecasting Improvement Project in Complex Terrain." By researching the physical processes that take place in complex

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

    Office of Environmental Management (EM)

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

  7. Microsoft Word - table_15.doc

    Gasoline and Diesel Fuel Update (EIA)

    0 Table 15. Consumption of natural gas by state, 2010-2014 (million cubic feet) a Lease fuel quantities were estimated by assuming that the proportions of onsystem production used as lease fuel by respondents to the Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," were the same as the proportions of gross withdrawals as reported on Form EIA-895, "Annual Quantity and Value of Natural Gas Production Report," used as lease by all operators.

  8. Microsoft Word - table_21.doc

    Gasoline and Diesel Fuel Update (EIA)

    9 Table 21. Number of natural gas commercial consumers by type of service and state, 2013-2014 R Revised data. Note: Totals may not equal sum of components due to independent rounding. Source: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition." Please see the cautionary note regarding the number of residential and commercial customers located on the second page of Appendix A of this report. Alabama 67,006 130

  9. Table-top job analysis

    SciTech Connect (OSTI)

    Not Available

    1994-12-01

    The purpose of this Handbook is to establish general training program guidelines for training personnel in developing training for operation, maintenance, and technical support personnel at Department of Energy (DOE) nuclear facilities. TTJA is not the only method of job analysis; however, when conducted properly TTJA can be cost effective, efficient, and self-validating, and represents an effective method of defining job requirements. The table-top job analysis is suggested in the DOE Training Accreditation Program manuals as an acceptable alternative to traditional methods of analyzing job requirements. DOE 5480-20A strongly endorses and recommends it as the preferred method for analyzing jobs for positions addressed by the Order.

  10. EM International Program Action Table

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

    EM INTERNATIONAL COOPERATIVE PROGRAM] October, 2012 E M I n t e r n a t i o n a l P r o g r a m s Page 1 ACTION TABLE Subject Lead Office Engaging Country Meeting Location Purpose Status Date of Event 3 rd US/German Workshop on Salt Repository Research, Design and Operations N. Buschman, EM-22 Germany Albuquerque & Carlsbad, NM Continue collaboration with Germans on salt repository research, design and operations. Draft agenda prepared. October 8-12, 2012 International Framework for Nuclear

  11. NREL: Resource Assessment and Forecasting - Webmaster

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

    Webmaster Use this form to send us your comments and questions, report problems with the site, or ask for help finding information on the site. Please enter your name and email address in the boxes provided, then type your message below. When you are finished, click "Send Message." NOTE: If you enter your e-mail address incorrectly, we will be unable to reply. Your name: Your email address: Your message: Send Message Printable Version Resource Assessment & Forecasting Home

  12. 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.

  13. 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.

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

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

    research project whose overarching goals are to improve the accuracy of short-term wind energy forecasts, and to demonstrate the economic value of these improvements. WFIP Round...

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

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

    Opportunity, DOE is funding solar projects that are helping utilities, grid operators, solar power plant owners, and other stakeholders better forecast when, where, and how much...

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

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

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

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

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

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

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

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

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

  19. Environmental Regulatory Update Table, November 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1991-12-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  20. Environmental regulatory update table, July 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1991-08-01

    This Environmental Regulatory Update Table (July 1991) provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  1. Environmental Regulatory Update Table, October 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1991-11-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  2. Environmental Regulatory Update Table, October 1990

    SciTech Connect (OSTI)

    Houlberg, L.M.; Noghrei-Nikbakht, P.A.; Salk, M.S.

    1990-11-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  3. Environmental regulatory update table, March 1989

    SciTech Connect (OSTI)

    Houlberg, L.; Langston, M.E.; Nikbakht, A.; Salk, M.S.

    1989-04-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  4. Environmental Regulatory Update Table, September 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1991-10-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  5. Environmental Regulatory Update Table, August 1991

    SciTech Connect (OSTI)

    Houlberg, L.M., Hawkins, G.T.; Salk, M.S.

    1991-09-01

    This Environmental Regulatory Update Table (August 1991) provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  6. Environmental Regulatory Update Table, April 1989

    SciTech Connect (OSTI)

    Houlberg, L.; Langston, M.E.; Nikbakht, A.; Salk, M.S.

    1989-05-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  7. Environmental Regulatory Update Table, December 1989

    SciTech Connect (OSTI)

    Houlbert, L.M.; Langston, M.E. ); Nikbakht, A.; Salk, M.S. )

    1990-01-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  8. TableHC2.12.xls

    Gasoline and Diesel Fuel Update (EIA)

    Table HC2.12 Home Electronics Usage Indicators by Type of Housing Unit, 2005 5 or More Units Mobile Homes Type of Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Home Electonics Usage Indicators Detached Attached 2 to 4 Units Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units Table HC2.12 Home Electronics Usage Indicators by Type of Housing Unit, 2005 5 or

  9. Community Leaders Round Table | Argonne National Laboratory

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

    Community Leaders Round Table The Round Table consists of citizens with regional constituencies, including elected officials on the village, city, township, county and state levels; leaders of school districts, environmental boards and other agencies; and officers of labor unions and home owners associations. The Argonne National Laboratory/U.S. Department of Energy Community Leaders Round Table provides an informal and convenient forum for sharing information about Argonne plans and activities

  10. ARM - Lesson Plans: Rainfall and Water Table

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

    Rainfall and Water Table Outreach Home Room News Publications Traditional Knowledge Kiosks Barrow, Alaska Tropical Western Pacific Site Tours Contacts Students Study Hall About ARM Global Warming FAQ Just for Fun Meet our Friends Cool Sites Teachers Teachers' Toolbox Lesson Plans Lesson Plans: Rainfall and Water Table Objective The objective is to show how an increase of rainfall under climate change can affect the water table and soil salinity underground. Materials Each student or group of

  11. Public Notice Applicability Table | Open Energy Information

    Open Energy Info (EERE)

    http:crossref.org Citation Retrieved from "http:en.openei.orgwindex.php?titlePublicNoticeApplicabilityTable&oldid792160" Feedback Contact needs updating Image...

  12. TABLE11.CHP:Corel VENTURA

    Gasoline and Diesel Fuel Update (EIA)

    (Thousand Barrels) Table 11. PAD District II-Year-to-Date Supply, Disposition, and Ending Stocks of Crude Oil and Petroleum January-July 2004 Products, Crude Oil...

  13. TABLE15.CHP:Corel VENTURA

    Gasoline and Diesel Fuel Update (EIA)

    Table 15. PAD District III-Year-to-Date Supply, Disposition, and Ending Stocks of Crude Oil and Petroleum (Thousand Barrels) January-July 2004 Products, Crude Oil...

  14. TABLE19.CHP:Corel VENTURA

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

    Table 19. PAD District IV-Year-to-Date Supply, Disposition, and Ending Stocks of Crude Oil and Petroleum (Thousand Barrels) January-July 2004 Products, Crude Oil...

  15. TABLE53.CHP:Corel VENTURA

    Gasoline and Diesel Fuel Update (EIA)

    Table 53. Movements of Crude Oil and Petroleum Products by Pipeline, Tanker, and Barge Between July 2004 Crude Oil ... 0 383 0...

  16. TABLE54.CHP:Corel VENTURA

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

    Administration (EIA) Forms EIA-812, "Monthly Product Pipeline Report," and EIA-813, Monthly Crude Oil Report." Table 54. Movements of Crude Oil and Petroleum Products by Pipeline...

  17. 1995 CECS C&E Tables

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

    (3 pages, 20 kb) CONTENTS PAGES Table 19. Distribution of Peak Watts per Square Foot and Load Factors, 1995 These data are from the 1995 Commercial Buildings Energy...

  18. Action Codes Table | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    NNSA Blog Home About Us Our Programs Defense Nuclear Security Nuclear Materials Management & Safeguards System NMMSS Information, Reports & Forms Code Tables Action...

  19. 1995 CECS C&E Tables

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

    15. Season of Peak Electricity Demand, Number of Buildings and Floorspace, 1995 Table 16. Electricity Consumption and Conditional Energy Intensity by Season of Peak Demand, 1995...

  20. TABLES1.CHP:Corel VENTURA

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

    Energy Information AdministrationPetroleum Supply Monthly, September 2004 2 Table S1. Crude Oil and Petroleum Products Overview, 1988 - Present (Continued) (Thousand Barrels...

  1. Summary Statistics Table 1. Crude Oil Prices

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

    from Table 24. Refiner acquisition costs -- Energy Information Administration, Form FEA-P110-M-1, "Refiners' Monthly Cost Allocation Report," January 1978 through June 1978;...

  2. 1995 CECS C&E Tables

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

    reported for fewer than 20 buildings. Notes: * To obtain the RSE percentage for any table cell, multiply the corresponding RSE column and RSE row factors. * See Glossary for...

  3. FY 2015 Summary Control Table by Appropriation

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

    Summary Control Table by Appropriation Page 1 FY 2015 ... +416,108 +21.9% Electricity delivery and energy ... -67,598 -11.3% Energy information administration......

  4. TableHC7.3.xls

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

    Income Relative to Poverty Line Below 100 Percent...... Below Poverty Line Eligible for Federal Assistance 1 80,000 or More Table HC7.3 Household ...

  5. FY 2005 Control Table by Appropriation

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

    Appropriation (dollars in thousands - OMB Scoring) Table of Contents Summary...................................................................................................... 1 Mandatory Funding....................................................................................... 3 Energy Supply.............................................................................................. 4 Non-Defense site acceleration completion................................................... 5 Uranium

  6. FY 2005 Control Table by Organization

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

    Organization (dollars in thousands - OMB Scoring) Table of Contents Summary...................................................................................................... 1 Mandatory Funding....................................................................................... 2 National Nuclear Security Administration..................................................... 3 Energy Efficiency and Renewable Energy.................................................... 4 Electric Transmission

  7. Health Care Buildings : Basic Characteristics Tables

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

    Basic Characteristics Tables Buildings and Size Data by Basic Characteristics for Health Care Buildings Number of Buildings (thousand) Percent of Buildings Floorspace (million...

  8. 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.

  9. Microsoft Word - table_03.doc

    Gasoline and Diesel Fuel Update (EIA)

    9 Table 3. Gross withdrawals and marketed production of natural gas by state and the Gulf of Mexico, 2010-2014 (million cubic feet) 2010 Total 13,247,498 5,834,703 1,916,762 5,817,122 26,816,085 3,431,587 165,928 836,698 22,381,873 1,066,366 21,315,507 2011 Total 12,291,070 5,907,919 1,779,055 8,500,983 28,479,026 3,365,313 209,439 867,922 24,036,352 1,134,473 22,901,879 2012 Total 12,504,227 4,965,833 1,539,395 10,532,858 29,542,313 3,277,588 212,848 768,598 25,283,278 1,250,012 24,033,266 2013

  10. Microsoft Word - table_04.doc

    Gasoline and Diesel Fuel Update (EIA)

    2 Table 4. Offshore gross withdrawals of natural gas by state and the Gulf of Mexico, 2010-2014 (million cubic feet) 2010 Total 234,236 341,365 575,601 1,701,665 598,679 2,300,344 2,875,945 Alabama 101,487 0 101,487 NA NA NA 101,487 Alaska 42,034 328,114 370,148 0 0 0 370,148 California 71 5,483 5,554 1,757 39,444 41,200 46,755 Gulf of Mexico 0 0 0 1,699,908 559,235 2,259,144 2,259,144 Louisiana 63,222 6,614 69,836 NA NA NA 69,836 Texas 27,421 1,153 28,574 NA NA NA 28,574 2011 Total 208,970

  11. Microsoft Word - table_08.doc

    Gasoline and Diesel Fuel Update (EIA)

    5 Table 8. Summary of U.S. natural gas imports, 2010-2014 Imports Volume (million cubic feet) Pipeline Canada a 3,279,752 3,117,081 2,962,827 2,785,427 2,634,375 Mexico 29,995 2,672 314 1,069 1,426 Total Pipeline Imports 3,309,747 3,119,753 2,963,140 2,786,496 2,635,801 LNG by Truck Canada 0 0 0 555 132 LNG by Vessel Egypt 72,990 35,120 2,811 0 0 Nigeria 41,733 2,362 0 2,590 0 Norway 26,014 15,175 6,212 5,627 5,616 Peru 16,045 16,620 0 0 0 Qatar 45,583 90,972 33,823 7,320 0 Trinidad/Tobago

  12. Microsoft Word - table_09.doc

    Gasoline and Diesel Fuel Update (EIA)

    0 Table 10. Summary of U.S. natural gas exports, 2010-2014 Exports Volume (million cubic feet) Pipeline Canada 738,745 936,993 970,729 911,007 769,258 Mexico 333,251 498,657 619,802 658,368 728,513 Total Pipeline Exports 1,071,997 1,435,649 1,590,531 1,569,375 1,497,771 LNG Exports By Vessel China 0 1,127 0 0 0 Japan 30,100 15,271 9,342 0 13,310 By Truck Canada 0 0 2 71 99 Mexico 208 236 153 128 181 Re-Exports By Vessel Brazil 3,279 11,049 8,142 0 2,664 Chile 0 2,910 0 0 0 China 0 6,201 0 0 0

  13. Microsoft Word - table_13.doc

    Gasoline and Diesel Fuel Update (EIA)

    3 Table 13. Additions to and withdrawals from gas storage by state, 2014 (million cubic feet) Alabama 34,286 28,683 5,603 1,664 1,869 -206 5,397 Alaska 11,675 6,523 5,152 0 0 0 5,152 Arkansas 3,398 3,866 -468 56 42 14 -453 California 280,516 235,181 45,335 83 82 1 45,336 Colorado 72,510 70,692 1,818 0 0 0 1,818 Connecticut 0 0 0 1,032 1,359 -327 -327 Delaware 0 0 0 157 128 29 29 Georgia 0 0 0 7,130 4,046 3,085 3,085 Idaho 0 0 0 64 740 -676 -676 Illinois 270,831 260,100 10,730 61 503 -442 10,288

  14. Microsoft Word - table_17.doc

    Gasoline and Diesel Fuel Update (EIA)

    4 Table 17. Natural gas delivered to residential consumers for the account of others by state, 2010-2014 (volumes in million cubic feet) Alabama 0 -- 0 -- 0 -- 0 -- 0 -- Alaska 0 -- 0 -- 0 -- 0 -- 0 -- Arizona 0 -- 2 < 2 < 3 < 2 < Arkansas 0 -- 0 -- 0 -- 0 -- 0 -- California 7,205 1.5 8,769 1.7 12,108 2.5 18,795 3.9 20,703 5.2 Colorado 21 < 18 < 16 < 19 < 18 < Connecticut 1,156 2.7 1,438 3.2 1,364 3.3 2,199 4.7 2,096 4.1 Delaware 0 -- 0 -- 0 -- 0 -- 0 -- District of

  15. Microsoft Word - table_20.doc

    Gasoline and Diesel Fuel Update (EIA)

    8 Table 20. Number of natural gas residential consumers by type of service and state, 2013-2014 Alabama 765,957 0 765,957 769,418 0 769,418 Alaska 124,411 0 124,411 126,416 0 126,416 Arizona 1,171,997 6 1,172,003 1,186,788 6 1,186,794 Arkansas R 549,764 0 R 549,764 549,034 0 549,034 California 10,471,814 283,094 10,754,908 10,372,973 408,747 10,781,720 Colorado 1,672,307 5 1,672,312 1,690,576 5 1,690,581 Connecticut 512,110 1,382 513,492 521,460 1,198 522,658 Delaware 155,627 0 155,627 158,502 0

  16. Microsoft Word - table_22.doc

    Gasoline and Diesel Fuel Update (EIA)

    0 Table 22. Number of natural gas industrial consumers by type of service and state, 2013-2014 Alabama 2,876 267 3,143 2,973 271 3,244 Alaska 2 1 3 1 0 1 Arizona 257 126 383 256 130 386 Arkansas 513 507 1,020 531 478 1,009 California 32,662 5,334 37,996 32,266 5,282 37,548 Colorado 946 6,347 7,293 986 6,837 7,823 Connecticut 3,360 1,094 4,454 3,340 877 4,217 Delaware 28 110 138 28 113 141 Florida 166 362 528 165 355 520 Georgia 984 1,258 2,242 887 1,594 2,481 Hawaii 22 0 22 23 0 23 Idaho 109 R

  17. Biomass Webinar Text Version | Department of Energy

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

    Text Version Biomass Webinar Text Version Dowload the text version of the audio from the DOE Office of Indian Energy webinar on biomass. PDF icon DOE Office of Indian Energy Foundational Course Webinar on Biomass: Text Version More Documents & Publications Biomass Webinar Presentation Slides Assessing Energy Resources Webinar Text Version Transcript: Biomass Clean Cities Webinar - Workforce Development

  18. International Program Action Table - October 2012 | Department of Energy

    Energy Savers [EERE]

    Communication & Engagement » International Programs » International Program Action Table - October 2012 International Program Action Table - October 2012 International Program Action Table - October 2012 PDF icon EM International Program Action Table - October 2012 More Documents & Publications EM International Program Action Table - June 2014 Across the Pond Newsletter Issue 4 Across the Pond Newsletter Issue 6

  19. EM International Program Action Table - June 2014 | Department of Energy

    Energy Savers [EERE]

    Action Table - June 2014 EM International Program Action Table - June 2014 EM International Program Action Table - June 2014 PDF icon EM International Program Action Table - June 2014 More Documents & Publications International Program Action Table - October 2012 Across the Pond Newsletter Issue 9 Across the Pond Newsletter Issue 3

  20. FY 2014 Budget Request Summary Table | Department of Energy

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

    Summary Table FY 2014 Budget Request Summary Table PDF icon Summary Table by Appropriations PDF icon Summary Table by Organization More Documents & Publications FY 2014 Budget Request Statistical Table FY 2014 Budget Justification FY 2014 Department of Energy Budget Highlights

  1. 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.

  2. Supplemental Tables to the Annual Energy Outlook

    Reports and Publications (EIA)

    2015-01-01

    The Annual Energy Outlook (AEO) Supplemental tables were generated for the reference case of the AEO using the National Energy Modeling System, a computer-based model which produces annual projections of energy markets. Most of the tables were not published in the AEO, but contain regional and other more detailed projections underlying the AEO projections.

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

    Energy Savers [EERE]

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

  4. Widget:AnchorText | Open Energy Information

    Open Energy Info (EERE)

    you can specify a target, title, and style to the link. Parameters include: page - pagearticle title for href link text - anchor text title - title to display for anchor...

  5. 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.

  6. 3TIER Environmental Forecast Group Inc 3TIER | Open Energy Information

    Open Energy Info (EERE)

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

  7. Energy Savings Forecast of Solid-State Lighting in General Illuminatio...

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

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

  8. 1999 Commercial Building Characteristics--Detailed Tables--Size...

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

    Complete Set of 1999 CBECS Detailed Tables Detailed Tables- of Buildings Table B6. Building Size, Number of Buildings b6.pdf (PDF file), b6.xls (Excel spreadsheet file), b6.txt...

  9. 1999 Commercial Buildings Characteristics--Detailed Tables--Conservati...

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

    as rowstubs in most detailed tables. Total buildings, total floorspace, and average building size for these categories are shown in Table B1. The PDF and spreadsheet data tables...

  10. 2007 CBECS Large Hospital Building List of Tables

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

    in Large Hospitals Table H4: Lighting and Window Features in Large Hospitals Table H5: Major Fuels Usage for Large Hospitals Table H6: Electricity Usage for Large Hospitals...

  11. FY 2014 Budget Request Statistical Table | Department of Energy

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

    Statistical Table FY 2014 Budget Request Statistical Table PDF icon Stats Table FY2014.pdf More Documents & Publications FY 2009 Environmental Management Budget Request to Congress Fiscal Year 2013 President's Budget Request Fiscal Year 2013 President's

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

    SciTech Connect (OSTI)

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

    2011-12-06

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

  13. 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.

  14. 1999 CBECS Summary Table for All Building Activities

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

    Tables 1999 Commercial Buildings Consumption Survey SUMMARY TABLES FOR ALL PRINCIPAL BUILDING ACTIVITIES Number of Buildings (thousand) Floorspace (million square feet) Square...

  15. Energy Information Administration - Energy Efficiency-Table 3...

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

    Energy Efficiency > Iron and Steel Manufacturing Energy, 1998 and 2002 > Table 3 Page Last Modified: June 2010 Table 3. Offsite-Produced Fuel Consumption, 1998, 2002, and 2006...

  16. Headquarters Facilities Master Security Plan- Table of Contents

    Broader source: Energy.gov [DOE]

    2016 Headquarters Facilities Master Security Plan - Table of Contents Table of Contents for the 2016 Headquarters Facilities Master Security Plan (HQFMSP).

  17. EIA - Annual Energy Outlook (AEO) 2013 Data Tables

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

    Table 55.2. Electric Power Projections by Electricity Market Module Region - Florida Reliability Coordinating Council XLS Table 55.3. Electric Power Projections by Electricity...

  18. Petroleum Products Table 43. Refiner Motor Gasoline Volumes...

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

    of table. 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State 262 Energy Information Administration Petroleum Marketing Annual 1997 Table 43....

  19. Petroleum Products Table 43. Refiner Motor Gasoline Volumes...

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

    of table. 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State 262 Energy Information Administration Petroleum Marketing Annual 1996 Table 43....

  20. Petroleum Products Table 31. Motor Gasoline Prices by Grade...

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

    at end of table. 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 56 Energy Information Administration Petroleum Marketing Annual 1996 Table 31. Motor...

  1. Microsoft Word - table_05.doc

    Gasoline and Diesel Fuel Update (EIA)

    3 Table 5. Number of producing gas wells by state and the Gulf of Mexico, December 31, 2010-2014 Alabama 7,026 7,063 6,327 R 6,165 6,118 Alaska 269 277 185 R 159 170 Arizona 5 5 5 5 5 Arkansas 7,397 8,388 8,538 R 9,843 10,150 California 1,580 1,308 1,423 R 1,335 1,118 Colorado 28,813 30,101 32,000 R 32,468 38,346 Gulf of Mexico 1,852 1,559 1,474 R 1,146 1,400 Illinois 50 40 40 R 34 36 Indiana 620 914 819 R 921 895 Kansas 22,145 25,758 24,697 R 23,792 24,354 Kentucky 17,670 14,632 17,936 R 19,494

  2. Microsoft Word - table_14.doc

    Gasoline and Diesel Fuel Update (EIA)

    44 Table 14. Underground natural gas storage capacity by state, December 31, 2014 (million cubic feet) Alabama 1 21,950 30,100 0 0 0 1 11,200 13,500 2 33,150 43,600 Alaska 0 0 0 0 0 0 5 67,915 83,592 5 67,915 83,592 Arkansas 0 0 0 0 0 0 2 12,178 21,853 2 12,178 21,853 California 0 0 0 1 10,000 12,000 13 364,296 587,711 14 374,296 599,711 Colorado 0 0 0 0 0 0 10 63,774 130,186 10 63,774 130,186 Illinois 0 0 0 19 292,544 978,624 9 11,768 25,923 28 304,312 1,004,547 Indiana 0 0 0 12 19,215 80,746

  3. Microsoft Word - table_18.doc

    Gasoline and Diesel Fuel Update (EIA)

    5 Table 18. Natural gas delivered to commercial consumers for the account of others by state, 2010-2014 (volumes in million cubic feet) Alabama 5,494 20.3 5,313 21.1 5,126 23.8 5,935 23.4 5,941 21.6 Alaska 1,951 12.3 2,208 11.4 1,005 5.1 1,022 5.5 980 5.5 Arizona 3,605 11.3 3,988 12.2 4,213 13.4 4,772 14.5 4,743 15.6 Arkansas 17,862 44.4 19,402 48.5 24,772 59.8 26,797 56.3 27,604 54.5 California 113,903 45.9 112,448 45.7 126,571 50.0 127,588 50.1 122,637 51.6 Colorado 3,118 5.4 3,457 6.2 4,061

  4. Microsoft Word - table_24.doc

    Gasoline and Diesel Fuel Update (EIA)

    Table 24. Average price of natural gas delivered to consumers by state and sector, 2014 (dollars per thousand cubic feet) Alabama 14.59 100.0 11.92 78.4 5.49 23.3 4.74 Alaska 9.11 100.0 8.30 94.5 7.97 100.0 5.06 Arizona 17.20 100.0 10.34 84.4 7.52 12.8 5.30 Arkansas 10.39 100.0 7.88 45.5 6.99 1.8 W California 11.51 94.8 9.05 48.4 7.65 3.7 5.23 Colorado 8.89 100.0 8.15 94.5 6.84 7.7 5.49 Connecticut 14.13 95.9 10.24 67.2 8.07 39.4 6.82 Delaware 13.21 100.0 11.42 46.2 10.95 0.3 W District of

  5. Microsoft Word - table_27.doc

    Gasoline and Diesel Fuel Update (EIA)

    8 Table 28. Percent distribution of natural gas delivered to consumers by state, 2014 Alabama 0.8 0.8 2.5 0.6 4.2 Alaska 0.3 0.5 0.1 < 0.4 Arizona 0.6 0.9 0.3 5.8 2.5 Arkansas 0.7 1.5 1.2 0.1 0.9 California 7.8 6.9 10.3 47.0 10.1 Colorado 2.6 1.7 1.0 0.9 1.2 Connecticut 1.0 1.5 0.4 0.2 1.2 Delaware 0.2 0.3 0.4 < 0.6 District of Columbia 0.3 0.5 -- 2.9 -- Florida 0.3 1.8 1.2 0.6 12.9 Georgia 2.6 1.7 2.1 3.3 3.6 Hawaii < 0.1 < < -- Idaho 0.5 0.5 0.4 0.4 0.2 Illinois 9.4 7.1 3.9 1.0

  6. 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.

  7. Searching for Text (pbl/help)

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

    for Text Other Navigation Aids PDF File Info Firstgov Searching for Text The Power Services web site features a Search tool (powered by Google) in the upper right corner of...

  8. Text Redelegation Procedures - DOE Directives, Delegations, and...

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

    Text Redelegation Procedures by Website Administrator Delegation Procedures Redelegation Procedures Redelegation Procedures for Functional Area Managers This page contains...

  9. Assessing Energy Resources Webinar Text Version

    Broader source: Energy.gov [DOE]

    Download the text version of the audio from the DOE Office of Indian Energy webinar on assessing energy resources.

  10. TableHC9.13.xls

    Gasoline and Diesel Fuel Update (EIA)

    ... 0.3 Q Q Q Q Q Less than 4,000 HDD Housing Units (millions) Climate Zone 1 Table HC9.13 Lighting Usage Indicators by Climate Zone, 2005 Lighting Usage...

  11. TableHC7.13.xls

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

    ... Table HC7.13 Lighting Usage Indicators by Household Income, 2005 Below Poverty Line ... Below Poverty Line Eligible for Federal Assistance 1 Million U.S. Housing Units 2005 ...

  12. Table of Contents for Desk Guide

    Energy Savers [EERE]

    September, 2014 U. S. Department of Energy - Real Estate Desk Guide Revised 2014 Real Estate Desk Guide Table of Contents Chapter 1-- Purpose of Desk Guide............................................................................... 1 Chapter 2-- Introduction ................................................................................................. 3 Chapter 3-- Planning Policy ........................................................................................... 9 Chapter 4-- Real

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

    Open Energy Info (EERE)

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

  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. 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,...

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

    Reports and Publications (EIA)

    2003-01-01

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

  17. Value of Improved Short-Term Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2015-02-01

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

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

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

    The Energy Department will present a live webinar titled "Solar Forecasting Metrics" on Thursday, February 13, from 3:00 p.m. to 5:00 p.m. Eastern Standard Time. During this ...

  19. Improving the Accuracy of Solar Forecasting Funding Opportunity

    Broader source: Energy.gov [DOE]

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

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

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

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

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

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

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

  2. FY 2015 Statistical Table by Appropriation

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

    Statistical Table by Appropriation (dollars in thousands - OMB Scoring) Statistical Table by Appropriation Page 1 FY 2015 Congressional Request FY 2013 FY 2014 FY 2014 FY 2014 FY 2015 Current Enacted Adjustment Current Congressional Approp. Approp. Approp. Request Discretionary Summary By Appropriation Energy And Water Development And Related Agencies Appropriation Summary: Energy Programs Energy efficiency and renewable energy............................... 1,691,757 1,900,641 ---- 1,900,641

  3. FY 2015 Summary Control Table by Appropriation

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

    Summary Control Table by Appropriation (dollars in thousands - OMB Scoring) Summary Control Table by Appropriation Page 1 FY 2015 Congressional Request FY 2013 FY 2014 FY 2014 FY 2014 FY 2015 Current Enacted Adjustment Current Congressional Approp. Approp. Approp. Request Discretionary Summary By Appropriation Energy And Water Development And Related Agencies Appropriation Summary: Energy Programs Energy efficiency and renewable energy................................... 1,691,757 1,900,641 ----

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

    Broader source: Energy.gov [DOE]

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

  5. Study forecasts disappearance of conifers due to climate change

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Environmental Management (EM)

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

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

    Office of Environmental Management (EM)

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

  9. "RSE Table C12.1. Relative Standard Errors for Table C12.1;...

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

    2.1. Relative Standard Errors for Table C12.1;" " Units: Percents." ,,"Approximate",,,"Approximate","Average" ,,"Enclosed Floorspace",,"Average","Number","Number" "NAICS"," ","of...

  10. Connected Buildings Interoperability Vision Webinar (Text Version) |

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

    Department of Energy Connected Buildings Interoperability Vision Webinar (Text Version) Connected Buildings Interoperability Vision Webinar (Text Version) Below is the text version of the webinar Connected Buildings Interoperability Vision, presented in May 2015. Steve Widergren: Presentation cover slide: ... the webinar that we have for you today on Connected Buildings Interoperability Vision. I wanted -- My name is Steve Widergren. I'm with Pacific Northwest National Laboratory. I'm going

  11. Welcome and Advanced Manufacturing Partnership (Text Version)

    Broader source: Energy.gov [DOE]

    This is a text version of the Welcome and Advanced Manufacturing Partnership video, originally presented on March 12, 2012 at the MDF Workshop held in Chicago, Illinois.

  12. Text Delegation Procedures - DOE Directives, Delegations, and...

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

    Text Delegation Procedures Delegation Procedures Re-Delegation Procedures by Website Administrator Procedures for Line Managers' Delegations of Authority when proposing new...

  13. Manufacturing Ecosystems and Keystone Technologies (Text Version)

    Broader source: Energy.gov [DOE]

    This is a text version of the Manufacturing Ecosystems and Keystone Technologies video, originally presented on March 12, 2012 at the MDF Workshop held in Chicago, Illinois.

  14. Fuel Cell Animation- Chemical Process (Text Version)

    Broader source: Energy.gov [DOE]

    This text version of the fuel cell animation demonstrates how a fuel cell uses hydrogen to produce electricity, with only water and heat as byproducts.

  15. DOE and Critical Materials Video (Text Version)

    Broader source: Energy.gov [DOE]

    This is a text version of the "DOE and Critical Materials" video presented at the Critical Materials Workshop, held on April 3, 2012 in Arlington, Virginia.

  16. Product Guide Product Guide Volumes Category Prices Table Crude...

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

    suppliers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -- 49 Product Guide Volumes Category Prices Table Energy Information Administration Petroleum...

  17. Product Guide Product Guide Volumes Category Prices Table Crude...

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

    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -- 49 Product Guide Volumes Category Prices Table Energy Information Administration Petroleum Marketing...

  18. Qualified Energy Conservation Bond State-by-State Summary Tables

    Broader source: Energy.gov [DOE]

    Provides a list of qualified energy conservation bond state summary tables. Author: Energy Programs Consortium

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

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

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

  20. AVLIS: a technical and economic forecast

    SciTech Connect (OSTI)

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

    1986-01-01

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

  1. Style Guide Full Text | Department of Energy

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

    Style Guide Full Text Style Guide Full Text Below is the full text of the Style Guide for Web pages for the Office of Energy Efficiency and Renewable Energy. The guide features formatting, spelling, punctuation, capitalization, grammar, and language guidelines. Guidelines are listed alphabetically for easy reference. You may also use the topic index to locate information covered in the guide. A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z a

  2. Full Text Glossary | Department of Energy

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

    Full Text Glossary Full Text Glossary The full-text glossary includes terms used throughout the website and in Biomass Program publications. Terms are listed alphabetically for easy reference. The term index lists all of the terms defined in the glossary. A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z A acid: A solution that has an excess of hydrogen ions (H+), with a pH of less than 7. acetic acid: An acid with the structure of C2H4O2.

  3. Texts to Hillary-- from Secretary Chu

    Broader source: Energy.gov [DOE]

    We showed the "Texts from Hillary" Tumblr to Secretary Chu and he thought is was as hilarious as everyone else on the Internet, so we got to work on a contribution on his behalf.

  4. Vehicle Technologies Office: Lightweighting Video Text Version

    Broader source: Energy.gov [DOE]

    This is a text version of the Motorweek video segment Materials Technology / Vehicle Lightweighting, which aired on April 21, 2014. The full video is on the Lightweight Materials for Cars and...

  5. MDF Form and Function (Text Version)

    Broader source: Energy.gov [DOE]

    This is a text version of the Manufacturing Demonstration Facilities (MDF) Form and Function video, originally presented on March 12, 2012 at the MDF Workshop held in Chicago, Illinois.

  6. Forecasting the 2013–2014 influenza season using Wikipedia

    SciTech Connect (OSTI)

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

    2015-05-14

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

  7. 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

  8. Computation of term dominance in text documents

    DOE Patents [OSTI]

    Bauer, Travis L. (Albuquerque, NM); Benz, Zachary O. (Albuquerque, NM); Verzi, Stephen J. (Albuquerque, NM)

    2012-04-24

    An improved entropy-based term dominance metric useful for characterizing a corpus of text documents, and is useful for comparing the term dominance metrics of a first corpus of documents to a second corpus having a different number of documents.

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2012-04-01

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

  10. SimTable key tool for preparing, responding to wildfire

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

    SimTable key tool for preparing, responding to wildfire SimTable key tool for preparing, responding to wildfire Camera tracks movement and objects and project them onto a sand table. May 30, 2012 SimTable: Stephen Guerin (L) and Chip Garner (R) with SimTable, a Santa Fe company helping firefighters model and predict where a fire is most likely to spread, received support for their business through Lab economic development programs: VAF, NMSBA, Springboard. SimTable: Stephen Guerin (L) and Chip

  11. Extraction of information from unstructured text

    SciTech Connect (OSTI)

    Irwin, N.H.; DeLand, S.M.; Crowder, S.V.

    1995-11-01

    Extracting information from unstructured text has become an emphasis in recent years due to the large amount of text now electronically available. This status report describes the findings and work done by the end of the first year of a two-year LDRD. Requirements of the approach included that it model the information in a domain independent way. This means that it would differ from current systems by not relying on previously built domain knowledge and that it would do more than keyword identification. Three areas that are discussed and expected to contribute to a solution include (1) identifying key entities through document level profiling and preprocessing, (2) identifying relationships between entities through sentence level syntax, and (3) combining the first two with semantic knowledge about the terms.

  12. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

    2008-01-15

    Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).

  13. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

    Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).

  14. FY 2008 Control Table by Appriopriation

    Energy Savers [EERE]

    Control Table by Appropriation (dollars in thousands - OMB Scoring) FY 2006 FY 2007 FY 2008 Current Congressional Congressional Approp. Request Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy supply and Conservation..................................... 1,812,397 1,923,361 2,187,943 +264,582 +13.8% Fossil energy programs Clean coal technology...................................................

  15. Table of Contents for Desk Guide

    Energy Savers [EERE]

    May, 2013 U. S. Department of Energy - Real Estate Desk Guide Revised 2013 Real Estate Desk Guide Table of Contents Chapter 1-- Purpose of Desk Guide ........................................................................ 1 Chapter 2-- Introduction ......................................................................................... 3 Chapter 3-- Planning Policy .................................................................................... 7 Chapter 4-- Real Estate Function

  16. Help:Tables | Open Energy Information

    Open Energy Info (EERE)

    on tables 3.2 Attributes on cells 3.3 Attributes on rows 3.4 HTML colspan and rowspan 3.5 With HTML attributes and CSS styles 4 Caveats 4.1 Negative numbers 4.2 CSS vs Attributes...

  17. FY 2015 Summary Control Table by Organization

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

    5 Summary Control Table by Organization (dollars in thousands - OMB Scoring) Summary Control by Organization Page 1 FY 2015 Congressional Request FY 2013 FY 2014 FY 2014 FY 2014 FY 2015 Current Enacted Adjustments Current Congressional Approp. Approp. Approp. Request Discretionary Summary By Organization Department Of Energy By Organization National Nuclear Security Administration Weapons Activities............................................................................. 6,966,855 7,781,000

  18. EIA Energy Efficiency-Table 1a. Table 1a. Consumption of Site...

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

    a Page Last Modified: May 2010 Table 1a. Consumption of Energy (Site Energy) for All Purposes (First Use) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) MECS Survey...

  19. CBECS - Buildings and Energy in the 1980's, Table Titles

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

    for primary or site energy ("p" or "s"). For example, Table R8.90p, shows primary energy data for residential buildings for the 1990 survey year. The tables are arranged into...

  20. Widget:UtilityRateEntryHelperTable | Open Energy Information

    Open Energy Info (EERE)

    UtilityRateEntryHelperTable Jump to: navigation, search This widget displays the utility rate database form. For example: Widget:UtilityRateEntryHelperTable Retrieved from...

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

    SciTech Connect (OSTI)

    Piwko, R.; Jordan, G.

    2011-11-01

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

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

    Broader source: Energy.gov [DOE]

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

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2010-04-01

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

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

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

    Forecasting Gets a Boost from Watson, Accuracy Improved by 30% EERE Success Story-Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% October 27, 2015 - 11:48am ...

  5. Environmental Regulatory Update Table, January/February 1992

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1992-03-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action. This table is for January/February 1992.

  6. Minimum Efficiency Requirements Tables for Heating and Cooling Product

    Energy Savers [EERE]

    Categories | Department of Energy Minimum Efficiency Requirements Tables for Heating and Cooling Product Categories Minimum Efficiency Requirements Tables for Heating and Cooling Product Categories The Federal Energy Management Program (FEMP) created tables that mirror American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1-2013 tables, which include minimum efficiency requirements for FEMP-designated and ENERGY STAR-qualified heating and cooling product

  7. Table IV: Technical Targets for Membranes: Stationary | Department of

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

    Energy IV: Technical Targets for Membranes: Stationary Table IV: Technical Targets for Membranes: Stationary "Technical targets for fuel cell membranes in stationary applications defined by the High Temperature Working Group (February 2003). " PDF icon technical_targets_membr_stat.pdf More Documents & Publications Table II: Technical Targets for Membranes: Automotive Table III: Technical Targets for Catalyst Coated Membranes (CCMs): Stationary Table I: Technical Targets for

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

    SciTech Connect (OSTI)

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

    2009-03-01

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

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

    Energy Science and Technology Software Center (OSTI)

    2012-05-01

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

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

    SciTech Connect (OSTI)

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

    2011-03-28

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

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

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

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

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2009-12-01

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

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

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

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

  14. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

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

    2011-11-29

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

  15. Environmental Regulatory Update Table, January/February 1995

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Bock, R.E.; Mayer, S.J.; Salk, M.S.

    1995-03-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives impacting environmental, health, and safety management responsibilities. the table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

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

    SciTech Connect (OSTI)

    1995-04-01

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

  18. AVLIS documentation overview and tables of contents

    SciTech Connect (OSTI)

    Not Available

    1984-11-15

    Three documents constitute the executive summary series in Data Package III: this document (Documentation Overview and Tables of Contents (E001)) plus the AVLIS Production Plant Executive Summary (E010) and the AVLIS Production Plant Overall Design Report (E020). They provide progressively greater detail on the key information and conclusions contained within the data package. The Executive Summary and Overall Design Report present summaries of each Data Package III document. They are intended to provide a global overview of AVLIS Production Plant deployment including program planning, project management, schedules, engineering design, production, operations, capital cost, and operating cost. The purpose of Overview and Tables of Contents is threefold: to briefly review AVLIS goals for Data Package III documentation, to present an overview of the contents of the data package, and to provide a useful guide to information contained in the numerous documents comprising the package.

  19. FY 2008 Control Table by Organization

    Energy Savers [EERE]

    Control Table by Organization (dollars in thousands - OMB Scoring) FY 2006 FY 2007 FY 2008 Current Congressional Congressional Approp. Request Request $ % Discretionary Summary By Organization National Security Weapons.............................................................................. 6,355,297 6,407,889 6,511,312 +103,423 +1.6% Defense Nuclear Nonproliferation....................................... 1,619,179 1,726,213 1,672,646 -53,567 -3.1% Naval

  20. FY 2010 Control Table by Organization

    Energy Savers [EERE]

    0 Control Table by Organization (dollars in thousands - OMB Scoring) FY 2008 FY 2009 FY 2009 FY 2010 Current Current Current Congressional Approp. Approp. Recovery Request $ % Discretionary Summary By Organization National Security Weapons........................................................................................... 6,302,366 6,380,000 -- 6,384,431 +4,431 +0.1% Defense Nuclear Nonproliferation....................................................... 1,334,922 1,482,350 -- 2,136,709

  1. Code Tables | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    Code Tables | National Nuclear Security Administration Facebook Twitter Youtube Flickr RSS People Mission Managing the Stockpile Preventing Proliferation Powering the Nuclear Navy Emergency Response Recapitalizing Our Infrastructure Countering Nuclear Terrorism About Our Programs Our History Who We Are Our Leadership Our Locations Budget Our Operations Library Bios Congressional Testimony Fact Sheets Newsletters Press Releases Photo Gallery Jobs Apply for Our Jobs Our Jobs Working at NNSA Blog

  2. FY 2013 Control Table by Appropriation

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

    Summary Control Table by Appropriation (dollars in thousands - OMB Scoring) FY 2011 FY 2012 FY 2013 Current Enacted Congressional Approp. Approp. * Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy efficiency and renewable energy......................................... 1,771,721 1,809,638 2,337,000 +527,362 +29.1% Electricity delivery and energy reliability..........................................

  3. EXECUTIVE SUMMARY- Inserted before Table of Contents

    National Nuclear Security Administration (NNSA)

    DRAFT ENVIRONMENTAL ASSESSMENT FOR REMOVAL ACTIONS AT THE TECHNICAL AREA III CLASSIFIED WASTE LANDFILL, SANDIA NATIONAL LABORATORIES, NEW MEXICO DOE/EA-1729 June 2010 National Nuclear Security Administration Sandia Site Office P.O. Box 5400 Albuquerque, New Mexico 87185-5400 DOE/EA-1729: Environmental Assessment for Removal Actions at the Technical Area III June 2010 Classified Waste Landfill, Sandia National Laboratories, New Mexico i TABLE OF CONTENTS Section Page 1.0 PURPOSE AND NEED FOR

  4. Action Codes Table | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    Action Codes Table | National Nuclear Security Administration Facebook Twitter Youtube Flickr RSS People Mission Managing the Stockpile Preventing Proliferation Powering the Nuclear Navy Emergency Response Recapitalizing Our Infrastructure Countering Nuclear Terrorism About Our Programs Our History Who We Are Our Leadership Our Locations Budget Our Operations Library Bios Congressional Testimony Fact Sheets Newsletters Press Releases Photo Gallery Jobs Apply for Our Jobs Our Jobs Working at NNSA

  5. SimTable helps firefighters model and predict fire direction

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

    SimTable models and predicts fire path SimTable helps firefighters model and predict fire direction In 2009, SimTable received $100,000 from the LANS Venture Acceleration Fund to improve the user interface and seed firefighting academies with customized set ups. April 3, 2012 Stephen Guerin (L) and Chip Garner (R) with SimTable Stephen Guerin (L), and Chip Garner (R), with SimTable, a Santa Fe company helping firefighters model and predict where a fire is most likely to spread, received support

  6. Table of QTR comments in response to Federal Register RFI | Department of

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

    Energy Table of QTR comments in response to Federal Register RFI QTR table of respondents

  7. text_sunshot_rtc.docx | Department of Energy

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

    text_sunshot_rtc.docx text_sunshot_rtc.docx text_sunshot_rtc.docx File text_sunshot_rtc.docx More Documents & Publications text_sunshot_csp.docx text_sunshot_pdil.docx text_sunshot_softcosts.docx

  8. Forecast of transportation energy demand through the year 2010

    SciTech Connect (OSTI)

    Mintz, M.M.; Vyas, A.D.

    1991-04-01

    Since 1979, the Center for Transportation Research (CTR) at Argonne National Laboratory (ANL) has produced baseline projections of US transportation activity and energy demand. These projections and the methodologies used to compute them are documented in a series of reports and research papers. As the lastest in this series of projections, this report documents the assumptions, methodologies, and results of the most recent projection -- termed ANL-90N -- and compares those results with other forecasts from the current literature, as well as with the selection of earlier Argonne forecasts. This current forecast may be used as a baseline against which to analyze trends and evaluate existing and proposed energy conservation programs and as an illustration of how the Transportation Energy and Emission Modeling System (TEEMS) works. (TEEMS links disaggregate models to produce an aggregate forecast of transportation activity, energy use, and emissions). This report and the projections it contains were developed for the US Department of Energy's Office of Transportation Technologies (OTT). The projections are not completely comprehensive. Time and modeling effort have been focused on the major energy consumers -- automobiles, trucks, commercial aircraft, rail and waterborne freight carriers, and pipelines. Because buses, rail passengers services, and general aviation consume relatively little energy, they are projected in the aggregate, as other'' modes, and used primarily as scaling factors. These projections are also limited to direct energy consumption. Projections of indirect energy consumption, such as energy consumed in vehicle and equipment manufacturing, infrastructure, fuel refining, etc., were judged outside the scope of this effort. The document is organized into two complementary sections -- one discussing passenger transportation modes, and the other discussing freight transportation modes. 99 refs., 10 figs., 43 tabs.

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

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

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

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

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

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

  11. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect (OSTI)

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

    2015-01-01

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

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

    SciTech Connect (OSTI)

    Lemont, S.

    1980-01-01

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

  13. text_sunshot_csp.docx | Department of Energy

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

    csp.docx text_sunshot_csp.docx text_sunshot_csp.docx File text_sunshot_csp.docx More Documents & Publications text_sunshot_rtc.docx text_sunshot_softcosts.docx text_sunshot_pdil

  14. text_sunshot_pdil.docx | Department of Energy

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

    pdil.docx text_sunshot_pdil.docx text_sunshot_pdil.docx File text_sunshot_pdil.docx More Documents & Publications text_sunshot_rtc.docx text_sunshot_csp.docx text_sunshot_softcosts

  15. text_sunshot_softcosts.docx | Department of Energy

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

    softcosts.docx text_sunshot_softcosts.docx text_sunshot_softcosts.docx File text_sunshot_softcosts.docx More Documents & Publications text_sunshot_rtc.docx text_sunshot_csp.docx text_sunshot_pdil

  16. Table 2. Nuclear power plant data

    Gasoline and Diesel Fuel Update (EIA)

    Revised: February 3, 2016 (revision) Next release date: Late 2018 Table 2. Nuclear power plant data as of June 30, 2013 Reactor name State Reactor type Reactor vendora Core size (number of assemblies) Startup date (year) b License expiration (year) Actual retirement (year) Arkansas Nuclear 1 AR PWR B&W 177 1974 2034 Arkansas Nuclear 2 AR PWR CE 177 1978 2038 Beaver Valley 1 PA PWR WE 157 1976 2036 Beaver Valley 2 PA PWR WE 157 1987 2047 Big Rock Point MI BWR GE 84 1964 2057 1997 Braidwood 1

  17. Microsoft Word - table_A2.doc

    Gasoline and Diesel Fuel Update (EIA)

    195 19 4 Figure A1. Natural gas processing plant capacity in the United States, 2014 2014 Table A2. Natural gas processing plant capacity, by state, 2014 (million cubic feet per day) Alabama 1,459 Arkansas 37 California 898 Colorado 6,130 Florida 90 Illinois 2,102 Kansas 1,664 Kentucky 255 Louisiana 10,870 Michigan 126 Mississippi 1,883 State Plant Capacity Notes: Coverage includes the Lower 48 States (excluding Alaska and Hawaii). Source: Energy Information Administration (EIA), Form EIA-757,

  18. Forecast of Standard Atomic Weights for the Mononuclidic Elements 2011

    SciTech Connect (OSTI)

    Holden, N.E.; Holden, N.; Holden,N.E.

    2011-07-27

    In this short report, I will provide an early warning about potential changes to the standard atomic weight values for the twenty mononuclidic and the so-called pseudo-mononuclidic ({sup 232}Th and {sup 231}Pa) chemical elements due to the estimated changes in the mass values to be published in the next Atomic Mass Tables within the next two years. There have been many new measurements of atomic masses, since the last published Atomic Mass Table. The Atomic Mass Data Center has released an unpublished version of the present status of the atomic mass values as a private communication. We can not update the Standard Atomic Weight Table at this time based on these unpublished values but we can anticipate how many changes are probably going to be expected in the next few years on the basis of the forthcoming publication of the Atomic Mass Table. I will briefly discuss the procedures that the Atomic Weights Commission used in deriving the recommended Standard Atomic Weight values and their uncertainties from the atomic mass values. I will also discuss some concern raised about a proposed change in the definition of the mole. The definition of the mole is now connected directly to the mass of a {sup 12}C isotope (which is defined as 12 exactly) and to the kilogram. A change in the definition of the mole will probably impact the mass of {sup 12}C.

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

    SciTech Connect (OSTI)

    Hnilo, J J

    2006-03-17

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

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

    SciTech Connect (OSTI)

    Hnilo, J J

    2006-09-22

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

  1. International energy indicators. [Statistical tables and graphs

    SciTech Connect (OSTI)

    Bauer, E.K.

    1980-05-01

    International statistical tables and graphs are given for the following: (1) Iran - Crude Oil Capacity, Production and Shut-in, June 1974-April 1980; (2) Saudi Arabia - Crude Oil Capacity, Production, and Shut-in, March 1974-Apr 1980; (3) OPEC (Ex-Iran and Saudi Arabia) - Capacity, Production and Shut-in, June 1974-March 1980; (4) Non-OPEC Free World and US Production of Crude Oil, January 1973-February 1980; (5) Oil Stocks - Free World, US, Japan, and Europe (Landed, 1973-1st Quarter, 1980); (6) Petroleum Consumption by Industrial Countries, January 1973-December 1979; (7) USSR Crude Oil Production and Exports, January 1974-April 1980; and (8) Free World and US Nuclear Generation Capacity, January 1973-March 1980. Similar statistical tables and graphs included for the United States include: (1) Imports of Crude Oil and Products, January 1973-April 1980; (2) Landed Cost of Saudi Oil in Current and 1974 Dollars, April 1974-January 1980; (3) US Trade in Coal, January 1973-March 1980; (4) Summary of US Merchandise Trade, 1976-March 1980; and (5) US Energy/GNP Ratio, 1947 to 1979.

  2. Environmental Regulatory Update Table, November--December 1992

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Lewis, E.B.; Salk, M.S.

    1993-01-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly wit information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  3. Environmental sciences division: Environmental regulatory update table July 1988

    SciTech Connect (OSTI)

    Langston, M.E.; Nikbakht, A.; Salk, M.S.

    1988-08-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  4. Environmental Regulatory Update Table, March/April 1992

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1992-05-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  5. Environmental regulatory update table, September--October 1992

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Lewis, E.B.; Salk, M.S.

    1992-11-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  6. Environmental Regulatory Update Table, July--August 1992

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Lewis, E.B.; Salk, M.S.

    1992-09-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  7. Environmental regulatory update table November--December 1994

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Bock, R.E.; Mayer, S.J.; Salk, M.S.

    1995-01-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  8. Environmental Regulatory Update Table, January--February 1994

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.; Danford, G.S.; Lewis, E.B.

    1994-03-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations ad contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  9. Environmental regulatory update table: September/October 1994

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Bock, R.E.; Salk, M.S.

    1994-11-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  10. Environmental Regulatory Update Table, November--December 1993

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.; Danford, G.S.; Lewis, E.B.

    1994-01-01

    The Environmental Regulatory Update Table provides information on regulatory of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  11. EIA - Greenhouse Gas Emissions - Table-Figure Notes and Sources

    Gasoline and Diesel Fuel Update (EIA)

    A1. Notes and Sources Tables Chapter 1: Greenhouse gas emissions overview Table 1. U.S. emissions of greenhouse gases, based on global warming potential, 1990-2009: Sources: Emissions: EIA estimates. Data in this table are revised from the data contained in the previous EIA report, Emissions of Greenhouse Gases in the United States 2008, DOE/EIA-0573(2008) (Washington, DC, December 2009). Global warming potentials: Intergovernmental Panel on Climate Change, Climate Change 2007: The Physical

  12. Environmental Regulatory Update Table, September/October 1993

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.; Danford, G.S.; Lewis, E.B.

    1993-11-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operation and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  13. Composite slip table of dissimilar materials for damping longitudinal modes

    DOE Patents [OSTI]

    Gregory, Danny L. (Albuquerque, NM); Priddy, Tommy G. (Albuquerque, NM); Smallwood, David O. (Albuquerque, NM); Woodall, Tommy D. (Albuquerque, NM)

    1991-01-01

    A vibration slip table for use in a vibration testing apparatus. The table s comprised of at least three composite layers of material; a first metal layer, a second damping layer, and a third layer having a high acoustic velocity relative to the first layer. The different acoustic velocities between the first and third layers cause relative shear displacements between the layers with the second layer damping the displacements between the first and third layers to reduce the table longitudinal vibration modes.

  14. Environmental Regulatory Update Table, January--February 1993

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.; Danford, G.S.; Lewis, E.B.

    1993-03-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  15. FY 2014 Vehicles FOA 991 Selection Table | Department of Energy

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

    Vehicles FOA 991 Selection Table FY 2014 Vehicles FOA 991 Selection Table The Energy Department announced more than $55 million for 31 new projects to accelerate research and development of critical vehicle technologies that will improve fuel efficiency and reduce costs. Download the PDF to see a full list of projects. PDF icon FOA 991 Selection Table.pdf More Documents & Publications Fact Sheet: Collaboration of Oak Ridge, Argonne, and Livermore (CORAL) 1703 Process Letter Director's

  16. Table II: Technical Targets for Membranes: Automotive | Department of

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

    Energy II: Technical Targets for Membranes: Automotive Table II: Technical Targets for Membranes: Automotive Technical targets for fuel cell membranes in automotive applications defined by the High Temperature Working Group (February 2003). PDF icon technical_targets_membr_auto.pdf More Documents & Publications Table IV: Technical Targets for Membranes: Stationary Table I: Technical Targets for Catalyst Coated Membranes (CCMs): Automotive R&D Plan for the High Temperature Membrane

  17. Environmental regulatory update table, March--April 1994

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Bock, R.E.; Salk, M.S.

    1994-03-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  18. Tree_Select_Probes, Build_Hybr_Index, and Build_Hybr_Table

    Energy Science and Technology Software Center (OSTI)

    2006-08-01

    Tree_Select_Probes: This program is part of a 3 program package that replaces the older probe selection software. The purpose of the package is to generate probes specific for the group of sequences that belong to a given phylogenetic node. This software employs modified proble selection algorithm that improves speed of calculations in comparison with older software. For each node of the input tree, this program selects probes that are positive for all sequences that belongmore » to this node and negative for all that doesn't. For speed it uses probe database created by build_hybr_index program and hybridization table database created by build_hyper_table program. As a result of calculation, the program prints lists for each node from the tree. Input file formats: FASTA for sequences database, internal INDEX for probe database, internal table for hybridization database. Output file format: text file. Build_Hybr_Index: This program is part of a 3 program package that replaces the older probe selection software. The purpose of the package is to generate probles specific for the group of sequences that belong to a given phylogenetic node. This software employs modified probe selection algorithm that improves speed of calculations in comparison with older software. This program creates database of potential probes based on given sequence database, reducing it in the way so it doesn't contain repeats or substrings with meta-nucleotides. Input file format: FASTA. Output file format: itnernal INDEX file. Build_Hybr_Table: This program is part of a 3-program package that replaces the older probe selection software. The purpose of the package is to generate probles specific for the group of sequences that belong to a given phylogenetic node. This software employes modified probe selection algorithm that improves speed of calculations in comparison with older software. For each node of he input tree, this program selects probles that are positive for all sequences that belong to this node and negative for all that doesn't. For speed, it uses probe database created by build_hybr_index program and dhybridization table database created by build_hybr_table program. As a result of calculation, the program prints lists for each node from the tree. Input file formats: FASTA for sequence database, internal INDEX for probe database, internal table for hybridization database. Output file format: text file.« less

  19. Trends in Commercial Buildings--Energy Sources Consumption Tables

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

    ** estimates adjusted to match the 1995 CBECS definition of target population Energy Information Administration Commercial Buildings Energy Consumption Survey Table 2....

  20. Table 3a. Total Natural Gas Consumption per Effective Occupied...

    Gasoline and Diesel Fuel Update (EIA)

    3a. Natural Gas Consumption per Sq Ft Table 3a. Total Natural Gas Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Natural Gas...

  1. Table 21. Domestic Crude Oil First Purchase Prices

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

    Administration Petroleum Marketing Annual 1996 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

  2. Table 21. Domestic Crude Oil First Purchase Prices

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

    AdministrationPetroleum Marketing Annual 1998 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

  3. Table 21. Domestic Crude Oil First Purchase Prices

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

    Administration Petroleum Marketing Annual 1995 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

  4. Energy.gov Content Management System Data Tables

    Broader source: Energy.gov [DOE]

    For Office of Energy Efficiency and Renewable Energy (EERE) websites, follow these guidelines for creating Section 508-compliant data tables in the Energy.gov content management system.

  5. First-principles opacity table of warm dense deuterium forinertial...

    Office of Scientific and Technical Information (OSTI)

    ...ial-confinement-fusion applications Citation Details In-Document Search Title: First-principles opacity table of warm dense deuterium for inertial-confinement-fusion applications ...

  6. Table III: Technical Targets for Catalyst Coated Membranes (CCMs...

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

    III: Technical Targets for Catalyst Coated Membranes (CCMs): Stationary Table III: Technical Targets for Catalyst Coated Membranes (CCMs): Stationary Technical targets for CCMs in ...

  7. DOE Zero Energy Ready Home Second Production Builder Round Table

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

    ... Branding and Messaging * Write a press release on the round table, listing attendees * ... that will be trusted more than builder marketing efforts DOE will continue leveraging a ...

  8. Residential Transportation Historical Data Tables for 1983-2001

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

    per household and per vehicle; fuel consumption; fuel expenditures; and fuel economy. Excel PDF Trends in Households & Vehicles Table 1. Number of Households with Vehicles excel...

  9. Crude Oil Prices Table 21. Domestic Crude Oil First Purchase...

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

    Information Administration Petroleum Marketing Annual 1995 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

  10. Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane...

    Gasoline and Diesel Fuel Update (EIA)

    See footnotes at end of table. 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane, and Residual Fuel Oil by PAD District and State 386 Energy Information...

  11. Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane...

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

    Marketing Annual 1998 Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane, and Residual Fuel Oil by PAD District and State (Thousand Gallons per Day) -...

  12. Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane...

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

    Marketing Annual 1995 Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane, and Residual Fuel Oil by PAD District and State (Thousand Gallons per Day) -...

  13. Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane...

    Gasoline and Diesel Fuel Update (EIA)

    Marketing Annual 1999 Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane, and Residual Fuel Oil by PAD District and State (Thousand Gallons per Day) -...

  14. 1991 Tables and Spreadsheets and Answers to Frequently Asked...

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

    (Table A49) Relationship between Energy and Manufacturing Operations Q:How does energy consumption relate to operating costs? A: :For a review of selected operating ratios,...

  15. 2008 Annual Merit Review Results Summary - Cover and Table of...

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

    Documents & Publications 2008 Annual Merit Review Results Summary Headquarters Facilities Master Security Plan - Table of Contents EIS-0436: Draft Environmental Impact Statement...

  16. Commercial Buildings Energy Consumption Survey 2003 - Detailed Tables

    Reports and Publications (EIA)

    2008-01-01

    The tables contain information about energy consumption and expenditures in U.S. commercial buildings and information about energy-related characteristics of these buildings.

  17. Table 50. Prime Supplier Sales Volumes of Distillate Fuel Oils...

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

    Marketing Annual 1999 359 Table 50. Prime Supplier Sales Volumes of Distillate Fuel Oils and Kerosene by PAD District and State (Thousand Gallons per Day) - Continued...

  18. EERE Program Management Guide - Cover and Table of Contents

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

    .........5-35 December 2007 http:www1.eere.energy.govbaprogmgmtguide.html i EERE Program Management Guide Table of Contents ...

  19. Buildings and Energy in the 1980's (TABLES)

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

    than 10 households were sampled. Notes: * To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. * Because of rounding, data may...

  20. Petroleum Products Table 43. Refiner Motor Gasoline Volumes...

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

    1995 Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State (Thousand Gallons per Day) - Continued Geographic Area Month Premium All Grades Sales...

  1. Petroleum Products Table 43. Refiner Motor Gasoline Volumes...

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

    2000 Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State (Thousand Gallons per Day) - Continued Geographic Area Month Premium All Grades Sales...

  2. Petroleum Products Table 31. Motor Gasoline Prices by Grade...

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

    Annual 1995 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) - Continued Geographic Area Month Premium All...

  3. Petroleum Products Table 31. Motor Gasoline Prices by Grade...

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

    Annual 2000 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) - Continued Geographic Area Month Premium All...

  4. Table 1b. Relative Standard Errors for Effective, Occupied, and...

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

    b.Relative Standard Errors Table 1b. Relative Standard Errors for Effective Occupied, and Vacant Square Footage, 1992 Building Characteristics All Buildings (thousand) Total...

  5. Table 34. Reformulated Motor Gasoline Prices by Grade, Sales...

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

    Information AdministrationPetroleum Marketing Annual 1999 Table 34. Reformulated Motor Gasoline Prices by Grade, Sales Type, PAD District, and Selected States (Cents per...

  6. Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type...

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

    Energy Information Administration Petroleum Marketing Annual 1995 Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  7. Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales...

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

    250 Energy Information AdministrationPetroleum Marketing Annual 1999 Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales Type, PAD District, and State (Thousand Gallons...

  8. Table 32. Conventional Motor Gasoline Prices by Grade, Sales...

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

    Information Administration Petroleum Marketing Annual 1995 Table 32. Conventional Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  9. Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales...

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

    Energy Information Administration Petroleum Marketing Annual 1995 Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales Type, PAD District, and State (Thousand Gallons...

  10. Table 48. Prime Supplier Sales Volumes of Motor Gasoline by...

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

    Petroleum Marketing Annual 1998 Table 48. Prime Supplier Sales Volumes of Motor Gasoline by Grade, Formulation, PAD District, and State (Thousand Gallons per Day) -...

  11. Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type...

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

    134 Energy Information AdministrationPetroleum Marketing Annual 1998 Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  12. Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type...

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

    134 Energy Information AdministrationPetroleum Marketing Annual 1999 Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  13. Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type...

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

    220 Energy Information AdministrationPetroleum Marketing Annual 1998 Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State (Thousand Gallons per...

  14. Table 33. Oxygenated Motor Gasoline Prices by Grade, Sales Type...

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

    - - - - - - - - - - - - See footnotes at end of table. 33. Oxygenated Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 116 Energy Information...

  15. Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales...

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

    - - - - W W - - - - - - See footnotes at end of table. 44. Refiner Motor Gasoline Volumes by Formulation, Sales Type, PAD District, and State 292 Energy...

  16. Table 48. Prime Supplier Sales Volumes of Motor Gasoline by...

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

    Petroleum Marketing Annual 1999 Table 48. Prime Supplier Sales Volumes of Motor Gasoline by Grade, Formulation, PAD District, and State (Thousand Gallons per Day) -...

  17. Table 34. Reformulated Motor Gasoline Prices by Grade, Sales...

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

    Information AdministrationPetroleum Marketing Annual 1998 Table 34. Reformulated Motor Gasoline Prices by Grade, Sales Type, PAD District, and Selected States (Cents per...

  18. Table 32. Conventional Motor Gasoline Prices by Grade, Sales...

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

    - - - - W W - - - - - - See footnotes at end of table. 32. Conventional Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 86 Energy Information...

  19. Table 48. Prime Supplier Sales Volumes of Motor Gasoline by...

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

    Petroleum Marketing Annual 1995 Table 48. Prime Supplier Sales Volumes of Motor Gasoline by Grade, Formulation, PAD District, and State (Thousand Gallons per Day) -...

  20. Table 32. Conventional Motor Gasoline Prices by Grade, Sales...

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

    - - - - 64.7 64.7 - - - - - - See footnotes at end of table. 32. Conventional Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 86 Energy Information...

  1. Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales...

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

    250 Energy Information AdministrationPetroleum Marketing Annual 1998 Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales Type, PAD District, and State (Thousand Gallons...

  2. Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type...

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

    220 Energy Information AdministrationPetroleum Marketing Annual 1999 Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State (Thousand Gallons per...

  3. Table 34. Reformulated Motor Gasoline Prices by Grade, Sales...

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

    Information Administration Petroleum Marketing Annual 1995 Table 34. Reformulated Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  4. Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type...

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

    Energy Information Administration Petroleum Marketing Annual 1995 Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State (Thousand Gallons per...

  5. Table 32. Conventional Motor Gasoline Prices by Grade, Sales...

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

    Information AdministrationPetroleum Marketing Annual 1998 Table 32. Conventional Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  6. Table 33. Oxygenated Motor Gasoline Prices by Grade, Sales Type...

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

    Information Administration Petroleum Marketing Annual 1995 Table 33. Oxygenated Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  7. Table 2b. Relative Standard Errors for Electricity Consumption...

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

    2b. Relative Standard Errors for Electricity Table 2b. Relative Standard Errors for Electricity Consumption and Electricity Intensities, per Square Foot, Specific to Occupied and...

  8. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...

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

    2011" ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2009 and Projected 2010 through 2014 "...

  9. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...

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

    2010" ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2008 and Projected 2009 through 2013 "...

  10. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...

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

    2007" ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Council Region, " ,"2005 and Projected 2006 through 2010 "...

  11. EJ and EK Pay Table | Department of Energy

    Office of Environmental Management (EM)

    EJ and EK Pay Table EJ and EK Pay Table The 2014 EJ and EK pay table excludes locality pay. Refer to the General Schedule Complete Set of Locality Pay Tables to determine the locality pay for your applicable geographic area. INCORPORATING THE 1% GENERAL SCHEDULE INCREASE AND A LOCALITY PAYMENT OF 24.22% FOR THE LOCALITY PAY AREA OF WASHINGTON-BALTIMORE-NORTHERN VIRGINIA, DC-MD-VA-WV-PA Special Grade Min. base Min. Locality Max. Base Max. Locality GS Grade/Step Equivalent 01 $27,705 $34,415

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

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

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

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

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

    Office of Environmental Management (EM)

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

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

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

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

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

    SciTech Connect (OSTI)

    Hodge, B.

    2013-12-01

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

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

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

    ProductsCCPP-ARM Parameterization Testbed Model Forecast Data ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : CCPP-ARM Parameterization Testbed Model Forecast Data Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are

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

    SciTech Connect (OSTI)

    None, None

    2006-12-20

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

  19. Microsoft Word - table_B2.doc

    Gasoline and Diesel Fuel Update (EIA)

    00 Table B2. Thermal conversion factors and data, 2010-2014 Conversion Factor (Btu per cubic foot) Production Marketed 1,098 1,142 1,091 R 1,101 1,116 NGPL Production 2,598 2,550 2,383 2,417 2,462 Total Dry Production 1,023 1,022 1,024 1,027 1,032 Supply Dry Production 1,023 1,022 1,024 1,027 1,032 Receipts at U.S. Borders Imports 1,025 1,025 1,025 1,025 1,025 Intransit Receipts 1,025 1,025 1,025 1,025 1,025 Withdrawals from Storage Underground Storage 1,023 1,022 1,024 1,027 1,032 LNG Storage

  20. Electricity Grid Basics Webinar Presentation Slides and Text...

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

    Electricity Grid Basics Webinar Presentation Slides and Text Version Electricity Grid Basics Webinar Presentation Slides and Text Version Download presentation slides and a text...

  1. DOE Challenge Home Comprehensive Building Science Webinar (Text...

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

    Comprehensive Building Science Webinar (Text Version) DOE Challenge Home Comprehensive Building Science Webinar (Text Version) Below is the text version of the webinar, DOE Zero...

  2. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2009 … Main Text

    National Nuclear Security Administration (NNSA)

    xiii Table 4-82: HCFC-22 Production (Gg) .................................................................................................................. 4-61 Table 4-83: Quantitative Uncertainty Estimates for HFC-23 Emissions from HCFC-22 Production (Tg CO 2 Eq. and Percent) .................................................................................................................................................................... 4-62 Table 4-84: Emissions of HFCs and PFCs from ODS

  3. Table B2. Summary Table: Totals and Medians of Floorspace, Number of Workers,

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

    . Summary Table: Totals and Medians of Floorspace, Number of Workers, Hours of Operation, and Age of Building, 1999" ,"All Buildings (thousand)","Total Floorspace (million square feet)","Total Workers in All Buildings (thousand)","Median Square Feet per Building (thousand)","Median Square Feet per Worker","Median Hours per Week","Median Age of Buildings (years)" "All Buildings

  4. RSE Table 10.12 Relative Standard Errors for Table 10.12

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

    2 Relative Standard Errors for Table 10.12;" " Unit: Percents." ,,"LPG",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,"and" "Code(a)","Subsector and

  5. RSE Table 10.13 Relative Standard Errors for Table 10.13

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

    3 Relative Standard Errors for Table 10.13;" " Unit: Percents." ,,"LPG(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,"and" "Code(a)","Subsector and

  6. RSE Table 3.1 Relative Standard Errors for Table 3.1

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

    1 Relative Standard Errors for Table 3.1;" " Unit: Percents." " "," " " "," " "NAICS"," "," ","Net","Residual","Distillate","Natural","LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Electricity(b)","Fuel Oil","Fuel

  7. RSE Table 3.5 Relative Standard Errors for Table 3.5

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

    5 Relative Standard Errors for Table 3.5;" " Unit: Percents." " "," "," "," "," "," "," "," ","Waste",," " " "," "," ","Blast"," "," ","Pulping Liquor"," ","Oils/Tars" "NAICS"," ","

  8. RSE Table 4.1 Relative Standard Errors for Table 4.1

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

    1 Relative Standard Errors for Table 4.1;" " Unit: Percents." " "," " " "," " "NAICS"," "," ",,"Residual","Distillate","Natural","LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Electricity(b)","Fuel Oil","Fuel

  9. RSE Table 7.6 Relative Standard Errors for Table 7.6

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

    6 Relative Standard Errors for Table 7.6;" " Unit: Percents." " "," " " "," ",,,,,,,,," " "NAICS"," "," ",,"Residual","Distillate","Natural ","LPG and",,"Coke" "Code(a)","Subsector and Industry","Total","Electricity","Fuel Oil","Fuel

  10. RSE Table 7.7 Relative Standard Errors for Table 7.7

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

    7 Relative Standard Errors for Table 7.7;" " Unit: Percents." ,,,"Electricity","Components",,"Natural Gas","Components",,"Steam","Components" " "," ",,,,,,,,,,," " " "," ",,,"Electricity",,,"Natural Gas",,,"Steam" " "," ",,"Electricity","from Sources",,"Natural Gas","from

  11. RSE Table 8.2 Relative Standard Errors for Table 8.2

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

    2 Relative Standard Errors for Table 8.2;" " Unit: Percents." " "," ",,"Computer Control of Building Wide Evironment(c)",,,"Computer Control of Processes or Major Energy-Using Equipment(d)",,,"Waste Heat Recovery",,,"Adjustable - Speed Motors",,,"Oxy - Fuel Firing" " "," " "NAICS"," " "Code(a)","Subsector and

  12. Alt Text Requirements for Web Images | Department of Energy

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

    Graphics & Images » Alt Text Requirements for Web Images Alt Text Requirements for Web Images Per Section 508 requirements, images on Office of Energy Efficiency and Renewable Energy (EERE) websites and applications must have alt text. Alt text describes what an image looks like in words, making it accessible to screen readers. Writing Alt Text Alt text is a written description of the items, events, and text in the image. Briefly summarize the image. Most alt text should look like this:

  13. U.S. Spent Nuclear Fuel Data as of December 31,2002 -Table 2

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

    6 Table 1 | Table 3 Table 2. Nuclear Power Plant Data as of December 31, 2002 Reactor Name State Reactor Type Reactor Vendor a Core Size (number of assemblies) Startup Date (year)b...

  14. Peetz Table Wind Energy Center (3Q07) | Open Energy Information

    Open Energy Info (EERE)

    Peetz Table Wind Energy Center (3Q07) Jump to: navigation, search Name Peetz Table Wind Energy Center (3Q07) Facility Peetz Table Wind Energy Center (3Q07) Sector Wind energy...

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

    SciTech Connect (OSTI)

    Finley, Cathy

    2014-04-30

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

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

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

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

    2015-06-23

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

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

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

    Applications | Department of Energy Forecast of Solid-State Lighting in General Illumination Applications Energy Savings Forecast of Solid-State Lighting in General Illumination Applications PDF icon energysavingsforecast14.pdf More Documents & Publications Energy Savings Potential of Solid-State Lighting in General Illumination Applications - Report LED ADOPTION REPORT Solid-State Lighting R&D

  19. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect (OSTI)

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

    2015-06-23

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

  20. EIA Energy Efficiency-Table 5c. Economic and Physical Indicators...

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

    Energy Efficiency > Manufacturing Trend Data, 1998, 2002, and 2006 > Table 5c Page Last Modified: May 2010 Table 5c. Economic and Physical Indicators for the Aluminum Industry...