National Library of Energy BETA

Sample records for forecasts energy consumption

  1. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

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

  2. Forecasting Hot Water Consumption in Residential Houses

    E-Print Network [OSTI]

    MacDonald, Mark

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

  3. Energy consumption and expenditure projections by population group on the basis of the annual energy outlook 1999 forecast

    SciTech Connect (OSTI)

    Poyer, D.A.; Balsley, J.H.

    2000-01-07

    This report presents an analysis of the relative impact of the base-case scenario used in Annual Energy Outlook 1999 on different population groups. Projections of energy consumption and expenditures, as well as energy expenditure as a share of income, from 1996 to 2020 are given. The projected consumption of electricty, natural gas, distillate fuel, and liquefied petroleum gas during this period is also reported for each population group. In addition, this report compares the findings of the Annual Energy Outlook 1999 report with the 1998 report. Changes in certain indicators and information affect energy use forecasts, and these effects are analyzed and discussed.

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

    E-Print Network [OSTI]

    MacDonald, Mark

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

  5. Energy consumption and expenditure projections by income quintile on the basis of the Annual Energy Outlook 1997 forecast

    SciTech Connect (OSTI)

    Poyer, D.A.; Allison, T.

    1998-03-01

    This report presents an analysis of the relative impacts of the base-case scenario used in the Annual Energy Outlook 1997, published by the US Department of Energy, Energy Information Administration, on income quintile groups. Projected energy consumption and expenditures, and projected energy expenditures as a share of income, for the period 1993 to 2015 are reported. Projected consumption of electricity, natural gas, distillate fuel, and liquefied petroleum gas over this period is also reported for each income group. 33 figs., 11 tabs.

  6. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

    Hwang, Kai

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

  8. Reduces electric energy consumption

    E-Print Network [OSTI]

    BENEFITS · Reduces electric energy consumption · Reduces peak electric demand · Reduces natural gas consumption · Reduces nonhazardous solid waste and wastewater generation · Potential annual savings products for the automotive industry, electrical equipment, and miscellaneous other uses nationwide. ALCOA

  9. Tiree Energy Pulse: Exploring Renewable Energy Forecasts on the Edge of the Grid

    E-Print Network [OSTI]

    MacDonald, Mark

    Tiree Energy Pulse: Exploring Renewable Energy Forecasts on the Edge of the Grid Will Simm1 , Maria energy consumption with supply, and together built a prototype renewable energy forecast display. A num local renewable energy was expected to be available, despite having no financial in- centive to do so

  10. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar2-0057-EA Jump to:ofEnia SpAFlex Fuels Energy JumpVyncke Jump to:Forecast

  11. Detrending Daily Natural Gas Consumption Series to Improve Short-Term Forecasts

    E-Print Network [OSTI]

    Povinelli, Richard J.

    Detrending Daily Natural Gas Consumption Series to Improve Short-Term Forecasts Ronald H. Brown1 that allows long-term natural gas demand signals to be used effect- ively to generate high quality short-term natural gas demand forecasting models. Short data sets in natural gas forecasting inadequately represent

  12. Energy Consumption Profile for Energy

    E-Print Network [OSTI]

    Langendoen, Koen

    ...................................................................................318 12.2.1 Motivations for Energy Harvesting...............................................319 12 the example of a "smart application'' assisted by a decision engine that transforms itself into an "energy317 Chapter 12 Energy Consumption Profile for Energy Harvested WSNs T. V. Prabhakar, R Venkatesha

  13. Short-Term Energy Outlook Model Documentation: Motor Gasoline Consumption Model

    Reports and Publications (EIA)

    2011-01-01

    The motor gasoline consumption module of the Short-Term Energy Outlook (STEO) model is designed to provide forecasts of total U.S. consumption of motor gasolien based on estimates of vehicle miles traveled and average vehicle fuel economy.

  14. Classification of Energy Consumption in Buildings with Outlier Detection

    E-Print Network [OSTI]

    Yao, Xin

    1 Classification of Energy Consumption in Buildings with Outlier Detection Xiaoli Li, Chris P is to enable a building management system to be used for forecasting and detection of abnormal energy use. First, an outlier detection method is proposed to identify abnormally high or low energy use in building

  15. Energy Information Administration - Commercial Energy Consumption...

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

    5A. Electricity Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings...

  16. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update (EIA)

    9A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 3 Total Electricity Consumption (billion kWh) Total Floorspace of...

  17. Energy Information Administration - Commercial Energy Consumption...

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

    2A. Electricity Consumption and Conditional Energy Intensity by Year Constructed for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings...

  18. Energy Information Administration - Commercial Energy Consumption...

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

    1A. Electricity Consumption and Conditional Energy Intensity by Building Size for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings...

  19. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update (EIA)

    8A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 2 Total Electricity Consumption (billion kWh) Total Floorspace of...

  20. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update (EIA)

    7A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 1 Total Electricity Consumption (billion kWh) Total Floorspace of...

  1. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update (EIA)

    0A. Electricity Consumption and Conditional Energy Intensity by Climate Zonea for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings...

  2. Energy Information Administration - Commercial Energy Consumption...

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

    Table C22. Electricity Consumption and Conditional Energy Intensity by Year Constructed for Non-Mall Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace...

  3. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update (EIA)

    A. Consumption and Gross Energy Intensity by Climate Zonea for All Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of Buildings (million square feet)...

  4. World energy consumption

    SciTech Connect (OSTI)

    NONE

    1995-12-01

    Historical and projected world energy consumption information is displayed. The information is presented by region and fuel type, and includes a world total. Measurements are in quadrillion Btu. Sources of the information contained in the table are: (1) history--Energy Information Administration (EIA), International Energy Annual 1992, DOE/EIA-0219(92); (2) projections--EIA, World Energy Projections System, 1994. Country amounts include an adjustment to account for electricity trade. Regions or country groups are shown as follows: (1) Organization for Economic Cooperation and Development (OECD), US (not including US territories), which are included in other (ECD), Canada, Japan, OECD Europe, United Kingdom, France, Germany, Italy, Netherlands, other Europe, and other OECD; (2) Eurasia--China, former Soviet Union, eastern Europe; (3) rest of world--Organization of Petroleum Exporting Countries (OPEC) and other countries not included in any other group. Fuel types include oil, natural gas, coal, nuclear, and other. Other includes hydroelectricity, geothermal, solar, biomass, wind, and other renewable sources.

  5. Manufacturing consumption of energy 1991

    SciTech Connect (OSTI)

    Not Available

    1994-12-01

    This report provides estimates on energy consumption in the manufacturing sector of the US economy. These estimates are based on data from the 1991 Manufacturing Energy Consumption Survey (MECS). This survey--administered by the Energy End Use and Integrated Statistics Division, Office of Energy Markets and End Use, Energy Information Administration (EIA)--is the most comprehensive source of national-level data on energy-related information for the manufacturing industries.

  6. TV Energy Consumption Trends and Energy-Efficiency Improvement Options

    E-Print Network [OSTI]

    Park, Won Young

    2011-01-01

    and Low Power Mode Energy Consumption”, Energy Efficiency inEnergy Consumption ..26 3.1.3. 3D TV Energy Consumption and Efficiency

  7. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

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

  8. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

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

  9. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

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

  10. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

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

  11. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

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

  12. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

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

  13. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

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

  14. Electricity Demand and Energy Consumption Management System

    E-Print Network [OSTI]

    Sarmiento, Juan Ojeda

    2008-01-01

    This project describes the electricity demand and energy consumption management system and its application to the Smelter Plant of Southern Peru. It is composted of an hourly demand-forecasting module and of a simulation component for a plant electrical system. The first module was done using dynamic neural networks, with backpropagation training algorithm; it is used to predict the electric power demanded every hour, with an error percentage below of 1%. This information allows management the peak demand before this happen, distributing the raise of electric load to other hours or improving those equipments that increase the demand. The simulation module is based in advanced estimation techniques, such as: parametric estimation, neural network modeling, statistic regression and previously developed models, which simulates the electric behavior of the smelter plant. These modules allow the proper planning because it allows knowing the behavior of the hourly demand and the consumption patterns of the plant, in...

  15. Residential Energy Consumption Survey Results: Total Energy Consumptio...

    Open Energy Info (EERE)

    Residential Energy Consumption Survey Results: Total Energy Consumption, Expenditures, and Intensities (2005) The Residential Energy Consumption Survey (RECS) is a national survey...

  16. Energy Consumption of Minimum Energy Coding in

    E-Print Network [OSTI]

    Johansson, Karl Henrik

    Energy Consumption of Minimum Energy Coding in CDMA Wireless Sensor Networks Benigno Zurita Ares://www.ee.kth.se/control Abstract. A theoretical framework is proposed for accurate perfor- mance analysis of minimum energy coding energy consumption is analyzed for two coding schemes proposed in the literature: Minimum Energy coding

  17. New York: Weatherizing Westbeth Reduces Energy Consumption |...

    Office of Environmental Management (EM)

    York: Weatherizing Westbeth Reduces Energy Consumption New York: Weatherizing Westbeth Reduces Energy Consumption August 21, 2013 - 12:00am Addthis The New York State Homes and...

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

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Univariate Modeling and Forecasting of Monthly Energy Demand Time Series Using Abductive and Neural networks, Neural networks, Modeling, Forecasting, Energy demand, Time series forecasting, Power system demand time series based only on data for six years to forecast the demand for the seventh year. Both

  19. Monitoring Energy Consumption of Smartphones

    E-Print Network [OSTI]

    Ding, Fangwei; Zhang, Wei; Zhao, Xuhai; Ma, Chengchuan

    2012-01-01

    With the rapid development of new and innovative applications for mobile devices like smartphones, advances in battery technology have not kept pace with rapidly growing energy demands. Thus energy consumption has become a more and more important issue of mobile devices. To meet the requirements of saving energy, it is critical to monitor and analyze the energy consumption of applications on smartphones. For this purpose, we develop a smart energy monitoring system called SEMO for smartphones using Android operating system. It can profile mobile applications with battery usage information, which is vital for both developers and users.

  20. Energy Intensity Indicators: Commercial Source Energy Consumption

    Broader source: Energy.gov [DOE]

    Figure C1 below reports as index numbers over the period 1970 through 2011: 1) commercial building floor space, 2) energy use based on source energy consumption, 3) energy intensity, and 4) the...

  1. Consumption

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

    . Electricity Consumption and Conditional Energy Intensity by Climate Zonea for Non-Mall Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,,,"Total Floorspace of...

  2. Consumption

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

    A. Electricity Consumption and Conditional Energy Intensity by Climate Zonea for All Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,,,"Total Floorspace of...

  3. Consumption

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

    A. Electricity Consumption and Conditional Energy Intensity by Building Size for All Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace of...

  4. Consumption

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

    3. Electricity Consumption and Conditional Energy Intensity, 1999" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace of Buildings Using Electricity (million square...

  5. Consumption

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

    A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 1" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace...

  6. Consumption

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

    . Electricity Consumption and Conditional Energy Intensity by Building Size for Non-Mall Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace of...

  7. Consumption

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

    . Electricity Consumption and Conditional Energy Intensity by Census Division for Non-Mall Buildings, 2003: Part 1" ,"Total Electricity Consumption (billion kWh)",,,"Total...

  8. Consumption

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

    . Electricity Consumption and Conditional Energy Intensity by Census Division for Non-Mall Buildings, 2003: Part 2" ,"Total Electricity Consumption (billion kWh)",,,"Total...

  9. Consumption

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

    9A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 3" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace...

  10. Consumption

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

    Electricity Consumption and Conditional Energy Intensity by Census Region, 1999" ,"Total Electricity Consumption (billion kWh)",,,,"Total Floorspace of Buildings Using Electricity...

  11. Consumption

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

    . Electricity Consumption and Conditional Energy Intensity by Census Region for Non-Mall Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,,"Total Floorspace of...

  12. Consumption

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

    A. Electricity Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,,"Total Floorspace of...

  13. Consumption

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

    . Electricity Consumption and Conditional Energy Intensity by Year Constructed for Non-Mall Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace of...

  14. Consumption

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

    4. Electricity Consumption and Conditional Energy Intensity by Year Constructed, 1999" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace of Buildings Using...

  15. Consumption

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

    A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 2" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace...

  16. Consumption

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

    A. Electricity Consumption and Conditional Energy Intensity by Year Constructed for All Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace of...

  17. Consumption

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

    . Electricity Consumption and Conditional Energy Intensity by Census Division for Non-Mall Buildings, 2003: Part 3" ,"Total Electricity Consumption (billion kWh)",,,"Total...

  18. Consumption

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

    5. Fuel Oil Consumption and Conditional Energy Intensity by Census Region for Non-Mall Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,"Total Floorspace of...

  19. Consumption

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

    3. Fuel Oil Consumption and Conditional Energy Intensity by Census Region, 1999" ,"Total Fuel Oil Consumption (million gallons)",,,,"Total Floorspace of Buildings Using Fuel Oil...

  20. Consumption

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

    A. Fuel Oil Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,"Total Floorspace of Buildings...

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

    E-Print Network [OSTI]

    Povinelli, Richard J.

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

  2. The Effects of External Temperature on the Energy Consumption of Household Refrigerator-Freezers and Freezers 

    E-Print Network [OSTI]

    Burgess, Tiffany

    2015-06-30

    to improve efficiency and reduce consumption, it is important to understand how a unit behaves outside the design conditions. The forecasted annual energy consumption as published on the EnergyGuide sticker is determined by testing the unit at a specified...

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

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

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

  4. Continuous Improvement Energy Projects Reduce Energy Consumption 

    E-Print Network [OSTI]

    Niemeyer, E.

    2014-01-01

    Projects Reduce Energy Consumption Eric Niemeyer, Operations Superintendent Drilling Specialties Company A division of Chevron Phillips Chemical Company LP ESL-IE-14-05-31 Proceedings of the Thrity-Sixth Industrial Energy Technology Conference New... of the paper “Continuous Improvement Energy Projects Reduce Energy Consumption” by Bruce Murray and Allison Myers ESL-IE-14-05-31 Proceedings of the Thrity-Sixth Industrial Energy Technology Conference New Orleans, LA. May 20-23, 2014 Conroe, TX Facility ESL...

  5. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

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

  6. Manufacturing consumption of energy 1994

    SciTech Connect (OSTI)

    1997-12-01

    This report provides estimates on energy consumption in the manufacturing sector of the U.S. economy based on data from the Manufacturing Energy Consumption Survey. The sample used in this report represented about 250,000 of the largest manufacturing establishments which account for approximately 98 percent of U.S. economic output from manufacturing, and an expected similar proportion of manufacturing energy use. The amount of energy use was collected for all operations of each establishment surveyed. Highlights of the report include profiles for the four major energy-consuming industries (petroleum refining, chemical, paper, and primary metal industries), and an analysis of the effects of changes in the natural gas and electricity markets on the manufacturing sector. Seven appendices are included to provide detailed background information. 10 figs., 51 tabs.

  7. Transportation Energy Consumption Surveys

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYearbyWithdrawalsHome6,672(MillionFeet)Product:Energy

  8. National Lighting Energy Consumption

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:Financing Tool Fits the BillDepartmentSites KDFNational Fuel Cell andEnergy NationalLighting

  9. Office Buildings - Energy Consumption

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYear Jan FebElements)Feet) Decade8

  10. Short-Term Energy Outlook Model Documentation: Other Petroleum Products Consumption Model

    Reports and Publications (EIA)

    2011-01-01

    The other petroleum product consumption module of the Short-Term Energy Outlook (STEO) model is designed to provide U.S. consumption forecasts for 6 petroleum product categories: asphalt and road oil, petrochemical feedstocks, petroleum coke, refinery still gas, unfinished oils, and other miscvellaneous products

  11. Energy Consumption ESPRIMO E7935 E80+

    E-Print Network [OSTI]

    Ott, Albrecht

    Computers is also taking significant effort to reduce the energy consumption in data centres by providingEnergy Consumption ESPRIMO E7935 E80+ White Paper Issue: September 2008 In order to strengthen all important energy information about their products. With the publication of energy consumption

  12. Commercial Buildings Energy Consumption and Expenditures 1992

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

    Distribution Category UC-950 Commercial Buildings Energy Consumption and Expenditures 1992 April 1995 Energy Information Adminstration Office of Energy Markets and End Use U.S....

  13. Energy Intensity Indicators: Residential Source Energy Consumption

    Broader source: Energy.gov [DOE]

    Figure R1 below reports as index numbers over the period 1970 through 2011: 1) the number of U.S. households, 2) the average size of those housing units, 3) residential source energy consumption, 4...

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

    SciTech Connect (OSTI)

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

    2015-01-01

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

  15. State energy data report 1992: Consumption estimates

    SciTech Connect (OSTI)

    Not Available

    1994-05-01

    This is a report of energy consumption by state for the years 1960 to 1992. The report contains summaries of energy consumption for the US and by state, consumption by source, comparisons to other energy use reports, consumption by energy use sector, and describes the estimation methodologies used in the preparation of the report. Some years are not listed specifically although they are included in the summary of data.

  16. TV Energy Consumption Trends and Energy-Efficiency Improvement Options

    E-Print Network [OSTI]

    Park, Won Young

    2011-01-01

    of LCD TVs to global energy consumption due to theoverall household or global energy consumption is uncertainFigure ES-3. Global TV Energy Consumption by Display Type in

  17. Modelling the impact of user behaviour on heat energy consumption

    E-Print Network [OSTI]

    Combe, Nicola Miss; Harrison, David Professor; Way, Celia Miss

    2011-01-01

    strategies impact on energy consumption in residentialBEHAVIOUR ON HEAT ENERGY CONSUMPTION Nicola Combe 1 ,2 ,nearly 60% of domestic energy consumption and 27% of total

  18. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    Solar Adoption and Energy Consumption in the ResidentialFall 2012 Solar Adoption and Energy Consumption in theAbstract Solar Adoption and Energy Consumption in the

  19. Energy consumption in thermomechanical pulping

    SciTech Connect (OSTI)

    Marton, R.; Tsujimoto, N.; Eskelinen, E.

    1981-08-01

    Various components of refining energy were determined experimentally and compared with those calculated on the basis of the dimensions of morphological elements of wood. The experimentally determined fiberization energy of spruce was 6 to 60 times larger than the calculated value and that of birch 3 to 15 times larger. The energy consumed in reducing the Canadian standard freeness of isolated fibers from 500 to 150 ml was found to be approximately 1/3 of the total fiber development energy for both spruce and birch TMP. Chip size affected the refining energy consumption; the total energy dropped by approximately 30% when chip size was reduced from 16 mm to 3 mm in the case of spruce and approximately 40% for birch. 6 refs.

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

    E-Print Network [OSTI]

    Heinemann, Detlev

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

  1. Electrical appliance energy consumption control methods and electrical energy consumption systems

    DOE Patents [OSTI]

    Donnelly, Matthew K. (Kennewick, WA); Chassin, David P. (Pasco, WA); Dagle, Jeffery E. (Richland, WA); Kintner-Meyer, Michael (Richland, WA); Winiarski, David W. (Kennewick, WA); Pratt, Robert G. (Kennewick, WA); Boberly-Bartis, Anne Marie (Alexandria, VA)

    2008-09-02

    Electrical appliance energy consumption control methods and electrical energy consumption systems are described. In one aspect, an electrical appliance energy consumption control method includes providing an electrical appliance coupled with a power distribution system, receiving electrical energy within the appliance from the power distribution system, consuming the received electrical energy using a plurality of loads of the appliance, monitoring electrical energy of the power distribution system, and adjusting an amount of consumption of the received electrical energy via one of the loads of the appliance from an initial level of consumption to an other level of consumption different than the initial level of consumption responsive to the monitoring.

  2. Electrical appliance energy consumption control methods and electrical energy consumption systems

    DOE Patents [OSTI]

    Donnelly, Matthew K. (Kennewick, WA); Chassin, David P. (Pasco, WA); Dagle, Jeffery E. (Richland, WA); Kintner-Meyer, Michael (Richland, WA); Winiarski, David W. (Kennewick, WA); Pratt, Robert G. (Kennewick, WA); Boberly-Bartis, Anne Marie (Alexandria, VA)

    2006-03-07

    Electrical appliance energy consumption control methods and electrical energy consumption systems are described. In one aspect, an electrical appliance energy consumption control method includes providing an electrical appliance coupled with a power distribution system, receiving electrical energy within the appliance from the power distribution system, consuming the received electrical energy using a plurality of loads of the appliance, monitoring electrical energy of the power distribution system, and adjusting an amount of consumption of the received electrical energy via one of the loads of the appliance from an initial level of consumption to an other level of consumption different than the initial level of consumption responsive to the monitoring.

  3. Consumption

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

    . Consumption and Gross Energy Intensity by Building Size for Sum of Major Fuels for Non-Mall Buildings, 2003" ,"Sum of Major Fuel Consumption (trillion Btu)",,,"Total Floorspace...

  4. Trends in Renewable Energy Consumption and Electricity

    Reports and Publications (EIA)

    2012-01-01

    Presents a summary of the nation’s renewable energy consumption in 2010 along with detailed historical data on renewable energy consumption by energy source and end-use sector. Data presented also includes renewable energy consumption for electricity generation and for non-electric use by energy source, and net summer capacity and net generation by energy source and state. The report covers the period from 2006 through 2010.

  5. Commercial Buildings Energy Consumption and Expenditures 1992

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

    Appendix A How the Survey Was Conducted Introduction The Commercial Buildings Energy Consumption Survey (CBECS) is conducted by the Energy Information Administration (EIA) on a...

  6. Trends in Commercial Buildings--Trends in Energy Consumption...

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

    2 Part 1. Energy Consumption Data Tables Total Energy Intensity Intensity by Energy Source Background: Site and Primary Energy Trends in Energy Consumption and Energy Sources Part...

  7. Household energy consumption and expenditures 1993

    SciTech Connect (OSTI)

    1995-10-05

    This presents information about household end-use consumption of energy and expenditures for that energy. These data were collected in the 1993 Residential Energy Consumption Survey; more than 7,000 households were surveyed for information on their housing units, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information represents all households nationwide (97 million). Key findings: National residential energy consumption was 10.0 quadrillion Btu in 1993, a 9% increase over 1990. Weather has a significant effect on energy consumption. Consumption of electricity for appliances is increasing. Houses that use electricity for space heating have lower overall energy expenditures than households that heat with other fuels. RECS collected data for the 4 most populous states: CA, FL, NY, TX.

  8. Modelling the impact of user behaviour on heat energy consumption

    E-Print Network [OSTI]

    Combe, Nicola Miss; Harrison, David Professor; Way, Celia Miss

    2011-01-01

    3. Actual heating and hot water energy consumption of theon-site energy consumption for heating and hot water. The

  9. Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center

    E-Print Network [OSTI]

    Washington at Seattle, University of

    Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at wind energy sites are becoming paramount. Regime-switching space-time (RST) models merge meteorological forecast regimes at the wind energy site and fits a conditional predictive model for each regime

  10. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    /Individuals Providing Comments California Natural Gas Vehicle Coalition/ Mike Eaves League of Women VotersCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY AND TRANSPORTATION DIVISION B. B. Blevins Executive Director DISCLAIMER This report was prepared by a California

  11. Monitoring Energy Consumption In Wireless Sensor Networks

    E-Print Network [OSTI]

    Turau, Volker

    Monitoring Energy Consumption In Wireless Sensor Networks Matthias Witt, Christoph Weyer to monitor the consump- tion of energy in wireless sensor networks based on video streams com- posed from energy consumption in both standby and active modes is the basis of wireless networks. Energy preserving

  12. Changes in Natural Gas Monthly Consumption Data Collection and the Short-Term Energy Outlook

    Reports and Publications (EIA)

    2010-01-01

    Beginning with the December 2010 issue of the Short-Term Energy Outlook (STEO), the Energy Information Administration (EIA) will present natural gas consumption forecasts for the residential and commercial sectors that are consistent with recent changes to the Form EIA-857 monthly natural gas survey.

  13. Commercial Buildings Energy Consumption and Expenditures 1992

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

    Appendix I Related EIA Publications on Energy Consumption For information about how to obtain these publi- cations, see the inside cover of this report. Please note that the...

  14. Commercial Buildings Energy Consumption and Expenditures 1992

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

    in this report were based on monthly billing records submitted by the buildings' energy suppliers. The section, "Annual Consumption and Expenditures" provide a detailed...

  15. ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; GREENHOUSES...

    Office of Scientific and Technical Information (OSTI)

    fuel-fired peak heating for geothermal greenhouses Rafferty, K. 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; GREENHOUSES; AUXILIARY HEATING; CAPITALIZED COST; OPERATING...

  16. Energy consumption in optical modulators for interconnects

    E-Print Network [OSTI]

    Miller, David A. B.

    Energy consumption in optical modulators for interconnects David A. B. Miller* Ginzton Laboratory@ee.stanford.edu Abstract: We analyze energy consumption in optical modulators operated in depletion and intended for low, even conceivably being more energy-efficient than an ideal loss-less modulator. ©2012 Optical Society

  17. Energy consumption metrics of MIT buildings

    E-Print Network [OSTI]

    Schmidt, Justin David

    2010-01-01

    With world energy demand on the rise and greenhouse gas levels breaking new records each year, lowering energy consumption and improving energy efficiency has become vital. MIT, in a mission to help improve the global ...

  18. State Energy Data Report, 1991: Consumption estimates

    SciTech Connect (OSTI)

    Not Available

    1993-05-01

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to the Government, policy makers, and the public; and (2) to provide the historical series necessary for EIA`s energy models.

  19. State energy data report 1993: Consumption estimates

    SciTech Connect (OSTI)

    1995-07-01

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public; and (2) to provide the historical series necessary for EIA`s energy models.

  20. Energy: a historical perspective and 21st century forecast

    SciTech Connect (OSTI)

    Salvador, Amos [University of Texas, Austin, TX (United States)

    2005-07-01

    Contents are: Preface; Chapter 1: introduction, brief history, and chosen approach; Chapter 2: human population and energy consumption: the future; Chapter 4: sources of energy (including a section on coal); Chapter 5: electricity: generation and consumption; and Chapter 6: energy consumption and probable energy sources during the 21st century.

  1. State energy data report 1994: Consumption estimates

    SciTech Connect (OSTI)

    1996-10-01

    This document provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), operated by EIA. SEDS provides State energy consumption estimates to members of Congress, Federal and State agencies, and the general public, and provides the historical series needed for EIA`s energy models. Division is made for each energy type and end use sector. Nuclear electric power is included.

  2. State energy data report 1996: Consumption estimates

    SciTech Connect (OSTI)

    1999-02-01

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the Combined State Energy Data System (CSEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining CSEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. CSEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public and (2) to provide the historical series necessary for EIA`s energy models. To the degree possible, energy consumption has been assigned to five sectors: residential, commercial, industrial, transportation, and electric utility sectors. Fuels covered are coal, natural gas, petroleum, nuclear electric power, hydroelectric power, biomass, and other, defined as electric power generated from geothermal, wind, photovoltaic, and solar thermal energy. 322 tabs.

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

    SciTech Connect (OSTI)

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

    2005-10-31

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

  4. Home, Habits, and Energy: Examining Domestic Interactions and Energy Consumption

    E-Print Network [OSTI]

    Paulos, Eric

    Home, Habits, and Energy: Examining Domestic Interactions and Energy Consumption James Pierce1 in the home are performed without conscious consideration of energy consumption but rather are unconscious. Put another way, energy consumption can be characterized as "the routine accomplishment of what people

  5. Residential Energy Consumption Survey: Quality Profile

    SciTech Connect (OSTI)

    1996-03-01

    The Residential Energy Consumption Survey (RECS) is a periodic national survey that provides timely information about energy consumption and expenditures of U.S. households and about energy-related characteristics of housing units. The survey was first conducted in 1978 as the National Interim Energy Consumption Survey (NIECS), and the 1979 survey was called the Household Screener Survey. From 1980 through 1982 RECS was conducted annually. The next RECS was fielded in 1984, and since then, the survey has been undertaken at 3-year intervals. The most recent RECS was conducted in 1993.

  6. Energy Information Administration - Commercial Energy Consumption...

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

    4A. Electricity Consumption and Expenditure Intensities for All Buildings, 2003 Electricity Consumption Electricity Expenditures per Building (thousand kWh) per Square Foot (kWh)...

  7. Energy Information Administration - Commercial Energy Consumption...

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

    Table C13. Total Electricity Consumption and Expenditures for Non-Mall Buildings, 2003 All Buildings* Using Electricity Electricity Consumption Electricity Expenditures Number of...

  8. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update (EIA)

    3A. Total Electricity Consumption and Expenditures for All Buildings, 2003 All Buildings Using Electricity Electricity Consumption Electricity Expenditures Number of Buildings...

  9. Estimates of US biomass energy consumption 1992

    SciTech Connect (OSTI)

    Not Available

    1994-05-06

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass-derived primary energy used by the US economy. It presents estimates of 1991 and 1992 consumption. The objective of this report is to provide updated estimates of biomass energy consumption for use by Congress, Federal and State agencies, biomass producers and end-use sectors, and the public at large.

  10. Research on Building Energy Consumption Situation in Shanghai 

    E-Print Network [OSTI]

    Yang, X.; Tan, H.

    2006-01-01

    This paper surveys the present situation of building energy consumption in Shanghai and points out the problems of insufficient energy consumption statistics based on the survey data. We analyze the relationships of energy consumption between...

  11. PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022

    E-Print Network [OSTI]

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

  12. Energy Information Administration - Transportation Energy Consumption by

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry NaturalPrices1Markets 9,WhyConsumption SurveyVehicles Energy

  13. State energy data report 1995 - consumption estimates

    SciTech Connect (OSTI)

    1997-12-01

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public, and (2) to provide the historical series necessary for EIA`s energy models.

  14. Optimizing Energy Consumption in Terahertz Band Nanonetworks

    E-Print Network [OSTI]

    Weigle, Michele

    1 Optimizing Energy Consumption in Terahertz Band Nanonetworks Shahram Mohrehkesh, IEEE Student the maximum utilization of harvested energy in perpetual wireless nanonetworks, where nanonodes communicate of energy. Compounding the problem, the arrival of energy is not constant, but follows a stochastic process

  15. Power to the Plug: An Introduction to Energy, Electricity, Consumption...

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

    to the Plug: An Introduction to Energy, Electricity, Consumption, and Efficiency Power to the Plug: An Introduction to Energy, Electricity, Consumption, and Efficiency Below is...

  16. ,"Total Fuel Oil Consumption (trillion Btu)",,,,,"Fuel Oil Energy...

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

    A. Fuel Oil Consumption (Btu) and Energy Intensities by End Use for All Buildings, 2003" ,"Total Fuel Oil Consumption (trillion Btu)",,,,,"Fuel Oil Energy Intensity (thousand Btu...

  17. GIS-based energy consumption mapping 

    E-Print Network [OSTI]

    Balta, Chrysi

    2014-11-27

    This project aims to provide a methodology to map energy consumption of the housing stock at a city level and visualise and evaluate different retrofitting scenarios. It is based on an engineering, bottom-up approach. It ...

  18. Solar Energy Market Forecast | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EIS ReportEurope GmbH JumpSlough HeatMccoyProject-Energy

  19. Energy for 500 Million Homes: Drivers and Outlook for Residential Energy Consumption in China

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    of Commercial Building Energy Consumption in China, 2008,The China Residential Energy Consumption Survey, Human andfor Residential Energy Consumption in China Nan Zhou,

  20. Smoothing the Energy Consumption: Peak Demand Reduction in Smart Grid

    E-Print Network [OSTI]

    Li, Xiang-Yang

    % of the nation's total electricity consumption. Unfortunately, due to inefficient energy consumption patternSmoothing the Energy Consumption: Peak Demand Reduction in Smart Grid Shaojie Tang , Qiuyuan Huang of Software, TNLIST, Tsinghua University Department of Electrical & Computer Engineering, University

  1. Empowering Developers to Estimate App Energy Consumption

    E-Print Network [OSTI]

    Shihada, Basem

    are not even aware of the amount of energy their app consumes un- der a typical usage pattern. While they couldEmpowering Developers to Estimate App Energy Consumption Radhika Mittal , Aman Kansal , Ranveer on mobile devices. However, it is difficult for app developers to mea- sure the energy used by their apps

  2. Energy Consumption of Die Casting Operations

    SciTech Connect (OSTI)

    Jerald Brevick; clark Mount-Campbell; Carroll Mobley

    2004-03-15

    Molten metal processing is inherently energy intensive and roughly 25% of the cost of die-cast products can be traced to some form of energy consumption [1]. The obvious major energy requirements are for melting and holding molten alloy in preparation for casting. The proper selection and maintenance of melting and holding equipment are clearly important factors in minimizing energy consumption in die-casting operations [2]. In addition to energy consumption, furnace selection also influences metal loss due to oxidation, metal quality, and maintenance requirements. Other important factors influencing energy consumption in a die-casting facility include geographic location, alloy(s) cast, starting form of alloy (solid or liquid), overall process flow, casting yield, scrap rate, cycle times, number of shifts per day, days of operation per month, type and size of die-casting form of alloy (solid or liquid), overall process flow, casting yield, scrap rate, cycle times, number of shifts per day, days of operation per month, type and size of die-casting machine, related equipment (robots, trim presses), and downstream processing (machining, plating, assembly, etc.). Each of these factors also may influence the casting quality and productivity of a die-casting enterprise. In a die-casting enterprise, decisions regarding these issues are made frequently and are based on a large number of factors. Therefore, it is not surprising that energy consumption can vary significantly from one die-casting enterprise to the next, and within a single enterprise as function of time.

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

    E-Print Network [OSTI]

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

    2000-01-01

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

  4. 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.

  5. Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems

    E-Print Network [OSTI]

    Shenoy, Prashant

    Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems Navin Sharma,gummeson,irwin,shenoy}@cs.umass.edu Abstract--To sustain perpetual operation, systems that harvest environmental energy must carefully regulate their usage to satisfy their demand. Regulating energy usage is challenging if a system's demands

  6. Leveraging Weather Forecasts in Renewable Energy Navin Sharmaa,

    E-Print Network [OSTI]

    Shenoy, Prashant

    Leveraging Weather Forecasts in Renewable Energy Systems Navin Sharmaa, , Jeremy Gummesonb , David, Binghamton, NY 13902 Abstract Systems that harvest environmental energy must carefully regulate their us- age to satisfy their demand. Regulating energy usage is challenging if a system's demands are not elastic, since

  7. Short-Term Solar Energy Forecasting Using Wireless Sensor Networks

    E-Print Network [OSTI]

    Cerpa, Alberto E.

    Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Stefan Achleitner, Tao Liu an advantage for output power prediction. Solar Energy Prediction System Our prediction model is based variability of more then 100 kW per minute. For practical usage of solar energy, predicting times of high

  8. Energy consumption series: Lighting in commercial buildings

    SciTech Connect (OSTI)

    Not Available

    1992-03-11

    Lighting represents a substantial fraction of commercial electricity consumption. A wide range of initiatives in the Department of Energy`s (DOE) National Energy Strategy have focused on commercial lighting as a potential source of energy conservation. This report provides a statistical profile of commercial lighting, to examine the potential for lighting energy conservation in commercial buildings. The principal conclusion from this analysis is that energy use for lighting could be reduced by as much as a factor of four using currently available technology. The analysis is based primarily on the Energy Information Administration`s (EIA) 1986 Commercial Buildings Energy Consumption Survey (CBECS). The more recent 1989 survey had less detail on lighting, for budget reasons. While changes have occurred in the commercial building stock since 1986, the relationships identified by this analysis are expected to remain generally valid. In addition, the analytic approach developed here can be applied to the data that will be collected in the 1992 CBECS.

  9. Implementation of a Corporate Energy Accounting and Forecasting Model 

    E-Print Network [OSTI]

    Kympton, H. W.; Bowman, B. M.

    1981-01-01

    pieces of equipment which are used as energy performance 'yardsticks'. Monthly reports permit equitable comparisons of plant energy consumption and isolation of those plants with the lowest efficiencies. The financial impact of increasing energy...

  10. Energy Information Administration - Commercial Energy Consumption...

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

    2003 Fuel Oil Consumption Fuel Oil Expenditures per Building (gallons) per Square Foot (gallons) per Building (thousand dollars) per Square Foot (dollars) per Gallon...

  11. Energy Information Administration - Commercial Energy Consumption...

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

    Gas Consumption Natural Gas Expenditures per Building (thousand cubic feet) per Square Foot (cubic feet) Distribution of Building-Level Intensities (cubic feetsquare foot) 25th...

  12. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update (EIA)

    Heat Consumption District Heat Expenditures per Building (million Btu) per Square Foot (thousand Btu) per Building (thousand dollars) per Square Foot (dollars) per Thousand...

  13. Energy Information Agency's 2003 Commercial Building Energy Consumption Survey Tables

    Broader source: Energy.gov [DOE]

    Energy use intensities in commercial buildings vary widely and depend on activity and climate, as shown in this data table, which was derived from the Energy Information Agency's 2003 Commercial Building Energy Consumption Survey.

  14. Energy Information Administration - Energy Efficiency, energy consumption

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear, ElectricRhode Island ElectricityYearand Tables1995savings

  15. Uncertainties in Energy Consumption Introduced by Building Operations and

    E-Print Network [OSTI]

    Uncertainties in Energy Consumption Introduced by Building Operations and Weather for a Medium-Size Office Building Liping Wang, Paul Mathew, Xiufeng Pang Environmental Energy Technologies Division between predicted and actual building energy consumption can be attributed to uncertainties introduced

  16. Energy Consumption of Personal Computing Including Portable

    E-Print Network [OSTI]

    Namboodiri, Vinod

    processing unit (CPU) processing power and capacity of mass storage devices doubles every 18 months. Such growth in both processing and storage capabilities fuels the production of ever more powerful portableEnergy Consumption of Personal Computing Including Portable Communication Devices Pavel Somavat1

  17. Energy Consumption Characteriation of Heterogeneous Servers School of Computer Science

    E-Print Network [OSTI]

    Qin, Xiao

    Energy Consumption Characteriation of Heterogeneous Servers Xiao Zhang School of Computer Science Machine between servers to save energy. An accurate energy consumption model is the basic of energy management. Most past studies show that energy consumption has linear relation with resource utilization. We

  18. Household Energy Consumption Segmentation Using Hourly Data

    SciTech Connect (OSTI)

    Kwac, J; Flora, J; Rajagopal, R

    2014-01-01

    The increasing US deployment of residential advanced metering infrastructure (AMI) has made hourly energy consumption data widely available. Using CA smart meter data, we investigate a household electricity segmentation methodology that uses an encoding system with a pre-processed load shape dictionary. Structured approaches using features derived from the encoded data drive five sample program and policy relevant energy lifestyle segmentation strategies. We also ensure that the methodologies developed scale to large data sets.

  19. Manufacturing Consumption of Energy 1994

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-03.82 4.235,382 6,358 (Million Cubic S ˆ Y M n i 1E

  20. On the Interplay of Parallelization, Program Performance, and Energy Consumption

    E-Print Network [OSTI]

    Scarano, Vittorio

    On the Interplay of Parallelization, Program Performance, and Energy Consumption Sangyeun Cho to either minimize the total energy consumption or minimize the energy-delay product. The impact of static through parallel execution of applications, suppressing the power and energy consumption remains an even

  1. Electrical energy consumption control apparatuses and electrical energy consumption control methods

    SciTech Connect (OSTI)

    Hammerstrom, Donald J.

    2012-09-04

    Electrical energy consumption control apparatuses and electrical energy consumption control methods are described. According to one aspect, an electrical energy consumption control apparatus includes processing circuitry configured to receive a signal which is indicative of current of electrical energy which is consumed by a plurality of loads at a site, to compare the signal which is indicative of current of electrical energy which is consumed by the plurality of loads at the site with a desired substantially sinusoidal waveform of current of electrical energy which is received at the site from an electrical power system, and to use the comparison to control an amount of the electrical energy which is consumed by at least one of the loads of the site.

  2. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    al. (2000). "Energy efficiency and consumption – the reboundinnovation, energy efficient design and the rebound effect."of an energy service, the greater the rebound effect (

  3. User-needs study for the 1992 Commercial Buildings Energy Consumption Survey. [Energy Consumption Series

    SciTech Connect (OSTI)

    Not Available

    1992-09-01

    The Commercial Buildings Energy Consumption Survey (CBECS) that is conducted by the Energy Information Administration (EIA) is the primary source of energy data for commercial buildings in the United States. The survey began in 1979 and has subsequently been conducted in 1983, 1986, and 1989. The next survey will cover energy consumption during the year 1992. The building characteristic data will be collected between August 1992 and early December 1992. Requests for energy consumption data are mailed to the energy suppliers in January 1993, with data due by March 1993. Before each survey is sent into the field, the data users' needs are thoroughly assessed. The purpose of this report is to document the findings of that user-needs assessment for the 1992 survey.

  4. CALIFORNIA ENERGY DEMAND 2014-2024 PRELIMINARY

    E-Print Network [OSTI]

    supervised data preparation. Steven Mac and Keith O'Brien prepared the historical energy consumption data. Nahid Movassagh forecasted consumption for the agriculture and water pumping CALIFORNIA ENERGY DEMAND 2014-2024 PRELIMINARY FORECAST Volume 1

  5. Impacts of Electric Vehicles on Primary Energy Consumption and Petroleum Displacement

    E-Print Network [OSTI]

    Wang, Quanlu; Delucchi, Mark A.

    1991-01-01

    on Primary Energy Consumption and Petroleum Displacementon Primary Energy Consumption and Petroleum Displacementprimary energy savings impacts and petroleum displacement

  6. Energy Consumption in Coded Queues for Wireless Information Exchange

    E-Print Network [OSTI]

    Boucherie, Richard J.

    Energy Consumption in Coded Queues for Wireless Information Exchange Jasper Goseling, Richard J customers. We use this relation to ob- tain bounds on the energy consumption in a wireless information. In this work we will analyze the energy consumption of coded wireless networks under the scenario that the ar

  7. Optimizing Communication Energy Consumption in Perpetual Wireless Nanosensor Networks

    E-Print Network [OSTI]

    Weigle, Michele

    Optimizing Communication Energy Consumption in Perpetual Wireless Nanosensor Networks Shahram}@cs.odu.edu Abstract--This paper investigates the effect of various param- eters of energy consumption. Finding the optimum combination of parameters to minimize energy consumption while satisfying the Qo

  8. Reducing the Energy Consumption of Mobile Applications Behind the Scenes

    E-Print Network [OSTI]

    Tilevich, Eli

    Reducing the Energy Consumption of Mobile Applications Behind the Scenes Young-Woo Kwon and Eli, an increasing number of perfective maintenance tasks are concerned with optimizing energy consumption. However, optimizing a mobile application to reduce its energy consumption is non-trivial due to the highly volatile

  9. Minimizing Energy Consumption in Body Sensor Networks via Convex Optimization

    E-Print Network [OSTI]

    Poovendran, Radha

    Minimizing Energy Consumption in Body Sensor Networks via Convex Optimization Sidharth Nabar energy consumption while limiting the latency in data transfer. In this paper, we focus on polling energy consumption and latency. We show that this problem can be posed as a geometric program, which

  10. Automated Analysis of Performance and Energy Consumption for Cloud Applications

    E-Print Network [OSTI]

    Schneider, Jean-Guy

    Automated Analysis of Performance and Energy Consumption for Cloud Applications Feifei Chen, John providers is thus to develop resource provisioning and management solutions at minimum energy consumption system performance and energy consumption patterns in complex cloud systems is imperative to achieve

  11. On the Energy Consumption and Performance of Systems Software

    E-Print Network [OSTI]

    Zadok, Erez

    On the Energy Consumption and Performance of Systems Software Appears in the proceedings of the 4th,grosu,psehgal,sas,stoller,ezk}@cs.stonybrook.edu ABSTRACT Models of energy consumption and performance are necessary to understand and identify system. This paper considers the energy consumption and performance of servers running a relatively simple file

  12. The Impact of Distributed Programming Abstractions on Application Energy Consumption

    E-Print Network [OSTI]

    Tilevich, Eli

    The Impact of Distributed Programming Abstractions on Application Energy Consumption Young-Woo Kwon of their energy consumption patterns. By varying the abstractions with the rest of the functionality fixed, we measure and analyze the impact of distributed programming abstractions on application energy consumption

  13. On the Energy Consumption and Performance of Systems Software

    E-Print Network [OSTI]

    Grosu, Radu

    On the Energy Consumption and Performance of Systems Software Zhichao Li, Radu Grosu, Priya Sehgal,grosu,psehgal,sas,stoller,ezk}@cs.stonybrook.edu Abstract Models of energy consumption and performance are necessary to understand and identify system consid- ers the energy consumption and performance of servers running a relatively simple file

  14. Influences of landscape and lifestyle on home energy consumption

    E-Print Network [OSTI]

    Langerhans, Brian

    Influences of landscape and lifestyle on home energy consumption Cara Nelson & Melissa R. Mc conservation and carbon dioxide emissions reduction. Urban residential energy consumption is a valuable place to increase considerably, therefore, understanding the drivers of home energy consumption should be a priority

  15. Large-scale Probabilistic Forecasting in Energy Systems using Sparse Gaussian Conditional Random Fields

    E-Print Network [OSTI]

    Kolter, J. Zico

    in a wide range of energy systems, including forecasting demand, renewable generation, and electricityLarge-scale Probabilistic Forecasting in Energy Systems using Sparse Gaussian Conditional Random demonstrated that in the context of electrical demand and wind power, probabilistic forecasts can offer

  16. Current Status and Future Scenarios of Residential Building Energy Consumption in China

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    accounting for 79% of non-biomass energy consumption inreliance on biomass for rural energy consumption shows thereliance on biomass for rural energy consumption shows the

  17. Window-Related Energy Consumption in the US Residential and Commercial Building Stock

    E-Print Network [OSTI]

    Apte, Joshua; Arasteh, Dariush

    2008-01-01

    2001). "Residential Energy Consumption Survey." 2006, fromCommercial Building Energy Consumption Survey." from http://Scale window-related energy consumption to account for new

  18. The Impact of Residential Density on Vehicle Usage and Energy Consumption

    E-Print Network [OSTI]

    Golob, Thomas F.; Brownstone, David

    2005-01-01

    Vehicle Usage and Energy Consumption Table 2 Housing Unitsresidential vehicular energy consumption is graphed as aon Vehicle Usage and Energy Consumption with vehicles, but

  19. Energy Consumption, Efficiency, Conservation, and Greenhouse Gas Mitigation in Japan's Building Sector

    E-Print Network [OSTI]

    2006-01-01

    comparison o f energy consumption i n housing (1998) (Trends i n household energy consumption (Jyukankyo Research4) Average (N=2976) Energy consumption [GJ / household-year

  20. ResPoNSe: modeling the wide variability of residential energy consumption.

    E-Print Network [OSTI]

    Peffer, Therese; Burke, William; Auslander, David

    2010-01-01

    affect appliance energy consumption. For example, differentStates, 2005 Residential Energy Consumption Survey: HousingModeling of End-Use Energy Consumption in the Residential

  1. Energy Consumption Scheduling in Smart Grid: A Non-Cooperative Game Approach

    E-Print Network [OSTI]

    Ma, Kai; Hu, Guoqiang; Spanos, Costas J

    2014-01-01

    on Game- Theoretic Energy Consumption Scheduling for theIn this paper, energy consumption scheduling based on non-Energy Consumption Scheduling in Smart Grid: A Non-

  2. One of These Homes is Not Like the Other: Residential Energy Consumption Variability

    E-Print Network [OSTI]

    Kelsven, Phillip

    2013-01-01

    the total annual energy consumption. The behavior patternsin total residential energy consumption per home, even whenthe variability in energy consumption can vary by factors of

  3. Current Status and Future Scenarios of Residential Building Energy Consumption in China

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    The China Residential Energy Consumption Survey, Human andof Commercial Building Energy Consumption in China, 2008,and Policy of Uniti Energy Consumption (kWh/yr) Ordinary

  4. The Reality and Future Scenarios of Commercial Building Energy Consumption in China

    E-Print Network [OSTI]

    Zhou, Nan

    2008-01-01

    to slow the growth of energy consumption in buildings. Thisimprovement on energy consumption in commercial buildings inCommercial Building Energy Consumption in China The service

  5. Energy Consumption Scheduling in Smart Grid:A Non-Cooperative Game Approach

    E-Print Network [OSTI]

    Kai, Ma; Guoqiang, Hu; Spanos, Costas

    2013-01-01

    on Game- Theoretic Energy Consumption Scheduling for theIn this paper, energy consumption scheduling based on non-Energy Consumption Scheduling in Smart Grid: A Non-

  6. Energy Consumption Scheduling in Smart Grid: A Non-Cooperative Game Approach

    E-Print Network [OSTI]

    Kai, Ma; Guoqiang, Hu; Spanos, Costas

    2013-01-01

    on Game- Theoretic Energy Consumption Scheduling for theIn this paper, energy consumption scheduling based on non-Energy Consumption Scheduling in Smart Grid: A Non-

  7. Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01

    Estimating Total Energy Consumption and Emissions of China’sof China’s total energy consumption mix. However, accuratelyof China’s total energy consumption, while others estimate

  8. Window-Related Energy Consumption in the US Residential and Commercial Building Stock

    E-Print Network [OSTI]

    Apte, Joshua; Arasteh, Dariush

    2008-01-01

    Loads SHGC Window Solar Energy Consumption Cond InfiltrationLoads SHGC Window Solar Energy Consumption Cond InfiltrationLoads SHGC Window Solar Energy Consumption Cond Infiltration

  9. Energy for 500 Million Homes: Drivers and Outlook for Residential Energy Consumption in China

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    accounting for 79% of non-biomass energy consumption in2000 and 2020. Biomass, the leading energy source in thehigh reliance on biomass for rural energy consumption as

  10. User-needs study for the 1993 residential energy consumption survey

    SciTech Connect (OSTI)

    Not Available

    1993-09-24

    During 1992, the Energy Information Administration (EIA) conducted a user-needs study for the 1993 Residential Energy Consumption Survey (RECS). Every 3 years, the RECS collects information on energy consumption and expenditures for various classes of households and residential buildings. The RECS is the only source of such information within EIA, and one of only a few sources of such information anywhere. EIA sent letters to more than 750 persons, received responses from 56, and held 15 meetings with users. Written responses were also solicited by notices published in the April 14, 1992 Federal Register and in several energy-related publications. To ensure that the 1993 RECS meets current information needs, EIA made a specific effort to get input from policy makers and persons needing data for forecasting efforts. These particular needs relate mainly to development of the National Energy Modeling System and new energy legislation being considered at the time of the user needs survey.

  11. 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.

  12. 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.

  13. Energy Information Administration - Commercial Energy Consumption Survey-

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun2003 Detailed Tables 0. Consumption and

  14. Energy Information Administration - Commercial Energy Consumption Survey-

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun2003 Detailed Tables 0. Consumption and2003

  15. Energy Information Administration - Commercial Energy Consumption Survey-

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun2003 Detailed Tables 0. Consumption

  16. Energy Information Administration - Commercial Energy Consumption Survey-

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun2003 Detailed Tables 0. Consumption2003

  17. Energy Information Administration - Commercial Energy Consumption Survey-

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun2003 Detailed Tables 0. Consumption20032003

  18. Energy Information Administration (EIA)- Manufacturing Energy Consumption

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry NaturalPrices1Markets 9,WhyConsumption Survey (CBECS)aboutSurvey

  19. Energy Information Administration (EIA)- Manufacturing Energy Consumption

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry NaturalPrices1Markets 9,WhyConsumption Survey

  20. Energy Preview: Residential Transportation Energy Consumption Survey,

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry NaturalPrices1Markets 9,WhyConsumption6 1 April 2006January5t 7

  1. Trends in Commercial Buildings--Trends in Energy Consumption...

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

    the energy consumed (elsewhere) to generate and transmit the electricity supplied to the building (see Site and Primary Energy for additional information). The primary consumption...

  2. 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....

  3. Fossil Fuel-Generated Energy Consumption Reduction for New Federal...

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

    Buildings Fossil Fuel-Generated Energy Consumption Reduction for New Federal Buildings and Major Renovations of Federal Buildings Document details Fossil Fuel-Generated Energy...

  4. Power to the Plug: An Introduction to Energy, Electricity, Consumption...

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

    Grades: All Topics: Biomass, Wind Energy, Hydropower, Solar, Geothermal Owner: The NEED Project Power to the Plug: An Introduction to Energy, Electricity, Consumption, and...

  5. The Analysis and Assessment on Heating Energy Consumption of SAT 

    E-Print Network [OSTI]

    Zhang, J.

    2006-01-01

    The article introduced the fuel-energy consumption and outdoor temperatures of three heating terms from year 1999 to 2002 of SAT's fuel-boiler heating system. It demonstrated the relationship between the consumption and the temperatures by using...

  6. China's Top-1000 Energy-Consuming Enterprises Program: Reducing Energy Consumption of the 1000 Largest Industrial Enterprises in China

    E-Print Network [OSTI]

    Price, Lynn

    2008-01-01

    Monitoring of Direct Energy Consumption in Long-Term2007. “Constraining Energy Consumption of China’s LargestProgram: Reducing Energy Consumption of the 1000 Largest

  7. Wind Forecasting Improvement Project | Department of Energy

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LIST OFAMERICA'S FUTURE. regulatorsEnergyDepartmentEnergyWideWind

  8. Energy Information Administration - Commercial Energy Consumption...

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

    Using Natural Gas (million square feet) Natural Gas Energy Intensity (cubic feetsquare foot) West South Central Moun- tain Pacific West South Central Moun- tain Pacific West...

  9. Energy Information Administration - Commercial Energy Consumption...

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

    Buildings (million square feet) Energy Intensity for Sum of Major Fuels (thousand Btu square foot) New England Middle Atlantic East North Central New England Middle Atlantic East...

  10. Energy Information Administration - Commercial Energy Consumption...

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

    Buildings (million square feet) Energy Intensity for Sum of Major Fuels (thousand Btu square foot) West North Central South Atlantic East South Central West North Central South...

  11. Energy Information Administration - Commercial Energy Consumption...

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

    Using Natural Gas (million square feet) Natural Gas Energy Intensity (cubic feetsquare foot) New England Middle Atlantic East North Central New England Middle Atlantic East...

  12. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update (EIA)

    Buildings (million square feet) Energy Intensity for Sum of Major Fuels (thousand Btu square foot) West South Central Moun- tain Pacific West South Central Moun- tain Pacific West...

  13. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update (EIA)

    Using Natural Gas (million square feet) Natural Gas Energy Intensity (cubic feetsquare foot) North- east Mid- west South West North- east Mid- west South West North- east...

  14. Energy Information Administration - Commercial Energy Consumption...

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

    Using Natural Gas (million square feet) Natural Gas Energy Intensity (cubic feetsquare foot) West North Central South Atlantic East South Central West North Central South...

  15. Energy Information Administration - Commercial Energy Consumption...

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

    Buildings (million square feet) Energy Intensity for Sum of Major Fuels (thousand Btusquare foot) 1959 or Before 1960 to 1989 1990 to 2003 1959 or Before 1960 to 1989 1990 to...

  16. Energy Information Administration - Commercial Energy Consumption...

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

    Buildings (million square feet) Energy Intensity for Sum of Major Fuels (thousand Btu square foot) 1,001 to 10,000 Square Feet 10,001 to 100,000 Square Feet Over 100,000 Square...

  17. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update (EIA)

    Buildings (million square feet) Energy Intensity for Sum of Major Fuels (thousand Btu square foot) North- east Mid- west South West North- east Mid- west South West North- east...

  18. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update (EIA)

    Buildings (million square feet) Energy Intensity for Sum of Major Fuels (thousand Btu square foot) Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 Zone 1...

  19. Energy Information Administration - Commercial Energy Consumption...

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

    Using Natural Gas (million square feet) Natural Gas Energy Intensity (cubic feetsquare foot) Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 Zone 1...

  20. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update (EIA)

    Using Natural Gas (million square feet) Natural Gas Energy Intensity (cubic feetsquare foot) 1959 or Before 1960 to 1989 1990 to 2003 1959 or Before 1960 to 1989 1990 to...

  1. Energy Information Administration - Commercial Energy Consumption...

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

    104 306 3,611 Fuel Oil ... 5 1,864 403 179 1,993 District Heat ... 67 5,576 83 636 7,279 Energy End Uses...

  2. Energy Intensity Indicators: Transportation Energy Consumption

    Broader source: Energy.gov [DOE]

    This section contains an overview of the aggregate transportation sector, combining both passenger and freight segments of this sector. The specific energy intensity indicators for passenger and freight can be obtained from the links, passenger transportation, or freight transportation. For further detail within the transportation sector, download the appropriate Trend Data worksheet containing detailed data and graphics for specific transportation modes.

  3. Long-term energy consumptions of urban transportation: A prospective...

    Open Energy Info (EERE)

    can significantly curb the trajectories of energy consumption and the ensuing carbon dioxide emissions, if and only if they are implemented in the framework of appropriate urban...

  4. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    expenditure on energy. PV adoption differs conceptually fromeffect around residential PV adoption, and if so what arein consumption changes after PV adoption. Figure 5.5 shows

  5. Fossil Fuel-Generated Energy Consumption Reduction for New Federal...

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

    Buildings OIRA Comparison Document Fossil Fuel-Generated Energy Consumption Reduction for New Federal Buildings and Major Renovations of Federal Buildings OIRA Comparison Document...

  6. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    Electric Solar Energy Industries Association Self Generationsolar-electric generation systems and its impacts on energyenergy consumption changes with the installation of a solar electric generation

  7. Modelling the impact of user behaviour on heat energy consumption

    E-Print Network [OSTI]

    Combe, Nicola Miss; Harrison, David Professor; Way, Celia Miss

    2011-01-01

    world data from buildings, observational data from users and energyworld data indicates that the houses heated during the night had higher annual heat energy consumption. The data

  8. Impact of Extended Daylight Saving Time on National Energy Consumption...

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

    Report to Congress Impact of Extended Daylight Saving Time on National Energy Consumption, Report to Congress This report presents the detailed results, data, and analytical...

  9. Impact of Extended Daylight Saving Time on National Energy Consumption...

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

    Technical Documentation Impact of Extended Daylight Saving Time on National Energy Consumption, Technical Documentation This report presents the detailed results, data, and...

  10. New Water Booster Pump System Reduces Energy Consumption by 80...

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

    BENEFITS A Motor Challeng NEW WATER BOOSTER PUMP SYSTEM REDUCES ENERGY CONSUMPTION BY 80 PERCENT AND INCREASES RELIABILITY Summary Due to major renovations at their Pontiac...

  11. Statistical Mechanics of Money, Income, Debt, and Energy Consumption

    E-Print Network [OSTI]

    Lathrop, Daniel P.

    Statistical Mechanics of Money, Income, Debt, and Energy Consumption Physics Colloquium Presented in financial markets. Globally, data analysis of energy consumption per capita around the world shows@american.edu Similarly to the probability distribution of energy in physics, the probability distribution of money among

  12. Elective Participation in Ad Hoc Networks Based on Energy Consumption

    E-Print Network [OSTI]

    Deng, Jing

    Elective Participation in Ad Hoc Networks Based on Energy Consumption Marc R. Pearlman , Jing Deng of determining the op- timal transmission radius for minimal interference and energy consumption is considered be significant. There- fore, in order to more aggressively conserve energy, one must Currently with the GE Global

  13. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    and energy efficiency policies California Solar Initiative (CSI) data,solar installation and energy consumption, through the analysis of pre- and post-installation consumption datadata regarding 5,243 residential solar system installations located in SDG&E service territory, the energy

  14. Energy for 500 Million Homes: Drivers and Outlook for Residential Energy Consumption in China

    SciTech Connect (OSTI)

    Zhou, Nan; McNeil, Michael A.; Levine, Mark

    2009-06-01

    China's rapid economic expansion has propelled it to the rank of the largest energy consuming nation in the world, with energy demand growth continuing at a pace commensurate with its economic growth. The urban population is expected to grow by 20 million every year, accompanied by construction of 2 billion square meters of buildings every year through 2020. Thus residential energy use is very likely to continue its very rapid growth. Understanding the underlying drivers of this growth helps to identify the key areas to analyze energy efficiency potential, appropriate policies to reduce energy use, as well as to understand future energy in the building sector. This paper provides a detailed, bottom-up analysis of residential building energy consumption in China using data from a wide variety of sources and a modelling effort that relies on a very detailed characterization of China's energy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecast the future outlook for the critical period extending to 2020, based on assumptions of likely patterns of economic activity, availability of energy services, technology improvement and energy intensities. From this analysis, we can conclude that Chinese residential energy consumption will more than double by 2020, from 6.6 EJ in 2000 to 15.9 EJ in 2020. This increase will be driven primarily by urbanization, in combination with increases in living standards. In the urban and higher income Chinese households of the future, most major appliances will be common, and heated and cooled areas will grow on average. These shifts will offset the relatively modest efficiency gains expected according to current government plans and policies already in place. Therefore, levelling and reduction of growth in residential energy demand in China will require a new set of more aggressive efficiency policies.

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

    E-Print Network [OSTI]

    Genton, Marc G.

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

  16. Improving Energy Use Forecast for Campus Micro-grids using Indirect Indicators Department of Computer Science

    E-Print Network [OSTI]

    Hwang, Kai

    peak demand periods using pricing incentives. Reliable building energy forecast models can help predictImproving Energy Use Forecast for Campus Micro-grids using Indirect Indicators Saima Aman prasanna@usc.edu Abstract--The rising global demand for energy is best addressed by adopting and promoting

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

    E-Print Network [OSTI]

    Islam, M. Saif

    is familiar with solar energy issues, we hope that you will take a few moments to answer this short survey on your needs for information on solar energy resources and forecasting. This survey is conducted with the California Solar Energy Collaborative (CSEC) and the California Solar Initiative (CSI) our objective

  18. Fitting and forecasting non-linear coupled dark energy

    E-Print Network [OSTI]

    Casas, Santiago; Baldi, Marco; Pettorino, Valeria; Vollmer, Adrian

    2015-01-01

    We consider cosmological models in which dark matter feels a fifth force mediated by the dark energy scalar field, also known as coupled dark energy. Our interest resides in estimating forecasts for future surveys like Euclid when we take into account non-linear effects, relying on new fitting functions that reproduce the non-linear matter power spectrum obtained from N-body simulations. We obtain fitting functions for models in which the dark matter-dark energy coupling is constant. Their validity is demonstrated for all available simulations in the redshift range $z=0-1.6$ and wave modes below $k=10 \\text{h/Mpc}$. These fitting formulas can be used to test the predictions of the model in the non-linear regime without the need for additional computing-intensive N-body simulations. We then use these fitting functions to perform forecasts on the constraining power that future galaxy-redshift surveys like Euclid will have on the coupling parameter, using the Fisher matrix method for galaxy clustering (GC) and w...

  19. DOE/EIA-0321/HRIf Residential Energy Consumption Survey. Consumption

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry NaturalPrices1 Table272/S The National Interim Energy/HRIf

  20. Fact #792: August 12, 2013 Energy Consumption by Sector and Energy...

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

    2: August 12, 2013 Energy Consumption by Sector and Energy Source, 1982 and 2012 Fact 792: August 12, 2013 Energy Consumption by Sector and Energy Source, 1982 and 2012 In the...

  1. Commercial Buildings Energy Consumption and Expenditures 1995...

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

    fuel oil, and district heat consumption and expenditures for commercial buildings by building characteristics. Previous Page Arrow Separater Bar File Last Modified: January 29,...

  2. Energy consumption of personal computer workstations

    SciTech Connect (OSTI)

    Szydlowski, R.F.; Chvala, W.D. Jr.

    1994-02-01

    The explosive growth of the information age has had a profound effect on the appearance of today`s office. Although the telephone still remains an important part of the information exchange and processing system within an office, other electronic devices are now considered required equipment within this environment. This office automation equipment includes facsimile machines, photocopiers, personal computers, printers, modems, and other peripherals. A recent estimate of the installed base indicated that 42 million personal computers and 7.3 million printers are in place, consuming 18.2 billion kWh/yr-and this installed base is growing (Luhn 1992). From a productivity standpoint, it can be argued that this equipment greatly improves the efficiency of those working in the office. But of primary concern to energy system designers, building managers, and electric utilities is the fact that this equipment requires electric energy. Although the impact of each incremental piece of equipment is small, installation of thousands of devices per building has resulted in office automation equipment becoming the major contributor to electric consumption and demand growth in commercial buildings. Personal computers and associated equipment are the dominant part of office automation equipment. In some cases, this electric demand growth has caused office buildings electric and cooling systems to overload.

  3. Tuning Fuzzy Logic Controllers for Energy Efficiency Consumption in Buildings

    E-Print Network [OSTI]

    Casillas Barranquero, Jorge

    Tuning Fuzzy Logic Controllers for Energy Efficiency Consumption in Buildings R. Alcal´a DECSAI- tion in buildings represents about 40% of to- tal energy consumption and more than a half controllers, tuning techniques, multiobjective optimisation, en- ergy efficiency, buildings, BEMS, HVAC sys

  4. Energy Consumption and Air Pollutant Emissions Barnard College

    E-Print Network [OSTI]

    1 Energy Consumption and Air Pollutant Emissions Barnard College 2005 - 2010 *Total campus square(MBtu) based on electricity, light fuel oil, and natural gas. Barnard's CO2 Emissions 2005 to 2010 (lbs/ft2/ft2 ) 0 20 40 60 80 100 120 140 2005 2006 2007 2008 2009 2010 #12;2 Energy Consumption and Air

  5. TV Energy Consumption Trends and Energy-Efficiency Improvement Options

    E-Print Network [OSTI]

    Park, Won Young

    2011-01-01

    technology. Power consumption of self-emissive displays suchtechnology. Power consumption of self-emissive displays suchof PDP Power Consumption PDPs are self-emissive displays

  6. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    renewable energy technologies, solar photovoltaic (PV) technologies hold significant potentialenergy consumption: Potential savings and environmental impact." Renewable andpotential new value stream from NEM solar is monetization of the renewable energy

  7. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    and future energy consumption: Potential savings and environmental impact." Renewable andrenewable energy installation in practice. This dissertation will provide insight and make recommendations for program design principles and future

  8. Estimates of U.S. Biomass Energy Consumption 1992

    Reports and Publications (EIA)

    1994-01-01

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass derived primary energy used by the U.S. economy. It presents estimates of 1991 and 1992 consumption.

  9. Development of Energy Consumption Database Management System of Existing Large Public Buildings 

    E-Print Network [OSTI]

    Li, Y.; Zhang, J.; Sun, D.

    2006-01-01

    The statistic data of energy consumption are the base of analyzing energy consumption. The scientific management method of energy consumption data and the development of database management system plays an important role in building energy...

  10. The Impact of Residential Density on Vehicle Usage and Energy Consumption

    E-Print Network [OSTI]

    Golob, Thomas F.; Brownstone, David

    2005-01-01

    residential transportation energy usage is vital for theDensity on Vehicle Usage and Energy Consumption Table 2Density on Vehicle Usage and Energy Consumption with

  11. One of These Homes is Not Like the Other: Residential Energy Consumption Variability

    E-Print Network [OSTI]

    Kelsven, Phillip

    2013-01-01

    ABSTRACT Households consume energy in many different waysvariations in energy consumption consume considerably morevariations in energy consumption tend to consume a lot more

  12. Energy consumption series: Development of the 1991 Manufacturing Energy Consumption Survey

    SciTech Connect (OSTI)

    Not Available

    1992-05-18

    The implementation and results of the proceedings concerning the Energy Information Administration assessment of the Manufacturing Energy Consumption Survey (MECS) are documented in this report. The text and Appendices C, D, and E summarize the background of the MECS data system, the events that led to the MECS redesign, the major issues address during the review process, and the eventual 1991 MECS design that resulted. For many readers, the most useful part of the report may be Appendices A and B, which contain overall summaries of the users' groups and the industrial roundtables. These appendices capture the rationale for additional data needs as provided by the users. Also, they are a rich source of information on how manufacturers deal with energy use day-to-day, how they have addressed the need for energy efficiency improvement in the past, and the opportunities and problems associated with future efforts to improve efficiency. (VC)

  13. Energy consumption series: Development of the 1991 Manufacturing Energy Consumption Survey

    SciTech Connect (OSTI)

    Not Available

    1992-05-18

    The implementation and results of the proceedings concerning the Energy Information Administration assessment of the Manufacturing Energy Consumption Survey (MECS) are documented in this report. The text and Appendices C, D, and E summarize the background of the MECS data system, the events that led to the MECS redesign, the major issues address during the review process, and the eventual 1991 MECS design that resulted. For many readers, the most useful part of the report may be Appendices A and B, which contain overall summaries of the users` groups and the industrial roundtables. These appendices capture the rationale for additional data needs as provided by the users. Also, they are a rich source of information on how manufacturers deal with energy use day-to-day, how they have addressed the need for energy efficiency improvement in the past, and the opportunities and problems associated with future efforts to improve efficiency. (VC)

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

    Broader source: Energy.gov [DOE]

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

  15. Input Substitution and Business Energy Consumption: Evidence from ABS Energy Survey Data

    E-Print Network [OSTI]

    1 Input Substitution and Business Energy Consumption: Evidence from ABS Energy Survey Data Kay Cao applies the system of equations approach to energy consumption modelling using the ABS 2008-09 Energy of equations, energy consumption modelling, elasticity of substitution JEL codes: C51, D24 * Please do

  16. Study of Air Infiltration Energy Consumption 

    E-Print Network [OSTI]

    Liu, Mingsheng

    1992-01-01

    consumption, showed that results from earlier steady-state measurements can be approximately applied to dynamic conditions when solar radiation is not present. However, this study has shown for the first time that IHEE is strongly dependent on air flow...

  17. China's Industrial Energy Consumption Trends and Impacts of the Top-1000 Enterprises Energy-Saving Program and the Ten Key Energy-Saving Projects

    E-Print Network [OSTI]

    Ke, Jing

    2014-01-01

    Choices, and Energy Consumption. Praeger Publishers,The decomposition effect of energy consumption in China'sThe challenge of reducing energy consumption of the Top-1000

  18. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

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

  19. Energy Consumption Scheduling in Smart Grid: A Non-Cooperative Game Approach

    E-Print Network [OSTI]

    Kai, Ma; Guoqiang, Hu; Spanos, Costas

    2013-01-01

    is cast into a non- cooperative energy consumption game,prove that the non-cooperative energy consumption game has aby introducing a non-cooperative energy consumption game in

  20. Energy Consumption Scheduling in Smart Grid: A Non-Cooperative Game Approach

    E-Print Network [OSTI]

    Ma, Kai; Hu, Guoqiang; Spanos, Costas J

    2014-01-01

    is cast into a non- cooperative energy consumption game,prove that the non-cooperative energy consumption game has aby introducing a non-cooperative energy consumption game in

  1. Energy Consumption Scheduling in Smart Grid:A Non-Cooperative Game Approach

    E-Print Network [OSTI]

    Kai, Ma; Guoqiang, Hu; Spanos, Costas

    2013-01-01

    is cast into a non- cooperative energy consumption game,prove that the non-cooperative energy consumption game has aby introducing a non-cooperative energy consumption game in

  2. The Impact of Residential Density on Vehicle Usage and Energy Consumption

    E-Print Network [OSTI]

    Golob, Thomas F; Brownstone, David

    2005-01-01

    on Vehicle Usage and Energy Consumption References Bento,Vehicle Usage and Energy Consumption UCI-ITS-WP-05-1 Thomason Vehicle Usage and Energy Consumption Thomas F. Golob

  3. Uncertainties in Energy Consumption Introduced by Building Operations and Weather for a Medium-Size Office Building

    E-Print Network [OSTI]

    Wang, Liping

    2014-01-01

    Uncertainties in Energy Consumption Introduced by Buildingand actual building energy consumption can be attributed touncertainties in energy consumption due to actual weather

  4. Monitoring and optimization of energy consumption of base transceiver stations

    E-Print Network [OSTI]

    Spagnuolo, Antonio; Vetromile, Carmela; Formosi, Roberto; Lubritto, Carmine

    2015-01-01

    The growth and development of the mobile phone network has led to an increased demand for energy by the telecommunications sector, with a noticeable impact on the environment. Monitoring of energy consumption is a great tool for understanding how to better manage this consumption and find the best strategy to adopt in order to maximize reduction of unnecessary usage of electricity. This paper reports on a monitoring campaign performed on six Base Transceiver Stations (BSs) located central Italy, with different technology, typology and technical characteristics. The study focuses on monitoring energy consumption and environmental parameters (temperature, noise, and global radiation), linking energy consumption with the load of telephone traffic and with the air conditioning functions used to cool the transmission equipment. Moreover, using experimental data collected, it is shown, with a Monte Carlo simulation based on power saving features, how the BS monitored could save energy.

  5. Modeling overall energy consumption in Wireless Sensor Networks

    E-Print Network [OSTI]

    Kamyabpour, Najmeh

    2011-01-01

    Minimizing the energy consumption of a wireless sensor network application is crucial for effective realization of the intended application in terms of cost, lifetime, and functionality. However, the minimizing task is hardly possible as no overall energy cost function is available for optimization. Optimizing a specific component of the total energy cost does not help in reducing the total energy cost as this reduction may be negated by an increase in the energy consumption of other components of the application. Recently we proposed Hierarchy Energy Driven Architecture as a robust architecture that takes into account all principal energy constituents of wireless sensor network applications. Based on the proposed architecture, this paper presents a single overall model and proposes a feasible formulation to express the overall energy consumption of a generic wireless sensor network application in terms of its energy constituents. The formulation offers a concrete expression for evaluating the performance of ...

  6. The effects of energy policies in China on energy consumption and GDP1

    E-Print Network [OSTI]

    Lin, C.-Y. Cynthia

    policies have significant impacts on diesel oil, gasoline and natural gas consumption. However, some energy The effects of energy policies in China on energy consumption and GDP1 Ming-Jie Lu, C.-Y. Cynthia policies; energy consumption; GDP; China JEL codes: Q48, Q41, Q58

  7. Visualization of United States Energy Consumption | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page| Open Energy Information Serbia-EnhancingEt Al.,Turin,Village of Wellington,FL LLC Jump to:Energy Consumption Jump to:

  8. BURNING BURIED SUNSHINE: HUMAN CONSUMPTION OF ANCIENT SOLAR ENERGY

    E-Print Network [OSTI]

    Dukes, Jeffrey

    BURNING BURIED SUNSHINE: HUMAN CONSUMPTION OF ANCIENT SOLAR ENERGY JEFFREY S. DUKES Department of as a vast store of solar energy from which society meets >80% of its current energy needs. Here, using of ancient solar energy decline, humans are likely to use an increasing share of modern solar resources. I

  9. DOE/EIA-0318/1 Nonresidential Buildings Energy Consumption Survey...

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

    1 Nonresidential Buildings Energy Consumption Survey: 1979 Consumption and Expenditures D Part I: Natural Gas and Electricity March 1983 Energy Information Administration...

  10. Smart Meters Help Balance Energy Consumption at Solar Decathlon

    Broader source: Energy.gov [DOE]

    Clouds, rain, thunderstorms… at Solar Decathlon Village? Oh my, you may say. But less-than-ideal weather conditions are no match for this year's teams, thanks to smart grid technology that is helping them monitor their energy consumption.

  11. November 2012 Key Performance Indicator (KPI): Energy Consumption

    E-Print Network [OSTI]

    Evans, Paul

    and district heating scheme* data. Year Energy Consumption (KWh) Percentage Change 2005/06 65,916,243 N/A 2006 buildings are connected to the Nottingham District Heating Scheme. This service meets all the heating

  12. New Water Booster Pump System Reduces Energy Consumption by 80...

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

    be adjusted to meet plant requirements. As a result, the company reduced pumping system energy consumption by 80 percent (225,100 kWh per year), saving an annual 11,255 in...

  13. Reducing 3G energy consumption on mobile devices

    E-Print Network [OSTI]

    Deng, Shuo

    2012-01-01

    The 3G wireless interface is a significant contributor to battery drain on mobile devices. This paper describes the design, implementation, and experimental evaluation of methods to reduce the energy consumption of the 3G ...

  14. Efficiency alone as a solution to increasing energy consumption

    E-Print Network [OSTI]

    Haidorfer, Luke

    2005-01-01

    A statistical analysis was performed to determine the effect of efficiency on the total US energy consumption of automobiles and refrigerators. Review of literature shows that there are many different opinions regarding ...

  15. Federal Government's Energy Consumption Lowest in Almost 40 Years...

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

    the U.S. federal government continues to be one of the largest energy consumers in the world, its consumption has been steadily declining for nearly four decades, and now stands...

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

    SciTech Connect (OSTI)

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

    2011-10-01

    The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span three operating companies1, serving customers in eight states2, and three market structures3. The great majority of the wind energy is contracted through power purchase agreements (PPAs). The remainder is utility owned, Qualifying Facilities (QF), distributed resources (i.e., 'behind the meter'), or merchant entities within Xcel Energy's Balancing Authority footprints. Regardless of the contractual or ownership arrangements, the output of the wind energy is balanced by Xcel Energy's generation resources that include fossil, nuclear, and hydro based facilities that are owned or contracted via PPAs. These facilities are committed and dispatched or bid into day-ahead and real-time markets by Xcel Energy's Commercial Operations department. Wind energy complicates the short and long-term planning goals of least-cost, reliable operations. Due to the uncertainty of wind energy production, inherent suboptimal commitment and dispatch associated with imperfect wind forecasts drives up costs. For example, a gas combined cycle unit may be turned on, or committed, in anticipation of low winds. The reality is winds stayed high, forcing this unit and others to run, or be dispatched, to sub-optimal loading positions. In addition, commitment decisions are frequently irreversible due to minimum up and down time constraints. That is, a dispatcher lives with inefficient decisions made in prior periods. In general, uncertainty contributes to conservative operations - committing more units and keeping them on longer than may have been necessary for purposes of maintaining reliability. The downside is costs are higher. In organized electricity markets, units that are committed for reliability reasons are paid their offer price even when prevailing market prices are lower. Often, these uplift charges are allocated to market participants that caused the inefficient dispatch in the first place. Thus, wind energy facilities are burdened with their share of costs proportional to their forecast errors. For Xcel Energy, wind energy uncertainty costs manifest depending on specific market structures. In the Public Service of Colorado (PSCo), inefficient commitment and dispatch caused by wind uncertainty increases fuel costs. Wind resources participating in the Midwest Independent System Operator (MISO) footprint make substantial payments in the real-time markets to true-up their day-ahead positions and are additionally burdened with deviation charges called a Revenue Sufficiency Guarantee (RSG) to cover out of market costs associated with operations. Southwest Public Service (SPS) wind plants cause both commitment inefficiencies and are charged Southwest Power Pool (SPP) imbalance payments due to wind uncertainty and variability. Wind energy forecasting helps mitigate these costs. Wind integration studies for the PSCo and Northern States Power (NSP) operating companies have projected increasing costs as more wind is installed on the system due to forecast error. It follows that reducing forecast error would reduce these costs. This is echoed by large scale studies in neighboring regions and states that have recommended adoption of state-of-the-art wind forecasting tools in day-ahead and real-time planning and operations. Further, Xcel Energy concluded reduction of the normalized mean absolute error by one percent would have reduced costs in 2008 by over $1 million annually in PSCo alone. The value of reducing forecast error prompted Xcel Energy to make substantial investments in wind energy forecasting research and development.

  17. Bounds on the Energy Consumption of Computational Andrew Gearhart

    E-Print Network [OSTI]

    California at Berkeley, University of

    in energy efficiency can significantly reduce operating costs. Such challenges have influenced re- search variety of machines. Motivated by the large and increas- ingly growing dominant cost (in time and energyBounds on the Energy Consumption of Computational Kernels Andrew Gearhart Electrical Engineering

  18. How Efficient Can We Be?: Bounds on Algorithm Energy Consumption

    E-Print Network [OSTI]

    California at Irvine, University of

    How Efficient Can We Be?: Bounds on Algorithm Energy Consumption Andrew Gearhart #12;Relation design use feedback to "cotune" compute kernel energy efficiency #12;Previous Work: Communication Lower-optimal" algorithms #12;Communication is energy inefficient! · On-chip/Off-chip gap isn't going to improve much Data

  19. Constraining Energy Consumption of China's Largest Industrial Enterprises Through the Top-1000 Energy-Consuming Enterprise Program

    E-Print Network [OSTI]

    Price, Lynn; Wang, Xuejun

    2007-01-01

    Industry Constraining Energy Consumption of China’s Largestone-to-one ratio of energy consumption to GDP – given China’goal of reducing energy consumption per unit of GDP by 20%

  20. Current Status and Future Scenarios of Residential Building Energy Consumption in China

    SciTech Connect (OSTI)

    Zhou, Nan; Nishida, Masaru; Gao, Weijun

    2008-12-01

    China's rapid economic expansion has propelled it into the ranks of the largest energy consuming nation in the world, with energy demand growth continuing at a pace commensurate with its economic growth. Even though the rapid growth is largely attributable to heavy industry, this in turn is driven by rapid urbanization process, by construction materials and equipment produced for use in buildings. Residential energy is mostly used in urban areas, where rising incomes have allowed acquisition of home appliances, as well as increased use of heating in southern China. The urban population is expected to grow by 20 million every year, accompanied by construction of 2 billion square meters of buildings every year through 2020. Thus residential energy use is very likely to continue its very rapid growth. Understanding the underlying drivers of this growth helps to identify the key areas to analyze energy efficiency potential, appropriate policies to reduce energy use, as well as to understand future energy in the building sector. This paper provides a detailed, bottom-up analysis of residential building energy consumption in China using data from a wide variety of sources and a modeling effort that relies on a very detailed characterization of China's energy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecast the future outlook for the critical period extending to 2020, based on assumptions of likely patterns of economic activity, availability of energy services, technology improvement and energy intensities.

  1. Energy Consumption Series: Assessment of energy use in multibuilding facilities

    SciTech Connect (OSTI)

    Not Available

    1993-08-01

    This study originally had two primary objectives: (1) to improve EIA`s estimates of district heat consumption for commercial buildings in the CBECS sample that lacked individual metering and (2) to provide a basis for estimating primary fuel consumption by central plants serving commercial buildings. These objectives were expanded to include additional questions relating to these central plants. Background information is provided on the CBECS and on district heating and cooling, which is the most important type of energy-related service provided by multibuilding facilities with central physical plants. Chapters 2 and 3 present data results on multibuilding facilities from the 1989 CBECS and the pilot Facility Survey. Chapter 2 presents the characteristics of multibuilding facilities and the individual buildings located on these facilities. Chapter 3 provides estimates of energy inputs and outputs of multibuilding facilities with central physical plants. Chapter 4 assesses the quality of the pilot Facility Survey and includes recommendations for future work in this area. The appendices provide more detailed information on the Facility Survey itself, in particular the limitations on the use of these results. Appendix B, ``Data Quality``, provides detailed information relating to the limitations of the data and the conclusions presented in this report. As a pilot study, the 1989 Facility Survey has some serious flaws and limitations which are recognized in this report.

  2. Delivered Energy Consumption Projections by Industry in the Annual Energy Outlook 2002

    Reports and Publications (EIA)

    2002-01-01

    This paper presents delivered energy consumption and intensity projections for the industries included in the industrial sector of the National Energy Modeling System.

  3. Energy for 500 Million Homes: Drivers and Outlook for Residential Energy Consumption in China

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    consumption, increasing imports, supply shortages, and difficulties integrating fully into global energyconsumption has a growing impact on world energy markets, affecting the availability of energy resources and global

  4. uFLIP: Understanding the Energy Consumption of Flash Devices Matias Bjrling

    E-Print Network [OSTI]

    uFLIP: Understanding the Energy Consumption of Flash Devices Matias Bjørling IT University Abstract Understanding the energy consumption of flash devices is important for two reasons. First, energy about the energy consumption of flash devices beyond their approximate aggregate consumption (low power

  5. Consumption

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

    Using Natural Gas (million square feet)",,,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"North- east","Mid- west","South","West","North- east","Mid-...

  6. Consumption

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

    Using Natural Gas (million square feet)",,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"West South Central","Moun- tain","Pacific","West South Central","Moun-...

  7. Consumption

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

    (million square feet)",,,"Energy Intensity for Sum of Major Fuels (thousand Btu square foot)" ,"West North Central","South Atlantic","East South Central","West North...

  8. Consumption

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

    (million square feet)",,,,"Energy Intensity for Sum of Major Fuels (thousand Btu square foot)" ,"North- east","Mid- west","South","West","North- east","Mid-...

  9. Consumption

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

    Using Natural Gas (million square feet)",,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"New England","Middle Atlantic","East North Central","New England","Middle...

  10. Consumption

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

    Using Natural Gas (million square feet)",,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"West North Central","South Atlantic","East South Central","West North...

  11. Consumption

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

    (million square feet)",,,"Energy Intensity for Sum of Major Fuels (thousand Btu square foot)" ,"West South Central","Moun- tain","Pacific","West South Central","Moun-...

  12. Consumption

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

    (million square feet)",,,,"Energy Intensity for Sum of Major Fuels (thousand Btusquare foot)" ,"North- east","Mid- west","South","West","North- east","Mid-...

  13. World Energy Consumption and Carbon Dioxide Emissions: 1950 2050

    E-Print Network [OSTI]

    World Energy Consumption and Carbon Dioxide Emissions: 1950 Ñ 2050 Richard Schmalensee, Thomas M. Stoker, andRuth A. Judson* Emissions of carbon dioxide from combustion of fossil fuels, which may-U" relation with a within- sample peak between carbon dioxide emissions (and energy use) per capita and per

  14. California Energy and Consumption Projections 2005-2050

    E-Print Network [OSTI]

    Keller, Arturo A.

    US Gas/Diesel Foreign Gas/Diesel Biomass-Ethanol, Bio. D, H2 Solar - H2 Wind - H2 Geothermal - H2 3 Natural Gas - Heating Natural Gas - Electrical Generation Gas/Diesel Coal Non-Fossil Fuels Nuclear Large Hydro Renewable Energy Biomass Solar Wind Geothermal #12;Model Energy Consumption in Quads Take the 2005

  15. Vending Machine Energy Consumption and VendingMiser Evaluation 

    E-Print Network [OSTI]

    Ritter, J.; Hugghins, J.

    2000-01-01

    As an effort to decrease the amount of non-critical energy used on the Texas A&M campus, and to assist Dixie Narco in evaluating the efficiency of their vending machines, the Texas A&M Energy Systems Laboratory investigated the power consumption...

  16. On-line economic optimization of energy systems using weather forecast information.

    SciTech Connect (OSTI)

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

    2009-01-01

    We establish an on-line optimization framework to exploit weather forecast information in the operation of energy systems. We argue that anticipating the weather conditions can lead to more proactive and cost-effective operations. The framework is based on the solution of a stochastic dynamic real-time optimization (D-RTO) problem incorporating forecasts generated from a state-of-the-art weather prediction model. The necessary uncertainty information is extracted from the weather model using an ensemble approach. The accuracy of the forecast trends and uncertainty bounds are validated using real meteorological data. We present a numerical simulation study in a building system to demonstrate the developments.

  17. Commercial Buildings Energy Consumption and Expenditures 1992

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

    in CBECS. In addition, the same customer may be classified differently by each of its energy suppliers. Activities with Large Amounts of Hot Water: One of the energy-related space...

  18. Commercial Buildings Energy Consumption and Expenditures 1992

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

    at the national level as well as State level in several EIA reports, including State Energy Data Report (SEDR) and the Monthly Energy Review (MER). When comparing the CBECS totals...

  19. A Parallel Statistical Learning Approach to the Prediction of Building Energy Consumption Based on Large Datasets

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    A Parallel Statistical Learning Approach to the Prediction of Building Energy Consumption Based consumption of buildings based on historical performances is an important approach to achieve energy (SVMs), Prediction, Model, Energy Efficiency, Parallel Computing. 1. INTRODUCTION Building energy

  20. Energy consumption series: Lighting in commercial buildings. [Contains glossary

    SciTech Connect (OSTI)

    Not Available

    1992-03-11

    Lighting represents a substantial fraction of commercial electricity consumption. A wide range of initiatives in the Department of Energy's (DOE) National Energy Strategy have focused on commercial lighting as a potential source of energy conservation. This report provides a statistical profile of commercial lighting, to examine the potential for lighting energy conservation in commercial buildings. The principal conclusion from this analysis is that energy use for lighting could be reduced by as much as a factor of four using currently available technology. The analysis is based primarily on the Energy Information Administration's (EIA) 1986 Commercial Buildings Energy Consumption Survey (CBECS). The more recent 1989 survey had less detail on lighting, for budget reasons. While changes have occurred in the commercial building stock since 1986, the relationships identified by this analysis are expected to remain generally valid. In addition, the analytic approach developed here can be applied to the data that will be collected in the 1992 CBECS.

  1. Consumption

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

    Using Natural Gas (million square feet)",,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"1959 or Before","1960 to 1989","1990 to 2003","1959 or Before","1960 to...

  2. Consumption

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

    Using Natural Gas (million square feet)",,,,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"Zone 1","Zone 2","Zone 3","Zone 4","Zone 5","Zone 1","Zone 2","Zone 3","Zone...

  3. Consumption

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

    (million square feet)",,,"Energy Intensity for Sum of Major Fuels (thousand Btusquare foot)" ,"1959 or Before","1960 to 1989","1990 to 2003","1959 or Before","1960 to...

  4. Consumption

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

    (million square feet)",,,"Energy Intensity for Sum of Major Fuels (thousand Btusquare foot)" ,"1,001 to 10,000 Square Feet","10,001 to 100,000 Square Feet","Over 100,000...

  5. Consumption

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

    Using Natural Gas (million square feet)",,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"1,001 to 10,000 Square Feet","10,001 to 100,000 Square Feet","Over 100,000...

  6. Consumption

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

    (million square feet)",,,"Energy Intensity for Sum of Major Fuels (thousand Btu square foot)" ,"New England","Middle Atlantic","East North Central","New England","Middle...

  7. Consumption

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

    (million square feet)",,,"Energy Intensity for Sum of Major Fuels (thousand Btu square foot)" ,"1,001 to 10,000 Square Feet","10,001 to 100,000 Square Feet","Over 100,000...

  8. Consumption

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

    (million square feet)",,,,,"Energy Intensity for Sum of Major Fuels (thousand Btu square foot)" ,"Zone 1","Zone 2","Zone 3","Zone 4","Zone 5","Zone 1","Zone 2","Zone 3","Zone...

  9. Consumption

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

    Using Natural Gas (million square feet)",,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"1959 or Before","1960 to 1989","1990 to 1999","1959 or Before","1960 to...

  10. Consumption

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

    (million square feet)",,,"Energy Intensity for Sum of Major Fuels (thousand Btusquare foot)" ,"1959 or Before","1960 to 1989","1990 to 1999","1959 or Before","1960 to...

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

    SciTech Connect (OSTI)

    Stoffel, T.

    2012-06-01

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

  12. Commercial Buildings Energy Consumption and Expenditures 1992

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

    the sponsor the government, utility or sponsored in-house. Energy Management and Control System Heating or cooling system monitored or controlled by a computerized building...

  13. Signatures of Heating and Cooling Energy Consumption for Typical AHUs 

    E-Print Network [OSTI]

    Wei, G.; Liu, M.; Claridge, D. E.

    1998-01-01

    -patient measured values, respectively. hospital facility with a total conditioned floor area of 298,500 ft2. There are four constant 40 50 60 70 80 90 Tdb (OF) Figure 4. Comparison of measured and initial model predicted heating and cooling energy consumption.... 20 A M-Steam o S-Steam o M-CHW S-CHW La 9 \\ a g 10 --- ---------A r, 2 40 50 60 70 80 90 Tdb (OF) Figure 5. Comparison of measured and calibrated model predicted heating and cooling energy consumption 20 Measured chilled water...

  14. Social Network Users Share Electricity Consumption Habits to Reduce Energy Costs for Consumers and Utility Companies

    E-Print Network [OSTI]

    Wu, Dapeng Oliver

    Social Network Users Share Electricity Consumption Habits to Reduce Energy Costs for Consumers approximately 74 percent of the nation's electricity consumption. During peaks in electricity demand, generators companies keep generators on, ready to respond to sudden upswings in electricity consumption

  15. Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01

    electricity, oil and coal consumption, offset by increasedsaved in electricity, oil and gas consumption, offset by 2.4energy consumption by fuel type. Natural gas, oil and some

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

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

  17. Determinants of measured energy consumption in public housing

    SciTech Connect (OSTI)

    Greely, K.M.; Mills, E.; Goldman, C.A.; Ritschard, R.L. )

    1988-01-01

    In this study, the authors used a two-part methodology to analyze metered energy use patterns in 91 public housing projects. Their goal was to develop a technique that could be used by the U.S. Department of Housing and Urban Development (HUD) and public housing authorities (PHAs) to derive reasonable energy use guidelines for different segments of the public housing stock. In the authors' approach, actual energy use was first normalized to consumption in a year with ''typical'' weather and then used in a multiple regression analysis of different cross-sectional variables. The regression model explained 80% of the variation in energy use, with the type of account and the management practices of PHAs emerging as important explanatory factors. As compared to previous engineering estimates of public housing consumption, the projects in this study used 8% (per square foot) to 16% (per apartment) less fuel and electricity, but consumption was still significantly higher (43%) than that of privately owned multifamily housing. They conclude that this methodology could be used to help HUD and PHAs increase their understanding of energy use patterns and appropriate consumption levels in public housing.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on771/6/14 Contact:NewsWebmasterWorkingElla Zhou Photo of EllaEnergy

  19. Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01

    Table 12 Projected Primary Energy Savings between ReferenceEnergy (Primary Energy) .18 Figure 6 Primary Energy Consumption by End-Use in

  20. Current Status and Future Scenarios of Residential Building Energy Consumption in China

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    energy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecastenergy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecast

  1. Monitoring and Management of Refinery Energy Consumption 

    E-Print Network [OSTI]

    Pelham, R. O.; Moriarty, R. D.; Hudgens, P. D.

    1986-01-01

    GASOLINE REFORMER FIGURE 4 14 ESL-IE-86-06-03 Proceedings from the Eighth Annual Industrial Energy Technology Conference, Houston, TX, June 17-19, 1986 REFORMER FEED QUALITY VS ENERGY FIG?URE 5 BASIS: CONSTANT SEVERITY AROMATICS CONSTANT NAP HTHF... is canbined with hydrogen, heated and passed over successive beds of catalyst. The complex reac tions are endothermic, requirirq heatirq prior to each reactor stage. Reactor inlet temperatures are 900 to 950?F and pressures rarqe from 150 to 400 psig...

  2. The Impact of Residential Density on Vehicle Usage and Energy Consumption

    E-Print Network [OSTI]

    Golob, Thomas F; Brownstone, David

    2005-01-01

    residential transportation energy usage is vital for theDensity on Vehicle Usage and Energy Consumption ReferencesDensity on Vehicle Usage and Energy Consumption UCI-ITS-WP-

  3. Towards Energy Consumption Measurement in a Cloud Computing Wireless Testbed

    E-Print Network [OSTI]

    Braun, Torsten

    systems such as Long Term Evolution (LTE), Worldwide Interoperability for Microwave Access (WiTowards Energy Consumption Measurement in a Cloud Computing Wireless Testbed Vitor Bernardo, Marilia Curado Center for Informatics and Systems University of Coimbra Polo II, Pinhal de Marrocos, 3030

  4. Comparison of Life Cycle Emissions and Energy Consumption for

    E-Print Network [OSTI]

    Clarens, Andres

    Comparison of Life Cycle Emissions and Energy Consumption for Environmentally Adapted Metalworking of environmentally adapted lubricants have been proposed in response to the environmental and health impacts/or deliver minimum quantities of lubricant in gas rather than water, with the former strategy being more

  5. A method for evaluating transport energy consumption in suburban areas

    SciTech Connect (OSTI)

    Marique, Anne-Francoise Reiter, Sigrid

    2012-02-15

    Urban sprawl is a major issue for sustainable development. It represents a significant contribution to energy consumption of a territory especially due to transportation requirements. However, transport energy consumption is rarely taken into account when the sustainability of suburban structures is studied. In this context, the paper presents a method to estimate transport energy consumption in residential suburban areas. The study aimed, on this basis, at highlighting the most efficient strategies needed to promote awareness and to give practical hints on how to reduce transport energy consumption linked to urban sprawl in existing and future suburban neighborhoods. The method uses data collected by using empirical surveys and GIS. An application of this method is presented concerning the comparison of four suburban districts located in Belgium to demonstrate the advantages of the approach. The influence of several parameters, such as distance to work places and services, use of public transport and performance of the vehicles, are then discussed to allow a range of different development situations to be explored. The results of the case studies highlight that traveled distances, and thus a good mix between activities at the living area scale, are of primordial importance for the energy performance, whereas means of transport used is only of little impact. Improving the performance of the vehicles and favoring home-work give also significant energy savings. The method can be used when planning new areas or retrofitting existing ones, as well as promoting more sustainable lifestyles regarding transport habits. - Highlights: Black-Right-Pointing-Pointer The method allows to assess transport energy consumption in suburban areas and highlight the best strategies to reduce it. Black-Right-Pointing-Pointer Home-to-work travels represent the most important part of calculated transport energy consumption. Black-Right-Pointing-Pointer Energy savings can be achieved by reducing distances to travel through a good mix between activities at the local scale. Black-Right-Pointing-Pointer Means of transport used in only of little impact in the studied suburban neighborhoods. Black-Right-Pointing-Pointer Improving the performance of the vehicles and favoring home-work can significant energy savings.

  6. Analysis of federal incentives used to stimulate energy consumption

    SciTech Connect (OSTI)

    Cole, R.J.; Cone, B.W.; Emery, J.C.; Huelshoff, M.; Lenerz, D.E.; Marcus, A.; Morris, F.A.; Sheppard, W.J.; Sommers, P.

    1981-08-01

    The purpose of the analysis is to identify and quantify Federal incentives that have increased the consumption of coal, oil, natural gas, and electricity. The introductory chapter is intended as a device for presenting the policy questions about the incentives that can be used to stimulate desired levels of energy development. In the theoretical chapter federal incentives were identified for the consumption of energy as Federal government actions whose major intent or result is to stimulate energy consumption. The stimulus comes through changing values of variables included in energy demand functions, thereby inducing energy consumers to move along the function in the direction of greater quantity of energy demanded, or through inducing a shift of the function to a position where more energy will be demanded at a given price. The demand variables fall into one of six categories: price of the energy form, price of complements, price of substitutes, preferences, income, and technology. The government can provide such incentives using six different policy instruments: taxation, disbursements, requirements, nontraditional services, traditional services, and market activity. The four major energy forms were examined. Six energy-consuming sectors were examined: residential, commercial, industrial, agricultural, transportation, and public. Two types of analyses of incentive actions are presented in this volume. The generic chapter focused on actions taken in 1978 across all energy forms. The subsequent chapters traced the patterns of incentive actions, energy form by energy form, from the beginning of the 20th century, to the present. The summary chapter includes the results of the previous chapters presented by energy form, incentive type, and user group. Finally, the implications of these results for solar policy are presented in the last chapter. (MCW)

  7. 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.

  8. Investigation and Analysis of Summer Energy Consumption of Energy Efficient Residential Buildings in Xi'an 

    E-Print Network [OSTI]

    Ma, B.; Yan, Z.; Gui, Z.; He, J.

    2006-01-01

    Tests and questionnaire surveys on the summer energy consumption structure of 100 energy efficient residential buildings have been performed in a certain residential district in Xi'an, China. The relationship between the formation of the energy...

  9. Canada's Fuel Consumption Guide | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar Energy LLC JumpBiossenceBrunswick,Calendar HomeGmbHFundsCampeauCanada's Fuel

  10. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    49 3.3.3. Pre-installation electricity consumption of CSIE. Kahn (2011). Electricity Consumption and Durable Housing:on Electricity Consumption .

  11. Building and occupant characteristics as determinants of residential energy consumption

    SciTech Connect (OSTI)

    Nieves, L.A.; Nieves, A.L.

    1981-10-01

    The major goals of the research are to gain insight into the probable effects of building energy performance standards on energy consumption; to obtain observations of actual residential energy consumption that could affirm or disaffirm comsumption estimates of the DOE 2.0A simulation model; and to investigate home owner's conservation investments and home purchase decisions. The first chapter covers the investigation of determinants of household energy consumption. The presentation begins with the underlying economic theory and its implications, and continues with a description of the data collection procedures, the formulation of variables, and then of data analysis and findings. In the second chapter the assumptions and limitations of the energy use projections generated by the DOE 2.0A model are discussed. Actual electricity data for the houses are then compared with results of the simulation. The third chapter contains information regarding households' willingness to make energy conserving investments and their ranking of various conservation features. In the final chapter conclusions and recommendations are presented with an emphasis on the policy implications of this study. (MCW)

  12. MPC for Wind Power Gradients --Utilizing Forecasts, Rotor Inertia, and Central Energy Storage

    E-Print Network [OSTI]

    MPC for Wind Power Gradients -- Utilizing Forecasts, Rotor Inertia, and Central Energy Storage the control of a wind power plant, possibly consisting of many individual wind turbines. The goal. INTRODUCTION Today, wind power is the most important renewable energy source. For the years to come, many

  13. Bet and Energy -From Load Forecasting to Demand Response in a Web of Things

    E-Print Network [OSTI]

    Beigl, Michael

    Bet and Energy - From Load Forecasting to Demand Response in a Web of Things Yong Ding TECO (DSM) [7, 19]. Within DSM, mainly two principal activities i.e. load shifting (demand response programs) and load reduction (energy efficiency and conser- vation programs) can be realized [4]. 1.1 Demand Response

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

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred [ORNL

    2008-01-01

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

  15. Derived annual estimates of manufacturing energy consumption, 1974--1988

    SciTech Connect (OSTI)

    Not Available

    1992-08-05

    This report presents a complete series of annual estimates of purchased energy used by the manufacturing sector of the US economy, for the years 1974 to 1988. These estimates interpolate over gaps in the actual data collections, by deriving estimates for the missing years 1982--1984 and 1986--1987. For the purposes of this report, ``purchased`` energy is energy brought from offsite for use at manufacturing establishments, whether the energy is purchased from an energy vendor or procured from some other source. The actual data on purchased energy comes from two sources, the US Department of Commerce Bureau of the Census`s Annual Survey of Manufactures (ASM) and EIA`s Manufacturing Energy Consumption Survey (MECS). The ASM provides annual estimates for the years 1974 to 1981. However, in 1982 (and subsequent years) the scope of the ASM energy data was reduced to collect only electricity consumption and expenditures and total expenditures for other purchased energy. In 1985, EIA initiated the triennial MECS collecting complete energy data. The series equivalent to the ASM is referred to in the MECS as ``offsite-produced fuels.``

  16. Commercial Office Plug Load Energy Consumption Trends and the Role of Occupant Behavior

    E-Print Network [OSTI]

    Gandhi, Priya

    2015-01-01

    ULI-Documents/TheBullittCenter.pdf U.S. Energy InformationCommercial Buildings Energy Consumption Survey. Retrievedcommercial/ U.S. Energy Information Administration. (2014).

  17. Energy Consumption, Efficiency, Conservation, and Greenhouse Gas Mitigation in Japan's Building Sector

    E-Print Network [OSTI]

    2006-01-01

    w i t h global warming, Japan's energy consumption for spaceGlobal-warming Impactfrom Daily-life Activities and Home Energy Consumptionenergy consumption, the technologies for the prevention o f global

  18. Optimal Energy Consumption Scheduling Using Mechanism Design for the Future Smart Grid

    E-Print Network [OSTI]

    Wong, Vincent

    Optimal Energy Consumption Scheduling Using Mechanism Design for the Future Smart Grid Pedram may need to collect various information about users and their energy consumption behavior, which can this problem, different programs have been proposed to shape the energy consumption pattern of the users

  19. StressCloud: A Tool for Analysing Performance and Energy Consumption of Cloud Applications

    E-Print Network [OSTI]

    Yang, Yun

    StressCloud: A Tool for Analysing Performance and Energy Consumption of Cloud Applications Feifei. It requires the evaluation of system performance and energy consumption under a wide variety of realistic and energy consumption analysis tool for cloud applications in real-world cloud environments. Stress

  20. Measuring the Client Performance and Energy Consumption in Mobile Cloud Gaming

    E-Print Network [OSTI]

    Chen, Sheng-Wei

    Measuring the Client Performance and Energy Consumption in Mobile Cloud Gaming Chun-Ying Huang1, Po-constrained devices may lead to inferior performance and high energy consumption. For example, the gaming frame rate and energy consumption of mobile clients is critical to the success of the new mobile cloud gaming ecosystem

  1. Bounding the Energy Consumption of Mobile Sensor Nodes For Triangulation-based Coverage

    E-Print Network [OSTI]

    Krovi, Venkat

    1 Bounding the Energy Consumption of Mobile Sensor Nodes For Triangulation-based Coverage Asheq the energy consumption of the MTA interms of the distance and time taken to complete the full coverage of the field. The bounds on the minimum total and individual energy consumption per MSN is determined. A prior

  2. INFLUENCES OF RAKE RECEIVER/TURBO DECODER PARAMETERS ON ENERGY CONSUMPTION AND QUALITY

    E-Print Network [OSTI]

    Al Hanbali, Ahmad

    INFLUENCES OF RAKE RECEIVER/TURBO DECODER PARAMETERS ON ENERGY CONSUMPTION AND QUALITY Lodewijk T are selected and their influences on the energy consumption and quality are investigated by means power hardware is needed to save energy consumption. Furthermore, an adequate quality of the wireless

  3. IEEE TRANSACTIONS ON AUTOMATIC CONTROL 1 Coverage and Energy Consumption Control in

    E-Print Network [OSTI]

    Wang, Xinbing

    IEEE TRANSACTIONS ON AUTOMATIC CONTROL 1 Coverage and Energy Consumption Control in Mobile Abstract--In this paper 1 , we investigate the coverage and energy consumption control in mobile. Meanwhile, we can operate a tradeoff control between coverage performance and energy consumption

  4. UBC Social Ecological Economic Development Studies (SEEDS) Student Report Elevator Drive Systems Energy Consumption Study Report

    E-Print Network [OSTI]

    Energy Consumption Study Report Benny ChunYin Chan University of British Columbia EECE 492 April 6th the current status of the subject matter of a project/report". #12;Elevator Drive Systems Energy Consumption Study Report April 2012 0 2012 Elevator Drive Systems Energy Consumption Study Report Benny CY Chan UBC

  5. Balancing Energy and Water Consumption in an Urban Desert Environment: A Case

    E-Print Network [OSTI]

    Hall, Sharon J.

    at the Census block group level for 2005 3. Energy consumption data from 2005 Census Mesic Landscaping XericBalancing Energy and Water Consumption in an Urban Desert Environment: A Case Study on Phoenix, AZ effect, water scarcity, and energy consumption. The transformation of native landscapes into built

  6. Modelling Business Energy Consumption using Agent-based Simulation Modelling Jason Wong and Kay Cao1

    E-Print Network [OSTI]

    to develop a prototype agent based simulation model for business energy consumption, using data from the 2008 presents a framework of the model for estimating business energy consumption. Section V discusses the dataModelling Business Energy Consumption using Agent-based Simulation Modelling Jason Wong and Kay Cao

  7. Global Inequality in Energy Consumption from 1980 to 2010

    E-Print Network [OSTI]

    Lawrence, Scott; Yakovenko, Victor M

    2013-01-01

    We study the global probability distribution of energy consumption per capita around the world using data from the U.S. Energy Information Administration (EIA) for 1980-2010. We find that the Lorenz curves have moved up during this time period, and the Gini coefficient G has decreased from 0.66 in 1980 to 0.55 in 2010, indicating a decrease in inequality. The global probability distribution of energy consumption per capita in 2010 is close to the exponential distribution with G=0.5. We attribute this result to the globalization of the world economy, which mixes the world and brings it closer to the state of maximal entropy. We argue that global energy production is a limited resource that is partitioned among the world population. The most probable partition is the one that maximizes entropy, thus resulting in the exponential distribution function. A consequence of the latter is the law of 1/3: the top 1/3 of the world population consumes 2/3 of produced energy. We also find similar results for the global pro...

  8. European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind Generation by a Dynamic

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind. Abstract-Short-term wind power forecasting is recognized nowadays as a major requirement for a secure and economic integration of wind power in a power system. In the case of large-scale integration, end users

  9. The Energy Dashboard: Improving the Visibility of Energy Consumption at a Campus-Wide Scale

    E-Print Network [OSTI]

    Gupta, Rajesh

    energy use. Our detailed observations identify the primary components of the baseline energy useThe Energy Dashboard: Improving the Visibility of Energy Consumption at a Campus-Wide Scale Yuvraj- tation and implementation of energy use policies, the Univer- sity of California at San Diego provides

  10. Figure 1:Energy Consumption in USg gy p 1E Roberts, Energy in US

    E-Print Network [OSTI]

    Sutton, Michael

    ;Figure 32: Alternative Transportation Fuels T k l fTank volume for same energy as 55 liters of gasolineFigure 1:Energy Consumption in USg gy p 2008 1E Roberts, Energy in US Source: www.eia.gov #12;Figure 2: US Liquid Demand by Sector and Fuel 2E Roberts, Energy in US Source: EIA: Annual Energy Outlook

  11. Nonresidential buildings energy consumption survey: 1979 consumption and expenditures. Part 2. Steam, fuel oil, LPG, and all fuels

    SciTech Connect (OSTI)

    Patinkin, L.

    1983-12-01

    This report presents data on square footage and on total energy consumption and expenditures for commercial buildings in the contiguous United States. Also included are detailed consumption and expenditures tables for fuel oil or kerosene, liquid petroleum gas (LPG), and purchased steam. Commercial buildings include all nonresidential buildings with the exception of those where industrial activities occupy more of the total square footage than any other type of activity. 7 figures, 23 tables.

  12. Current Status and Future Scenarios of Residential Building Energy Consumption in China

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    Energy Intensity by End-use Assumptions Urban enduse intensity SpaceEnergy Consumption by Fuel Table 3 End Use Saturations and Intensities Saturation, % Urban Space

  13. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

    s economy. Demand Forecasts The three energy futures wereto meet the forecast demand in each energy futurE2. e e1£~energy saved through improved appliance efficiencies. Also icit in our demand forecasts

  14. Secure Distributed Solution for Optimal Energy Consumption Scheduling in Smart Grid

    E-Print Network [OSTI]

    Shehab, Mohamed

    periods. The peak value of electricity consumption data is extremely important for electric companiesSecure Distributed Solution for Optimal Energy Consumption Scheduling in Smart Grid Mohammad usage. The scheduling of the energy consumption is often formulated as a game- theoretic problem, where

  15. TRANSACTION ON PARALLEL AND DISTRIBUTED SYSTEMS 1 Minimizing Energy Consumption for

    E-Print Network [OSTI]

    Wu, Jie

    % of commercial electrici- ty consumption; a large data center can consume as much electricity as a city. HighTRANSACTION ON PARALLEL AND DISTRIBUTED SYSTEMS 1 Minimizing Energy Consumption for Frame. As the performance increases, the energy consumption in these systems also increases significantly. Dynamic Voltage

  16. Accounting for the Energy Consumption of Personal Computing Including Portable Devices

    E-Print Network [OSTI]

    Namboodiri, Vinod

    that computing consumes more than 3% of the global electricity consumption. (ii) We characterize the powerAccounting for the Energy Consumption of Personal Computing Including Portable Devices Pavel.S.A vinod.namboodiri@wichita.edu ABSTRACT In light of the increased awareness of global energy consumption

  17. TV Energy Consumption Trends and Energy-Efficiency Improvement Options

    E-Print Network [OSTI]

    Park, Won Young

    2011-01-01

    television sets. ” Austrian Energy Agency, June. Chen, H.F.of Options for Improving Energy Efficiency Test Proceduresfor Displays”, March. Energy Conservation Center, Japan (

  18. TV Energy Consumption Trends and Energy-Efficiency Improvement Options

    E-Print Network [OSTI]

    Park, Won Young

    2011-01-01

    TV Specification Revision Update (ENERGY STAR 2007) uses atv_vcr/TV_update_doc ument_Final.pdf ENERGY STAR. 2010. “ENERGY STAR Qualified Televisions Specification Revision Update”,

  19. Practicing Energy, or Energy Consumption as Social Practice

    E-Print Network [OSTI]

    Lipschutz, Ronnie

    2015-01-01

    practice”: people don’t “consume” energy directly or evenpeople do at home which consume energy, such as cooking or

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

    SciTech Connect (OSTI)

    none,

    2014-08-29

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

  1. CALIFORNIA ENERGY CALIFORNIA ENERGY DEMAND 2010-2020

    E-Print Network [OSTI]

    , and utilities. Ted Dang, Steven Mac, and Libbie Bessman prepared the historical energy consumption data. Miguel CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2010-2020 ADOPTED FORECAST Schwarzenegger, Governor #12; #12; CALIFORNIA ENERGY COMMISSION Chris Kavalec Tom Gorin

  2. Sample design for the residential energy consumption survey

    SciTech Connect (OSTI)

    Not Available

    1994-08-01

    The purpose of this report is to provide detailed information about the multistage area-probability sample design used for the Residential Energy Consumption Survey (RECS). It is intended as a technical report, for use by statisticians, to better understand the theory and procedures followed in the creation of the RECS sample frame. For a more cursory overview of the RECS sample design, refer to the appendix entitled ``How the Survey was Conducted,`` which is included in the statistical reports produced for each RECS survey year.

  3. Annual Energy Consumption Analysis Report for Richland Middle School

    SciTech Connect (OSTI)

    Liu, Bing

    2003-12-18

    Richland Middle School is a single story, 90,000 square feet new school located in Richland, WA. The design team proposed four HVAC system options to serve the building. The proposed HVAC systems are listed as following: (1) 4-pipe fan coil units served by electrical chiller and gas-fired boilers, (2) Ground-source closed water loop heat pumps with water loop heat pumps with boiler and cooling tower, and (3) VAV system served by electrical chiller and gas-fired boiler. This analysis estimates the annual energy consumptions and costs of each system option, in order to provide the design team with a reasonable basis for determining which system is most life-cycle cost effective. eQuest (version 3.37), a computer-based energy simulation program that uses the DOE-2 simulation engine, was used to estimate the annual energy costs.

  4. Overview of the Electrical Energy Segment of the Energy Information Administration/ Manufacturing Consumption Report 

    E-Print Network [OSTI]

    Lockhead, S.

    1999-01-01

    , liquefied petroleum gas, coke and breeze, coal, and electricity, only the electricity segment is overviewed. Along with pure electrical energy consumption information, newly available data covers methods that manufacturers used to purchase and modify...

  5. Trends in energy use in commercial buildings -- Sixteen years of EIA's commercial buildings energy consumption survey

    SciTech Connect (OSTI)

    Davis, J.; Swenson, A.

    1998-07-01

    The Commercial Buildings Energy Consumption Survey (CBECS) collects basic statistical information on energy consumption and energy-related characteristics of commercial buildings in the US. The first CBECS was conducted in 1979 and the most recent was completed in 1995. Over that period, the number of commercial bindings and total amount of floorspace increased, total consumption remained flat, and total energy intensity declined. By 1995, there were 4.6 million commercial buildings and 58.8 billion square feet of floorspace. The buildings consumed a total of 5.3 quadrillion Btu (site energy), with a total intensity of 90.5 thousand Btu per square foot per year. Electricity consumption exceeded natural gas consumption (2.6 quadrillion and 1.9 quadrillion Btu, respectively). In 1995, the two major users of energy were space heating (1.7 quadrillion Btu) and lighting (1.2 quadrillion Btu). Over the period 1979 to 1995, natural gas intensity declined from 71.4 thousand to 51.0 thousand Btu per square foot per year. Electricity intensity did not show a similar decline (44.2 thousand Btu per square foot in 1979 and 45.7 thousand Btu per square foot in 1995). Two types of commercial buildings, office buildings and mercantile and service buildings, were the largest consumers of energy in 1995 (2.0 quadrillion Btu, 38% of total consumption). Three building types, health care, food service, and food sales, had significantly higher energy intensities. Buildings constructed since 1970 accounted for half of total consumption and a majority (59%) of total electricity consumption.

  6. TV Energy Consumption Trends and Energy-Efficiency Improvement Options

    E-Print Network [OSTI]

    Park, Won Young

    2011-01-01

    in 3D mode is likely to consume more energy than in 2D modeTVs are expected to consume more energy relative to currentcompose 3D images. consume more energy in standby mode than

  7. Analyzing the Trade-offs Between Minimizing Makespan and Minimizing Energy Consumption in a Heterogeneous Resource Allocation Problem

    E-Print Network [OSTI]

    Maciejewski, Anthony A. "Tony"

    Analyzing the Trade-offs Between Minimizing Makespan and Minimizing Energy Consumption@engr.colostate.edu, wcoliver@rams.colostate.edu, HJ@colostate.edu, aam@colostate.edu Abstract--The energy consumption of data their energy consumption while maintaining a high level of performance. Minimizing energy consumption while

  8. Analyzing the Impact of Useless Write-Backs on the Endurance and Energy Consumption of PCM

    E-Print Network [OSTI]

    Zhang, Youtao

    -effective and energy-efficient alternative to traditional DRAM main memory. Due to the high energy consumptionAnalyzing the Impact of Useless Write-Backs on the Endurance and Energy Consumption of PCM Main in considerable energy savings and endurance improvement. In this paper, we introduce the concept of useless write

  9. Biodiesel Supply and Consumption in the Short-Term Energy Outlook

    Reports and Publications (EIA)

    2009-01-01

    The historical biodiesel consumption data published in the Energy Information Administration's Monthly Energy Review March 2009 edition were revised to account for imports and exports. Table 10.4 of the Monthly Energy Review was expanded to display biodiesel imports, exports, stocks, stock change, and consumption. Similar revisions were made in the April 2009 edition of the Short-Term Energy Outlook (STEO).

  10. Managing the Cost, Energy Consumption, and Carbon Footprint of Internet Services

    E-Print Network [OSTI]

    Bianchini, Ricardo

    or "green" energy. This paper introduces a general, optimization-based framework for enabling multi-data-center services to manage their brown en- ergy consumption and leverage green energy, while respecting their SLAs. "green" or renewable energy.) We argue that placing caps on the brown energy consumption of data centers

  11. Fine-grained Energy Consumption Characterization and Modeling Catherine Mills Olschanowsky, Tajana Rosing, and

    E-Print Network [OSTI]

    Simunic, Tajana

    supercomputer. As with performance, energy-efficiency is not an attribute of a compute resource alone the performance and energy-efficiency of candidate resources. Predicting the energy consumption of an HPC resource of the applications in the workload affect the energy consumption of the resource. Our experiments confirm that data

  12. Modelling Office Energy Consumption: An Agent Based Approach , Peer-Olaf Siebers1

    E-Print Network [OSTI]

    Aickelin, Uwe

    1 Modelling Office Energy Consumption: An Agent Based Approach Tao Zhang1 , Peer-Olaf Siebers1 integrates four important elements, i.e. organisational energy management policies/regulations, energy, to simulate the energy consumption in office buildings. With the model, we test the effectiveness of different

  13. Experimental Analysis of Task-based Energy Consumption in Cloud Computing Systems

    E-Print Network [OSTI]

    Schneider, Jean-Guy

    computing, green cloud, energy consumption, performance analysis, energy efficiency. 1. INTRODUCTION Cloud in green cloud computing systems [4]. Many efforts have been made to improve the energy efficiency of cloudExperimental Analysis of Task-based Energy Consumption in Cloud Computing Systems Feifei Chen, John

  14. Energy-Aware Networks: Reducing Power Consumption By Switching Off Network Elements

    E-Print Network [OSTI]

    Giaccone, Paolo

    service quality. Keywords: green networks, power-aware, optimization I. INTRODUCTION Power consumptionEnergy-Aware Networks: Reducing Power Consumption By Switching Off Network Elements Luca}@tlc.polito.it Abstract--According to several studies, the power consumption of the Internet accounts for up to 10

  15. The effects of energy policies on energy consumption in China1

    E-Print Network [OSTI]

    Lin, C.-Y. Cynthia

    to more efficient or more careful use of resources and to more environmentally sustainable behavior studies have found that environmental protection policies that lead to energy efficiency improvements have1 The effects of energy policies on energy consumption in China1 Ming-Jie Lu, C.-Y. Cynthia Lin

  16. Instrumenting Linear Algebra Energy Consumption via On-chip Energy Counters

    E-Print Network [OSTI]

    California at Berkeley, University of

    and cooling [17]. By increasing the energy efficiency of algorithms, both costs can be reduced. On the otherInstrumenting Linear Algebra Energy Consumption via On-chip Energy Counters James Demmel Andrew Gearhart Electrical Engineering and Computer Sciences University of California at Berkeley Technical Report

  17. Energy Consumption and Potential for Energy Conservation in the Steel Industry 

    E-Print Network [OSTI]

    Hughes, M. L.

    1979-01-01

    The domestic steel industry, being energy-use intensive, requires between 4 and 5 percent of total annual domestic energy consumption. More than two-thirds of total steel industry energy, however, is derived from coal. During the post-World War II...

  18. TV Energy Consumption Trends and Energy-Efficiency Improvement Options

    E-Print Network [OSTI]

    Park, Won Young

    2011-01-01

    a PDP’s luminous efficacy is the key to saving energy in PDPENERGY STAR-qualified PDP TVs appear to have achieved luminousluminous efficacy (lumens per watt [lm/W]) improves, the energy

  19. Short-Term Energy Carbon Dioxide Emissions Forecasts August 2009

    Reports and Publications (EIA)

    2009-01-01

    Supplement to the Short-Term Energy Outlook. Short-term projections for U.S. carbon dioxide emissions of the three fossil fuels: coal, natural gas, and petroleum.

  20. Biomass Stove Pollution Sam Beck ATOC-3500 Biomass energy accounts for about 15% of the world's primary energy consumption and

    E-Print Network [OSTI]

    Toohey, Darin W.

    , institutions and industries leads to reduced fuel consumption, faster processing, improved product quality's primary energy consumption and about 38% of the primary energy consumption in developing countries Air Pollution due to bad combustion (production of smoke). The improved use of biomass in households

  1. RECENT TRENDS IN EMERGING TRANSPORTATION FUELS AND ENERGY CONSUMPTION

    SciTech Connect (OSTI)

    Bunting, Bruce G

    2012-01-01

    Abundance of energy can be improved both by developing new sources of fuel and by improving efficiency of energy utilization, although we really need to pursue both paths to improve energy accessibility in the future. Currently, 2.7 billion people or 38% of the world s population do not have access to modern cooking fuel and depend on wood or dung and 1.4 billion people or 20% do not have access to electricity. It is estimated that correcting these deficiencies will require an investment of $36 billion dollars annually through 2030. In growing economies, energy use and economic growth are strongly linked, but energy use generally grows at a lower rate due to increased access to modern fuels and adaptation of modern, more efficient technology. Reducing environmental impacts of increased energy consumption such as global warming or regional emissions will require improved technology, renewable fuels, and CO2 reuse or sequestration. The increase in energy utilization will probably result in increased transportation fuel diversity as fuels are shaped by availability of local resources, world trade, and governmental, environmental, and economic policies. The purpose of this paper is to outline some of the recently emerging trends, but not to suggest winners. This paper will focus on liquid transportation fuels, which provide the highest energy density and best match with existing vehicles and infrastructure. Data is taken from a variety of US, European, and other sources without an attempt to normalize or combine the various data sources. Liquid transportation fuels can be derived from conventional hydrocarbon resources (crude oil), unconventional hydrocarbon resources (oil sands or oil shale), and biological feedstocks through a variety of biochemical or thermo chemical processes, or by converting natural gas or coal to liquids.

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

    E-Print Network [OSTI]

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

  3. Energy Consumption Characterization and Reduction Strategies for Milling Machine Tool Use

    E-Print Network [OSTI]

    Diaz, Nancy; E. Redelsheimer; Dornfeld, David

    2011-01-01

    2010): Environmental Analysis of Milling Machine Tool Use inand Reduction Strategies for Milling Machine Tool Use Nancythe energy consumption of milling machine tools during their

  4. Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) | Open

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTIONRobertsdale, AlabamaETEC GmbH JumpEllenville, NewLtd EILEnergy Datadata TypeEnergyFocus IncEnergy

  5. Energy consumption models for ad-hoc mobile Emmanuel Lochin1

    E-Print Network [OSTI]

    Lochin, Emmanuel

    1 Energy consumption models for ad-hoc mobile terminals Emmanuel Lochin1 Anne Fladenmuller1 Jean describes a set of experiments based on ACPI BIOS measurements which evaluate the energy consumption of an IEEE802.11 wireless net- work interface. Based on our ACPI measurements, two models of energy

  6. Reducing Network-on-Chip Energy Consumption Through Spatial Locality Speculation

    E-Print Network [OSTI]

    Grot, Boris

    Reducing Network-on-Chip Energy Consumption Through Spatial Locality Speculation Hyungjun Kim, an efficient communication substrate is critical for meeting performance and energy targets. In this work, we target the root cause of network energy consumption through techniques that re- duce link and router

  7. SmartTecO: Context-Based Ambient Sensing and Monitoring for Optimizing Energy Consumption

    E-Print Network [OSTI]

    Beigl, Michael

    SmartTecO: Context-Based Ambient Sensing and Monitoring for Optimizing Energy Consumption Yong Ding networks and a context awareness system, the acquired data will be interpreted into different energy the actuation mod- ule a certain context, which allows managing and saving the energy consumption of home

  8. Can Mobile-to-Mobile Browser Cache Cooperation Reduce Energy Consumption of

    E-Print Network [OSTI]

    New South Wales, University of

    Can Mobile-to-Mobile Browser Cache Cooperation Reduce Energy Consumption of Internet Access? Abdul find that short-range cache cooperation can reduce 3G browsing energy consumption by 13%. Finally, we for determining the energy performance of mobile- to-mobile cooperative caching schemes. However, to the best

  9. 1. INTRODUCTION Energy consumption and noise emission are the most im-

    E-Print Network [OSTI]

    Podgornik, Rudolf

    1. INTRODUCTION Energy consumption and noise emission are the most im- portant functional into the strategy for the reduction of energy consumption of the drying machine. The difference between various decisions.1 The condenser, whose energy characteris- tics make a particularly important imprint

  10. Abstract--Energy consumption and the concomitant Green House Gases (GHG) emissions of network infrastructures are

    E-Print Network [OSTI]

    Politècnica de Catalunya, Universitat

    Abstract--Energy consumption and the concomitant Green House Gases (GHG) emissions of network on the overall power consumption and on the GHG emissions with just 25% of green energy sources. I. INTRODUCTION]. In the zero carbon approach, renewable (green) energy sources (e.g. sun, wind, tide) are employed and no GHGs

  11. Evaluating Network-Based DoS Attacks Under the Energy Consumption Perspective

    E-Print Network [OSTI]

    Politècnica de Catalunya, Universitat

    with great opportunities for raising the target facility energy consumption and consequently its green house green, energy- sustainable computing paradigms has gained a lot of attention in both the researchEvaluating Network-Based DoS Attacks Under the Energy Consumption Perspective New security issues

  12. Revised: 6 November 1991 Trends in the Consumption of Energy-Intensive Basic Materials

    E-Print Network [OSTI]

    materials consumption patterns on energy use is the recognition that physical units (kilograms) are moreRevised: 6 November 1991 Trends in the Consumption of Energy-Intensive Basic Materials. 1. INTRODUCTION} Industry accounts for 50% of total energy use in developing countries

  13. Energy Consumption Tools Pack Leandro Fontoura Cupertino, Georges DaCosta,

    E-Print Network [OSTI]

    Lefèvre, Laurent

    Resource Manager Energy Efficiency 2 Software development Power consumption of a same functionality varies load Workload classes differ depending on DC type App Monitor App Profiler Resource Manager Energy Efficiency Cupertino, DaCosta, Sayah, Pierson (IRIT) Energy Consumption Tools Pack 4 / 23 #12;Introduction

  14. Investigating the Energy Consumption of a Wireless Network Interface in an Ad Hoc Networking

    E-Print Network [OSTI]

    Sirer, Emin Gun

    Investigating the Energy Consumption of a Wireless Network Interface in an Ad Hoc Networking Environment Laura Marie Feeney, Martin Nilsson Abstract--Energy-aware design and evaluation of network protocols re- quires knowledge of the energy consumption behavior of actual wireless interfaces. But little

  15. On the Trade-off between Energy Consumption and Food Quality Loss in Supermarket Refrigeration Systems

    E-Print Network [OSTI]

    Skogestad, Sigurd

    On the Trade-off between Energy Consumption and Food Quality Loss in Supermarket Refrigeration-off between energy consumption and food quality loss, at varying ambient con- ditions, in supermarket for energy savings without extra loss of food quality is demonstrated. We also show that by utilizing

  16. Balancing Energy Consumption and Food Quality Loss in Supermarket Refrigeration System

    E-Print Network [OSTI]

    Skogestad, Sigurd

    Balancing Energy Consumption and Food Quality Loss in Supermarket Refrigeration System J. Cai and J energy consumption and food quality loss, at varying ambient condition, in a supermarket refrigeration for energy savings without extra loss of food quality. We also show that by utilizing the relatively slow

  17. Energy Consumption and Economic Growth The Case of Australia Hong To a, *

    E-Print Network [OSTI]

    ;3 depend on imports of crude oil, natural gas, and coal for their industrial and residential energy needs energy consumption and economic growth. Peak oil, energy security and climate change have become key

  18. Prey consumption and energy transfer by marine birds in the Gulf of Alaska

    E-Print Network [OSTI]

    Hunt, GL; Drew, GS; Jahncke, J; Piatt, JF

    2005-01-01

    Prey consumption and energy transfer by marine birds in thebut they do remove energy from the marine system throughTo determine energy demand by marine birds in the Gulf of

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels DataEnergyInformation Form EmployeeAvailableExplores Deep Direct Use

  20. Capping the Brown Energy Consumption of Internet Services at Low Cost

    E-Print Network [OSTI]

    Bianchini, Ricardo

    energy" (produced via carbon-intensive means) relative to renewable or "green" energy. This paper their brown energy consumption and lever- age green energy, while respecting their SLAs and minimizing energy-intensive energy as "brown" energy, in contrast with "green" or renewable energy.) We argue that placing caps

  1. New Forecasting Tools Enhance Wind Energy Integration In Idaho and Oregon

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i nAand DOEDepartment ofProgramImportsEnergyForecasting Tools Enhance Wind

  2. DOE Announces Webinars on Real Time Energy Management, Solar Forecasting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative FuelsofProgram:Y-12Power,5Energyof| DepartmentCell ElectricHurricane

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-Inspired Solar FuelTechnologyTel:FebruaryEIA's Today In Energy stories at

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergy A plug-in electricLaboratory | Department ofPotawatomi Community |Barrels3 study

  5. Comfort, Indoor Air Quality, and Energy Consumption in Low Energy Homes

    SciTech Connect (OSTI)

    Englemann, P.; Roth, K.; Tiefenbeck, V.

    2013-01-01

    This report documents the results of an in-depth evaluation of energy consumption and thermal comfort for two potential net zero-energy homes (NZEHs) in Massachusetts, as well as an indoor air quality (IAQ) evaluation performed in conjunction with Lawrence Berkeley National Laboratory (LBNL).

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

    SciTech Connect (OSTI)

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

    2014-04-30

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

  7. Appliance Energy Consumption in Australia | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar Energy LLC Jump to: navigation,Summaries | Open EnergyRoadmap

  8. Energy Consumption in Wireless Sensor Networks is a fundamental issue in terms of functionality and network lifetime. Minimization

    E-Print Network [OSTI]

    Vouyioukas, Demosthenes

    ABSTRACT Energy Consumption in Wireless Sensor Networks is a fundamental issue in terms, wireless sensor networks, energy model, biomedical applications 1. INTRODUCTION The concept of ubiquitous capacities and low energy consumption electronics. Wireless sensor network node functions such as sensing

  9. TV Energy Consumption Trends and Energy-Efficiency Improvement Options

    SciTech Connect (OSTI)

    Park, Won Young; Phadke, Amol; Shah, Nihar; Letschert, Virginie

    2011-07-01

    The SEAD initiative aims to transform the global market by increasing the penetration of highly efficient equipment and appliances. SEAD is a government initiative whose activities and projects engage the private sector to realize the large global energy savings potential from improved appliance and equipment efficiency. SEAD seeks to enable high-level global action by informing the Clean Energy Ministerial dialogue as one of the initiatives in the Global Energy Efficiency Challenge. In keeping with its goal of achieving global energy savings through efficiency, SEAD was approved as a task within the International Partnership for Energy Efficiency Cooperation (IPEEC) in January 2010. SEAD partners work together in voluntary activities to: (1) ?raise the efficiency ceiling? by pulling super-efficient appliances and equipment into the market through cooperation on measures like incentives, procurement, awards, and research and development (R&D) investments; (2) ?raise the efficiency floor? by working together to bolster national or regional policies like minimum efficiency standards; and (3) ?strengthen the efficiency foundations? of programs by coordinating technical work to support these activities. Although not all SEAD partners may decide to participate in every SEAD activity, SEAD partners have agreed to engage actively in their particular areas of interest through commitment of financing, staff, consultant experts, and other resources. In addition, all SEAD partners are committed to share information, e.g., on implementation schedules for and the technical detail of minimum efficiency standards and other efficiency programs. Information collected and created through SEAD activities will be shared among all SEAD partners and, to the extent appropriate, with the global public.As of April 2011, the governments participating in SEAD are: Australia, Brazil, Canada, the European Commission, France, Germany, India, Japan, Korea, Mexico, Russia, South Africa, Sweden, the United Arab Emirates, the United Kingdom, and the United States. More information on SEAD is available from its website at http://www.superefficient.org/.

  10. An Integrated Geovisual Analytics Framework for Analysis of Energy Consumption Data and Renewable Energy Potentials

    SciTech Connect (OSTI)

    Omitaomu, Olufemi A; Maness, Christopher S; Kramer, Ian S; Kodysh, Jeffrey B; Bhaduri, Budhendra L; Steed, Chad A; Karthik, Rajasekar; Nugent, Philip J; Myers, Aaron T

    2012-01-01

    We present an integrated geovisual analytics framework for utility consumers to interactively analyze and benchmark their energy consumption. The framework uses energy and property data already available with the utility companies and county governments respectively. The motivation for the developed framework is the need for citizens to go beyond the conventional utility bills in understanding the patterns in their energy consumption. There is also a need for citizens to go beyond one-time improvements that are often not monitored and measured over time. Some of the features of the framework include the ability for citizens to visualize their historical energy consumption data along with weather data in their location. The quantity of historical energy data available is significantly more than what is available from utility bills. An overlay of the weather data provides users with a visual correlation between weather patterns and their energy consumption patterns. Another feature of the framework is the ability for citizens to compare their consumption on an aggregated basis to that of their peers other citizens living in houses of similar size and age and within the same or different geographical boundaries, such as subdivision, zip code, or county. The users could also compare their consumption to others based on the size of their family and other attributes. This feature could help citizens determine if they are among the best in class . The framework can also be used by the utility companies to better understand their customers and to plan their services. To make the framework easily accessible, it is developed to be compatible with mobile consumer electronics devices.

  11. 2009 Energy Consumption Per Person | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels DataEnergy Webinar: Demonstration ofDepartment ofofAppendices) 2001082009

  12. JOURNAL OF LIGHTWAVE TECHNOLOGY, VOL. 27, NO. 13, JULY 1, 2009 2391 Energy Consumption in Optical IP Networks

    E-Print Network [OSTI]

    Shihada, Basem

    consumes about 0.4% of electricity consumption in broadband-en- abled countries. While the energy and multicast, the power consumption of the Internet could approach 1% of electricity consumption as accessJOURNAL OF LIGHTWAVE TECHNOLOGY, VOL. 27, NO. 13, JULY 1, 2009 2391 Energy Consumption in Optical

  13. On Quality-of-Service and Energy Consumption Tradeoffs in FEC-Encoded Audio Streaming

    E-Print Network [OSTI]

    McKinley, Philip K.

    On Quality-of-Service and Energy Consumption Tradeoffs in FEC-Encoded Audio Streaming Z. Zhou, P. KS 2004), Mon- treal, Canada, June 2004. Abstract This paper addresses the energy consumption of for- ward streams are multicast to mobile computers across a WLAN. Results of these experiments quantify the trade

  14. On Quality-of-Service and Energy Consumption Tradeoffs in FEC-Encoded Audio Streaming

    E-Print Network [OSTI]

    Sadjadi, S. Masoud

    On Quality-of-Service and Energy Consumption Tradeoffs in FEC-Encoded Audio Streaming Z. Zhou, P. K,mckinley,sadjadis}@cse.msu.edu Abstract This paper addresses the energy consumption of for- ward error correction (FEC) protocols as used (WLANs). Ex- periments are described in which FEC-encoded audio streams are multicast to mobile computers

  15. Building Technologies Research and Integration Center Reducing the energy consumption of the nation's buildings is

    E-Print Network [OSTI]

    Pennycook, Steve

    2/21/2011 Building Technologies Research and Integration Center Reducing the energy consumption of the nation's buildings is essential for achieving a sustainable clean energy future and will be an enormous challenge. Buildings account for 40% of the nation's carbon emissions and the consumption of 40% of our

  16. SIMULATING ENERGY CONSUMPTION OF AUXILIARY UNITS IN HEAVY VEHICLES1 Niklas Pettersson, Karl Henrik Johansson

    E-Print Network [OSTI]

    Johansson, Karl Henrik

    SIMULATING ENERGY CONSUMPTION OF AUXILIARY UNITS IN HEAVY VEHICLES1 Niklas Pettersson, Karl Henrik that can be used to evaluate alternative architectures for the electrical system in heavy vehicles. The vehicle model has been validated with respect to the energy consumption of the combustion engine

  17. Energy Consumption in Data Analysis for On-board and Distributed Applications

    E-Print Network [OSTI]

    Kargupta, Hilol

    Energy Consumption in Data Analysis for On-board and Distributed Applications Ruchita Bhargava of Computer Science and Electrical Engineering University of Maryland Baltimore County, MD 21250 Abstract Energy consumption is an important issue in the growing number of data mining and machine learning

  18. Directional versus Omnidirectional Antennas for Energy Consumption and k-Connectivity of

    E-Print Network [OSTI]

    Kranakis, Evangelos

    Directional versus Omnidirectional Antennas for Energy Consumption and k-Connectivity of Networks of directional antennas so that the energy consumption required to maintain k-connectivity of the re- sulting]). Sensor nodes enable autonomy, self-configurability, and self-awareness, in the sense that they can

  19. Minimizing Energy Consumption in IR-UWB Based Wireless Sensor Networks

    E-Print Network [OSTI]

    Heinzelman, Wendi

    Minimizing Energy Consumption in IR-UWB Based Wireless Sensor Networks Tianqi Wang, Wendi communications systems, where transmit power can be flexibly adjusted to minimize the energy consumption [3] [4 Heinzelman and Alireza Seyedi Department of Electrical and Computer Engineering, University of Rochester

  20. Energy Information Administration - Energy Efficiency-Table 5a. Consumption

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun2003 Detailed Tablesof Energy for all

  1. Energy Information Administration - Energy Efficiency-Table 5b. Consumption

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun2003 Detailed Tablesof Energy for allof

  2. Manufacturing Energy Consumption Survey (MECS) - U.S. Energy Information

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural GasNatural GasEIARegional energy challengesLower

  3. Hawaii Energy Strategy: Program guide. [Contains special sections on analytical energy forecasting, renewable energy resource assessment, demand-side energy management, energy vulnerability assessment, and energy strategy integration

    SciTech Connect (OSTI)

    Not Available

    1992-09-01

    The Hawaii Energy Strategy program, or HES, is a set of seven projects which will produce an integrated energy strategy for the State of Hawaii. It will include a comprehensive energy vulnerability assessment with recommended courses of action to decrease Hawaii's energy vulnerability and to better prepare for an effective response to any energy emergency or supply disruption. The seven projects are designed to increase understanding of Hawaii's energy situation and to produce recommendations to achieve the State energy objectives of: Dependable, efficient, and economical state-wide energy systems capable of supporting the needs of the people, and increased energy self-sufficiency. The seven projects under the Hawaii Energy Strategy program include: Project 1: Develop Analytical Energy Forecasting Model for the State of Hawaii. Project 2: Fossil Energy Review and Analysis. Project 3: Renewable Energy Resource Assessment and Development Program. Project 4: Demand-Side Management Program. Project 5: Transportation Energy Strategy. Project 6: Energy Vulnerability Assessment Report and Contingency Planning. Project 7: Energy Strategy Integration and Evaluation System.

  4. Household operational energy consumption in urban China : a multilevel analysis on Jinan

    E-Print Network [OSTI]

    Wang, Dong, M.C.P. Massachusetts Institute of Technology

    2012-01-01

    With decades of economic growth and socio-economic transformation, China's residential sector has seen rapid expansion in energy consumption, and is now the second largest energy consuming sector in the country. Faced with ...

  5. Research on the Statistical Method of Energy Consumption for Public Buildings in China 

    E-Print Network [OSTI]

    Chen, S.; Li, N.

    2006-01-01

    The purpose of this research is to develop a national statistical system for energy consumption data for public buildings in China, in order to provide data support for building energy efficiency work. The framework for a national statistical system...

  6. An Operational Energy Consumption Evaluation Index System for Large Public Buildings 

    E-Print Network [OSTI]

    Li, Y.; Zhang, J.; Sun, D.

    2006-01-01

    Large public buildings have been the emphasis of energy conservation in China. In this paper, the design and operational energy consumption evaluation indices for large public buildings are generalized, their differences and deficiencies...

  7. Window-Related Energy Consumption in the US Residential and Commercial Building Stock

    E-Print Network [OSTI]

    Apte, Joshua; Arasteh, Dariush

    2008-01-01

    related primary energy consumption of today’s US buildingis, the energy savings that would result if today’s entireenergy efficiency that reflect the properties of today’s

  8. U. S. Industrial Energy Consumption and Conservation: Past and Future Perspectives 

    E-Print Network [OSTI]

    Ganeriwal, R; Ross, M. H.

    1980-01-01

    This paper examines U.S. industrial energy consumption and conservation potentials by defining the concept of energy service which, in turn, leads to more precise consideration of various aspects of conservation. It is seen that there are a number...

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

    SciTech Connect (OSTI)

    Edwards, J.D.

    1997-08-01

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

  10. Energy Consumption Simulation and Analysis of Heat Pump Air Conditioning System in Wuhan by the BIN Method 

    E-Print Network [OSTI]

    Wen, Y.; Zhao, F.

    2006-01-01

    to simulate the annual energy consumption of groundwater heat pump systems (GWHPS) for an office building in Wuhan. Its annual energy consumption was obtained and compared with the partner of the air source heat pump systems (ASHPS). The results show...

  11. A Simple Method to Continuous Measurement of Energy Consumption of Tank Less Gas Water Heaters for Commercial Buildings 

    E-Print Network [OSTI]

    Yamaha, M.; Fujita, M.; Miyoshi, T.

    2006-01-01

    energy consumptions of hot water supply in restaurants or residential houses are large amount, guidelines for optimal design are not presented. measurements of energy consumption of tank less gas water heaters very difficult unless gas flow meters...

  12. Evaluating Texas State University Energy Consumption According to Productivity 

    E-Print Network [OSTI]

    Carnes, D.; Hunn, B. D.; Jones, J. W.

    1998-01-01

    by an institution of higher education cannot be measured by a single, readily available number. Data Envelopment Analysis, a tool used primarily in management science, can find "benchmark" input consumption levels for productive entities with multiple inputs...

  13. ,"Total Fuel Oil Consumption (trillion Btu)",,,,,"Fuel Oil Energy...

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

    in this table do not include enclosed malls and strip malls. In the 1999 CBECS, total fuel oil consumption in malls was not statistically significant. (*)Value rounds to zero...

  14. University of Hawai`i Watt Watcher: Energy Consumption Data Analysis

    E-Print Network [OSTI]

    Award No. DE-FC26-06NT42847 Hawai`i Distributed Energy Resource Technologies for Energy Security SubtaskUniversity of Hawai`i Watt Watcher: Energy Consumption Data Analysis Phase I Interim Report Prepared for the U.S. Department of Energy Office of Electricity Delivery and Energy Reliability Under

  15. University of Hawai`i Watt Watcher: Energy Consumption Data Analysis

    E-Print Network [OSTI]

    -FC26-06NT42847 Hawai`i Distributed Energy Resource Technologies for Energy Security Subtask 11University of Hawai`i Watt Watcher: Energy Consumption Data Analysis Phase I Final Report Prepared for the U.S. Department of Energy Office of Electricity Delivery and Energy Reliability Under Award No. DE

  16. Managing the Cost, Energy Consumption, and Carbon Footprint of Internet Services

    E-Print Network [OSTI]

    Singh, Jaswinder Pal

    that enable multi-data-center services to manage their brown energy consumption and leverage green energy by carbon-intensive means as "brown" energy, in contrast with "green" or renewable energy.) We argue. Governments may impose Kyoto-style cap- and-trade schemes to curb carbon emissions and promote green energy

  17. Forecasting the Hourly Ontario Energy Price by Multivariate Adaptive Regression Splines

    E-Print Network [OSTI]

    Cañizares, Claudio A.

    for forecasting the Spanish electricity market prices. On the other hand, ARIMA, dynamic regression and transfer been used to forecast the Spanish market prices [7], [9], Californian market prices [9], Leipzig power have been used for forecasting the Spanish and Californian market prices [11] and the PJM market prices

  18. PSM-throttling: Minimizing Energy Consumption for Bulk Data Communications in WLANs

    E-Print Network [OSTI]

    Chen, Songqing

    PSM-throttling: Minimizing Energy Consumption for Bulk Data Communications in WLANs Enhua Tan1, Lei saving mode (PSM) and its enhancements can reduce power consumption by putting the wireless network/downloading servers. We propose an application-independent protocol, called PSM-throttling. With a quick detection

  19. Comparison of Two Statistical Approaches to Detect Abnormal Building Energy Consumption with Simulation Test 

    E-Print Network [OSTI]

    Lin, G.; Claridge, D.

    2012-01-01

    :?How?to?keep?the?optimal?building?energy? performance?after?Cx? ? Solution:?Whole?building?fault?detection? ? A?process?of?identifying?abnormal?energy?consumption ? Alert?operators?early?after?the?onset?of?significant? increases/decreases?in?consumption 2 Paper Model Fault Detection Dodier and...?Kreider (1999) Neural?network |Energy consumption index| > 1 Seem (2007) Historical measurement Outliers identification Lee and Claridge (2007) Calibrated simulation model (ASHRAE SEAP) Visual?comparison?of?E_Meas and?E_Sim Curtin (2007): ABCAT Calibrated...

  20. ,"Total Fuel Oil Consumption

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

    0. Fuel Oil Consumption (gallons) and Energy Intensities by End Use for Non-Mall Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,,"Fuel Oil Energy Intensity...

  1. ,"Total Fuel Oil Consumption

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

    A. Fuel Oil Consumption (gallons) and Energy Intensities by End Use for All Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,,"Fuel Oil Energy Intensity...

  2. How can we compare or add up our energy consumption?

    Reports and Publications (EIA)

    2012-01-01

    Energy in Brief article on the use of energy conversion factors to compare energy usage from different fuels.

  3. Power to the Plug: An Introduction to Energy, Electricity, Consumption and Efficiency

    SciTech Connect (OSTI)

    DOE / EERE / NEED Project

    2011-06-07

    The NEED Project and the U.S. Department of Energy have collaborated to bring you this educational four-page guide to energy, electricity, consumption and efficiency. It includes, on the last page, a home energy survey to help you analyze your home energy use.

  4. Dynamic Simulation and Analysis of Heating Energy Consumption in a Residential Building 

    E-Print Network [OSTI]

    Liu, J.; Yang, M.; Zhao, X.; Zhu, N.

    2006-01-01

    In winter, much of the building energy is used for heating in the north region of China. In this study, the heating energy consumption of a residential building in Tianjin during a heating period was simulated by using the EnergyPlus energy...

  5. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    and renewable energy technologies, solar photovoltaic (PV)National Renewable Energy Law New Solar Homes Partnershipand promote renewable energy, such as solar energy R&D and

  6. Minimizing Energy Consumption in a Water Distribution System: A Systems Modeling Approach 

    E-Print Network [OSTI]

    Johnston, John

    2011-08-08

    In a water distribution system from groundwater supply, the bulk of energy consumption is expended at pump stations. These pumps pressurize the water and transport it from the aquifer to the distribution system and to elevated storage tanks. Each...

  7. Indoor Conditions Study and Impact on the Energy Consumption for a Large Commercial Building 

    E-Print Network [OSTI]

    Catalina, T.

    2011-01-01

    that were studied using dynamic simulations. The article provides interesting insights of the building indoor conditions (summer/winter comfort), humidity, air temperature, mean operative temperature and energy consumption using hourly climate data. A...

  8. The Operation Management and Energy Consumption Analysis of the District Cooling System 

    E-Print Network [OSTI]

    Xu, Q.; Li, D.; Xu, W.

    2006-01-01

    Based on the investigation of the district cooling system of the Zhongguancun Square in Beijing, we thoroughly analyzed the process of its operation management and the main factors that affect energy consumption. The basis was provided...

  9. Comparative analysis of energy consumption trends in cohousing and alternate housing arrangements

    E-Print Network [OSTI]

    Brown, Jason R. (Jason Robert), 1975-

    2004-01-01

    The sizes of both single-family and multifamily homes have grown steadily in the United States over the last fifty years. During this time, despite more efficient production processes, energy consumption in the country ...

  10. Commissioning to Meet Space Qualification Criteria vs. Energy Consumption Optimization Focused Commissioning 

    E-Print Network [OSTI]

    Sellers, D.; Irvine, L.

    2001-01-01

    In many cases, the commissioning process is driven by space quality criteria rather than by energy consumption and optimization criteria. This is especially true for the HVAC systems serving clean rooms in the semi-conductor and pharmaceuticals...

  11. Dynamic Simulation and Analysis of Factors Impacting the Energy Consumption of Residential Buildings 

    E-Print Network [OSTI]

    Lian, Y.; Hao, Y.

    2006-01-01

    Buildings have a close relationship with climate. There are a lot of important factors that influence building energy consumption such as building shape coefficient, insulation work of building envelope, covered area, and the area ratio of window...

  12. Energy consumption characterization as an input to building management and performance benchmarking - a case study PPT 

    E-Print Network [OSTI]

    Bernardo, H.; Neves, L.; Oliveira, F.; Quintal, E.

    2012-01-01

    performance characterization of each of its buildings, looking specifically at the typology of canteen. Developing building energy performance benchmarking systems enables the comparison of actual consumption of individual buildings against others of the same...

  13. Analysis of Energy Consumption of Duplex Residences in College Station, Texas 

    E-Print Network [OSTI]

    Kim, S. B.; Woods, P. K.

    1998-01-01

    This paper characterizes the variability of energy consumption due to a series of construction, occupant, and weather-related effects in duplex residences in College Station, Texas. In this paper, spline regression was used to estimate cooling...

  14. Scenario analysis of retrofit strategies for reducing energy consumption in Norwegian office buildings

    E-Print Network [OSTI]

    Engblom, Lisa A. (Lisa Allison)

    2006-01-01

    Model buildings were created for simulation to describe typical office buildings from different construction periods. A simulation program was written to predict the annual energy consumption of the buildings in their ...

  15. Comparison of Real World Energy Consumption to Models and Department of Energy Test Procedures

    SciTech Connect (OSTI)

    Goetzler, William; Sutherland, Timothy; Kar, Rahul; Foley, Kevin

    2011-09-01

    This study investigated the real-world energy performance of appliances and equipment as it compared with models and test procedures. The study looked to determine whether the U.S. Department of Energy and industry test procedures actually replicate real world conditions, whether performance degrades over time, and whether installation patterns and procedures differ from the ideal procedures. The study first identified and prioritized appliances to be evaluated. Then, the study determined whether real world energy consumption differed substantially from predictions and also assessed whether performance degrades over time. Finally, the study recommended test procedure modifications and areas for future research.

  16. Reduction in Energy Consumption & Variability in Steel Foundry Operations

    SciTech Connect (OSTI)

    Frank Peters

    2005-05-04

    This project worked to improve the efficiency of the steel casting industry by reducing the variability that occurs because of process and product variation. The project focused on the post shakeout operations since roughly half of the production costs are in this area. These improvements will reduce the amount of variability, making it easier to manage the operation and improve the competitiveness. The reduction in variability will also reduce the need for many rework operations, which will result in a direct reduction of energy usage, particularly by the reduction of repeated heat treatment operations. Further energy savings will be realized from the reduction of scrap and reduced handling. Field studies were conducted at ten steel foundries that represented the U.S. steel casting industry, for a total of over 100 weeks of production observation. These studies quantified the amount of variability, and looked toward determining the source. A focus of the data collected was the grinding operations since this is a major effort in the cleaning room, and it represents the overall casting quality. The grinding was divided into two categories, expected and unexpected. Expected grinding is that in which the location of the effort is known prior to making the casting, such as smoothing parting lines, gates, and riser contacts. Unexpected grinding, which was approximately 80% of the effort, was done to improve the surfaces at weld repair locations, to rectify burnt on sand, and other surface anomalies at random locations. Unexpected grinding represents about 80% of the grinding effort. By quantifying this effort, the project raised awareness within the industry and the industry is continuing to make improvements. The field studies showed that the amount of variation of grinding operations (normalized because of the diverse set of parts studied) was very consistent across the industry. The field studies identified several specific sources that individually contributed to large process variation. This indicates the need for ongoing monitoring of the process and system to quantify the effort being expended. A system to measure the grinding effort was investigated but did not prove to be successful. A weld wire counting system was shown to be very successful in tracking casting quality by monitoring the quantity of weld wire being expended on a per casting basis. Further use of such systems is highly recommended. The field studies showed that the visual inspection process for the casting surface was a potentially large source of process variation. Measurement system analysis studies were conducted at three steel casting producers. The tests measured the consistency of the inspectors in identifying the same surface anomalies. The repeatability (variation of the same operator inspecting the same casting) was found to be relatively consistent across the companies at about 60-70%. However, this is still are very large amount of variation. Reproducibility (variation of different operators inspecting the same casting) was worse, ranging between 20 to 80% at the three locations. This large amount of variation shows that there is a great opportunity for improvement. Falsely identifying anomalies for reworking will cause increased expense and energy consumption. This is particularly true if a weld repair and repeated heat treatment is required. However, not identifying an anomaly could also result in future rework processing, a customer return, or scrap. To help alleviate this problem, casting surface comparator plates were developed and distributed to the industry. These plates are very inexpensive which enables them to be provided to all those involved with casting surface quality, such as operators, inspectors, sales, and management.

  17. Macromodeling and characterization of filesystem energy consumption for diskless embedded systems 

    E-Print Network [OSTI]

    Choudhuri, Siddharth

    2004-09-30

    =ISO-8859-1 MACROMODELING AND CHARACTERIZATION OF FILESYSTEM ENERGY CONSUMPTION FOR DISKLESS EMBEDDED SYSTEMS A Thesis by SIDDHARTH CHOUDHURI Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment... of the requirements for the degree of MASTER OF SCIENCE August 2003 Major Subject: Computer Engineering MACROMODELING AND CHARACTERIZATION OF FILESYSTEM ENERGY CONSUMPTION FOR DISKLESS EMBEDDED SYSTEMS A Thesis by SIDDHARTH CHOUDHURI Submitted to Texas A&M University...

  18. U.S. Lighting Market Characterization Volume I: National Lighting Inventory and Energy Consumption Estimate Final Report

    SciTech Connect (OSTI)

    None, None

    2002-09-01

    Multiyear study to evaluate light sources and identify opportunities for saving energy. This report estimates energy consumption for residential, commercial, industrial, and outdoor stationary.

  19. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    Conservation vs. renewable energy: Cases (sic) studies from2009). Distributed Renewable Energy Operating Impacts anddeployment, National Renewable Energy Lab CPUC (2006). D.

  20. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    et al. (2005). Renewable energy policies and markets in theefficiency and renewable energy policy in the state. Inand Renewable Energy Technology and Policy. Washington,

  1. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    of household energy technologies by installing solar systemssolar systems do not produce more gross energy than the householda solar system, households also become generators of energy

  2. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    in the Race Toward a Clean Energy Future. Sacramento,of a continued effort towards clean energy practices moreunder which they also adopt clean energy technologies and

  3. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    Kaya (2009). "Conservation vs. renewable energy: Cases (sic)in social housing." Renewable and Sustainable Energy ReviewsR. W. (2009). Distributed Renewable Energy Operating Impacts

  4. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    Process in the Adoption of Solar Energy Systems." Journal ofthe diffusion of innovation: Solar energy technology in Sri2010. Washington, DC, Solar Energy Industries Association:

  5. User-needs study for the 1992 Commercial Buildings Energy Consumption Survey

    SciTech Connect (OSTI)

    Not Available

    1992-09-01

    The Commercial Buildings Energy Consumption Survey (CBECS) that is conducted by the Energy Information Administration (EIA) is the primary source of energy data for commercial buildings in the United States. The survey began in 1979 and has subsequently been conducted in 1983, 1986, and 1989. The next survey will cover energy consumption during the year 1992. The building characteristic data will be collected between August 1992 and early December 1992. Requests for energy consumption data are mailed to the energy suppliers in January 1993, with data due by March 1993. Before each survey is sent into the field, the data users` needs are thoroughly assessed. The purpose of this report is to document the findings of that user-needs assessment for the 1992 survey.

  6. The Building Energy Report Card is used to compare the actual annual energy consumption of buildings to a

    E-Print Network [OSTI]

    are performing from an energy efficiency perspective. Buildings that consume less than 95 percent of the energyThe Building Energy Report Card is used to compare the actual annual energy consumption of buildings to a State of Minnesota "target." This target represents the amount of energy that would

  7. The Model Is Not Enough: Understanding Energy Consumption in Mobile Devices

    E-Print Network [OSTI]

    McKinley, Kathryn S.

    The Model Is Not Enough: Understanding Energy Consumption in Mobile Devices James Bornholt also made energy a fundamental concern of software developers. On the desktop, software developers generally ignored energy, but in the mobile environment, battery life is critical to the user experience

  8. URBAN FORM AND LIFE-CYCLE ENERGY CONSUMPTION:1 CASE STUDIES AT THE CITY SCALE2

    E-Print Network [OSTI]

    Kockelman, Kara M.

    1 URBAN FORM AND LIFE-CYCLE ENERGY CONSUMPTION:1 CASE STUDIES AT THE CITY SCALE2 3 Brice G. Nichols it should31 be included in planning analyses. Overall, average life-cycle per-capita energy use ranges from residential and commercial sectors are affected by density.37 38 Keywords: urban energy use, city-level scale

  9. A High-Fidelity Energy Monitoring and Feedback Architecture for Reducing Electrical Consumption in Buildings

    E-Print Network [OSTI]

    Jiang, Xiaofan

    2010-01-01

    architecture that provides fine-grained real-time visibility into building energy consumption enables significant and sustainablearchitecture, to create actionable views of energy usages, which lead to significant and sustainablearchitecture for local energy generation, distribution, and sharing. IEEE Conference on Global Sustainable

  10. Reducing the energy consumption of the nation's buildings is essential for achieving a sustainable

    E-Print Network [OSTI]

    Pennycook, Steve

    Reducing the energy consumption of the nation's buildings is essential for achieving a sustainable that improve the energy efficiency, moisture durability, and environmental sustainability of residential clean energy future and will be an enormous challenge. Buildings account for 40% of the nation's carbon

  11. Autonomous Demand Side Management Based on Game-Theoretic Energy Consumption

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    Autonomous Demand Side Management Based on Game-Theoretic Energy Consumption Scheduling side energy management system among users that takes advantage of a two-way digital communication distributed demand side energy management strategy requires each user to simply apply its best response

  12. Tackling the Load Uncertainty Challenges for Energy Consumption Scheduling in Smart Grid

    E-Print Network [OSTI]

    Wong, Vincent

    both users, by reducing their energy expenses, and utility companies, by improving the peak T Number of time slots a Nominal power of appliance a Ea Total required energy of appliance a a OperatingTackling the Load Uncertainty Challenges for Energy Consumption Scheduling in Smart Grid Pedram

  13. Building Technologies Research and Integration Center Reducing the energy consumption of the nation's buildings is

    E-Print Network [OSTI]

    Oak Ridge National Laboratory

    2/21/2011 Building Technologies Research and Integration Center Reducing the energy consumption of the nation's buildings is essential for achieving a sustainable clean energy future and will be an enormous renewable energy technologies are most economical when using buildings as their deployment platforms

  14. Modelling the impact of user behaviour on heat energy consumption

    E-Print Network [OSTI]

    Combe, Nicola Miss; Harrison, David Professor; Way, Celia Miss

    2011-01-01

    did in reality consume more energy. The study is limited todevelopment consume a comparable amount of energy annually

  15. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    Renewable Energy Council: 2009 Updates and Trends, Anaheim,s 2012 Integrated Energy Policy Report Update maintains the

  16. Modelling the impact of user behaviour on heat energy consumption

    E-Print Network [OSTI]

    Combe, Nicola Miss; Harrison, David Professor; Way, Celia Miss

    2011-01-01

    building design does not guarantee low-energy performance.energy dwellings: the contribution of behaviours to actual performance" Building

  17. Transportation Energy Futures: Combining Strategies for Deep Reductions in Energy Consumption and GHG Emissions (Brochure)

    SciTech Connect (OSTI)

    Not Available

    2013-03-01

    This fact sheet summarizes actions in the areas of light-duty vehicle, non-light-duty vehicle, fuel, and transportation demand that show promise for deep reductions in energy use. Energy efficient transportation strategies have the potential to simultaneously reduce oil consumption and greenhouse gas (GHG) emissions. The Transportation Energy Futures (TEF) project examined how the combination of multiple strategies could achieve deep reductions in GHG emissions and petroleum use on the order of 80%. Led by NREL, in collaboration with Argonne National Laboratory, the project's primary goal was to help inform domestic decisions about transportation energy strategies, priorities, and investments, with an emphasis on underexplored opportunities. TEF findings reveal three strategies with the potential to displace most transportation-related petroleum use and GHG emissions: 1) Stabilizing energy use in the transportation sector through efficiency and demand-side approaches. 2) Using additional advanced biofuels. 3) Expanding electric drivetrain technologies.

  18. Future Air Conditioning Energy Consumption in Developing Countriesand what can be done about it: The Potential of Efficiency in theResidential Sector

    SciTech Connect (OSTI)

    McNeil, Michael A.; Letschert, Virginie E.

    2007-05-01

    The dynamics of air conditioning are of particular interestto energy analysts, both because of the high energy consumption of thisproduct, but also its disproportionate impact on peak load. This paperaddresses the special role of this end use as a driver of residentialelectricity consumption in rapidly developing economies. Recent historyhas shown that air conditioner ownership can grow grows more rapidly thaneconomic growth in warm-climate countries. In 1990, less than a percentof urban Chinese households owned an air conditioner; by 2003 this numberrose to 62 percent. The evidence suggests a similar explosion of airconditioner use in many other countries is not far behind. Room airconditioner purchases in India are currently growing at 20 percent peryear, with about half of these purchases attributed to the residentialsector. This paper draws on two distinct methodological elements toassess future residential air conditioner 'business as usual' electricityconsumption by country/region and to consider specific alternative 'highefficiency' scenarios. The first component is an econometric ownershipand use model based on household income, climate and demographicparameters. The second combines ownership forecasts and stock accountingwith geographically specific efficiency scenarios within a uniqueanalysis framework (BUENAS) developed by LBNL. The efficiency scenariomodule considers current efficiency baselines, available technologies,and achievable timelines for development of market transformationprograms, such as minimum efficiency performance standards (MEPS) andlabeling programs. The result is a detailed set of consumption andemissions scenarios for residential air conditioning.

  19. Using occupancy to reduce energy consumption of buildings

    E-Print Network [OSTI]

    Balaji, Bharathan

    2011-01-01

    Interfaces to Reduce PC Energy Usage. In Proceedings of46.2% of this primary energy usage[9]. Since buildings havecontributors to the total energy usage. Then, we can study

  20. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    studies from Hawaii." Energy Policy 37: 3268-3273. Yunker,2010). "Behavior and Energy Policy." Science 327: 1204-and the UK economy." Energy Policy 35: 4935-4946. Beck, R.

  1. Energy Consumption and Conservation Potential at a Georgia Textile Plant 

    E-Print Network [OSTI]

    Gurta, M. E.; Brown, M. L.

    1994-01-01

    is air-conditioned, the plant is an intensive user of electricity, fossil fuel, and water. Following completion of the energy analysis, recommendations to conserve energy and water resources were developed. Potential energy savings of approximately thirty...

  2. Using occupancy to reduce energy consumption of buildings

    E-Print Network [OSTI]

    Balaji, Bharathan

    2011-01-01

    4.2 Smart Energy Meter . . . . . . 4.2.1 Hardwarewe have developed the Smart Energy Meter to monitor andin the building. Our Smart Energy Meter allows us to study

  3. Using occupancy to reduce energy consumption of buildings

    E-Print Network [OSTI]

    Balaji, Bharathan

    2011-01-01

    for Solar Energy Harvesting Wireless Embedded Systems. Inwww.enocean.com/en/energy- harvesting-wireless/. [11] V. L.a High-Fidelity Wireless Building Energy Auditing Network.

  4. 1999 Commercial Buildings Energy Consumption Survey Detailed Tables

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963 1.969 1.979Coal Consumers THURSDAY, APRIL Consumption and

  5. Commercial Buildings Energy Consumption and Expenditures 1992 - Index Page

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963 1.969 1.979Coal4Cubic Feet)Cubic1992 Consumption and Expenditures

  6. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    a detailed analysis of solar photovoltaics in San Diego: 60.The viability of solar photovoltaics." Energy Policy Jager,types of solar energy systems (photovoltaics systems are

  7. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    10 1.5. The Coordination of Solar and Energytension between solar and energy efficiency remains muchand rates: namely solar and energy efficiency. In our case,

  8. RECENT TRENDS IN EMERGING TRANSPORTATION FUELS AND ENERGY CONSUMPTION...

    Office of Scientific and Technical Information (OSTI)

    can be improved both by developing new sources of fuel and by improving efficiency of energy utilization, although we really need to pursue both paths to improve energy...

  9. Using occupancy to reduce energy consumption of buildings

    E-Print Network [OSTI]

    Balaji, Bharathan

    2011-01-01

    Driven Energy Management for Smart Building Automation” InDriven Energy Management for Smart Building Au- tomation” Innetwork for all our smart building solutions. For this we

  10. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    10 1.5. The Coordination of Solar and Energyintegration of solar and energy efficiency. Currentlytension between solar and energy efficiency remains much

  11. The Building Energy Report Card is used to compare the actual annual energy consumption of buildings to a

    E-Print Network [OSTI]

    Ciocan-Fontanine, Ionut

    The Building Energy Report Card is used to compare the actual annual energy consumption of buildings to a State of Minnesota "target." This target represents the amount of energy that would be consumed by a similar building built to today's State Energy Code. The target takes into account

  12. Retrofits: A Means for Reducing Energy Consumption in Ammonia Manufacture 

    E-Print Network [OSTI]

    LeBlanc, J. R.; Moore, D. O.; Schneider, R. V., III

    1982-01-01

    The manufacture of ammonia is an energy intensive process. Existing large scale plants typically require 33-40 MM BTU (LHV)/ST as energy input. New plant designs can achieve energy levels below 27 MM BTU (LHV)/ST. Therefore, with the cost of energy...

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

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01

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

  14. Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings

    SciTech Connect (OSTI)

    Fridley, David; Fridley, David G.; Zheng, Nina; Zhou, Nan

    2008-03-01

    Buildings represent an increasingly important component of China's total energy consumption mix. However, accurately assessing the total volume of energy consumed in buildings is difficult owing to deficiencies in China's statistical collection system and a lack of national surveys. Official statistics suggest that buildings account for about 19% of China's total energy consumption, while others estimate the proportion at 23%, rising to 30% over the next few years. In addition to operational energy, buildings embody the energy used in the in the mining, extraction, harvesting, processing, manufacturing and transport of building materials as well as the energy used in the construction and decommissioning of buildings. This embodied energy, along with a building's operational energy, constitutes the building's life-cycle energy and emissions footprint. This report first provides a review of international studies on commercial building life-cycle energy use from which data are derived to develop an assessment of Chinese commercial building life-cycle energy use, then examines in detail two cases for the development of office building operational energy consumption to 2020. Finally, the energy and emissions implications of the two cases are presented.

  15. A look at commercial buildings in 1995: Characteristics, energy consumption, and energy expenditures

    SciTech Connect (OSTI)

    1998-10-01

    The commercial sector consists of business establishments and other organizations that provide services. The sector includes service businesses, such as retail and wholesale stores, hotels and motels, restaurants, and hospitals, as well as a wide range of facilities that would not be considered commercial in a traditional economic sense, such as public schools, correctional institutions, and religious and fraternal organizations. Nearly all energy use in the commercial sector takes place in, or is associated with, the buildings that house these commercial activities. Analysis of the structures, activities, and equipment associated with different types of buildings is the clearest way to evaluate commercial sector energy use. The Commercial Buildings Energy Consumption Survey (CBECS) is a national-level sample survey of commercial buildings and their energy suppliers conducted quadrennially (previously triennially) by the Energy Information Administration (EIA). The target population for the 1995 CBECS consisted of all commercial buildings in the US with more than 1,000 square feet of floorspace. Decision makers, businesses, and other organizations that are concerned with the use of energy--building owners and managers, regulators, legislative bodies and executive agencies at all levels of government, utilities and other energy suppliers--are confronted with a buildings sector that is complex. Data on major characteristics (e.g., type of building, size, year constructed, location) collected from the buildings, along with the amount and types of energy the buildings consume, help answer fundamental questions about the use of energy in commercial buildings.

  16. FORECASTS ON THE DARK ENERGY AND PRIMORDIAL NON-GAUSSIANITY OBSERVATIONS WITH THE TIANLAI CYLINDER ARRAY

    SciTech Connect (OSTI)

    Xu, Yidong; Chen, Xuelei [National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012 (China); Wang, Xin [Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218 (United States)

    2015-01-01

    The Tianlai experiment is dedicated to the observation of large-scale structures (LSS) by the 21 cm intensity mapping technique. In this paper, we make forecasts concerning its ability to observe or constrain the dark energy parameters and the primordial non-Gaussianity. From the LSS data, one can use the baryon acoustic oscillation (BAO) and growth rate derived from the redshift space distortion (RSD) to measure the dark energy density and equation of state. The primordial non-Gaussianity can be constrained either by looking for scale-dependent bias in the power spectrum, or by using the bispectrum. Here, we consider three cases: the Tianlai cylinder array pathfinder that is currently being built, an upgrade of the Pathfinder Array with more receiver units, and the full-scale Tianlai cylinder array. Using the full-scale Tianlai experiment, we expect ?{sub w{sub 0}}?0.082 and ?{sub w{sub a}}?0.21 from the BAO and RSD measurements, ?{sub f{sub N{sub L}{sup local}}}?14 from the power spectrum measurements with scale-dependent bias, and ?{sub f{sub N{sub L}{sup local}}}?22 and ?{sub f{sub N{sub L}{sup equil}}}?157 from the bispectrum measurements.

  17. Non-Blocking, Localized Routing Algorithm for Balanced Energy Consumption in Mobile Ad Hoc Networks

    E-Print Network [OSTI]

    Yu, Chansu

    relevant nodes but also to balance individual battery levels. Unbalanced energy usage will result1 Non-Blocking, Localized Routing Algorithm for Balanced Energy Consumption in Mobile Ad Hoc Networks Kyungtae Woo, Chansu Yu, and Dongman Lee Hee Yong Youn Ben Lee School of Engineering Information

  18. Energy Consumption, Efficiency, Conservation, and Greenhouse Gas Mitigation in Japan's Building Sector

    E-Print Network [OSTI]

    2006-01-01

    Solar thermal collectors are not widely used i n Japan, the total energy consumptionsolar shading for a l l openings. End-Use Energy Consumptionenergy consumption for cooling i n office buildings is greater than for heating; as a result, solar

  19. MODELICA LIBRARY FOR SIMULATING ENERGY CONSUMPTION OF AUXILIARY UNITS IN HEAVY VEHICLES1

    E-Print Network [OSTI]

    Johansson, Karl Henrik

    MODELICA LIBRARY FOR SIMULATING ENERGY CONSUMPTION OF AUXILIARY UNITS IN HEAVY VEHICLES1 Niklas vehicle models that can be used to evaluate alternative architectures for the drive of auxiliary units in heavy vehicles. With aid of the simulation models, the energy savings of new designs can be assessed

  20. Capping the Brown Energy Consumption of Internet Services at Low Cost

    E-Print Network [OSTI]

    Capping the Brown Energy Consumption of Internet Services at Low Cost Kien T. Le Ricardo Bianchini Thu D. Nguyen Rutgers University Ozlem Bilgir Margaret Martonosi Princeton University #12;Energy Electricity sources Coal Natural Gas Nuclear Renewables Others 100 105 110 115 120 Nigeria Data Centers Czech

  1. "Table A51. Selected Energy Operating Ratios for Total Energy Consumption for"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981"0. Total Consumption of LPG, Distillate6. Total1. Selected Energy

  2. The water consumption of energy production: an international comparison

    E-Print Network [OSTI]

    Marks, David H.

    Producing energy resources requires significant quantities of fresh water. As an energy sector changes or expands, the mix of technologies deployed to produce fuels and electricity determines the associated burden on ...

  3. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    R. W. (2009). Distributed Renewable Energy Operating Impactsdistributed renewable generation. 15 With respect to existing buildings, however, the perceived tension between solar and energydistributed renewable generators to install and operate these systems cost-effectively. In particular, net energy

  4. Improved Building Energy Consumption with the Help of Modern ICT 

    E-Print Network [OSTI]

    Pietilainen, J.

    2003-01-01

    Kyoto process and the global combat against climate change will require more intensive energy saving efforts especially in all developed countries. Key for the success in building sector is the energy efficiency of the existing building stock...

  5. AEO2011: Energy Consumption by Sector and Source - Mountain ...

    Open Energy Info (EERE)

    comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 8, and contains only the reference...

  6. Using occupancy to reduce energy consumption of buildings

    E-Print Network [OSTI]

    Balaji, Bharathan

    2011-01-01

    and is designed with Smart Home applications in mind.Smart Thermostat: Using Occupancy Sensors to Save Energy in Homes.

  7. Energy Consumption: Costs and the Annual Efficiency Index

    SciTech Connect (OSTI)

    2004-01-01

    This document explains to municipal workers how they can measure and reduce the energy usage of their buildings.

  8. Solar Adoption and Energy Consumption in the Residential Sector

    E-Print Network [OSTI]

    McAllister, Joseph Andrew

    2012-01-01

    clean energy arena, such as the nascent building performance industry, are the subject of large-scale policy initiatives.

  9. Potential for the Use of Energy Savings Performance Contracts to Reduce Energy Consumption and Provide Energy and Cost Savings in Non-Building Applications

    E-Print Network [OSTI]

    Williams, Charles

    2014-01-01

    Consumption and Provide Energy and Cost Savings in Non-applications to save energy and costs. This potential couldof ESPCs to provide energy and cost savings in non-building

  10. An Analysis Framework for Investigating the Trade-offs Between System Performance and Energy Consumption in a Heterogeneous Computing Environment

    E-Print Network [OSTI]

    Maciejewski, Anthony A. "Tony"

    An Analysis Framework for Investigating the Trade-offs Between System Performance and Energy that will allow a system administrator to investigate the trade- offs between system energy consumption be useful to examine the trade-offs between minimizing energy consumption and maximizing computing

  11. This paper introduces a methodology for estimation of energy consumption in peripherals such as audio and video devices.

    E-Print Network [OSTI]

    Simunic, Tajana

    ABSTRACT This paper introduces a methodology for estimation of energy consumption in peripherals such as audio and video devices. Peripherals can be responsible for significant amount of the energy consumption in current embedded systems. We introduce a cycle- accurate energy simulator and profiler capable

  12. Considering the Energy Consumption of Mobile Storage Alternatives Fengzhou Zheng # Nitin Garg # Sumeet Sobti # Chi Zhang # Russell E. Joseph +

    E-Print Network [OSTI]

    Krishnamurthy, Arvind

    Considering the Energy Consumption of Mobile Storage Alternatives Fengzhou Zheng # Nitin Garg it is true that a log­structured storage system can translate its performance benefits into energy savings This paper is motivated by a simple question: what are the energy consumption characteristics of mobile

  13. Comparison of Real World Energy Consumption to Models and DOE...

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

    energy performance of appliances and equipment as it compares with models and test procedures. The study looked to determine whether DOE and industry test procedures...

  14. On Minimizing the Energy Consumption of an Electrical Vehicle

    E-Print Network [OSTI]

    2011-04-19

    Abstract. The electrical vehicle energy management can be expressed ... concerns only hybrid vehicles and discussed about the efficiency of some adapta

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

    Office of Environmental Management (EM)

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

  16. Energy Consumption Characteristics of Light Manufacturing Facilities in The Northern Plains: A Study of Detailed Data from 10 Industrial Energy Audits Conducted in 1993 

    E-Print Network [OSTI]

    Twedt, M.; Bassett, K.

    1994-01-01

    Extensive research has been done on residential and commercial applications of existing technologies for energy conservation. This study specifically examines industrial facilities for energy consumption profiles and ...

  17. Bounding Energy Consumption in Large-Scale MPI Programs

    E-Print Network [OSTI]

    Funk, Shelby Hyatt

    can execute parts of a program at a slower CPU speed to achieve energy savings with a relatively small savings is NP-complete, which has led to many heuristic energy- saving algorithms. To determine how closely these algorithms approach optimal savings, we developed a system that determines a bound on the en

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

    SciTech Connect (OSTI)

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

    2010-01-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. Currently, uncertainties associated with wind and load forecasts, as well as uncertainties associated with random generator outages and unexpected disconnection of supply lines, are not taken into account in power grid operation. Thus, operators have little means to weigh the likelihood and magnitude of upcoming events of power imbalance. In this project, funded by the U.S. Department of Energy (DOE), a framework has been developed for incorporating uncertainties associated with wind and load forecast errors, unpredicted ramps, and forced generation disconnections into the energy management system (EMS) as well as generation dispatch and commitment applications. A new approach to evaluate the uncertainty ranges for the required generation performance envelope including balancing capacity, ramping capability, and ramp duration has been proposed. The approach includes three stages: forecast and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence levels. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis, incorporating all sources of uncertainties of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the “flying brick” technique has been developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation algorithm has been developed to validate the accuracy of the confidence intervals.

  19. Nonparametric models for electricity load forecasting

    E-Print Network [OSTI]

    Genève, Université de

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

  20. Preliminary Analysis of Energy Consumption for Cool Roofing Measures

    SciTech Connect (OSTI)

    Mellot, Joe [The Garland Company; New, Joshua Ryan [ORNL; Sanyal, Jibonananda [ORNL

    2013-01-01

    The spread of cool roofing has been more than prolific over the last decade. Driven by public demand and by government initiatives cool roofing has been a recognized low cost method to reduce energy demand by reflecting sunlight away from structures and back in to the atmosphere. While much of the country can benefit from the use of cool coatings it remains to be seen whether the energy savings described are appropriate in cooler climates. By use of commonly available calculators one can analyze the potential energy savings based on environmental conditions and construction practices.