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Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
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they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
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1

Exploiting Domain Knowledge to Forecast Heating Oil Consumption  

Science Conference Proceedings (OSTI)

The GasDay laboratory at Marquette University provides forecasts of energy consumption. One such service is the Heating Oil Forecaster

George F. Corliss; Tsuginosuke Sakauchi; Steven R. Vitullo; Ronald H. Brown

2011-01-01T23:59:59.000Z

2

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Table 2. Total Energy Consumption, Actual vs. Forecasts Table 3. Total Petroleum Consumption, Actual vs. Forecasts Table 4. Total Natural Gas Consumption, Actual vs. Forecasts Table 5. Total Coal Consumption, Actual vs. Forecasts Table 6. Total Electricity Sales, Actual vs. Forecasts Table 7. Crude Oil Production, Actual vs. Forecasts Table 8. Natural Gas Production, Actual vs. Forecasts Table 9. Coal Production, Actual vs. Forecasts Table 10. Net Petroleum Imports, Actual vs. Forecasts Table 11. Net Natural Gas Imports, Actual vs. Forecasts Table 12. Net Coal Exports, Actual vs. Forecasts Table 13. World Oil Prices, Actual vs. Forecasts Table 14. Natural Gas Wellhead Prices, Actual vs. Forecasts Table 15. Coal Prices to Electric Utilities, Actual vs. Forecasts

3

Vapnik's learning theory applied to energy consumption forecasts in residential buildings  

Science Conference Proceedings (OSTI)

For the purpose of energy conservation, we present in this paper an introduction to the use of support vector (SV) learning machines used as a data mining tool applied to buildings energy consumption data from a measurement campaign. Experiments using ... Keywords: data mining, energy conservation, energy efficiency, predictive modelling, statistical learning theory

Florence Lai; Frederic Magoules; Fred Lherminier

2008-10-01T23:59:59.000Z

4

Energy consumption forecasting in process industry using support vector machines and particle swarm optimization  

Science Conference Proceedings (OSTI)

In this paper, Support Vector Machines (SVMs) are applied in predicting energy consumption in the first phase of oil refining at a particular oil refinery. During cross-validation process of the SVM training Particle Swarm Optimization (PSO) algorithm ... Keywords: energy prediction, particle swarm optimization (PSO), support vector machines (SVM)

Milena R. Petkovi?; Milan R. Rapai?; Boris B. Jakovljevi?

2009-09-01T23:59:59.000Z

5

Load forecasting framework of electricity consumptions for an Intelligent Energy Management System in the user-side  

Science Conference Proceedings (OSTI)

This work presents an electricity consumption-forecasting framework configured automatically and based on an Adaptative Neural Network Inference System (ANFIS). This framework is aimed to be implemented in industrial plants, such as automotive factories, ... Keywords: ANFIS, Forecasting, Genetic algorithm, Intelligent EMS, Modelling

Juan J. Cárdenas; Luis Romeral; Antonio Garcia; Fabio Andrade

2012-04-01T23:59:59.000Z

6

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

SciTech Connect

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.

Poyer, D.A.; Allison, T.

1998-03-01T23:59:59.000Z

7

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation by Susan H. Holte In this paper, the Office of Integrated Analysis and Forecasting (OIAF) of the Energy Information Administration (EIA) evaluates the projections published in the Annual Energy Outlook (AEO), (1) by comparing the projections from the Annual Energy Outlook 1982 through the Annual Energy Outlook 2001 with actual historical values. A set of major consumption, production, net import, price, economic, and carbon dioxide emissions variables are included in the evaluation, updating similar papers from previous years. These evaluations also present the reasons and rationales for significant differences. The Office of Integrated Analysis and Forecasting has been providing an

8

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Title of Paper Annual Energy Outlook Forecast Evaluation Title of Paper Annual Energy Outlook Forecast Evaluation by Susan H. Holte OIAF has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: Natural gas has generally been the fuel with the least accurate forecasts of consumption, production, and prices. Natural gas was the last fossil fuel to be deregulated following the strong regulation of energy markets in the 1970s and early 1980s. Even after deregulation, the behavior

9

Energy consumption and expenditure projections by population group on the basis on the annual energy outlook 2000 forecast.  

SciTech Connect

The changes in the patterns of energy use and expenditures by population group are analyzed by using the 1993 and 1997 Residential Energy Consumption Surveys. Historically, these patterns have differed among non-Hispanic White households, non-Hispanic Black households, and Hispanic households. Patterns of energy use and expenditures are influenced by geographic and metropolitan location, the composition of housing stock, economic and demographic status, and the composition of energy use by end-use category. As a consequence, as energy-related factors change across groups, patterns of energy use and expenditures also change. Over time, with changes in the composition of these factors by population group and their variable influences on energy use, the impact on energy use and expenditures has varied across these population groups.

Poyer, D. A.; Decision and Information Sciences

2001-05-31T23:59:59.000Z

10

Artificial neural networks for electricity consumption forecasting considering climatic factors  

Science Conference Proceedings (OSTI)

This work develops Artificial Neural Networks (ANN) models applied to predict the consumption forecasting considering climatic factors. It is intended to verify the influence of climatic factors on the electricity consumption forecasting through the ... Keywords: artificial neural networks, electricity consumption forecasting

Francisco David Moya Chaves

2010-06-01T23:59:59.000Z

11

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Analysis Papers > Annual Energy Outlook Forecast Evaluation Analysis Papers > Annual Energy Outlook Forecast Evaluation Release Date: February 2005 Next Release Date: February 2006 Printer-friendly version Annual Energy Outlook Forecast Evaluation* Table 1.Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Printer Friendly Version Average Absolute Percent Error Variable AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 AEO82 to AEO2003 AEO82 to AEO2004 Consumption Total Energy Consumption 1.9 2.0 2.1 2.1 2.1 2.1 Total Petroleum Consumption 2.9 3.0 3.1 3.1 3.0 2.9 Total Natural Gas Consumption 7.3 7.1 7.1 6.7 6.4 6.5 Total Coal Consumption 3.1 3.3 3.5 3.6 3.7 3.8 Total Electricity Sales 1.9 2.0 2.3 2.3 2.3 2.4 Production Crude Oil Production 4.5 4.5 4.5 4.5 4.6 4.7

12

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Analysis Papers > Annual Energy Outlook Forecast Evaluation>Tables Analysis Papers > Annual Energy Outlook Forecast Evaluation>Tables Annual Energy Outlook Forecast Evaluation Download Adobe Acrobat Reader Printer friendly version on our site are provided in Adobe Acrobat Spreadsheets are provided in Excel Actual vs. Forecasts Formats Table 2. Total Energy Consumption Excel, PDF Table 3. Total Petroleum Consumption Excel, PDF Table 4. Total Natural Gas Consumption Excel, PDF Table 5. Total Coal Consumption Excel, PDF Table 6. Total Electricity Sales Excel, PDF Table 7. Crude Oil Production Excel, PDF Table 8. Natural Gas Production Excel, PDF Table 9. Coal Production Excel, PDF Table 10. Net Petroleum Imports Excel, PDF Table 11. Net Natural Gas Imports Excel, PDF Table 12. World Oil Prices Excel, PDF Table 13. Natural Gas Wellhead Prices

13

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Modeling and Analysis Papers> Annual Energy Outlook Forecast Evaluation>Tables Modeling and Analysis Papers> Annual Energy Outlook Forecast Evaluation>Tables Annual Energy Outlook Forecast Evaluation Actual vs. Forecasts Available formats Excel (.xls) for printable spreadsheet data (Microsoft Excel required) MS Excel Viewer PDF (Acrobat Reader required Download Acrobat Reader ) Adobe Acrobat Reader Logo Table 2. Total Energy Consumption Excel, PDF Table 3. Total Petroleum Consumption Excel, PDF Table 4. Total Natural Gas Consumption Excel, PDF Table 5. Total Coal Consumption Excel, PDF Table 6. Total Electricity Sales Excel, PDF Table 7. Crude Oil Production Excel, PDF Table 8. Natural Gas Production Excel, PDF Table 9. Coal Production Excel, PDF Table 10. Net Petroleum Imports Excel, PDF Table 11. Net Natural Gas Imports Excel, PDF

14

Modelling of Turkey's net energy consumption using artificial neural network  

Science Conference Proceedings (OSTI)

The main goal of this study is to develop the equations for forecasting net energy consumption (NEC) using artificial neural network (ANN) technique in order to determine the future level of the energy consumption in Turkey. Two different models ... Keywords: Turkey, artificial neural networks, energy forecasting, energy sources, estimation, gross generation, net energy consumption

Adnan Sozen; Erol Arcaklioglu; Mehmet Ozkaymak

2005-04-01T23:59:59.000Z

15

RESIDENTIAL ENERGY CONSUMPTION SURVEY 1997 CONSUMPTION AND ...  

U.S. Energy Information Administration (EIA)

Residential Sector energy Intensities for 1978-1997 using data from EIA Residential Energy Consumption Survey.

16

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation Actual vs. Forecasts Available formats Excel (.xls) for printable spreadsheet data (Microsoft Excel required) PDF (Acrobat Reader required) Table 2. Total Energy Consumption HTML, Excel, PDF Table 3. Total Petroleum Consumption HTML, Excel, PDF Table 4. Total Natural Gas Consumption HTML, Excel, PDF Table 5. Total Coal Consumption HTML, Excel, PDF Table 6. Total Electricity Sales HTML, Excel, PDF Table 7. Crude Oil Production HTML, Excel, PDF Table 8. Natural Gas Production HTML, Excel, PDF Table 9. Coal Production HTML, Excel, PDF Table 10. Net Petroleum Imports HTML, Excel, PDF Table 11. Net Natural Gas Imports HTML, Excel, PDF Table 12. Net Coal Exports HTML, Excel, PDF Table 13. World Oil Prices HTML, Excel, PDF

17

ENERGY DEMAND FORECAST METHODS REPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400 .......................................................................................................................................1-1 ENERGY DEMAND FORECASTING AT THE CALIFORNIA ENERGY COMMISSION: AN OVERVIEW

18

Fuel Consumption - Energy Information Administration  

U.S. Energy Information Administration (EIA)

The Energy Information Administration, Residential Energy Consumption Survey(RTECS), 1994 Fuel Consumption

19

Forecast Energy | Open Energy Information  

Open Energy Info (EERE)

Forecast Energy Forecast Energy Jump to: navigation, search Name Forecast Energy Address 2320 Marinship Way, Suite 300 Place Sausalito, California Zip 94965 Sector Services Product Intelligent Monitoring and Forecasting Services Year founded 2010 Number of employees 11-50 Company Type For profit Website http://www.forecastenergy.net Coordinates 37.865647°, -122.496315° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.865647,"lon":-122.496315,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

20

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Energy Consumption by End-Use Sector Energy Consumption by End-Use Sector In the IEO2005 projections, end-use energy consumption in the residential, commercial, industrial, and transportation sectors varies widely among regions and from country to country. One way of looking at the future of world energy markets is to consider trends in energy consumption at the end-use sector level. With the exception of the transportation sector, which is almost universally dominated by petroleum products at present, the mix of energy use in the residential, commercial, and industrial sectors can vary widely from country to country, depending on a combination of regional factors, such as the availability of energy resources, the level of economic development, and political, social, and demographic factors. This chapter outlines the International Energy Outlook 2005 (IEO2005) forecast for regional energy consumption by end-use sector.

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

International Energy Outlook 2001 - World Energy Consumption  

Gasoline and Diesel Fuel Update (EIA)

World Energy Consumption World Energy Consumption picture of a printer Printer Friendly Version (PDF) This report presents international energy projections through 2020, prepared by the Energy Information Administration, including outlooks for major energy fuels and issues related to electricity, transportation, and the environment. The International Energy Outlook 2001 (IEO2001) presents the Energy Information Administration (EIA) outlook for world energy markets to 2020. Current trends in world energy markets are discussed in this chapter, followed by a presentation of the IEO2001 projections for energy consumption by primary energy source and for carbon emissions by fossil fuel. Uncertainty in the forecast is highlighted by an examination of alternative assumptions about economic growth and their impacts on the

22

UK Energy Consumption by Sector The energy consumption data consists...  

Open Energy Info (EERE)

Consumption by Sector The energy consumption data consists of five spreadsheets: "overall data tables" plus energy consumption data for each of the following...

23

Annual Energy Outlook Forecast Evaluation - Table 1. Forecast Evaluations:  

Gasoline and Diesel Fuel Update (EIA)

Average Absolute Percent Errors from AEO Forecast Evaluations: Average Absolute Percent Errors from AEO Forecast Evaluations: 1996 to 2000 Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Variable 1996 Evaluation: AEO82 to AEO93 1997 Evaluation: AEO82 to AEO97 1998 Evaluation: AEO82 to AEO98 1999 Evaluation: AEO82 to AEO99 2000 Evaluation: AEO82 to AEO2000 Consumption Total Energy Consumption 1.8 1.6 1.7 1.7 1.8 Total Petroleum Consumption 3.2 2.8 2.9 2.8 2.9 Total Natural Gas Consumption 6.0 5.8 5.7 5.6 5.6 Total Coal Consumption 2.9 2.7 3.0 3.2 3.3 Total Electricity Sales 1.8 1.6 1.7 1.8 2.0 Production Crude Oil Production 5.1 4.2 4.3 4.5 4.5

24

Solar Energy Market Forecast | Open Energy Information  

Open Energy Info (EERE)

Solar Energy Market Forecast Solar Energy Market Forecast Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar Energy Market Forecast Agency/Company /Organization: United States Department of Energy Sector: Energy Focus Area: Solar Topics: Market analysis, Technology characterizations Resource Type: Publications Website: giffords.house.gov/DOE%20Perspective%20on%20Solar%20Market%20Evolution References: Solar Energy Market Forecast[1] Summary " Energy markets / forecasts DOE Solar America Initiative overview Capital market investments in solar Solar photovoltaic (PV) sector overview PV prices and costs PV market evolution Market evolution considerations Balance of system costs Silicon 'normalization' Solar system value drivers Solar market forecast Additional resources"

25

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Highlights Highlights World energy consumption is projected to increase by 57 percent from 2002 to 2025. Much of the growth in worldwide energy use in the IEO2005 reference case forecast is expected in the countries with emerging economies. Figure 1. World Marketed Energy Consumptiion by Region, 1970-2025. Need help, contact the National Energy Information Center at 202-586-8800. Figure Data In the International Energy Outlook 2005 (IEO2005) reference case, world marketed energy consumption is projected to increase on average by 2.0 percent per year over the 23-year forecast horizon from 2002 to 2025—slightly lower than the 2.2-percent average annual growth rate from 1970 to 2002. Worldwide, total energy use is projected to grow from 412 quadrillion British thermal units (Btu) in 2002 to 553 quadrillion Btu in

26

Annual Energy Outlook 2001 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Economic Growth World Oil Prices Total Energy Consumption Residential and Commercial Sectors Industrial Sector Transportation Sector Electricity Natural Gas Petroleum Coal Three other organizations—Standard & Poor’s DRI (DRI), the WEFA Group (WEFA), and the Gas Research Institute (GRI) [95]—also produce comprehensive energy projections with a time horizon similar to that of AEO2001. The most recent projections from those organizations (DRI, Spring/Summer 2000; WEFA, 1st Quarter 2000; GRI, January 2000), as well as other forecasts that concentrate on petroleum, natural gas, and international oil markets, are compared here with the AEO2001 projections. Economic Growth Differences in long-run economic forecasts can be traced primarily to

27

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Robert P. Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast

28

Manufacturing Consumption of Energy 1991  

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

J Related EIA Publications on Energy Consumption Energy Information AdministrationManufacturing Consumption of Energy 1991 526 Appendix J Related EIA Publications on Energy...

29

Forecast of the electricity consumption by aggregation of specialized experts; application to Slovakian and French  

E-Print Network (OSTI)

Forecast of the electricity consumption by aggregation of specialized experts; application-term forecast of electricity consumption based on ensemble methods. That is, we use several possibly independent base forecasters and design meta-forecasters which combine the base predictions that are output by them

30

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by Esmeralda Sánchez The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors,

31

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by Esmeralda Sanchez by Esmeralda Sanchez Errata -(7/14/04) The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors, expressed as the percentage difference between the Reference Case projection and actual historic value, shown for every AEO and for each year in the forecast horizon (for a given variable). The historical data are typically taken from the Annual Energy Review (AER). The last column of Table 1 provides a summary of the most recent average absolute forecast errors. The calculation of the forecast error is shown in more detail in Tables 2 through 18. Because data for coal prices to electric generating plants were not available from the AER, data from the Monthly Energy Review (MER), July 2003 were used.

32

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Natural Gas Natural gas is the fastest growing primary energy source in the IEO2005 forecast. Consumption of natural gas is projected to increase by nearly 70 percent between 2002 and 2025, with the most robust growth in demand expected among the emerging economies. Figure 34. World Natural Gas Consumption, 1980-2025 (Trillion Cubic Feet). Need help, contact the National Energy Information Center on 202-586-8800. Figure Data Figure 35. Natural Gas Consumption by Region, 1980-2025 (Trillion Cubic Feet). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 36. Increase in Natural Gas Consumption by Region and Country, 2002-2025. Need help, contact the National Energy Information Center at 202-586-8800. Figure Data

33

Household Energy Consumption and Expenditures  

Reports and Publications (EIA)

Presents information about household end use consumption of energy and expenditures for that energy. These data were collected in the 2005 Residential Energy Consumption Survey (RECS)

Information Center

2008-09-01T23:59:59.000Z

34

Manufacturing Consumption of Energy 1991  

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

3. Energy Consumption in the Manufacturing Sector, 1991 In 1991, the amount of energy consumed in the manufacturing sector was as follows: * Primary Consumption of Energy for All...

35

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Electricity Electricity Electricity consumption nearly doubles in the IEO2005 projection period. The emerging economies of Asia are expected to lead the increase in world electricity use. Figure 58. World Net Electricity Consumption, 2002-2025 (Billion Kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 59. World Net Electricity Consumption by Region, 2002-2025 (Billion Kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data The International Energy Outlook 2005 (IEO2005) reference case projects that world net electricity consumption will nearly double over the next two decades.10 Over the forecast period, world electricity demand is projected to grow at an average rate of 2.6 percent per year, from 14,275 billion

36

Energy-consumption modelling  

SciTech Connect

A highly sophisticated and accurate approach is described to compute on an hourly or daily basis the energy consumption for space heating by individual buildings, urban sectors, and whole cities. The need for models and specifically weather-sensitive models, composite models, and space-heating models are discussed. Development of the Colorado State University Model, based on heat-transfer equations and on a heuristic, adaptive, self-organizing computation learning approach, is described. Results of modeling energy consumption by the city of Minneapolis and Cheyenne are given. Some data on energy consumption in individual buildings are included.

Reiter, E.R.

1980-01-01T23:59:59.000Z

37

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand The demand forecast is the combined product of the hard work and expertise of numerous California Energy previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare

38

Office Buildings - Energy Consumption  

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

Energy Consumption Energy Consumption Office buildings consumed more than 17 percent of the total energy used by the commercial buildings sector (Table 4). At least half of total energy, electricity, and natural gas consumed by office buildings was consumed by administrative or professional office buildings (Figure 2). Table 4. Energy Consumed by Office Buildings for Major Fuels, 2003 All Buildings Total Energy Consumption (trillion Btu) Number of Buildings (thousand) Total Floorspace (million sq. ft.) Sum of Major Fuels Electricity Natural Gas Fuel Oil District Heat All Buildings 4,859 71,658 6,523 3,559 2,100 228 636 All Non-Mall Buildings 4,645 64,783 5,820 3,037 1,928 222 634 All Office Buildings 824 12,208 1,134 719 269 18 128 Type of Office Building

39

Household Vehicles Energy Consumption 1991  

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

methodology used to estimate these statistics relied on data from the 1990 Residential Energy Consumption Survey (RECS), the 1991 Residential Transportation Energy Consumption...

40

Energy conservation and official UK energy forecasts  

SciTech Connect

Behind the latest United Kingdom (UK) official forecasts of energy demand are implicit assumptions about future energy-price elasticities. Mr. Pearce examines the basis of the forecasts and finds that the long-term energy-price elasticities that they imply are two or three times too low. The official forecasts substantially understate the responsiveness of demand to energy price rises. If more-realistic price elasticities were assumed, the official forecasts would imply a zero primary energy-demand growth to 2000. This raises the interesting possibility of a low energy future being brought about entirely by market forces. 15 references, 3 tables.

Pearce, D.

1980-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Annual Energy Outlook with Projections to 2025-Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Annual Energy Outlook 2004 with Projections to 2025 Forecast Comparisons Index (click to jump links) Economic Growth World Oil Prices Total Energy Consumption Electricity Natural Gas Petroleum Coal The AEO2004 forecast period extends through 2025. One other organization—Global Insight, Incorporated (GII)—produces a comprehensive energy projection with a similar time horizon. Several others provide forecasts that address one or more aspects of energy markets over different time horizons. Recent projections from GII and others are compared here with the AEO2004 projections. Economic Growth Printer Friendly Version Average annual percentage growth Forecast 2002-2008 2002-2013 2002-2025 AEO2003 3.2 3.3 3.1 AEO2004 Reference 3.3 3.2 3.0

42

Evaluation of errors in national energy forecasts.  

E-Print Network (OSTI)

??Energy forecasts are widely used by the U.S. government, politicians, think tanks, and utility companies. While short-term forecasts were reasonably accurate, medium and long-range forecasts… (more)

Sakva, Denys

2005-01-01T23:59:59.000Z

43

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand.Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product to the contributing authors listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad

44

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

the entire forecast period, primarily because both weather-adjusted peak and electricity consumption were forecast. Keywords Electricity demand, electricity consumption, demand forecast, weather normalization, annual peak demand, natural gas demand, self-generation, conservation, California Solar Initiative. #12

45

Consumption & Efficiency - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

46

ENERGY CONSUMPTION SURVEY  

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

5 RESIDENTIAL TRANSPORTATION 5 RESIDENTIAL TRANSPORTATION ENERGY CONSUMPTION SURVEY Prepared for: UNITED STATES DEPARTMENT OF ENERGY ENERGY INFORMATION ADMINISTRATION OFFICE OF ENERGY MARKETS AND END USE ENERGY END USE DIVISION RESIDENTIAL AND COMMERCIAL BRANCH WASHINGTON, DC 20585 Prepared by: THE ORKAND CORPORATION 8484 GEORGIA AVENUE SILVER SPRING, MD 20910 October 1986 Contract Number DE-AC01-84EI19658 TABLE OF CONTENTS FRONT MATTER Index to Program Descriptions........................................... vi List of Exhibits ....................................................... viii Acronyms and Abbreviations ............................................. ix SECTION 1: GENERAL INFORMATION ........................................ 1-1 1.1. Summary ....................................................... 1-1

47

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity forecast is the combined product of the hard work and expertise of numerous staff members in the Demand the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast. Miguel Garcia

48

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by by Esmeralda Sanchez The Office of Integrated Analysis and Forecasting has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: * Over the last two decades, there have been many significant changes in laws, policies, and regulations that could not have been anticipated and were not assumed in the projections prior to their implementation. Many of these actions have had significant impacts on energy supply, demand, and prices; however, the

49

Household Vehicles Energy Consumption 1991  

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

DOEEIA-0464(91) Distribution Category UC-950 Household Vehicles Energy Consumption 1991 December 1993 Energy Information Administration Office of Energy Markets and End Use U.S....

50

Manufacturing Consumption of Energy 1994  

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

Detailed Tables 28 Energy Information AdministrationManufacturing Consumption of Energy 1994 1. In previous MECS, the term "primary energy" was used to denote the "first use" of...

51

Residential Energy Consumption Survey:  

Gasoline and Diesel Fuel Update (EIA)

E/EIA-0262/2 E/EIA-0262/2 Residential Energy Consumption Survey: 1978-1980 Consumption and Expenditures Part II: Regional Data May 1981 U.S. Department of Energy Energy Information Administration Assistant Administrator for Program Development Office of the Consumption Data System Residential and Commercial Data Systems Division -T8-aa * N uojssaooy 'SOS^-m (£03) ao£ 5925 'uofSfAfQ s^onpojj aa^ndmoo - aojAaag T BU T3gN am rcoj? aig^IT^^ '(adBx Q-naugBH) TOO/T8-JQ/30Q 30^703 OQ ' d jo :moaj ajqBfT^A^ 3J^ sjaodaa aAoqe aqa jo 's-TZTOO-eoo-Tgo 'ON ^ois odo 'g^zo-via/aoQ 'TBST Sujpjjng rXaAang uojidmnsuoo XSaaug sSu-ppjprig ON ^oo^s OdO '^/ZOZO-Via/aOQ *086T aunr '6L6I ?sn§ny og aunf ' jo suja^Bd uoj^dmnsuoo :XaAjng uo^^dmnsuoQ XSaaug OS '9$ '6-ieTOO- 00-T90 OdD 'S/ZOZO-Via/aOa C

52

Building Energy Software Tools Directory: Energy Usage Forecasts  

NLE Websites -- All DOE Office Websites (Extended Search)

Alphabetically Tools by Platform PC Mac UNIX Internet Tools by Country Related Links Energy Usage Forecasts Energy Usage Forecasts Quick and easy web-based tool that provides...

53

2009 Energy Consumption Per Person  

Energy.gov (U.S. Department of Energy (DOE))

Per capita energy consumption across all sectors of the economy. Click on a state for more information.

54

Annual Energy Outlook Forecast Evaluation-Table 1  

Annual Energy Outlook 2012 (EIA)

Annual Energy Outlook Forecast Evaluation > Table 1 Annual Energy Outlook Forecast Evaluation Table 1. Comparison of Absolute Percent Errors for AEO Forecast Evaluation, 1996 to...

55

Air-Conditioning Effect Estimation for Mid-Term Forecasts of Tunisian Electricity Consumption  

E-Print Network (OSTI)

: Engineering-industry, secondary: Econometrics. 1 Introduction The electric power mid-term loads forecasting: Estimated annual temperature sensitive electricity load components 3 Mid-term load forecasting StatisticalAir-Conditioning Effect Estimation for Mid-Term Forecasts of Tunisian Electricity Consumption

Paris-Sud XI, Université de

56

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Contacts Contacts The International Energy Outlook is prepared by the Energy Information Administration (EIA). General questions concerning the contents of the report should be referred to John J. Conti (john.conti@eia.doe.gov, 202-586-2222), Director, Office of Integrated Analysis and Forecasting. Specific questions about the report should be referred to Linda E. Doman (202/586-1041) or the following analysts: World Energy and Economic Outlook Linda Doman (linda.doman@eia.doe.gov, 202-586-1041) Macroeconomic Assumptions Nasir Khilji (nasir.khilji@eia.doe.gov, 202-586-1294) Energy Consumption by End-Use Sector Residential Energy Use John Cymbalsky (john.cymbalsky@eia.doe.gov, 202-586-4815) Commercial Energy Use Erin Boedecker (erin.boedecker@eia.doe.gov, 202-586-4791)

57

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Evaluation Evaluation Annual Energy Outlook Forecast Evaluation by Esmeralda Sanchez The Office of Integrated Analysis and Forecasting has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: Over the last two decades, there have been many significant changes in laws, policies, and regulations that could not have been anticipated and were not assumed in the projections prior to their implementation. Many of these actions have had significant impacts on energy supply, demand, and prices; however, the impacts were not incorporated in the AEO projections until their enactment or effective dates in accordance with EIA's requirement to remain policy neutral and include only current laws and regulations in the AEO reference case projections.

58

Electrical appliance energy consumption control methods and ...  

Electrical appliance energy consumption control methods and electrical energy consumption systems are described. In one aspect, an electrical appliance energy ...

59

Perils of Long-Range Energy Forecasting: Reflections on Looking Far Ahead  

E-Print Network (OSTI)

! #12;PERILS OF LONG-RANGE ENERGY FORCASTING 255 Fig. 1. Forecasts of the U.S. primary energy notable forecasts of the U.S. primary energy consumption in the year 2000 that were released between have been around energy matters for some time--is the goal of U.S. energy independence charted

Smil, Vaclav

60

Residential Energy Consumption Survey (RECS) - Energy ...  

U.S. Energy Information Administration (EIA)

State Energy Data System ... An Assessment of EIA's Building Consumption Data. ... Commercial Buildings - CBECS. Manufacturing - MECS.

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Manufacturing Consumption of Energy 1994  

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

Energy Information AdministrationManufacturing Consumption of Energy 1994 Introduction The market for natural gas has been changing for quite some time. As part of natural gas...

62

Household Vehicles Energy Consumption 1991  

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

Appendix A How the Survey Was Conducted Introduction The Residential Transportation Energy Consumption Survey (RTECS) was designed by the Energy Information Administration (EIA)...

63

Manufacturing Consumption of Energy 1991  

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

B Survey Design, Implementation, and Estimates Introduction The 1991 Manufacturing Energy Consumption Survey (MECS) has been designed by the Energy Information Administration...

64

Household Vehicles Energy Consumption 1991  

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

a regular basis at the time of the 1990 RECS personal interviews. Electricity: See Main Heating Fuel. Energy Information AdministrationHousehold Vehicles Energy Consumption 1991...

65

Household Vehicles Energy Consumption 1994  

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

AdministrationHousehold Vehicles Energy Consumption 1994 110 Electricity: See Main Heating Fuel. Energy Used in the Home: For electricity or natural gas, the quantity is the...

66

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Table 1. Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Table 1. Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Average Absolute Percent Error Variable AEO82 to AEO98 AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 AEO82 to AEO2003 Consumption Total Energy Consumption 1.7 1.7 1.8 1.9 1.9 2.1 Total Petroleum Consumption 2.9 2.8 2.9 3.0 2.9 2.9 Total Natural Gas Consumption 5.7 5.6 5.6 5.5 5.5 6.5 Total Coal Consumption 3.0 3.2 3.3 3.5 3.6 3.7 Total Electricity Sales 1.7 1.8 1.9 2.4 2.5 2.4 Production Crude Oil Production 4.3 4.5 4.5 4.5 4.5 4.7 Natural Gas Production 4.8 4.7 4.6 4.6 4.4 4.4 Coal Production 3.6 3.6 3.5 3.7 3.6 3.8 Imports and Exports Net Petroleum Imports 9.5 8.8 8.4 7.9 7.4 7.5 Net Natural Gas Imports 16.7 16.0 15.9 15.8 15.8 15.4

67

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

Reports and Publications (EIA)

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.

Tancred Lidderdale

2011-11-30T23:59:59.000Z

68

Forecasting for energy and chemical decision analysis  

SciTech Connect

This paper focuses on uncertainty and bias in forecasts used for major energy and chemical investment decisions. Probability methods for characterizing uncertainty in the forecast are reviewed. Sources of forecasting bias are classified based on the results of relevant psychology research. Examples are drawn from the energy and chemical industry to illustrate the value of explicit characterization of uncertainty and reduction of bias in forecasts.

Cazalet, E.G.

1984-08-01T23:59:59.000Z

69

Residential Energy Consumption Survey Results: Total Energy Consumption,  

Open Energy Info (EERE)

Survey Results: Total Energy Consumption, Survey Results: Total Energy Consumption, Expenditures, and Intensities (2005) Dataset Summary Description The Residential Energy Consumption Survey (RECS) is a national survey that collects residential energy-related data. The 2005 survey collected data from 4,381 households in housing units statistically selected to represent the 111.1 million housing units in the U.S. Data were obtained from residential energy suppliers for each unit in the sample to produce the Consumption & Expenditures data. The Consumption & Expenditures and Intensities data is divided into two parts: Part 1 provides energy consumption and expenditures by census region, population density, climate zone, type of housing unit, year of construction and ownership status; Part 2 provides the same data according to household size, income category, race and age. The next update to the RECS survey (2009 data) will be available in 2011.

70

World energy consumption  

Science Conference Proceedings (OSTI)

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.

NONE

1995-12-01T23:59:59.000Z

71

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work to the contributing authors listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad

72

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped

73

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work and expertise of numerous, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare

74

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped

75

A forecasting system for car fuel consumption using a radial basis function neural network  

Science Conference Proceedings (OSTI)

A predictive system for car fuel consumption using a radial basis function (RBF) neural network is proposed in this paper. The proposed work consists of three parts: information acquisition, fuel consumption forecasting algorithm and performance evaluation. ... Keywords: Artificial neural network, Car fuel consumption, Radial basis function algorithm

Jian-Da Wu; Jun-Ching Liu

2012-02-01T23:59:59.000Z

76

RESIDENTIAL ENERGY CONSUMPTION SURVEY 1997  

U.S. Energy Information Administration (EIA)

RESIDENTIAL ENERGY CONSUMPTION SURVEY 1997. OVERVIEW: MOST POPULOUS STATES ... Homes with air-conditioning: 95%... with a central air-conditioning system: 83%

77

Manufacturing Consumption of Energy 1991  

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

includes descriptions of the 30 groups that comprise the strata of the Manufacturing Energy Consumption Survey. These are the 20 major industrial groups (two-digit SIC) and...

78

2001 Residential Energy Consumption Survey  

U.S. Energy Information Administration (EIA)

Residential Energy Consumption Survey ... Office of Management and Budget, Washington, DC 20503. Form EIA-457A (2001) Form Approval: OMB No. 1905-0092 ...

79

Household Vehicles Energy Consumption 1994  

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

W as hi ng to n, DC DOEEIA-0464(94) Distribution Category UC-950 Household Vehicles Energy Consumption 1994 August 1997 Energy Information Administration Office of Energy Markets...

80

Context-aware parameter estimation for forecast models in the energy domain  

Science Conference Proceedings (OSTI)

Continuous balancing of energy demand and supply is a fundamental prerequisite for the stability and efficiency of energy grids. This balancing task requires accurate forecasts of future electricity consumption and production at any point in time. For ... Keywords: energy, forecasting, maintenance, parameter estimation

Lars Dannecker; Robert Schulze; Matthias Böhm; Wolfgang Lehner; Gregor Hackenbroich

2011-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

Modeling energy consumption of residential furnaces and boilers in U.S. homes  

E-Print Network (OSTI)

ENERGY CONSUMPTION . . . . . . . . . . . . . . . . . . . . . . . . . .28 ENERGY CONSUMPTIONENERGY CONSUMPTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Lutz, James; Dunham-Whitehead, Camilla; Lekov, Alex; McMahon, James

2004-01-01T23:59:59.000Z

82

Residential Energy Consumption Survey (RECS) - Energy Information ...  

U.S. Energy Information Administration (EIA)

Maps by energy source and topic, includes ... Total United States energy consumption in homes has remained relatively stable for many years as increased energy ...

83

Residential Energy Consumption Survey (RECS) - Energy Information ...  

U.S. Energy Information Administration (EIA)

Heating and cooling no longer majority of U.S. home energy use. Source: U.S. Energy Information Administration, Residential Energy Consumption Survey.

84

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

to totals. Source: Energy Information Administration, Office of Energy Markets and End Use, Forms EIA-871A, C, and E of the 2003 Commercial Buildings Energy Consumption Survey....

85

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

may not sum to totals. Source: Energy Information Administration, Office of Energy Markets and End Use, Form EIA-871A of the 2003 Commercial Buildings Energy Consumption Survey....

86

Manufacturing consumption of energy 1991  

SciTech Connect

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.

1994-12-01T23:59:59.000Z

87

Energy Consumption | OpenEI  

Open Energy Info (EERE)

Consumption Consumption Dataset Summary Description This dataset contains hourly load profile data for 16 commercial building types (based off the DOE commercial reference building models) and residential buildings (based off the Building America House Simulation Protocols). This dataset also includes the Residential Energy Consumption Survey (RECS) for statistical references of building types by location. Source Commercial and Residential Reference Building Models Date Released April 18th, 2013 (9 months ago) Date Updated July 02nd, 2013 (7 months ago) Keywords building building demand building load Commercial data demand Energy Consumption energy data hourly kWh load profiles Residential Data Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage

88

Energy consumption of building 39  

E-Print Network (OSTI)

The MIT community has embarked on an initiative to the reduce energy consumption and in accordance with the Kyoto Protocol. This thesis seeks to further expand our understanding of how the MIT campus consumes energy and ...

Hopeman, Lisa Maria

2007-01-01T23:59:59.000Z

89

Manufacturing Consumption of Energy 1994  

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

S Y M n i 1 y 2 i (W i ) (W i 1) , Energy Information Administration, Manufacturing Energy Consumption Survey: Methodological Report 1985. Although this report describes 44...

90

TV Energy Consumption Trends and Energy-Efficiency Improvement Options  

E-Print Network (OSTI)

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

Park, Won Young

2011-01-01T23:59:59.000Z

91

Manufacturing Consumption of Energy 1994  

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

energy data used in this report do not reflect adjustments for losses in electricity generation or transmission. energy data used in this report do not reflect adjustments for losses in electricity generation or transmission. 1 The manufacturing sector is composed of establishments classified in Standard Industrial Classification 20 through 39 of the U.S. economy as defined 2 by the Office of Management and Budget. The manufacturing sector is a part of the industrial sector, which also includes mining; construction; and agriculture, forestry, and fishing. The EIA also conducts energy consumption surveys in the residential, commercial buildings, and residential transportation sectors: the Residential Energy 3 Consumption Survey (RECS); the Commercial Buildings Energy Consumption Survey (CBECS); and, until recently, the Residential Transportation Energy Consumption Survey (RTECS).

92

CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST Demand Forecast report is the product of the efforts of many current and former California Energy Commission staff. Staff contributors to the current forecast are: Project Management and Technical Direction

93

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

Next CBECS will be conducted in 2007 Table C31A. Natural Gas Consumption and Conditional Energy Intensity by Building Size for All Buildings, 2003 Total Natural Gas Consumption...

94

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

Next CBECS will be conducted in 2007 Table C25A. Natural Gas Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003 Total Natural Gas Consumption...

95

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

Next CBECS will be conducted in 2007 Table C32A. Natural Gas Consumption and Conditional Energy Intensity by Year Constructed for All Buildings, 2003 Total Natural Gas Consumption...

96

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

Released: Dec 2006 Next CBECS will be conducted in 2007 Table C10A. Consumption and Gross Energy Intensity by Climate Zonea for All Buildings, 2003 Sum of Major Fuel Consumption...

97

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

Next CBECS will be conducted in 2007 Table C30A. Natural Gas Consumption and Conditional Energy Intensity by Climate Zonea for All Buildings, 2003 Total Natural Gas Consumption...

98

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

Next CBECS will be conducted in 2007 Table C35A. Fuel Oil Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003 Total Fuel Oil Consumption...

99

Residential Energy Consumption Survey (RECS) - Energy ...  

U.S. Energy Information Administration (EIA)

A B C D E F G H I J K L M N O P Q R S T U V W XYZ ‹ Consumption & Efficiency Residential Energy Consumption Survey (RECS) Glossary ...

100

Implementation of a Corporate Energy Accounting and Forecasting Model  

E-Print Network (OSTI)

The development and implementation of a Frito-Lay computer based energy consumption reporting and modeling program is discussed. The system has been designed to relate actual plant energy consumption to a standard consumption which incorporates the effects of weather, product mix, specific equipment types, and other plant factors. The model also provides energy consumption forecasts based on projected production, equipment improvements, and fuels mix. Development of the model began in August 1979 and was preceded by two years of complete auditing of all areas in two manufacturing plants plus specific processing lines in other plants to determine typical energy usage. Extensive analyses of the data resulted in the formulation of standards for the various 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 consumption, of the projected energy use for new plants or plant expansions, and of the effect of process changes on overall energy consumption can be also evaluated.

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

1981-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

H Tables H Tables Appendix H Comparisons With Other Forecasts, and Performance of Past IEO Forecasts for 1990, 1995, and 2000 Forecast Comparisons Three organizations provide forecasts comparable with those in the International Energy Outlook 2005 (IEO2005). The International Energy Agency (IEA) provides “business as usual” projections to the year 2030 in its World Energy Outlook 2004; Petroleum Economics, Ltd. (PEL) publishes world energy forecasts to 2025; and Petroleum Industry Research Associates (PIRA) provides projections to 2015. For this comparison, 2002 is used as the base year for all the forecasts, and the comparisons extend to 2025. Although IEA’s forecast extends to 2030, it does not publish a projection for 2025. In addition to forecasts from other organizations, the IEO2005 projections are also compared with those in last year’s report (IEO2004). Because 2002 data were not available when IEO2004 forecasts were prepared, the growth rates from IEO2004 are computed from 2001.

102

Electricity Demand and Energy Consumption Management System  

E-Print Network (OSTI)

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...

Sarmiento, Juan Ojeda

2008-01-01T23:59:59.000Z

103

Reduces a processor's energy consumption  

E-Print Network (OSTI)

). Clearly, this is energy inefficient and wasteful of energy. 2 More precisely, the faster that a processor decide that energy is being wasted and will decrease the frequency/voltage level. Translation: LowerReduces a processor's energy consumption by up to 70% Diminishes greenhouse gas emissions Improves

104

Wind Energy Forecasting Technology Update: 2004  

Science Conference Proceedings (OSTI)

This report describes the status of wind energy forecasting technology for predicting wind speed and energy generation of wind energy facilities short-term (minutes to hours), intermediate-term (hours to days), and long-term (months to years) average wind speed and energy generation. The information should be useful to companies that are evaluating or planning to incorporate wind energy forecasting into their operations.

2005-04-26T23:59:59.000Z

105

2009 Energy Consumption Per Person | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Field Sites Power Marketing Administration Other Agencies You are here Home 2009 Energy Consumption Per Person 2009 Energy Consumption Per Person 2009 Energy Consumption...

106

Technical and economic analysis of energy efficiency of Chinese room air conditioners  

E-Print Network (OSTI)

the impact on national energy consumption by adoption of thecase forecast of national energy consumption assumes thatcase forecast of national energy consumption assumes the

Fridley, David G.; Rosenquist, Gregory; Jiang, Lin; Li, Aixian; Xin, Dingguo; Cheng, Jianhong

2001-01-01T23:59:59.000Z

107

Manufacturing Consumption of Energy 1994  

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

(MECS) > MECS 1994 Combined Consumption and Fuel Switching (MECS) > MECS 1994 Combined Consumption and Fuel Switching Manufacturing Energy Consumption Survey 1994 (Combined Consumption and Fuel Switching) Manufacturing Energy Consumption Logo Full Report - (file size 5.4 MB) pages:531 Selected Sections (PDF format) Contents (file size 56 kilobytes, 10 pages). Overview (file size 597 kilobytes, 11 pages). Chapters 1-3 (file size 265 kilobytes, 9 pages). Chapter 4 (file size 1,070 kilobytes, 15 pages). Appendix A - Detailed Tables Tables A1 - A8 (file size 1,031 kilobytes, 139 pages). Tables A9 - A23 (file size 746 kilobytes, 119 pages). Tables A24 - A29 (file size 485 kilobytes, 84 pages). Tables A30 - A44 (file size 338 kilobytes, 39 pages). Appendix B (file size 194 kilobytes, 24 pages). Appendix C (file size 116 kilobytes, 16 pages).

108

Building Energy Software Tools Directory: Energy Usage Forecasts  

NLE Websites -- All DOE Office Websites (Extended Search)

Energy Usage Forecasts Energy Usage Forecasts Energy Usage Forecasts Quick and easy web-based tool that provides free 14-day ahead energy usage forecasts based on the degree day forecasts for 1,200 stations in the U.S. and Canada. The user enters the daily non-weather base load and the usage per degree day weather factor; the tool applies the degree day forecast and displays the total energy usage forecast. Helpful FAQs explain the process and describe various options for the calculation of the base load and weather factor. Historical degree day reports and 14-day ahead degree day forecasts are available from the same site. Keywords degree days, historical weather, mean daily temperature, load calculation, energy simulation Validation/Testing Degree day data provided by AccuWeather.com, updated daily at 0700.

109

Monitoring Energy Consumption of Smartphones  

E-Print Network (OSTI)

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.

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

2012-01-01T23:59:59.000Z

110

Manufacturing Consumption of Energy 1994  

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

2(94) 2(94) Distribution Category UC-950 Manufacturing Consumption of Energy 1994 December 1997 Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. ii Energy Information Administration/Manufacturing Consumption of Energy 1994 Contacts This publication was prepared by the Energy Information Administration (EIA) under the general direction of W. Calvin

111

Residential Energy Consumption Survey (RECS) - Analysis ...  

U.S. Energy Information Administration (EIA)

RECS data show decreased energy consumption per household. RECS 2009 — Release date: June 6, 2012. Total United States energy consumption in homes has remained ...

112

Residential Energy Consumption Survey (RECS) - Energy ...  

U.S. Energy Information Administration (EIA)

... video - Keeping Our Homes Warm, released November 2, 2012. Energy consumption per home has steadily declined over the last three decades ...

113

Residential Energy Consumption Survey (RECS) - Energy ...  

U.S. Energy Information Administration (EIA)

This Week in Petroleum › Weekly Petroleum Status Report › Weekly Natural Gas ... Total United States energy consumption in homes has remained relatively ...

114

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

sum to totals. Source: Energy Information Administration, Office of Energy Markets and End Use, Forms EIA-871A, C, and E of the 2003 Commercial Buildings Energy Consumption Survey....

115

Residential Energy Consumption Survey (RECS) - Energy Information...  

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

Heating and cooling no longer majority of U.S. home energy use Pie chart of energy consumption in homes by end uses Source: U.S. Energy Information Administration, Residential...

116

Consumption & Efficiency - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Consumption & Efficiency. Energy use in homes, commercial buildings, ... State Energy Data System: Noncombustible Renewable Energy for 2011 ...

117

energy data + forecasting | OpenEI Community  

Open Energy Info (EERE)

energy data + forecasting energy data + forecasting Home FRED Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in formulating policies and energy plans based on easy to use forecasting tools, visualizations, sankey diagrams, and open data. The platform will live on OpenEI and this community was established to initiate discussion around continuous development of this tool, integrating it with new datasets, and connecting with the community of users who will want to contribute data to the tool and use the tool for planning purposes. Links: FRED beta demo energy data + forecasting Syndicate content 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2084382122

118

Energy Information Administration - Energy Efficiency, energy consumption  

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

Efficiency Efficiency Energy Efficiency energy consumption savings households, buildings, industry & vehicles The Energy Efficiency Page reflects EIA's information on energy efficiency and related information. This site provides an in depth discussion of the concept of energy efficiency and how it is measured, measurement, summaries of formal user meetings on energy efficiency data and measurement, as well as analysis of greenhouse gas emissions as related to energy use and energy efficiency. At the site you will find links to other sources of information, and via a listserv all interested analysts can share ideas, data, and ask for assistance on methodological problems associated with energy use, energy efficiency, and greenhouse gas issues. Contact: Behjat.Hojjati@eia.doe.gov

119

TV Energy Consumption Trends and Energy-Efficiency Improvement Options  

E-Print Network (OSTI)

2008 Standby Power Consumption Report”, March. http://of measurement for the power consumption of audio, video andand Low Power Mode Energy Consumption”, Energy Efficiency in

Park, Won Young

2011-01-01T23:59:59.000Z

120

Annual Energy Outlook Forecast Evaluation 2005  

Gasoline and Diesel Fuel Update (EIA)

Forecast Evaluation 2005 Forecast Evaluation 2005 Annual Energy Outlook Forecast Evaluation 2005 Annual Energy Outlook Forecast Evaluation 2005 * Then Energy Information Administration (EIA) produces projections of energy supply and demand each year in the Annual Energy Outlook (AEO). The projections in the AEO are not statements of what will happen but of what might happen, given the assumptions and methodologies used. The projections are business-as-usual trend projections, given known technology, technological and demographic trends, and current laws and regulations. Thus, they provide a policy-neutral reference case that can be used to analyze policy initiatives. EIA does not propose or advocate future legislative and regulatory changes. All laws are assumed to remain as currently enacted; however, the impacts of emerging regulatory changes, when defined, are reflected.

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

Manufacturing Consumption of Energy 1991--Combined Consumption and Fuel  

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

< < Welcome to the U.S. Energy Information Administration's Manufacturing Web Site. If you are having trouble, call 202-586-8800 for help. Return to Energy Information Administration Home Page. Home > Energy Users > Manufacturing > Consumption and Fuel Switching Manufacturing Consumption of Energy 1991 (Combined Consumption and Fuel Switching) Overview Full Report Tables & Spreadsheets This report presents national-level estimates about energy use and consumption in the manufacturing sector as well as manufacturers' fuel-switching capability. Contact: Stephanie.battle@eia.doe.gov Stephanie Battle Director, Energy Consumption Division Phone: (202) 586-7237 Fax: (202) 586-0018 URL: http://www.eia.gov/emeu/mecs/mecs91/consumption/mecs1a.html File Last Modified: May 25, 1996

122

Household Vehicles Energy Consumption  

Reports and Publications (EIA)

This report provides newly available national and regional data and analyzes the nation's energy use by light-duty vehicles. This release represents the analytical component of the report, with a data component having been released in early 2005.

Mark Schipper

2005-11-30T23:59:59.000Z

123

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Projection Tables (1990-2025) Projection Tables (1990-2025) Formats All Reference Case Data Projection Tables (1 to 14 complete) Excel PDF Table Title Table A1 World Total Primary Energy Consumption by Region, Reference Case Excel PDF Table A2 World Total Energy Consumption by Region and Fuel, Reference Case Excel PDF Table A3 World Gross Domestic Product (GDP) by Region, Reference Case Excel PDF Table A4 World Oil Consumption by Region, Reference Case Excel PDF Table A5 World Natural Gas Consumption by Region, Reference Case Excel PDF Table A6 World Coal Consumption by Region, Reference Case Excel PDF Table A7 World Nuclear Energy Consumption by Region, Reference Case Excel PDF Table A8 World Consumption of Hydroelectricity and Other Renewable Energy by Region, Reference Case Excel PDF Table A9 World Net Electricity Consumption by Region, Reference Case

124

Energy Information Administration - Transportation Energy Consumption by  

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

Energy Consumption Energy Consumption Transportation Energy Consumption Surveys energy used by vehicles EIA conducts numerous energy-related surveys and other information programs. In general, the surveys can be divided into two broad groups: supply surveys, directed to the suppliers and marketers of specific energy sources, that measure the quantities of specific fuels produced for and/or supplied to the market; and consumption surveys, which gather information on the types of energy used by consumer groups along with the consumer characteristics that are associated with energy use. In the transportation sector, EIA's core consumption survey was the Residential Transportation Energy Consumption Survey. RTECS belongs to the consumption group because it collects information directly from the consumer, the household. For roughly a decade, EIA fielded the RTECS--data were first collected in 1983. This survey, fielded for the last time in 1994, was a triennial survey of energy use and expenditures, vehicle miles-traveled (VMT), and vehicle characteristics for household vehicles. For the 1994 survey, a national sample of more than 3,000 households that own or use some 5,500 vehicles provided data.

126

Annual Energy Outlook Forecast Evaluation 2004  

Gasoline and Diesel Fuel Update (EIA)

2004 2004 * The Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) has produced annual evaluations of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and replacing the historical year of data with the most recent. The forecast evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute percent errors for several of the major variables for AEO82 through AEO2004. (There is no report titled Annual Energy Outlook 1988 due to a change in the naming convention of the AEOs.) The average absolute percent error is the simple mean of the absolute values of the percentage difference between the Reference Case projection and the

127

Residential Energy Consumption Survey (RECS) - Energy Information  

NLE Websites -- All DOE Office Websites (Extended Search)

Consumption Survey (RECS) - U.S. Energy Information Consumption Survey (RECS) - U.S. Energy Information Administration (EIA) U.S. Energy Information Administration - EIA - Independent Statistics and Analysis Sources & Uses Petroleum & Other Liquids Crude oil, gasoline, heating oil, diesel, propane, and other liquids including biofuels and natural gas liquids. Natural Gas Exploration and reserves, storage, imports and exports, production, prices, sales. Electricity Sales, revenue and prices, power plants, fuel use, stocks, generation, trade, demand & emissions. Consumption & Efficiency Energy use in homes, commercial buildings, manufacturing, and transportation. Coal Reserves, production, prices, employ- ment and productivity, distribution, stocks, imports and exports. Renewable & Alternative Fuels

128

Mathematical and computer modelling reports: Modeling and forecasting energy markets with the intermediate future forecasting system  

Science Conference Proceedings (OSTI)

This paper describes the Intermediate Future Forecasting System (IFFS), which is the model used to forecast integrated energy markets by the U.S. Energy Information Administration. The model contains representations of supply and demand for all of the ...

Frederic H. Murphy; John J. Conti; Susan H. Shaw; Reginald Sanders

1989-09-01T23:59:59.000Z

129

Federal Energy Management Program: Data Center Energy Consumption Trends  

NLE Websites -- All DOE Office Websites (Extended Search)

Data Center Energy Data Center Energy Consumption Trends to someone by E-mail Share Federal Energy Management Program: Data Center Energy Consumption Trends on Facebook Tweet about Federal Energy Management Program: Data Center Energy Consumption Trends on Twitter Bookmark Federal Energy Management Program: Data Center Energy Consumption Trends on Google Bookmark Federal Energy Management Program: Data Center Energy Consumption Trends on Delicious Rank Federal Energy Management Program: Data Center Energy Consumption Trends on Digg Find More places to share Federal Energy Management Program: Data Center Energy Consumption Trends on AddThis.com... Sustainable Buildings & Campuses Operations & Maintenance Greenhouse Gases Water Efficiency Data Center Energy Efficiency Energy Consumption Trends

130

Renewable Energy Consumption for Nonelectric Use by Energy Use...  

Open Energy Info (EERE)

Renewable Energy Consumption for Nonelectric Use by Energy Use Sector and Energy Source, 2004 - 2008 This dataset provides annual renewable energy consumption (in quadrillion Btu)...

131

Historical Renewable Energy Consumption by Energy Use Sector...  

Open Energy Info (EERE)

Historical Renewable Energy Consumption by Energy Use Sector and Energy Source, 1989-2008 Provides annual renewable energy consumption by source and end use between 1989 and 2008....

132

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

NLE Websites -- All DOE Office Websites (Extended Search)

TV Energy Consumption Trends and Energy-Efficiency Improvement Options Title TV Energy Consumption Trends and Energy-Efficiency Improvement Options Publication Type Report LBNL...

133

Manufacturing Consumption of Energy 1994  

Gasoline and Diesel Fuel Update (EIA)

Energy Information Administration/Manufacturing Consumption of Energy 1994 Energy Information Administration/Manufacturing Consumption of Energy 1994 Introduction The market for natural gas has been changing for quite some time. As part of natural gas restructuring, gas pipelines were opened to multiple users. Manufacturers or their representatives could go directly to the wellhead to purchase their natural gas, arrange the transportation, and have the natural gas delivered either by the local distribution company or directly through a connecting pipeline. More recently, the electricity markets have been undergoing change. When Congress passed the Energy Policy Act of 1992, requirements were included not only to open access to the ownership of electricity generation, but also to open access to the transmission lines so that wholesale trade in electricity would be possible. Now several States, including California and

134

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Low Economic Growth Case Projection Tables (1990-2025) Low Economic Growth Case Projection Tables (1990-2025) Formats Low Economic Growth Case Data Projection Tables (1 to 13 complete) Excel PDF Table Title Table C1 World Total Primary Energy Consumption by Region, Low Economic Growth Case Excel PDF Table C2 World Total Energy Consumption by Region and Fuel, Low Economic Growth Case Excel PDF Table C3 World Gross Domestic Product (GDP) by Region, Low Economic Growth Case Excel PDF Table C4 World Oil Consumption by Region, Low Economic Growth Case Excel PDF Table C5 World Natural Cas Consumption by Region, Low Economic Growth Case Excel PDF Table C6 World Coal Consumption by Region, Low Economic Growth Case Excel PDF Table C7 World Nuclear Energy Consumption by Region, Low Economic Growth Case Excel PDF Table C8 World Consumption of Hydroelectricity and Other Renewable Energy by Region, Low Economic Growth Case

135

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

High Economic Growth Case Projection Tables (1990-2025) High Economic Growth Case Projection Tables (1990-2025) Formats High Economic Growth Case Data Projection Tables (1 to 13 complete) Excel PDF Table Title Table B1 World Total Primary Energy Consumption by Region, High Economic Growth Case Excel PDF Table B2 World Total Energy Consumption by Region and Fuel, High Economic Growth Case Excel PDF Table B3 World Gross Domestic Product (GDP) by Region, High Economic Growth Case Excel PDF Table B4 World Oil Consumption by Region, High Economic Growth Case Excel PDF Table B5 World Natural Cas Consumption by Region, High Economic Growth Case Excel PDF Table B6 World Coal Consumption by Region, High Economic Growth Case Excel PDF Table B7 World Nuclear Energy Consumption by Region, High Economic Growth Case Excel PDF Table B8 World Consumption of Hydroelectricity and Other Renewable Energy by Region, High Economic Growth Case

136

The 1997 Residential Energy Consumption Survey -- Two Decades  

U.S. Energy Information Administration (EIA)

1997 Residential Energy Consumption Survey presents two decades of changes in energy consumption related Household Characteristics

137

TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY  

E-Print Network (OSTI)

CALIFORNIA 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 has developed longterm forecasts of transportation energy demand as well as projected ranges

138

Manufacturing Consumption of Energy 1994  

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

E E U.S. Census Regions and Divisions 489 Energy Information Administration/Manufacturing Consumption of Energy 1994 Source: U.S. Department of Commerce, Bureau of the Census, Statistical Abstract of the United States,1996 (Washington, DC, October 1996), Figure 1. Appendix E U.S. Census Regions and Divisions Appendix F Descriptions of Major Industrial Groups and Selected Industries Executive Office of the President, Office of Management and Budget, Standard Industrial Classification Manual, 1987, pp. 67-263. 54 493 Energy Information Administration/Manufacturing Consumption of Energy 1994 Appendix F Descriptions of Major Industrial Groups and Selected Industries This appendix contains descriptions of industrial groups and selected industries taken from the Standard Industrial

139

Manufacturing Consumption of Energy 1994  

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

Manufacturing Manufacturing Energy Consumption Survey Forms Form EIA-846A (4-6-95) U.S. Department of Commerce Bureau of the Census Acting as Collecting and Compiling Agent For 1994 MANUFACTURING ENERGY CONSUMPTION SURVEY Public reporting burden for this collection of information is estimated to average 9 hours per response, including the time of reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to the Energy Information Administration, Office of Statistical Standards, EI-73, 1707 H-Street, NW, Washington, DC 20585; and to the Office of Information and Regulatory Affairs, Office of

140

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

Released: Dec 2006 Next CBECS will be conducted in 2007 Table C12A. Consumption and Gross Energy Intensity by Year Constructed for Sum of Major Fuels for All Buildings, 2003 Sum of...

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

Released: Dec 2006 Next CBECS will be conducted in 2007 Table C3A. Consumption and Gross Energy Intensity for Sum of Major Fuels for All Buildings, 2003 All Buildings Sum of Major...

142

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

Next CBECS will be conducted in 2007 Table C29A. Natural Gas Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 3 Total Natural Gas...

143

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

Released: Dec 2006 Next CBECS will be conducted in 2007 Table C7A. Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for All Buildings, 2003: Part 1...

144

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

Next CBECS will be conducted in 2007 Table C28A. Natural Gas Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 2 Total Natural Gas...

145

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

Next CBECS will be conducted in 2007 Table C27A. Natural Gas Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 1 Total Natural Gas...

146

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

Released: Dec 2006 Next CBECS will be conducted in 2007 Table C9A. Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for All Buildings, 2003: Part 3...

147

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

Released: Dec 2006 Next CBECS will be conducted in 2007 Table C11A. Consumption and Gross Energy Intensity by Building Size for Sum of Major Fuels for All Buildings, 2003 Sum of...

148

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

Released: Dec 2006 Next CBECS will be conducted in 2007 Table C5A. Consumption and Gross Energy Intensity by Census Region for Sum of Major Fuels for All Buildings, 2003 Sum of...

149

Price and Load Forecasting in Volatile Energy Markets  

Science Conference Proceedings (OSTI)

With daily news stories about wildly fluctuating electricity prices and soaring natural gas prices, forecasters' responsibilities are expanding, visibility is increasing, and pressure exists to produce more frequent forecasts and more kinds of forecasts. The proceedings of EPRI's 13th Forecasting Symposium, held November 13-15 in Nashville, Tennessee, address current forecasting issues and developments, as well as explain the role that forecasters have played in recent events in energy markets.

2001-12-05T23:59:59.000Z

150

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST forecast is the combined product of the hard work and expertise of numerous staff members in the Demand prepared the residential sector forecast. Mohsen Abrishami prepared the commercial sector forecast. Lynn

151

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

U.S. Energy Information Administration (EIA)

How can we compare or add up our energy consumption? To compare or aggregate energy consumption across different energy sources like oil, natural gas, ...

152

Table CT1. Energy Consumption Estimates for Major Energy Sources ...  

U.S. Energy Information Administration (EIA)

R A D O. U.S. Energy Information Administration State Energy Data 2011: Consumption 89 Table CT6. Industrial Sector Energy Consumption Estimates, Selected Years, 1960 ...

153

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

U.S. Energy Information Administration (EIA)

How can we compare or add up our energy consumption? To compare or aggregate energy consumption across different energy sources like oil, natural gas, and electricity ...

154

Table CT1. Energy Consumption Estimates for Major Energy ...  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration State Energy Data 2011: Consumption 365 Table CT2. Primary Energy Consumption Estimates, Selected Years, 1960-2011, North ...

155

Modelling Energy Consumption in China  

E-Print Network (OSTI)

Energy consumption in China has attracted considerable research interest since the middle 1990s. This is largely prompted by the environmental ramifications of the extensive use of fossil fuels in the country to propel two decades of high economic growth. Since the late 1980s, there has been an increasing awareness on the part of the Chinese government of the imperative for the balance of economic growth and environmental protection. The government has since taken various measures ranging from encouraging energy-saving practice, controlling waste discharges to financing R & D programs on improving energy efficiency. Against this backdrop has seen a constant decline of the energy intensity of the economy, measured as the ratio of total energy consumed in standard coal equivalent to the real GDP since 1989. Using the 1987 and 1997 input-output tables for China, the present study examines the impact of technical and structural changes in the economy on industry fuel consumption over the 10-year period. Technical changes are reflected in changes in direct input-output coefficients, which capture the technical evolvement of intermediate production processes. Structural changes refer to shifts in the pattern of final demand for energy, including the import and export composition of various fuels. Six fuels are included in the study, namely, coal, oil, natural gas, electricity, petroleum and coke and gas, which cover all of the energy types available in the input-output tables. It is found that the predominant force of falling energy intensity was changes in direct energy input requirements in various industries. Such changes were responsible for a reduction in the consumption of four of the six fuels per unit of total output. Structural changes were not conducive for improv...

Baiding Hu Department; Baiding Hu

2004-01-01T23:59:59.000Z

156

Household vehicles energy consumption 1994  

SciTech Connect

Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use some 6,000 vehicles provided information to describe vehicle stock, vehicle-miles traveled, energy end-use consumption, and energy expenditures for personal vehicles. The survey results represent the characteristics of the 84.9 million households that used or had access to vehicles in 1994 nationwide. (An additional 12 million households neither owned or had access to vehicles during the survey year.) To be included in then RTECS survey, vehicles must be either owned or used by household members on a regular basis for personal transportation, or owned by a company rather than a household, but kept at home, regularly available for the use of household members. Most vehicles included in the RTECS are classified as {open_quotes}light-duty vehicles{close_quotes} (weighing less than 8,500 pounds). However, the RTECS also includes a very small number of {open_quotes}other{close_quotes} vehicles, such as motor homes and larger trucks that are available for personal use.

NONE

1997-08-01T23:59:59.000Z

157

Projecting household energy consumption within a conditional demand framework  

SciTech Connect

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Teotia, A.; Poyer, D.

1991-01-01T23:59:59.000Z

158

Projecting household energy consumption within a conditional demand framework  

Science Conference Proceedings (OSTI)

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Teotia, A.; Poyer, D.

1991-12-31T23:59:59.000Z

159

Consumption & Efficiency - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Energy Information Administration ... Annual state-level estimates of consumption for hydroelectric power, wind, geothermal, and solar energy. Annual Energy Outlook 2013.

160

All Consumption Tables - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Table C1. Energy Consumption Overview: Estimates by Energy Source and End-Use Sector, 2009 (Trillion Btu) State Total Energy b Sources End-Use Sectors a

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Manufacturing Consumption of Energy 1994  

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

A24. A24. Total Inputs of Energy for Heat, Power, and Electricity Generation by Program Sponsorship, Industry Group, Selected Industries, and Type of Energy- Management Program, 1994: Part 1 (Estimates in Trillion Btu) See footnotes at end of table. Energy Information Administration/Manufacturing Consumption of Energy 1994 285 SIC Management Any Type of Sponsored Self-Sponsored Sponsored Sponsored Code Industry Group and Industry Program Sponsorship Involvement Involvement Involvement Involvement a No Energy Electric Utility Government Third Party Type of Sponsorship of Management Programs (1992 through 1994) RSE Row Factors Federal, State, or Local RSE Column Factors: 0.7 1.1 1.0 0.7 1.9 0.9 20-39 ALL INDUSTRY GROUPS Participation in One or More of the Following Types of Programs . .

162

State energy data report 1992: Consumption estimates  

SciTech Connect

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.

Not Available

1994-05-01T23:59:59.000Z

163

Residential Energy Consumption Survey Data Tables  

U.S. Energy Information Administration (EIA)

Below are historical data tables from the Residential Energy Consumption Survey (RECS). These tables cover the total number of households ...

164

Energy Consumption and Expenditures RECS 2001  

U.S. Energy Information Administration (EIA)

Water Heating. Space Heating. Appliances. Air-Conditioning. About the Data. Tables: Total Energy Consumption in U.S ...

165

Annual Energy Outlook 2006 with Projections to 2030 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Annual Energy Outlook 2006 with Projections to 2030 Only GII produces a comprehensive energy projection with a time horizon similar to that of AEO2006. Other organizations address one or more aspects of the energy markets. The most recent projection from GII, as well as others that concentrate on economic growth, international oil prices, energy consumption, electricity, natural gas, petroleum, and coal, are compared here with the AEO2006 projections. Economic Growth In the AEO2006 reference case, the projected growth in real GDP, based on 2000 chain-weighted dollars, is 3.0 percent per year from 2004 to 2030 (Table 19). For the period from 2004 to 2025, real GDP growth in the AEO2006 reference case is similar to the average annual growth projected in AEO2005. The AEO2006 projections of economic growth are based on the August short-term forecast of GII, extended by EIA through 2030 and modified to reflect EIAÂ’s view on energy prices, demand, and production.

166

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022  

E-Print Network (OSTI)

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022 AUGUST 2011 CEC-200-2011-011-SD CALIFORNIA or adequacy of the information in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast forecast. Bryan Alcorn and Mehrzad Soltani Nia prepared the industrial forecast. Miguel Garcia- Cerrutti

167

Household Vehicles Energy Consumption 1991  

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

Detailed Detailed Tables The following tables present detailed characteristics of vehicles in the residential sector. Data are from the 1991 Residential Transportation Energy Consumption Survey. The "Glossary" contains the definitions of terms used in the tables. Table Organization The "Detailed Tables" section consists of three types of tables: (1) Tables of totals such as number of vehicle miles traveled (VMT) or gallons consumed; (2) Tables of per household statistics such as VMT per household; and (3) Tables of per vehicle statistics such as vehicle fuel consumption per vehicle. The tables have been grouped together by specific topics such as model year data, or family income data to facilitate finding related information. The Quick-Reference Guide to the detailed tables indicates major topics of each table. Row and Column Factors These tables present estimates

168

Household Vehicles Energy Consumption 1991  

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

1. 1. Introduction The purpose of this report is to provide information on the use of energy in residential vehicles in the 50 States and the District of Columbia. Included are data about: the number and type of vehicles in the residential sector, the characteristics of those vehicles, the total annual Vehicle Miles Traveled (VMT), the per household and per vehicle VMT, the vehicle fuel consumption and expenditures, and vehicle fuel efficiencies. The Energy Information Administration (EIA) is mandated by Congress to collect, analyze, and disseminate impartial, comprehensive data about energy--how much is produced, who uses it, and the purposes for which it is used. To comply with this mandate, EIA collects energy data from a variety of sources covering a range of topics 1 . Background The data for this report are based on the household telephone interviews from the 1991 RTECS, conducted

169

Manufacturing Consumption of Energy 1994  

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

Manufacturing Manufacturing Sector Overview 1991-1994 Energy Information Administration/Manufacturing Consumption of Energy 1994 xiii Why Do We Investigate Energy Use in the Manufacturing Sector? What Data Do EIA Use To Investigate Energy Use in the Manufacturing Sector? In 1991, output in the manufactur- ing sector fell as the country went into a recession. After 1991, however, output increased as the country slowly came out of the recession. Between 1991 and 1994, manufacturers, especially manu- facturers of durable goods such as steel and glass, experienced strong growth. The industrial production index for durable goods during the period increased by 21 percent. Real gross domestic product for durable goods increased a corre- sponding 16 percent. The growth of nondurables was not as strong-- the production index increased by only 9 percent during this time period.

170

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Oil Markets Oil Markets IEO2005 projects that world crude oil prices in real 2003 dollars will decline from their current level by 2010, then rise gradually through 2025. In the International Energy Outlook 2005 (IEO2005) reference case, world demand for crude oil grows from 78 million barrels per day in 2002 to 103 million barrels per day in 2015 and to just over 119 million barrels per day in 2025. Much of the growth in oil consumption is projected for the emerging Asian nations, where strong economic growth results in a robust increase in oil demand. Emerging Asia (including China and India) accounts for 45 percent of the total world increase in oil use over the forecast period in the IEO2005 reference case. The projected increase in world oil demand would require an increment to world production capability of more than 42 million barrels per day relative to the 2002 crude oil production capacity of 80.0 million barrels per day. Producers in the Organization of Petroleum Exporting Countries (OPEC) are expected to be the major source of production increases. In addition, non-OPEC supply is expected to remain highly competitive, with major increments to supply coming from offshore resources, especially in the Caspian Basin, Latin America, and deepwater West Africa. The estimates of incremental production are based on current proved reserves and a country-by-country assessment of ultimately recoverable petroleum. In the IEO2005 oil price cases, the substantial investment capital required to produce the incremental volumes is assumed to exist, and the investors are expected to receive at least a 10-percent return on investment.

171

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Projections by End-Use Sector and Region Tables (2002-2025) Projections by End-Use Sector and Region Tables (2002-2025) Formats Reference Case Projections by End-Use Sector and Region Data Tables (1 to 15 complete) Excel PDF Table Title Table D1 Delivered Energy Consumption in the United States by End-Use Sector and Fuel Excel PDF Table D2 Delivered Energy Consumption in Canada by End-Use Sector and Fuel Excel PDF Table D3 Delivered Energy Consumption in Mexico by End-Use Sector and Fuel Excel PDF Table D4 Delivered Energy Consumption in Western Europe by End-Use Sector and Fuel Excel PDF Table D5 Delivered Energy Consumption in Japan by End-Use Sector and Fuel Excel PDF Table D6 Delivered Energy Consumption in Australia/New Zealand by End-Use Sector and Fuel Excel PDF Table D7 Delivered Energy Consumption in the Former Soviet Union by End-Use Sector and Fuel

172

EIA Average Energy Consumption 2005  

U.S. Energy Information Administration (EIA)

Table US8. Average Consumption by Fuels Used, 2005 Physical Units per Household Fuels Used (physical units of consumption per household using the fuel)

173

Trends in Renewable Energy Consumption and Electricity  

Reports and Publications (EIA)

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.

2012-12-11T23:59:59.000Z

174

Modelling the impact of user behaviour on heat energy consumption  

E-Print Network (OSTI)

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

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

2011-01-01T23:59:59.000Z

175

Historical Renewable Energy Consumption by Energy Use Sector and Energy  

Open Energy Info (EERE)

Historical Renewable Energy Consumption by Energy Use Sector and Energy Historical Renewable Energy Consumption by Energy Use Sector and Energy Source, 1989-2008 Dataset Summary Description Provides annual renewable energy consumption by source and end use between 1989 and 2008. This data was published and compiled by the Energy Information Administration. Source EIA Date Released August 01st, 2010 (4 years ago) Date Updated August 01st, 2010 (4 years ago) Keywords annual energy consumption consumption EIA renewable energy Data application/vnd.ms-excel icon historical_renewable_energy_consumption_by_sector_and_energy_source_1989-2008.xls (xls, 41 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually Time Period 1989-2008 License License Creative Commons CCZero Comment Rate this dataset

176

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

Reports and Publications (EIA)

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

Tancred Lidderdale

2011-11-30T23:59:59.000Z

177

Electrical appliance energy consumption control methods and electrical energy consumption systems  

DOE Patents (OSTI)

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.

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)

2008-09-02T23:59:59.000Z

178

Electrical appliance energy consumption control methods and electrical energy consumption systems  

DOE Patents (OSTI)

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.

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)

2006-03-07T23:59:59.000Z

179

Consumption & Efficiency - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

A video about changes in home heating in the United States. Annual Energy Review Consumption Statistics. Released September 27, 2012. A report of annual energy ...

180

Commercial Buildings Energy Consumption and Expenditures 1992  

Annual Energy Outlook 2012 (EIA)

(92) Distribution Category UC-950 Commercial Buildings Energy Consumption and Expenditures 1992 April 1995 Contacts The Energy Information Administration (EIA) prepared this...

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

Residential Energy Consumption Survey data show decreased ...  

U.S. Energy Information Administration (EIA)

Total U.S. energy consumption in homes has remained relatively stable for many years as increased energy efficiency has offset the increase in the ...

182

Manufacturing Consumption of Energy 1994  

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

3 3 Energy Information Administration/Manufacturing Consumption of Energy 1994 Glossary Anthracite: A hard, black, lustrous coal containing a high percentage of fixed carbon and a low percentage of volatile matter. Often referred to as hard coal. Barrel: A volumetric unit of measure equivalent to 42 U.S. gallons. Biomass: Organic nonfossil material of biological origin constituting a renewable energy source. Bituminous Coal: A dense, black coal, often with well-defined bands of bright and dull material, with a moisture content usually less than 20 percent. Often referred to as soft coal. It is the most common coal. Blast Furnace: A shaft furnace in which solid fuel (coke) is burned with an air blast to smelt ore in a continuous operation. Blast Furnace Gas: The waste combustible gas generated in a blast furnace when iron ore is being reduced with coke to

183

Manufacturing Consumption of Energy 1994  

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

A9. A9. Total Inputs of Energy for Heat, Power, and Electricity Generation by Fuel Type, Census Region, and End Use, 1994: Part 1 (Estimates in Btu or Physical Units) See footnotes at end of table. Energy Information Administration/Manufacturing Consumption of Energy 1994 166 End-Use Categories (trillion Btu) kWh) (1000 bbl) (1000 bbl) cu ft) (1000 bbl) tons) (trillion Btu) Total (million Fuel Oil Diesel Fuel (billion LPG (1000 short Other Net Distillate Natural and Electricity Residual Fuel Oil and Gas Breeze) a b c Coal (excluding Coal Coke d RSE Row Factors Total United States RSE Column Factors: NF 0.5 1.3 1.4 0.8 1.2 1.2 NF TOTAL INPUTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16,515 778,335 70,111 26,107 5,962 25,949 54,143 5,828 2.7 Indirect Uses-Boiler Fuel . . . . . . . . . . . . . . . . . . . . . . . --

184

OpenEI Community - energy data + forecasting  

Open Energy Info (EERE)

FRED FRED http://en.openei.org/community/group/fred Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in formulating policies and energy plans based on easy to use forecasting tools, visualizations, sankey diagrams, and open data. The platform will live on OpenEI and this community was established to initiate discussion around continuous development of this tool, integrating it with new datasets, and connecting with the community of users who will want to contribute data to the tool and use the tool for planning purposes. energy data + forecasting Fri, 22 Jun 2012 15:30:20 +0000 Dbrodt 34

185

Household energy consumption and expenditures 1993  

Science Conference Proceedings (OSTI)

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.

NONE

1995-10-05T23:59:59.000Z

186

Manufacturing Consumption of Energy 1994  

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

Survey Design, Survey Design, Implementation, and Estimates 411 Energy Information Administration/Manufacturing Consumption of Energy 1994 Overview of Changes from Previous Surveys Sample Design. The MECS has increased its sample size by roughly 40 percent since the 1991 survey, increasing the designed sample size from 16,054 establishments to 22,922. This increase in size and change in sampling criteria required a departure from using the Annual Survey of Manufactures (ASM) as the MECS sampling frame. For 1994, establishments were selected directly from the 1992 Census of Manufactures (CM) mail file, updated by 1993 ASM. Sample Frame Coverage. The coverage in the 1994 MECS is 98 percent of the manufacturing population as measured in total payroll. The sampling process itself provided that level of coverage, and no special adjustments were

187

Manufacturing Consumption of Energy 1994  

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

0. 0. Number of Establishments that Actually Switched Fuels from Natural Gas to Residual Fuel Oil, by Industry Group and Selected Industries, 1994 369 Energy Information Administration/Manufacturing Consumption of Energy 1994 SIC Residual Fuel Oil Total Code Industry Group and Industry (billion cu ft) Factors (counts) (counts) (percents) (counts) (percents) a Natural Gas Switchable to Establishments RSE Row Able to Switch Actually Switched RSE Column Factors: 1.3 0.1 1.4 1.7 1.6 1.8 20 Food and Kindred Products . . . . . . . . . . . . . . . . . . . . . . . . . 81 14,698 702 4.8 262 1.8 5.6 2011 Meat Packing Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 759 23 3.0 10 1.3 9.0 2033 Canned Fruits and Vegetables . . . . . . . . . . . . . . . . . . . . . 9 531 112 21.2 33 6.2 11.6 2037 Frozen Fruits and Vegetables . . . . . . . . . . . . . . . . . . . . . . 5 232 Q 5.3

188

annual energy consumption | OpenEI  

Open Energy Info (EERE)

energy consumption energy consumption Dataset Summary Description Provides annual renewable energy consumption by source and end use between 1989 and 2008. This data was published and compiled by the Energy Information Administration. Source EIA Date Released August 01st, 2010 (4 years ago) Date Updated August 01st, 2010 (4 years ago) Keywords annual energy consumption consumption EIA renewable energy Data application/vnd.ms-excel icon historical_renewable_energy_consumption_by_sector_and_energy_source_1989-2008.xls (xls, 41 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually Time Period 1989-2008 License License Creative Commons CCZero Comment Rate this dataset Usefulness of the metadata Average vote Your vote Usefulness of the dataset

189

Annual Energy Outlook 1998 Forecasts  

Gasoline and Diesel Fuel Update (EIA)

EIA Administrator's Press Briefing on the Annual Energy Outlook 1998 (AEO98) Annual Energy Outlook 1998 - Errata as of 3698 Data from the AEO98 Assumptions to the AEO98 (Nat'Gas...

190

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST  

E-Print Network (OSTI)

Policy Report, over the entire forecast period, primarily because both weather-adjusted peak and commercial sectors. Keywords Electricity demand, electricity consumption, demand forecast, weather normalization, annual peak demand, natural gas demand, self-generation, California Solar Initiative. #12;ii #12

191

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Coal Coal Although coal use is expected to be displaced by natural gas in some parts of the world, only a slight drop in its share of total energy consumption is projected by 2025. Coal continues to dominate electricity and industrial sector fuel markets in emerging Asia. Figure 50. World Coal Consumption by Region, 1970-2025 (Billion Short Tons). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 51. Coal Share of World Energy Consumption by Sector, 2002, 2015, and 2025 (Percent). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 52. World Recoverable Coal Reserves. Need help, contact the National Energy Information Center at 202-586-8800. Figure Data In the International Energy Outlook 2005 (IEO2005) reference case, world

192

Modelling Office Energy Consumption: An Agent Based  

E-Print Network (OSTI)

Modelling Office Energy Consumption: An Agent Based Approach Tao Zhang, Peer-Olaf Siebers, Uwe · Overall Project Background · Office Energy Consumption · Case Study · Simulation Experiments · Conclusions #12;Overall Project Background · EPSRC funded City Energy Future Project ­ Under Energy & Complexity

Aickelin, Uwe

193

Univariate Modeling and Forecasting of Monthly Energy Demand Time Series  

E-Print Network (OSTI)

in this report. #12;i ABSTRACT These electricity demand forms and instructions ask load-serving entities and Instructions for Electricity Demand Forecasts. California Energy Commission, Electricity Supply Analysis.................................................................................................................................7 Form 1 Historic and Forecast Electricity Demand

Abdel-Aal, Radwan E.

194

Consumption & Efficiency | U.S. Energy Information Administration ...  

U.S. Energy Information Administration (EIA)

Consumption and efficiency analysis & projections. Annual Energy Outlook 2013 Reference Case: consumption by sector projections; energy intensity projections

195

Household Vehicles Energy Consumption 1991  

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

C C Quality of the Data Appendix C Quality of the Data Introduction This appendix discusses several issues relating to the quality of the Residential Transportation Energy Consumption Survey (RTECS) data and to the interpretation of conclusions based on these data. The first section discusses under- coverage of the vehicle stock in the residential sector. The second section discusses the effects of using July 1991 as a time reference for the survey. The remainder of this appendix discusses the treatment of sampling and nonsampling errors in the RTECS, the quality of specific data items such as the Vehicle Identification Number (VIN) and fuel prices, and poststratification procedures used in the 1991 RTECS. The quality of the data collection and the processing of the data affects the accuracy of estimates based on survey data. All the statistics published in this report such as total

196

Household vehicles energy consumption 1991  

Science Conference Proceedings (OSTI)

The purpose of this report is to provide information on the use of energy in residential vehicles in the 50 States and the District of Columbia. Included are data about: the number and type of vehicles in the residential sector, the characteristics of those vehicles, the total annual Vehicle Miles Traveled (VMT), the per household and per vehicle VMT, the vehicle fuel consumption and expenditures, and vehicle fuel efficiencies. The data for this report are based on the household telephone interviews from the 1991 RTECS, conducted during 1991 and early 1992. The 1991 RTECS represents 94.6 million households, of which 84.6 million own or have access to 151.2 million household motor vehicles in the 50 States and the District of Columbia.

Not Available

1993-12-09T23:59:59.000Z

197

Forecasts of intercity passenger demand and energy use through 2000  

SciTech Connect

The development of national travel demand and energy-use forecasts for automobile and common-carrier intercity travel through the year 2000. The forecasts are driven by the POINTS (Passenger Oriented Intercity Network Travel Simulation) model, a model direct-demand model which accounts for competition among modes and destinations. Developed and used to model SMSA-to-SMSA business and nonbusiness travel, POINTS is an improvement over earlier direct demand models because it includes an explicit representation of cities' relative accessibilities and a utility maximizing behavorial multimodal travel function. Within POINTS, pathbuilding algorithms are used to determine city-pair travel times and costs by mode, including intramodal transfer times. Other input data include projections of SMSA population, public and private sector employment, and hotel and other retail receipts. Outputs include forecasts of SMSA-to-SMSA person trips and person-miles of travel by mode. For the national forecasts, these are expanded to represent all intercity travel (trips greater than 100 miles, one way) for two fuel-price cases. Under both cases rising fuel prices, accompanied by substantial reductions in model-energy intensities, result in moderate growth in total intercity passenger travel. Total intercity passenger travel is predicted to grow at approximately one percent per year, slightly fster than population growth, while air travel grows almost twice as fast as population. The net effect of moderate travel growth and substantial reduction in model energy intensities is a reduction of approximately 50 percent in fuel consumption by the intercity passenger travel market.

Kaplan, M.P.; Vyas, A.D.; Millar, M.; Gur, Y.

1982-01-01T23:59:59.000Z

198

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

Open Energy Info (EERE)

Consumption Survey Results: Total Energy Consumption, Expenditures, and Intensities (2005)

199

EIA Renewable Energy- The Role of Renewable Energy Consumption in ...  

U.S. Energy Information Administration (EIA)

Pie graph and bar graph showing the percentage of renewable energy consumption in the Nation's overall energy supply

200

Wind Energy Forecasting Technology Update: 2006  

Science Conference Proceedings (OSTI)

The worldwide installed wind generation capacity increased by 25 and reached almost 60,000 MW worldwide during 2005. As wind capacity continues to grow and large regional concentrations of wind generation emerge, utilities and regional transmission organizations will increasingly need accurate same-day and next-day forecasts of wind energy generation to dispatch system generation and transmission resource and anticipate rapid changes of wind generation.

2006-12-05T23:59:59.000Z

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Wind Energy Forecasting Technology Update: 2005  

Science Conference Proceedings (OSTI)

The worldwide installed wind generation capacity increased by 25 and reached almost 60,000 MW worldwide during 2005. As wind capacity continues to grow and large regional concentrations of wind generation emerge, utilities and regional transmission organizations will increasingly need accurate same-day and next-day forecasts of wind energy generation to dispatch system generation and transmission resource and anticipate rapid changes of wind generation. The project objective is to summarize the results o...

2006-03-31T23:59:59.000Z

202

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

I: System for the Analysis of Global Energy Markets (SAGE) I: System for the Analysis of Global Energy Markets (SAGE) The projections of world energy consumption appearing in this yearÂ’s International Energy Outlook (IEO) are based on the Energy Information AdministrationÂ’s (EIAÂ’s) international energy modeling tool, System for the Analysis of Global Energy markets (SAGE). SAGE is an integrated set of regional models that provide a technology-rich basis for estimating regional energy consumption. For each region, reference case estimates of 42 end-use energy service demands (e.g., car, commercial truck, and heavy truck road travel; residential lighting; steam heat requirements in the paper industry) are developed on the basis of economic and demographic projections. Projections of energy consumption to meet the energy demands are estimated on the basis of each regionÂ’s existing energy use patterns, the existing stock of energy-using equipment, and the characteristics of available new technologies, as well as new sources of primary energy supply.

203

A Green Solution To Energy Consumption  

Science Conference Proceedings (OSTI)

Presentation Title, MAX HT® Bayer Sodalite Scale Inhibiter: A Green Solution To Energy Consumption. Author(s), Morris E. Lewellyn, Alan Rothenberg, Calvin ...

204

Manufacturing Energy Consumption Survey (MECS) - Analysis ...  

U.S. Energy Information Administration (EIA)

The gross output for the petroleum and coal products subsector grew by about 3 percent, ... Manufacturing Energy Consumption Survey, MECS Definition of Fuel Use, ...

205

Figure 70. Delivered energy consumption for transportation ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 70. Delivered energy consumption for transportation by mode, 2011 and 2040 (quadrillion Btu) Total Rail Pipeline Marine ...

206

Renewable Energy Consumption and Electricity Preliminary ...  

U.S. Energy Information Administration (EIA)

Renewable Energy Consumption and Electricity Preliminary Statistics 2010 June 2011 ... and Job Creation Act of 2010 (H.R. 4853) was signed in December

207

Residential Energy Consumption Survey (RECS) 2009 Technical ...  

U.S. Energy Information Administration (EIA)

Residential Energy Consumption Survey (RECS) Using the 2009 microdata file to compute estimates and standard errors (RSEs) February 2013 Independent Statistics & Analysis

208

California Energy Commission - Electricity Consumption by Planning...  

Open Energy Info (EERE)

Planning Area (1990-2009) Electricity consumption data from the California Energy Commission by planning area for Commercial, Residential, Ag & Water Pump, Streetlight,...

209

Energy consumption metrics of MIT buildings  

E-Print Network (OSTI)

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 ...

Schmidt, Justin David

2010-01-01T23:59:59.000Z

210

TECHNICAL DOCUMENTATION Commercial Buildings Energy Consumption Survey  

Reports and Publications (EIA)

This is the technical documentation for the public use data set based on the 1992 Commercial Buildings Energy Consumption Survey (CBECS), the national sample survey of commercial buildings and their energy suppliers conducted by the Energy Information Administration.

Information Center

1996-07-01T23:59:59.000Z

211

NREL: Energy Analysis - Energy Forecasting and Modeling Staff  

NLE Websites -- All DOE Office Websites (Extended Search)

Energy Forecasting and Modeling Energy Forecasting and Modeling The following includes summary bios of staff expertise and interests in analysis relating to energy economics, energy system planning, risk and uncertainty modeling, and energy infrastructure planning. Team Lead: Nate Blair Administrative Support: Geraly Amador Clayton Barrows Greg Brinkman Brian W Bush Stuart Cohen Carolyn Davidson Paul Denholm Victor Diakov Aron Dobos Easan Drury Kelly Eurek Janine Freeman Marissa Hummon Jennie Jorganson Jordan Macknick Trieu Mai David Mulcahy David Palchak Ben Sigrin Daniel Steinberg Patrick Sullivan Aaron Townsend Laura Vimmerstedt Andrew Weekley Owen Zinaman Photo of Clayton Barrows. Clayton Barrows Postdoctoral Researcher Areas of expertise Power system modeling Primary research interests Power and energy systems

212

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

U.S. Energy Information Administration (EIA)

Energy use in homes, commercial buildings, ... Manufacturing energy consumption data show large reductions in both manufacturing energy use and the energy intensity ...

213

State energy data report 1993: Consumption estimates  

SciTech Connect

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.

NONE

1995-07-01T23:59:59.000Z

214

State Energy Data Report, 1991: Consumption estimates  

DOE Green Energy (OSTI)

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.

Not Available

1993-05-01T23:59:59.000Z

215

Annual Energy Outlook 1998 Forecasts - Preface  

Gasoline and Diesel Fuel Update (EIA)

1998 With Projections to 2020 1998 With Projections to 2020 Annual Energy Outlook 1999 Report will be Available on December 9, 1998 Preface The Annual Energy Outlook 1998 (AEO98) presents midterm forecasts of energy supply, demand, and prices through 2020 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA's National Energy Modeling System (NEMS). The report begins with an “Overview” summarizing the AEO98 reference case. The next section, “Legislation and Regulations,” describes the assumptions made with regard to laws that affect energy markets and discusses evolving legislative and regulatory issues. “Issues in Focus” discusses three current energy issues—electricity restructuring, renewable portfolio standards, and carbon emissions. It is followed by the analysis

216

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

9A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 3 9A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 3 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity Energy Intensity (kWh/square foot) West South Central Moun- tain Pacific West South Central Moun- tain Pacific West South Central Moun- tain Pacific All Buildings ................................ 141 68 117 8,634 4,165 8,376 16.3 16.3 14.0 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 17 7 12 696 439 857 24.1 15.7 14.0 5,001 to 10,000 .............................. 12 5 15 865 451 868 13.8 12.1 17.7 10,001 to 25,000 ............................ 16 12 16 1,493 933 1,405 11.0 13.0 11.5

217

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

2A. Electricity Consumption and Conditional Energy Intensity by Year Constructed for All Buildings, 2003 2A. Electricity Consumption and Conditional Energy Intensity by Year Constructed for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity Energy Intensity (kWh/square foot) 1959 or Before 1960 to 1989 1990 to 2003 1959 or Before 1960 to 1989 1990 to 2003 1959 or Before 1960 to 1989 1990 to 2003 All Buildings ................................ 162 538 343 17,509 32,945 19,727 9.2 16.3 17.4 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 24 54 38 2,072 2,767 1,640 11.4 19.4 23.0 5,001 to 10,000 .............................. 16 41 29 1,919 3,154 1,572 8.2 13.0 18.4 10,001 to 25,000 ............................ 28 69 45 3,201 5,610 3,683 8.7 12.3 12.2

218

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

2A. Natural Gas Consumption and Conditional Energy Intensity by Year Constructed for All Buildings, 2003 2A. Natural Gas Consumption and Conditional Energy Intensity by Year Constructed for All Buildings, 2003 Total Natural Gas Consumption (billion cubic feet) Total Floorspace of Buildings Using Natural Gas (million square feet) Natural Gas Energy Intensity (cubic feet/square foot) 1959 or Before 1960 to 1989 1990 to 2003 1959 or Before 1960 to 1989 1990 to 2003 1959 or Before 1960 to 1989 1990 to 2003 All Buildings ............................... 580 986 471 12,407 22,762 13,304 46.8 43.3 35.4 Building Floorspace (Square Feet) 1,001 to 5,000 ............................... 86 103 61 1,245 1,271 659 69.0 81.0 92.1 5,001 to 10,000 ............................. 57 101 60 1,154 1,932 883 49.4 52.3 67.6 10,001 to 25,000 ........................... 105 174 65 2,452 3,390 1,982 42.6 51.2 32.7

219

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

7A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 1 7A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 1 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity Energy Intensity (kWh/square foot) New England Middle Atlantic East North Central New England Middle Atlantic East North Central New England Middle Atlantic East North Central All Buildings ................................ 41 131 168 3,430 10,469 12,202 12.0 12.5 13.8 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 5 9 20 369 662 921 12.9 13.9 21.9 5,001 to 10,000 .............................. 3 8 9 360 768 877 8.4 10.4 10.8 10,001 to 25,000 ............................ Q 16 24 674 1,420 2,113 Q 11.6 11.2

220

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

5A. Fuel Oil Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003 5A. Fuel Oil Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003 Total Fuel Oil Consumption (million gallons) Total Floorspace of Buildings Using Fuel Oil (million square feet) Fuel Oil Energy Intensity (gallons/square foot) North- east Mid- west South West North- east Mid- west South West North- east Mid- west South West All Buildings .............................. 1,302 172 107 64 6,464 2,909 4,663 2,230 0.20 0.06 0.02 Q Building Floorspace (Square Feet) 1,001 to 10,000 ............................ 381 Q Q Q 763 Q 274 Q 0.50 Q 0.10 Q 10,001 to 100,000 ........................ 404 63 Q Q 1,806 648 985 351 0.22 0.10 Q Q Over 100,000 ............................... 517 21 45 Q 3,894 2,055 3,404 1,780 0.13 0.01 0.01 Q

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

7A. Natural Gas Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 1 7A. Natural Gas Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 1 Total Natural Gas Consumption (billion cubic feet) Total Floorspace of Buildings Using Natural Gas (million square feet) Natural Gas Energy Intensity (cubic feet/square foot) New England Middle Atlantic East North Central New England Middle Atlantic East North Central New England Middle Atlantic East North Central All Buildings ................................ 85 364 550 1,861 8,301 10,356 45.4 43.8 53.1 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ Q 42 69 Q 427 741 Q 98.4 92.9 5,001 to 10,000 .............................. Q 32 49 Q 518 743 Q 62.1 65.5 10,001 to 25,000 ............................ Q 47 102 Q 952 1,860 Q 49.7 54.6

222

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

8A. Natural Gas Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 2 8A. Natural Gas Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 2 Total Natural Gas Consumption (billion cubic feet) Total Floorspace of Buildings Using Natural Gas (million square feet) Natural Gas Energy Intensity (cubic feet/square foot) West North Central South Atlantic East South Central West North Central South Atlantic East South Central West North Central South Atlantic East South Central All Buildings ................................ 178 238 104 3,788 7,286 2,521 47.0 32.7 41.3 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 23 27 11 346 360 218 66.6 75.8 51.9 5,001 to 10,000 .............................. 14 36 Q 321 662 Q 45.1 53.8 Q 10,001 to 25,000 ............................ 31 33 Q 796 1,102 604 39.5 29.9 Q

223

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

1A. Electricity Consumption and Conditional Energy Intensity by Building Size for All Buildings, 2003 1A. Electricity Consumption and Conditional Energy Intensity by Building Size for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity Energy Intensity (kWh/square foot) 1,001 to 10,000 Square Feet 10,001 to 100,000 Square Feet Over 100,000 Square Feet 1,001 to 10,000 Square Feet 10,001 to 100,000 Square Feet Over 100,000 Square Feet 1,001 to 10,000 Square Feet 10,001 to 100,000 Square Feet Over 100,000 Square Feet All Buildings ................................ 201 412 431 13,124 31,858 25,200 15.3 12.9 17.1 Principal Building Activity Education ....................................... 9 55 45 806 5,378 3,687 11.1 10.2 12.2 Food Sales ..................................... 36 24 Q 747 467 Q 48.8 51.1 Q

224

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

. Consumption and Gross Energy Intensity by Year Constructed for Sum of Major Fuels for Non-Mall Buildings, 2003 . Consumption and Gross Energy Intensity by Year Constructed for Sum of Major Fuels for Non-Mall Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of Buildings (million square feet) Energy Intensity for Sum of Major Fuels (thousand Btu/square foot) 1959 or Before 1960 to 1989 1990 to 2003 1959 or Before 1960 to 1989 1990 to 2003 1959 or Before 1960 to 1989 1990 to 2003 All Buildings* ............................. 1,488 2,794 1,539 17,685 29,205 17,893 84.1 95.7 86.0 Building Floorspace (Square Feet) 1,001 to 5,000 .............................. 191 290 190 2,146 2,805 1,838 89.1 103.5 103.5 5,001 to 10,000 ............................ 131 231 154 1,972 2,917 1,696 66.2 79.2 91.0 10,001 to 25,000 .......................... 235 351 191 3,213 4,976 3,346 73.1 70.5 57.0

225

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

0A. Natural Gas Consumption and Conditional Energy Intensity by Climate Zonea for All Buildings, 2003 0A. Natural Gas Consumption and Conditional Energy Intensity by Climate Zonea for All Buildings, 2003 Total Natural Gas Consumption (billion cubic feet) Total Floorspace of Buildings Using Natural Gas (million square feet) Natural Gas Energy Intensity (cubic feet/square foot) Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 All Buildings .............................. 454 715 356 378 134 8,486 14,122 8,970 11,796 5,098 53.5 50.6 39.7 32.0 26.3 Building Floorspace (Square Feet) 1,001 to 5,000 ............................. 57 84 35 58 16 666 1,015 427 832 234 84.8 83.1 81.9 69.6 66.6 5,001 to 10,000 ........................... 50 57 33 61 17 666 1,030 639 1,243 392 75.2 54.9 51.2 49.2 44.0

226

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

A. Total Energy Consumption by Major Fuel for All Buildings, 2003 A. Total Energy Consumption by Major Fuel for All Buildings, 2003 All Buildings Total Energy Consumption (trillion Btu) Number of Buildings (thousand) Floorspace (million square feet) Sum of Major Fuels Electricity Natural Gas Fuel Oil District Heat Primary Site All Buildings ................................ 4,859 71,658 6,523 10,746 3,559 2,100 228 636 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 2,586 6,922 685 1,185 392 257 34 Q 5,001 to 10,000 .............................. 948 7,033 563 883 293 224 36 Q 10,001 to 25,000 ............................ 810 12,659 899 1,464 485 353 28 Q 25,001 to 50,000 ............................ 261 9,382 742 1,199 397 278 17 Q 50,001 to 100,000 .......................... 147 10,291 913 1,579 523 277 29 Q

227

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

0A. Electricity Consumption and Conditional Energy Intensity by Climate Zonea for All Buildings, 2003 0A. Electricity Consumption and Conditional Energy Intensity by Climate Zonea for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity Energy Intensity (kWh/square foot) Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 All Buildings .............................. 137 254 189 261 202 11,300 18,549 12,374 17,064 10,894 12.1 13.7 15.3 15.3 18.5 Building Floorspace (Square Feet) 1,001 to 5,000 ............................. 19 27 14 32 23 1,210 1,631 923 1,811 903 15.7 16.4 15.0 17.8 25.8 5,001 to 10,000 ........................... 12 18 15 27 14 1,175 1,639 1,062 1,855 914 10.2 10.9 14.3 14.3 15.5

228

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

5A. Electricity Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003 5A. Electricity Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity Energy Intensity (kWh/square foot) North- east Mid- west South West North- east Mid- west South West North- east Mid- west South West All Buildings ................................ 172 234 452 185 13,899 17,725 26,017 12,541 12.4 13.2 17.4 14.7 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 14 30 52 19 1,031 1,742 2,410 1,296 13.5 17.4 21.5 14.6 5,001 to 10,000 .............................. 11 17 37 21 1,128 1,558 2,640 1,319 9.8 10.8 14.0 15.8 10,001 to 25,000 ............................ 22 33 59 28 2,094 3,317 4,746 2,338 10.4 10.0 12.5 12.1

229

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

5A. Natural Gas Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003 5A. Natural Gas Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003 Total Natural Gas Consumption (billion cubic feet) Total Floorspace of Buildings Using Natural Gas (million square feet) Natural Gas Energy Intensity (cubic feet/square foot) North- east Mid- west South West North- east Mid- west South West North- east Mid- west South West All Buildings ................................ 448 728 511 350 10,162 14,144 15,260 8,907 44.1 51.5 33.5 39.3 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 50 92 68 40 547 1,086 912 629 90.6 84.6 74.5 63.7 5,001 to 10,000 .............................. 39 63 69 46 661 1,064 1,439 806 59.2 59.4 48.1 57.4 10,001 to 25,000 ............................ 58 133 81 70 1,293 2,656 2,332 1,542 45.2 50.1 34.7 45.7

230

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

1A. Natural Gas Consumption and Conditional Energy Intensity by Building Size for All Buildings, 2003 1A. Natural Gas Consumption and Conditional Energy Intensity by Building Size for All Buildings, 2003 Total Natural Gas Consumption (billion cubic feet) Total Floorspace of Buildings Using Natural Gas (million square feet) Natural Gas Energy Intensity (cubic feet/square foot) 1,001 to 10,000 Square Feet 10,001 to 100,000 Square Feet Over 100,000 Square Feet 1,001 to 10,000 Square Feet 10,001 to 100,000 Square Feet Over 100,000 Square Feet 1,001 to 10,000 Square Feet 10,001 to 100,000 Square Feet Over 100,000 Square Feet All Buildings ................................ 467 882 688 7,144 21,928 19,401 65.4 40.2 35.5 Principal Building Activity Education ....................................... Q 137 101 419 3,629 2,997 53.9 37.6 33.7 Food Sales ..................................... 16 Q Q 339 Q Q 46.6 Q Q

231

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

9A. Natural Gas Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 3 9A. Natural Gas Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 3 Total Natural Gas Consumption (billion cubic feet) Total Floorspace of Buildings Using Natural Gas (million square feet) Natural Gas Energy Intensity (cubic feet/square foot) West South Central Moun- tain Pacific West South Central Moun- tain Pacific West South Central Moun- tain Pacific All Buildings ................................ 168 185 165 5,453 3,263 5,644 30.9 56.6 29.2 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 29 18 Q 334 266 363 87.9 68.5 60.2 5,001 to 10,000 .............................. 25 Q Q 545 291 514 45.6 62.7 54.4 10,001 to 25,000 ............................ 20 45 26 626 699 844 32.1 63.9 30.6

232

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

8A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 2 8A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 2 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity Energy Intensity (kWh/square foot) West North Central South Atlantic East South Central West North Central South Atlantic East South Central West North Central South Atlantic East South Central All Buildings ................................ 66 254 57 5,523 13,837 3,546 12.0 18.3 16.2 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 10 28 7 821 1,233 481 12.4 22.4 15.4 5,001 to 10,000 .............................. 7 20 5 681 1,389 386 10.8 14.4 13.3 10,001 to 25,000 ............................ 9 31 12 1,204 2,411 842 7.8 12.8 14.1

233

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

C8. Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for Non-Mall Buildings, 2003: Part 2 C8. Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for Non-Mall Buildings, 2003: Part 2 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of 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 Atlantic East South Central West North Central South Atlantic East South Central All Buildings* ............................... 436 1,064 309 5,485 12,258 3,393 79.5 86.8 91.1 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 60 116 36 922 1,207 538 64.9 96.5 67.8 5,001 to 10,000 .............................. 44 103 Q 722 1,387 393 60.5 74.0 Q

234

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

A. Consumption and Gross Energy Intensity by Building Size for Sum of Major Fuels for All Buildings, 2003 A. Consumption and Gross Energy Intensity by Building Size for Sum of Major Fuels for All Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of 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 Feet 1,001 to 10,000 Square Feet 10,001 to 100,000 Square Feet Over 100,000 Square Feet 1,001 to 10,000 Square Feet 10,001 to 100,000 Square Feet Over 100,000 Square Feet All Buildings ............................... 1,248 2,553 2,721 13,955 32,332 25,371 89.4 79.0 107.3 Principal Building Activity Education ...................................... 63 423 334 808 5,378 3,687 78.3 78.6 90.7 Food Sales ................................... 144 Q Q 765 467 Q 188.5 Q Q

235

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

0. Consumption and Gross Energy Intensity by Climate Zonea for Non-Mall Buildings, 2003 0. Consumption and Gross Energy Intensity by Climate Zonea for Non-Mall Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of 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 Zone 2 Zone 3 Zone 4 Zone 5 All Buildings* ........................... 990 1,761 1,134 1,213 724 10,622 17,335 11,504 15,739 9,584 93.2 101.6 98.5 77.0 75.5 Building Floorspace (Square Feet) 1,001 to 5,000 ............................ 143 187 90 170 95 1,313 1,709 1,010 1,915 975 108.7 109.6 88.8 89.0 97.9 5,001 to 10,000 .......................... 110 137 91 156 69 1,248 1,725 1,077 2,024 959 88.1 79.3 84.6 77.1 71.7

236

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

. Consumption and Gross Energy Intensity by Building Size for Sum of Major Fuels for Non-Mall Buildings, 2003 . 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 of 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 Feet 1,001 to 10,000 Square Feet 10,001 to 100,000 Square Feet Over 100,000 Square Feet 1,001 to 10,000 Square Feet 10,001 to 100,000 Square Feet Over 100,000 Square Feet All Buildings* ............................. 1,188 2,208 2,425 13,374 29,260 22,149 88.8 75.5 109.5 Principal Building Activity Education ...................................... 63 423 334 808 5,378 3,687 78.3 78.6 90.7

237

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

. Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for Non-Mall Buildings, 2003: Part 3 . Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for Non-Mall Buildings, 2003: Part 3 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of 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 South Central Moun- tain Pacific All Buildings* ............................... 575 381 530 7,837 3,675 7,635 73.4 103.8 69.4 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 87 44 64 788 464 871 110.9 94.7 73.0 5,001 to 10,000 .............................. 60 36 76 879 418 820 68.2 86.7 92.9 10,001 to 25,000 ............................ 53 76 73 1,329 831 1,256 40.2 91.7 58.4

238

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

Table C8A. Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for All Buildings, 2003: Part 2 Table C8A. Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for All Buildings, 2003: Part 2 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of 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 Atlantic East South Central West North Central South Atlantic East South Central All Buildings ................................ 456 1,241 340 5,680 13,999 3,719 80.2 88.7 91.4 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 60 123 37 922 1,283 547 64.9 96.2 67.6 5,001 to 10,000 .............................. 45 111 27 738 1,468 420 61.6 75.4 63.2

239

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

. Consumption and Gross Energy Intensity by Census Region for Sum of Major Fuels for Non-Mall Buildings, 2003 . Consumption and Gross Energy Intensity by Census Region for Sum of Major Fuels for Non-Mall Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of 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 Mid- west South West All Buildings* ............................. 1,271 1,690 1,948 911 12,905 17,080 23,489 11,310 98.5 98.9 82.9 80.6 Building Floorspace (Square Feet) 1,001 to 5,000 .............................. 118 206 240 108 1,025 1,895 2,533 1,336 115.1 108.5 94.9 80.6 5,001 to 10,000 ............................ 102 117 185 112 1,123 1,565 2,658 1,239 90.7 74.7 69.5 90.8

240

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

A. Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for All Buildings, 2003: Part 3 A. Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for All Buildings, 2003: Part 3 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of 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 South Central Moun- tain Pacific All Buildings ................................ 684 446 617 9,022 4,207 8,613 75.8 106.1 71.6 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 87 44 64 788 466 871 110.9 94.8 73.0 5,001 to 10,000 .............................. 67 39 84 957 465 878 69.7 84.8 95.1 10,001 to 25,000 ............................ 77 91 89 1,555 933 1,429 49.4 97.2 62.4

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

C7A. Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for All Buildings, 2003: Part 1 C7A. Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for All Buildings, 2003: Part 1 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of 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 North Central New England Middle Atlantic East North Central All Buildings ................................ 345 1,052 1,343 3,452 10,543 12,424 99.8 99.7 108.1 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 37 86 147 383 676 986 95.9 127.9 148.9 5,001 to 10,000 .............................. 39 68 83 369 800 939 106.0 85.4 88.2 10,001 to 25,000 ............................ Q 121 187 674 1,448 2,113 Q 83.4 88.4

242

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

A. Consumption and Gross Energy Intensity by Year Constructed for Sum of Major Fuels for All Buildings, 2003 A. Consumption and Gross Energy Intensity by Year Constructed for Sum of Major Fuels for All Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of Buildings (million square feet) Energy Intensity for Sum of Major Fuels (thousand Btu/square foot) 1959 or Before 1960 to 1989 1990 to 2003 1959 or Before 1960 to 1989 1990 to 2003 1959 or Before 1960 to 1989 1990 to 2003 All Buildings ............................... 1,522 3,228 1,772 18,031 33,384 20,243 84.4 96.7 87.6 Building Floorspace (Square Feet) 1,001 to 5,000 .............................. 193 300 193 2,168 2,904 1,850 89.0 103.2 104.2 5,001 to 10,000 ............................ 134 263 165 2,032 3,217 1,784 66.0 81.9 92.5 10,001 to 25,000 .......................... 241 432 226 3,273 5,679 3,707 73.6 76.1 60.9

243

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

A. Consumption and Gross Energy Intensity by Climate Zonea for All Buildings, 2003 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) 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 Zone 2 Zone 3 Zone 4 Zone 5 All Buildings ............................ 1,086 1,929 1,243 1,386 879 11,529 18,808 12,503 17,630 11,189 94.2 102.6 99.4 78.6 78.6 Building Floorspace (Square Feet) 1,001 to 5,000 ............................ 143 187 90 170 95 1,313 1,709 1,010 1,915 975 108.7 109.6 88.8 89.0 97.9 5,001 to 10,000 .......................... 110 137 91 156 69 1,248 1,725 1,077 2,024 959 88.1 79.3 84.6 77.1 71.7

244

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

. Total Energy Consumption by Major Fuel for Non-Mall Buildings, 2003 . Total Energy Consumption by Major Fuel for Non-Mall Buildings, 2003 All Buildings* Total Energy Consumption (trillion Btu) Number of Buildings (thousand) Floorspace (million square feet) Sum of Major Fuels Electricity Natural Gas Fuel Oil District Heat Primary Site All Buildings* ............................... 4,645 64,783 5,820 9,168 3,037 1,928 222 634 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 2,552 6,789 672 1,164 386 250 34 Q 5,001 to 10,000 .............................. 889 6,585 516 790 262 209 36 Q 10,001 to 25,000 ............................ 738 11,535 776 1,229 407 309 27 Q 25,001 to 50,000 ............................ 241 8,668 673 1,058 350 258 16 Q 50,001 to 100,000 .......................... 129 9,057 759 1,223 405 244 26 Q

245

Consumption & Efficiency - Data - U.S. Energy Information Administration  

Gasoline and Diesel Fuel Update (EIA)

Consumption & Efficiency Consumption & Efficiency Glossary › FAQS › Overview Data Residential Energy Consumption Survey Data Commercial Energy Consumption Survey Data Manufacturing Energy Consumption Survey Data Vehicle Energy Consumption Survey Data Energy Intensity Consumption Summaries Average cost of fossil-fuels for electricity generation All Consumption & Efficiency Data Reports Analysis & Projections All Sectors Commercial Buildings Efficiency Manufacturing Projections Residential Transportation All Reports Find statistics on energy consumption and efficiency across all fuel sources. + EXPAND ALL Residential Energy Consumption Survey Data Household characteristics Release Date: March 28, 2011 Survey data for occupied primary housing units. Residential Energy Consumption Survey (RECS)

246

Short-Term Solar Energy Forecasting Using Wireless Sensor Networks  

E-Print Network (OSTI)

Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Stefan Achleitner, Tao Liu in power output is a major concern and forecasting is, therefore, a top priority. We propose a sensing infrastructure to enable sensing of solar irradiance with application to solar array output forecasting

Cerpa, Alberto E.

247

State energy data report 1994: Consumption estimates  

Science Conference Proceedings (OSTI)

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.

NONE

1996-10-01T23:59:59.000Z

248

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

C3A. Consumption and Gross Energy Intensity for Sum of Major Fuels for All Buildings, 2003 C3A. Consumption and Gross Energy Intensity for Sum of Major Fuels for All Buildings, 2003 All Buildings Sum of Major Fuel Consumption Number of Buildings (thousand) Floorspace (million square feet) Floorspace per Building (thousand square feet) Total (trillion Btu) per Building (million Btu) per Square Foot (thousand Btu) All Buildings ................................ 4,859 71,658 14.7 6,523 1,342 91.0 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 2,586 6,922 2.7 685 265 99.0 5,001 to 10,000 .............................. 948 7,033 7.4 563 594 80.0 10,001 to 25,000 ............................ 810 12,659 15.6 899 1,110 71.0 25,001 to 50,000 ............................ 261 9,382 36.0 742 2,843 79.0

249

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

C3. Consumption and Gross Energy Intensity for Sum of Major Fuels for Non-Mall Buildings, 2003 C3. Consumption and Gross Energy Intensity for Sum of Major Fuels for Non-Mall Buildings, 2003 All Buildings* Sum of Major Fuel Consumption Number of Buildings (thousand) Floorspace (million square feet) Floorspace per Building (thousand square feet) Total (trillion Btu) per Building (million Btu) per Square Foot (thousand Btu) per Worker (million Btu) All Buildings* ............................... 4,645 64,783 13.9 5,820 1,253 89.8 79.9 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 2,552 6,789 2.7 672 263 98.9 67.6 5,001 to 10,000 .............................. 889 6,585 7.4 516 580 78.3 68.7 10,001 to 25,000 ............................ 738 11,535 15.6 776 1,052 67.3 72.0 25,001 to 50,000 ............................ 241 8,668 35.9 673 2,790 77.6 75.8

250

State energy data report 1996: Consumption estimates  

Science Conference Proceedings (OSTI)

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.

NONE

1999-02-01T23:59:59.000Z

251

Nearest neighbor technique and artificial neural networks for short-term electric consumptions forecast  

Science Conference Proceedings (OSTI)

Promoting both energy savings and renewable energy development are two objectives of the actual and national French energy policy. In this sense, the present work takes part in a global development of various tools allowing managing energy demand. So, ... Keywords: Kohonen Self-Organizing Map, Multi-Layer Perceptron, Short-Term Electric Consumption, The Nearest Neighbor Technique, Virtual Power Plant

Van Giang Tran; Stéphane Grieu; Monique Polit

2008-07-01T23:59:59.000Z

252

TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY  

E-Print Network (OSTI)

of future contributions from various emerging transportation fuels and technologies is unknown. PotentiallyCALIFORNIA 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

253

ANL Wind Power Forecasting and Electricity Markets | Open Energy  

Open Energy Info (EERE)

ANL Wind Power Forecasting and Electricity Markets ANL Wind Power Forecasting and Electricity Markets Jump to: navigation, search Logo: Wind Power Forecasting and Electricity Markets Name Wind Power Forecasting and Electricity Markets Agency/Company /Organization Argonne National Laboratory Partner Institute for Systems and Computer Engineering of Porto (INESC Porto) in Portugal, Midwest Independent System Operator and Horizon Wind Energy LLC, funded by U.S. Department of Energy Sector Energy Focus Area Wind Topics Pathways analysis, Technology characterizations Resource Type Software/modeling tools Website http://www.dis.anl.gov/project References Argonne National Laboratory: Wind Power Forecasting and Electricity Markets[1] Abstract To improve wind power forecasting and its use in power system and electricity market operations Argonne National Laboratory has assembled a team of experts in wind power forecasting, electricity market modeling, wind farm development, and power system operations.

254

Energy Information Administration (EIA)- Manufacturing Energy Consumption  

Gasoline and Diesel Fuel Update (EIA)

Steel Industry Analysis Brief Change Topic: Steel | Chemical Steel Industry Analysis Brief Change Topic: Steel | Chemical JUMP TO: Introduction | Energy Consumption | Energy Expenditures | Producer Prices and Production | Energy Intensity | Energy Management Activities Introduction The steel industry is critical to the U.S. economy. Steel is the material of choice for many elements of construction, transportation, manufacturing, and a variety of consumer products. It is the backbone of bridges, skyscrapers, railroads, automobiles, and appliances. Most grades of steel used today - particularly high-strength steels that are lighter and more versatile - were not available a decade ago.1 The U.S. steel industry (including iron production) relies significantly on natural gas and coal coke and breeze for fuel, and is one of the largest

255

Energy Information Administration (EIA)- Manufacturing Energy Consumption  

Gasoline and Diesel Fuel Update (EIA)

Chemical Industry Analysis Brief Change Topic: Steel | Chemical Chemical Industry Analysis Brief Change Topic: Steel | Chemical JUMP TO: Introduction | Energy Consumption | Energy Expenditures | Producer Prices and Production | Energy Intensity | Energy Management Activities | Fuel Switching Capacity Introduction The chemical industries are a cornerstone of the U.S. economy, converting raw materials such as oil, natural gas, air, water, metals, and minerals into thousands of various products. Chemicals are key materials for producing an extensive assortment of consumer goods. They are also crucial materials in creating many resources that are essential inputs to the numerous industries and sectors of the U.S. economy.1 The manufacturing sector is classified by the North American Industry Classification System (NAICS) of which the chemicals sub-sector is NAICS

256

Building Energy Software Tools Directory: Degree Day Forecasts  

NLE Websites -- All DOE Office Websites (Extended Search)

Forecasts Forecasts Degree Day Forecasts example chart Quick and easy web-based tool that provides free 14-day ahead degree day forecasts for 1,200 stations in the U.S. and Canada. Degree Day Forecasts charts show this year, last year and three-year average. Historical degree day charts and energy usage forecasts are available from the same site. Keywords degree days, historical weather, mean daily temperature Validation/Testing Degree day data provided by AccuWeather.com, updated daily at 0700. Expertise Required No special expertise required. Simple to use. Users Over 1,000 weekly users. Audience Anyone who needs degree day forecasts (next 14 days) for the U.S. and Canada. Input Select a weather station (1,200 available) and balance point temperature. Output Charts show (1) degree day (heating and cooling) forecasts for the next 14

257

Compiler Support for Reducing Leakage Energy Consumption  

Science Conference Proceedings (OSTI)

Current trends indicate that leakage energy consumption will be an important concern in upcoming process technologies. In this paper, we propose a compiler-based leakage energy optimization strategy. Our strategy is built upon a data-flow analysis that ...

W. Zhang; M. Kandemir; N. Vijaykrishnan; M. J. Irwin; V. De

2003-03-01T23:59:59.000Z

258

Reducing the Energy Consumption of Networked Devices  

NLE Websites -- All DOE Office Websites (Extended Search)

Reducing the Energy Consumption of Networked Devices Speaker(s): Ken Christensen Date: July 19, 2005 - 12:00pm Location: 90-4133 When Personal Computers are networked, energy...

259

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

Reports and Publications (EIA)

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

Information Center

2010-12-01T23:59:59.000Z

260

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

U.S. Energy Information Administration (EIA)

The major energy sources in the United States are petroleum (oil), natural ... To compare or aggregate energy consumption across different energy sources like oil, ...

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

8A. District Heat Consumption and Expenditure Intensities for All Buildings, 2003 District Heat Consumption District Heat Expenditures per Building (million Btu) per Square Foot...

262

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

7A. Total District Heat Consumption and Expenditures for All Buildings, 2003 All Buildings Using District Heat District Heat Consumption District Heat Expenditures Number of...

263

Household Vehicles Energy Consumption 1991  

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

. . Vehicle Fuel Efficiency and Consumption Fuel consumption is estimated from RTECS data on the vehicle stock (Chapter 2) and miles traveled (Chapter 3), in combination with vehicle fuel efficiency ratings, adjusted to account for individual driving circumstances. The first two sections of this chapter present estimates of household vehicle fuel efficiency and household fuel consumption calculated from these fuel efficiency estimates. These sections also discuss variations in fuel efficiency and consumption based on differences in household and vehicle characteristics. The third section presents EIA estimates of the potential savings from replacing the oldest (and least fuel-efficient) household vehicles with new (and more fuel-efficient) vehicles. The final section of this chapter focuses on households receiving (or eligible to receive) supplemental income under

264

Table 2.1d Industrial Sector Energy Consumption Estimates ...  

U.S. Energy Information Administration (EIA)

Table 2.1d Industrial Sector Energy Consumption Estimates, 1949-2011 (Trillion Btu) Year: Primary Consumption 1: Electricity

265

Table 2.1e Transportation Sector Energy Consumption Estimates ...  

U.S. Energy Information Administration (EIA)

Table 2.1e Transportation Sector Energy Consumption Estimates, 1949-2011 (Trillion Btu) Year: Primary Consumption 1: Electricity

266

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

NLE Websites -- All DOE Office Websites (Extended Search)

in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar --...

267

Renewable Energy Consumption | OpenEI  

Open Energy Info (EERE)

Consumption Consumption Dataset Summary Description Total annual renewable electricity consumption by country, 2005 to 2009 (available in Billion Kilowatt-hours or as Quadrillion Btu). Compiled by Energy Information Administration (EIA). Source EIA Date Released Unknown Date Updated Unknown Keywords EIA renewable electricity Renewable Energy Consumption world Data text/csv icon total_renewable_electricity_net_consumption_2005_2009billion_kwh.csv (csv, 8.5 KiB) text/csv icon total_renewable_electricity_net_consumption_2005_2009quadrillion_btu.csv (csv, 8.9 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Time Period 2005 - 2009 License License Other or unspecified, see optional comment below Comment Rate this dataset Usefulness of the metadata

268

Residential Energy Consumption Survey: Quality Profile  

SciTech Connect

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.

NONE

1996-03-01T23:59:59.000Z

269

Consensus forecast of U. S. energy supply and demand to the year 2000  

DOE Green Energy (OSTI)

Methods used in forecasting energy supply and demand are described, and recent forecasts are reviewed briefly. Forecasts to the year 2000 are displayed in tables and graphs and are used to prepare consensus forecasts for each form of fuel and energy supply. Fuel demand and energy use by consuming sector are tabulated for 1972 and 1975 for the various fuel forms. The distribution of energy consumption by use sector, as projected for the years 1985 and 2000 in the ERDA-48 planning report (Scenario V), is normalized to match the consensus energy supply forecasts. The results are tabulated listing future demand for each fuel and energy form by each major energy-use category. Recent estimates of U.S. energy resources are also reviewed briefly and are presented in tables for each fuel and energy form. The outlook for fossil fuel resources to the year 2040, as developed by the Institute for Energy Analysis at the Oak Ridge Associated Universities, is also presented.

Lane, J.A.

1976-02-01T23:59:59.000Z

270

Consumption & Efficiency - U.S. Energy Information Administration ...  

U.S. Energy Information Administration (EIA)

Maps by energy source and topic, includes forecast maps. Countries. Country energy information, detailed and overviews. Highlights State Energy Data System (SEDS) ...

271

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

U.S. Energy Information Administration (EIA)

Crude oil, gasoline ... Manufacturing Energy Consumption Survey (MECS ... transportation, manufacturing, and a variety of consumer products. It is the ...

272

Mid-range energy-forecasting system: structure, forecasts, and critique  

SciTech Connect

The Mid-Range Energy Forecasting System (MEFS) is a large-scale, interdisciplinary model of the US energy system maintained by the US Department of Energy. MEFS provides long-run regional forecasts of delivered prices for electricity, coal, gasoline, residual, distillate, and natural gas. A number of sets of MEFS forecasts are usually issued, each set corresponding to a different scenario. Because it forecasts prices and since these forecasts are regularly disseminated, MEFS is of considerable practical interest. A critical guide of the model's output for potential users is provided in this paper. The model's logic is described, the latest forecasts from MEFS are presented, and the reasonableness of both the forecasts and the methodology are critically evaluated. The manner in which MEFS interfaces with the Oil Market Simulation Model, which forecasts crude oil price, is also discussed. The evaluation concludes that while there are serious problems with MEFS, selective use can prove very helpful. 17 references, 1 figure, 2 tables.

DeSouza, G.

1980-01-01T23:59:59.000Z

273

How much of world energy consumption and electricity generation is ...  

U.S. Energy Information Administration (EIA)

How much of world energy consumption and electricity generation is from renewable energy? EIA estimates that about 10% of world marketed energy consumption is from ...

274

Industrial Biomass Energy Consumption and Electricity Net Generation...  

Open Energy Info (EERE)

Industrial Biomass Energy Consumption and Electricity Net Generation by Industry and Energy Source, 2008 Biomass energy consumption and electricity net generation in the industrial...

275

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center  

E-Print Network (OSTI)

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

Washington at Seattle, University of

276

Modeling and Analysis Papers - Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Evaluation > Table 1 Evaluation > Table 1 Table 1. Comparison of Absolute Percent Errors for AEO Forecast Evaluation, 1996 to 2002 Average Absolute Percent Error Variable AEO82 to AEO97 AEO82 to AEO98 AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 Consumption Total Energy Consumption 1.6 1.7 1.7 1.8 1.9 1.9 Total Petroleum Consumption 2.8 2.9 2.8 2.9 3.0 2.9 Total Natural Gas Consumption 5.8 5.7 5.6 5.6 5.5 5.5 Total Coal Consumption 2.7 3.0 3.2 3.3 3.5 3.6 Total Electricity Sales 1.6 1.7 1.8 1.9 2.4 2.5 Production Crude Oil Production 4.2 4.3 4.5 4.5 4.5 4.5 Natural Gas Production 5.0 4.8 4.7 4.6 4.6 4.4 Coal Production 3.7 3.6 3.6 3.5 3.7 3.6 Imports and Exports Net Petroleum Imports 10.1 9.5 8.8 8.4 7.9 7.4 Net Natural Gas Imports 17.4 16.7 16.0 15.9 15.8 15.8 Net Coal Exports

277

Estimates of US biomass energy consumption 1992  

DOE Green Energy (OSTI)

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.

Not Available

1994-05-06T23:59:59.000Z

278

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

Table C22. Electricity Consumption and Conditional Energy Intensity by Year Constructed for Non-Mall Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity Energy Intensity (kWh/square foot) 1959 or Before 1960 to 1989 1990 to 2003 1959 or Before 1960 to 1989 1990 to 2003 1959 or Before 1960 to 1989 1990 to 2003 All Buildings* ............................... 155 447 288 17,163 28,766 17,378 9.0 15.5 16.6 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 23 52 37 2,049 2,668 1,628 11.3 19.6 23.0 5,001 to 10,000 .............................. 15 35 27 1,859 2,854 1,484 8.1 12.2 18.1 10,001 to 25,000 ............................ 27 55 37 3,141 4,907 3,322 8.5 11.3 11.2

279

Consumption & Efficiency - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Consumption & Efficiency Consumption & Efficiency Glossary › FAQS › Overview Data Residential Energy Consumption Survey Data Commercial Energy Consumption Survey Data Manufacturing Energy Consumption Survey Data Vehicle Energy Consumption Survey Data Energy Intensity Consumption Summaries Average cost of fossil-fuels for electricity generation All Consumption & Efficiency Data Reports Analysis & Projections All Sectors Commercial Buildings Efficiency Manufacturing Projections Residential Transportation All Reports An Assessment of EIA's Building Consumption Data Background image of CNSTAT logo The U.S. Energy Information Administration (EIA) routinely uses feedback from customers and outside experts to help improve its programs and products. As part of an assessment of its consumption

280

Energy Consumption Issues on Mobile Network Systems  

Science Conference Proceedings (OSTI)

This paper describes energy consumption demographic data in operating real mobile networks. We examine published data from NTT DoCoMo, which is the largest mobile telecommunication operator in Japan and operating nation-wide 3G networks, and identify ... Keywords: Moble Network, Power Consumption, Battery, CO2, Green Network

Minoru Etoh; Tomoyuki Ohya; Yuji Nakayama

2008-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Predicting summer energy consumption from homeowners attitudes  

SciTech Connect

Two surveys examined the relationship between homeowners attitudes toward energy use and their actual summer electric consumption. In Survey 1, 56 couples filled out questionnaires concerning their energy attitudes. A factor analysis of their responses revealed four factors: comfort and health concerns, effort to conserve and monetary savings, role of the individual, and legitimacy of the energy crisis. The factors were entered into a multiple regression analysis to predict actual summer electric consumption. The attitudinal factors together significantly accounted for 55% of the variance in summer electric consumption. The comfort and health factor by itself explained 30% of the consumption variance. Survey 2, consisting of 69 couples, was conducted to elaborate the meaning of the factors. The results of the factor analysis of Survey 2 revealed six factors: comfort, health, individual's role, belief in science, legitimacy of the energy crisis, and effort to conserve. An overall regression analysis showed that the factors significantly explained nearly 60% of the summer consumption variance. The comfort factor was again the best predictor of summer electric consumption, accounting for 42% of the variance. It was concluded that attitudes about one's comfort are significantly related to household energy consumption (primarily air conditioning). The implications for energy conservation campaigns were discussed. 10 references, 3 tables.

Seligman, C.; Kriss, M.; Darley, J.M.; Fazio, R.H.; Becker, L.J.; Pryor, J.B.

1979-01-01T23:59:59.000Z

282

Annual Energy Outlook Forecast Evaluation - Tables 2-18  

Gasoline and Diesel Fuel Update (EIA)

Total Energy Consumption: AEO Forecasts, Actual Values, and Total Energy Consumption: AEO Forecasts, Actual Values, and Absolute and Percent Errors, 1985-1999 Publication 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Average Absolute Error (Quadrillion Btu) AEO82 79.1 79.6 79.9 80.8 82.0 83.3 1.8 AEO83 78.0 79.5 81.0 82.4 83.8 84.6 89.5 1.2 AEO84 78.5 79.4 81.2 83.1 85.0 86.4 93.5 1.5 AEO85 77.6 78.5 79.8 81.2 82.6 83.3 84.2 85.2 85.9 86.7 87.7 1.3 AEO86 77.0 78.8 79.8 80.6 81.5 82.9 84.0 84.8 85.7 86.5 87.9 88.4 87.8 88.7 3.6 AEO87 78.9 80.0 81.9 82.8 83.9 85.3 86.4 87.5 88.4 1.5 AEO89 82.2 83.7 84.5 85.4 86.4 87.3 88.2 89.2 90.8 91.4 90.9 91.7 1.8

283

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.

284

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.

285

State energy data report 1995 - consumption estimates  

Science Conference Proceedings (OSTI)

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.

NONE

1997-12-01T23:59:59.000Z

286

UN Alcohol Energy Data: Consumption by Other Consumers The Energy  

Open Energy Info (EERE)

Other Consumers The Energy Statistics Database contains comprehensive energy statistics on the production, trade, conversion and final consumption of primary and secondary;...

287

Residential Energy Consumption - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

The Residential Energy Consumption Survey provides national and regional information about U.S. households and their energy usage. The first survey was conducted in 1978.

288

Number, Energy Consumption, and Energy-Related Carbon ...  

U.S. Energy Information Administration (EIA)

Tabulation of changes in the number, energy consumption, and energy-related carbon emissions of U.S. households, 1980-1997.

289

Floorspace, Energy Consumption, and Energy-Related Carbon ...  

U.S. Energy Information Administration (EIA)

Tabulation of changes in the amount of floorspace, energy consumption, and energy-related carbon emissions of U.S. commercial buildings, 1979-1995.

290

Figure 66. Change in delivered energy consumption for energy ...  

U.S. Energy Information Administration (EIA)

Change in delivered energy consumption for energy-intensive industries in three cases, 2011-2040 ... Iron and steel Bulk chemicals Glass Paper products Food products

291

California Energy Commission - Electricity Consumption by County  

Open Energy Info (EERE)

County (2006-2009) Electricity consumption data from the California Energy Commission sorted by County for Residential and Non-residential from 2006 to 2009.


...

292

Illinois energy consumption 1963-1977  

SciTech Connect

This report contains current and historical Illinois energy consumption data by consuming sector and fuel type. It also contains detailed description of mapping techniques used in developing the data.

Hill, L.; Biermann, W.

1979-06-01T23:59:59.000Z

293

OpenEI - Renewable Energy Consumption  

Open Energy Info (EERE)

Jul 2011 18:05:28 +0000 Meredith1219 758 at http:en.openei.orgdatasets EIA Data: 2009 United States Renewable Energy Consumption by Sector and Source http:en.openei.org...

294

Using occupancy to reduce energy consumption of buildings  

E-Print Network (OSTI)

breakdown of the energy consumption of the CSE mixed- useFigure 3.7: The energy consumption of HVAC during ourSpring 2011 tests - Energy consumption for electricity and

Balaji, Bharathan

2011-01-01T23:59:59.000Z

295

Household Vehicles Energy Consumption 1991  

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

3. 3. Vehicle Miles Traveled This chapter presents information on household vehicle usage, as measured by the number of vehicle miles traveled (VMT). VMT is one of the two most important components used in estimating household vehicle fuel consumption. (The other, fuel efficiency, is discussed in Chapter 4). In addition, this chapter examines differences in driving behavior based on the characteristics of the household and the type of vehicle driven. Trends in household driving patterns are also examined using additional information from the Department of Transportation's Nationwide Personal Transportation Survey (NPTS). Household VMT is a measure of the demand for personal transportation. Demand for transportation may be viewed from either an economic or a social perspective. From the economic point-of-view, the use of a household vehicle represents the consumption of one

296

TV Energy Consumption Trends and Energy-Efficiency Improvement Options  

E-Print Network (OSTI)

3D Technology and its Display Trends. ” DisplaySearch, 20102010. “3D TV Technology Trend and Forecast” LG Electronics,Price et al. 2006. “Sectoral Trends in Global Energy Use and

Park, Won Young

2011-01-01T23:59:59.000Z

297

Hybrid modeling of industrial energy consumption and greenhouse gas emissions with an application to Canada  

E-Print Network (OSTI)

Hybrid modeling of industrial energy consumption and greenhouse gas emissions with an application explore the implications for Canada's industrial sector of an economy-wide, compulsory greenhouse gas of these strengths is linked to challenges when it comes to forecasting the impact of greenhouse gas policy. We

298

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

U.S. Energy Information Administration (EIA)

A B C D E F G H I J K L M N O P Q R S T U V W XYZ ‹ Consumption & Efficiency Manufacturing Energy Consumption Survey (MECS) Glossary ...

299

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

The International Energy Outlook 2005 (IEO2005) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2025. U.S. projections appearing in IEO2005 are consistent with those published in EIA's Annual Energy Outlook 2005 (AEO2005), which was prepared using the National Energy Modeling System (NEMS). The International Energy Outlook 2005 (IEO2005) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2025. U.S. projections appearing in IEO2005 are consistent with those published in EIA's Annual Energy Outlook 2005 (AEO2005), which was prepared using the National Energy Modeling System (NEMS). Table of Contents Projection Tables Reference Case High Economic Growth Case Low Economic Growth Case Reference Case Projections by End-Use Sector and Region Projections of Oil Production Capacity and Oil Production in Three Cases Projections of Nuclear Generating Capacity Highlights World Energy and Economic Outlook Outlook for World Energy Consumption World Economic Outlook Alternative Growth Cases

300

Study on optimal train movement for minimum energy consumption.  

E-Print Network (OSTI)

?? The presented thesis project is a study on train energy consumption calculation and optimal train driving strategies for minimum energy consumption. This study is… (more)

Gkortzas, Panagiotis

2013-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Manufacturing Energy Consumption Survey (MECS) - Data - U.S....  

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

| 1998 | 1994 | 1991 | Archive Data Methodology & Forms + EXPAND ALL Consumption of Energy for All Purposes (First Use) Total First Use (formerly Primary Consumption) of Energy...

302

EIA Data: Total International Primary Energy Consumption

This...  

Open Energy Info (EERE)

EIA Data: Total International Primary Energy Consumption

This table lists total primary energy consumption by country and region in Quadrillion Btu.  Figures in this table...

303

Residential Energy Consumption for Water Heating (2005) Provides...  

Open Energy Info (EERE)

Residential Energy Consumption for Water Heating (2005) Provides total and average annual residential energy consumption for water heating in U.S. households in 2005, measured in...

304

California Energy Commission - Natural Gas Consumption by Utility  

Open Energy Info (EERE)

California Energy Commission - Natural Gas Consumption by Utility (1990-2009) California Energy Commission natural gas consumption data by Utility company for Commercial,...

305

Energy forecasting: the troubled past of looking the future  

SciTech Connect

Energy forecasts have hardly been distinguished by their accuracy. Why forecasts go awry, and the impact these prominent tools have, is explored. A brief review of the record is given. Because of their allure, their popularity in he media, and their usefulness as tools in political battles, forecasts have played a significant role so far. The danger is that they represent and enhance a fix 'em up, tinkering approach, to the detriment of more efficient free-market policies.

Kutler, E.

1986-01-01T23:59:59.000Z

306

Consumption  

E-Print Network (OSTI)

www.eia.gov Annual Energy Outlook 2013 projections to 2040 • Growth in energy production outstrips consumption growth • Crude oil production rises sharply over the next decade • Motor gasoline consumption reflects more stringent fuel economy standards • The U.S. becomes a net exporter of natural gas in the early 2020s • U.S. energy-related carbon dioxide emissions remain below their 2005 level through 2040

Adam Sieminski Administrator; Adam Sieminski; Adam Sieminski; Adam Sieminski; Adam Sieminski

2013-01-01T23:59:59.000Z

307

Video game console usage and national energy consumption: Results from a field-metering study  

E-Print Network (OSTI)

console usage and national energy consumption: Results fromNational Energy Consumption .Discussion National Energy Consumption Under the assumption

Desroches, Louis-Benoit

2013-01-01T23:59:59.000Z

308

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

E-Print Network (OSTI)

commercial). National Energy Consumption Estimates We usedsection entitled “National Energy Consumption Estimates”).section entitled “National Energy Consumption Estimates”).

Apte, Joshua; Arasteh, Dariush

2008-01-01T23:59:59.000Z

309

Figure 1.6 State-Level Energy Consumption Estimates and Estimated ...  

U.S. Energy Information Administration (EIA)

Figure 1.6 State-Level Energy Consumption Estimates and Estimated Consumption per Capita, 2010 Consumption Consumption per Capita

310

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

Gasoline and Diesel Fuel Update (EIA)

/HRIf /HRIf Residential Energy Consumption Survey. Consumption and Expenditures, April 1981 Through March 1982 an Part I: National Data Energy Information Administration Washington, D.C. (202) 20fr02 'O'Q 'uoifkjjUSBM ujiuud juaoiujeAog 'S'n siuawnooQ jo luapuaiuuadns - 0088-292 (202) 98S02 '0'Q 8f 0-d I 6ujp|ing uoiieflSjUjiup v UOIIBUJJOJU | ABjau 3 02-13 'jaiuao UOIJBUJJOJUI XBjaug IBUO!;BN noA pasopua s; uujoi japjo uy 'MO|aq jeadde sjaqoinu auoydajaj PUB sassajppv 'OI3N 9>4i oi papajip aq pinoqs X6jaue uo suotjsenQ '(OIBN) J9»ueo aqjeiMJO^ui ASjaug (BUOIJEN s,vi3 QMi JO OdO 941 UUGJJ peuiBiqo eq ABOI suoijBonqnd (vi3) UO!JBJ;S!UILUPV UOIIBUUJO|U| XBjeug jaiflo PUB SJMJ p ssBiiojnd PUB UOIIBLUJO^JI 6uuepjQ (Od9) 90IWO Bujjuud luetuujaAOQ -g'n 'sjuaiunooa p juapuaiuuedng aqt LUOJI aiqB||BAB si uoHBOjiqnd sjt|i

311

Energy consumption of building 39; Energy consumption of building thirty-nine.  

E-Print Network (OSTI)

??The MIT community has embarked on an initiative to the reduce energy consumption and in accordance with the Kyoto Protocol. This thesis seeks to further… (more)

Hopeman, Lisa Maria

2007-01-01T23:59:59.000Z

312

Wind forecasting objectives for utility schedulers and energy traders  

DOE Green Energy (OSTI)

The wind energy industry and electricity producers can benefit in a number of ways from increased wind forecast accuracy. Higher confidence in the reliability of wind forecasts can help persuade an electric utility to increase the penetration of wind energy into its operating system and to augment the capacity value of wind electric generation. Reliable forecasts can also assist daily energy traders employed by utilities in marketing the available and anticipated wind energy to power pools and other energy users. As the number of utilities with wind energy experience grows, and wind energy penetration levels increase, the need for reliable wind forecasts will likely grow as well. This period of wind energy growth also coincides with advances in computer weather prediction technology that could lead to more accurate wind forecasts. Thus, it is important to identify the type of forecast information needed by utility schedulers and energy traders. This step will help develop approaches to the challenge of wind forecasting that will result in useful products being supplied to utilities or other energy generating entities. This paper presents the objectives, approach, and current findings of a US Department of Energy National Renewable Energy Laboratory (DOE/NREL) initiative to develop useful wind forecasting tools for utilities involved with wind energy generation. The focus of this initiative thus far has been to learn about the needs of prospective utility users. NREL representatives conducted a series of onsite interviews with key utility staff, usually schedulers and research planners, at seven US utilities. The purpose was to ascertain information on actual scheduling and trading procedures, and how utilities could integrate wind forecasting into these activities.

Schwartz, M.N. [National Renewable Energy Lab., Golden, CO (United States); Bailey, B.H. [AWS Scientific, Inc., Albany, NY (United States)

1998-05-01T23:59:59.000Z

313

Performance Evaluation of Energy Consumption in MANETs  

E-Print Network (OSTI)

The mobility of nodes in MANET may result in dynamic topology with high rate of link breakage and network partitions leading to interruption in communication and packet loss. Many routing protocols have been proposed in the literature with different characteristics and properties. The routing protocols suffer from various overheads causing energy loss which is further aggravated by link breaks. The present work concentrate on the energy consumption issues of routing protocols. We have evaluated the performance of DSDV, DSR and AODV routing protocols with respect to energy consumption indicating their usage of node’s energy.

Ashish Kumar; M. Q. Rafiq; Kamal Bansal

2012-01-01T23:59:59.000Z

314

Appliance Energy Consumption in Australia | Open Energy Information  

Open Energy Info (EERE)

Appliance Energy Consumption in Australia Appliance Energy Consumption in Australia Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Appliance Energy Consumption in Australia Focus Area: Appliances & Equipment Topics: Policy Impacts Website: www.energyrating.gov.au/resources/program-publications/?viewPublicatio Equivalent URI: cleanenergysolutions.org/content/appliance-energy-consumption-australi DeploymentPrograms: Industry Codes & Standards Regulations: Appliance & Equipment Standards and Required Labeling The document sets out the equations necessary to calculate the star rating index for appliances that carry an energy label in Australia. Equations for new air conditioner and refrigerator algorithms from April 2010 are included. Televisions, which have carried a mandatory energy label from

315

Energy Consumption of Die Casting Operations  

SciTech Connect

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.

Jerald Brevick; clark Mount-Campbell; Carroll Mobley

2004-03-15T23:59:59.000Z

316

Consumption & Efficiency - U.S. Energy Information Administration (EIA)  

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

Consumption & Efficiency Consumption & Efficiency Glossary › FAQS › Overview Data Residential Energy Consumption Survey Data Commercial Energy Consumption Survey Data Manufacturing Energy Consumption Survey Data Vehicle Energy Consumption Survey Data Energy Intensity Consumption Summaries Average cost of fossil-fuels for electricity generation All Consumption & Efficiency Data Reports Analysis & Projections All Sectors Commercial Buildings Efficiency Manufacturing Projections Residential Transportation All Reports Technical Workshop on Behavior Economics Presentations Technical Workshop on Behavior Economics Presentations Cost of Natural Gas Used in Manufacturing Sector Has Fallen Graph showing Cost of Natural Gas Used in Manufacturing Sector Has Fallen Source: U.S. Energy Information Administration, Manufacturing Energy

317

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

E-Print Network (OSTI)

of Commercial Building Energy Consumption in China, 2008,Residential Energy Consumption Survey, Human and Socialfor Residential Energy Consumption in China Nan Zhou,

Zhou, Nan

2010-01-01T23:59:59.000Z

318

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

E-Print Network (OSTI)

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

Zhou, Nan

2010-01-01T23:59:59.000Z

319

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

by Year Constructed for Non-Mall Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity...

320

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

by Building Size for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity...

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

by Year Constructed for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity...

322

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

by Census Region for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity...

323

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

by Climate Zonea for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity...

324

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

Census Division for All Buildings, 2003: Part 1 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity...

325

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

Buildings, 2003 Electricity Consumption Electricity Expenditures per Building (thousand kWh) per Square Foot (kWh) Distribution of Building-Level Intensities (kWhsquare foot)...

326

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

Census Division for All Buildings, 2003: Part 2 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity...

327

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

Census Division for All Buildings, 2003: Part 3 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings Using Electricity (million square feet) Electricity...

328

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

Open Energy Info (EERE)

Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Jump to: navigation, search LEDSGP green logo.png FIND MORE DIA TOOLS This tool is part of the Development Impacts Assessment (DIA) Toolkit from the LEDS Global Partnership. Tool Summary LAUNCH TOOL Name: Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Agency/Company /Organization: Energy Sector Management Assistance Program of the World Bank Sector: Energy Focus Area: Non-renewable Energy Topics: Baseline projection, Co-benefits assessment, GHG inventory Resource Type: Software/modeling tools User Interface: Spreadsheet Complexity/Ease of Use: Simple Website: www.esmap.org/esmap/EFFECT Cost: Free Equivalent URI: www.esmap.org/esmap/EFFECT Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Screenshot

330

Manufacturing Consumption of Energy 1991  

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

at the extent to which manufacturers exercised their ability to choose the mix of energy sources at their discretion. Nonswitchable Minimum Requirements Generally, a...

331

Manufacturing Consumption of Energy 1991  

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

establishments within a stratum would also be homogeneous with respect to the quantities, types, and shares of energy consumed as fuels and for nonfuel purposes. Also, the weight...

332

Manufacturing Consumption of Energy 1991  

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

with Other Series Appendix D Comparability of MECS Estimates with Other Series The Energy Information Administration (EIA) collects data from two distinct sources that, in...

333

Household energy consumption and expenditures 1987  

SciTech Connect

This report is the third in the series of reports presenting data from the 1987 Residential Energy Consumption Survey (RECS). The 1987 RECS, seventh in a series of national surveys of households and their energy suppliers, provides baseline information on household energy use in the United States. Data from the seven RECS and its companion survey, the Residential Transportation Energy Consumption Survey (RTECS), are made available to the public in published reports such as this one, and on public use data files. This report presents data for the four Census regions and nine Census divisions on the consumption of and expenditures for electricity, natural gas, fuel oil and kerosene (as a single category), and liquefied petroleum gas (LPG). Data are also presented on consumption of wood at the Census region level. The emphasis in this report is on graphic depiction of the data. Data from previous RECS surveys are provided in the graphics, which indicate the regional trends in consumption, expenditures, and uses of energy. These graphs present data for the United States and each Census division. 12 figs., 71 tabs.

Not Available

1990-01-22T23:59:59.000Z

334

Federal Energy Management Program: Data Center Energy Consumption Trends  

NLE Websites -- All DOE Office Websites (Extended Search)

Consumption Trends Consumption Trends Data centers can consume up to 100 times more energy than a standard office building. Often, less than 15% of original source energy is used for the information technology equipment within a data center. Figure 1 outlines typical data center energy consumption ratios. An illustration that features a graphic of a coal container representing 100 units of coal. This enters a graphic of a power plant, where those 100 units of coal are turned into 35 units of energy. The 35 units of energy are distributed by power lines, represented by a graphic of power lines, where 33 units are delivered to a pie chart representing data typical data center energy end use. The data center pie chart features 48% representing server load and computing operation consumption; 43% representing cooling equipment consumption; and 9% representing power conversion and distribution consumption.

335

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

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

Cost of Natural Gas Used in Manufacturing Sector Has Fallen Graph showing Cost of Natural Gas Used in Manufacturing Sector Has Fallen Source: U.S. Energy Information Administration, Manufacturing Energy Consumption Survey (MECS) 1998-2010, September 6, 2013. New 2010 Manufacturing Energy Consumption Survey (MECS) Data Released › Graph showing total U.S. manufacturing energy consumption for all purposes has declined 17 percent from 2002 to 2010. Source: U.S. Energy Information Administration, Manufacturing Energy Consumption Data Show Large Reductions in Both Manufacturing Energy Use and the Energy Intensity of Manufacturing Activity between 2002 and 2010, March 19, 2013. First Estimates from 2010 Manufacturing Energy Consumption Survey (MECS) Released ›

336

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

U.S. Energy Information Administration (EIA)

Sales, revenue and prices, power plants, fuel use, stocks, generation, trade, demand & emissions. Consumption & Efficiency. Energy use in homes, commercial buildings, ...

337

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

U.S. Energy Information Administration (EIA)

Cost of Natural Gas Used in Manufacturing Sector ... Early-release estimates from the 2010 MECS show that energy consumption in the manufacturing sector decreased ...

338

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

U.S. Energy Information Administration (EIA)

Early-release estimates from the 2010 MECS show that energy consumption in the manufacturing sector decreased between 2006 and 2010. Release Date: March 28, 2012.

339

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

U.S. Energy Information Administration (EIA)

Early-release estimates from the 2010 MECS show that energy consumption in the manufacturing sector decreased between 2006 and 2010. Release Date: ...

340

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

U.S. Energy Information Administration (EIA)

A-Z Index A B C D E F G H I J K L M ... Manufacturing energy consumption data show large reductions in both manufacturing energy use and the energy intensity of ...

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Monitoring and Management of Refinery Energy Consumption  

E-Print Network (OSTI)

Since 1972, the U.S. refining industry has made much progress in reducing energy consumption. Lately, falling energy prices have de-emphasized the need to appropriate new capital for additional energy conservation projects. One area neglected in most refineries is the need to monitor and manage the daily use of energy. Setting up an energy auditing system will tell management how well each unit in the refinery is being operated and can be used as a valuable tool in reducing energy costs. An example of an energy monitorirg and management system is discussed and illustrated with examples.

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

1986-06-01T23:59:59.000Z

342

State Energy Data System Consumption Estimates Technical Notes  

U.S. Energy Information Administration (EIA)

as street lighting and public services; and the Manufacturing Energy Consumption Survey covers only manufacturing establishments,

343

Renewable energy consumption and economic efficiency: Evidence from European countries  

Science Conference Proceedings (OSTI)

This paper examines the relationship between renewable energy consumption and economic efficiency. For this reason

2013-01-01T23:59:59.000Z

344

Household Vehicles Energy Consumption 1991  

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

Aggregate Aggregate Ratio: See Mean and Ratio Estimate. AMPD: Average miles driven per day. See Appendix B, "Estimation Methodologies." Annual Vehicle Miles Traveled: See Vehicle Miles Traveled. Automobile: Includes standard passenger car, 2-seater car and station wagons; excludes passenger vans, cargo vans, motor homes, pickup trucks, and jeeps or similar vehicles. See Vehicle. Average Household Energy Expenditures: A ratio estimate defined as the total household energy expenditures for all RTECS households divided by the total number of households. See Ratio Estimate, and Combined Household Energy Expenditures. Average Number of Vehicles per Household: The average number of vehicles used by a household for personal transportation during 1991. For this report, the average number of vehicles per household is computed as the ratio of the total number of vehicles to the

345

The Impact of Distributed Programming Abstractions on Application Energy Consumption  

E-Print Network (OSTI)

The Impact of Distributed Programming Abstractions on Application Energy Consumption Young-Woo Kwon measure and analyze the impact of distributed programming abstractions on application energy consumption future efforts in creating energy efficient distributed programming abstractions. Keywords: energy

Ryder, Barbara G.

346

Consumption & Efficiency - Analysis & Projections - U.S. Energy ...  

U.S. Energy Information Administration (EIA)

Energy Technologies on the Horizon (released in AEO2006) ... A key issue in mid-term forecasting is the representation of changing and developing technologies.

347

Table 37. Light-Duty Vehicle Energy Consumption by Technology ...  

U.S. Energy Information Administration (EIA)

Table 37. Light-Duty Vehicle Energy Consumption by Technology Type and Fuel Type (trillion Btu) Light-Duty Consumption by Technology Type Conventional Vehicles 1/

348

Cost forecasts: Euyropean International High-Energy Physics facilities - Million Swiss Francs at 1966 prices  

E-Print Network (OSTI)

Cost forecasts: Euyropean International High-Energy Physics facilities - Million Swiss Francs at 1966 prices

ECFA meeting

1966-01-01T23:59:59.000Z

349

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

DOE Green Energy (OSTI)

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

Lantz, E.; Hand, M.

2010-05-01T23:59:59.000Z

350

The Value of Seasonal Climate Forecasts in Managing Energy Resources  

Science Conference Proceedings (OSTI)

Research and interviews with officials of the United States energy industry and a systems analysis of decision making in a natural gas utility lead to the conclusion that seasonal climate forecasts would only have limited value in fine tuning the ...

Edith Brown Weiss

1982-04-01T23:59:59.000Z

351

Consumption & Efficiency - U.S. Energy Information Administration ...  

U.S. Energy Information Administration (EIA)

Energy use in homes, commercial buildings, manufacturing, and transportation. Coal. ... New 2010 Manufacturing Energy Consumption Survey (MECS) ...

352

A model for Long-term Industrial Energy Forecasting (LIEF)  

SciTech Connect

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model's parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

Ross, M. (Lawrence Berkeley Lab., CA (United States) Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.); Hwang, R. (Lawrence Berkeley Lab., CA (United States))

1992-02-01T23:59:59.000Z

353

A model for Long-term Industrial Energy Forecasting (LIEF)  

SciTech Connect

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model`s parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

Ross, M. [Lawrence Berkeley Lab., CA (United States)]|[Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics]|[Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.; Hwang, R. [Lawrence Berkeley Lab., CA (United States)

1992-02-01T23:59:59.000Z

354

Measuring energy consumption of a database cluster  

E-Print Network (OSTI)

Abstract: Energy consumption of database servers is a growing concern for companies as it is a critical part of a data center’s cost. To address the rising cost and the waste of energy, a new paradigm called GreenIT arose. Hardware and software developers are aiming at more energy-efficient systems. To improve the energy footprint of database servers, we developed a cluster of small-scale nodes, that can be dynamically powered dependent on the workload. This demo shows the measurement framework we set up to measure hardware components as well as an entire cluster of nodes. We’ll exhibit the measurement devices for components and servers and show the system’s behavior under varying workloads. Attendees will be able to adjust workloads and experience their impact on energy consumption. 1

Volker Hudlet; Daniel Schall; Ag Dbis; Tu Kaiserslautern

2011-01-01T23:59:59.000Z

355

State Residential Energy Consumption Shares  

Gasoline and Diesel Fuel Update (EIA)

This next slide shows what fuels are used in the residential market. When a This next slide shows what fuels are used in the residential market. When a energy supply event happens, particularly severe winter weather, it is this sector that the government becomes most concerned about. As you can see, natural gas is very important to the residential sector not only in DC, MD and VA but in the United States as well. DC residents use more natural gas for home heating than do MD and VA. While residents use heating oil in all three states, this fuel plays an important role in MD and VA. Note: kerosene is included in the distillate category because it is an important fuel to rural households in MD and VA. MD and VA rely more on electricity than DC. Both MD and VA use propane as well. While there are some similarities in this chart, it is interesting to note

356

Using occupancy to reduce energy consumption of buildings  

E-Print Network (OSTI)

Figure 4.4: Power consumption of a desktop PC + 3 LCDChapter 2 Trends in Building Consumption 2.1 UCSD as abreakdown of the energy consumption of the CSE mixed- use

Balaji, Bharathan

2011-01-01T23:59:59.000Z

357

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

8A. District Heat Consumption and Expenditure Intensities for All Buildings, 2003 8A. District Heat Consumption and Expenditure Intensities for All Buildings, 2003 District Heat Consumption District Heat Expenditures per Building (million Btu) per Square Foot (thousand Btu) per Building (thousand dollars) per Square Foot (dollars) per Thousand Pounds (dollars) All Buildings ................................ 9,470 113.98 108.4 1.31 11.45 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ Q Q Q Q Q 5,001 to 10,000 .............................. Q Q Q Q Q 10,001 to 25,000 ............................ Q Q Q Q Q 25,001 to 50,000 ............................ Q Q Q Q Q 50,001 to 100,000 .......................... Q Q Q Q Q 100,001 to 200,000 ........................ 17,452 118.10 Q Q Q

358

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

3A. Total Fuel Oil Consumption and Expenditures for All Buildings, 2003 3A. Total Fuel Oil Consumption and Expenditures for All Buildings, 2003 All Buildings Using Fuel Oil Fuel Oil Consumption Fuel Oil Expenditures Number of Buildings (thousand) Floorspace (million square feet) Floorspace per Building (thousand square feet) Total (trillion Btu) Total (million gallons) Total (million dollars) All Buildings ................................ 465 16,265 35 228 1,644 1,826 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 211 606 3 34 249 292 5,001 to 10,000 .............................. 102 736 7 36 262 307 10,001 to 25,000 ............................ 66 1,043 16 28 201 238 25,001 to 50,000 ............................ 24 895 38 17 124 134 50,001 to 100,000 .......................... 25 1,852 76 29 209 229

359

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

7A. Total District Heat Consumption and Expenditures for All Buildings, 2003 7A. Total District Heat Consumption and Expenditures for All Buildings, 2003 All Buildings Using District Heat District Heat Consumption District Heat Expenditures Number of Buildings (thousand) Floorspace (million square feet) Floorspace per Building (thousand square feet) Total (trillion Btu) Total (million dollars) All Buildings ................................ 67 5,576 83 636 7,279 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ Q Q Q Q Q 5,001 to 10,000 .............................. Q Q Q Q Q 10,001 to 25,000 ............................ 18 289 16 Q Q 25,001 to 50,000 ............................ 10 369 35 Q Q 50,001 to 100,000 .......................... 8 574 70 Q Q 100,001 to 200,000 ........................ 9 1,399 148 165 Q

360

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

3A. Total Natural Gas Consumption and Expenditures in All Buildings, 2003 3A. Total Natural Gas Consumption and Expenditures in All Buildings, 2003 All Buildings Using Natural Gas Natural Gas Consumption Natural Gas Expenditures Number of Buildings (thousand) Floorspace (million square feet) Floorspace per Building (thousand square feet) Total (trillion Btu) Total (billion cubic feet) Total (million dollars) All Buildings ................................ 2,538 48,473 19.1 2,100 2,037 16,010 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 1,134 3,175 2.8 257 249 2,227 5,001 to 10,000 .............................. 531 3,969 7.5 224 218 1,830 10,001 to 25,000 ............................ 500 7,824 15.6 353 343 2,897 25,001 to 50,000 ............................ 185 6,604 35.8 278 270 2,054

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Minneapolis residential energy consumption. Final report  

SciTech Connect

This report deals with residential energy consumption in single - family, townhouse, low - rise, and high - rise structures in Minnapolis, Minn., with the year 1957 chosen as a typical weather year for the area. Design and structural features considered important in defining the residences were structural parameters (construction details, dimensions, and materials), energy consumption parameters (heating and cooling equipment, types of fuels and energy used, and appliances and their energy consumption levels), and lifestyle parameters (thermostat set points, relative humidity set points, type and number of appliances, daily profile of appliance use, and use of ventilation fans). Annual heating and cooling loads and resultant energy requirements were calculated using a time - response computer program. This program included subroutines for determining hourly load contributions throughout the year due to conduction, convection, air infiltration, radiation, and internal heat gain. The heating load was significantly higher than the cooling load for single - family and townhouse residences, as would be expected for the cold Minneapolis climate. Due to increased internal heat generation, low - rise and high - rise cooling and heating loads were similar in magnitude. Energy - conserving modifications involving both structural and comfort control system changes resulted in the following: single - family residences consumed 47 percent, townhouse residences consumed 52 percent, low - rise residences consumed 53 percent, and high - rise residences consumed 34 percent of the primary energy required by the characteristic residence. Supporting data, layouts of the residences, and references are included.

Reed, J.E.; Barber, J.E.; White, B.

1976-11-01T23:59:59.000Z

362

Energy consumption in the pipeline industry  

SciTech Connect

Estimates are developed of the energy consumption and energy intensity (EI) of five categories of U.S. pipeline industries: natural gas, crude oil, petroleum products, coal slurry, and water. For comparability with other transportation modes, it is desirable to calculate EI in Btu/Ton-Mile, and this is done, although the necessary unit conversions introduce additional uncertainties. Since water and sewer lines operate by lift and gravity, a comparable EI is not definable.

Banks, W. F.

1977-12-31T23:59:59.000Z

363

Table 1.5 Energy Consumption, Expenditures, and Emissions ...  

U.S. Energy Information Administration (EIA)

Consumption per Capita: Energy Expenditures 1: Energy ... 2009. 94,559,407 [R] 308 : 1,061,220 [R] ... 2 Carbon dioxide emissions from energy consumption. See Table 11.1.

364

Energy Information Administration/Household Vehicles Energy Consumption 1994  

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

, , Energy Information Administration/Household Vehicles Energy Consumption 1994 ix Household Vehicles Energy Consumption 1994 presents statistics about energy-related characteristics of highway vehicles available for personal use by members of U.S. households. The data were collected in the 1994 Residential Transportation Energy Consumption Survey, the final cycle in a series of nationwide energy consumption surveys conducted during the 1980's and 1990's by the Energy Information Administrations. Engines Became More Powerful . . . Percent Distribution of Total Residential Vehicle Fleet by Number of Cylinders, 1988 and 1994 Percent Distribution of Vehicle Fleet by Engine Size, 1988 and 1994 Percent Percent 4 cyl Less than 2.50 liters 6 cyl 2.50- 4.49 liters 8 cyl 4.50 liters or greater 20 20 40 40 Vehicle

365

Manufacturing Energy Consumption Survey (MECS) - Data - U.S. Energy  

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

1 MECS Survey Data 2010 | 2006 | 2002 | 1998 | 1994 | 1991 | Archive 1 MECS Survey Data 2010 | 2006 | 2002 | 1998 | 1994 | 1991 | Archive Data Methodology & Forms + EXPAND ALL Consumption of Energy for All Purposes (First Use) Total Primary Consumption of Energy for All Purposes by Census Region, Industry Group, and Selected Industries, 1991: Part 1 (Estimates in Btu or Physical Units) XLS Total Primary Consumption of Energy for All Purposes by Census Region, Industry Group, and Selected Industries, 1991: Part 2 (Estimates in Trillion Btu) XLS Total Consumption of LPG, Distillate Fuel Oil, and Residual Fuel Oil for Selected Purposes by Census Region, Industry Group, and Selected Industries, 1991 (Estimates in Barrels per Day) XLS Total Primary Consumption of Energy for All Purposes by Census Region and Economic Characteristics of the Establishment, 1991 (Estimates in Btu or Physical Units) XLS

366

Residential Energy Consumption Survey (RECS) - Energy ...  

U.S. Energy Information Administration (EIA)

Energy Information Administration - EIA - Official Energy Statistics from the U.S. Government ... solar, wind, geothermal, ... particularly for space heating, ...

367

Annual Energy Outlook with Projections to 2025 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Annual Energy Outlook 2005 Forecast Comparisons Table 32. Forecasts of annual average economic growth, 2003-2025 Printer Friendly Version Average annual percentage growth Forecast 2003-2009 2003-2014 2003-2025 AEO2004 3.5 3.2 3.0 AEO2005 Reference 3.4 3.3 3.1 Low growth 2.9 2.8 2.5 High growth 4.1 3.9 3.6 GII 3.4 3.2 3.1 OMB 3.6 NA NA CBO 3.5 3.1 NA OEF 3.5 3.5 NA Only one other organization—Global Insight, Incorporated (GII)—produces a comprehensive energy projection with a time horizon similar to that of AEO2005. Other organizations address one or more aspects of the energy markets. The most recent projection from GII, as well as other forecasts that concentrate on economic growth, international oil prices, energy

368

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

Table C13. Total Electricity Consumption and Expenditures for Non-Mall Buildings, 2003 All Buildings* Using Electricity Electricity Consumption Electricity Expenditures Number of Buildings (thousand) Floorspace (million square feet) Floorspace per Building (thousand square feet) Primary Site Total (million dollars) Total (trillion Btu) Total (trillion Btu) Total (billion kWh) All Buildings* ............................... 4,404 63,307 14.4 9,168 3,037 890 69,032 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 2,384 6,346 2.7 1,164 386 113 10,348 5,001 to 10,000 .............................. 834 6,197 7.4 790 262 77 7,296 10,001 to 25,000 ............................ 727 11,370 15.6 1,229 407 119 10,001

369

Electrical energy consumption control apparatuses and electrical energy consumption control methods  

DOE Patents (OSTI)

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.

Hammerstrom, Donald J.

2012-09-04T23:59:59.000Z

370

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

4A. Fuel Oil Consumption and Expenditure Intensities for All Buildings, 2003 4A. Fuel Oil Consumption and Expenditure Intensities for All Buildings, 2003 Fuel Oil Consumption Fuel Oil Expenditures per Building (gallons) per Square Foot (gallons) per Building (thousand dollars) per Square Foot (dollars) per Gallon (dollars) All Buildings ................................ 3,533 0.10 3.9 0.11 1.11 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 1,177 0.41 1.4 0.48 1.18 5,001 to 10,000 .............................. 2,573 0.36 3.0 0.42 1.17 10,001 to 25,000 ............................ 3,045 0.19 3.6 0.23 1.18 25,001 to 50,000 ............................ 5,184 0.14 5.6 0.15 1.09 50,001 to 100,000 .......................... 8,508 0.11 9.3 0.12 1.10 100,001 to 200,000 ........................ 12,639 0.09 13.1 0.09 1.03

371

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

4A. Electricity Consumption and Expenditure Intensities for All Buildings, 2003 4A. Electricity Consumption and Expenditure Intensities for All Buildings, 2003 Electricity Consumption Electricity Expenditures per Building (thousand kWh) per Square Foot (kWh) Distribution of Building-Level Intensities (kWh/square foot) 25th Per- centile Median 75th Per- centile per Building (thousand dollars) per Square Foot (dollars) per kWh (dollars) All Buildings ................................ 226 14.9 3.8 8.8 18.1 17.9 1.18 0.079 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 48 17.8 3.8 9.0 20.0 4.4 1.63 0.092 5,001 to 10,000 .............................. 96 12.9 4.0 8.2 15.5 9.2 1.23 0.096 10,001 to 25,000 ............................ 178 11.4 3.1 7.2 15.0 15.2 0.97 0.086

372

Data Center Energy Consumption Trends | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Program Areas » Data Center Energy Efficiency » Data Center Program Areas » Data Center Energy Efficiency » Data Center Energy Consumption Trends Data Center Energy Consumption Trends October 8, 2013 - 10:09am Addthis Data centers can consume up to 100 times more energy than a standard office building. Often, less than 15% of original source energy is used for the information technology equipment within a data center. Figure 1 outlines typical data center energy consumption ratios. An illustration that features a graphic of a coal container representing 100 units of coal. This enters a graphic of a power plant, where those 100 units of coal are turned into 35 units of energy. The 35 units of energy are distributed by power lines, represented by a graphic of power lines, where 33 units are delivered to a pie chart representing data typical data center energy end use. The data center pie chart features 48% representing server load and computing operation consumption; 43% representing cooling equipment consumption; and 9% representing power conversion and distribution consumption.

373

Map Data: State Consumption | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Consumption Map Data: State Consumption stateconsumptionpc2009.csv More Documents & Publications Map Data: Renewable Production Map Data: State Spending...

374

Los angeles residential energy consumption. Final report  

SciTech Connect

Heating and cooling energy requirements were determined for characteristic single - family, townhouse, low - rise, and high - rise residences in Los Angeles, Calif. Using 1951 as a typical weather year for the area, heating and cooling energy requirements were determined for modified versions of these characteristic residences after both structural and comfort control modifications had been incorporated. Parameters of concern were structural (construction details, dimensions, and materials), energy consumption (heating and cooling equipment, types of fuel and energy used, and appliances and their energy consumption levels), and lifestyle (thermostat set points, relative humidity points, type and number of appliances, daily profile of appliance use, and use of ventilation fans). Annual heating and cooling loads and resultant energy requirements were calculated with the aid of a computer program. This program included subroutines for determining hourly load contributions throughout the year due to conduction, convection, air infiltration, radiation, and internal heat gain. The cooling load for the single - family residence was moderately larger than the heating load. Due to increased internal heat generation, the cooling load for the remaining residences was much larger than the heating load. Energy - conserving modifications resulted in the following: single - family residences required 55 percent, townhouse residences required 57 percent, low - rise residences required 55 percent, and high - rise residences required 82 percent of the primary energy consumed by the characteristic structure. Supporting data, illustrative layouts of the residences, and a list of references are included.

Reed, J.E.; Barber, J.E.; White, B.

1976-09-01T23:59:59.000Z

375

Energy Information Administration - Transportation Energy Consumption...  

NLE Websites -- All DOE Office Websites (Extended Search)

energy used by vehicles EIA conducts numerous energy-related surveys and other information programs. In general, the surveys can be divided into two broad groups: supply...

376

Residential Energy Consumption Survey (RECS) - Energy Information ...  

U.S. Energy Information Administration (EIA)

Energy use in homes, commercial buildings, ... State Energy Data System ... routinely uses feedback from customers and outside experts to help improve its programs ...

377

" Column: Energy-Consumption Ratios;"  

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

3 Consumption Ratios of Fuel, 2006;" 3 Consumption Ratios of Fuel, 2006;" " Level: National Data; " " Row: Values of Shipments within NAICS Codes;" " Column: Energy-Consumption Ratios;" " Unit: Varies." ,,,,"Consumption" ,,,"Consumption","per Dollar" ,,"Consumption","per Dollar","of Value" "NAICS",,"per Employee","of Value Added","of Shipments" "Code(a)","Economic Characteristic(b)","(million Btu)","(thousand Btu)","(thousand Btu)" ,,"Total United States" " 311 - 339","ALL MANUFACTURING INDUSTRIES"

378

" Column: Energy-Consumption Ratios;"  

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

3 Consumption Ratios of Fuel, 2002;" 3 Consumption Ratios of Fuel, 2002;" " Level: National Data; " " Row: Values of Shipments within NAICS Codes;" " Column: Energy-Consumption Ratios;" " Unit: Varies." " "," ",,,"Consumption"," " " "," ",,"Consumption","per Dollar" " "," ","Consumption","per Dollar","of Value","RSE" "NAICS",,"per Employee","of Value Added","of Shipments","Row" "Code(a)","Economic Characteristic(b)","(million Btu)","(thousand Btu)","(thousand Btu)","Factors"

379

How much of world energy consumption and electricity ...  

U.S. Energy Information Administration (EIA)

How much of world energy consumption and electricity generation is from renewable energy? EIA estimates that about 10% of world marketed energy ...

380

Table 2.1 Energy Consumption by Sector (Trillion Btu)  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration / Monthly Energy Review October 2013 23 Table 2.1 Energy Consumption by Sector (Trillion Btu) End-Use Sectors Electric

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Table 2.4 Industrial Sector Energy Consumption (Trillion Btu)  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration / Monthly Energy Review October 2013 29 Table 2.4 Industrial Sector Energy Consumption (Trillion Btu) Primary Consumptiona

382

Table US1. Total Energy Consumption, Expenditures, and Intensities ...  

U.S. Energy Information Administration (EIA)

Part 1: Housing Unit Characteristics and Energy Usage Indicators Energy Consumption 2 Energy Expenditures 2 Total U.S. (quadrillion Btu) Per Household (Dollars) Per

383

Commercial Buildings Energy Consumption Survey (CBECS) - U.S. Energy  

Gasoline and Diesel Fuel Update (EIA)

Estimation of Energy End-use Consumption Estimation of Energy End-use Consumption 2003 CBECS The energy end-use consumption tables for 2003 (Detailed Tables E1-E11 and E1A-E11A) provide estimates of the amount of electricity, natural gas, fuel oil, and district heat used for ten end uses: space heating, cooling, ventilation, water heating, lighting, cooking, refrigeration, personal computers, office equipment (including servers), and other uses. Although details vary by energy source (Table 1), there are four basic steps in the end-use estimation process: Regressions of monthly consumption on degree-days to establish reference temperatures for the engineering models, Engineering modeling by end use, Cross-sectional regressions to calibrate the engineering estimates and account for additional energy uses, and

384

Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption  

Buildings Energy Data Book (EERE)

0 2003 Commercial Primary Energy Consumption Intensities, by Principal Building Type Consumption Percent of Total | Consumption Percent of Total Building Type (thousand BtuSF)...

385

Atlanta residential energy consumption. Final report  

SciTech Connect

Energy consumption in Atlanta, Ga., was analyzed for single - family, townhouse, low - rise, and high - rise structures for 1955, which was selected as a typical weather year. A two - step procedure was employed in calculating energy requirements. In the first step, hourly heating and cooling loads were determined for each dwelling unit. In the second step, monthly and annual energy required to meet heating and cooling loads was calculated using specific heating, cooling, and ventilation systems. Design and structural features considered important in defining the residential structures were construction details and materials, heating and cooling equipment, types of fuels and energy used, and appliances and their energy consumption levels. Lifestyle parameters incorporated in the analysis included thermostat set points, relative humidity set points, type and number of appliances, daily profile of appliance use, and use of ventilation fans. The computer program for determining heating and cooling loads, or heat delivery / removal requirements, for each residence involved subroutines for ascertaining hourly load contributions throughout the year due to conduction, convection, air infiltration, radiation, and internal heat gain. The low - rise type of structure had a cooling load that was more than twice as large as the heating load. The other structures had cooling loads about 1.5 times as large as heating loads. Energy - conserving modifications, involving both structural and comfort control system changes, resulted in the following: single - family and townhouse residences achieved a 32 - percent annual heating load reduction and a 16 - percent cooling load reduction through structural modifications; and low - rise and high - rise residences achieved a 43 - percent reduction in primary energy consumption. Supporting data, illustrative layouts of the residences, and references are included.

Reed, J.E.; Barber, J.E.; White, B.

1976-08-01T23:59:59.000Z

386

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

E-Print Network (OSTI)

An important determinant of our energy future is the rate at which energy conservation technologies, once developed, are put into use. At Synergic Resources Corporation, we have adapted and applied a methodology to forecast the use of conservation technologies. This paper briefly discusses the observed patterns of the diffusion of new' technologies and the determinants (both sociological and economic) which have been proposed to explain the variation in the diffusion rates. Existing market penetration models are reviewed and their capability to forecast the use of conservation technologies is assessed using a set of criteria developed for this purpose. The reasoning behind the choice of criteria is discussed. The criteria includes the range of hypothesized influences to market penetration that are incorporated into the models and the applicability of the available parameter estimates. The attributes of our methodology and forecasting model choice (a behavioral lag equation developed by Mathtech, Inc.), are displayed using a list of the judgment criteria. This method was used to forecast the use of electricity conservation technologies in industries located in the Pacific Northwest for the Bonneville Power Administration.

Lang, K.

1982-01-01T23:59:59.000Z

387

Three Essays on Energy Economics and Forecasting  

E-Print Network (OSTI)

This dissertation contains three independent essays relating energy economics. The first essay investigates price asymmetry of diesel in South Korea by using the error correction model. Analyzing weekly market prices in the pass-through of crude oil, this model shows asymmetric price response does not exist at the upstream market but at the downstream market. Since time-variant residuals are found by the specified models for both weekly and daily retail prices at the downstream level, these models are implemented by a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) process. The estimated results reveal that retail prices increase fast in the rise of crude oil prices but decrease slowly in the fall of those. Surprisingly, retail prices rarely respond to changes of crude oil prices for the first five days. Based on collusive behaviors of retailers, this price asymmetry in Korea diesel market is explained. The second essay aims to evaluate the new incentive system for biodiesel in South Korea, which keeps the blend mandate but abolishes tax credits for government revenues. To estimate changed welfare from the new policy, a multivariate stochastic simulation method is applied into time-series data for the last five years. From the simulation results, the new biodiesel policy will lead government revenues to increases with the abolishment of tax credit. However, increased prices of blended diesel will cause to decrease demands of both biodiesel and blended diesel, so consumer and producer surplus in the transport fuel market will decrease. In the third essay, the Regression - Seasonal Autoregressive Integrated Moving Average (REGSARIMA) model is employed to predict the impact of air temperature on daily peak load demand in Houston. Compared with ARIMA and Seasonal Model, a REGARIMA model provides the more accurate prediction for daily peak load demand for the short term. The estimated results reveal air temperature in the Houston areas causes an increase in electricity consumption for cooling but to save that for heating. Since the daily peak electricity consumption is significantly affected by hot air temperature, this study makes a conclusion that it is necessary to establish policies to reduce urban heat island phenomena in Houston.

Shin, Yoon Sung

2011-12-01T23:59:59.000Z

388

Renewable Energy Consumption for Electricity Generation by Energy Use  

Open Energy Info (EERE)

Electricity Generation by Energy Use Electricity Generation by Energy Use Sector and Energy Source, 2004 - 2008 Dataset Summary Description Provides annual renewable energy consumption (in quadrillion btu) for electricity generation in the United States by energy use sector (commercial, industrial and electric power) and by energy source (e.g. biomass, geothermal, etc.) This data was compiled and published by the Energy Information Administration (EIA). Source EIA Date Released August 01st, 2010 (4 years ago) Date Updated Unknown Keywords biomass Commercial Electric Power Electricity Generation geothermal Industrial PV Renewable Energy Consumption solar wind Data application/vnd.ms-excel icon 2008_RE.Consumption.for_.Elec_.Gen_EIA.Aug_.2010.xls (xls, 19.5 KiB) Quality Metrics Level of Review Some Review

389

Modeling Energy Consumption of Residential Furnaces and Boilers...  

NLE Websites -- All DOE Office Websites (Extended Search)

Energy Consumption of Residential Furnaces and Boilers in U.S. homes Title Modeling Energy Consumption of Residential Furnaces and Boilers in U.S. homes Publication Type Report...

390

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

Reports and Publications (EIA)

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.

Information Center

2010-06-01T23:59:59.000Z

391

Residential Energy Consumption Survey (RECS) - Energy ...  

U.S. Energy Information Administration (EIA)

... solar, wind, geothermal, biomass and ethanol. Nuclear & Uranium. Uranium fuel, nuclear reactors, generation, spent fuel. ... State Energy Data System ...

392

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

U.S. Energy Information Administration (EIA)

Energy consumption in the U.S. manufacturing sector fell from 21,098 trillion Btu (tBtu) in 2006 to 19,062 tBtu in 2010, a decline of almost 10 percent, ...

393

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

U.S. Energy Information Administration (EIA)

Units & Calculators ... 2012. Energy consumption in the U.S. manufacturing sector fell from 21,098 trillion Btu (tBtu) in 2006 to 19,062 tBtu in 2010, ...

394

Residential Energy Consumption Survey: housing characteristics, 1982  

Science Conference Proceedings (OSTI)

Data in this report cover fuels and their use in the home, appliances, square footage of floor space, heating equipment, thermal characteristics of the housing unit, conservation activities, wood consumption, indoor temperatures, and weather. The 1982 survey included a number of questions on the reasons households make energy conservation improvements to their homes. Results of these questions are presented. Discussion also highlights data pertaining to: trends in home heating fuels, trends in conservation improvements, and characteristics of households whose energy costs are included in their rent.

Thompson, W.

1984-08-01T23:59:59.000Z

395

Consumption & Efficiency - U.S. Energy Information Administration ...  

U.S. Energy Information Administration (EIA)

A video about changes in home heating in the United States. Annual Energy Review Consumption Statistics. Released September 27, ...

396

Table 2.9 Commercial Buildings Consumption by Energy Source ...  

U.S. Energy Information Administration (EIA)

parking garages. Web Page: For related information, ... "Commercial Buildings Energy Consumption Survey." 6 Distillate fuel oil, residual fuel oil, ...

397

Table F28: Wind Energy Consumption Estimates, 2011  

U.S. Energy Information Administration (EIA)

Table F28: Wind Energy Consumption Estimates, 2011 State Commercial Industrial Electric Power Total Commercial Industrial Electric Power Total

398

Consumption & Efficiency - Analysis & Projections - U.S. Energy ...  

U.S. Energy Information Administration (EIA)

Vehicle Energy Consumption Survey Data; ... Manufacturers or their representatives could go directly to the wellhead to purchase their natural gas, ...

399

Consumption & Efficiency - U.S. Energy Information Administration ...  

U.S. Energy Information Administration (EIA)

Vehicle Energy Consumption Survey Data; ... The major users are residential and commercial buildings, industry, transportation, and electric power generators.

400

Waste-to-Energy Biomass Digester with Decreased Water Consumption  

Waste-to-Energy Biomass Digester with Decreased Water Consumption Contact Information: Jeremy Nelson Phone: 970.491.7100 Email: ...

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

U.S. energy-related carbon-dioxide emissions, including both direct fuel consumption (primarily natural gas)

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

402

Research on Building Energy Consumption Situation in Shanghai  

E-Print Network (OSTI)

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 the building and the whole society, and between the building and the air conditioning system. Eight public buildings in Shanghai have been chosen for analyzing the characteristics of energy consumption of the air conditioning system in real time.

Yang, X.; Tan, H.

2006-01-01T23:59:59.000Z

403

Chapter 2. Consumption of Fossil Fuels - U.S. Energy ...  

U.S. Energy Information Administration (EIA)

48 U.S. Energy Information Administration/Electric Power Monthly June 2012 Chapter 2. Consumption of Fossil Fuels

404

Household energy and consumption and expenditures, 1990. Supplement, Regional  

Science Conference Proceedings (OSTI)

The purpose of this supplement to the Household Energy Consumption and Expenditures 1990 report is to provide information on the use of energy in residential housing units, specifically at the four Census regions and nine Census division levels. This report includes household energy consumption, expenditures, and prices for natural gas, electricity, fuel oil, liquefied petroleum gas (LPG), and kerosene as well as household wood consumption. For national-level data, see the main report, Household Energy Consumption and Expenditures 1990.

Not Available

1993-03-02T23:59:59.000Z

405

CoNNECT: Analytics for Energy Consumption Data  

• Ability to correlate data with weather patterns • Ability to benchmark consumption with peers – ... solar energy potential on individual building ...

406

United States energy supply and demand forecasts 1979-1995  

SciTech Connect

Forecasts of U.S. energy supply and demand by fuel type and economic sector, as well as historical background information, are presented. Discussion and results pertaining to the development of current and projected marginal energy costs, and their comparison with market prices, are also presented.

Walton, H.L.

1979-01-01T23:59:59.000Z

407

Income Growth, Energy Consumption and Carbon Emissions in China  

Science Conference Proceedings (OSTI)

The paper examines the long-run relationship between per capita income growth, energy consumption, and pollutant emissions in China during the period 1953–2004. We find that energy consumption, pollutant emissions and income are cointegrated in ... Keywords: Energy consumption, Pollutant emissions, Causality, Multivariate cointegration, China

Zhi Zhao; Jiahai Yuan

2008-11-01T23:59:59.000Z

408

Energy Consumption in Downlink MIMO Relay Systems with Multiple Users  

Science Conference Proceedings (OSTI)

This paper focuses on the energy consumption problem in the downlink MIMO relay systems with multiple users. Power consumption under the target sum capacity is used as the energy efficient performance metric. Three transmission schemes, i.e. regenerate ... Keywords: Energy Consumption, MIMO, Relay, Multiple Users

Jie Xu; Ling Qiu

2010-12-01T23:59:59.000Z

409

Residential Energy Consumption Survey (RECS) - Energy Information ...  

U.S. Energy Information Administration (EIA)

Features Heating and cooling no longer majority of U.S. home energy use. Release Date: March 7, 2013. For decades, space heating and cooling (space conditioning ...

410

Residential Energy Consumption Survey (RECS) - Energy ...  

U.S. Energy Information Administration (EIA)

Features Heating and cooling no longer majority of U.S. home energy use. Release Date: March 7, 2013. For decades, space heating and cooling (space ...

411

Residential Energy Consumption Survey (RECS) - Energy Information ...  

U.S. Energy Information Administration (EIA)

Heating and cooling no longer majority of ... 2012. Total United States ... as increased energy efficiency has offset the increase in the number and average size of ...

412

International Energy Outlook 2000 - World Energy Consumption  

Gasoline and Diesel Fuel Update (EIA)

The IEO2000 projections indicate continued growth in world energy use, including large increases for the developing economies of Asia and South America. Energy resources are thought to be adequate to support the growth expected through 2020. The IEO2000 projections indicate continued growth in world energy use, including large increases for the developing economies of Asia and South America. Energy resources are thought to be adequate to support the growth expected through 2020. Current Trends Influencing World Energy Demand Changing world events and their effects on world energy markets shape the long-term view of trends in energy demand. Several developments in 1999—shifting short-term world oil markets, the recovery of developing Asian markets, and a faster than expected recovery in the economies of the former Soviet Union— are reflected in the projections presented in this year’s International Energy Outlook 2000 (IEO2000). In 1998, oil prices reached 20-year lows as a result of oil surpluses

413

International Energy Outlook 1999 - World Energy Consumption  

Gasoline and Diesel Fuel Update (EIA)

world.gif (5615 bytes) world.gif (5615 bytes) The IEO99 projections indicate substantial growth in world energy use,including substantial increases for the developing economies of Asia and South America. Resource availability is not expected to limit the growth of energy markets. In 1998, expectations for economic growth and energy market performance in many areas of the world were dashed. The Asian economic crisis proved to be deeper and more persistent than originally anticipated, and the threat and reality of spillover effects grew through the year. Oil prices crashed. RussiaÂ’s economy collapsed. Economic and social problems intensified in energy- exporting countries and in emerging economies of Asia and South America. Deepening recession in Japan made recovery more difficult in Asia

414

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

... 2,581 51,163 5,170 8,161 2,703 1,659 196 612 Energy Management and Control System (EMCS) ... 252 15,630 1,782 2,881 954 477 31 320...

415

Commercial Buildings Energy Consumption and Expenditures 1992...  

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

1992 Consumption and Expenditures 1992 Consumption & Expenditures Overview Full Report Tables National estimates of electricity, natural gas, fuel oil, and district heat...

416

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

E-Print Network (OSTI)

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

2006-01-01T23:59:59.000Z

417

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

E-Print Network (OSTI)

Residential Energy Consumption Survey, Human and Socialof Residential Building Energy Consumption in China Nan ZhouResidential Building Energy Consumption in China Nan Zhou*,

Zhou, Nan

2010-01-01T23:59:59.000Z

418

Video game console usage and national energy consumption: Results from a field-metering study  

E-Print Network (OSTI)

I. Azevedo. 2012, Electricity consumption and energy savingsMcKenney. 2007. Energy consumption by consumer electronicsK. Roth. 2011. Energy Consumption of Consumer Electronics in

Desroches, Louis-Benoit

2013-01-01T23:59:59.000Z

419

ResPoNSe: modeling the wide variability of residential energy consumption.  

E-Print Network (OSTI)

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

Peffer, Therese; Burke, William; Auslander, David

2010-01-01T23:59:59.000Z

420

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

E-Print Network (OSTI)

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

Apte, Joshua; Arasteh, Dariush

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

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

E-Print Network (OSTI)

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

Fridley, David G.

2008-01-01T23:59:59.000Z

422

The Impact of Residential Density on Vehicle Usage and Energy Consumption  

E-Print Network (OSTI)

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

Golob, Thomas F.; Brownstone, David

2005-01-01T23:59:59.000Z

423

Energy Consumption Characterization and Reduction Strategies for Milling Machine Tool Use  

E-Print Network (OSTI)

Energy Consumption Characterization and Reduction Strategiesand reducing the energy consumption of milling machine toolsGreen Machine Tools; Energy Consumption Reduction; Specific

Diaz, Nancy; E. Redelsheimer; Dornfeld, David

2011-01-01T23:59:59.000Z

424

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

E-Print Network (OSTI)

The China Residential Energy Consumption Survey, Human andof Residential Building Energy Consumption in China Nan ZhouResidential Building Energy Consumption in China Nan Zhou*,

Zhou, Nan

2010-01-01T23:59:59.000Z

425

PIA - Form EIA-475 A/G Residential Energy Consumption Survey...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Form EIA-475 AG Residential Energy Consumption Survey PIA - Form EIA-475 AG Residential Energy Consumption Survey PIA - Form EIA-475 AG Residential Energy Consumption Survey PIA...

426

Table 24. Refining Industry Energy Consumption  

Gasoline and Diesel Fuel Update (EIA)

- Corrections to Tables 24 to 32 - Corrections to Tables 24 to 32 Table 24. Refining Industry Energy Consumption 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2002- 2025 Carbon Dioxide Emissions 4/ (million metric tons) 190.4 185.7 188.0 191.3 207.3 215.6 220.0 222.8 225.1 226.3 228.0 230.7 234.1 237.5 238.5 239.4 239.4 238.6 240.6 240.5 242.2 244.2 245.9 246.3 246.6 1.2% Table 25. Food Industry Energy Consumption 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2002- 2025 Carbon Dioxide Emissions 3/ (million metric tons) 87.8 89.4 87.5 87.8 89.2 90.2 90.9 91.4 92.2 93.5 94.5 95.7 96.7 97.7 98.6 99.6 100.8 101.9 102.9 104.1 105.4 107.0 108.7 110.3 112.1 1.0% Table 26. Paper Industry Energy Consumption 2001 2002 2003 2004 2005 2006 2007

427

Manufacturing Energy Consumption Survey (MECS) - Residential - U.S. Energy  

Gasoline and Diesel Fuel Update (EIA)

About the MECS About the MECS Survey forms Maps MECS Terminology Archives Features First 2010 Data Press Release 2010 Data Brief Other End Use Surveys Commercial Buildings - CBECS Residential - RECS Transportation DOE Uses MECS Data Manufacturing Energy and Carbon Footprints Associated Analysis Early-release estimates from the 2010 MECS show that energy consumption in the manufacturing sector decreased between 2006 and 2010 MECS 2006-2010 - Release date: March 28, 2012 Energy consumption in the U.S. manufacturing sector fell from 21,098 trillion Btu (tBtu) in 2006 to 19,062 tBtu in 2010, a decline of almost 10 percent, based on preliminary estimates released from the 2010 Manufacturing Energy Consumption Survey (MECS). This decline continues the downward trend in manufacturing energy use since the 1998 MECS report.

428

UN Alcohol Energy Data: Consumption by other industries and constructi...  

Open Energy Info (EERE)

other industries and construction The Energy Statistics Database contains comprehensive energy statistics on the production, trade, conversion and final consumption of primary and...

429

UN Alcohol Energy Data: Consumption by transportation industry...  

Open Energy Info (EERE)

by transportation industry The Energy Statistics Database contains comprehensive energy statistics on the production, trade, conversion and final consumption of primary and...

430

Table 2.10 Commercial Buildings Energy Consumption and Expenditure ...  

U.S. Energy Information Administration (EIA)

Table 2.10 Commercial Buildings Energy Consumption and Expenditure Indicators, Selected Years, 1979-2003: Energy Source and Year: Building Characteristics

431

EIA projects world energy consumption will increase 56% by ...  

U.S. Energy Information Administration (EIA)

EIA's recently released International Energy Outlook 2013 (IEO2013) projects that world energy consumption will grow by 56% between 2010 and 2040, ...

432

Figure 2. Energy Consumption of Vehicles, Selected Survey Years  

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

Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use > Figure 2 Figure 2. Energy Consumption of Vehicles, Selected Survey Years...

433

AEO2011: Renewable Energy Consumption by Sector and Source This...  

Open Energy Info (EERE)

Consumption by Sector and Source This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset...

434

Table 2.9 Commercial Buildings Consumption by Energy Source ...  

U.S. Energy Information Administration (EIA)

Table 2.9 Commercial Buildings Consumption by Energy Source, Selected Years, 1979-2003 (Trillion Btu) Energy Source and Year

435

Energy Consumption by Sector 1. Energy Overview  

U.S. Energy Information Administration (EIA)

Crude Oil and NGPLa Nuclear Electric Power Renewable Energy 51.388 52.848 54.349 2011 2012 2013 0 10 20 30 40 50 60 2.126 1.851 1.653 0.747 0.730 ...

436

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

... 261 899 1,121 2,311 8,736 9,424 112.8 102.9 119.0 Energy Management and Control System (EMCS) ... Q 350 356 429 2,573 2,835 Q 135.9 125.7...

437

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

... 512 333 488 5,836 3,065 6,282 87.7 108.8 77.8 Energy Management and Control System (EMCS) ... 197 117 178 1,834 857 2,170 107.6 136.6...

438

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

... 336 959 261 3,704 9,547 2,258 90.7 100.4 115.5 Energy Management and Control System (EMCS) ... 103 331 80 965 3,426 542 107.2 96.6 148.5...

439

Energy Information Administration - Commercial Energy Consumption...  

Annual Energy Outlook 2012 (EIA)

... 2,581 51,163 81,328 60,420 12,356 1,565 6,987 Energy Management and Control System (EMCS) ... 252 15,630 27,646 20,451 3,318 241 3,636...

440

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

Maintenance ... 2,581 51,163 19.8 5,170 2,003 101.1 81.3 Energy Management and Control System (EMCS) ... 252 15,630 62.0 1,782 7,068 114.0 82.4...

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

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

E-Print Network (OSTI)

of biogas, stalks and firewood by rural residents by region, and fossil fuel energy consumption refers variable is: Biogas consumption per capita Stalks consumption per capita Firewood consumption per capita FE

Lin, C.-Y. Cynthia

442

Today in Energy - Residential Consumption & Efficiency  

Reports and Publications (EIA)

Short, timely articles with graphs about recent residential consumption and efficiency issues and trends

443

Today in Energy - Commercial Consumption & Efficiency  

Reports and Publications (EIA)

Short, timely articles with graphs about recent commercial consumption and efficiency issues and trends

444

User-needs study for the 1993 residential energy consumption survey  

Science Conference Proceedings (OSTI)

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.

Not Available

1993-09-24T23:59:59.000Z

445

Commercial Buildings Energy Consumption and Expenditures 1992 - Executive  

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

& Expenditures > Executive Summary & Expenditures > Executive Summary 1992 Consumption & Expenditures Executive Summary Commercial Buildings Energy Consumption and Expenditures 1992 presents statistics about the amount of energy consumed in commercial buildings and the corresponding expenditures for that energy. These data are based on the 1992 Commercial Buildings Energy Consumption Survey (CBECS), a national energy survey of buildings in the commercial sector, conducted by the Energy Information Administration (EIA) of the U.S. Department of Energy. Figure ES1. Energy Consumption is Commercial Buidings by Energy Source, 1992 Energy Consumption: In 1992, the 4.8 million commercial buildings in the United States consumed 5.5 quadrillion Btu of electricity, natural gas, fuel oil, and district heat. Of those 5.5 quadrillion Btu, consumption of site electricity accounted for 2.6 quadrillion Btu, or 48.0 percent, and consumption of natural gas accounted for 2.2 quadrillion Btu, or 39.6 percent. Fuel oil consumption made up 0.3 quadrillion Btu, or 4.0 percent of the total, while consumption of district heat made up 0.4 quadrillion Btu, or 7.9 percent of energy consumption in that sector. When the energy losses that occur at the electricity generating plants are included, the overall energy consumed by commercial buildings increases to about 10.8 quadrillion Btu (Figure ES1).

446

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

C2A. Total Energy Expenditures by Major Fuel for All Buildings, 2003 C2A. Total Energy Expenditures by Major Fuel for All Buildings, 2003 All Buildings Total Energy Expenditures (million dollars) Number of Buildings (thousand) Floorspace (million square feet) Sum of Major Fuels Electricity Natural Gas Fuel Oil District Heat All Buildings ................................ 4,859 71,658 107,897 82,783 16,010 1,826 7,279 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 2,586 6,922 13,083 10,547 2,227 292 Q 5,001 to 10,000 .............................. 948 7,033 10,443 8,199 1,830 307 Q 10,001 to 25,000 ............................ 810 12,659 15,689 12,172 2,897 238 Q 25,001 to 50,000 ............................ 261 9,382 11,898 9,179 2,054 134 Q 50,001 to 100,000 .......................... 147 10,291 15,171 11,694 2,140 229 Q

447

Energy Information Administration - Commercial Energy Consumption Survey-  

Gasoline and Diesel Fuel Update (EIA)

. Total Energy Expenditures by Major Fuel for Non-Mall Buildings, 2003 . Total Energy Expenditures by Major Fuel for Non-Mall Buildings, 2003 All Buildings* Total Energy Expenditures (million dollars) Number of Buildings (thousand) Floorspace (million square feet) Sum of Major Fuels Electricity Natural Gas Fuel Oil District Heat All Buildings* ............................... 4,645 64,783 92,577 69,032 14,525 1,776 7,245 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 2,552 6,789 12,812 10,348 2,155 292 Q 5,001 to 10,000 .............................. 889 6,585 9,398 7,296 1,689 307 Q 10,001 to 25,000 ............................ 738 11,535 13,140 10,001 2,524 232 Q 25,001 to 50,000 ............................ 241 8,668 10,392 7,871 1,865 127 Q 50,001 to 100,000 .......................... 129 9,057 11,897 8,717 1,868 203 Q

448

California Regional Wind Energy Forecasting System Development, Vol. 3  

Science Conference Proceedings (OSTI)

The rated capacity of wind generation in California is expected to grow rapidly in the future beyond the approximately 2100 MW in place at the end of 2005. The main drivers are the state's 20 percent Renewable Portfolio Standard requirement in 2010 and the low cost of wind energy relative to other renewable energy sources. As wind is an intermittent generation resource and weather changes can cause large and rapid changes in output, system operators will need accurate and robust wind energy forecasting ...

2006-11-15T23:59:59.000Z

449

1999 Commercial Buildings Energy Consumption Survey Detailed Tables  

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

Consumption and Expenditures Tables Table C1. Total Energy Consumption by Major Fuel ............................................... 124 Table C2. Total Energy Expenditures by Major Fuel................................................ 130 Table C3. Consumption for Sum of Major Fuels ...................................................... 135 Table C4. Expenditures for Sum of Major Fuels....................................................... 140 Table C5. Consumption and Gross Energy Intensity by Census Region for Sum of Major Fuels................................................................................................... 145 Table C6. Expenditures by Census Region for Sum of Major Fuels......................... 150 Table C7. Consumption and Gross Energy Intensity by Building Size for Sum of

450

California Wind Energy Forecasting System Development and Testing Phase 2: 12-Month Testing  

Science Conference Proceedings (OSTI)

This report describes results from the second phase of the California Wind Energy Forecasting System Development and Testing Project.

2003-07-22T23:59:59.000Z

451

Energy consumption of personal computer workstations  

SciTech Connect

A field study directly measured the electric demand of 189 personal computer workstations for 1-week intervals, and a survey recorded the connected equipment at 1,846 workstations in six buildings. Each separate workstation component (e.g., computer, monitor, printer, modem, and other peripheral) was individually monitored to obtain detailed electric demand profiles. Other analyses included comparison of nameplate power rating with measured power consumption and the energy savings potential and cost-effectiveness of a controller that automatically turns off computer workstation equipment during inactivity. An important outcome of the work is the development of a standard workstation demand profile and a technique for estimating a whole-building demand profile. Together, these provide a method for transferring this information to utility energy analysts, design engineers, building energy modelers, and others. A life-cycle cost analysis was used to determine the cost-effectiveness of three energy conservation measures: (1) energy awareness education, (2) retrofit power controller installation, and (3) purchase of energy-efficient PCs.

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

1994-08-01T23:59:59.000Z

452

(1) Who owns energy consumption data  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Elster July 12, 2010 Reply to DOE Request for Information of May 11, 2010 Elster July 12, 2010 Reply to DOE Request for Information of May 11, 2010 regarding Data Privacy The DOE questions are restated followed by an answer. Please note that this matter is also related to the May 11, 2010 RFI on needs for utility communications. If data is provided to third parties there is a data processing and communications cost that depends on how many parties data is provided to and by how often data is communicated. These costs are minimized if an in-home display and/or smart thermostat are provided data directly from a smart meter. (1) Q. Who owns energy consumption data? A. Typically by state law the consumer owns the data. (2) Q. Who should be entitled to privacy protections relating to energy information? A. The consumer.

453

ELECTRICITY DEMAND FORECAST COMPARISON REPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005 ..............................................................................3 Residential Forecast Comparison ..............................................................................................5 Nonresidential Forecast Comparisons

454

Modeling energy consumption of residential furnaces and boilers in U.S. homes  

E-Print Network (OSTI)

CONSUMPTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Lutz, James; Dunham-Whitehead, Camilla; Lekov, Alex; McMahon, James

2004-01-01T23:59:59.000Z

455

UN Alcohol Energy Data: Consumption for Non-Energy Uses The Energy  

Open Energy Info (EERE)

for Non-Energy Uses The Energy Statistics Database contains comprehensive energy statistics on the production, trade, conversion and final consumption of primary and secondary;...

456

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

E-Print Network (OSTI)

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

Price, Lynn

2008-01-01T23:59:59.000Z

457

Residential energy consumption survey: housing characteristics 1984  

SciTech Connect

Data collected in the 1984 Residential Energy Consumption Survey (RECS), the sixth national survey of households and their fuel suppliers, provides baseline information on how households use energy. Households living in all types of housing units - single-family homes (including townhouses), apartments, and mobile homes - were chosen to participate. Data from the surveys are available to the public. The housing characteristics this report describes include fuels and the uses they are put to in the home; appliances; square footage of floorspace; heating (and cooling) equipment; thermal characteristics of housing structures; conservation features and measures taken; the consumption of wood; temperatures indoors; and regional weather. These data are tabulated in sets, first showing counts of households and then showing percentages. Results showed: Fewer households are changing their main heating fuel. More households are air conditioned than before. Some 50% of air-conditioned homes now use central systems. The three appliances considered essential are the refrigerator, the range, and the television set. At least 98% of US homes have at least one television set; but automatic dishwashers are still not prevalent. Few households use the budget plans tht are available from their utility companies to ease the payment burden of seasonal surges in fuel bills. The most common type of heating equipment in the United States is the natural-gas forced-air furnace. About 40% ofthose furnaces are at least 15 years old. The oldest water heaters are those that use fuel oil. The most common conservation feature in 1984 is ceiling or attic insulation - 80% of homes report having this item. Relatively few households claimed tax credits in 1984 for energy-conservation improvements.

Not Available

1986-10-08T23:59:59.000Z

458

DOETEIAO32l/2 Residential Energy Consumption Survey; Consumption  

Gasoline and Diesel Fuel Update (EIA)

sample custom-designed to meet the analytic objectives for surveys of residential energy use; sample as many as 5,500 households; provide 2-day personal training sessions...

459

Visualization of United States Energy Consumption | Open Energy Information  

Open Energy Info (EERE)

Visualization of United States Energy Consumption Visualization of United States Energy Consumption Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Visualization of United States Energy Consumption Agency/Company /Organization: Energy Information Administration Sector: Energy Resource Type: Software/modeling tools User Interface: Website Website: en.openei.org/wiki/Visualization_of_United_States_Energy_Consumption Country: United States Cost: Free OpenEI Keyword(s): Community Generated UN Region: Northern America Coordinates: 37.09024°, -95.712891° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.09024,"lon":-95.712891,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

460

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

E-Print Network (OSTI)

that per-capita energy consumption increases significantly wi n an increase per-capita energy consumption (Hasegawa and

2006-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

The Impact of Residential Density on Vehicle Usage and Energy Consumption  

E-Print Network (OSTI)

Kenworthy (1989a). Gasoline consumption and cities. JournalVehicle Usage and Energy Consumption Table 2 Housing Unitsvehicular energy consumption is graphed as a function of

Golob, Thomas F.; Brownstone, David

2005-01-01T23:59:59.000Z

462

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

E-Print Network (OSTI)

Like the Other: Residential Consumption Variability Phillipthe total annual energy consumption. The behavior patternsin total residential energy consumption per home, even when

Kelsven, Phillip

2013-01-01T23:59:59.000Z

463

Energy Consumption Characterization and Reduction Strategies for Milling Machine Tool Use  

E-Print Network (OSTI)

Cutting Condition on Power Consumption of Machine Tools, in:Energy Consumption Characterization and Reduction Strategiesand reducing the energy consumption of milling machine tools

Diaz, Nancy; E. Redelsheimer; Dornfeld, David

2011-01-01T23:59:59.000Z

464

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

E-Print Network (OSTI)

2001). "Residential Energy Consumption Survey." 2006, fromCommercial Building Energy Consumption Survey." from http://Study: Window % of Consumption 1. Categorize component loads

Apte, Joshua; Arasteh, Dariush

2008-01-01T23:59:59.000Z

465

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Energy-Related Carbon Dioxide Emissions Energy-Related Carbon Dioxide Emissions In the coming decades, responses to environmental issues could affect patterns of energy use around the world. Actions to limit greenhouse gas emissions could alter the level and composition of energy-related carbon dioxide emissions by energy source. Figure 67. World Carbon Dioxide Emissions by Region, 2002-2025 (Gigawatts). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Carbon dioxide is one of the most prevalent greenhouse gases in the atmosphere. Anthropogenic (human-caused) emissions of carbon dioxide result primarily from the combustion of fossil fuels for energy, and as a result world energy use has emerged at the center of the climate change debate. In the International Energy Outlook 2005 (IEO2005) reference case, world

466

Emerging challenges in wind energy forecasting for Australia  

E-Print Network (OSTI)

Growing concern about climate change has led to significant interest in renewable energy resources such as wind energy. However, such non-storable energy sources present a significant issue – how to maintain continuity of supply in the event of possible disturbances to power production. For example, in the case of wind energy, such disturbances can result from extreme weather events due to frontal systems or rapidly evolving low pressure systems. Such events cannot be avoided, but if they can be accurately forecast, their impact can be minimized by ensuring that alternative sources are available to make up any power shortfalls. Thus as wind energy makes up an ever greater component of our energy supply, there is greater interest in developing models to produce accurate, local scale, wind-focused forecasts for wind farm sites that push the boundaries of current weather prediction techniques. In this article we present a case study focusing on the Woolnorth wind farm on the northwest tip of Tasmania, to highlight some of the key challenges that will be involved in developing such forecasts.

Merlinde J. Kay; Nicholas Cutler; Adam Micolich; Iain Macgill; Hugh Outhred Centre For Energy; Environmental Markets; South Wales

2008-01-01T23:59:59.000Z

467

Household Vehicles Energy Consumption 1994 - Appendix C  

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

Introduction This appendix discusses several issues relating to the quality of the Residential Transportation Energy Consumption Survey (RTECS) data and to the interpretation of conclusions based on these data. The first section discusses undercoverage of the vehicle stock in the residential sector. The second section discusses the effects of using July 1994 as a time reference for the survey. The remainder of this appendix discusses the treatment of sampling and nonsampling errors in the RTECS, the quality of specific data items such as the Vehicle Identification Number (VIN) and fuel prices, and poststratification procedures used in the 1994 RTECS. The quality of the data collection and the processing of the data affects the accuracy of estimates based on survey data. All the statistics

468

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

G: Key Assumptions for the IEO2005 Kyoto Protocol Case G: Key Assumptions for the IEO2005 Kyoto Protocol Case Energy-Related Emissions of Greenhouse Gases The System for the Analysis of Global energy Markets (SAGE)—the model used by the Energy Information Administration (EIA) to prepare the International Energy Outlook 2005 (IEO2005) mid-term projections—does not include non-energy-related emissions of greenhouse gases, which are estimated at about 15 to 20 percent of total greenhouse gas emissions, based on inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC). SAGE models global energy supply and demand and, therefore, does not address agricultural and other non-energy-related emissions. EIA implicitly assumes that percentage reductions of non-energy-related emissions and their associated abatement costs will be similar to those for energy-related emissions. Non-energy-related greenhouse gas emissions are likely to grow faster than energy-related emissions; however, the marginal abatement costs for non-energy-related greenhouse gas emissions are not known and cannot be estimated reliably. In SAGE, each region’s emissions reduction goal under the Kyoto Protocol is based only on the corresponding estimate of that region’s energy-related carbon dioxide emissions, as determined by EIA data. It is assumed that the required reductions will also be proportionately less than if all gases were included.

469

Evaluating Texas State University Energy Consumption According to Productivity  

E-Print Network (OSTI)

The Energy Utilization Index, energy consumption per square foot of floor area, is the most commonly used index of building energy consumption. However, a building or facility exists solely to support the activities of its occupants. Floor area alone is not a complete measure of the amount of service a facility provides. The energy consumption of a service institution, such as a university, could be evaluated according to its annual level of service. However, the variety of services delivered 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 and outputs. It finds a consumption target for each form of energy consumed by an institution, based on the actual performance of comparable institutions. This method is applicable to the energy consumption of Texas state institutions of higher education.

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

1998-01-01T23:59:59.000Z

470

San Francisco residential energy consumption. Final report  

SciTech Connect

Heating and cooling energy requirements were determined by a computerized program for characteristic single-family, townhouse, low - rise, and high - rise residences in San Francisco, Calif., with 1951 selected as being a typical weather year for the area. Energy requirements were calculated using a two - step process. In the first step, hourly heating and cooling loads were calculated for each dwelling unit. In the second step, monthly and annual energy required to meet heating and cooling loads was calculated using specific heating, cooling, and ventilation systems. Examples of lifestyle parameters included in the analysis were thermostat set points, relative humidity set points, type and number of appliances, daily profile of appliance use, and use of ventilation fans. The computer program used to determine heating and cooling loads, or heat delivery / removal requirements, included subroutines for computing hourly load contributions throughout the year due to conduction, convection, air infiltration, radiation, and internal heat gain. The heating load was much greater than the cooling load for single - family and high - rise residences, due to large amounts of infiltration. Heating and cooling loads were similar in the townhouses. The low - rise residences had a cooling load larger than their heating load because of internal heat generation. After structural and comfort control system modifications were made to the residences, heating and cooling energy requirements were again determined. Reduced energy consumption as a result of the modifications were as follows: single - family residences consumed 50 percent, townhouses consumed 50 percent, low - rise residences consumed 57 percent, and high - rise residences consumed 64 percent of the primary energy required by the characteristic structure. Supporting data, illustrative layouts of the residences, and references are included.

Reed, J.E.; Barber, J.E.; White, B.

1976-12-01T23:59:59.000Z

471

Canada's Fuel Consumption Guide | Open Energy Information  

Open Energy Info (EERE)

Canada's Fuel Consumption Guide Canada's Fuel Consumption Guide Jump to: navigation, search Tool Summary Name: Canada's Fuel Consumption Guide Agency/Company /Organization: Natural Resources Canada Focus Area: Fuels & Efficiency Topics: Analysis Tools Website: oee.nrcan.gc.ca/transportation/tools/fuel-consumption-guide/fuel-consu Natural Resources Canada has compiled fuel consumption ratings for passenger cars and light-duty pickup trucks, vans, and special purpose vehicles sold in Canada. The website links to the Fuel Consumption Guide and allows users to search for vehicles from current and past model years. It also provides information about vehicle maintenance and other practices to reduce fuel consumption. How to Use This Tool This tool is most helpful when using these strategies:

472

Analysis of federal incentives used to stimulate energy consumption  

SciTech Connect

Conclusions of an analysis which identifies and quantifies Federal incentives that have increased the consumption of coal, oil, natural gas, and electricity are summarized. Data on estimated cost of incentives used to stimulate energy consumption by incentive type and energy source are tabulated for coal, oil, gas, and electricity. It is suggested that the examination of past incentives can be useful in developing guidelines and limits for the use of incentives to stimulate consumption of solar energy. (MCW)

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

1981-04-01T23:59:59.000Z

473

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

E-Print Network (OSTI)

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 developed for industrial energy analysis at the Pacific Northwest National Laboratory. Although the results are mixed, generally ITEMS show greater penetration of energy efficient technologies and thus lower energy use, even though the business as usual forecasts for ITEMS uses a higher discount rate than NEMS uses.

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

2000-04-01T23:59:59.000Z

474

Adapting state and national electricity consumption forecasting methods to utility service areas. Final report  

SciTech Connect

This report summarizes the experiences of six utilities (Florida Power and Light Co., Municipal Electric Authority of Georgia, Philadelphia Electric Co., Public Service Co. of Colorado, Sacramento Municipal Utility District, and TVA) in adapting to their service territories models that were developed for forecasting loads on a national or regional basis. The models examined were of both end-use and econometric design and included the three major customer classes: residential, commercial, and industrial.

Swift, M.A.

1984-07-01T23:59:59.000Z

475

Understanding the Energy Consumption of Dynamic Random Access Memories  

Science Conference Proceedings (OSTI)

Energy consumption has become a major constraint on the capabilities of computer systems. In large systems the energy consumed by Dynamic Random Access Memories (DRAM) is a significant part of the total energy consumption. It is possible to calculate ... Keywords: DRAM, power

Thomas Vogelsang

2010-12-01T23:59:59.000Z

476

Table 2.10 Commercial Buildings Energy Consumption and Expenditure ...  

U.S. Energy Information Administration (EIA)

parking garages. Note: Data are estimates. Statistics for individual fuels are for all buildings using each fuel. ... "Nonresidential Buildings Energy Consumption

477

EIA publishes state fact sheets on residential energy consumption ...  

U.S. Energy Information Administration (EIA)

EIA has recently published state fact sheets highlighting interesting aspects of residential energy consumption and housing characteristics based on data released ...

478

Manufacturing Energy Consumption Survey (MECS) - Data - U.S ...  

U.S. Energy Information Administration (EIA)

U.S. States. State energy information, detailed and ... 2010 MECS Survey Data 2010 | 2006 ... Table 5.7 By Region with Total Consumption of Electricity (physical ...

479

"Table 17. Total Delivered Residential Energy Consumption, Projected...  

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

Total Delivered Residential Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,...

480

Consumption & Efficiency - U.S. Energy Information Administration ...  

U.S. Energy Information Administration (EIA)

Sales, revenue and prices, power plants, fuel use, stocks, generation, trade, demand & emissions. Consumption & Efficiency. Energy use in homes, commercial buildings, ...

Note: This page contains sample records for the topic "forecasts energy consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

Consumption & Efficiency - U.S. Energy Information Administration ...  

U.S. Energy Information Administration (EIA)

Cost of Natural Gas Used in Manufacturing Sector Has Fallen. ... Annual state-level estimates of consumption for hydroelectric power, wind, geothermal, and solar energy.

482

Table 1.5 Energy Consumption, Expenditures, and Emissions ...  

U.S. Energy Information Administration (EIA)

1 Expenditures include taxes where data are available. 5 In chained (2005) dollars. See "Chained Dollars" in Glossary. 2 Carbon dioxide emissions from energy consumption.

483

Table E1. Estimated Primary Energy Consumption in the United ...  

U.S. Energy Information Administration (EIA)

Table E1. Estimated Primary Energy Consumption in the United States, Selected Years, 1635-1945 (Quadrillion Btu) Year: Fossil Fuels

484

Consumption & Efficiency - U.S. Energy Information Administration ...  

U.S. Energy Information Administration (EIA)

Vehicle Energy Consumption Survey Data; ... That increase in supply has in turn lowered the price of natural gas to manufacturers as well as other consumers.

485

Waste-to-Energy Biomass Digester with Decreased Water Consumption  

Waste-to-Energy Biomass Digester with Decreased Water Consumption ... Able to digest multiple types of waste, including bovine, equine, and poultry manure

486

Manufacturing Energy Consumption Survey (MECS) - Data - U.S ...  

U.S. Energy Information Administration (EIA)

2002 Manufacturing Energy Consumption Survey Methodology and ... where Op,MECS is the MECS estimate of the amount of petroleum product p produced offsite and ...

487

Does EIA have projections for energy production, consumption ...  

U.S. Energy Information Administration (EIA)

Does EIA have projections for energy production, consumption, and prices for individual states? No, EIA does not make projections for individual ...

488

On Minimizing the Energy Consumption of an Electrical Vehicle  

E-Print Network (OSTI)

Apr 20, 2011 ... The problem that we focus on, is the minimization of the energy consumption of an electrical vehicle achievable on a given driving cycle.

489

Figure 64. Industrial energy consumption by fuel, 2011, 2025, and ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 64. Industrial energy consumption by fuel, 2011, 2025, and 2040 (quadrillion Btu) Natural Gas Petroleum and other liquids

490

Figure 63. Industrial delivered energy consumption by application ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 63. Industrial delivered energy consumption by application, 2011-2040 (quadrillion Btu) Manufacturing heat and power Nonmanufacturing heat ...

491

Does EIA have projections for energy production, consumption ...  

U.S. Energy Information Administration (EIA)

Does EIA have gasoline prices by city, county, or zip code? Does EIA have projections for energy production, consumption, and prices for individual states?

492

Table 10.1 Renewable Energy Production and Consumption by ...  

U.S. Energy Information Administration (EIA)

1 Production equals consumption for all renewable energy sources except biofuels. 9 Wood and wood-derived fuels. 2 Total biomass inputs to the ...

493

Solar Adoption and Energy Consumption in the Residential Sector.  

E-Print Network (OSTI)

??This dissertation analyzes the energy consumption behavior of residential adopters of solar photovoltaic systems (solar-PV). Based on large data sets from the San Diego region… (more)

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

494

Psychological strategies to reduce energy consumption: first annual progress report  

SciTech Connect

A multidisciplinary program composed of a mix of physical and social scientists is studying the behavior of occupants as well as the engineering aspects of household energy consumption. A study of the Twin Rivers, New Jersey area examined and tested psychological strategies for helping people achieve significant reductions in their residential energy consumption. The results show that homeowners are motivated by cost and other pressures provided by daily feedback on their actual energy consumption. Four feedback experiments suggest that feedback helps homeowners to reduce their energy consumption, but the optimal nature of the feedback system has yet to be identified. The project also included research on thermostat control and on attitudes.

Seligman, C.; Darley, J.M.; Becker, L.J.

1976-01-01T23:59:59.000Z

495

Figure 57. Change in residential delivered energy consumption ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 57. Change in residential delivered energy consumption for selected end uses in four cases, 2011-2040 (percent) Best Available Technology

496

Does EIA have projections for energy production, consumption, and ...  

U.S. Energy Information Administration (EIA)

Does EIA have projections for energy production, consumption, and prices for individual states? No, EIA does not make projections for individual states.

497

Using occupancy to reduce energy consumption of buildings.  

E-Print Network (OSTI)

??Buildings account for 73% of the total electricity consumption in the US. To get an in depth view of where this energy is consumed within… (more)

Balaji, Bharathan

2011-01-01T23:59:59.000Z

498

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

U.S. Energy Information Administration (EIA)

Early-release estimates from the 2010 MECS show that energy consumption in the manufacturing sector decreased between 2006 and 2010. Release Date: ...

499

Energy consumption in commerical buildings: a comparison with BEPS budgets  

SciTech Connect

Metered energy consumption data have been collected on existing commercial buildings to help establish the proposed Building Energy Performance Standards (BEPS). The search has identified 84 buildings whose metered energy consumption is equal to or less than that proposed for their BEPS budgets and another 7 buildings whose metered consumption is less than 20% above their BEPS budgets. The methodology used to identify the buildings and to collect their metered energy consumption data are described. The data are analyzed and summarized and conclusions are drawn.

1980-09-22T23:59:59.000Z

500

2003 Commercial Buildings Energy Consumption - What is an RSE  

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

Home > Households, Buildings & Industry > Commercial Buildings Energy Consumption Survey (CBECS) > 2003 Detailed Tables > What is an RSE? What is an RSE? The estimates in the...