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Note: This page contains sample records for the topic "residential sector 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

Table A4. Residential sector key indicators and consumption  

Gasoline and Diesel Fuel Update (EIA)

3 3 U.S. Energy Information Administration | Annual Energy Outlook 2013 Reference case Table A4. Residential sector key indicators and consumption (quadrillion Btu per year, unless otherwise noted) Energy Information Administration / Annual Energy Outlook 2013 Table A4. Residential sector key indicators and consumption (quadrillion Btu per year, unless otherwise noted) Key indicators and consumption Reference case Annual growth 2011-2040 (percent) 2010 2011 2020 2025 2030 2035 2040 Key indicators Households (millions) Single-family ....................................................... 82.85 83.56 91.25 95.37 99.34 103.03 106.77 0.8% Multifamily ........................................................... 25.78 26.07 29.82 32.05 34.54 37.05 39.53 1.4%

2

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

38 3.2.1. SDG&E Residential Electric Rates and TheirFootprint of Single-Family Residential New Construction.Solar photovoltaic financing: residential sector deployment,

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

3

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.

4

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

5

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

the predominant residential electricity rate structure. Itresidential electricity customers, over 90%, are on the standard domestic residential (DR) rate,

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

6

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

installation Total Electricity Consumption 1 Year Pre & PostGWh total Total Electricity Consumption 1 Year Pre & 2 YearsInstall Total Electricity Consumption 1 Year Pre & 3 Years

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

7

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

8

Buildings Energy Data Book: 1.2 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

Residential Sector Energy Consumption March 2012 1.2.9 Implicit Price Deflators (2005 1.00) Year Year Year 1980 0.48 1990 0.72 2000 0.89 1981 0.52 1991 0.75 2001 0.91 1982 0.55...

9

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

7 7 Range 10 4 48 Clothes Dryer 359 (2) 4 49 Water Heating Water Heater-Family of 4 40 64 (3) 26 294 Water Heater-Family of 2 40 32 (3) 12 140 Note(s): Source(s): 1) $1.139/therm. 2) Cycles/year. 3) Gallons/day. A.D. Little, EIA-Technology Forecast Updates - Residential and Commercial Building Technologies - Reference Case, Sept. 2, 1998, p. 30 for range and clothes dryer; LBNL, Energy Data Sourcebook for the U.S. Residential Sector, LBNL-40297, Sept. 1997, p. 62-67 for water heating; GAMA, Consumers' Directory of Certified Efficiency Ratings for Heating and Water Heating Equipment, Apr. 2002, for water heater capacity; and American Gas Association, Gas Facts 1998, December 1999, www.aga.org for range and clothes dryer consumption. Operating Characteristics of Natural Gas Appliances in the Residential Sector

10

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

4 4 Ownership (1) Owned 54.9 104.5 40.3 78% Rented 77.4 71.7 28.4 22% Public Housing 75.7 62.7 28.7 2% Not Public Housing 77.7 73.0 28.4 19% 100% Note(s): Source(s): 1) Energy consumption per square foot was calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the U.S. was 1,618 square feet. Average total floor space, which includes garages, attics and unfinished basements, equaled 2,309 square feet. EIA, 2005 Residential Energy Consumption Survey, Oct. 2008 2005 Residential Delivered Energy Consumption Intensities, by Ownership of Unit Per Square Per Household Per Household Percent of Foot (thousand Btu) (million Btu) Members (million Btu) Total Consumption

11

Modeling diffusion of electrical appliances in the residential sector  

E-Print Network (OSTI)

Efficiency Standards in the Residential Electricity Sector.France. USDOE (2001). Residential Energy Consumption Survey,long-term response of residential cooling energy demand to

McNeil, Michael A.

2010-01-01T23:59:59.000Z

12

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

1 1 Type (1) Single-Family: 55.4 106.6 39.4 80.5% Detached 55.0 108.4 39.8 73.9% Attached 60.5 89.3 36.1 6.6% Multi-Family: 78.3 64.1 29.7 14.9% 2 to 4 units 94.3 85.0 35.2 6.3% 5 or more units 69.8 54.4 26.7 8.6% Mobile Homes 74.6 70.4 28.5 4.6% All Housing Types 58.7 95.0 37.0 100% Note(s): Source(s): 1) Energy consumption per square foot was calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the U.S. was 1,618 square feet. Average total floor space, which includes garages, attics and unfinished basements, equaled 2,309 square feet. EIA, 2005 Residential Energy Consumption Survey, Oct. 2008. 2005 Residential Delivered Energy Consumption Intensities, by Housing Type

13

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

2 2 Year Built (1) Prior to 1950 74.5 114.9 46.8 24% 1950 to 1969 66.0 96.6 38.1 23% 1970 to 1979 59.4 83.4 33.5 15% 1980 to 1989 51.9 81.4 32.3 14% 1990 to 1999 48.2 94.4 33.7 16% 2000 to 2005 44.7 94.7 34.3 8% Average 58.7 95.0 40.0 Note(s): Source(s): 1) Energy consumption per square foot was calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the U.S. was 1,618 square feet. Average total floor space, which includes garages, attics and unfinished basements, equaled 2,309 square feet. EIA, 2005 Residential Energy Consumption Survey, Oct. 2008. 2005 Residential Delivered Energy Consumption Intensities, by Vintage Per Square Per Household Per Household

14

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

3 3 Building Type Pre-1995 1995-2005 Pre-1995 1995-2005 Pre-1995 1995-2005 Single-Family 38.4 44.9 102.7 106.2 38.5 35.5 Detached 37.9 44.7 104.5 107.8 38.8 35.4 Attached 43.8 55.5 86.9 85.1 34.2 37.6 Multi-Family 63.8 58.7 58.3 49.2 27.2 24.3 2 to 4 units 69.0 55.1 70.7 59.4 29.5 25.0 5 or more units 61.5 59.6 53.6 47.2 26.3 24.2 Mobile Homes 82.4 57.1 69.6 74.5 29.7 25.2 Note(s): Source(s): 2005 Residential Delivered Energy Consumption Intensities, by Principal Building Type and Vintage Per Square Foot (thousand Btu) (1) Per Household (million Btu) Per Household Member (million Btu) 1) Energy consumption per square foot was calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the U.S. was 1,618 square feet. Average

15

Residential Sector Demand Module  

Reports and Publications (EIA)

Model Documentation - Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

Owen Comstock

2012-12-19T23:59:59.000Z

16

Residential Sector Demand Module  

Reports and Publications (EIA)

Model Documentation - Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

Owen Comstock

2013-11-05T23:59:59.000Z

17

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

20 20 Site Consumption Primary Consumption Total Residential Industry Electric Gen. Transportation Residential Industry Transportation (quads) 1980 5% 28% 8% 56% | 8% 31% 56% 34.2 1981 5% 26% 7% 59% | 7% 29% 59% 31.9 1982 5% 26% 5% 61% | 6% 28% 61% 30.2 1983 4% 25% 5% 62% | 6% 27% 62% 30.1 1984 5% 26% 4% 61% | 6% 27% 61% 31.1 1985 5% 25% 4% 63% | 6% 26% 63% 30.9 1986 5% 24% 5% 63% | 6% 26% 63% 32.2 1987 5% 25% 4% 63% | 6% 26% 63% 32.9 1988 5% 24% 5% 63% | 6% 26% 63% 34.2 1989 5% 24% 5% 63% | 7% 25% 63% 34.2 1990 4% 25% 4% 64% | 5% 26% 64% 33.6 1991 4% 24% 4% 65% | 5% 26% 65% 32.8 1992 4% 26% 3% 65% | 5% 27% 65% 33.5 1993 4% 25% 3% 65% | 5% 26% 65% 33.8 1994 4% 25% 3% 65% | 5% 26% 65% 34.7 1995 4% 25% 2% 67% | 5% 26% 67% 34.6 1996 4% 25% 2% 66% | 5% 26% 66% 35.8 1997 4% 26% 3% 66% | 5% 26% 66% 36.3 1998 3% 25% 4% 66% | 5% 26% 66% 36.9 1999 4% 25% 3% 66% | 5% 26% 66% 38.0 2000 4% 24% 3% 67% | 5% 25% 67% 38.4 2001 4% 24% 3% 67% | 5% 25% 67% 38.3 2002 4% 24% 3% 68% | 5% 25% 68% 38.4 2003

18

residential sector key indicators | OpenEI  

Open Energy Info (EERE)

residential sector key indicators residential sector key indicators Dataset Summary Description This dataset is the 2009 United States Residential Sector Key Indicators and Consumption, part of the Source EIA Date Released March 01st, 2009 (5 years ago) Date Updated Unknown Keywords AEO consumption EIA energy residential sector key indicators Data application/vnd.ms-excel icon 2009 Residential Sector Key Indicators and Consumption (xls, 55.3 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually Time Period License License Open Data Commons Public Domain Dedication and Licence (PDDL) Comment http://www.eia.gov/abouteia/copyrights_reuse.cfm Rate this dataset Usefulness of the metadata Average vote Your vote Usefulness of the dataset Average vote Your vote

19

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

0 0 Region (1) Northeast 73.5 122.2 47.7 24% New England 77.0 129.4 55.3 7% Middle Atlantic 72.2 119.7 45.3 17% Midwest 58.9 113.5 46.0 28% East North Central 61.1 117.7 47.3 20% West North Central 54.0 104.1 42.9 8% South 51.5 79.8 31.6 31% South Atlantic 47.4 76.1 30.4 16% East South Central 56.6 87.3 36.1 6% West South Central 56.6 82.4 31.4 9% West 56.6 77.4 28.1 18% Mountain 54.4 89.8 33.7 6% Pacific 58.0 71.8 25.7 11% U.S. Average 58.7 94.9 37.0 100% Note(s): Source(s): 1) Energy consumption per square foot was calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the U.S. was 1,618 square feet. Average total floor space, which includes garages, attics and unfinished basements, equaled 2,309 square feet.

20

Buildings Energy Data Book: 8.2 Residential Sector Water Consumption  

Buildings Energy Data Book (EERE)

2 2 1999 Single-Family Home Daily Water Consumption by End Use (Gallons per Capita) (1) Fixture/End Use Toilet 18.5 18.3% Clothes Washer 15 14.9% Shower 11.6 11.5% Faucet 10.9 10.8% Other Domestic 1.6 1.6% Bath 1.2 1.2% Dishwasher 1 1.0% Leaks 9.5 9.4% Outdoor Use (2) 31.7 31.4% Total (2) 101 100% Note(s): Source(s): Average gallons Total Use per capita per day Percent 1) Based analysis of 1,188 single-family homes at 12 study locations. 2) Total Water use derived from USGS. Outdoor use is the difference between total and indoor uses. American Water Works Association Research Foundation, Residential End Uses of Water, 1999; U.S. Geological Survey, Estimated Use of Water in the U.S. in 2000, U.S. Geological Survey Circular 1268, 2004, Table 6, p. 17; and Vickers, Amy, Handbook of Water Use and Conservation, June 2002, p. 15.

Note: This page contains sample records for the topic "residential sector 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

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

Residential Building Component Loads as of 1998 (1) 1) "Load" represents the thermal energy lossesgains that when combined will be offset by a building's heatingcooling system...

22

Operational energy consumption and GHG emissions in residential sector in urban China : an empirical study in Jinan  

E-Print Network (OSTI)

Driven by rapid urbanization and increasing household incomes, residential energy consumption in urban China has been growing steadily in the past decade, posing critical energy and greenhouse gas emission challenges. ...

Zhang, Jiyang, M.C.P. Massachusetts Institute of Technology

2010-01-01T23:59:59.000Z

23

Buildings Energy Data Book: 8.2 Residential Sector Water Consumption  

Buildings Energy Data Book (EERE)

1 1 Residential Water Use by Source (Million Gallons per Day) Year 1980 3,400 1985 3,320 1990 3,390 1995 3,390 2000 (3) (3) 3,590 2005 3,830 Note(s): Source(s): 29,430 25,600 1) Public supply water use: water withdrawn by public and private water suppliers that furnish water to at least 25 people or have a minimum of 15 connections. 2) Self-supply water use: Water withdrawn from a groundwater or surface-water source by a user rather than being obtained from a public supply. 3) USGS did not provide estimates of residential use from public supplies in 2000. This value was estimated based on the residential portion of public supply in 1995 and applied to the total public supply water use in 2000. U.S. Geological Survey, Estimated Use of Water in the U.S. in 1985, U.S. Geological Survey Circular 1004, 1988; U.S. Geological Survey, Estimated Use of

24

Propane demand modeling for residential sectors- A regression analysis.  

E-Print Network (OSTI)

??This thesis presents a forecasting model for the propane consumption within the residential sector. In this research we explore the dynamic behavior of different variables… (more)

Shenoy, Nitin K.

2011-01-01T23:59:59.000Z

25

Buildings Energy Data Book: 8.2 Residential Sector Water Consumption  

Buildings Energy Data Book (EERE)

6 6 Residential Water Billing Rate Structures for Community Water Systems Rate Structure Uniform Rates Declining Block Rate Increasing Block Rate Peak Period or Seasonal Rate Separate Flat Fee Annual Connection Fee Combined Flat Fee Other Rate Structures Note(s): Source(s): 3.0% 9.0% 1) Systems serving more than 10,000 users provide service to 82% of the population served by community water systems. Columns do not sum to 100% because some systems use more than one rate structure. 2) Uniform rates charge a set price for each unit of water. Block rates charge a different price for each additional increment of usage. The prices for each increment is higher for increasing block rates and lower for decreasing block rates. Peak rates and seasonal rates charge higher prices when demand is highest. Flat fees charge a set price for

26

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

9 9 Total Residential Industry Electric Gen. Transportation Residential Industry Transportation (quads) 1980 24% 41% 19% 3% | 30% 49% 3% 20.22 1981 23% 42% 19% 3% | 30% 49% 3% 19.74 1982 26% 39% 18% 3% | 32% 45% 3% 18.36 1983 26% 39% 17% 3% | 32% 46% 3% 17.20 1984 25% 40% 17% 3% | 31% 47% 3% 18.38 1985 25% 40% 18% 3% | 32% 46% 3% 17.70 1986 26% 40% 16% 3% | 32% 46% 3% 16.59 1987 25% 41% 17% 3% | 31% 47% 3% 17.63 1988 26% 42% 15% 3% | 31% 47% 3% 18.44 1989 25% 41% 16% 3% | 30% 47% 3% 19.56 1990 23% 43% 17% 3% | 29% 49% 4% 19.57 1991 23% 43% 17% 3% | 29% 49% 3% 20.03 1992 23% 43% 17% 3% | 29% 49% 3% 20.71 1993 24% 43% 17% 3% | 30% 48% 3% 21.24 1994 23% 42% 18% 3% | 29% 48% 3% 21.75 1995 22% 42% 19% 3% | 28% 49% 3% 22.71 1996 23% 43% 17% 3% | 29% 49% 3% 23.14 1997 22% 43% 18% 3% | 28% 49% 3% 23.34 1998 20% 43% 20% 3% | 27% 50% 3% 22.86 1999 21% 41% 21% 3% | 28% 48% 3% 22.88 2000 21% 40% 22% 3% | 29% 47% 3% 23.66 2001 21% 38% 24% 3% | 30% 45% 3% 22.69 2002 21% 38% 24% 3% | 30% 45%

27

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

5 5 Natural Fuel Other Renw. Site Site Primary Gas Oil LPG Fuel(1) En.(2) Electric Total Percent Electric (3) Total Percent Space Heating (4) 3.50 0.53 0.30 0.04 0.43 0.44 5.23 44.7% | 1.35 6.15 27.8% Water Heating 1.29 0.10 0.07 0.01 0.45 1.92 16.4% | 1.38 2.86 12.9% Space Cooling 0.00 1.08 1.08 9.2% | 3.34 3.34 15.1% Lighting 0.69 0.69 5.9% | 2.13 2.13 9.7% Refrigeration (6) 0.45 0.45 3.9% | 1.41 1.41 6.4% Electronics (5) 0.54 0.54 4.7% | 1.68 1.68 7.6% Wet Cleaning (7) 0.06 0.33 0.38 3.3% | 1.01 1.06 4.8% Cooking 0.22 0.03 0.18 0.43 3.7% | 0.57 0.81 3.7% Computers 0.17 0.17 1.5% | 0.53 0.53 2.4% Other (8) 0.00 0.16 0.01 0.20 0.37 3.2% | 0.63 0.80 3.6% Adjust to SEDS (9) 0.42 0.42 3.6% | 1.29 1.29 5.8% Total 5.06 0.63 0.56 0.04 0.45 4.95 11.69 100% | 15.34 22.07 100% Note(s): Source(s): 2010 Residential Energy End-Use Splits, by Fuel Type (Quadrillion Btu) Primary 1) Kerosene and coal are assumed attributable to space heating. 2) Comprised of wood space heating (0.42 quad), solar water heating (0.01

28

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

8 8 Natural Fuel Other Renw. Site Site Primary Gas Oil LPG Fuel(1) En.(2) Electric Total Percent Electric (3) Total Percent Space Heating (4) 3.20 0.31 0.22 0.03 0.46 0.49 4.72 38.9% | 1.45 5.67 23.9% Water Heating 1.27 0.04 0.03 0.02 0.54 1.90 15.6% | 1.60 2.96 12.5% Space Cooling 0.00 1.25 1.25 10.3% | 3.68 3.68 15.5% Lighting 0.48 0.48 3.9% | 1.41 1.41 5.9% Refrigeration (5) 0.52 0.52 4.3% | 1.54 1.54 6.5% Electronics (6) 0.44 0.44 3.6% | 1.29 1.29 5.4% Wet Cleaning (7) 0.07 0.32 0.39 3.2% | 0.95 1.01 4.3% Cooking 0.23 0.02 0.15 0.40 3.3% | 0.44 0.69 2.9% Computers 0.27 0.27 2.2% | 0.79 0.79 3.3% Other (8) 0.00 0.22 0.07 1.48 1.77 14.6% | 4.35 4.64 19.6% Total 4.76 0.35 0.51 0.03 0.55 5.94 12.14 100% | 17.50 23.69 100% Note(s): Source(s): 2035 Residential Energy End-Use Splits, by Fuel Type (Quadrillion Btu) Primary 1) Kerosene and coal are assumed attributable to space heating. 2) Comprised of wood space heating (0.44 quad), solar water heating (0.02

29

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

7 7 Natural Fuel Other Renw. Site Site Primary Gas Oil LPG Fuel(1) En.(2) Electric Total Percent Electric (3) Total Percent Space Heating (4) 3.28 0.38 0.24 0.03 0.46 0.46 4.85 41.5% | 1.40 5.78 25.8% Water Heating 1.32 0.05 0.04 0.02 0.53 1.96 16.8% | 1.60 3.03 13.5% Space Cooling 0.00 1.12 1.12 9.6% | 3.38 3.38 15.1% Lighting 0.47 0.47 4.0% | 1.42 1.42 6.3% Refrigeration (5) 0.48 0.48 4.1% | 1.45 1.45 6.5% Electronics (6) 0.37 0.37 3.2% | 1.12 1.12 5.0% Wet Cleaning (7) 0.06 0.30 0.37 3.1% | 0.91 0.98 4.4% Cooking 0.22 0.03 0.13 0.38 3.2% | 0.40 0.64 2.9% Computers 0.24 0.24 2.0% | 0.72 0.72 3.2% Other (8) 0.00 0.20 0.07 1.20 1.46 12.5% | 3.61 3.87 17.3% Total 4.88 0.43 0.50 0.03 1.00 5.30 11.69 100% | 16.00 22.39 100% Note(s): Source(s): 2025 Residential Energy End-Use Splits, by Fuel Type (Quadrillion Btu) Primary 1) Kerosene and coal are assumed attributable to space heating. 2) Comprised of wood space heating (0.43 quad), solar water heating (0.02

30

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

6 6 Natural Fuel Other Renw. Site Site Primary Gas Oil LPG Fuel(1) En.(2) Electric Total Percent Electric (3) Total Percent Space Heating (4) 3.40 0.48 0.26 0.03 0.44 0.42 5.03 44.2% | 1.27 5.88 27.9% Water Heating 1.31 0.07 0.05 0.02 0.48 1.92 16.9% | 1.44 2.88 13.7% Space Cooling 0.00 1.02 1.02 8.9% | 3.07 3.07 14.6% Lighting 0.53 0.53 4.6% | 1.60 1.60 7.6% Refrigeration (5) 0.45 0.45 4.0% | 1.37 1.37 6.5% Electronics (6) 0.33 0.33 2.9% | 0.99 0.99 4.7% Wet Cleaning (7) 0.06 0.33 0.39 3.4% | 0.98 1.04 5.0% Cooking 0.22 0.03 0.11 0.36 3.1% | 0.34 0.59 2.8% Computers 0.19 0.19 1.7% | 0.57 0.57 2.7% Other (8) 0.00 0.17 0.05 0.94 1.17 10.2% | 2.85 3.07 14.6% Total 4.99 0.55 0.51 0.03 0.51 4.79 11.38 100% | 14.47 21.06 100% Note(s): Source(s): 2015 Residential Energy End-Use Splits, by Fuel Type (Quadrillion Btu) Primary 1) Kerosene and coal are assumed attributable to space heating. 2) Comprised of wood space heating (0.43 quad), solar water heating (0.02

31

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

4 4 Primary Energy Consumption Total Per Household 1980 79.6 N.A. 123.5 15.72 197.4 1981 82.8 N.A. 114.2 15.23 184.0 1982 83.7 N.A. 114.6 15.48 184.9 1983 84.6 N.A. 110.6 15.38 181.9 1984 86.3 N.A. 113.9 15.90 184.2 1985 87.9 N.A. 111.7 16.02 182.3 1986 89.1 N.A. 108.4 15.94 178.8 1987 90.5 N.A. 108.2 16.21 179.1 1988 92.0 N.A. 112.7 17.12 186.0 1989 93.5 N.A. 113.7 17.76 190.0 1990 94.2 N.A. 102.7 16.92 179.5 1991 95.3 N.A. 104.6 17.38 182.4 1992 96.4 N.A. 104.7 17.31 179.6 1993 97.7 N.A. 107.5 18.19 186.1 1994 98.7 N.A. 105.2 18.08 183.2 1995 100.0 N.A. 104.6 18.49 185.0 1996 101.0 N.A. 110.2 19.48 192.9 1997 102.2 N.A. 104.4 18.94 185.3 1998 103.5 N.A. 98.9 18.93 182.8 1999 104.9 N.A. 101.5 19.53 186.1 2000 105.7 N.A. 105.6 20.37 192.7 2001 107.0 1.7% 102.1 20.01 187.0 2002 105.0 3.3% 106.6 20.75 197.7 2003 105.6 5.2% 109.2 21.07 199.6 2004 106.6 7.1% 106.6 21.06 197.6 2005 108.8 9.0% 105.7 21.59

32

Energy Efficiency Report: Chapter 3: Residential Sector  

U.S. Energy Information Administration (EIA)

3. The Residential Sector Introduction. More than 90 million single-family, multifamily, and mobile home households encompass the residential sector.

33

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

34

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%

35

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 ...

36

EIA Data: 2011 United States Residential Sector Key Indicators and  

Open Energy Info (EERE)

Residential Sector Key Indicators and Residential Sector Key Indicators and Consumption Dataset Summary Description This dataset is the 2011 United States Residential Sector Key Indicators and Consumption, part of the Annual Energy Outlook that highlights changes in the AEO Reference case projections for key energy topics. Source EIA Date Released December 16th, 2010 (4 years ago) Date Updated Unknown Keywords consumption EIA energy residential sector key indicators Data application/vnd.ms-excel icon Residential Sector Key Indicators and Consumption (xls, 62.5 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually Time Period License License Open Data Commons Public Domain Dedication and Licence (PDDL) Comment http://www.eia.gov/abouteia/copyrights_reuse.cfm

37

Energy Data Sourcebook for the U.S. Residential Sector  

E-Print Network (OSTI)

the U.S. Department of Energy (US DOE). It is the mostmodels that forecast US residential energy consumption bySurveys of sector energy use (US DOE 1990a; A G A 1991; EEI

Wenzel, T.P.

2010-01-01T23:59:59.000Z

38

EIA Data: 2011 United States Residential Sector Key Indicators...  

Open Energy Info (EERE)

Residential Sector Key Indicators and Consumption This dataset is the 2011 United...

39

Today in Energy - Residential Consumption & Efficiency  

Reports and Publications (EIA)

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

40

Energy Data Sourcebook for the U.S. Residential Sector  

E-Print Network (OSTI)

1989. Residential End-Use Energy Consumption: A Survey ofCathy R. Zoi. 1986. Unit Energy Consumption of ResidentialResidential Unit Energy Consumption Coefficients, Palo Alto,

Wenzel, T.P.

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "residential sector 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

Residential sector: the demand for energy services  

Science Conference Proceedings (OSTI)

The purpose of this report is to project the demand for residential services, and, thereby, the demand for energy into the future. The service demands which best represent a complete breakdown of residential energy consumption is identified and estimates of the amount of energy, by fuel type, used to satisfy each service demand for an initial base year (1978) are detailed. These estimates are reported for both gross (or input) energy use and net or useful energy use, in the residential sector. The various factors which affect the consumption level for each type of energy and each identified service demand are discussed. These factors include number of households, appliance penetration, choice of fuel type, technical conversion efficiency of energy using devices, and relative energy efficiency of the building shell (extent of insulation, resistance to air infiltration, etc.). These factors are discussed relative to both the present and expected future values, for the purpose of projections. The importance of the housing stock to service demand estimation and projection and trends in housing in Illinois are discussed. How the housing stock is projected based on population and household projections is explained. The housing projections to the year 2000 are detailed. The projections of energy consumption by service demand and fuel type are contrasted with the various energy demand projections in Illinois Energy Consumption Trends: 1960 to 2000 and explains how and why the two approaches differ. (MCW)

Not Available

1981-01-01T23:59:59.000Z

42

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

43

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 ...

44

MISCELLANEOUS ELECTRICITY USE IN THE U.S. RESIDENTIAL SECTOR  

E-Print Network (OSTI)

-2010). Our study has two components: a historical analysis of miscellaneous electricity use (1976- 1995 consumption increased at an annual rate of 4.6%. In 1995, miscellaneous electricity consumption totaled 235LBNL-40295 UC-1600 MISCELLANEOUS ELECTRICITY USE IN THE U.S. RESIDENTIAL SECTOR M. C. Sanchez, J. G

45

Electricity savings potentials in the residential sector of Bahrain  

SciTech Connect

Electricity is the major fuel (over 99%) used in the residential, commercial, and industrial sectors in Bahrain. In 1992, the total annual electricity consumption in Bahrain was 3.45 terawatt-hours (TWh), of which 1.95 TWh (56%) was used in the residential sector, 0.89 TWh (26%) in the commercial sector, and 0.59 TWh (17%) in the industrial sector. Agricultural energy consumption was 0.02 TWh (less than 1%) of the total energy use. In Bahrain, most residences are air conditioned with window units. The air-conditioning electricity use is at least 50% of total annual residential use. The contribution of residential AC to the peak power consumption is even more significant, approaching 80% of residential peak power demand. Air-conditioning electricity use in the commercial sector is also significant, about 45% of the annual use and over 60% of peak power demand. This paper presents a cost/benefit analysis of energy-efficient technologies in the residential sector. Technologies studied include: energy-efficient air conditioners, insulating houses, improved infiltration, increasing thermostat settings, efficient refrigerators and freezers, efficient water heaters, efficient clothes washers, and compact fluorescent lights. We conservatively estimate a 32% savings in residential electricity use at an average cost of about 4 fils per kWh. (The subsidized cost of residential electricity is about 12 fils per kWh. 1000 fils = 1 Bahrain Dinar = US$ 2.67). We also discuss major policy options needed for implementation of energy-efficiency technologies.

Akbari, H. [Lawrence Berkeley National Lab., CA (United States); Morsy, M.G.; Al-Baharna, N.S. [Univ. of Bahrain, Manama (Bahrain)

1996-08-01T23:59:59.000Z

46

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

47

End-use electrification in the residential sector : a general equilibrium analysis of technology advancements  

E-Print Network (OSTI)

The residential sector in the U.S. is responsible for about 20% of the country's primary energy use (EIA, 2011). Studies estimate that efficiency improvements in this sector can reduce household energy consumption by over ...

Madan, Tanvir Singh

2012-01-01T23:59:59.000Z

48

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.

49

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

50

Residential Sector Demand Module 2000, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

1999-12-01T23:59:59.000Z

51

Residential Sector Demand Module 2004, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2004-02-01T23:59:59.000Z

52

Residential Sector Demand Module 2001, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2000-12-01T23:59:59.000Z

53

Residential Sector Demand Module 2002, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2001-12-01T23:59:59.000Z

54

Residential Sector Demand Module 2005, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2005-04-01T23:59:59.000Z

55

Residential Sector Demand Module 2003, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2003-01-01T23:59:59.000Z

56

Residential Sector Demand Module 2008, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2008-10-10T23:59:59.000Z

57

Residential Sector Demand Module 2006, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2006-03-01T23:59:59.000Z

58

Residential Sector Demand Module 2009, Model Documentation  

Reports and Publications (EIA)

Model Documentation - Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2009-05-01T23:59:59.000Z

59

Residential Sector Demand Module 1999, Model Documentation  

Reports and Publications (EIA)

This is the fifth edition of the Model Documentation Report: Residential Sector DemandModule of the National Energy Modeling System (NEMS). It reflects changes made to themodule over the past year for the Annual Energy Outlook 1999.

John H. Cymbalsky

1998-12-01T23:59:59.000Z

60

Residential Sector Demand Module 2007, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2007-04-26T23:59:59.000Z

Note: This page contains sample records for the topic "residential sector 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

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 ...

62

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...

63

Energy Data Sourcebook for the U.S. Residential Sector  

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

Data Sourcebook for the U.S. Residential Sector Data Sourcebook for the U.S. Residential Sector Title Energy Data Sourcebook for the U.S. Residential Sector Publication Type Report LBNL Report Number LBNL-40297 Year of Publication 1997 Authors Wenzel, Thomas P., Jonathan G. Koomey, Gregory J. Rosenquist, Marla C. Sanchez, and James W. Hanford Date Published 09/1997 Publisher Lawrence Berkeley National Laboratory City Berkeley, CA ISBN Number LBNL-40297, UC-1600 Keywords Enduse, Energy End-Use Forecasting, EUF Abstract Analysts assessing policies and programs to improve energy efficiency in the residential sector require disparate input data from a variety of sources. This sourcebook, which updates a previous report, compiles these input data into a single location. The data provided include information on end-use unit energy consumption (UEC) values of appliances and equipment; historical and current appliance and equipment market shares; appliance and equipment efficiency and sales trends; appliance and equipment efficiency standards; cost vs. efficiency data for appliances and equipment; product lifetime estimates; thermal shell characteristics of buildings; heating and cooling loads; shell measure cost data for new and retrofit buildings; baseline housing stocks; forecasts of housing starts; and forecasts of energy prices and other economic drivers. This report is the essential sourcebook for policy analysts interested in residential sector energy use. The report can be downloaded from the Web at http://enduse.lbl.gov/Projects/RED.html. Future updates to the report, errata, and related links, will also be posted at this address.

64

Future Air Conditioning Energy Consumption in Developing Countriesand what can be done about it: The Potential of Efficiency in theResidential Sector  

SciTech Connect

The dynamics of air conditioning are of particular interestto energy analysts, both because of the high energy consumption of thisproduct, but also its disproportionate impact on peak load. This paperaddresses the special role of this end use as a driver of residentialelectricity consumption in rapidly developing economies. Recent historyhas shown that air conditioner ownership can grow grows more rapidly thaneconomic growth in warm-climate countries. In 1990, less than a percentof urban Chinese households owned an air conditioner; by 2003 this numberrose to 62 percent. The evidence suggests a similar explosion of airconditioner use in many other countries is not far behind. Room airconditioner purchases in India are currently growing at 20 percent peryear, with about half of these purchases attributed to the residentialsector. This paper draws on two distinct methodological elements toassess future residential air conditioner 'business as usual' electricityconsumption by country/region and to consider specific alternative 'highefficiency' scenarios. The first component is an econometric ownershipand use model based on household income, climate and demographicparameters. The second combines ownership forecasts and stock accountingwith geographically specific efficiency scenarios within a uniqueanalysis framework (BUENAS) developed by LBNL. The efficiency scenariomodule considers current efficiency baselines, available technologies,and achievable timelines for development of market transformationprograms, such as minimum efficiency performance standards (MEPS) andlabeling programs. The result is a detailed set of consumption andemissions scenarios for residential air conditioning.

McNeil, Michael A.; Letschert, Virginie E.

2007-05-01T23:59:59.000Z

65

Future Air Conditioning Energy Consumption in Developing Countriesand what can be done about it: The Potential of Efficiency in theResidential Sector  

SciTech Connect

The dynamics of air conditioning are of particular interestto energy analysts, both because of the high energy consumption of thisproduct, but also its disproportionate impact on peak load. This paperaddresses the special role of this end use as a driver of residentialelectricity consumption in rapidly developing economies. Recent historyhas shown that air conditioner ownership can grow grows more rapidly thaneconomic growth in warm-climate countries. In 1990, less than a percentof urban Chinese households owned an air conditioner; by 2003 this numberrose to 62 percent. The evidence suggests a similar explosion of airconditioner use in many other countries is not far behind. Room airconditioner purchases in India are currently growing at 20 percent peryear, with about half of these purchases attributed to the residentialsector. This paper draws on two distinct methodological elements toassess future residential air conditioner 'business as usual' electricityconsumption by country/region and to consider specific alternative 'highefficiency' scenarios. The first component is an econometric ownershipand use model based on household income, climate and demographicparameters. The second combines ownership forecasts and stock accountingwith geographically specific efficiency scenarios within a uniqueanalysis framework (BUENAS) developed by LBNL. The efficiency scenariomodule considers current efficiency baselines, available technologies,and achievable timelines for development of market transformationprograms, such as minimum efficiency performance standards (MEPS) andlabeling programs. The result is a detailed set of consumption andemissions scenarios for residential air conditioning.

McNeil, Michael A.; Letschert, Virginie E.

2007-05-01T23:59:59.000Z

66

EIA Energy Efficiency-Residential Sector Energy Intensities, 1978-2001  

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

Residential Sector Energy Intensities Residential Sector Energy Intensities RESIDENTIAL SECTOR ENERGY INTENSITIES: 1978-2005 Released Date: August 2004 Page Last Modified:June 2009 These tables provide estimates of residential sector energy consumption and energy intensities for 1978 -1984, 1987, 1990, 1993, 1997, 2001 and 2005 based on the Residential Energy Consumption Survey (RECS). Total Site Energy Consumption (U.S. and Census Region) Html Excel PDF By Type of Housing Unit (Table 1a) html Table 1a excel table 1a. excel table 1a. Weather-Adjusted by Type of Housing Unit (Table 1b) html table 1b excel table 1b excel table 1b Total Primary Energy Consumption (U.S. and Census Region) By Type of Housing Unit (Table 1c) html Table 1c excel table 1c excel table 1c Weather-Adjusted by Type of Housing Unit (Table 1d)

67

Texas Natural Gas Residential Consumption (Million Cubic Feet...  

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

View History: Monthly Annual Download Data (XLS File) Texas Natural Gas Residential Consumption (Million Cubic Feet) Texas Natural Gas Residential Consumption (Million Cubic Feet)...

68

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...

69

South Dakota Natural Gas Residential Consumption (Million Cubic...  

Gasoline and Diesel Fuel Update (EIA)

View History: Monthly Annual Download Data (XLS File) South Dakota Natural Gas Residential Consumption (Million Cubic Feet) South Dakota Natural Gas Residential Consumption...

70

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

All Reports & Publications All Reports & Publications Search By: Go Pick a date range: From: To: Go graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years December 20, 2013 Gas furnace efficiency has large implications for residential natural gas use December 5, 2013 EIA publishes state fact sheets on residential energy consumption and characteristics August 19, 2013 All 48 related articles › ResidentialAvailable formats PDF Modeling Distributed Generation in the Buildings Sectors Released: August 29, 2013 This report focuses on how EIA models residential and commercial sector distributed generation, including combined heat and power, for the Annual Energy Outlook. State Fact Sheets on Household Energy Use

71

California Natural Gas Residential Consumption (Million Cubic ...  

U.S. Energy Information Administration (EIA)

California Natural Gas Residential Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9; 1960's: 522,122 ...

72

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...

73

,"New Mexico Natural Gas Residential Consumption (MMcf)"  

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

,,"(202) 586-8800",,,"10312013 3:27:06 PM" "Back to Contents","Data 1: New Mexico Natural Gas Residential Consumption (MMcf)" "Sourcekey","N3010NM2" "Date","New Mexico...

74

Analysis of ultimate energy consumption by sector in Islamic republic of Iran  

Science Conference Proceedings (OSTI)

Total ultimate energy consumption in Iran was 1033.32 MBOE in 2006, and increased at an average annual rate of 6% in 1996-2006. Household and commercial sector has been the main consumer sector (418.47 MBOE) and the fastest-growing sector (7.2%) that ... Keywords: Iran, agricultural sector, energy audits, energy consumption, industrial sector, residential and commercial sector, transportation sector

B. Farahmandpour; I. Nasseri; H. Houri Jafari

2008-02-01T23:59:59.000Z

75

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.

76

Country Review of Energy-Efficiency Financial Incentives in the Residential Sector  

E-Print Network (OSTI)

Financial Incentives in the Residential Sector Stephane deFinancial Incentives in the Residential Sector Stephane desavings achieved in the residential sector. In contrast,

Can, Stephane de la Rue du

2011-01-01T23:59:59.000Z

77

Strategies for Low Carbon Growth In India: Industry and Non Residential Sectors  

E-Print Network (OSTI)

Efficiency Scenario (non-residential sector only) – AssumesIndia: Industry and Non Residential Sectors Jayant Sathaye,and support. The Non Residential sector analysis benefited

Sathaye, Jayant

2011-01-01T23:59:59.000Z

78

Energy Data Sourcebook for the U.S. Residential Sector  

E-Print Network (OSTI)

J.E. 1986. The LBL Residential Energy Model. LawrenceInc. MEANS. 1992. Residential Cost Data: 11th Annual EditionInstitute. 1989. Residential End-Use Energy Consumption: A

Wenzel, T.P.

2010-01-01T23:59:59.000Z

79

1997 Consumption and Expenditures-Data Tables RECS  

U.S. Energy Information Administration (EIA)

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

80

Solar Photovoltaic Financing: Residential Sector Deployment  

DOE Green Energy (OSTI)

This report presents the information that homeowners and policy makers need to facilitate PV financing at the residential level. The full range of cash payments, bill savings, and tax incentives is covered, as well as potentially available solar attribute payments. Traditional financing is also compared to innovative solutions, many of which are borrowed from the commercial sector. Together, these mechanisms are critical for making the economic case for a residential PV installation, given its high upfront costs. Unfortunately, these programs are presently limited to select locations around the country. By calling attention to these innovative initiatives, this report aims to help policy makers consider greater adoption of these models to benefit homeowners interested installing a residential PV system.

Coughlin, J.; Cory, K.

2009-03-01T23:59:59.000Z

Note: This page contains sample records for the topic "residential sector 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

Future Air Conditioning Energy Consumption in Developing Countries and what can be done about it: The Potential of Efficiency in the Residential Sector  

E-Print Network (OSTI)

Survey on Electricity Consumption Characteristics of Homethe stakes for energy consumption are high, as we hope atAir Conditioning Energy Consumption in Developing Countries

McNeil, Michael A.; Letschert, Virginie E.

2008-01-01T23:59:59.000Z

82

Residential Sector Demand Module 1998, Model Documentation  

Reports and Publications (EIA)

This is the fourth edition of the Model Documentation Report: Residential Sector DemandModule of the National Energy Modeling System (NEMS). It reflects changes made to themodule over the past year for the Annual Energy Outlook 1998. Since last year, severalnew end-use services were added to the module, including: Clothes washers,dishwashers, furnace fans, color televisions, and personal computers. Also, as with allNEMS modules, the forecast horizon has been extended to the year 2020.

John H. Cymbalsky

1998-01-01T23:59:59.000Z

83

1997 Residential Energy Consumption and Expenditures per Household ...  

U.S. Energy Information Administration (EIA)

Return to: Residential Home Page . Changes in the 1997 RECS: Housing Unit Type Per Household Member Per Building Increase. Residential Energy Consumption ...

84

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

85

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

86

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...

87

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...

88

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

89

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.

90

Is Efficiency Enough? Towards a New Framework for Carbon Savings in the California Residential Sector  

E-Print Network (OSTI)

Report. 2004. California Residential Appliance SaturationAdministration (EIA). 1996. Residential Energy ConsumptionEIA). 1999. “A Look at Residential Energy Consumption in

Moezzi, Mithra; Diamond, Rick

2005-01-01T23:59:59.000Z

91

Residential Sector Demand Module 1997, Model Documentation  

Reports and Publications (EIA)

This is the third edition of the Model Documentation Report: Residential Sector DemandModule of the National Energy Modeling System. It reflects changes made to the moduleover the past year for the Annual Energy Outlook 1997. Since last year, a subroutinewas added to the model which allows technology and fuel switching when space heaters,heat pump air conditioners, water heaters, stoves, and clothes dryers are retired in bothpre-1994 and post-1993 single-family homes. Also, a time-dependant function forcomputing the installed capital cost of equipment in new construction and the retail costof replacement equipment in existing housing was added.

John H. Cymbalsky

1997-01-01T23:59:59.000Z

92

Statistical Review of UK Residential Sector Electrical Loads  

E-Print Network (OSTI)

This paper presents a comprehensive statistical review of data obtained from a wide range of literature on the most widely used electrical appliances in the UK residential load sector. It focuses on individual appliances and begins by consideration of the electrical operations performed by the load. This approach allows for the loads to be categorised based on the electrical characteristics, and also provides information on the reactive power characteristics of the load, which is often neglected from standard consumption statistics. This data is particularly important for power system analysis. In addition to this, device ownership statistics and probability distribution functions of power demand are presented for the main residential loads. Although the data presented is primarily intended as a resource for the development of load profiles for power system analysis, it contains a large volume of information which provides a useful database for the wider research community.

Tsagarakis, G; Kiprakis, A E

2013-01-01T23:59:59.000Z

93

Figure 7. U.S. dry natural gas consumption by sector, 2005-2040 ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 7. U.S. dry natural gas consumption by sector, 2005-2040 (trllion cubic feet) Residential Commercial Transportation Gas to liquids

94

Figure 58. Residential sector adoption of renewable energy ...  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 58. Residential sector adoption of renewable energy technologies in two cases, 2005-2040 PV and wind (gigawatts) Heat pump ...

95

Fuel consumption: Industrial, residential, and general studies. (Latest citations from the NTIS Bibliographic database). Published Search  

SciTech Connect

The bibliography contains citations concerning fuel consumption in industrial and residential sectors. General studies of fuel supply, demand, policy, forecasts, and consumption models are presented. Citations examine fuel information and forecasting systems, fuel production, international economic and energy activities, heating oils, and pollution control. Fuel consumption in the transportation sector is covered in a separate bibliography. (Contains 250 citations and includes a subject term index and title list.)

Not Available

1994-08-01T23:59:59.000Z

96

Major models and data sources for residential and commercial sector energy conservation analysis. Final report  

SciTech Connect

Major models and data sources are reviewed that can be used for energy-conservation analysis in the residential and commercial sectors to provide an introduction to the information that can or is available to DOE in order to further its efforts in analyzing and quantifying their policy and program requirements. Models and data sources examined in the residential sector are: ORNL Residential Energy Model; BECOM; NEPOOL; MATH/CHRDS; NIECS; Energy Consumption Data Base: Household Sector; Patterns of Energy Use by Electrical Appliances Data Base; Annual Housing Survey; 1970 Census of Housing; AIA Research Corporation Data Base; RECS; Solar Market Development Model; and ORNL Buildings Energy Use Data Book. Models and data sources examined in the commercial sector are: ORNL Commercial Sector Model of Energy Demand; BECOM; NEPOOL; Energy Consumption Data Base: Commercial Sector; F.W. Dodge Data Base; NFIB Energy Report for Small Businesses; ADL Commercial Sector Energy Use Data Base; AIA Research Corporation Data Base; Nonresidential Buildings Surveys of Energy Consumption; General Electric Co: Commercial Sector Data Base; The BOMA Commercial Sector Data Base; The Tishman-Syska and Hennessy Data Base; The NEMA Commercial Sector Data Base; ORNL Buildings Energy Use Data Book; and Solar Market Development Model. Purpose; basis for model structure; policy variables and parameters; level of regional, sectoral, and fuels detail; outputs; input requirements; sources of data; computer accessibility and requirements; and a bibliography are provided for each model and data source.

Not Available

1980-09-01T23:59:59.000Z

97

Buildings Energy Data Book: 2.2 Residential Sector Characteristics  

Buildings Energy Data Book (EERE)

Square footage includes attic, garage, and basement square footage. EIA, 2005 Residential Energy Consumption Survey, Oct. 2008. Share of Average Home Size (1) Average Home Size...

98

Residential Sector Demand Module 1995, Model Documentation  

Reports and Publications (EIA)

This updated version of the NEMS Residential Module Documentation includes changesmade to the residential module for the production of the Annual Energy Outlook 1995.

John H. Cymbalsky

1995-03-01T23:59:59.000Z

99

Future Air Conditioning Energy Consumption in Developing Countries and what can be done about it: The Potential of Efficiency in the Residential Sector  

E-Print Network (OSTI)

years later, standards on these products alone were estimated to have reduced annual national electricity consumptionyear, given by UEC 0c (y) = UEC 0 (Income c (y),CDD) The total electricity consumption

McNeil, Michael A.; Letschert, Virginie E.

2008-01-01T23:59:59.000Z

100

Future Air Conditioning Energy Consumption in Developing Countries and what can be done about it: The Potential of Efficiency in the Residential Sector  

E-Print Network (OSTI)

Henderson (2005) Home air conditioning in Europe – how muchA.A. Pavlova ( 2003). Air conditioning market saturation and+ paper 6,306 Future Air Conditioning Energy Consumption in

McNeil, Michael A.; Letschert, Virginie E.

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "residential sector 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

Strategies for Low Carbon Growth In India: Industry and Non Residential Sectors  

Science Conference Proceedings (OSTI)

This report analyzed the potential for increasing energy efficiency and reducing greenhouse gas emissions (GHGs) in the non-residential building and the industrial sectors in India. The first two sections describe the research and analysis supporting the establishment of baseline energy consumption using a bottom up approach for the non residential sector and for the industry sector respectively. The third section covers the explanation of a modeling framework where GHG emissions are projected according to a baseline scenario and alternative scenarios that account for the implementation of cleaner technology.

Sathaye, Jayant; de la Rue du Can, Stephane; Iyer, Maithili; McNeil, Michael; Kramer, Klaas Jan; Roy, Joyashree; Roy, Moumita; Chowdhury, Shreya Roy

2011-04-15T23:59:59.000Z

102

Energy data sourcebook for the US residential sector  

Science Conference Proceedings (OSTI)

Analysts assessing policies and programs to improve energy efficiency in the residential sector require disparate input data from a variety of sources. This sourcebook, which updates a previous report, compiles these input data into a single location. The data provided include information on end-use unit energy consumption (UEC) values of appliances and equipment efficiency; historical and current appliance and equipment market shares; appliances and equipment efficiency and sales trends; appliance and equipment efficiency standards; cost vs. efficiency data for appliances and equipment; product lifetime estimates; thermal shell characteristics of buildings; heating and cooling loads; shell measure cost data for new and retrofit buildings; baseline housing stocks; forecasts of housing starts; and forecasts of energy prices and other economic drivers. This report is the essential sourcebook for policy analysts interested in residential sector energy use. The report can be downloaded from the Web at http://enduse.lbl. gov/Projects/RED.html. Future updates to the report, errata, and related links, will also be posted at this address.

Wenzel, T.P.; Koomey, J.G.; Sanchez, M. [and others

1997-09-01T23:59:59.000Z

103

Projected Regional Impacts of Appliance Efficiency Standards for the U.S. Residential Sector  

E-Print Network (OSTI)

Price. 1994. Baseline Data for the Residential Sector andDevelopment of a Residential Forecasting Database. LawrenceG . Koomey. 1994. Residential HVAC Data, Assumptions and

Koomey, J.G.

2010-01-01T23:59:59.000Z

104

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

105

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

106

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

107

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

108

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

109

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

110

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.

111

Solid-State Lighting: Residential Lighting End-Use Consumption  

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

Lighting End-Use Consumption Study aims to improve the understanding of lighting energy usage in U.S. residential dwellings using a regional estimation framework. The...

112

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 ...

113

"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,...

114

Trends in U.S. Residential Natural Gas Consumption  

U.S. Energy Information Administration (EIA)

Natural gas prices may have also contributed to the decrease in natural gas consumption over the last 19 years. Residential natural gas prices have

115

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

116

Trends in U.S. Residential Natural Gas Consumption  

Annual Energy Outlook 2012 (EIA)

the Residential Energy Consumption Survey. Energy Information Administration, Office of Oil and Gas, June 2010 1 Natural gas prices may have also contributed to the decrease...

117

Trends in U.S. Residential Natural Gas Consumption  

Reports and Publications (EIA)

This report presents an analysis of residential natural gas consumption trends in the United States through 2009 and analyzes consumption trends for the United States as a whole (1990 through 2009) and for each Census Division (1998 through 2009).

Lejla Alic

2010-06-23T23:59:59.000Z

118

Solar Photovoltaic Financing: Residential Sector Deployment  

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

(a subsidiary of U.S. Bancorp), AFC First Financial Corporation, and Gemstone Lease Management, LLC, announced a residential solar lease program for homeowners who meet certain...

119

Energy Data Sourcebook for the U.S. Residential Sector  

E-Print Network (OSTI)

and 2% of total natural gas usage in the residential sector.ignition systems, which will decrease gas usage andincrease electricity usage for gas ranges. Figure 11.4. Cost

Wenzel, T.P.

2010-01-01T23:59:59.000Z

120

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

Note: This page contains sample records for the topic "residential sector 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

Modeling diffusion of electrical appliances in the residential sector  

SciTech Connect

This paper presents a methodology for modeling residential appliance uptake as a function of root macroeconomic drivers. The analysis concentrates on four major energy end uses in the residential sector: refrigerators, washing machines, televisions and air conditioners. The model employs linear regression analysis to parameterize appliance ownership in terms of household income, urbanization and electrification rates according to a standard binary choice (logistic) function. The underlying household appliance ownership data are gathered from a variety of sources including energy consumption and more general standard of living surveys. These data span a wide range of countries, including many developing countries for which appliance ownership is currently low, but likely to grow significantly over the next decades as a result of economic development. The result is a 'global' parameterization of appliance ownership rates as a function of widely available macroeconomic variables for the four appliances studied, which provides a reliable basis for interpolation where data are not available, and forecasting of ownership rates on a global scale. The main value of this method is to form the foundation of bottom-up energy demand forecasts, project energy-related greenhouse gas emissions, and allow for the construction of detailed emissions mitigation scenarios.

McNeil, Michael A.; Letschert, Virginie E.

2009-11-22T23:59:59.000Z

122

AEO2011: Renewable Energy Consumption by Sector and Source | OpenEI  

Open Energy Info (EERE)

Consumption by Sector and Source Consumption by Sector and Source Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 17, and contains only the reference case. The dataset uses quadrillion Btu. The data is broken down into marketed renewable energy, residential, commercial, industrial, transportation and electric power. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords Commercial Electric Power Industrial Renewable Energy Consumption Residential sector source transportation Data application/vnd.ms-excel icon AEO2011: Renewable Energy Consumption by Sector and Source- Reference Case (xls, 105 KiB) Quality Metrics Level of Review Peer Reviewed

123

The Impact of Residential Density on Vehicle Usage and Energy Consumption  

E-Print Network (OSTI)

DC. Steiner, R.L. (1994). Residential density and traveland Brownstone The Impact of Residential Density on VehicleUsage Total annual residential vehicular energy consumption

Golob, Thomas F.; Brownstone, David

2005-01-01T23:59:59.000Z

124

Trends in U.S. Residential Natural Gas Consumption  

Gasoline and Diesel Fuel Update (EIA)

Trends in U.S. Residential Natural Gas Consumption Trends in U.S. Residential Natural Gas Consumption This report presents an analysis of residential natural gas consumption trends in the United States through 2009 and analyzes consumption trends for the United States as a whole (1990 through 2009) and for each Census Division (1998 through 2009). It examines a long-term downward per- customer consumption trend and analyzes whether this trend persists across Census Divisions. The report also examines some of the factors that have contributed to the decline in per-customer consumption. To provide a more meaningful measure of per-customer consumption, EIA adjusted consumption data presented in the report for weather. Questions or comments on the contents of this article should be directed to Lejla Alic at Lejla.Alic@eia.doe.gov or (202) 586-0858.

125

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

126

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

127

State Residential Energy Consumption Shares 1996  

Gasoline and Diesel Fuel Update (EIA)

Residential customers in the Northeast are more heavily dependent on heating oil than are residential consumers in the rest of the country. Rhode Island is no exception. In 1996,...

128

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

129

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

130

Residential Energy Consumption Survey: Housing Characteristics,  

Gasoline and Diesel Fuel Update (EIA)

tni tni Residential Energy Consumption Survey: Housing Characteristics, 1981 Energy Information Administration Washington. D.C August 1983 T86T -UJ9AO9 aiji uuojj pasenojnd uaaq (OdO) i|oii)/v\ suoijdijosqns o; Ajdde jou saop aoiiou :e|ON asBa|d 'pjBo^sod at|j noA j| 3Sj| Suiije'Lu vi3 3M1 uo ;u!Buuaj o^sn o} }i ujnja> isnoi nox 'pJBOisod iuB»jodoi! UB aABL) pjnons hoA '}s\\ BujUBUJ VI3 9L|} uo ajB noA|| 'MaiAaj jsij SUJMBUJ suouBOjiqnd |BnuuBS}j BUJ -jonpuoo Sj (vi3) uoijej^siujuupv UOIJBLUJOIUI Afijau^ agj 'uoiieinBaj iuaoiujaAOQ Aq pajmbaj sv 30HON 02-13 maoj aapao ay 05. pa^oajjp aq pus siuamnooa jo 0088-353 (303) S8SOZ "D'Q 'uoiSu-pqsBtt T rao°H 50 UOT^BOLIOJUI

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

Is Efficiency Enough? Towards a New Framework for Carbon Savings in the California Residential Sector  

E-Print Network (OSTI)

of residential electricity consumption surpassed the rate ofresidential electricity consumption increased at a rate ofresidential electricity consumption grew 49%, a slightly lower growth rate

Moezzi, Mithra; Diamond, Rick

2005-01-01T23:59:59.000Z

133

Residential energy-consumption survey: consumption and expenditures, April 1978-March 1979  

SciTech Connect

Tables present data on energy consumption and expenditures for US households during a 12-month period. The total amount of energy consumed by the residential sector from April 1978 through March 1979 is estimated to have been 10,563 trillion Btu with an average household consumption of 138 million Btu. Table 1 summarizes residential energy consumption for all fuels (totals and averages) as wells as total amounts consumed and expenditures for each of the major fuel types (natural gas, electricity, fuel oil, and liquid petroleum gas). Tables 2 and 3 give the number of households and the average energy prices, respectively, for each of the major fuel types. In Tables 4 to 9, totals and averages for both consumption and expenditures are given for each of the major fuels. The consumption of each fuel is given first for all households using the fuel. Then, households are divided into those that use the fuel as their main source of heat and those using the fuel for other purposes. Electricity data (Tables 5 to 7) are further broken down into households that use electricity for air conditioning and those not using it for this purpose. Limited data are also presented on households that use each of the major fuels for heating water. Each of the consumption tables is given for a variety of general household features, including: geographical, structural and physical, and demographic characteristics. Tables 10 to 18 present the same information for the subgroup of households living in single-family owner-occupied detached houses. The third set of tables (19 to 27) is limited to households that paid directly for all of the energy they used. Tables 28 to 36 provide variance estimates for the data.

Not Available

1980-07-01T23:59:59.000Z

134

Is Efficiency Enough? Towards a New Framework for Carbon Savings in the California Residential Sector  

E-Print Network (OSTI)

only 27% of national energy consumption is consumed directlynational policies affecting the state. Nationwide, energy consumptionNational Association of Home Builders Personal Computer Portland Gas and Electric Residential Appliance Saturation Survey Residential Energy Consumption

Moezzi, Mithra; Diamond, Rick

2005-01-01T23:59:59.000Z

135

The Residential Sector: Changing Markets, Changing Technologies  

Science Conference Proceedings (OSTI)

Residential customers in the U.S. are confronted with markets for home services that continue to change rapidly. Not only are markets for traditional "utilities" such as telecommunications services, energy services, and entertainment services transitioning to competitive choice scenarios, but the technology which customers use in each of these arenas is changing rapidly as well. This report outlines the way that customers are responding to these changing market dynamics, in terms of the way they think ab...

1999-12-02T23:59:59.000Z

136

Indoor Environment and Energy Consumption of Urban Residential...  

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

Indoor Environment and Energy Consumption of Urban Residential Buildings in China Speaker(s): Hiroshi Yoshino Date: September 18, 2009 - 12:00pm Location: 90-3122 In China, the...

137

Wisconsin Natural Gas Residential Consumption (Million Cubic Feet)  

U.S. Energy Information Administration (EIA)

Wisconsin Natural Gas Residential Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9; 1960's: 90,994 ...

138

U.S. Natural Gas Residential Consumption (Million Cubic Feet)  

U.S. Energy Information Administration (EIA)

U.S. Natural Gas Residential Consumption (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 1973: 843,900: 747,331: 648,504: 465,867: 326,313 ...

139

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 ...

140

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 "residential sector 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

Buildings Energy Data Book: 2.2 Residential Sector Characteristics  

Buildings Energy Data Book (EERE)

to 1,499 24% 1,500 to 1,999 16% 2,000 to 2,499 9% 2,500 to 2,999 7% 3,000 or more 11% Total 100% Source(s): EIA, 2005 Residential Energy Consumption Survey, Oct. 2008, Table HC1-3....

142

Buildings Energy Data Book: 2.2 Residential Sector Characteristics  

Buildings Energy Data Book (EERE)

6.9% 5 or more units 2.1% 13.0% 15.0% Mobile Homes 5.1% 1.1% 6.2% Total 70.3% 29.6% 100% Source(s): EIA, 2005 Residential Energy Consumption Survey, Oct. 2008, Table HC3-1 and HC4...

143

2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions  

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

D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Bottled Gas (LPG or Propane) Usage Form What is the purpose of the Residential Energy Consumption Survey? The Residential Energy Consumption Survey (RECS) collects data on energy consumption and expenditures in U.S. housing units. Over 5,000 statistically selected households across the U.S. have already provided information about their household, the physical characteristics of their housing unit, their energy-using equipment, and their energy suppliers. Now we are requesting the energy billing records for these households from each of their energy suppliers. After all this information has been collected, the information will be used to

144

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

145

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

146

Renewable Energy Consumption by Energy Use Sector and Energy Source, 2004 -  

Open Energy Info (EERE)

by Energy Use Sector and Energy Source, 2004 - by Energy Use Sector and Energy Source, 2004 - 2008 Dataset Summary Description Provides annual consumption (in quadrillion Btu) of renewable energy by energy use sector (residential, commercial, industrial, transportation and electricity) and by energy source (e.g. solar, biofuel) for 2004 through 2008. Original sources for data are cited on spreadsheet. Also available from: www.eia.gov/cneaf/solar.renewables/page/trends/table1_2.xls Source EIA Date Released August 01st, 2010 (4 years ago) Date Updated Unknown Keywords annual energy consumption biodiesel Biofuels biomass energy use by sector ethanol geothermal Hydroelectric Conventional Landfill Gas MSW Biogenic Other Biomass renewable energy Solar Thermal/PV Waste wind Wood and Derived Fuels Data application/vnd.ms-excel icon RE Consumption by Energy Use Sector, Excel file (xls, 32.8 KiB)

147

New Zealand Energy Data: Oil Consumption by Fuel and Sector | OpenEI  

Open Energy Info (EERE)

Oil Consumption by Fuel and Sector Oil Consumption by Fuel and Sector Dataset Summary Description The New Zealand Ministry of Economic Development publishes energy data including many datasets related to oil and other petroleum products. Included here are two oil consumption datasets: quarterly petrol consumption by sector (agriculture, forestry and fishing; industrial; commercial; residential; transport industry; and international transport), from 1974 to 2010; and oil consumption by fuel type (petrol, diesel, fuel oil, aviation fuels, LPG, and other), also for the years 1974 through 2010. The full 2010 Energy Data File is available: http://www.med.govt.nz/upload/73585/EDF%202010.pdf. Source New Zealand Ministry of Economic Development Date Released Unknown Date Updated July 02nd, 2010 (4 years ago)

148

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...

149

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 ...

150

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 ...

151

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 ...

152

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 ...

153

Residential and Transport Energy Use in India: Past Trend and Future Outlook  

E-Print Network (OSTI)

16 Figure 10. Residential Primary Energy Use in 2000 and3. Fuel Consumption in the Residential Sector in 2005 in10 Table 6. Residential Activity

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

154

AEO2011: Energy Consumption by Sector and Source - West South...  

Open Energy Info (EERE)

residential, commercial, industrial, transportation, electric power and total energy consumption.
2011-08-01T19:02:48Z 2011-08-04T15:59:26Z http:www.eia.govoiafaeo...

155

AEO2011: Energy Consumption by Sector and Source - New England...  

Open Energy Info (EERE)

residential, commercial, industrial, transportation, electric power and total energy consumption.
2011-08-01T18:48:13Z 2011-08-31T17:26:50Z http:www.eia.govoiafaeo...

156

AEO2011: Energy Consumption by Sector and Source - East North...  

Open Energy Info (EERE)

residential, commercial, industrial, transportation, electric power and total energy consumption.

2011-08-01T18:53:34Z 2011-08-23T22:30:24Z...

157

AEO2011: Energy Consumption by Sector and Source - East South...  

Open Energy Info (EERE)

residential, commercial, industrial, transportation, electric power and total energy consumption.
2011-08-01T19:00:44Z 2011-08-04T16:01:41Z http:www.eia.govoiafaeo...

158

AEO2011: Energy Consumption by Sector and Source - United States...  

Open Energy Info (EERE)

residential, commercial, industrial, transportation, electric power and total energy consumption.
2011-08-01T19:10:42Z 2011-08-04T15:37:20Z http:www.eia.govoiafaeo...

159

AEO2011: Energy Consumption by Sector and Source - West North...  

Open Energy Info (EERE)

residential, commercial, industrial, transportation, electric power and total energy consumption.
2011-08-01T18:55:30Z 2011-08-23T22:29:34Z http:www.eia.govoiafaeo...

160

AEO2011: Energy Consumption by Sector and Source - Mountain ...  

Open Energy Info (EERE)

residential, commercial, industrial, transportation, electric power and total energy consumption.
2011-08-01T19:04:37Z 2011-08-04T15:57:20Z http:www.eia.govoiafaeo...

Note: This page contains sample records for the topic "residential sector 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

AEO2011: Energy Consumption by Sector and Source - South Atlantic...  

Open Energy Info (EERE)

residential, commercial, industrial, transportation, electric power and total energy consumption.
2011-08-01T18:57:56Z 2011-08-04T18:09:40Z http:www.eia.govoiafaeo...

162

Greening the Residential Sector: Efforts to Transform the Homebuilding  

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

Greening the Residential Sector: Efforts to Transform the Homebuilding Greening the Residential Sector: Efforts to Transform the Homebuilding Market Speaker(s): Doug King Date: October 16, 2007 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Rich Brown The world is changing- regional and global environmental problems have gained prominence, natural resources are becoming increasingly scarce and expensive, people spend more time indoors, and consumers have higher expectations for comfort than ever before - but the way new homes are built has remained largely stagnant. This is a significant problem, as more than 1.5 million new homes are built each year and the typical home will last anywhere between 50 and 75 years. There are various strategies for driving progress, including upgrades to local building codes and increased minimum

163

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

1 1 2005 Energy Expenditures per Household, by Housing Type and Square Footage ($2010) Per Household Single-Family 1.16 Detached 1.16 Attached 1.20 Multi-Family 1.66 2 to 4 units 1.90 5 or more units 1.53 Mobile Home 1.76 All Homes 1.12 Note(s): Source(s): 1) Energy expenditures per square foot were calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the U.S. was 1,618 square feet. Average total floor space, which includes garages, attics and unfinished basements, equaled 2,309 square feet. EIA, 2005 Residential Energy Consumption Survey, Oct. 2008, Table US-1 part1; and EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for

164

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

2 2 2005 Household Energy Expenditures, by Vintage ($2010) | Year | Prior to 1950 887 | 22% 1950 to 1969 771 | 22% 1970 to 1979 736 | 16% 1980 to 1989 741 | 16% 1990 to 1999 752 | 16% 2000 to 2005 777 | 9% | Average 780 | Total 100% Note(s): Source(s): 1.24 2,003 1) Energy expenditures per square foot were calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the U.S. was 1,618 square feet. Average total floor space, which includes garages, attics and unfinished basements, equaled 2,309 square feet. EIA, 2005 Residential Energy Consumption Survey, Oct. 2008 for 2005 expenditures; and EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for price inflators.

165

AEO2011: Natural Gas Consumption by End-Use Sector and Census Division |  

Open Energy Info (EERE)

Consumption by End-Use Sector and Census Division Consumption by End-Use Sector and Census Division Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 136, and contains only the reference case. This dataset is in trillion cubic feet. The data is broken down into residential, commercial, industrial, electric power and transportation. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Natural gas consumption Data application/vnd.ms-excel icon AEO2011: Natural Gas Consumption by End-Use Sector and Census Division- Reference Case (xls, 138.4 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage

166

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

167

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

168

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...

169

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

Gasoline and Diesel Fuel Update (EIA)

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years December 20, 2013 Gas furnace efficiency has large implications for residential natural gas use December 5, 2013 EIA publishes state fact sheets on residential energy consumption and characteristics August 19, 2013 All 48 related articles › Other End Use Surveys Commercial Buildings - CBECS Manufacturing - MECS Transportation About the RECS EIA administers the Residential Energy Consumption Survey (RECS) to a nationally representative sample of housing units. Specially trained interviewers collect energy characteristics on the housing unit, usage

170

Natural gas consumption reflects shifting sectoral patterns ...  

U.S. Energy Information Administration (EIA)

U.S. natural gas consumption since 1997 reflects shifting patterns. Total U.S. natural gas consumption rose 7% between 1997 and 2011, but this modest ...

171

Residential Energy Consumption for Water Heating (2005) | OpenEI  

Open Energy Info (EERE)

for Water Heating (2005) for Water Heating (2005) Dataset Summary Description Provides total and average annual residential energy consumption for water heating in U.S. households in 2005, measured in both physical units and Btus. The data is presented for numerous categories including: Census Region and Climate Zone; Housing Unit Characteristics (type, year of construction, size, income, race, age); and Water Heater and Water-using Appliance Characteristics (size, age, frequency of use, EnergyStar rating). Source EIA Date Released September 01st, 2008 (6 years ago) Date Updated January 01st, 2009 (5 years ago) Keywords Energy Consumption Residential Water Heating Data application/vnd.ms-excel icon 2005_Consumption.for_.Water_.Heating.Phys_.Units_EIA.Sep_.2008.xls (xls, 67.6 KiB)

172

Effects of feedback on residential electricity consumption: A literature review  

SciTech Connect

This report reviews 17 studies assessing the effect of information feedback on residential electricity consumption. Most of the studies were conducted in experimental or quasi-experimental conditions. The studies reviewed used (1) both feedback and incentives, (2) goal setting, (3) cost information feedback, and (4) displays. The study findings, taken together, provide some evidence that feedback is effective in reducing electricity consumption, although questions remain concerning the conditions under which feedback can best be provided. Reductions in consumption found in most of the studies ranged from 5% to 20%. Utility companies are the most likely source of feedback information for residential customers. Three of the studies investigated utility feedback projects. The report discusses the policy implications of these as well as the other studies. The report also lists questions remaining to be researched. 13 refs., 1 tab.

Farhar, B.C.; Fitzpatrick, C.

1989-01-01T23:59:59.000Z

173

The Impact of Residential Density on Vehicle Usage and Energy Consumption  

E-Print Network (OSTI)

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

Golob, Thomas F.; Brownstone, David

2005-01-01T23:59:59.000Z

174

The Impact of Residential Density on Vehicle Usage and Energy Consumption  

E-Print Network (OSTI)

Understanding total residential transportation energy usageon Vehicle Usage and Energy Consumption total annual fuelUsage and Energy Consumption Gasoline-equivalent gallons per year total

Golob, Thomas F; Brownstone, David

2005-01-01T23:59:59.000Z

175

Is Efficiency Enough? Towards a New Framework for Carbon Savings in the California Residential Sector  

E-Print Network (OSTI)

these years, residential electricity consumption grew 49%, aElectricity consumption has increased over the past 20 years,electricity consumption for single-family residences (7,105 kWh/year).

Moezzi, Mithra; Diamond, Rick

2005-01-01T23:59:59.000Z

176

Renewable Energy Consumption for Nonelectric Use by Energy Use Sector and  

Open Energy Info (EERE)

Nonelectric Use by Energy Use Sector and Nonelectric Use by Energy Use Sector and Energy Source, 2004 - 2008 Dataset Summary Description This dataset provides annual renewable energy consumption (in quadrillion Btu) for nonelectric use in the United States by energy use sector and energy source between 2004 and 2008. The data was compiled and published by EIA; the spreadsheet provides more details about specific sources for data used in the analysis. Source EIA Date Released August 01st, 2010 (4 years ago) Date Updated Unknown Keywords Commercial Electric Power Industrial Nonelectric Renewable Energy Consumption Residential transportation Data application/vnd.ms-excel icon 2008_RE.Consumption.for_.Non-Elec.Gen_EIA.Aug_.2010.xls (xls, 27.1 KiB) Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage

177

Space-Heating energy used by households in the residential sector.  

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

Detailed Tables Detailed Tables Energy End Uses Ranked by Energy Consumption, 1989 The following 28 tables present detailed data describing the consumption of and expenditures for energy used by households in the residential sector. The data are presented at the national level, Census region and division levels, for climate zones and for the most populous States, as well as for other selected characteristics of households. This section provides assistance in reading the tables by explaining some of the headings for the categories of data. It also explains the use of the row and column factors to compute the relative standard error of the estimates given in the tables. Organization of the Tables The tables cover consumption and expenditures for six topical areas: Major Energy Source

178

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

179

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

180

AEO2011: Energy Consumption by Sector and Source - East South Central |  

Open Energy Info (EERE)

South Central South Central Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 6, and contains only the reference case. The dataset uses quadrillion btu. The data is broken down into residential, commercial, industrial, transportation, electric power and total energy consumption. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO Commercial East South Central EIA Electric Power Energy Consumption Industrial Residential transportation Data application/vnd.ms-excel icon AEO2011: Energy Consumption by Sector and Source - East South Central- Reference Case (xls, 297.5 KiB) Quality Metrics Level of Review Peer Reviewed

Note: This page contains sample records for the topic "residential sector 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 (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

Where does RECS square footage data come from? Where does RECS square footage data come from? RECS 2009 - Release date: July 11, 2012 The size of a home is a fixed characteristic strongly associated with the amount of energy consumed within it, particularly for space heating, air conditioning, lighting, and other appliances. As a part of the Residential Energy Consumption Survey (RECS), trained interviewers measure the square footage of each housing unit. RECS square footage data allow comparison of homes with varying characteristics. In-person measurements are vital because many alternate data sources, including property tax records, real estate listings, and, respondent estimates use varying definitions and under-estimate square footage as defined for the purposes of evaluating residential energy consumption.

182

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

183

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

184

Residential energy consumption: An analysis-of-variance study  

SciTech Connect

In this report, tests of statistical significance of five sets of variables with household energy consumption (at the point of end-use) are described. Five models, in sequence, were empirically estimated and tested for statistical significance by using the Residential Energy Consumption Survey of the US Department of Energy, Energy Information Administration. Each model incorporated additional information, embodied in a set of variables not previously specified in the energy demand system. The variable sets were generally labeled as economic variables, weather variables, household-structure variables, end-use variables, and housing-type variables. The tests of statistical significance showed each of the variable sets to be highly significant in explaining the overall variance in energy consumption. The findings imply that the contemporaneous interaction of different types of variables, and not just one exclusive set of variables, determines the level of household energy consumption.

Poyer, D.A.

1992-01-01T23:59:59.000Z

185

Lifestyle Factors in U.S. Residential Electricity Consumption  

Science Conference Proceedings (OSTI)

A multivariate statistical approach to lifestyle analysis of residential electricity consumption is described and illustrated. Factor analysis of selected variables from the 2005 U.S. Residential Energy Consumption Survey (RECS) identified five lifestyle factors reflecting social and behavioral choices associated with air conditioning, laundry usage, personal computer usage, climate zone of residence, and TV use. These factors were also estimated for 2001 RECS data. Multiple regression analysis using the lifestyle factors yields solutions accounting for approximately 40% of the variance in electricity consumption for both years. By adding the associated household and market characteristics of income, local electricity price and access to natural gas, variance accounted for is increased to approximately 54%. Income contributed only {approx}1% unique variance to the 2005 and 2001 models, indicating that lifestyle factors reflecting social and behavioral choices better account for consumption differences than income. This was not surprising given the 4-fold range of energy use at differing income levels. Geographic segmentation of factor scores is illustrated, and shows distinct clusters of consumption and lifestyle factors, particularly in suburban locations. The implications for tailored policy and planning interventions are discussed in relation to lifestyle issues.

Sanquist, Thomas F.; Orr, Heather M.; Shui, Bin; Bittner, Alvah C.

2012-03-30T23:59:59.000Z

186

LBL-34044 UC-1600 RESIDENTIAL SECTOR END-USE FORECASTING WITH...  

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

primary energy intensity per household of the residential sector is declining, and the electricity intensity per household is remaining roughly constant over the forecast...

187

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

4 4 Cost of a Generic Quad Used in the Residential Sector ($2010 Billion) (1) Residential 1980 10.45 1981 11.20 1982 11.58 1983 11.85 1984 11.65 1985 11.43 1986 10.90 1987 10.55 1988 10.18 1989 9.98 1990 10.12 1991 9.94 1992 9.78 1993 9.77 1994 9.78 1995 9.44 1996 9.44 1997 9.59 1998 9.23 1999 8.97 2000 9.57 2001 10.24 2002 9.33 2003 10.00 2004 10.32 2005 11.10 2006 11.60 2007 11.61 2008 12.29 2009 11.65 2010 9.98 2011 9.99 2012 9.87 2013 9.77 2014 9.76 2015 9.88 2016 9.85 2017 9.83 2018 9.86 2019 9.88 2020 9.91 2021 10.00 2022 10.09 2023 10.11 2024 10.12 2025 10.09 2026 10.10 2027 10.13 2028 10.11 2029 10.06 2030 10.06 2031 10.13 2032 10.23 2033 10.34 2034 10.45 2035 10.57 Note(s): 1) See Table 1.5.1 for generic quad definition. This table provides the consumer cost of a generic quad in the buildings sector. Use this table to estimate the average consumer cost savings resulting from the savings of a generic (primary) quad in the buildings sector. 2) Price of

188

New Zealand Energy Data: Oil Consumption by Fuel and Sector ...  

Open Energy Info (EERE)

Oil Consumption by Fuel and Sector The New Zealand Ministry of Economic Development publishes energy data including many datasets related to oil and other...

189

The Boom of Electricity Demand in the Residential Sector in the Developing World and the Potential for Energy Efficiency  

E-Print Network (OSTI)

with Residential Electricity Demand in India's Future - HowThe Boom of Electricity Demand in the Residential Sector instraightforward. Electricity demand per end use and region

Letschert, Virginie

2010-01-01T23:59:59.000Z

190

AEO2011: Energy Consumption by Sector and Source - South Atlantic | OpenEI  

Open Energy Info (EERE)

South Atlantic South Atlantic Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 5, and contains only the reference case. The dataset uses quadrillion btu. The data is broken down into residential, commercial, industrial, transportation, electric power and total energy consumption. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Energy Consumption sector South Atlantic Data application/vnd.ms-excel icon AEO2011: Energy Consumption by Sector and Source - South Atlantic- Reference Case (xls, 297.6 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually

191

AEO2011: Energy Consumption by Sector and Source - Middle Atlantic | OpenEI  

Open Energy Info (EERE)

Middle Atlantic Middle Atlantic Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is Table 2, and contains only the reference case. The dataset uses quadrillion btu. The energy consumption data is broken down by sector (residential, commercial, industrial, transportation, electric power) as well as source, and also provides total energy consumption. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA middle atlantic Data application/vnd.ms-excel icon AEO2011: Energy Consumption by Sector and Source - Middle Atlantic- Reference Case (xls, 297.6 KiB) Quality Metrics Level of Review Peer Reviewed Comment

192

Residential fuelwood consumption and production in South Dakota, 1994. Forest Service resource bulletin  

SciTech Connect

Reports findings of the latest survey of residential fuelwood consumption and production in South Dakota. Topics examined include the geographic distribution of residential fuelwood consumption and production within the State; the species of trees used for residential fuelwood; the types of wood-burning facilities used; the reasons for burning fuelwood; and the land, ownership, and tree classes from which fuelwood was produced.

May, D.M.

1996-02-23T23:59:59.000Z

193

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

How does EIA estimate energy consumption and end uses in U.S. homes? How does EIA estimate energy consumption and end uses in U.S. homes? RECS 2009 - Release date: March 28, 2011 EIA administers the Residential Energy Consumption Survey (RECS) to a nationally representative sample of housing units. Specially trained interviewers collect energy characteristics on the housing unit, usage patterns, and household demographics. This information is combined with data from energy suppliers to these homes to estimate energy costs and usage for heating, cooling, appliances and other end uses â€" information critical to meeting future energy demand and improving efficiency and building design. RECS uses a multi-stage area probability design to select sample methodology figure A multi-stage area probability design ensures the selection

194

Building and occupant characteristics as determinants of residential energy consumption  

Science Conference Proceedings (OSTI)

The major goals of the research are to gain insight into the probable effects of building energy performance standards on energy consumption; to obtain observations of actual residential energy consumption that could affirm or disaffirm comsumption estimates of the DOE 2.0A simulation model; and to investigate home owner's conservation investments and home purchase decisions. The first chapter covers the investigation of determinants of household energy consumption. The presentation begins with the underlying economic theory and its implications, and continues with a description of the data collection procedures, the formulation of variables, and then of data analysis and findings. In the second chapter the assumptions and limitations of the energy use projections generated by the DOE 2.0A model are discussed. Actual electricity data for the houses are then compared with results of the simulation.

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

1981-10-01T23:59:59.000Z

195

Modeling diffusion of electrical appliances in the residential sector  

E-Print Network (OSTI)

Regression Results for Appliances Refrigerator Coefficientdiffusion of electrical appliances in the residential sectorfor modeling residential appliance uptake as a function of

McNeil, Michael A.

2010-01-01T23:59:59.000Z

196

Analysis of changes in residential energy consumption, 1973-1980  

Science Conference Proceedings (OSTI)

The progress of energy conservation in the residential sector since the 1973 to 1974 Arab oil embargo is assessed. To accomplish this goal, the reduction in residential energy use per household since 1973 is disaggregated into six possible factors. The factors considered were: (1) building shell efficiencies, (2) geographic distribution of households, (3) appliance efficiency, (4) size of dwelling units, (5) fuel switching, and (6) consumer attitudes. The most important factor identified was improved building shell efficiency, although the impact of appliance efficiency is growing rapidly. Due to data limitations, PNL was not able to quantify the effects of two factors (size of dwelling units and fuel switching) within the framework of this study. The total amount of the energy reduction explained ranged from 18 to 46% over the years 1974 to 1980.

King, M.J.; Belzer, D.B.; Callaway, J.M.; Adams, R.C.

1982-09-01T23:59:59.000Z

197

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

4 4 2005 Average Household Expenditures as Percent of Annual Income, by Census Region ($2010) Item Energy (1) Shelter (2) Food Telephone, water and other public services Household supplies, furnishings and equipment (3) Transportation (4) Healthcare Education Personal taxes (5) Average Annual Expenditures Average Annual Income Note(s): Source(s): 1) Average household energy expenditures are calculated from the Residential Energy Consumption Survey (RECS), while average expenditures for other categories are calculated from the Consumer Expenditure Survey (CE). RECS assumed total US households to be 111,090,617 in 2005, while the CE data is based on 117,356,000 "consumer units," which the Bureau of Labor Statistics defines to be financially independent persons or groups of people that use their incomes to make joint expenditure decisions, including all members of a

198

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

3 3 2005 Average Household Expenditures, by Census Region ($2010) Item Energy (1) Shelter (2) Food Telephone, water and other public services Household supplies, furnishings and equipment (3) Transportation (4) Healthcare Education Personal taxes (5) Other expenditures Average Annual Income Note(s): Source(s): 1) Average household energy expenditures are calculated from the Residential Energy Consumption Survey (RECS), while average expenditures for other categories are calculated from the Consumer Expenditure Survey (CE). RECS assumed total US households to be 111,090,617 in 2005, while the CE data is based on 117,356,000 "consumer units," which the Bureau of Labor Statistics defines to be financially independent persons or groups of people that use their incomes to make joint expenditure decisions, including all members of a

199

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

EIA household energy use data now includes detail on 16 States EIA household energy use data now includes detail on 16 States RECS 2009 - Release date: March 28, 2011 EIA is releasing new benchmark estimates for home energy use for the year 2009 that include detailed data for 16 States, 12 more than in past EIA residential energy surveys. EIA has conducted the Residential Energy Consumption Survey (RECS) since 1978 to provide data on home energy characteristics, end uses of energy, and expenses for the four Census Regions and nine Divisions. In 1997, EIA produced additional tabulations for the four most populous States (California, New York, Texas, and Florida). A threefold increase in the number of households included in the 2009 RECS offers more accuracy and coverage for understanding energy usage for all estimated States, Regions and Divisions.

200

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

Gasoline and Diesel Fuel Update (EIA)

RECS Terminology RECS Terminology A B C D E F G H I J K L M N O P Q R S T U V W XYZ A Account Classification: The method in which suppliers of electricity, natural gas, or fuel oil classify and bill their customers. Commonly used account classifications are "Commercial," "Industrial," "Residential," and "Other" Suppliers' definitions of these terms vary from supplier to supplier and from the definitions used in the Residential Energy Consumption Survey (RECS). In addition, the same customer may be classified differently by each of its energy suppliers. Adequacy of Insulation: The respondent's perception of the adequacy of the housing unit's insulation. Aggregate Ratio: The ratio of two population aggregates (totals). For

Note: This page contains sample records for the topic "residential sector 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

DOE/EIA-0314(82) Residential Energy Consumption Survey:  

Gasoline and Diesel Fuel Update (EIA)

4(82) 4(82) Residential Energy Consumption Survey: Housing Characteri stics 1982 Published: August 1984 U-'VVv*' ^**" ^ Energy Information Administration Washington, D.C. This public ation is availa ble from the Supe rinten dent of Docu ments , U.S. Gove rnme nt Printin g Office (GPO ). Order ing inform ation and purch ase of this and other Energ y Inform ation Admi nistra tion (EIA) public ations may be obtain ed from the GPO or the ElA's Natio nal Energ y Inform ation Cente r (NEIC ). Ques tions on energ y statis tics

202

An analysis of residential energy consumption in a temperate climate  

SciTech Connect

Electrical energy consumption data have been recorded for several hundred submetered residential structures in Middle Tennessee. All houses were constructed with a common energy package.'' Specifically, daily cooling usage data have been collected for 130 houses for the 1985 and 1986 cooling seasons, and monthly heating usage data for 186 houses have been recorded by occupant participation over a seven-year period. Cooling data have been analyzed using an SPSSx multiple regression analysis and results are compared to several cooling models. Heating, base, and total energy usage are also analyzed and regression correlation coefficients are determined as a function of several house parameters.

Clark, Y.Y.; Vincent, W.

1987-06-01T23:59:59.000Z

203

Sample design for the residential energy consumption survey  

SciTech Connect

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

1994-08-01T23:59:59.000Z

204

UK Energy Consumption by Sector | OpenEI  

Open Energy Info (EERE)

68 68 Varnish cache server Browse Upload data GDR 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2142278068 Varnish cache server UK Energy Consumption by Sector Dataset Summary Description The energy consumption data consists of five spreadsheets: "overall data tables" plus energy consumption data for each of the following sectors: transport, domestic, industrial and service. Each of the five spreadsheets contains a page of commentary and interpretation. In addition, a user guide is available as a supplement to the full set of spreadsheets to explain the technical concepts and vocabulary found within Energy Consumption in the UK (http://www.decc.gov.uk/assets/decc/Statistics/publications/ecuk/272-ecuk-user-guide.pdf). Energy Consumption in the United Kingdom is an annual publication currently published by the UK Department of Energy and Climate Change (DECC) for varying time periods, generally 1970 to 2009 (though some time periods are shorter).

205

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

The impact of increasing home size on energy demand The impact of increasing home size on energy demand RECS 2009 - Release date: April 19, 2012 Homes built since 1990 are on average 27% larger than homes built in earlier decades, a significant trend because most energy end-uses are correlated with the size of the home. As square footage increases, the burden on heating and cooling equipment rises, lighting requirements increase, and the likelihood that the household uses more than one refrigerator increases. Square footage typically stays fixed over the life of a home and it is a characteristic that is expensive, even impractical to alter to reduce energy consumption. According to results from EIA's 2009 Residential Energy Consumption Survey (RECS), the stock of homes built in the 1970s and 1980s averages less than

206

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

Share of energy used by appliances and consumer electronics increases in Share of energy used by appliances and consumer electronics increases in U.S. homes RECS 2009 - Release date: March 28, 2011 Over the past three decades, the share of residential electricity used by appliances and electronics in U.S. homes has nearly doubled from 17 percent to 31 percent, growing from 1.77 quadrillion Btu (quads) to 3.25 quads. This rise has occurred while Federal energy efficiency standards were enacted on every major appliance, overall household energy consumption actually decreased from 10.58 quads to 10.55 quads, and energy use per household fell 31 percent. Federal energy efficiency standards have greatly reduced consumption for home heating Total energy use in all U.S. homes occupied as primary residences decreased slightly from 10.58 quads in 1978 to 10.55 quads in 2005 as reported by the

207

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

E-Print Network (OSTI)

Tests and questionnaire surveys on the summer energy consumption structure of 100 energy efficient residential buildings have been performed in a certain residential district in Xi'an, China. The relationship between the formation of the energy consumption structure and building conditions, living customs, family income, and thermal environment, as well as local climatic conditions, etc., is analyzed. Measures to optimize the energy utilization consumption are proposed, and further improvements to the energy efficiency of current residential buildings is also discussed.

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

2006-01-01T23:59:59.000Z

208

Potential Impact of Adopting Maximum Technologies as Minimum Efficiency Performance Standards in the U.S. Residential Sector  

SciTech Connect

The US Department of Energy (US DOE) has placed lighting and appliance standards at a very high priority of the U.S. energy policy. However, the maximum energy savings and CO2 emissions reduction achievable via minimum efficiency performance standards (MEPS) has not yet been fully characterized. The Bottom Up Energy Analysis System (BUENAS), first developed in 2007, is a global, generic, and modular tool designed to provide policy makers with estimates of potential impacts resulting from MEPS for a variety of products, at the international and/or regional level. Using the BUENAS framework, we estimated potential national energy savings and CO2 emissions mitigation in the US residential sector that would result from the most aggressive policy foreseeable: standards effective in 2014 set at the current maximum technology (Max Tech) available on the market. This represents the most likely characterization of what can be maximally achieved through MEPS in the US. The authors rely on the latest Technical Support Documents and Analytical Tools published by the U.S. Department of Energy as a source to determine appliance stock turnover and projected efficiency scenarios of what would occur in the absence of policy. In our analysis, national impacts are determined for the following end uses: lighting, television, refrigerator-freezers, central air conditioning, room air conditioning, residential furnaces, and water heating. The analyzed end uses cover approximately 65percent of site energy consumption in the residential sector (50percent of the electricity consumption and 80percent of the natural gas and LPG consumption). This paper uses this BUENAS methodology to calculate that energy savings from Max Tech for the U.S. residential sector products covered in this paper will reach an 18percent reduction in electricity demand compared to the base case and 11percent in Natural Gas and LPG consumption by 2030 The methodology results in reductions in CO2 emissions of a similar magnitude.

Letschert, Virginie; Desroches, Louis-Benoit; McNeil, Michael; Saheb, Yamina

2010-05-03T23:59:59.000Z

209

ResPoNSe: modeling the wide variability of residential energy consumption.  

E-Print Network (OSTI)

motivations that will affect appliance energy consumption.that target specific appliances, whether air conditioning,California Statewide Residential Appliance Saturation Study.

Peffer, Therese; Burke, William; Auslander, David

2010-01-01T23:59:59.000Z

210

Energy Data Sourcebook for the U.S. Residential Sector  

E-Print Network (OSTI)

of stocks, UECs, and national energy consumption for theseSanchez 1997). National energy consumption of these end-usesUECs, and National Energy Consumption of Miscellaneous

Wenzel, T.P.

2010-01-01T23:59:59.000Z

211

Baseline data for the residential sector and development of a residential forecasting database  

SciTech Connect

This report describes the Lawrence Berkeley Laboratory (LBL) residential forecasting database. It provides a description of the methodology used to develop the database and describes the data used for heating and cooling end-uses as well as for typical household appliances. This report provides information on end-use unit energy consumption (UEC) values of appliances and equipment historical and current appliance and equipment market shares, appliance and equipment efficiency and sales trends, cost vs efficiency data for appliances and equipment, product lifetime estimates, thermal shell characteristics of buildings, heating and cooling loads, shell measure cost data for new and retrofit buildings, baseline housing stocks, forecasts of housing starts, and forecasts of energy prices and other economic drivers. Model inputs and outputs, as well as all other information in the database, are fully documented with the source and an explanation of how they were derived.

Hanford, J.W.; Koomey, J.G.; Stewart, L.E.; Lecar, M.E.; Brown, R.E.; Johnson, F.X.; Hwang, R.J.; Price, L.K.

1994-05-01T23:59:59.000Z

212

AEO2011: Energy Consumption by Sector and Source - West North Central |  

Open Energy Info (EERE)

North Central North Central Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 4, and contains only the reference case. The dataset uses quadrillion btu. The data is broken down into residential, commercial, industrial, transportation, electric power and total energy consumption. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Energy Consumption Data application/vnd.ms-excel icon AEO2011: Energy Consumption by Sector and Source - West North Central- Reference Case (xls, 297.4 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually Time Period 2008-2035

213

AEO2011: Energy Consumption by Sector and Source - United States | OpenEI  

Open Energy Info (EERE)

United States United States Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 10, and contains only the reference case. The dataset uses quadrillion btu. The data is broken down into residential, commercial, industrial, transportation, electric power and total energy consumption. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Energy Consumption United States Data application/vnd.ms-excel icon AEO2011: Energy Consumption by Sector and Source - United States- Reference Case (xls, 298.4 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually

214

AEO2011: Energy Consumption by Sector and Source - Mountain | OpenEI  

Open Energy Info (EERE)

Mountain Mountain Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 8, and contains only the reference case. The dataset uses quadrillion btu. The data is broken down into residential, commercial, industrial, transportation, electric power and total energy consumption. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Energy Consumption mountain region Data application/vnd.ms-excel icon AEO2011: Energy Consumption by Sector and Source - Mountain- Reference Case (xls, 297.4 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually Time Period 2008-2035

215

AEO2011: Energy Consumption by Sector and Source - New England | OpenEI  

Open Energy Info (EERE)

New England New England Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 1, and contains only the reference case. The dataset uses quadrillion btu. The data is broken down into residential, commercial, industrial, transportation, electric power and total energy consumption. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Energy Consumption New England Data application/vnd.ms-excel icon AEO2011: Energy Consumption by Sector and Source - New England- Reference Case (xls, 297.3 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually Time Period 2008-2035

216

AEO2011: Energy Consumption by Sector and Source - West South Central |  

Open Energy Info (EERE)

South Central South Central Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 7, and contains only the reference case. The dataset uses quadrillion btu. The data is broken down into residential, commercial, industrial, transportation, electric power and total energy consumption. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Energy Consumption West South Central Data application/vnd.ms-excel icon AEO2011: Energy Consumption by Sector and Source - West South Central- Reference Case (xls, 297.7 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually

217

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

5 5 2005 Households and Energy Expenditures, by Income Level ($2010) Energy Expenditures by Household Income Households (millions) Household Less than $10,000 9.9 9% $10,000 to $14,999 8.5 8% $15,000 to $19,999 8.4 8% $20,000 to $29,999 15.1 14% $30,000 to $39,999 13.6 12% $40,000 to $49,999 11.0 10% $50,000 to $74,999 19.8 18% $75,000 to $99,999 10.6 10% $100,000 or more 14.2 13% Total 111.1 100% Note(s): Source(s): 7% 1) See Table 2.3.15 for more on energy burdens. 2) A household is defined as a family, an individual, or a group of up to nine unrelated individuals occupying the same housing unit. EIA, 2005 Residential Energy Consumption Survey, Oct. 2008, Table US-1 part 2; and EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for price inflators. 2,431 847 3% 2,774 909 3% 1,995

218

The Impact of Residential Density on Vehicle Usage and Energy Consumption  

E-Print Network (OSTI)

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

Golob, Thomas F; Brownstone, David

2005-01-01T23:59:59.000Z

219

Building and occupant characteristics as determinants of residential energy consumption  

Science Conference Proceedings (OSTI)

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

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

1981-10-01T23:59:59.000Z

220

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

SciTech Connect

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

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

2009-06-01T23:59:59.000Z

Note: This page contains sample records for the topic "residential sector 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 for 500 Million Homes: Drivers and Outlook for Residential Energy Consumption in China  

SciTech Connect

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

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

2009-06-01T23:59:59.000Z

222

U.S. Residential Housing Weather Adjusted Site Energy Consumption ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency > Residential Housing Energy Intensities > Table 1b Glossary U.S. Residential Housing Weather Adjusted ...

223

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

What's new in our home energy use? What's new in our home energy use? RECS 2009 - Release date: March 28, 2011 First results from EIA's 2009 Residential Energy Consumption Survey (RECS) The 2009 RECS collected home energy characteristics data from over 12,000 U.S. households. This report highlights findings from the survey, with details presented in the Household Energy Characteristics tables. How we use energy in our homes has changed substantially over the past three decades. Over this period U.S. homes on average have become larger, have fewer occupants, and are more energy-efficient. In 2005, energy use per household was 95 million British thermal units (Btu) of energy compared with 138 million Btu per household in 1978, a drop of 31 percent. Did You Know? Over 50 million U.S. homes have three or more televisions.

224

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

Air conditioning in nearly 100 million U.S. homes Air conditioning in nearly 100 million U.S. homes RECS 2009 - Release date: August 19, 2011 line chart:air conditioning in U.S. figure dataExcept in the temperate climate regions along the West coast, air conditioners (AC) are now standard equipment in most U.S. homes (Figure 1). As recently as 1993, only 68% of all occupied housing units had AC. The latest results from the 2009 Residential Energy Consumption Survey (RECS) show that 87 percent of U.S. households are now equipped with AC. This growth occurred among all housing types and in every Census region. Wider use has coincided with much improved energy efficiency standards for AC equipment, a population shift to hotter and more humid regions, and a housing boom during which average housing sizes increased.

225

Energy Data Sourcebook for the U.S. Residential Sector  

E-Print Network (OSTI)

Cason. 1990. Residential Energy Usage Comparison Project: AnResearch, Inc. 1985. Energy Usage Analysis of Residentialthere are few data on the energy usage of new buildings,

Wenzel, T.P.

2010-01-01T23:59:59.000Z

226

Carbon dioxide emissions grow in the residential sector ...  

U.S. Energy Information Administration (EIA)

Accounting for this increased CO 2 share is the 19-fold growth in residential ... illustrates the importance of the relationship of power plant ...

227

Energy Data Sourcebook for the U.S. Residential Sector  

E-Print Network (OSTI)

Options for Residential Appliances and Space ConditioningAHAM, Association of Home Appliance Manufacturers. 1991.AHAM, Association of Home Appliance Manufacturers. 1996.

Wenzel, T.P.

2010-01-01T23:59:59.000Z

228

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

SciTech Connect

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

Zhou, Nan; Nishida, Masaru; Gao, Weijun

2008-12-01T23:59:59.000Z

229

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

SciTech Connect

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

Zhou, Nan; Nishida, Masaru; Gao, Weijun

2008-12-01T23:59:59.000Z

230

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

231

DOE/EIA-0262/1 Residential Energy Consumption Survey:  

Gasoline and Diesel Fuel Update (EIA)

62/1 62/1 Residential Energy Consumption Survey: 1979-1980 Consumption and Expenditures Part I: National Data (including Conservation) April 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 ' 1 7 T Z 8 0 T T 8 - 8 d * N u o f s s a o o y ' S O S ^ - m ( E O Z ) a u o q d a i a i . ' t j a o j S 9 j g ' u o - p s - p A f a s ^ o n p o a ^ a a ^ n d m o o - m o j j a j q B T T B A B ' ( a d B i J - p a a u S B K ) T O O / T 8 - J Q / 3 0 Q p j o q a s n o H r X a A j n s u o - p ^ d m n s u o o O Q ' 3 j o : m o a j a j q B j f ^ A ^ ^ ^ ^ s a a o d a a a A o q B a q ^ j o ' 8 - T Z T O O - C O O - T 9 0 ' Q N ^ 3 3 S O d O ' 9 f r Z Q - V I 3 / 3 0 Q * T 8 6 T € < 7 - 9 i T O O - e 0 0 - 1 9 0 O d O ' ^ / Z O Z O - V i a / a O Q ' 0 8 6 T a u n r * 6 ^ 6 T 3 s n 3 n y o ^ a u n f ' p j o q a s n o H j o s u a a ^ ^ B ^ u o f a d n m s u o o : X a A j n g u o f ^ d m n s u o o X

232

Residential Energy Consumption Survey: Consumption and expenditures, April 1984 through March 1985: Part 1, National data  

Science Conference Proceedings (OSTI)

This report presents data collected in the 1984 Residential Energy Consumption Survey (RECS) conducted by the Energy Information Administration (EIA). The 1984 RECS was the sixth national survey of US households and their energy suppliers. The purpose of these surveys is to provide baseline information on how households use energy. Households 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 in published reports such as this one and on public-use data tapes. The report presents data on the US consumption and expenditures for residential use of these ''major fuels'' - natural gas, electricity, fuel oil, kerosene, and liquefied petroleum gas (LPG) - from April 1984 through March 1985. These data are presented in tables in the Detailed Statistics section of this report. Except for kerosene and wood fuel, the consumption and expenditures data are based on actual household bills obtained, with the permission of the household, from the companies supplying energy to the household. Purchases of kerosene are based on respondent reports because records of ''cash and carry'' purchases of kerosene for individual households are usually unavailable. Data on the consumption of wood fuel (Table 27) covers the 12-month period ending November 1984 and are based on respondent recall of the amount of wood burned during the 12-month period. Both the kerosene and wood consumption data are subject to memory errors and other reporting errors. This report does not cover household use of motor fuel, which is reported separately.

Not Available

1987-03-04T23:59:59.000Z

233

Is Efficiency Enough? Towards a New Framework for Carbon Savings in the California Residential Sector  

E-Print Network (OSTI)

STAT-ABS/Sa_home.htm. California Energy Circuit. August 13,to Surge in Inland Empire. ” California Energy Commission.2002. California Energy Consumption by Sector.

Moezzi, Mithra; Diamond, Rick

2005-01-01T23:59:59.000Z

234

Buildings Energy Data Book: 2.2 Residential Sector Characteristics  

Buildings Energy Data Book (EERE)

3 3 Share of Total U.S. Households, by Census Region, Division, and Vintage, as of 2005 Prior to 1950 to 1970 to 1980 to 1990 to 2000 to Region 1950 1969 1979 1989 1999 2005 Northeast 6.7% 5.2% 2.4% 2.1% 1.3% 0.8% 18.5% New England 2.1% 1.2% 0.5% 0.5% 0.3% 0.3% 4.9% Middle Atlantic 4.6% 4.0% 1.9% 1.6% 1.0% 0.5% 13.6% Midwest 5.7% 5.8% 3.6% 2.5% 3.7% 1.7% 23.0% East North Central 4.3% 3.9% 2.7% 1.8% 2.1% 1.1% 16.0% West North Central 1.4% 1.9% 0.9% 0.7% 1.6% 0.6% 7.1% South 4.0% 6.9% 6.4% 7.5% 7.5% 4.3% 36.6% South Atlantic 2.0% 3.4% 3.5% 4.2% 4.3% 2.2% 17.4% East South Central 0.9% 1.3% 0.9% 1.0% 1.3% 0.7% 6.2% West South Central 1.2% 2.3% 4.7% 2.2% 1.8% 1.4% 13.6% West 3.4% 4.6% 4.5% 4.6% 3.1% 1.5% 21.8% Mountain 0.7% 1.2% 1.3% 1.5% 1.3% 0.9% 6.8% Pacific 2.8% 3.4% 3.3% 3.1% 1.8% 0.6% 15.0% United States 19.9% 22.5% 17.0% 16.7% 15.6% 8.3% 100% Source(s): All Vintages EIA, 2005 Residential Energy Consumption Survey, Oct. 2008, Table HC10

235

Potential Energy Choices and Their Determinants for the Residential Sector  

Science Conference Proceedings (OSTI)

This report is part of the Understanding Energy Markets research initiative and is the third in a series of four reports championed by EPRIsolutions to deepen the understanding of the residential marketplace. It is designed to support energy suppliers in predicting and winning market share potential. In particular, it examines residential customers' past switching behavior, reasons for switching electricity providers, profiles of likely electric switchers, and interest in bundled energy offers. The exper...

2000-11-22T23:59:59.000Z

236

Table 2.1f Electric Power Sector Energy Consumption, 1949-2011 ...  

U.S. Energy Information Administration (EIA)

Table 2.1f Electric Power Sector Energy Consumption, 1949-2011 (Trillion Btu) Year: Primary Consumption 1: Fossil Fuels: Nuclear

237

Table 17. Total Delivered Residential Energy Consumption, Projected vs. Actual  

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

Total Delivered Residential Energy Consumption, Projected vs. Actual 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 2008 2009 2010 2011 AEO 1994 10.3 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.5 10.5 10.5 10.5 10.5 10.6 10.6 AEO 1995 11.0 10.8 10.8 10.8 10.8 10.8 10.8 10.7 10.7 10.7 10.7 10.7 10.7 10.7 10.8 10.8 10.9 AEO 1996 10.4 10.7 10.7 10.7 10.8 10.8 10.9 10.9 11.0 11.2 11.2 11.3 11.4 11.5 11.6 11.7 11.8 AEO 1997 11.1 10.9 11.1 11.1 11.2 11.2 11.2 11.3 11.4 11.5 11.5 11.6 11.7 11.8 11.9 12.0 AEO 1998 10.7 11.1 11.2 11.4 11.5 11.5 11.6 11.7 11.8 11.9 11.9 12.1 12.1 12.2 12.3 AEO 1999 10.5 11.1 11.3 11.3 11.4 11.5 11.5 11.6 11.6 11.7 11.8 11.9 12.0 12.1 AEO 2000 10.7 10.9 11.0 11.1 11.2 11.3 11.4 11.5 11.6 11.7 11.8 11.9 12.0

238

Table 18. Total Residential Energy Consumption, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Residential Energy Consumption, Projected vs. Actual Residential Energy Consumption, Projected vs. Actual (quadrillion Btu) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 10.1 10.1 10.1 10.1 10.2 10.2 AEO 1983 9.8 9.9 10.0 10.1 10.2 10.1 10.0 AEO 1984 9.9 9.9 10.0 10.2 10.3 10.3 10.5 AEO 1985 9.8 10.0 10.1 10.3 10.6 10.6 10.9 AEO 1986 9.6 9.8 10.0 10.3 10.4 10.8 10.9 AEO 1987 9.9 10.2 10.3 10.3 10.4 10.5 10.5 10.5 10.5 10.6 AEO 1989* 10.3 10.5 10.4 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 AEO 1990 10.4 10.7 10.8 11.0 11.3 AEO 1991 10.2 10.7 10.7 10.8 10.8 10.8 10.9 10.9 10.9 11.0 11.0 11.0 11.1 11.2 11.2 11.3 11.4 11.4 11.5 11.6 AEO 1992 10.6 11.1 11.1 11.1 11.1 11.1 11.2 11.2 11.3 11.3 11.4 11.5 11.5 11.6 11.7 11.8 11.8 11.9 12.0 AEO 1993 10.7 10.9 11.0 11.0 11.0 11.1 11.1 11.1 11.1 11.2 11.2 11.2 11.2 11.3 11.3 11.4 11.4 11.5 AEO 1994 10.3 10.4 10.4 10.4

239

U.S. Residential Housing Primary Energy Consumption  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency > Residential Housing Energy Intensities > Table 1c Glossary U.S. Resident ...

240

U.S. Residential Buildings Weather-Adjusted Primary Consumption  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities > Table 8c Glossary U.S. Residential Buildings ...

Note: This page contains sample records for the topic "residential sector 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

Residential energy consumption and expenditure patterns of black and nonblack households in the United States  

Science Conference Proceedings (OSTI)

Residential energy consumption and expenditures by black and nonblack households are presented by Census region and for the nation based on the Energy Information Administration's 1982-83 Residential Energy Consumption Survey (RECS). Black households were found to have significantly lower levels of electricity consumption at both the national and regional level. Natural gas is the dominant space heating fuel used by black households. Natural gas consumption was typically higher for black households. However, when considering natural gas consumption conditional on natural gas space heating no significant differences were found. 10 refs., 1 fig., 8 tabs.

Vyas, A.D.; Poyer, D.A.

1987-01-01T23:59:59.000Z

242

Pacific Northwest Residential Energy Consumption Survey : Sample Selection Activities.  

Science Conference Proceedings (OSTI)

The primary purpose of the 1983 Pacific Northwest Residential Energy Consumption Survey is to obtain a comprehensive data base regarding household energy usage patterns incorporating not only general behavioral indicators of usage (e.g., temperature at which the dwelling is maintained at different times of day during the months of the year in which heating systems are activated or conservation measures effected) but also those characteristics lying further beyond the realm of immediate influence of the household dwellers which directly effect energy consumption (e.g., housing and household characteristics including square footage, number of floors or levels, the number and characteristics of the appliances in the household and household demographics/composition). The data base to be assembled as part of this research effort is also to include households' actual level of energy use for two major fuels (i.e., electricity and natural gas) obtained, with the consent of respondents, from their servicing utility(ies). Two samples have been incorporated in the study. The primary sample - the Regional Sample - will generate a large and comprehensive data base from a representative cross-section of individual households in the Pacific Northwest. A second, Supplementary Sample was incorporated in the survey design to ensure that a sufficient number of households not participating in qualified loan or grant programs, but comparable to participant households on a number of key descriptive characteristics, were included in the assessment. Inclusion of such households in the assessment will permit a formal evaluation of the loan/grant programs to be accomplished. Sampling procedures are described thoroughly.

Louis Harris and Associates

1983-08-03T23:59:59.000Z

243

Electricity Generation and Consumption by State (2008 ) Provides...  

Open Energy Info (EERE)

Electricity Generation and Consumption by State (2008 ) Provides total annual electricity consumption by sector (residential, commercial and industrial) for all states in 2008,...

244

Residential Energy Consumption Survey (RECS) - Data - U.S. Energy ...  

U.S. Energy Information Administration (EIA)

Housing Characteristics; Consumption & Expenditures; Microdata; Consumption & Expenditures Tables + EXPAND ALL. Summary Statistics (revised January 2009) PDF (all tables)

245

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

customer groups. While the cost per kWh for each respectivewith the average cost declines, per kWh for average andcost of doing so would be zero (prior to 2011), or small, on the order of 5 cents per kWh (

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

246

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

Energy Rating System (HERS) may provide such actionable market information.market is administered by the Western Region Renewable Energy Generation Information

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

247

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

project with both efficiency and solar may be the optimal solution for some customers—and the one that costs

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

248

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

was largely overcome, and PV prices globally had begun toNemet 2006; Nemet 2007). PV price reduction is one of theand indeed the global price of PV modules is a central part

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

249

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

Renewable portfolio standards and cost-effective energy-for low-cost financing for renewable energy and energycost of renewable onsite generation systems and energy

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

250

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

of offering NEM for biogas-electric systems and fuel cells.but AB 2228 (2002) allowed biogas-electric facilities up to

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

251

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

Energy and Buildings Herring, H. and R. Roy (2007). "quality of energy service” (Herring and Roy 2007: 195). TheEkins et al. 2007: 4935-36; Herring and Roy 2007: 196). As

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

252

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

respond to having a rooftop solar system. There is a robustindustry, since a small rooftop solar system can producecompliance. 27 . Each kW of rooftop solar capacity produces

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

253

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

impact of rate design and net metering on the bill savingsJ. , K. Fox, et al. (2009). Net Metering & Interconnectionsmetering (NEM, or “net metering”), to which we turn next. By

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

254

Table 2.1b Residential Sector Energy Consumption Estimates ...  

U.S. Energy Information Administration (EIA)

R=Revised. P=Preliminary. NA=Not available. 4 Based on petroleum product supplied. For petroleum, product supplied is used as an approximation of

255

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

referents (MPRs) for non-renewable energy that serve asPolicies to promote non-hydro renewable energy in the United

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

256

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

10 1.5. The Coordination of Solar and Energyintegration of solar and energy efficiency. Currentlytension between solar and energy efficiency remains much

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

257

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

meteorological year (TMY) solar radiation data. The goaleither TMY or actual solar radiation data, and thus servesmodeling (using actual solar radiation data, though this

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

258

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

capture such savings: the solar provider has unique pricingscale solar industry. Solar providers will need both to

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

259

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

renewable energy; and calculating market price referents (Market price referent Net excess generation Net energy

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

260

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

non-low- income electricity bill, according to specificsto offset any future electricity bills. All systems withinunderstand their electricity bills, even if early adopters

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "residential sector 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

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

actual solar radiation and other necessary weather dataSolar 71 Table 5.2. 10x10km Weathersolar energy is actually generated; this makes intuitive sense as edge effects such as shading and weather

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

262

Solar Adoption and Energy Consumption in the Residential Sector  

E-Print Network (OSTI)

59. City of San Diego and California Center for SustainablePOLICIES AND FUNDING FOR THE CALIFORNIA SOLAR INITIATIVE.San Francisco, California Public Utilities Commission: 44.

McAllister, Joseph Andrew

2012-01-01T23:59:59.000Z

263

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

E-Print Network (OSTI)

G. Koomey. 1994. Residential Appliance Data, Assumptions andunits) Table A 3 : Number of Appliances in Existing Homes (sector, including appliances and heating, ventilation, and

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

264

Purification of Vegetable Oils Post-Consumption Residential and ...  

Science Conference Proceedings (OSTI)

The viscosity residential treated with clay Tonsil was lower compared to the crude ... Designing a Collaborative System for Socio-Environmental Management of ...

265

State energy price projections for the residential sector, 1992--1993  

Science Conference Proceedings (OSTI)

The purpose of this report, State Energy Price Projections for the Residential Sector, 1992--1993, is to provide projections of State-level residential prices for 1992 and 1993 for the following fuels: electricity, natural gas, heating oil, liquefied petroleum gas (LPG), kerosene, and coal. Prices for 1991 are also included for comparison purposes. This report also explains the methodology used to produce these estimates and the limitations.

Not Available

1992-09-24T23:59:59.000Z

266

State energy price projections for the residential sector, 1992--1993. [Contains model documentation  

SciTech Connect

The purpose of this report, State Energy Price Projections for the Residential Sector, 1992--1993, is to provide projections of State-level residential prices for 1992 and 1993 for the following fuels: electricity, natural gas, heating oil, liquefied petroleum gas (LPG), kerosene, and coal. Prices for 1991 are also included for comparison purposes. This report also explains the methodology used to produce these estimates and the limitations.

Not Available

1992-09-24T23:59:59.000Z

267

Energy Data Sourcebook for the U.S. Residential Sector  

E-Print Network (OSTI)

energy consumption (UECs) of appliances and equipment; Historical and current appliance and equipment market shares; Appliance and equipment efficiency and sales trends;energy consumption (UEC) values of appliances and equipment; historical and current appliance and equipment market shares; appliance and equipment efficiency and sales trends;

Wenzel, T.P.

2010-01-01T23:59:59.000Z

268

Model documentation report: Residential sector demand module of the national energy modeling system  

SciTech Connect

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This reference document provides a detailed description for energy analysts, other users, and the public. The NEMS Residential Sector Demand Module is currently used for mid-term forecasting purposes and energy policy analysis over the forecast horizon of 1993 through 2020. The model generates forecasts of energy demand for the residential sector by service, fuel, and Census Division. Policy impacts resulting from new technologies, market incentives, and regulatory changes can be estimated using the module. 26 refs., 6 figs., 5 tabs.

NONE

1998-01-01T23:59:59.000Z

269

A Water Conservation Scenario for the Residential and Industrial Sectors in California: Potential Saveings of Water and Related Energy  

E-Print Network (OSTI)

A WATER CONSERVATION SCENARIO FOR THE RESIDENTIAL ANDWater 'consumption, water conservation. City of Sacramento.Daniel Stockton. Water conservation. Contra Costa County

Benenson, P.

2010-01-01T23:59:59.000Z

270

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

Open Energy Info (EERE)

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

271

Energy Data Sourcebook for the U.S. Residential Sector  

E-Print Network (OSTI)

Energy kWh/cycle Total Energy Annual Usage kWh/yr Motor +Energy kWh/cycle Total Energy Annual Usage kWb/yr Motortotal incandescent lighting energy consumption attributable to each usage

Wenzel, T.P.

2010-01-01T23:59:59.000Z

272

Energy Perspectives: Industrial and transportation sectors ...  

U.S. Energy Information Administration (EIA)

Since 2008, energy use in the transportation, residential, and commercial sectors stayed relatively constant or fell slightly. Industrial consumption grew in 2010 and ...

273

Fuel Consumption for Electricity Generation, All Sectors United States  

Gasoline and Diesel Fuel Update (EIA)

Fuel Consumption for Electricity Generation, All Sectors Fuel Consumption for Electricity Generation, All Sectors United States Coal (thousand st/d) .................... 2,361 2,207 2,586 2,287 2,421 2,237 2,720 2,365 2,391 2,174 2,622 2,286 2,361 2,437 2,369 Natural Gas (million cf/d) ............. 20,952 21,902 28,751 21,535 20,291 22,193 28,174 20,227 20,829 22,857 29,506 21,248 23,302 22,736 23,627 Petroleum (thousand b/d) ........... 128 127 144 127 135 128 135 119 131 124 134 117 131 129 127 Residual Fuel Oil ...................... 38 28 36 29 30 31 33 29 31 30 34 27 33 31 30 Distillate Fuel Oil ....................... 26 24 27 28 35 30 30 26 31 26 28 25 26 30 28 Petroleum Coke (a) .................. 59 72 78 66 63 63 66 59 62 63 67 60 69 63 63 Other Petroleum Liquids (b) ..... 5 3 4 4 7 5 5 5 7 5 5 5 4 6 6 Northeast Census Region Coal (thousand st/d) ....................

274

End use energy consumption data base: transportation sector  

SciTech Connect

The transportation fuel and energy use estimates developed a Oak Ridge National Laboratory (ORNL) for the End Use Energy Consumption Data Base are documented. The total data base contains estimates of energy use in the United States broken down into many categories within all sectors of the economy: agriculture, mining, construction, manufacturing, commerce, the household, electric utilities, and transportation. The transportation data provided by ORNL generally cover each of the 10 years from 1967 through 1976 (occasionally 1977 and 1978), with omissions in some models. The estimtes are broken down by mode of transport, fuel, region and State, sector of the economy providing transportation, and by the use to which it is put, and, in the case of automobile and bus travel, by the income of the traveler. Fuel types include natural gas, motor and aviation gasoline, residual and diesel oil, liuqefied propane, liquefied butane, and naphtha- and kerosene-type jet engine fuels. Electricity use is also estimated. The mode, fuel, sector, and use categories themselves subsume one, two, or three levels of subcategories, resulting in a very detailed categorization and definitive accounting.

Hooker, J.N.; Rose, A.B.; Greene, D.L.

1980-02-01T23:59:59.000Z

275

Demand-side Management Strategies and the Residential Sector: Lessons from International Experience  

E-Print Network (OSTI)

in producing a given level of output or activity. It is measured by the quantity of energy required to perform a particular activity (service) expressed as energy per unit of output or activity measure of service (EERE, 2010). In the residential sector...

Haney, Aoife Brophy; Jamasb, Tooraj; Platchkov, Laura M.; Pollitt, Michael G.

276

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

5 5 2010 Residential Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. LPG Kerosene Total Coal Electricity Total Percent Space Heating (2) 38.7 11.2 8.0 19.8 0.0 14.3 72.9 28.9% Space Cooling (3) 0.0 35.4 35.4 14.0% Water Heating (4) 14.3 2.1 2.0 4.0 14.2 32.6 12.9% Lighting 22.6 22.6 9.0% Refrigeration (5) 14.9 14.9 5.9% Electronics (6) 17.8 17.8 7.1% Cooking 2.4 0.8 0.8 6.0 9.2 3.7% Wet Cleaning (7) 0.6 10.7 11.3 4.5% Computers 5.6 5.6 2.2% Other (8) 0.0 4.4 4.4 6.7 11.1 4.4% Adjust to SEDS (9) 13.6 13.6 5.4% Total 56.1 13.3 15.2 29.0 0.0 166.8 251.8 100% Note(s): Source(s): 0.5 0.5 1) Expenditures include coal and exclude wood. 2) Includes furnace fans ($4.5 billion). 3) Fan energy use included. 4) Includes residential recreational water heating ($1.4 billion). 5) Includes refrigerators ($15.3 billion) and freezers ($4.4 billion). 6) Includes color televisions ($11.0

277

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

3 3 Residential Aggregate Energy Expenditures, by Year and Major Fuel Type ($2010 Billion) (1) Electricity Total 1980 158.5 1981 164.0 1982 172.3 1983 176.1 1984 178.5 1985 176.8 1986 169.2 1987 167.1 1988 170.1 1989 172.8 1990 168.2 1991 169.9 1992 166.7 1993 175.6 1994 174.9 1995 172.7 1996 181.8 1997 180.0 1998 173.5 1999 174.0 2000 192.8 2001 203.3 2002 192.1 2003 208.8 2004 215.1 2005 236.7 2006 240.0 2007 246.1 2008 259.6 2009 241.6 2010 251.8 2011 251.3 2012 247.1 2013 240.3 2014 239.4 2015 241.7 2016 241.8 2017 243.0 2018 244.7 2019 246.4 2020 247.9 2021 250.4 2022 253.3 2023 255.6 2024 257.8 2025 260.3 2026 263.2 2027 266.0 2028 267.6 2029 268.1 2030 269.7 2031 272.9 2032 276.6 2033 280.4 2034 284.6 2035 288.6 Note(s): Source(s): 1) Residential petroleum products include distillate fuel oil, LPG, and kerosene. EIA, State Energy Data 2009: Prices and Expenditures, Jun. 2011, Table 2 for 1980-2009; EIA, Annual Energy Outlook 2012 Early Release, Jan. 2012, Table

278

Residential Energy Consumption Survey (RECS) - Data - U.S ...  

U.S. Energy Information Administration (EIA)

ZIP (all tables) Release Date: January 11, 2013 : CE4.1 End-Use Consumption by Fuel Totals, U.S. Homes: XLS: CE4.2 End-Use Consumption by Fuel Totals, Northeast Homes ...

279

The Boom of Electricity Demand in the Residential Sector in the Developing World and the Potential for Energy Efficiency  

SciTech Connect

With the emergence of China as the world's largest energy consumer, the awareness of developing country energy consumption has risen. According to common economic scenarios, the rest of the developing world will probably see an economic expansion as well. With this growth will surely come continued rapid growth in energy demand. This paper explores the dynamics of that demand growth for electricity in the residential sector and the realistic potential for coping with it through efficiency. In 2000, only 66% of developing world households had access to electricity. Appliance ownership rates remain low, but with better access to electricity and a higher income one can expect that households will see their electricity consumption rise significantly. This paper forecasts developing country appliance growth using econometric modeling. Products considered explicitly - refrigerators, air conditioners, lighting, washing machines, fans, televisions, stand-by power, water heating and space heating - represent the bulk of household electricity consumption in developing countries. The resulting diffusion model determines the trend and dynamics of demand growth at a level of detail not accessible by models of a more aggregate nature. In addition, the paper presents scenarios for reducing residential consumption through cost-effective and/or best practice efficiency measures defined at the product level. The research takes advantage of an analytical framework developed by LBNL (BUENAS) which integrates end use technology parameters into demand forecasting and stock accounting to produce detailed efficiency scenarios, which allows for a realistic assessment of efficiency opportunities at the national or regional level. The past decades have seen some of the developing world moving towards a standard of living previously reserved for industrialized countries. Rapid economic development, combined with large populations has led to first China and now India to emerging as 'energy giants', a phenomenon that is expected to continue, accelerate and spread to other countries. This paper explores the potential for slowing energy consumption and greenhouse gas emissions in the residential sector in developing countries and evaluates the potential of energy savings and emissions mitigation through market transformation programs such as, but not limited to Energy Efficiency Standards and Labeling (EES&L). The bottom-up methodology used allows one to identify which end uses and regions have the greatest potential for savings.

Letschert, Virginie; McNeil, Michael A.

2008-05-13T23:59:59.000Z

280

The Boom of Electricity Demand in the Residential Sector in the Developing World and the Potential for Energy Efficiency  

SciTech Connect

With the emergence of China as the world's largest energy consumer, the awareness of developing country energy consumption has risen. According to common economic scenarios, the rest of the developing world will probably see an economic expansion as well. With this growth will surely come continued rapid growth in energy demand. This paper explores the dynamics of that demand growth for electricity in the residential sector and the realistic potential for coping with it through efficiency. In 2000, only 66% of developing world households had access to electricity. Appliance ownership rates remain low, but with better access to electricity and a higher income one can expect that households will see their electricity consumption rise significantly. This paper forecasts developing country appliance growth using econometric modeling. Products considered explicitly - refrigerators, air conditioners, lighting, washing machines, fans, televisions, stand-by power, water heating and space heating - represent the bulk of household electricity consumption in developing countries. The resulting diffusion model determines the trend and dynamics of demand growth at a level of detail not accessible by models of a more aggregate nature. In addition, the paper presents scenarios for reducing residential consumption through cost-effective and/or best practice efficiency measures defined at the product level. The research takes advantage of an analytical framework developed by LBNL (BUENAS) which integrates end use technology parameters into demand forecasting and stock accounting to produce detailed efficiency scenarios, which allows for a realistic assessment of efficiency opportunities at the national or regional level. The past decades have seen some of the developing world moving towards a standard of living previously reserved for industrialized countries. Rapid economic development, combined with large populations has led to first China and now India to emerging as 'energy giants', a phenomenon that is expected to continue, accelerate and spread to other countries. This paper explores the potential for slowing energy consumption and greenhouse gas emissions in the residential sector in developing countries and evaluates the potential of energy savings and emissions mitigation through market transformation programs such as, but not limited to Energy Efficiency Standards and Labeling (EES&L). The bottom-up methodology used allows one to identify which end uses and regions have the greatest potential for savings.

Letschert, Virginie; McNeil, Michael A.

2008-05-13T23:59:59.000Z

Note: This page contains sample records for the topic "residential sector 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

Directory of energy efficiency information services for the residential and commercial sectors  

SciTech Connect

This directory is a compilation of organizations which disseminate a wide range of information on the efficient use of energy in the residential and commercial sectors. Each organization's services are defined by the informations' targeted audience, types of services offered, topics and sectors addressed and access terms required. The organizations included in this directory are based on the Guide to Energy Efficiency Information Services for the Residential and Commercial Sectors, June 1987. The information is presented in two formats in this directory, each focusing on different manners of data retrieval. Section One provides a matrix illustrating the information available by the type of energy-efficiency services offered and Section Two presents information on available services in an alphabetized list by the organization name.

Not Available

1988-11-30T23:59:59.000Z

282

Energy-Efficient Water Heating Program for the Residential Sector.  

Science Conference Proceedings (OSTI)

During the power surplus period of the late 1980's, Bonneville sponsored market research which provided an understanding of the market environment in the water heating end-use. The major areas of investigation included market trends, consumer purchasing practices, unit price, and availability of energy-efficient models. In 1988, Bonneville conducted a series of meetings with utilities operating water heater programs. Discussions focused on utility program concerns and the appropriate role for Bonneville as the region seeks efficiency in residential water heating. The design of the Program is based to a large degree on the experiences gained by regional utilities operating water heater incentive programs. In addition, an analysis of incentive programs operated outside the region has been helpful in the development of a regional program. Bonneville is a member of the Appliance Efficiency Group (AEG), formerly the Northwest Appliance Efficiency Group, and participates in discussions on water heating issues as they relate to the Pacific Northwest. The work done with the Appliance Efficiency Group has provided additional input in the development of the Program. This Program has been developed using a Public Involvement Process. A draft program strategy was made available to the public for comment during April 1990. The comments received were considered in the development of this document.

United States. Bonneville Power Administration.

1990-09-01T23:59:59.000Z

283

Table 10.2a Renewable Energy Consumption: Residential and ...  

U.S. Energy Information Administration (EIA)

Includes distributed solar thermal and PV energy used in the commercial, industrial, and electric power sectors. R=Revised. P=Preliminary. NA=Not available.

284

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

8 8 2035 Residential Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. LPG Kerosene Total Coal Electricity Total Percent Space Heating (2) 44.3 10.3 7.7 18.6 0.0 16.0 79.0 27.4% Space Cooling (3) 0.0 40.6 40.6 14.1% Water Heating 17.6 1.2 1.2 2.3 17.7 37.6 13.0% Lighting 15.5 15.5 5.4% Refrigeration (4) 17.0 17.0 5.9% Electronics (5) 14.2 14.2 4.9% Wet Cleaning (6) 0.9 10.4 11.3 3.9% Cooking 3.2 0.8 0.8 4.8 8.9 3.1% Computers 8.7 8.7 3.0% Other (7) 0.0 7.7 7.7 47.9 55.7 19.3% Total 66.0 11.5 17.5 29.6 0.0 193.0 288.6 100% Note(s): Source(s): 0.6 0.6 1) Expenditures include coal and exclude wood. 2) Includes furnace fans ($4.8 billion). 3) Fan energy use included. 4) Includes refrigerators ($14.1 billion) and freezers ($2.9 billion). 5) Includes color televisions ($14.2 billion). 6) Includes clothes washers ($0.8 billion), natural gas

285

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

2 2 Residential Energy Prices, by Year and Fuel Type ($2010) LPG ($/gal) 1980 2.24 1981 2.51 1982 2.30 1983 2.14 1984 2.10 1985 1.96 1986 1.54 1987 1.42 1988 1.39 1989 1.48 1990 1.69 1991 1.56 1992 1.40 1993 1.33 1994 1.27 1995 1.22 1996 1.37 1997 1.34 1998 1.15 1999 1.16 2000 1.70 2001 1.59 2002 1.42 2003 1.67 2004 1.84 2005 2.36 2006 2.64 2007 2.81 2008 3.41 2009 2.52 2010 2.92 2011 3.62 2012 3.65 2013 3.43 2014 3.60 2015 3.74 2016 3.79 2017 3.86 2018 3.89 2019 3.92 2020 3.96 2021 3.99 2022 4.02 2023 4.07 2024 4.10 2025 4.15 2026 4.19 2027 4.23 2028 4.26 2029 4.30 2030 4.34 2031 4.35 2032 4.38 2033 4.43 2034 4.50 2035 4.55 Source(s): EIA, State Energy Data 2009: Prices and Expenditures, Jun. 2011, Table 2, p. 24-25 for 1980-2009; EIA, Annual Energy Outlook 2012 Early Release, Jan. 2012, Table A3, p. 6-8 for 2010-2035 and Table G1, p. 215 for fuels' heat content; and EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for

286

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

7 7 2025 Residential Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. LPG Kerosene Total Coal Electricity Total Percent Space Heating (2) 39.7 11.5 7.8 19.9 0.0 15.0 74.5 28.6% Space Cooling (3) 0.0 36.2 36.2 13.9% Water Heating 16.0 1.4 1.3 2.7 17.1 35.9 13.8% Lighting 15.2 15.2 5.8% Refrigeration (4) 15.5 15.5 6.0% Electronics (5) 12.0 12.0 4.6% Wet Cleaning (6) 0.8 9.8 10.5 4.1% Cooking 2.7 0.8 0.8 4.3 7.8 3.0% Computers 7.7 7.7 2.9% Other (7) 0.0 6.4 6.4 38.7 45.0 17.3% Total 59.1 12.9 16.3 29.8 0.0 171.3 260.3 100% Note(s): Source(s): 0.6 0.6 1) Expenditures include coal and exclude wood. 2) Includes furnace fans ($4.7 billion). 3) Fan energy use included. 4) Includes refrigerators ($12.7 billion) and freezers ($2.8 billion). 5) Includes color televisions ($12 billion). 6) Includes clothes washers ($0.8 billion), natural gas

287

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

6 6 2015 Residential Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. LPG Kerosene Total Coal Electricity Total Percent Space Heating (2) 35.0 13.0 8.1 21.6 0.0 14.0 70.6 29.2% Space Cooling (3) 0.0 33.8 33.8 14.0% Water Heating 13.5 1.9 1.5 3.4 15.8 32.7 13.5% Lighting 17.6 17.6 7.3% Refrigeration (4) 15.0 15.0 6.2% Electronics (5) 10.9 10.9 4.5% Wet Cleaning (6) 0.6 10.8 11.4 4.7% Cooking 2.2 0.9 0.9 3.8 6.8 2.8% Computers 6.3 6.3 2.6% Other (7) 0.0 5.2 5.2 31.3 36.5 15.1% Total 51.3 14.9 15.7 31.1 0.0 159.3 241.7 100% Note(s): Source(s): 0.6 0.6 1) Expenditures include coal and exclude wood. 2) Includes furnace fans ($4.6 billion). 3) Fan energy use included. 4) Includes refrigerators ($12.3 billion) and freezers ($2.8 billion). 5) Includes color televisions ($10.9 billion). 6) Includes clothes washers ($1.1 billion), natural gas

288

Table 10.2c Renewable Energy Consumption: Electric Power Sector...  

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

Energy Consumption: Electric Power Sector, 1949-2011" " (Billion Btu)" "Year",,,"Geothermal 2",,"SolarPV 3",,"Wind 4",,"Biomass",,,,,,"Total" ,"Hydroelectric" ,"Power...

289

Table 2.1a Energy Consumption Estimates by Sector, Selected Years ...  

U.S. Energy Information Administration (EIA)

40 U.S. Energy Information Administration / Annual Energy Review 2011 Table 2.1a Energy Consumption Estimates by Sector, Selected Years, 1949-2011

290

Table 10.2c Renewable Energy Consumption: Electric Power Sector ...  

U.S. Energy Information Administration (EIA)

Table 10.2c Renewable Energy Consumption: Electric Power Sector, 1949-2011 ... Through 2000, also includes non-renewable waste (municipal solid waste from

291

Table F4. Delivered energy consumption in Canada by end-use sector ...  

U.S. Energy Information Administration (EIA)

228 U.S. Energy Information Administration International Energy Outloo 2013 Appendix F Table F4. Delivered energy consumption in Canada by end-use sector and fuel ...

292

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

Residential Energy Prices, by Year and Major Fuel Type ($2010 per Million Btu) Electricity Natural Gas Petroleum (1) Avg. 1980 36.40 8.35 16.77 17.64 1981 38.50 8.88 18.35 19.09 1982 40.15 10.08 17.28 19.98 1983 40.43 11.30 16.08 21.00 1984 38.80 11.02 15.61 20.20 1985 38.92 10.68 14.61 20.10 1986 38.24 9.98 11.88 19.38 1987 37.29 9.22 11.23 18.73 1988 36.22 8.80 10.83 18.02 1989 35.67 8.71 11.96 17.93 1990 35.19 8.63 13.27 18.64 1991 34.88 8.38 12.49 18.31 1992 34.79 8.28 11.23 17.76 1993 34.52 8.47 10.75 17.76 1994 34.04 8.63 10.63 17.87 1995 33.43 8.00 10.33 17.50 1996 32.63 8.21 11.70 17.28 1997 32.34 8.83 11.47 17.69 1998 31.33 8.55 9.96 17.73 1999 30.52 8.29 10.13 17.09 2000 30.13 9.54 14.18 18.06 2001 30.71 11.50 13.98 19.38 2002 29.73 9.24 12.26 17.89 2003 30.05 10.87 14.21 18.88 2004 29.98 11.97 15.54 19.76 2005 30.64 13.66 18.93 21.50 2006 32.67 14.30 21.06 23.34 2007 32.50

293

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)

294

Heating Degree Day Data Applied to Residential Heating Energy Consumption  

Science Conference Proceedings (OSTI)

Site-specific total electric energy and heating oil consumption for individual residences show a very high correlation with National Weather Service airport temperature data when transformed to heating degree days. Correlations of regional total ...

Robert G. Quayle; Henry F. Diaz

1980-03-01T23:59:59.000Z

295

Regional comparisons of on-site solar potential in the residential and industrial sectors  

SciTech Connect

Regional and sub-regional differences in the potential development of decentralized solar technologies are studied. Two sectors of the economy were selected for intensive analysis: the residential and industrial sectors. In both investigations, the sequence of analysis follows the same general steps: (1) selection of appropriate prototypes within each land-use sector disaggregated by census region; (2) characterization of the end-use energy demand of each prototype in order to match an appropriate decentralized solar technology to the energy demand; (3) assessment of the energy conservation potential within each prototype limited by land use patterns, technology efficiency, and variation in solar insolation; and (4) evaluation of the regional and sub-regional differences in the land use implications of decentralized energy supply technologies that result from the combination of energy demand, energy supply potential, and the subsequent addition of increasingly more restrictive policies to increase the percent contribution of on-site solar energy. Results are presented and discussed. It is concluded that determining regional variations in solar energy contribution for both the residential and industrial sectors appears to be more dependent upon a characterization of existing demand and conservation potential than regional variations in solar insolation. Local governmental decisions influencing developing land use patterns can significantly promote solar energy use and reduce reliance on non-renewable energy sources. These decisions include such measures as solar access protection through controls on vegetation and on building height and density in the residential sector, and district heating systems and industrial co-location in the manufacturing sector. (WHK)

Gatzke, A.E.; Skewes-Cox, A.O.

1980-10-01T23:59:59.000Z

296

LBL-40297 UC-1600 ENERGY DATA SOURCEBOOK FOR THE U.S. RESIDENTIAL SECTOR  

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

40297 40297 UC-1600 ENERGY DATA SOURCEBOOK FOR THE U.S. RESIDENTIAL SECTOR Tom P. Wenzel, Jonathan G. Koomey, Gregory J. Rosenquist, Marla Sanchez, and James W. Hanford September 1997 Energy Analysis Program Environmental Energy Technologies Division Lawrence Berkeley National Laboratory University of California Berkeley, CA 94720 http://enduse.lbl.gov/Projects/RED.html This work was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Building Technology, State, and Community Programs of the U.S. Department of Energy under Contract No. DE-AC03- 76SF00098. i ABSTRACT Analysts assessing policies and programs to improve energy efficiency in the residential sector require disparate input data from a variety of sources. This sourcebook, which updates a previous

297

DOE/EIA-0207/3 Residential Energy Consumption Survey: Conservation  

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

3 3 Residential Energy Consumption Survey: Conservation February 1980 U.S. Department of Energy Energy Information Adminstration Assistant Administrater for Program Development Other NEICS Reports Preliminary Conservation Tables from the National Interim Energy Consumption Survey, August 1979, DOE/EIA-0193/P Characteristics of the Housing Stocks and Households: Preliminary Findings from the National Interim Energy Consumption Survey, October 1979, DOETllA-0199/P The above reports are available from the following address; U.S. Department of Energy Technical Information Center Attn:; EIA Coordinator P.O. Box 62 Oak Ridge, TN 37830 Residential Energy Consumption Survey; Characteristics of the Housing Stock and Households, DOE/EIA-0207/2, GPO Stock No,, 061-003-00093-2; $4.25

298

Kartläggning av energianvändning under byggfasen vid nyproduktion av flerbostadshus; Investigation of the energy consumption during production of apartment buildings.  

E-Print Network (OSTI)

?? The energy consumption in the sectors of residential and public buildings is 40 % of the total energy consumption in Sweden. The main part,… (more)

Hatami, Valid

2007-01-01T23:59:59.000Z

299

Window-Related Energy Consumption in the US Residential and Commercial  

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

Window-Related Energy Consumption in the US Residential and Commercial Window-Related Energy Consumption in the US Residential and Commercial Building Stock Title Window-Related Energy Consumption in the US Residential and Commercial Building Stock Publication Type Report LBNL Report Number LBNL-60146 Year of Publication 2006 Authors Apte, Joshua S., and Dariush K. Arasteh Call Number LBNL-60146 Abstract We present a simple spreadsheet-based tool for estimating window-related energy consumption in the United States. Using available data on the properties of the installed US window stock, we estimate that windows are responsible for 2.15 quadrillion Btu (Quads) of heating energy consumption and 1.48 Quads of cooling energy consumption annually. We develop estimates of average U-factor and SHGC for current window sales. We estimate that a complete replacement of the installed window stock with these products would result in energy savings of approximately 1.2 quads. We demonstrate that future window technologies offer energy savings potentials of up to 3.9 Quads.

300

Predicting Future Hourly Residential Electrical Consumption: A Machine Learning Case Study  

E-Print Network (OSTI)

(e.g., HVAC) for a specific building, optimizing control systems and strategies for a buildingPredicting Future Hourly Residential Electrical Consumption: A Machine Learning Case Study Richard building energy modeling suffers from several factors, in- cluding the large number of inputs required

Tennessee, University of

Note: This page contains sample records for the topic "residential sector 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

Residential energy-consumption survey: housing characteristics, 1981  

SciTech Connect

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, and consumption of wood. Collected for the first time are data related to indoor temperatures and the use of air conditioning. A unique feature of the 1981 survey is an increased sampling of low-income households funded by the Social Security Administration to provide them information for the Low-Income Home Energy Assistance Program. Discussion highlights data pertaining to these topics: changes in home heating fuel, secondary heating, indoor temperatures, features of new homes, use of air conditioning, use of solar collectors, and wood consumption.

Thompson, W.

1983-08-01T23:59:59.000Z

302

Residential energy consumption of low-income and elderly households: how non-discretionary is it  

SciTech Connect

The energy literature is replete with opinions that the poor and elderly have cut their residential energy consumption to a minimum. This paper challenges such conclusions through an analysis of data on a sample of 319 Decatur, Illinois homeowners. The data include utility bill histories and survey information on housing characteristics, energy-related behaviors, attitudes, and socio-economic and demographic characteristics. It shows that residential energy consumption per square foot of living space is significantly higher for the elderly and poor than for other groups of Decatur homeowners. By breaking energy use into seasonal components, the paper estimates consumption for various household uses. This information, combined with the survey data, suggests that both subgroups heat and cool their homes inefficiently, due in part to the conditions of their homes, but also due to energy-related behaviors. The public policy implications of the findings are discussed.

Brown, M.A.; Rollinson, P.A.

1984-01-01T23:59:59.000Z

303

Residential Sector  

Gasoline and Diesel Fuel Update (EIA)

5.94 5.94 15.88 15.47 15.61 15.61 16.19 16.30 16.49 16.10 16.51 16.45 16.78 15.71 16.14 16.45 Middle Atlantic ............. 14.85 15.35 15.64 15.16 15.08 15.70 16.48 15.74 15.27 16.00 16.67 15.96 15.27 15.77 15.99 E. N. Central ................ 11.72 12.37 12.12 12.00 11.48 12.45 12.30 12.03 11.80 12.69 12.68 12.19 12.05 12.05 12.33 W. N. Central .............. 9.64 11.03 11.45 10.12 9.94 11.39 12.05 10.27 10.28 11.56 11.99 10.51 10.59 10.91 11.08 S. Atlantic .................... 11.07 11.48 11.65 11.22 10.89 11.48 11.77 11.31 10.99 11.64 11.85 11.42 11.38 11.38 11.49 E. S. Central ................ 10.05 10.44 10.38 10.41 10.04 10.69 10.65 10.45 10.35 10.96 11.01 10.73 10.32 10.45 10.76 W. S. Central ............... 10.14 10.30 10.35 10.37 10.23 10.94 10.91 10.73 10.59 10.97 11.07 10.80 10.30 10.73 10.88 Mountain .....................

304

Statistical Analysis of Historical State-Level Residential Energy Consumption Trends  

SciTech Connect

Developing an accurate picture of the major trends in energy consumption in the nation’s stock of residential buildings can serve a variety of national and regional program planning and policy needs related to energy use. This paper employs regression analysis and uses the PRISM (Princeton Scorekeeping Method) approach with historical data to provide some insight into overall changes in the thermal integrity of the residential building stock by state. Although national energy use intensity estimates exist in aggregate, these numbers shed little light on what drives building consumption, as opposing influences are hidden within the measurement (e.g., more appliances that increase energy use while shell improvements reduce it). This study addresses this issue by estimating changes in the reference temperatures that best characterize the existing residential building stock on a state basis. Improvements in building thermal integrity are reflected by declines in the heating reference temperature, holding other factors constant. Heating and cooling-day estimates to various reference temperatures were computed from monthly average temperature data for approximately 350 climatic divisions in the U.S. A simple cross-sectional analysis is employed to try to explain the differential impacts across states. Among other factors, this analysis considers the impact that the relative growth in the number of residential buildings and the stringency of building energy codes has had on residential building energy use. This paper describes the methodology used, presents results, and suggests directions for future research.

Belzer, David B.; Cort, Katherine A.

2004-08-01T23:59:59.000Z

305

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

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 All Sectors Change category... All Sectors Commercial Buildings Efficiency Manufacturing Projections Residential Transportation All Reports Filter by: All Data Analysis Projections Today in Energy - Commercial Consumption & Efficiency Short, timely articles with graphs about recent commercial consumption and

306

Residential energy consumption survey. Consumption patterns of household vehicles, supplement: January 1981-September 1981  

Science Conference Proceedings (OSTI)

Information on the fuel consumption characteristics on household vehicles in the 48 contiguous States and the District of Columbia is presented by monthly statistics of fuel consumption, expenditures, miles per gallon, and miles driven.

Not Available

1983-02-01T23:59:59.000Z

307

Is Efficiency Enough? Towards a New Framework for Carbon Savingsin the California Residential Sector  

SciTech Connect

The overall implementation of energy efficiency in the United States is not adequately aligned with the environmental benefits claimed for efficiency, because it does not consider absolute levels of energy use, pollutant emissions, or consumption. In some ways, promoting energy efficiency may even encourage consumption. A more effective basis for environmental policy could be achieved by recognizing the degree and nature of the synchronization between environmental objectives and efficiency. This research seeks to motivate and initiate exploration of alternative ways of defining efficiency or otherwise moderating energy use toward reaching environmental objectives, as applicable to residential electricity use in California. The report offers three main recommendations: (1) produce definitions of efficiency that better integrate absolute consumption, (2) attend to the deeper social messages of energy efficiency communications, and (3) develop a more critical perspective on benefits and limitations of energy efficiency for delivering environmental benefits. In keeping with the exploratory nature of this project, the report also identifies ten questions for further investigation.

Moezzi, Mithra; Diamond, Rick

2005-10-01T23:59:59.000Z

308

Residential Energy Consumption Survey: Consumption and expenditures, April 1984 through March 1985: Part 2, Regional data. [Contains glossary  

SciTech Connect

Included here are data at the Census region and division level on consumption of and expenditures for the major fuels used in residential households - electricity, natural gas, fuel oil/kerosene, and liquefied petroleum gas (LPG). Data are also presented on wood consumption. Section 1 of this report contains data on the average amount of energy consumed per household for space heating in 1984 and the corresponding expenditures. Sections 2 through 7 summarize the energy consumption and expenditure patterns. Appendices A through D contain information on how the survey was conducted, estimates of the size of the housing unit in square feet and the quality of the data. Procedures for calculating relative standard errors (RSE) are located in Appendix C, Quality of the Data. Procedures for estimating the end-use statistics are located in Appendix D. Census and weather maps, and related publications are located in Appendices E through G.

Not Available

1987-05-13T23:59:59.000Z

309

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

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

Window-Related Energy Consumption in the US Window-Related Energy Consumption in the US Residential and Commercial Building Stock Joshua Apte and Dariush Arasteh, Lawrence Berkeley National Laboratory LBNL-60146 Abstract We present a simple spreadsheet-based tool for estimating window-related energy consumption in the United States. Using available data on the properties of the installed US window stock, we estimate that windows are responsible for 2.15 quadrillion Btu (Quads) of heating energy consumption and 1.48 Quads of cooling energy consumption annually. We develop estimates of average U-factor and SHGC for current window sales. We estimate that a complete replacement of the installed window stock with these products would result in energy savings of approximately 1.2 quads. We demonstrate

310

Consumption of Coal for Electricity Generation by State by Sector...  

Open Energy Info (EERE)

Coal for Electricity Generation by State by Sector, January 2011 and 2010 This dataset contains state by state comparisons of coal for electricity generation in the United States....

311

Residential Energy Consumption Survey (RECS) - Data - U.S. Energy  

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

1997 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous 1997 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing Characteristics Consumption & Expenditures Microdata Methodology Housing Characteristics Tables Table Titles (Released: February 2004) Entire Section Percents Tables: HC1 Housing Unit Characteristics, Million U.S. Households PDF PDF NOTE: As of 10/31/01, numbers in the "Housing Units" TABLES section for stub item: "Number of Floors in Apartment Buildings" were REVISED. These numbers will differ from the numbers in the published report. Tables: HC2 Household Characteristics, Million U.S. Households PDF PDF Tables: HC3 Space Heating, Million U.S. Households PDF PDF Tables: HC4 Air-Conditioning, Million U.S. Households PDF PDF Tables: HC5 Appliances, Million U.S. Households PDF PDF

312

Residential Energy Consumption Survey (RECS) - Data - U.S. Energy  

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

3 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous 3 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing Characteristics Consumption & Expenditures Microdata Methodology Housing Characteristics Tables Topical Sections Entire Section All Detailed Tables PDF Tables: HC1 Household Characteristics, Million U.S. Households Presents data relating to location, type, ownership, age, size, construction, and householder demographic and income characteristics. PDF Tables: HC2 Space Heating, Million U.S. Households Presents data describing the types of heating fuel and equipment used for main and secondary heating purposes. PDF Tables: HC3 Air-Conditioning, Million U.S. Households Presents data describing selected household characteristics including location, number of rooms and area cooled and air-conditioning usage. PDF

313

Residential Energy Consumption Survey (RECS) - Data - U.S. Energy  

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

5 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous 5 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing Characteristics Consumption & Expenditures Microdata Housing Characteristics Tables + EXPAND ALL Floorspace - Housing Characteristics PDF (all tables) Total Floorspace All, Heated, and Cooled Floorspace (HC1.1.1) PDF XLS Average Floorspace All Housing Units (HC1.1.2) PDF XLS Single Family and Mobile Homes (HC1.1.3) PDF XLS Apartments (HC1.1.4) PDF XLS Usage Indicators Heated Floorspace (HC1.3) PDF XLS Cooled Floorspace (HC1.4) PDF XLS Floorspace - Living Space PDF (all tables) Total Floorspace All, Heated, and Cooled Floorspace (HC1.2.1) PDF XLS Average Floorspace All Housing Units (HC1.2.2) PDF XLS Single Family and Mobile Homes (HC1.2.3) PDF XLS Apartments (HC1.2.4) PDF XLS

314

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

315

Residential Energy Consumption Survey (RECS) - Data - U.S. Energy  

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

2001 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous 2001 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing Characteristics Consumption & Expenditures Microdata Methodology Housing Characteristics Tables + EXPAND ALL Tables HC1: Housing Unit Characteristics, Million U.S. Households PDF (all tables) Climate Zone PDF Year of Construction PDF Household Income PDF Type of Owner-Occupied Housing Unit PDF Four Most Populated States PDF Urban/Rural Location PDF Northeast Census Region PDF Midwest Census Region PDF South Census Region PDF West Census Region PDF Tables HC2: Household Characteristics, Million U.S. Households PDF (all tables) Climate Zone PDF Year of Construction PDF Household Income PDF Type of Housing Unit PDF Type of Owner-Occupied Housing Unit PDF Type of Rented Housing Unit PDF

316

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

Gasoline and Diesel Fuel Update (EIA)

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

317

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

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

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

318

,"South Carolina Natural Gas Residential Consumption (MMcf)"  

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

Monthly","9/2013" Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3010sc2m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3010sc2m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:21:55 PM" "Back to Contents","Data 1: South Carolina Natural Gas Residential Consumption (MMcf)" "Sourcekey","N3010SC2" "Date","South Carolina Natural Gas Residential Consumption (MMcf)" 32523,3768 32554,3029 32582,3327 32613,1875

319

,"South Dakota Natural Gas Residential Consumption (MMcf)"  

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

Monthly","9/2013" Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3010sd2m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3010sd2m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:21:56 PM" "Back to Contents","Data 1: South Dakota Natural Gas Residential Consumption (MMcf)" "Sourcekey","N3010SD2" "Date","South Dakota Natural Gas Residential Consumption (MMcf)" 32523,1762 32554,1865 32582,1639 32613,1036 32643,562

320

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

Note: This page contains sample records for the topic "residential sector 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

Predicting Future Hourly Residential Electrical Consumption: A Machine Learning Case Study  

Science Conference Proceedings (OSTI)

Whole building input models for energy simulation programs are frequently created in order to evaluate specific energy savings potentials. They are also often utilized to maximize cost-effective retrofits for existing buildings as well as to estimate the impact of policy changes toward meeting energy savings goals. Traditional energy modeling suffers from several factors, including the large number of inputs required to characterize the building, the specificity required to accurately model building materials and components, simplifying assumptions made by underlying simulation algorithms, and the gap between the as-designed and as-built building. Prior works have attempted to mitigate these concerns by using sensor-based machine learning approaches to model energy consumption. However, a majority of these prior works focus only on commercial buildings. The works that focus on modeling residential buildings primarily predict monthly electrical consumption, while commercial models predict hourly consumption. This means there is not a clear indicator of which techniques best model residential consumption, since these methods are only evaluated using low-resolution data. We address this issue by testing seven different machine learning algorithms on a unique residential data set, which contains 140 different sensors measurements, collected every 15 minutes. In addition, we validate each learner's correctness on the ASHRAE Great Energy Prediction Shootout, using the original competition metrics. Our validation results confirm existing conclusions that Neural Network-based methods perform best on commercial buildings. However, the results from testing our residential data set show that Feed Forward Neural Networks, Support Vector Regression (SVR), and Linear Regression methods perform poorly, and that Hierarchical Mixture of Experts (HME) with Least Squares Support Vector Machines (LS-SVM) performs best - a technique not previously applied to this domain.

Edwards, Richard E [ORNL; New, Joshua Ryan [ORNL; Parker, Lynne Edwards [ORNL

2012-01-01T23:59:59.000Z

322
323

Feedback as a means of decreasing residential energy consumption. Report PU/CES 34  

SciTech Connect

When residential units are analyzed in human factor terms, it is apparent that the consumption level feedback (typically a bill, calculated once a month, over all appliances) is inadequate to give the resident useful information about his energy consuming actions. The present study tested the hypothesis that providing immediate feedback to homeowners concerning their daily rate of electric usage would be effective in reducing electric consumption. In the studied homes, central air-conditioning is the largest single source of electric power consumption during the summer. Accordingly, it was possible to predict the household's expected electric consumption in terms of the average daily outdoor temperature. Predicted electric consumption was derived from a previous month's modeling period during which a regression line was fitted to predict consumption from average daily temperature, for each home. Feedback was expressed as a percentage of actual consumption over predicted consumption. Feedback was displayed to homeowners four times a week for approximately one month. The results confirmed the prediction. Before feedback began, the feedback and control groups were consuming electricity at approximately equal rates. During the feedback period, the feedback group used 10.5 percent less electricity. The effectiveness of the feedback procedure was explained in terms of its cueing, motivational, and commitment functions.

Seligman, C.; Darley, J.M.

1976-08-01T23:59:59.000Z

324

State energy price projections for the residential sector, 1993--1994  

Science Conference Proceedings (OSTI)

The purpose of tills report, State Energy Price Projections for the Residential Sector, 1993--1994, is to provide projections of State-level residential prices for 1993 and 1994 for the following fuels: electricity, natural gas, heating oil, liquefied petroleum gas (LPG), kerosene, and coal. Prices for 1992 are also included for comparison purposes. This report also explains the methodology used to produce estimates and the limitations. This report is provided at the request of the Administration for Children and Families, US Department of Health and Human Services, which provides State grants to assist eligible households in meeting the costs of home energy use for space heating or cooling under the Low Income Home Energy Assistance Program (LIHEAP). Funds for LIHEAP are allocated according to each State`s share of home energy expenditures by low income households, if Congress allocates more than $1.975 billion for LIHEAP. Whenever less than $1.975 billion is allocated for LIHEAP, funds are allocated based on the allotment percentages for fiscal year 1984. This has been the case for the last several years. Each State`s share of the funds above $1.975 billion is determined using a formula based, in part, on the price estimates in this report. Several data sources and factors are used in deriving estimates on each State`s share of home energy expenditures by low-income households. One such factor is State-level residential energy prices. The State-level residential energy price projections presented in this report are derived from a set of forecasting equations estimated for each State, based on annual time series data from the Energy Information Administration`s (EIA) State Energy Price and Expenditure Report (SEPER) database, the EIA Natural Gas Monthly (NGM), the EIA Petroleum Marketing Annual (PMA), and the EIA Electric Power Monthly (EPM).

Not Available

1993-11-01T23:59:59.000Z

325

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

326

The impact of residential density on vehicle usage and fuel consumption  

E-Print Network (OSTI)

characteristics on household residential choice and auto2009. The impact of residential density on vehicle usage and2010-05) The impact of residential density on vehicle usage

Kim, Jinwon; Brownstone, David

2010-01-01T23:59:59.000Z

327

ResPoNSe: modeling the wide variability of residential energy consumption.  

E-Print Network (OSTI)

of Decision Making and Residential Energy Use. Annual Reviewand David Auslander. 2010. Residential Occupied NeighborhoodCommission (CEC). 2001. Residential Alternative Calculation

Peffer, Therese; Burke, William; Auslander, David

2010-01-01T23:59:59.000Z

328

Analysis of Energy Consumption and Research on Energy-Saving Technology of Rural Residential Buildings in Southern Shaanxi  

Science Conference Proceedings (OSTI)

The article was to grasp trends of energy consumption of village in southern Shaanxi province. Selecting Huangjiagou village of Mian county in Hanzhong city as the investigation base ¡£Respectively, in January 2009 and July2010, investigation was conducted ... Keywords: rural region, investigation, residential dwellings, energy consumption, energy conservation

Yang Liu; Xia Fang; Meng Dan; An Yungang

2011-02-01T23:59:59.000Z

329

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

330

Model documentation report: Residential sector demand module of the National Energy Modeling System  

SciTech Connect

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This document serves three purposes. First, it is a reference document providing a detailed description for energy analysts, other users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

NONE

1995-03-01T23:59:59.000Z

331

Model documentation report: Residential sector demand module of the National Energy Modeling System  

Science Conference Proceedings (OSTI)

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This document serves three purposes. First, it is a reference document that provides a detailed description for energy analysts, other users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

NONE

1997-01-01T23:59:59.000Z

332

A Statistical Model to Assess Indirect CO2 Emissions of the UAE Residential Sector  

E-Print Network (OSTI)

This study presents a regional bottom-up model for assessing space cooling energy and related greenhouse gas emissions. The model was developed with the aim of improving the quality and quantity of cooling energy and emission data, especially for the benefit of local decision making. Based on a benchmarking study, a representative archetype was developed, simulation software used and linear statistical model constructed. This model explores the way in which CO2 emission levels are affected by different energy efficiency measures to reduce cooling energy consumption in buildings. The analysis showed that improving building energy efficiency could generate considerable carbon emissions reduction credits with competitive benefit. The developed model was found to be capable in selecting cost-effective, environmentally-preferred building efficiency measures and evaluating the future trend of CO2 emissions in the residential building of Al-Ain city.

Radhi, H.; Fikry, F.

2010-01-01T23:59:59.000Z

333

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).

334

Residential fuelwood consumption and production in Michigan, 1992. Forest Service resource bulletin  

SciTech Connect

Since fuelwood's heyday in the late 1800's, its use as a primary home heating and cooking fuel has declined dramatically as homeowners opted for the convenience and efficiency of fossil-based fuels. In Michigan, the resurgence in residential fuelwood use resulted in one in three households taking advantage of wood energy (Michigan Department of Natural Resources 1982), and sent the volume of fuelwood burned, i.e. consumption, skyrocketing to levels not seen in half a century.

May, D.M.; Weatherspoon, A.K.; Hackett, R.L.

1993-01-01T23:59:59.000Z

335

Dynamic Simulation and Analysis of Heating Energy Consumption in a Residential Building  

E-Print Network (OSTI)

In winter, much of the building energy is used for heating in the north region of China. In this study, the heating energy consumption of a residential building in Tianjin during a heating period was simulated by using the EnergyPlus energy simulation program. The study showed that the heat loss from exterior walls, exterior windows and infiltration took three main parts of the total heat loss. Furthermore, the results of on-site measurement are presented with the conclusion that the EnergyPlus program provides sufficient accuracy for this energy simulation application.

Liu, J.; Yang, M.; Zhao, X.; Zhu, N.

2006-01-01T23:59:59.000Z

336

An analysis of residential energy consumption in a temperate climate. Volume 1  

SciTech Connect

Electrical energy consumption data have been recorded for several hundred submetered residential structures in Middle Tennessee. All houses were constructed with a common ``energy package.`` Specifically, daily cooling usage data have been collected for 130 houses for the 1985 and 1986 cooling seasons, and monthly heating usage data for 186 houses have been recorded by occupant participation over a seven-year period. Cooling data have been analyzed using an SPSSx multiple regression analysis and results are compared to several cooling models. Heating, base, and total energy usage are also analyzed and regression correlation coefficients are determined as a function of several house parameters.

Clark, Y.Y.; Vincent, W.

1987-06-01T23:59:59.000Z

337

Residential energy consumption and expenditures by end use for 1978, 1980, and 1981  

Science Conference Proceedings (OSTI)

The end-use estimates of the average household consumption and expenditures are statistical estimates based on the 1978, 1980, and 1981 Residential Enery Consumption Surveys (RECS) conducted by the Energy Information Administration (EIA) rather than on metered observations. The end-use estimates were obtained by developing a set of equations that predict the percentage of energy used for each broad end-use category. The equations were applied separately to each household and to each fuel. The resulting household end-use estimates were averaged to produce estimates of the average end-use consumption and expenditures on a national and regional basis. The accuracy and potential biases of these end-use estimates vary depending on the fuel type, on the year of the survey, and on the type of end use. The figures and tables presented show the amount and the type of energy cosumed, plus the cost of this energy. National averages are given as well as averages for various categories including region, size and age of dwelling, number of heating degree-days, and income. Some of the significant findings; energy trends by end use for all fuels used in the home for 1978, 1980, and 1981; and electricity consumption and expenditures and natural gas consumption and expenditures are discussed.

Johnson, M.

1984-12-01T23:59:59.000Z

338

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

SciTech Connect

In 2001, DOE initiated a rulemaking process to consider whether to amend the existing energy efficiency standards for furnaces and boilers. A key factor in DOE's consideration of new standards is their cost-effectiveness to consumers. Determining cost-effectiveness requires an appropriate comparison of the additional first cost of energy efficiency design options with the savings in operating costs. This report describes calculation of equipment energy consumption (fuel and electricity) based on estimated conditions in a sample of homes that are representative of expected furnace and boiler installations. To represent actual houses with furnaces and boilers in the United States, we used a set of houses from the Residential Energy Consumption Survey of 1997 conducted by the Energy Information Administration. Our calculation methodology estimates the energy consumption of alternative (more-efficient) furnaces, if they were to be used in each house in place of the existing equipment. We developed the method of calculation described in this report for non-weatherized gas furnaces. We generalized the energy consumption calculation for this product class to the other furnace product classes. Fuel consumption calculations for boilers are similar to those for the other furnace product classes. The electricity calculations for boilers are simpler than for furnaces, because boilers do not provide thermal distribution for space cooling as furnaces often do.

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

2004-02-01T23:59:59.000Z

339

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

SciTech Connect

In 2001, DOE initiated a rulemaking process to consider whether to amend the existing energy efficiency standards for furnaces and boilers. A key factor in DOE's consideration of new standards is their cost-effectiveness to consumers. Determining cost-effectiveness requires an appropriate comparison of the additional first cost of energy efficiency design options with the savings in operating costs. This report describes calculation of equipment energy consumption (fuel and electricity) based on estimated conditions in a sample of homes that are representative of expected furnace and boiler installations. To represent actual houses with furnaces and boilers in the United States, we used a set of houses from the Residential Energy Consumption Survey of 1997 conducted by the Energy Information Administration. Our calculation methodology estimates the energy consumption of alternative (more-efficient) furnaces, if they were to be used in each house in place of the existing equipment. We developed the method of calculation described in this report for non-weatherized gas furnaces. We generalized the energy consumption calculation for this product class to the other furnace product classes. Fuel consumption calculations for boilers are similar to those for the other furnace product classes. The electricity calculations for boilers are simpler than for furnaces, because boilers do not provide thermal distribution for space cooling as furnaces often do.

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

2004-02-01T23:59:59.000Z

340

Consumption & Prices by Sector & Census Division Tables  

Gasoline and Diesel Fuel Update (EIA)

- New England-01 - New England-01 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Residential Liquefied Petroleum Gases 0.027 0.026 0.026 0.027 0.027 0.027 0.027 0.028 0.028 0.028 0.028 0.029 0.029 Kerosene 0.026 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.016 0.016 0.016 0.016 Distillate Fuel Oil 0.356 0.345 0.336 0.334 0.330 0.329 0.330 0.331 0.333 0.333 0.333 0.331 0.330 Liquid Fuels Subtotal 0.409 0.386 0.378 0.376 0.372 0.370 0.372 0.374 0.376 0.377 0.377 0.376 0.375 Natural Gas 0.193 0.202 0.183 0.207 0.210 0.212 0.213 0.215 0.217 0.217 0.218 0.219 0.219 Coal 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Renewable Energy 1/ 0.027 0.028 0.027 0.028 0.028 0.028 0.027 0.027 0.027 0.026 0.026 0.026 0.026 Electricity 0.159 0.166 0.170 0.173 0.177 0.179 0.182 0.183 0.186 0.187 0.188 0.189 0.191 Delivered Energy

Note: This page contains sample records for the topic "residential sector 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

Residential energy consumption and expenditure patterns of low-income households in the United States  

SciTech Connect

The principal objective of this study is to compare poor and non-poor households with respect to energy consumption and expenditures, housing characteristics, and energy-related behavior. We based our study on an analysis of a national data base created by the US Department of Energy, the 1982-1983 Residential Energy Consumption Survey (RECS). RECS includes detailed information on individual households: demographic characteristics, energy-related features of the structure, heating equipment and appliances, recent conservation actions taken by the household, and fuel consumption and costs for April 1982-March 1983. We found a number of statistically significant (at the 0.05 level) differences between the two income groups in terms of demographics, heating/cooling/water heating systems, appliance saturation, the thermal integrity of their home, energy conservation behavior, energy consumption, energy expenditures, and the percentage of income spent on energy costs. For example, the non-poor used 22% more energy and paid 25% more money on utilities than the poor; however, the poor spent 20% more energy per square foot than the non-poor and spent about 25% of their income on energy expenditures, compared to 7% for the non-poor. These differences suggest different approaches that might be taken for targeting energy conservation programs to low-income households. Since the poor's ''energy burden'' is large, informational, technical, and financial assistance to low-income households remains an urgent, national priority. 13 refs., 26 tabs.

Vine, E.L.; Reyes, I.

1987-09-01T23:59:59.000Z

342

An analysis of residential energy consumption and expenditures by minority households by home type and housing vintage  

SciTech Connect

In this paper a descriptive analysis of the relationship between energy consumption, patterns of energy use, and housing stock variables is presented. The purpose of the analysis is to uncover evidence of variations in energy consumption and expenditures, and patterns of energy use between majority households (defines as households with neither a black nor Hispanic head of household), black households (defined as households with a black head of household), and Hispanic households (defined as households with a Hispanic head of household) between 1980 (time of the first DOE/EIA Residential Energy Consumption Survey, 1982a) and 1987 (time of the last DOE/EIA Residential Energy Consumption Survey, 1989a). The analysis is three-dimensional: energy consumption and expenditures are presented by time (1980 to 1987), housing vintage, and housing type. A comparative analysis of changes in energy variables for the three population groups -- majority, black, and Hispanic -- within and between specific housing stock categories is presented.

Poyer, D.A.

1992-01-01T23:59:59.000Z

343

An analysis of residential energy consumption and expenditures by minority households by home type and housing vintage  

SciTech Connect

In this paper a descriptive analysis of the relationship between energy consumption, patterns of energy use, and housing stock variables is presented. The purpose of the analysis is to uncover evidence of variations in energy consumption and expenditures, and patterns of energy use between majority households (defines as households with neither a black nor Hispanic head of household), black households (defined as households with a black head of household), and Hispanic households (defined as households with a Hispanic head of household) between 1980 (time of the first DOE/EIA Residential Energy Consumption Survey, 1982a) and 1987 (time of the last DOE/EIA Residential Energy Consumption Survey, 1989a). The analysis is three-dimensional: energy consumption and expenditures are presented by time (1980 to 1987), housing vintage, and housing type. A comparative analysis of changes in energy variables for the three population groups -- majority, black, and Hispanic -- within and between specific housing stock categories is presented.

Poyer, D.A.

1992-06-01T23:59:59.000Z

344

The Impact of Residential Density on Vehicle Usage and Energy Consumption  

E-Print Network (OSTI)

DC. Steiner, R.L. (1994). Residential density and traveland Brownstone The Impact of Residential Density on VehicleWP-05-1 The Impact of Residential Density on Vehicle Usage

Golob, Thomas F; Brownstone, David

2005-01-01T23:59:59.000Z

345

Is Efficiency Enough? Towards a New Framework for Carbon Savings in the California Residential Sector  

E-Print Network (OSTI)

in the Patterns of Energy Consumption and Expenditures OverEfficiency from Energy Consumption,” Energy and Environment2000. “Analysis of Energy Consumption, Rating Score, and

Moezzi, Mithra; Diamond, Rick

2005-01-01T23:59:59.000Z

346

Strategies for Low Carbon Growth In India: Industry and Non Residential Sectors  

E-Print Network (OSTI)

9 Table 4. International Estimates of Energy Consumption in16 Table 10. Industrial energy consumption, India in 2003-25. India Specific energy consumption, including feedstock (

Sathaye, Jayant

2011-01-01T23:59:59.000Z

347

Impact of conservation measures on Pacific Northwest residential energy consumption. Final report  

SciTech Connect

The objective of this study was to estimate the relationship between residential space conditioning energy use and building conservation programs in the Pacific Northwest. The study was divided into two primary tasks. In the first, the thermal relationship between space conditioning energy consumption under controlled conditions and the physical characteristics of the residence was estimated. In this task, behavioral characteristics such as occupant schedules and thermostat settings were controlled in order to isolate the physical relationships. In the second task, work from the first task was used to calculate the thermal efficiency of a residence's shell. Thermal efficiency was defined as the ability of a shell to prevent escapement of heat generated within a building. The relationship between actual space conditioning energy consumption and the shell thermal efficiency was then estimated. Separate thermal equations for mobile homes, single-family residences, and multi-family residences are presented. Estimates of the relationship between winter electricity consumption for heating and the building's thermal shell efficiency are presented for each of the three building categories.

Moe, R.J.; Owzarski, S.L.; Streit, L.P.

1983-04-01T23:59:59.000Z

348

Buildings Energy Data Book: 8.1 Buildings Sector Water Consumption  

Buildings Energy Data Book (EERE)

1 1 Total Use of Water by Buildings (Million Gallons per Day) (1) Year 1985 1990 1995 2000 (2) 2005 (3) Note(s): Source(s): 1) Includes water from the public supply and self-supplied sources (e.g., wells) for residential and commercial sectors. 2) USGS did not estimate water use in the commercial and residential sectors for 2000. Estimates are based on available data and 1995 splits between domestic and commercial use. 3) USGS did not estimate commercial sector use for 2005. Estimated based on available data and commercial percentage in 1995. U.S. Geological Survey, Estimated Use of Water in the U.S. in 1985, U.S. Geological Survey Circular 1004, 1988; U.S. Geological Survey, Estimated Use of Water in the U.S. in 1990, U.S. Geological Survey Circular 1081, 1993; U.S. Geological Survey, Estimated Use of Water in the U.S. in 1995, U.S. Geological

349

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

E-Print Network (OSTI)

million Homes: Drivers and Outlook for Residential Energymillion Homes: Drivers and Outlook for Residential Energyconsumption, future outlook, end-use, bottom-up analysis

Zhou, Nan

2010-01-01T23:59:59.000Z

350

Modeling Energy Consumption of Residential Furnaces and Boilers in U.S. Homes  

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

24 24 Modeling Energy Consumption of Residential Furnaces and Boilers in U.S. Homes James Lutz, Camilla Dunham-Whitehead, Alex Lekov, and James McMahon Energy Analysis Department Environmental Energy Technologies Division Ernest Orlando Lawrence Berkeley National Laboratory University of California Berkeley, CA 94720 February 2004 This work was supported by the Office of Building Technologies and Community Systems of the U.S. Department of Energy, under Contract No. DE-AC03-76SF00098. ABSTRACT In 2001, DOE initiated a rulemaking process to consider whether to amend the existing energy efficiency standards for furnaces and boilers. A key factor in DOE's consideration of new standards is their cost-effectiveness to consumers. Determining cost-effectiveness requires an

351

Assessment of IP Addressable Microprocessor-Based Adjustable Speed Drives for Small Motors in the Residential Sector Applications  

Science Conference Proceedings (OSTI)

This technical update explores use of microprocessor-based adjustable speed drives (ASDs) used in the residential sector for small motor applications. It provides a detailed summary of the key players in the industry who are involved with the motor control design. It also provides insights about advantages of going from traditional motor control to embedded microprocessor-based electric motor drive systems. Finally, this technical updates describes the possibility of connecting these devices to the Inter...

2008-12-16T23:59:59.000Z

352

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

353

Econometric model of the joint production and consumption of residential space heat  

Science Conference Proceedings (OSTI)

This study models the production and comsumption of residential space heat, a nonmarket good. Production reflects capital investment decisions of households; consumption reflects final demand decisions given the existing capital stock. In the model, the production relationship is represented by a translog cost equation and an anergy factor share equation. Consumption is represented by a log-linear demand equation. This system of three equations - cost, fuel share, and final demand - is estimated simultaneously. Results are presented for two cross-sections of households surveyed in 1973 and 1981. Estimates of own-price and cross-price elasticities of factor demand are of the correct sign, and less than one in magnitude. The price elasticity of final demand is about -0.4; the income elasticity of final demand is less than 0.1. Short-run and long-run elasticities of demand for energy are about -0.3 and -0.6, respectively. These results suggest that price-induced decreases in the use of energy for space heat are attributable equally to changes in final demand and to energy conservation, the substitution of capital for energy in the production of space heat. The model is used to simulate the behavior of poor and nonpoor households during a period of rising energy prices. This simulation illustrates the greater impact of rising prices on poor households.

Klein, Y.L.

1985-12-01T23:59:59.000Z

354

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

355

Monitoring Electricity Consumption in the Tertiary Sector- A Project within the Intelligent Energy Europe Program  

E-Print Network (OSTI)

The electricity consumption in the tertiary sector in the EU is still increasing and a further increase is expected of more than 2 % per year during the next 15 years. This sector includes companies and institutions of public and private services with heterogeneous economic and energy-related characteristics. Building managers and decision-makers are not enough informed about the electricity consumption structure and electricity-saving potentials. Within the EU Intelligent Energy project EL-TERTIARY an overview of existing studies showed that the availability of disaggregated data on electricity consumption and its use by purpose (lighting, office equipment, ventilation, air conditioning, etc.) is poor. The methods of determining the types of end-uses are weak; most studies are based on calculations and estimations, only a few on measurement. In addition, many of the results are not published. EL-TERTIARY developed an internet-based methodology for monitoring electricity consumption. It was applied in more than 120 case studies in 12 EU countries. They cover various types of buildings: offices, schools, universities, kindergartens, hotels, supermarkets, and hospitals evaluating more than 900 technical systems. On the background of ongoing activities on EU level, such as directives, research and implementation projects the paper illustrates the concept of EL-TERTIARY, the newly developed methodology for the documentation of building audits and monitoring as well as selected results.

Plesser, S.; Fisch, M. N.; Gruber, E.; Schlomann, B.

2008-10-01T23:59:59.000Z

356

Residential sector end-use forecasting with EPRI-Reeps 2.1: Summary input assumptions and results  

SciTech Connect

This paper describes current and projected future energy use by end-use and fuel for the U.S. residential sector, and assesses which end-uses are growing most rapidly over time. The inputs to this forecast are based on a multi-year data compilation effort funded by the U.S. Department of Energy. We use the Electric Power Research Institute`s (EPRI`s) REEPS model, as reconfigured to reflect the latest end-use technology data. Residential primary energy use is expected to grow 0.3% per year between 1995 and 2010, while electricity demand is projected to grow at about 0.7% per year over this period. The number of households is expected to grow at about 0.8% per year, which implies that the overall primary energy intensity per household of the residential sector is declining, and the electricity intensity per household is remaining roughly constant over the forecast period. These relatively low growth rates are dependent on the assumed growth rate for miscellaneous electricity, which is the single largest contributor to demand growth in many recent forecasts.

Koomey, J.G.; Brown, R.E.; Richey, R. [and others

1995-12-01T23:59:59.000Z

357

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

E-Print Network (OSTI)

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

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

2012-01-01T23:59:59.000Z

358

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

E-Print Network (OSTI)

to predict blower motor electrical power consumption for thegives the blower motor electrical power consumption. BE =the blower motor electrical power consumption. The following

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

2004-01-01T23:59:59.000Z

359

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

E-Print Network (OSTI)

4 and 5, the distributions of electricity consumption among01 Figure 4 – Distribution of Electricity Consumption AmongSample Figure 5 - Distribution of Electricity Consumption

Kelsven, Phillip

2013-01-01T23:59:59.000Z

360

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

Note: This page contains sample records for the topic "residential sector 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

The impact of residential density on vehicle usage and fuel consumption  

E-Print Network (OSTI)

on vehicle usage and energy consumption. Journal of Urbanon vehicle usage and fuel consumption Jinwon Kim and Davidon vehicle usage and fuel consumption* Jinwon Kim and David

Kim, Jinwon; Brownstone, David

2010-01-01T23:59:59.000Z

362

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

363

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

E-Print Network (OSTI)

gas and electricity sectors of fully displacing biomass usagegas and electricity sectors of fully displacing biomass usage

Zhou, Nan

2010-01-01T23:59:59.000Z

364

Achieving real transparency : optimizing building energy ratings and disclosure in the U.S. residential sector  

E-Print Network (OSTI)

Residential energy efficiency in the U.S. has the potential to generate significant energy, carbon, and financial savings. Nonetheless, the market of home energy upgrades remains fragmented, and the number of homes being ...

Nadkarni, Nikhil S. (Nikhil Sunil)

2012-01-01T23:59:59.000Z

365

Potential Impact of Adopting Maximum Technologies as Minimum Efficiency Performance Standards in the U.S. Residential Sector  

E-Print Network (OSTI)

appliance_standards/residential/heating_p roducts_fr_appliance_standards/residential/cac_heatp umps_new_buildings/appliance_standards/residential/fb_tsd_09 07.html

Letschert, Virginie

2010-01-01T23:59:59.000Z

366

Application analysis of solar total energy systems to the residential sector. Volume IV, market penetration. Final report  

DOE Green Energy (OSTI)

This volume first describes the residential consumption of energy in each of the 11 STES regions by fuel type and end-use category. The current and projected costs and availability of fossil fuels and electricity for the STES regions are reported. Projections are made concerning residential building construction and the potential market for residential STES. The effects of STES ownership options, institutional constraints, and possible government actions on market penetration potential were considered. Capital costs for two types of STES were determined, those based on organic Rankine cycle (ORC) heat engines and those based on flat plate, water-cooled photovoltaic arrays. Both types of systems utilized parabolic trough collectors. The capital cost differential between conventional and STE systems was calculated on an incremental cost per dwelling unit for comparison with projected fuel savings in the market penetration analysis. The market penetration analysis was planned in two phases, a preliminary analysis of each of the geographical regions for each of the STE systems considered; and a final, more precise analysis of those regions and systems showing promise of significant market penetration. However, the preliminary analysis revealed no geographical regions in which any of the STES considered promised to be competitive with conventional energy systems using utility services at the prices projected for future energy supplies in the residential market. Because no promising situations were found, the analysis was directed toward an examination of the parameters involved in an effort to identify those factors which make a residential STES less attractive than similar systems in the commercial and industrial areas. Results are reported. (WHK)

Not Available

1979-07-01T23:59:59.000Z

367

AEO2011: Energy Consumption by Sector and Source - East North Central |  

Open Energy Info (EERE)

North Central North Central Dataset Summary Description http://en.openei.org/w/skins/openei/images/ui-bg_gloss_wave-medium_40_d6...); background-attachment: scroll; background-origin: initial; background-clip: initial; background-color: rgb(214, 235, 225); line-height: 17px; width: 650px; background-position: 50% 0%; background-repeat: repeat no-repeat; ">This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 3, and contains only the reference case. The dataset uses quadrillion btu. The data is broken down into residential, commercial, industrial, transportation, electric power and total energy consumption. Source EIA Date Released April 26th, 2011 (3 years ago)

368

Application analysis of solar total energy systems to the residential sector. Volume II, energy requirements. Final report  

DOE Green Energy (OSTI)

This project analyzed the application of solar total energy systems to appropriate segments of the residential sector and determined their market penetration potential. This volume covers the work done on energy requirements definition and includes the following: (1) identification of the single-family and multi-family market segments; (2) regionalization of the United States; (3) electrical and thermal load requirements, including time-dependent profiles; (4) effect of conservation measures on energy requirements; and (5) verification of simulated load data with real data.

Not Available

1979-07-01T23:59:59.000Z

369

Is Efficiency Enough? Towards a New Framework for Carbon Savings in the California Residential Sector  

E-Print Network (OSTI)

Lifestyle Approach to US Energy Use and the Related CO 21999 total site energy consumption of U.S. housing units by32 Figure 13. 1999 energy consumption of U.S. houses per

Moezzi, Mithra; Diamond, Rick

2005-01-01T23:59:59.000Z

370

Is Efficiency Enough? Towards a New Framework for Carbon Savings in the California Residential Sector  

E-Print Network (OSTI)

electricity consumption, but at a lower rate than for the United Stateselectricity consumption surpassed the rate of growth of housing units (32%) and of stateelectricity consumption and peak load growth rates were substantially lower than the observed growth rate in gross state

Moezzi, Mithra; Diamond, Rick

2005-01-01T23:59:59.000Z

371

AEO2011: Energy Consumption by Sector and Source - Pacific | OpenEI  

Open Energy Info (EERE)

Pacific Pacific Dataset Summary Description This dataset comes from the Electric Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This data reflects Table 9, and contains only the reference case. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Energy Consumption Pacific Data application/vnd.ms-excel icon AEO2011: Energy Consumption by Sector and Source - Pacific- Reference Case (xls, 297.5 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually Time Period 2008-2035 License License Open Data Commons Public Domain Dedication and Licence (PDDL) Comment Rate this dataset Usefulness of the metadata Average vote Your vote Usefulness of the dataset

372

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

E-Print Network (OSTI)

trends in residential space conditioning are affected byinto space heating, air conditioning, appliances, cookingSpace heating North Transition Ordinary efficient Highly efficient Incandescent Florescent CFL Air conditioning

Zhou, Nan

2010-01-01T23:59:59.000Z

373

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

E-Print Network (OSTI)

to Estimate Window % of Space Conditioning Use Original LBNLfactors to estimate space conditioning energy consumptionof Energy, in 2003 space conditioning in residential and

Apte, Joshua; Arasteh, Dariush

2008-01-01T23:59:59.000Z

374

Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 Residential Demand Module The NEMS Residential Demand Module projects future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the "unit energy consumption" (UEC) by appliance (in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type

375

Building-Integrated Photovoltaics (BIPV) in the Residential Sector: An Analysis of Installed Rooftop System Prices  

DOE Green Energy (OSTI)

For more than 30 years, there have been strong efforts to accelerate the deployment of solar-electric systems by developing photovoltaic (PV) products that are fully integrated with building materials. This report examines the status of building-integrated PV (BIPV), with a focus on the cost drivers of residential rooftop systems, and explores key opportunities and challenges in the marketplace.

James, T.; Goodrich, A.; Woodhouse, M.; Margolis, R.; Ong, S.

2011-11-01T23:59:59.000Z

376

Renewable energy options in Saudi Arabia: the economic viability of solar photovoltaics within the residential sector  

Science Conference Proceedings (OSTI)

Renewable energy options, including solar power, are becoming progressively more viable and thus increasingly pose challenges to conventional sources of energy, such as oil, coal and natural gas. Solar Photovoltaic technology is one type of solar energy ... Keywords: Saudi Arabia, feasibility study, renewable energy, residential buildings, solar photovoltaics

Yasser Al-Saleh; Hanan Taleb

2009-02-01T23:59:59.000Z

377

State energy price projections for the residential sector, 1991--1992  

Science Conference Proceedings (OSTI)

The purpose of this report is to provide projections of State-level residential prices for 1991 and 1992 for the following fuels: electricity, natural gas, heating oil, liquefied petroleum gas (LPG), kerosene, and coal. Prices for 1990 are also included for comparison purposes. This report also explains the methodology used to produce these estimates and the limitations. (VC)

Not Available

1991-11-08T23:59:59.000Z

378

Fuel Consumption - Energy Information Administration  

U.S. Energy Information Administration (EIA)

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

379

Buildings Energy Data Book: 8.1 Buildings Sector Water Consumption  

Buildings Energy Data Book (EERE)

1 Buildings Sector Water Consumption 1 Buildings Sector Water Consumption March 2012 8.1.2 Average Energy Intensity of Public Water Supplies by Location (kWh per Million Gallons) Location United States (2) 627 437 1,363 United States (3) 65 (6) 1,649 Northern California Indoor 111 1,272 1,911 Northern California Outdoor 111 1,272 0 Southern California Indoor (5) 111 1,272 1,911 Southern California Outdoor 111 1,272 0 Iowa (6) 380 1,570 Massachusetts (6) (6) 1,750 Wisconsin Class AB (4) - - Wisconsin Class C (4) - - Wisconsin Class D (4) - - Wisconsin Total (4) - - Note(s): Source(s): 836 3,263 Sourcing Treatment (1) Distribution Wastewater Total 2,230 2,295 2,117 5,411 2,117 3,500 - not included 1,850 9,727 13,021 9,727 11,110 2390 4,340 1,500 3,250 - not included 1,510 1) Treatment before delivery to customer. 2) Source: Electric Policy Research Institute (EPRI) 2009. Wastewater estimated based on EPRI

380

Strategies for Low Carbon Growth In India: Industry and Non Residential Sectors  

E-Print Network (OSTI)

area and pond - Reduced requirement of electrical power -Reduces electrical power consumption - Lower compressed airEnergy Management Cell Electrical Power Survey Energy Use

Sathaye, Jayant

2011-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "residential sector 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

The Impact of Residential Density on Vehicle Usage and Energy Consumption  

E-Print Network (OSTI)

Kenworthy (1989a). Gasoline consumption and cities. Journalon Vehicle Usage and Energy Consumption References Bento,Vehicle Usage and Energy Consumption UCI-ITS-WP-05-1 Thomas

Golob, Thomas F; Brownstone, David

2005-01-01T23:59:59.000Z

382

The Impact of Residential Density on Vehicle Usage and Energy Consumption  

E-Print Network (OSTI)

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

Golob, Thomas F; Brownstone, David

2005-01-01T23:59:59.000Z

383

1996-2004 Trends in the Single-Family Housing Market: Spatial Analysis of the Residential Sector  

SciTech Connect

This report provides a detailed geographic analysis of two specific topics affecting the residential sector. First, we performed an analysis of new construction market trends using annual building permit data. We report summarized tables and national maps to help illustrate market conditions. Second, we performed a detailed geographic analysis of the housing finance market. We analyzed mortgage application data to provide citable statistics and detailed geographic summarization of the residential housing picture in the US for each year in the 1996-2004 period. The databases were linked to geographic information system tools to provide various map series detailing the results geographically. Looking at these results geographically may suggest potential new markets for TD programs addressing the residential sector that have not been considered previously. For example, we show which lenders affect which regions and which income or mortgage product classes. These results also highlight the issue of housing affordability. Energy efficiency R&D programs focused on developing new technology for the residential sector must be conscious of the costs of products resulting from research that will eventually impact the home owner or new home buyer. Results indicate that home values as a proportion of median family income in Building America communities are closely aligned with the national average of home value as a proportion of median income. Other key findings: • The share of home building and home buying activity continues to rise steadily in the Hot-Dry and Hot-Humid climate zones, while the Mixed-Humid and Cold climate zone shares continue to decline. Other zones remain relatively stable in terms of share of housing activity. • The proportion of home buyers having three times the median family income for their geography has been steadily increasing during the study period. • Growth in the Hispanic/Latino population and to a lesser degree in the Asian population has translated into proportional increases in share of home purchasing by both groups. White home buyers continue to decline as a proportion all home buyers. • Low interest rate climate resulted in lenders moving back to conventional financing, as opposed to government-backed financing, for cases that would be harder to financing in higher rate environments. Government loan products are one mechanism for affecting energy efficiency gains in the residential sector. • The rate environment and concurrent deregulation of the finance industry resulted unprecedented merger and acquisition activity among financial institutions during the study period. This study conducted a thorough accounting of this merger activity to inform the market share analysis provided. • The home finance industry quartiles feature 5 lenders making up the first quartile of home purchase loans, 18 lenders making up the second quartile, 111 lenders making up the third quartile, and the remaining nearly 8,000 lenders make up the fourth quartile.

Anderson, Dave M.; Elliott, Douglas B.

2006-09-05T23:59:59.000Z

384

sector | OpenEI  

Open Energy Info (EERE)

sector sector Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 5, and contains only the reference case. The dataset uses quadrillion btu. The data is broken down into residential, commercial, industrial, transportation, electric power and total energy consumption. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Energy Consumption sector South Atlantic Data application/vnd.ms-excel icon AEO2011: Energy Consumption by Sector and Source - South Atlantic- Reference Case (xls, 297.6 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually

385

Comparative Attitudes Toward Utility Type Services: Tracking Perceptions in the Residential Sector  

Science Conference Proceedings (OSTI)

This report is the first in a series of three EPRIsolutions research reports tracking customer perceptions toward five utility providers (electric, natural gas, cable TV, long distance telephone and local telephone), and comparing the performance trends ratings among these different utility companies over time. This particular market assessment focuses on the attitudes of the Residential segment. The next two reports will assess customer attitudes for the large business and mass market segments. The Unde...

2000-10-31T23:59:59.000Z

386

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

Renewables Natural Gas Petroleum Coal Hydro. Other Total Nuclear Total (quad) 1980 41% 12% 28% 7% 6% 13% 6% 14.84 1981 40% 10% 29% 6% 6% 13% 7% 14.51 1982 39% 9% 30% 8% 7% 14% 7% 14.95 1983 37% 9% 31% 8% 7% 15% 8% 14.86 1984 37% 10% 31% 7% 7% 14% 8% 15.49 1985 36% 10% 32% 6% 7% 13% 9% 15.69 1986 34% 10% 32% 7% 6% 13% 10% 15.47 1987 34% 10% 33% 6% 6% 12% 10% 15.82 1988 34% 10% 33% 5% 6% 11% 12% 16.62 1989 35% 10% 32% 6% 7% 12% 11% 17.24 1990 34% 8% 34% 6% 5% 11% 13% 16.54 1991 34% 8% 33% 6% 5% 11% 13% 17.03 1992 35% 8% 33% 5% 6% 11% 13% 17.05 1993 35% 8% 34% 6% 5% 11% 12% 17.89 1994 35% 8% 33% 5% 5% 10% 13% 17.79 1995 35% 8% 33% 6% 5% 11% 13% 18.31 1996 35% 8% 33% 6% 5% 11% 13% 19.27 1997 35% 8% 35% 7% 4% 11% 12% 18.71 1998 34% 7% 36% 6% 4% 10% 13% 18.57 1999 34% 8% 35% 6% 4% 10% 14% 19.20 2000 34% 8% 35% 5% 4% 9% 14% 20.06 2001 35% 8% 35% 4% 4% 7% 14% 19.65 2002 34% 7% 35% 5% 4% 8% 14% 20.52 2003 34% 7% 36% 5% 4% 9% 14% 20.75 2004 34% 8% 36% 5% 4% 8% 14% 20.76 2005 34% 7% 36%

387

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

Electricity Growth Rate Natural Gas Petroleum (1) Coal Renewable(2) Sales Losses Total TOTAL (2) 2010-Year 1980 4.79 30% 1.72 11% 0.03 0% 0.85 5% 2.45 5.89 8.33 53% 15.72 100% - 1981 4.57 30% 1.52 10% 0.03 0% 0.87 6% 2.46 5.77 8.24 54% 15.23 100% - 1982 4.68 30% 1.42 9% 0.03 0% 0.97 6% 2.49 5.89 8.38 54% 15.48 100% - 1983 4.45 29% 1.33 9% 0.03 0% 0.97 6% 2.56 6.03 8.59 56% 15.38 100% - 1984 4.64 29% 1.51 10% 0.04 0% 0.98 6% 2.66 6.07 8.73 55% 15.90 100% - 1985 4.51 28% 1.55 10% 0.04 0% 1.01 6% 2.71 6.21 8.92 56% 16.02 100% - 1986 4.38 28% 1.52 10% 0.04 0% 0.92 6% 2.79 6.27 9.07 57% 15.94 100% - 1987 4.40 27% 1.60 10% 0.04 0% 0.85 5% 2.90 6.42 9.32 58% 16.21 100% - 1988 4.72 28% 1.66 10% 0.04 0% 0.91 5% 3.05 6.75 9.79 57% 17.12 100% - 1989 4.88 28% 1.64 9% 0.03 0% 0.97 5% 3.09 7.13 10.22 58% 17.76 100% - 1990 4.47 26% 1.37 8% 0.03 0% 0.64 4% 3.15 7.24 10.39 61% 16.91 100% - 1991 4.64 27% 1.36 8% 0.03 0% 0.67 4% 3.26 7.42 10.68 61% 17.37 100%

388

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

6 6 Annual Cost Active Idle Off Active Idle Off ($) (2) Kitchen Coffee Maker 1,000 70 0 38 229 8,493 58 5.6 Dishwasher (3) 365 (4) 120 11.6 Microwave Oven 1,500 3 70 8,690 131 12.6 Toaster Oven 1,051 37 54 5.2 Refrigerator-Freezer 660 63.1 Freezer 470 45.0 Lighting 18-W Compact Fluorescent 18 1,189 20 2.1 60-W Incandescent Lamp 60 672 40 3.9 100-W Incandescent Lamp 100 672 70 6.4 Torchiere Lamp-Halogen 300 1,460 440 42.0 Bedroom and Bathroom Hair Dryer 710 50 40 3.4 Waterbed Heater 350 3,051 1,070 102.7 Laundry Room Clothes Dryer 359 (4) 1,000 96.0 Clothes Washer (3) 392 (4) 110 (3) 10.4 Home Electronics Desktop PCs 75 4 2 2,990 330 5,440 237 22.8 Notebook PCs 25 2 2 2,368 935 5,457 72 6.9 Desktop Computer Monitors 42 1 1 1,865 875 6,020 85 8.2 Stereo Systems 33 30 3 1,510 1,810 5,440 119 11.4 Televisions 97 4 1,860 6,900 222 (7) 21.3 Analog, <40" 86 1,095 (5) 184 17.7 Analog, >40"

389

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

3 3 Growth Rate Wood Solar Thermal Solar PV GSHP Total 2010-Year 1980 0.846 0.000 N.A. 0.000 0.846 - 1981 0.873 0.000 N.A. 0.000 0.873 - 1982 0.971 0.000 N.A. 0.000 0.971 - 1983 0.970 0.000 N.A. 0.000 0.970 - 1984 0.980 0.000 N.A. 0.000 0.980 - 1985 1.010 0.000 N.A. 0.000 1.010 - 1986 0.920 0.000 N.A. 0.000 0.920 - 1987 0.853 0.000 N.A. 0.000 0.853 - 1988 0.910 0.000 N.A. 0.000 0.910 - 1989 0.920 0.052 N.A. 0.005 0.977 - 1990 0.582 0.056 N.A. 0.006 0.643 - 1991 0.610 0.057 N.A. 0.006 0.673 - 1992 0.640 0.059 N.A. 0.006 0.706 - 1993 0.548 0.061 N.A. 0.007 0.616 - 1994 0.520 0.063 N.A. 0.006 0.589 - 1995 0.520 0.064 N.A. 0.007 0.591 - 1996 0.540 0.065 N.A. 0.007 0.612 - 1997 0.428 0.064 N.A. 0.007 0.499 - 1998 0.380 0.064 N.A. 0.008 0.452 - 1999 0.400 0.063 N.A. 0.009 0.471 - 2000 0.430 0.060 N.A. 0.009 0.499 - 2001 0.374 0.059 N.A. 0.009 0.442 - 2002 0.380 0.057 N.A. 0.010 0.448 - 2003 0.400 0.057 N.A. 0.013 0.470 -

390

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

by Fuel and Region (Million BtuHousehold) Region Electricity Natural Gas Fuel Oil Total Northeast 21.2 34.9 36.2 54.7 Midwest 16.6 36.6 N.A. 51.8 South 39.4 20.0 N.A....

391

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

Buildings, by Fuel and Region (Thousand BtuSF) Region Electricity Natural Gas Fuel Oil Total Northeast 27.7 45.9 39.9 71.5 Midwest 22.5 49.9 N.A. 70.3 South 53.5 27.9 N.A....

392

Table 2.1b Residential Sector Energy Consumption Estimates, 1949 ...  

U.S. Energy Information Administration (EIA)

6 Solar thermal direct use energy, and photovoltaic (PV) electricity net generation (converted to Btu ... Includes small amounts of distributed solar thermal and PV

393

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

4,622 3,903 72,095 24,853 6,367 4,930 8,216 85,241 24,032 5,238 4,930 9,448 Furnaces Water Heaters Ranges Clothes Dryers Fireplaces million Btu million Btu million Btu million...

394

Buildings Energy Data Book: 8.2 Residential Sector Water Consumption  

Buildings Energy Data Book (EERE)

4 Per Capita Use of Hot Water in Single Family Homes by End Use (Gallons per Capita per Day) (1) FixtureEnd Use Toilet 0.0 0.0 0.0% 0.0% Clothes Washer 3.9 10.1 15.5% 27.8% Shower...

395

Buildings Energy Data Book: 8.2 Residential Sector Water Consumption  

Buildings Energy Data Book (EERE)

3 2004 Water Use in Multi-Family Housing Units, In-Rent and Submetered Billing (Gallons per Unit per Day) In-Rent Indoor Water Use 143 121 15.3% Note(s): Source(s): Based on a...

396

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

West National Space Heating 70.3 56.6 20.4 23.8 38.7 Space Cooling 3.6 5.6 13.9 4.0 7.9 Water Heating 21.1 20.4 15.8 21.2 19.0 Refrigerator 5.4 7.0 6.6 5.7 6.3 Other Appliances &...

397

Buildings Energy Data Book: 8.2 Residential Sector Water Consumption  

Buildings Energy Data Book (EERE)

5 2010 Community Water Systems by Size and Type System Size (1) Less than 500 4.9 501 - 3,300 20.1 3,301 - 10,000 28.6 10,001 - 100,000 108.5 More than 100,000 138.1 Total 300.2...

398

Relations between Temperature and Residential Natural Gas Consumption in the Central and Eastern United States  

Science Conference Proceedings (OSTI)

The increased U.S. natural gas price volatility since the mid-to-late-1980s deregulation generally is attributed to the deregulated market being more sensitive to temperature-related residential demand. This study therefore quantifies relations ...

Reed P. Timmer; Peter J. Lamb

2007-11-01T23:59:59.000Z

399

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

400

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)...

Note: This page contains sample records for the topic "residential sector 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

Potential Impact of Adopting Maximum Technologies as Minimum Efficiency Performance Standards in the U.S. Residential Sector  

E-Print Network (OSTI)

buildings/appliance_standards/residential/cac_heatp umps_buildings/appliance_standards/residential/fb_tsd_09 07.htmlof Energy Efficiency Standards and Labeling Programs, LBNL

Letschert, Virginie

2010-01-01T23:59:59.000Z

402

State energy price projections for the residential sector, 1990--1991  

Science Conference Proceedings (OSTI)

This report was prepared by the Energy Information Administration, Office of Energy Markets and End Use. This service report was developed in response to a request from the Family Support Administration of the US Department of Health and Human Services. Forecasts of State-level residential energy prices for 1990 and 1991 were required as input for the Low-Income Home Energy Assistance Program. This program allocates funds to the States to provide assistance to low-income households in meeting energy cost. (VC)

Not Available

1991-01-18T23:59:59.000Z

403

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

404

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

E-Print Network (OSTI)

appliance, lighting, and heating and cooling usage in theseusage in rural households. Primary Energy Consumption (EJ) Appliance Cooking lighting

Zhou, Nan

2010-01-01T23:59:59.000Z

405

Improving the Energy Efficiency of Residential Buildings | Department of  

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

Residential Buildings Residential Buildings Improving the Energy Efficiency of Residential Buildings Visitors Tour Solar Decathlon Homes Featuring the Latest in Energy Efficient Building Technology. Learn More Visitors Tour Solar Decathlon Homes Featuring the Latest in Energy Efficient Building Technology. Learn More The Building Technologies Office (BTO) collaborates with the residential building industry to improve the energy efficiency of both new and existing homes. By developing, demonstrating, and deploying cost-effective solutions, BTO strives to reduce energy consumption across the residential building sector by at least 50%. Research and Development Conduct research that focuses on engineering solutions to design, test, and

406

Residential Buildings  

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

Residential Residential Residential Buildings Residential buildings-such as single family homes, townhomes, condominiums, and apartment buildings-are all covered by the Residential Energy Consumption Survey (RECS). See the RECS home page for further information. However, buildings that offer multiple accomodations such as hotels, motels, inns, dormitories, fraternities, sororities, convents, monasteries, and nursing homes, residential care facilities are considered commercial buildings and are categorized in the CBECS as lodging. Specific questions may be directed to: Joelle Michaels joelle.michaels@eia.doe.gov CBECS Manager Release date: January 21, 2003 Page last modified: May 5, 2009 10:18 AM http://www.eia.gov/consumption/commercial/data/archive/cbecs/pba99/residential.html

407

2001 Residential Energy Consumption Survey Form EIA-457C (2001)--Rental Agents, Landlords, and Apartment Managers Questionnaire  

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

Form EIA-457C (2001)--Rental Agents, Landlords, and Apartment Managers Questionnaire OMB No. 1905-0092, Expiring March 31, 200X i U.S. Department of Energy Energy Information Administration 2001 Residential Energy Consumption Survey Rental Agents, Landlords, and Apartment Managers Questionnaire INTRODUCTION TO INTERVIEW Hello, I am __________________________ from Roper Starch Worldwide Inc., a social science research firm. We are conducting a study for the U.S. Department of Energy about energy consumption in homes. Although your participation is voluntary, we hope you will participate in this important study of energy usage. Your identity and all the responses you give me will be kept strictly confidential. The survey will take about 15 minutes.

408

Behaviour Oriented Optimisation Strategies for Energy Efficiency in the Residential Sector  

E-Print Network (OSTI)

The aim of this paper is to combine the approaches of engineering and sociology in the assessment of behavioural influences on the energy demand of residential buildings and to define a common language and strategy for their description. For this purpose the calculation methods of the German Energy Conservation Regulations (EnEV 2007) further defined in the DIN 4108-6: 2003-06 will be evaluated to illustrate the relevant linkages to behavioural approaches. So far, there are few attempts to differentiate the large influence of individual behaviour (see Richter 2003, Loga 2003). The assessment of these values and their behavioural implications require a sociological approach towards energy relevant practices. Based on the calculation of the building’s energy balance an analytical framework will be suggested to link the heat demand with the lifestyles of consumers.

Koch, A.; Huber, A.; Avci, N.

2008-10-01T23:59:59.000Z

409

Energy consumption and usage characteristics from field measurements of residential dishwashers, clothes washers and clothes dryers  

SciTech Connect

The measured energy consumption and usage characteristics for household dishwashers, clothes washers, and clothes dryers for ten townhouses at Twin Rivers, N.J., are presented. Whenever the dishwashers and/or clothes washers were in use, the energy consumption, water consumption, frequency of usage, and water temperature were measured by a data acquisition system. The electrical energy of electric clothes dryers and the gas consumption of gas clothes dryers were measured, as well as their frequency and duration of use, and exhaust temperature. Typical household usage patterns of these major appliances are included.

Chang, Y.L.; Grot, R.A.

1980-10-01T23:59:59.000Z

410

The dubuque electricity portal: evaluation of a city-scale residential electricity consumption feedback system  

Science Conference Proceedings (OSTI)

This paper describes the Dubuque Electricity Portal, a city-scale system aimed at supporting voluntary reductions of electricity consumption. The Portal provided each household with fine-grained feedback on its electricity use, as well as using incentives, ... Keywords: behavior change, consumption feedback systems, ecf, electricity, smart meters, social comparison, sustainability

Thomas Erickson; Ming Li; Younghun Kim; Ajay Deshpande; Sambit Sahu; Tian Chao; Piyawadee Sukaviriya; Milind Naphade

2013-04-01T23:59:59.000Z

411

The dubuque water portal: evaluation of the uptake, use and impact of residential water consumption feedback  

Science Conference Proceedings (OSTI)

The Dubuque Water Portal is a system aimed at supporting voluntary reductions of water consumption that is intended to be deployed city-wide. It provides each household with fine-grained, near real time feedback on their water consumption, as well as ... Keywords: behavior change, games, smart meters, social comparison, sustainability, water, water and energy feedback systems

Thomas Erickson; Mark Podlaseck; Sambit Sahu; Jing D. Dai; Tian Chao; Milind Naphade

2012-05-01T23:59:59.000Z

412

Fuel consumption: industrial, residential, and general studies. Volume 2. 1977-October, 1979 (a bibliography with abstracts). Report for 1977-October 1979  

SciTech Connect

Citations of research on fuel supply, demand, shortages, and conservation through effective utilization are presented. A few abstracts pertain to energy consumption in the agricultural sector, fuel substitution, economic studies, and environmental concerns relating to energy consumption. Bibliographies on electric power consumption and fuel consumption by transportation also are available. (This updated bibliography contains 159 abstracts, 29 of which are new entries to the previous edition.)

Hundemann, A.S.

1979-11-01T23:59:59.000Z

413

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

E-Print Network (OSTI)

is standard in HVAC design and fan selection books 6 . Theof modulating design options. The cooling fan curve passesfan curve and the duct system curve. We calculated the furnace fuel consumption for each design

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

2004-01-01T23:59:59.000Z

414

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

E-Print Network (OSTI)

adding thermal insulation to buildings and i m p r o v i n grespect to insulation for residential buildings, the reportbuildings; these calculations include fluorocarbon emissions from thermal insulation

2006-01-01T23:59:59.000Z

415

Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption  

Buildings Energy Data Book (EERE)

U.S. Residential and Commercial Buildings Total Primary Energy Consumption (Quadrillion Btu and Percent of Total) Electricity Growth Rate Natural Gas Petroleum (1) Coal Renewable(2) Sales Losses Total TOTAL (2) 2010-Year 1980 7.42 28.2% 3.04 11.5% 0.15 0.6% 0.87 3.3% 4.35 10.47 14.82 56.4% 26.29 100% - 1981 7.11 27.5% 2.63 10.2% 0.17 0.6% 0.89 3.5% 4.50 10.54 15.03 58.2% 25.84 100% - 1982 7.32 27.8% 2.45 9.3% 0.19 0.7% 0.99 3.8% 4.57 10.80 15.37 58.4% 26.31 100% - 1983 6.93 26.4% 2.50 9.5% 0.19 0.7% 0.99 3.8% 4.68 11.01 15.68 59.6% 26.30 100% - 1984 7.20 26.4% 2.74 10.0% 0.21 0.8% 1.00 3.7% 4.93 11.24 16.17 59.2% 27.31 100% - 1985 6.98 25.4% 2.62 9.5% 0.18 0.6% 1.03 3.8% 5.06 11.59 16.65 60.6% 27.47 100% - 1986 6.74 24.5% 2.68 9.7% 0.18 0.6% 0.95 3.4% 5.23 11.75 16.98 61.7% 27.52 100% - 1987 6.87 24.4% 2.73 9.7% 0.17 0.6% 0.88 3.1% 5.44 12.04 17.48 62.2% 28.13 100% - 1988 7.44 25.0%

416

Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption  

Buildings Energy Data Book (EERE)

2 2 Buildings Share of U.S. Petroleum Consumption (Million Barrels per Day) Buildings Residential Commercial Total Industry Transportation Total 1980 2.62 2.01 l 4.63 10.55 19.01 34.19 1981 2.26 1.73 l 3.98 9.13 18.81 31.93 1982 1.96 1.49 l 3.45 8.35 18.42 30.23 1983 1.87 1.61 l 3.48 7.97 18.60 30.05 1984 1.95 1.60 l 3.55 8.48 19.02 31.05 1985 1.92 1.40 l 3.32 8.13 19.47 30.92 1986 2.03 1.60 l 3.62 8.39 20.18 32.20 1987 2.04 1.51 l 3.54 8.50 20.82 32.86 1988 2.20 1.57 l 3.77 8.88 21.57 34.22 1989 2.23 1.56 l 3.79 8.71 21.71 34.21 1990 1.81 1.38 l 3.20 8.73 21.63 33.55 1991 1.77 1.30 l 3.07 8.40 21.38 32.85 1992 1.73 1.19 l 2.92 8.93 21.68 33.52 1993 1.81 1.16 l 2.97 8.80 22.07 33.84 1994 1.75 1.15 l 2.90 9.16 22.61 34.67 1995 1.61 1.00 l 2.62 8.87 23.07 34.56 1996 1.74 1.04 l 2.78 9.33 23.65 35.76 1997 1.71 1.04 l 2.75 9.60 23.92 36.27 1998 1.73 1.13 l 2.86 9.54 24.54 36.93 1999 1.85 1.10 l 2.96 9.78 25.22 37.96

417

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...

418

EIA - International Energy Outlook 2007-Energy Consumption by End-Use  

Gasoline and Diesel Fuel Update (EIA)

Energy Consumption by End Use Sector Energy Consumption by End Use Sector International Energy Outlook 2007 Figure 25. OECD and Non-OECD Transportation Sector Delivered Energy Consumption, 2004-2030 Figure 25 Data. Need help, contact the National Energy Information Center at 202-586-8800. Figure 26. OECD and Non-OECD Residential Sector Delivered Energy Consumption, 2004-2030 Figure 26 Data. Need help, contact the National Energy Information Center at 202-586-8800. Figure 27. Growth in OECD and Non-OECD Residential Sector Delivered Energy Consumption by Fuel, 2004 and 2030 Figure 27 Data. Need help, contact the National Energy Information Center at 202-586-8800. Figure 28. OECD and Non-OECD Commercial Sector Delivered Energy Consumption, 2004-2030 Figure 28 Data. Need help, contact the National Energy Information Center at 202-586-8800.

419

Window-Related Energy Consumption in the US Residential andCommercial Building Stock  

SciTech Connect

We present a simple spreadsheet-based tool for estimating window-related energy consumption in the United States. Using available data on the properties of the installed US window stock, we estimate that windows are responsible for 2.15 quadrillion Btu (Quads) of heating energy consumption and 1.48 Quads of cooling energy consumption annually. We develop estimates of average U-factor and SHGC for current window sales. We estimate that a complete replacement of the installed window stock with these products would result in energy savings of approximately 1.2 quads. We demonstrate that future window technologies offer energy savings potentials of up to 3.9 Quads.

Apte, Joshua; Arasteh, Dariush

2006-06-16T23:59:59.000Z

420

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

E-Print Network (OSTI)

2004, "Household Energy Consumption Reported o n A National2006, "Household Energy consumption Reported i n a Nationalconsumption for different uses i n housing and energy usage analysis based on national

2006-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "residential sector 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

Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption  

Buildings Energy Data Book (EERE)

8 Commercial Delivered Energy Consumption Intensities, by Vintage Consumption per Year Constructed Square Foot (thousand BtuSF) Prior to 1960 84.4 23% 1960 to 1969 91.5 12% 1970...

422

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

E-Print Network (OSTI)

consumed. Total energy consumption for hotels and hospitalshotels and hospitals, by contrast, the hot-water supply accounts for the majority o f total energyenergy consumption ratio per certain floor area is larger for hotels,

2006-01-01T23:59:59.000Z

423

Miscellaneous Electricity Services in the Buildings Sector (released in AEO2007)  

Reports and Publications (EIA)

Residential and commercial electricity consumption for miscellaneous services has grown significantly in recent years and currently accounts for more electricity use than any single major end-use service in either sector (including space heating, space cooling, water heating, and lighting). In the residential sector, a proliferation of consumer electronics and information technology equipment has driven much of the growth. In the commercial sector, telecommunications and network equipment and new advances in medical imaging have contributed to recent growth in miscellaneous electricity use

Information Center

2007-03-11T23:59:59.000Z

424

Burlington Electric Department - Residential Energy Efficiency...  

Open Energy Info (EERE)

Sector Residential Eligible Technologies Clothes Washers, Lighting, Water Heaters, LED Lighting, Tankless Water Heaters Active Incentive Yes Implementing Sector Utility...

425

South Alabama Electric Cooperative - Residential Energy Efficiency...  

Open Energy Info (EERE)

Sector Residential Eligible Technologies Building Insulation, Doors, Heat pumps, Windows, Geothermal Heat Pumps Active Incentive Yes Implementing Sector Utility Energy...

426

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

E-Print Network (OSTI)

alternative furnaces used in each house required derivation of the heating and coolingalternative efficiency levels and design options to meet the same heating and coolingand cooling loads of each sample house are known, it is possible to estimate what the energy consumption of alternative (

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

2004-01-01T23:59:59.000Z

427

Regression analysis of residential air-conditioning energy consumption at Dhahran, Saudi Arabia  

Science Conference Proceedings (OSTI)

The energy consumption of a house air conditioner located at Dhahran, Saudi Arabia, is modeled as a function of weather parameters and total (global) solar radiation on a horizontal surface. The selection of effective parameters that significantly influence energy consumption is carried out using general stepping regression methods. The problem of collinearity between the regressors is also investigated. The final model involves parameters of total solar radiation on a horizontal surface, wind speed, and temperature difference between the indoor and outdoor condition. However, the model coefficients are functions of relative humidity and/or temperature difference between the indoor and outdoor condition. Model adequacy is examined by the residual analysis technique. Model validation is carried out by the data-splitting technique. The sensitivity of the model indicates that relative humidity and temperature difference strongly influence the cooling energy consumption. It was found that an increase in relative humidity from 20% to 100% can cause a 100% increase in cooling energy consumption during the high cooling season.

Abdel-Nabi, D.Y.; Zubair, S.M.; Abdelrahman, M.A.; Bahel, V. (Energy Systems Group, Div. of Energy Resources, Research Inst., King Fahd Univ. of Petroleum and Minerals, Dhahran (SA))

1990-01-01T23:59:59.000Z

428

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

429

Sensor-based physical interactions as interventions for change in residential energy consumption  

Science Conference Proceedings (OSTI)

Interventions for behavior change in domestic energy consumption rely critically on energy usage data. To obtain this data, collection systems must be established. Pervasive sensing systems enable such monitoring, but populating homes with sensors is ... Keywords: just in time motivations, physical data interfaces, sensor networks, ubiquitous computing

Mailyn Fidler; Sharon Tan; Samar Alqatari; Nishant Bhansali; Alex Chang; Mia Davis; Eric Kofman; Krystal Lee; Phounsouk Sivilay; Marilyn Cornelius; Brendan Wypich; Banny Banerjee

2012-05-01T23:59:59.000Z

430

Residential energy consumption across different population groups: Comparative analysis for Latino and non-Latino households in U.S.A.  

SciTech Connect

Residential energy cost, an important part of the household budget, varies significantly across different population groups. In the United States, researchers have conducted many studies of household fuel consumption by fuel type -- electricity, natural gas, fuel oil, and liquefied petroleum gas (LPG) -- and by geographic areas. The results of past research have also demonstrated significant variation in residential energy use across various population groups, including white, black, and Latino. However, research shows that residential energy demand by fuel type for Latinos, the fastest-growing population group in the United States, has not been explained by economic and noneconomic factors in any available statistical model. This paper presents a discussion of energy demand and expenditure patterns for Latino and non-Latino households in the United States. The statistical model developed to explain fuel consumption and expenditures for Latino households is based on Stone and Geary`s linear expenditure system model. For comparison, the authors also developed models for energy consumption in non-Latino, black, and nonblack households. These models estimate consumption of and expenditures for electricity, natural gas, fuel oil, and LPG by various households at the national level. The study revealed significant variations in the patterns of fuel consumption for Latinos and non-Latinos. The model methodology and results of this research should be useful to energy policymakers in government and industry, researchers, and academicians who are concerned with economic and energy issues related to various population groups.

Poyer, D.A.; Teotia, A.P.S. [Argonne National Lab., IL (United States); Henderson, L. [Univ. of Baltimore, MD (United States)

1998-05-01T23:59:59.000Z

431

The impact of thermostat performance on energy consumption and occupant comfort in residential electric heating systems  

SciTech Connect

A digital computer simulation was used to compare the energy consumption and comfort of an electric baseboard heating system using high performance thermostats (low droop, fast cycling) to that of the same system using poorer performing thermostats (high droop, slow cycling, such as many line voltage types). Since a thermostat which allows the controlled temperature to fall below the setpoint will obviously cause less energy consumption than a thermostat which maintains the controlled temperature closer to the setpoint, the key hypothesis of this study was that the user will reset the thermostat setpoint in some fashion during the heating season to obtain acceptable conditions for all heating loads. The major assumption of this study, therefore, was the mode of this ''user-thermostat interaction''. For every case in which the simulated ''user'' could intervene, the energy consumption using high performance thermostats was found to be less, while a greater degree of comfort was maintained, than systems using poorer performing thermostats. Energy savings ranged from 2% to 18% depending upon the mode of user interaction simulated. Where energy savings were small, the ''user'' was resetting the poorly performing thermostat as often as twice a day; i.e., the ''user'' was performing the function of a better performing thermostat.

Benton, R.

1982-01-01T23:59:59.000Z

432

Table 2.1c Commercial Sector Energy Consumption Estimates, 1949 ...  

U.S. Energy Information Administration (EIA)

1 See "Primary Energy Consumption" in Glossary. 9 Wind electricity net generation (converted to Btu using the fossil-fuels heat rate—see Table A6).

433

Table C10. Energy Consumption by End-Use Sector, Ranked by ...  

U.S. Energy Information Administration (EIA)

R A N K I N G S. Title: All Consumption Tables.vp Author: KSM Created Date: 6/27/2013 12:52:48 PM ...

434

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

E-Print Network (OSTI)

usage and analysis o f operations data to enable effective management o f lighting andlighting Rated powe consumption and standby power consumptio: . ofrelevantequipment Usage

2006-01-01T23:59:59.000Z

435

Table 2.1f Electric Power Sector Energy Consumption, 1949-2011 ...  

U.S. Energy Information Administration (EIA)

1 See "Primary Energy Consumption" in Glossary. 9 Wind electricity net generation (converted to Btu using the fossil-fuels heat rate—see Table A6).

436

Residential energy-consumption analysis utilizing the DOE-1 computer program  

SciTech Connect

The DOE-1 computer program is used to examine energy consumption in a typical middle-class household in Cincinnati, Ohio. The program is used to compare energy consumption under different structural and environmental conditions, including various levels of insulation in the walls and ceiling, double and single glazing of windows, and thermostat setback schedules. In addition, the DOE-1 program is used to model the house under three energy distribution systems: a unit heater, a single-zone fan system with optional subzone reheat; and a unitary heat pump. A plant equipment simulation is performed to model the heating and cooling plant currently installed in the house. A simple economic analysis of life-cycle costs for the house is done utilizing the economic simulation portion of DOE-1. Utility bills over the past six years are analyzed to gain an actual energy-use profile for the house to compare with computer results. Results indicate that a 35% savings in heating load may be obtained with addition of proper amounts of insulation as compared with the house with no insulation. The installation of double glazing on windows may save close to 6% on heating load. Thermostat setbacks may result in savings of around 25% on energy consumed for heating. Similar results are achieved with regard to cooling load. Comparison of actual energy consumed by the household (from utility bills) with the computer results shows a 4.25% difference in values between the two. This small percent difference certainly strengthens the case for future use of computer programs in comparing construction alternatives and predicting building energy consumption.

Arentsen, S K

1979-04-01T23:59:59.000Z

437

Dynamic Simulation and Analysis of Factors Impacting the Energy Consumption of Residential Buildings  

E-Print Network (OSTI)

Buildings have a close relationship with climate. There are a lot of important factors that influence building energy consumption such as building shape coefficient, insulation work of building envelope, covered area, and the area ratio of window to wall. The integrated influence result will be different when the building is in different climate zone. This paper studies the variation rule of some aggregative indicators and building energy efficiency rates by simulation and analysis of the same building in different climate zones by eQuest, in order to determine how building energy efficiency works in different climate zones.

Lian, Y.; Hao, Y.

2006-01-01T23:59:59.000Z

438

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

E-Print Network (OSTI)

A comparison of national energy consumption by fuel typeenergy consumption in homes under differing assumptions, scenarios, and policies. At the national

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

439

Potential Impact of Adopting Maximum Technologies as Minimum Efficiency Performance Standards in the U.S. Residential Sector  

E-Print Network (OSTI)

Gas and LPG consumption by 2030 The methodology results inin natural gas consumption by 2030 resulting from upcomingthe 2008- 2013 trend to 2030. Based on these assumptions,

Letschert, Virginie

2010-01-01T23:59:59.000Z

440

Table 10.2c Renewable Energy Consumption: Electric Power Sector ...  

U.S. Energy Information Administration (EIA)

3 Solar thermal and photovoltaic (PV) electricity net generation (converted to Btu using the fossil-fuels heat rate-see Table A6). Notes: - The electric power sector ...

Note: This page contains sample records for the topic "residential sector 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

Energy efficiency standards for residential and commercial equipment: Additional opportunities  

E-Print Network (OSTI)

Savings in the Residential and Commercial Sectors with High Efficiency Electric Motors. ”Savings in the Residential and Commercial Sectors with High Efficiency Electric Motors. ”Savings in the Residential and Commercial Sectors with High Efficiency Electric Motors. ”

Rosenquist, Greg; McNeil, Michael; Iyer, Maithili; Meyers, Steve; McMahon, Jim

2004-01-01T23:59:59.000Z

442

Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption  

Buildings Energy Data Book (EERE)

1 2003 Commercial Delivered Energy Consumption Intensities, by Ownership of Unit (1) Ownership Nongovernment Owned 85.1 72% Owner-Occupied 87.3 35% Nonowner-Occupied 88.4 36%...

443

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

E-Print Network (OSTI)

Development of a Residential Forecasting Database. Lawrenceand Methodology for End-Use Forecasting with EPRI-REEPS 2.1.and Methodology for End-Use Forecasting with EPRI-REEPS 2.1.

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

444

Residential/commercial market for energy technologies  

SciTech Connect

The residential/commercial market sector, particularly as it relates to energy technologies, is described. Buildings account for about 25% of the total energy consumed in the US. Market response to energy technologies is influenced by several considerations. Some considerations discussed are: industry characteristics; market sectors; energy-consumption characeristics; industry forecasts; and market influences. Market acceptance may be slow or nonexistent, the technology may have little impact on energy consumption, and redesign or modification may be necessary to overcome belatedly perceived market barriers. 7 figures, 20 tables.

Glesk, M.M.

1979-08-01T23:59:59.000Z

445

Residential | OpenEI  

Open Energy Info (EERE)

Residential Residential 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 (7 months ago) Date Updated July 02nd, 2013 (5 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

446

Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption  

Buildings Energy Data Book (EERE)

3 3 Commercial Delivered and Primary Energy Consumption Intensities, by Year Percent Delivered Energy Consumption Primary Energy Consumption Floorspace Post-2000 Total Consumption per Total Consumption per (million SF) Floorspace (1) (10^15 Btu) SF (thousand Btu/SF) (10^15 Btu) SF (thousand Btu/SF) 1980 50.9 N.A. 5.99 117.7 10.57 207.7 1990 64.3 N.A. 6.74 104.8 13.30 207.0 2000 (2) 68.5 N.A. 8.20 119.7 17.15 250.3 2010 81.1 26% 8.74 107.7 18.22 224.6 2015 84.1 34% 8.88 105.5 18.19 216.2 2020 89.1 43% 9.02 101.2 19.15 214.9 2025 93.9 52% 9.56 101.8 20.06 213.6 2030 98.2 60% 9.96 101.5 20.92 213.1 2035 103.0 68% 10.38 100.8 21.78 211.4 Note(s): Source(s): EIA, State Energy Consumption Database, June 2011 for 1980-2009; DOE for 1980 floorspace; EIA, Annual Energy Outlook 1994, Jan. 1994, Table A5, p. 62 for 1990 floorspace; EIA, AEO 2003, Jan. 2003, Table A5, p. 127 for 2000 floorspace; and EIA, Annual Energy Outlook 2012 Early Release, Jan. 2012,

447

EIA - Natural Gas Consumption Data & Analysis  

Gasoline and Diesel Fuel Update (EIA)

Consumption Consumption Consumption by End Use U.S. and State consumption by lease and plant, pipeline, and delivered to consumers by sector (monthly, annual). Number of Consumers Number of sales and transported consumers for residential, commercial, and industrial sectors by State (monthly, annual). State Shares of U.S. Deliveries By sector and total consumption (annual). Delivered for the Account of Others Commercial, industrial and electric utility deliveries; percentage of total deliveries by State (annual). Heat Content of Natural Gas Consumed Btu per cubic foot of natural gas delivered to consumers by State (annual) and other components of consumption for U.S. (annual). Natural Gas Weekly Update Analysis of current price, supply, and storage data; and a weather snapshot.

448

Table 2.1a Energy Consumption Estimates by Sector, 1949-2011 ...  

U.S. Energy Information Administration (EIA)

R 8: R 97,722: 2011 P: 6,585: 21,619: 4,090: 18,021: 20,291: 30,592: 26,999: 27,079: 39,346-9: 97,301: 1 Commercial sector, including commercial combined-heat-and ...

449

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

E-Print Network (OSTI)

year consumption estimates. DISCUSSION The Importance of Miscellaneous ElectricityConsumption of New Equipment Index kWh/Year MMBtu/Year MMBtu/Year ElectricityConsumption of Equipment in Existing Homes Index kWh/Year MMBtu/Year MMBtu/Year Electricity

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

450

Energy Efficiency Report: Chapter 3 Figures (Residential)  

U.S. Energy Information Administration (EIA)

Figure 3.1. Total Site Residential Energy Consumption and Personal Consumption Expenditures Indices, 1980 to 1993. Notes: Personal consumption expenditures used ...

451

New Zealand Energy Data: Electricity Demand and Consumption | OpenEI  

Open Energy Info (EERE)

Electricity Demand and Consumption Electricity Demand and Consumption Dataset Summary Description The New Zealand Ministry of Economic Development publishes energy data including many datasets related to electricity. Included here are three electricity consumption and demand datasets, specifically: annual observed electricity consumption by sector (1974 to 2009); observed percentage of consumers by sector (2002 - 2009); and regional electricity demand, as a percentage of total demand (2009). The sectors included are: agriculture, forestry and fishing; industrial (mining, food processing, wood and paper, chemicals, basic metals, other minor sectors); commercial; and residential. Source New Zealand Ministry of Economic Development Date Released Unknown Date Updated July 03rd, 2009 (5 years ago)

452

EIA - Assumptions to the Annual Energy Outlook 2010 - Residential Demand  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2010 Residential Demand Module Figure 5. United States Census Divisions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Residential Demand Module projects future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the "unit energy consumption" by appliance (or UEC-in million Btu per household per year). The projection process adds new housing units to the stock,

453

Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption  

Buildings Energy Data Book (EERE)

9 9 2003 Commercial Delivered Energy Consumption Intensities, by Principal Building Type and Vintage (1) | Building Type Pre-1959 1960-1989 1990-2003 | Building Type Pre-1959 1960-1989 1990-2003 Health Care 178.1 216.0 135.7 | Education 77.7 88.3 80.6 Inpatient 230.3 255.3 253.8 | Service 62.4 86.0 74.8 Outpatient 91.6 110.4 84.4 | Food Service 145.2 290.1 361.2 Food Sales 205.8 197.6 198.3 | Religious Worship 46.6 39.9 43.3 Lodging 88.2 111.5 88.1 | Public Order & Safety N.A. 101.3 110.6 Office 93.6 94.4 88.0 | Warehouse & Storage N.A. 38.9 33.3 Mercantile 80.4 91.8 94.4 | Public Assembly 61.9 107.6 119.7 Retail (Non-Malls) 74.1 63.7 86.4 | Vacant 21.4 23.1 N.A. Retail (Malls) N.A. 103.9 99.5 | Other 161.3 204.9 125.3 Note(s): Source(s): Consumption (kBtu/SF) Consumption (kBtu/SF) 1) See Table 3.1.3 for primary versus delivered energy consumption.

454

Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption  

Buildings Energy Data Book (EERE)

5 5 Commercial Buildings Share of U.S. Petroleum Consumption (Percent) Site Consumption Primary Consumption Total Commercial Industry Electric Gen. Transportation Commercial Industry Transportation (quads) 1980 4% 28% 8% 56% | 6% 31% 56% 34.2 1981 4% 26% 7% 59% | 5% 29% 59% 31.9 1982 3% 26% 5% 61% | 5% 28% 61% 30.2 1983 4% 25% 5% 62% | 5% 27% 62% 30.1 1984 4% 26% 4% 61% | 5% 27% 61% 31.1 1985 3% 25% 4% 63% | 5% 26% 63% 30.9 1986 4% 24% 5% 63% | 5% 26% 63% 32.2 1987 3% 25% 4% 63% | 5% 26% 63% 32.9 1988 3% 24% 5% 63% | 5% 26% 63% 34.2 1989 3% 24% 5% 63% | 5% 25% 63% 34.2 1990 3% 25% 4% 64% | 4% 26% 64% 33.6 1991 3% 24% 4% 65% | 4% 26% 65% 32.8 1992 3% 26% 3% 65% | 4% 27% 65% 33.5 1993 2% 25% 3% 65% | 3% 26% 65% 33.8 1994 2% 25% 3% 65% | 3% 26% 65% 34.7 1995 2% 25% 2% 67% | 3% 26% 67% 34.6 1996 2% 25% 2% 66% | 3% 26% 66% 35.8 1997 2% 26% 3% 66% | 3% 26% 66% 36.3 1998 2% 25% 4% 66% | 3% 26% 66% 36.9 1999 2% 25% 3% 66% | 3% 26% 66% 38.0 2000 2% 24% 3% 67% | 3% 25%

455

Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption  

Buildings Energy Data Book (EERE)

4 4 Commercial Buildings Share of U.S. Natural Gas Consumption (Percent) Site Consumption Primary Consumption Total Commercial Industry Electric Gen. Transportation Commercial Industry Transportation (quads) 1980 13% 41% 19% 3% | 18% 49% 3% 20.22 1981 13% 42% 19% 3% | 18% 49% 3% 19.74 1982 14% 39% 18% 3% | 20% 45% 3% 18.36 1983 14% 39% 17% 3% | 19% 46% 3% 17.20 1984 14% 40% 17% 3% | 19% 47% 3% 18.38 1985 14% 40% 18% 3% | 19% 46% 3% 17.70 1986 14% 40% 16% 3% | 19% 46% 3% 16.59 1987 14% 41% 17% 3% | 19% 47% 3% 17.63 1988 15% 42% 15% 3% | 19% 47% 3% 18.44 1989 14% 41% 16% 3% | 19% 47% 3% 19.56 1990 14% 43% 17% 3% | 19% 49% 4% 19.57 1991 14% 43% 17% 3% | 19% 49% 3% 20.03 1992 14% 43% 17% 3% | 19% 49% 3% 20.71 1993 14% 43% 17% 3% | 19% 48% 3% 21.24 1994 14% 42% 18% 3% | 19% 48% 3% 21.75 1995 14% 42% 19% 3% | 20% 49% 3% 22.71 1996 14% 43% 17% 3% | 19% 49% 3% 23.14 1997 14% 43% 18% 3% | 20% 49% 3% 23.34 1998 13% 43% 20% 3% | 20% 50% 3% 22.86 1999 14%

456

Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption  

Buildings Energy Data Book (EERE)

1 1 Buildings Share of U.S. Petroleum Consumption (Percent) U.S. Petroleum Site Consumption Primary Consumption Total Buildings Industry Electric Gen. Transportation Buildings Industry Transportation (quads) 1980 9% 28% 8% 56% | 14% 31% 56% 34.2 1981 8% 26% 7% 59% | 12% 29% 59% 31.9 1982 8% 26% 5% 61% | 11% 28% 61% 30.2 1983 8% 25% 5% 62% | 12% 27% 62% 30.1 1984 9% 26% 4% 61% | 11% 27% 61% 31.1 1985 8% 25% 4% 63% | 11% 26% 63% 30.9 1986 8% 24% 5% 63% | 11% 26% 63% 32.2 1987 8% 25% 4% 63% | 11% 26% 63% 32.9 1988 8% 24% 5% 63% | 11% 26% 63% 34.2 1989 8% 24% 5% 63% | 11% 25% 63% 34.2 1990 7% 25% 4% 64% | 10% 26% 64% 33.6 1991 7% 24% 4% 65% | 9% 26% 65% 32.8 1992 7% 26% 3% 65% | 9% 27% 65% 33.5 1993 7% 25% 3% 65% | 9% 26% 65% 33.8 1994 6% 25% 3% 65% | 8% 26% 65% 34.7 1995 6% 25% 2% 67% | 8% 26% 67% 34.6 1996 6% 25% 2% 66% | 8% 26% 66% 35.8 1997 6% 26% 3% 66% | 8% 26% 66% 36.3 1998 5% 25% 4% 66% | 8% 26% 66% 36.9 1999 6% 25% 3% 66% | 8% 26% 66% 38.0 2000 6% 24%

457

Detroit Public Lighting Department - Residential Energy Wise...  

Open Energy Info (EERE)

Multi-Family Residential, Residential Eligible Technologies Ceiling Fan, Lighting, LED Lighting Active Incentive Yes Implementing Sector Utility Energy Category Energy...

458

Potential Impact of Adopting Maximum Technologies as Minimum Efficiency Performance Standards in the U.S. Residential Sector  

E-Print Network (OSTI)

US to achieve 18% reduction in its electricity demand compared to the base case by 2030 and 11% in Natural Gas and LPG consumption.

Letschert, Virginie

2010-01-01T23:59:59.000Z

459

A Water Conservation Scenario for the Residential and Industrial Sectors in California: Potential Saveings of Water and Related Energy  

E-Print Network (OSTI)

Part A: 1966-1975. Sacramento, CA: Employment Developmentand consumption. Sacramento, CA. Department of WaterPopulation for HSAs. Sacramento, CA. L.E. Moberg. Department

Benenson, P.

2010-01-01T23:59:59.000Z

460

Sector-specific issues and reporting methodologies supporting the General Guidelines for the voluntary reporting of greenhouse gases under Section 1605(b) of the Energy Policy Act of 1992. Volume 1: Part 1, Electricity supply sector; Part 2, Residential and commercial buildings sector; Part 3, Industrial sector  

Science Conference Proceedings (OSTI)

DOE encourages you to report your achievements in reducing greenhouse gas emissions and sequestering carbon under this program. Global climate change is increasingly being recognized as a threat that individuals and organizations can take action against. If you are among those taking action, reporting your projects may lead to recognition for you, motivation for others, and synergistic learning for the global community. This report discusses the reporting process for the voluntary detailed guidance in the sectoral supporting documents for electricity supply, residential and commercial buildings, industry, transportation, forestry, and agriculture. You may have reportable projects in several sectors; you may report them separately or capture and report the total effects on an entity-wide report.

Not Available

1994-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "residential sector 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

U.S. Energy Information Administration (EIA) - Sector  

Gasoline and Diesel Fuel Update (EIA)

coal Residential coal Residential market trends icon Market Trends In the AEO2011 Reference case, residential energy use per capita declines by 17.0 percent from 2009 to 2035 (Figure 58). Delivered energy use stays relatively constant while population grows by 26.7 percent during the period. Growth in the number of homes and in average square footage leads to increased demand for energy services, which is offset in part by efficiency gains in space heating, water heating, and lighting equipment. Population shifts to warmer and drier climates also reduce energy demand for space heating. See more issues Issues in Focus In 2009, the residential and commercial buildings sectors used 19.6 quadrillion Btu of delivered energy, or 21 percent of total U.S. energy consumption. The residential sector accounted for 57 percent of that energy

462

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

463

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

E-Print Network (OSTI)

Analysis: Studies in Residential Energy Demand. AcademicHousing Characteristics 1987, Residential Energy ConsumptionHousing Characteristics 1990, Residential Energy Consumption

Johnson, F.X.

2010-01-01T23:59:59.000Z

464

Buildings Energy Data Book: 8.1 Buildings Sector Water Consumption  

Buildings Energy Data Book (EERE)

3 3 Energy Use of Wastewater Treatment Plants by Capacity and Treatment Level (kWh per Million Gallons) 1 - 5 - 10 - 20 - 50 - 100 - Note(s): Source(s): 673 1,028 1,188 1,558 The level of treatment indicates the amount of processing involved before water is released from the treatment facility. Primary treatment removes solids and oils from wastewater. Secondary treatment uses biological processes to remove organic material from the water. Tertiary treatment includes additional processes to further refine the water. Nitrification is a process to remove nitrogen from water. Electric Power Research Institute, Water & Sustainability (Volume 4): U.S. Electricity Consumption for Water Supply & Treatment - The Next Half Century,

465

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

466

Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption  

Buildings Energy Data Book (EERE)

3 3 Buildings Share of U.S. Primary Energy Consumption (Percent) Total Consumption Total Industry Transportation Total (quads) 1980(1) 20.1% 13.5% | 33.7% 41.1% 25.2% 100% | 78.1 1981 20.0% 13.9% | 33.9% 40.4% 25.6% 100% | 76.1 1982 21.2% 14.8% | 36.0% 37.9% 26.1% 100% | 73.1 1983 21.1% 15.0% | 36.1% 37.7% 26.3% 100% | 72.9 1984 20.8% 14.9% | 35.7% 38.7% 25.7% 100% | 76.6 1985 21.0% 15.0% | 35.9% 37.8% 26.3% 100% | 76.5 1986 20.8% 15.1% | 35.9% 37.0% 27.1% 100% | 76.6 1987 20.5% 15.1% | 35.6% 37.2% 27.2% 100% | 79.0 1988 20.7% 15.2% | 35.9% 37.2% 27.0% 100% | 82.8 1989 20.9% 15.5% | 36.5% 37.0% 26.5% 100% | 84.8 1990 20.0% 15.7% | 35.8% 37.7% 26.5% 100% | 84.5 1991 20.6% 16.0% | 36.5% 37.3% 26.2% 100% | 84.4 1992 20.2% 15.6% | 35.8% 38.0% 26.1% 100% | 85.8 1993 20.8% 15.8% | 36.6% 37.4% 26.0% 100% | 87.5 1994 20.3% 15.8% | 36.1% 37.7% 26.2% 100% | 89.1 1995 20.3% 16.1% | 36.4% 37.4% 26.2% 100% | 91.1 1996 20.7%

467

Residential Transportation Historical Publications reports, data and  

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

Historical Publications Historical Publications Residential Transportation reports, data tables and transportation questionnaires Released: May 2008 The Energy Information Administration conducts several core consumption surveys. Among them was the Residential Transportation Energy Consumption Survey (RTECS). RTECS was designed by EIA to provide information on how energy is used by households for personal vehicles. It was an integral part of a series of surveys (i.e., core consumption surveys) designed by EIA to collect data on energy used by end-use economic sectors. The RTECS collected data on the number and type of vehicles used by the household. For each vehicle, data were collected on the number of miles traveled (commonly called VMT) for the year, the number of gallons of fuel consumed, the type of fuel used, the priced paid for fuel, and the number of miles per gallon. Additional electronic releases are available on the Transportation homepage.

468

Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption  

Buildings Energy Data Book (EERE)

9 9 Buildings Share of U.S. Electricity Consumption (Percent) Total Industry Transportation Total | (quads) 1980 34% 27% | 61% 39% 0% 100% | 7.15 1981 34% 28% | 61% 38% 0% 100% | 7.33 1982 35% 29% | 64% 36% 0% 100% | 7.12 1983 35% 29% | 64% 36% 0% 100% | 7.34 1984 34% 29% | 63% 37% 0% 100% | 7.80 1985 34% 30% | 64% 36% 0% 100% | 7.93 1986 35% 30% | 65% 35% 0% 100% | 8.08 1987 35% 30% | 65% 35% 0% 100% | 8.38 1988 35% 30% | 65% 35% 0% 100% | 8.80 1989 34% 31% | 65% 35% 0% 100% | 9.03 1990 34% 31% | 65% 35% 0% 100% | 9.26 1991 35% 31% | 66% 34% 0% 100% | 9.42 1992 34% 31% | 65% 35% 0% 100% | 9.43 1993 35% 31% | 66% 34% 0% 100% | 9.76 1994 34% 31% | 65% 34% 0% 100% | 10.01 1995 35% 32% | 66% 34% 0% 100% | 10.28 1996 35% 32% | 67% 33% 0% 100% | 10.58 1997 34% 33% | 67% 33% 0% 100% | 10.73 1998 35% 33% | 68% 32% 0% 100% | 11.14 1999 35% 33% | 68% 32% 0% 100% | 11.30 2000 35% 34% | 69% 31% 0% 100% | 11.67 2001 35% 35% | 70% 29% 0% 100% | 11.58 2002 37% 35% | 71% 29% 0% 100% | 11.82

469

Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption  

Buildings Energy Data Book (EERE)

3 3 2003 Commercial Buildings Delivered Energy End-Use Intensities, by Building Activity (Thousand Btu per SF) (1) Space Heating Cooling Ventilation Water Heating Lighting Cooking Refrigeration Office Equipment Computers Other Total Space Heating Cooling Ventilation Water Heating Lighting Cooking Refrigeration Office Equipment Computers Other Total Space Heating Cooling Ventilation Water Heating Lighting Cooking Refrigeration Office Equipment Computers Other Total Note(s): Source(s): 43.5 45.2 164.4 20.9 1) Due to rounding, end-uses do not sum to total. EIA, 2003 Commercial Building Energy Consumption Survey, Energy End-Uses, Oct. 2008, Table E.2A. 0.3 0.6 3.0 N.A. 4.9 4.8 18.9 3.1 1.7 3.5 6.0 N.A. 0.1 0.2 N.A. N.A. 4.4 13.1 34.1 1.7 0.8 N.A. N.A. N.A. 1.4 2.0 6.1 0.4 0.8 0.6 2.1 0.1 26.2 19.3 79.4 14.4 2.9 1.3 10.5 0.6 Religious

470

Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption  

Buildings Energy Data Book (EERE)

0 0 Buildings Share of U.S. Natural Gas Consumption (Percent) Total Buildings Industry Electric Gen. Transportation Buildings Industry Transportation 1980 37% 41% 19% 3% | 48% 49% 3% 20.22 1981 36% 42% 19% 3% | 48% 49% 3% 19.74 1982 40% 39% 18% 3% | 51% 45% 3% 18.36 1983 40% 39% 17% 3% | 51% 46% 3% 17.20 1984 39% 40% 17% 3% | 50% 47% 3% 18.38 1985 39% 40% 18% 3% | 51% 46% 3% 17.70 1986 41% 40% 16% 3% | 51% 46% 3% 16.59 1987 39% 41% 17% 3% | 50% 47% 3% 17.63 1988 40% 42% 15% 3% | 50% 47% 3% 18.44 1989 39% 41% 16% 3% | 50% 47% 3% 19.56 1990 36% 43% 17% 3% | 47% 49% 4% 19.57 1991 37% 43% 17% 3% | 48% 49% 3% 20.03 1992 37% 43% 17% 3% | 48% 49% 3% 20.71 1993 38% 43% 17% 3% | 48% 48% 3% 21.24 1994 36% 42% 18% 3% | 48% 48% 3% 21.75 1995 35% 42% 19% 3% | 48% 49% 3% 22.71 1996 37% 43% 17% 3% | 48% 49% 3% 23.14 1997 36% 43% 18% 3% | 48% 49% 3% 23.34 1998 34% 43% 20% 3% | 47% 50% 3% 22.86 1999 35% 41% 21% 3% | 49% 48% 3% 22.88 2000 35% 40% 22% 3% | 50% 47% 3% 23.66 2001

471

California DREAMing: the design of residential demand responsive technology with people in mind  

E-Print Network (OSTI)

in daily household energy consumption. Proceedings of thefeedback into energy consumption. Oxford: Environmentalin Residential Energy Consumption. Proceedings of the 2008

Peffer, Therese E.

2009-01-01T23:59:59.000Z

472

Realized and prospective impacts of U.S. energy efficiency standards for residential appliances: 2004 update  

E-Print Network (OSTI)

Energy Consumption . . . . . . . . . . . . . . . . . . . .residential primary energy consumption and CO 2 emissions inenergy efficiency and energy consumption of a given product

Meyers, Stephen; McMahon, James; McNeil, Michael

2005-01-01T23:59:59.000Z

473

Assumptions to the Annual Energy Outlook 2002 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and

474

Assumptions to the Annual Energy Outlook 2001 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and

475

Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption  

Buildings Energy Data Book (EERE)

3 3 World Primary Energy Consumption and Population, by Country/Region 1990-2000 2000-2010 Region/Country 1990 2000 2010 1990 2000 2010 Energy Pop. Energy Pop. United States 85.0 99.8 97.8 18.7% 250 282 311 4.6% 1.6% 1.2% -0.2% 1.0% China 27.0 36.4 104.6 20.0% 1,148 1,264 1,343 20.0% 3.0% 1.0% 11.1% 0.6% OECD Europe 69.9 76.8 79.6 15.2% 402 522 550 8.2% 0.9% 2.6% 0.4% 0.5% Other Non-OECD Asia 12.5 20.6 31.3 6.0% 781 1,014 1,086 16.2% 5.1% 2.6% 4.2% 0.7% Russia (1) 61.0 27.2 29.9 5.7% 288 147 140 2.1% -7.7% -6.5% 0.9% -0.5% Central & S. America 14.5 20.8 28.1 5.4% 359 422 462 6.9% 3.7% 1.6% 3.0% 0.9% Middle East 11.2 17.3 27.6 5.3% 135 173 213 3.2% 4.5% 2.5% 4.8% 2.1% Japan 18.8 22.4 20.8 4.0% 124 127 127 1.9% 1.8% 0.3% -0.8% 0.0% India 7.9 13.5 23.8 4.6% 838 1,006 1,214 18.1% 5.5% 1.8% 5.9% 1.9% Canada 11.0 13.1 14.3 2.7% 28 31 34 0.5% 1.8% 1.1% 0.9% 0.9% Oth. Non-OECD Europe 6.4 17.6

476

Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption  

Buildings Energy Data Book (EERE)

Commercial Primary Energy Consumption, by Year and Fuel Type (Quadrillion Btu and Percent of Total) Electricity Growth Rate Natural Gas Petroleum (1) Coal Renewable(2) Sales Losses Total Total(3) 2010-Year 1980 2.63 24.9% 1.31 12.4% 0.12 1.1% 0.02 0.2% 1.91 4.58 6.49 61.4% 1981 2.54 23.9% 1.12 10.5% 0.14 1.3% 0.02 0.2% 2.03 4.76 6.80 64.1% 1982 2.64 24.3% 1.03 9.5% 0.16 1.4% 0.02 0.2% 2.08 4.91 6.99 64.5% 1983 2.48 22.7% 1.16 10.7% 0.16 1.5% 0.02 0.2% 2.12 4.98 7.09 65.0% 1984 2.57 22.5% 1.22 10.7% 0.17 1.5% 0.02 0.2% 2.26 5.17 7.43 65.1% 1985 2.47 21.6% 1.08 9.4% 0.14 1.2% 0.02 0.2% 2.35 5.39 7.74 67.6% 1986 2.35 20.3% 1.16 10.0% 0.14 1.2% 0.03 0.2% 2.44 5.47 7.91 68.3% 1987 2.47 20.8% 1.13 9.5% 0.13 1.1% 0.03 0.2% 2.54 5.62 8.16 68.5% 1988 2.72 21.6% 1.09 8.7% 0.13 1.0% 0.03 0.3% 2.68 5.92 8.60 68.4% 1989 2.77 21.0% 1.04 7.9% 0.12 0.9% 0.10 0.8% 2.77 6.39 9.16 69.5% 1990 2.67 20.1%

477

Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption  

Buildings Energy Data Book (EERE)

2 2 U.S. Buildings Site Renewable Energy Consumption (Quadrillion Btu) (1) Growth Rate Wood (2) Solar Thermal (3) Solar PV (3) GSHP (4) Total 2010-Year 1980 0.867 0.000 N.A. 0.000 0.867 - 1981 0.894 0.000 N.A. 0.000 0.894 - 1982 0.993 0.000 N.A. 0.000 0.993 - 1983 0.992 0.000 N.A. 0.000 0.992 - 1984 1.002 0.000 N.A. 0.000 1.002 - 1985 1.034 0.000 N.A. 0.000 1.034 - 1986 0.947 0.000 N.A. 0.000 0.947 - 1987 0.882 0.000 N.A. 0.000 0.882 - 1988 0.942 0.000 N.A. 0.000 0.942 - 1989 1.018 0.052 N.A. 0.008 1.078 - 1990 0.675 0.056 N.A. 0.008 0.739 - 1991 0.705 0.057 N.A. 0.009 0.771 - 1992 0.744 0.059 N.A. 0.010 0.813 - 1993 0.657 0.061 N.A. 0.010 0.728 - 1994 0.626 0.063 N.A. 0.010 0.700 - 1995 0.633 0.064 N.A. 0.011 0.708 - 1996 0.669 0.065 N.A. 0.012 0.746 - 1997 0.559 0.064 N.A. 0.013 0.636 - 1998 0.498 0.064 N.A. 0.015 0.577 - 1999 0.521 0.063 N.A. 0.016 0.599 - 2000 0.549 0.060 N.A. 0.016 0.625 - 2001

478

Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption  

Buildings Energy Data Book (EERE)

2 2 Commercial Site Renewable Energy Consumption (Quadrillion Btu) (1) Growth Rate Wood (2) Solar Thermal (3) Solar PV (3) GHP Total 2010-Year 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 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 2026 2027 2028 2029 0.110 0.035 0.010 N.A. 0.155 0.4% 0.110 0.035 0.009 N.A. 0.154 0.4% 0.110 0.035 0.009 N.A. 0.153 0.4% 0.110 0.034 0.009 N.A. 0.153 0.4% 0.110 0.034 0.009 N.A. 0.152 0.4% 0.110 0.034 0.008 N.A. 0.152 0.4% 0.110 0.034 0.008 N.A. 0.151 0.4% 0.110 0.033 0.008 N.A. 0.151 0.4% 0.110 0.033 0.008 N.A. 0.150 0.4% 0.110 0.033 0.007 N.A. 0.150 0.4% 0.110 0.032 0.007 N.A. 0.149 0.4% 0.110 0.032 0.007 N.A. 0.149 0.4% 0.110 0.032 0.007 N.A. 0.149 0.5% 0.110 0.032 0.007 N.A. 0.149 0.5% 0.110 0.032 0.007 N.A. 0.148 0.6%

479

978-3-901882-56-2 c 2013 IFIP Effective Consumption Scheduling for Demand-Side  

E-Print Network (OSTI)

grids hold the promise of connecting electricity producers, consumers, and prosumers (who act as both their consumption behavior every day. I. INTRODUCTION Today's electricity sector faces significant challenges consumption in a group of Irish residential homes occurs in the evening. Maximum electricity production

Diggavi, Suhas

480

Fuel choice and aggregate energy demand in the commercial sector  

SciTech Connect

This report presents a fuel choice and aggregate-demand model of energy use in the commercial sector of the United States. The model structure is dynamic with short-run fuel-price responses estimated to be close to those of the residential sector. Of the three fuels analyzed, electricity consumption exhibits a greater response to its own price than either natural gas or fuel oil. In addition, electricity price increases have the largest effect on end-use energy conservation in the commercial sector. An improved commercial energy-use data base is developed which removes the residential portion of electricity and natural gas use that traditional energy-consumption data sources assign to the commercial sector. In addition, household and commercial petroleum use is differentiated on a state-by-state basis.

Cohn, S.

1978-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "residential sector 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

Thermal Performance of Phase Change Wallboard for Residential Cooling Application  

E-Print Network (OSTI)

USA ABSTRACT Cooling of residential California buildings contributes significantly to electrical consumption and peak power demand

Feustel, H.E.

2011-01-01T23:59:59.000Z

482

North Arkansas Electric Cooperative, Inc - Residential Energy...  

Open Energy Info (EERE)

Sector Residential Eligible Technologies Doors, DuctAir sealing, Heat pumps, Windows Active Incentive Yes Implementing Sector Utility Energy Category Energy Efficiency...

483

Clark Public Utilities - Residential Weatherization Loan Program...  

Open Energy Info (EERE)

Sector Residential Eligible Technologies Building Insulation, DuctAir sealing, Windows Active Incentive Yes Implementing Sector Utility Energy Category Energy Efficiency...

484

EIA - International Energy Outlook 2007 - Energy Consumption by End-Use  

Gasoline and Diesel Fuel Update (EIA)

Energy Consumption by End-Use Sector Energy Consumption by End-Use Sector International Energy Outlook 2007 Chapter 2 - Energy Consumption by End-Use Sector In the IEO2007 projections, end-use energy consumption depends on resource endowment, economic growth, and other political, social, and demographic factors.. 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 dominated by petroleum-based liquids products at present, the mix of energy use in the residential, commercial, and industrial sectors varies widely by region, depending on a combination of regional factors, such as the availability of energy resources, the level of economic development, and political, social,

485

OpenEI - Residential  

Open Energy Info (EERE)

Commercial and Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States http://en.openei.org/datasets/node/961 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 consumption/residential/">Residential Energy Consumption Survey (RECS) for statistical references of building types

486

Strategies for Low Carbon Growth In India: Industry and Non Residential  

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

Strategies for Low Carbon Growth In India: Industry and Non Residential Strategies for Low Carbon Growth In India: Industry and Non Residential Sectors Title Strategies for Low Carbon Growth In India: Industry and Non Residential Sectors Publication Type Report Refereed Designation Unknown LBNL Report Number LBNL-4557E Year of Publication 2011 Authors Sathaye, Jayant A., Stephane Rue de la du Can, Maithili Iyer, Michael A. McNeil, Klaas Jan Kramer, Joyashree Roy, Moumita Roy, and Shreya Roy Chowdhury Date Published 5/2011 Publisher LBNL Keywords Buildings Energy Efficiency, CO2 Accounting Methodology, CO2 mitigation, Demand Side Management, energy efficiency, greenhouse gas (ghg), india, industrial energy efficiency, industrial sector, Low Carbon Growth, Low Growth, Non Residential Abstract This report analyzed the potential for increasing energy efficiency and reducing greenhouse gas emissions (GHGs) in the non-residential building and the industrial sectors in India. The first two sections describe the research and analyses supporting the establishment of baseline energy consumption using a bottom up approach for the non residential sector and for the industry sector respectively. The third section covers the explanation of a modeling framework where GHG emissions are projected according to a baseline scenario and alternative scenarios that account for the implementation of cleaner technology.

487

An Empirical Analysis of Causality in the Relationship between Telecommuting and Residential and Job Relocation  

E-Print Network (OSTI)

on Travel Behavior and Residential Location). Report to BMWwork places on urban residential location, consumption andapplication in study of residential mobility. Transportation

Ory, David T.; Mokhtarian, Patricia L.

2005-01-01T23:59:59.000Z

488

An Empirical Analysis of Causality in the Relationship between Telecommuting and Residential and Job Relocation  

E-Print Network (OSTI)

New telecommunications and residential location flexibility.on Travel Behavior and Residential Location). Report to BMWwork places on urban residential location, consumption and

Ory, D T; Mokhtarian, Patricia L

2005-01-01T23:59:59.000Z

489

An Empirical Analysis of Causality in the Relationship Between Telecommuting and Residential and Job Relocation  

E-Print Network (OSTI)

New telecommunications and residential location flexibility.on Travel Behavior and Residential Location). Report to BMWwork places on urban residential location, consumption and

Ory, David T; Mokhtarian, Patricia L

2005-01-01T23:59:59.000Z

490

Economics of Condensing Gas Furnaces and Water Heaters Potential in Residential Single Family Homes  

E-Print Network (OSTI)

seds.html. USDOE. 2009. Residential Energy ConsumptionUSEPA) 2008. Energy Star Residential Water Heaters: FinalExperiences of residential consumers and utilities. Oak

Lekov, Alex

2011-01-01T23:59:59.000Z

491

Application analysis of solar total energy systems to the residential sector. Volume III, conceptual design. Final report  

DOE Green Energy (OSTI)

The objective of the work described in this volume was to conceptualize suitable designs for solar total energy systems for the following residential market segments: single-family detached homes, single-family attached units (townhouses), low-rise apartments, and high-rise apartments. Conceptual designs for the total energy systems are based on parabolic trough collectors in conjunction with a 100 kWe organic Rankine cycle heat engine or a flat-plate, water-cooled photovoltaic array. The ORC-based systems are designed to operate as either independent (stand alone) systems that burn fossil fuel for backup electricity or as systems that purchase electricity from a utility grid for electrical backup. The ORC designs are classified as (1) a high temperature system designed to operate at 600/sup 0/F and (2) a low temperature system designed to operate at 300/sup 0/F. The 600/sup 0/F ORC system that purchases grid electricity as backup utilizes the thermal tracking principle and the 300/sup 0/F ORC system tracks the combined thermal and electrical loads. Reject heat from the condenser supplies thermal energy for heating and cooling. All of the ORC systems utilize fossil fuel boilers to supply backup thermal energy to both the primary (electrical generating) cycle and the secondary (thermal) cycle. Space heating is supplied by a central hot water (hydronic) system and a central absorption chiller supplies the space cooling loads. A central hot water system supplies domestic hot water. The photovoltaic system uses a central electrical vapor compression air conditioning system for space cooling, with space heating and domestic hot water provided by reject heat from the water-cooled array. All of the systems incorporate low temperature thermal storage (based on water as the storage medium) and lead--acid battery storage for electricity; in addition, the 600/sup 0/F ORC system uses a therminol-rock high temperature storage for the primary cycle. (WHK)

Not Available

1979-07-01T23:59:59.000Z

492

Toward a National Plan for the Accelerated Commercialization of Solar Energy: residential/commercial buildings market sector workbook  

Science Conference Proceedings (OSTI)

This workbook contains preliminary data and assumptions used during the preparation of inputs to a National Plan for the Accelerated Commercialization of Solar Energy (NPAC). The workbook indicates the market potential, competitive position, market penetration, and technological characteristics of solar technologies for this market sector over the next twenty years. The workbook also presents projections of the mix of solar technologies by US Census Regions. In some cases, data have been aggregated to the national level. Emphasis of the workbook is on a mid-price fuel scenario, Option II, that meets about a 20% solar goal by the year 2000. The energy demand for the mid-price scenario is projected at 115 quads in the year 2000. The workbook, prepared in April 1979, represents government policies and programs anticipated at that time.

Taul, Jr., J. W.; de Jong, D. L.

1980-01-01T23:59:59.000Z

493

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

494

Residential Two-Stage Gas Furnaces - Do They Save Energy?  

E-Print Network (OSTI)

Method for Measuring the Energy Consumption of Furnaces andcalculating the energy consumption of two-stage furnaces.residential gas furnace energy consumption in the DOE test

Lekov, Alex; Franco, Victor; Lutz, James

2006-01-01T23:59:59.000Z

495

EIA-Assumptions to the Annual Energy Outlook - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2007 Residential Demand Module Figure 5. United States Census Divisions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the "unit energy consumption" by appliance (or UEC-in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new

496

All Consumption Tables.vp  

Gasoline and Diesel Fuel Update (EIA)

3. Energy Consumption per Capita by End-Use Sector, Ranked by State, 2011 3. Energy Consumption per Capita by End-Use Sector, Ranked by State, 2011 Rank Residential Sector Commercial Sector Industrial Sector Transportation Sector Total Consumption State Million Btu State Million Btu State Million Btu State Million Btu State Million Btu 1 North Dakota 99.8 District of Columbia 193.1 Louisiana 585.8 Alaska 277.3 Wyoming 974.7 2 West Virginia 90.9 Wyoming 119.2 Wyoming 568.2 Wyoming 200.7 Louisiana 886.5 3 Missouri 89.4 North Dakota 106.9 Alaska 435.7 North Dakota 172.8 Alaska 881.3 4 Tennessee 87.8 Alaska 94.1 North Dakota 388.9 Louisiana 158.0 North Dakota 768.4 5 Kentucky 87.4 Montana 78.4 Iowa 243.4 Oklahoma 122.3 Iowa 493.6

497

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...

498

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

499

Black Hills Power - Residential Customer Rebate Program (South...  

Open Energy Info (EERE)

Program Applicable Sector Multi-Family Residential, Residential Eligible Technologies Energy Mgmt. SystemsBuilding Controls, Heat pumps, Water Heaters, Geothermal Heat Pumps,...

500

Black Hills Power - Residential Customer Rebate Program (Wyoming...  

Open Energy Info (EERE)

Program Applicable Sector Multi-Family Residential, Residential Eligible Technologies Energy Mgmt. SystemsBuilding Controls, Heat pumps, Water Heaters, Geothermal Heat Pumps,...