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Note: This page contains sample records for the topic "household electricity usage" 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
to obtain the most current and comprehensive results.


1

usage_household2001.pdf  

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

Usage Indicators Tables Usage Indicators Tables (Million U.S. Households; 60 pages, 247 kb) Contents Pages HC6-1a. Usage Indicators by Climate Zone, Million U.S. Households, 2001 5 HC6-2a. Usage Indicators by Year of Construction, Million U.S. Households, 2001 5 HC6-3a. Usage Indicators by Household Income, Million U.S. Households, 2001 5 HC6-4a. Usage Indicators by Type of Housing Unit, Million U.S. Households, 2001 5 HC6-5a. Usage Indicators by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 5 HC6-6a. Usage Indicators by Type of Rented Housing Unit, Million U.S. Households, 2001 5 HC6-7a. Usage Indicators by Four Most Populated States, Million U.S. Households, 2001 5

2

Residential Energy Usage by Origin of Householder  

U.S. Energy Information Administration (EIA)

Home > Energy Users > Residential Home Page > Energy Usage by Origin of Householder. Consumption and Expenditures. NOTE: To View and/or Print PDF's ...

3

Form EIA-457E (2001) -- Household Bottled Gas Usage  

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

E (2001) - Household Electricity Usage Form E (2001) - Household Electricity Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Electricity 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

4

Electric household equipment and electric fuel usage in the Tri-State Region and the United States: 1960-70. Working paper  

SciTech Connect

The possible impact of areawide residential location policy on future residential electricity usage in the Tri-State Metropolitan Region centering on New York City is investigated. This report is concerned with selected residential electric appliance usage in the Tri-State Region as compared with usage of these appliances across the United States between 1960 and 1970. Included are tabular representations of comparisons between residential air conditioner usage in the Tri-State Region and the United States. Tabular comparisons also are made with respect to residential appliance usage and electric fuel usage.

Hillman, B.

1973-08-01T23:59:59.000Z

5

Form EIA-457E (2001) -- Household Bottled Gas Usage  

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

F (2001) -- Household Natural Gas Usage Form F (2001) -- Household Natural Gas Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Natural Gas 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

6

Recommending energy tariffs and load shifting based on smart household usage profiling  

Science Conference Proceedings (OSTI)

We present a system and study of personalized energy-related recommendation. AgentSwitch utilizes electricity usage data collected from users' households over a period of time to realize a range of smart energy-related recommendations on energy tariffs, ... Keywords: demand response, energy tariffs, load shifting, personalization, recommender systems, smart grid

Joel E. Fischer; Sarvapali D. Ramchurn; Michael Osborne; Oliver Parson; Trung Dong Huynh; Muddasser Alam; Nadia Pantidi; Stuart Moran; Khaled Bachour; Steve Reece; Enrico Costanza; Tom Rodden; Nicholas R. Jennings

2013-03-01T23:59:59.000Z

7

Table HC6.7 Air-Conditioning Usage Indicators by Number of Household...  

Gasoline and Diesel Fuel Update (EIA)

7 Air-Conditioning Usage Indicators by Number of Household Members, 2005 Total... 111.1 30.0 34.8 18.4 15.9...

8

U.S. Household Electricity Report  

Reports and Publications (EIA)

Brief analysis reports on the amount of electricity consumed annually by U.S. households for each of several end uses, including space heating and cooling, water heating, lighting, and the operation of more than two dozen appliances.

Barbara Fichman

2005-07-14T23:59:59.000Z

9

Form EIA-457E (2001) -- Household Bottled Gas Usage  

Annual Energy Outlook 2012 (EIA)

Fuel Oil or Kerosene Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the...

10

Electricity Use in California: Past Trends and Present Usage...  

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

Use in California: Past Trends and Present Usage Patterns Title Electricity Use in California: Past Trends and Present Usage Patterns Publication Type Journal Article Year of...

11

HOUSEHOLD RESPONSE TO DYNAMIC PRICING OF ELECTRICITY A SURVEY OF SEVENTEEN PRICING EXPERIMENTS  

E-Print Network (OSTI)

(DOE) defines demand response as "changes in electric usage by end-use customers from their normalHOUSEHOLD RESPONSE TO DYNAMIC PRICING OF ELECTRICITY A SURVEY OF SEVENTEEN PRICING EXPERIMENTS response in electricity markets. One of the best ways to let that happen is to let customers see

12

Electricity Prices for Households - EIA  

Gasoline and Diesel Fuel Update (EIA)

Households for Selected Countries1 Households for Selected Countries1 (U.S. Dollars per Kilowatthour) Country 2001 2002 2003 2004 2005 2006 2007 2008 2009 Argentina NA NA NA NA NA NA 0.023 NA NA Australia 0.091 0.092 0.094 0.098 NA NA NA NA NA Austria 0.144 0.154 0.152 0.163 0.158 0.158 0.178 0.201 NA Barbados NA NA NA NA NA NA NA NA NA Belgium NA NA NA NA NA NA NA NA NA Bolivia NA NA NA NA NA NA NA NA NA Brazil NA NA NA NA NA NA 0.145 0.171 NA Canada 0.067 0.069 0.070 0.071 0.076 0.078 NA NA NA Chile NA NA NA NA NA NA 0.140 0.195 NA China NA NA NA NA NA NA NA NA NA Chinese Taipei (Taiwan) 0.075 0.071 0.074 0.076 0.079 0.079 0.080 0.086 NA Colombia NA NA NA NA NA NA 0.111 0.135 NA

13

"Table HC7.5 Space Heating Usage Indicators by Household Income, 2005"  

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

5 Space Heating Usage Indicators by Household Income, 2005" 5 Space Heating Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Space Heating Usage Indicators" "Total U.S. Housing Units",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Do Not Have Heating Equipment",1.2,0.5,0.3,0.2,"Q",0.2,0.3,0.6 "Have Space Heating Equipment",109.8,26.2,28.5,20.4,13,21.8,16.3,37.9 "Use Space Heating Equipment",109.1,25.9,28.1,20.3,12.9,21.8,16,37.3

14

"Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005"  

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

0 Home Appliances Usage Indicators by Household Income, 2005" 0 Home Appliances Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Home Appliances Usage Indicators" "Total",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A Day",8.2,2.9,2.5,1.3,0.5,1,2.4,4.6 "2 Times A Day",24.6,6.5,7,4.3,3.2,3.6,4.8,10.3 "Once a Day",42.3,8.8,9.8,8.7,5.1,10,5,12.9

15

PHEV Utility Factors (UFs) Derived from Households' Vehicle Usage Patterns Jamie Davies, Ken Kurani  

E-Print Network (OSTI)

to calculate electrical consumption, emissions, fuel costs, and battery lifetime and degradation. Of particular of Battery Electric Vehicles (BEVs) while allowing consumers to make use of the familiar gasoline refueling, each household starts the day with a fully charged battery and does not recharge throughout the day

California at Davis, University of

16

Electricity Use in California: Past Trends and Present Usage...  

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

Electricity Use in California: Past Trends and Present Usage Patterns Speaker(s): Rich Brown Date: May 16, 2002 - 12:00pm Location: Bldg. 90 Was explosive growth in electricity...

17

Table HC6.5 Space Heating Usage Indicators by Number of Household Members, 2005  

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

5 Space Heating Usage Indicators by Number of Household Members, 2005 5 Space Heating Usage Indicators by Number of Household Members, 2005 Total U.S. Housing Units.................................. 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Heating Equipment..................... 1.2 0.3 0.3 Q 0.2 0.2 Have Space Heating Equipment....................... 109.8 29.7 34.5 18.2 15.6 11.8 Use Space Heating Equipment........................ 109.1 29.5 34.4 18.1 15.5 11.6 Have But Do Not Use Equipment.................... 0.8 Q Q Q Q Q Space Heating Usage During 2005 Heated Floorspace (Square Feet) None............................................................ 3.6 1.0 0.8 0.5 0.5 0.7 1 to 499........................................................ 6.1 3.0 1.6 0.6 0.6 0.3 500 to 999.................................................... 27.7 11.6 8.3 3.6 2.7 1.6 1,000 to 1,499..............................................

18

Testing Electric Vehicle Demand in `Hybrid Households' Using a Reflexive Survey  

E-Print Network (OSTI)

1994) Demand for Electric Vehicles in Hybrid Households: A nand the Household Electric Vehicle Market: A Constraintsthe mar- ket for electric vehicles in California. Presented

Kurani, Kenneth; Turrentine, Thomas; Sperling, Daniel

1996-01-01T23:59:59.000Z

19

Table HC6.7 Air-Conditioning Usage Indicators by Number of Household Members, 2005  

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

7 Air-Conditioning Usage Indicators by Number of Household Members, 2005 7 Air-Conditioning Usage Indicators by Number of Household Members, 2005 Total........................................................................ 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Cooling Equipment.......................... 17.8 5.4 5.3 2.7 2.5 2.0 Have Cooling Equipment...................................... 93.3 24.6 29.6 15.7 13.4 10.0 Use Cooling Equipment....................................... 91.4 24.0 29.1 15.5 13.2 9.7 Have Equipment But Do Not Use it...................... 1.9 0.6 0.5 Q 0.2 0.4 Type of Air-Conditioning Equipment 1, 2 Central System................................................... 65.9 15.3 22.6 10.7 9.9 7.3 Without a Heat Pump....................................... 53.5 12.5 17.9 8.7 8.2 6.3 With a Heat Pump............................................ 12.3

20

Table HC6.12 Home Electronics Usage Indicators by Number of Household Members, 2005  

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

2 Home Electronics Usage Indicators by Number of Household Members, 2005 2 Home Electronics Usage Indicators by Number of Household Members, 2005 Total................................................................................ 111.1 30.0 34.8 18.4 15.9 12.0 Personal Computers Do Not Use a Personal Computer............................. 35.5 16.3 9.4 4.0 2.7 3.2 Use a Personal Computer.......................................... 75.6 13.8 25.4 14.4 13.2 8.8 Most-Used Personal Computer Type of PC Desk-top Model..................................................... 58.6 10.0 20.0 11.2 10.1 7.3 Laptop Model........................................................ 16.9 3.7 5.4 3.2 3.1 1.5 Hours Turned on Per Week Less than 2 Hours................................................. 13.6 4.0 4.7 1.7 1.8 1.4 2 to 15 Hours........................................................

Note: This page contains sample records for the topic "household electricity usage" 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

How Households Use Different Types of Vehicles: A Structural Driver Allocation and Usage Model  

E-Print Network (OSTI)

types Mini cars have approximately average usage. SubcompactCompact cars have greater than average usage only if theycar is driven morethan otherwise expected. The . -elationships between usage

Golob, Thomas F.; Kim, Seyoung; Ren, Weiping

1996-01-01T23:59:59.000Z

22

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis--A Reflively Designed Survey of New-car-buying, Multi-vehicle California Households  

E-Print Network (OSTI)

by electric and hybrid vehicles", SAE Technical Papers No.household response to hybrid vehicles. Finally, we suggestas electric or hybrid vehicles. Transitions in choices of

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

23

Household Electricity Usage Form - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

2005 Residential Energy Consumption Survey. Sponsored by the Energy Information Administration . U.S. Department of Energy . Washington, DC 20585 . Form EIA-457E ...

24

How Households Use Different Types of Vehicles: A Structural Driver Allocation and Usage Model  

E-Print Network (OSTI)

the first car. Mid-size car usage also involves the secondTypes Mini cars have approximately average usage. SubcompactCompact cars have greater than average usage only if they

Golob, Thomas F.; Kim, Seyoung K.; Ren, Weiping Willliam

1995-01-01T23:59:59.000Z

25

Elasticities of Electricity Demand in Urban Indian Households  

E-Print Network (OSTI)

Energy demand, and in particular electricity demand in India has been growing at a very rapid rate over the last decade. Given, current trends in population growth, industrialisation, urbanisation, modernisation and income growth, electricity consumption is expected to increase substantially in the coming decades as well. Tariff reforms could play a potentially important role as a demand side management tool in India. However, the effects of any price revisions on consumption will depend on the price elasticity of demand for electricity. In the past, electricity demand studies for India published in international journals have been based on aggregate macro data at the country or sub-national / state level. In this paper, price and income elasticities of electricity demand in the residential sector of all urban areas of India are estimated for the first time using disaggregate level survey data for over thirty thousand households. Three electricity demand functions have been estimated using monthly data for the following seasons: winter, monsoon and summer. The results show electricity demand is income and price inelastic in all three seasons, and that household, demographic and geographical variables are important in determining electricity demand, something that is not possible to determine using aggregate macro models alone. Key Words Residential electricity demand, price elasticity, income elasticity Short Title Electricity demand in Indian households Acknowledgements: The authors would like to gratefully acknowledge the National Sample Survey Organisation, Department of Statistics of the Government of India, for making available to us the unit level, household survey data. We would also like to thank Prof. Daniel Spreng for his support of our research. 2 1.

Shonali Pachauri

2002-01-01T23:59:59.000Z

26

Answers to Frequently Asked Questions About the Household ...  

U.S. Energy Information Administration (EIA)

Form EIA-457E (2001) – Household Electricity Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey

27

A functional analysis of electrical load curve modelling for some households specific electricity end-uses  

E-Print Network (OSTI)

A functional analysis of electrical load curve modelling for some households specific electricity and the way electrical devices are used will evolve significantly. The energy consumption is likely of electrical devices; · integration of decentralized energy production and stocking (PV modules with battery

Paris-Sud XI, Université de

28

Testing Electric Vehicle Demand in "Hybrid Households" Using a Reflexive Survey  

E-Print Network (OSTI)

In contrast to a hybrid vehicle whichcombines multiple1994) "Demand Electric Vehicles in Hybrid for Households:or 180 mile hybrid electric vehicle. Natural gas vehicles (

Kurani, Kenneth S.; Turrentine, Thomas; Sperling, Daniel

2001-01-01T23:59:59.000Z

29

Table CE3-6.1u. Electric Air-Conditioning Energy Consumption and ...  

U.S. Energy Information Administration (EIA)

Table CE3-6.1u. Electric Air-Conditioning Energy Consumption and Expenditures by Household Member and Usage Indicators, 2001 Usage Indicators RSE Column Factor:

30

The Impact of Carbon Control on Low-Income Household Electricity and Gasoline Expenditures  

SciTech Connect

In July of 2007 The Department of Energy's (DOE's) Energy Information Administration (EIA) released its impact analysis of 'The Climate Stewardship And Innovation Act of 2007,' known as S.280. This legislation, cosponsored by Senators Joseph Lieberman and John McCain, was designed to significantly cut U.S. greenhouse gas emissions over time through a 'cap-and-trade' system, briefly described below, that would gradually but extensively reduce such emissions over many decades. S.280 is one of several proposals that have emerged in recent years to come to grips with the nation's role in causing human-induced global climate change. EIA produced an analysis of this proposal using the National Energy Modeling System (NEMS) to generate price projections for electricity and gasoline under the proposed cap-and-trade system. Oak Ridge National Laboratory integrated those price projections into a data base derived from the EIA Residential Energy Consumption Survey (RECS) for 2001 and the EIA public use files from the National Household Transportation Survey (NHTS) for 2001 to develop a preliminary assessment of impact of these types of policies on low-income consumers. ORNL will analyze the impacts of other specific proposals as EIA makes its projections for them available. The EIA price projections for electricity and gasoline under the S.280 climate change proposal, integrated with RECS and NHTS for 2001, help identify the potential effects on household electric bills and gasoline expenditures, which represent S.280's two largest direct impacts on low-income household budgets in the proposed legislation. The analysis may prove useful in understanding the needs and remedies for the distributive impacts of such policies and how these may vary based on patterns of location, housing and vehicle stock, and energy usage.

Eisenberg, Joel Fred [ORNL

2008-06-01T23:59:59.000Z

31

The Impact of Carbon Control on Low-Income Household Electricity and Gasoline Expenditures  

SciTech Connect

In July of 2007 The Department of Energy's (DOE's) Energy Information Administration (EIA) released its impact analysis of 'The Climate Stewardship And Innovation Act of 2007,' known as S.280. This legislation, cosponsored by Senators Joseph Lieberman and John McCain, was designed to significantly cut U.S. greenhouse gas emissions over time through a 'cap-and-trade' system, briefly described below, that would gradually but extensively reduce such emissions over many decades. S.280 is one of several proposals that have emerged in recent years to come to grips with the nation's role in causing human-induced global climate change. EIA produced an analysis of this proposal using the National Energy Modeling System (NEMS) to generate price projections for electricity and gasoline under the proposed cap-and-trade system. Oak Ridge National Laboratory integrated those price projections into a data base derived from the EIA Residential Energy Consumption Survey (RECS) for 2001 and the EIA public use files from the National Household Transportation Survey (NHTS) for 2001 to develop a preliminary assessment of impact of these types of policies on low-income consumers. ORNL will analyze the impacts of other specific proposals as EIA makes its projections for them available. The EIA price projections for electricity and gasoline under the S.280 climate change proposal, integrated with RECS and NHTS for 2001, help identify the potential effects on household electric bills and gasoline expenditures, which represent S.280's two largest direct impacts on low-income household budgets in the proposed legislation. The analysis may prove useful in understanding the needs and remedies for the distributive impacts of such policies and how these may vary based on patterns of location, housing and vehicle stock, and energy usage.

Eisenberg, Joel Fred [ORNL

2008-06-01T23:59:59.000Z

32

Energy Usage Evaluation and Condition Monitoring for Electric Machines using Wireless Sensor Networks.  

E-Print Network (OSTI)

??Energy usage evaluation and condition monitoring for electric machines are important in industry for overall energy savings. Traditionally these functions are realized only for large… (more)

Lu, Bin

2006-01-01T23:59:59.000Z

33

"Table HC7.5 Space Heating Usage Indicators by Household Income...  

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

5,11.2,6.7,13.2,5.8,14.5 "Housing Unit Characteristics Affecting Usage" "Adequacy of Insulation" "Well Insulated",42.8,9,11,8.2,5.1,9.5,4.8,13.1 "Adequately Insulated",46.3,10.4,11...

34

Testing Electric Vehicle Demand in `Hybrid Households' Using a Reflexive Survey  

E-Print Network (OSTI)

or 180 mile hybrid electric vehicle. Natural gas vehicles (1994) Demand for Electric Vehicles in Hybrid Households: A nof Electric, Hybrid and Other Alternative Vehicles. A r t h

Kurani, Kenneth; Turrentine, Thomas; Sperling, Daniel

1996-01-01T23:59:59.000Z

35

Integrate Real-Time Weather with Thermostat Electrical Usage...  

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

Xiufeng Pang Weather and its dynamics are big drivers of energy usage. Integration of key weather variables - solar, wind, and temperature - into home energy management and demand...

36

1 HOUSEHOLD RESPONSE TO DYNAMIC PRICING OF ELECTRICITY—A SURVEY OF THE EXPERIMENTAL EVIDENCE  

E-Print Network (OSTI)

Since the energy crisis of 2000-2001 in the western United States, much attention has been given to boosting demand response in electricity markets. One of the best ways to let that happen is to pass through wholesale energy costs to retail customers. This can be accomplished by letting retail prices vary dynamically, either entirely or partly. For the overwhelming majority of customers, that requires a changeout of the metering infrastructure, which may cost as much as $40 billion for the US as a whole. While a good portion of this investment can be covered by savings in distribution system costs, about 40 percent may remain uncovered. This investment gap could be covered by reductions in power generation costs that could be brought about through demand response. Thus, state regulators in many states are investigating whether customers will respond to the higher prices by lowering demand and if so, by how much. To help inform this assessment, we survey the evidence from the 15 most recent experiments with dynamic pricing of electricity. We find conclusive evidence that households (residential customers) respond to higher prices by lowering usage. The magnitude of price response depends on several factors, such as the magnitude of the price increase, the presence of central air conditioning and the availability of enabling technologies such as two-way

Ahmad Faruqui; Sanem Sergici

2009-01-01T23:59:59.000Z

37

DND: a model for forecasting electrical energy usage by water-resource subregion  

SciTech Connect

A forecast methodology was derived from principles of econometrics using exogenous variables, i.e., cost of electricity, consumer income, and price elasticity as indicators of growth for each consuming sector: residential, commercial, and industrial. The model was calibrated using forecast data submitted to the Department of Energy (DOE) by the nine Regional Electric Reliability Councils. Estimates on electrical energy usage by specific water-resource subregion were obtained by normalizing forecasted total electrical energy usage by state into per capita usage. The usage factor and data on forecasted population were applied for each water resource subregion. The results derived using the model are self-consistent and in good agreement with DOE Energy Information Administration projections. The differences that exist are largely the result of assumptions regarding specific aggregations and assignment of regional-system reliability and load factors. 8 references, 2 figures, 13 tables.

Sonnichsen, J.C. Jr.

1980-02-01T23:59:59.000Z

38

Household Markets for Neighborhood Electric Vehicles in California  

E-Print Network (OSTI)

A Statewide ELECTRIC ELECTRIC and VEHICLES: Survey Sandrafor Neighborhood Electric Vehicles. Report prepared for theD. (1994). Future Drive: Electric Vehicles and Sustainable

Kurani, Kenneth S.; Sperling, Daniel; Lipman, Timothy; Stanger, Deborah; Turrentine, Thomas; Stein, Aram

2001-01-01T23:59:59.000Z

39

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis--A Reflively Designed Survey of New-car-buying, Multi-vehicle California Households  

E-Print Network (OSTI)

HOW MANY HYBRID HOUSEHOLDS IN THE CALIFORNIA NEW CAR MARKET?average 2.43 cars per household, then the hybrid householdnumber of multi-car households that fit our hybrid household

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

40

Demand for Electric Vehicles in Hybrid Households: An Exploratory Analysis  

E-Print Network (OSTI)

stated they wouldlikely add an electric and vehicle to theirhouseholdsand the demand electric vehicles", Transportation1983) "A Critical Reviewof Electric Vehicle MarketStudies",

Kurani, Kenneth S.; Turrentine, Tom; Sperling, Daniel

1994-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household electricity usage" 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

Household Markets for Neighborhood Electric Vehicles in California  

E-Print Network (OSTI)

for Neighborhood Electric Vehicles. Report prepared for theD. (1994). Future Drive: Electric Vehicles and Sustainablefor Neighborhood Electric Vehicles. Report prepared for the

Kurani, Kenneth S; Sperling, Daniel; Lipman, Timothy; Stanger, Deborah; Turrentine, Thomas; Stein, Aram

1995-01-01T23:59:59.000Z

42

Learning policies for battery usage optimization in electric vehicles  

Science Conference Proceedings (OSTI)

The high cost, limited capacity, and long recharge time of batteries pose a number of obstacles for the widespread adoption of electric vehicles. Multi-battery systems that combine a standard battery with supercapacitors are currently one of the most ...

Stefano Ermon; Yexiang Xue; Carla Gomes; Bart Selman

2012-09-01T23:59:59.000Z

43

Household Markets for Neighborhood Electric Vehicles in California  

E-Print Network (OSTI)

of electric and compressed natural gas vehicles; and Twogasoline, compressed natural gas, hybrid electric, and threethe batteries. f-v Compressed natural gas vehicle Natural g

Kurani, Kenneth S; Sperling, Daniel; Lipman, Timothy; Stanger, Deborah; Turrentine, Thomas; Stein, Aram

1995-01-01T23:59:59.000Z

44

Electricity Use in California: Past Trends and Present Usage Patterns  

E-Print Network (OSTI)

; thus, it includes loads served by self-generation. System peak load is measured at the power plant-use. We examine the growth in electricity demand between 1980 and 2000, as well as the composition in California in the 1990s did not grow explosively, nor was the amount of growth unanticipated. In both

45

A Mixed Nordic Experience: Implementing Competitive Retail Electricity Markets for Household Customers  

Science Conference Proceedings (OSTI)

Although the Nordic countries were among the first to develop competition in the electricity industry, it took a long time to make retail competition work. In Norway and Sweden a considerable number of households are actively using the market but very few households are active in Finland and Denmark. One problem has been institutional barriers involving metering, limited unbundling of distribution and supply, and limited access to reliable information on contracts and prices. (author)

Olsen, Ole Jess; Johnsen, Tor Arnt; Lewis, Philip

2006-11-15T23:59:59.000Z

46

Household Markets for Neighborhood Electric Vehicles in California  

E-Print Network (OSTI)

electric vehicles designed for local, neighborhood travel How we are funded — Calstart: a consortium of private industry,

Kurani, Kenneth S; Sperling, Daniel; Lipman, Timothy; Stanger, Deborah; Turrentine, Thomas; Stein, Aram

1995-01-01T23:59:59.000Z

47

Household Response To Dynamic Pricing Of Electricity: A Survey...  

Open Energy Info (EERE)

property. This report surveys evidence from 15 recent experiments with dynamic pricing of electricity in the United States and Canada. The report suggests conclusive evidence that...

48

Household Markets for Neighborhood Electric Vehicles in California  

E-Print Network (OSTI)

of electric and compressed natural gas vehicles; and Twogasoline, compressed natural gas, hybridelectric, and threeon the batteries. Compressed natural gas vehicle Natural

Kurani, Kenneth S.; Sperling, Daniel; Lipman, Timothy; Stanger, Deborah; Turrentine, Thomas; Stein, Aram

2001-01-01T23:59:59.000Z

49

Determinants of residential electrical appliance usage in the Tri-State Region, 1960-1970: a regression study. Working paper  

SciTech Connect

The possible impact of areawide residential location policy on future residential electricity usage in the Tri-State Metropolitan Region centering on New York City is investigated. This study was undertaken to assess residential electricity usage, particularly electrical appliance use, in the residential sector of the New York Metropolitan area from 1960 to 1970. The attempts to choose and quantify the contribution of various determinants of electrical appliance usage using multiple regression analyses has been relatively successful. In addition, these results were compared with 1960 and 1970 data in an effort to establish a degree of consistency over time. The implications of the findings here point toward two complementary institutions for change: urban planning and public administration. The relationship between single family structures and high energy usage argue strongly for more dense communities, while price elasticities can be used by regulators to control electrical usage.

Stone, B.

1974-05-01T23:59:59.000Z

50

On the energy sources of Mozambican households and the demand-supply curves for domestic electricity in the northern electrical grid in Mozambique.  

E-Print Network (OSTI)

??The development of electrical infrastructure to supply rural households is considered economically unfeasible because of the high cost of capital investment required to expand the… (more)

Arthur, Maria de Fatima Serra Ribeiro

2009-01-01T23:59:59.000Z

51

Residential hot water usage: A review of published metered studies. Topical report, August-December 1994  

SciTech Connect

The report presents a review of residential hot water usage studies. The studies included were published and publicly available, they measured actual hot water usage or energy usage, and they had sufficient demographic information to determine the number of people per household. The available hot water usage data were normalized to a 135 F setpoint temperature to eliminate the variations in usage caused by different water heater thermostat settings. Typical hot water usage as a function of family size was determined from linear regression analyses of the normalized metered studies` data points. A national average hot water usage of 53 gallons per day was determined from the regression analyses and census data on average household size. The review of metered studies also shows that there is no discernible difference in hot water usage for households with either electric or gas water heaters.

Paul, D.D.; Ide, B.E.; Hartford, P.A.

1994-12-01T23:59:59.000Z

52

Commercializing Light-Duty Plug-In/Plug-Out Hydrogen-Fuel-Cell Vehicles: "Mobile Electricity" Technologies, Early California Household Markets, and Innovation Management  

E-Print Network (OSTI)

assessment for fuel cell electric vehicles." Argonne, Ill. :of Plug-In Hybrid Electric Vehicles on Wind Energy Markets,"Recharging and Household Electric Vehicle Market: A Near-

Williams, Brett D

2010-01-01T23:59:59.000Z

53

Household Response To Dynamic Pricing Of Electricity: A Survey Of The  

Open Energy Info (EERE)

Household Response To Dynamic Pricing Of Electricity: A Survey Of The Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Focus Area: Crosscutting Topics: Market Analysis Website: www.hks.harvard.edu/hepg/Papers/2009/The%20Power%20of%20Experimentatio Equivalent URI: cleanenergysolutions.org/content/household-response-dynamic-pricing-el Language: English Policies: "Deployment Programs,Regulations,Financial Incentives" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Demonstration & Implementation Regulations: "Mandates/Targets,Cost Recovery/Allocation,Enabling Legislation" is not in the list of possible values (Agriculture Efficiency Requirements, Appliance & Equipment Standards and Required Labeling, Audit Requirements, Building Certification, Building Codes, Cost Recovery/Allocation, Emissions Mitigation Scheme, Emissions Standards, Enabling Legislation, Energy Standards, Feebates, Feed-in Tariffs, Fuel Efficiency Standards, Incandescent Phase-Out, Mandates/Targets, Net Metering & Interconnection, Resource Integration Planning, Safety Standards, Upgrade Requirements, Utility/Electricity Service Costs) for this property.

54

Leaking electricity: Standby and off-mode power consumption in consumer electronics and household appliances  

Science Conference Proceedings (OSTI)

This report assesses ``leaking`` electricity from consumer electronics and small household appliances when they are in standby mode or turned off, and examines the impacts of these losses. The report identifies trends in relevant product industries and gives technical and policy options for reducing standby and off-mode power loss.

Thorne, J.; Suozzo, M.

1998-12-31T23:59:59.000Z

55

A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact  

DOE Green Energy (OSTI)

The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level. It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.

Cui, Xiaohui [ORNL; Liu, Cheng [ORNL; Kim, Hoe Kyoung [ORNL; Kao, Shih-Chieh [ORNL; Tuttle, Mark A [ORNL; Bhaduri, Budhendra L [ORNL

2011-01-01T23:59:59.000Z

56

Own-price and income elasticities for household electricity demand : a survey of literature using meta-regression analysis.  

E-Print Network (OSTI)

??Maria Wist Langmoen Own-price and income elasticities for household electricity demand -A Literature survey using meta-regression analysis Economists have been modelling the electricity demand for… (more)

Langmoen, Maria Wist

2004-01-01T23:59:59.000Z

57

A statistical analysis of structural differences in minority household electricity demand  

SciTech Connect

In this paper, the structures for electricity demand in non-Latino Black and White households are compared. Electricity demand will be analyzed within the context of a complete demand system, and statistical tests for structural differences will be systematically conducted in the hope of pinpointing the location of differences within the context of this model. Structural differences in demand are defined as statistically significant differences in a parameter or group of parameters that identify the quantitative relationship between explanatory variables and electricity consumption. Along with population taste differences, which might emanate from historical and cultural population differences, structural differences might also occur because of differences in housing and geographic patterns and as a result of differences in access to markets and information. As a consequence, energy consumption decisions will differ, and the level and composition of energy consumption are likely to vary. In practice, it is nearly impossible to untangle the causes contributing to structural differences, but it is reasonably easy to test for statistical differences. The superficial evidence indicates there is a strong likelihood that structural differences do exist in electricity demand between White and Black households. The null hypothesis, which states that there exist no differences in the structures for electricity demand for Black and White households, is tested.

Poyer, D.A.; Earl, E.

1994-09-01T23:59:59.000Z

58

Electricity displacement by wood used for space heating in PNWRES (Pacific Northwest Residential Energy Survey) (1983) households  

DOE Green Energy (OSTI)

This report evaluates the amount of electricity for residential space heating displaced by the use of wood in a sample of single-family households that completed the 1983 Pacific Northwest Residential Energy Survey. Using electricity bills and daily weather data from the period of July 1981 to July 1982, it was determined that the average household used 21,800 kWh per year, normalized with respect to weather. If no households had used any wood, electricity use would have increased 9%, to 23,700 kWh; space heating electricity use would also have increased, by 21%, to 47% of total electricity use. In the unlikely event that all households had used a great deal of wood for space heating, electricity use could have dropped by 23.5% from the average use, to 16,700 kWh; space heating electricity use would have dropped by 56%, to 24% of total electricity use. Indications concerning future trends regarding the displacement of electricity by wood use are mixed. On one hand, continuing to weatherize homes in the Pacific Northwest may result in less wood use as households find using electricity more economical. On the other hand, historical trends in replacement decisions regarding old space heating systems show a decided preference for wood. 11 refs., 6 figs., 8 tabs.

White, D.L.; Tonn, B.E.

1988-12-01T23:59:59.000Z

59

A Model of Household Demand for Activity Participation and Mobility  

E-Print Network (OSTI)

household car ownership, car usage, and travel by differentownership demand, and car usage demand. Modal travel demand,mode), car ownership, and car usage for spatial aggregations

Golob, Thomas F.

1996-01-01T23:59:59.000Z

60

Usage of Electric Vehicle Supply Equipment Along the Corridors between the EV Project Major Cities  

DOE Green Energy (OSTI)

The report explains how the EVSE are being used along the corridors between the EV Project cities. The EV Project consists of a nationwide collaboration between Idaho National Laboratory (INL), ECOtality North America, Nissan, General Motors, and more than 40 other city, regional and state governments, and electric utilities. The purpose of the EV Project is to demonstrate the deployment and use of approximately 14,000 Level II (208-240V) electric vehicle supply equipment (EVSE) and 300 fast chargers in 16 major cities. This research investigates the usage of all currently installed EV Project commercial EVSE along major interstate corridors. ESRI ArcMap software products are utilized to create geographic EVSE data layers for analysis and visualization of commercial EVSE usage. This research locates the crucial interstate corridors lacking sufficient commercial EVSE and targets locations for future commercial EVSE placement. The results and methods introduced in this research will be used by INL for the duration of the EV Project.

Mindy Kirkpatrick

2012-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "household electricity usage" 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

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis--A Reflively Designed Survey of New-car-buying, Multi-vehicle California Households  

E-Print Network (OSTI)

gas vehicles and hybrid electric vehicles, in addition toof range, and hybrid electric vehicles with 140 and 180possible designs of hybrid electric vehicles pose complex

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

62

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis -- A Reflexively Designed Survey of New-Car-Buying Multi-Vehicle California Households  

E-Print Network (OSTI)

gas vebacles and hybrid electric vehicles, maddition tocontrast to a hybrid electric vehicle that combines electrichousehold.In contrast to a hybrid electric vehicle that of

Turrentine, Thomas; Kurani, Kenneth S.

2001-01-01T23:59:59.000Z

63

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis -- A Reflexively Designed Survey of New-Car-Buying Multi-Vehicle California Households  

E-Print Network (OSTI)

Gromer, C Newage of the electric car. Popular Mechanics.VEHICLES strongly favor electric cars, but on the other,electric vehicles, if an electric car wasavailable to buy

Turrentine, Thomas; Kurani, Kenneth S.

2001-01-01T23:59:59.000Z

64

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis--A Reflively Designed Survey of New-car-buying, Multi-vehicle California Households  

E-Print Network (OSTI)

Gromer, C. New age of the electric car. Popular Mechanics.VEHICLES strongly favor electric cars, but on the other,electric vehicles, if an electric car was available to buy

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

65

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

66

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis -- A Reflexively Designed Survey of New-Car-Buying Multi-Vehicle California Households  

E-Print Network (OSTI)

and the demand electric vehicles", Transportation ResearchA,Critical Review Electric Vehicle MarketStudies", ReleasableR. (1993) Report of the Electric Vehicle at-HomeRefi~ehng

Turrentine, Thomas; Kurani, Kenneth S.

2001-01-01T23:59:59.000Z

67

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis--A Reflively Designed Survey of New-car-buying, Multi-vehicle California Households  

E-Print Network (OSTI)

a sidebar to a longer article on electric vehicles. ) Cogan,R. Electric vehicles: Powerplay on the auto circuit. MotorA Critical Review of Electric Vehicle Market Studies",

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

68

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis--A Reflively Designed Survey of New-car-buying, Multi-vehicle California Households  

E-Print Network (OSTI)

size styles) 5. Compressed natural gas, ranges 80 or 120,Hybrid electric: Compressed natural gas: Reformulatedof electric, compressed natural gas and methanol fueled

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

69

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis--A Reflively Designed Survey of New-car-buying, Multi-vehicle California Households  

E-Print Network (OSTI)

of electric vehicles the safety of compressed gas vehicleselectric vehicles the practicality of home recharging or the safety

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

70

EREV and BEV Economic Viability vs. Household Retail Electric Pricing Strategies: Two Charges a Day?  

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

EREV and BEV Economic Viability vs. EREV and BEV Economic Viability vs. Household Retail Electric Pricing Strategies: Two Charges a Day? By Dan Santini Argonne National Laboratory dsantini@anl.gov Remarks are attributable only to the author; not to Argonne or U.S. Department of Energy NAATBatt Conference: The Impact of PEVs on T&D Systems: Challenges and Solutions Dec. 7, 2010 The submitted manuscript has been created by Argonne National Laboratory, a U.S. Department of Energy laboratory managed by UChicago Argonne, LLC, under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up, nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly,

71

Electrical Usage Profiling The roll out of Smart Meters between now and 2020 will allow  

E-Print Network (OSTI)

be the first to be targeted · Black houses are heavier users · Blue houses use less power so probably wouldn generation such as solar power and how it affects the household's behaviours Summer 2012 Possible of the households to target for particular incentives. · Red houses are creatures of habit, show very little

Aickelin, Uwe

72

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis -- A Reflexively Designed Survey of New-Car-Buying Multi-Vehicle California Households  

E-Print Network (OSTI)

by electric and hybrid vehicles", SAETechmcal Papers No.may response to hybrid vehicles Finally, we suggest thatsamebetweenvehicle tyoes. Hybrid Vehicles for examplecost a

Turrentine, Thomas; Kurani, Kenneth S.

2001-01-01T23:59:59.000Z

73

Techno-economics analysis of a wind/PV hybrid system to provide electricity for a household in Malaysia  

Science Conference Proceedings (OSTI)

This paper is study on techno-economics analysis of a wind/PV hybrid system for a household in Malaysia. One year recorded wind speed and solar radiation are used for the design of a hybrid energy system. In 2004 average annual wind speed in Kuala Terengganu ... Keywords: electrical load, techno-economics analysis, wind/PV hybrid system

Ahmad Fudholi; Mohd Zamri Ibrahim; Mohd Hafidz Ruslan; Lim Chin Haw; Sohif Mat; Mohd Yusof Othman; Azami Zaharim; Kamaruzzaman Sopian

2012-01-01T23:59:59.000Z

74

Electric  

U.S. Energy Information Administration (EIA)

Average Retail Price of Electricity to ... Period Residential Commercial Industrial ... or usage falling within specified limits by rate ...

75

Assessing the Environmental Costs and Benefits of Households Electricity Consumption Management.  

E-Print Network (OSTI)

?? In this study the environmental costs and benefits of smart metering technology systems installed in households in Norway have been assessed. Smart metering technology… (more)

Segtnan, Ida Lund

2011-01-01T23:59:59.000Z

76

Residential energy usage comparison project: An overview  

SciTech Connect

This report provides an overveiw of the residential energy usage comparison project, an integrated load and market research project sponsored by EPRI and the Southern California Edison Company. Traditional studies of the relative energy consumption of electric and gas household appliances have relied on laboratory analyses and computer simulations. This project was designed to study the appliance energy consumption patterns of actual households. Ninety-two households in Orange County, California, southeast of Los Angeles, served as the study sample. Half of the households received new electric space-conditioning, water-heating, cooking, and clothes-drying equipment; the other half received gas equipment. The electric space-conditioning and water-heating appliances were heat pump technologies. All of the appliances were metered to collect load-shape and energy consumption data. The households were also surveyed periodically to obtain information on their energy needs and their acceptance of the appliances. The metered energy consumption data provide an important benchmark for comparing the energy consumption and costs of alternative end-use technologies. The customer research results provide new insights into customer preferences for fuel and appliance types. 15 figs., 3 tabs.

Smith, B.A.; Uhlaner, R.T.; Cason, T.N. (Quantum Consulting, Inc., Berkeley, CA (USA))

1990-10-01T23:59:59.000Z

77

Usage of Appliances in U - Energy Information Administration  

U.S. Energy Information Administration (EIA)

U.S. Households Usage of Appliances in 1997. Household PCs by Year. The number of personal computers (PCs) in U.S. households has risen from zero in 1976, when the ...

78

Guidelines for Energy Cost Savings Resulting from Tracking and Monitoring Electrical nad Natural Gas Usage, Cost, and Rates  

E-Print Network (OSTI)

This paper discusses how improved energy information in schools and hospitals from tracking and monitoring electrical and natural gas usage, cost, and optional rate structures, can reduce energy costs. Recommendations, methods, and guidelines for monitoring and tracking of utilities are provided. These recommendations, methods, and guidelines are the result of on-site work for schools and hospitals . Recently completed energy usage survey and observations of several hospitals in Texas are included. Opportunities exist for schools, hospitals, and other buildings t o achieve significant dollar savings by good utility management. Understanding utility rate structures is essential for minimizing energy costs. The authors' data is for Texas schools and hospitals, but the principles presented apply to other geographic areas.

McClure, J. D.; Estes, M. C.; Estes, J. M.

1989-01-01T23:59:59.000Z

79

A dynamic model system of household car ownership, trip generation, and modal split: model development and simulation experiment  

E-Print Network (OSTI)

household car ownership, mode usage, and sociodemographictrip making and mode usage upon car ownership appears to beto predict car ownership and mode usage by the panel

Kitamura, Ryuichi

2009-01-01T23:59:59.000Z

80

Annotated compilation of the sources of information related to the usage of electricity in non-industrial applications. [Includes about 400 abstracts and glossary  

SciTech Connect

This report presents a thorough compilation of the sources of information related to the usage of electricity in non-industrial applications, as available in the open literature and from the U.S. electrical power industry. The report's scope encompasses all aspects of: electric load management; end use; and the various methods of acquisition, analysis and implementation of electricity usage data. There are over 400 abstracts; 156 from the Load Research Committee of Association of Edison Illuminating Companies (LRC/AEIC) reports and 264 from the open literature. The abstracts over references containing over 12,000 pages plus about 2,500 references and 6,200 graphs and tables pertinent to electricity usage in non-industrial applications. In addition to the LRC/AEIC abstracts, this document identifies over 100 sources of directly relevant information (in contrast to general interest sources and material of secondary relevance).

1978-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "household electricity usage" 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

An annotated compilation of the sources of information related to the usage of electricity in non-industrial applications. Final report  

SciTech Connect

The report is a thorough compilation of the sources of information related to the usage of electricity in non-industrial applications, as available in the open literature and from the U.S. electrical power industry. The report's scope encompasses all aspects of: electric load management; end-use; and the various methods of acquisition, analysis, and implementation of electricity usage data. There are over 400 abstracts; 156 from LRC/AEIC reports, and 264 from the open literature. The abstracts cover references containing over 12,000 pages plus about 2,500 references and 6,200 graphs and tables pertinent to electricity usage in non-industrial applications. In addition to the LRC/AEIC abstracts, this document identifies over 100 sources of directly relevant information (in contrast to general interest sources and material of secondary relevance).

Reznek, B.

1978-07-01T23:59:59.000Z

82

Testing Electric Vehicle Demand in "Hybrid Households" Using a Reflexive Survey  

E-Print Network (OSTI)

the demand electric vehicles’, TransportationResearchA,1994) ~tive NewsCalifornia Electric Vehicle ConsumerStudy.1995) Forecasting Electric Vehicle Ownership Use in the

Kurani, Kenneth S.; Turrentine, Thomas; Sperling, Daniel

2001-01-01T23:59:59.000Z

83

Use of electricity billing data to determine household energy use fingerprints  

Science Conference Proceedings (OSTI)

Ways to analyze billing data are discussed. The starting point for these analyses is a method developed at Princeton University. Their Scorekeeping model permits decomposition of total household energy use into its weather- and nonweather-sensitive elements; the weather-sensitive portion is assumed proportional to heating degree days. The Scorekeeping model also allows one to compute weather-adjusted energy consumption for each household based on its billing data and model parameters; this is the model's estimate of annual consumption under long-run weather conditions. The methods discussed here extend the Scorekeeping results to identify additional characteristics of household energy use. In particular, the methods classify households in terms of the intensity with which the particular fuel is used for space heating (primary heating fuel vs supplemental heating fuel vs no heating at all with the fuel). In addition, households that use the particular fuel for air conditioning are identified. In essence, the billing data and model results are used to determine household energy use fingerprints. The billing data and model results can also be used to identify and correct anomalous bills. The automated method discussed here identifies anomalously high or low utility bills, which are then dropped before re-estimation of the Scorekeeping model parameters. Alternatively, a pair of bills may be combined if one is very high and a temporally adjacent bill is very low. The Scorekeeping model is then re-estimated after the two bills are combined into one. The methods permit careful examination and analysis of changes in energy use from one year to another.

Hirst, E.; Goeltz, R.; White, D.

1984-08-01T23:59:59.000Z

84

The Load Leveling Approach to Removing Appliance Features from Home Electricity Usage Profiles.  

E-Print Network (OSTI)

??For the past twenty years, researchers have developed a class of algorithms that are capable of disaggregating a residential electric load into its set of… (more)

McLaughlin, Stephen

2011-01-01T23:59:59.000Z

85

202-328-5000 www.rff.orgA New Look at Residential Electricity Demand Using Household Expenditure Data  

E-Print Network (OSTI)

We estimate residential electricity demand for different regions of the country, assuming that consumers respond to average electricity prices. We circumvent the need for individual billing information by developing a novel generalized method of moments approach that allows us to estimate demand based on household electricity expenditure data from the Consumer Expenditure Survey, which does not have quantity and price information. We find that price elasticity estimates vary across the four census regions—the South at –1.02 is the most price-elastic region and the Northeast at –0.82 is the least—and are essentially equivalent across income quartiles. In general, these price elasticity estimates are considerably larger in magnitude than those found in other studies using household-level data that assume that consumers respond to marginal prices. We also apply our elasticity estimates in a U.S. climate policy simulation to determine how these elasticity estimates alter consumption and price outcomes compared to the more conservative elasticity estimates commonly used in policy analysis.

Harrison Fell; Shanjun Li; Anthony Paul; Harrison Fell; Shanjun Li; Anthony Paul; Monte Carlo Analysis

2010-01-01T23:59:59.000Z

86

Household activities through various lenses: crossing surveys, diaries and electric consumption  

E-Print Network (OSTI)

comparison between electricity consumption and behavioralK. 2013. “Domestic energy consumption-What role do comfort,residential electricity consumption” Energy Policy, 42(2012)

Durand-Daubin, Mathieu

2013-01-01T23:59:59.000Z

87

Household Vehicles Energy Consumption 1994  

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

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

88

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

89

Present coal potential of Turkey and coal usage in electricity generation  

SciTech Connect

Total coal reserve (hard coal + lignite) in the world is 984 billion tons. While hard coal constitutes 52% of the total reserve, lignite constitutes 48% of it. Turkey has only 0.1% of world hard coal reserve and 1.5% of world lignite reserves. Turkey has 9th order in lignite reserve, 8th order in lignite production, and 12th order in total coal (hard coal and lignite) consumption. While hard coal production meets only 13% of its consumption, lignite production meets lignite consumption in Turkey. Sixty-five percent of produced hard coal and 78% of produced lignite are used for electricity generation. Lignites are generally used for electricity generation due to their low quality. As of 2003, total installed capacity of Turkey was 35,587 MW, 19% (6,774 MW) of which is produced from coal-based thermal power plants. Recently, use of natural gas in electricity generation has increased. While the share of coal in electricity generation was about 50% for 1986, it is replaced by natural gas today.

Yilmaz, A.O. [Karadeniz Technical University, Trabzon (Turkey). Mining Engineering Department

2009-07-01T23:59:59.000Z

90

Testing Electric Vehicle Demand in `Hybrid Households' Using a Reflexive Survey  

E-Print Network (OSTI)

travel by electric and hybrid vehicles. SAE Technical PapersIn contrast to a hybrid vehicle which combines multipleElectric, Hybrid and Other Alternative Vehicles. A r t h u r

Kurani, Kenneth; Turrentine, Thomas; Sperling, Daniel

1996-01-01T23:59:59.000Z

91

Testing Electric Vehicle Demand in `Hybrid Households' Using a Reflexive Survey  

E-Print Network (OSTI)

new features of compressed natural gas, battery poweredgasoline, compressed natural gas, hybrid electric, two typesNatural gas vehicles (NGVs) were available with one or two compressed

Kurani, Kenneth; Turrentine, Thomas; Sperling, Daniel

1996-01-01T23:59:59.000Z

92

Household activities through various lenses: crossing surveys, diaries and electric consumption  

E-Print Network (OSTI)

changes differ from one appliance to another. Referencespeople activities, appliances use, and electric consumption.of use of the three appliances studied. However, variations

Durand-Daubin, Mathieu

2013-01-01T23:59:59.000Z

93

A Study of the Electrical Energy Usage Patterns of a Texas Dairy  

E-Print Network (OSTI)

A one-year study was done on a modern dairy operation located in Hopkins County, Texas to determine the load patterns and total energy use of the major electrical loads in the dairy. It was found that the vacuum pumps for the milking machines consumed the most energy, followed by the water heater and milk coolers. Consumption for water heating and milk cooling was found to vary seasonally. Peak demands for the dairy occurred at 6 a.m. and 5 p.m. throughout the year during the morning and afternoon milkings. The morning peak occurred two hours prior to Texas Power & Light Company's winter peak hour, and the evening peak is coincident with TP&L's summer peak hour. It was estimated that a savings of approximately 33% on water heating kWh was attained through a waste heat recovery system connected to the milk coolers. The water heating load was found to have the highest load factor coincident with TP&L's summer peak of any of the loads monitored.

Schneider, K. C.; Pollard, K. W.

1984-01-01T23:59:59.000Z

94

Electricity storage for grid-connected household dwellings with PV panels  

SciTech Connect

Classically electricity storage for PV panels is mostly designed for stand-alone applications. In contrast, we focus in this article on houses connected to the grid with a small-scale storage to store a part of the solar power for postponed consumption within the day or the next days. In this way the house owner becomes less dependent on the grid and does only pay for the net shortage of his energy production. Local storage solutions pave the way for many new applications like omitting over-voltage of the line and bridging periods of power-line black-out. Since 2009 using self-consumption of PV energy is publicly encouraged in Germany, which can be realised by electric storage. This paper develops methods to determine the optimal storage size for grid-connected dwellings with PV panels. From measurements in houses we were able to establish calculation rules for sizing the storage. Two situations for electricity storage are covered: - the storage system is an optimum to cover most of the electricity needs; - it is an optimum for covering the peak power need of a dwelling. After these calculation rules a second step is needed to determine the size of the real battery. The article treats the aspects that should be taken into consideration before buying a specific battery like lead-acid and lithium-ion batteries. (author)

Mulder, Grietus; Six, Daan [Vlaamse Instelling voor Technologisch Onderzoek, Unit Energy Technology, Mol (Belgium); Ridder, Fjo De [Vrije Universiteit Brussel (Belgium)

2010-07-15T23:59:59.000Z

95

Household Vehicles Energy Consumption 1991  

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

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

96

Usage Demographics 2010  

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

NERSC Usage Demographics 2010 Academic Usage Usage by Discipline DOE & Other Lab Usage Usage by Institution Type Last edited: 2012-10-30 13:51:35...

97

Household Vehicles Energy Consumption 1991  

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

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

98

Answers to Frequently Asked Questions About the Household Bottled ...  

U.S. Energy Information Administration (EIA)

Form EIA-457D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey

99

Household Fuel Oil or Kerosene Usage Form  

U.S. Energy Information Administration (EIA)

Contractor’s Street Address . Contractor’s City, State, and ZIP Code . ... is a light distillate fuel oil intended for use in vaporizing pot-type burners.

100

Table CE3-1e. Electric Air-Conditioning Energy Expenditures in U.S ...  

U.S. Energy Information Administration (EIA)

Dollars per Household4,a Electric Air-Conditioning Expenditures per Household ... per Household4 2001 Cooling Degree-Days per Household Total U.S. Households ...

Note: This page contains sample records for the topic "household electricity usage" 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

Robotics and Energy Usage  

E-Print Network (OSTI)

It is commonly assumed that the use of robots in an industrial plant will cut energy usage, because robots require no heat, light, or air conditioning in their work space. However, in analyzing industrial installations, we have found that, in practice, energy usage may either increase or decrease depending on the parameters of the particular facility. This paper describes our findings at the plants of various manufacturers. We performed on-site studies at plants operated by Chrysler Corporation in St. Louis (62 welding robots) and Franklin Manufacturing Company in St. Cloud, Minnesota (4 spray painting robots used in freezer manufacture), We also examined data on energy effects of robots from John Deere, caterpillar, and GM Guide Division. The effect of robots on electricity usage and other forms of energy usage are analyzed in this paper.

Hershey, R. L.; Fenton, S. E.; Letzt, A. M.

1983-01-01T23:59:59.000Z

102

Modeling patterns of hot water use in households  

E-Print Network (OSTI)

various usage characteristics associated with electric, gas-Usage: A Review of Published Metered Studies. Prepared for Gasgas, may be an incentive for people with electric water heaters to reduce their hot water usage.

Lutz, James D.; Liu, Xiaomin; McMahon, James E.; Dunham, Camilla; Shown, Leslie J.; McCure, Quandra T.

1996-01-01T23:59:59.000Z

103

Brain usage  

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

usage Name: A W Chen Status: NA Age: NA Location: NA Country: NA Date: NA Question: For my science fair project I would like to know if every part of the brain is used all the...

104

Brain Usage  

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

Usage Name: Matt Location: NA Country: NA Date: NA Question: what percentage of the brain does the average human use? Replies: This is a very difficult question to address. Your...

105

Modelling household electricity consumption.  

E-Print Network (OSTI)

??A number of conclusions are drawn, however given the limited and non-representative na- ture of the data on which the model is calibrated, these can… (more)

de la Rue, Philip Martin

2010-01-01T23:59:59.000Z

106

step 1: retrieve usage step 2: convert usage  

E-Print Network (OSTI)

planet #12;step 2: convert usage data to ghg electricity conversion EPA eGRID database provides state by state data on: lbs CO2 / MWh lbs NOx / MWH eGRID Massachusetts ­ specific conversion factors only

Paulsson, Johan

107

Table HC6.12 Home Electronics Usage Indicators by Number of...  

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

2 Home Electronics Usage Indicators by Number of Household Members, 2005 Total... 111.1 30.0 34.8 18.4...

108

Variability of Battery Wear in Light Duty Plug-In Electric Vehicles Subject to Ambient Temperature, Battery Size, and Consumer Usage: Preprint  

DOE Green Energy (OSTI)

Battery wear in plug-in electric vehicles (PEVs) is a complex function of ambient temperature, battery size, and disparate usage. Simulations capturing varying ambient temperature profiles, battery sizes, and driving patterns are of great value to battery and vehicle manufacturers. A predictive battery wear model developed by the National Renewable Energy Laboratory captures the effects of multiple cycling and storage conditions in a representative lithium chemistry. The sensitivity of battery wear rates to ambient conditions, maximum allowable depth-of-discharge, and vehicle miles travelled is explored for two midsize vehicles: a battery electric vehicle (BEV) with a nominal range of 75 mi (121 km) and a plug-in hybrid electric vehicle (PHEV) with a nominal charge-depleting range of 40 mi (64 km). Driving distance distributions represent the variability of vehicle use, both vehicle-to-vehicle and day-to-day. Battery wear over an 8-year period was dominated by ambient conditions for the BEV with capacity fade ranging from 19% to 32% while the PHEV was most sensitive to maximum allowable depth-of-discharge with capacity fade ranging from 16% to 24%. The BEV and PHEV were comparable in terms of petroleum displacement potential after 8 years of service, due to the BEV?s limited utility for accomplishing long trips.

Wood, E.; Neubauer, J.; Brooker, A. D.; Gonder, J.; Smith, K. A.

2012-08-01T23:59:59.000Z

109

Ownership and usage of small passenger vehicles: findings from the 1977 National Personal Transportation Study  

SciTech Connect

This report examines current patterns in the ownership and usage of small vehicles by private households. The analysis was conducted to shed additional light on the market potential for smaller, energy efficient vehicles, in particular, electric cars. The 1977 Nationwide Personal Transportation Survey (NPTS) was used to obtain information on the socio-demographic characteristics and the travel and vehicle ownership behavior of US households based on a national probability sample. The issues posed to direct the investigation of small vehicle ownership and use behavior include: the ownership of small vehicles; the proportion of the private vehicle population accounted for by small vehicles; how small and large vehicles compare in terms of physical characteristics and performance and terms of usage; and how small/large vehicle ownership and usage differences are explained by household differences or physical differences in the vehicles themselves. The study's approach to these issues has focused on descriptive data analysis, employing such tools as cross-classification tables, distributions, and graphic displays. (MCW)

1981-12-01T23:59:59.000Z

110

Usage of Electronic Monograph  

Science Conference Proceedings (OSTI)

Usage of Electronic Monograph. The following table shows the approximate usage of the monograph since April 1998. ...

2013-08-02T23:59:59.000Z

111

Commercializing Light-Duty Plug-In/Plug-Out Hydrogen-Fuel-Cell Vehicles: "Mobile Electricity" Technologies, Early California Household Markets, and Innovation Management  

E-Print Network (OSTI)

and vehicular-distributed-generation model to estimate zero-power, Vehicular distributed generation, Household marketdistributed generation .25

Williams, Brett D

2010-01-01T23:59:59.000Z

112

Commercializing Light-Duty Plug-In/Plug-Out Hydrogen-Fuel-Cell Vehicles:“Mobile Electricity” Technologies, Early California Household Markets, and Innovation Management  

E-Print Network (OSTI)

and vehicular-distributed-generation model to estimate zero-power, Vehicular distributed generation, Household marketdistributed generation .25

Williams, Brett D

2007-01-01T23:59:59.000Z

113

Exploring iPhone Usage: The Influence of Socioeconomic Differences on Smartphone Adoption, Usage and Usability  

E-Print Network (OSTI)

on device usage. Among our findings are that a large number of applications were uninstalled, lower SESExploring iPhone Usage: The Influence of Socioeconomic Differences on Smartphone Adoption, Usage. of Electrical and Computer Engineering, 2 Dept. of Psychology, Rice University, Houston, TX {rahmati, chad

Zhong, Lin

114

EIA - Household Transportation report: Household Vehicles ...  

U.S. Energy Information Administration (EIA)

This report, Household Vehicles Energy Use: Latest Data & Trends, provides details on the nation's energy use for household passenger travel. A primary purpose of ...

115

Modeling diffusion of electrical appliances in the residential sector  

E-Print Network (OSTI)

and usage patterns, and because data sources covering these parameters are more scarce, modeling of household lighting

McNeil, Michael A.

2010-01-01T23:59:59.000Z

116

ac_household2001.pdf  

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

3a. Air Conditioning by Household Income, 3a. Air Conditioning by Household Income, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.5 1.4 1.1 1.0 0.9 1.5 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 12.3 17.4 21.5 31.7 9.6 23.4 3.9 Air Conditioners Not Used ............ 2.1 0.4 0.7 0.5 0.5 0.4 0.9 20.8 Households Using Electric Air-Conditioning 2 .......................... 80.8 11.9 16.7 21.0 31.2 9.1 22.6 3.9 Type of Electric Air-Conditioning Used Central Air-Conditioning 3 .............. 57.5 6.2 10.7 15.2 25.3 4.5 12.4 5.3 Without a Heat Pump .................. 46.2 4.9 9.1 12.1 20.1 3.6 10.4 6.1 With a Heat Pump

117

Use characteristics and mode choice behavior of electric bike users in China  

E-Print Network (OSTI)

by surveying electric bike usage in two large Chineseelectric bikes. Electric bike usage increases with age up tobicycle riders support electric bike usage of bike lanes.

Cherry, Christopher; Cervero, Robert

2007-01-01T23:59:59.000Z

118

Electricity Demand of PHEVs Operated by Private Households and Commercial Fleets: Effects of Driving and Charging Behavior  

SciTech Connect

Automotive and energy researchers have made considerable efforts to predict the impact of plug-in hybrid vehicle (PHEV) charging on the electrical grid. This work has been done primarily through computer modeling and simulation. The US Department of Energy’s (DOE) Advanced Vehicle Testing Activity (AVTA), in partnership with the University of California at Davis’s Institute for Transportation Stuides, have been collecting data from a diverse fleet of PHEVs. The AVTA is conducted by the Idaho National Laboratory for DOE’s Vehicle Technologies Program. This work provides the opportunity to quantify the petroleum displacement potential of early PHEV models, and also observe, rather than simulate, the charging behavior of vehicle users. This paper presents actual charging behavior and the resulting electricity demand from these PHEVs operating in undirected, real-world conditions. Charging patterns are examined for both commercial-use and personal-use vehicles. Underlying reasons for charging behavior in both groups are also presented.

John Smart; Matthew Shirk; Ken Kurani; Casey Quinn; Jamie Davies

2010-11-01T23:59:59.000Z

119

Development of a commercial-sector data base and forecasting model for electricity usage and demand. Volume I. Preliminary model specification. [Description of subprograms BEHAV, DEMAND, ECON, ENER, and INGEN  

SciTech Connect

This is the first of twelve major technical reports under the Commission's contract with Hittman Associates. The contract will lead to the development of a data base on commercial space, and the development of a model to forecast electricity usage and demand. This report presents a preliminary specification of the model to be developed. The model being developed combines econometric and engineering approaches, and consists of five subprograms and an overall executing program. The first subprogram forecasts the stock of commercial space, based on employment data and other economic inputs. It also distinguishes among various types of commercial space, and breaks the commercial space into segments according to fuels for various end uses, such as heating, cooling, etc. The second subprogram uses detailed building-survey data to specify a typical, or characteristic building for each unique type of floorspace considered in the study. The third subprogram calculates monthly electricity usage for the typical buildings specified, using standard engineering techniques, and then scales up the electricity use for each building type according to the amount of space, of that type, in the entire building stock. The fourth subprogram performs a similar function, but produces hourly electricity demands, rather than monthly electricity usage. The fifth, and final subprogram adjusts the energy usage and demand values calculated to simulate the impact of certain economic conditions or policy measures. The report presents a flow chart for each subprogram, and a table of inputs and outputs required for each. The logic, structure, flow, and information transfer of each is described.

1980-02-01T23:59:59.000Z

120

Section J: HOUSEHOLD CHARACTERISTICS  

U.S. Energy Information Administration (EIA)

2001 Residential Energy Consumption Survey Form EIA-457A (2001)--Household Questionnaire OMB No.: 1905-0092, Expiring February 29, 2004 42 Section J: HOUSEHOLD ...

Note: This page contains sample records for the topic "household electricity usage" 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

Urban household energy use in Thailand  

SciTech Connect

Changes in household fuel and electricity use that accompany urbanization in Third World countries bear large economic and environmental costs. The processes driving the fuel transition, and the policy mechanisms by which it can be influenced, need to be better understood for the sake of forecasting and planning, especially in the case of electricity demand. This study examines patterns of household fuel use and electrical appliance utilization in Bangkok, Chieng Mai and Ayutthaya, Thailand, based on the results of a household energy survey. Survey data are statistically analyzed using a variety of multiple regression techniques to evaluate the relative influence of various household and fuel characteristics on fuel and appliance choice. Results suggest that changes to the value of women's time in urban households, as women become increasingly active in the labor force, have a major influence on patterns of household energy use. The use of the home for small-scale commercial activities, particularly food preparation, also has a significant influence on fuel choice. In general, household income does not prove to be an important factor in fuel and appliance selection in these cities, although income is closely related to total electricity use. The electricity use of individual household appliances is also analyzed using statistical techniques as well as limited direct metering. The technology of appliance production in Thailand is evaluated through interviews with manufacturers and comparisons of product performance. These data are used to develop policy recommendations for improving the efficiency of electrical appliances in Thailand by relying principally on the dynamism of the consumer goods market, rather than direct regulation. The annual electricity savings from the recommended program for fostering rapid adoption of efficient technologies are estimated to reach 1800 GWh by the year 2005 for urban households alone.

Tyler, S.R.

1992-01-01T23:59:59.000Z

122

Brookhaven Logo Usage  

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

Logo Usage The Correct Usage of the BNL Logo - The following examples picture correct and incorrect use of the Laboratory logo. If you need assistance in using the logo, contact...

123

Context: Usage and Effectiveness  

Science Conference Proceedings (OSTI)

*. Bookmark and Share. Context: Usage and Effectiveness. US Navy Aircraft Halon 1301 Effectivity Analysis.. Tedeschi, M.; Leach, W.; 1995. ...

2011-12-14T23:59:59.000Z

124

Analysis of the energy requirement for household consumption.  

E-Print Network (OSTI)

??Humans in households use energy for their activities. This use is both direct, for example electricity and natural gas, but also indirect, for the production,… (more)

Vringer, Kees

2005-01-01T23:59:59.000Z

125

Commercializing Light-Duty Plug-In/Plug-Out Hydrogen-Fuel-Cell Vehicles: "Mobile Electricity" Technologies, Early California Household Markets, and Innovation Management  

E-Print Network (OSTI)

to produce clean, quiet electrical power for purposes otherHEVWG), led by the Electrical Power Research Institute (section), as well as if electrical power, flowing along the

Williams, Brett D

2010-01-01T23:59:59.000Z

126

Commercializing Light-Duty Plug-In/Plug-Out Hydrogen-Fuel-Cell Vehicles:“Mobile Electricity” Technologies, Early California Household Markets, and Innovation Management  

E-Print Network (OSTI)

to produce clean, quiet electrical power for purposes otherHEVWG), led by the Electrical Power Research Institute (section), as well as if electrical power, flowing along the

Williams, Brett D

2007-01-01T23:59:59.000Z

127

Commercializing Light-Duty Plug-In/Plug-Out Hydrogen-Fuel-Cell Vehicles:“Mobile Electricity” Technologies, Early California Household Markets, and Innovation Management  

E-Print Network (OSTI)

and S. E. Letendre, "Electric Vehicles as a New Power Sourceassessment for fuel cell electric vehicles." Argonne, Ill. :at 20th International Electric Vehicle Symposium (EVS-20),

Williams, Brett D

2007-01-01T23:59:59.000Z

128

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

Science Conference Proceedings (OSTI)

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

Not Available

1993-03-02T23:59:59.000Z

129

Household Vehicles Energy Use: Latest Data and Trends - Table A04  

U.S. Energy Information Administration (EIA)

... Buildings & Industry > Transportation Surveys > Household Vehicles Energy ... U.S. Vehicles by Model ... Office of Coal, Nuclear, Electric, and Alternate ...

130

char_household2001.pdf  

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

Household Tables Household Tables (Million U.S. Households; 24 pages, 122 kb) Contents Pages HC2-1a. Household Characteristics by Climate Zone, Million U.S. Households, 2001 2 HC2-2a. Household Characteristics by Year of Construction, Million U.S. Households, 2001 2 HC2-3a. Household Characteristics by Household Income, Million U.S. Households, 2001 2 HC2-4a. Household Characteristics by Type of Housing Unit, Million U.S. Households, 2001 2 HC2-5a. Household Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 2 HC2-6a. Household Characteristics by Type of Rented Housing Unit, Million U.S. Households, 2001 2 HC2-7a. Household Characteristics by Four Most Populated States, Million U.S. Households, 2001 2

131

char_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

9a. Household Characteristics by Northeast Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row...

132

Transportation Statistics Analysis for Electric Transportation  

Science Conference Proceedings (OSTI)

Plug-in Electric Vehicles (PEVs) are still in the initial stages of deployment in the American vehicle market. Much of the currently available data on PEVs is from special applications and early adopters. EPRI has analyzed existing transportation data on conventional vehicles from the National Household Travel Survey (NHTS) to study the potential long-term patterns of PEV use. This study used the NHTS data to investigate several aspects of potential PEV usage patterns and their effects on U.S. electric l...

2011-12-21T23:59:59.000Z

133

Table CE3-3e. Electric Air-Conditioning Energy Expenditures in U.S ...  

U.S. Energy Information Administration (EIA)

Electric Air-Conditioning Energy Expenditures in U.S. Households by Household Income, 2001 RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli-

134

APS LOM Shop Usage  

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

Division XSD Groups Industry Argonne Home Advanced Photon Source APS LOM Shop Usage User Shop Access - Policies and Procedures User Shop Orientation User Shop...

135

Characterizing Household Plug Loads through Self-Administered Load Research  

Science Conference Proceedings (OSTI)

Household miscellaneous loads, which include consumer electronics, are the fastest growing segment of household energy use in the United States. Although the relative energy intensity of applications such as heating and cooling is declining, the DOEAnnual Energy Outlook forecasts that the intensity of residential miscellaneous end uses will increase substantially by 2030. Studies by TIAX and Ecos Consulting reveal that miscellaneous devices8212smaller devices in terms of energy draw but growing in usage8...

2009-12-09T23:59:59.000Z

136

Electric Vehicle (EV) Carsharing in A Senior Adult Community  

E-Print Network (OSTI)

Electric Vehicle (EV) Carsharing in A Senior Adult Community Susan;86% 0 0 65% 35% 0% 72% 25% 3% Single-car households Two-car households No-car households % of Respondents Cars per Household Interview (n=7) Focus

Kammen, Daniel M.

137

Commercializing Light-Duty Plug-In/Plug-Out Hydrogen-Fuel-Cell Vehicles:“Mobile Electricity” Technologies, Early California Household Markets, and Innovation Management  

E-Print Network (OSTI)

goals for automotive fuel cell power systems hydrogen vs.a comparative assessment for fuel cell electric vehicles."plug-out hydrogen-fuel- cell vehicles: “Mobile Electricity"

Williams, Brett D

2007-01-01T23:59:59.000Z

138

ac_household2001.pdf  

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

0a. Air Conditioning by Midwest Census Region, 0a. Air Conditioning by Midwest Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 20.5 13.6 6.8 2.2 Air Conditioners Not Used ........................... 2.1 0.3 Q Q 27.5 Households Using Electric Air-Conditioning 1 ........................................ 80.8 20.2 13.4 6.7 2.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 14.3 9.5 4.8 3.8 Without a Heat Pump ................................ 46.2 13.6 9.0 4.6 3.9 With a Heat Pump .....................................

139

ac_household2001.pdf  

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

8a. Air Conditioning by Urban/Rural Location, 8a. Air Conditioning by Urban/Rural Location, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 36.8 13.6 18.9 13.6 4.3 Air Conditioners Not Used ........................... 2.1 1.2 0.2 0.4 0.3 21.4 Households Using Electric Air-Conditioning 2 ........................................ 80.8 35.6 13.4 18.6 13.3 4.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 3 ............................ 57.5 23.6 8.6 15.8 9.4 5.1 Without a Heat Pump ................................ 46.2 19.3 7.4 13.1 6.4 6.3 With a Heat Pump ..................................... 11.3 4.4

140

ac_household2001.pdf  

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

5a. Air Conditioning by Type of Owner-Occupied Housing Unit, 5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 59.5 58.7 6.5 12.4 5.3 5.2 Air Conditioners Not Used ............ 1.2 1.1 Q 0.6 Q 23.3 Households Using Electric Air-Conditioning 1 .......................... 58.2 57.6 6.3 11.8 5.1 5.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 .............. 44.7 43.6 3.2 7.1 3.5 7.0 Without a Heat Pump .................. 35.6 35.0 2.4 6.1 2.7 7.7 With a Heat Pump .......................

Note: This page contains sample records for the topic "household electricity usage" 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

ac_household2001.pdf  

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

6a. Air Conditioning by Type of Rented Housing Unit, 6a. Air Conditioning by Type of Rented Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.8 0.5 1.4 1.2 1.6 Households With Electric Air-Conditioning Equipment ........ 23.4 58.7 6.5 12.4 5.3 6.1 Air Conditioners Not Used ............ 0.9 1.1 Q 0.6 Q 23.0 Households Using Electric Air-Conditioning 1 .......................... 22.5 57.6 6.3 11.8 5.1 6.2 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 .............. 12.7 43.6 3.2 7.1 3.5 8.5 Without a Heat Pump .................. 10.6 35.0 2.4 6.1 2.7 9.3 With a Heat Pump ....................... 2.2 8.6 0.8 1.0

142

ac_household2001.pdf  

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

1a. Air Conditioning by South Census Region, 1a. Air Conditioning by South Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 37.2 19.3 6.4 11.5 1.5 Air Conditioners Not Used ........................... 2.1 0.4 Q Q Q 28.2 Households Using Electric Air-Conditioning 1 ........................................ 80.8 36.9 19.0 6.4 11.5 1.6 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 30.4 16.1 5.0 9.2 2.8 Without a Heat Pump ................................ 46.2 22.1 10.4 3.4 8.3 5.6 With a Heat Pump

143

ac_household2001.pdf  

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

9a. Air Conditioning by Northeast Census Region, 9a. Air Conditioning by Northeast Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.8 Households With Electric Air-Conditioning Equipment ...................... 82.9 14.5 11.3 3.2 3.3 Air Conditioners Not Used ........................... 2.1 0.3 0.3 Q 28.3 Households Using Electric Air-Conditioning 1 ........................................ 80.8 14.2 11.1 3.2 3.4 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 5.7 4.9 0.8 8.9 Without a Heat Pump ................................ 46.2 5.2 4.5 0.7 9.2 With a Heat Pump .....................................

144

ac_household2001.pdf  

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

2a. Air Conditioning by Year of Construction, 2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.1 1.2 1.1 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 13.6 16.0 14.7 10.4 10.5 17.6 4.7 Air Conditioners Not Used ............ 2.1 Q 0.3 0.5 0.3 0.4 0.5 27.2 Households Using Electric Air-Conditioning 2 .......................... 80.8 13.4 15.8 14.2 10.1 10.2 17.1 4.7 Type of Electric Air-Conditioning Used Central Air-Conditioning 3 .............. 57.5 12.6 13.7 11.0 7.1 6.6 6.4 5.9 Without a Heat Pump .................. 46.2 10.1 10.4 8.0 6.1 5.9 5.7 7.0 With a Heat Pump ....................... 11.3 2.5 3.3

145

ac_household2001.pdf  

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

4a. Air Conditioning by Type of Housing Unit, 4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.6 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 82.9 58.7 6.5 12.4 5.3 4.9 Air Conditioners Not Used ............ 2.1 1.1 Q 0.6 Q 21.8 Households Using Electric Air-Conditioning 1 .......................... 80.8 57.6 6.3 11.8 5.1 4.9 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 .............. 57.5 43.6 3.2 7.1 3.5 6.7 Without a Heat Pump .................. 46.2 35.0 2.4 6.1 2.7 7.7 With a Heat Pump ....................... 11.3 8.6 0.8 1.0 0.8 19.7 Room Air-Conditioning

146

Microsoft Word - Household Energy Use CA  

Gasoline and Diesel Fuel Update (EIA)

0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household ï‚· California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site consumption results in households spending 30% less for energy than the U.S. average. ï‚· Average site electricity consumption in California homes is among the lowest in the nation, as the mild climate in much of the state leads to less reliance on

147

Microsoft Word - Household Energy Use CA  

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

0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household ï‚· California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site consumption results in households spending 30% less for energy than the U.S. average. ï‚· Average site electricity consumption in California homes is among the lowest in the nation, as the mild climate in much of the state leads to less reliance on

148

Household energy consumption and expenditures 1993  

Science Conference Proceedings (OSTI)

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

NONE

1995-10-05T23:59:59.000Z

149

Energy usage in super markets  

SciTech Connect

The supermarket industry used 450 billion Btu's of energy each day, enough to heat 2 million homes. But more important than the overall energy usage is what energy is costing the supermarket operator; in many cases energy costs exceed rent. This special research report is designed to help the supermarket management determine if their stores are excessive energy users and to provide valuable data for planning remodels and new stores. The report is presented in five sections. The first two sections, General Observations and Monthly Electrical Usage and Demand Power, can easily be used by all supermarket operators. The third and fourth sections contain more detailed statistics that will be valuable to industry people who want to analyze energy usage more thoroughly. The statistics in section 1-4 are reported for various geographic regions and store sizes. Section five is the sample distribution which provides an insight into what other stores are using for refrigeration, lighting, etc. The information in this report is average for a typical supermarket and should be used only as that when compared to a specific supermarket facility.

Gerke, E.

1976-01-01T23:59:59.000Z

150

Household carbon dioxide production in relation to the greenhouse effect  

SciTech Connect

A survey of 655 households from eastern suburbs of Melbourne was undertaken to determine householders[prime] attitudes to, and understanding of, the greenhouse effect. Carbon dioxide emissions resulting from car, electricity and gas use were computed and household actions which could reduce CO[sub 2] emissions were addressed. Preliminary analysis of the results indicates that householders in this area are aware of, and concerned about, the greenhouse effect, although their understanding of its causes is often poor. Many appreciate the contribution of cars, but are unclear about the relative importance of other household activities. Carbon dioxide emissions from the three sources examined averaged 21[center dot]2 tonnes/year per household and 7[center dot]4 tonnes/year per person. Electricity was the largest contributor (8[center dot]6 tonnes/year), cars the next largest (7[center dot]7 tonnes/year) and gas third (5[center dot] tonnes/year) per household. Emissions varied considerably from household to household. There was a strong positive correlation between availability of economic resources and household CO[sub 2] output from all sources. Carbon dioxide production, particularly from car use, was greater from households which were most distant from a railway station, and from larger households, and numbers of children in the household had little effect on emissions. There were also some economics of scale for households containing more adults. Understanding the causes of the greenhouse bore little relation to change in CO[sub 2] emissions; being concerned about it was associated with a small reduction; but actual actions to reduce car use and household heating, however motivated, produced significant reductions. 12 refs., 9 figs., 6 tabs.

Stokes, D.; Lindsay, A.; Marinopoulos, J.; Treloar, A.; Wescott, G. (Deakin Univ., Clayton (Australia))

1994-03-01T23:59:59.000Z

151

Adaptive web usage profiling  

Science Conference Proceedings (OSTI)

Web usage models and profiles capture significant interests and trends from past accesses. They are used to improve user experience, say through recommendation of pages, pre-fetching of pages, etc. While browsing behavior changes dynamically over time, ...

Bhushan Shankar Suryavanshi; Nematollaah Shiri; Sudhir P. Mudur

2005-08-01T23:59:59.000Z

152

Exemplary Units Markup Language usage  

Science Conference Proceedings (OSTI)

Sample UnitsML tools and usage. ... Its usage is limited to demonstrating capabilities of plain XSLT processing with the data stored in UnitsML. ...

153

Mitigating Carbon Emissions: the Potential of Improving Efficiency of Household Appliances in China  

E-Print Network (OSTI)

or by electric thermos. Table 6: Annual Energy Usage of Gasusage, which assumes no further efficiency improvement after 2009. Further, annual electric

Lin, Jiang

2006-01-01T23:59:59.000Z

154

EIA - Household Transportation report: Household Vehicles Energy  

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

4 4 Transportation logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1994 August 1997 Release Next Update: EIA has discontinued this series. Based on the 1994 Residential Transportation Energy Consumption Survey conducted by the Energy Information Administration (EIA) - survey series has been discontinued Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses. Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use

155

Table 1. Total Energy Consumption in U.S. Households by Origin ...  

U.S. Energy Information Administration (EIA)

Wood (million cords) ..... 21.4 19.8 0.8 0.6 0.3 19.3 Million Btu per Household3 Total Btu Consumption per Household, Fuels Used: Electricity Primary ...

156

Device for monitoring utility usage  

SciTech Connect

A device for monitoring utility usage for installation and use by homeowners and consumers with existing public utility meters having a disk that is mounted inside a transparent case and that rotates in response to electrical current usage, the device is described comprising: a disk rotation monitoring assembly for mounting on the exterior of the transparent case, said monitoring assembly comprising: (a) a sensor for sensing disk rotation speed and generating a signal in response thereto; and (b) means for mounting said sensor on the transparent case, said mounting means further comprising means for holding said sensor, means for attaching said holding means to the transparent case, and means for adjusting the position of said holding means to enable precise alignment of said sensor with the plane of the disk such that said sensor is in optical communication with the edge of said disk; one or more remote display terminals in electrical communication with said monitoring assembly, each of said one or more remote terminals comprising: (a) means for receiving said signal and processing said signal into utility consumption data; (b) an electronic memory for storing said data; (c) a visual display for displaying data in a reader-usable format about consumption; and (d) a display controller that enables selective displaying of any of said data on said visual display.

Green, R.G.

1993-05-25T23:59:59.000Z

157

Laboratory Testing of Demand-Response Enabled Household Appliances  

SciTech Connect

With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses.The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

Sparn, B.; Jin, X.; Earle, L.

2013-10-01T23:59:59.000Z

158

Car Sharing within Households  

E-Print Network (OSTI)

The objective of this paper was to analyse two activities: who rents a car and why? Which households share the driving of their cars? In order to do that, the Parc-Auto (Car-Fleet) database, built from annual postal surveys conducted with a panel of 10,000 French households, has been processed. Among approximately one hundred questions in the survey, two key questions have been crossed against many social, economic, demographic, geographic or time variables. KQ1: “During the last 12 months, did you — or another person from your home — rent a car in France for personal purposes? ” KQ2: “Is this car occasionally used by other persons?” Here are the main findings. Renting households are mainly working, high income households, living in the core of big cities, and in particular in Paris. Most of them have two wage-sheets and two cars, one of which is generally a recent, high power, high quality car. Car rental is mainly an occasional practice. Yet for a minority of renters, it is a sustained habit. Households with more licence holders than cars share the most: about three quarters of them share their cars. On the contrary, single driver-single car households have less opportunity to share: only 15 % share. Household car sharing shed light on the gender role within households: while 58 % of the main users of the shared cars are male, 55 % of secondary users are female. Household car sharing is mainly a regular practice. Finally, without diminishing the merits of innovative transport solutions proposed here and there, it is not a waste of time to give some insight on self established behaviour within households. This reveals that complex patterns have been built over time by the people themselves, to cope with diverse situations that cannot be easily handled by straightforward classifications. The car cannot be reduced to a personal object. Household car sharing also carries strong links with the issue of car dependency. Sifting car availability and choice

Francis Papon; Laurent Hivert

2008-01-01T23:59:59.000Z

159

Investigating the impacts of time-of-use electricity rates on lower-income and senior-headed households: A case study of Milton, Ontario (Canada).  

E-Print Network (OSTI)

??Through the Smart Metering Initiative in the Canadian province of Ontario, all residential electricity customers will be converted from a tiered rate regime to a… (more)

Simmons, Sarah Ivy

2010-01-01T23:59:59.000Z

160

Commercializing Light-Duty Plug-In/Plug-Out Hydrogen-Fuel-Cell Vehicles: "Mobile Electricity" Technologies, Early California Household Markets, and Innovation Management  

E-Print Network (OSTI)

goals for automotive fuel cell power systems hydrogen vs.a comparative assessment for fuel cell electric vehicles."Transition: Designing a Fuel- Cell Hypercar. ” 8th Annual

Williams, Brett D

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household electricity usage" 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

PRELIMINARY DATA Housing Unit and Household Characteristics  

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

PRELIMINARY DATA Housing Unit and Household Characteristics RSE Column Factor: Total Households (million) Households With Fans (million) Percent of Households With Fans Number of...

162

ac_household2001.pdf  

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

2001 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Households With Electric Air-Conditioning Equipment ...................... 82.9 4.9 6.0 7.4 6.2 2.4 Air Conditioners Not Used ........................... 2.1 0.1 0.8 Q 0.1 23.2 Households Using Electric Air-Conditioning 1 ........................................ 80.8 4.7 5.2 7.4 6.1 2.6 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 1.3 3.9 6.2 5.7 6.7 Without a Heat Pump ................................ 46.2 1.2 3.2 5.5 3.8 8.1 With a Heat Pump ..................................... 11.3 Q 0.8 0.6 1.9 14.7 Room Air-Conditioning ................................ 23.3 3.4 1.2 1.2 0.3 13.6 1 Unit

163

Automotive materials usage trends  

SciTech Connect

The materials composition of US passenger cars is traced from 1960 and projected into 1990's. Sales-weighted average vehicle-weight trends are analyzed in terms of shifts in the large/small car mix, downsizing, and downweighting. The growth in the usage of lightweight materials: -high strength steels, cast/wrought aluminum, plastics and composites - are examined in detail. Usage trends in a host of other materials such as alloy steels, zinc, lead, copper, etc. are also discussed. An approximate quantitative analysis of changes in the usage of steel by the automotive industry worldwide show that about 10% of total decline in Western-World steel consumption is accounted for by the automotive industry. An assessment is presented for automotive industry use of critical materials such as chromium in alloy steels/cast irons and the platinum group metals in exhaust-gas catalysts. 10 references, 13 figures, 9 tables.

Gjostein, N.A.

1986-01-01T23:59:59.000Z

164

Development of a data base and forecasting model for commercial-sector electricity usage and demand. Volume VII. Detailed survey, sampling methodology  

Science Conference Proceedings (OSTI)

This report describes the work performed toward obtaining two sets of primary data, from which econometric and engineering parameters for the model were to be derived. The first type will be collected in a mail survey of utility-company customers determined by an analysis of customer-account data. These data have been collected from Pacific Gas and Electric, Los Angeles Div. of Water and Power, San Diego Gas and Electric, and Sacramento Municipal Utility District (SMUD) and have been analyzed and the survey customers selected. The second type will consist of detailed technical data on buildings in the SMSA's of Los Angeles, San Diego, San Francisco, and Sacramento. This report presents the final methodology for the selection of building samples, by type and location, for the detailed building data collection. Eleven tables present the results of the analysis. Within service areas and/or SMSA's, significant establishment classifications are illustrated with their energy characteristics. The allocation of the detailed survey-sample members is illustrated, according to establishment classifications and the 24 different building types. This specification is further detailed as to allocations within the SMUD service area and those to be taken from other areas. The methodology presented in this final report is being used to select sample members for the detailed survey.

Not Available

1980-02-01T23:59:59.000Z

165

A Framework for Corporate Householding  

E-Print Network (OSTI)

Previous research on corporate household and corporate householding has presented examples, literature review, and working definitions. In this paper, we first improve our ...

Madnick, Stuart

2003-03-21T23:59:59.000Z

166

High-Intensity Discharge Industrial Lighting Design Strategies for the Minimization of Energy Usage and Life-Cycle Cost.  

E-Print Network (OSTI)

??Worldwide, the electrical energy consumed by artificial lighting is second only to the amount consumed by electric machinery. Of the energy usage attributed to lighting… (more)

Flory IV, Isaac L.

2008-01-01T23:59:59.000Z

167

Towards sustainable household energy use in the Netherlands, Int  

E-Print Network (OSTI)

Abstract: Households consume direct energy, using natural gas, heating oil, gasoline and electricity, and consume indirect energy, the energy related to the production of goods and the delivery of services for the households. Past trends and present-day household energy use (direct and indirect) are analysed and described. A comparison of these findings with objectives concerning ecological sustainability demonstrates that present-day household energy use is not sustainable. A scenario towards sustainable household energy use is designed containing far-reaching measures with regard to direct energy use. Scenario evaluation shows a substantial reduction of direct energy use; however, this is not enough to meet the sustainability objectiv es. Based on these results, the possibilities and the limitations are discussed to enable households to make their direct and indirect energy use sustainable on the long run.

Jack Van Der Wal; Henri C. Moll

2001-01-01T23:59:59.000Z

168

Energy Usage | Department of Energy  

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

Usage Energy Usage How much do you spend per year compared to others? A state-by-state map of per capita energy expenditures. Subtopics Storage Consumption Transmission Smart Grid...

169

Memory Usage Considerations on Franklin  

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

the memory requirement vvia internal checking in their codes or by some tools. Craypat could track heap usage. And IPM also tracks memory usage. Last edited: 2013-06-30 08:33:51...

170

Usage by Job Size  

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

Usage by Job Usage by Job Size Table Usage by Job Size Table page loading animation Usage Query Interface System All Hopper Edison Carver Planck Matgen Franklin Hopper 1 Magellan Dirac Bassi Jacquard Seaborg User Account (Repo) Execution Queue All Debug Interactive Premium Regular Short Regular Long Regular Small Regular Medium Regular Big Regular Extra Big Killable Low Transfer IO Task Special System Serial Big Memory Westmere === Inactive === Magellan Serial Magellan Short Magellan Small Magellan Medium Magellan Big Magellan Long Regular 1 Regular 1 Long Regular 16 Regular 32 Regular 48 Full Config Seaborg Serial Batch 16 Batch 32 Batch 64 Submit Queue all interactive debug premium regular low DOE Office all ASCR BER BES FES HEP NP Summary for jobs that completed after Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 @ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 : 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59

171

Table AP1. Total Households Using Home Appliances and Lighting by ...  

U.S. Energy Information Administration (EIA)

Total Consumption for Home Appliances and Lighting by Fuels Used, 2005 Quadrillion British Thermal Units (Btu) U.S. Households (millions) Electricity

172

Table CE1-4c. Total Energy Consumption in U.S. Households by Type ...  

U.S. Energy Information Administration (EIA)

Total Energy Consumption in U.S. Households by Type of Housing Unit, 2001 RSE Column Factor: Total ... where the end use is electric air-conditioning, ...

173

U.S. household expenditures for gasoline account for nearly 4% of ...  

U.S. Energy Information Administration (EIA)

Electricity. Sales, revenue and prices, power plants, fuel use, ... a rise in average gasoline prices has led to higher overall household gasoline expenditures.

174

Material World: Forecasting Household Appliance Ownership in a Growing Global Economy  

E-Print Network (OSTI)

and V. Letschert (2005). Forecasting Electricity Demand in8364 Material World: Forecasting Household ApplianceMcNeil, 2008). Forecasting Diffusion Forecasting Variables

Letschert, Virginie

2010-01-01T23:59:59.000Z

175

Table SH2. Total Households by Space Heating Fuels Used, 2005 ...  

U.S. Energy Information Administration (EIA)

Total Households by Space Heating Fuels Used, 2005 ... 2005 Residential Energy Consumption Survey: ... Electricity Natural Gas Fuel Oil Kerosene LPG Other

176

Household Vehicles Energy Use: Latest Data and Trends - Table A01  

U.S. Energy Information Administration (EIA)

U.S. Per Household Vehicle-Miles Traveled ... and Alternate Fuels, Form EIA-826, "Monthly Electric Utility Sales and Revenue Report with State Distributions."

177

Household energy and consumption and expenditures, 1990. [Contains Division, Census Region, and Climate Zone maps  

Science Conference Proceedings (OSTI)

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

Not Available

1993-03-02T23:59:59.000Z

178

New energy usage patterns in manufacturing  

SciTech Connect

Long term energy demands of industrial societies will exceed energy production capabilities if present usage patterns remain unchanged. Thus the central core of the current energy dilemma involves the change from reliance on petroleum sources to the utilization of more plentiful energy resources. The two energy resources which are plentiful and the technology already exists for their development are coal and uranium. Several concepts of substituting electricity for oil and natural gas are presented.

Hauser, L.G.

1976-01-01T23:59:59.000Z

179

Quantum Electrical Measurements Programs/Projects in PML  

Science Conference Proceedings (OSTI)

... and manufacturers use NIST electrical standards and calibrations for all kinds of measurements from home electricity usage to electrocardiograms ...

2010-10-05T23:59:59.000Z

180

housingunit_household2001.pdf  

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

Housing Unit Tables Housing Unit Tables (Million U.S. Households; 49 pages, 210 kb) Contents Pages HC1-1a. Housing Unit Characteristics by Climate Zone, Million U.S. Households, 2001 5 HC1-2a. Housing Unit Characteristics by Year of Construction, Million U.S. Households, 2001 4 HC1-3a. Housing Unit Characteristics by Household Income, Million U.S. Households, 2001 4 HC1-4a. Housing Unit Characteristics by Type of Housing Unit, Million U.S. Households, 2001 4 HC1-5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 4 HC1-6a. Housing Unit Characteristics by Type of Rented Housing Unit, Million U.S. Households, 2001 4 HC1-7a. Housing Unit Characteristics by Four Most Populated States, Million U.S. Households, 2001 4

Note: This page contains sample records for the topic "household electricity usage" 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

homeoffice_household2001.pdf  

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

Home Office Equipment Tables Home Office Equipment Tables (Million U.S. Households; 12 pages, 123 kb) Contents Pages HC7-1a. Home Office Equipment by Climate Zone, Million U.S. Households, 2001 1 HC7-2a. Home Office Equipment by Year of Construction, Million U.S. Households, 2001 1 HC7-3a. Home Office Equipment by Household Income, Million U.S. Households, 2001 1 HC7-4a. Home Office Equipment by Type of Housing Unit, Million U.S. Households, 2001 1 HC7-5a. Home Office Equipment by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 1 HC7-6a. Home Office Equipment by Type of Rented Housing Unit, Million U.S. Households, 2001 1 HC7-7a. Home Office Equipment by Four Most Populated States, Million U.S. Households, 2001 1

182

Customer Strategies for Responding to Day-Ahead Market Hourly Electricity Pricing  

E-Print Network (OSTI)

nature of electric service and usage, defining the hoursElectric. 12 The resulting evaluation report estimated elasticities and found measurable reductions in energy usage

2005-01-01T23:59:59.000Z

183

Woodfuel Usage Update 1 I Wood fuel use in Scotland 2010 I Hudson Consulting I October 2010  

E-Print Network (OSTI)

woodfuel usage in the commercial, industrial and electrical energy sectors of the Scottish market) to 30 of electrical energy generation, was paramount in the initial survey and remains so. Total woodfuel usageWoodfuel Usage Update 1 I Wood fuel use in Scotland 2010 I Hudson Consulting I October 2010

184

Electrical Usage Characterization of Semiconductor Processing Tools  

E-Print Network (OSTI)

This paper presents the basic concepts in performing an energy and power audit of a semiconductor process tool. A protocol exists that fully describes these measurements and their use and applicability and it will be described. This protocol is currently being examined by SEMATECH for future publication. Example data will be presented showing the power, energy, and current load profiles of a typical tool.

Hinson, S. R.

2000-04-01T23:59:59.000Z

185

Household Vehicles Energy Use Cover Page  

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

Household Vehicles Energy Use Cover Page Glossary Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use Cover Page Contact Us * Feedback *...

186

appl_household2001.pdf  

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

9a. Appliances by Northeast Census Region, 9a. Appliances by Northeast Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.3 1.6 Total .............................................................. 107.0 20.3 14.8 5.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 19.6 14.5 5.2 1.1 1 .............................................................. 95.2 18.2 13.3 4.9 1.1 2 or More ................................................. 6.5 1.4 1.1 0.3 11.7 Most Used Oven ...................................... 101.7 19.6 14.5 5.2 1.1 Electric .....................................................

187

appl_household2001.pdf  

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

2a. Appliances by West Census Region, 2a. Appliances by West Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.7 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 22.1 6.6 15.5 1.1 1 .............................................................. 95.2 20.9 6.4 14.5 1.1 2 or More ................................................. 6.5 1.2 0.2 1.0 14.6 Most Used Oven ...................................... 101.7 22.1 6.6 15.5 1.1 Electric .....................................................

188

Household Vehicles Energy Consumption 1991  

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

. . Trends in Household Vehicle Stock The 1991 RTECS counted more than 150 million vehicles in use by U.S. households. This chapter examines recent trends in the vehicle stock, as measured by the RTECS and other reputable vehicle surveys. It also provides some details on the type and model year of the household vehicle stock, and identifies regional differences in vehicle stock. Because vehicles are continuously being bought and sold, this chapter also reports findings relating to turnover of the vehicle stock in 1991. Finally, it examines the average vehicle stock in 1991 (which takes into account the acquisition and disposal of household vehicles over the course of the year) and identifies variations in the average number of household vehicles based on differences in household characteristics. Number of Household Vehicles Over the past 8 years, the stock of household vehicles has

189

Household Vehicles Energy Consumption 1991  

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

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

190

Improving energy usage  

SciTech Connect

The Phillips Petroleum Company's Borger Refinery and NGL Process Center Energy Conservation program has been one of surveying, making revisions and additions to, and redesign of processes and equipment to conserve energy. Special emphasis has been placed on minimizing energy usage in the design of new processes in the plants. In 1972 an average of 758,800 Btu's were used to process each barrel of fresh charge. Now 7.5 days of fresh charge are being saved to the plant each year. The energy-use reduction programs discussed were: (1) furnace and boiler excess-oxygen and combustibles control program; (2) installation of an Applied Automation, Inc., Fractionator Computer Control System named Optrol; and (3) the steam-trap program. 1 figure. (DP)

Haage, P.R.

1983-03-01T23:59:59.000Z

191

HPSS Usage Examples at NERSC  

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

Examples Advanced Usage Examples Transferring Data from Batch Jobs Once you have set up your automatic HPSS authentication you can access HPSS within batch scripts. Read More ...

192

Palmetto Electric Cooperative - Buried Treasure Rebate Program...  

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

Electric Cooperative - Buried Treasure Rebate Program Palmetto Electric Cooperative - Buried Treasure Rebate Program Eligibility Residential Maximum Rebate 1,000 per household...

193

Household Hazardous Waste Household hazardous waste is the discarded, unused, or leftover portion of household products  

E-Print Network (OSTI)

Household Hazardous Waste Household hazardous waste is the discarded, unused, or leftover portion of household products containing toxic chemicals. These wastes CANNOT be disposed of in regular garbage. Any should be considered hazardous. You cannot treat hazardous wastes like other kinds of garbage

de Lijser, Peter

194

Modelling the Energy Demand of Households in a Combined  

E-Print Network (OSTI)

. Emissions from passenger transport, households'electricity and heat consumption are growing rapidly despite demand analysis for electricity (e.g. Larsen and Nesbakken, 2004; Holtedahl and Joutz, 2004; Hondroyiannis, 2004) and passenger cars (Meyer et al., 2007). Some recent studies cover the whole residential

Steininger, Karl W.

195

The UCONABC usage control model  

Science Conference Proceedings (OSTI)

In this paper, we introduce the family of UCONABC models for usage control (UCON), which integrate Authorizations (A), oBligations (B), and Conditions (C). We call these core models because they address the essence of UCON, leaving ... Keywords: access control, digital rights management, privacy, trust, usage control

Jaehong Park; Ravi Sandhu

2004-02-01T23:59:59.000Z

196

Definition: Reduced Oil Usage (Not Monetized) | Open Energy Information  

Open Energy Info (EERE)

Usage (Not Monetized) Usage (Not Monetized) Jump to: navigation, search Dictionary.png Reduced Oil Usage (Not Monetized) The functions that provide this benefit eliminate the need to send a line worker or crew to the switch or capacitor locations to operate them eliminate the need for truck rolls to perform diagnosis of equipment condition, and reduce truck rolls for meter reading and measurement purposes. This reduces the fuel consumed by a service vehicle or line truck. The use of plug-in electric vehicles can also lead to this benefit since the electrical energy used by plug-in electric vehicles displaces the equivalent amount of oil.[1] References ↑ SmartGrid.gov 'Description of Benefits' An LikeLike UnlikeLike You like this.Sign Up to see what your friends like. inline Glossary Definition

197

The Growth in Electricity Demand in U - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

responsible almost for 70 percent of household emissions. ... Weather is a major cause of the variation in household electricity use for space cooling and

198

ac_household2001.pdf  

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

Air Conditioning Tables Air Conditioning Tables (Million U.S. Households; 24 pages, 138 kb) Contents Pages HC4-1a. Air Conditioning by Climate Zone, Million U.S. Households, 2001 2 HC4-2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 2 HC4-3a. Air Conditioning by Household Income, Million U.S. Households, 2001 2 HC4-4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 2 HC4-5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 2 HC4-6a. Air Conditioning by Type of Rented Housing Unit, Million U.S. Households, 2001 2 HC4-7a. Air Conditioning by Four Most Populated States, Million U.S. Households, 2001 2 HC4-8a. Air Conditioning by Urban/Rural Location, Million U.S. Households, 2001 2

199

Load-shifting in a new perspective: Smart scheduling of smart household appliances using an Agent-Bsaed Modelling Approach.  

E-Print Network (OSTI)

??The electricity demand of households in the Netherlands has been growing rapidly for the last decades and will continue to grow in the near future.… (more)

De Blécourt, M.J.

2012-01-01T23:59:59.000Z

200

California customer load reductions during the electricity crisis: Did they help to keep the lights on?  

E-Print Network (OSTI)

solar PV systems or virtually eliminating their electricity usage through dramatic changes in their energy-

Goldman, Charles A.; Eto, Joseph H.; Barbose, Galen L.

2002-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household electricity usage" 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

Energy Spending and Vulnerable Households  

E-Print Network (OSTI)

 off than before. In particular large households with low  incomes seem to have been adversely affected by the new tariff structures since  they have comparably large energy expenditure (Bennet et al., 2002).    5. Vulnerable Households and Energy Spending  The...  tariffs can play an important part in the public debate  on  eradicating  fuel  poverty  and  helping  the  vulnerable  households.  Smart  metering  can  provide  consumers  with  information  on  the  actual  energy  consumption and might  lead  to...

Jamasb, Tooraj; Meier, Helena

2011-01-26T23:59:59.000Z

202

Household Vehicles Energy Consumption 1991  

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

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

203

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

204

EIA - Electricity Data - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Electricity. Sales, revenue and ... codes or demands or usage falling within specified limits by rate ... Monthly Electric Sales and Revenue Report with State ...

205

Learning from Consumers: Plug-In Hybrid Electric Vehicle (PHEV) Demonstration and Consumer Education, Outreach, and Market Research Program  

E-Print Network (OSTI)

electricity and actual electricity demand to recharge PHEVs.the Project households, electricity demand to recharge theirAs with weekday electricity demand, most actual weekend

Kurani, Kenneth S; Axsen, Jonn; Caperello, Nicolette; Davies, Jamie; Stillwater, Tai

2009-01-01T23:59:59.000Z

206

Water Usage Law, Major Water Users (Missouri) | Department of Energy  

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

Water Usage Law, Major Water Users (Missouri) Water Usage Law, Major Water Users (Missouri) Water Usage Law, Major Water Users (Missouri) < Back Eligibility Agricultural Commercial Construction Fed. Government Industrial Institutional Investor-Owned Utility Local Government Municipal/Public Utility Retail Supplier Rural Electric Cooperative Systems Integrator Tribal Government Utility Savings Category Water Buying & Making Electricity Program Info State Missouri Program Type Environmental Regulations Provider Missouri Department of Natural Resources Any water user with the capability to withdraw or divert 100,000 gallons or more per day from any stream, river, lake, well, spring or other water source must register and file for a permit for water withdrawal and diversion from the Department of Natural Resources. Additionally, no major

207

appl_household2001.pdf  

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

4a. Appliances by Type of Housing Unit, 4a. Appliances by Type of Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.5 1.7 1.6 1.9 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 69.1 9.4 16.7 6.6 4.3 1 ................................................ 95.2 63.7 8.9 16.2 6.3 4.3 2 or More .................................. 6.5 5.4 0.4 0.4 0.2 15.9 Most Used Oven ........................ 101.7 69.1 9.4 16.7 6.6 4.3 Electric ...................................... 63.0 43.3 5.2 10.9 3.6

208

appl_household2001.pdf  

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

5a. Appliances by Type of Owner-Occupied Housing Unit, 5a. Appliances by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.3 0.4 2.1 3.1 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Kitchen Appliances Cooking Appliances Oven ........................................... 68.3 59.1 2.0 1.7 5.4 7.0 1 ................................................ 62.9 54.1 2.0 1.6 5.2 7.1 2 or More .................................. 5.4 5.0 Q Q 0.2 22.1 Most Used Oven ........................ 68.3 59.1 2.0 1.7 5.4 7.0 Electric ......................................

209

appl_household2001.pdf  

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

2a. Appliances by Year of Construction, 2a. Appliances by Year of Construction, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.5 1.2 1.1 1.2 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 14.3 17.2 17.8 12.9 13.7 25.9 4.2 1 ................................................ 95.2 13.1 16.3 16.6 12.1 12.7 24.3 4.4 2 or More .................................. 6.5 1.2 0.9 1.1 0.7 1.0 1.6 14.8 Most Used Oven ........................ 101.7 14.3 17.2 17.8 12.9 13.7 25.9 4.2 Electric ......................................

210

Electricity  

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

Electricity is an essential part of modern life. The Energy Department is working to create technology solutions that will reduce our energy use and save Americans money.

211

char_household2001.pdf  

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

3a. Household Characteristics by Household Income, 3a. Household Characteristics by Household Income, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Household Size 1 Person ....................................... 28.2 9.7 -- -- -- 6.5 11.3 5.7 2 Persons ...................................... 35.1 4.3 -- -- -- 2.0 7.8 5.8 3 Persons ...................................... 17.0 -- 3.3 -- -- 2.2 5.2 7.3 4 Persons ...................................... 15.6 -- 2.2 -- -- -- 4.3 8.1 5 Persons ...................................... 7.1

212

char_household2001.pdf  

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

2a. Household Characteristics by West Census Region, 2a. Household Characteristics by West Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.8 1.1 Total .............................................................. 107.0 23.3 6.7 16.6 NE Household Size 1 Person ...................................................... 28.2 5.6 1.8 3.8 5.4 2 Persons .................................................... 35.1 7.3 1.9 5.5 4.9 3 Persons .................................................... 17.0 3.5 0.9 2.6 7.6 4 Persons .................................................... 15.6 3.5 1.1 2.4 6.4 5 Persons .................................................... 7.1 2.0 0.6 1.4 9.7 6 or More Persons

213

Household Vehicles Energy Consumption 1991  

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

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

214

char_household2001.pdf  

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

0a. Household Characteristics by Midwest Census Region, 0a. Household Characteristics by Midwest Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 24.5 17.1 7.4 NE Household Size 1 Person ...................................................... 28.2 6.7 4.7 2.0 6.2 2 Persons .................................................... 35.1 8.0 5.4 2.6 5.0 3 Persons .................................................... 17.0 3.8 2.7 1.1 7.9 4 Persons .................................................... 15.6 3.5 2.5 1.0 8.1 5 Persons .................................................... 7.1 1.7

215

Forecasting multi-appliance usage for smart home energy management  

Science Conference Proceedings (OSTI)

We address the problem of forecasting the usage of multiple electrical appliances by domestic users, with the aim of providing suggestions about the best time to run appliances in order to reduce carbon emissions and save money (assuming time-of-use ...

Ngoc Cuong Truong, James McInerney, Long Tran-Thanh, Enrico Costanza, Sarvapali D. Ramchurn

2013-08-01T23:59:59.000Z

216

Extending Efficiency Services to Underserved Households: NYSERDA...  

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

Extending Efficiency Services to Underserved Households: NYSERDA's Assisted Home Performance with ENERGY STAR Program Title Extending Efficiency Services to Underserved Households:...

217

Reducing Energy Usage of NULL Convention Logic Circuits using NULL Cycle Reduction  

E-Print Network (OSTI)

in approximately 25% overall lower energy usage. Keywords: asynchronous circuits; NULL Convention Logic (NCL); NULLReducing Energy Usage of NULL Convention Logic Circuits using NULL Cycle Reduction Combined with Supply Voltage Scaling Brett Sparkman and Scott C. Smith Department of Electrical Engineering, University

Smith, Scott C.

218

Table CE3-6.2u. Electric Air-Conditioning Energy Consumption and ...  

U.S. Energy Information Administration (EIA)

Table CE3-6.2u. Electric Air-Conditioning Energy Consumption and Expenditures by Square Feet and Usage Indicators, 2001 Usage Indicators RSE Column Factor:

219

Household vehicles energy consumption 1994  

SciTech Connect

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

NONE

1997-08-01T23:59:59.000Z

220

UK Electricity Consumption and Number of Meters at MLSOA level (2008) |  

Open Energy Info (EERE)

8) 8) Dataset Summary Description The UK Department of Energy and Climate Change (DECC) releases annual statistics on domestic and non-domestic electricity and gas consumption (and number of meters) at the Middle Layer Super Output Authority (MLSOA) and Intermediate Geography Zone (IGZ) level (there are over 950 of these subregions throughout England, Scotland and Wales). Both MLSOAs (England and Wales) and IGZs (Scotland) include a minimum of approximately 2,000 households. The electricity consumption data data is split by ordinary electricity and economy7 electricity usage. All data in this set are classified as UK National Statistics. Related socio-economic data for MLSOA and IGZ levels can be accessed: http://decc.gov.uk/assets/decc/Statistics/regional/mlsoa2008/181-mlsoa-i...

Note: This page contains sample records for the topic "household electricity usage" 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

Potential Benefits from Improved Energy Efficiency of Key Electrical Products: The Case of India  

E-Print Network (OSTI)

on projections of electricity prices or avoided costs forthe projected marginal electricity price for households orfirst cost. Marginal Electricity Prices The consumer impacts

McNeil, Michael; Iyer, Maithili; Meyers, Stephen; Letschert, Virginie; McMahon, James E.

2005-01-01T23:59:59.000Z

222

Use characteristics and mode choice behavior of electric bike users in China  

E-Print Network (OSTI)

in the household Car* Bicycle Electric bike Motorcyclehousehold Car Motorcycle Bicycle Electric bike LPG scooteror a 21 few) electric bike users shifted to cars? The safety

Cherry, Christopher; Cervero, Robert

2007-01-01T23:59:59.000Z

223

EIA - Household Transportation report: Household Vehicles Energy Use:  

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

Transportation logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Use: Latest Data & Trends November 2005 Release (Next Update: Discontinued) Based on the 2001 National Household Travel Survey conducted by the U.S. Department of Transportation and augmented by EIA Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses in an effort to maintain consistency with its past residential transportation series, which was discontinued after 1994. This report, Household Vehicles Energy Use: Latest Data & Trends, provides details on the nation's energy use for household passenger travel. A primary purpose of this report is to release the latest consumer-based data

224

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

225

Household Vehicles Energy Consumption 1994  

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

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

226

ac_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

2a. Air Conditioning by West Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total...

227

Household savings and portfolio choice  

E-Print Network (OSTI)

This thesis consists of three essays that examine household savings and portfolio choice behavior. Chapter One analyses the effects of employer matching contributions and tax incentives on participation and contribution ...

Klein, Sean Patrick

2010-01-01T23:59:59.000Z

228

Household vehicles energy consumption 1991  

Science Conference Proceedings (OSTI)

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

Not Available

1993-12-09T23:59:59.000Z

229

Cover Page of Household Vehicles Energy Use: Latest Data & Trends  

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

Household Vehicles Energy Use Cover Page Cover Page of Household Vehicles Energy Use: Latest Data & Trends...

230

OpenEI - Unit Cost Electricity  

Open Energy Info (EERE)

at University of Texas at Austin http:en.openei.orgdatasetsnode62

Provides annual energy usage for years 1989 through 2010 for UT at Austin; specifically, electricity usage...

231

Table CE1-4c. Total Energy Consumption in U.S. Households by Type ...  

U.S. Energy Information Administration (EIA)

Table CE1-4c. Total Energy Consumption in U.S. Households by Type of Housing Unit, 1997 ... where the end use is electric air-conditioning, ...

232

ELECTRIC  

Office of Legacy Management (LM)

ELECTRIC cdrtrokArJclaeT 3 I+ &i, y I &OF I*- j< t j,fci..- ir )(yiT E-li, ( -,v? Cl -p4.4 RESEARCH LABORATORIES EAST PITTSBURGH, PA. 8ay 22, 1947 Mr. J. Carrel Vrilson...

233

Household Energy Expenditure and Income Groups: Evidence from Great Britain  

E-Print Network (OSTI)

  and  0.024  for  district heating However, as income is not observed its effect cannot be analysed.  Wu et al. (2004) examine the demand for space heating in Armenia, Moldova, and  Kyrgyz  Republic  using  household  survey  data.  In  these  countries...  and in some regions incomes are not sufficient to  afford space heating from district heating systems making these systems unviable.  We  analyse  electricity,  gas  and  overall  energy  spending  for  a  large  sample  of  households  in  Great  Britain.  We  discern  inflection  points  and  discuss...

Jamasb, Tooraj; Meier, H

234

ELECTRIC  

Office of Legacy Management (LM)

ELECTRIC ELECTRIC cdrtrokArJclaeT 3 I+ &i, y$ \I &OF I*- j< t j,fci..- ir )(yiT !E-li, ( \-,v? Cl -p/4.4 RESEARCH LABORATORIES EAST PITTSBURGH, PA. 8ay 22, 1947 Mr. J. Carrel Vrilson General ?!!mager Atomic Qxzgy Commission 1901 Constitution Avenue Kashington, D. C. Dear Sir: In the course of OUT nuclenr research we are planning to study the enc:ri;y threshold anti cross section for fission. For thib program we require a s<>piAroted sample of metallic Uranium 258 of high purity. A quantity of at lezst 5 grams would probably be sufficient for our purpose, and this was included in our 3@icntion for license to the Atonic Energy Coskqission.. This license has been approved, 2nd rre would Llp!Jreciate informztion as to how to ?r*oceed to obtain thit: m2teria.l.

235

Lincoln Electric System (Residential)- Sustainable Energy Program  

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

Lincoln Electric System (LES) offers several rebates to residential customers who are interested in upgrading to energy efficient household equipment. The program includes rebates for insulation...

236

Smart Metering for Smart Electricity Consumption.  

E-Print Network (OSTI)

??In recent years, the demand for electricity has increased in households with the use of different appliances. This raises a concern to many developed and… (more)

Vadda, Praveen

2013-01-01T23:59:59.000Z

237

The welfare effects of raising household energy prices in Poland  

Science Conference Proceedings (OSTI)

We examine the welfare effects from increasing household energy prices in Poland. Subsidizing household energy prices, common in the transition economies, is shown to be highly regressive. The wealthy spend a larger portion of their income on energy and consume more energy in absolute terms. We therefore rule out the oft-used social welfare argument for delaying household energy price increases. Raising prices, while targeting relief to the poor through a social assistance program is the first-best response. However, if governments want to ease the adjustment, several options are open, including: in-kind transfers to the poor, vouchers, in-cash transfers, and lifeline pricing for electricity. Our simulations show that if raising prices to efficient levels is not politically feasible at present and social assistance targeting is sufficiently weak, it may be socially better to use lifeline pricing and a large price increase than an overall, but smaller, price increase.

Freund, C.L. [Columbia Univ., New York, NY (United States); Wallich, C.I. [World Bank, Washington, DC (United States)

1996-06-01T23:59:59.000Z

238

char_household2001.pdf  

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

5a. Household Characteristics by Type of Owner-Occupied Housing Unit, 5a. Household Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Homes Two to Four Units Five or More Units 0.3 0.4 2.0 2.9 1.3 Total Owner-Occupied Units ....... 72.7 63.2 2.1 1.8 5.7 6.7 Household Size 1 Person ....................................... 15.8 12.5 0.8 0.9 1.6 10.3 2 Persons ...................................... 25.9 23.4 0.5 0.5 1.5 10.1 3 Persons ...................................... 11.6 9.6 0.5 Q 1.3 12.1 4 Persons ...................................... 11.8 10.9 Q Q 0.7 15.7 5 Persons ...................................... 5.1 4.5 Q Q 0.4 24.2 6 or More Persons

239

char_household2001.pdf  

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

1a. Household Characteristics by South Census Region, 1a. Household Characteristics by South Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.1 1.5 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Household Size 1 Person ...................................................... 28.2 9.9 5.0 1.8 3.1 6.3 2 Persons .................................................... 35.1 13.0 6.7 2.5 3.8 4.2 3 Persons .................................................... 17.0 6.6 3.7 1.2 1.7 8.8 4 Persons .................................................... 15.6 6.0 3.3 0.8 1.9 10.7 5 Persons ....................................................

240

char_household2001.pdf  

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

8a. Household Characteristics by Urban/Rural Location, 8a. Household Characteristics by Urban/Rural Location, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.1 Household Size 1 Person ...................................................... 28.2 14.6 5.3 4.8 3.6 6.4 2 Persons .................................................... 35.1 15.7 5.7 6.9 6.8 5.4 3 Persons .................................................... 17.0 7.6 2.8 3.5 3.1 7.2 4 Persons .................................................... 15.6 6.8 2.3 4.1 2.4 8.1 5 Persons .................................................... 7.1 3.1 1.3 1.3 1.4 12.3 6 or More Persons

Note: This page contains sample records for the topic "household electricity usage" 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

char_household2001.pdf  

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

a. Household Characteristics by Climate Zone, a. Household Characteristics by Climate Zone, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.0 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Household Size 1 Person ....................................... 28.2 2.5 8.1 6.5 4.8 6.2 9.9 2 Persons ...................................... 35.1 3.1 9.4 8.2 6.5 7.9 8.7 3 Persons ...................................... 17.0 1.3 4.3 4.0 3.3 4.1 10.7 4 Persons ...................................... 15.6 1.4 3.9 3.4 3.4 3.5 10.5 5 Persons ......................................

242

char_household2001.pdf  

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

6a. Household Characteristics by Type of Rented Housing Unit, 6a. Household Characteristics by Type of Rented Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total Rented Units ........................ 34.3 10.5 7.4 15.2 1.1 6.9 Household Size 1 Person ....................................... 12.3 2.5 2.6 7.0 0.3 10.0 2 Persons ...................................... 9.2 2.5 2.5 4.1 Q 11.8 3 Persons ...................................... 5.4 2.0 1.1 2.0 0.4 13.9 4 Persons ...................................... 3.8 1.6 0.7 1.4 Q 17.7 5 Persons ...................................... 2.0 0.9 0.4 0.6 Q 24.1 6 or More Persons ........................

243

homeoffice_household2001.pdf  

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

3a. Home Office Equipment by Household Income, 3a. Home Office Equipment by Household Income, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.4 1.9 1.2 1.0 0.6 1.9 0.9 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 47.6 3.0 Households Using Office Equipment .......................... 96.2 13.2 19.8 25.5 37.7 10.7 38.8 3.2 Personal Computers 2 ................... 60.0 3.7 8.7 16.0 31.6 3.7 17.4 4.6 Number of Desktop PCs 1 .................................................. 45.1 2.8 7.1 12.8 22.4 2.8 13.6 5.1 2 or more .................................... 9.1 0.6 0.7 1.7 6.2 0.6 2.2 13.0 Number of Laptop PCs

244

char_household2001.pdf  

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

2a. Household Characteristics by Year of Construction, 2a. Household Characteristics by Year of Construction, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.0 1.2 1.2 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Household Size 1 Person ....................................... 28.2 2.5 4.5 5.1 4.0 3.7 8.3 7.5 2 Persons ...................................... 35.1 4.8 6.2 6.6 4.5 5.3 7.8 5.8 3 Persons ...................................... 17.0 2.5 3.3 2.9 2.3 1.9 4.1 8.4 4 Persons ...................................... 15.6 3.4 2.8 2.3 1.9 1.8 3.4 9.6 5 Persons ...................................... 7.1 1.6 1.2 1.3 0.6 0.7 1.6 14.3 6 or More Persons

245

Delivering Energy Efficiency to Middle Income Single Family Households  

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

Delivering Energy Efficiency to Middle Income Single Family Households Delivering Energy Efficiency to Middle Income Single Family Households Title Delivering Energy Efficiency to Middle Income Single Family Households Publication Type Report Year of Publication 2011 Authors Zimring, Mark, Merrian Borgeson, Ian M. Hoffman, Charles A. Goldman, Elizabeth Stuart, Annika Todd, and Megan A. Billingsley Pagination 102 Date Published 12/2011 Publisher LBNL City Berkeley Keywords electricity markets and policy group, energy analysis and environmental impacts department Abstract The question posed in this report is: How can programs motivate these middle income single family households to seek out more comprehensive energy upgrades, and empower them to do so? Research methods included interviews with more than 35 program administrators, policy makers, researchers, and other experts; case studies of programs, based on interviews with staff and a review of program materials and data; and analysis of relevant data sources and existing research on demographics, the financial status of Americans, and the characteristics of middle income American households. While there is no 'silver bullet' to help these households overcome the range of barriers they face, this report describes outreach strategies, innovative program designs, and financing tools that show promise in increasing the attractiveness and accessibility of energy efficiency for this group. These strategies and tools should be seen as models that are currently being honed to build our knowledge and capacity to deliver energy improvements to middle income households. However, the strategies described in this report are probably not sufficient, in the absence of robust policy frameworks, to deliver these improvements at scale. Instead, these strategies must be paired with enabling and complementary policies to reach their full potential.

246

Towards Sustainable Material Usage: Investigating Limits to ...  

Science Conference Proceedings (OSTI)

Presentation Title, Towards Sustainable Material Usage: Investigating Limits to ... secondary resources decreases energy consumption; this energy advantage ...

247

Resource and Fuels Usage Contacting the Authors  

E-Print Network (OSTI)

) % of 1990 usage Natural gas 577 24% Biomass 494 1190% Renewables 182 106% Nuclear 73 62% Coal 561 908 sectors · LDV is least carbon-intensive Total Energy (PJ) % of 1990 usage Natural gas 122 5% Biomass 891T activity) 9% line (218% PxT activity) In-State Emissions Total Energy (PJ) % of 1990 usage Natural gas 123

California at Davis, University of

248

Household energy in South Asia  

Science Conference Proceedings (OSTI)

This research study on the use of energy in South Asis (India, Pakistan, Sri Lanka and Bangladesh) was sponsored by the Food and Agriculture Organization of the UN, the International Bank for Reconstruction and Development (the World Bank), and the Directorate-General for Development of the Commission of the European Communities. The aim of this book is to improve the understanding of household energy and its linkages, by reviewing the data resources on household energy use, supply, prices and other relevant factors that exist in South Asia.

Leach, G.

1987-01-01T23:59:59.000Z

249

Appliance Commitment for Household Load Scheduling  

Science Conference Proceedings (OSTI)

This paper presents a novel appliance commitment algorithm that schedules thermostatically-controlled household loads based on price and consumption forecasts considering users comfort settings to meet an optimization objective such as minimum payment or maximum comfort. The formulation of an appliance commitment problem was described in the paper using an electrical water heater load as an example. The thermal dynamics of heating and coasting of the water heater load was modeled by physical models; random hot water consumption was modeled with statistical methods. The models were used to predict the appliance operation over the scheduling time horizon. User comfort was transformed to a set of linear constraints. Then, a novel linear, sequential, optimization process was used to solve the appliance commitment problem. The simulation results demonstrate that the algorithm is fast, robust, and flexible. The algorithm can be used in home/building energy-management systems to help household owners or building managers to automatically create optimal load operation schedules based on different cost and comfort settings and compare cost/benefits among schedules.

Du, Pengwei; Lu, Ning

2011-06-30T23:59:59.000Z

250

Household energy consumption and expenditures 1987  

SciTech Connect

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

Not Available

1990-01-22T23:59:59.000Z

251

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

252

" Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"  

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

3 Lighting Usage Indicators by Household Income, 2005" 3 Lighting Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Lighting Usage Indicators" "Total U.S. Housing Units",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between 1 and 4 Hours per Day",91.8,20.8,23.6,17,11.3,19.1,13,30.7 "1.",28.6,9.4,9.1,4.5,2.4,3.2,5.7,12.6 "2.",29.5,6.8,8,5.8,3.7,5.2,4.2,10.2

253

Assumptions to the Annual Energy Outlook 2002 - Household Expenditures...  

Annual Energy Outlook 2012 (EIA)

Expenditures Module The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and...

254

Table WH1. Total Households Using Water Heating Equipment, 2005 ...  

U.S. Energy Information Administration (EIA)

Table WH1. Total Households Using Water Heating Equipment, 2005 Million U.S. Households Fuels Used (million U.S. households) Number of Water Heaters Used

255

Predicting hourly building energy usage  

SciTech Connect

This article presents the results of an evaluation to identify the most accurate method for making hourly energy use predictions. The prediction of energy usage by HVAC systems is important for the purposes of HVAC diagnostics, system control, parameter and system identification, optimization and energy management. Many new techniques are now being applied to the analysis problems involved with predicting the future behavior of HVAC systems and deducing properties of these systems. Similar problems arise in most observational disciplines, including physics, biology and economics.

Kreider, J.F. (Univ. of Colorado, Boulder, CO (United States). Dept. of Civil, Environmental and Architectural Engineering); Haberl, J.S. (Texas A and M Univ., College Station, TX (United States). Mechanical Engineering Dept.)

1994-06-01T23:59:59.000Z

256

spaceheat_household2001.pdf  

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

3a. Space Heating by Household Income, 3a. Space Heating by Household Income, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Heat Home ..................................... 106.0 18.4 22.7 26.8 38.1 14.6 33.4 3.3 Do Not Heat Home ........................ 1.0 0.3 Q 0.3 0.3 0.3 0.4 23.4 No Heating Equipment .................. 0.5 Q Q Q 0.2 Q Q 35.0 Have Equipment But Do Not Use It ................................ 0.4 Q Q Q Q 0.2 0.3 22.8 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 106.0 18.4 22.7

257

appl_household2001.pdf  

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

3a. Appliances by Household Income, 3a. Appliances by Household Income, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.5 1.4 1.1 1.0 0.8 1.6 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 18.0 22.0 26.1 35.6 14.4 32.6 3.2 1 ................................................ 95.2 17.3 21.1 24.8 32.0 13.8 31.1 3.4 2 or More .................................. 6.5 0.8 0.9 1.3 3.6 0.6 1.5 13.1 Most Used Oven ........................ 101.7 18.0 22.0 26.1 35.6 14.4 32.6 3.2

258

NEWTON: Blood Group Systems Usage  

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

Blood Group Systems Usage Blood Group Systems Usage Name: Kishori Status: student Grade: n/a Location: Outside U.S. Country: India Date: Summer 2013 Question: What is the difference between MN blood group system and ABO bloodgroup system? Although, we nowadays prefer ABO blood groups why do we use MN blood groups in the forensic department? Replies: Humans actually have multiple blood antigens on the surface of our blood cells. Wikipedia says that there are over 50 different blood group antigens. ABO and Rh are just the most dominant. Rh actually has 3 alleles called C, D and E. So one could be CCddee, for example, but clinically, when referring to Rh, only the D antigen is considered. So MN is another system that is also present. The reason it would be considered in forensics is due to population genetics considerations. Certain combinations are found in different percentages depending on what ancestry a person is a part of. Humans evolved in isolation from each other and until relatively recently, were separated due to difficult travel/migration. But even though we can move around the planet easily now, we still carry the history of our ancestry in our DNA. M and N are codominant, like the ABO system.

259

"Table HC7.12 Home Electronics Usage Indicators by Household...  

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

",0.3,"Q",0.5,"Q","Q" "Monitor is Turned Off",0.5,"N","Q","Q","Q","Q","N","Q" "Use of Internet" "Have Access to Internet" "Yes",66.9,7.2,15.1,14.6,10.4,19.6,4.9,14 "Dial-up...

260

"Table HC7.10 Home Appliances Usage Indicators by Household...  

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

"4 or More",25.8,2.8,5.8,5.5,3.8,7.9,1.4,5.1 "Use of Most-Used Ceiling Fan" "Used All Summer",18.7,4.2,4.9,4.1,2.1,3.4,2.4,6.3 "Used Quite a Bit",16.2,3.4,3.8,3.3...

Note: This page contains sample records for the topic "household electricity usage" 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

Table HC6.10 Home Appliances Usage Indicators by Number of Household...  

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

... 25.8 4.1 9.3 4.7 4.5 3.2 Use of Most-Used Ceiling Fan Used All Summer... 18.7 4.7 6.0 2.9 2.9...

262

Household Energy Consumption and Expenditures 1993 -- Executive ...  

U.S. Energy Information Administration (EIA)

national level data on energy-related issues on households and energy expenditures in the residential sector.

263

Definition: Reduced Electricity Cost | Open Energy Information  

Open Energy Info (EERE)

Cost Jump to: navigation, search Dictionary.png Reduced Electricity Cost Functions that provide this benefit could help alter customer usage patterns (demand response with price...

264

Modeling Long-Term Search Engine Usage Ryen W. White, Ashish Kapoor, and Susan T. Dumais  

E-Print Network (OSTI)

photosensor design accurately senses daylight availability, cutting electric light usage 40­60 percent or morePhotosensors and associated control systems can dim or raise fluorescent lighting systems to decrease or increase the electrical lighting used as the amount of daylight changes during the day. However

Dumais, Susan

265

EART 265 Lecture Notes: Energy Energy Usage  

E-Print Network (OSTI)

EART 265 Lecture Notes: Energy Energy Usage US per capita energy usage is 10 kW. This represents 1 of 2 kW. Euro- pean countries tend to use less energy per capita by a factor of 2. China's per capita/4 of the worldwide energy usage, and with 1/20th of the world population gives a global average power consumption

Nimmo, Francis

266

Memory Usage Considerations on Hopper  

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

Memory Considerations Memory Considerations Memory Considerations Memory Usage Considerations on Hopper Most Hopper compute nodes have 32 GB of physical memory, but, not all that memory is available to user programs. Compute Node Linux (the kernel), the Lustre file system software, and message passing library buffers all consume memory, as does loading the executable into memory. Thus the precise memory available to an application varies. Approximately 31 GB of memory can be allocated from within an MPI program using all 24 cores per node, i.e., 1.29 GB per MPI task on average. If an application uses 12 MPI tasks per node, then each MPI task could use about 2.58 GB of memory. You may see an error message such as "OOM killer terminated this process." "OOM" means Out of Memory and it means that your code has exhausted the

267

The dynamics of electricity demand and supply in the low voltage distribution grid: a model study:.  

E-Print Network (OSTI)

??In this thesis a simulation study is executed that analyses how new developments of household electricity demand and decentralised electricity generation affect the low voltage… (more)

Van Zoest, P.L.A.

2013-01-01T23:59:59.000Z

268

Residential energy use and conservation actions: analysis of disaggregate household data  

Science Conference Proceedings (OSTI)

The Energy Information Administration recently published data they collected from the National Interim Energy Consumption Survey (NIECS). NIECS includes detailed information on 4081 individual households: demographic characteristics, energy-related features of the structure, heating equipment and appliances therein, recent conservation actions taken by the household, and fuel consumption and cost for the April 1978 to March 1979 one-year period. This data set provides a new and valuable resource for analysis. The NIECS data on household energy consumption - total energy use, electricity use, and use of the primary space heating fuel, are summarized and analyzed. The regression equations constructed explain roughly half the variation in energy use among households. These equations contain ten or fewer independent variables, the most important of which are fuel price, year house was built, floor area, and heating degree days. Regression equations were developed that estimate the energy saving achieved by each household based on their recent retrofit actions. These equations predict 20 to 40% of the variation among households. Total annual energy use is the most important determinant of retrofit energy saving; other significant variables include age of household head, household income, year house was built, housing tenure, and proxies for the cost of heating and air conditioning the house.

Hirst, E.; Goeltz, R.; Carney, J.

1981-03-01T23:59:59.000Z

269

Electric Water Heater Modeling and Control Strategies for Demand Response  

Science Conference Proceedings (OSTI)

Abstract— Demand response (DR) has a great potential to provide balancing services at normal operating conditions and emergency support when a power system is subject to disturbances. Effective control strategies can significantly relieve the balancing burden of conventional generators and reduce investment on generation and transmission expansion. This paper is aimed at modeling electric water heaters (EWH) in households and tests their response to control strategies to implement DR. The open-loop response of EWH to a centralized signal is studied by adjusting temperature settings to provide regulation services; and two types of decentralized controllers are tested to provide frequency support following generator trips. EWH models are included in a simulation platform in DIgSILENT to perform electromechanical simulation, which contains 147 households in a distribution feeder. Simulation results show the dependence of EWH response on water heater usage . These results provide insight suggestions on the need of control strategies to achieve better performance for demand response implementation. Index Terms— Centralized control, decentralized control, demand response, electrical water heater, smart grid

Diao, Ruisheng; Lu, Shuai; Elizondo, Marcelo A.; Mayhorn, Ebony T.; Zhang, Yu; Samaan, Nader A.

2012-07-22T23:59:59.000Z

270

Household Vehicles Energy Consumption 1991  

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

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

271

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

272

homeoffice_household2001.pdf  

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

0a. Home Office Equipment by Midwest Census Region, 0a. Home Office Equipment by Midwest Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Households Using Office Equipment ......................................... 96.2 22.4 15.7 6.7 1.3 Personal Computers 1 ................................. 60.0 14.1 9.9 4.2 3.7 Number of Desktop PCs 1 ................................................................ 45.1 10.4 7.2 3.2 3.7 2 or more ................................................... 9.1 2.3 1.6 0.7 10.1 Number of Laptop PCs 1 ................................................................

273

Energy and household expenditure patterns  

Science Conference Proceedings (OSTI)

Since households account, either directly or indirectly, for two-thirds of the energy consumed in the US, changes in household activities will affect energy use. Expected changes in prices, personal income, and family spending over the next 20 years are looked at as well as the implications for energy consumption. The analysis shows that direct energy purchases will break with past trends, dropping from 2.6% to 0.2% annual growth for the rest of the century. Growth in spending on energy-using goods is also likely to slow down. The year 2000 will see a marked decrease in the growth of national energy consumption. 58 references, 3 figures, 35 tables.

Lareau, T.J.; Darmstadter, J.

1983-01-01T23:59:59.000Z

274

homeoffice_household2001.pdf  

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

9a. Home Office Equipment by Northeast Census Region, 9a. Home Office Equipment by Northeast Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.1 1.4 1.2 Total .............................................................. 107.0 20.3 14.8 5.4 NE Households Using Office Equipment ......................................... 96.2 17.9 12.8 5.0 1.3 Personal Computers 1 ................................. 60.0 10.9 7.7 3.3 3.1 Number of Desktop PCs 1 ................................................................ 45.1 8.7 6.2 2.5 3.7 2 or more ................................................... 9.1 1.4 0.9 0.5 12.9 Number of Laptop PCs 1 ................................................................

275

char_household2001.pdf  

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

2001 2001 Household Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Total .............................................................. 107.0 7.1 12.3 7.7 6.3 NE Household Size 1 Person ...................................................... 28.2 2.2 2.4 1.8 1.7 7.3 2 Persons .................................................... 35.1 2.2 4.0 2.4 2.0 6.9 3 Persons .................................................... 17.0 1.1 2.0 1.2 1.2 9.5 4 Persons .................................................... 15.6 0.8 1.9 1.3 0.9 11.2 5 Persons .................................................... 7.1 0.4 1.1 0.4 0.5 19.8 6 or More Persons ....................................... 4.0 0.4 0.9 0.4 0.1 16.4 2001 Household Income Category

276

Inconsistent pathways of household waste  

Science Conference Proceedings (OSTI)

The aim of this study was to provide policy-makers and waste management planners with information about how recycling programs affect the quantities of specific materials recycled and disposed of. Two questions were addressed: which factors influence household waste generation and pathways? and how reliable are official waste data? Household waste flows were studied in 35 Swedish municipalities, and a wide variation in the amount of waste per capita was observed. When evaluating the effect of different waste collection policies, it was found to be important to identify site-specific factors influencing waste generation. Eleven municipal variables were investigated in an attempt to explain the variation. The amount of household waste per resident was higher in populous municipalities and when net commuting was positive. Property-close collection of dry recyclables led to increased delivery of sorted metal, plastic and paper packaging. No difference was seen in the amount of separated recyclables per capita when weight-based billing for the collection of residual waste was applied, but the amount of residual waste was lower. Sixteen sources of error in official waste statistics were identified and the results of the study emphasize the importance of reliable waste generation and composition data to underpin waste management policies.

Dahlen, Lisa [Division of Waste Science and Technology, Lulea University of Technology, SE, 971 87 Lulea (Sweden)], E-mail: lisa.dahlen@ltu.se; Aberg, Helena [Department of Food, Health and Environment, University of Gothenburg, P.O. Box 12204, SE, 402 42 Gothenburg (Sweden); Lagerkvist, Anders [Division of Waste Science and Technology, Lulea University of Technology, SE, 971 87 Lulea (Sweden); Berg, Per E.O. [HB Anttilator, Stagnellsgatan 3, SE, 652 23, Karlstad (Sweden)

2009-06-15T23:59:59.000Z

277

Muffled Price Signals: Household Water Demand Under Increasing-Block Prices  

E-Print Network (OSTI)

The distinction has been quite important in the electricity demand literature, in which long-run price elasticity and electricity pricing, and volume discounts in general. Under increasing blocks, the budget constraintMuffled Price Signals: Household Water Demand Under Increasing-Block Prices Sheila M. Cavanagh, W

Kammen, Daniel M.

278

A Joint Household Travel Distance Generation and Car Ownership Model  

E-Print Network (OSTI)

at a~ljustmentsof car ownership usage that representare from previous car ownership, train usage, and bus-tram-car usageare moreimportantthan the laggedeffects of public transport usage.

Golob, Thomas F.; Van Wissen , Leo

1989-01-01T23:59:59.000Z

279

A Joint Household Travel Distance Generation And Car Ownership Model  

E-Print Network (OSTI)

at a~ljustmentsof car ownership usage that representare from previous car ownership, train usage, and bus-tram-car usageare moreimportantthan the laggedeffects of public transport usage.

Golob, Thomas F.; Van Wissen, Leo

1989-01-01T23:59:59.000Z

280

Household energy use in urban Venezuela: Implications from surveys in Maracaibo, Valencia, Merida, and Barcelona-Puerto La Cruz  

Science Conference Proceedings (OSTI)

This report identifies the most important results of a comparative analysis of household commercial energy use in Venezuelan urban cities. The use of modern fuels is widespread among all cities. Cooking consumes the largest share of urban household energy use. The survey documents no use of biomass and a negligible use of kerosene for cooking. LPG, natural gas, and kerosene are the main fuels available. LPG is the fuel choice of low-income households in all cities except Maracaibo, where 40% of all households use natural gas. Electricity consumption in Venezuela`s urban households is remarkably high compared with the levels used in households in comparable Latin American countries and in households of industrialized nations which confront harsher climatic conditions and, therefore, use electricity for water and space heating. The penetration of appliances in Venezuela`s urban households is very high. The appliances available on the market are inefficient, and there are inefficient patterns of energy use among the population. Climate conditions and the urban built form all play important roles in determining the high level of energy consumption in Venezuelan urban households. It is important to acknowledge the opportunities for introducing energy efficiency and conservation in Venezuela`s residential sector, particularly given current economic and financial constraints, which may hamper the future provision of energy services.

Figueroa, M.J.; Sathaye, J.

1993-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "household electricity usage" 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

Alaska Village Electric Load Calculator  

DOE Green Energy (OSTI)

As part of designing a village electric power system, the present and future electric loads must be defined, including both seasonal and daily usage patterns. However, in many cases, detailed electric load information is not readily available. NREL developed the Alaska Village Electric Load Calculator to help estimate the electricity requirements in a village given basic information about the types of facilities located within the community. The purpose of this report is to explain how the load calculator was developed and to provide instructions on its use so that organizations can then use this model to calculate expected electrical energy usage.

Devine, M.; Baring-Gould, E. I.

2004-10-01T23:59:59.000Z

282

Usage analysis and the web of data  

Science Conference Proceedings (OSTI)

The workshop on Usage Analysis and the Web of Data (USEWOD2011) was the first workshop in the field to investigate combinations of usage data with semantics and the Web of Data. Questions the workshop aims to address are for example: How can semantics ...

Bettina Berendt; Laura Hollink; Vera Hollink; Markus Luczak-Rösch; Knud Möller; David Vallet

2011-05-01T23:59:59.000Z

283

Detecting and analyzing insecure component usage  

Science Conference Proceedings (OSTI)

Software is commonly built from reusable components that provide desired functionalities. Although component reuse significantly improves software productivity, insecure component usage can lead to security vulnerabilities in client applications. ... Keywords: differential testing, insecure component usage, testing and analysis of real-world software

Taeho Kwon; Zhendong Su

2012-11-01T23:59:59.000Z

284

2001 Consumption and Expenditures -- Electric Air-Conditioning ...  

U.S. Energy Information Administration (EIA)

CE3-1c. Electric Air-Conditioning Energy Consumption in U.S. Households by Climate Zone, 2001 : 2: CE3-2c. ...

285

Center for the Commercialization of Electric Technologies Smart...  

Open Energy Info (EERE)

and the use of integrated Smart Grid technologies, including household and community battery storage, smart meters and appliances, plug-in hybrid electric vehicles, and homes...

286

Residential Energy Usage Comparison: Findings  

Science Conference Proceedings (OSTI)

The load shapes of major residential electric and gas appliances were compared in an integrated load and market research project in southern California. The energy consumption data provide a benchmark for comparing the costs of alternative technologies; the market research data relate customer attitudes with appliance load shapes.

1991-08-19T23:59:59.000Z

287

Do Heat Pump Clothes Dryers Make Sense for the U.S. Market?  

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

American homes. The results show that HPCDs have positive economic benefits only for households with high clothes dryer usage or for households with high electricity prices and...

288

Regional patterns of U.S. household carbon emissions  

E-Print Network (OSTI)

2 (continued) in natural gas usage, with adjacent countiesgas is much more prevalent in the Midwest. Gasoline usage ?

Pizer, William; Sanchirico, James N.; Batz, Michael

2010-01-01T23:59:59.000Z

289

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities >Table 7a Glossary U.S. Residential Housing Primary Page Last Revised: July 2009

290

Home > Households, Buildings & Industry > Energy Efficiency ...  

U.S. Energy Information Administration (EIA)

Glossary Home > Households, Buildings & Industry > Energy Efficiency > Residential Buildings Energy Intensities > Table 4 Total Square Feet of U.S. Housing Units

291

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities > Table 5c Glossary U.S. Residential Housing Site Page Last Revised: July 2009

292

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities >Table 7b Glossary U.S. Residential Housing Primary Energy Intensity

293

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

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

294

Nationwide Survey on Household Energy Use  

U.S. Energy Information Administration (EIA)

4 ~ Apartment in house or building divided into 2, 3, or 4 apartments ... of your family (living in your household). Include income from all sources--before taxes

295

Alston S. Householder Fellowship | Careers | ORNL  

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

in Scientific Computing honors Dr. Alston S. Householder, founding Director of the Mathematics Division (now Computer Science and Mathematics Division) at the Oak Ridge National...

296

Household Vehicles Energy Consumption 1994 - PDF Tables  

U.S. Energy Information Administration (EIA)

Table 1 U.S. Number of Vehicles, Vehicle Miles, Motor Fuel Consumption and Expenditures, 1994 Table 2 U.S. per Household Vehicle Miles Traveled, Vehicle Fuel ...

297

homeoffice_household2001.pdf  

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

2a. Home Office Equipment by Year of Construction, 2a. Home Office Equipment by Year of Construction, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.4 1.1 1.1 1.2 1.2 1.0 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Households Using Office Equipment .......................... 96.2 14.9 16.7 17.0 12.2 13.0 22.4 4.4 Personal Computers 2 ................... 60.0 11.0 11.6 10.3 7.2 7.8 12.0 5.3 Number of Desktop PCs 1 .................................................. 45.1 8.0 9.0 7.7 5.3 6.1 9.1 5.8 2 or more .................................... 9.1 1.8 1.6 2.0 1.1 1.0 1.6 11.8 Number of Laptop PCs 1 ..................................................

298

homeoffice_household2001.pdf  

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

1a. Home Office Equipment by South Census Region, 1a. Home Office Equipment by South Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Households Using Office Equipment ......................................... 96.2 34.6 18.4 6.0 10.1 1.2 Personal Computers 1 ................................. 60.0 20.7 11.7 3.2 5.8 4.0 Number of Desktop PCs 1 ................................................................ 45.1 15.5 8.6 2.6 4.3 4.9 2 or more ................................................... 9.1 3.1 2.0 0.4 0.7 9.6 Number of Laptop PCs

299

homeoffice_household2001.pdf  

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

a. Home Office Equipment by Climate Zone, a. Home Office Equipment by Climate Zone, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.2 1.1 1.0 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 7.9 Households Using Office Equipment .......................... 96.2 8.4 26.2 21.1 19.0 21.5 7.8 Personal Computers 2 ................... 60.0 5.7 16.7 13.1 12.1 12.6 7.4 Number of Desktop PCs 1 .................................................. 45.1 4.2 12.8 9.6 8.8 9.6 7.8 2 or more .................................... 9.1 0.8 2.4 2.3 2.0 1.7 12.1 Number of Laptop PCs 1 ..................................................

300

Assumptions to the Annual Energy Outlook - Household Expenditures Module  

Gasoline and Diesel Fuel Update (EIA)

Household Expenditures Module Household Expenditures Module Assumption to the Annual Energy Outlook Household Expenditures Module Figure 5. United States Census Divisions. Having problems, call our National Energy Information Center at 202-586-8800 for help. The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and demographic characteristics, and consumption and expenditures for fuels for various end-uses. These data are combined with NEMS forecasts of household disposable income, fuel consumption, and fuel expenditures by end-use and household type. The HEM disaggregation algorithm uses these combined results to forecast household fuel consumption and expenditures by income quintile and Census Division (see

Note: This page contains sample records for the topic "household electricity usage" 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

General Guidance on Data Usage and Management  

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

General Guidance on Data Usage and Management General Guidance on Data Usage and Management Summary Data Usage Credit Data Management and Documentation: Introduction Our philosophy Data management Record measured values Zero versus missing value Metadata Data documentation Define variables Specify units Provide citations For additional information Summary Ensure long-term preservation of, and full and open access to, high-quality data sets Give proper credit to the researchers providing the data Provide thorough, yet simple, documentation: how the data were produced, what they mean Generate ASCII data and documentation files; they ensure readibility by virtually all users Define variable names and units Point to, or provide, important publications that further document the data Data usage CDIAC fully supports the July 1991 Policy Statements on Data Management for

302

ERP Usage in Practice: An Empirical Investigation  

Science Conference Proceedings (OSTI)

This study presents the results of an exploratory study of Fortune 1000 firms and their enterprise resource planning ERP usage, as well as benefits and changes they have realized from ERP. The study empirically examines ERP in these organizations to ...

Mary C. Jones; Randall Young

2006-01-01T23:59:59.000Z

303

Material impacts on operational energy usage  

E-Print Network (OSTI)

Decisions regarding materials and construction of a building are made all the time in the architectural process, but thought is not always given to how those choices may affect the buildings ultimate energy usage and the ...

Love, Andrea, S.M. Massachusetts Institute of Technology

2011-01-01T23:59:59.000Z

304

Microsoft Word - Epoxy Usage Form.docx  

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

Division Form Rev. 41111 Monthly Epoxy Usage Form (Weight in Grams) Date Initials CTD 101K Stycast Catalyst Epon Resin Epicure Part A Part B Part C 2850 24LV 815828 3140...

305

Building Energy Software Tools Directory: Energy Usage Forecasts  

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

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

306

CNST NanoFab Facility User Computer Security and Usage ...  

Science Conference Proceedings (OSTI)

Page 1. CNST NanoFab Facility User Computer Security and Usage Policy ... CNST NanoFab Facility User Computer Security and Usage Policy ...

2013-07-31T23:59:59.000Z

307

arXiv.org help - arXiv usage statistics  

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

by major subject areas through January 2013 Access and download statistics: Today's usage for arXiv.org (not including mirrors) Institutional Usage Statistics: 2009, 2010,...

308

spaceheat_household2001.pdf  

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

1a. Space Heating by South Census Region, 1a. Space Heating by South Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.9 1.2 1.4 1.3 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Heat Home .................................................... 106.0 38.8 20.2 6.8 11.8 NE Do Not Heat Home ....................................... 1.0 Q Q Q Q 20.1 No Heating Equipment ................................ 0.5 Q Q Q Q 39.8 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q Q 39.0 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0

309

spaceheat_household2001.pdf  

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

9a. Space Heating by Northeast Census Region, 9a. Space Heating by Northeast Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 20.3 14.8 5.4 NE Heat Home .................................................... 106.0 20.1 14.7 5.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.9 No Heating Equipment ................................ 0.5 Q Q Q 39.5 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q 38.7 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 20.1 14.7 5.4 NE Natural Gas .................................................

310

spaceheat_household2001.pdf  

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

0a. Space Heating by Midwest Census Region, 0a. Space Heating by Midwest Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Heat Home .................................................... 106.0 24.5 17.1 7.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.8 No Heating Equipment ................................ 0.5 Q Q Q 39.2 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q 38.4 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 24.5 17.1 7.4 NE Natural Gas

311

spaceheat_household2001.pdf  

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

2a. Space Heating by West Census Region, 2a. Space Heating by West Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.6 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Heat Home .................................................... 106.0 22.6 6.7 15.9 NE Do Not Heat Home ....................................... 1.0 0.7 Q 0.7 10.6 No Heating Equipment ................................ 0.5 0.4 Q 0.4 18.1 Have Equipment But Do Not Use It ............................................... 0.4 0.2 Q 0.2 27.5 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 22.6 6.7 15.9 NE Natural Gas .................................................

312

Factors influencing county level household fuelwood use  

Science Conference Proceedings (OSTI)

This study explains household fuelwood consumption behavior at the county level by linking it to economic and demographic conditions in counties. Using this link, counties are identified where potential fuelwood use problems and benefits are greatest. A probit equation estimates household probability of wood use (percent woodburners in a county heating degree days, household income, nonwood fuel price, fuelwood price, percent forest land, population density, and fraction of households using various types of heating equipment. A linear-in-parameters equation estimates average wood consumed by a woodburner based on county heating degree days, household income, percent forest land, and price of nonwood fuel divided by fuelwood price. Parameters are estimated using fuelwood use data for individual households from a 1908-81 nationwide survey. The probit equation predicts percentage of wood burns well over a wide range of county conditions. The wood consumption equation overpredicts for counties with high income and high population density (over 6000 persons per square mile). The model shows average woodburning per household over all households decreases with increasing population density, and the influence of county economic characteristics varies with density.

Skog, K.E.

1986-01-01T23:59:59.000Z

313

Characterization of household waste in Greenland  

Science Conference Proceedings (OSTI)

The composition of household waste in Greenland was investigated for the first time. About 2 tonnes of household waste was sampled as every 7th bag collected during 1 week along the scheduled collection routes in Sisimiut, the second largest town in Greenland with about 5400 inhabitants. The collection bags were sorted manually into 10 material fractions. The household waste composition consisted primarily of biowaste (43%) and the combustible fraction (30%), including anything combustible that did not belong to other clean fractions as paper, cardboard and plastic. Paper (8%) (dominated by magazine type paper) and glass (7%) were other important material fractions of the household waste. The remaining approximately 10% constituted of steel (1.5%), aluminum (0.5%), plastic (2.4%), wood (1.0%), non-combustible waste (1.8%) and household hazardous waste (1.2%). The high content of biowaste and the low content of paper make Greenlandic waste much different from Danish household waste. The moisture content, calorific value and chemical composition (55 elements, of which 22 were below detection limits) were determined for each material fraction. These characteristics were similar to what has been found for material fractions in Danish household waste. The chemical composition and the calorific value of the plastic fraction revealed that this fraction was not clean but contained a lot of biowaste. The established waste composition is useful in assessing alternative waste management schemes for household waste in Greenland.

Eisted, Rasmus, E-mail: raei@env.dtu.dk [Department of Environmental Engineering, Technical University of Denmark, Kongens Lyngby (Denmark); Christensen, Thomas H. [Department of Environmental Engineering, Technical University of Denmark, Kongens Lyngby (Denmark)

2011-07-15T23:59:59.000Z

314

The Power to Change: Sustainable Electricity Usage in  

E-Print Network (OSTI)

) Light Bulb Exchange program: replaces inefficient incandescent bulbs with integrated compact fluorescent Lighting Project - The UHC (University Housing Council) and the CCSC (Columbia College Student Council bulbs Watt and Woodbridge residence halls Bulbs - 15X longer, save $38,000 in energy cost and 446

Colorado at Boulder, University of

315

RECS Electricity Usage Form_v2 (25418 - Activated, Traditional...  

Gasoline and Diesel Fuel Update (EIA)

Period Enter the End Date for each billing period MMDDYY Enter the Amount used in kWh XXXX kWh were: AActual EEstimated RRead by Customer (select one) A E R 1 2 3 4 5 6 7...

316

Sizing Wind/Photovoltaic Hybrids for Households in Inner Mongolia  

DOE Green Energy (OSTI)

Approximately 140,000 wind turbines currently provide electricity to about one-third of the non-grid-connected households in Inner Mongolia. However, these households often suffer from a lack of power during the low-wind summer months. This report describes an analysis of hybrid wind/photovoltaic (PV) systems for such households. The sizing of the major components is based on a subjective trade-off between the cost of the system and the percent unmet load, as determined by the Hybrid 2 software in conjunction with a simplified time-series model. Actual resource data (wind speed and solar radiation) from the region are processed so as to best represent the scenarios of interest. Small wind turbines of both Chinese and U.S. manufacture are considered in the designs. The results indicate that combinations of wind and PV are more cost-effective than either one alone, and that the relative amount of PV in the design increases as the acceptable unmet load decreases and as the average wind sp eed decreases.

Barley, C. D.; Lew, D. J.; Flowers, L. T.

1997-06-01T23:59:59.000Z

317

The federal energy policy: An example of its potential impact on energy consumption and expenditures in minority and poor households  

SciTech Connect

This report presents an analysis of the relative impacts of the National Energy Strategy on majority and minority households and on nonpoor and poor households. (Minority households are defined as those headed by black or Hispanic persons; poor households are defined as those having combined household income less than or equal to 125% of the Office of Management and Budget`s poverty-income threshold.) Energy consumption and expenditures, and projected energy expenditures as a share of income, for the period 1987 to 2009 are reported. Projected consumptions of electricity and nonelectric energy over this period are also reported for each group. An analysis of how these projected values are affected under different housing growth scenarios is performed. The analysis in this report presents a preliminary set of projections generated under a set of simplifying assumptions. Future analysis will rigorously assess the sensitivity of the projected values to various changes in a number of these assumptions.

Poyer, D.A.

1991-09-01T23:59:59.000Z

318

Design of Electric Drive Vehicle Batteries for Long Life and...  

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

Kandler Smith, NREL EDV Battery Robust Design - 1 Design of Electric Drive Vehicle Batteries for Long Life and Low Cost Robustness to Geographic and Consumer-Usage Variation...

319

ON THE USAGE OF ANTENNAS IN MIMO AND MISO INTERFERENCE CHANNELS Mariam Kaynia  

E-Print Network (OSTI)

ON THE USAGE OF ANTENNAS IN MIMO AND MISO INTERFERENCE CHANNELS Mariam Kaynia , Andrea J. Goldsmith. of Science and Technology Dept. of Electrical Engineering, Stanford University, Stanford Mobile and small), we derive upper and lower bounds to both our per- formance metrics. Moreover, the particular

Gesbert, David

320

UDP: Usage-based Dynamic Pricing with Privacy Preservation for Smart Grid  

E-Print Network (OSTI)

UDP: Usage-based Dynamic Pricing with Privacy Preservation for Smart Grid Xiaohui Liang, Student for smart grid in a community environment, which enables the electricity price to correspond-preserving manner. Index Terms--Smart grid; dynamic price; privacy preserva- tion; community-specific I

Shen, Xuemin "Sherman"

Note: This page contains sample records for the topic "household electricity usage" 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

Modeling patterns of hot water use in households  

E-Print Network (OSTI)

7 No Dishwashers . . . . . . . .to households without dishwashers. no_cw is only applied towasher; the absence of a dishwasher; a household consisting

Lutz, James D.; Liu, Xiaomin; McMahon, James E.; Dunham, Camilla; Shown, Leslie J.; McCure, Quandra T.

1996-01-01T23:59:59.000Z

322

Probit Model Estimation Revisited: Trinomial Models of Household Car Ownership  

E-Print Network (OSTI)

Household Ownership of Car Davidon, W. C. (1959) VariableStudy Report 9: Models of Car Ownership and License Holding.Trinomial Models of Household Car Ownership. Transportation

Bunch, David S.; Kitamura, Ryuichi

1991-01-01T23:59:59.000Z

323

Annual fuel usage charts for oil-fired boilers. [Building space heating and hot water supplies  

SciTech Connect

On the basis of laboratory-determined boiler efficiency data, one may calculate the annual fuel usage (AFU) for any oil-fired boiler, serving a structure of a given design heat load, for any specified hourly weather pattern. Further, where data are available regarding the energy recapture rates of the strucutre due to direct gain solar energy (windows), lighting, cooking, electrical appliances, metabolic processes, etc., the annual fuel usage savings due to such (re) capture are straightforwardly determinable. Employing the Brookhaven National Laboratory annual fuel usage formulation, along with efficiency data determined in the BNL Boiler Laboratory, computer-drawn annual fuel usage charts can be generated for any selected boiler for a wide range of operating conditions. For two selected boilers operating in any one of the hour-by-hour weather patterns which characterize each of six cities over a wide range of firing rates, domestic hot water consumption rates, design heat loads, and energy (re) capture rates, annual fuel usages are determined and graphically presented. Figures 1 to 98, inclusive, relate to installations for which energy recapture rates are taken to be zero. Figures 97 to 130, inclusive, apply to a range of cases for which energy recapture rates are nonzero and determinable. In all cases, simple, direct and reliable annual fuel usage values can be determined by use of charts and methods such as those illustrated.

Berlad, A.L.; Yeh, Y.J.; Salzano, F.J.; Hoppe, R.J.; Batey, J.

1978-07-01T23:59:59.000Z

324

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

SciTech Connect

The term ?household carbon footprint? refers to the total annual carbon emissions associated with household consumption of energy, goods, and services. In this project, Lawrence Berkeley National Laboratory developed a carbon footprint modeling framework that characterizes the key underlying technologies and processes that contribute to household carbon footprints in California and the United States. The approach breaks down the carbon footprint by 35 different household fuel end uses and 32 different supply chain fuel end uses. This level of end use detail allows energy and policy analysts to better understand the underlying technologies and processes contributing to the carbon footprint of California households. The modeling framework was applied to estimate the annual home energy and supply chain carbon footprints of a prototypical California household. A preliminary assessment of parameter uncertainty associated with key model input data was also conducted. To illustrate the policy-relevance of this modeling framework, a case study was conducted that analyzed the achievable carbon footprint reductions associated with the adoption of energy efficient household and supply chain technologies.

Kramer, Klaas Jan; Homan, Greg; Brown, Rich; Worrell, Ernst; Masanet, Eric

2009-04-15T23:59:59.000Z

325

Did Household Consumption Become More Volatile?  

E-Print Network (OSTI)

I show that after accounting for predictable variation arising from movements in real interest rates, preferences, income shocks, liquidity constraints and measurement errors, volatility of household consumption in the US increased between 1970 and 2004. For households headed by nonwhite and/or poorly educated individuals, this rise was significantly larger. This stands in sharp contrast with the dramatic fall in instability of the aggregate U.S. economy over the same period. Thus, while aggregate shocks affecting households fell over time, idiosyncratic shocks increased. This finding may lead to significant welfare implications.

Olga Gorbachev

2009-01-01T23:59:59.000Z

326

appl_household2001.pdf  

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

a. Appliances by Climate Zone, a. Appliances by Climate Zone, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.1 Total .................................................. 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Kitchen Appliances Cooking Appliances Oven .............................................. 101.7 9.1 27.9 23.1 19.4 22.2 7.8 1 ................................................... 95.2 8.7 26.0 21.6 17.7 21.2 7.9 2 or More ..................................... 6.5 0.4 1.9 1.5 1.7 1.0 14.7 Most Used Oven ........................... 101.7 9.1 27.9 23.1 19.4 22.2

327

spaceheat_household2001.pdf  

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

8a. Space Heating by Urban/Rural Location, 8a. Space Heating by Urban/Rural Location, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.6 0.9 1.3 1.3 1.2 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.3 Heat Home .................................................... 106.0 49.1 18.0 21.2 17.8 4.3 Do Not Heat Home ....................................... 1.0 0.7 0.1 0.1 0.1 25.8 No Heating Equipment ................................ 0.5 0.4 0.1 Q 0.1 33.2 Have Equipment But Do Not Use It ............................................... 0.4 0.3 Q Q Q 30.2 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 49.1 18.0 21.2 17.8 4.3 Natural Gas

328

spaceheat_household2001.pdf  

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

2a. Space Heating by Year of Construction, 2a. Space Heating by Year of Construction, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.5 1.5 1.1 1.1 1.1 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.3 Heat Home ..................................... 106.0 15.4 18.2 18.6 13.6 13.9 26.4 4.3 Do Not Heat Home ........................ 1.0 Q Q Q 0.2 0.3 Q 23.2 No Heating Equipment .................. 0.5 Q Q Q 0.2 Q Q 30.3 Have Equipment But Do Not Use It ................................ 0.4 Q Q Q Q Q Q 37.8 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 106.0 15.4 18.2 18.6 13.6 13.9 26.4 4.3 Natural Gas ...................................

329

spaceheat_household2001.pdf  

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

4a. Space Heating by Type of Housing Unit, 4a. Space Heating by Type of Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.7 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.4 Heat Home ..................................... 106.0 73.4 9.4 16.4 6.8 4.5 Do Not Heat Home ........................ 1.0 0.3 Q 0.6 Q 19.0 No Heating Equipment .................. 0.5 0.2 Q 0.3 Q 24.2 Have Equipment But Do Not Use It ................................ 0.4 Q Q 0.3 Q 28.1 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 106.0 73.4 9.4 16.4 6.8 4.5 Natural Gas ...................................

330

spaceheat_household2001.pdf  

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

5a. Space Heating by Type of Owner-Occupied Housing Unit, 5a. Space Heating by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.4 1.9 3.0 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Heat Home ..................................... 72.4 63.0 2.0 1.7 5.7 6.7 Do Not Heat Home ........................ 0.4 0.2 Q Q Q 46.2 No Heating Equipment .................. 0.3 0.2 Q Q Q 39.0 Have Equipment But Do Not Use It ................................ Q Q Q Q Q NF Main Heating Fuel and Equipment (Have and Use Equipment) ............ 72.4 63.0 2.0 1.7 5.7 6.7 Natural Gas

331

spaceheat_household2001.pdf  

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

6a. Space Heating by Type of Rented Housing Unit, 6a. Space Heating by Type of Rented Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total ............................................... 34.3 10.5 7.4 15.2 1.1 6.9 Heat Home ..................................... 33.7 10.4 7.4 14.8 1.1 6.9 Do Not Heat Home ........................ 0.6 Q Q 0.5 Q 21.4 No Heating Equipment .................. 0.2 Q Q Q Q 84.5 Have Equipment But Do Not Use It ................................ 0.4 Q Q 0.3 Q 36.4 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 33.7 10.4 7.4 14.8 1.1 6.9 Natural Gas ...................................

332

How Usage is Charged at NERSC  

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

usage usage is charged How usage is charged MPP Charging (Computational Systems) When a job runs on a NERSC MPP system, such as Hopper, charges accrue against one of the user's repository allocations. The unit of accounting for these charges is the "MPP Hour". A parallel job is charged for exclusive use of each multi-core node allocated to the job. The MPP charge for such a job is calculated as the product of: the job's elapsed wall-clock time in hours, the number of nodes allocated to the job (regardless of the number actually used), the number of cores available on each allocated node, a machine charge factor (MCF) based on typical performance of the machine relative to Hopper (MCF=1.0), and a queue charge factor (QCF). Queue priority scheduling gives users

333

Automobile usage patterns. Highlight report. Volume XIV  

SciTech Connect

A report is given as part of a series of studies dealing with general public behavior and attitudes towards energy conservation. Specifically, this study concentrates on automobile usage patterns. The study is based on 1,007 telephone interviews and includes topics such as car usage affected by lifestyle, car usage patterns, planned trips as compared with routine or spontaneous trips, times per week trip is usually made, analysis of trips, the extent to which shopping trips are done by phone instead of by car, willingness to cut out trips, factors deterring car use, and a summary which concludes that the primary way that people could cut down automobile use without eliminating leisure time use would be in more careful planning of trip for shopping and errands. Another important finding in this study is lack of sensitivity to gasoline prices. (GRA)

Rappeport, M.; Labaw, P.

1975-09-01T23:59:59.000Z

334

CloudMonitor: Profiling Power Usage  

E-Print Network (OSTI)

In Cloud Computing platforms the addition of hardware monitoring devices to gather power usage data can be impractical or uneconomical due to the large number of machines to be metered. CloudMonitor, a monitoring tool that can generate power models for software-based power estimation, can provide insights to the energy costs of deployments without additional hardware. Accurate power usage data leads to the possibility of Cloud providers creating a separate tariff for power and therefore incentivizing software developers to create energy-efficient applications.

Smith, James William; Ward, Jonathan Stuart; Sommerville, Ian

2012-01-01T23:59:59.000Z

335

Reducing the Energy Usage of Office Applications  

E-Print Network (OSTI)

In this paper, we demonstrate how component-based middleware can reduce the energy usage of closed-source applications. We rst describe how the Puppeteer system exploits well-dened interfaces exported by applications to modify their behavior. We then present a detailed study of the energy usage of Microsoft's PowerPoint application and show that adaptive policies can reduce energy expenditure by 49% in some instances. In addition, we use the results of the study to provide general advice to developers of applications and middleware that will enable them to create more energy-ecient software. 1

Jason Flinn; Eyal De Lara; M. Satyanarayanan; Dan S. Wallach; Willy Zwaenepoel; Willy

2001-01-01T23:59:59.000Z

336

Household gasoline demand in the United States  

E-Print Network (OSTI)

Continuing rapid growth in U.S. gasoline consumption threatens to exacerbate environmental and congestion problems. We use flexible semiparametric and nonparametric methods to guide analysis of household gasoline consumption, ...

Schmalensee, Richard

1995-01-01T23:59:59.000Z

337

Do Disaster Expectations Explain Household Portfolios?  

E-Print Network (OSTI)

use the American Consumer Expenditure Survey (CEX) for consumption ex- penditure information. The data covers the period between 1983 and 2004. The expenditure information is recorded quarterly with approximately 5000 households in each wave. Every...

Alan, Sule

338

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

339

appl_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

Units ... 11.9 8.7 1.5 1.5 0.2 14.9 Heaters (other) Hot Tub or Spa (heaters) ... 4.4 1.6 0.6 1.2 1.0 14.8 Electric...

340

appl_household2001.pdf  

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

or More Units ... 11.9 2.3 2.0 0.4 19.8 Heaters (other) Hot Tub or Spa (heaters) ... 4.4 0.6 0.4 0.2 19.5 Electric...

Note: This page contains sample records for the topic "household electricity usage" 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

appl_household2001.pdf  

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

More Units ... 11.9 1.9 0.9 Q 0.8 24.6 Heaters (other) Hot Tub or Spa (heaters) ... 4.4 1.5 0.6 0.2 0.8 12.2 Electric...

342

appl_household2001.pdf  

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

Units ... 11.9 2.6 1.9 0.8 0.2 15.2 Heaters (other) Hot Tub or Spa (heaters) ... 4.4 0.2 0.9 0.6 Q 14.6 Electric...

343

Identifying diverse usage behaviors of smartphone apps  

Science Conference Proceedings (OSTI)

Smartphone users are increasingly shifting to using apps as "gateways" to Internet services rather than traditional web browsers. App marketplaces for iOS, Android, and Windows Phone platforms have made it attractive for developers to deploy apps and ... Keywords: app usage behavior, smartphone apps

Qiang Xu; Jeffrey Erman; Alexandre Gerber; Zhuoqing Mao; Jeffrey Pang; Shobha Venkataraman

2011-11-01T23:59:59.000Z

344

Two perspectives on household electricity use - Today in Energy ...  

U.S. Energy Information Administration (EIA)

... power plants, fuel use, stocks ... Unlike natural gas consumption in the ... and an ever-growing number of home entertainment and rechargeable devices.

345

Demand for Electric Vehicles in Hybrid Households: An Exploratory Analysis  

E-Print Network (OSTI)

heating coffee or cooking any of hundreds of products which have been specifically repackaged for microwave ovens.

Kurani, Kenneth S.; Turrentine, Tom; Sperling, Daniel

1994-01-01T23:59:59.000Z

346

Two perspectives on household electricity use - Today in Energy ...  

U.S. Energy Information Administration (EIA)

Tools; Glossary › All Reports ... weather; capacity; gasoline; exports; nuclear; forecast; View All Tags ...

347

Electricity over IP  

Science Conference Proceedings (OSTI)

Mostly Pointless Lamp Switching (MPLampS) is an architecture for carrying electricity over IP (with an MPLS control plane). According to our marketing department, MPLampS has the potential to dramatically lower the price, ease the distribution and usage, ...

B. Rajagopalan

2002-04-01T23:59:59.000Z

348

Electricity 101 | Department of Energy  

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

Resources » Electricity 101 Resources » Electricity 101 Electricity 101 FREQUENTLY ASKED QUESTIONS: Why do other countries use different shaped plugs? Why do outlets have three holes? Why do we have AC electricity? Can we harness lightning as an energy source? Can we have wireless transmission of electricity? SYSTEM: What is electricity? Where does electricity come from? What is the "grid"? How much electricity does a typical household use? How did the electric system evolve? What does the future look like? PEOPLE: Who owns the electric system? Who runs the grid? Who uses electricity? Where can I find out more about potential careers? How can I improve my energy use? POLICY: How is electricity regulated? Where can I find out about State incentives for renewables? What is a national corridor?

349

Trends in Building Energy Usage in Texas State Agencies  

E-Print Network (OSTI)

In late 1983, a cost containment program was initiated out of the governor's office directed at the major state agencies. The Energy Management Group at Texas A&M University provided technical expertise in obtaining agency energy usage and cost figures for the fiscal years 1981 to 1983. While there is considerable diversity from agency to agency, the trend is toward dramatically higher energy cost per square foot for virtually all agencies. This alarming trend can be partially explained by rising unit costs for gas and electricity and a lack of incentives for conservation efforts due to the method of utility budget allocations. A building standard signed into law in 1976 could have reduced energy consumption, but was never enforced. Beginning in fiscal year 1986, universities will be allowed to comingle utility money with capital operating money so that conservation can really pay off for them.

Murphy, W. E.; Turner, W. D.; O'Neal, D. L.; Seshan, S.

1985-01-01T23:59:59.000Z

350

Household and environmental characteristics related to household energy-consumption change: A human ecological approach  

Science Conference Proceedings (OSTI)

This study focused on the family household as an organism and on its interaction with the three environments of the human ecosystem (natural, behavioral, and constructed) as these influence energy consumption and energy-consumption change. A secondary statistical analysis of data from the US Department of Energy Residential Energy Consumption Surveys (RECS) was completed. The 1980 and 1983 RECS were used as the data base. Longitudinal data, including household, environmental, and energy-consumption measures, were available for over 800 households. The households were selected from a national sample of owner-occupied housing units surveyed in both years. Results showed a significant( p = household, cooling degree days, heating degree days, year the housing unit was built, and number of stories in the housing unit.

Guerin, D.A.

1988-01-01T23:59:59.000Z

351

Energy usage of rotating biological contractor facilities  

SciTech Connect

A recent US Environmental Protection Agency field study investigated the energy requirements for rotating biological contactor (RBC) units. The energy measurements for mechanically driven units varied considerably, but the overall average of 2.03 kW/shaft was very close to current manufacturer estimates. The power factor of most of the mechanically driven units was very low, and most installations could benefit from power factor correction. The energy requirements of air driven units also were highly variable and must be evaluated on an individual plant basis. The results of this study provide factual data on energy usage of RBC units, as well as a basis for developing design and operational considerations to reduce energy usage and maximize operational flexibility and plant performance. 9 references, 7 tables.

Gilbert, W.G.; Wheeler, J.F.; MacGregor, A.

1986-01-01T23:59:59.000Z

352

Green Button Helps More Consumers Click with Their Energy Usage...  

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

Helps More Consumers Click with Their Energy Usage Data Green Button Helps More Consumers Click with Their Energy Usage Data September 12, 2013 - 2:41pm Addthis At the White House...

353

Soy Protein ProductsChapter 7 Regulations Regarding Usage  

Science Conference Proceedings (OSTI)

Soy Protein Products Chapter 7 Regulations Regarding Usage Health Nutrition Biochemistry eChapters Health - Nutrition - Biochemistry AOCS Press Downloadable pdf of Chapter 7 Regulations Regarding Usage from the

354

Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle  

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

1: January 8, 1: January 8, 2007 Household Vehicle Trips to someone by E-mail Share Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Facebook Tweet about Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Twitter Bookmark Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Google Bookmark Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Delicious Rank Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Digg Find More places to share Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on AddThis.com... Fact #451: January 8, 2007 Household Vehicle Trips In a day, the average household traveled 32.7 miles in 2001 (the latest

355

Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle  

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

2: October 3, 2: October 3, 2005 Household Vehicle Ownership to someone by E-mail Share Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Facebook Tweet about Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Twitter Bookmark Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Google Bookmark Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Delicious Rank Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Digg Find More places to share Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on AddThis.com... Fact #392: October 3, 2005 Household Vehicle Ownership Household vehicle ownership has changed significantly over the last 40

356

Energy Usage Data Standard for US Smart Grid Passes Key ...  

Science Conference Proceedings (OSTI)

Energy Usage Data Standard for US Smart Grid Passes Key Advisory Panel Vote. From NIST Tech Beat: March 1, 2011. ...

2011-03-01T23:59:59.000Z

357

Rethinking Real-Time Electricity Pricing  

E-Print Network (OSTI)

Most US consumers are charged a near-constant retail price for electricity, despite substantial hourly variation in the wholesale market price. This paper evaluates the …rst program to expose residential consumers to hourly real-time pricing (RTP). I …nd that enrolled households are statistically signi…cantly price elastic and that consumers responded by conserving energy during peak hours, but remarkably did not increase average consumption during o¤-peak times. The program increased consumer surplus by $10 per household per year. While this is only one to two percent of electricity costs, it illustrates a potential additional bene…t from investment in retail Smart Grid applications, including the advanced electricity meters required to observe a household’s hourly consumption.

Hunt Allcott; Bill Hogan; Erich Muehlegger; Larry Katz; Erin Mansur; Sendhil Mullainathan; Paul Niehaus; Chris Nosko; Ariel Pakes; Dave Rapson; Rob Stavins; Frank Wolak

2010-01-01T23:59:59.000Z

358

Miscellaneous electricity use in U.S. homes  

SciTech Connect

Historically, residential energy and carbon saving efforts have targeted conventional end uses such as water heating, lighting and refrigeration. The emergence of new household appliances has transformed energy use from a few large and easily identifiable end uses into a broad array of ''miscellaneous'' energy services. This group of so called miscellaneous appliances has been a major contributor to growth in electricity demand in the past two decades. We use industry shipment data, lifetimes, and wattage and usage estimates of over 90 individual products to construct a bottom-up end use model (1976-2010). The model is then used to analyze historical and forecasted growth trends, and to identify the largest individual products within the miscellaneous end use. We also use the end use model to identify and analyze policy priorities. Our forecast projects that over the period 1996 to 2010, miscellaneous consumption will increase 115 TWh, accounting for over 90 percent of future residential electricity growth. A large portion of this growth will be due to halogen torchiere lamps and consumer electronics, making these two components of miscellaneous electricity a particularly fertile area for efficiency programs. Approximately 20 percent (40 TWh) of residential miscellaneous electricity is ''leaking electricity'' or energy consumed by appliances when they are not performing their principal function. If the standby power of all appliances with a standby mode is reduced to one watt, the potential energy savings equal 21 TWh/yr, saving roughly $1-2 billion annually.

Sanchez, Marla C.; Koomey, Jonathan G.; Moezzi, Mithra M.; Meier, Alan; Huber, Wolfgang

1999-09-30T23:59:59.000Z

359

UK Electricity Consumption and Number of Meters at MLSOA level (2005 -  

Open Energy Info (EERE)

5 - 5 - 2007) Dataset Summary Description The UK Department of Energy and Climate Change (DECC) releases annual statistics on domestic and industrial/commercial electricity and gas consumption (and number of meters) at the Middle Layer Super Output Authority (MLSOA) and Intermediate Geography Zone (IGZ) level (there are over 950 of these subregions throughout England, Scotland and Wales). Both MLSOAs (England and Wales) and IGZs (Scotland) include a minimum of approximately 2,000 households. The domestic electricity consumption data data is split by ordinary electricity and economy7 electricity usage. These data are classified as UK National Statistics. Note about spreadsheets: separate tabs exist for each local authority (LA), but the tabs are hidden. To view data, simply 'unhide' the appropriate tab(s). You do not need to "enable macros" to view the data. Related socio-economic data for MLSOA and IGZ levels can be accessed: http://decc.gov.uk/assets/decc/Statistics/regional/mlsoa2008/181-mlsoa-i...

360

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

Note: This page contains sample records for the topic "household electricity usage" 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 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

362

Affording Gas and Electricity: Self Disconnection and  

E-Print Network (OSTI)

electricity, but this seems to be because gas prepayers have lower average income than electricity prepayersAffording Gas and Electricity: Self Disconnection and Rationing by Prepayment and Low Income Credit interview schedule................................... liv #12;2 Fuel Usage and Consumption Patterns of Low

Feigon, Brooke

363

Load Component Database of Household Appliances and Small Office Equipment  

Science Conference Proceedings (OSTI)

This paper discusses the development of a load component database for household appliances and office equipment. To develop more accurate load models at both transmission and distribution level, a better understanding on the individual behaviors of home appliances and office equipment under power system voltage and frequency variations becomes more and more critical. Bonneville Power Administration (BPA) has begun a series of voltage and frequency tests against home appliances and office equipments since 2005. Since 2006, Researchers at Pacific Northwest National Laboratory has collaborated with BPA personnel and developed a load component database based on these appliance testing results to facilitate the load model validation work for the Western Electricity Coordinating Council (WECC). In this paper, the testing procedure and testing results are first presented. The load model parameters are then derived and grouped. Recommendations are given for aggregating the individual appliance models to feeder level, the models of which are used for distribution and transmission level studies.

Lu, Ning; Xie, YuLong; Huang, Zhenyu; Puyleart, Francis; Yang, Steve

2008-07-24T23:59:59.000Z

364

Model documentation: household model of energy  

Science Conference Proceedings (OSTI)

The Household Model of Energy is an econometric model, meaning that energy use is determined quantitatively with the use of economic variables such as fuel prices and income. HOME is also primarily a structural model, meaning that energy use is determined as the result of interactions of intermediate components such as the number of households, the end use fuel shares and the energy use per household. HOME forecasts energy consumption in all occupied residential structures (households) in the United States on an annual basis through 1990. The forecasts are made based upon a number of initial conditions in 1980, various estimated elasticities, various parameters and assumptions, and a set of forecasted fuel prices and income. In addition to the structural detail, HOME operates on a more disaggregated level. This includes four end-use services (space heating, water heating, air conditioning, and others), up to seven fuel/technology types (dependent upon the end use service), two housing types, four structure vintages, and four Census regions. When the model is run as a module in IFFS, a sharing scheme further disaggregates the model to 10 Federal regions.

Holte, J.A.

1984-02-01T23:59:59.000Z

365

Controlling electrical costs with energy management  

SciTech Connect

Energy Management Systems have been proven to be extremely effective in reducing electrical energy costs. This particular system is also capable of monitoring natural gas usage and even regulating that usage with the control of valves. Controlling electrical energy usage must be a cooperative effort between the plant where the system is to be installed and the manufacturer of the Energy Management Controller. The latter can be assisted by being advised of which loads are able to be shed and how shedding those loads affect production.

Collins, W.M.

1984-07-01T23:59:59.000Z

366

Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle  

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

3: January 22, 3: January 22, 2007 Household Vehicle Ownership to someone by E-mail Share Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Facebook Tweet about Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Twitter Bookmark Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Google Bookmark Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Delicious Rank Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Digg Find More places to share Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on AddThis.com... Fact #453: January 22, 2007 Household Vehicle Ownership

367

Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle  

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

5: February 5, 5: February 5, 2007 Household Vehicle Miles to someone by E-mail Share Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Facebook Tweet about Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Twitter Bookmark Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Google Bookmark Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Delicious Rank Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Digg Find More places to share Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on AddThis.com... Fact #455: February 5, 2007 Household Vehicle Miles The graphs below show the average vehicle miles of travel (VMT) - daily

368

Competition Helps Kids Learn About Energy and Save Their Households...  

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

Competition Helps Kids Learn About Energy and Save Their Households Some Money Competition Helps Kids Learn About Energy and Save Their Households Some Money May 21, 2013 - 2:40pm...

369

Vehicle Technologies Office: Fact #259: March 17, 2003 Household...  

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

9: March 17, 2003 Household Travel by Gender to someone by E-mail Share Vehicle Technologies Office: Fact 259: March 17, 2003 Household Travel by Gender on Facebook Tweet about...

370

Essays on household decision making in developing countries  

E-Print Network (OSTI)

This dissertation contains three essays on household decision making in the areas of education and health in developing countries. The first chapter explores intra-household decision making in the context of conditional ...

Berry, James W. (James Wesley)

2009-01-01T23:59:59.000Z

371

Development of the Household Sample for Furnace and Boiler Life...  

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

households in the country. The data sample provides the household energy consumption and energy price inputs to the life-cycle cost analysis segment of the furnace and boiler...

372

ANALYSIS OF CEE HOUSEHOLD SURVEY NATIONAL AWARENESS OF ENERGY STAR  

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

ANALYSIS OF CEE HOUSEHOLD SURVEY ANALYSIS OF CEE HOUSEHOLD SURVEY NATIONAL AWARENESS OF ENERGY STAR ® FOR 2012 TABLE OF CONTENTS Acknowledgements .................................................................................. ii Executive Summary ............................................................................ ES-1 Introduction ............................................................................................... 1 Methodology Overview ............................................................................. 2 Key Findings ............................................................................................. 5 Recognition .................................................................................................................. 5 Understanding ........................................................................................................... 12

373

Simple strategies for minimization of cooling water usage in binary power plants  

SciTech Connect

The geothermal resources which could be used for the production of electrical power in the United States are located for the most part in the semi-arid western regions of the country. The availability of ground or surface water in the quantity or quality desired for a conventional wet'' heat rejections system represents a barrier to the development of these resources with the binary cycle technology. This paper investigates some simple strategies to minimize the cooling water usage of binary power plants. The cooling water usage is reduced by increasing the thermal efficiency of the plant. Three methods of accomplishing this are considered here: increasing the average source temperature, by increasing the geofluid outlet temperature; decreasing pinch points on the heat rejection heat exchangers, increasing their size; and using internal recuperation within the cycle. In addition to the impact on water usage, the impact on cost-of-electricity is determined. The paper shows that some of these strategies can reduce the cooling water requirements 20 to 30% over that for a plant similar to the Heber Binary Plant, with a net reduction in the cost-of-electricity of about 15%. 13 refs., 4 figs., 3 tabs.

Bliem, C.J.; Mines, G.L. (EG and G Idaho, Inc., Idaho Falls, ID (USA))

1989-01-01T23:59:59.000Z

374

Simple strategies for minimization of cooling water usage in binary power plants  

SciTech Connect

The geothermal resources which could be used for the production of electrical power in the United States are located for the most part in the semi-arid western regions of the country. The availability of ground or surface water in the quantity or quality desired for a conventional wet'' heat rejections system represents a barrier to the development of these resources with the binary cycle technology. This paper investigates some simple strategies to minimize the cooling water usage of binary power plants. The cooling water usage is reduced by increasing the thermal efficiency of the plant. Three methods of accomplishing this are considered here: increasing the average source temperature, by increasing the geofluid outlet temperature; decreasing pinch points on the heat rejection heat exchangers, increasing their size; and using internal recuperation within the cycle. In addition to the impact on water usage, the impact on cost-of-electricity is determined. The paper shows that some of these strategies can reduce the cooling water requirements 20 to 30% over that for a plant similar to the Heber Binary Plant, with a net reduction in the cost-of-electricity of about 15%. 13 refs., 4 figs., 3 tabs.

Bliem, C.J.; Mines, G.L. (EG and G Idaho, Inc., Idaho Falls, ID (USA))

1989-01-01T23:59:59.000Z

375

An assessment of worldwide supercomputer usage  

SciTech Connect

This report provides a comparative study of advanced supercomputing usage in Japan and the United States as of Spring 1994. It is based on the findings of a group of US scientists whose careers have centered on programming, evaluating, and designing high-performance supercomputers for over ten years. The report is a follow-on to an assessment of supercomputing technology in Europe and Japan that was published in 1993. Whereas the previous study focused on supercomputer manufacturing capabilities, the primary focus of the current work was to compare where and how supercomputers are used. Research for this report was conducted through both literature studies and field research in Japan.

Wasserman, H.J.; Simmons, M.L.; Hayes, A.H.

1995-01-01T23:59:59.000Z

376

Battery management system for Li-Ion batteries in hybrid electric vehicles.  

E-Print Network (OSTI)

??The Battery Management System (BMS) is the component responsible for the effcient and safe usage of a Hybrid Electric Vehicle (HEV) battery pack. Its main… (more)

Marangoni, Giacomo

2010-01-01T23:59:59.000Z

377

Optimal Planning and Operation of Smart Grids with Electric Vehicle Interconnection  

E-Print Network (OSTI)

or cooling loads via absorption cooling. The outputs of DER-for hot water usage and absorption cooling, thereby allowingutilization and absorption cooling reduces the electricity

Stadler, Michael

2012-01-01T23:59:59.000Z

378

Electrical engineering Electricity  

E-Print Network (OSTI)

generation Transmission Distribution · Electrical generators · Electric motors · High voltage engineering associated with the systems Electrical engineering · Electric power generation Transmission Distribution The electricity transported to load locations from a power station transmission subsystem The transmission system

Ã?nay, Devrim

379

Reducing Energy Usage in Extractive Distillation  

E-Print Network (OSTI)

Butadiene 1:3 is separated from other C4-hydrocarbons by extractive distillation in a sieve plate tower. Prior to the development work to be described, the pressure in the extraction tower was controlled at a fixed value. The tower pressure-boilup control loop did not behave satisfactorily in the presence of non-condensables which entered with the feed. The capacity of the flooded reflux drum condenser for the tower was limiting production during summer months. The tower pressure control loop was put on manual. The pressure was allowed to drop to its lowest attainable value for the existing conditions of boilup and condenser cooling capability. This manner of operation is known as floating pressure control. By taking advantage of the higher relative volatility at the lower tower pressure, energy usage was reduced and there was an increase in production capacity. The tower operation at a lower temperature reduced tower and reboiler fouling. Substantial savings have resulted from these improvements. The annual energy consumption has been reduced by 25% and maximum productive capacity is higher by 15%. The rate of tower and reboiler fouling has not been fully quantified but is greatly reduced. A more stable tower operation has also contributed to higher productivity and reduced energy usage. Venting of non-condensables does not affect tower stability and the operators have adapted well to the new control strategy.

Saxena, A. C.; Bhandari, V. A.

1985-05-01T23:59:59.000Z

380

Pricing Experiments for a Computer-Telephony-Service Usage Allocation Jimmy S. Shih, Randy H. Katz, Anthony D. Joseph  

E-Print Network (OSTI)

Pricing Experiments for a Computer-Telephony-Service Usage Allocation Jimmy S. Shih, Randy H. Katz, Anthony D. Joseph Department of Electrical Engineering and Computer Science University of California to entice users to talk less, talk at another time, or use a lower quality connection. With our token scheme

Joseph, Anthony D.

Note: This page contains sample records for the topic "household electricity usage" 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

Mitigating Carbon Emissions: the Potential of Improving Efficiency of Household Appliances in China  

E-Print Network (OSTI)

Efficiency of Household Appliances in China Jiang Lin8 Appliance Market inEfficiency of Household Appliances in China Executive

Lin, Jiang

2006-01-01T23:59:59.000Z

382

The comparative impact of the market penetration of energy-efficient measures: A sensitivity analysis of its impact on minority households  

SciTech Connect

A sensitivity study was made of the potential market penetration of residential energy efficiency as energy service ratio (ESR) improvements occurred in minority households, by age of house. The study followed a Minority Energy Assessment Model analysis of the National Energy Strategy projections of household energy consumption and prices, with majority, black, and Hispanic subgroup divisions. Electricity and total energy consumption and expenditure patterns were evaluated when the households` ESR improvement followed a logistic negative growth (i.e., market penetration) path. Earlier occurrence of ESR improvements meant greater discounted savings over the 22-year period.

Bozinovich, L.V.; Poyer, D.A.; Anderson, J.L.

1993-12-01T23:59:59.000Z

383

Building Energy Software Tools Directory: Energy Usage Forecasts  

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

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

384

Cleaning optimization for reduced chemical usage  

SciTech Connect

The use of dilute SC-1 (NH40H:H202:H20) chemistry cleaning processes for particle removal from silicon surfaces has been investigated. Dilute chemistries can be highly effective, especially when high- frequency acoustic energy (megasonics) is applied. The high particle removal efficacy of the dilute chemistry processes presumably arises due to increased double layer effects caused by reduced ionic strength. Dilute chemistry SC- I solutions exhibit somewhat reduced efficacy for removal of certain light organics; however, when dilute SC-1 is used along with other pre-gate cleaning steps (e.g. HF, SC-2, and piranha), then the overall cleaning sequence is quite effective. In addition to providing robust cleaning processes, dilute chemistries also result in significantly lower chemical and rinse water usage. Waste water treatment requirements are also lessened when dilute chemistry cleaning solutions are employed.

Resnick, P.J.; Simonson, G.C.; Matlock, C.A.; Kelly, M.J.

1996-11-01T23:59:59.000Z

385

POWER PLANT WATER USAGE AND LOSS STUDY - Final  

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

POWER PLANT WATER USAGE AND LOSS STUDY August 2005 Revised May 2007 Prepared for: The United States Department of Energy National Energy Technology Laboratory DOE Gasification...

386

Child Care Availability and Usage Among Welfare Recipients  

E-Print Network (OSTI)

Child Care Availability and Usage Among Welfare Recipients 1the impact that the availability of nearby licensed care hasemployment and that the availability of nearby licensed care

Houston, Douglas; Ong, Paul M.

2003-01-01T23:59:59.000Z

387

NANOFAB TOOL USAGE RATES Effective 1/1/13  

Science Conference Proceedings (OSTI)

... Application specific training beyond general tool usage will require additional training time and should be discussed with process engineer prior to ...

2013-07-18T23:59:59.000Z

388

VEHICLE USAGE LOG Department ________________________________________ Vehicle Homebase ____________________________ Week Ended (Sunday) _________________  

E-Print Network (OSTI)

VEHICLE USAGE LOG Department ________________________________________ Vehicle Homebase of the owning Unit. Vehicle Homebase: Enter the City, Zip Code, Building, or other location designation. Week

Johnston, Daniel

389

Electrical energy consideration and payment in an Australian University  

SciTech Connect

This article discusses an attempt to obtain a formula to calculate the energy consumption for each faculty of a university from the faculty statistics or, at least, to calculate a change of energy allowance based on changing faculty statistics. Topics considered include the university plant, factors contributing to electrical energy usage (base load component, personnel component, laboratory-workshop component), the faculty energy usage equation, establishing the values of the formula constants, estimating energy usage, and faculty energy savings.

Bonwick, W.J.; Cappadona, J.

1984-01-01T23:59:59.000Z

390

Heat wave contributes to higher summer electricity demand in...  

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

more than a decade, according to the U.S. Energy Information Administration EIA's new forecast shows household electricity use is expected to drop 1.1 percent this year and then...

391

Electric Power Waveform Distortion  

Science Conference Proceedings (OSTI)

Engineering issues regarding waveform distortion, harmonics, radio-frequency noise, and similar concerns have existed as long as there has been a power industry. These deal with consequences ranging from heating of transformers and machinery to telephone and radio interference. While waveform distortion has been around for a long time, the sources of harmonics and electromagnetic noise owned by the electricity customer have proliferated in recent years with the widespread usage of such things as switchin...

2012-05-23T23:59:59.000Z

392

Householder’s Perceptions of Insulation Adequacy and Drafts in the Home in 2001  

E-Print Network (OSTI)

In order to improve the estimation of end-use heating consumption, the Energy Information Administration's (EIA), 2001 Residential Energy Consumption Survey (RECS), for the first time, asked respondents to judge how drafty they perceived their homes to be as a measure of insulation quality. The analysis of the 2001 RECS data shows that householders in newlyconstructed homes perceived their homes to be better insulated and less drafty than do householders in older homes. Single-family homes are perceived to be better insulated and less drafty than are apartments in buildings with two to four units. Cross-variable comparisons also provide the associations between the level of insulation and winter drafts in the homes with household characteristics and location of the home.

Behjat Hojjati

2004-01-01T23:59:59.000Z

393

Predicting Energy Usage in a Supermarket  

E-Print Network (OSTI)

Very little is known about the energy using systems in commercial and retail stores, which consume 24.8% of the energy used by all commercial buildings. This paper describes development of a change-point regression model for predicting the hourly and daily electrical use of a supermarket. Operational improvements already identified with the model can save the store over 4% of their electricity cost annually. Further analysis is expected to save the store additional energy costs.

Schrock, D. W.; Claridge, D. E.

1989-01-01T23:59:59.000Z

394

SmartCap: Flattening Peak Electricity Demand in Smart Homes Sean Barker, Aditya Mishra, David Irwin, Prashant Shenoy, and Jeannie Albrecht  

E-Print Network (OSTI)

SmartCap: Flattening Peak Electricity Demand in Smart Homes Sean Barker, Aditya Mishra, David Irwin--Flattening household electricity demand reduces generation costs, since costs are disproportionately affected by peak demands. While the vast majority of household electrical loads are interactive and have little scheduling

Shenoy, Prashant

395

Usage derived recommendations for a video digital library  

Science Conference Proceedings (OSTI)

We describe a minimalist methodology to develop usage-based recommender systems for multimedia digital libraries. A prototype recommender system based on this strategy was implemented for the Open Video Project, a digital library of videos that are freely ... Keywords: Open Video Project, Recommender systems, Usage analysis, Video

Johan Bollen; Michael L. Nelson; Gary Geisler; Raquel Araujo

2007-08-01T23:59:59.000Z

396

Towards appliance usage prediction for home energy management  

Science Conference Proceedings (OSTI)

In this paper, we address the problem of predicting the usage of home appliances where a key challenge is to model the everyday routine of homeowners and the inter-dependency between the use of different appliances. To this end, we propose an agent based ... Keywords: home energy management, usage prediction

Ngoc Cuong Truong, Long Tran-Thanh, Enrico Costanza, Sarvapali D. Ramchurn

2013-01-01T23:59:59.000Z

397

A MOOS MODULE FOR MONITORING ENERGY USAGE OF AUTONOMOUS VEHICLES  

E-Print Network (OSTI)

A MOOS MODULE FOR MONITORING ENERGY USAGE OF AUTONOMOUS VEHICLES Anthony Kanago, Kevin Roos, James--Tracking the energy usage of an autonomous underwater vehicle (AUV) and making accurate data available provides especially effectively in energy-aware systems, allowing inspection vehicles (which typically travel farther

Idaho, University of

398

Cloud resource usage: extreme distributions invalidating traditional capacity planning models  

Science Conference Proceedings (OSTI)

For years Capacity Planning professionals knew or suspected that various characteristics of computer usage have non-normal distribution. At the same time much of the traditional workload modeling and forecasting is based on mathematical techniques assuming ... Keywords: capacity planning, power law, probability distributions, resource usage, volatility

Charles Z. Loboz

2011-06-01T23:59:59.000Z

399

Unit Cost Electricity | OpenEI  

Open Energy Info (EERE)

8 8 Varnish cache server Browse Upload data GDR 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2142281518 Varnish cache server Unit Cost Electricity Dataset Summary Description Provides annual energy usage for years 1989 through 2010 for UT at Austin; specifically, electricity usage (kWh), natural gas usage (Mcf), associated costs. Also provides water consumption for 2005 through 2010. Source University of Texas (UT) at Austin, Utilities & Energy Management Date Released Unknown Date Updated Unknown Keywords Electricity Consumption Natural Gas Texas Unit Cost Electricity Unit Cost Natural Gas University Water Data application/vnd.ms-excel icon Energy and Water Use Data for UT-Austin (xls, 32.8 KiB) Quality Metrics

400

A Structural Model of Vehicle Use in Two-Vehicle Households  

E-Print Network (OSTI)

vehicle sports car implies that usage is shifted towardthecars as secondcars have a weakerpositive relationship to usage,

Golob, Thomas F.; Kim, Seyoung; Ren, Weiping

1994-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household electricity usage" 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

Designing a Residential Hybrid Electrical Energy Storage System Based on the Energy Buffering Strategy  

E-Print Network (OSTI)

the electricity price is low and supply energy for usage when the electricity price is high [6], and thereby energy buffering. Figure 3 shows the structure of a typical grid-connected HEES system. Without loss the proposed energy management system is targeting residential usage, we must limit its overall form factor

Pedram, Massoud

402

Evidence from Two Large Field Experiments that Peer Comparison Feedback Can Reduce Residential Energy Usage  

E-Print Network (OSTI)

Abstract: By providing feedback to customers on home electricity and natural gas usage with a focus on peer comparisons, utilities can reduce energy consumption at a low cost. We analyze data from two large-scale, random-assignment field experiments conducted by utility companies providing electricity (the Sacramento Municipal Utility District (SMUD)) and electricity and natural gas (Puget Sound Energy (PSE)), in partnership with a private company, Positive Energy/oPower, which provides monthly or quarterly mailed peer feedback reports to customers. We find reductions in energy consumption of 1.2 % (PSE) to 2.1% percent (SMUD), with the decrease sustained over time (seven months (PSE) and twelve months (SMUD)).

Ian Ayres Yale; Sophie Raseman Yale; Alice Shih Yale; Ian Ayres; Sophie Raseman; Alice Shih

2010-01-01T23:59:59.000Z

403

Essays on the effects of demographics on household consumption.  

E-Print Network (OSTI)

??My dissertation analyses the relationship between households' consumption behavior and changes in family demographic characteristics. The first paper studies consumption over the period of the… (more)

Stepanova, Ekaterina, 1977-

2006-01-01T23:59:59.000Z

404

Crime and the Nation’s Households, 2000 By  

E-Print Network (OSTI)

experienced 1 or more violent or property crimes in 2000, according to data from the National Crime Victimization Survey (NCVS). About 4.3 million households had members who experienced 1 or more nonfatal violent crimes, including rape, sexual assault, robbery, and aggravated or simple assault. About 14.8 million households experienced 1 or more property crimes — household burglary, motor vehicle theft, or theft. Vandalism, presented for the first time in a Bureau of Justice Statistics (BJS) report, victimized about 6.1 million households. The households that sustained vandalism were counted separately from those experiencing other crimes. Because vandalism is included for the first time, findings are presented in a box on page 4. Beginning in 2001, NCVS victimizations will be measured both with and without vandalism. Measuring the extent to which households are victimized by crime One measure of the impact of crime throughout the Nation is gained through estimating the number and percentage of households victimized Highlights During 2000, 16 % of U.S. households had a member who experienced a crime, with 4 % having a member victimized by violent crime. During 1994, 25 % of households experienced at least one crime; 7 % a violent crime.

Patsy A. Klaus

2002-01-01T23:59:59.000Z

405

Table 1. Household Characteristics by Ceiling Fans, 2001  

U.S. Energy Information Administration (EIA)

A reporting of the number of housing units using ceiling fans in U.S. households as reported in the 2001 Residential Energy Consumption Survey

406

U.S. households are incorporating energy–efficient features ...  

U.S. Energy Information Administration (EIA)

... area of increased efficiency: about 60% of households use at least some energy-efficient compact fluorescent (CFL) or light-emitting diode (LED) ...

407

Householder's Perceptions of Insulation Adequacy and Drafts in the ...  

U.S. Energy Information Administration (EIA)

The 2001 RECS was the first RECS to request household perceptions regarding the presence of winter drafts in the home. The data presented in this report ...

408

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 ...

409

Barriers to household investment in residential energy conservation: preliminary assessment  

Science Conference Proceedings (OSTI)

A general assessment of the range of barriers which impede household investments in weatherization and other energy efficiency improvements for their homes is provided. The relationship of similar factors to households' interest in receiving a free energy audits examined. Rates of return that underly household investments in major conservation improvements are assessed. A special analysis of household knowledge of economically attractive investments is provided that compares high payback improvements specified by the energy audit with the list of needed or desirable conservation improvements identified by respondents. (LEW)

Hoffman, W.L.

1982-12-01T23:59:59.000Z

410

Household Responses to the Financial Crisis in Indonesia  

E-Print Network (OSTI)

on farm households in Indonesia and Thailand,” World Bank20. Cameron, Lisa. (1999). “Indonesia: a quarterly review,”The Real Costs of Indonesia's Economic Crisis: Preliminary

Thomas, Duncan; Frankenberg, Elizabeth

2005-01-01T23:59:59.000Z

411

SUPPLEMENTAL ENERGY-RELATED DATA FOR THE 2001 NATIONAL HOUSEHOLD ...  

U.S. Energy Information Administration (EIA)

... vehicle manufacturer, vehicle model, vehicle model year, and vehicle type – several ENERGY INFORMATION ADMINISTRATION/2001 NATIONAL HOUSEHOLD TRAVEL SURVEY K-23 ...

412

In-vessel composting of household wastes  

Science Conference Proceedings (OSTI)

The process of composting has been studied using five different types of reactors, each simulating a different condition for the formation of compost; one of which was designed as a dynamic complete-mix type household compost reactor. A lab-scale study was conducted first using the compost accelerators culture (Trichoderma viridae, Trichoderma harzianum, Trichorus spirallis, Aspergillus sp., Paecilomyces fusisporus, Chaetomium globosum) grown on jowar (Sorghum vulgare) grains as the inoculum mixed with cow-dung slurry, and then by using the mulch/compost formed in the respective reactors as the inoculum. The reactors were loaded with raw as well as cooked vegetable waste for a period of 4 weeks and then the mulch formed was allowed to maturate. The mulch was analysed at various stages for the compost and other environmental parameters. The compost from the designed aerobic reactor provides good humus to build up a poor physical soil and some basic plant nutrients. This proves to be an efficient, eco-friendly, cost-effective, and nuisance-free solution for the management of household solid wastes.

Iyengar, Srinath R. [Civil and Environmental Engineering Department, V.J. Technological Institute, H.R. Mahajani Road, Matunga, Mumbai 400 019 (India)]. E-mail: srinathrangamani@yahoo.com; Bhave, Prashant P. [Civil and Environmental Engineering Department, V.J. Technological Institute, H.R. Mahajani Road, Matunga, Mumbai 400 019 (India)]. E-mail: drppbhave@vsnl.net

2006-07-01T23:59:59.000Z

413

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

414

Scalable Feature Mining for Sequential Data Mitsubishi Electric Research Lab.  

E-Print Network (OSTI)

Scalable Feature Mining for Sequential Data Neal Lesh Mitsubishi Electric Research Lab. 201, DNA sequences, web usage data, multi­player games, and plan execution traces. In sequential domains

Zaki, Mohammed Javeed

415

2012 Portland General Electric. All rights reserved. Planning for Demand  

E-Print Network (OSTI)

2/13/2013 1 © 2012 Portland General Electric. All rights reserved. Planning for Demand Response their usage. Demand Response ­ PGE Current Status 10 Automated Demand R

416

POWER PLANT WATER USAGE AND LOSS STUDY - Final  

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

POWER PLANT WATER USAGE AND LOSS STUDY POWER PLANT WATER USAGE AND LOSS STUDY August 2005 Revised May 2007 Prepared for: The United States Department of Energy National Energy Technology Laboratory DOE Gasification Technology Manager: Gary J. Stiegel DOE Project Manager: James R. Longanbach Project Manager: Michael D. Rutkowski Principal Investigators: Michael G. Klett Norma J. Kuehn Ronald L. Schoff Vladimir Vaysman Jay S. White Power Plant Water Usage and Loss Study i August 2005 TABLE OF CONTENTS TABLE OF CONTENTS ...................................................................................................................... I LIST OF TABLES.............................................................................................................................III

417

Predicting the Market Potential of Plug-In Electric Vehicles Using Multiday GPS Data  

E-Print Network (OSTI)

GPS data for a year’s worth of travel by 255 Seattle households illuminate how plug-in electric vehicles can match household needs. The results suggest that a battery-electric vehicle (BEV) with 100 miles of range should meet the needs of 50 % of one-vehicle households and 80 % of multiple-vehicle households, when charging once a day and relying on another vehicle or mode just 4 days a year. Moreover, the average one-vehicle Seattle household uses each vehicle 23 miles per day and should be able to electrify close to 80 % of its miles using a plug-in hybrid electric vehicle (PHEV) with 40-mile all-electric-range. Households owning two or more vehicles can electrify 50 to 70 % of their miles using a PHEV40, depending on how they assign the vehicle across drivers each day. Cost comparisons between the average single-vehicle household owning a Chevrolet Cruze versus a Volt PHEV suggest that when gas prices are $3.50 per gallon and electricity rates at 11.2 ct per kWh, the Volt will save the household $535 per year in operating costs. Similarly, the Toyota Prius PHEV will provide an annual savings of $538 per year over the Corolla.

Mobashwir Khan; Kara M. Kockelman; William J. Murray Jr. Fellow

2011-01-01T23:59:59.000Z

418

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

E-Print Network (OSTI)

of usage nationwide, we can estimate total national energythe total combined energy use. 3. Average usage over alltotal game console usage, this suggests that an appreciable fraction of console energy

Desroches, Louis-Benoit

2013-01-01T23:59:59.000Z

419

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

420

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

Note: This page contains sample records for the topic "household electricity usage" 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

Simulating household activities to lower consumption peaks: demonstration  

Science Conference Proceedings (OSTI)

Energy experts need fine-grained dynamics oriented tools to investigate household activities in order to improve power management in the residential sector. This paper presents the SMACH framework for modelling, simulating and analy- sis of household ... Keywords: agent-based modelling, energy, social simulation

Edouard Amouroux, Francois Sempé, Thomas Huraux, Nicolas Sabouret, Yvon Haradji

2013-05-01T23:59:59.000Z

422

Elements of consumption: an abstract visualization of household consumption  

Science Conference Proceedings (OSTI)

To promote sustainability consumers must be informed about their consumption behaviours. Ambient displays can be used as an eco-feedback technology to convey household consumption information. Elements of Consumption (EoC) demonstrates this by visualizing ... Keywords: a-life, eco-feedback, household consumption, sustainability

Stephen Makonin; Philippe Pasquier; Lyn Bartram

2011-07-01T23:59:59.000Z

423

A REVIEW OF ASSUMPTIONS AND ANALYSIS IN EPRI EA-3409, "HOUSEHOLD APPLIANCE CHOICE: REVISION OF REEPS BEHAVIORAL MODELS"  

E-Print Network (OSTI)

EPRI EA-3409, "Household Appliance Choice: Revision of REEPSEA",3409: "HOUSEHOLD APPLIANCE CHOICE: REVISION OF REEPSreport EA-3409, "Household Appliance Choice: Revi- sion of

Wood, D.J.

2010-01-01T23:59:59.000Z

424

Broad Initiatives/Sharp Focus- Cuts Electricity Consumption 15%  

E-Print Network (OSTI)

Analysis of electrical consumption can payout in reduced energy costs. Continuous monitoring of electrical usage coupled with improvements and optimization in system(s) operations can have a favorable impact on annual operating expenditures. Further, participation in local utility rebate programs to reduce electrical consumption will enhance funding of energy efficient programs.

Gialanella, V.

1998-04-01T23:59:59.000Z

425

Energy Usage Information: Lessons from the Credit Reporting Industry.  

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

Energy Usage Information: Lessons from the Credit Reporting Industry. Energy Usage Information: Lessons from the Credit Reporting Industry. Speaker(s): Philip Henderson Date: October 4, 2012 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Janie Page There has been much discussion about the use of customer energy usage information to deliver value, such as with benchmarking tools that compare energy use in a building to a peer set, continuous commissioning services that diagnose faults in building systems, and tools that estimate expected savings from upgrades. A utility can use customer information to deliver these kinds of services to its customers directly, but most utilities today do not enable companies to obtain a customer's energy usage information in a systematic, automated way to deliver services to the customer, even if

426

Memory Usage Inference for Object-Oriented Programs  

E-Print Network (OSTI)

We present a type-based approach to statically derive symbolic closed-form formulae that characterize the bounds of heap memory usages of programs written in object-oriented languages. Given a program with size and alias ...

Nguyen, Huu Hai

427

People are Strange: Current Behavioral Insights into Energy Usage  

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

People are Strange: Current Behavioral Insights into Energy Usage Speaker(s): Susan Mazur-Stommen Date: October 10, 2011 - 12:00pm Location: 90-1099 Seminar HostPoint of Contact:...

428

Energy Usage Information: Lessons from the Credit Reporting Industry...  

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

Energy Usage Information: Lessons from the Credit Reporting Industry. Speaker(s): Philip Henderson Date: October 4, 2012 - 12:00pm Location: 90-3122 Seminar HostPoint of Contact:...

429

UC Libraries Academic e-Book Usage Survey  

E-Print Network (OSTI)

Usage Study [Q1. Create condition: academic e-book users] 1.Do you use e-books for your academic work? (Select one) a.you generally prefer print books or e-books? (Select one) a.

Li, Chan; Poe, Felicia; Potter, Michele; Quigley, Brian; Wilson, Jacqueline

2011-01-01T23:59:59.000Z

430

RECS Propane Usage Form_v1 (Draft).xps  

Gasoline and Diesel Fuel Update (EIA)

propane usage for this housing unit between September 2008 and April 2010. Delivery Number Enter the Delivery Date for each delivery 1 2 3 4 5 6 7 8 9 10 Enter the Total Dollar...

431

FATIGUEPRO: On-Line Fatigue Usage Transient Monitoring System  

Science Conference Proceedings (OSTI)

FATIGUEPRO accurately monitors plant data to calculate actual fatigue usage for critical nuclear plant components. This system should improve plant reliability and contribute to plant life extension by providing a more realistic estimation of fatigue demands.

1988-05-01T23:59:59.000Z

432

NanoFab User Facility Usage Fee Schedule  

Science Conference Proceedings (OSTI)

Page 1. NanoFab User Facility Usage Fee Schedule Effective 11/1/09 Tool Full Rate ($/hr) Reduced Rate ($/hr) Base NanoFab Use 60 30 ...

433

Identify Vehicle Usage Mission Constraints for Reducing Greenhouse Gas  

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

Identify Vehicle Usage Mission Constraints for Reducing Greenhouse Identify Vehicle Usage Mission Constraints for Reducing Greenhouse Gas Emissions Identify Vehicle Usage Mission Constraints for Reducing Greenhouse Gas Emissions October 7, 2013 - 11:46am Addthis YOU ARE HERE: Step 2 As Federal agencies work to identify opportunities for right-sizing the fleet and replacing inefficient vehicles with new, efficient, and/or alternatively fueled models to reduce greenhouse gas (GHG) emissions, they should flag potential mission constraints associated with vehicle usage. This may involve further data collection to understand the mission considerations associated with individual vehicles. For instance, in Figure 1, Vehicle 004 appears to be underutilized, having both a low user-to-vehicle ratio and a relatively low time in use per day. However,

434

The Plugger : EnergySmart School Inventors  

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

Inventors The Plugger Annie Austin Inventor: Annie Austin The Concept: The Plugger is an electricity usage monitoring device. It beeps to alert you when your household energy use...

435

Measuring the energy efficiency of households: an application of frontier production function analysis  

SciTech Connect

A new method to estimate the energy efficiency of households is presented. Households are viewed as productive units organized to provide the occupants with numerous services requiring fuel as an input: house heating to achieve a desired interior temperature, lighting for recreation, etc. The focus is on the efficiency of energy use, not the demand for energy. The approach to measuring efficiency compares a group of productive units along several dimensions of input resources and service outputs. The comparison identifies a subset of units that are considered efficient because they require the least resources per unit of service provided. The efficient units form a production possibility frontier of best practice in service provision. A regression of the two sets of efficiency scores on other variables reflecting locational, dwelling unit, and occupational characteristics is performed to identify factors accounting for differences in efficiency. The results indicate that the more efficient units used electric heat, had higher ratios of non-electric to electric fuel inputs, were owner-occupied, and were built after 1974. The findings also suggest that both family life cycle and income effects account for efficiency differences.

Baxter, L.W.

1984-01-01T23:59:59.000Z

436

Model of home heating and calculation of rates of return to household energy conservation investment  

Science Conference Proceedings (OSTI)

This study attempts to find out if households' investments on energy conservation yield expected returns. It first builds a home-heating regression model, then uses the results of the model to calculate the rates of return for households' investments on the energy conservation. The home heating model includes housing characteristics, economic and demographic variables, appliance related variables, and regional dummy variables. Housing characteristic variables are modeled according to the specific physical relationship between the house and its heating requirement. Data from the Residential Energy Consumption Survey (RECS) of 1980-1981 is used for the empirical testing of the model. The model is estimated for single-detached family houses separately for three major home-heating fuel types: electricity, natural gas and fuel oil. Four scenarios are used to calculate rates of return for each household. The results show in the Northern areas the rates of return in most of the cases are a lot higher than market interest rates. In the Western and Southern areas, with few exceptions, the rates of return are lower than market interest rates. The variation of heating degree days and energy prices can affect the rates of return up to 20 percentage points.

Hsueh, L.M.

1984-01-01T23:59:59.000Z

437

Table CE2-3e. Space-Heating Energy Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Table CE2-3e. Space-Heating Energy Expenditures in U.S. Households by Household Income, 2001 RSE Column Factor: Total 2001 Household Income Below Poverty

438

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

439

"Table HC15.13 Lighting Usage Indicators by Four Most Populated...  

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

3 Lighting Usage Indicators by Four Most Populated States, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","Four Most Populated States" "Lighting Usage...

440

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

Note: This page contains sample records for the topic "household electricity usage" 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

Evaluation of evolving residential electricity tariffs  

Science Conference Proceedings (OSTI)

Residential customers in California's Pacific Gas and Electric (PG&E) territory have seen several electricity rate structure changes in the past decade. This poster: examines the history of the residential pricing structure and key milestones; summarizes and analyzes the usage between 2006 and 2009 for different baseline/climate areas; discusses the residential electricity Smart Meter roll out; and compares sample bills for customers in two climates under the current pricing structure and also the future time of use (TOU) structure.

Lai, Judy; DeForest, Nicholas; Kiliccote, Sila; Stadler, Michael; Marnay, Chris; Donadee, Jon

2011-05-15T23:59:59.000Z

442

Household attitudes toward energy conservation in the Pacific Northwest: overview and comparisons  

SciTech Connect

This report presents an overview of a baseline residential energy conservation study for the Pacific Northwest conducted in November 1983 by RMH Research, Inc. It also compares the study results with available data from other surveys. The primary focus of the RMH study is conservation marketing. As such it assesses the attitudes, perceptions, and past conservation actions of the region's residents and provides market segmentation based upon past conservation actions and the propensity to invest in conservation in the future. Excluding renters, who account for about 24% of the region's households, three prospect groups for marketing conservation investments are identified: First Tier Prospects who are very likely to invest in additional conservation measures requiring larger sums of money (estimated at about 547,000 households, or 18 percent of the region's households); Second Tier Prospects who are somewhat likely to invest in full weatherization (estimated at about 22% of the region's households or 695,700); and Non-Prospects who are unlikely to invest in energy conservation in the near future (estimated to be 1,113,400 or 36% of the regional total). A summary comparison of the most important distinguishing attributes of the three prospect groups is presented. Considering the current surplus status of the region's electricity supply situation and the overall strategy in capability building, implications include (1) using public information programs through utilities and the news media to maintain the conservation interests of the first-tier prospects and (2) exploring ways to move the second-tier prospects into the first tier and to reach the so-called non-prospect and rental housing groups.

Fang, J.M.

1985-06-01T23:59:59.000Z

443

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis--A Reflively Designed Survey of New-car-buying, Multi-vehicle California Households  

E-Print Network (OSTI)

even after purchase incentives for natural gas and electricnatural gas, and gasoline vehicles. The use of purchase incentives

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

444

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis -- A Reflexively Designed Survey of New-Car-Buying Multi-Vehicle California Households  

E-Print Network (OSTI)

B. C. D. E. F. Compressed natural gas Reformulated gasolineelectric ~]1 compressed natural gas [~1 reformulatedgasolinefull size styles) Compressed natural gas, ranges 80 or 120,

Turrentine, Thomas; Kurani, Kenneth S.

2001-01-01T23:59:59.000Z

445

Table AC1. Total Households Using Air-Conditioning Equipment, 2005 ...  

U.S. Energy Information Administration (EIA)

Table AC1. Total Households Using Air-Conditioning Equipment, 2005 Million U.S. Households Type of Air-Conditioning Equipment (millions) Central System

446

Table CE2-3c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household4,a Physical Units of Space-Heating Consumption per Household,3 Where the Main Space-Heating Fuel Is:

447

Table CE2-7c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3,a Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

448

Table CE2-12c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3,a Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

449

Table CE2-4c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3,a Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

450

Table CE2-7c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3 Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

451

Material World: Forecasting Household Appliance Ownership in a Growing Global Economy  

E-Print Network (OSTI)

of Household Income and Appliance Ownership. ECEEE Summerof decreasing prices of appliances, if price data becomesForecasting Household Appliance Ownership in a Growing

Letschert, Virginie

2010-01-01T23:59:59.000Z

452

Table SH1. Total Households Using a Space Heating Fuel, 2005 ...  

U.S. Energy Information Administration (EIA)

Total Households Using a Space Heating Fuel, 2005 Million U.S. Households Using a Non-Major Fuel 5 ... Space Heating (millions) Energy Information Administration

453

Projecting household energy consumption within a conditional demand framework  

SciTech Connect

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

Teotia, A.; Poyer, D.

1991-01-01T23:59:59.000Z

454

Projecting household energy consumption within a conditional demand framework  

Science Conference Proceedings (OSTI)

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

Teotia, A.; Poyer, D.

1991-12-31T23:59:59.000Z

455

Customer reponse to day-ahead wholesale market electricity prices: Case study of RTP program experience in New York  

E-Print Network (OSTI)

Response to Electricity Real-Time Prices: Short Run and LongElectricity Usage to Real Time Prices A-31 v List ofwere linked to real-time prices, most customers indicated

2004-01-01T23:59:59.000Z

456

Portland General Electric Company P.U.C. Oregon No. E-17 Original Sheet No. 86-1  

E-Print Network (OSTI)

service that allows participating Consumers an opportunity to voluntarily reduce their Electricity usagePortland General Electric Company P.U.C. Oregon No. E-17 Original Sheet No. 86-1 Advice No. 00-14A participating Consumers of the opportunity to reduce Energy usage. AVAILABLE In all territory served

457

Measurement of nicotine in household dust  

Science Conference Proceedings (OSTI)

An analytical method of measuring nicotine in house dust was optimized and associations among three secondhand smoking exposure markers were evaluated, i.e., nicotine concentrations of both house dust and indoor air, and the self-reported number of cigarettes smoked daily in a household. We obtained seven house dust samples from self-reported nonsmoking homes and 30 samples from smoking homes along with the information on indoor air nicotine concentrations and the number of cigarettes smoked daily from an asthma cohort study conducted by the Johns Hopkins Center for Childhood Asthma in the Urban Environment. House dust nicotine was analyzed by isotope dilution gas chromatography-mass spectrometry (GC/MS). Using our optimized method, the median concentration of nicotine in the dust of self-reported nonsmoking homes was 11.7 ng/mg while that of smoking homes was 43.4 ng/mg. We found a substantially positive association (r=0.67, P<0.0001) between house dust nicotine concentrations and the numbers of cigarettes smoked daily. Optimized analytical methods showed a feasibility to detect nicotine in house dust. Our results indicated that the measurement of nicotine in house dust can be used potentially as a marker of longer term SHS exposure.

Kim, Sungroul [Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Institute for Global Tobacco Control, 627 N. Washington Street, 2nd Floor Baltimore, MD 21205 (United States); Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States)], E-mail: srkim@jhsph.edu; Aung, Ther; Berkeley, Emily [Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States); Diette, Gregory B. [Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States); Department of Medicine, Johns Hopkins University School of Medicine (United States); Breysse, Patrick N. [Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States)

2008-11-15T23:59:59.000Z

458

2011 Radioactive Materials Usage Survey for Unmonitored Point Sources  

SciTech Connect

This report provides the results of the 2011 Radioactive Materials Usage Survey for Unmonitored Point Sources (RMUS), which was updated by the Environmental Protection (ENV) Division's Environmental Stewardship (ES) at Los Alamos National Laboratory (LANL). ES classifies LANL emission sources into one of four Tiers, based on the potential effective dose equivalent (PEDE) calculated for each point source. Detailed descriptions of these tiers are provided in Section 3. The usage survey is conducted annually; in odd-numbered years the survey addresses all monitored and unmonitored point sources and in even-numbered years it addresses all Tier III and various selected other sources. This graded approach was designed to ensure that the appropriate emphasis is placed on point sources that have higher potential emissions to the environment. For calendar year (CY) 2011, ES has divided the usage survey into two distinct reports, one covering the monitored point sources (to be completed later this year) and this report covering all unmonitored point sources. This usage survey includes the following release points: (1) all unmonitored sources identified in the 2010 usage survey, (2) any new release points identified through the new project review (NPR) process, and (3) other release points as designated by the Rad-NESHAP Team Leader. Data for all unmonitored point sources at LANL is stored in the survey files at ES. LANL uses this survey data to help demonstrate compliance with Clean Air Act radioactive air emissions regulations (40 CFR 61, Subpart H). The remainder of this introduction provides a brief description of the information contained in each section. Section 2 of this report describes the methods that were employed for gathering usage survey data and for calculating usage, emissions, and dose for these point sources. It also references the appropriate ES procedures for further information. Section 3 describes the RMUS and explains how the survey results are organized. The RMUS Interview Form with the attached RMUS Process Form(s) provides the radioactive materials survey data by technical area (TA) and building number. The survey data for each release point includes information such as: exhaust stack identification number, room number, radioactive material source type (i.e., potential source or future potential source of air emissions), radionuclide, usage (in curies) and usage basis, physical state (gas, liquid, particulate, solid, or custom), release fraction (from Appendix D to 40 CFR 61, Subpart H), and process descriptions. In addition, the interview form also calculates emissions (in curies), lists mrem/Ci factors, calculates PEDEs, and states the location of the critical receptor for that release point. [The critical receptor is the maximum exposed off-site member of the public, specific to each individual facility.] Each of these data fields is described in this section. The Tier classification of release points, which was first introduced with the 1999 usage survey, is also described in detail in this section. Section 4 includes a brief discussion of the dose estimate methodology, and includes a discussion of several release points of particular interest in the CY 2011 usage survey report. It also includes a table of the calculated PEDEs for each release point at its critical receptor. Section 5 describes ES's approach to Quality Assurance (QA) for the usage survey. Satisfactory completion of the survey requires that team members responsible for Rad-NESHAP (National Emissions Standard for Hazardous Air Pollutants) compliance accurately collect and process several types of information, including radioactive materials usage data, process information, and supporting information. They must also perform and document the QA reviews outlined in Section 5.2.6 (Process Verification and Peer Review) of ES-RN, 'Quality Assurance Project Plan for the Rad-NESHAP Compliance Project' to verify that all information is complete and correct.

Sturgeon, Richard W. [Los Alamos National Laboratory

2012-06-27T23:59:59.000Z

459

2011 Radioactive Materials Usage Survey for Unmonitored Point Sources  

SciTech Connect

This report provides the results of the 2011 Radioactive Materials Usage Survey for Unmonitored Point Sources (RMUS), which was updated by the Environmental Protection (ENV) Division's Environmental Stewardship (ES) at Los Alamos National Laboratory (LANL). ES classifies LANL emission sources into one of four Tiers, based on the potential effective dose equivalent (PEDE) calculated for each point source. Detailed descriptions of these tiers are provided in Section 3. The usage survey is conducted annually; in odd-numbered years the survey addresses all monitored and unmonitored point sources and in even-numbered years it addresses all Tier III and various selected other sources. This graded approach was designed to ensure that the appropriate emphasis is placed on point sources that have higher potential emissions to the environment. For calendar year (CY) 2011, ES has divided the usage survey into two distinct reports, one covering the monitored point sources (to be completed later this year) and this report covering all unmonitored point sources. This usage survey includes the following release points: (1) all unmonitored sources identified in the 2010 usage survey, (2) any new release points identified through the new project review (NPR) process, and (3) other release points as designated by the Rad-NESHAP Team Leader. Data for all unmonitored point sources at LANL is stored in the survey files at ES. LANL uses this survey data to help demonstrate compliance with Clean Air Act radioactive air emissions regulations (40 CFR 61, Subpart H). The remainder of this introduction provides a brief description of the information contained in each section. Section 2 of this report describes the methods that were employed for gathering usage survey data and for calculating usage, emissions, and dose for these point sources. It also references the appropriate ES procedures for further information. Section 3 describes the RMUS and explains how the survey results are organized. The RMUS Interview Form with the attached RMUS Process Form(s) provides the radioactive materials survey data by technical area (TA) and building number. The survey data for each release point includes information such as: exhaust stack identification number, room number, radioactive material source type (i.e., potential source or future potential source of air emissions), radionuclide, usage (in curies) and usage basis, physical state (gas, liquid, particulate, solid, or custom), release fraction (from Appendix D to 40 CFR 61, Subpart H), and process descriptions. In addition, the interview form also calculates emissions (in curies), lists mrem/Ci factors, calculates PEDEs, and states the location of the critical receptor for that release point. [The critical receptor is the maximum exposed off-site member of the public, specific to each individual facility.] Each of these data fields is described in this section. The Tier classification of release points, which was first introduced with the 1999 usage survey, is also described in detail in this section. Section 4 includes a brief discussion of the dose estimate methodology, and includes a discussion of several release points of particular interest in the CY 2011 usage survey report. It also includes a table of the calculated PEDEs for each release point at its critical receptor. Section 5 describes ES's approach to Quality Assurance (QA) for the usage survey. Satisfactory completion of the survey requires that team members responsible for Rad-NESHAP (National Emissions Standard for Hazardous Air Pollutants) compliance accurately collect and process several types of information, including radioactive materials usage data, process information, and supporting information. They must also perform and document the QA reviews outlined in Section 5.2.6 (Process Verification and Peer Review) of ES-RN, 'Quality Assurance Project Plan for the Rad-NESHAP Compliance Project' to verify that all information is complete and correct.

Sturgeon, Richard W. [Los Alamos National Laboratory

2012-06-27T23:59:59.000Z

460

Ames Electric Department - Residential Energy Efficiency Rebate Programs |  

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

Ames Electric Department - Residential Energy Efficiency Rebate Ames Electric Department - Residential Energy Efficiency Rebate Programs Ames Electric Department - Residential Energy Efficiency Rebate Programs < Back Eligibility Multi-Family Residential Residential Savings Category Heating & Cooling Commercial Heating & Cooling Cooling Appliances & Electronics Home Weatherization Construction Commercial Weatherization Design & Remodeling Heat Pumps Commercial Lighting Lighting Maximum Rebate Appliances: 50% of the equipment cost Programmable Thermostats: 3 per household Room AC: 2 per household Program Info State Iowa Program Type Utility Rebate Program Rebate Amount Energy Star New Home: $500 Energy Audit: FREE Lighting: $2 - $16 per fixture Lighting Sensors: $10 per unit Refrigerators: $25 - $100 Freezers: $50 Dishwashers: $50

Note: This page contains sample records for the topic "household electricity usage" 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

Associating Internet usage with depressive behavior among college students  

E-Print Network (OSTI)

Abstract — Depression is a mental health problem affecting a large population of college students. Since college students are active users of the Internet today, investigating associations between symptoms of depression and Internet usage has been an active area of research. While existing studies do provide critical insights, they are limited due to the fact that Internet usage of subjects is characterized by means of self-reported surveys only. In this paper, we report our findings on a month long experiment conducted at Missouri University of Science and Technology on associating depressive symptoms among college students and Internet usage using real Internet data collected continuously, unobtrusively and preserving privacy. In our study, 216 undergraduates were surveyed for depressive symptoms using the CES-D scale. We then collected their on-campus Internet usage via Cisco NetFlow records. Subsequent analysis revealed that several Internet usage features like average packets per flow, peer-to-peer (octets, packets and duration), chat octets, mail (packets and duration), ftp duration, and remote file octets exhibit a statistically significant correlation with depressive symptoms. Additionally, Mann-Whitney U-tests revealed that average packets per flow, remote file octets, chat (octets, packets and duration) and flow duration entropy demonstrate statistically significant differences in the mean values across groups with and without depressive symptoms. To the best of our knowledge, this is the first study that associates depressive symptoms among college students with continuously collected real Internet data.

Raghavendra Kotikalapudi; Frances Montgomery; Donald Wunsch

2012-01-01T23:59:59.000Z

462

MESUR: USAGE-BASED METRICS OF SCHOLARLY IMPACT  

SciTech Connect

The evaluation of scholarly communication items is now largely a matter of expert opinion or metrics derived from citation data. Both approaches can fail to take into account the myriad of factors that shape scholarly impact. Usage data has emerged as a promising complement to existing methods o fassessment but the formal groundwork to reliably and validly apply usage-based metrics of schlolarly impact is lacking. The Andrew W. Mellon Foundation funded MESUR project constitutes a systematic effort to define, validate and cross-validate a range of usage-based metrics of schlolarly impact by creating a semantic model of the scholarly communication process. The constructed model will serve as the basis of a creating a large-scale semantic network that seamlessly relates citation, bibliographic and usage data from a variety of sources. A subsequent program that uses the established semantic network as a reference data set will determine the characteristics and semantics of a variety of usage-based metrics of schlolarly impact. This paper outlines the architecture and methodology adopted by the MESUR project and its future direction.

BOLLEN, JOHAN [Los Alamos National Laboratory; RODRIGUEZ, MARKO A. [Los Alamos National Laboratory; VAN DE SOMPEL, HERBERT [Los Alamos National Laboratory

2007-01-30T23:59:59.000Z

463

The use of web structure and content to identify subjectively interesting web usage patterns  

Science Conference Proceedings (OSTI)

The discipline of Web Usage Mining has grown rapidly in the past few years, despite the crash of the e-commerce boom of the late 1990s. Web Usage Mining is the application of data mining techniques to Web clickstream data in order to extract usage patterns. ... Keywords: Data mining, Web usage mining, World Wide Web

Robert Cooley

2003-05-01T23:59:59.000Z

464

Potentials and limits of secondary spectrum usage by CDMA base stations  

Science Conference Proceedings (OSTI)

With the progress of transmission technology and fast growing demand for ubiquitous high speed wireless services, it is clear that the pressure towards more flexibility in usage of limited spectrum will increase. With concept of spectrum sharing, in ... Keywords: primary exclusive region (PER), secondary spectrum usage, secondary usage allowable region (SAR), secondary usage prohibitive region (SPR)

Eun-Hee Shin; Dongwoo Kim

2009-01-01T23:59:59.000Z

465

A practical ontology for the large-scale modeling of scholarly artifacts and their usage  

Science Conference Proceedings (OSTI)

The large-scale analysis of scholarly artifact usage is constrained primarily by current practices in usage data archiving, privacy issues concerned with the dissemination of usage data, and the lack of a practical ontology for modeling the usage domain. ... Keywords: resource description framework and schema, semantic networks, web ontology language

Marko A. Rodriguez; Johan Bollen; Herbert Van de Sompel

2007-06-01T23:59:59.000Z

466

Assumptions to the Annual Energy Outlook 2000 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Key Assumptions Key Assumptions The historical input data used to develop the HEM version for the AEO2000 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2000 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and transportation sectors as inputs to the disaggregation algorithm that results in the direct fuel expenditure analysis. Household end-use and personal transportation service consumption are obtained by HEM from the NEMS Residential and Transportation Demand Modules. Household disposable income is adjusted with forecasts of total disposable income from the NEMS Macroeconomic Activity Module.

467

Appliance Standby Power and Energy Consumption in South African Households  

Open Energy Info (EERE)

Appliance Standby Power and Energy Consumption in South African Households Appliance Standby Power and Energy Consumption in South African Households Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Appliance Standby Power and Energy Consumption in South African Households Focus Area: Appliances & Equipment Topics: Policy Impacts Website: active.cput.ac.za/energy/web/DUE/DOCS/422/Paper%20-%20Shuma-Iwisi%20M. Equivalent URI: cleanenergysolutions.org/content/appliance-standby-power-and-energy-co Language: English Policies: Deployment Programs DeploymentPrograms: Technical Assistance A modified engineering model is proposed to estimate standby power and energy losses in households. The modified model accounts for the randomness of standby power and energy losses due to unpredicted user appliance operational behavior.

468

A Theoretical Basis for Household Energy Conservation UsingProduct...  

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

A Theoretical Basis for Household Energy Conservation Using Product-Integrated Feedback Speaker(s): Teddy McCalley Date: October 11, 2002 - 12:00pm Location: Bldg. 90 Seminar Host...

469

Household Preferences for Supporting Renewable Energy, and Barriers...  

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

Household Preferences for Supporting Renewable Energy, and Barriers to Green Power Demand Speaker(s): Ryan Wiser Date: May 9, 2002 - 12:00pm Location: Bldg. 90 Nearly 40% of the...

470

Energy Consumption of Refrigerators in Ghana - Outcomes of Household...  

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

Energy Consumption of Refrigerators in Ghana - Outcomes of Household Surveys Speaker(s): Essel Ben Hagan Date: July 12, 2007 - 12:00pm Location: 90-3122 Seminar HostPoint of...

471

Profiling energy use in households and office spaces  

Science Conference Proceedings (OSTI)

Energy consumption is largely studied in the context of different environments, such as domestic, corporate, industrial, and public sectors. In this paper, we discuss two environments, households and office spaces, where people have an especially ...

Salman Taherian; Marcelo Pias; George Coulouris; Jon Crowcroft

2010-04-01T23:59:59.000Z

472

Smoothing consumption across households and time : essays in development economics  

E-Print Network (OSTI)

This thesis studies two strategies that households may use to keep their consumption smooth in the face of fluctuations in income and expenses: credit (borrowing and savings) and insurance (state contingent transfers between ...

Kinnan, Cynthia Georgia

2010-01-01T23:59:59.000Z

473

Electric Power Systems Research 81 (2011) 20992107 Contents lists available at ScienceDirect  

E-Print Network (OSTI)

electricity usage. It is estimated that by 2020, about 12% of the world's electricity will be supplied by windElectric Power Systems Research 81 (2011) 2099­2107 Contents lists available at ScienceDirect Electric Power Systems Research journal homepage: www.elsevier.com/locate/epsr Short-term wind power

474

The Dynamics of Household Travel Time Expenditures and Car Ownership Decisions  

E-Print Network (OSTI)

or more of the others (say, car usage as a function of carnumberof workers, explains car usage, but not car ownership;locations imply higher car usage in terms of travel times

Golob, Thomas F.

1990-01-01T23:59:59.000Z

475

APS Guideline for Hand Tool and Portable Power Tool Usage  

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

Hand Tool and Portable Power Tool Usage Hand Tool and Portable Power Tool Usage Introduction CAT/XSD recognizes that the misuse and improper maintenance of hand tools and portable power tools cause a significant number of injuries to even "experienced" workers. Consequently, CAT/XSD has adopted the following policies and procedures to minimize the hazards associated with the use of such equipment at the APS. These guidelines apply to all use of hand tools and portable power tools by CAT/XSD personnel while performing maintenance or installation activities at the APS. Although CAT/XSD feels that most of the guidelines also apply to tool usage during experimental activities, CAT/XSD will not require that short-term users complete the training described below. Using Tools Safely If you have not had formal training in the use of common tools, either view

476

Ethanol Usage in Urban Public Transportation - Presentation of Results |  

Open Energy Info (EERE)

Ethanol Usage in Urban Public Transportation - Presentation of Results Ethanol Usage in Urban Public Transportation - Presentation of Results Jump to: navigation, search Tool Summary Name: Ethanol Usage in Urban Public Transportation - Presentation of Results Agency/Company /Organization: BioEthanol for Sustainable Transport Focus Area: Fuels & Efficiency Topics: Best Practices Website: cenbio.iee.usp.br/download/publicacoes/SAE_BEST_2010.pdf This paper presents the BioEthanol for Sustainable Transport (BEST) project in Brazil, its partners, and the results from the demonstration tests performed in field, as well as the proposals of public policies that were elaborated and are being implemented. The BEST project was implemented in Sao Paulo as well as eight other cities located in Europe and Asia. How to Use This Tool

477

Mining Software Usage with the Automatic Library Tracking Database (ALTD)  

Science Conference Proceedings (OSTI)

Tracking software usage is important for HPC centers, computer vendors, code developers and funding agencies to provide more efficient and targeted software support, and to forecast needs and guide HPC software effort towards the Exascale era. However, accurately tracking software usage on HPC systems has been a challenging task. In this paper, we present a tool called Automatic Library Tracking Database (ALTD) that has been developed and put in production on several Cray systems. The ALTD infrastructure prototype automatically and transparently stores information about libraries linked into an application at compilation time and also the executables launched in a batch job. We will illustrate the usage of libraries, compilers and third party software applications on a system managed by the National Institute for Computational Sciences.

Hadri, Bilel [ORNL; Fahey, Mark R [ORNL

2013-01-01T23:59:59.000Z

478

Transferring 2001 National Household Travel Survey  

Science Conference Proceedings (OSTI)

Policy makers rely on transportation statistics, including data on personal travel behavior, to formulate strategic transportation policies, and to improve the safety and efficiency of the U.S. transportation system. Data on personal travel trends are needed to examine the reliability, efficiency, capacity, and flexibility of the Nation's transportation system to meet current demands and to accommodate future demand. These data are also needed to assess the feasibility and efficiency of alternative congestion-mitigating technologies (e.g., high-speed rail, magnetically levitated trains, and intelligent vehicle and highway systems); to evaluate the merits of alternative transportation investment programs; and to assess the energy-use and air-quality impacts of various policies. To address these data needs, the U.S. Department of Transportation (USDOT) initiated an effort in 1969 to collect detailed data on personal travel. The 1969 survey was the first Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990, 1995, and 2001. Data on daily travel were collected in 1969, 1977, 1983, 1990 and 1995. In 2001, the survey was renamed the National Household Travel Survey (NHTS) and it collected both daily and long-distance trips. The 2001 survey was sponsored by three USDOT agencies: Federal Highway Administration (FHWA), Bureau of Transportation Statistics (BTS), and National Highway Traffic Safety Administration (NHTSA). The primary objective of the survey was to collect trip-based data on the nature and characteristics of personal travel so that the relationships between the characteristics of personal travel and the demographics of the traveler can be established. Commercial and institutional travel were not part of the survey. Due to the survey's design, data in the NHTS survey series were not recommended for estimating travel statistics for categories smaller than the combination of Census division (e.g., New England, Middle Atlantic, and Pacific), MSA size, and the availability of rail. Extrapolating NHTS data within small geographic areas could risk developing and subsequently using unreliable estimates. For example, if a planning agency in City X of State Y estimates travel rates and other travel characteristics based on survey data collected from NHTS sample households that were located in City X of State Y, then the agency could risk developing and using unreliable estimates for their planning process. Typically, this limitation significantly increases as the size of an area decreases. That said, the NHTS contains a wealth of information that could allow statistical inferences about small geographic areas, with a pre-determined level of statistical certainty. The question then becomes whether a method can be developed that integrates the NHTS data and other data to estimate key travel characteristics for small geographic areas such as Census tract and transportation analysis zone, and whether this method can outperform other, competing methods.

Hu, Patricia S [ORNL; Reuscher, Tim [ORNL; Schmoyer, Richard L [ORNL; Chin, Shih-Miao [ORNL

2007-05-01T23:59:59.000Z

479

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

E-Print Network (OSTI)

the period. The usage of electric lighting was estimatedelectric lighting, we first projected the level of electrification with income level and then projected the number of bulbs per household (usage

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

480

Source separation of household waste: A case study in China  

SciTech Connect

A pilot program concerning source separation of household waste was launched in Hangzhou, capital city of Zhejiang province, China. Detailed investigations on the composition and properties of household waste in the experimental communities revealed that high water content and high percentage of food waste are the main limiting factors in the recovery of recyclables, especially paper from household waste, and the main contributors to the high cost and low efficiency of waste disposal. On the basis of the investigation, a novel source separation method, according to which household waste was classified as food waste, dry waste and harmful waste, was proposed and performed in four selected communities. In addition, a corresponding household waste management system that involves all stakeholders, a recovery system and a mechanical dehydration system for food waste were constituted to promote source separation activity. Performances and the questionnaire survey results showed that the active support and investment of a real estate company and a community residential committee play important roles in enhancing public participation and awareness of the importance of waste source separation. In comparison with the conventional mixed collection and transportation system of household waste, the established source separation and management system is cost-effective. It could be extended to the entire city and used by other cities in China as a source of reference.

Zhuang Ying; Wu Songwei; Wang Yunlong [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China); Wu Weixiang [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China)], E-mail: weixiang@zju.edu.cn; Chen Yingxu [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China)

2008-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "household electricity usage" 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

Household waste disposal in Mekelle city, Northern Ethiopia  

SciTech Connect

In many cities of developing countries, such as Mekelle (Ethiopia), waste management is poor and solid wastes are dumped along roadsides and into open areas, endangering health and attracting vermin. The effects of demographic factors, economic and social status, waste and environmental attributes on household solid waste disposal are investigated using data from household survey. Household level data are then analyzed using multinomial logit estimation to determine the factors that affect household waste disposal decision making. Results show that demographic features such as age, education and household size have an insignificant impact over the choice of alternative waste disposal means, whereas the supply of waste facilities significantly affects waste disposal choice. Inadequate supply of waste containers and longer distance to these containers increase the probability of waste dumping in open areas and roadsides relative to the use of communal containers. Higher household income decreases the probability of using open areas and roadsides as waste destinations relative to communal containers. Measures to make the process of waste disposal less costly and ensuring well functioning institutional waste management would improve proper waste disposal.

Tadesse, Tewodros [Agricultural Economics and Rural Policy Group, Wageningen University, Hollandseweg 1 6706 KN Wageningen (Netherlands)], E-mail: tewodroslog@yahoo.com; Ruijs, Arjan [Environmental Economics and Natural Resources Group, Wageningen University, P.O. Box 8130, 6700 EW Wageningen (Netherlands); Hagos, Fitsum [International Water Management Institute (IWMI), Subregional Office for the Nile Basin and East Africa, P.O. Box 5689, Addis Ababa (Ethiopia)

2008-07-01T23:59:59.000Z

482

Ventilation Behavior and Household Characteristics in NewCalifornia Houses  

SciTech Connect

A survey was conducted to determine occupant use of windows and mechanical ventilation devices; barriers that inhibit their use; satisfaction with indoor air quality (IAQ); and the relationship between these factors. A questionnaire was mailed to a stratified random sample of 4,972 single-family detached homes built in 2003, and 1,448 responses were received. A convenience sample of 230 houses known to have mechanical ventilation systems resulted in another 67 completed interviews. Some results are: (1) Many houses are under-ventilated: depending on season, only 10-50% of houses meet the standard recommendation of 0.35 air changes per hour. (2) Local exhaust fans are under-utilized. For instance, about 30% of households rarely or never use their bathroom fan. (3) More than 95% of households report that indoor air quality is ''very'' or ''somewhat'' acceptable, although about 1/3 of households also report dustiness, dry air, or stagnant or humid air. (4) Except households where people cook several hours per week, there is no evidence that households with significant indoor pollutant sources get more ventilation. (5) Except households containing asthmatics, there is no evidence that health issues motivate ventilation behavior. (6) Security and energy saving are the two main reasons people close windows or keep them closed.

Price, Phillip N.; Sherman, Max H.

2006-02-01T23:59:59.000Z

483

Variable-response model of electricity demand by time of day: Results of a Wisconsin pricing experiment: Final report  

Science Conference Proceedings (OSTI)

Observationally alike households may differ in demand parameters and thus in economic quantities that are functions of those parameters. We have proposed a methodology for dealing with this variation. Estimation of both translog and CES versions of the model with data from the Wisconsin Electricity Pricing Experiment revealed considerable variation among households in time-of-day electricity consumption demand parameters for both summer and winter seasons and for several different definitions of the peak period. Observed household characteristics explained only a small share of total household differences, but permanent household differences dominated month-to-month variation in either expenditure shares or log consumption ratios in most cases. Permanent differences among households are important relative to total variation, including transitory month-to-month variation. We calculated various economic variables from the demand parameters, including the partial elasticity of substitution, compensated and uncompensated elasticities, and a measure of electricity expenditure under peak load pricing required to maintain the utility level under flat rate pricing relative to the flat rate expenditure. Because these are nonlinear functions of the household demand parameters, the mean parameter value over households with different demand parameters may be substantially different from the value of the function at mean values, under the representative household paradigm. For time-of-day electricity demand, variation among households is significant but small relative to mean parameter values. Therefore, controlling for the effect of household variation makes little difference in these mean calculations, but it does imply substantial variation among households in the welfare implications (and elasticities of response) of the introduction of time-of-day pricing. 25 refs., 12 tabs.

Lillard, L.

1987-06-01T23:59:59.000Z

484

Average U.S. residential summer 2013 electric bill expected to be ...  

U.S. Energy Information Administration (EIA)

The average U.S. household electric bill for June through August is expected to total $395, down 2.5% from last summer and the cheapest in four years.

485

Table CE3-10e. Electric Air-Conditioning Energy Expenditures in U ...  

U.S. Energy Information Administration (EIA)

Table CE3-10e. Electric Air-Conditioning Energy Expenditures in U.S. Households by Midwest Census Region, 2001 RSE Column Factor: Total U.S. Midwest Census Region

486

Table CE3-4c. Electric Air-Conditioning Energy Consumption in U.S ...  

U.S. Energy Information Administration (EIA)

Table CE3-4c. Electric Air-Conditioning Energy Consumption in U.S. Households by Type of Housing Unit, 2001 RSE Column Factor: Total Type of Housing Unit

487

Table CE3-1c. Electric Air-Conditioning Energy Consumption in U.S ...  

U.S. Energy Information Administration (EIA)

Table CE3-1c. Electric Air-Conditioning Energy Consumption in U.S. Households by Climate Zone, 2001 RSE Column Factor: Total Climate Zone1 RSE Row

488

THE APPLICATION OF A DATA MINING FRAMEWORK TO ENERGY USAGE PROFILING IN DOMESTIC RESIDENCES USING UK DATA  

E-Print Network (OSTI)

Abstract: This paper describes a method for defining representative load profiles for domestic electricity users in the UK. It considers bottom up and clustering methods and then details the research plans for implementing and improving existing framework approaches based on the overall usage profile. The work focuses on adapting and applying analysis framework approaches to UK energy data in order to determine the effectiveness of creating a few (single figures) archetypical users with the intention of improving on the current methods of determining usage profiles. The work is currently in progress and the paper details initial results using data collected in Milton Keynes around 1990. Various possible enhancements to the work are considered including a split based on temperature to reflect the varying UK weather conditions.

Ian Dent; Uwe Aickelin; Tom Rodden

2011-01-01T23:59:59.000Z

489

SYRIAN ARAB REPUBLIC MINISTRY OF ELECTRICITY  

E-Print Network (OSTI)

the energy efficiency improvements studies and facilitate the renewable energy usage in Syria1 SYRIAN ARAB REPUBLIC MINISTRY OF ELECTRICITY SUPPLY SIDE EFFICIENCY & ENERGY CONSERVATION & PLANNING PROJECT Identification of National Energy Policies and Energy Access in SYRIA March 15, 2005 #12

490

Traffic characterization and internet usage in rural Africa  

Science Conference Proceedings (OSTI)

While Internet connectivity has reached a significant part of the world's population, those living in rural areas of the developing world are still largely disconnected. Recent efforts have provided Internet connectivity to a growing number of remote ... Keywords: internet usage, interviews, rural networks

David L. Johnson; Veljko Pejovic; Elizabeth M. Belding; Gertjan van Stam

2011-03-01T23:59:59.000Z

491

Editorial Style Guide: Word List and General Usage  

Science Conference Proceedings (OSTI)

The EPRI "Editorial Style Guide," together with the Company's "Graphic Standards Guide," provides information for building a strong corporate identity in EPRI publications. Providing lists of frequently used terms, EPRI software, and chemical elements, plus examples of word usage, the style guide can help authors both develop text efficiently and economically and brand EPRI as an integrated, global science and technology company.

1998-08-17T23:59:59.000Z

492

Security Implications of Typical Grid Computing Usage Scenarios  

Science Conference Proceedings (OSTI)

Grid Computing consists of a collection of heterogeneous computers and resources spread across multiple administrative domains with the intent of providing users uniform access to these resources. There are many ways to access the resources of a Grid, ... Keywords: Global Grid Forum, Globus, Grid Computing, Legion, computer security, usage scenarios

Marty Humphrey; Mary R. Thompson

2002-07-01T23:59:59.000Z

493

Identifying and Testing the Inhibitors of Technology Usage Intentions  

Science Conference Proceedings (OSTI)

An important area of information systems (IS) research has been the identification of the individual-level beliefs that enable technology acceptance such as the usefulness, reliability, and flexibility of a system. This study posits the existence of ... Keywords: inhibitors, nonacceptance, technology rejection, usage intentions

Ronald T. Cenfetelli; Andrew Schwarz

2011-12-01T23:59:59.000Z

494

Exploiting Service Usage Information for Optimizing Server Resource Management  

Science Conference Proceedings (OSTI)

It is often difficult to tune the performance of modern component-based Internet services because: (1) component middleware are complex software systems that expose several independently tuned server resource management mechanisms; (2) session-oriented ... Keywords: Internet application, client behavior, component middleware, optimization, quality-of-service, server resource management, service usage information

Alexander Totok; Vijay Karamcheti

2011-07-01T23:59:59.000Z

495

Fuel bundle design for enhanced usage of plutonium fuel  

DOE Patents (OSTI)

A nuclear fuel bundle includes a square array of fuel rods each having a concentration of enriched uranium and plutonium. Each rod of an interior array of the rods also has a concentration of gadolinium. The interior array of rods is surrounded by an exterior array of rods void of gadolinium. By this design, usage of plutonium in the nuclear reactor is enhanced.

Reese, Anthony P. (San Jose, CA); Stachowski, Russell E. (Fremont, CA)

1995-01-01T23:59:59.000Z

496

Designation of facility usage categories for Hanford Site facilities  

SciTech Connect

This report summarizes the Hanford Site methodology used to ensure facility compliance with the natural phenomena design criteria set forth in the US Department of Energy Orders and guidance. The current Hanford Site methodology for Usage Category designation is based on an engineered feature's safety function and on the feature's assigned Safety Class. At the Hanford Site, Safety Class assignments are deterministic in nature and are based on teh consequences of failure, without regard to the likelihood of occurrence. The report also proposes a risk-based approach to Usage Category designation, which is being considered for future application at the Hanford Site. To establish a proper Usage Category designation, the safety analysis and engineering design processes must be coupled. This union produces a common understanding of the safety function(s) to be accomplished by the design feature(s) and a sound basis for the assignment of Usage Categories to the appropriate systems, structures, and components. 4 refs., 9 figs., 1 tab.

Woodrich, D.D.; Ellingson, D.R.; Scott, M.A.; Schade, A.R.

1991-10-01T23:59:59.000Z

497

Resource usage analysis for a functional language with exceptions  

Science Conference Proceedings (OSTI)

Igarashi and Kobayashi have proposed a general type system for checking whether resources such as files and memory are accessed in a valid manner. Their type system is, however, for call-by-value ?-calculus with resource primitives, and does not ... Keywords: effect system, exception, resource usage analysis, type inference, type system

Futoshi Iwama; Atsushi Igarashi; Naoki Kobayashi

2006-01-01T23:59:59.000Z

498

Determine Vehicle Usage and Refueling Trends to Minimize Greenhouse Gas  

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

Vehicle Usage and Refueling Trends to Minimize Greenhouse Vehicle Usage and Refueling Trends to Minimize Greenhouse Gas Emissions Determine Vehicle Usage and Refueling Trends to Minimize Greenhouse Gas Emissions October 7, 2013 - 11:42am Addthis YOU ARE HERE Step 2 Once a Federal agency has identified its most important mobile greenhouse gas (GHG) emission sources overall, it can work with individual sites to determine vehicle usage and refueling trends. Agencies can compare the results of this analysis to internal standards and requirements to identify GHG mitigation opportunities for assets that are underperforming or underutilized. Two examples of this type of analysis focus on: Alternative fuel consumption Vehicle utilization. Figure 1 - An image of a vertical, stacked bar chart titled 'Alternative Fuel Use in AFVs.' The frequency data axis is labeled 'Gallons of Gasoline Equivalent' with a scale of 0-1,400,000 in increments of 200,000. The stacked bar labeled 'CNG Dual Fuel Vehicles' shows CNG from 0-300,000 gallons and Gasoline from 300,000-800,000 gallons. The stacked bar labeled 'E-85 Flex Fuel Vehicles' shows E85 from 0-1,000,000 gallons and Gasoline from 1,000,000-1,250,000 gallons.

499

Household solid waste characteristics and management in Chittagong, Bangladesh  

Science Conference Proceedings (OSTI)

Solid waste management (SWM) is a multidimensional challenge faced by urban authorities, especially in developing countries like Bangladesh. We investigated per capita waste generation by residents, its composition, and the households' attitudes towards waste management at Rahman Nagar Residential Area, Chittagong, Bangladesh. The study involved a structured questionnaire and encompassed 75 households from five different socioeconomic groups (SEGs): low (LSEG), lower middle (LMSEG), middle (MSEG), upper middle (UMSEG) and high (HSEG). Wastes, collected from all of the groups of households, were segregated and weighed. Waste generation was 1.3 kg/household/day and 0.25 kg/person/day. Household solid waste (HSW) was comprised of nine categories of wastes with vegetable/food waste being the largest component (62%). Vegetable/food waste generation increased from the HSEG (47%) to the LSEG (88%). By weight, 66% of the waste was compostable in nature. The generation of HSW was positively correlated with family size (r{sub xy} = 0.236, p management initiative. Of the respondents, an impressive 44% were willing to pay US$0.3 to US$0.4 per month to waste collectors and it is recommended that service charge be based on the volume of waste generated by households. Almost a quarter (22.7%) of the respondents preferred 12-1 pm as the time period for their waste to be collected. This study adequately shows that household solid waste can be converted from burden to resource through segregation at the source, since people are aware of their role in this direction provided a mechanism to assist them in this pursuit exists and the burden is distributed according to the amount of waste generated.

Sujauddin, Mohammad [Institute of Forestry and Environmental Sciences, Chittagong University, Chittagong-4331 (Bangladesh)], E-mail: mohammad.sujauddin@gmail.com; Huda, S.M.S. [Institute of Forestry and Environmental Sciences, Chittagong University, Chittagong-4331 (Bangladesh); Hoque, A.T.M. Rafiqul [Institute of Forestry and Environmental Sciences, Chittagong University, Chittagong-4331 (Bangladesh); Laboratory of Ecology and Systematics (Plant Ecophysiology Section), Faculty of Science, Biology Division, University of the Ryukyus, Okinawa 903-0213 (Japan)

2008-07-01T23:59:59.000Z

500

Future Electricity Supplies MIT ENGINEERING SYSTEMS SYMPOSIUM (31 Mar 04, pg. 1) FUTURE ELECTRICITY SUPPLIES  

E-Print Network (OSTI)

and Europe have re- energized the debate over aging electricity and other infrastructures. Whether long. To these "common" challenges we must add now infrastructure security and long-term environmental stewardship bulbs, or household appliances. Energy "utilization" efficiency opportunities however offer great

de Weck, Olivier L.