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Note: This page contains sample records for the topic "demand ten end-use" 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.


1

China End-Use Energy Demand Modeling  

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

China End-Use Energy Demand Modeling China End-Use Energy Demand Modeling Speaker(s): Nan Zhou Date: October 8, 2009 (All day) Location: 90-3122 As a consequence of soaring energy demand due to the staggering pace of its economic growth, China overtook the United States in 2007 to become the world's biggest contributor to CO2 emissions (IEA, 2007). Since China is still in an early stage of industrialization and urbanization, economic development promises to keep China's energy demand growing strongly. Furthermore, China's reliance on fossil fuel is unlikely to change in the long term, and increased needs will only heighten concerns about energy security and climate change. In response, the Chinese government has developed a series of policies and targets aimed at improving energy efficiency, including both short-term targets and long-term strategic

2

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

Institute, “Curbing Global Energy Demand Growth: The Energyup Assessment of Energy Demand in India Transportationa profound effect on energy demand. Policy analysts wishing

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

3

Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity;  

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

7 End Uses of Fuel Consumption, 2006; 7 End Uses of Fuel Consumption, 2006; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Demand Residual and Natural Gas(c) LPG and Coke and Breeze) for Electricity(a) Fuel Oil Diesel Fuel(b) (billion NGL(d) (million End Use (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) Total United States TOTAL FUEL CONSUMPTION 977,338 40 22 5,357 21 46 Indirect Uses-Boiler Fuel 24,584 21 4 2,059 2 25 Conventional Boiler Use 24,584 11 3 1,245 2 6 CHP and/or Cogeneration Process 0 10 1 814 * 19 Direct Uses-Total Process 773,574 10 9 2,709 10 19 Process Heating

4

Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity;  

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

Next MECS will be conducted in 2010 Table 5.8 End Uses of Fuel Consumption, 2006; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal Net Demand Residual and LPG and (excluding Coal End Use for Electricity(a) Fuel Oil Diesel Fuel(b) Natural Gas(c) NGL(d) Coke and Breeze) Total United States TOTAL FUEL CONSUMPTION 3,335 251 129 5,512 79 1,016 Indirect Uses-Boiler Fuel 84 133 23 2,119 8 547 Conventional Boiler Use 84 71 17 1,281 8 129 CHP and/or Cogeneration Process 0 62 6 838 1 417 Direct Uses-Total Process 2,639 62 52 2,788 39 412 Process Heating 379 59 19 2,487 32 345 Process Cooling and Refrigeration

5

Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity;  

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

4 End Uses of Fuel Consumption, 2006; 4 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal NAICS Net Demand Residual and LPG and (excluding Coal Code(a) End Use for Electricity(b) Fuel Oil Diesel Fuel(c) Natural Gas(d) NGL(e) Coke and Breeze) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 3,335 251 129 5,512 79 1,016 Indirect Uses-Boiler Fuel 84 133 23 2,119 8 547 Conventional Boiler Use 84 71 17 1,281 8 129 CHP and/or Cogeneration Process 0 62 6 838 1 417 Direct Uses-Total Process 2,639 62 52 2,788 39 412 Process Heating 379 59 19 2,487 32 345 Process Cooling and Refrigeration

6

Analysis of PG&E`s residential end-use metered data to improve electricity demand forecasts -- final report  

SciTech Connect

This report summarizes findings from a unique project to improve the end-use electricity load shape and peak demand forecasts made by the Pacific Gas and Electric Company (PG&E) and the California Energy Commission (CEC). First, the direct incorporation of end-use metered data into electricity demand forecasting models is a new approach that has only been made possible by recent end-use metering projects. Second, and perhaps more importantly, the joint-sponsorship of this analysis has led to the development of consistent sets of forecasting model inputs. That is, the ability to use a common data base and similar data treatment conventions for some of the forecasting inputs frees forecasters to concentrate on those differences (between their competing forecasts) that stem from real differences of opinion, rather than differences that can be readily resolved with better data. The focus of the analysis is residential space cooling, which represents a large and growing demand in the PG&E service territory. Using five years of end-use metered, central air conditioner data collected by PG&E from over 300 residences, we developed consistent sets of new inputs for both PG&E`s and CEC`s end-use load shape forecasting models. We compared the performance of the new inputs both to the inputs previously used by PG&E and CEC, and to a second set of new inputs developed to take advantage of a recently added modeling option to the forecasting model. The testing criteria included ability to forecast total daily energy use, daily peak demand, and demand at 4 P.M. (the most frequent hour of PG&E`s system peak demand). We also tested the new inputs with the weather data used by PG&E and CEC in preparing their forecasts.

Eto, J.H.; Moezzi, M.M.

1993-12-01T23:59:59.000Z

7

Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity;  

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

Next MECS will be conducted in 2010 Next MECS will be conducted in 2010 Table 5.3 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Demand Residual and Natural Gas(d) LPG and Coke and Breeze) NAICS for Electricity(b) Fuel Oil Diesel Fuel(c) (billion NGL(e) (million Code(a) End Use (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 977,338 40 22 5,357 21 46 Indirect Uses-Boiler Fuel 24,584 21 4 2,059 2 25 Conventional Boiler Use 24,584 11 3

8

Renewable Electricity Futures Study. Volume 3: End-Use Electricity Demand  

SciTech Connect

The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).

Hostick, D.; Belzer, D.B.; Hadley, S.W.; Markel, T.; Marnay, C.; Kintner-Meyer, M.

2012-06-01T23:59:59.000Z

9

Analysis of Michigan's demand-side electricity resources in the residential sector: Volume 3, End-use studies: Revised final report  

SciTech Connect

This volume of the ''Analysis of Michigan's Demand-Side Electricity Resources in the Residential Sector'' contains end-use studies on various household appliances including: refrigerators, freezers, lighting systems, water heaters, air conditioners, space heaters, and heat pumps. (JEF)

Krause, F.; Brown, J.; Connell, D.; DuPont, P.; Greely, K.; Meal, M.; Meier, A.; Mills, E.; Nordman, B.

1988-04-01T23:59:59.000Z

10

" Row: End Uses within NAICS Codes;"  

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

End Uses within NAICS Codes;" " Column: Energy Sources, including Net Demand for Electricity;" " Unit: Trillion Btu." " "," ",," ","Distillate"," "," ",," " " "," ",,,"Fuel...

11

" Row: End Uses;"  

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

8 End Uses of Fuel Consumption, 2002;" 8 End Uses of Fuel Consumption, 2002;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Demand for Electricity;" " Unit: Trillion Btu." " ",," ","Distillate"," "," ",," " " ","Net Demand",,"Fuel Oil",,,"Coal","RSE" " ","for ","Residual","and","Natural ","LPG and","(excluding Coal","Row" "End Use","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Gas(c)","NGL(d)","Coke and Breeze)","Factors"

12

" Row: End Uses;"  

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

3. End Uses of Fuel Consumption, 1998;" 3. End Uses of Fuel Consumption, 1998;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Demand for Electricity;" " Unit: Physical Units or Btu." " ",," ","Distillate"," "," ","Coal"," " " ",,,"Fuel Oil",,,"(excluding Coal" " ","Net Demand","Residual","and","Natural Gas(c)","LPG and","Coke and Breeze)","RSE" " ","for Electricity(a)","Fuel Oil","Diesel Fuel(b)","(billion","NGL(d)","(million","Row"

13

" Row: End Uses;"  

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

8 End Uses of Fuel Consumption, 2010;" 8 End Uses of Fuel Consumption, 2010;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Demand for Electricity;" " Unit: Trillion Btu." ,,,"Distillate" ,,,"Fuel Oil",,,"Coal" ,"Net Demand","Residual","and",,"LPG and","(excluding Coal" "End Use","for Electricity(a)","Fuel Oil","Diesel Fuel(b)","Natural Gas(c)","NGL(d)","Coke and Breeze)" ,"Total United States" "TOTAL FUEL CONSUMPTION",2886,79,130,5211,69,868

14

" Row: End Uses;"  

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

7 End Uses of Fuel Consumption, 2006;" 7 End Uses of Fuel Consumption, 2006;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Demand for Electricity;" " Unit: Physical Units or Btu." ,,,"Distillate",,,"Coal" ,,,"Fuel Oil",,,"(excluding Coal" ,"Net Demand","Residual","and","Natural Gas(c)","LPG and","Coke and Breeze)" ,"for Electricity(a)","Fuel Oil","Diesel Fuel(b)","(billion","NGL(d)","(million" "End Use","(million kWh)","(million bbl)","(million bbl)","cu ft)","(million bbl)","short tons)"

15

Table 5.3 End Uses of Fuel Consumption, 2010;  

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

Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Demand...

16

" Row: End Uses;"  

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

","LPG and","(excluding Coal","RSE" " ","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Gas(c)","NGL(d)","Coke and Breeze)","Row" "End Use","(million kWh)","(million...

17

" Row: End Uses within NAICS Codes;"  

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

4 End Uses of Fuel Consumption, 2010;" 4 End Uses of Fuel Consumption, 2010;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Demand for Electricity;" " Unit: Trillion Btu." " "," ",," ","Distillate"," "," " " "," ",,,"Fuel Oil",,,"Coal" "NAICS"," ","Net Demand","Residual","and",,"LPG and","(excluding Coal" "Code(a)","End Use","for Electricity(b)","Fuel Oil","Diesel Fuel(c)","Natural Gas(d)","NGL(e)","Coke and Breeze)"

18

" Row: End Uses within NAICS Codes;"  

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

4 End Uses of Fuel Consumption, 2006;" 4 End Uses of Fuel Consumption, 2006;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Demand for Electricity;" " Unit: Trillion Btu." " "," ",," ","Distillate"," "," " " "," ",,,"Fuel Oil",,,"Coal" "NAICS"," ","Net Demand","Residual","and",,"LPG and","(excluding Coal" "Code(a)","End Use","for Electricity(b)","Fuel Oil","Diesel Fuel(c)","Natural Gas(d)","NGL(e)","Coke and Breeze)"

19

" Row: End Uses within NAICS Codes;"  

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

4 End Uses of Fuel Consumption, 2002;" 4 End Uses of Fuel Consumption, 2002;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Demand for Electricity;" " Unit: Trillion Btu." " "," ",," ","Distillate"," "," ",," " " "," ","Net Demand",,"Fuel Oil",,,"Coal","RSE" "NAICS"," ","for ","Residual","and","Natural ","LPG and","(excluding Coal","Row" "Code(a)","End Use","Electricity(b)","Fuel Oil","Diesel Fuel(c)","Gas(d)","NGL(e)","Coke and Breeze)","Factors"

20

" Row: End Uses within NAICS Codes;"  

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

3 End Uses of Fuel Consumption, 2010;" 3 End Uses of Fuel Consumption, 2010;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Demand for Electricity;" " Unit: Physical Units or Btu." " "," ",," ","Distillate"," "," ","Coal" " "," ",,,"Fuel Oil",,,"(excluding Coal" " "," ","Net Demand","Residual","and","Natural Gas(d)","LPG and","Coke and Breeze)" "NAICS"," ","for Electricity(b)","Fuel Oil","Diesel Fuel(c)","(billion","NGL(e)","(million"

Note: This page contains sample records for the topic "demand ten end-use" 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

" Row: End Uses within NAICS Codes;"  

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

3. End Uses of Fuel Consumption, 1998;" 3. End Uses of Fuel Consumption, 1998;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Demand for Electricity;" " Unit: Physical Units or Btu." " "," ",," ","Distillate"," "," ","Coal"," " " "," ",,,"Fuel Oil",,,"(excluding Coal" " "," ","Net Demand","Residual","and","Natural Gas(d)","LPG and","Coke and Breeze)","RSE" "NAICS"," ","for Electricity(b)","Fuel Oil","Diesel Fuel(c)","(billion","NGL(e)","(million","Row"

22

" Row: End Uses within NAICS Codes;"  

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

3 End Uses of Fuel Consumption, 2006;" 3 End Uses of Fuel Consumption, 2006;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Demand for Electricity;" " Unit: Physical Units or Btu." " "," ",," ","Distillate"," "," ","Coal" " "," ",,,"Fuel Oil",,,"(excluding Coal" " "," ","Net Demand","Residual","and","Natural Gas(d)","LPG and","Coke and Breeze)" "NAICS"," ","for Electricity(b)","Fuel Oil","Diesel Fuel(c)","(billion","NGL(e)","(million"

23

" Row: End Uses within NAICS Codes;"  

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

3 End Uses of Fuel Consumption, 2002;" 3 End Uses of Fuel Consumption, 2002;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Demand for Electricity;" " Unit: Physical Units or Btu." " "," ",," ","Distillate"," "," ",," " " "," ","Net Demand",,"Fuel Oil",,,"Coal" " "," ","for ","Residual","and","Natural ","LPG and","(excluding Coal","RSE" "NAICS"," ","Electricity(b)","Fuel Oil","Diesel Fuel(c)","Gas(d)","NGL(e)","Coke and Breeze)","Row"

24

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

4 4 The commercial module forecasts consumption by fuel 15 at the Census division level using prices from the NEMS energy supply modules, and macroeconomic variables from the NEMS Macroeconomic Activity Module (MAM), as well as external data sources (technology characterizations, for example). Energy demands are forecast for ten end-use services 16 for eleven building categories 17 in each of the nine Census divisions (see Figure 5). The model begins by developing forecasts of floorspace for the 99 building category and Census division combinations. Next, the ten end-use service demands required for the projected floorspace are developed. The electricity generation and water and space heating supplied by distributed generation and combined heat and power technologies are projected. Technologies are then

25

End Use and Fuel Certification  

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

Breakout Session 2: Frontiers and Horizons Session 2–B: End Use and Fuel Certification John Eichberger, Vice President of Government Relations, National Association for Convenience Stores

26

Energy End-Use Intensities in Commercial Buildings 1989 -- Executive  

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

9 Energy End-Use Intensities > Executive Summary 9 Energy End-Use Intensities > Executive Summary Executive Summary Energy End Uses Ranked by Energy Consumption, 1989 Energy End Uses Ranked by Energy Consumption, 1989 Source: Energy Information Administration, Office of Energy Markets and End Use, Forms EIA-871A through F of the 1989 Commercial Buildings Energy Consumption Survey. divider line The demand for energy in U.S. stores, offices, schools, hospitals, and other commercial buildings has been increasing. This report examines energy intensities in commercial buildings for nine end uses: space heating, cooling, ventilation, lighting, water heating, cooking, refrigeration, office equipment, and "other." The objective of this analysis was to increase understanding of how energy is used in commercial buildings and to identify targets for greater energy efficiency which could moderate future growth in demand.

27

Table 5.7 End Uses of Fuel Consumption, 2010;  

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

7 End Uses of Fuel Consumption, 2010; 7 End Uses of Fuel Consumption, 2010; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Demand Residual and Natural Gas(c) LPG and Coke and Breeze) for Electricity(a) Fuel Oil Diesel Fuel(b) (billion NGL(d) (million End Use (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) Total United States TOTAL FUEL CONSUMPTION 845,727 13 22 5,064 18 39 Indirect Uses-Boiler Fuel 12,979 7 3 2,074 3 26 Conventional Boiler Use 12,979 3 1 712 1 3 CHP and/or Cogeneration Process -- 4 3 1,362 2 23 Direct Uses-Total Process 675,152 4 9 2,549 7 13 Process Heating

28

Table 5.4 End Uses of Fuel Consumption, 2010;  

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

4 End Uses of Fuel Consumption, 2010; 4 End Uses of Fuel Consumption, 2010; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal NAICS Net Demand Residual and LPG and (excluding Coal Code(a) End Use for Electricity(b) Fuel Oil Diesel Fuel(c) Natural Gas(d) NGL(e) Coke and Breeze) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 2,886 79 130 5,211 69 868 Indirect Uses-Boiler Fuel 44 46 19 2,134 10 572 Conventional Boiler Use 44 20 4 733 3 72 CHP and/or Cogeneration Process -- 26 15 1,401 7 500 Direct Uses-Total Process 2,304 26 54 2,623 29 289 Process Heating 318 25 14 2,362 24 280 Process Cooling and Refrigeration

29

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

8 Table 3. Electric and Diesel Pump Characteristics andhectare by fuel type (electric or diesel pump) in number perTable 3. Electric and Diesel Pump Characteristics and

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

30

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

rural, k=Kerosene m=rural, k=biogas m =urban, k=LPG m=urban,k=LPG k=wood k=kerosene k=biogas k=electricity k=electricity

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

31

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

for cooking and lighting. Biomass energy consumption willused in an economy, biomass energy consumption is certainlyby a large share of biomass energy use representing 50% of

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

32

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

an estimated total energy consumption of 19 GWh (0.07PJ),to 28% in 2005. Total energy consumption in 2020 in thecan have similar total energy consumption but produce very

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

33

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

Efficiency in Electricity Consumption", HWWA Discussionelectricity includes electricity consumption plus thedistribution. Total electricity consumption represents 1,654

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

34

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

10. Final and Primary Energy Consumption in the Industry35 Figure 16. Primary Energy Consumption byby end users while primary energy consumption includes final

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

35

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

s=retail k=electricity, s=private office k=electricity, s==private office s=gov office s=hotel s=other k=electricity k

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

36

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

5% of its reserve is coking coal used by the steel industry.imports around 70% of coking coal annually. More recently,

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

37

,"Colorado Natural Gas Consumption by End Use"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Consumption by End Use",6,"Monthly","112014","1151989" ,"Release...

38

Alternative Strategies for Low Pressure End Uses  

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

This tip sheet outlines alternative strategies for low-pressure end uses as a pathway to reduced compressed air energy costs.

39

,"California Natural Gas Consumption by End Use"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Consumption by End Use",11,"Annual",2013,"6301967" ,"Release...

40

End-use taxes: Current EIA practices  

SciTech Connect

There are inconsistencies in the EIA published end-use price data with respect to Federal, state, and local government sales and excise taxes; some publications include end-use taxes and others do not. The reason for including these taxes in end-use energy prices is to provide consistent and accurate information on the total cost of energy purchased by the final consumer. Preliminary estimates are made of the effect on prices (bias) reported in SEPER (State Energy Price and Expenditure Report) resulting from the inconsistent treatment of taxes. EIA has undertaken several actions to enhance the reporting of end-use energy prices.

Not Available

1994-08-17T23:59:59.000Z

Note: This page contains sample records for the topic "demand ten end-use" 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

Energy End-Use Intensities in Commercial Buildings1992 -- Overview/End-Use  

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

> Overview > Overview 1992 Energy End-Use Intensities Overview Energy Consumption by End Use, 1992 Figure on Energy Consumption By End Use, 1992 Source: Energy Information Administration, Office of Energy Markets and End Use, Forms EIA-871A through F of the 1992 Commercial Buildings Energy Consumption Survey. End-Use Estimation Methodology The end-use estimates had two main sources: (1) survey data collected by the Commercial Buildings Energy Consumption Survey (CBECS) and (2) building energy simulations provided by the Facility Energy Decision Screening (FEDS) system. The CBECS provided data on building characteristics and total energy consumption (i.e., for all end uses) for a national sample of commercial buildings. Using data collected by the CBECS, the FEDS engineering modules were used to produce estimates of energy consumption by end use. The FEDS engineering estimates were then statistically adjusted to match the CBECS total energy consumption.

42

Metering Campaign on All Cooking End-Uses in 100 Households  

Science Journals Connector (OSTI)

This paper presents the findings of an experimental study performed in 100 French households on the end-use power demand and energy consumption of domestic appliances focusing on cooking appliances [1].

Olivier Sidler

2001-01-01T23:59:59.000Z

43

Calculation method for electricity end-use for residential lighting  

Science Journals Connector (OSTI)

Abstract Knowledge of the electricity demand for different electrical appliances in households is very important in the work to reduce electricity use in households. Metering of end-uses is expensive and time consuming and therefore other methods for calculation of end-use electricity can be very useful. This paper presents a method to calculate the electricity used for lighting in households based on regression analysis of daily electricity consumption, out-door temperatures and the length of daylight at the same time and location. The method is illustrated with analyses of 45 Norwegian households. The electricity use for lighting in an average Norwegian household is calculated to 1050 kWh/year or 6% of total electricity use. The results are comparable to metering results of lighting in other studies in the Nordic countries. The methodology can also be used to compensate for the seasonal effect when metering electricity for lighting less than a year. When smart meters are more commonly available, the possible adaption of this method will increase, and the need for end-use demand calculations will still be present.

Eva Rosenberg

2014-01-01T23:59:59.000Z

44

Energy end-use intensities in commercial buildings  

SciTech Connect

This report examines energy intensities in commercial buildings for nine end uses: space heating, cooling, ventilation, lighting, water heating, cooking, refrigeration, office equipment, and other. The objective of this analysis was to increase understanding of how energy is used in commercial buildings and to identify targets for greater energy efficiency which could moderate future growth in demand. The source of data for the analysis is the 1989 Commercial Buildings Energy Consumption survey (CBECS), which collected detailed data on energy-related characteristics and energy consumption for a nationally representative sample of approximately 6,000 commercial buildings. The analysis used 1989 CBECS data because the 1992 CBECS data were not yet available at the time the study was initiated. The CBECS data were fed into the Facility Energy Decision Screening (FEDS) system, a building energy simulation program developed by the US Department of Energy`s Pacific Northwest Laboratory, to derive engineering estimates of end-use consumption for each building in the sample. The FEDS estimates were then statistically adjusted to match the total energy consumption for each building. This is the Energy Information Administration`s (EIA) first report on energy end-use consumption in commercial buildings. This report is part of an effort to address customer requests for more information on how energy is used in buildings, which was an overall theme of the 1992 user needs study. The end-use data presented in this report were not available for publication in Commercial Buildings Energy Consumption and Expenditures 1989 (DOE/EIA-0318(89), Washington, DC, April 1992). However, subsequent reports on end-use energy consumption will be part of the Commercial Buildings Energy Consumption and Expenditures series, beginning with a 1992 data report to be published in early 1995.

Not Available

1994-09-01T23:59:59.000Z

45

Healthcare Energy End-Use Monitoring  

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

This report describes the NREL partnership with two hospitals (MGH and SUNY UMU) to collect data on the energy used for multiple thermal and electrical end-use categories, which can be used to more effectively prioritize and refine the scope of investments in new metering and energy audits.

46

Office Buildings - End-Use Equipment  

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

End-Use Equipment End-Use Equipment The types of space heating equipment used in office buildings were similar to those of the commercial buildings sector as a whole (Table 8 and Figure 5). Furnaces were most used followed by packaged heating systems. Individual space heaters were third-most used but were primarily used to supplement the building's main heating system. Boilers and district heat systems were more often used in larger buildings. Table 8. Types of Heating Equipment Used in Office Buildings, 2003 Number of Buildings (thousand) Total Floorspace (million square feet) All Buildings* All Office Buildings All Buildings* All Office Buildings All Buildings 4,645 824 64,783 12,208 All Buildings with Space Heating 3,982 802 60,028 11,929 Heating Equipment (more than one may apply)

47

Biomass Resource Allocation among Competing End Uses  

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

Biomass Resource Allocation Biomass Resource Allocation among Competing End Uses Emily Newes, Brian Bush, Daniel Inman, Yolanda Lin, Trieu Mai, Andrew Martinez, David Mulcahy, Walter Short, Travis Simpkins, and Caroline Uriarte National Renewable Energy Laboratory Corey Peck Lexidyne, LLC Technical Report NREL/TP-6A20-54217 May 2012 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. National Renewable Energy Laboratory 15013 Denver West Parkway Golden, Colorado 80401 303-275-3000 * www.nrel.gov Contract No. DE-AC36-08GO28308 Biomass Resource Allocation among Competing End Uses Emily Newes, Brian Bush, Daniel Inman,

48

Residential Lighting End-Use Consumption  

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

The U.S. DOE Residential Lighting End-Use Consumption Study aims to improve the understanding of lighting energy usage in U.S. residential dwellings using a regional estimation framework. The framework allows for the estimation of lamp usage and energy consumption 1) nationally and by region of the United States, 2) by certain household characteristics, 3) by location within the home, 4) by certain lamp characteristics, and 5) by certain categorical cross-classifications.

49

Healthcare Energy End-Use Monitoring  

SciTech Connect

NREL partnered with two hospitals (MGH and SUNY UMU) to collect data on the energy used for multiple thermal and electrical end-use categories, including preheat, heating, and reheat; humidification; service water heating; cooling; fans; pumps; lighting; and select plug and process loads. Additional data from medical office buildings were provided for an analysis focused on plug loads. Facility managers, energy managers, and engineers in the healthcare sector will be able to use these results to more effectively prioritize and refine the scope of investments in new metering and energy audits.

Sheppy, M.; Pless, S.; Kung, F.

2014-08-01T23:59:59.000Z

50

Energy End-Use Intensities in Commercial Buildings 1995 - Index...  

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

1995 End-Use Data 1995 End-Use Data Overview Tables National estimates of energy consumption by fuel (electricity and natural gas) and end use (heating, cooling, lighting, etc.)...

51

Energy End-Use Intensities in Commercial Buildings 1992 - Index...  

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

2 Energy End-Use Intensities 1992 Energy End-Use Intensities Overview Tables National estimates of energy consumption by fuel (electricity and natural gas) and end use (heating,...

52

Realizing Building End-Use Efficiency with Ermerging Technologies  

Office of Energy Efficiency and Renewable Energy (EERE)

Information about the implementation of emerging technologies to maximize end-use efficiency in buildings.

53

Energy End-Use Intensities in Commercial Buildings 1992  

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

Overview > Tables Overview > Tables 1992 Energy End-Use Intensities Tables Energy Consumption by End Use, 1992 Figure on Energy Consumption By End Use, 1992 Source: Energy Information Administration, Office of Energy Markets and End Use, Forms EIA-871A through F of the 1992 Commercial Buildings Energy Consumption Survey. divider line To View and/or Print Reports (requires Adobe Acrobat Reader) - Download Adobe Acrobat Reader If you experience any difficulties, visit our Technical Frequently Asked Questions. divider line Tables - (file size 31,655 bytes), pages 6. - requires Adobe Acrobat Reader Consumption of All Major Fuels by End Uses, 1992 Energy End-Use Intensities for All Major Fuels, 1992 Consumption of Electricity by End Uses, 1992 Energy End-Use Intensities for Electricity, 1992

54

Healthcare Energy: Using End-Use Data to Inform Decisions  

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

The relative magnitude of the energy consumption of different end uses can be a starting point for prioritizing energy investments and action, whether the scope under consideration involves new metering, targeted energy audits, or end-use equipment upgrades.

55

" Row: End Uses within NAICS Codes;"  

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

2 End Uses of Fuel Consumption, 2006;" 2 End Uses of Fuel Consumption, 2006;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Electricity;" " Unit: Trillion Btu." ,,,,,"Distillate" ,,,,,"Fuel Oil",,,"Coal" "NAICS",,,"Net","Residual","and",,"LPG and","(excluding Coal" "Code(a)","End Use","Total","Electricity(b)","Fuel Oil","Diesel Fuel(c)","Natural Gas(d)","NGL(e)","Coke and Breeze)","Other(f)" ,,"Total United States"

56

" Row: End Uses within NAICS Codes;"  

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

2 End Uses of Fuel Consumption, 2002;" 2 End Uses of Fuel Consumption, 2002;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Electricity;" " Unit: Trillion Btu." " "," "," ",," ","Distillate"," "," ",," "," " " "," ",,,,"Fuel Oil",,,"Coal",,"RSE" "NAICS"," "," ","Net","Residual","and","Natural ","LPG and","(excluding Coal"," ","Row" "Code(a)","End Use","Total","Electricity(b)","Fuel Oil","Diesel Fuel(c)","Gas(d)","NGL(e)","Coke and Breeze)","Other(f)","Factors"

57

United States Industrial Sector Energy End Use Analysis  

E-Print Network (OSTI)

natural gas, petroleum, coal, steam, and biomass/byproducts, respectively – disaggregated by end-use for each of the NAICS

Shehabi, Arman

2014-01-01T23:59:59.000Z

58

" Row: End Uses within NAICS Codes;"  

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

2. End Uses of Fuel Consumption, 1998;" 2. End Uses of Fuel Consumption, 1998;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Electricity;" " Unit: Trillion Btu." " "," "," ",," ","Distillate"," "," ",," "," " " "," ",,,,"Fuel Oil",,,"Coal",,"RSE" "NAICS"," "," ","Net","Residual","and",,"LPG and","(excluding Coal"," ","Row" "Code(a)","End Use","Total","Electricity(b)","Fuel Oil","Diesel Fuel(c)","Natural Gas(d)","NGL(e)","Coke and Breeze)","Other(f)","Factors"

59

" Row: End Uses within NAICS Codes;"  

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

2 End Uses of Fuel Consumption, 2010;" 2 End Uses of Fuel Consumption, 2010;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Electricity;" " Unit: Trillion Btu." ,,,,,"Distillate" ,,,,,"Fuel Oil",,,"Coal" "NAICS",,,"Net","Residual","and",,"LPG and","(excluding Coal" "Code(a)","End Use","Total","Electricity(b)","Fuel Oil","Diesel Fuel(c)","Natural Gas(d)","NGL(e)","Coke and Breeze)","Other(f)" ,,"Total United States"

60

" Row: End Uses within NAICS Codes;"  

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

1. End Uses of Fuel Consumption, 1998;" 1. End Uses of Fuel Consumption, 1998;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Electricity;" " Unit: Physical Units or Btu." " "," "," ",," ","Distillate"," "," ","Coal"," "," " " "," ",,,,"Fuel Oil",,,"(excluding Coal" " "," "," ","Net","Residual","and","Natural Gas(d)","LPG and","Coke and Breeze)"," ","RSE"

Note: This page contains sample records for the topic "demand ten end-use" 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

A new approach to estimate commercial sector end-use load shapes and energy use intensities  

SciTech Connect

We discuss the application of an end-use load shape estimation technique to develop annual energy use intensities (EUIs) and hourly end-use load shapes (LSs) for commercial buildings in the Pacific Gas and Electric Company (PG&E) service territory. Results will update inputs for the commercial sector energy and peak demand forecasting models used by PG&E and the California Energy Commission (CEC). EUIs were estimated for 11 building types, up to 10 end uses, 3 fuel types, 2 building vintages, and up to 5 climate regions. The integrated methodology consists of two major parts. The first part is the reconciliation of initial end-use load-shape estimates with measured whole-building load data to produce intermediate EUIs and load shapes, using LBL`s End-use Disaggregation Algorithm, EDA. EDA is a deterministic hourly algorithm that relies on the observed characteristics of the measured hourly whole-building electricity use and disaggregates it into major end-use components. The end-use EUIs developed through the EDA procedure represent a snap-shot of electricity use by building type and end-use for two regions of the PG&E service territory, for the year that disaggregation is performed. In the second part of the methodology, we adjust the EUIs for direct application to forecasting models based on factors such as climatic impacts on space-conditioning EUIs, fuel saturation effects, building and equipment vintage, and price impacts. Core data for the project are detailed on-site surveys for about 800 buildings, mail surveys ({approximately}6000), load research data for over 1000 accounts, and hourly weather data for five climate regions.

Akbari, H.; Eto, J.; Konopacki, S.; Afzal, A.; Heinemeier, K.; Rainer, L.

1994-08-01T23:59:59.000Z

62

1999 Commercial Buildings Characteristics--Energy Sources and End Uses  

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

Energy Sources and End Uses Energy Sources and End Uses Topics: Energy Sources and End Uses End-Use Equipment Conservation Features and Practices Energy Sources and End Uses CBECS collects information that is used to answer questions about the use of energy in the commercial buildings sector. Questions such as: What kind of energy sources are used? What is energy used for? and What kinds of equipment use energy? Energy Sources Nearly all commercial buildings used at least one source of energy for some end use (Figure 1). Electricity was the most commonly used energy source in commercial buildings (94 percent of buildings comprising 98 percent of commercial floorspace). More than half of commercial buildings (57 percent) and two-thirds of commercial floorspace (68 percent) were served by natural gas. Three sources-fuel oil, district heat, and district chilled water-when used, were used more often in larger buildings.

63

" Row: End Uses within NAICS Codes;"  

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

1 End Uses of Fuel Consumption, 2002;" 1 End Uses of Fuel Consumption, 2002;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Electricity;" " Unit: Physical Units or Btu." " "," "," ",," ","Distillate"," "," ",," "," " " "," ",,,,"Fuel Oil",,,"Coal" " "," "," ","Net","Residual","and","Natural ","LPG and","(excluding Coal"," ","RSE" "NAICS"," ","Total","Electricity(b)","Fuel Oil","Diesel Fuel(c)","Gas(d)","NGL(e)","Coke and Breeze)","Other(f)","Row"

64

" Row: End Uses within NAICS Codes;"  

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

1 End Uses of Fuel Consumption, 2006;" 1 End Uses of Fuel Consumption, 2006;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Electricity;" " Unit: Physical Units or Btu." ,,,,,"Distillate",,,"Coal" ,,,,,"Fuel Oil",,,"(excluding Coal" ,,,"Net","Residual","and","Natural Gas(d)","LPG and","Coke and Breeze)" "NAICS",,"Total","Electricity(b)","Fuel Oil","Diesel Fuel(c)","(billion","NGL(e)","(million","Other(f)" "Code(a)","End Use","(trillion Btu)","(million kWh)","(million bbl)","(million bbl)","cu ft)","(million bbl)","short tons)","(trillion Btu)"

65

" Row: End Uses within NAICS Codes;"  

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

1 End Uses of Fuel Consumption, 2010;" 1 End Uses of Fuel Consumption, 2010;" " Level: National Data; " " Row: End Uses within NAICS Codes;" " Column: Energy Sources, including Net Electricity;" " Unit: Physical Units or Btu." ,,,,,"Distillate",,,"Coal" ,,,,,"Fuel Oil",,,"(excluding Coal" ,,,"Net","Residual","and","Natural Gas(d)","LPG and","Coke and Breeze)" "NAICS",,"Total","Electricity(b)","Fuel Oil","Diesel Fuel(c)","(billion","NGL(e)","(million","Other(f)" "Code(a)","End Use","(trillion Btu)","(million kWh)","(million bbl)","(million bbl)","cu ft)","(million bbl)","short tons)","(trillion Btu)"

66

,"New York Natural Gas Consumption by End Use"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New York Natural Gas Consumption by End Use",6,"Monthly","102014","1151989" ,"Release...

67

,"New York Natural Gas Consumption by End Use"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New York Natural Gas Consumption by End Use",10,"Annual",2013,"6301967" ,"Release Date:","10...

68

Engineer End Uses for Maximum Efficiency | Department of Energy  

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

for Maximum Efficiency (August 2004) More Documents & Publications Maintaining System Air Quality Compressed Air Storage Strategies Alternative Strategies for Low Pressure End Uses...

69

Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

page intentionally left blank page intentionally left blank 69 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Transportation Demand Module The NEMS Transportation Demand Module estimates transportation energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), buses, freight and passenger aircraft, freight and passenger rail, freight shipping, and miscellaneous

70

Monitoring of Electrical End-Use Loads in Commercial Buildings  

E-Print Network (OSTI)

Southern California Edison is currently conducting a program to collect end-use metered data from commercial buildings in its service area. The data will provide actual measurements of end-use loads and will be used in research and in designing...

Martinez, M.; Alereza, T.; Mort, D.

1988-01-01T23:59:59.000Z

71

Energy Demand Staff Scientist  

E-Print Network (OSTI)

Energy Demand in China Lynn Price Staff Scientist February 2, 2010 #12;Founded in 1988 Focused on End-Use Energy Efficiency ~ 40 Current Projects in China Collaborations with ~50 Institutions in China Researcher #12;Talk OutlineTalk Outline · Overview · China's energy use and CO2 emission trends · Energy

Eisen, Michael

72

End-Use Load and Consumer Assessment Program: Analysis of residential refrigerator/freezer performance  

SciTech Connect

The Bonneville Power Administration (Bonneville) is conducting a large end-use data acquisition program in an effort to understand how energy is utilized in buildings with permanent electric space heating equipment in the Pacific Northwest. The initial portion of effort, known as the End-Use Load and Consumer Assessment Program (ELCAP), was conducted for Bonneville by the Pacific Northwest Laboratory (PNL). The collection of detailed end-use data provided an opportunity to analyze the amount of energy consumed by both refrigerators and separate freezers units located in residential buildings. By obtaining this information, the uncertainty of long- term regional end-use forecasting can be improved and potential utility marketing programs for new appliances with a reduced overall energy demand can be identified. It was found that standby loads derived from hourly averages between 4 a.m. and 5 a.m. reflected the minimum consumption needed to maintain interior refrigerator temperatures at a steady-state condition. Next, an average 24-hour consumption that included cooling loads from door openings and cooling food items was also determined. Later, analyses were conducted to develop a model capable of predicting refrigerator standby loads and 24-hour consumption for comparison with national refrigerator label ratings. Data for 140 residential sites with a refrigeration end-use were screened to develop a sample of 119 residences with pure refrigeration for use in this analysis. To identify those refrigerators that were considered to be pure (having no other devices present on the circuit) in terms of their end-use classification, the screening procedure used a statistical clustering technique that was based on standby loads with 24-hour consumption. 5 refs., 18 figs., 4 tabs.

Ross, B.A.

1991-09-01T23:59:59.000Z

73

Table 5.2 End Uses of Fuel Consumption, 2010;  

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

2 End Uses of Fuel Consumption, 2010; 2 End Uses of Fuel Consumption, 2010; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal NAICS Net Residual and LPG and (excluding Coal Code(a) End Use Total Electricity(b) Fuel Oil Diesel Fuel(c) Natural Gas(d) NGL(e) Coke and Breeze) Other(f) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 14,228 2,437 79 130 5,211 69 868 5,435 Indirect Uses-Boiler Fuel -- 27 46 19 2,134 10 572 -- Conventional Boiler Use -- 27 20 4 733 3 72 -- CHP and/or Cogeneration Process -- 0 26 15 1,401 7 500 -- Direct Uses-Total Process -- 1,912 26 54 2,623 29 289 -- Process Heating -- 297 25 14 2,362 24 280

74

Table 5.1 End Uses of Fuel Consumption, 2010;  

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

5.1 End Uses of Fuel Consumption, 2010; 5.1 End Uses of Fuel Consumption, 2010; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Residual and Natural Gas(d) LPG and Coke and Breeze) NAICS Total Electricity(b) Fuel Oil Diesel Fuel(c) (billion NGL(e) (million Other(f) Code(a) End Use (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) (trillion Btu) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 14,228 714,166 13 22 5,064 18 39 5,435 Indirect Uses-Boiler Fuel -- 7,788 7 3 2,074 3 26 -- Conventional Boiler Use -- 7,788 3 1 712 1 3 -- CHP and/or Cogeneration Process

75

Table 5.5 End Uses of Fuel Consumption, 2010;  

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

5 End Uses of Fuel Consumption, 2010; 5 End Uses of Fuel Consumption, 2010; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Residual and Natural Gas(c) LPG and Coke and Breeze) Total Electricity(a) Fuel Oil Diesel Fuel(b) (billion NGL(d) (million Other(e) End Use (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) (trillion Btu) Total United States TOTAL FUEL CONSUMPTION 14,228 714,166 13 22 5,064 18 39 5,435 Indirect Uses-Boiler Fuel -- 7,788 7 3 2,074 3 26 -- Conventional Boiler Use -- 7,788 3 1 712 1 3 -- CHP and/or Cogeneration Process -- 0 4 3 1,362 2 23 -- Direct Uses-Total Process

76

Table 5.6 End Uses of Fuel Consumption, 2010;  

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

6 End Uses of Fuel Consumption, 2010; 6 End Uses of Fuel Consumption, 2010; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal Net Residual and LPG and (excluding Coal End Use Total Electricity(a) Fuel Oil Diesel Fuel(b) Natural Gas(c) NGL(d) Coke and Breeze) Other(e) Total United States TOTAL FUEL CONSUMPTION 14,228 2,437 79 130 5,211 69 868 5,435 Indirect Uses-Boiler Fuel -- 27 46 19 2,134 10 572 -- Conventional Boiler Use -- 27 20 4 733 3 72 -- CHP and/or Cogeneration Process -- 0 26 15 1,401 7 500 -- Direct Uses-Total Process -- 1,912 26 54 2,623 29 289 -- Process Heating -- 297 25 14 2,362 24 280 -- Process Cooling and Refrigeration -- 182 * Q 25

77

United States Industrial Sector Energy End Use Analysis  

E-Print Network (OSTI)

by end uses (e.g. , boilers, process, electric drives,MECS 2002, and MECS 1998 data. Indirect Uses-Boiler FuelConventional Boiler Use CHP and/or Cogeneration Process

Shehabi, Arman

2014-01-01T23:59:59.000Z

78

Distribution Load Modelling for Demand Side Management and End-Use Efficiency  

Science Journals Connector (OSTI)

The problem of electric load modelling for low aggregation levels is addressed in the paper, being the object to obtain good “response” behaviour models of any group of loads in an electric energy distribution...

C. Álvarez; A. Gabaldón

1994-01-01T23:59:59.000Z

79

Opportunities for Energy Efficiency and Demand Response in the California Cement Industry  

E-Print Network (OSTI)

Opportunities for Energy  Efficiency and Demand Response in Agricultural/Water End?Use Energy Efficiency Program.    i 1   4.0   Energy Efficiency and Demand Response 

Olsen, Daniel

2012-01-01T23:59:59.000Z

80

End-Use Load and Consumer Assessment Program: motivation and overview  

Science Journals Connector (OSTI)

The End-Use Load and Consumer Assessment Program (ELCAP) was a major end-use data collection program undertaken by the Bonneville Power Administration from 1983 through 1990 to obtain specific information to support a variety of conservation and forecasting activities. The objectives of the program were to test key assumptions used in current engineering and forecasting models, provide insights regarding how various factors affect energy consumption, provide information to support load management conservation and marketing programs, and identify conservation resource potential from new demand-side technologies or programs. To accomplish this, a well-designed experiment was required that accounted for adequate representation of both existing and new buildings in the residential and commercial sector of the Pacific Northwest. This paper summarizes the motivations for obtaining the data, information regarding the sample, an overview of the analysis agenda, and specifics regarding the data set, both engineering and characteristics.

F.J. Peterson; J.E. Patton; M.E. Miller; R.A. Gillman; W.M. Warwick; W.F. Sandusky

1993-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "demand ten end-use" 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

Realizing Building End-Use Efficiency with Ermerging Technologies  

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

Realizing Building End-Use Efficiency Realizing Building End-Use Efficiency with Emerging Technologies Jonathan Livingston Livingston Energy Innovations, LLC What is End-Use Efficiency (EE)? * EE is an energy resource * Broadly accepted in the U.S. as the single most effective step toward reducing pollution, power costs and price volatility * Treated as equivalent to supply-side resources * Recognized by states and regions as first priority when costs are comparable (CA, MO, NM, Pacific Northwest) The Northwest Power Act 839b(e)(1). The plan shall, as provided in this paragraph, give priority to resources which the Council determines to be cost-effective. Priority shall be given: first, to conservation; second, to renewable resources; third, to generating resources utilizing waste heat or generating resources of high fuel conversion

82

Energy End-Use Flow Maps for the Buildings Sector  

SciTech Connect

Graphical presentations of energy flows are widely used within the industrial sector to depict energy production and use. PNNL developed two energy flow maps, one each for the residential and commercial buildings sectors, in response to a need for a clear, concise, graphical depiction of the flows of energy from source to end-use in the building sector.

Belzer, David B.

2006-12-04T23:59:59.000Z

83

Industrial Steam Power Cycles Final End-Use Classification  

E-Print Network (OSTI)

Final end uses of steam include two major classifications: those uses that condense the steam against heat transfer surfaces to provide heat to an item of process or service equipment; and those that require a mass flow of steam for stripping...

Waterland, A. F.

1983-01-01T23:59:59.000Z

84

Transportation Demand This  

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

Transportation Demand Transportation Demand This page inTenTionally lefT blank 75 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Transportation Demand Module The NEMS Transportation Demand Module estimates transportation energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific and associated technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), buses, freight and passenger aircraft, freight

85

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 non-manufacturing industries. The manufacturing industries are further subdivided into the energy- intensive manufacturing industries and non-energy-intensive manufacturing industries (Table 6.1). The manufacturing industries are modeled through the use of a detailed process-flow or end-use accounting procedure, whereas the non- manufacturing industries are modeled with substantially less detail. The petroleum refining industry is not included in the Industrial Demand Module, as it is simulated separately in the Petroleum Market Module of NEMS. The Industrial Demand Module calculates energy consumption for the four Census Regions (see Figure 5) and disaggregates the energy consumption

86

Integrated estimation of commercial sector end-use load shapes and energy use intensities  

SciTech Connect

The Southern California Edison Company (SCE) and the California Energy Commission (CEC) have contracted with the Energy Analysis Program of the Applied Science Division at the Lawrence Berkeley Laboratory (LBL) to develop an integrated set of commercial sector load shapes (LS) and energy utilization indices (EUI) for use in forecasting electricity demand. The objectives of this project are to conduct detailed analyses of SCE data on commercial building characteristics, energy use, and whole-building load shapes; and in conjunction with other data, to develop, test, and apply an integrated approach for the estimation of end-use LSs and EUIs. The project represents one of the first attempts to combine simulation-based, prototypical building analyses with direct reconciliation to measured hourly load data. The project examined electricity and gas use for nine building types, including large offices, small offices, large retails, small retails, food stores, sitdown restaurants, fastfood restaurants, refrigerated warehouses, and non-refrigerated warehouses. For each building type, nine end uses were examined, including cooling, heating, ventilation, indoor lighting, outdoor lighting, miscellaneous equipment, water heating, cooking, and refrigeration. For the HVAC end uses (cooling, ventilation, and heating), separate analyses were performed for three climate zones: coastal, inland, and desert.

Akbari, H.; Eto, J.; Turiel, I.; Heinemeier, K.; Lebot, B.; Nordman, B.; Rainer, L.

1989-01-01T23:59:59.000Z

87

Commercial building end-use energy metering inventory  

SciTech Connect

Pacific Northwest Laboratory conducted a comprehensive inventory of end-use metered data. The inventory did not discover many sources of metered end-use data; however, research into existing data bases and extensive discussions with professionals associated with building energy conservation have enabled a clear characterization to be developed of the types of metered data that are required to further energy conservation in commercial buildings. Based on the results of the inventory and this clarification of data requirements, the adequacy of existing data bases has been assessed, and recommendations have been developed for future federal data collection efforts. A summary of sources of existing metered end-use data is provided in Section 2.1 and its adequacy has been summarized. Collection of further end-use metered data is both desirable and valuable for many areas of building energy conservation research. Empirical data are needed to address many issues which to date have been addressed using only simulation techniques. The adequacy of using simulation techniques for various purposes needs to be assessed through comparison with measured data. While these data are expensive to acquire, it is cost-effective to do so in the long run, and the need is not being served by the private market. The preceding conclusion based on results from the inventory of existing data highlights two important facts: First, although the data are widely desired in the private sector, they are not widely available. Second, where suitable data are publicly available and contain the desired supporting information, their collection has generally been funded by government-sponsored research.

Heidell, J.A.; Mazzucchi, R.P.; Reilly, R.W.

1985-03-01T23:59:59.000Z

88

REFINING AND END USE STUDY OF COAL LIQUIDS  

SciTech Connect

This document summarizes all of the work conducted as part of the Refining and End Use Study of Coal Liquids. There were several distinct objectives set, as the study developed over time: (1) Demonstration of a Refinery Accepting Coal Liquids; (2) Emissions Screening of Indirect Diesel; (3) Biomass Gasification F-T Modeling; and (4) Updated Gas to Liquids (GTL) Baseline Design/Economic Study.

Unknown

2002-01-01T23:59:59.000Z

89

Demand Reduction  

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

Grantees may use funds to coordinate with electricity supply companies and utilities to reduce energy demands on their power systems. These demand reduction programs are usually coordinated through...

90

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 12 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module forecasts energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region forecast using the SEDS 27 data.

91

Energy Information Administration - Table 2. End Uses of Fuel Consumption,  

Gasoline and Diesel Fuel Update (EIA)

2 2 Page Last Modified: June 2010 Table 2. End Uses of Fuel Consumption, 1998, 2002, and 2006 (trillion Btu) MECS Survey Years Iron and Steel Mills (NAICS1 331111) 1998 2002 2006 Total 2 1,672 1,455 1,147 Net Electricity 3 158 184 175 Natural Gas 456 388 326 Coal 48 36 14 Boiler Fuel -- -- -- Coal 8 W 1 Residual Fuel Oil 10 * 4 Natural Gas 52 39 27 Process Heating -- -- -- Net Electricity 74 79 76 Residual Fuel Oil 19 * 11 Natural Gas 369 329 272 Machine Drive -- -- -- Net Electricity 68 86 77 Notes 1. The North American Industry Classification System (NAICS) has replaced the Standard Industrial Classification (SIC) system. NAICS 331111 includes steel works, blast furnaces (including coke ovens), and rolling mills. 2. 'Total' is the sum of all energy sources listed below, including net steam (the sum of purchases, generation from renewable resources, and net transfers), and other energy that respondents indicated was used to produce heat and power. It is the fuel quantities across all end-uses.

92

Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study  

E-Print Network (OSTI)

used to produce electrical energy and the technologies usedHealth Benefits of End-Use Electrical Energy Efficiency inhow increasing end-use electrical energy efficiency from

McKone, Thomas E.

2011-01-01T23:59:59.000Z

93

The Role of Demand Response Policy Forum Series  

E-Print Network (OSTI)

The Role of Demand Response Policy Forum Series Beyond 33 Percent: California's Renewable Future and Demand Response #12;Historic focus on Seasonal Grid Stress PG&E Demand Bid Test Day 0 2000 4000 6000 8000 Communication Latency #12;Bottom Up Review of End-Use Loads for Demand Response 5 Commercial Residential

California at Davis, University of

94

Integrated estimation of commercial sector end-use load shapes and energy use intensities  

SciTech Connect

The Southern California Edison Company (SCE) and the California Energy Commission (CEC) have contracted with Energy Analysis Program of the Applied Science Division at the Lawrence Berkeley Laboratory (LBL) to develop an integrated set of commercial sector load shapes (LS) and energy utilization indices (EUI) for use in forecasting electricity demand. The overall objectives of this project are to conduct detailed analyses of SCE data on commercial building characteristics, energy use, and whole-building load shapes, and, in conjunction with other data, to develop, test, and apply an integrated approach for the estimation of end-use LSs and EUIs. The project is one of the first attempts ever to combine simulation-based, prototypical building analyses with direct reconciliation to measured hourly load data.

Akbari, H.; Eto, J.; Turiel, I.; Heinemeier, K.; Lebot, B.; Nordman, B.; Rainer, L.

1989-01-01T23:59:59.000Z

95

Top Ten Lists  

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

Fueleconomy Top Ten Fueleconomy Top Ten EPA Rated - 2014 EPA Rated - All Years Shared Estimates - All Years Misconceptions Fueleconomy.gov's Top Ten EPA-Rated Fuel Sippers (2014) Include all-electric and plug-in hybrid vehicles? Yes No Vehicles are ranked by their combined rating (weighted by 55% city and 45% highway). In the event of a tie, multiple vehicles may share the same ranking. Electric vehicles are measured in Miles Per Gallon equivalent (MPGe) where 33.7 kW-hrs = 1 gallon of gasoline. 1. 2014 Chevrolet Spark EV 2014 Chevrolet Spark EV Combined 119 City 128/Highway 109 All-electric, Auto (A1) 2. 2014 Honda Fit EV 2014 Honda Fit EV Combined 118 City 132/Highway 105 All-electric, Auto (A1) 3. 2014 Fiat 500e 2014 Fiat 500e Combined 116 City 122/Highway 108 All-electric, Auto (A1)

96

Technology data characterizing refrigeration in commercial buildings: Application to end-use forecasting with COMMEND 4.0  

SciTech Connect

In the United States, energy consumption is increasing most rapidly in the commercial sector. Consequently, the commercial sector is becoming an increasingly important target for state and federal energy policies and also for utility-sponsored demand side management (DSM) programs. The rapid growth in commercial-sector energy consumption also makes it important for analysts working on energy policy and DSM issues to have access to energy end-use forecasting models that include more detailed representations of energy-using technologies in the commercial sector. These new forecasting models disaggregate energy consumption not only by fuel type, end use, and building type, but also by specific technology. The disaggregation of the refrigeration end use in terms of specific technologies, however, is complicated by several factors. First, the number of configurations of refrigeration cases and systems is quite large. Also, energy use is a complex function of the refrigeration-case properties and the refrigeration-system properties. The Electric Power Research Institute`s (EPRI`s) Commercial End-Use Planning System (COMMEND 4.0) and the associated data development presented in this report attempt to address the above complications and create a consistent forecasting framework. Expanding end-use forecasting models so that they address individual technology options requires characterization of the present floorstock in terms of service requirements, energy technologies used, and cost-efficiency attributes of the energy technologies that consumers may choose for new buildings and retrofits. This report describes the process by which we collected refrigeration technology data. The data were generated for COMMEND 4.0 but are also generally applicable to other end-use forecasting frameworks for the commercial sector.

Sezgen, O.; Koomey, J.G.

1995-12-01T23:59:59.000Z

97

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 51 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 non-manufacturing industries. The manufacturing industries are further subdivided into the energy- intensive manufacturing industries and nonenergy-intensive manufacturing industries (Table 6.1). The manufacturing industries are modeled through the use of a detailed process-flow or end-use accounting procedure, whereas the non- manufacturing industries are modeled with substantially less detail. The petroleum refining industry is not included in the Industrial Module, as it is simulated separately in the Petroleum Market Module of NEMS. The Industrial Module calculates

98

Energy demand  

Science Journals Connector (OSTI)

The basic forces pushing up energy demand are population increase and economic growth. From ... of these it is possible to estimate future energy requirements.

Geoffrey Greenhalgh

1980-01-01T23:59:59.000Z

99

Technology data characterizing space conditioning in commercial buildings: Application to end-use forecasting with COMMEND 4.0  

SciTech Connect

In the US, energy consumption is increasing most rapidly in the commercial sector. Consequently, the commercial sector is becoming an increasingly important target for state and federal energy policies and also for utility-sponsored demand side management (DSM) programs. The rapid growth in commercial-sector energy consumption also makes it important for analysts working on energy policy and DSM issues to have access to energy end-use forecasting models that include more detailed representations of energy-using technologies in the commercial sector. These new forecasting models disaggregate energy consumption not only by fuel type, end use, and building type, but also by specific technology. The disaggregation of space conditioning end uses in terms of specific technologies is complicated by several factors. First, the number of configurations of heating, ventilating, and air conditioning (HVAC) systems and heating and cooling plants is very large. Second, the properties of the building envelope are an integral part of a building`s HVAC energy consumption characteristics. Third, the characteristics of commercial buildings vary greatly by building type. The Electric Power Research Institute`s (EPRI`s) Commercial End-Use Planning System (COMMEND 4.0) and the associated data development presented in this report attempt to address the above complications and create a consistent forecasting framework. This report describes the process by which the authors collected space-conditioning technology data and then mapped it into the COMMEND 4.0 input format. The data are also generally applicable to other end-use forecasting frameworks for the commercial sector.

Sezgen, O.; Franconi, E.M.; Koomey, J.G.; Greenberg, S.E.; Afzal, A.; Shown, L.

1995-12-01T23:59:59.000Z

100

CBECS 1989 - Energy End-use Intensities in Commercial Buildings -- Detailed  

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

Publication > Detailed Tables Publication > Detailed Tables 1989 Energy End-Use Intensities Detailed Tables Energy End Uses Ranked by Energy Consumption, 1989 Energy End Uses Ranked by Energy Consumption, 1989 Source: Energy Information Administration, Office of Energy Markets and End Use, Forms EIA-871A through F of the 1989 Commercial Buildings Energy Consumption Survey. Table Organization The following 13 tables present detailed energy end-use consumption data from the 1989 CBECS. Summary tables for all major fuels (electricity, natural gas, fuel oil, and district heat) appear first, followed by separate tables for each of the four major fuels. Within each energy sourceÂ’s group of tables, there is a table showing end-use consumption, a table showing end-use intensities (consumption per square foot), and a table (except for fuel oil and district heat) showing the end-use shares of total consumption.

Note: This page contains sample records for the topic "demand ten end-use" 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

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

6 End Uses of Fuel Consumption, 2006;" 6 End Uses of Fuel Consumption, 2006;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Trillion Btu." " "," ",," ","Distillate"," "," ",," " " ",,,,"Fuel Oil",,,"Coal" " "," ","Net","Residual","and",,"LPG and","(excluding Coal"," " "End Use","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Natural Gas(c)","NGL(d)","Coke and Breeze)","Other(e)"

102

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

2. End Uses of Fuel Consumption, 1998;" 2. End Uses of Fuel Consumption, 1998;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Trillion Btu." " "," ",," ","Distillate"," "," ",," "," " " ",,,,"Fuel Oil",,,"Coal",,"RSE" " "," ","Net","Residual","and",,"LPG and","(excluding Coal"," ","Row" "End Use","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Natural Gas(c)","NGL(d)","Coke and Breeze)","Other(e)","Factors"

103

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

6 End Uses of Fuel Consumption, 2010;" 6 End Uses of Fuel Consumption, 2010;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Trillion Btu." " "," ",," ","Distillate"," "," ",," " " ",,,,"Fuel Oil",,,"Coal" " "," ","Net","Residual","and",,"LPG and","(excluding Coal"," " "End Use","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Natural Gas(c)","NGL(d)","Coke and Breeze)","Other(e)"

104

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

6 End Uses of Fuel Consumption, 2002;" 6 End Uses of Fuel Consumption, 2002;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Trillion Btu." " "," ",," ","Distillate"," "," ",," "," " " ",,,,"Fuel Oil",,,"Coal",,"RSE" " "," ","Net","Residual","and","Natural ","LPG and","(excluding Coal"," ","Row" "End Use","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Gas(c)","NGL(d)","Coke and Breeze)","Other(e)","Factors"

105

Opportunities, Barriers and Actions for Industrial Demand Response in  

E-Print Network (OSTI)

LBNL-1335E Opportunities, Barriers and Actions for Industrial Demand Response in California A.T. Mc of Global Energy Partners. This work described in this report was coordinated by the Demand Response Demand Response in California. PIER Industrial/Agricultural/Water EndUse Energy Efficiency Program. CEC

106

The Value of End-Use Energy Efficiency in Mitigation of U.S. Carbon Emissions  

SciTech Connect

This report documents a scenario analysis exploring the value of advanced technologies in the U.S. buildings, industrial, and transportation sectors in stabilizing atmospheric greenhouse gas concentrations. The analysis was conducted by staff members of Pacific Northwest National Laboratory (PNNL), working at the Joint Global Change Research Institute (JGCRI) in support of the strategic planning process of the U.S. Department of Energy (U.S. DOE) Office of Energy Efficiency and Renewable Energy (EERE). The conceptual framework for the analysis is an integration of detailed buildings, industrial, and transportation modules into MiniCAM, a global integrated assessment model. The analysis is based on three technology scenarios, which differ in their assumed rates of deployment of new or presently available energy-saving technologies in the end-use sectors. These technology scenarios are explored with no carbon policy, and under two CO2 stabilization policies, in which an economic price on carbon is applied such that emissions follow prescribed trajectories leading to long-term stabilization of CO2 at roughly 450 and 550 parts per million by volume (ppmv). The costs of meeting the emissions targets prescribed by these policies are examined, and compared between technology scenarios. Relative to the reference technology scenario, advanced technologies in all three sectors reduce costs by 50% and 85% for the 450 and 550 ppmv policies, respectively. The 450 ppmv policy is more stringent and imposes higher costs than the 550 ppmv policy; as a result, the magnitude of the economic value of energy efficiency is four times greater for the 450 ppmv policy than the 550 ppmv policy. While they substantially reduce the costs of meeting emissions requirements, advanced end-use technologies do not lead to greenhouse gas stabilization without a carbon policy. This is due mostly to the effects of increasing service demands over time, the high consumption of fossil fuels in the electricity sector, and the use of unconventional feedstocks in the liquid fuel refining sector. Of the three end-use sectors, advanced transportation technologies have the greatest potential to reduce costs of meeting carbon policy requirements. Services in the buildings and industrial sectors can often be supplied by technologies that consume low-emissions fuels such as biomass or, in policy cases, electricity. Passenger transportation, in contrast, is especially unresponsive to climate policies, as the fuel costs are small compared to the time value of transportation and vehicle capital and operating costs. Delaying the transition from reference to advanced technologies by 15 years increases the costs of meeting 450 ppmv stabilization emissions requirements by 21%, but the costs are still 39% lower than the costs assuming reference technology. The report provides a detailed description of the end-use technology scenarios and provides a thorough analysis of the results. Assumptions are documented in the Appendix.

Kyle, G. Page; Smith, Steven J.; Clarke, Leon E.; Kim, Son H.; Wise, Marshall A.

2007-11-27T23:59:59.000Z

107

Energy End-Use Intensities in Commercial Buildings 1989 data -- Publication  

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

End-Use Intensities Executive Summary > Publication and Tables End-Use Intensities Executive Summary > Publication and Tables Publication and Tables Energy End Uses Ranked by Energy Consumption, 1989 Figure on Energy End Uses Ranked by Energy Consumption, 1989 Source: Energy Information Administration, Office of Energy Markets and End Use, Forms EIA-871A through F of the 1989 Commercial Buildings Energy Consumption Survey. Divider Bar To View and/or Print Reports (requires Adobe Acrobat Reader) - Download Adobe Acrobat Reader If you experience any difficulties, visit our Technical Frequently Asked Questions. Divider Bar You have the option of downloading the entire report or selected sections of the report. Full Report - Energy End-Use Intensities in Commercial Buildings (1989 data) (file size .89 MB) pages: 140

108

EIA - Appendix F-Reference Case Projections by End-Use Sector and Country  

Gasoline and Diesel Fuel Update (EIA)

Reference Case Projections by End-Use Sector and Country Grouping Data Tables (2005-2030) Reference Case Projections by End-Use Sector and Country Grouping Data Tables (2005-2030) International Energy Outlook 2008 Reference Case Projections by End-Use Sector and Country Grouping Data Tables (2005-2030) Formats Data Table Titles (1 to 19 complete) Reference Case Projections by End-Use Sector and Country Gruping Data Tables. Need help, contact the National Energy Information Center at 202-586-8800. Projections of Nuclear Generating Capacity Data Tables. Need help, contact the National Energy Information Center at 202-586-8800. F1 Total World Delivered Energy Consumption by End-Use Sector and Fuel Table F1. Total World Delivered Energy Consumption by End-Use Sector and Fuel. Need help, contact the National Energy Information Center at 202-586-8800.

109

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

1. End Uses of Fuel Consumption, 1998;" 1. End Uses of Fuel Consumption, 1998;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Physical Units or Btu." " "," ",," ","Distillate"," "," ","Coal"," "," " " ",,,,"Fuel Oil",,,"(excluding Coal" " "," ","Net","Residual","and","Natural Gas(c)","LPG and","Coke and Breeze)"," ","RSE" " ","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","(billion","NGL(d)","(million","Other(e)","Row"

110

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

5 End Uses of Fuel Consumption, 2010;" 5 End Uses of Fuel Consumption, 2010;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Physical Units or Btu." " "," ",," ","Distillate"," "," ","Coal"," " " ",,,,"Fuel Oil",,,"(excluding Coal" " "," ","Net","Residual","and","Natural Gas(c)","LPG and","Coke and Breeze)"," " " ","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","(billion","NGL(d)","(million","Other(e)"

111

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

5 End Uses of Fuel Consumption, 2002;" 5 End Uses of Fuel Consumption, 2002;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Physical Units or Btu." " "," ",," ","Distillate"," "," ",," "," " " ",,,,"Fuel Oil",,,"Coal" " "," ","Net","Residual","and","Natural ","LPG and","(excluding Coal"," ","RSE" " ","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","Gas(c)","NGL(d)","Coke and Breeze)","Other(e)","Row"

112

" Row: End Uses;" " Column: Energy Sources, including Net Electricity;"  

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

5 End Uses of Fuel Consumption, 2006;" 5 End Uses of Fuel Consumption, 2006;" " Level: National and Regional Data; " " Row: End Uses;" " Column: Energy Sources, including Net Electricity;" " Unit: Physical Units or Btu." " "," ",," ","Distillate"," "," ","Coal"," " " ",,,,"Fuel Oil",,,"(excluding Coal" " "," ","Net","Residual","and","Natural Gas(c)","LPG and","Coke and Breeze)"," " " ","Total","Electricity(a)","Fuel Oil","Diesel Fuel(b)","(billion","NGL(d)","(million","Other(e)"

113

Data on energy end-use patterns and energy efficiencies in major CO sub 2 emitting countries  

SciTech Connect

This is a report of the basic data regarding energy end-uses and efficiencies in major CO{sub 2} emitting countries. The task is part of the multi-lab carbon dioxide energy system research program. Fossil energy production and use are the largest anthropogenic source of CO{sub 2} emissions. To gain an insight into the relationship between CO{sub 2} emission and energy use, the global energy consumption patterns and the changing energy efficiencies must be better analyzed and understood. This work attempts to collect and organize the data on energy use and energy efficiency for the ten major CO{sub 2} emitting countries: USA, USSR, the People's Republic of China, Japan, the Federal Republic of Germany, the United Kingdom, France, Canada, Italy, and Australia. A wide variety of information sources have been examined. The data base is presented in tabular format. It is documented by three main parts, the first shows the total final energy consumption by fuel type and end-use sector for each nation. The second shows the detailed energy use by fuel type and function for each end-use sector: residential, commercial, transportation and industrial. The third part shows the country-specific energy balances for electricity generation and use. The data base is a living document and will be updated as additional information becomes available. The data base is to be used to accomplish the ultimate objective of improving the reliability of future CO{sub 2}-emissions estimates. 7 refs., 12 tabs.

Cheng, Hsing C.

1990-08-01T23:59:59.000Z

114

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

E-Print Network (OSTI)

domestic end-uses, the development of plug-in hybrid and electric vehicles, the increase of heat pumps heating systems such as heat pumps in new building or which will replace old installed fossil fuels based systems; · integration of new end-uses such as Plug-in Electric Vehicles and an always growing number

Paris-Sud XI, Université de

115

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

Gasoline and Diesel Fuel Update (EIA)

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

116

Utility Sector Impacts of Reduced Electricity Demand  

SciTech Connect

This report presents a new approach to estimating the marginal utility sector impacts associated with electricity demand reductions. The method uses publicly available data and provides results in the form of time series of impact factors. The input data are taken from the Energy Information Agency's Annual Energy Outlook (AEO) projections of how the electric system might evolve in the reference case, and in a number of side cases that incorporate different effciency and other policy assumptions. The data published with the AEO are used to define quantitative relationships between demand-side electricity reductions by end use and supply-side changes to capacity by plant type, generation by fuel type and emissions of CO2, Hg, NOx and SO2. The impact factors define the change in each of these quantities per unit reduction in site electricity demand. We find that the relative variation in these impacts by end use is small, but the time variation can be significant.

Coughlin, Katie

2014-12-01T23:59:59.000Z

117

EIA - Reference Case Projections by End-Use Sector and Region Tables  

Gasoline and Diesel Fuel Update (EIA)

6 > Reference Case Projections by End-Use Sector and Region Tables (2003-2030) 6 > Reference Case Projections by End-Use Sector and Region Tables (2003-2030) International Energy Outlook 2006 Reference Case Projections by End-Use Sector and Region Tables (2003-2030) Formats Data Table Titles (1 to 19 complete) Reference Case Projections by End-Use Sector and Region Data Tables. Need help, contact the National Energy Information Center at 202-586-8800. Reference Case Projections by End-Use Sector and Region Data Tables. Need help, contact the National Energy Information Center at 202-586-8800. Table D1 Total World Delivered Energy Consumption Reference Case Projections by End-Use Sector and Region Data Tables. Need help, contact the National Energy Information Center at 202-586-8800. Reference Case Projections by End-Use Sector and Region Data Tables. Need help, contact the National Energy Information Center at 202-586-8800.

118

,"U.S. Total Sales of Residual Fuel Oil by End Use"  

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

Residual Fuel Oil by End Use" Residual Fuel Oil by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Total Sales of Residual Fuel Oil by End Use",8,"Annual",2012,"6/30/1984" ,"Release Date:","11/15/2013" ,"Next Release Date:","10/31/2014" ,"Excel File Name:","pet_cons_821rsd_dcu_nus_a.xls" ,"Available from Web Page:","http://www.eia.gov/dnav/pet/pet_cons_821rsd_dcu_nus_a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.gov"

119

,"U.S. Adjusted Sales of Residual Fuel Oil by End Use"  

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

Residual Fuel Oil by End Use" Residual Fuel Oil by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Adjusted Sales of Residual Fuel Oil by End Use",8,"Annual",2012,"6/30/1984" ,"Release Date:","11/15/2013" ,"Next Release Date:","10/31/2014" ,"Excel File Name:","pet_cons_821rsda_dcu_nus_a.xls" ,"Available from Web Page:","http://www.eia.gov/dnav/pet/pet_cons_821rsda_dcu_nus_a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.gov"

120

Demand Response  

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

Assessment for Eastern Interconnection Youngsun Baek, Stanton W. Hadley, Rocio Martinez, Gbadebo Oladosu, Alexander M. Smith, Fran Li, Paul Leiby and Russell Lee Prepared for FY12 DOE-CERTS Transmission Reliability R&D Internal Program Review September 20, 2012 2 Managed by UT-Battelle for the U.S. Department of Energy DOE National Laboratory Studies Funded to Support FOA 63 * DOE set aside $20 million from transmission funding for national laboratory studies. * DOE identified four areas of interest: 1. Transmission Reliability 2. Demand Side Issues 3. Water and Energy 4. Other Topics * Argonne, NREL, and ORNL support for EIPC/SSC/EISPC and the EISPC Energy Zone is funded through Area 4. * Area 2 covers LBNL and NREL work in WECC and

Note: This page contains sample records for the topic "demand ten end-use" 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

Demand Response and Open Automated Demand Response  

E-Print Network (OSTI)

LBNL-3047E Demand Response and Open Automated Demand Response Opportunities for Data Centers G described in this report was coordinated by the Demand Response Research Center and funded by the California. Demand Response and Open Automated Demand Response Opportunities for Data Centers. California Energy

122

Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity;  

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

6 End Uses of Fuel Consumption, 2006; 6 End Uses of Fuel Consumption, 2006; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal Net Residual and LPG and (excluding Coal End Use Total Electricity(a) Fuel Oil Diesel Fuel(b) Natural Gas(c) NGL(d) Coke and Breeze) Other(e) Total United States TOTAL FUEL CONSUMPTION 15,658 2,850 251 129 5,512 79 1,016 5,820 Indirect Uses-Boiler Fue -- 41 133 23 2,119 8 547 -- Conventional Boiler Use 41 71 17 1,281 8 129 CHP and/or Cogeneration Process 0 62 6 838 1 417 Direct Uses-Total Process -- 2,244 62 52 2,788 39 412 -- Process Heating -- 346 59 19 2,487 32 345 -- Process Cooling and Refrigeration -- 206 * 1 32 * * -- Machine Drive

123

Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity;  

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

2 End Uses of Fuel Consumption, 2006; 2 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal NAICS Net Residual and LPG and (excluding Coal Code(a) End Use Total Electricity(b) Fuel Oil Diesel Fuel(c) Natural Gas(d) NGL(e) Coke and Breeze) Other(f) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 15,658 2,850 251 129 5,512 79 1,016 5,820 Indirect Uses-Boiler Fuel -- 41 133 23 2,119 8 547 -- Conventional Boiler Use -- 41 71 17 1,281 8 129 -- CHP and/or Cogeneration Process -- -- 62 6 838 1 417 -- Direct Uses-Total Process -- 2,244 62 52 2,788 39 412 -- Process Heating -- 346 59 19 2,487

124

Distribution Category UC-98 Consumption End-Use A Comparison of Measures  

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

Distribution Category UC-98 Distribution Category UC-98 Consumption End-Use A Comparison of Measures by Consumption and Supply Surveys Energy information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, D.C. 20585 General information concerning the contents of the report may be obtained from Lynda T. Carlson, Director of the Energy End Use Division (202/586-1112). Specific information regarding the contents or preparation of the publication may be obtained from Nancy L. Leach, Chief of the Residential and Commercial Branch (202/586-1114). The Residential Energy Consumption Survey manager and a major contributor to this report is Wendel Thompson (202/586-1119). The report was written by Gerald Peabody (202/586-6160). Energy Consumption by End-Use Sector

125

Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity;  

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

1 End Uses of Fuel Consumption, 2006; 1 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Residual and Natural Gas(d) LPG and Coke and Breeze) NAICS Total Electricity(b) Fuel Oil Diesel Fuel(c) (billion NGL(e) (million Other(f) Code(a) End Use (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) (trillion Btu) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 15,658 835,382 40 22 5,357 21 46 5,820 Indirect Uses-Boiler Fuel -- 12,109 21 4 2,059 2 25 -- Conventional Boiler Use -- 12,109 11 3 1,245 2 6 -- CHP and/or Cogeneration Process

126

Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity;  

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

5 End Uses of Fuel Consumption, 2006; 5 End Uses of Fuel Consumption, 2006; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Residual and Natural Gas(c) LPG and Coke and Breeze) Total Electricity(a) Fuel Oil Diesel Fuel(b) (billion NGL(d) (million Other(e) End Use (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) (trillion Btu) Total United States TOTAL FUEL CONSUMPTION 15,658 835,382 40 22 5,357 21 46 5,820 Indirect Uses-Boiler Fuel -- 12,109 21 4 2,059 2 25 -- Conventional Boiler Use 12,109 11 3 1,245 2 6 CHP and/or Cogeneration Process 0 10 1 814 * 19 Direct Uses-Total Process

127

Estimates of Energy Consumption by Building Type and End Use at U.S. Army Installations  

E-Print Network (OSTI)

4. Figure 5-5. 1993 Electricity Consumption Estimates by EndkWh/ft ) 1993 Electricity Consumption Estimates by End Useof Total) 1993 Electricity Consumption Estimates by End Use

Konopacki, S.J.

2010-01-01T23:59:59.000Z

128

Measuring Short-term Air Conditioner Demand Reductions for Operations and  

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

Measuring Short-term Air Conditioner Demand Reductions for Operations and Measuring Short-term Air Conditioner Demand Reductions for Operations and Settlement Title Measuring Short-term Air Conditioner Demand Reductions for Operations and Settlement Publication Type Report LBNL Report Number LBNL-5330E Year of Publication 2012 Authors Bode, Josh, Michael J. Sullivan, and Joseph H. Eto Pagination 120 Date Published 01/2012 Publisher LBNL City Berkeley Keywords consortium for electric reliability technology solutions (certs), electricity markets and policy group, energy analysis and environmental impacts department Abstract Several recent demonstrations and pilots have shown that air conditioner (AC) electric loads can be controlled during the summer cooling season to provide ancillary services and improve the stability and reliability of the electricity grid. A key issue for integration of air conditioner load control into grid operations is how to accurately measure shorter-term (e.g., ten's of minutes to a couple of hours) demand reductions from AC load curtailments for operations and settlement. This report presents a framework for assessing the accuracy of shorter-term AC load control demand reduction measurements. It also compares the accuracy of various alternatives for measuring AC reductions - including methods that rely on regression analysis, load matching and control groups - using feeder data, household data and AC end-use data. A practical approach is recommended for settlement that relies on set of tables, updated annually, with pre-calculated load reduction estimates. The tables allow users to look up the demand reduction per device based on the daily maximum temperature, geographic region and hour of day and simplify the settlement process.

129

Commercial & Industrial Demand Response  

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

Resources News & Events Expand News & Events Skip navigation links Smart Grid Demand Response Agricultural Residential Demand Response Commercial & Industrial Demand Response...

130

High Temperatures & Electricity Demand  

E-Print Network (OSTI)

High Temperatures & Electricity Demand An Assessment of Supply Adequacy in California Trends.......................................................................................................1 HIGH TEMPERATURES AND ELECTRICITY DEMAND.....................................................................................................................7 SECTION I: HIGH TEMPERATURES AND ELECTRICITY DEMAND ..........................9 BACKGROUND

131

Smart Buildings and Demand Response  

Science Journals Connector (OSTI)

Advances in communications and control technology the strengthening of the Internet and the growing appreciation of the urgency to reduce demand side energy use are motivating the development of improvements in both energy efficiency and demand response (DR) systems in buildings. This paper provides a framework linking continuous energy management and continuous communications for automated demand response (Auto?DR) in various times scales. We provide a set of concepts for monitoring and controls linked to standards and procedures such as Open Automation Demand Response Communication Standards (OpenADR). Basic building energy science and control issues in this approach begin with key building components systems end?uses and whole building energy performance metrics. The paper presents a framework about when energy is used levels of services by energy using systems granularity of control and speed of telemetry. DR when defined as a discrete event requires a different set of building service levels than daily operations. We provide examples of lessons from DR case studies and links to energy efficiency.

2011-01-01T23:59:59.000Z

132

Assessment of U.S. Electric End-Use Energy Efficiency Potential  

SciTech Connect

Demand-side management holds significant potential to reduce growth in U.S. energy consumption and peak demand, and in a cost-effective manner. But significant policy interventions will be required to achieve these benefits. (author)

Gellings, Clark W.; Wikler, Greg; Ghosh, Debyani

2006-11-15T23:59:59.000Z

133

Report: Impacts of Demand-Side Resources on Electric Transmission Planning  

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

Demand for new transmission can be driven by different factors, including connection of new generation, reliability, economics, environmental policy compliance and replacement of retiring infrastructure. This report assesses the relationship between high levels of demand-side resources (including end-use efficiency, demand response, and distributed generation) and investment in new transmission or utilization of existing transmission.

134

Development of an End-Use Sector- Based Low-Carbon Indicator System for  

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

Development of an End-Use Sector- Based Low-Carbon Indicator System for Development of an End-Use Sector- Based Low-Carbon Indicator System for Cities in China Title Development of an End-Use Sector- Based Low-Carbon Indicator System for Cities in China Publication Type Conference Proceedings Year of Publication 2012 Authors Price, Lynn K., Nan Zhou, David Fridley, Hongyou Lu, Nina Zheng, Cecilia Fino-Chen, and Stephanie Ohshita Conference Name the ACEEE's 2012 Summer Study on Energy Efficiency in Buildings Date Published 08/2012 Publisher the American Council for an Energy-Efficient Economy Conference Location Pacific Grove, California, U.S.A. Keywords 12th five year plan, buildings, china, china energy, china energy group, co2 emissions, energy analysis and environmental impacts department, low carbon indicator, policy studies

135

AEO2011: Natural Gas Delivered Prices by End-Use Sector and Census Division  

Open Energy Info (EERE)

Delivered Prices by End-Use Sector and Census Division Delivered Prices by End-Use Sector and Census Division Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 137, and contains only the reference case. This dataset is in trillion cubic feet. The data is broken down into residential, commercial, industrial, electric power and transportation. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Natural Gas Data application/vnd.ms-excel icon AEO2011: Natural Gas Delivered Prices by End-Use Sector and Census Division- Reference Case (xls, 140.7 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually

136

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

Open Energy Info (EERE)

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

137

Service Report Enwgy Information Administration Office of Energy Markets and End Use  

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

Enwgy Information Administration Enwgy Information Administration Office of Energy Markets and End Use U;S. Department of Energy Washington, O.C. 20585 ^ ± SR-EEUD--84-I leather izat ion Program Evaluation §]*: b? .. Gerald E. Pealjody of Energy Markets and End Use Energy End Use Division August 20, 1984 This raport has not received a complete technical review by the Energy In formation Administration (E1A) and, therefore, should not be represented as an official EIA product. |||lsS|; program in 198 l^^lRia; study is based -on a scatii;f|^ipiiii|', national samp 1* Of : - households chac aarcicipscac in the pr; 3 §S||tMi-lfc|Sis2?ia covers ;he ^tiecrr^n: of conditions under vhich the p This ,s«;;5^H:«lil-lSi|iuGcaG ac che requesic of :rva

138

Service Report Energy Information Administration Office of Energy Markets and End Use  

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

Energy Information Administration Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, D C 20585 SR/EEUD/86/01 Residential Conservation Measures Energy End Use Division Office of Energy Markets and End Use Energy Information Administration July 1986 This report has not received a complete technical review by the Energy In formation Administration (EIA) and, therefore, should not be represented as an official EIA product. PREFACE This study was undertaken at the request of Senator James A. McClure, Chairman, Committee on Energy and Natural Resources, United States Senate. The purpose of the study is to examine the potential for achieving energy savings in the residential sector through conservation measures. The report is to be submitted

139

Assessment of Interval Data and Their Potential Application to Residential Electricity End-Use Modeling, An  

Reports and Publications (EIA)

The Energy Information Administration (EIA) is investigating the potential benefits of incorporating interval electricity data into its residential energy end use models. This includes interval smart meter and submeter data from utility assets and systems. It is expected that these data will play a significant role in informing residential energy efficiency policies in the future. Therefore, a long-term strategy for improving the RECS end-use models will not be complete without an investigation of the current state of affairs of submeter data, including their potential for use in the context of residential building energy modeling.

2015-01-01T23:59:59.000Z

140

Estimates of energy consumption by building type and end use at U.S. Army installations  

SciTech Connect

This report discusses the use of LBNL`s End-use Disaggregation Alogrithm (EDA) to 12 US Army installations nationwide in order to obtain annual estimates of electricity use for all major building types and end uses. The building types include barrack, dining hall, gymnasium, administration, vehicle maintenance, hospital, residential, warehouse, and misc. Up to 8 electric end uses for each type were considered: space cooling, ventilation (air handling units, fans, chilled and hot water pumps), cooking, misc./plugs, refrigeration, exterior and interior lighting, and process loads. Through building simulations, we also obtained estimates of natural gas space heating energy use. Average electricity use for these 12 installations and Fort Hood are: HVAC, misc., and indoor lighting end uses consumed the most electricity (28, 27, and 26% of total[3.8, 3.5, and 3.3 kWh/ft{sup 2}]). Refrigeration, street lighting, exterior lighting, and cooking consumed 7, 7, 3, and 2% of total (0.9, 0.9, 0.4, and 0.3 kWh/ft{sup 2})

Konopacki, S.J.; Akbari, H.

1996-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "demand ten end-use" 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

Estimates of Energy Consumption by Building Type and End Use at U.S. Army Installations  

E-Print Network (OSTI)

energy use intensity (EUI) by end use for major buildingare shown in Table 3-4. EDA_EUI j k u a l ) l A v a C j i jk annualihvaCii jjj x EDA_EUI ai,hvac,FtHood = EDA.EUIaniiu^

Konopacki, S.J.

2010-01-01T23:59:59.000Z

142

Impacts of Temperature Variation on Energy Demand in Buildings (released in AEO2005)  

Reports and Publications (EIA)

In the residential and commercial sectors, heating and cooling account for more than 40% of end-use energy demand. As a result, energy consumption in those sectors can vary significantly from year to year, depending on yearly average temperatures.

2005-01-01T23:59:59.000Z

143

Modelling useful energy demand system as derived from basic needs in the household sector  

Science Journals Connector (OSTI)

Inter-fuel substitution in the household sector depends on whether their target energy use is similar or not. To account ... for the effect of end-use application on energy demand, the concept of useful energy is...

Zahra A. Barkhordar; Yadollah Saboohi

2014-10-01T23:59:59.000Z

144

Assumptions to the Annual Energy Outlook 2002 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The distinction between the two sets of manufacturing industries pertains to the level of modeling. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 19). The Industrial Demand Module forecasts energy consumption at the four Census region levels; energy consumption at the Census Division level is allocated

145

"Code(a)","End Use","for Electricity(b)","Fuel Oil","Diesel Fuel...  

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

for Table 5.4;" " Unit: Percents." " "," ",," ","Distillate"," "," " " "," ",,,"Fuel Oil",,,"Coal" "NAICS"," ","Net Demand","Residual","and",,"LPG and","(excluding Coal"...

146

China's energy and emissions outlook to 2050: Perspectives from bottom-up energy end-use model  

E-Print Network (OSTI)

CCS) technology and demand side management. 2.1. Scenariosgeneration and demand-side management that differentiate thedispatch order Demand side management Installed capacity of

Zhou, Nan

2014-01-01T23:59:59.000Z

147

China's energy and emissions outlook to 2050: Perspectives from bottom-up energy end-use model  

E-Print Network (OSTI)

Implications for Chinese energy demand and imports in 2020.for China to reduce energy demand and emissions. Thisand physical drivers of energy demand and thereby help

Zhou, Nan

2014-01-01T23:59:59.000Z

148

Advanced Demand Responsive Lighting  

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

Demand Demand Responsive Lighting Host: Francis Rubinstein Demand Response Research Center Technical Advisory Group Meeting August 31, 2007 10:30 AM - Noon Meeting Agenda * Introductions (10 minutes) * Main Presentation (~ 1 hour) * Questions, comments from panel (15 minutes) Project History * Lighting Scoping Study (completed January 2007) - Identified potential for energy and demand savings using demand responsive lighting systems - Importance of dimming - New wireless controls technologies * Advanced Demand Responsive Lighting (commenced March 2007) Objectives * Provide up-to-date information on the reliability, predictability of dimmable lighting as a demand resource under realistic operating load conditions * Identify potential negative impacts of DR lighting on lighting quality Potential of Demand Responsive Lighting Control

149

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

Gasoline and Diesel Fuel Update (EIA)

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

150

Microsoft Word - US Industrial Sector Energy End Use Analysis_051812.docx  

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

United States Industrial Sector Energy End Use Analysis United States Industrial Sector Energy End Use Analysis Arman Shehabi, William R. Morrow, Eric Masanet This work was supported by the Advanced Manufacturing Office of the Energy Efficiency and Renewable Energy Program through the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. 2 Disclaimer This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process

151

"Table B25. Energy End Uses, Floorspace for Non-Mall Buildings, 2003"  

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

5. Energy End Uses, Floorspace for Non-Mall Buildings, 2003" 5. Energy End Uses, Floorspace for Non-Mall Buildings, 2003" ,"Total Floorspace (million square feet)" ,"All Buildings*","Energy Used For (more than one may apply)" ,,"Space Heating","Cooling","Water Heating","Cooking","Manu- facturing" "All Buildings* ...............",64783,60028,56940,56478,22237,3138 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",6789,5668,5007,4759,997,"Q" "5,001 to 10,000 ..............",6585,5786,5408,5348,1136,214 "10,001 to 25,000 .............",11535,10387,9922,9562,1954,472 "25,001 to 50,000 .............",8668,8060,7776,7734,2511,"Q"

152

End-use energy consumption estimates for U.S. commercial buildings, 1992  

SciTech Connect

An accurate picture of how energy is used in the nation`s stock of commercial buildings can serve a variety of program planning and policy needs of the US Department of Energy, utilities, and other groups seeking to improve the efficiency of energy use in the building sector. This report describes an estimation of energy consumption by end use based upon data from the 1992 Commercial Building Energy Consumption Survey (CBECS). The methodology used in the study combines elements of engineering simulations and statistical analysis to estimate end-use intensities for heating, cooling, ventilation, lighting, refrigeration, hot water, cooking, and miscellaneous equipment. Statistical Adjusted Engineering (SAE) models were estimated by building type. The nonlinear SAE models used variables such as building size, vintage, climate region, weekly operating hours, and employee density to adjust the engineering model predicted loads to the observed consumption (based upon utility billing information). End-use consumption by fuel was estimated for each of the 6,751 buildings in the 1992 CBECS. The report displays the summary results for 11 separate building types as well as for the total US commercial building stock. 4 figs., 15 tabs.

Belzer, D.B.; Wrench, L.E.

1997-03-01T23:59:59.000Z

153

EIA - AEO2010 - Natural Gas Demand  

Gasoline and Diesel Fuel Update (EIA)

Gas Demand Gas Demand Annual Energy Outlook 2010 with Projections to 2035 Natural Gas Demand Figure 68. Regional growth in nonhydroelectric renewable electricity capacity including end-use capacity, 2008-2035 Click to enlarge » Figure source and data excel logo Figure 69. Annual average lower 48 wellhead and Henry Hub spot market prices for natural gas, 1990-2035. Click to enlarge » Figure source and data excel logo Figure 70. Ratio of low-sulfur light crude oil price to Henry Hub natural gas price on an energy equivalent basis, 1990-2035 Click to enlarge » Figure source and data excel logo Figure 71. Annual average lower 48 wellhead prices for natural gas in three technology cases, 1990-2035. Click to enlarge » Figure source and data excel logo Figure 72. Annual average lower 48 wellhead prices for natural gas in three oil price cases, 1990-2035

154

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

Addressing Energy Demand through Demand Response:both the avoided energy costs (and demand charges) as wellCoordination of Energy Efficiency and Demand Response,

Shen, Bo

2013-01-01T23:59:59.000Z

155

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

E-Print Network (OSTI)

and the size of refrigerators and freezers; for all otherwhile water heating, refrigerator, and freezer end-uses showas projected by REEPS. Refrigerator and freezer percentage

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

156

Demand Response Valuation Frameworks Paper  

E-Print Network (OSTI)

benefits of Demand Side Management (DSM) are insufficient toefficiency, demand side management (DSM) cost effectivenessResearch Center Demand Side Management Demand Side Resources

Heffner, Grayson

2010-01-01T23:59:59.000Z

157

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

E-Print Network (OSTI)

LBL-34045 UC-1600 Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting-uses include Heating, Ventilation and Air Conditioning (HVAC). Our analysis uses the modeling framework provided by the HVAC module in the Residential End-Use Energy Planning System (REEPS), which was developed

158

"Code(a)","End Use","Electricity(b)","Fuel Oil","Diesel Fuel(c)"," Gas(d)","NGL(e)","Coke and Breeze)"  

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

3 Relative Standard Errors for Table 5.3;" 3 Relative Standard Errors for Table 5.3;" " Unit: Percents." " "," " " "," ",," ","Distillate"," "," " " "," ","Net Demand",,"Fuel Oil",,,"Coal" "NAICS"," ","for ","Residual","and","Natural","LPG and","(excluding Coal" "Code(a)","End Use","Electricity(b)","Fuel Oil","Diesel Fuel(c)"," Gas(d)","NGL(e)","Coke and Breeze)" ,,"Total United States" " 311 - 339","ALL MANUFACTURING INDUSTRIES" ,"TOTAL FUEL CONSUMPTION",2,3,6,2,4,9

159

Mass Market Demand Response  

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

Mass Market Demand Response Mass Market Demand Response Speaker(s): Karen Herter Date: July 24, 2002 - 12:00pm Location: Bldg. 90 Demand response programs are often quickly and poorly crafted in reaction to an energy crisis and disappear once the crisis subsides, ensuring that the electricity system will be unprepared when the next crisis hits. In this paper, we propose to eliminate the event-driven nature of demand response programs by considering demand responsiveness a component of the utility obligation to serve. As such, demand response can be required as a condition of service, and the offering of demand response rates becomes a requirement of utilities as an element of customer service. Using this foundation, we explore the costs and benefits of a smart thermostat-based demand response system capable of two types of programs: (1) a mandatory,

160

Demand Response Assessment INTRODUCTION  

E-Print Network (OSTI)

Demand Response Assessment INTRODUCTION This appendix provides more detail on some of the topics raised in Chapter 4, "Demand Response" of the body of the Plan. These topics include 1. The features, advantages and disadvantages of the main options for stimulating demand response (price mechanisms

Note: This page contains sample records for the topic "demand ten end-use" 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

DemandDirect | Open Energy Information  

Open Energy Info (EERE)

DemandDirect DemandDirect Jump to: navigation, search Name DemandDirect Place Woodbury, Connecticut Zip 6798 Sector Efficiency, Renewable Energy, Services Product DemandDirect provides demand response, energy efficiency, load management, and distributed generation services to end-use electricity customers in order to reduce electricity consumption, improve grid reliability, and promote renewable energy. Coordinates 44.440496°, -72.414991° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":44.440496,"lon":-72.414991,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

162

Energy Information Administration - Energy Efficiency, Table 6b-End Uses of  

Gasoline and Diesel Fuel Update (EIA)

and 2002 > Table 6b and 2002 > Table 6b Table 6b. End Uses of Energy per Ton of Steel, 1998, 2002, and 2006 (thousand Btu per ton) MECS Survey Years Iron and Steel Mills (NAICS1 331111) 19982 20022 20062 Total3 16,957 15,884 17,796 Net Electricity 4 1,602 2,009 4,673 Natural Gas 4,625 4,236 5,969 Coal 487 393 214 Boiler Fuel -- -- -- Coal 81 W 10 Residual Fuel Oil 101 W 266 Natural Gas 527 426 276 Process Heating -- -- -- Net Electricity 751 862 830 Residual Fuel Oil 193 W 112 Natural Gas 3,742 3,592 2,776 Machine Drive -- -- -- Net Electricity 690 939 786 Notes: 1. The North American Industry Classification System (NAICS) has replaced the Standard Industrial Classification (SIC) system. NAICS 331111 includes steel works, blast furnaces (including coke ovens), and rolling mills.

163

Residential Lighting End-Use Consumption Study: Estimation Framework and Initial Estimates  

SciTech Connect

The U.S. DOE Residential Lighting End-Use Consumption Study is an initiative of the U.S. Department of Energy’s (DOE’s) Solid-State Lighting Program that aims to improve the understanding of lighting energy usage in residential dwellings. The study has developed a regional estimation framework within a national sample design that allows for the estimation of lamp usage and energy consumption 1) nationally and by region of the United States, 2) by certain household characteristics, 3) by location within the home, 4) by certain lamp characteristics, and 5) by certain categorical cross-classifications (e.g., by dwelling type AND lamp type or fixture type AND control type).

Gifford, Will R.; Goldberg, Miriam L.; Tanimoto, Paulo M.; Celnicker, Dane R.; Poplawski, Michael E.

2012-12-01T23:59:59.000Z

164

Technology data characterizing water heating in commercial buildings: Application to end-use forecasting  

SciTech Connect

Commercial-sector conservation analyses have traditionally focused on lighting and space conditioning because of their relatively-large shares of electricity and fuel consumption in commercial buildings. In this report we focus on water heating, which is one of the neglected end uses in the commercial sector. The share of the water-heating end use in commercial-sector electricity consumption is 3%, which corresponds to 0.3 quadrillion Btu (quads) of primary energy consumption. Water heating accounts for 15% of commercial-sector fuel use, which corresponds to 1.6 quads of primary energy consumption. Although smaller in absolute size than the savings associated with lighting and space conditioning, the potential cost-effective energy savings from water heaters are large enough in percentage terms to warrant closer attention. In addition, water heating is much more important in particular building types than in the commercial sector as a whole. Fuel consumption for water heating is highest in lodging establishments, hospitals, and restaurants (0.27, 0.22, and 0.19 quads, respectively); water heating`s share of fuel consumption for these building types is 35%, 18% and 32%, respectively. At the Lawrence Berkeley National Laboratory, we have developed and refined a base-year data set characterizing water heating technologies in commercial buildings as well as a modeling framework. We present the data and modeling framework in this report. The present commercial floorstock is characterized in terms of water heating requirements and technology saturations. Cost-efficiency data for water heating technologies are also developed. These data are intended to support models used for forecasting energy use of water heating in the commercial sector.

Sezgen, O.; Koomey, J.G.

1995-12-01T23:59:59.000Z

165

Definition: Interruptible Load Or Interruptible Demand | Open Energy  

Open Energy Info (EERE)

Interruptible Load Or Interruptible Demand Interruptible Load Or Interruptible Demand Jump to: navigation, search Dictionary.png Interruptible Load Or Interruptible Demand Demand that the end-use customer makes available to its Load-Serving Entity via contract or agreement for curtailment.[1] View on Wikipedia Wikipedia Definition View on Reegle Reegle Definition No reegle definition available. Also Known As non-firm service Related Terms transmission lines, electricity generation, transmission line, firm transmission service, smart grid References ↑ Glossary of Terms Used in Reliability Standards An inli LikeLike UnlikeLike You like this.Sign Up to see what your friends like. ne Glossary Definition Retrieved from "http://en.openei.org/w/index.php?title=Definition:Interruptible_Load_Or_Interruptible_Demand&oldid=502615"

166

EIA - Assumptions to the Annual Energy Outlook 2008 - Industrial Demand  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2008 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 21 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module projects energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region projection using the SEDS1 data.

167

EIA - Assumptions to the Annual Energy Outlook 2008 - Commercial Demand  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2008 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIAÂ’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.1

168

EIA - Assumptions to the Annual Energy Outlook 2009 - Commercial Demand  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2009 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIAÂ’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.1

169

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

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2009 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2035. The definition of the commercial sector is consistent with EIAÂ’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services [1].

170

Scenario Analysis of Peak Demand Savings for Commercial Buildings with  

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

Scenario Analysis of Peak Demand Savings for Commercial Buildings with Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California Title Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California Publication Type Conference Paper LBNL Report Number LBNL-3636e Year of Publication 2010 Authors Yin, Rongxin, Sila Kiliccote, Mary Ann Piette, and Kristen Parrish Conference Name 2010 ACEEE Summer Study on Energy Efficiency in Buildings Conference Location Pacific Grove, CA Keywords demand response and distributed energy resources center, demand response research center, demand shifting (pre-cooling), DRQAT Abstract This paper reports on the potential impact of demand response (DR) strategies in commercial buildings in California based on the Demand Response Quick Assessment Tool (DRQAT), which uses EnergyPlus simulation prototypes for office and retail buildings. The study describes the potential impact of building size, thermal mass, climate, and DR strategies on demand savings in commercial buildings. Sensitivity analyses are performed to evaluate how these factors influence the demand shift and shed during the peak period. The whole-building peak demand of a commercial building with high thermal mass in a hot climate zone can be reduced by 30% using an optimized demand response strategy. Results are summarized for various simulation scenarios designed to help owners and managers understand the potential savings for demand response deployment. Simulated demand savings under various scenarios were compared to field-measured data in numerous climate zones, allowing calibration of the prototype models. The simulation results are compared to the peak demand data from the Commercial End-Use Survey for commercial buildings in California. On the economic side, a set of electricity rates are used to evaluate the impact of the DR strategies on economic savings for different thermal mass and climate conditions. Our comparison of recent simulation to field test results provides an understanding of the DR potential in commercial buildings.

171

Ten Years of Public Acceptance in Transports  

SciTech Connect

This paper discusses ten years of public acceptance experience in transports for Europe and coastal states between France and Japan and examples of Central and South America.

Guais, J.C.; Neau, H.J.

2004-10-03T23:59:59.000Z

172

Public Meeting: Physical Characterization of Smart and Grid-Connected Commercial and Residential Building End-Use Equipment and Appliances  

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

These documents contain slide decks presented at the Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances public meeting held on April 30, 2014.

173

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

E-Print Network (OSTI)

Richard E. Brown, James W. Hanford, Alan H . Sanstad, andFrancis X . , James W. Hanford, Richard E. Brown, Alan H.place for these end-uses (Hanford et al. 1994, Hwang et al.

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

174

Measured commercial load shapes and energy-use intensities and validation of the LBL end-use disaggregation algorithm  

SciTech Connect

The Southern California Edison Company (SCE) has conducted an extensive metering project in which electricity end use in 53 commercial buildings in Southern California has been measured. The building types monitored include offices, retail stores, groceries, restaurants, and warehouses. One year (June 1989 through May 1990) of the SCE measured hourly end-use data are reviewed in this report. Annual whole-building and end-use energy use intensities (EUIs) and monthly load shapes (LSs) have been calculated for the different building types based on the monitored data. This report compares the monitored buildings' EUIs and LSs to EUIs and LSs determined using whole-building load data and the End-Use Disaggregation Algorithm (EDA). Two sets of EDA determined EUIs and LSs are compared to the monitored data values. The data sets represent: (1) average buildings in the SCE service territory and (2) specific buildings that were monitored.

Akbari, H.; Rainer, L.; Heinemeier, K.; Huang, J.; Franconi, E.

1993-01-01T23:59:59.000Z

175

Demand response enabling technology development  

E-Print Network (OSTI)

Demand Response Enabling Technology Development Phase IEfficiency and Demand Response Programs for 2005/2006,Application to Demand Response Energy Pricing” SenSys 2003,

2006-01-01T23:59:59.000Z

176

Demand Response Spinning Reserve Demonstration  

E-Print Network (OSTI)

F) Enhanced ACP Date RAA ACP Demand Response – SpinningReserve Demonstration Demand Response – Spinning Reservesupply spinning reserve. Demand Response – Spinning Reserve

2007-01-01T23:59:59.000Z

177

Cross-sector Demand Response  

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

Resources News & Events Expand News & Events Skip navigation links Smart Grid Demand Response Agricultural Residential Demand Response Commercial & Industrial Demand Response...

178

Demand Response Programs for Oregon  

E-Print Network (OSTI)

Demand Response Programs for Oregon Utilities Public Utility Commission May 2003 Public Utility ....................................................................................................................... 1 Types of Demand Response Programs............................................................................ 3 Demand Response Programs in Oregon

179

Demand response enabling technology development  

E-Print Network (OSTI)

behavior in developing a demand response future. Phase_II_Demand Response Enabling Technology Development Phase IIYi Yuan The goal of the Demand Response Enabling Technology

Arens, Edward; Auslander, David; Huizenga, Charlie

2008-01-01T23:59:59.000Z

180

Automated Demand Response and Commissioning  

E-Print Network (OSTI)

Fully-Automated Demand Response Test in Large Facilities14in DR systems. Demand Response using HVAC in Commercialof Fully Automated Demand Response in Large Facilities”

Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Bourassa, Norman

2005-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "demand ten end-use" 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

Demand Response In California  

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

Presentation covers the demand response in California and is given at the FUPWG 2006 Fall meeting, held on November 1-2, 2006 in San Francisco, California.

182

Energy Demand Forecasting  

Science Journals Connector (OSTI)

This chapter presents alternative approaches used in forecasting energy demand and discusses their pros and cons. It... Chaps. 3 and 4 ...

S. C. Bhattacharyya

2011-01-01T23:59:59.000Z

183

Energy Information Administration - Energy Efficiency-Table 6a- End uses of  

Gasoline and Diesel Fuel Update (EIA)

6a 6a Page Last Modified: June 2010 Table 6a. End Uses of Fuel Consumption per Value of Production, 1998, 2002, and 2006 (thousand Btu per constant 2000 dollar 1) MECS Survey Years Iron and Steel Mills (NAICS2 331111) 1998 3 2002 3 2006 3 Total 4 32.0 30.2 18.7 Net Electricity 5 3.0 3.8 2.8 Natural Gas 8.7 8.1 5.3 Coal 0.9 0.7 0.2 Boiler Fuel -- -- -- Coal 0.2 W 0.02 Residual Fuel Oil 0.2 * 0.1 Natural Gas 1.0 0.8 0.4 Process Heating -- -- -- Net Electricity 1.4 1.6 1.2 Residual Fuel Oil 0.4 * 0.2 Natural Gas 7.1 6.8 4.4 Machine Drive -- -- -- Net Electricity 1.3 1.8 1.3 Notes:1. Value of production is deflated by the chain-type price indices for iron and steel mills shipments. 2. The North American Industry Classification System (NAICS) has replaced the Standard Industrial Classification (SIC) system. NAICS 331111 includes steel works, blast furnaces (including coke ovens), and rolling mills.

184

Global warming and end-use efficiency implications of replacing CFCs  

SciTech Connect

The direct contribution of CFCs to calculated global warming has been recognized for some time. As a result of the international agreement to phase out CFCs due to stratospheric ozone and the ensuing search for suitable alternatives, there has recently been increased attention on the DIRECT global warming potential (GWP) of the fluorocarbon alternatives as greenhouse gases. However, to date there has been little focus on the INDIRECT global warming effect arising from end-use efficiency changes and associated CO{sub 2} emissions. A study being conducted at Oak Ridge National Laboratory (ORNL) addresses this combined or total global warming impact of viable options to replace CFCs in their major energy-related applications. This paper reviews selected results for air-conditioning, refrigeration, and heat pump applications. The analysis indicates that the CFC user industries have made substantial progress in approaching near-equal energy efficiency with the HCFC/HFC alternative refrigerants. The findings also bring into question the relative importance of the DIRECT (chemical-related) effect in many applications. Replacing CFCs is an important step in reducing the total global warming impact, and at present the HCFC and HFCS appear to offer the best efficiency and lowest total impact of options available in the relatively short time period required for the transition away from CFCs.

Fairchild, P.D.; Fischer, S.K.

1991-12-31T23:59:59.000Z

185

most are government agencies --local, national and international. A ten-year industry forecast put together  

E-Print Network (OSTI)

most are government agencies -- local, national and international. A ten-year industry forecast put environmental, civil government, defence and security, and transportation as the most active market segments combine geographic information systems with satellite data are in demand in a variety of disciplines

Wisconsin at Madison, University of

186

Significant ELCAP analysis results: Summary report. [End-use Load and Consumer Assessment Program  

SciTech Connect

The evolution of the End-Use Load and Consumer Assessment Program (ELCAP) since 1983 at Bonneville Power Administration (Bonneville) has been eventful and somewhat tortuous. The birth pangs of a data set so large and encompassing as this have been overwhelming at times. The early adolescent stage of data set development and use has now been reached and preliminary results of early analyses of the data are becoming well known. However, the full maturity of the data set and the corresponding wealth of analytic insights are not fully realized. This document is in some sense a milestone in the brief history of the program. It is a summary of the results of the first five years of the program, principally containing excerpts from a number of previous reports. It is meant to highlight significant accomplishments and analytical results, with a focus on the principal results. Many of the results have a broad application in the utility load research community in general, although the real breadth of the data set remains largely unexplored. The first section of the document introduces the data set: how the buildings were selected, how the metering equipment was installed, and how the data set has been prepared for analysis. Each of the sections that follow the introduction summarize a particular analytic result. A large majority of the analyses to date involve the residential samples, as these were installed first and had highest priority on the analytic agenda. Two exploratory analyses using commercial data are included as an introduction to the commercial analyses that are currently underway. Most of the sections reference more complete technical reports which the reader should refer to for details of the methodology and for more complete discussion of the results. Sections have been processed separately for inclusion on the data base.

Pratt, R.G.; Conner, C.C.; Drost, M.K.; Miller, N.E.; Cooke, B.A.; Halverson, M.A.; Lebaron, B.A.; Lucas, R.G.; Jo, J.; Richman, E.E.; Sandusky, W.F. (Pacific Northwest Lab., Richland, WA (USA)); Ritland, K.G. (Ritland Associates, Seattle, WA (USA)); Taylor, M.E. (USDOE Bonneville Power Administration, Portland, OR (USA)); Hauser, S.G. (Solar Energy Research Inst., Golden, CO (USA))

1991-02-01T23:59:59.000Z

187

Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study  

SciTech Connect

This study assesses for California how increasing end-use electrical energy efficiency from installing residential insulation impacts exposures and disease burden from power-plant pollutant emissions. Installation of fiberglass attic insulation in the nearly 3 million electricity-heated homes throughout California is used as a case study. The pollutants nitrous oxides (NO{sub x}), sulfur dioxide (SO{sub 2}), fine particulate matter (PM2.5), benzo(a)pyrene, benzene, and naphthalene are selected for the assessment. Exposure is characterized separately for rural and urban environments using the CalTOX model, which is a key input to the US Environmental Protection Agency (EPA) Tool for the Reduction and Assessment of Chemicals and other environmental Impacts (TRACI). The output of CalTOX provides for urban and rural populations emissions-to-intake factors, which are expressed as an individual intake fraction (iFi). The typical iFi from power plant emissions are on the order of 10{sup -13} (g intake per g emitted) in urban and rural regions. The cumulative (rural and urban) product of emissions, population, and iFi is combined with toxic effects factors to determine human damage factors (HDFs). HDF are expressed as disability adjusted life years (DALYs) per kilogram pollutant emitted. The HDF approach is applied to the insulation case study. Upgrading existing residential insulation to US Department of Energy (DOE) recommended levels eliminates over the assmned 50-year lifetime of the insulation an estimated 1000 DALYs from power-plant emissions per million tonne (Mt) of insulation installed, mostly from the elimination of PM2.5 emissions. In comparison, the estimated burden from the manufacture of this insulation in DALYs per Mt is roughly four orders of magnitude lower than that avoided.

McKone, Thomas E.; Lobscheid, A.B.

2006-06-01T23:59:59.000Z

188

Benefits of Demand Response in Electricity Markets and Recommendations for  

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

Demand Response in Electricity Markets and Demand Response in Electricity Markets and Recommendations for Achieving Them. A report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005 (February 2006) Benefits of Demand Response in Electricity Markets and Recommendations for Achieving Them. A report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005 (February 2006) Most electricity customers see electricity rates that are based on average electricity costs and bear little relation to the true production costs of electricity as they vary over time. Demand response is a tariff or program established to motivate changes in electric use by end-use customers in response to changes in the price of electricity over time, or to give

189

EIA - Assumptions to the Annual Energy Outlook 2009 - Industrial Demand  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2009 Industrial Demand Module Table 6.1. Industry Categories. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Table 6.2.Retirement Rates. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries (Table 6.1). The manufacturing industries are modeled through the use of a detailed process flow or end use accounting

190

Detailed Modeling and Response of Demand Response Enabled Appliances  

SciTech Connect

Proper modeling of end use loads is very important in order to predict their behavior, and how they interact with the power system, including voltage and temperature dependencies, power system and load control functions, and the complex interactions that occur between devices in such an interconnected system. This paper develops multi-state time variant residential appliance models with demand response enabled capabilities in the GridLAB-DTM simulation environment. These models represent not only the baseline instantaneous power demand and energy consumption, but the control systems developed by GE Appliances to enable response to demand response signals and the change in behavior of the appliance in response to the signal. These DR enabled appliances are simulated to estimate their capability to reduce peak demand and energy consumption.

Vyakaranam, Bharat; Fuller, Jason C.

2014-04-14T23:59:59.000Z

191

Ten Year Site Plans | Department of Energy  

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

Ten Year Ten Year Site Plans Ten Year Site Plans A Ten Year Site Plan (TYSP) is the essential planning document linking a site's real property requirements to its mission in support of the Department of Energy's overall strategic plan. It is a comprehensive site-wide plan encompassing the needs of tenant activities. The TYSP is integral to and supports the Department's Planning, Programming, Budgeting, and Evaluation System (PPBES). The TYSP also describes site-specific actions the programs plans in order to meet stewardship, recapitalization and sustainability goals for their facilities. The Department requires all programs to update their TYSPs at least annually and submitted either concurrently with responses to the field budget call, or as directed to be consistent with the PPBES cycle.

192

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2035. The definition of the commercial sector is consistent with EIA's State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA

193

demand | OpenEI  

Open Energy Info (EERE)

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

194

RTP Customer Demand Response  

Science Journals Connector (OSTI)

This paper provides new evidence on customer demand response to hourly pricing from the largest and...real-time pricing...(RTP) program in the United States. RTP creates value by inducing load reductions at times...

Steven Braithwait; Michael O’Sheasy

2002-01-01T23:59:59.000Z

195

World Energy Demand  

Science Journals Connector (OSTI)

A reliable forecast of energy resources, energy consumption, and population in the future is a ... So, instead of absolute figures about future energy demand and sources worldwide, which would become...3.1 correl...

Giovanni Petrecca

2014-01-01T23:59:59.000Z

196

Open Automated Demand Response for Small Commerical Buildings  

SciTech Connect

This report characterizes small commercial buildings by market segments, systems and end-uses; develops a framework for identifying demand response (DR) enabling technologies and communication means; and reports on the design and development of a low-cost OpenADR enabling technology that delivers demand reductions as a percentage of the total predicted building peak electric demand. The results show that small offices, restaurants and retail buildings are the major contributors making up over one third of the small commercial peak demand. The majority of the small commercial buildings in California are located in southern inland areas and the central valley. Single-zone packaged units with manual and programmable thermostat controls make up the majority of heating ventilation and air conditioning (HVAC) systems for small commercial buildings with less than 200 kW peak electric demand. Fluorescent tubes with magnetic ballast and manual controls dominate this customer group's lighting systems. There are various ways, each with its pros and cons for a particular application, to communicate with these systems and three methods to enable automated DR in small commercial buildings using the Open Automated Demand Response (or OpenADR) communications infrastructure. Development of DR strategies must consider building characteristics, such as weather sensitivity and load variability, as well as system design (i.e. under-sizing, under-lighting, over-sizing, etc). Finally, field tests show that requesting demand reductions as a percentage of the total building predicted peak electric demand is feasible using the OpenADR infrastructure.

Dudley, June Han; Piette, Mary Ann; Koch, Ed; Hennage, Dan

2009-05-01T23:59:59.000Z

197

,"U.S. Total Adjusted Distillate Fuel Oil and Kerosene Sales by End Use"  

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

Distillate Fuel Oil and Kerosene Sales by End Use" Distillate Fuel Oil and Kerosene Sales by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Residential",4,"Annual",2012,"6/30/1984" ,"Data 2","Commercial",10,"Annual",2012,"6/30/1984" ,"Data 3","Industrial",9,"Annual",2012,"6/30/1984" ,"Data 4","Farm",4,"Annual",2012,"6/30/1984" ,"Data 5","Electric Power",2,"Annual",2012,"6/30/1984" ,"Data 6","Oil Company",2,"Annual",2012,"6/30/1984"

198

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

shift in the short-run price elasticity of gasoline demand.A meta-analysis of the price elasticity of gasoline demand.2007. Consumer demand un- der price uncertainty: Empirical

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

199

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

analysis of the demand for oil in the Middle East. EnergyEstimates elasticity of demand for crude oil, not gasoline.World crude oil and natural gas: a demand and supply model.

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

200

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

analysis of the demand for oil in the Middle East. EnergyEstimates elasticity of demand for crude oil, not gasoline.World crude oil and natural gas: a demand and supply model.

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "demand ten end-use" 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

TenTen: A New Array of Multi-TeV Imaging Cherenkov Telescopes  

E-Print Network (OSTI)

The exciting results from H.E.S.S. point to a new population of gamma-ray sources at energies E > 10 TeV, paving the way for future studies and new discoveries in the multi-TeV energy range. Connected with these energies is the search for sources of PeV cosmic-rays (CRs) and the study of multi-TeV gamma-ray production in a growing number of astrophysical environments. TenTen is a proposed stereoscopic array (with a suggested site in Australia) of modest-sized (10 to 30m^2) Cherenkov imaging telescopes with a wide field of view (8 to 10deg diameter) optimised for the E~10 to 100 TeV range. TenTen will achieve an effective area of ~10 km^2 at energies above 10 TeV. We outline here the motivation for TenTen and summarise key performance parameters.

Rowell, G; Clay, R; Dawson, B; Denman, J; Protheroe, R; Smith, A G K; Thornton, G; Wild, N

2007-01-01T23:59:59.000Z

202

TenTen: A New Array of Multi-TeV Imaging Cherenkov Telescopes  

E-Print Network (OSTI)

The exciting results from H.E.S.S. point to a new population of gamma-ray sources at energies E > 10 TeV, paving the way for future studies and new discoveries in the multi-TeV energy range. Connected with these energies is the search for sources of PeV cosmic-rays (CRs) and the study of multi-TeV gamma-ray production in a growing number of astrophysical environments. TenTen is a proposed stereoscopic array (with a suggested site in Australia) of modest-sized (10 to 30m^2) Cherenkov imaging telescopes with a wide field of view (8 to 10deg diameter) optimised for the E~10 to 100 TeV range. TenTen will achieve an effective area of ~10 km^2 at energies above 10 TeV. We outline here the motivation for TenTen and summarise key performance parameters.

G. Rowell; V. Stamatescu; R. Clay; B. Dawson; J. Denman; R. Protheroe; A. G. K. Smith; G. Thornton; N. Wild

2007-10-10T23:59:59.000Z

203

Changing Energy Demand Behavior: Potential of Demand-Side Management  

Science Journals Connector (OSTI)

There is a great theoretical potential to save resources by managing our demand for energy. However, demand-side management (DSM) programs targeting behavioral patterns of...

Dr. Sylvia Breukers; Dr. Ruth Mourik…

2013-01-01T23:59:59.000Z

204

End-use load control for power system dynamic stability enhancement  

SciTech Connect

Faced with the prospect of increasing utilization of the transmission and distribution infrastructure without significant upgrade, the domestic electric power utility industry is investing heavily in technologies to improve network dynamic performance through a program loosely referred to as Flexible AC Transmission System (FACTS). Devices exploiting recent advances in power electronics are being installed in the power system to offset the need to construct new transmission lines. These devices collectively represent investment potential of several billion dollars over the next decade. A similar development, designed to curtail the peak loads and thus defer new transmission, distribution, and generation investment, falls under a category of technologies referred to as demand side management (DSM). A subset of broader conservation measures, DSM acts directly on the load to reduce peak consumption. DSM techniques include direct load control, in which a utility has the ability to curtail specific loads as conditions warrant. A novel approach has been conceived by Pacific Northwest National Laboratory (PNNL) to combine the objectives of FACTS and the technologies inherent in DSM to provide a distributed power system dynamic controller. This technology has the potential to dramatically offset major investments in FACTS devices by using direct load control to achieve dynamic stability objectives. The potential value of distributed versus centralized grid modulation has been examined by simulating the western power grid under extreme loading conditions. In these simulations, a scenario is analyzed in which active grid stabilization enables power imports into the southern California region to be increased several hundred megawatts beyond present limitations. Modeling results show distributed load control is up to 30 percent more effective than traditional centralized control schemes in achieving grid stability.

Dagle, J.E.; Winiarski, D.W.; Donnelly, M.K.

1997-02-01T23:59:59.000Z

205

Solar Decathlon Turns Ten | Department of Energy  

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

Turns Ten Turns Ten Solar Decathlon Turns Ten September 28, 2012 - 2:22pm Addthis For the past 10 years, the Solar Decathlon has educated consumers about affordable clean energy products that save energy and money, and provided hands-on training for jobs in the clean energy economy. | Photo courtesy of Stefano Paltera, U.S. Department of Energy Solar Decathlon. For the past 10 years, the Solar Decathlon has educated consumers about affordable clean energy products that save energy and money, and provided hands-on training for jobs in the clean energy economy. | Photo courtesy of Stefano Paltera, U.S. Department of Energy Solar Decathlon. Rebecca Matulka Rebecca Matulka Digital Communications Specialist, Office of Public Affairs Solar Decathlon 2013 The next Solar Decathlon event will be held in Irvine, California,

206

TenKsolar Inc | Open Energy Information  

Open Energy Info (EERE)

TenKsolar Inc TenKsolar Inc Jump to: navigation, search Name tenKsolar Inc Place Bloomington, Minnesota Zip 55431 Product Minnesota-based PV module maker. Coordinates 42.883574°, -90.926122° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":42.883574,"lon":-90.926122,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

207

Solar Decathlon Turns Ten | Department of Energy  

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

Solar Decathlon Turns Ten Solar Decathlon Turns Ten Solar Decathlon Turns Ten September 28, 2012 - 2:22pm Addthis For the past 10 years, the Solar Decathlon has educated consumers about affordable clean energy products that save energy and money, and provided hands-on training for jobs in the clean energy economy. | Photo courtesy of Stefano Paltera, U.S. Department of Energy Solar Decathlon. For the past 10 years, the Solar Decathlon has educated consumers about affordable clean energy products that save energy and money, and provided hands-on training for jobs in the clean energy economy. | Photo courtesy of Stefano Paltera, U.S. Department of Energy Solar Decathlon. Rebecca Matulka Rebecca Matulka Digital Communications Specialist, Office of Public Affairs Solar Decathlon 2013

208

Solar Decathlon Turns Ten | Department of Energy  

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

Solar Decathlon Turns Ten Solar Decathlon Turns Ten Solar Decathlon Turns Ten September 28, 2012 - 2:22pm Addthis For the past 10 years, the Solar Decathlon has educated consumers about affordable clean energy products that save energy and money, and provided hands-on training for jobs in the clean energy economy. | Photo courtesy of Stefano Paltera, U.S. Department of Energy Solar Decathlon. For the past 10 years, the Solar Decathlon has educated consumers about affordable clean energy products that save energy and money, and provided hands-on training for jobs in the clean energy economy. | Photo courtesy of Stefano Paltera, U.S. Department of Energy Solar Decathlon. Rebecca Matulka Rebecca Matulka Digital Communications Specialist, Office of Public Affairs Solar Decathlon 2013

209

Demand Response Valuation Frameworks Paper  

E-Print Network (OSTI)

No. ER06-615-000 CAISO Demand Response Resource User Guide -8 2.1. Demand Response Provides a Range of Benefits to8 2.2. Demand Response Benefits can be Quantified in Several

Heffner, Grayson

2010-01-01T23:59:59.000Z

210

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 39 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2035. The definition of the commercial sector is consistent with EIA's State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial.

211

Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

212

Demand Response In California  

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

Energy Efficiency & Energy Efficiency & Demand Response Programs Dian M. Grueneich, Commissioner Dian M. Grueneich, Commissioner California Public Utilities Commission California Public Utilities Commission FUPWG 2006 Fall Meeting November 2, 2006 Commissioner Dian M. Grueneich November 2, 2006 1 Highest Priority Resource Energy Efficiency is California's highest priority resource to: Meet energy needs in a low cost manner Aggressively reduce GHG emissions November 2, 2006 2 Commissioner Dian M. Grueneich November 2, 2006 3 http://www.cpuc.ca.gov/PUBLISHED/REPORT/51604.htm Commissioner Dian M. Grueneich November 2, 2006 4 Energy Action Plan II Loading order continued "Pursue all cost-effective energy efficiency, first." Strong demand response and advanced metering

213

Analysis of Residential Demand Response and Double-Auction Markets  

SciTech Connect

Demand response and dynamic pricing programs are expected to play increasing roles in the modern Smart Grid environment. While direct load control of end-use loads has existed for decades, price driven response programs are only beginning to be explored at the distribution level. These programs utilize a price signal as a means to control demand. Active markets allow customers to respond to fluctuations in wholesale electrical costs, but may not allow the utility to control demand. Transactive markets, utilizing distributed controllers and a centralized auction can be used to create an interactive system which can limit demand at key times on a distribution system, decreasing congestion. With the current proliferation of computing and communication resources, the ability now exists to create transactive demand response programs at the residential level. With the combination of automated bidding and response strategies coupled with education programs and customer response, emerging demand response programs have the ability to reduce utility demand and congestion in a more controlled manner. This paper will explore the effects of a residential double-auction market, utilizing transactive controllers, on the operation of an electric power distribution system.

Fuller, Jason C.; Schneider, Kevin P.; Chassin, David P.

2011-10-10T23:59:59.000Z

214

On Demand Guarantees in Iran.  

E-Print Network (OSTI)

??On Demand Guarantees in Iran This thesis examines on demand guarantees in Iran concentrating on bid bonds and performance guarantees. The main guarantee types and… (more)

Ahvenainen, Laura

2009-01-01T23:59:59.000Z

215

Computer Ethics Institute page The Ten Commandments  

E-Print Network (OSTI)

Computer Ethics Institute page The Ten Commandments of Computer Ethics by the Computer Ethics and respect for your fellow humans. Computer Ethics Institute A project of the Brookings Institution http://www.brook.edu/its/cei/cei_hp.htm Contact: Ramon Barquin rbarquin@aol.com http://www.cpsr.org/program/ethics/cei.html (1 of 2)11/17/2003 4

Redmiles, David F.

216

Energy Demand Modeling  

Science Journals Connector (OSTI)

From the end of World War II until the early 1970s there was a strong and steady increase in the demand for energy. The abundant supplies of fossil and other ... an actual fall in the real price of energy of abou...

S. L. Schwartz

1980-01-01T23:59:59.000Z

217

The next ten years in the Rockies:  

Science Journals Connector (OSTI)

...permit and build the offshore facilities and pipelines...gas demand by 2020. Wind energy becomes very...times for delivery of wind turbines. Optimistic estimates call for wind to provide 6 of Americas...build a pipeline to an offshore field to recover 100...

Rutt Bridges

218

Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

and clothes drying. In addition to the major equipment-driven and clothes drying. In addition to the major equipment-driven end-uses, the average energy consumption per household is projected for other electric and nonelectric Energy Information Administration/Assumptions to the Annual Energy Outlook 2006 19 Pacific East South Central South Atlantic Middle Atlantic New England West South Central West North Central East North Central Mountain AK WA MT WY ID NV UT CO AZ NM TX OK IA KS MO IL IN KY TN MS AL FL GA SC NC WV PA NJ MD DE NY CT VT ME RI MA NH VA WI MI OH NE SD MN ND AR LA OR CA HI Middle Atlantic New England East North Central West North Central Pacific West South Central East South Central South Atlantic Mountain Figure 5. United States Census Divisions Source:Energy Information Administration,Office of Integrated Analysis and Forecasting. Report #:DOE/EIA-0554(2006) Release date: March 2006

219

Agenda for Public Meeting on the Physical Characterization of Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances  

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

Download the agenda below for the July 11 Public Meeting on the Physical Characterization of Grid-Connected Commercial and  Residential Buildings End-Use Equipment and Appliances.

220

Assumptions to the Annual Energy Outlook - Transportation Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumption to the Annual Energy Outlook Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, sport utility vehicles and vans), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger airplanes, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

Note: This page contains sample records for the topic "demand ten end-use" 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

EIA - Assumptions to the Annual Energy Outlook 2008 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2008 Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger aircraft, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

222

EIA - Assumptions to the Annual Energy Outlook 2009 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2009 Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger aircraft, freight, rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

223

Development and Validation of Aggregated Models for Thermostatic Controlled Loads with Demand Response  

SciTech Connect

Demand response is playing an increasingly important role in smart grid research and technologies being examined in recently undertaken demonstration projects. The behavior of load as it is affected by various load control strategies is important to understanding the degree to which different classes of end-use load can contribute to demand response programs at various times. This paper focuses on developing aggregated control models for a population of thermostatically controlled loads. The effects of demand response on the load population dynamics are investigated.

Kalsi, Karanjit; Elizondo, Marcelo A.; Fuller, Jason C.; Lu, Shuai; Chassin, David P.

2012-01-04T23:59:59.000Z

224

Demand Response | Department of Energy  

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

Demand Response Demand Response Demand Response Demand Response Demand response provides an opportunity for consumers to play a significant role in the operation of the electric grid by reducing or shifting their electricity usage during peak periods in response to time-based rates or other forms of financial incentives. Demand response programs are being used by electric system planners and operators as resource options for balancing supply and demand. Such programs can lower the cost of electricity in wholesale markets, and in turn, lead to lower retail rates. Methods of engaging customers in demand response efforts include offering time-based rates such as time-of-use pricing, critical peak pricing, variable peak pricing, real time pricing, and critical peak rebates. It also includes direct load control programs which provide the

225

Understanding and Analysing Energy Demand  

Science Journals Connector (OSTI)

This chapter introduces the concept of energy demand using basic micro-economics and presents the three-stage decision making process of energy demand. It then provides a set of simple ... (such as price and inco...

Subhes C. Bhattacharyya

2011-01-01T23:59:59.000Z

226

Demand Response: Load Management Programs  

E-Print Network (OSTI)

CenterPoint Load Management Programs CATEE Conference October, 2012 Agenda Outline I. General Demand Response Definition II. General Demand Response Program Rules III. CenterPoint Commercial Program IV. CenterPoint Residential Programs... V. Residential Discussion Points Demand Response Definition of load management per energy efficiency rule 25.181: ? Load control activities that result in a reduction in peak demand, or a shifting of energy usage from a peak to an off...

Simon, J.

2012-01-01T23:59:59.000Z

227

Marketing Demand-Side Management  

E-Print Network (OSTI)

they the only game in town, enjoying a captive market. Demand-side management (DSM) again surfaced as a method for increasing customer value and meeting these competitive challenges. In designing and implementing demand-side management (DSM) programs we... have learned a great deal about what it takes to market and sell DSM. This paper focuses on how to successfully market demand-side management. KEY STEPS TO MARKETING DEMAND-SIDE MANAGEMENT Management Commitment The first key element in marketing...

O'Neill, M. L.

1988-01-01T23:59:59.000Z

228

Demand Charges | Open Energy Information  

Open Energy Info (EERE)

Charges Jump to: navigation, search Retrieved from "http:en.openei.orgwindex.php?titleDemandCharges&oldid488967"...

229

Assessment of Demand Response Resource  

E-Print Network (OSTI)

Assessment of Demand Response Resource Potentials for PGE and Pacific Power Prepared for: Portland January 15, 2004 K:\\Projects\\2003-53 (PGE,PC) Assess Demand Response\\Report\\Revised Report_011504.doc #12;#12;quantec Assessment of Demand Response Resource Potentials for I-1 PGE and Pacific Power I. Introduction

230

ERCOT Demand Response Paul Wattles  

E-Print Network (OSTI)

ERCOT Demand Response Paul Wattles Senior Analyst, Market Design & Development, ERCOT Whitacre;Definitions of Demand Response · `The short-term adjustment of energy use by consumers in response to price to market or reliability conditions.' (NAESB) #12;Definitions of Demand Response · The common threads

Mohsenian-Rad, Hamed

231

Pricing data center demand response  

Science Journals Connector (OSTI)

Demand response is crucial for the incorporation of renewable energy into the grid. In this paper, we focus on a particularly promising industry for demand response: data centers. We use simulations to show that, not only are data centers large loads, ... Keywords: data center, demand response, power network, prediction based pricing

Zhenhua Liu; Iris Liu; Steven Low; Adam Wierman

2014-06-01T23:59:59.000Z

232

Overview of Demand Response  

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

08 PJM 08 PJM www.pjm.com ©2003 PJM Overview of Demand Response PJM ©2008 PJM www.pjm.com ©2003 PJM Growth, Statistics, and Current Footprint AEP, Dayton, ComEd, & DUQ Dominion Generating Units 1,200 + Generation Capacity 165,000 MW Peak Load 144,644 MW Transmission Miles 56,070 Area (Square Miles) 164,250 Members 500 + Population Served 51 Million Area Served 13 States and DC Generating Units 1,200 + Generation Capacity 165,000 MW Peak Load 144,644 MW Transmission Miles 56,070 Area (Square Miles) 164,250 Members 500 + Population Served 51 Million Area Served 13 States and DC Current PJM RTO Statistics Current PJM RTO Statistics PJM Mid-Atlantic Integrations completed as of May 1 st , 2005 ©2008 PJM

233

Oxygenate Supply/Demand Balances  

Gasoline and Diesel Fuel Update (EIA)

Oxygenate Supply/Demand Oxygenate Supply/Demand Balances in the Short-Term Integrated Forecasting Model By Tancred C.M. Lidderdale This article first appeared in the Short-Term Energy Outlook Annual Supplement 1995, Energy Information Administration, DOE/EIA-0202(95) (Washington, DC, July 1995), pp. 33-42, 83-85. The regression results and historical data for production, inventories, and imports have been updated in this presentation. Contents * Introduction o Table 1. Oxygenate production capacity and demand * Oxygenate demand o Table 2. Estimated RFG demand share - mandated RFG areas, January 1998 * Fuel ethanol supply and demand balance o Table 3. Fuel ethanol annual statistics * MTBE supply and demand balance o Table 4. EIA MTBE annual statistics * Refinery balances

234

Assumptions to the Annual Energy Outlook 2001 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Comleted Copy in PDF Format Comleted Copy in PDF Format Related Links Annual Energy Outlook 2001 Supplemental Data to the AEO 2001 NEMS Conference To Forecasting Home Page EIA Homepage Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The distinction between the two sets of manufacturing industries pertains to the level of modeling. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 19). The

235

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

commercial.gif (5196 bytes) commercial.gif (5196 bytes) The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. The definition of the commercial sector is consistent with EIAÂ’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings, however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.12

236

Ten Years Later: A Joint Library Evolves  

Science Journals Connector (OSTI)

Abstract In 2003, a unique joint library was created. A partnership between the San Jose Public Library system and San Jose State University, the Dr. Martin Luther King, Jr. Library serves a city population of more than a million and a campus population of over 30,000 students. With different patrons and different missions, bringing the two library cultures and functions together presented many challenges, but the library today is a vital, innovative space for learning. In the ten years since its opening, however, the cost savings envisioned when the library was created have not been realized. Also, the partnership originally presented in the library's organizational structure has undergone alterations. This restructuring was driven by changes in funding, staffing, and patron needs. Despite this organizational evolution, the King Library still provides a richer resource to its communities than either partner could have provided alone and can serve as a model to other communities considering the creation of a joint library.

Ann Agee

2014-01-01T23:59:59.000Z

237

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

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2007 Commercial Demand Module The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIA's State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.12

238

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

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2007 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 21 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module forecasts energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region forecast using the SEDS25 data.

239

Demand Response Opportunities and Enabling Technologies for Data Centers:  

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

Demand Response Opportunities and Enabling Technologies for Data Centers: Demand Response Opportunities and Enabling Technologies for Data Centers: Findings From Field Studies Title Demand Response Opportunities and Enabling Technologies for Data Centers: Findings From Field Studies Publication Type Report LBNL Report Number LBNL-5763E Year of Publication 2012 Authors Ghatikar, Girish, Venkata Ganti, Nance Matson, and Mary Ann Piette Publisher PG&E/SDG&E/CEC/LBNL Keywords communication and standards, control systems, data centers, demand response, enabling technologies, end-use technologies, load migration, market sectors, technologies Abstract The energy use in data centers is increasing and, in particular, impacting the data center energy cost and electric grid reliability during peak and high price periods. As per the 2007 U.S. Environmental Protection Agency (EPA), in the Pacific Gas and Electric Company territory, data centers are estimated to consume 500 megawatts of annual peak electricity. The 2011 data confirm the increase in data center energy use, although it is slightly lower than the EPA forecast. Previous studies have suggested that data centers have significant potential to integrate with supply-side programs to reduce peak loads. In collaboration with California data centers, utilities, and technology vendors, this study conducted field tests to improve the understanding of the demand response opportunities in data centers. The study evaluated an initial set of control and load migration strategies and economic feasibility for four data centers. The findings show that with minimal or no impact to data center operations a demand savings of 25% at the data center level or 10% to 12% at the whole building level can be achieved with strategies for cooling and IT equipment, and load migration. These findings should accelerate the grid-responsiveness of data centers through technology development, integration with the demand response programs, and provide operational cost savings.

240

The evolution of carbon dioxide emissions from energy use in industrialized countries: an end-use analysis  

SciTech Connect

There has been much attention drawn to plans for reductions or restraint in future C02 emissions, yet little analysis of the recent history of those emissions by end use or economic activity. Understanding the components of C02 emissions, particularly those related to combustion of fossil fuels, is important for judging the likely success of plans for dealing with future emissions. Knowing how fuel switching, changes in economic activity and its structure, or changes in energy-use efficiency affected emissions in the past, we can better judge both the realism of national proposals to restrain future emissions and the outcome as well. This study presents a first step in that analysis. The organization of this paper is as follows. We present a brief background and summarize previous work analyzing changes in energy use using the factorial method. We then describe our data sources and method. We then present a series of summary results, including a comparison of C02 emissions in 1991 by end use or sector. We show both aggregate change and change broken down by factor, highlighting briefly the main components of change. We then present detailed results, sector by sector. Next we highlight recent trends. Finally, we integrate our results, discussing -the most important factors driving change - evolution in economic structure, changes in energy intensities, and shifts in the fuel mix. We discuss briefly some of the likely causes of these changes - long- term technological changes, effects of rising incomes, the impact of overall changes in energy prices, as well as changes in the relative prices of energy forms.

Schipper, L.; Ting, M.; Khrushch, M.; Unander, F.; Monahan, P.; Golove, W.

1996-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "demand ten end-use" 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

Twenty In Ten: Strengthening America's Energy Security | Department...  

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

leaders and entrepreneurs to join him in pursuing the goal of reducing U.S. gasoline usage by 20 percent in the next ten years. Twenty In Ten: Strengthening America's Energy...

242

Demand Response Programs, 6. edition  

SciTech Connect

The report provides a look at the past, present, and future state of the market for demand/load response based upon market price signals. It is intended to provide significant value to individuals and companies who are considering participating in demand response programs, energy providers and ISOs interested in offering demand response programs, and consultants and analysts looking for detailed information on demand response technology, applications, and participants. The report offers a look at the current Demand Response environment in the energy industry by: defining what demand response programs are; detailing the evolution of program types over the last 30 years; discussing the key drivers of current initiatives; identifying barriers and keys to success for the programs; discussing the argument against subsidization of demand response; describing the different types of programs that exist including:direct load control, interruptible load, curtailable load, time-of-use, real time pricing, and demand bidding/buyback; providing examples of the different types of programs; examining the enablers of demand response programs; and, providing a look at major demand response programs.

NONE

2007-10-15T23:59:59.000Z

243

Implications of maximizing China's technical potential for residential end-use energy efficiency: A 2030 outlook from the bottom-up  

E-Print Network (OSTI)

4 3. Basis for Residential Energy Demandand the subsequent energy demand and CO 2 emissionsa smaller share of total energy demand followed by space

Khanna, Nina

2014-01-01T23:59:59.000Z

244

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network (OSTI)

of control. Water heater demand response options are notcurrent water heater and air conditioning demand responsecustomer response Demand response water heater participation

Levy, Roger

2014-01-01T23:59:59.000Z

245

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

and D. Kathan (2009). Demand Response in U.S. ElectricityEnergy Financial Group. Demand Response Research Center [2008). Assessment of Demand Response and Advanced Metering.

Goldman, Charles

2010-01-01T23:59:59.000Z

246

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network (OSTI)

Like HECO actual utility demand response implementations canindustry-wide utility demand response applications tend toobjective. Figure 4. Demand Response Objectives 17  

Levy, Roger

2014-01-01T23:59:59.000Z

247

Installation and Commissioning Automated Demand Response Systems  

E-Print Network (OSTI)

their partnership in demand response automation research andand Techniques for Demand Response. LBNL Report 59975. Mayof Fully Automated Demand Response in Large Facilities.

Kiliccote, Sila; Global Energy Partners; Pacific Gas and Electric Company

2008-01-01T23:59:59.000Z

248

Barrier Immune Radio Communications for Demand Response  

E-Print Network (OSTI)

of Fully Automated Demand Response in Large Facilities,”Fully Automated Demand Response Tests in Large Facilities.for Automated Demand Response. Technical Document to

Rubinstein, Francis

2010-01-01T23:59:59.000Z

249

Retail Demand Response in Southwest Power Pool  

E-Print Network (OSTI)

23 ii Retail Demand Response in SPP List of Figures and10 Figure 3. Demand Response Resources by11 Figure 4. Existing Demand Response Resources by Type of

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

250

Home Network Technologies and Automating Demand Response  

E-Print Network (OSTI)

and Automating Demand Response Charles McParland, Lawrenceand Automating Demand Response Charles McParland, LBNLCommercial and Residential Demand Response Overview of the

McParland, Charles

2010-01-01T23:59:59.000Z

251

Wireless Demand Response Controls for HVAC Systems  

E-Print Network (OSTI)

Strategies Linking Demand Response and Energy Efficiency,”Fully Automated Demand Response Tests in Large Facilities,technical support from the Demand Response Research Center (

Federspiel, Clifford

2010-01-01T23:59:59.000Z

252

Strategies for Demand Response in Commercial Buildings  

E-Print Network (OSTI)

Fully Automated Demand Response Tests in Large Facilities”of Fully Automated Demand Response in Large Facilities”,was coordinated by the Demand Response Research Center and

Watson, David S.; Kiliccote, Sila; Motegi, Naoya; Piette, Mary Ann

2006-01-01T23:59:59.000Z

253

Option Value of Electricity Demand Response  

E-Print Network (OSTI)

Table 1. “Economic” demand response and real time pricing (Implications of Demand Response Programs in CompetitiveAdvanced Metering, and Demand Response in Electricity

Sezgen, Osman; Goldman, Charles; Krishnarao, P.

2005-01-01T23:59:59.000Z

254

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

3 2.1 Demand-Side Managementbuildings. The demand side management framework is discussedIssues 2.1 Demand-Side Management Framework Forecasting

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

255

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

of Energy demand-side management energy information systemdemand response. Demand-side management (DSM) program goalsa goal for demand-side management (DSM) coordination and

Goldman, Charles

2010-01-01T23:59:59.000Z

256

China's Coal: Demand, Constraints, and Externalities  

E-Print Network (OSTI)

raising transportation oil demand. Growing internationalcoal by wire could reduce oil demand by stemming coal roadEastern oil production. The rapid growth of coal demand

Aden, Nathaniel

2010-01-01T23:59:59.000Z

257

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

World: Renewable Energy and Demand Response Proliferation intogether the renewable energy and demand response communityimpacts of renewable energy and demand response integration

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

258

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

District Small Business Summer Solutions: Energy and DemandSummer Solutions: Energy and Demand Impacts Monthly Energy> B-2 Coordination of Energy Efficiency and Demand Response

Goldman, Charles

2010-01-01T23:59:59.000Z

259

electricity demand | OpenEI  

Open Energy Info (EERE)

demand demand Dataset Summary Description The New Zealand Ministry of Economic Development publishes energy data including many datasets related to electricity. Included here are three electricity consumption and demand datasets, specifically: annual observed electricity consumption by sector (1974 to 2009); observed percentage of consumers by sector (2002 - 2009); and regional electricity demand, as a percentage of total demand (2009). Source New Zealand Ministry of Economic Development Date Released Unknown Date Updated July 03rd, 2009 (5 years ago) Keywords Electricity Consumption electricity demand energy use by sector New Zealand Data application/vnd.ms-excel icon Electricity Consumption by Sector (1974 - 2009) (xls, 46.1 KiB) application/vnd.ms-excel icon Percentage of Consumers by Sector (2002 - 2009) (xls, 43.5 KiB)

260

Annual World Oil Demand Growth  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: Following relatively small increases of 1.3 million barrels per day in 1999 and 0.9 million barrels per day in 2000, EIA is estimating world demand may grow by 1.6 million barrels per day in 2001. Of this increase, about 3/5 comes from non-OECD countries, while U.S. oil demand growth represents more than half of the growth projected in OECD countries. Demand in Asia grew steadily during most of the 1990s, with 1991-1997 average growth per year at just above 0.8 million barrels per day. However, in 1998, demand dropped by 0.3 million barrels per day as a result of the Asian economic crisis that year. Since 1998, annual growth in oil demand has rebounded, but has not yet reached the average growth seen during 1991-1997. In the Former Soviet Union, oil demand plummeted during most of the

Note: This page contains sample records for the topic "demand ten end-use" 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

Assumptions to the Annual Energy Outlook 2001 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption. Key Assumptions Macroeconomic Sector Inputs

262

The National Energy Modeling System: An Overview 2000 - Residential Demand  

Gasoline and Diesel Fuel Update (EIA)

residential demand module (RDM) forecasts energy consumption by Census division for seven marketed energy sources plus solar and geothermal energy. RDM is a structural model and its forecasts are built up from projections of the residential housing stock and of the energy-consuming equipment contained therein. The components of RDM and its interactions with the NEMS system are shown in Figure 5. NEMS provides forecasts of residential energy prices, population, and housing starts, which are used by RDM to develop forecasts of energy consumption by fuel and Census division. residential demand module (RDM) forecasts energy consumption by Census division for seven marketed energy sources plus solar and geothermal energy. RDM is a structural model and its forecasts are built up from projections of the residential housing stock and of the energy-consuming equipment contained therein. The components of RDM and its interactions with the NEMS system are shown in Figure 5. NEMS provides forecasts of residential energy prices, population, and housing starts, which are used by RDM to develop forecasts of energy consumption by fuel and Census division. Figure 5. Residential Demand Module Structure RDM incorporates the effects of four broadly-defined determinants of energy consumption: economic and demographic effects, structural effects, technology turnover and advancement effects, and energy market effects. Economic and demographic effects include the number, dwelling type (single-family, multi-family or mobile homes), occupants per household, and location of housing units. Structural effects include increasing average dwelling size and changes in the mix of desired end-use services provided by energy (new end uses and/or increasing penetration of current end uses, such as the increasing popularity of electronic equipment and computers). Technology effects include changes in the stock of installed equipment caused by normal turnover of old, worn out equipment with newer versions which tend to be more energy efficient, the integrated effects of equipment and building shell (insulation level) in new construction, and in the projected availability of even more energy-efficient equipment in the future. Energy market effects include the short-run effects of energy prices on energy demands, the longer-run effects of energy prices on the efficiency of purchased equipment and the efficiency of building shells, and limitations on minimum levels of efficiency imposed by legislated efficiency standards.

263

2014-04-30 Public Meeting Agenda: Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances  

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

This document is the agenda for the Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances public meeting being held on April 30, 2014.

264

Measured commercial load shapes and energy-use intensities and validation of the LBL end-use disaggregation algorithm. Final report  

SciTech Connect

The Southern California Edison Company (SCE) has conducted an extensive metering project in which electricity end use in 53 commercial buildings in Southern California has been measured. The building types monitored include offices, retail stores, groceries, restaurants, and warehouses. One year (June 1989 through May 1990) of the SCE measured hourly end-use data are reviewed in this report. Annual whole-building and end-use energy use intensities (EUIs) and monthly load shapes (LSs) have been calculated for the different building types based on the monitored data. This report compares the monitored buildings` EUIs and LSs to EUIs and LSs determined using whole-building load data and the End-Use Disaggregation Algorithm (EDA). Two sets of EDA determined EUIs and LSs are compared to the monitored data values. The data sets represent: (1) average buildings in the SCE service territory and (2) specific buildings that were monitored.

Akbari, H.; Rainer, L.; Heinemeier, K.; Huang, J.; Franconi, E.

1993-01-01T23:59:59.000Z

265

Vehicle Technologies Office: Fact #629: June 28, 2010 Top Ten  

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

9: June 28, 2010 9: June 28, 2010 Top Ten Misconceptions about Fuel Economy to someone by E-mail Share Vehicle Technologies Office: Fact #629: June 28, 2010 Top Ten Misconceptions about Fuel Economy on Facebook Tweet about Vehicle Technologies Office: Fact #629: June 28, 2010 Top Ten Misconceptions about Fuel Economy on Twitter Bookmark Vehicle Technologies Office: Fact #629: June 28, 2010 Top Ten Misconceptions about Fuel Economy on Google Bookmark Vehicle Technologies Office: Fact #629: June 28, 2010 Top Ten Misconceptions about Fuel Economy on Delicious Rank Vehicle Technologies Office: Fact #629: June 28, 2010 Top Ten Misconceptions about Fuel Economy on Digg Find More places to share Vehicle Technologies Office: Fact #629: June 28, 2010 Top Ten Misconceptions about Fuel Economy on AddThis.com...

266

Harnessing the power of demand  

SciTech Connect

Demand response can provide a series of economic services to the market and also provide ''insurance value'' under low-likelihood, but high-impact circumstances in which grid reliablity is enhanced. Here is how ISOs and RTOs are fostering demand response within wholesale electricity markets. (author)

Sheffrin, Anjali; Yoshimura, Henry; LaPlante, David; Neenan, Bernard

2008-03-15T23:59:59.000Z

267

China, India demand cushions prices  

SciTech Connect

Despite the hopes of coal consumers, coal prices did not plummet in 2006 as demand stayed firm. China and India's growing economies, coupled with solid supply-demand fundamentals in North America and Europe, and highly volatile prices for alternatives are likely to keep physical coal prices from wide swings in the coming year.

Boyle, M.

2006-11-15T23:59:59.000Z

268

Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California  

SciTech Connect

This paper reports on the potential impact of demand response (DR) strategies in commercial buildings in California based on the Demand Response Quick Assessment Tool (DRQAT), which uses EnergyPlus simulation prototypes for office and retail buildings. The study describes the potential impact of building size, thermal mass, climate, and DR strategies on demand savings in commercial buildings. Sensitivity analyses are performed to evaluate how these factors influence the demand shift and shed during the peak period. The whole-building peak demand of a commercial building with high thermal mass in a hot climate zone can be reduced by 30percent using an optimized demand response strategy. Results are summarized for various simulation scenarios designed to help owners and managers understand the potential savings for demand response deployment. Simulated demand savings under various scenarios were compared to field-measured data in numerous climate zones, allowing calibration of the prototype models. The simulation results are compared to the peak demand data from the Commercial End-Use Survey for commercial buildings in California. On the economic side, a set of electricity rates are used to evaluate the impact of the DR strategies on economic savings for different thermal mass and climate conditions. Our comparison of recent simulation to field test results provides an understanding of the DR potential in commercial buildings.

Yin, Rongxin; Kiliccote, Sila; Piette, Mary Ann; Parrish, Kristen

2010-05-14T23:59:59.000Z

269

Honeywell Demonstrates Automated Demand Response Benefits for...  

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

Honeywell Demonstrates Automated Demand Response Benefits for Utility, Commercial, and Industrial Customers Honeywell Demonstrates Automated Demand Response Benefits for Utility,...

270

Retail Demand Response in Southwest Power Pool  

E-Print Network (OSTI)

Data Collection for Demand-side Management for QualifyingPrepared by Demand-side Management Task Force of the

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

271

Automated Demand Response and Commissioning  

SciTech Connect

This paper describes the results from the second season of research to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve the electric grid reliability and manage electricity costs. Fully-Automated Demand Response does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. We refer to this as Auto-DR. The evaluation of the control and communications must be properly configured and pass through a set of test stages: Readiness, Approval, Price Client/Price Server Communication, Internet Gateway/Internet Relay Communication, Control of Equipment, and DR Shed Effectiveness. New commissioning tests are needed for such systems to improve connecting demand responsive building systems to the electric grid demand response systems.

Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Bourassa, Norman

2005-04-01T23:59:59.000Z

272

Demand Activated Manufacturing Architecture  

SciTech Connect

Honeywell Federal Manufacturing & Technologies (FM&T) engineers John Zimmerman and Tom Bender directed separate projects within this CRADA. This Project Accomplishments Summary contains their reports independently. Zimmerman: In 1998 Honeywell FM&T partnered with the Demand Activated Manufacturing Architecture (DAMA) Cooperative Business Management Program to pilot the Supply Chain Integration Planning Prototype (SCIP). At the time, FM&T was developing an enterprise-wide supply chain management prototype called the Integrated Programmatic Scheduling System (IPSS) to improve the DOE's Nuclear Weapons Complex (NWC) supply chain. In the CRADA partnership, FM&T provided the IPSS technical and business infrastructure as a test bed for SCIP technology, and this would provide FM&T the opportunity to evaluate SCIP as the central schedule engine and decision support tool for IPSS. FM&T agreed to do the bulk of the work for piloting SCIP. In support of that aim, DAMA needed specific DOE Defense Programs opportunities to prove the value of its supply chain architecture and tools. In this partnership, FM&T teamed with Sandia National Labs (SNL), Division 6534, the other DAMA partner and developer of SCIP. FM&T tested SCIP in 1998 and 1999. Testing ended in 1999 when DAMA CRADA funding for FM&T ceased. Before entering the partnership, FM&T discovered that the DAMA SCIP technology had an array of applications in strategic, tactical, and operational planning and scheduling. At the time, FM&T planned to improve its supply chain performance by modernizing the NWC-wide planning and scheduling business processes and tools. The modernization took the form of a distributed client-server planning and scheduling system (IPSS) for planners and schedulers to use throughout the NWC on desktops through an off-the-shelf WEB browser. The planning and scheduling process within the NWC then, and today, is a labor-intensive paper-based method that plans and schedules more than 8,000 shipped parts per month based on more than 50 manually-created document types. The fact that DAMA and FM&T desired to move from paper-based manual architectures to digitally based computer architectures gave further incentive for the partnership to grow. FM&T's greatest strength was its knowledge of NWC-wide scheduling and planning with its role as the NWC leader in manufacturing logistics. DAMA's asset was its new knowledge gained in the research and development of advanced architectures and tools for supply chain management in the textiles industry. These complimentary strengths allowed the two parties to provide both the context and the tools for the pilot. Bender: Honeywell FM&T participated in a four-site supply chain project, also referred to as an Inter-Enterprise Pipeline Evaluation. The MSAD project was selected because it involves four NWC sites: FM&T, Pantex, Los Alamos National Laboratory (LANL), and Lawrence Livermore National Laboratory (LLNL). FM&T had previously participated with Los Alamos National Laboratory in FY98 to model a two-site supply chain project, between FM&T and LANL. Evaluation of a Supply Chain Methodology is a subset of the DAMA project for the AMTEX consortium. LANL organization TSA-7, Enterprise Modeling and Simulation, has been involved in AMTEX and DAMA through development of process models and simulations for LANL, the NWC, and others. The FY 1998 and this FY 1999 projects directly involved collaboration between Honeywell and the Enterprise Modeling and Simulation (TSA-7) and Detonation Science and Technology (DX1) organizations at LANL.

Bender, T.R.; Zimmerman, J.J.

2001-02-07T23:59:59.000Z

273

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

global gasoline and diesel price and income elasticities.shift in the short-run price elasticity of gasoline demand.Habits and Uncertain Relative Prices: Simulating Petrol Con-

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

274

Concurrence' Lawrence Livermore National Laboratory FY2015 Ten...  

National Nuclear Security Administration (NNSA)

manufacturing * Special nuclear materials-plutonium and tritium * High performance computing FY2015 Ten Year Site Plan Limited Report Page 3 of 6 Lawrence Livermore...

275

Data Acquisition-Manipulation At Valley Of Ten Thousand Smokes...  

Open Energy Info (EERE)

Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Data Acquisition-Manipulation At Valley Of Ten Thousand Smokes Region Area (Kodosky & Keith,...

276

A TEN MEGAWATT BOILING HETEROGENEOUS PACKAGE POWER REACTOR. Reactor...  

Office of Scientific and Technical Information (OSTI)

A TEN MEGAWATT BOILING HETEROGENEOUS PACKAGE POWER REACTOR. Reactor Design and Feasibility Problem Re-direct Destination: Temp Data Fields Rosen, M. A.; Coburn, D. B.; Flynn, T....

277

Northwest Open Automated Demand Response Technology Demonstration Project  

SciTech Connect

The Lawrence Berkeley National Laboratory (LBNL) Demand Response Research Center (DRRC) demonstrated and evaluated open automated demand response (OpenADR) communication infrastructure to reduce winter morning and summer afternoon peak electricity demand in commercial buildings the Seattle area. LBNL performed this demonstration for the Bonneville Power Administration (BPA) in the Seattle City Light (SCL) service territory at five sites: Seattle Municipal Tower, Seattle University, McKinstry, and two Target stores. This report describes the process and results of the demonstration. OpenADR is an information exchange model that uses a client-server architecture to automate demand-response (DR) programs. These field tests evaluated the feasibility of deploying fully automated DR during both winter and summer peak periods. DR savings were evaluated for several building systems and control strategies. This project studied DR during hot summer afternoons and cold winter mornings, both periods when electricity demand is typically high. This is the DRRC project team's first experience using automation for year-round DR resources and evaluating the flexibility of commercial buildings end-use loads to participate in DR in dual-peaking climates. The lessons learned contribute to understanding end-use loads that are suitable for dispatch at different times of the year. The project was funded by BPA and SCL. BPA is a U.S. Department of Energy agency headquartered in Portland, Oregon and serving the Pacific Northwest. BPA operates an electricity transmission system and markets wholesale electrical power at cost from federal dams, one non-federal nuclear plant, and other non-federal hydroelectric and wind energy generation facilities. Created by the citizens of Seattle in 1902, SCL is the second-largest municipal utility in America. SCL purchases approximately 40% of its electricity and the majority of its transmission from BPA through a preference contract. SCL also provides ancillary services within its own balancing authority. The relationship between BPA and SCL creates a unique opportunity to create DR programs that address both BPA's and SCL's markets simultaneously. Although simultaneously addressing both market could significantly increase the value of DR programs for BPA, SCL, and the end user, establishing program parameters that maximize this value is challenging because of complex contractual arrangements and the absence of a central Independent System Operator or Regional Transmission Organization in the northwest.

Kiliccote, Sila; Piette, Mary Ann; Dudley, Junqiao

2010-03-17T23:59:59.000Z

278

building demand | OpenEI  

Open Energy Info (EERE)

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

279

Demand Response Research in Spain  

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

Demand Response Research in Spain Demand Response Research in Spain Speaker(s): Iñigo Cobelo Date: August 22, 2007 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Mary Ann Piette The Spanish power system is becoming increasingly difficult to operate. The peak load grows every year, and the permission to build new transmission and distribution infrastructures is difficult to obtain. In this scenario Demand Response can play an important role, and become a resource that could help network operators. The present deployment of demand response measures is small, but this situation however may change in the short term. The two main Spanish utilities and the transmission network operator are designing research projects in this field. All customer segments are targeted, and the research will lead to pilot installations and tests.

280

EIA - AEO2010 - Electricity Demand  

Gasoline and Diesel Fuel Update (EIA)

Electricity Demand Electricity Demand Annual Energy Outlook 2010 with Projections to 2035 Electricity Demand Figure 69. U.S. electricity demand growth 1950-2035 Click to enlarge » Figure source and data excel logo Figure 60. Average annual U.S. retail electricity prices in three cases, 1970-2035 Click to enlarge » Figure source and data excel logo Figure 61. Electricity generation by fuel in three cases, 2008 and 2035 Click to enlarge » Figure source and data excel logo Figure 62. Electricity generation capacity additions by fuel type, 2008-2035 Click to enlarge » Figure source and data excel logo Figure 63. Levelized electricity costs for new power plants, 2020 and 2035 Click to enlarge » Figure source and data excel logo Figure 64. Electricity generating capacity at U.S. nuclear power plants in three cases, 2008, 2020, and 2035

Note: This page contains sample records for the topic "demand ten end-use" 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

Full Rank Rational Demand Systems  

E-Print Network (OSTI)

as a nominal income full rank QES. R EFERENCES (A.84)S. G. Donald. “Inferring the Rank of a Matrix. ” Journal of97-102. . “A Demand System Rank Theorem. ” Econometrica 57 (

LaFrance, Jeffrey T; Pope, Rulon D.

2006-01-01T23:59:59.000Z

282

Demand Forecasting of New Products  

E-Print Network (OSTI)

Keeping Unit or SKU) employing attribute analysis techniques. The objective of this thesis is to improve Abstract This thesis is a study into the demand forecasting of new products (also referred to as Stock

Sun, Yu

283

Integrated estimation of commercial sector end-use load shapes and energy use intensities in the PG&E service area  

SciTech Connect

This project represents a unique research effort to address the commercial sector end-use energy forecasting data needs of the Pacific Gas and Electric Company (PG&E) and the California Energy Commission (CEC). The object of the project was to develop an updated set of commercial sector end-use energy use intensity (EUI) data that has been fully reconciled with measured data. The research was conducted in two stages. First, we developed reconciled electricity end-use EUIs and load shapes for each of the 11 building types in the inland and coastal regions of the PG&E service territory using information collected in 1986. Second, we developed procedures to translate these results into a consistent set of commercial sector forecasting model inputs recognizing the separate modeling conventions used by PG&E and CEC. EUIs have been developed for: II commercial building types; up to 10 end uses; up to 3 fuel types; 2 and 5 subservice territory forecasting regions (as specified by the PG&E and CEC forecasting models, respectively); and up to 2 distinct vintages corresponding to the period prior to and immediately following the adoption of the first generation of California building and equipment standards. For the electricity end uses, 36 sets of daily load shapes have been developed representing average weekday, average weekend, and peak weekday electricity use for each month of the year by building type for both the inland and coastal climate zones.

Akbari, H.; Eto, J.; Konopacki, S.; Afzal, A.; Heinemeier, K.; Rainer, L.

1993-12-01T23:59:59.000Z

284

Demand Response and Energy Efficiency  

E-Print Network (OSTI)

Demand Response & Energy Efficiency International Conference for Enhanced Building Operations ESL-IC-09-11-05 Proceedings of the Ninth International Conference for Enhanced Building Operations, Austin, Texas, November 17 - 19, 2009 2 ?Less than 5..., 2009 4 An Innovative Solution to Get the Ball Rolling ? Demand Response (DR) ? Monitoring Based Commissioning (MBCx) EnerNOC has a solution involving two complementary offerings. ESL-IC-09-11-05 Proceedings of the Ninth International Conference...

285

Demand Response Spinning Reserve Demonstration  

SciTech Connect

The Demand Response Spinning Reserve project is a pioneeringdemonstration of how existing utility load-management assets can providean important electricity system reliability resource known as spinningreserve. Using aggregated demand-side resources to provide spinningreserve will give grid operators at the California Independent SystemOperator (CAISO) and Southern California Edison (SCE) a powerful, newtool to improve system reliability, prevent rolling blackouts, and lowersystem operating costs.

Eto, Joseph H.; Nelson-Hoffman, Janine; Torres, Carlos; Hirth,Scott; Yinger, Bob; Kueck, John; Kirby, Brendan; Bernier, Clark; Wright,Roger; Barat, A.; Watson, David S.

2007-05-01T23:59:59.000Z

286

National Action Plan on Demand Response  

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

Action Plan on Demand National Action Plan on Demand Action Plan on Demand National Action Plan on Demand Response Response Federal Utilities Partnership Working Group Federal Utilities Partnership Working Group November 18, 2008 November 18, 2008 Daniel Gore Daniel Gore Office of Energy Market Regulation Office of Energy Market Regulation Federal Energy Regulatory Commission Federal Energy Regulatory Commission The author's views do not necessarily represent the views of the Federal Energy Regulatory Commission Presentation Contents Presentation Contents Statutory Requirements Statutory Requirements National Assessment [Study] of Demand Response National Assessment [Study] of Demand Response National Action Plan on Demand Response National Action Plan on Demand Response General Discussion on Demand Response and Energy Outlook

287

Demand Response Projects: Technical and Market Demonstrations  

E-Print Network (OSTI)

Demand Response Projects: Technical and Market Demonstrations Philip D. Lusk Deputy Director Energy Analyst #12;PLACE CAPTION HERE. #12;#12;#12;#12;City of Port Angeles Demand Response History energy charges · Demand charges during peak period only ­ Reduced demand charges for demand response

288

Another Ten-Year Index to Chemical Abstracts  

Science Journals Connector (OSTI)

After the completion of Volume 20 an index covering the last ten volumes should be published. ... There is a big difference between the time required to examine ten annual indexes and that required to use one big collective index covering the same period. ...

E. J. CRANE

1925-03-20T23:59:59.000Z

289

Open Automated Demand Response Communications in Demand Response for Wholesale Ancillary Services  

E-Print Network (OSTI)

A. Barat, D. Watson. 2006 Demand Response Spinning ReserveKueck, and B. Kirby 2008. Demand Response Spinning ReserveReport 2009. Open Automated Demand Response Communications

Kiliccote, Sila

2010-01-01T23:59:59.000Z

290

Demand Response and Open Automated Demand Response Opportunities for Data Centers  

E-Print Network (OSTI)

Standardized Automated Demand Response Signals. Presented atand Automated Demand Response in Industrial RefrigeratedActions for Industrial Demand Response in California. LBNL-

Mares, K.C.

2010-01-01T23:59:59.000Z

291

Paraho environmental data. Part IV. Land reclamation and revegetation. Part V. Biological effects. Part VI. Occupational health and safety. Part VII. End use  

SciTech Connect

Characteristics of the environment and ecosystems at Anvil Points, reclamation of retorted shale, revegetation of retorted shale, and ecological effects of retorted shale are reported in the first section of this report. Methods used in screening shale oil and retort water for mutagens and carcinogens as well as toxicity studies are reported in the second section of this report. The third section contains information concerning the industrial hygiene and medical studies made at Anvil Points during Paraho research operations. The last section discusses the end uses of shale crude oil and possible health effects associated with end use. (DMC)

Limbach, L.K.

1982-06-01T23:59:59.000Z

292

Final Environmental Impact Report: North Brawley Ten Megawatt Geothermal  

Open Energy Info (EERE)

Final Environmental Impact Report: North Brawley Ten Megawatt Geothermal Final Environmental Impact Report: North Brawley Ten Megawatt Geothermal Demonstration Facility Jump to: navigation, search OpenEI Reference LibraryAdd to library Report: Final Environmental Impact Report: North Brawley Ten Megawatt Geothermal Demonstration Facility Abstract N/A Author County of Imperial Planning Department Published WESTEC SERVICES, INC., 1979 Report Number N/A DOI Not Provided Check for DOI availability: http://crossref.org Online Internet link for Final Environmental Impact Report: North Brawley Ten Megawatt Geothermal Demonstration Facility Citation County of Imperial Planning Department. 1979. Final Environmental Impact Report: North Brawley Ten Megawatt Geothermal Demonstration Facility. (!) : WESTEC SERVICES, INC.. Report No.: N/A. Retrieved from

293

Facilitating Renewable Integration by Demand Response  

Science Journals Connector (OSTI)

Demand response is seen as one of the resources ... expected to incentivize small consumers to participate in demand response. This chapter models the involvement of small consumers in demand response programs wi...

Juan M. Morales; Antonio J. Conejo…

2014-01-01T23:59:59.000Z

294

Demand Response as a System Reliability Resource  

E-Print Network (OSTI)

Barat, and D. Watson. 2007. Demand Response Spinning ReserveKueck, and B. Kirby. 2009. Demand Response Spinning ReserveFormat of 2009-2011 Demand Response Activity Applications.

Joseph, Eto

2014-01-01T23:59:59.000Z

295

Demand response-enabled residential thermostat controls.  

E-Print Network (OSTI)

human dimension of demand response technology from a caseArens, E. , et al. 2008. Demand Response Enabling TechnologyArens, E. , et al. 2006. Demand Response Enabling Technology

Chen, Xue; Jang, Jaehwi; Auslander, David M.; Peffer, Therese; Arens, Edward A

2008-01-01T23:59:59.000Z

296

Value of Demand Response -Introduction Klaus Skytte  

E-Print Network (OSTI)

Value of Demand Response - Introduction Klaus Skytte Systems Analysis Department February 7, 2006 Energinet.dk, Ballerup #12;What is Demand Response? Demand response (DR) is the short-term response

297

World Energy Use — Trends in Demand  

Science Journals Connector (OSTI)

In order to provide adequate energy supplies in the future, trends in energy demand must be evaluated and projections of future demand developed. World energy use is far from static, and an understanding of the demand

Randy Hudson

1996-01-01T23:59:59.000Z

298

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

California Energy Demand Scenario Projections to 2050 RyanCEC (2003a) California energy demand 2003-2013 forecast.CEC (2005a) California energy demand 2006-2016: Staff energy

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

299

Balancing of Energy Supply and Residential Demand  

Science Journals Connector (OSTI)

Power demand of private households shows daily fluctuations and ... (BEV) and heat pumps. This additional demand, especially when it remains unmanaged, will ... to an increase in fluctuations. To balance demand,

Martin Bock; Grit Walther

2014-01-01T23:59:59.000Z

300

Definition: Demand | Open Energy Information  

Open Energy Info (EERE)

form form View source History View New Pages Recent Changes All Special Pages Semantic Search/Querying Get Involved Help Apps Datasets Community Login | Sign Up Search Definition Edit with form History Facebook icon Twitter icon » Definition: Demand Jump to: navigation, search Dictionary.png Demand The rate at which electric energy is delivered to or by a system or part of a system, generally expressed in kilowatts or megawatts, at a given instant or averaged over any designated interval of time., The rate at which energy is being used by the customer.[1] Related Terms energy, electricity generation References ↑ Glossary of Terms Used in Reliability Standards An i Like Like You like this.Sign Up to see what your friends like. nline Glossary Definition Retrieved from "http://en.openei.org/w/index.php?title=Definition:Demand&oldid=480555"

Note: This page contains sample records for the topic "demand ten end-use" 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

Winter Demand Impacted by Weather  

Gasoline and Diesel Fuel Update (EIA)

8 8 Notes: Heating oil demand is strongly influenced by weather. The "normal" numbers are the expected values for winter 2000-2001 used in EIA's Short-Term Energy Outlook. The chart indicates the extent to which the last winter exhibited below-normal heating degree-days (and thus below-normal heating demand). Temperatures were consistently warmer than normal throughout the 1999-2000 heating season. This was particularly true in November 1999, February 2001 and March 2001. For the heating season as a whole (October through March), the 1999-2000 winter yielded total HDDs 10.7% below normal. Normal temperatures this coming winter would, then, be expected to bring about 11% higher heating demand than we saw last year. Relative to normal, the 1999-2000 heating season was the warmest in

302

Turkey's energy demand and supply  

SciTech Connect

The aim of the present article is to investigate Turkey's energy demand and the contribution of domestic energy sources to energy consumption. Turkey, the 17th largest economy in the world, is an emerging country with a buoyant economy challenged by a growing demand for energy. Turkey's energy consumption has grown and will continue to grow along with its economy. Turkey's energy consumption is high, but its domestic primary energy sources are oil and natural gas reserves and their production is low. Total primary energy production met about 27% of the total primary energy demand in 2005. Oil has the biggest share in total primary energy consumption. Lignite has the biggest share in Turkey's primary energy production at 45%. Domestic production should be to be nearly doubled by 2010, mainly in coal (lignite), which, at present, accounts for almost half of the total energy production. The hydropower should also increase two-fold over the same period.

Balat, M. [Sila Science, Trabzon (Turkey)

2009-07-01T23:59:59.000Z

303

International Oil Supplies and Demands  

SciTech Connect

The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--90 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

Not Available

1991-09-01T23:59:59.000Z

304

International Oil Supplies and Demands  

SciTech Connect

The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--1990 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

Not Available

1992-04-01T23:59:59.000Z

305

Demand Response as a System Reliability Resource  

E-Print Network (OSTI)

for Demand Response Technology Development The objective ofin planning demand response technology RD&D by conductingNew and Emerging Technologies into the California Smart Grid

Joseph, Eto

2014-01-01T23:59:59.000Z

306

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

California Long-term Energy Efficiency Strategic Plan. B-2 Coordination of Energy Efficiency and Demand Response> B-4 Coordination of Energy Efficiency and Demand Response

Goldman, Charles

2010-01-01T23:59:59.000Z

307

Demand Response - Policy | Department of Energy  

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

Demand Response - Policy Demand Response - Policy Since its inception, the Office of Electricity Delivery and Energy Reliability (OE) has been committed to modernizing the nation's...

308

Sandia National Laboratories: demand response inverter  

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

demand response inverter ECIS-Princeton Power Systems, Inc.: Demand Response Inverter On March 19, 2013, in DETL, Distribution Grid Integration, Energy, Energy Surety, Facilities,...

309

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

and Demand Response A pilot program from NSTAR in Massachusetts,Massachusetts, aiming to test whether an intensive program of energy efficiency and demand response

Goldman, Charles

2010-01-01T23:59:59.000Z

310

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

annual per-capita electricity consumption by demand15 California electricity consumption projections by demandannual per-capita electricity consumption by demand

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

311

Marketing & Driving Demand: Social Media Tools & Strategies ...  

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

Demand: Social Media Tools & Strategies - January 16, 2011 Marketing & Driving Demand: Social Media Tools & Strategies - January 16, 2011 January 16, 2011 Conference Call...

312

Marketing & Driving Demand Collaborative - Social Media Tools...  

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

Demand Collaborative - Social Media Tools & Strategies Marketing & Driving Demand Collaborative - Social Media Tools & Strategies Presentation slides from the BetterBuildings...

313

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

Vehicle Conventional and Alternative Fuel Response Simulatormodified to include alternative fuel demand scenarios (whichvehicle adoption and alternative fuel demand) later in the

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

314

B O N N E V I L L E P O W E R A D M I N I S T R A T I O N Demand Response  

E-Print Network (OSTI)

1 Slide 1 B O N N E V I L L E P O W E R A D M I N I S T R A T I O N Demand Response BPA Program I S T R A T I O N What is Demand Response? Changes in electric usage by end-use customers from reliability is jeopardized. -Demand Response Research Center, Lawrence Berkeley National Lab And

315

TopTen Energy Efficient Products Website | Open Energy Information  

Open Energy Info (EERE)

TopTen Energy Efficient Products Website TopTen Energy Efficient Products Website Jump to: navigation, search Tool Summary LAUNCH TOOL Name: TopTen Energy Efficient Products Website Focus Area: Energy Efficiency Topics: Market Analysis Website: www.topten.info/ Equivalent URI: cleanenergysolutions.org/content/topten-energy-efficient-products-webs Language: English Policies: "Deployment Programs,Regulations" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Industry Codes & Standards Regulations: Appliance & Equipment Standards and Required Labeling This Web portal intends to: 1) guide consumers to the most energy efficient products in Europe, China, and the United States; 2) provide policy

316

Water demand management in Kuwait  

E-Print Network (OSTI)

Kuwait is an arid country located in the Middle East, with limited access to water resources. Yet water demand per capita is much higher than in other countries in the world, estimated to be around 450 L/capita/day. There ...

Milutinovic, Milan, M. Eng. Massachusetts Institute of Technology

2006-01-01T23:59:59.000Z

317

DOE Selects Ten Projects to Conduct Advanced Turbine Technology Research |  

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

Ten Projects to Conduct Advanced Turbine Technology Ten Projects to Conduct Advanced Turbine Technology Research DOE Selects Ten Projects to Conduct Advanced Turbine Technology Research August 14, 2013 - 1:44pm Addthis WASHINGTON, D.C. - Ten university projects to conduct advanced turbine technology research under the Office of Fossil Energy's University Turbine Systems Research (UTSR) Program have been selected by the U.S. Department of Energy (DOE) for additional development. Developing gas turbines that run with greater cleanness and efficiency than current models is of great benefit both to the environment and the power industry, but development of such advanced turbine systems requires significant advances in high-temperature materials science, an understanding of combustion phenomena, and development of innovative

318

Valley Of Ten Thousand Smokes Region Geothermal Area | Open Energy  

Open Energy Info (EERE)

Valley Of Ten Thousand Smokes Region Geothermal Area Valley Of Ten Thousand Smokes Region Geothermal Area (Redirected from Valley Of Ten Thousand Smokes Region Area) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Geothermal Resource Area: Valley Of Ten Thousand Smokes Region Geothermal Area Contents 1 Area Overview 2 History and Infrastructure 3 Regulatory and Environmental Issues 4 Exploration History 5 Well Field Description 6 Geology of the Area 7 Geofluid Geochemistry 8 NEPA-Related Analyses (0) 9 Exploration Activities (8) 10 References Area Overview Geothermal Area Profile Location: Alaska Exploration Region: Alaska Geothermal Region GEA Development Phase: 2008 USGS Resource Estimate Mean Reservoir Temp: Estimated Reservoir Volume: Mean Capacity: Click "Edit With Form" above to add content

319

HYBRID LOGICS Carlos Areces and Balder ten Cate  

E-Print Network (OSTI)

14 HYBRID LOGICS Carlos Areces and Balder ten Cate 1 What are Hybrid Logics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 828 2.3 Very Expressive Hybrid Languages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 863 This chapter provides a modern overview of the field of hybrid logic. Hybrid logics are ex

Sattler, Ulrike

320

HYBRID LOGICS Carlos Areces and Balder ten Cate  

E-Print Network (OSTI)

14 HYBRID LOGICS Carlos Areces and Balder ten Cate 1 What are Hybrid Logics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.3 Very Expressive Hybrid Languages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 This chapter provides a modern overview of the field of hybrid logic. Hybrid logics are ex

ten Cate, Balder

Note: This page contains sample records for the topic "demand ten end-use" 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

Compound and Elemental Analysis At Valley Of Ten Thousand Smokes...  

Open Energy Info (EERE)

DOE-funding Unknown References T. E. C. Keith, J. M. Thompson, R. A. Hutchinson, L. D. White (1992) Geochemistry Of Waters In The Valley Of Ten Thousand Smokes Region, Alaska...

322

The alchemy of demand response: turning demand into supply  

SciTech Connect

Paying customers to refrain from purchasing products they want seems to run counter to the normal operation of markets. Demand response should be interpreted not as a supply-side resource but as a secondary market that attempts to correct the misallocation of electricity among electric users caused by regulated average rate tariffs. In a world with costless metering, the DR solution results in inefficiency as measured by deadweight losses. (author)

Rochlin, Cliff

2009-11-15T23:59:59.000Z

323

Assumptions to the Annual Energy Outlook 2000 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module estimates energy consumption across the nine Census Divisions and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, mass transit, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption. Transportation Demand Module estimates energy consumption across the nine Census Divisions and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, mass transit, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption. Key Assumptions Macroeconomic Sector Inputs

324

Q:\asufinal_0107_demand.vp  

Gasoline and Diesel Fuel Update (EIA)

00 00 (AEO2000) Assumptions to the January 2000 With Projections to 2020 DOE/EIA-0554(2000) Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Natural Gas Transmission and Distribution

325

Assessment of Demand Response and Advanced Metering  

E-Print Network (OSTI)

#12;#12;2008 Assessment of Demand Response and Advanced Metering Staff Report Federal Energy metering penetration and potential peak load reduction from demand response have increased since 2006. Significant activity to promote demand response or to remove barriers to demand response occurred at the state

Tesfatsion, Leigh

326

INTEGRATION OF PV IN DEMAND RESPONSE  

E-Print Network (OSTI)

INTEGRATION OF PV IN DEMAND RESPONSE PROGRAMS Prepared by Richard Perez et al. NREL subcontract response programs. This is because PV generation acts as a catalyst to demand response, markedly enhancing by solid evidence from three utility case studies. BACKGROUND Demand Response: demand response (DR

Perez, Richard R.

327

Demand Side Management in Rangan Banerjee  

E-Print Network (OSTI)

Demand Side Management in Industry Rangan Banerjee Talk at Baroda in Birla Corporate Seminar August 31,2007 #12;Demand Side Management Indian utilities ­ energy shortage and peak power shortage. Supply for Options ­ Demand Side Management (DSM) & Load Management #12;DSM Concept Demand Side Management (DSM) - co

Banerjee, Rangan

328

Building Technologies Office: Integrated Predictive Demand Response  

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

Integrated Predictive Integrated Predictive Demand Response Controller Research Project to someone by E-mail Share Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Facebook Tweet about Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Twitter Bookmark Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Google Bookmark Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Delicious Rank Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Digg Find More places to share Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on AddThis.com...

329

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

Report 2009. Open Automated Demand Response Communicationsand Techniques for Demand Response. California Energyand S. Kiliccote. Estimating Demand Response Load Impacts:

Kiliccote, Sila

2010-01-01T23:59:59.000Z

330

Incorporating Demand Response into Western Interconnection Transmission Planning  

E-Print Network (OSTI)

Aggregator Programs. Demand Response Measurement andIncorporating Demand Response into Western Interconnection13 Demand Response Dispatch

Satchwell, Andrew

2014-01-01T23:59:59.000Z

331

Opportunities, Barriers and Actions for Industrial Demand Response in California  

E-Print Network (OSTI)

and Techniques for Demand Response, report for theand Reliability Demand Response Programs: Final Report.Demand Response

McKane, Aimee T.

2009-01-01T23:59:59.000Z

332

Automated Demand Response Opportunities in Wastewater Treatment Facilities  

E-Print Network (OSTI)

Interoperable Automated Demand Response Infrastructure,study of automated demand response in wastewater treatmentopportunities for demand response control strategies in

Thompson, Lisa

2008-01-01T23:59:59.000Z

333

Global energy demand to 2060  

SciTech Connect

The projection of global energy demand to the year 2060 is of particular interest because of its relevance to the current greenhouse concerns. The long-term growth of global energy demand in the time scale of climatic change has received relatively little attention in the public discussion of national policy alternatives. The sociological, political, and economic issues have rarely been mentioned in this context. This study emphasizes that the two major driving forces are global population growth and economic growth (gross national product per capita), as would be expected. The modest annual increases assumed in this study result in a year 2060 annual energy use of >4 times the total global current use (year 1986) if present trends continue, and >2 times with extreme efficiency improvements in energy use. Even assuming a zero per capita growth for energy and economics, the population increase by the year 2060 results in a 1.5 times increase in total annual energy use.

Starr, C. (Electric Power Research Institute, Palo Alto, CA (USA))

1989-01-01T23:59:59.000Z

334

Energy Demand | Open Energy Information  

Open Energy Info (EERE)

Energy Demand Energy Demand Jump to: navigation, search Click to return to AEO2011 page AEO2011 Data Figure 55 From AEO2011 report . Market Trends Growth in energy use is linked to population growth through increases in housing, commercial floorspace, transportation, and goods and services. These changes affect not only the level of energy use, but also the mix of fuels used. Energy consumption per capita declined from 337 million Btu in 2007 to 308 million Btu in 2009, the lowest level since 1967. In the AEO2011 Reference case, energy use per capita increases slightly through 2013, as the economy recovers from the 2008-2009 economic downturn. After 2013, energy use per capita declines by 0.3 percent per year on average, to 293 million Btu in 2035, as higher efficiency standards for vehicles and

335

April 30 Public Meeting: Physical Characterization of Smart and Grid-Connected Commercial and Residential Building End-Use Equipment and Appliances  

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

These documents contain slide decks presented at the Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances public meeting held on April 30, 2014. The first document includes the first presentation from the meeting: DOE Vision and Objectives. The second document includes all other presentations from the meeting: Terminology and Definitions; End-User and Grid Services; Physical Characterization Framework; Value, Benefits & Metrics.

336

The FY 2008 Budget Request - Twenty in Ten: Strengthening America's Energy Security  

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

8 Budget Request 8 Budget Request Twenty in Ten: Strengthening America's Energy Security Alexander Karsner Assistant Secretary Office of Energy Efficiency and Renewable Energy February 2007 2 President's State of the Union Address "Tonight, I ask Congress to join me in pursuing a great goal. Let us build on the work we've done and reduce gasoline usage in the United States by 20 percent in the next 10 years." Strengthening America's Energy Security 3 The President's "20 in 10" Goal * Increasing the transportation sector's energy diversity. * Increasing the supply of oil alternatives and reducing oil demand. Strengthening America's Energy Security Enables Us to Further Enhance Our Energy Security By: 4 Building on the Advanced Energy Initiative * We need to continue with important research

337

Valley Of Ten Thousand Smokes Region Geothermal Area | Open Energy  

Open Energy Info (EERE)

Valley Of Ten Thousand Smokes Region Geothermal Area Valley Of Ten Thousand Smokes Region Geothermal Area Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Geothermal Resource Area: Valley Of Ten Thousand Smokes Region Geothermal Area Contents 1 Area Overview 2 History and Infrastructure 3 Regulatory and Environmental Issues 4 Exploration History 5 Well Field Description 6 Geology of the Area 7 Geofluid Geochemistry 8 NEPA-Related Analyses (0) 9 Exploration Activities (8) 10 References Area Overview Geothermal Area Profile Location: Alaska Exploration Region: Alaska Geothermal Region GEA Development Phase: 2008 USGS Resource Estimate Mean Reservoir Temp: Estimated Reservoir Volume: Mean Capacity: Click "Edit With Form" above to add content History and Infrastructure Operating Power Plants: 0 No geothermal plants listed.

338

Regulations for Electric Transmission and Fuel Gas Transmission Lines Ten  

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

Electric Transmission and Fuel Gas Transmission Electric Transmission and Fuel Gas Transmission Lines Ten or More Miles Long (New York) Regulations for Electric Transmission and Fuel Gas Transmission Lines Ten or More Miles Long (New York) < Back Eligibility Commercial Fuel Distributor Investor-Owned Utility Municipal/Public Utility Rural Electric Cooperative Tribal Government Utility Savings Category Buying & Making Electricity Water Home Weatherization Solar Wind Program Info State New York Program Type Siting and Permitting Provider New York State Public Service Commission Any person who wishes to construct an electric or gas transmission line that is more than ten miles long must file documents describing the construction plans and potential land use and environmental impacts of the proposed transmission line. The regulations describe application and review

339

Green Power Network: Top Ten Utility Green Power Programs  

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

Top Ten Utility Green Power Programs (as of December 2012) Which utilities are having the greatest success with their green power programs? NREL has compiled extensive data on utility green power programs and produced the following "Top Ten" lists of program characteristics and results: total sales of renewable energy to program participants; total number of customer participants; customer participation rates; percentage of renewable energy in total retail sales; the lowest premium charged to support new renewables development; and utilities using at least two percent solar to supply their green pricing programs. Download Information Release: NREL Highlights 2012 Utility Green Power Leaders Previous Top Ten Lists - December 2010, December 2009, December 2008, December 2007, December 2006, December 2005, December 2004, December 2003, December 2002, December 2001, June 2001, November 2000, April 2000

340

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

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2007 Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption isthe sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger aircraft, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

Note: This page contains sample records for the topic "demand ten end-use" 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

Patterns of residential energy demand by type of household: white, black, Hispanic, and low- and nonlow-income  

SciTech Connect

This report compares patterns of residential energy use by white, black, Hispanic, low-income, and nonlow-income households. The observed downward trend in residential energy demand over the period of this study can be attributed primarily to changes in space-heating energy demand. Demand for space-heating energy has experienced a greater decline than energy demand for other end uses for two reasons: (1) it is the largest end use of residential energy, causing public attention to focus on it and on strategies for conserving it; and (2) space-heating expenditures are large relative to other residential energy expenditures. The price elasticity of demand is thus greater, due to the income effect. The relative demand for space-heating energy, when controlled for the effect of climate, declined significantly over the 1978-1982 period for all fuels studied. Income classes do not differ significantly. In contrast, black households were found to use more energy for space heating than white households were found to use, although those observed differences are statistically significant only for houses heated with natural gas. As expected, the average expenditure for space-heating energy increased significantly for dwellings heated by natural gas and fuel oil. No statistically significant increases were found in electricity expenditures for space heating. Electric space heat is, in general, confined to milder regions of the country, where space heating is relatively less essential. As a consequence, we would expect the electricity demand for space heating to be more price-elastic than the demand for other fuels.

Klein, Y.; Anderson, J.; Kaganove, J.; Throgmorton, J.

1984-10-01T23:59:59.000Z

342

Demand Side Bidding. Final Report  

SciTech Connect

This document sets forth the final report for a financial assistance award for the National Association of Regulatory Utility Commissioners (NARUC) to enhance coordination between the building operators and power system operators in terms of demand-side responses to Location Based Marginal Pricing (LBMP). Potential benefits of this project include improved power system reliability, enhanced environmental quality, mitigation of high locational prices within congested areas, and the reduction of market barriers for demand-side market participants. NARUC, led by its Committee on Energy Resources and the Environment (ERE), actively works to promote the development and use of energy efficiency and clean distributive energy policies within the framework of a dynamic regulatory environment. Electric industry restructuring, energy shortages in California, and energy market transformation intensifies the need for reliable information and strategies regarding electric reliability policy and practice. NARUC promotes clean distributive generation and increased energy efficiency in the context of the energy sector restructuring process. NARUC, through ERE's Subcommittee on Energy Efficiency, strives to improve energy efficiency by creating working markets. Market transformation seeks opportunities where small amounts of investment can create sustainable markets for more efficient products, services, and design practices.

Spahn, Andrew

2003-12-31T23:59:59.000Z

343

Definition: Peak Demand | Open Energy Information  

Open Energy Info (EERE)

Peak Demand Peak Demand Jump to: navigation, search Dictionary.png Peak Demand The highest hourly integrated Net Energy For Load within a Balancing Authority Area occurring within a given period (e.g., day, month, season, or year)., The highest instantaneous demand within the Balancing Authority Area.[1] View on Wikipedia Wikipedia Definition Peak demand is used to refer to a historically high point in the sales record of a particular product. In terms of energy use, peak demand describes a period of strong consumer demand. Related Terms Balancing Authority Area, energy, demand, balancing authority, smart grid References ↑ Glossary of Terms Used in Reliability Standards An inli LikeLike UnlikeLike You like this.Sign Up to see what your friends like. ne Glossary Definition Retrieved from

344

Demand Response Programs Oregon Public Utility Commission  

E-Print Network (OSTI)

Demand Response Programs Oregon Public Utility Commission January 6, 2005 Mike Koszalka Director;Demand Response Results, 2004 Load Control ­ Cool Keeper ­ ID Irrigation Load Control Price Responsive

345

Industrial Equipment Demand and Duty Factors  

E-Print Network (OSTI)

Demand and duty factors have been measured for selected equipment (air compressors, electric furnaces, injection molding machines, centrifugal loads, and others) in industrial plants. Demand factors for heavily loaded air compressors were near 100...

Dooley, E. S.; Heffington, W. M.

346

ConservationandDemand ManagementPlan  

E-Print Network (OSTI)

; Introduction Ontario Regulation 397/11 under the Green Energy Act 2009 requires public agencies and implement energy Conservation and Demand Management (CDM) plans starting in 2014. Requirementsofthe ConservationandDemand ManagementPlan 2014-2019 #12

Abolmaesumi, Purang

347

Energy Demand Analysis at a Disaggregated Level  

Science Journals Connector (OSTI)

The purpose of this chapter is to consider energy demand at the fuel level or at the ... . This chapter first presents the disaggregation of energy demand, discusses the information issues and introduces framewor...

Subhes C. Bhattacharyya

2011-01-01T23:59:59.000Z

348

Seasonal temperature variations and energy demand  

Science Journals Connector (OSTI)

This paper presents an empirical study of the relationship between residential energy demand and temperature. Unlike previous studies in this ... different regions and to the contrasting effects on energy demand ...

Enrica De Cian; Elisa Lanzi; Roberto Roson

2013-02-01T23:59:59.000Z

349

Decentralized demand management for water distribution  

E-Print Network (OSTI)

. Actual Daily Demand for Model 2 . . 26 4 Predicted vs. Actual Peak Hourly Demand for Model 1 27 5 Predicted vs. Actual Peak Hourly Demand for Model 2 28 6 Cumulative Hourly Demand Distribution 7 Bryan Distribution Network 8 Typical Summer Diurnal... locating and controlling water that has not been accounted for. The Ford Meter Box Company (1987) advises the testing and recalibration of existing water meters. Because operating costs in a distribution network can be quite substantial, a significant...

Zabolio, Dow Joseph

2012-06-07T23:59:59.000Z

350

Technical descriptions of ten irrigation technologies for conserving energy  

SciTech Connect

Technical description of ten technologies which were researched to save energy in irrigated agriculture are presented. These technologies are: well design and development ground water supply system optimization, column and pump redesign, variable-speed pumping, pipe network optimization, reduced-pressure center-pivot systems, low-energy precision application, automated gated-pipe system, computerized irrigation scheduling, and instrumented irrigation scheduling. (MHR)

Harrer, B.J.; Wilfert, G.L.

1983-05-01T23:59:59.000Z

351

Mobile Agents: Ten Reasons For Failure Giovanni Vigna  

E-Print Network (OSTI)

Mobile Agents: Ten Reasons For Failure Giovanni Vigna Reliable Software Group Department of Computer Science University of California, Santa Barbara vigna@cs.ucsb.edu Abstract Mobile agents have applications in a dynamic environment. Mobile agents pro- vide a very appealing, intuitive, and apparently

California at Santa Barbara, University of

352

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

LBNL-62226 Demand Responsive Lighting: A Scoping Study F. Rubinstein, S. Kiliccote Energy Environmental Technologies Division January 2007 #12;LBNL-62226 Demand Responsive Lighting: A Scoping Study in this report was coordinated by the Demand Response Research Center and funded by the California Energy

353

Demand Response Resources in Pacific Northwest  

E-Print Network (OSTI)

Demand Response Resources in Pacific Northwest Chuck Goldman Lawrence Berkeley National Laboratory cagoldman@lbl.gov Pacific Northwest Demand Response Project Portland OR May 2, 2007 #12;Overview · Typology Annual Reports ­ Journal articles/Technical reports #12;Demand Response Resources · Incentive

354

Leveraging gamification in demand dispatch systems  

Science Journals Connector (OSTI)

Modern demand-side management techniques are an integral part of the envisioned smart grid paradigm. They require an active involvement of the consumer for an optimization of the grid's efficiency and a better utilization of renewable energy sources. ... Keywords: demand response, demand side management, direct load control, gamification, smart grid, sustainability

Benjamin Gnauk; Lars Dannecker; Martin Hahmann

2012-03-01T23:59:59.000Z

355

Demand Response and Ancillary Services September 2008  

E-Print Network (OSTI)

Demand Response and Ancillary Services September 2008 #12;© 2008 EnerNOC, Inc. All Rights Reserved programs The purpose of this presentation is to offer insight into the mechanics of demand response and industrial demand response resources across North America in both regulated and restructured markets As of 6

356

THE STATE OF DEMAND RESPONSE IN CALIFORNIA  

E-Print Network (OSTI)

THE STATE OF DEMAND RESPONSE IN CALIFORNIA Prepared For: California Energy in this report. #12; ABSTRACT By reducing system loads during criticalpeak times, demand response can help reduce the threat of planned rotational outages. Demand response is also widely regarded as having

357

THE STATE OF DEMAND RESPONSE IN CALIFORNIA  

E-Print Network (OSTI)

THE STATE OF DEMAND RESPONSE IN CALIFORNIA Prepared For: California Energy in this report. #12; ABSTRACT By reducing system loads during criticalpeak times, demand response (DR) can.S. and internationally and lay out ideas that could help move California forward. KEY WORDS demand response, peak

358

Modeling Energy Demand Aggregators for Residential Consumers  

E-Print Network (OSTI)

The current world-wide increase of energy demand cannot be matched by energy production and power grid updateModeling Energy Demand Aggregators for Residential Consumers G. Di Bella, L. Giarr`e, M. Ippolito, A. Jean-Marie, G. Neglia and I. Tinnirello § January 2, 2014 Abstract Energy demand aggregators

Paris-Sud XI, Université de

359

Response to changes in demand/supply  

E-Print Network (OSTI)

Response to changes in demand/supply through improved marketing 21.2 #12;#12;111 Impacts of changes log demand in 1995. The composites board mills operating in Korea took advantage of flexibility environment changes on the production mix, some economic indications, statistics of demand and supply of wood

360

Response to changes in demand/supply  

E-Print Network (OSTI)

Response to changes in demand/supply through improved marketing 21.2 http with the mill consuming 450 000 m3 , amounting to 30% of total plywood log demand in 1995. The composites board, statistics of demand and supply of wood, costs and competitiveness were analysed. The reactions

Note: This page contains sample records for the topic "demand ten end-use" 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

Energy demand forecasting: industry practices and challenges  

Science Journals Connector (OSTI)

Accurate forecasting of energy demand plays a key role for utility companies, network operators, producers and suppliers of energy. Demand forecasts are utilized for unit commitment, market bidding, network operation and maintenance, integration of renewable ... Keywords: analytics, energy demand forecasting, machine learning, renewable energy sources, smart grids, smart meters

Mathieu Sinn

2014-06-01T23:59:59.000Z

362

Smart Buildings Using Demand Response March 6, 2011  

E-Print Network (OSTI)

Smart Buildings Using Demand Response March 6, 2011 Sila Kiliccote Deputy, Demand Response Division Lawrence Berkeley National Laboratory Demand Response Research Center 1 #12;Presentation Outline Demand Response Research Center ­ DRRC Vision and Research Portfolio Introduction to Demand

Kammen, Daniel M.

363

Estimating the energy consumption and power demand of small power equipment in office buildings  

Science Journals Connector (OSTI)

Abstract Small power is a substantial energy end-use in office buildings in its own right, but also significantly contributes to internal heat gains. Technological advancements have allowed for higher efficiency computers, yet current working practices are demanding more out of digital equipment. Designers often rely on benchmarks to inform predictions of small power consumption, power demand and internal gains. These are often out of date and fail to account for the variability in equipment speciation and usage patterns in different offices. This paper details two models for estimating small power consumption in office buildings, alongside typical power demand profiles. The first model relies solely on the random sampling of monitored data, and the second relies on a ‘bottom-up’ approach to establish likely power demand and operational energy use. Both models were tested through a blind validation demonstrating a good correlation between metered data and monthly predictions of energy consumption. Prediction ranges for power demand profiles were also observed to be representative of metered data with minor exceptions. When compared to current practices, which often rely solely on the use of benchmarks, both proposed methods provide an improved approach to predicting the operational performance of small power equipment in offices.

A.C. Menezes; A. Cripps; R.A. Buswell; J. Wright; D. Bouchlaghem

2014-01-01T23:59:59.000Z

364

Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards"Top-Runner Approach"  

SciTech Connect

As one of the measures to achieve the reduction in greenhouse gas emissions agreed to in the"Kyoto Protocol," an institutional scheme for determining energy efficiency standards for energy-consuming appliances, called the"Top-Runner Approach," was developed by the Japanese government. Its goal is to strengthen the legal underpinnings of various energy conservation measures. Particularly in Japan's residential sector, where energy demand has grown vigorously so far, this efficiency standard is expected to play a key role in mitigating both energy demand growth and the associated CO2 emissions. This paper presents an outlook of Japan's residential energy demand, developed by a stochastic econometric model for the purpose of analyzing the impacts of the Japan's energy efficiency standards, as well as the future stochastic behavior of income growth, demography, energy prices, and climate on the future energy demand growth to 2030. In this analysis, we attempt to explicitly take into consideration more than 30 kinds of electricity uses, heating, cooling and hot water appliances in order to comprehensively capture the progress of energy efficiency in residential energy end-use equipment. Since electricity demand, is projected to exhibit astonishing growth in Japan's residential sector due to universal increasing ownership of electric and other appliances, it is important to implement an elaborate efficiency standards policy for these appliances.

Lacommare, Kristina S H; Komiyama, Ryoichi; Marnay, Chris

2008-05-15T23:59:59.000Z

365

Automated Demand Response Technology Demonstration Project for Small and  

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

Technology Demonstration Project for Small and Technology Demonstration Project for Small and Medium Commercial Buildings Title Automated Demand Response Technology Demonstration Project for Small and Medium Commercial Buildings Publication Type Report LBNL Report Number LBNL-4982E Year of Publication 2011 Authors Page, Janie, Sila Kiliccote, Junqiao Han Dudley, Mary Ann Piette, Albert K. Chiu, Bashar Kellow, Edward Koch, and Paul Lipkin Date Published 07/2011 Publisher CEC/LBNL Keywords demand response, emerging technologies, market sectors, medium commercial business, openadr, small commercial, small commercial business, technologies Abstract Small and medium commercial customers in California make up about 20-25% of electric peak load in California. With the roll out of smart meters to this customer group, which enable granular measurement of electricity consumption, the investor-owned utilities will offer dynamic prices as default tariffs by the end of 2011. Pacific Gas and Electric Company, which successfully deployed Automated Demand Response (AutoDR) Programs to its large commercial and industrial customers, started investigating the same infrastructures application to the small and medium commercial customers. This project aims to identify available technologies suitable for automating demand response for small-medium commercial buildings; to validate the extent to which that technology does what it claims to be able to do; and determine the extent to which customers find the technology useful for DR purpose. Ten sites, enabled by eight vendors, participated in at least four test AutoDR events per site in the summer of 2010. The results showed that while existing technology can reliably receive OpenADR signals and translate them into pre-programmed response strategies, it is likely that better levels of load sheds could be obtained than what is reported here if better understanding of the building systems were developed and the DR response strategies had been carefully designed and optimized for each site.

366

Energy demand and population changes  

SciTech Connect

Since World War II, US energy demand has grown more rapidly than population, so that per capita consumption of energy was about 60% higher in 1978 than in 1947. Population growth and the expansion of per capita real incomes have led to a greater use of energy. The aging of the US population is expected to increase per capita energy consumption, despite the increase in the proportion of persons over 65, who consume less energy than employed persons. The sharp decline in the population under 18 has led to an expansion in the relative proportion of population in the prime-labor-force age groups. Employed persons are heavy users of energy. The growth of the work force and GNP is largely attributable to the growing participation of females. Another important consequence of female employment is the growth in ownership of personal automobiles. A third factor pushing up labor-force growth is the steady influx of illegal aliens.

Allen, E.L.; Edmonds, J.A.

1980-12-01T23:59:59.000Z

367

Electricity demand analysis - unconstrained vs constrained scenarios  

Science Journals Connector (OSTI)

In India, the electricity systems are chronically constrained by shortage of both capital and energy resources. These result in rationing and interruptions of supply with a severely disrupted electricity usage pattern. From this background, we try to analyse the demand patterns with and without resource constraints. Accordingly, it is necessary to model appropriately the dynamic nature of electricity demand, which cannot be captured by methods like annual load duration curves. Therefore, we use the concept - Representative Load Curves (RLCs) - to model the temporal and structural variations in demand. As a case study, the electricity system of the state of Karnataka in India is used. Four years demand data, two unconstrained and two constrained, are used and RLCs are developed using multiple discriminant analysis. It is found that these RLCs adequately model the variations in demand and bring out distinctions between unconstrained and constrained demand patterns. The demand analysis attempted here helped to study the differences in demand patterns with and without constraints, and the success of rationing measures in reducing demand levels as well as greatly disrupting the electricity usage patterns. Multifactor ANOVA analyses are performed to find out the statistical significance of the ability of logically obtained factors in explaining overall variations in demand. The results showed that the factors that are taken into consideration accounted for maximum variations in demand at very high significance levels.

P. Balachandra; V. Chandru; M.H. Bala Subrahmanya

2003-01-01T23:59:59.000Z

368

Distribution Infrastructure and End Use  

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

The expanded Renewable Fuel Standard (RFS2) created under the Energy Independence and Security Act (EISA) of 2007 requires 36 billion gallons of biofuels to be blended into transportation fuel by...

369

Enhanced End-Use Efficiency  

Science Journals Connector (OSTI)

Energy efficiency has been dubbed the sixth source of energy (Fig. 14.1). The other five sources of energy are coal, natural gas, petroleum, nuclear and renewable energy. This chapter is about energy success s...

David Hafemeister

2014-01-01T23:59:59.000Z

370

Enhanced End-Use Efficiency  

Science Journals Connector (OSTI)

This chapter is about energy success stories and potential success stories. Since the oil embargo, the United States has reduced its energy-use growth rate from 4.4% per year (1960–70) to about 1% per year. Th...

David Hafemeister

2007-01-01T23:59:59.000Z

371

Plastics End Use Application Fundamentals  

Science Journals Connector (OSTI)

An important aspect of the electrical/electronic market in many applications is the fast ... such applications. Without plastics, most of the electronic products used today would not be practical ... their electr...

Donald V. Rosato

2011-01-01T23:59:59.000Z

372

Measurement and Verification for Demand Response  

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

Measurement and Verification for Measurement and Verification for Demand Response Prepared for the National Forum on the National Action Plan on Demand Response: Measurement and Verification Working Group AUTHORS: Miriam L. Goldberg & G. Kennedy Agnew-DNV KEMA Energy and Sustainability National Forum of the National Action Plan on Demand Response Measurement and Verification for Demand Response was developed to fulfill part of the Implementation Proposal for The National Action Plan on Demand Response, a report to Congress jointly issued by the U.S. Department of Energy (DOE) and the Federal Energy Regulatory Commission (FERC) in June 2011. Part of that implementation proposal called for a "National Forum" on demand response to be conducted by DOE and FERC. Given that demand response has matured, DOE and FERC decided that a "virtual" project

373

Demand Response in the U.S. - Key trends and federal facility participation  

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

in the U.S. in the U.S. Key trends and federal facility participation Phil Coleman Lawrence Berkeley National Lab FUPWG Williamsburg Meeting November 19, 2008 OUTLINE * Demand response defined * Current status in U.S. * Key trends - Increasing opportunities in "economic" DR - Rise of DR in "capacity" markets - Rise of dynamic pricing - Rise of automated DR ("auto-DR") * Federal participation is small - why? * Ramping up federal participation Demand Response * Def.: A short-term decrease in electrical consumption by end-use customers due to either a) increased electricity prices, or b) incentive payments (triggered by high wholesale market prices or compromised grid reliability). * DR participation can be either through load curtailment (short-term

374

Assumptions to the Annual Energy Outlook 1999 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

transportation.gif (5318 bytes) transportation.gif (5318 bytes) The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, mass transit, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

375

Secure Demand Shaping for Smart Grid On constructing probabilistic demand response schemes  

E-Print Network (OSTI)

Secure Demand Shaping for Smart Grid On constructing probabilistic demand response schemes. Developing novel schemes for demand response in smart electric gird is an increasingly active research area/SCADA for demand response in smart infrastructures face the following dilemma: On one hand, in order to increase

Sastry, S. Shankar

376

US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier  

E-Print Network (OSTI)

that energy intensity is not necessarily a good indicator of energy efficiency, whereas by controllingUS Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach Massimo www.cepe.ethz.ch #12;US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier

377

The Killing superalgebra of ten-dimensional supergravity backgrounds  

E-Print Network (OSTI)

We construct the Killing superalgebra of supersymmetric backgrounds of ten-dimensional heterotic and type II supergravities and prove that it is a Lie superalgebra. We also show that if the fraction of supersymmetry preserved by the background is greater than 1/2, in the heterotic case, or greater than 3/4 in the type II case, then the background is locally homogeneous.

José Figueroa-O'Farrill; Emily Hackett-Jones; George Moutsopoulos

2007-03-21T23:59:59.000Z

378

OUTDOOR RECREATION DEMAND AND EXPENDITURES: LOWER SNAKE RIVER RESERVOIRS  

E-Print Network (OSTI)

i OUTDOOR RECREATION DEMAND AND EXPENDITURES: LOWER SNAKE RIVER RESERVOIRS John R. Mc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v SECTION ONE - OUTDOOR RECREATION DEMAND . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Recreation Demand Methods

O'Laughlin, Jay

379

LEED Demand Response Credit: A Plan for Research towards Implementation  

E-Print Network (OSTI)

C. McParland, Open Automated Demand Response Communicationsand Open Automated Demand Response", Grid Interop Forum,Testing of Automated Demand Response for Integration of

Kiliccote, Sila

2014-01-01T23:59:59.000Z

380

Demand Response Opportunities in Industrial Refrigerated Warehouses in California  

E-Print Network (OSTI)

and Open Automated Demand Response. In Grid Interop Forum.work was sponsored by the Demand Response Research Center (load-management.php. Demand Response Research Center (2009).

Goli, Sasank

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "demand ten end-use" 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

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network (OSTI)

A. Barat, D. Watson. Demand Response Spinning ReserveOpen Automated Demand Response Communication Standards:Dynamic Controls for Demand Response in a New Commercial

Piette, Mary Ann

2009-01-01T23:59:59.000Z

382

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

reliability signals for demand response GTA HTTPS HVAC IT kWand Commissioning Automated Demand Response Systems. ”and Techniques for Demand Response. California Energy

Kiliccote, Sila

2010-01-01T23:59:59.000Z

383

Open Automated Demand Response Communications Specification (Version 1.0)  

E-Print Network (OSTI)

and Techniques for Demand Response. May 2007. LBNL-59975.to facilitate automating  demand response actions at the Interoperable Automated Demand Response Infrastructure,

Piette, Mary Ann

2009-01-01T23:59:59.000Z

384

Open Automated Demand Response for Small Commerical Buildings  

E-Print Network (OSTI)

of Fully Automated Demand  Response in Large Facilities.  Fully Automated Demand Response Tests in Large Facilities.  Open Automated  Demand Response Communication Standards: 

Dudley, June Han

2009-01-01T23:59:59.000Z

385

Scenarios for Consuming Standardized Automated Demand Response Signals  

E-Print Network (OSTI)

of Fully Automated Demand Response in Large Facilities.Fully Automated Demand Response Tests in Large Facilities.Interoperable Automated Demand Response Infrastructure.

Koch, Ed

2009-01-01T23:59:59.000Z

386

Demand Response in U.S. Electricity Markets: Empirical Evidence  

E-Print Network (OSTI)

Reliability Corporation. Demand response data task force:Energy. Benefits of demand response in electricity marketsAssessment of demand response & advanced metering, staff

Cappers, Peter

2009-01-01T23:59:59.000Z

387

Direct versus Facility Centric Load Control for Automated Demand Response  

E-Print Network (OSTI)

Interoperable Automated Demand Response Infrastructure.and Techniques for Demand Response. LBNL Report 59975. Mayand Communications for Demand Response and Energy Efficiency

Piette, Mary Ann

2010-01-01T23:59:59.000Z

388

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

Goodin. 2009. “Open Automated Demand Response Communicationsin Demand Response for Wholesale Ancillary Services. ” InOpen Automated Demand Response Demonstration Project. LBNL-

Ghatikar, Girish

2010-01-01T23:59:59.000Z

389

Modeling, Analysis, and Control of Demand Response Resources  

E-Print Network (OSTI)

advanced metering and demand response in electricityGoldman, and D. Kathan. “Demand response in U.S. electricity29] DOE. Benefits of demand response in electricity markets

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

390

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network (OSTI)

Robinson, Michael, 2008, "Demand Response in Midwest ISOPresentation at MISO Demand Response Working Group Meeting,Coordination of Retail Demand Response with Midwest ISO

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

391

Opportunities, Barriers and Actions for Industrial Demand Response in California  

E-Print Network (OSTI)

13 Table 2. Demand Side Management Framework for IndustrialDR Strategies The demand-side management (DSM) frameworkpresented in Table 2. Demand Side Management Framework for

McKane, Aimee T.

2009-01-01T23:59:59.000Z

392

The Role of Demand Response in Default Service Pricing  

E-Print Network (OSTI)

THE ROLE OF DEMAND RESPONSE IN DEFAULT SERVICE PRICING Galenfor providing much-needed demand response in electricitycompetitive retail markets, demand response often appears to

Barbose, Galen; Goldman, Chuck; Neenan, Bernie

2006-01-01T23:59:59.000Z

393

The Role of Demand Response in Default Service Pricing  

E-Print Network (OSTI)

and coordinated by the Demand Response Research Center onThe Role of Demand Response in Default Service Pricing Galenfor providing much-needed demand response in electricity

Barbose, Galen; Goldman, Charles; Neenan, Bernie

2008-01-01T23:59:59.000Z

394

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network (OSTI)

description of six energy and demand management concepts.how quickly it can modify energy demand. This is not a newimprovements in both energy efficiency and demand response (

Piette, Mary Ann

2009-01-01T23:59:59.000Z

395

Definition: Demand Side Management | Open Energy Information  

Open Energy Info (EERE)

Side Management Side Management Jump to: navigation, search Dictionary.png Demand Side Management The term for all activities or programs undertaken by Load-Serving Entity or its customers to influence the amount or timing of electricity they use.[1] View on Wikipedia Wikipedia Definition Energy demand management, also known as demand side management (DSM), is the modification of consumer demand for energy through various methods such as financial incentives and education. Usually, the goal of demand side management is to encourage the consumer to use less energy during peak hours, or to move the time of energy use to off-peak times such as nighttime and weekends. Peak demand management does not necessarily decrease total energy consumption, but could be expected to reduce the need

396

Electricity Demand and Energy Consumption Management System  

E-Print Network (OSTI)

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

Sarmiento, Juan Ojeda

2008-01-01T23:59:59.000Z

397

Distributed Intelligent Automated Demand Response (DIADR) Building  

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

Distributed Intelligent Automated Demand Distributed Intelligent Automated Demand Response (DIADR) Building Management System Distributed Intelligent Automated Demand Response (DIADR) Building Management System The U.S. Department of Energy (DOE) is currently conducting research into distributed intelligent-automated demand response (DIADR) building management systems. Project Description This project aims to develop a DIADR building management system with intelligent optimization and control algorithms for demand management, taking into account a multitude of factors affecting cost including: Comfort Heating, ventilating, and air conditioning (HVAC) Lighting Other building systems Climate Usage and occupancy patterns. The key challenge is to provide the demand response the ability to address more and more complex building systems that include a variety of loads,

398

Transportation Demand Management (TDM) Encyclopedia | Open Energy  

Open Energy Info (EERE)

Transportation Demand Management (TDM) Encyclopedia Transportation Demand Management (TDM) Encyclopedia Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Transportation Demand Management (TDM) Encyclopedia Agency/Company /Organization: Victoria Transport Policy Institute Sector: Energy Focus Area: Transportation Topics: Implementation Resource Type: Guide/manual Website: www.vtpi.org/tdm/tdm12.htm Cost: Free Language: English References: Victoria Transport Policy Institute[1] "The Online TDM Encyclopedia is the world's most comprehensive information resource concerning innovative transportation management strategies. It describes dozens of Transportation Demand Management (TDM) strategies and contains information on TDM planning, evaluation and implementation. It has thousands of hyperlinks that provide instant access

399

The Retail Planning Problem under Demand Uncertainty.  

E-Print Network (OSTI)

and Rajaram K. , (2000), “Accurate Retail Testing of FashionThe Retail Planning Problem Under Demand Uncertainty GeorgeAbstract We consider the Retail Planning Problem in which

Georgiadis, G.; Rajaram, K.

2012-01-01T23:59:59.000Z

400

Retail Demand Response in Southwest Power Pool  

E-Print Network (OSTI)

17 6. Barriers to Retail23 ii Retail Demand Response in SPP List of Figures and6 Table 3. SPP Retail DR Survey

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "demand ten end-use" 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

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

water heaters with embedded demand responsive controls can be designed to automatically provide day-ahead and real-time response

Goldman, Charles

2010-01-01T23:59:59.000Z

402

Distributed Automated Demand Response - Energy Innovation Portal  

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

Transmission Find More Like This Return to Search Distributed Automated Demand Response Lawrence Livermore National Laboratory Contact LLNL About This Technology...

403

Demand Response (transactional control) - Energy Innovation Portal  

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

Transmission Electricity Transmission Find More Like This Return to Search Demand Response (transactional control) Pacific Northwest National Laboratory Contact PNNL About...

404

Regulation Services with Demand Response - Energy Innovation...  

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

Regulation Services with Demand Response Pacific Northwest National Laboratory Contact PNNL About This Technology Using grid frequency information, researchers have created...

405

Topics in Residential Electric Demand Response.  

E-Print Network (OSTI)

??Demand response and dynamic pricing are touted as ways to empower consumers, save consumers money, and capitalize on the “smart grid” and expensive advanced meter… (more)

Horowitz, Shira R.

2012-01-01T23:59:59.000Z

406

Maximum-Demand Rectangular Location Problem  

E-Print Network (OSTI)

Oct 1, 2014 ... Demand and service can be defined in the most general sense. ... Industrial and Systems Engineering, Texas A&M University, September 2014.

Manish Bansal

2014-10-01T23:59:59.000Z

407

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

in the presence of renewable resources and on the amount ofprimarily from renewable resources, and to a limited extentintegration of renewable resources and deferrable demand. We

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

408

Basic Theory of Demand-Side Management  

Science Journals Connector (OSTI)

Demand-Side Management (DSM) is pivotal in Integrated Resource ... to realize sustainable development, and advanced energy management activity. A project can be implemented only...

Zhaoguang Hu; Xinyang Han; Quan Wen

2013-01-01T23:59:59.000Z

409

Demand response at the Naval Postgraduate School .  

E-Print Network (OSTI)

??The purpose of this MBA project is to assist the Naval Postgraduate School's Public Works department to assimilate into a Demand Response program that will… (more)

Stouffer, Dean

2008-01-01T23:59:59.000Z

410

Demand response exchange in a deregulated environment .  

E-Print Network (OSTI)

??This thesis presents the development of a new and separate market for trading Demand Response (DR) in a deregulated power system. This market is termed… (more)

Nguyen, DT

2012-01-01T23:59:59.000Z

411

Demand response exchange in a deregulated environment.  

E-Print Network (OSTI)

??This thesis presents the development of a new and separate market for trading Demand Response (DR) in a deregulated power system. This market is termed… (more)

Nguyen, DT

2012-01-01T23:59:59.000Z

412

Geographically Based Hydrogen Demand and Infrastructure Rollout...  

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

Rollout Scenario Analysis Geographically Based Hydrogen Demand and Infrastructure Rollout Scenario Analysis Presentation by Margo Melendez at the 2010-2025 Scenario Analysis for...

413

Opportunities, Barriers and Actions for Industrial Demand Response in California  

SciTech Connect

In 2006 the Demand Response Research Center (DRRC) formed an Industrial Demand Response Team to investigate opportunities and barriers to implementation of Automated Demand Response (Auto-DR) systems in California industries. Auto-DR is an open, interoperable communications and technology platform designed to: Provide customers with automated, electronic price and reliability signals; Provide customers with capability to automate customized DR strategies; Automate DR, providing utilities with dispatchable operational capability similar to conventional generation resources. This research began with a review of previous Auto-DR research on the commercial sector. Implementing Auto-DR in industry presents a number of challenges, both practical and perceived. Some of these include: the variation in loads and processes across and within sectors, resource-dependent loading patterns that are driven by outside factors such as customer orders or time-critical processing (e.g. tomato canning), the perceived lack of control inherent in the term 'Auto-DR', and aversion to risk, especially unscheduled downtime. While industry has demonstrated a willingness to temporarily provide large sheds and shifts to maintain grid reliability and be a good corporate citizen, the drivers for widespread Auto-DR will likely differ. Ultimately, most industrial facilities will balance the real and perceived risks associated with Auto-DR against the potential for economic gain through favorable pricing or incentives. Auto-DR, as with any ongoing industrial activity, will need to function effectively within market structures. The goal of the industrial research is to facilitate deployment of industrial Auto-DR that is economically attractive and technologically feasible. Automation will make DR: More visible by providing greater transparency through two-way end-to-end communication of DR signals from end-use customers; More repeatable, reliable, and persistent because the automated controls strategies that are 'hardened' and pre-programmed into facility's software and hardware; More affordable because automation can help reduce labor costs associated with manual DR strategies initiated by facility staff and can be used for long-term.

McKane, Aimee T.; Piette, Mary Ann; Faulkner, David; Ghatikar, Girish; Radspieler Jr., Anthony; Adesola, Bunmi; Murtishaw, Scott; Kiliccote, Sila

2008-01-31T23:59:59.000Z

414

FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007  

E-Print Network (OSTI)

......................................................................... 11 3. Demand Side Management (DSM) Program Impacts................................... 13 4. Demand Sylvia Bender Manager DEMAND ANALYSIS OFFICE Scott W. Matthews Chief Deputy Director B.B. Blevins Forecast Methods and Models ....................................................... 14 5. Demand-Side

415

Demand Response and Electric Grid Reliability  

E-Print Network (OSTI)

Demand Response and Electric Grid Reliability Paul Wattles Senior Analyst, Market Design & Development, ERCOT CATEE Conference, Galveston October 10, 2012 2 North American Bulk Power Grids CATEE Conference October 10, 2012 ? The ERCOT... adequacy ? ?Achieving more DR participation would . . . displace some generation investments, but would achieve the same level of reliability... ? ?Achieving this ideal requires widespread demand response and market structures that enable loads...

Wattles, P.

2012-01-01T23:59:59.000Z

416

DEMAND SIMULATION FOR DYNAMIC TRAFFIC ASSIGNMENT  

E-Print Network (OSTI)

of the response of travelers to real-time pre- trip information. The demand simulator is an extension of dynamicDEMAND SIMULATION FOR DYNAMIC TRAFFIC ASSIGNMENT Constantinos Antoniou, Moshe Ben-Akiva, Michel Bierlaire, and Rabi Mishalani Massachusetts Institute of Technology, Cambridge, MA 02139 Abstract

Bierlaire, Michel

417

A Vision of Demand Response - 2016  

SciTech Connect

Envision a journey about 10 years into a future where demand response is actually integrated into the policies, standards, and operating practices of electric utilities. Here's a bottom-up view of how demand response actually works, as seen through the eyes of typical customers, system operators, utilities, and regulators. (author)

Levy, Roger

2006-10-15T23:59:59.000Z

418

SUMMER 2007 ELECTRICITY SUPPLY AND DEMAND OUTLOOK  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION SUMMER 2007 ELECTRICITY SUPPLY AND DEMAND OUTLOOK DRAFTSTAFFREPORT May ELECTRICITY ANALYSIS OFFICE Sylvia Bender Acting Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION B. B assessment of the capability of the physical electricity system to provide power to meet electricity demand

419

Incorporating Demand Response into Western Interconnection Transmission Planning  

E-Print Network (OSTI)

response DSM – Demand Side Management EE – energy efficiencywith the development of demand-side management (DSM)-related

Satchwell, Andrew

2014-01-01T23:59:59.000Z

420

NETL: News Release - Ten Projects Selected by DOE to Advance  

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

7, 2010 7, 2010 Ten Projects Selected by DOE to Advance State-of-the-Art Carbon Capture from Coal Power Plants Washington, D.C. -Ten projects aimed at developing advanced technologies for capturing carbon dioxide (CO2) from coal combustion have been selected by the U.S. Department of Energy (DOE) under its Innovations for Existing Plants (IEP) Program. Valued at approximately $67 million ($15 million in non-federal cost sharing) over three years, the projects are focused on reducing the "energy and efficiency penalties" associated with applying currently available carbon capture and storage (CCS) technologies to existing and new power plants. CO2 power plant capture systems currently require large amounts of energy for their operation, resulting in decreased efficiency and reduced net power output when compared to plants without CCS technology. These "penalties" can add as much as 80 percent to the cost of electricity for a new pulverized coal plant and about 35 percent to the cost of electricity for a new advanced gasification plant. The overall goal of research conducted by DOE's Office of Fossil Energy (FE) and managed by FE's National Energy Technology Laboratory (NETL) is to improve efficiencies and reduce these costs to less than 30 percent and 10 percent, respectively.

Note: This page contains sample records for the topic "demand ten end-use" 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

From the Lab to the Marketplace-Ten Years Later  

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

From the Lab to the Marketplace Ten Years Later, Energy Efficient Technologies from Research at the Lawrence Berkeley National Laboratory Berkeley Lab logo (left) with six rows of gray dots transitioning to a line art drawing of a cityscape and residential houses. From the Lab to the Marketplace Ten Years Later, Energy Efficient Technologies from Research at the Lawrence Berkeley National Laboratory Berkeley Lab logo (left) with six rows of gray dots transitioning to a line art drawing of a cityscape and residential houses. From the Lab to the Marketplace The United States consumes about 100 quadrillion BTUs (100 quads) of energy at the cost of $1 trillion each year, roughly 10% of our Gross Domestic Product. This energy is used by the nation's 114 million households, 82 billion square feet of commercial building floor space, 130 million cars, 95 million trucks, other modes of transportation, and by millions of manufacturing establishments large and small, to power the economy, and improve our lives. Burning fossil fuels to produce energy leads to a variety of well-known

422

Uranium 2009 resources, production and demand  

E-Print Network (OSTI)

With several countries currently building nuclear power plants and planning the construction of more to meet long-term increases in electricity demand, uranium resources, production and demand remain topics of notable interest. In response to the projected growth in demand for uranium and declining inventories, the uranium industry – the first critical link in the fuel supply chain for nuclear reactors – is boosting production and developing plans for further increases in the near future. Strong market conditions will, however, be necessary to trigger the investments required to meet projected demand. The "Red Book", jointly prepared by the OECD Nuclear Energy Agency and the International Atomic Energy Agency, is a recognised world reference on uranium. It is based on information compiled in 40 countries, including those that are major producers and consumers of uranium. This 23rd edition provides a comprehensive review of world uranium supply and demand as of 1 January 2009, as well as data on global ur...

Organisation for Economic Cooperation and Development. Paris

2010-01-01T23:59:59.000Z

423

Coordination of Energy Efficiency and Demand Response  

SciTech Connect

This paper reviews the relationship between energy efficiency and demand response and discusses approaches and barriers to coordinating energy efficiency and demand response. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025. Improving energy efficiency in our homes, businesses, schools, governments, and industries - which consume more than 70 percent of the nation's natural gas and electricity - is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demand response is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demand response resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demand response potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that 'the combination of demand response and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW' by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demand response programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

Goldman, Charles; Reid, Michael; Levy, Roger; Silverstein, Alison

2010-01-29T23:59:59.000Z

424

Strategies for Demand Response in Commercial Buildings  

SciTech Connect

This paper describes strategies that can be used in commercial buildings to temporarily reduce electric load in response to electric grid emergencies in which supplies are limited or in response to high prices that would be incurred if these strategies were not employed. The demand response strategies discussed herein are based on the results of three years of automated demand response field tests in which 28 commercial facilities with an occupied area totaling over 11 million ft{sup 2} were tested. Although the demand response events in the field tests were initiated remotely and performed automatically, the strategies used could also be initiated by on-site building operators and performed manually, if desired. While energy efficiency measures can be used during normal building operations, demand response measures are transient; they are employed to produce a temporary reduction in demand. Demand response strategies achieve reductions in electric demand by temporarily reducing the level of service in facilities. Heating ventilating and air conditioning (HVAC) and lighting are the systems most commonly adjusted for demand response in commercial buildings. The goal of demand response strategies is to meet the electric shed savings targets while minimizing any negative impacts on the occupants of the buildings or the processes that they perform. Occupant complaints were minimal in the field tests. In some cases, ''reductions'' in service level actually improved occupant comfort or productivity. In other cases, permanent improvements in efficiency were discovered through the planning and implementation of ''temporary'' demand response strategies. The DR strategies that are available to a given facility are based on factors such as the type of HVAC, lighting and energy management and control systems (EMCS) installed at the site.

Watson, David S.; Kiliccote, Sila; Motegi, Naoya; Piette, Mary Ann

2006-06-20T23:59:59.000Z

425

Encryption-on-Demand, [EOD-g8516] Page #-1 Encryption-On-Demand  

E-Print Network (OSTI)

Encryption-on-Demand, [EOD-g8516] Page #-1 Encryption-On-Demand: Practical and Theoretical be served by an 'encryption-on-demand' (EoD) service which will enable them to communicate securely with no prior preparations, and no after effects. We delineate a possible EoD service, and describe some of its

426

Coordination of Energy Efficiency and Demand Response  

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

Coordination of Energy Efficiency and Demand Response Coordination of Energy Efficiency and Demand Response Title Coordination of Energy Efficiency and Demand Response Publication Type Report Refereed Designation Unknown Year of Publication 2010 Authors Goldman, Charles A., Michael Reid, Roger Levy, and Alison Silverstein Pagination 74 Date Published 01/2010 Publisher LBNL City Berkeley Keywords electricity markets and policy group, energy analysis and environmental impacts department Abstract This paper reviews the relationship between energy efficiency and demand response and discusses approaches and barriers to coordinating energy efficiency and demand response. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025.1 Improving energy efficiency in our homes, businesses, schools, governments, and industries-which consume more than 70 percent of the nation's natural gas and electricity-is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demand response is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demand response resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demand response potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that "the combination of demand response and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW" by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demand response programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

427

Demand Response This is the first of the Council's power plans to treat demand response as a resource.1  

E-Print Network (OSTI)

Demand Response This is the first of the Council's power plans to treat demand response the resource and describes some of the potential advantages and problems of the development of demand response. WHAT IS DEMAND RESPONSE? Demand response is a change in customers' demand for electricity corresponding

428

Top ten list of user-hostile interface design  

SciTech Connect

This report describes ten of the most frequent ergonomic problems found in human-computer interfaces (HCIs) associated with complex industrial machines. In contrast with being thought of as ``user friendly,`` many of these machines are seen as exhibiting ``user-hostile`` attributes by the author. The historical lack of consistent application of ergonomic principles in the HCIs has led to a breed of very sophisticated, complex manufacturing equipment that few people can operate without extensive orientation, training, or experience. This design oversight has produced the need for extensive training programs and help documentation, unnecessary machine downtime, and reduced productivity resulting from operator stress and confusion. Ergonomic considerations affect industrial machines in at least three important areas: (1) the physical package including CRT and keyboard, maintenance access areas, and dedicated hardware selection, layout, and labeling; (2) the software by which the user interacts with the computer that controls the equipment; and (3) the supporting documentation.

Miller, D.P.

1994-10-01T23:59:59.000Z

429

Health Care Demand, Empirical Determinants of  

Science Journals Connector (OSTI)

Abstract Economic theory provides a powerful but incomplete guide to the empirical determinants of health care demand. This article seeks to provide guidance on the selection and interpretation of demand determinants in empirical models. The author begins by introducing some general rules of thumb derived from economic and statistical principles. A brief review of the recent empirical literature next describes the range of current practices. Finally, a representative example of health care demand is developed to illustrate the selection, use, and interpretation of empirical determinants.

S.H. Zuvekas

2014-01-01T23:59:59.000Z

430

Fact #770: March 11, 2013 Changes to the Top Ten Vehicles Sold...  

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

70: March 11, 2013 Changes to the Top Ten Vehicles Sold over the Last Five Years Fact 770: March 11, 2013 Changes to the Top Ten Vehicles Sold over the Last Five Years When...

431

NCEP_Demand_Response_Draft_111208.indd  

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

National Council on Electricity Policy: Electric Transmission Series for State Offi National Council on Electricity Policy: Electric Transmission Series for State Offi cials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials Prepared by the U.S. Demand Response Coordinating Committee for The National Council on Electricity Policy Fall 2008 i National Council on Electricity Policy: Electric Transmission Series for State Offi cials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials The National Council on Electricity Policy is funded by the U.S. Department of Energy and the U.S. Environmental Protection Agency. The views and opinions expressed herein are strictly those of the

432

Solar in Demand | Department of Energy  

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

Solar in Demand Solar in Demand Solar in Demand June 15, 2012 - 10:23am Addthis Kyle Travis, left and Jon Jackson, with Lighthouse Solar, install microcrystalline PV modules on top of Kevin Donovan's town home. | Credit: Dennis Schroeder. Kyle Travis, left and Jon Jackson, with Lighthouse Solar, install microcrystalline PV modules on top of Kevin Donovan's town home. | Credit: Dennis Schroeder. April Saylor April Saylor Former Digital Outreach Strategist, Office of Public Affairs What does this mean for me? A new study says U.S. developers are likely to install about 3,300 megawatts of solar panels in 2012 -- almost twice the amount installed last year. In case you missed it... This week, the Wall Street Journal published an article, "U.S. Solar-Panel Demand Expected to Double," highlighting the successes of

433

National Action Plan on Demand Response  

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

David Kathan, Ph.D David Kathan, Ph.D Federal Energy Regulatory Commission U.S. DOE Electricity Advisory Committee October 29, 2010 Demand Response as Power System Resources The author's views do not necessarily represent the views of the Federal Energy Regulatory Commission 2 Demand Response * FERC (Order 719) defines demand response as: - A reduction in the consumption of electric energy by customers from their expected consumption in response to an increase in the price of electric energy or to in incentive payments designed to induce lower consumption of electric energy. * The National Action Plan on Demand Response released by FERC staff broadens this definition to include - Consumer actions that can change any part of the load profile of a utility or region, not just the period of peak usage

434

EIA - Annual Energy Outlook 2008 - Electricity Demand  

Gasoline and Diesel Fuel Update (EIA)

Electricity Demand Electricity Demand Annual Energy Outlook 2008 with Projections to 2030 Electricity Demand Figure 60. Annual electricity sales by sector, 1980-2030 (billion kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 61. Electricity generation by fuel, 2006 and 2030 (billion kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. figure data Residential and Commercial Sectors Dominate Electricity Demand Growth Total electricity sales increase by 29 percent in the AEO2008 reference case, from 3,659 billion kilowatthours in 2006 to 4,705 billion in 2030, at an average rate of 1.1 percent per year. The relatively slow growth follows the historical trend, with the growth rate slowing in each succeeding

435

Demand Controlled Ventilation and Classroom Ventilation  

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

3 3 Authors Fisk, William J., Mark J. Mendell, Molly Davies, Ekaterina Eliseeva, David Faulkner, Tienzen Hong, and Douglas P. Sullivan Publisher Lawrence Berkeley National Laboratory City Berkeley Keywords absence, building s, carbon dioxide, demand - controlled ventilation, energy, indoor air quality, schools, ventilation Abstract This document summarizes a research effort on demand controlled ventilation and classroom ventilation. The research on demand controlled ventilation included field studies and building energy modeling. Major findings included: ï‚· The single-location carbon dioxide sensors widely used for demand controlled ventilation frequently have large errors and will fail to effectively control ventilation rates (VRs). ï‚· Multi-location carbon dioxide measurement systems with more expensive sensors connected to multi-location sampling systems may measure carbon dioxide more accurately.

436

Integrated Predictive Demand Response Controller Research Project |  

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

Predictive Demand Response Predictive Demand Response Controller Research Project Integrated Predictive Demand Response Controller Research Project The U.S. Department of Energy (DOE) is currently conducting research into integrated predictive demand response (IPDR) controllers. The project team will attempt to design an IPDR controller so that it can be used in new or existing buildings or in collections of buildings. In the case of collections of buildings, they may be colocated on a single campus or remotely located as long as they are served by a single utility or independent service operator. Project Description This project seeks to perform the necessary applied research, development, and testing to provide a communications interface using industry standard open protocols and emerging National Institute of Standards and Technology

437

Software demonstration: Demand Response Quick Assessment Tool  

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

Software demonstration: Demand Response Quick Assessment Tool Software demonstration: Demand Response Quick Assessment Tool Speaker(s): Peng Xu Date: February 4, 2008 - 12:00pm Location: 90-3122 The potential for utilizing building thermal mass for load shifting and peak demand reduction has been demonstrated in a number of simulation, laboratory, and field studies. The Demand Response Quick Assessment Tools developed at LBNL will be demonstrated. The tool is built on EnergyPlus simulation and is able to evaluate and compare different DR strategies, such as global temperature reset, chiller cycling, supply air temperature reset, etc. A separate EnergyPlus plotting tool will also be demonstrated during this seminar. Users can use the tool to test EnergyPlus models, conduct parametric analysis, or compare multiple EnergyPlus simulation

438

Power Consumption Analysis of Architecture on Demand  

Science Journals Connector (OSTI)

Abstract (40-Word Limit): Recently proposed Architecture on Demand (AoD) node shows considerable flexibility benefits against traditional ROADMs. We study the power consumption of AoD...

Garrich, Miquel; Amaya, Norberto; Zervas, Georgios; Giaccone, Paolo; Simeonidou, Dimitra

439

Integration of Demand Side Management, Distributed Generation...  

Open Energy Info (EERE)

States. Annex 8 provides a list of software tools for analysing various aspects of demand response, distributed generation, smart grid and energy storage. Annex 9 is a list of...

440

Capitalize on Existing Assets with Demand Response  

E-Print Network (OSTI)

Industrial facilities universally struggle with escalating energy costs. EnerNOC will demonstrate how commercial, industrial, and institutional end-users can capitalize on their existing assets—at no cost and no risk. Demand response, the voluntary...

Collins, J.

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "demand ten end-use" 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

SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY  

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

As a city that experiences seasonal spikes in energy demand and accompanying energy bills, San Antonio, Texas, wanted to help homeowners and businesses reduce their energy use and save on energy...

442

Global Energy: Supply, Demand, Consequences, Opportunities  

SciTech Connect

July 29, 2008 Berkeley Lab lecture: Arun Majumdar, Director of the Environmental Energy Technologies Division, discusses current and future projections of economic growth, population, and global energy demand and supply, and explores the implications of these trends for the environment.

Arun Majumdar

2008-08-14T23:59:59.000Z

443

Volatile coal prices reflect supply, demand uncertainties  

SciTech Connect

Coal mine owners and investors say that supply and demand are now finally in balance. But coal consumers find that both spot tonnage and new contract coal come at a much higher price.

Ryan, M.

2004-12-15T23:59:59.000Z

444

Global Energy: Supply, Demand, Consequences, Opportunities  

ScienceCinema (OSTI)

July 29, 2008 Berkeley Lab lecture: Arun Majumdar, Director of the Environmental Energy Technologies Division, discusses current and future projections of economic growth, population, and global energy demand and supply, and explores the implications of these trends for the environment.

Arun Majumdar

2010-01-08T23:59:59.000Z

445

Demand Controlled Ventilation and Classroom Ventilation  

E-Print Network (OSTI)

columns indicate the energy and cost savings for  demand class size.   (The energy costs  of classroom ventilation Total Increase in Energy Costs ($) Increased State Revenue

Fisk, William J.

2014-01-01T23:59:59.000Z

446

Transportation energy demand: Model development and use  

Science Journals Connector (OSTI)

This paper describes work undertaken and sponsored by the Energy Commission to improve transportation energy demand forecasting and policy analysis for California. Two ... , the paper discusses some of the import...

Chris Kavalec

1998-06-01T23:59:59.000Z

447

Measuring the capacity impacts of demand response  

SciTech Connect

Critical peak pricing and peak time rebate programs offer benefits by increasing system reliability, and therefore, reducing capacity needs of the electric power system. These benefits, however, decrease substantially as the size of the programs grows relative to the system size. More flexible schemes for deployment of demand response can help address the decreasing returns to scale in capacity value, but more flexible demand response has decreasing returns to scale as well. (author)

Earle, Robert; Kahn, Edward P.; Macan, Edo

2009-07-15T23:59:59.000Z

448

Real-Time Demand Side Energy Management  

E-Print Network (OSTI)

Real-Time Demand Side Energy Management Annelize Victor Michael Brodkorb Sr. Business Consultant Business Development Manager Aspen Technology, Inc. Aspen Technology España, S.A. Houston, TX Barcelona, Spain ABSTRACT To remain... competitive, manufacturers must capture opportunities to increase bottom-line profitability. The goal of this paper is to present a new methodology for reducing energy costs – “Demand-Side Energy Management.” Learn how process manufacturers assess energy...

Victor, A.; Brodkorb, M.

2006-01-01T23:59:59.000Z

449

Electric Utility Demand-Side Evaluation Methodologies  

E-Print Network (OSTI)

"::. ELECTRIC UTILITY DEMAND-SIDE EVALUATION METHODOLOGIES* Nat Treadway Public Utility Commission of Texas Austin, Texas ABSTRACT The electric. util ity industry's demand-side management programs can be analyzed ?from various points... of view using a standard benefit-cost methodology. The methodology now in use by several. electric utilities and the Public Utility Commlsslon of Texas includes measures of efficiency and equity. The nonparticipant test as a measure of equity...

Treadway, N.

450

Aviation fuel demand development in China  

Science Journals Connector (OSTI)

Abstract This paper analyzes the core factors and the impact path of aviation fuel demand in China and conducts a structural decomposition analysis of the aviation fuel cost changes and increase of the main aviation enterprises’ business profits. Through the establishment of an integrated forecast model for China’s aviation fuel demand, this paper confirms that the significant rise in China’s aviation fuel demand because of increasing air services demand is more than offset by higher aviation fuel efficiency. There are few studies which use a predictive method to decompose, estimate and analyze future aviation fuel demand. Based on a structural decomposition with indirect prediction, aviation fuel demand is decomposed into efficiency and total amount (aviation fuel efficiency and air transport total turnover). The core influencing factors for these two indexes are selected using path analysis. Then, univariate and multivariate models (ETS/ARIMA model and Bayesian multivariate regression) are used to analyze and predict both aviation fuel efficiency and air transport total turnover. At last, by integrating results, future aviation fuel demand is forecast. The results show that the aviation fuel efficiency goes up by 0.8% as the passenger load factor increases 1%; the air transport total turnover goes up by 3.8% and 0.4% as the urbanization rate and the per capita GDP increase 1%, respectively. By the end of 2015, China’s aviation fuel demand will have increased to 28 million tonnes, and is expected to be 50 million tonnes by 2020. With this in mind, increases in the main aviation enterprises’ business profits must be achieved through the further promotion of air transport.

Jian Chai; Zhong-Yu Zhang; Shou-Yang Wang; Kin Keung Lai; John Liu

2014-01-01T23:59:59.000Z

451

Ethanol Demand in United States Gasoline Production  

SciTech Connect

The Oak Ridge National Laboratory (OWL) Refinery Yield Model (RYM) has been used to estimate the demand for ethanol in U.S. gasoline production in year 2010. Study cases examine ethanol demand with variations in world oil price, cost of competing oxygenate, ethanol value, and gasoline specifications. For combined-regions outside California summer ethanol demand is dominated by conventional gasoline (CG) because the premised share of reformulated gasoline (RFG) production is relatively low and because CG offers greater flexibility for blending high vapor pressure components like ethanol. Vapor pressure advantages disappear for winter CG, but total ethanol used in winter RFG remains low because of the low RFG production share. In California, relatively less ethanol is used in CG because the RFG production share is very high. During the winter in California, there is a significant increase in use of ethanol in RFG, as ethanol displaces lower-vapor-pressure ethers. Estimated U.S. ethanol demand is a function of the refiner value of ethanol. For example, ethanol demand for reference conditions in year 2010 is 2 billion gallons per year (BGY) at a refiner value of $1.00 per gallon (1996 dollars), and 9 BGY at a refiner value of $0.60 per gallon. Ethanol demand could be increased with higher oil prices, or by changes in gasoline specifications for oxygen content, sulfur content, emissions of volatile organic compounds (VOCS), and octane numbers.

Hadder, G.R.

1998-11-24T23:59:59.000Z

452

Performance analysis of demand planning approaches for aggregating, forecasting and disaggregating interrelated demands  

Science Journals Connector (OSTI)

A synchronized and responsive flow of materials, information, funds, processes and services is the goal of supply chain planning. Demand planning, which is the very first step of supply chain planning, determines the effectiveness of manufacturing and logistic operations in the chain. Propagation and magnification of the uncertainty of demand signals through the supply chain, referred to as the bullwhip effect, is the major cause of ineffective operation plans. Therefore, a flexible and robust supply chain forecasting system is necessary for industrial planners to quickly respond to the volatile demand. Appropriate demand aggregation and statistical forecasting approaches are known to be effective in managing the demand variability. This paper uses the bivariate VAR(1) time series model as a study vehicle to investigate the effects of aggregating, forecasting and disaggregating two interrelated demands. Through theoretical development and systematic analysis, guidelines are provided to select proper demand planning approaches. A very important finding of this research is that disaggregation of a forecasted aggregated demand should be employed when the aggregated demand is very predictable through its positive autocorrelation. Moreover, the large positive correlation between demands can enhance the predictability and thus result in more accurate forecasts when statistical forecasting methods are used.

Argon Chen; Jakey Blue

2010-01-01T23:59:59.000Z

453

Automated Demand Response: The Missing Link in the Electricity Value Chain  

SciTech Connect

In 2006, the Public Interest Energy Research Program (PIER) Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory initiated research into Automated Demand Response (OpenADR) applications in California industry. The goal is to improve electric grid reliability and lower electricity use during periods of peak demand. The purpose of this research is to begin to define the relationship among a portfolio of actions that industrial facilities can undertake relative to their electricity use. This ?electricity value chain? defines energy management and demand response (DR) at six levels of service, distinguished by the magnitude, type, and rapidity of response. One element in the electricity supply chain is OpenADR, an open-standards based communications system to send signals to customers to allow them to manage their electric demand in response to supply conditions, such as prices or reliability, through a set of standard, open communications. Initial DRRC research suggests that industrial facilities that have undertaken energy efficiency measures are probably more, not less, likely to initiate other actions within this value chain such as daily load management and demand response. Moreover, OpenADR appears to afford some facilities the opportunity to develop the supporting control structure and to"demo" potential reductions in energy use that can later be applied to either more effective load management or a permanent reduction in use via energy efficiency. Under the right conditions, some types of industrial facilities can shift or shed loads, without any, or minimal disruption to operations, to protect their energy supply reliability and to take advantage of financial incentives.1 In 2007 and 2008, 35 industrial facilities agreed to implement OpenADR, representing a total capacity of nearly 40 MW. This paper describes how integrated or centralized demand management and system-level network controls are linked to OpenADR systems. Case studies of refrigerated warehouses and wastewater treatment facilities are used to illustrate OpenADR load reduction potential. Typical shed and shift strategies include: turning off or operating compressors, aerator blowers and pumps at reduced capacity, increasing temperature set-points or pre-cooling cold storage areas and over-oxygenating stored wastewater prior to a DR event. This study concludes that understanding industrial end-use processes and control capabilities is a key to support reduced service during DR events and these capabilities, if DR enabled, hold significant promise in reducing the electricity demand of the industrial sector during utility peak periods.

McKane, Aimee; Rhyne, Ivin; Lekov, Alex; Thompson, Lisa; Piette, MaryAnn

2009-08-01T23:59:59.000Z

454

An Operational Model for Optimal NonDispatchable Demand Response  

E-Print Network (OSTI)

An Operational Model for Optimal NonDispatchable Demand Response for Continuous PowerintensiveFACTS, $ Demand Response Energy Storage HVDC Industrial Customer PEV Renewable Energy Source: U.S.-Canada Power: To balance supply and demand of a power system, one can manipulate both: supply and demand demand response

Grossmann, Ignacio E.

455

Regional Allocation of Biomass to U.S. Energy Demands under a Portfolio of Policy Scenarios  

Science Journals Connector (OSTI)

This study develops a spatially explicit, best-use framework to optimally allocate cellulosic biomass feedstocks to energy demands in transportation, electricity, and residential heating sectors, while minimizing total system costs and tracking greenhouse gas emissions. ... Steubing et al.(6) consider the optimal use of several biomass feedstocks to substitute fossil energy technologies in Europe, which is broader than the previously listed studies, but the authors use a ranking method to identify preferred allocation strategies with a nonspatial model. ... This study builds on these studies in developing a spatially explicit, best-use framework for model year 2020 that optimally allocates cellulosic biomass feedstocks to competing energy end uses (heating, transportation, electricity) based on minimizing total system costs. ...

Kimberley A. Mullins; Aranya Venkatesh; Amy L. Nagengast; Matt Kocoloski

2014-02-10T23:59:59.000Z

456

Alternative Fuels Data Center: Ten Ways You Can Start to Cut Petroleum Use  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

About About Printable Version Share this resource Send a link to Alternative Fuels Data Center: Ten Ways You Can Start to Cut Petroleum Use Right Now to someone by E-mail Share Alternative Fuels Data Center: Ten Ways You Can Start to Cut Petroleum Use Right Now on Facebook Tweet about Alternative Fuels Data Center: Ten Ways You Can Start to Cut Petroleum Use Right Now on Twitter Bookmark Alternative Fuels Data Center: Ten Ways You Can Start to Cut Petroleum Use Right Now on Google Bookmark Alternative Fuels Data Center: Ten Ways You Can Start to Cut Petroleum Use Right Now on Delicious Rank Alternative Fuels Data Center: Ten Ways You Can Start to Cut Petroleum Use Right Now on Digg Find More places to share Alternative Fuels Data Center: Ten Ways You Can Start to Cut Petroleum Use Right Now on AddThis.com...

457

U.S. Coal Supply and Demand  

Gasoline and Diesel Fuel Update (EIA)

U.S. Coal Supply and Demand > U.S. Coal Supply and Demand U.S. Coal Supply and Demand > U.S. Coal Supply and Demand U.S. Coal Supply and Demand 2010 Review (entire report also available in printer-friendly format ) Previous Editions 2009 Review 2008 Review 2007 Review 2006 Review 2005 Review 2004 Review 2003 Review 2002 Review 2001 Review 2000 Review 1999 Review Data for: 2010 Released: May 2011 Next Release Date: April 2012 Table 3. Electric Power Sector Net Generation, 2009-2010 (Million Kilowatthours) New England Coal 14,378 14,244 -0.9 Hydroelectric 7,759 6,861 -11.6 Natural Gas 48,007 54,680 13.9 Nuclear 36,231 38,361 5.9 Other (1) 9,186 9,063 -1.3 Total 115,559 123,210 6.6 Middle Atlantic Coal 121,873 129,935 6.6 Hydroelectric 28,793 26,463 -8.1 Natural Gas 89,808 104,341 16.2 Nuclear 155,140 152,469 -1.7

458

Beyond kWh and kW demand: Understanding the new real-time electric power  

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

Beyond kWh and kW demand: Understanding the new real-time electric power Beyond kWh and kW demand: Understanding the new real-time electric power measurement system in LBNL Building 90 Speaker(s): Alex McEachern Date: January 14, 2010 - 12:00pm Location: 90-3122 In the Summer of 2009, LBNL researchers installed end-use sub-metering equipment and associated Energy Information System (EIS) tools to characterize energy use and comfort in Building 90. Seven of 40 key electric loads were measured using advanced meters that make sophisticated real-time measurements of dozens of power flow parameters, power disturbances, and harmonics. The talk will review some electrical engineering fundamentals, how use and interpret data measured in building 90 in real-time. The real-time data available includes power, volt-amps, VAR's, unbalance voltage and current, voltage and current distortion,

459

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network (OSTI)

LABORATORY Coordination of Retail Demand Response withXXXXX Coordination of Retail Demand Response with MidwestAC02-05CH11231. Coordination of Retail Demand Response with

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

460

Analysis of Open Automated Demand Response Deployments in California  

E-Print Network (OSTI)

LBNL-6560E Analysis of Open Automated Demand Response Deployments in California and Guidelines The work described in this report was coordinated by the Demand Response Research. #12; #12;Abstract This report reviews the Open Automated Demand Response

Note: This page contains sample records for the topic "demand ten end-use" 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

PIER: Demand Response Research Center Director, Mary Ann Piette  

E-Print Network (OSTI)

1 PIER: Demand Response Research Center Director, Mary Ann Piette Program Development and Outreach Response Research Plan #12;2 Demand Response Research Center Objective Scope Stakeholders Develop, prioritize, conduct and disseminate multi- institutional research to facilitate Demand Response. Technologies

462

Automated Demand Response Strategies and Commissioning Commercial Building Controls  

E-Print Network (OSTI)

4 9 . Piette et at Automated Demand Response Strategies andDynamic Controls for Demand Response in New and ExistingFully Automated Demand Response Tests in Large Facilities"

Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Linkugel, Eric

2006-01-01T23:59:59.000Z

463

Demand Response Enabling Technologies and Approaches for Industrial Facilities  

E-Print Network (OSTI)

, there are also huge opportunities for demand response in the industrial sector. This paper describes some of the demand response initiatives that are currently active in New York State, explaining applicability of industrial facilities. Next, we discuss demand...

Epstein, G.; D'Antonio, M.; Schmidt, C.; Seryak, J.; Smith, C.

2005-01-01T23:59:59.000Z

464

LEED Demand Response Credit: A Plan for Research towards Implementation  

E-Print Network (OSTI)

DR’s growing role in demand-side management activities andhow DR fits with demand-side management activities, DRemissions rates The demand-side management (DSM) framework

Kiliccote, Sila

2014-01-01T23:59:59.000Z

465

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network (OSTI)

Data Collection for Demand-side Management for QualifyingPrepared by Demand-side Management Task Force of the4. Status of Demand Side Management in Midwest ISO 5.

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

466

A Survey on Privacy in Residential Demand Side Management Applications  

Science Journals Connector (OSTI)

Demand Side Management (DSM) is an auspicious concept for ... on privacy energy issues and potential solutions in Demand Response systems. For this we give an ... the BSI and indicate three technical types of Demand

Markus Karwe; Jens Strüker

2014-01-01T23:59:59.000Z

467

Demand-Side Management and Energy Efficiency Revisited  

E-Print Network (OSTI)

EPRI). 1984. ”Demand Side Management. Vol. 1:Overview of Key1993. ”Industrial Demand-Side Management Programs: What’sJ. Kulick. 2004. ”Demand side management and energy e?ciency

Auffhammer, Maximilian; Blumstein, Carl; Fowlie, Meredith

2007-01-01T23:59:59.000Z

468

Commercial Fleet Demand for Alternative-Fuel Vehicles in California  

E-Print Network (OSTI)

Precursors of demand for alternative-fuel vehicles: resultsFLEET DEMAND FOR ALTERNATIVE-FUEL VEHICLES IN CALIFORNIA*Abstract—Fleet demand for alternative-fuel vehicles (‘AFVs’

Golob, Thomas F; Torous, Jane; Bradley, Mark; Brownstone, David; Crane, Soheila Soltani; Bunch, David S

1996-01-01T23:59:59.000Z

469

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

ED2, September. CEC (2005b) Energy demand forecast methodsCalifornia Baseline Energy Demands to 2050 for Advancedof a baseline scenario for energy demand in California for a

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

470

Behavioral Aspects in Simulating the Future US Building Energy Demand  

E-Print Network (OSTI)

Importance Total off- site energy demand (2030) 20% decreaseImportance Total off-site energy demand (2030) 20% decreaseImportance Total off-site energy demand (2030) 20% decrease

Stadler, Michael

2011-01-01T23:59:59.000Z

471

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network (OSTI)

iv Chapter 5: National energy demand and potential energyAs Figure 1-2 shows, HVAC energy demand is comparable to thefor reducing this high energy demand reaches beyond

Shehabi, Arman

2010-01-01T23:59:59.000Z

472

Production Will Meet Demand Increase This Summer  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: Production must meet increases in demand this year. Last year, increased imports met most of the summer demand increase, and increases in stock draws met almost all of the remainder. Production did not increase much. But this year, inventories will not be available, and increased imports seem unlikely. Thus, increases in production will be needed to meet increased demand. Imports availability is uncertain this summer. Imports in 1999 were high, and with Phase II RFG product requirements, maintaining this level could be challenging since not all refineries exporting to the U.S. will be able to meet the new gasoline specifications. Stocks will also contribute little supply this summer. Last year's high gasoline stocks allowed for a stock draw that was 58 MB/D higher than

473

EIA - Annual Energy Outlook 2008 - Energy Demand  

Gasoline and Diesel Fuel Update (EIA)

Energy Demand Energy Demand Annual Energy Outlook 2008 with Projections to 2030 Energy Demand Figure 40. Energy use per capita and per dollar of gross domestic product, 1980-2030 (index, 1980 = 1). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 41. Primary energy use by fuel, 2006-2030 (quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. figure data Average Energy Use per Person Levels Off Through 2030 Because energy use for housing, services, and travel in the United States is closely linked to population levels, energy use per capita is relatively stable (Figure 40). In addition, the economy is becoming less dependent on energy in general. Energy intensity (energy use per 2000 dollar of GDP) declines by an average

474

International Oil Supplies and Demands. Volume 1  

SciTech Connect

The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--90 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world`s dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group`s thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

Not Available

1991-09-01T23:59:59.000Z

475

Energy demand simulation for East European countries  

Science Journals Connector (OSTI)

The analysis and created statistical models of energy consumption tendencies in the European Union (EU25), including new countries in transition, are presented. The EU15 market economy countries and countries in transition are classified into six clusters by relative indicators of Gross Domestic Product (GDP/P) and energy demand (W/P) per capita. The specified statistical models of energy intensity W/GDP non-linear stochastic tendencies have been discovered with respect to the clusters of classified countries. The new energy demand simulation models have been developed for the demand management in timeâ??territory hierarchy in various scenarios of short-term and long-term perspective on the basis of comparative analysis methodology. The non-linear statistical models were modified to GDP, W/P and electricity (E/P) final consumption long-term forecasts for new associated East European countries and, as an example, for the Baltic Countries, including Lithuania.

Jonas Algirdas Kugelevicius; Algirdas Kuprys; Jonas Kugelevicius

2007-01-01T23:59:59.000Z

476

China's Coal: Demand, Constraints, and Externalities  

SciTech Connect

This study analyzes China's coal industry by focusing on four related areas. First, data are reviewed to identify the major drivers of historical and future coal demand. Second, resource constraints and transport bottlenecks are analyzed to evaluate demand and growth scenarios. The third area assesses the physical requirements of substituting coal demand growth with other primary energy forms. Finally, the study examines the carbon- and environmental implications of China's past and future coal consumption. There are three sections that address these areas by identifying particular characteristics of China's coal industry, quantifying factors driving demand, and analyzing supply scenarios: (1) reviews the range of Chinese and international estimates of remaining coal reserves and resources as well as key characteristics of China's coal industry including historical production, resource requirements, and prices; (2) quantifies the largest drivers of coal usage to produce a bottom-up reference projection of 2025 coal demand; and (3) analyzes coal supply constraints, substitution options, and environmental externalities. Finally, the last section presents conclusions on the role of coal in China's ongoing energy and economic development. China has been, is, and will continue to be a coal-powered economy. In 2007 Chinese coal production contained more energy than total Middle Eastern oil production. The rapid growth of coal demand after 2001 created supply strains and bottlenecks that raise questions about sustainability. Urbanization, heavy industrial growth, and increasing per-capita income are the primary interrelated drivers of rising coal usage. In 2007, the power sector, iron and steel, and cement production accounted for 66% of coal consumption. Power generation is becoming more efficient, but even extensive roll-out of the highest efficiency units would save only 14% of projected 2025 coal demand for the power sector. A new wedge of future coal consumption is likely to come from the burgeoning coal-liquefaction and chemicals industries. If coal to chemicals capacity reaches 70 million tonnes and coal-to-liquids capacity reaches 60 million tonnes, coal feedstock requirements would add an additional 450 million tonnes by 2025. Even with more efficient growth among these drivers, China's annual coal demand is expected to reach 3.9 to 4.3 billion tonnes by 2025. Central government support for nuclear and renewable energy has not reversed China's growing dependence on coal for primary energy. Substitution is a matter of scale: offsetting one year of recent coal demand growth of 200 million tonnes would require 107 billion cubic meters of natural gas (compared to 2007 growth of 13 BCM), 48 GW of nuclear (compared to 2007 growth of 2 GW), or 86 GW of hydropower capacity (compared to 2007 growth of 16 GW). Ongoing dependence on coal reduces China's ability to mitigate carbon dioxide emissions growth. If coal demand remains on a high growth path, carbon dioxide emissions from coal combustion alone would exceed total US energy-related carbon emissions by 2010. Within China's coal-dominated energy system, domestic transportation has emerged as the largest bottleneck for coal industry growth and is likely to remain a constraint to further expansion. China has a low proportion of high-quality reserves, but is producing its best coal first. Declining quality will further strain production and transport capacity. Furthermore, transporting coal to users has overloaded the train system and dramatically increased truck use, raising transportation oil demand. Growing international imports have helped to offset domestic transport bottlenecks. In the long term, import demand is likely to exceed 200 million tonnes by 2025, significantly impacting regional markets.

Aden, Nathaniel; Fridley, David; Zheng, Nina

2009-07-01T23:59:59.000Z

477

International Oil Supplies and Demands. Volume 2  

SciTech Connect

The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--1990 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world`s dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group`s thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

Not Available

1992-04-01T23:59:59.000Z

478

Demand Management Institute (DMI) | Open Energy Information  

Open Energy Info (EERE)

Demand Management Institute (DMI) Demand Management Institute (DMI) Jump to: navigation, search Name Demand Management Institute (DMI) Address 35 Walnut Street Place Wellesley, Massachusetts Zip 02481 Sector Buildings Product Provides analysis for buildings on reducing energy use Website http://www.dmiinc.com/ Coordinates 42.3256508°, -71.2530294° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":42.3256508,"lon":-71.2530294,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

479

Uranium 2014 resources, production and demand  

E-Print Network (OSTI)

Published every other year, Uranium Resources, Production, and Demand, or the "Red Book" as it is commonly known, is jointly prepared by the OECD Nuclear Energy Agency and the International Atomic Energy Agency. It is the recognised world reference on uranium and is based on official information received from 43 countries. It presents the results of a thorough review of world uranium supplies and demand and provides a statistical profile of the world uranium industry in the areas of exploration, resource estimates, production and reactor-related requirements. It provides substantial new information from all major uranium production centres in Africa, Australia, Central Asia, Eastern Europe and North America. Long-term projections of nuclear generating capacity and reactor-related uranium requirements are provided as well as a discussion of long-term uranium supply and demand issues. This edition focuses on recent price and production increases that could signal major changes in the industry.

Organisation for Economic Cooperation and Development. Paris

2014-01-01T23:59:59.000Z

480

DEMAND CONTROLLED VENTILATION AND CLASSROOM VENTILATION  

SciTech Connect

This document summarizes a research effort on demand controlled ventilation and classroom ventilation. The research on demand controlled ventilation included field studies and building energy modeling. Major findings included: ? The single-location carbon dioxide sensors widely used for demand controlled ventilation frequently have large errors and will fail to effectively control ventilation rates (VRs).? Multi-location carbon dioxide measurement systems with more expensive sensors connected to multi-location sampling systems may measure carbon dioxide more accurately.? Currently-available optical people counting systems work well much of the time but have large counting errors in some situations. ? In meeting rooms, measurements of carbon dioxide at return-air grilles appear to be a better choice than wall-mounted sensors.? In California, demand controlled ventilation in general office spaces is projected to save significant energy and be cost effective only if typical VRs without demand controlled ventilation are very high relative to VRs in codes. Based on the research, several recommendations were developed for demand controlled ventilation specifications in the California Title 24 Building Energy Efficiency Standards.The research on classroom ventilation collected data over two years on California elementary school classrooms to investigate associations between VRs and student illness absence (IA). Major findings included: ? Median classroom VRs in all studied climate zones were below the California guideline, and 40percent lower in portable than permanent buildings.? Overall, one additional L/s per person of VR was associated with 1.6percent less IA. ? Increasing average VRs in California K-12 classrooms from the current average to the required level is estimated to decrease IA by 3.4percent, increasing State attendance-based funding to school districts by $33M, with $6.2 M in increased energy costs. Further VR increases would provide additional benefits.? Confirming these findings in intervention studies is recommended. ? Energy costs of heating/cooling unoccupied classrooms statewide are modest, but a large portion occurs in relatively few classrooms.

Fisk, William J.; Mendell, Mark J.; Davies, Molly; Eliseeva, Ekaterina; Faulkner, David; Hong, Tienzen; Sullivan, Douglas P.

2014-01-06T23:59:59.000Z

Note: This page contains sample records for the topic "demand ten end-use" 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

Rice Supply, Demand and Related Government Programs.  

E-Print Network (OSTI)

, 1930-55 Year Weighted Year Weighted beginning average price beginning average price August per cwt. August per cwt. Dollars Dollars 'Includes an allowance for unredeemed loans. response to the strengthening of foreign demand, rice prices by 1952... 91 percent of the average parity price during 1935-54, with !he 4 years of World War I1 omitted. The elasticity of demand was assumed to be about -.2. The annually derived price based on the assumed elasticity and the percentage change in price...

Kincannon, John A.

1957-01-01T23:59:59.000Z

482

Demand Response Initiatives at CPS Energy  

E-Print Network (OSTI)

Demand Response Initiatives at CPS Energy Clean Air Through Energy Efficiency (CATEE) Conference December 17, 2013 ESL-KT-13-12-53 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 CPSE’s DR Program • DR... than the military bases and Toyota combined. • Schools & Universities contributed 6 MW’s of Demand Response in 2013. 2013 DR Participants Trinity University - $5,654 Fort Sam ISD - $18,860 Judson ISD - $45,540 Alamo Colleges - $98,222 UTSA - $168...

Luna, R.

2013-01-01T23:59:59.000Z

483

Demand Response and Smart Metering Policy Actions Since the Energy...  

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

Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Officials Demand Response and Smart Metering Policy Actions Since the...

484

Overview of Demand Side Response | Department of Energy  

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

and Energy Officials Need to Know High Electric Demand Days: Clean Energy Strategies for Improving Air Quality Demand Response in U.S. Electricity Markets: Empirical Evidence...

485

Robust Unit Commitment Problem with Demand Response and ...  

E-Print Network (OSTI)

Oct 29, 2010 ... sion, both Demand Response (DR) strategy and intermittent renewable ... Key Words: unit commitment, demand response, wind energy, robust ...

2010-10-31T23:59:59.000Z

486

National Action Plan on Demand Response | Department of Energy  

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

National Action Plan on Demand Response National Action Plan on Demand Response Presentation-given at the Federal Utility Partnership Working Group (FUPWG) Fall 2008...

487

ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES  

E-Print Network (OSTI)

ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES BY ANUPAMA SUNIL KOWLI B of consumers - called demand response resources (DRRs) - whose role has become increasingly important

Gross, George

488

The business value of demand response for balance responsible parties.  

E-Print Network (OSTI)

?? By using IT-solutions, the flexibility on the demand side in the electrical systems could be increased. This is called demand response and is part… (more)

Jonsson, Mattias

2014-01-01T23:59:59.000Z

489

Aggregator-Assisted Residential Participation in Demand Response Program.  

E-Print Network (OSTI)

??The demand for electricity of a particular location can vary significantly based on season, ambient temperature, time of the day etc. High demand can result… (more)

Hasan, Mehedi

2012-01-01T23:59:59.000Z

490

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

energy storage and demand management can complement solarwith energy storage to firm the resource, or solar thermaland solar generation. And demand response or energy storage

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

491

BUILDINGS SECTOR DEMAND-SIDE EFFICIENCY TECHNOLOGY SUMMARIES  

E-Print Network (OSTI)

............................................................................................... 2 Demand-Side Efficiency Technologies I. Energy Management Systems (EMSsLBL-33887 UC-000 BUILDINGS SECTOR DEMAND-SIDE EFFICIENCY TECHNOLOGY SUMMARIES Jonathan G. Koomey

492

Modeling, Analysis, and Control of Demand Response Resources.  

E-Print Network (OSTI)

??While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can plan an active role in… (more)

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

493

Modeling, Analysis, and Control of Demand Response Resources.  

E-Print Network (OSTI)

?? While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can plan an active role… (more)

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

494

Response to several FOIA requests - Renewable Energy. Demand...  

Energy Savers (EERE)

Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. nepdg251500.pdf....

495

Draft Chapter 3: Demand-Side Resources | Department of Energy  

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

3: Demand-Side Resources Draft Chapter 3: Demand-Side Resources Utilities in many states have been implementing energy efficiency and load management programs (collectively called...

496

Chapter 3: Demand-Side Resources | Department of Energy  

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

: Demand-Side Resources Chapter 3: Demand-Side Resources Utilities in many states have been implementing energy efficiency and load management programs (collectively called...

497

Tool Improves Electricity Demand Predictions to Make More Room...  

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

Tool Improves Electricity Demand Predictions to Make More Room for Renewables Tool Improves Electricity Demand Predictions to Make More Room for Renewables October 3, 2011 -...

498

SHORT-RUN MONEY DEMAND Laurence Ball  

E-Print Network (OSTI)

SHORT-RUN MONEY DEMAND Laurence Ball Johns Hopkins University August 2002 I am grateful with Goldfeld's partial adjustment model. A key innovation is the choice of the interest rate in the money on "near monies" -- close substitutes for M1 such as savings accounts and money market mutual funds

Niebur, Ernst

499

Indianapolis Offers a Lesson on Driving Demand  

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

Successful program managers know that understanding the factors that drive homeowners to make upgrades is critical to the widespread adoption of energy efficiency. What better place to learn about driving demand for upgrades than in Indianapolis, America's most famous driving city?

500

Senior Center Network Redesign Under Demand Uncertainty  

E-Print Network (OSTI)

Senior Center Network Redesign Under Demand Uncertainty Osman Y. ¨Ozaltin Department of Industrial of Massachusetts Boston, Boston, MA 02125-3393, USA, michael.johnson@umb.edu Andrew J. Schaefer Department. In response, we propose a two-echelon network of senior centers. We for- mulate a two-stage stochastic

Schaefer, Andrew