Powered by Deep Web Technologies
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

ANN-based residential water end-use demand forecasting model  

Science Conference Proceedings (OSTI)

Bottom-up urban water demand forecasting based on empirical data for individual water end uses or micro-components (e.g., toilet, shower, etc.) for different households of varying characteristics is undoubtedly superior to top-down estimates originating ... Keywords: Artificial neural network, Residential water demand forecasting, Water demand management, Water end use, Water micro-component

Christopher Bennett; Rodney A. Stewart; Cara D. Beal

2013-03-01T23:59:59.000Z

3

India Energy Outlook: End Use Demand in India to 2020  

SciTech Connect

Integrated economic models have been used to project both baseline and mitigation greenhouse gas emissions scenarios at the country and the global level. Results of these scenarios are typically presented at the sectoral level such as industry, transport, and buildings without further disaggregation. Recently, a keen interest has emerged on constructing bottom up scenarios where technical energy saving potentials can be displayed in detail (IEA, 2006b; IPCC, 2007; McKinsey, 2007). Analysts interested in particular technologies and policies, require detailed information to understand specific mitigation options in relation to business-as-usual trends. However, the limit of information available for developing countries often poses a problem. In this report, we have focus on analyzing energy use in India in greater detail. Results shown for the residential and transport sectors are taken from a previous report (de la Rue du Can, 2008). A complete picture of energy use with disaggregated levels is drawn to understand how energy is used in India and to offer the possibility to put in perspective the different sources of end use energy consumption. For each sector, drivers of energy and technology are indentified. Trends are then analyzed and used to project future growth. Results of this report provide valuable inputs to the elaboration of realistic energy efficiency scenarios.

de la Rue du Can, Stephane; McNeil, Michael; Sathaye, Jayant

2009-03-30T23:59:59.000Z

4

2012 End-Use Energy Efficiency and Demand Response, EPRI Program 170: Summary of Deliverables  

Science Conference Proceedings (OSTI)

The EPRI research program on End-Use Energy Efficiency and Demand Response (Program 170) is focused on the assessment, testing, and demonstration of energy-efficient and intelligent end-use devices, as well as analytical studies of the economic, environmental, and behavioral aspects of energy efficiency and demand response. The 2012 reports, tools and resources produced in this program are available to employees of funding companies, and can be accessed by clicking on the product number link listed after ..

2013-05-22T23:59:59.000Z

5

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

6

Evaluation of consumer demand for selected end-use markets for cotton  

E-Print Network (OSTI)

The U.S. cotton industry is facing a rapidly diminishing share of the domestic and foreign textile markets. To become more competitive in these markets, the textile industry should know where consumer demand is being directed. The objectives of this study were to quantitatively examine the demand for cotton in twelve selected end-uses from 1973 to 1997. Four structural models were developed to explain demand, two of which were built using the results from directed graphs. Changes in fashion and governmental policy were also assessed during this time period. Economic theory and prior literature suggested that the following factors influence demand at the end-use level: Disposable Personal Income, the Consumer Price Index for Apparel and Upkeep, cotton fiber prices lagged one year, polyester fiber prices lagged one year, and population segmented by age and gender. Regression results indicate that the Consumer Price Index, the lagged polyester prices, and the population variables most significantly contribute to the demand for cotton. A negative polyester coefficient was associated in all cases of significance, characterizing cotton and polyester fiber as complements in end-uses. Out-of-sample forecasts were generated for the years 1993 to 1997, and then evaluated using the Theil's U statistic, the Root Mean Square Error, and the Mean Absolute Percentage Error. The forecasts from the full models, those with all variables, outperformed the directed graph models in terms of predictive power. Differences in significant variables and variability in forecasting accuracy among the different end-uses suggests that there is an inherent difficulty in modeling the demand for a fiber in its end-use. A common saying in the fashion industry is that "the only constant is change." A constantly changing industry thus presents difficulty in quantifying, modeling, and forecasting.

Viator, Catherine Longman

2000-01-01T23:59:59.000Z

7

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

8

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

9

Demand Response-Ready End-Use Devices: Guiding Principles for Defining Criteria to Support Grid Needs  

Science Conference Proceedings (OSTI)

This report describes technology capabilities that support more automated and ubiquitous demand response. It reviews the Demand Response–Ready (DR-Ready) concept and related industry activities that support realization of the concept. In the DR-Ready vision, consumers receive DR-Ready end-use products at the point of purchase, thus eliminating the need for utility truck service visits to retrofit equipment, and thereby significantly reducing the cost of deploying DR-enabling ...

2013-12-21T23:59:59.000Z

10

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

11

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

12

Energy Demand: Limits on the Response to Higher Energy Prices in the End-Use Sectors (released in AEO2007)  

Reports and Publications (EIA)

Energy consumption in the end-use demand sectorsresidential, commercial, industrial, and transportationgenerally shows only limited change when energy prices increase. Several factors that limit the sensitivity of end-use energy demand to price signals are common across the end-use sectors. For example, because energy generally is consumed in long-lived capital equipment, short-run consumer responses to changes in energy prices are limited to reductions in the use of energy services or, in a few cases, fuel switching; and because energy services affect such critical lifestyle areas as personal comfort, medical services, and travel, end-use consumers often are willing to absorb price increases rather than cut back on energy use, especially when they are uncertain whether price increases will be long-lasting. Manufacturers, on the other hand, often are able to pass along higher energy costs, especially in cases where energy inputs are a relatively minor component of production costs. In economic terms, short-run energy demand typically is inelastic, and long-run energy demand is less inelastic or moderately elastic at best.

Information Center

2007-03-11T23:59:59.000Z

13

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

DOE Green Energy (OSTI)

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

14

Measured electric hot water standby and demand loads from Pacific Northwest homes. End-Use Load and Consumer Assessment Program  

SciTech Connect

The Bonneville Power Administration began the End-Use Load and Consumer Assessment Program (ELCAP) in 1983 to obtain metered hourly end-use consumption data for a large sample of new and existing residential and commercial buildings in the Pacific Northwest. Loads and load shapes from the first 3 years of data fro each of several ELCAP residential studies representing various segments of the housing population have been summarized by Pratt et al. The analysis reported here uses the ELCAP data to investigate in much greater detail the relationship of key occupant and tank characteristics to the consumption of electricity for water heating. The hourly data collected provides opportunities to understand electricity consumption for heating water and to examine assumptions about water heating that are critical to load forecasting and conservation resource assessments. Specific objectives of this analysis are to: (A) determine the current baseline for standby heat losses by determining the standby heat loss of each hot water tank in the sample, (B) examine key assumptions affecting standby heat losses such as hot water temperatures and tank sizes and locations, (C) estimate, where possible, impacts on standby heat losses by conservation measures such as insulating tank wraps, pipe wraps, anticonvection valves or traps, and insulating bottom boards, (D) estimate the EF-factors used by the federal efficiency standards and the nominal R-values of the tanks in the sample, (E) develop estimates of demand for hot water for each home in the sample by subtracting the standby load from the total hot water load, (F) examine the relationship between the ages and number of occupants and the hot water demand, (G) place the standby and demand components of water heating electricity consumption in perspective with the total hot water load and load shape.

Pratt, R.G.; Ross, B.A.

1991-11-01T23:59:59.000Z

15

Engineering Methods for Estimating the Impacts of Demand-Side Management Programs: Volume 1: Fundamentals of Engineering Simulations for Residential and Commercial End Uses  

Science Conference Proceedings (OSTI)

This handbook focuses on the use of building energy computer simulations for planning and evaluating demand-side management (DSM) measures. It presents techniques for estimating energy and demand savings for a list of common residential and commercial DSM technologies using widely available public-domain and EPRI computer programs.

1992-08-01T23:59:59.000Z

16

" 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"

17

" 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"

18

" 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)"

19

" 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

20

" 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)"

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

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)"

22

" 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"

23

" 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"

24

" 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"

25

" 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"

26

" 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"

27

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

28

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.

29

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 energy management programs oriented toward end-use applications. The focus of the program is on five major types of commercial buildings: offices, grocery stores, restaurants, retail stores, and warehouses. End-use metering equipment is installed at about 50 buildings, distributed among these five types. The buildings selected have average demands of 100 to 300 kW. The metered end-uses vary among building types and include HVAC, lighting, refrigeration. plug loads, and cooking. Procedures have been custom-designed to facilitate collection and validation of the end-use load data. For example, the Load Profile Viewer is a PC-based software program for reviewing and validating the end-use load data.

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

1988-01-01T23:59:59.000Z

30

Monitoring of electrical end-use loads in commercial buildings  

Science Conference Proceedings (OSTI)

A California utility 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 energy management programs oriented toward end-use applications. The focus of the program is on five major types of commercial buildings: offices, grocery stores, restaurants, retail stores, and warehouses. End-use metering equipment is installed at about 50 buildings selected have average demands of 100kW to 300 kW. The metered end-uses vary among building types and include HVAC, lighting, refrigeration, plug loads, and cooking. Procedures have been custom-designed to facilitate collection and validation of the end-use load data. PC-based software programs have been developed for reviewing and validating the end-sue load data and for generating reports.

Martinez, M. (Southern California Edison, CA (US)); Alereza, T.; Mort, D. (ADM Associates, Sacramento, CA (US))

1989-01-01T23:59:59.000Z

31

California Independent System Operator demand response & proxy demand resources  

Science Conference Proceedings (OSTI)

Demand response programs are designed to allow end use customers to contribute to energy load reduction individually or through a demand response provider. One form of demand response can occur when an end use customer reduces their electrical usage ...

John Goodin

2012-01-01T23:59:59.000Z

32

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

33

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

34

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

Price, 2008 “Sectoral Trends in Global Energy Use and Greenhouse GasTrends in Global Energy Use and Greenhouse Gas Emissions (Price

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)

share (71%) from coal, hydro power represents 14%, naturalgenerated from hydro or nuclear power plants is set equal to

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)

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

37

Kyoto - End-Use Energy Demand (Residential & Commercial)  

U.S. Energy Information Administration (EIA)

... the convenience of natural gas heating and the decline in real oil and gas prices over the past decade have led many ... (compact fluorescent ...

38

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

factor: first electricity distribution and transmission (Transmission and distribution losses Electricity deliveredTransmission and distribution loses Electricity delivered

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

39

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

MOSPI, 2008, a). quantities of fuel oil and diesel oil usequantity of transport activities (railways mostly). Oil is

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

40

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

and equity”, 2005, the Energy and Resources Institute (Tables Figures Figure 1. India Primary Energy Supply by fuel7 Figure 2. Final and Primary Energy (including biomass) by

de la Rue du Can, Stephane

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.


41

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

water (3%). Finally oil is a source of energy for theOil Diesel Oil LPG Electricity Source: CEA, 2006; MOSPI,countries, oil remains an important source of energy for

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

42

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

Commercial Building Energy Consumption Survey” (CBECS),7 Figure 3. Energy Consumption in the Agriculture Sector (13 Figure 6. Energy Consumption in the Service

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

43

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

kerosene Coal INDUSTRY electricity Coal oil gas COMMERCIALkerosene Coal INDUSTRY electricity Coal oil gas COMMERCIALin the industry sector and primary electricity represents

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

44

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

Past Trend and Future Outlook",LBNL forthcoming. de la Rue2006. “Building up India: Outlook for India’s real estate”,2006a. “World Energy Outlook”, IEA/OECD, Paris, France.

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

45

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

trends in the iron and steel industry” Energy Policy 30 (user is the iron and steel industry representing almost halfTable 9). The Indian steel industry is slowly shifting from

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

46

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

gas oil nuclear hydro Energy output Own Uses Transmissiongas oil nuclear hydro Energy output Own Uses Transmissionenergy equivalence of electricity generated from hydro or

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

47

CONSULTANT REPORT DEMAND FORECAST EXPERT  

E-Print Network (OSTI)

CONSULTANT REPORT DEMAND FORECAST EXPERT PANEL INITIAL forecast, end-use demand modeling, econometric modeling, hybrid demand modeling, energyMahon, Carl Linvill 2012. Demand Forecast Expert Panel Initial Assessment. California Energy

48

End-Use Load-Shape Estimation: Methods and Validation  

Science Conference Proceedings (OSTI)

In developing effective demand-side management plans and load forecasts, utilities need information on customer hourly load patterns over a range of end-uses. Such information may be obtained using the two methods described in this report for disaggregating whole-building load data. Both methods have been validated using end-use metered data. This report is available only to funders of Program 101A or 101.001. Funders may download this report at http://my.primen.com/Applications/DE/Community/index.asp .

1991-02-01T23:59:59.000Z

49

End-use taxes: Current EIA practices  

Science Conference Proceedings (OSTI)

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

50

,"Texas Natural Gas Consumption by End Use"  

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

,"Workbook Contents" ,"Texas Natural Gas Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest...

51

,"Idaho Natural Gas Consumption by End Use"  

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

,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Idaho Natural Gas Consumption by End Use",6,"Monthly","102013","1151989" ,"Release...

52

,"California Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","California Natural...

53

,"Tennessee Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Tennessee Natural...

54

,"Colorado Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural...

55

,"Washington Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Washington Natural...

56

,"Virginia Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Virginia Natural...

57

,"Nebraska Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Nebraska Natural...

58

,"Pennsylvania Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania...

59

,"Arkansas Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Arkansas Natural...

60

,"Kentucky Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural...

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

,"Mississippi Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Mississippi Natural...

62

,"Michigan Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural...

63

,"Delaware Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Delaware Natural...

64

,"Maryland Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Maryland Natural...

65

,"Louisiana Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural...

66

,"Missouri Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Missouri Natural...

67

,"Oklahoma Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural...

68

,"Idaho Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Idaho Natural Gas...

69

,"Wyoming Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas...

70

,"Alaska Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Alaska Natural Gas...

71

,"Oregon Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Oregon Natural Gas...

72

,"Alabama Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Alabama Natural Gas...

73

,"Florida Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas...

74

,"Arizona Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Arizona Natural Gas...

75

,"Kansas Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas...

76

,"Montana Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas...

77

,"Nevada Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Nevada Natural Gas...

78

,"Utah Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas...

79

,"Indiana Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Indiana Natural Gas...

80

,"Texas Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas...

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

,"Ohio Natural Gas Consumption by End Use"  

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

Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Ohio Natural Gas...

82

End-Use Taxes: Current EIA Practices  

Reports and Publications (EIA)

Addresses the Energy Information Administration's (EIA) current practices in treating taxes in the calculation of end use prices in the State Energy Price and Expenditure Report 1990 (SEPER), and other EIA data publications.

Information Center

1994-08-01T23:59:59.000Z

83

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.

84

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

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

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...

85

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

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

","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...

86

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.

1994-09-01T23:59:59.000Z

87

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)

88

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,

89

Biomass Resource Allocation among Competing End Uses  

DOE Green Energy (OSTI)

The Biomass Scenario Model (BSM) is a system dynamics model developed by the U.S. Department of Energy as a tool to better understand the interaction of complex policies and their potential effects on the biofuels industry in the United States. However, it does not currently have the capability to account for allocation of biomass resources among the various end uses, which limits its utilization in analysis of policies that target biomass uses outside the biofuels industry. This report provides a more holistic understanding of the dynamics surrounding the allocation of biomass among uses that include traditional use, wood pellet exports, bio-based products and bioproducts, biopower, and biofuels by (1) highlighting the methods used in existing models' treatments of competition for biomass resources; (2) identifying coverage and gaps in industry data regarding the competing end uses; and (3) exploring options for developing models of biomass allocation that could be integrated with the BSM to actively exchange and incorporate relevant information.

Newes, E.; Bush, B.; Inman, D.; Lin, Y.; Mai, T.; Martinez, A.; Mulcahy, D.; Short, W.; Simpkins, T.; Uriarte, C.; Peck, C.

2012-05-01T23:59:59.000Z

90

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,...

91

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.)...

92

Energy End-Use Intensities in Commercial Buildings 1989  

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

9 Energy End-Use Intensities 1989 Energy End-Use Intensities Overview Full Report Tables National estimates and analysis of energy consumption by fuel (electricity, natural gas,...

93

An intelligent pattern recognition model to automate the categorisation of residential water end-use events  

Science Conference Proceedings (OSTI)

The rapid dissemination of residential water end-use (e.g. shower, clothes washer, etc.) consumption data to the customer via a web-enabled portal interface is becoming feasible through the advent of high resolution smart metering technologies. However, ... Keywords: Dynamic time warping algorithm, Gradient vector filtering, Hidden Markov model, Residential water flow trace disaggregation, Water demand management, Water end-use event, Water micro-component

K. A. Nguyen, R. A. Stewart, H. Zhang

2013-09-01T23:59:59.000Z

94

Survey of End-Use Metering Equipment, Sensors, and Designers/Installers  

Science Conference Proceedings (OSTI)

End-use data metering technology has come of age in the last several years, with many new specialized products becoming available. This report represents the first survey of end-use metering and monitoring equipment and of sensors typically used with such equipment. It also surveys organizations that provide design and/or installation services for demand-side management metering and monitoring systems.

1992-10-01T23:59:59.000Z

95

Realizing Building End-Use Efficiency with Ermerging Technologies  

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

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

96

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

residential electricity consumption, the flattening of the demand curves (except Maximum demand) reflects decreasing population growth ratesresidential electricity demand are described in Table 11. For simplicity, end use-specific UEC and saturation rates

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

2008-01-01T23:59:59.000Z

97

Commercial equipment loads: End-Use Load and Consumer Assessment Program (ELCAP)  

SciTech Connect

The Office of Energy Resources of the Bonneville Power Administration is generally responsible for the agency's power and conservation resource planning. As associated responsibility which supports a variety of office functions is the analysis of historical trends in and determinants of energy consumption. The Office of Energy Resources' End-Use Research Section operates a comprehensive data collection program to provide pertinent information to support demand-side planning, load forecasting, and demand-side program development and delivery. Part of this on-going program is known as the End-Use Load and Consumer Assessment Program (ELCAP), an effort designed to collect electricity usage data through direct monitoring of end-use loads in buildings. This program is conducted for Bonneville by the Pacific Northwest Laboratory. This report provides detailed information on electricity consumption of miscellaneous equipment from the commercial portion of ELCAP. Miscellaneous equipment includes all commercial end-uses except heating, ventilating, air conditioning, and central lighting systems. Some examples of end-uses covered in this report are office equipment, computers, task lighting, refrigeration, and food preparation. Electricity consumption estimates, in kilowatt-hours per square food per year, are provided for each end-use by building type. The following types of buildings are covered: office, retail, restaurant, grocery, warehouse, school, university, and hotel/motel. 6 refs., 35 figs., 12 tabs.

Pratt, R.G.; Williamson, M.A.; Richman, E.E.; Miller, N.E.

1990-07-01T23:59:59.000Z

98

GridLAB-D Technical Support Document: Residential End-Use Module Version 1.0  

SciTech Connect

1.0 Introduction The residential module implements the following end uses and characteristics to simulate the power demand in a single family home: • Water heater • Lights • Dishwasher • Range • Microwave • Refrigerator • Internal gains (plug loads) • House (heating/cooling loads) The house model considers the following four major heat gains/losses that contribute to the building heating/cooling load: 1. Conduction through exterior walls, roof and fenestration (based on envelope UA) 2. Air infiltration (based on specified air change rate) 3. Solar radiation (based on CLTD model and using tmy data) 4. Internal gains from lighting, people, equipment and other end use objects. The Equivalent Thermal Parameter (ETP) approach is used to model the residential loads and energy consumption. The following sections describe the modeling assumptions for each of the above end uses and the details of power demand calculations in the residential module.

Taylor, Zachary T.; Gowri, Krishnan; Katipamula, Srinivas

2008-07-31T23:59:59.000Z

99

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

100

" 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"

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 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"

102

" 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"

103

" 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"

104

" 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"

105

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

106

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.

107

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

108

" 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"

109

" 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)"

110

" 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)"

111

Solid-State Lighting: Residential Lighting End-Use Consumption  

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

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

112

Energy End-Use Intensities in Commercial Buildings  

U.S. Energy Information Administration (EIA)

DOE/EIA-0555(94)/2 Distribution Category UC-950 Energy Consumption Series Energy End-Use Intensities in Commercial Buildings September 1994 Energy Information ...

113

Figure 60. Energy intensity of selected commercial end uses ...  

U.S. Energy Information Administration (EIA)

Refrigeration Lighting Heating, cooling, and ventilation Other 2040.00 2011.00 ... Energy intensity of selected commercial end uses, 2011 and 2040 ...

114

Table H2: Fuels and End Uses in Large Hospitals  

U.S. Energy Information Administration (EIA)

District Chilled Water ..... Propane ..... Space-Heating ... Cooling Energy Sources Water-Heating Energy Sources Cooking Energy Sources Energy End Uses (more than

115

Energy End-Use Intensities in Commercial Buildings  

Annual Energy Outlook 2012 (EIA)

2 Distribution Category UC-950 Energy Consumption Series Energy End-Use Intensities in Commercial Buildings September 1994 Energy Information Administration Office of Energy...

116

,"New Mexico 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 Mexico Natural Gas Consumption by End Use",11,"Annual",2012,"6301967" ,"Release Date:","10...

117

Automated Demand Response Tests  

Science Conference Proceedings (OSTI)

This report includes assessments and test results of four end-use technologies, representing products in the residential, commercial, and industrial sectors, each configured to automatically receive real-time pricing information and critical peak pricing (CPP) demand response (DR) event notifications. Four different vendors were asked to follow the interface requirements set forth in the Open Automated Demand Response (OpenADR) standard that was introduced to the public in 2008 and currently used in two ...

2008-12-22T23:59:59.000Z

118

Automated Demand Response Tests  

Science Conference Proceedings (OSTI)

This report, which is an update to EPRI Report 1016082, includes assessments and test results of four end-use vendor technologies. These technologies represent products in the residential, commercial, and industrial sectors, each configured to automatically receive real-time pricing information and critical peak pricing (CPP) demand response (DR) event notifications. Four different vendors were asked to follow the interface requirements set forth in the Open Automated Demand Response (OpenADR) Communicat...

2009-03-30T23:59:59.000Z

119

Demand Response - Policy | Department of Energy  

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

over the last 11 years when interest in demand response increased. Demand response is an electricity tariff or program established to motivate changes in electric use by end-use...

120

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

E-Print Network (OSTI)

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

Letschert, Virginie

2010-01-01T23:59:59.000Z

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

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

122

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

123

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

124

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

125

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

126

Table 5.3 End Uses of Fuel Consumption, 2010;  

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

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...

127

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

128

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

129

A Study of Achievable Potential for Transmission and Disitribution Loss Reduction and End-Use Energy Efficiency for Eskom  

Science Conference Proceedings (OSTI)

This report documents the results of a study undertaken to assess the "end-to-end" achievable efficiency potential for Eskom’s electrical system. The assessment includes potential energy and demand savings estimates due to transmission and distribution loss reduction measures and implementation of end-use energy-efficiency measures over the period of 20122030.

2012-08-14T23:59:59.000Z

130

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

131

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

132

End-use matching of solar energy systems  

SciTech Connect

The choice among available energy sources for a given task requires technical and economic tradeoffs on the part of the individual investor. From the national perspective, however, the effectiveness with which available energy sources are utilized may well become an overriding consideration. End-use matching is a procedure for introducing solar energy into the national energy infrastructure. The result of end-use matching is an identification of the most cost-effective combination of process energy needs, solar collector technology, geographic location, and economics by matching currently available solar system hardware with particular industrial processes and their locations. End-use matching is not intended to be a design tool for a specific plant, but rather a planning tool for determining where and for what general applications solar systems appear economically viable in the near- to immediate-term. This paper discusses the end-use matching methodology and illustrates first and second law thermodynamics analyses applied to a solar system producing process steam.

Kreith, F.; Kearney, D.; Bejan, A.

1979-01-01T23:59:59.000Z

133

,"U.S. Natural Gas Consumption by End Use"  

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

,,"(202) 586-8800",,,"10312013 3:05:49 PM" "Back to Contents","Data 1: U.S. Natural Gas Consumption by End Use" "Sourcekey","N9140US2","N9160US2","NA1840NUS2","NA18...

134

,"U.S. Natural Gas Consumption by End Use"  

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

,,"(202) 586-8800",,,"10312013 3:05:50 PM" "Back to Contents","Data 1: U.S. Natural Gas Consumption by End Use" "Sourcekey","N9140US2","N9160US2","N9170US2","N3060US2...

135

Refining and End Use Study of Coal Liquids  

SciTech Connect

This report summarizes revisions to the design basis for the linear programing refining model that is being used in the Refining and End Use Study of Coal Liquids. This revision primarily reflects the addition of data for the upgrading of direct coal liquids.

None

1997-10-01T23:59:59.000Z

136

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

137

Demand Response  

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

Peak load diagram Demand Response Demand Response (DR) is a set of time-dependent activities that reduce or shift electricity use to improve electric grid reliability, manage...

138

Demand Response  

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

Peak load diagram Demand Response Demand response (DR) is a set of time-dependent activities that reduce or shift electricity use to improve electric grid reliability, manage...

139

Ris Energy Report 4 Interaction between supply and end-use 4 8 Interaction between supply and end-use  

E-Print Network (OSTI)

Risø Energy Report 4 Interaction between supply and end-use 4 8 Interaction between supply and end vary, so we need to find a pricing mechanism that is broadly applicable. The issue of short-term supply balance take place. DR and the security of supply problem thus take different forms depending

140

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, dilution, a reaction ingredient, etc. These classifications are termed 'Btu' loads or 'Pound' loads. Some final end uses of steam are actually a combination of the two. The classification of steam loads is extremely important to the overall economics of the industrial plant steam system. These economic effects are explained in detail as they impact on both the thermal efficiency and the heat power cycle efficiency of an industrial system. The use of a powerful steam system mass and energy modeling program called MESA (Modular Energy System Analyzer, The MESA Company) in identifying and accurately evaluating these effects is described.

Waterland, A. F.

1983-01-01T23:59:59.000Z

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.


141

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

142

Flywheel Energy Storage for End-Use Power  

Science Conference Proceedings (OSTI)

Power quality represents both a challenge and an opportunity for utilities to provide quality and service to their customers. Flywheel systems are becoming commercially available for solving short-term power quality problems, specifically voltage sags and momentary interruptions, and a variety of products appears particularly attractive for this market. This report provides information on the subject of flywheel energy storage systems to utility personnel responsible for end-use power quality.

1998-12-15T23:59:59.000Z

143

REFINING AND END USE STUDY OF COAL LIQUIDS  

DOE Green Energy (OSTI)

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

144

Energy End-Use Technologies for the 21st Century  

SciTech Connect

The World Energy Council's recent study examined the potential of energy end-use technologies and of research, development, and demonstration (RD&D) into these technologies on a global scale. Surprises are likely, but nevertheless, current research and development offer a picture of what might happen in the future as new technologies face the competition of the marketplace. Given the breadth of energy end-use technologies and the differences between regions and economic conditions, the study focused on technologies that appear most important from today's vantage point. Globally, robust research and development followed by demonstrations of new end-use technologies can potentially save at least 110 EJ/year by 2020 and over 300 EJ/year by 2050. If achieved, this translates to worldwide energy savings of as much as 25% by 2020 and over 40% by 2050, over what may be required without these technologies. It is almost certain that no single technology, or even a small set of technologies, will dominate in meeting the needs of the globe in any foreseeable timeframe. Absent a significant joint government-industry effort on end-use technology RD&D, the technologies needed will not be ready for the marketplace in the timeframes required with even the most pessimistic scenarios. Based on previous detailed analyses for the United States, an international expenditure of $4 billion per year seems more than justified. The success of new energy end-use technologies depends on new RD&D investments and policy decisions made today. Governments, in close cooperation with industry, must carefully consider RD&D incentives that can help get technologies from the laboratory or test-bed to market. Any short-term impact areas are likely to benefit from focused RD&D. These include electricity transmission and distribution, distributed electricity production, transportation, the production of paper and pulp, iron and steel, aluminum, cement and chemicals, and information and communication technologies. For long-term impact, significant areas include fuel cells, hydrogen fuel, and integrated multi-task energy systems.

Gehl, S; Haegermark, H; Larsen, H; Morishita, M; Nakicenovic, N; Schock, R N; Suntola, T

2005-04-13T23:59:59.000Z

145

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.

146

Addressing Energy Demand through Demand Response: International...  

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

Addressing Energy Demand through Demand Response: International Experiences and Practices Title Addressing Energy Demand through Demand Response: International Experiences and...

147

Addressing Energy Demand through Demand Response: International...  

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

Energy Demand through Demand Response: International Experiences and Practices Title Addressing Energy Demand through Demand Response: International Experiences and Practices...

148

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.

149

Open Automated Demand Response for Small Commerical Buildings  

E-Print Network (OSTI)

of the small commercial peak demand.  The majority of the less than 200 kW of peak demand, make up 20?25% of  peak the small commercial  peak demand.  A ten percent reduction 

Dudley, June Han

2009-01-01T23:59:59.000Z

150

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

E-Print Network (OSTI)

5-5. 1993 Electricity Consumption Estimates by End Use forft ) 1993 Electricity Consumption Estimates by End Use forTotal) 1993 Electricity Consumption Estimates by End Use for

Konopacki, S.J.

2010-01-01T23:59:59.000Z

151

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)

152

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

153

End use energy consumption data base: transportation sector  

SciTech Connect

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

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

1980-02-01T23:59:59.000Z

154

Residential end-use energy planning system (REEPS). Final report  

Science Conference Proceedings (OSTI)

The Residential End-Use Energy Planning System (REEPS) is described. REEPS is a forecasting model of residential energy patterns that is capable of evaluating the impacts of a broad range of energy conservation measures. REEPS forecasts appliance installations, operating efficiencies, and utilization patterns for space heating, water heating, air conditioning, and cooking. Each of these decisions is sensitive to energy prices, mandatory policies, and household/dwelling and geographical characteristics. The parameters of these choice models have been estimated statistically from national household survey data. The structure of the choice models and the results of the statistical analysis are reported in detail. REEPS forecasts energy choices for a large number of market segments representing households with different socioeconomic, dwelling, and geographical characteristics. These segments reflect the joint distribution of characteristics in the population. Aggregate forecasts are generated by summing up the decisions for all population segments. This technique provides a consistent method of obtaining aggregate forecasts from disaggregate, nonlinear choice models. Moreover, it permits evaluation of the distributional impacts of prospective conservation policies. The results of simulation of REEPS are described. REEPS forecasts a moderate rise in electricity consumption per household and significant drops in other fuels. These are caused in part by high market penetrations of electric appliances which themselves reflect major shifts in relative energy prices.

Goett, A.; McFadden, D.

1982-07-01T23:59:59.000Z

155

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

156

Computerized data collection for end-use experiments  

SciTech Connect

The author presents a general overview of the use of microprocessors and computers in the collection of data for energy-usage test programs for electric utility research in demand-side management. Southern California Edison has several experiments designed to measure the energy usage of various equipment and appliances in customers' homes and businesses. These projects consist primarily of two types. Some are designed to provide statistically meaningful information on the use of real, commercially available equipment by real customers. Others are designed to study equipment in various phases of development in order to analyze its potential application to energy management. From a data collection standpoint, these projects are very similar. Energy-usage data are collected over relatively short periods (five or fifteen minutes) and stored in a local microprocessor. Other pertinent information such as temperature, humidity, or flow rates may also be collected. The stored data are then routinely transmitted to a central computers.

Shirilau, M.S.

1988-01-01T23:59:59.000Z

157

REFINING AND END USE STUDY OF COAL LIQUIDS  

Science Conference Proceedings (OSTI)

Two direct coal liquids were evaluated by linear programming analysis to determine their value as petroleum refinery feedstock. The first liquid, DL1, was produced from bitiuminous coal using the Hydrocarbon Technologies, Inc.(HTI) two-stage hydrogenation process in Proof of Concept Run No.1, POC-1. The second liquid, DL2,was produced from sub-bituminous coal using a three-stage HTI process in Proof of Concept Run No. 2, POC-2; the third stage being a severe hydrogenation process. A linear programming (LP) model was developed which simulates a generic 150,000 barrel per day refinery in the Midwest U.S. Data from upgrading tests conducted on the coal liquids and related petroleum fractions in the pilot plant testing phase of the Refining and End Use Study was inputed into the model. The coal liquids were compared against a generic petroleum crude feedstock. under two scenarios. In the first scenario, it was assumed that the refinery capacity and product slate/volumes were fixed. The coal liquids would be used to replace a portion of the generic crude. The LP results showed that the DL1 material had essentially the same value as the generic crude. Due to its higher quality, the DL2 material had a value of approximately 0.60 $/barrel higher than the petroleum crude. In the second scenario, it was assumed that a market opportunity exists to increase production by one-third. This requires a refinery expansion. The feedstock for this scenario could be either 100% petroleum crude or a combination of petroleum crude and the direct coal liquids. Linear programming analysis showed that the capital cost of the refinery expansion was significantly less when coal liquids are utilized. In addition, the pilot plant testing showed that both of the direct coal liquids demonstrated superior catalytic cracking and naphtha reforming yields. Depending on the coal liquid flow rate, the value of the DL1 material was 2.5-4.0 $/barrel greater than the base petroleum crude, while the DL2 material was 3.0-4.0 /barrel higher than the crude. Co-processing the coal liquids with lower quality, less expensive petroleum crudes that have higher sulfur, resid and metals contents was also examined. The coal liquids have higher values under this scenario, but the values are dependent on the prices of the alternative crudes.

NONE

1998-08-12T23:59:59.000Z

158

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

SciTech Connect

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

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

1995-12-01T23:59:59.000Z

159

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.

160

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

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

Analysis of PG&E's Residential End-Use Metered Data to Improve Electricity Demand Forecasts -Final Report  

E-Print Network (OSTI)

of Energy Management Division of the U. S. Department of Energy under Contract No. DE-AC03-76SFOOO9S. #12) and by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Utility Teclmologies. Office

162

" 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)"

163

" 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"

164

" 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)"

165

" 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"

166

2008-2010 Research Summary: Analysis of Demand Response Opportunities in California Industry  

E-Print Network (OSTI)

energy usage ..for bulk of the end-use energy usage), and by reducing theet al. 2010b). The energy usage and demand of key equipment

Goli, Sasank

2013-01-01T23:59:59.000Z

167

Estimating Demand Response Market Potential Among Large Commercial and Industrial Customers: A Scoping Study  

E-Print Network (OSTI)

response as: changes in electric usage by end-use customerselectric competition Typical rate design includes demand and/or volumetric distribution charges, with all commodity usage

Goldman, Charles; Hopper, Nicole; Bharvirkar, Ranjit; Neenan, Bernie; Cappers, Peter

2007-01-01T23:59:59.000Z

168

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

DOE Green Energy (OSTI)

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

169

Survey-guided load research: An end-use analysis methodology test  

SciTech Connect

Energy use by end-use equipment is a function of the rated capacity of the equipment, frequency of use, and duration of each use. Many end used include multiple states, each with a different capacity, frequency, and duration. Some equipment provides benefits that are related to other uses, resulting in an indirect linkage between the primary energy-using equipment and the end use. Water heaters are one example. End-use metering of energy-using equipment provides the most accurate measure of energy use. Nevertheless, this energy-use ``signal`` is buried in background ``noise`` due to variations in the capacity, frequency, and duration of each end use and end user. Reliable estimates of energy use depend on a variety of methods to increase the ``signal-to-noise`` ratio (i.e., reduce the variance). Research of the energy consumption of household end-uses contains some inherent sampling problems: intrusiveness, cost, extensive data generated, analyses are time and computationally intensive. The goal of the methodology test described in this paper was to address these problems through a method that focused end-use analyses on a limited set of issues and data for program evaluation purposes. The approach tested used a detailed survey of end-use metered subjects to identify the pattern of end-use behavior as an alternative to estimating the frequency and duration of each use from the end-use data itself.

Warwick, W.M.

1993-08-01T23:59:59.000Z

170

Proceedings: 1987 Annual Review of Demand-Side Planning Research  

Science Conference Proceedings (OSTI)

Recent EPRI research in demand-side planning (DSP) has focused on forecasting, end-use technology assessment, demand-side management (DSM), and innovative pricing. These 23 papers discuss vital DSP research, including customer response to interruptible rates, personal computer forecasting tools, integrated value-based planning, customer preference and behavior studies, and a database of end-use load shapes and DSM impacts.

None

1988-08-01T23:59:59.000Z

171

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.

172

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

173

Hot Water Electric Energy Use in Single-Family Residences in the Pacific Northwest : Regional End-Use Metering Project (REMP).  

SciTech Connect

The Office of Energy Resources of the Bonneville Power Administration carriers out generation and conservation resource planning. The analysis of historical trends in and determinants of energy consumption is carried out by the office's End-Use Research Section. The End-Use Research Section operates a comprehensive data collection program to provide pertinent information to support demand-side conservation planning, load forecasting, and conservation program development and delivery. Part of this on-going program, commonly known as the End-Use Load and Consumer Assessment Program (ELCAP), was recently renamed the Regional End-Use Metering Project (REMP) to reflect an emphasis on metering rather than analytical activities. REMP is designed to collect electricity usage data through direct monitoring of end-use loads in buildings in the residential and commercial sectors and is conducted for Bonneville by Pacific Northwest Laboratories (Battelle). The detailed summary information in this report is on energy used for water heaters in the residential sector and is based on data collected from September 1985 through December 1990 for 336 of the 499 REMP metered homes. Specific information is provided on annual loads averaged over the years and their variation across residences. Descriptions are given of use as associated with demographic and energy-related characteristics. Summaries are also provided for electricity use by each year, month, and daytype, as well as at peak hot water load and peak system times. This is the second residential report. This report focuses on a specific end use and adds detail to the first report. Subsequent reports are planned on other individual end uses or sets of end uses. 15 refs., 29 figs., 10 tabs.

Taylor, Megan E., Ritland, Keith G., Pratt, R.G.

1991-09-01T23:59:59.000Z

174

" 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)"

175

" 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"

176

" 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"

177

The Potential to Reduce CO2 Emissions by Expanding End-Use Applications of Electricity  

Science Conference Proceedings (OSTI)

Depending on the sources of electricity production, the use of electricity can be a contributing factor to net CO2 emissions. What is less obvious is that using efficient end-use electric technologies has the potential save energy and decrease overall CO2 emissions substantially. The two main mechanisms for saving energy and reducing CO2 emissions with electric end-use technologies are (1) upgrading existing electric technologies, processes, and building energy systems; and (2) expanding end-use applica...

2009-03-30T23:59:59.000Z

178

" 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)"

179

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

180

Table 4. Sales of Distillate Fuel Oil by End Use, 1999 and 2000 ...  

U.S. Energy Information Administration (EIA)

Energy Information Administration 13 Fuel Oil and Kerosene Sales 2000 Table 4. Sales of Distillate Fuel Oil by End Use, 1999 and 2000 (Thousand Gallons)

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

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

U.S. Energy Information Administration (EIA)

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

182

Energy end-use metering in two modular office buildings at Fort Irwin, California  

SciTech Connect

This report documents the application of the Mobile Energy Laboratory (MEL) at Fort Irwin for the period 21 December 1989 to 27 January 1992. The purpose of the test was to monitor electrical demands in Buildings 567 and 571 by end use and to monitor the response of the HVAC systems to internal and external loads. Results of two years of monitoring are summarized below. The observed energy-use intensities (EUIs) were 13.7 kWh/ft{sup 2}-yr for Building 567 and 10.4 kWh/ft{sup 2}-yr for Building 571. The corresponding numbers for HVAC energy were 5.9 and 5.3 kWh/ft{sup 2}-yr. Lighting used about 35%, primary HVAC 40% (heating 8%, cooling 32%), supply fans 3% and other equipment (mostly plug loads) about 20% of the total. Over 10% of the primary HVAC energy used in Building 567 was the result of simultaneous heating and cooling. Six energy conservation measures were evaluated: (1) delamping and retrofit of T-12 fluorescent fixtures with T-8 systems; (2) installation of two-speed fans with operation at the lower speed (67% of rated airflow) during occupied periods whenever a unit is not heating or cooling; (3) retrofit of heat pump compressors with two-speed compressors; (4) installation of controls that eliminate non-productive simultaneous heating and cooling and provide improved night and weekend setback; (5) coating the existing black roof material with a white reflective material; and (6) adding an economizer system to provide outside air cooling. The estimated energy savings as a percent of whole-building energy use are: Lighting HVAC Savings -- 26%; Two-Speed Fans -- 2%; Two-Speed Compressors -- 11%; Improved HVAC Controls -- 5%; White Roof Coating -- 5%; Economizer Cooling -- 5 %. The total energy savings that can be achieved through the measures is 49%.

Armstrong, P.R.; Keller, J.M.

1994-01-01T23:59:59.000Z

183

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

184

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

185

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

Science Conference Proceedings (OSTI)

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

Johnson, M.

1984-12-01T23:59:59.000Z

186

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,

187

Fast Automated Demand Response to Enable the Integration of Renewable Resources  

E-Print Network (OSTI)

peak demand, and natural gas demand forecasts for eachnatural gas and other fossil fuels are the predominant heating fuels for California’s commercial buildings, heating electricity demandDemand. The California End Use Survey 2004 (CEUS 2004) provides statewide hourly electricity and natural gas

Watson, David S.

2013-01-01T23:59:59.000Z

188

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

189

Annual Review of Demand-Side Planning Research: 1985 Proceedings  

Science Conference Proceedings (OSTI)

EPRI's demand-side planning research spans a wide range of utility activities: planning and evaluating demand-side management programs, investigating end-use forecasting techniques, and analyzing the effect of innovative rates. Reflecting efforts to develop utility applications of EPRI research products in 1985, this report focuses on computer models such as REEPS, COMMEND, HELM, and INDEPTH.

None

1987-01-01T23:59:59.000Z

190

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.

191

,"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"

192

Leveraging Limited Data Resources: Developing Commercial End-Use Information: B.C. Hydro Case Study  

Science Conference Proceedings (OSTI)

Using an innovative strategy, EPRI has combined model-based sampling, building total load research data, audits, DOE-2 models, and borrowed end-use data to produce statistically reliable end-use information for the commercial office sector. This project demonstrates that end-use data can be developed in shorter time, at less expense, with more statistically reliable results than conventionally thought. This report is available only to funders of Program 101A or 101.001. Funders may download this report a...

1996-02-07T23:59:59.000Z

193

,"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"

194

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

195

,"U.S. Total 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" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

196

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

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

,,"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...

197

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

198

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

199

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

200

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

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

Program on Technology Innovation: Opportunities for Advancing End-Use Energy Efficiency  

Science Conference Proceedings (OSTI)

This Strategic Science and Technology project identified promising opportunities to develop technologies that improve end-use energy efficiency and gauged interest within the utility industry and other stakeholders in funding research and development initiatives to develop these opportunities.

2005-05-10T23:59:59.000Z

202
203

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

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

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...

204

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

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

,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Total Adjusted Sales of Distillate Fuel Oil by End Use",13,"Annual",2012,"6301984"...

205
206

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.

207

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

208

ENERGY CONSERVATION: POLICY ISSUES AND END-USE SCENARIOS OF SAVINGS POTENTIAL PT.1  

E-Print Network (OSTI)

energy consumption in each sector (e.g. per capita value of industrial shipments, travel demand, rate of increase

Authors, Various

2011-01-01T23:59:59.000Z

209

The effect of efficiency standards on water use and water heating energy use in the US: A detailed end-use treatment  

SciTech Connect

Water heating is an important end-use, accounting for roughly 16% of total primary energy consumption in the US residential sector. Recently enacted efficiency standards on water heaters and hot water-using equipment (e.g., dishwashers, clothes washers, showerheads, and faucets) will substantially affect the energy use of water heaters in the future. Assessment of current and future utility programs and government policies requires that regulators, resource planners, and forecasters understand the effects of these regulations. In order to quantify these impacts, this paper presents a detailed end-use breakdown of household hot and cold water use developed for the US Department of Energy. This breakdown is based on both previous studies and new data and analysis. It is implemented in a spreadsheet forecasting framework, which allows significant flexibility in specifying end-use demands and linkages between water heaters and hot water-using appliances. We disaggregate total hot and cold water use (gallons per day) into their component parts: showers, baths, faucets (flow dominated and volume dominated), toilets, landscaping/other, dishwashers, and clotheswashers. We then use the end-use breakdown and data on equipment characteristics to assess the impacts of current efficiency standards on hot water use and water heater energy consumption.

Koomey, J.G.; Dunham, C.; Lutz, J.D.

1994-05-01T23:59:59.000Z

210

Energy End-Use Patterns in Full-Service Hotels: A Case Study  

SciTech Connect

The U.S. Department of Energy (DOE) recently initiated a program -- Commercial Building Partnerships (CBP) -- to work with private-sector companies in the design of highly-efficient retrofit and new construction projects. Pacific Northwest National Laboratory (PNNL) is conducting a project with a major hotel company to retrofit a full-service, large hotel with the goal of reducing energy consumption by at least 30%. The first step of the project was an intensive metering and monitoring effort aimed at understanding energy end use patterns in the hotel. About 10% of the guest rooms (32), as well as circuits for most of the end uses in public spaces (lighting, elevators, air handlers and other HVAC system components, and various equipment), were equipped with meters. Data are being collected at 1- or 5-minute intervals and downloaded on a monthly basis for analysis. This paper presents results from the first four months of the monitoring effort, which revealed energy end-use consumption patterns, variability of guest room energy use, daily load curves, monthly variations, and other aspects of hotel energy use. Metered end-use data for hotels at this level of detail are not available from any currently-available public sources. This study presents unique information and insight into energy end-use patterns in the lodging sector of commercial buildings and can also serve as a case study of a complex sub-metering project.

Placet, Marylynn; Katipamula, Srinivas; Liu, Bing; Dirks, James A.; Xie, YuLong; Sullivan, Greg; Walent, Jim; Williamson, Rebecca

2010-06-30T23:59:59.000Z

211

Ten Year Site Plans | Department of Energy  

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

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...

212

Residential Sector Demand Module 1998, Model Documentation  

Reports and Publications (EIA)

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

John H. Cymbalsky

1998-01-01T23:59:59.000Z

213

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

214

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

215

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

216

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

217

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

218

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

219

Demand Response Spinning Reserve  

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

Demand Response Spinning Reserve Title Demand Response Spinning Reserve Publication Type Report Year of Publication 2007 Authors Eto, Joseph H., Janine Nelson-Hoffman, Carlos...

220

Transportation Demand This  

Annual Energy Outlook 2012 (EIA)

69 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 Transportation Demand Module The NEMS Transportation Demand Module estimates...

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

Addressing Energy Demand  

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

Addressing Energy Demand through Demand Response: International Experiences and Practices Bo Shen, Girish Ghatikar, Chun Chun Ni, and Junqiao Dudley Environmental Energy...

222

Propane Sector Demand Shares  

U.S. Energy Information Administration (EIA)

... agricultural demand does not impact regional propane markets except when unusually high and late demand for propane for crop drying combines with early cold ...

223

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

E-Print Network (OSTI)

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

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

224

Electricity end-use efficiency: Experience with technologies, markets, and policies throughout the world  

Science Conference Proceedings (OSTI)

In its August meeting in Geneva, the Energy and Industry Subcommittee (EIS) of the Policy Response Panel of the Intergovernmental Panel on Climate Change (IPCC) identified a series of reports to be produced. One of these reports was to be a synthesis of available information on global electricity end-use efficiency, with emphasis on developing nations. The report will be reviewed by the IPCC and approved prior to the UN Conference on Environment and Development (UNCED), Brazil, June 1992. A draft outline for the report was submitted for review at the November 1991 meeting of the EIS. This outline, which was accepted by the EIS, identified three main topics to be addressed in the report: status of available technologies for increasing electricity end-use efficiency; review of factors currently limiting application of end-use efficiency technologies; and review of policies available to increase electricity end-use efficiency. The United States delegation to the EIS agreed to make arrangements for the writing of the report.

Levine, M.D.; Koomey, J.; Price, L. [Lawrence Berkeley Lab., CA (United States); Geller, H.; Nadel, S. [American Council for an Energy-Efficient Economy, Washington, DC (United States)

1992-03-01T23:59:59.000Z

225

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

E-Print Network (OSTI)

energy policy initiatives (EIA 1990). Utilities rely on end-use forecasting models in order to assess market trends

Johnson, F.X.

2010-01-01T23:59:59.000Z

226

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

E-Print Network (OSTI)

LBL-34046 UC-350 Residential Appliance Data, Assumptions and Methodology for End-Use Forecasting. DE-AC03-76SF00098 #12;i ABSTRACT This report details the data, assumptions and methodology for end-use provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which

227

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

228

Demand Response and Open Automated Demand Response Opportunities...  

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

Demand Response and Open Automated Demand Response Opportunities for Data Centers Title Demand Response and Open Automated Demand Response Opportunities for Data Centers...

229

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

of integrating demand response and energy efficiencyand D. Kathan (2009), Demand Response in U.S. ElectricityFRAMEWORKS THAT PROMOTE DEMAND RESPONSE 3.1. Demand Response

Shen, Bo

2013-01-01T23:59:59.000Z

230

Demand Trading: Building Liquidity  

Science Conference Proceedings (OSTI)

Demand trading holds substantial promise as a mechanism for efficiently integrating demand-response resources into regional power markets. However, regulatory uncertainty, the lack of proper price signals, limited progress toward standardization, problems in supply-side markets, and other factors have produced illiquidity in demand-trading markets and stalled the expansion of demand-response resources. This report shows how key obstacles to demand trading can be overcome, including how to remove the unce...

2002-11-27T23:59:59.000Z

231

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.

232

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

233

"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"

234

Evaluation of Embedded Solutions for Decreasing Sensitivity of End-Use Equipment to Power Quality Variations  

Science Conference Proceedings (OSTI)

This document provides a conceptual overview of embedded solutions for sensitivity to power quality variations, assesses its benefits, and describes its potential in four end-use equipment categories. The report focuses on the technical and market issues associated with equipment modification provided by original equipment manufacturers (OEMs) to improve equipment tolerance to various power quality phenomena. The report describes approaches and technologies for improving performance, discusses specific i...

1999-12-14T23:59:59.000Z

235

Project on restaurant energy performance: end-use monitoring and analysis. Appendixes I and II  

Science Conference Proceedings (OSTI)

This is the second volume of the report, ''The Porject on Restaurant Energy Performance - End-Use Monitoring and Analysis''. The first volume (PNL-5462) contains a summary and analysis of the metered energy performance data collected by the Project on Restaurant Energy Performance (PREP). Appendix I, presented here, contains monitoring site descriptions, measurement plans, and data summaries for the seven restaurants metered for PREP. Appendix II, also in this volume, is a description of the PREP computer system.

Claar, C.N.; Mazzucchi, R.P.; Heidell, J.A.

1985-05-01T23:59:59.000Z

236

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

237

End-use energy consumption estimates for US commercial buildings, 1989  

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 within the Department of Energy, by 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 1989 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. Billing data for electricity and natural gas were first decomposed into weather and nonweather dependent loads. Subsequently, Statistical Adjusted Engineering (SAE) models were estimated by building type with annual data. The 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. End-use consumption by fuel was estimated for each of the 5,876 buildings in the 1989 CBECS. The report displays the summary results for eleven separate building types as well as for the total US commercial building stock.

Belzer, D.B.; Wrench, L.E.; Marsh, T.L. [Pacific Northwest Lab., Richland, WA (United States)

1993-11-01T23:59:59.000Z

238

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

239

Solar Decathlon Turns Ten | Department of Energy  

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

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...

240

Demand Impacted by Weather  

U.S. Energy Information Administration (EIA)

When you look at demand, it’s also interesting to note the weather. The weather has a big impact on the demand of heating fuels, if it’s cold, consumers will use ...

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

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,

242

Demand Trading Toolkit  

Science Conference Proceedings (OSTI)

Download report 1006017 for FREE. The global movement toward competitive markets is paving the way for a variety of market mechanisms that promise to increase market efficiency and expand customer choice options. Demand trading offers customers, energy service providers, and other participants in power markets the opportunity to buy and sell demand-response resources, just as they now buy and sell blocks of power. EPRI's Demand Trading Toolkit (DTT) describes the principles and practice of demand trading...

2001-12-10T23:59:59.000Z

243

Analysis of Distribution Level Residential Demand Response  

SciTech Connect

Control of end use loads has existed in the form of direct load control for decades. Direct load control systems allow a utility to interrupt power to a medium to large size commercial or industrial customer a set number of times a year. With the current proliferation of computing resources and communications systems the ability to extend the direct load control systems now exists. Demand response systems now have the ability to not only engage commercial and industrial customers, but also the individual residential customers. Additionally, the ability exists to have automated control systems which operate on a continual basis instead of the traditional load control systems which could only be operated a set number of times a year. These emerging demand response systems have the capability to engage a larger portion of the end use load and do so in a more controlled manner. This paper will examine the impact that demand response systems have on the operation of an electric power distribution system.

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

2009-03-23T23:59:59.000Z

244

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

E-Print Network (OSTI)

Homes End-Use Equipment Type Equipment Market Shares Index Heating ElecFurnace Gas Furnace LPG Furnace OilHomes (millions) End-Use Equipment Type Appliance stock in millions of units Index Heating FJec Furnace Gas Furnace L P G Furnace OilHomes End-Use Equipment Type Units Efficiency for Stock Equipment Index Heating Elec Furnace Btu.out/Wh.in Gas Furnace AFUE LPG Furnace AFUE Oil

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

245

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

E-Print Network (OSTI)

Eighth Electric Utility Forecasting Symposium in Baltimore,Development of a Residential Forecasting Database. Lawrenceand Methodology for End-Use Forecasting with EPRI-REEPS 2.1.

Johnson, F.X.

2010-01-01T23:59:59.000Z

246

Project on Restaurant Energy Performance: end-use monitoring and analysis  

Science Conference Proceedings (OSTI)

Although energy bills for restaurants throughout the United States exceed 5 billion dollars annually, very little has been documented with respect to when and how restaurants use energy, or how such use can be reduced cost-effectively. This report summarizes the results of a multiyear collaborative research effort, designed to collect information on end-use energy consumption. Objective is to reveal the quantities and profiles of energy consumption of typical food service operations by time of day and end use. This information, when examined in conjunction with building characteristics, allows detailed study of energy use cause and effect and energy conservation potential. Seven representative monitoring sites were selected, a computerized data acquisition network was designed and implemented, and detailed energy performance was compiled for a 1 year period (July 1983 through June 1984). Each of the seven facilities monitored was selected to represent the seven most common restaurant types and to provide information on a wide variety of commonly used restaurant equipment. Preliminary findings are presented.

Claar, C.N.; Mazzucchi, R.P.; Heidell, J.A.

1985-05-01T23:59:59.000Z

247

How many people actually see the price signal? Quantifying marketfailures in the end use of energy  

SciTech Connect

"Getting the price right" is a goal of many market-orientedenergy policies. However, there are situations where the consumer payingfor the energy is separate from the owner of the energy-using device.Economists call this a "principal agent problem". A team organised by theInternational Energy Agency examined seven end uses and one sector whereprincipal agent problems existed: refrigerators, water heating, spaceheating, vending machines, commercial HVAC, company cars, lighting, andfirms. These investigations took place in Australia, Japan, theNetherlands, Norway, and the United States. About 2 100 percent of theenergy consumed in the end uses examined was affected by principal agentproblems. The size (and sometimes even the existence) varied greatly fromone country to another but all countries had significant amounts ofenergy affected by principal agent problems. The presence of a marketfailure does not mean that energy use would fall substantially if thefailure were eliminated; however it does suggest that raising energyprices such as in the form of carbon taxes will not necessarily increaseefficiency investments.

Meier, Alan; Eide, Anita

2007-09-01T23:59:59.000Z

248

Analysis of end-use electricity consumption during two Pacific Northwest cold snaps  

SciTech Connect

The Pacific Northwest has experienced unusually cold weather during two recent heating seasons. Hourly end-use load data was collected from a sample of residential and commercial buildings during both cold snaps. Earlier work documented the changes in end-use load shapes as outdoor temperature became colder. This paper extends analysis of cold snap load shapes by comparing results from both cold snaps, exploring the variability of electricity consumption between sites, and describing the use of load shapes in simulating system load. Load shapes from the first cold snap showed that hot water use shifted to later in the morning during extremely cold weather. This shift in load also occurred during the second cold snap and is similar to the shift observed on a typical weekend. Electricity consumption averaged across many sites can mask widely varying behavior at individual sites. For example, electricity consumption for space heat varies greatly between homes, especially when many homes are able to burn wood. Electricity consumption for space heat is compared between a group of energy-efficient homes and a group of older homes.

Sands, R.D.

1992-10-01T23:59:59.000Z

249

Analysis of end-use electricity consumption during two Pacific Northwest cold snaps  

SciTech Connect

The Pacific Northwest has experienced unusually cold weather during two recent heating seasons. Hourly end-use load data was collected from a sample of residential and commercial buildings during both cold snaps. Earlier work documented the changes in end-use load shapes as outdoor temperature became colder. This paper extends analysis of cold snap load shapes by comparing results from both cold snaps, exploring the variability of electricity consumption between sites, and describing the use of load shapes in simulating system load. Load shapes from the first cold snap showed that hot water use shifted to later in the morning during extremely cold weather. This shift in load also occurred during the second cold snap and is similar to the shift observed on a typical weekend. Electricity consumption averaged across many sites can mask widely varying behavior at individual sites. For example, electricity consumption for space heat varies greatly between homes, especially when many homes are able to burn wood. Electricity consumption for space heat is compared between a group of energy-efficient homes and a group of older homes.

Sands, R.D.

1992-01-01T23:59:59.000Z

250

Demand Response and Open Automated Demand Response Opportunities...  

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

Response and Open Automated Demand Response Opportunities for Data Centers Title Demand Response and Open Automated Demand Response Opportunities for Data Centers Publication Type...

251

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":""}]}

252

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

E-Print Network (OSTI)

Natural Gas Oil Lighting 0-1 hrs 1-2 his 2-3 hrs Usage levelgas Oil Dishwasher End-Use Lighting 0-1 hrs 1-2 hrs Usagegas Oil Dishwasher End-Use Lighting 0-1 hrs 1-2 hrs Usage

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

253

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

254

Electrical Demand Management  

E-Print Network (OSTI)

The Demand Management Plan set forth in this paper has proven to be a viable action to reduce a 3 million per year electric bill at the Columbus Works location of Western Electric. Measures are outlined which have reduced the peak demand 5% below the previous year's level and yielded $150,000 annual savings. These measures include rescheduling of selected operations and demand limiting techniques such as fuel switching to alternate power sources during periods of high peak demand. For example, by rescheduling the startup of five heat treat annealing ovens to second shift, 950 kW of load was shifted off peak. Also, retired, non-productive steam turbine chillers and a diesel air compressor have been effectively operated to displaced 1330 kW during peak periods each day. Installed metering devices have enabled the recognition of critical demand periods. The paper concludes with a brief look at future plans and long range objectives of the Demand Management Plan.

Fetters, J. L.; Teets, S. J.

1983-01-01T23:59:59.000Z

255

Demand Dispatch-Intelligent  

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

and energy efficiency throughout the value chain resulting in the most economical price for electricity. Having adequate quantities and capacities of demand resources is a...

256

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.

257

Project on restaurant energy performance end-use monitoring and analysis  

Science Conference Proceedings (OSTI)

This paper summarizes the results of a research program intended to build an understanding of restaurant energy performance upon an empirical foundation. This discussion provides some background for this effort, brief descriptions of the facilities selected for study, the measurement methods, the empirical findings, an overview of conservation opportunities revealed, and general conclusions. Seven monitoring sites were carefully selected to represent the most common categories of food service by the National Restaurant Association. A microcomputer based data acquisition was designed and implemented to acquire 15-minute interval data on end-use energy consumption, interior temperatures, and external climate conditions for a one year monitoring period. The project archived over 87% of the available data, which has been converted into several formats for dissemination. Restaurants are found to be very intensive users of energy due largely to the frequent usage of food preparation equipment and the high ventilation requirements.

Mazzucchi, R.P.

1986-04-01T23:59:59.000Z

258

The project on restaurant energy performance end-use monitoring and analysis  

SciTech Connect

This paper summarizes the results of a research program intended to build an understanding of restaurant energy performance upon an empirical foundation. This discussion provides some background for the effort, brief descriptions of the facilities selected for study, the methods of measurement, the empirical findings, an overview of conservation opportunities revealed, and general conclusions. Seven monitoring sites were carefully selected to represent the most common categories of food service by the National Restaurant Association. A microcomputer-based data acquisition was designed and implemented to acquire data at 15-minute intervals on end-use energy consumption, interior temperatures, and external climatic conditions for a one-year monitoring period. The project archived over 87% of the available data, which have been converted into several formats for dissemination.

Mazzucchi, R.P.

1986-01-01T23:59:59.000Z

259

Average regional end-use energy price projections to the year 2030  

Science Conference Proceedings (OSTI)

The energy prices shown in this report cover the period from 1991 through 2030. These prices reflect sector/fuel price projections from the Annual Energy Outlook 1991 (AEO) base case, developed using the Energy Information Administration's (EIA) Intermediate Future Forecasting System (IFFS) forecasting model. Projections through 2010 are AEO base case forecasts. Projections for the period from 2011 through 2030 were developed separately from the AEO for this report, and the basis for these projections is described in Chapter 3. Projections in this report include average energy prices for each of four Census Regions for the residential, commercial, industrial, and transportation end-use sectors. Energy sources include electricity, distillate fuel oil, liquefied petroleum gas, motor gasoline, residual fuel oil, natural gas, and steam coal. (VC)

Not Available

1991-01-01T23:59:59.000Z

260

Average regional end-use energy price projections to the year 2030  

SciTech Connect

The energy prices shown in this report cover the period from 1991 through 2030. These prices reflect sector/fuel price projections from the Annual Energy Outlook 1991 (AEO) base case, developed using the Energy Information Administration`s (EIA) Intermediate Future Forecasting System (IFFS) forecasting model. Projections through 2010 are AEO base case forecasts. Projections for the period from 2011 through 2030 were developed separately from the AEO for this report, and the basis for these projections is described in Chapter 3. Projections in this report include average energy prices for each of four Census Regions for the residential, commercial, industrial, and transportation end-use sectors. Energy sources include electricity, distillate fuel oil, liquefied petroleum gas, motor gasoline, residual fuel oil, natural gas, and steam coal. (VC)

Not Available

1991-12-31T23:59:59.000Z

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.


261

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

262

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

263

U.S. Propane Demand  

U.S. Energy Information Administration (EIA)

Demand is higher in 1999 due to higher petrochemical demand and a strong economy. We are also seeing strong demand in the first quarter of 2000; however, ...

264

Demand Response Valuation Frameworks Paper  

E-Print Network (OSTI)

xxxv Option Value of Electricity Demand Response, Osmanelasticity in aggregate electricity demand. With these newii) reduction in electricity demand during peak periods (

Heffner, Grayson

2010-01-01T23:59:59.000Z

265

"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

266

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.

267

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

268

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].

269

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"

270

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.

271

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

272

Automated Demand Response and Commissioning  

E-Print Network (OSTI)

internal conditions. Maximum Demand Saving Intensity [W/ft2]automated electric demand sheds. The maximum electric shed

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

2005-01-01T23:59:59.000Z

273

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

274

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

275

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.

276

Development of an Energy Savings Benchmark for All Residential End-Uses: Preprint  

DOE Green Energy (OSTI)

To track progress toward aggressive multi-year whole-house energy savings goals of 40-70% and onsite power production of up to 30%, the U.S. Department of Energy (DOE) Residential Buildings Program and the National Renewable Energy Laboratory (NREL) developed the Building America Research Benchmark in 2003. The Benchmark is generally consistent with mid-1990s standard practice, as reflected in the Home Energy Rating System (HERS) Technical Guidelines, with additional definitions that allow the analyst to evaluate all residential end-uses, an extension of the traditional HERS rating approach that focuses on space conditioning and hot water. A series of user profiles, intended to represent the behavior of a''standard'' set of occupants, was created for use in conjunction with the Benchmark. Finally, a set of tools was developed by NREL and other Building America partners to help analysts compare whole-house energy use for a Prototype house to the Benchmark in a fair and consistent manner.

Hendron, R.; Anderson, R.; Christensen, C.; Eastment, M.; Reeves, P.

2004-08-01T23:59:59.000Z

277

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

278

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

279

Residential applliance data, assumptions and methodology for end-use forecasting with EPRI-REEPS 2.1  

Science Conference Proceedings (OSTI)

This report details the data, assumptions and methodology for end-use forecasting of appliance energy use in the US residential sector. Our analysis uses the modeling framework provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which was developed by the Electric Power Research Institute. In this modeling framework, appliances include essentially all residential end-uses other than space conditioning end-uses. We have defined a distinct appliance model for each end-use based on a common modeling framework provided in the REEPS software. This report details our development of the following appliance models: refrigerator, freezer, dryer, water heater, clothes washer, dishwasher, lighting, cooking and miscellaneous. Taken together, appliances account for approximately 70% of electricity consumption and 30% of natural gas consumption in the US residential sector. Appliances are thus important to those residential sector policies or programs aimed at improving the efficiency of electricity and natural gas consumption. This report is primarily methodological in nature, taking the reader through the entire process of developing the baseline for residential appliance end-uses. Analysis steps documented in this report include: gathering technology and market data for each appliance end-use and specific technologies within those end-uses, developing cost data for the various technologies, and specifying decision models to forecast future purchase decisions by households. Our implementation of the REEPS 2.1 modeling framework draws on the extensive technology, cost and market data assembled by LBL for the purpose of analyzing federal energy conservation standards. The resulting residential appliance forecasting model offers a flexible and accurate tool for analyzing the effect of policies at the national level.

Hwang, R.J,; Johnson, F.X.; Brown, R.E.; Hanford, J.W.; Kommey, J.G.

1994-05-01T23:59:59.000Z

280

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

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

Demand Response Database & Demo  

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

Demand Response Database & Demo Speaker(s): Mike Graveley William M. Smith Date: June 7, 2005 - 12:00pm Location: Bldg. 90 Seminar HostPoint of Contact: Mary Ann Piette Infotility...

282

Tankless Demand Water Heaters  

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

Demand (tankless or instantaneous) water heaters have heating devices that are activated by the flow of water, so they provide hot water only as needed and without the use of a storage tank. They...

283

Residential Sector Demand Module  

Reports and Publications (EIA)

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

Owen Comstock

2012-12-19T23:59:59.000Z

284

Industrial Demand Module  

Reports and Publications (EIA)

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

Kelly Perl

2013-05-14T23:59:59.000Z

285

Industrial Demand Module  

Reports and Publications (EIA)

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

Kelly Perl

2013-09-30T23:59:59.000Z

286

Residential Sector Demand Module  

Reports and Publications (EIA)

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

Owen Comstock

2013-11-05T23:59:59.000Z

287

Ten commandments revisited: a ten-year perspective on the industrial application of formal methods  

Science Conference Proceedings (OSTI)

Ten years ago, our 1995 paper Ten Commandments of Formal Methods [5] suggested some guidelines to help ensure the success of a formal methods project. It proposed ten important requirements (or "commandments") for formal developers to consider ... Keywords: correctness, formal methods, industrial application, software engineering

Jonathan P. Bowen; Michael G. Hinchey

2005-09-01T23:59:59.000Z

288

Installation and Commissioning Automated Demand Response Systems  

Science Conference Proceedings (OSTI)

Demand Response (DR) can be defined as actions taken to reduce electric loads when contingencies, such as emergencies and congestion, occur that threaten supply-demand balance, or market conditions raise supply costs. California utilities have offered price and reliability DR based programs to customers to help reduce electric peak demand. The lack of knowledge about the DR programs and how to develop and implement DR control strategies is a barrier to participation in DR programs, as is the lack of automation of DR systems. Most DR activities are manual and require people to first receive notifications, and then act on the information to execute DR strategies. Levels of automation in DR can be defined as follows. Manual Demand Response involves a labor-intensive approach such as manually turning off or changing comfort set points at each equipment switch or controller. Semi-Automated Demand Response involves a pre-programmed demand response strategy initiated by a person via centralized control system. 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. The receipt of the external signal initiates pre-programmed demand response strategies. We refer to this as Auto-DR (Piette et. al. 2005). Auto-DR for commercial and industrial facilities can be defined as fully automated DR initiated by a signal from a utility or other appropriate entity and that provides fully-automated connectivity to customer end-use control strategies. One important concept in Auto-DR is that a homeowner or facility manager should be able to 'opt out' or 'override' a DR event if the event comes at time when the reduction in end-use services is not desirable. Therefore, Auto-DR is not handing over total control of the equipment or the facility to the utility but simply allowing the utility to pass on grid related information which then triggers facility defined and programmed strategies if convenient to the facility. From 2003 through 2006 Lawrence Berkeley National Laboratory (LBNL) and the Demand Response Research Center (DRRC) developed and tested a series of demand response automation communications technologies known as Automated Demand Response (Auto-DR). In 2007, LBNL worked with three investor-owned utilities to commercialize and implement Auto-DR programs in their territories. This paper summarizes the history of technology development for Auto-DR, and describes the DR technologies and control strategies utilized at many of the facilities. It outlines early experience in commercializing Auto-DR systems within PG&E DR programs, including the steps to configure the automation technology. The paper also describes the DR sheds derived using three different baseline methodologies. Emphasis is given to the lessons learned from installation and commissioning of Auto-DR systems, with a detailed description of the technical coordination roles and responsibilities, and costs.

Global Energy Partners; Pacific Gas and Electric Company; Kiliccote, Sila; Kiliccote, Sila; Piette, Mary Ann; Wikler, Greg; Prijyanonda, Joe; Chiu, Albert

2008-04-21T23:59:59.000Z

289

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

Science Conference Proceedings (OSTI)

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

290

Bos ten AG | Open Energy Information  

Open Energy Info (EERE)

Germany Zip 93049 Sector Solar Product Partner of Beck Energy in development of a 3.2MW solar PV plant. References Bos.ten AG1 LinkedIn Connections CrunchBase Profile No...

291

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.

292

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

293

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

time. 4 Reducing this peak demand through DR programs meansthat a 5% reduction in peak demand would have resulted insame 5% reduction in the peak demand of the US as a whole.

Shen, Bo

2013-01-01T23:59:59.000Z

294

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

295

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

296

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.

297

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

298

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

299

Automated Demand Response Today  

Science Conference Proceedings (OSTI)

Demand response (DR) has progressed over recent years beyond manual and semi-automated DR to include growing implementation and experience with fully automated demand response (AutoDR). AutoDR has been shown to be of great value over manual and semi-automated DR because it reduces the need for human interactions and decisions, and it increases the speed and reliability of the response. AutoDR, in turn, has evolved into the specification known as OpenADR v1.0 (California Energy Commission, PIER Program, C...

2012-03-29T23:59:59.000Z

300

Travel Demand Modeling  

SciTech Connect

This chapter describes the principal types of both passenger and freight demand models in use today, providing a brief history of model development supported by references to a number of popular texts on the subject, and directing the reader to papers covering some of the more recent technical developments in the area. Over the past half century a variety of methods have been used to estimate and forecast travel demands, drawing concepts from economic/utility maximization theory, transportation system optimization and spatial interaction theory, using and often combining solution techniques as varied as Box-Jenkins methods, non-linear multivariate regression, non-linear mathematical programming, and agent-based microsimulation.

Southworth, Frank [ORNL; Garrow, Dr. Laurie [Georgia Institute of Technology

2011-01-01T23:59:59.000Z

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.


301

United States lubricant demand  

Science Conference Proceedings (OSTI)

This paper examines United States Lubricant Demand for Automotive and Industrial Lubricants by year from 1978 to 1992 and 1997. Projected total United States Lubricant Demand for 1988 is 2,725 million (or MM) gallons. Automotive oils are expected to account for 1,469MM gallons or (53.9%), greases 59MM gallons (or 2.2%), and Industrial oils will account for the remaining 1,197MM gallons (or 43.9%) in 1988. This proportional relationship between Automotive and Industrial is projected to remain relatively constant until 1992 and out to 1997. Projections for individual years between 1978 to 1992 and 1997 are summarized.

Solomon, L.K.; Pruitt, P.R.

1988-01-01T23:59:59.000Z

302

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

303

Future demand for electricity in the Nassau--Suffolk region  

DOE Green Energy (OSTI)

Brookhaven National Laboratory established a new technology for load forecasting for the Long Island Lighting Company and prepared an independent forecast of the demand for electricity in the LILCO area. The method includes: demand for electricity placed in a total energy perspective so that substitutions between electricity and other fuels can be examined; assessment of the impact of conservation, new technology, gas curtailment, and other factors upon demand for electricity; and construction of the probability distribution of the demand for electricity. A detailed analysis of changing levels of demand for electricity, and other fuels, associated with these new developments is founded upon a disaggregated end-use characterization of energy utilization, including space heat, lighting, process energy, etc., coupled to basic driving forces for future demand, namely: population, housing mix, and economic growth in the region. The range of future events covers conservation, heat pumps, solar systems, storage resistance heaters, electric vehicles, extension of electrified rail, total energy systems, and gas curtailment. Based upon cost and other elements of the competition between technologies, BNL assessed the likelihood of these future developments. An optimistic view toward conservation leads to ''low'' demand for electricity, whereas rapid development of new technologies suggests ''high'' demand. (MCW)

Carroll, T.W.; Palmedo, P.F.; Stern, R.

1977-12-01T23:59:59.000Z

304

Open Automated Demand Response for Small Commerical Buildings  

Science Conference Proceedings (OSTI)

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

305

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

306

Transportation Demand Management Plan  

E-Print Network (OSTI)

Transportation Demand Management Plan FALL 2009 #12;T r a n s p o r t a t i o n D e m a n d M a n the transportation impacts the expanded enrollment will have. Purpose and Goal The primary goal of the TDM plan is to ensure that adequate measures are undertaken and maintained to minimize the transportation impacts

307

Commercial Sector Demand Module  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

Kevin Jarzomski

2012-11-15T23:59:59.000Z

308

Commercial Sector Demand Module  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

Kevin Jarzomski

2013-10-10T23:59:59.000Z

309

,"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"

310

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

311

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,

312

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":""}]}

313

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

314

A methodology for determining the relationship between air transportation demand and the level of service  

E-Print Network (OSTI)

Introduction: Within the last ten years significant advances in the state-of-the art in air travel demand analysis stimulated researchers in the domestic air transportation field. Among these advances, researchers in ...

Eriksen, Steven Edward

1976-01-01T23:59:59.000Z

315

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

316

Technology data characterizing lighting in commercial buildings: Application to end-use forecasting with commend 4.0  

SciTech Connect

End-use forecasting models typically utilize technology tradeoff curves to represent technology options available to consumers. A tradeoff curve, in general terms, is a functional form which relates efficiency to capital cost. Each end-use is modeled by a single tradeoff curve. This type of representation is satisfactory in the analysis of many policy options. On the other hand, for policies addressing individual technology options or groups of technology options, because individual technology options are accessible to the analyst, representation in such reduced form is not satisfactory. To address this and other analysis needs, the Electric Power Research Institute (EPRI) has enhanced its Commercial End-Use Planning System (COMMEND) to allow modeling of specific lighting and space conditioning (HVAC) technology options. This report characterizes the present commercial floorstock in terms of lighting technologies and develops cost-efficiency data for these lighting technologies. This report also characterizes the interactions between the lighting and space conditioning end uses in commercial buildings in the US In general, lighting energy reductions increase the heating and decrease the cooling requirements. The net change in a building`s energy requirements, however, depends on the building characteristics, operating conditions, and the climate. Lighting/HVAC interactions data were generated through computer simulations using the DOE-2 building energy analysis program.

Sezgen, A.O.; Huang, Y.J.; Atkinson, B.A.; Eto, J.H.; Koomey, J.G.

1994-05-01T23:59:59.000Z

317

ENERGY DEMAND FORECAST METHODS REPORT  

E-Print Network (OSTI)

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

318

Demand Forecast INTRODUCTION AND SUMMARY  

E-Print Network (OSTI)

Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required of any forecast of electricity demand and developing ways to reduce the risk of planning errors that could arise from this and other uncertainties in the planning process. Electricity demand is forecast

319

On Demand Paging Using  

E-Print Network (OSTI)

The power consumption of the network interface plays a major role in determining the total operating lifetime of wireless handheld devices. On demand paging has been proposed earlier to reduce power consumption in cellular networks. In this scheme, a low power secondary radio is used to wake up the higher power radio, allowing the latter to sleep or remain off for longer periods of time. In this paper we present use of Bluetooth radios to serve as a paging channel for the 802.11 wireless LAN. We have implemented an on-demand paging scheme on a WLAN consisting of iPAQ PDAs equipped with Bluetooth radios and Cisco Aironet wireless networking cards. Our results show power saving ranging from 19% to 46% over the present 802.11b standard operating modes with negligible impact on performance.

Bluetooth Radios On; Yuvraj Agarwal; Rajesh K. Gupta

2003-01-01T23:59:59.000Z

320

Net Demand3 Production  

E-Print Network (OSTI)

Contract Number: DE-FE0004002 (Subcontract: S013-JTH-PPM4002 MOD 00) Summary The US DOE has identified a number of materials that are both used by clean energy technologies and are at risk of supply disruptions in the short term. Several of these materials, especially the rare earth elements (REEs) yttrium, cerium, and lanthanum were identified by DOE as critical (USDOE 2010) and are crucial to the function and performance of solid oxide fuel cells (SOFCs) 1. In addition, US DOE has issued a second Request For Information regarding uses of and markets for these critical materials (RFI;(USDOE 2011)). This report examines how critical materials demand for SOFC applications could impact markets for these materials and vice versa, addressing categories 1,2,5, and 6 in the RFI. Category 1 – REE Content of SOFC Yttria (yttrium oxide) is the only critical material (as defined for the timeframe of interest for SOFC) used in SOFC 2. Yttrium is used as a dopant in the SOFC’s core ceramic cells.. In addition, continuing developments in SOFC technology will likely further reduce REE demand for SOFC, providing credible scope for at least an additional 50 % reduction in REE use if desirable. Category 2 – Supply Chain and Market Demand SOFC developers expect to purchase

J. Thijssen Llc

2011-01-01T23:59:59.000Z

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.


321

Analysis of Residential Demand Response and Double-Auction Markets  

Science Conference Proceedings (OSTI)

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

322

Open Automated Demand Response Communications Specification (Version 1.0)  

Science Conference Proceedings (OSTI)

The development of the Open Automated Demand Response Communications Specification, also known as OpenADR or Open Auto-DR, began in 2002 following the California electricity crisis. The work has been carried out by the Demand Response Research Center (DRRC), which is managed by Lawrence Berkeley National Laboratory. This specification describes an open standards-based communications data model designed to facilitate sending and receiving demand response price and reliability signals from a utility or Independent System Operator to electric customers. OpenADR is one element of the Smart Grid information and communications technologies that are being developed to improve optimization between electric supply and demand. The intention of the open automated demand response communications data model is to provide interoperable signals to building and industrial control systems that are preprogrammed to take action based on a demand response signal, enabling a demand response event to be fully automated, with no manual intervention. The OpenADR specification is a flexible infrastructure to facilitate common information exchange between the utility or Independent System Operator and end-use participants. The concept of an open specification is intended to allow anyone to implement the signaling systems, the automation server or the automation clients.

Piette, Mary Ann; Ghatikar, Girish; Kiliccote, Sila; Koch, Ed; Hennage, Dan; Palensky, Peter; McParland, Charles

2009-02-28T23:59:59.000Z

323

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

E-Print Network (OSTI)

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

Johnson, F.X.

2010-01-01T23:59:59.000Z

324

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

Natural Gas Demands..xi Annual natural gas demand for each alternativeused in natural gas demand projections. 34

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

2008-01-01T23:59:59.000Z

325

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

Minimum demand and Maximum demand incorporate assumptionslevels, or very minor Maximum demand household size, growthvehicles in Increasing Maximum demand 23 mpg truck share

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

2008-01-01T23:59:59.000Z

326

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

327

Dividends with Demand Response  

SciTech Connect

To assist facility managers in assessing whether and to what extent they should participate in demand response programs offered by ISOs, we introduce a systematic process by which a curtailment supply curve can be developed that integrates costs and other program provisions and features. This curtailment supply curve functions as bid curve, which allows the facility manager to incrementally offer load to the market under terms and conditions acceptable to the customer. We applied this load curtailment assessment process to a stylized example of an office building, using programs offered by NYISO to provide detail and realism.

Kintner-Meyer, Michael CW; Goldman, Charles; Sezgen, O.; Pratt, D.

2003-10-31T23:59:59.000Z

328

Demand Response-Ready Technology Capabilities: A Summary of Multi-Stakeholder Workshop and Survey Perspectives  

Science Conference Proceedings (OSTI)

This technical update describes technology capabilities that support more automated and ubiquitous demand response. It begins by describing the Demand Response-Ready (DR-Ready) concept and related industry activities that support realization of the concept. In the DR-Ready vision, consumers receive DR-Ready end-use products at the point of purchase, thus eliminating the need for utility truck service visits to retrofit equipment and significantly reducing the cost of deploying DR-enabling technologies. ...

2012-04-06T23:59:59.000Z

329

Demand Response-Ready Capabilities Roadmap: A Summary of Multi-Stakeholder Workshop and Survey Perspectives  

Science Conference Proceedings (OSTI)

The report describes a high-level roadmap for premise-level migration towards more automated and ubiquitous demand response. It begins by describing the Demand Response Ready (DR-Ready) concept and related industry activities supporting realization of the concept. In the DR-Ready vision, consumers receive DR-Ready end-use products at the point of purchase, thus eliminating the need for utility truck rolls to retrofit equipment, and thereby significantly reducing costs of deploying DR enabling ...

2012-12-31T23:59:59.000Z

330

Non-Intrusive Load Monitoring (NILM)Technologies for End-Use Load Disaggregation: Laboratory Evaluation I  

Science Conference Proceedings (OSTI)

This report presents the results of a laboratory evaluation to assess the cost versus accuracy performance of residential non-intrusive load monitoring (NILM) technology. NILM is an evolving technology that can be deployed for utility and customer applications, such as end-use load disaggregation, energy audits, real-time customer information and appliance or load diagnostics. Commercial NILM products for utility and customer applications continue to emerge, although most products available today ...

2013-05-22T23:59:59.000Z

331

Chinese demand drives global deforestation Chinese demand drives global deforestation  

E-Print Network (OSTI)

Chinese demand drives global deforestation Chinese demand drives global deforestation By Tansa Musa zones and do not respect size limits in their quest for maximum financial returns. "I lack words economy. China's demand for hardwood drives illegal logging says "Both illegal and authorized

332

Estimating a Demand System with Nonnegativity Constraints: Mexican Meat Demand  

E-Print Network (OSTI)

: Properties of the AIDS Generalized Maximum Entropy Estimator 24 #12;Estimating a Demand SystemEstimating a Demand System with Nonnegativity Constraints: Mexican Meat Demand Amos Golan* Jeffrey with nonnegativity constraints is presented. This approach, called generalized maximum entropy (GME), is more

Perloff, Jeffrey M.

333

CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST  

E-Print Network (OSTI)

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

334

The quality of the ELCAP (End-Use Load and Consumer Assessment Program) engineering data set: Background issues  

SciTech Connect

The Bonneville Power Administration (Bonneville) began the End-Use Load and Consumer Assessment Program (ELCAP) in 1983. Prior to beginning ELCAP, there was an abundance of information regarding total power consumption for residential structures in the Pacific Northwest, through billing records for example, and limited information regarding power consumption by various end uses (such as hot water, heating and cooling). This program, conducted for Bonneville by the Pacific Northwest Laboratory, involves collecting and analyzing hourly end-use data in commercial and residential buildings in the Pacific Northwest. The purpose of this document is to provide background information to analyses that may use ELCAP data. In general, the ELCAP data set is extremely high in quality, but analysts should be aware of potential problems that could exist with a data set of this size. This report describes the quality of the ELCAP data and emphasizes the guidelines for data review along with limitations and suggestions regarding engineering and characteristics data including missing data values, procedures for time-stamp assignments, and incomplete integration periods. 3 figs.

Crowder, R.S. III; Miller, N.E.

1990-06-01T23:59:59.000Z

335

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

336

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 percent 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.

Information Center

2005-04-01T23:59:59.000Z

337

ELECTRICITY DEMAND FORECAST COMPARISON REPORT  

E-Print Network (OSTI)

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

338

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.

339

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.

340

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.

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

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

342

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

343

" Row: End Uses;"  

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

" Conventional Boiler Use",3199,12,4,1271,2,11,5.6 " CHP andor Cogeneration Process",3515,8,2,834,"*",23,3.8 "Direct Uses-Total Process",768929,10,7,2907,16,17...

344

" Row: End Uses;"  

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

Fuel",12979,7,3,2074,3,26 " Conventional Boiler Use",12979,3,1,712,1,3 " CHP andor Cogeneration Process","--",4,3,1362,2,23 "Direct Uses-Total Process",675152,4,9,2549,7,13 "...

345

" Row: End Uses;"  

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

l",84,133,23,2119,8,547 " Conventional Boiler Use",84,71,17,1281,8,129 " CHP andor Cogeneration Process",0,62,6,838,1,417 "Direct Uses-Total Process",2639,62,52,2788,39,412 "...

346

Demand Response Programs, 6. edition  

Science Conference Proceedings (OSTI)

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

347

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

2007 EMCS EPACT ERCOT FCM FERC FRCC demand side managementEnergy Regulatory Commission (FERC). EPAct began the processin wholesale markets, which FERC Order 888 furthered by

Shen, Bo

2013-01-01T23:59:59.000Z

348

Price-elastic demand in deregulated electricity markets  

SciTech Connect

The degree to which any deregulated market functions efficiently often depends on the ability of market agents to respond quickly to fluctuating conditions. Many restructured electricity markets, however, experience high prices caused by supply shortages and little demand-side response. We examine the implications for market operations when a risk-averse retailer's end-use consumers are allowed to perceive real-time variations in the electricity spot price. Using a market-equilibrium model, we find that price elasticity both increases the retailers revenue risk exposure and decreases the spot price. Since the latter induces the retailer to reduce forward electricity purchases, while the former has the opposite effect, the overall impact of price responsive demand on the relative magnitudes of its risk exposure and end-user price elasticity. Nevertheless, price elasticity decreases cumulative electricity consumption. By extending the analysis to allow for early settlement of demand, we find that forward stage end-user price responsiveness decreases the electricity forward price relative to the case with price-elastic demand only in real time. Moreover, we find that only if forward stage end-user demand is price elastic will the equilibrium electricity forward price be reduced.

Siddiqui, Afzal S.

2003-05-01T23:59:59.000Z

349

Price-elastic demand in deregulated electricity markets  

SciTech Connect

The degree to which any deregulated market functions efficiently often depends on the ability of market agents to respond quickly to fluctuating conditions. Many restructured electricity markets, however, experience high prices caused by supply shortages and little demand-side response. We examine the implications for market operations when a risk-averse retailer's end-use consumers are allowed to perceive real-time variations in the electricity spot price. Using a market-equilibrium model, we find that price elasticity both increases the retailers revenue risk exposure and decreases the spot price. Since the latter induces the retailer to reduce forward electricity purchases, while the former has the opposite effect, the overall impact of price responsive demand on the relative magnitudes of its risk exposure and end-user price elasticity. Nevertheless, price elasticity decreases cumulative electricity consumption. By extending the analysis to allow for early settlement of demand, we find that forward stage end-user price responsiveness decreases the electricity forward price relative to the case with price-elastic demand only in real time. Moreover, we find that only if forward stage end-user demand is price elastic will the equilibrium electricity forward price be reduced.

Siddiqui, Afzal S.

2003-05-01T23:59:59.000Z

350

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)

351

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

352

Automated Demand Response and Commissioning  

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

and Commissioning Title Automated Demand Response and Commissioning Publication Type Conference Paper LBNL Report Number LBNL-57384 Year of Publication 2005 Authors Piette, Mary...

353

Demand Response Valuation Frameworks Paper  

E-Print Network (OSTI)

lvi Southern California Edison filed its SmartConnectinfrastructure (e.g. , Edison Electric Institute, DemandSouthern California Edison Standard Practice Manual

Heffner, Grayson

2010-01-01T23:59:59.000Z

354

Demand Uncertainty and Price Dispersion.  

E-Print Network (OSTI)

??Demand uncertainty has been recognized as one factor that may cause price dispersion in perfectly competitive markets with costly and perishable capacity. With the persistence… (more)

Li, Suxi

2007-01-01T23:59:59.000Z

355

1995 Demand-Side Managment  

U.S. Energy Information Administration (EIA)

U.S. Electric Utility Demand-Side Management 1995 January 1997 Energy Information Administration Office of Coal, Nuclear, Electric and Alternate Fuels

356

Purvin and Gertz; Asia Pacific natural gas demand to take off  

Science Conference Proceedings (OSTI)

This paper reports on growing Asia Pacific gas demand through 2010 that will dramatically increase competition for imports and indigenous regional supplies, a Houston consulting firm says. Deregulation of Asia Pacific energy markets, increased environmental awareness, and greater emphasis on economics of interfuel competition are among major factors expected to affect Asia Pacific gas markets for the next two decades, says a study by Purvin and Gertz Inc. (P and G). Aside from government mandated constraints, future gas prices in each country studied generally will be related to costs of fuels with which gas competes in each end use sector, P and G says. With regional gas demand expected in 2010 to reach 9.2 tcf, P and G advises Asia Pacific consumers in all sectors to begin negotiating now for long term supplies. P and G says more than 50% of new regional gas demand through 2000 will come from increased gas usage in power generation. Most new thermal power generating plants planned in Asia Pacific countries will be either gas or coal fired. but other end use sectors also will play significant roles in future demand growth. P and G predicts liquefied natural gas demand through the end of the century will increase by 4.2%/year. During 2000-2010, Asia Pacific LNG demand will grow by about 3%/year. Regional LNG demand in 2010 will reach 80 million tons of oil equivalent (TOE), increasing from 67 million TOE in 2000 and 45 million TOE in 1990.

Not Available

1991-11-04T23:59:59.000Z

357

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

energy efficiency and demand response programs and tariffs.energy efficiency and demand response program and tariffenergy efficiency and demand response programs and tariffs.

Goldman, Charles

2010-01-01T23:59:59.000Z

358

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

359

Demand Response Quick Assessment Tool (DRQAT)  

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

Demand Response Quick Assessment Tool (DRQAT) The opportunities for demand reduction and cost saving with building demand responsive control vary tremendously with building type...

360

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

2 2.0 Demand ResponseFully Automated Demand Response Tests in Large Facilities,was coordinated by the Demand Response Research Center and

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

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.


361

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

8.4 Demand Response Integration . . . . . . . . . . .for each day type for the demand response study - moderatefor each day type for the demand response study - moderate

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

362

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

363

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

364

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

365

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

366

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

367

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

8 Figure 7: Maximum Demands Savings Intensity due toaddressed in this report. Maximum Demand Savings Intensity (Echelon Figure 7: Maximum Demands Savings Intensity due to

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

368

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

369

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

370

Vehicle Technologies Office: Fact #781: May 27, 2013 Top Ten...  

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

1: May 27, 2013 Top Ten Natural Gas Producing Countries to someone by E-mail Share Vehicle Technologies Office: Fact 781: May 27, 2013 Top Ten Natural Gas Producing Countries on...

371

Federal Energy Management Program: Ten Ways to Lower Perceived...  

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

Ten Ways to Lower Perceived Risk and Finance Rates within Utility Contract to someone by E-mail Share Federal Energy Management Program: Ten Ways to Lower Perceived Risk and...

372

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

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

industry 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...

373

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.

374

Harnessing the power of demand  

Science Conference Proceedings (OSTI)

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

375

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

376

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

377

Demand Response for Ancillary Services  

Science Conference Proceedings (OSTI)

Many demand response resources are technically capable of providing ancillary services. In some cases, they can provide superior response to generators, as the curtailment of load is typically much faster than ramping thermal and hydropower plants. Analysis and quantification of demand response resources providing ancillary services is necessary to understand the resources economic value and impact on the power system. Methodologies used to study grid integration of variable generation can be adapted to the study of demand response. In the present work, we describe and illustrate a methodology to construct detailed temporal and spatial representations of the demand response resource and to examine how to incorporate those resources into power system models. In addition, the paper outlines ways to evaluate barriers to implementation. We demonstrate how the combination of these three analyses can be used to translate the technical potential for demand response providing ancillary services into a realizable potential.

Alkadi, Nasr E [ORNL; Starke, Michael R [ORNL

2013-01-01T23:59:59.000Z

378

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.

379

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

380

Demand Response Opportunities in Industrial Refrigerated Warehouses...  

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

Demand Response Opportunities in Industrial Refrigerated Warehouses in California Title Demand Response Opportunities in Industrial Refrigerated Warehouses in California...

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

Strategies for Demand Response in Commercial Buildings  

E-Print Network (OSTI)

the average and maximum peak demand savings. The electricity1: Average and Maximum Peak Electric Demand Savings during

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

2006-01-01T23:59:59.000Z

382

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

A Joint Model of the Global Crude Oil Market and the U.S.Noureddine. 2002. World crude oil and natural gas: a demandelasticity of demand for crude oil, not gasoline. Results

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

383

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

A Joint Model of the Global Crude Oil Market and the U.S.Noureddine. 2002. World crude oil and natural gas: a demandelasticity of demand for crude oil, not gasoline. Results

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

384

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

Model of the Global Crude Oil Market and the U.S. RetailNoureddine. 2002. World crude oil and natural gas: a demandanalysis of the demand for oil in the Middle East. Energy

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

385

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

386

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...

387

LBL-34046 UC-350 Residential Appliance Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

This report details the data, assumptions and methodology for end-use forecasting of appliance energy use in the U.S. residential sector. Our analysis uses the modeling framework provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which was developed by the Electric Power Research Institute (McMenamin et al. 1992). In this modeling framework, appliances include essentially all residential end-uses other than space conditioning end-uses. We have defined a distinct appliance model for each end-use based on a common modeling framework provided in the REEPS software. This report details our development of the following appliance models: refrigerator, freezer, dryer, water heater, clothes washer, dishwasher, lighting, cooking and miscellaneous. Taken together, appliances account for approximately 70 % of electricity consumption and 30 % of natural gas consumption in the U.S. residential sector (EIA 1993). Appliances are thus important to those residential sector policies or programs aimed at improving the efficiency of electricity and natural gas consumption. This report is primarily methodological in nature, taking the reader through the entire process of developing the baseline for residential appliance end-uses. Analysis steps documented in this report include: gathering technology and market data for each appliance end-use and specific

J. Hwang; Francis X. Johnson; Richard E. Brown; James W. Hanford; Jonathan G. Koomey

1994-01-01T23:59:59.000Z

388

Linking Continuous Energy Management and Open Automated Demand Response  

Science Conference Proceedings (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. 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 (Open Auto-DR or 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.

Piette, Mary Ann; Kiliccote, Sila; Ghatikar, Girish

2008-10-03T23:59:59.000Z

389

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.

390

Effects of the drought on California electricity supply and demand  

E-Print Network (OSTI)

Acknowledgments SUMMARY Electricity Demand ElectricityAdverse Impacts ELECTRICITY DEMAND . . . .Demand forElectricity Sales Electricity Demand by Major Utility

Benenson, P.

2010-01-01T23:59:59.000Z

391

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.

392

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

393

Winter Demand Impacted by Weather  

Gasoline and Diesel Fuel Update (EIA)

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...

394

Demand for money in China .  

E-Print Network (OSTI)

??This research investigates the long-run equilibrium relationship between money demand and its determinants in China over the period 1952-2004 for three definitions of money –… (more)

Zhang, Qing

2006-01-01T23:59:59.000Z

395

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

396

STEO December 2012 - coal demand  

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

coal demand seen below 1 billion tons in 2012 for fourth year in a row Coal consumption by U.S. power plants to generate electricity is expected to fall below 1 billion tons in...

397

Distillate Demand Strong Last Winter  

Gasoline and Diesel Fuel Update (EIA)

4 Notes: Well, distillate fuel demand wasn't the reason that stocks increased in January 2001 and kept prices from going higher. As you will hear shortly, natural gas prices spiked...

398

Thermal Mass and Demand Response  

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

Thermal Mass and Demand Response Speaker(s): Gregor Henze Phil C. Bomrad Date: November 2, 2011 - 12:00pm Location: 90-4133 Seminar HostPoint of Contact: Janie Page The topic of...

399

Automated Demand Response and Commissioning  

E-Print Network (OSTI)

Conference on Building Commissioning: May 4-6, 2005 Motegi,National Conference on Building Commissioning: May 4-6, 2005Demand Response and Commissioning Mary Ann Piette, David S.

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

2005-01-01T23:59:59.000Z

400

Leslie Mancebo (7234) Transportation Demand &  

E-Print Network (OSTI)

Leslie Mancebo (7234) Transportation Demand & Marketing Coordinator 1 FTE, 1 HC Administrative Vice Chancellor Transportation and Parking Services Clifford A. Contreras (0245) Director 30.10 FTE Alternative Transportation & Marketing Reconciliation Lourdes Lupercio (4723) Michelle McArdle (7512) Parking

Hammock, Bruce D.

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

Demand Response Spinning Reserve Demonstration  

Science Conference Proceedings (OSTI)

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

402

Financing end-use solar technologies in a restructured electricity industry: Comparing the cost of public policies  

DOE Green Energy (OSTI)

Renewable energy technologies are capital intensive. Successful public policies for promoting renewable energy must address the significant resources needed to finance them. Public policies to support financing for renewable energy technologies must pay special attention to interactions with federal, state, and local taxes. These interactions are important because they can dramatically increase or decrease the effectiveness of a policy, and they determine the total cost of a policy to society as a whole. This report describes a comparative analysis of the cost of public policies to support financing for two end-use solar technologies: residential solar domestic hot water heating (SDHW) and residential rooftop photovoltaic (PV) systems. The analysis focuses on the cost of the technologies under five different ownership and financing scenarios. Four scenarios involve leasing the technologies to homeowners in return for a payment that is determined by the financing requirements of each form of ownership. For each scenario, the authors examine nine public policies that might be used to lower the cost of these technologies: investment tax credits (federal and state), production tax credits (federal and state), production incentives, low-interest loans, grants (taxable and two types of nontaxable), direct customer payments, property and sales tax reductions, and accelerated depreciation.

Jones, E.; Eto, J.

1997-09-01T23:59:59.000Z

403

Policy Drivers for Improving Electricity End-Use Efficiency in the U.S.: An Economic-Engineering Analysis  

E-Print Network (OSTI)

This paper estimates the economically achievable potential for improving electricity end-use efficiency in the U.S. The approach involves identifying a series of energy-efficiency policies aimed at tackling market failures, and then examining their impacts and cost-effectiveness using Georgia Tech’s version of the National Energy Modeling System (GT-NEMS). By estimating the policy-driven electricity savings and the associated levelized costs, a policy supply curve for electricity efficiency is produced. Each policy is evaluated individually and in an Integrated Policy scenario to examine policy dynamics. The Integrated Policy scenario demonstrates significant achievable potential: 261 TWh (6.5%) of electricity savings in 2020, and 457 TWh (10.2%) in 2035. All eleven policies examined were estimated to have lower levelized costs than average electricity retail prices. Levelized costs range from 0.5 – 8.0 cent/kWh, with the regulatory and information policies tending to be most cost-effective. Policy impacts on the power sector, carbon dioxide emissions, and energy intensity are also estimated to be significant. *Corresponding author:

Yu Wang; Marilyn A. Brown; Yu Wang

2013-01-01T23:59:59.000Z

404

Making a difference: Ten case studies of DSM/IRP interactive efforts and related advocacy group activities  

Science Conference Proceedings (OSTI)

This report discusses the activities of organizations that seek to promote integrated resource planning and aggressive, cost-effective demand-side management by utilities. The activities of such groups -- here called energy efficiency advocacy groups (EEAGs) -- are examined in ten detailed am studies. Nine of the cases involve some form of interactive effort between investor-owned electric utilities and non-utility to develop policies, plans, or programs cooperatively. Many but not all of the interactive efforts examined are formal collaboratives. In addition, all ten cases include discussion of other EEAG activities, such as coalition-building, research, participation in statewide energy planning, and intervention in regulatory proceedings.

English, M.; Schexnayder, S.; Altman, J. [Tennessee Univ., Knoxville, TN (United States). Energy, Environment and Resources Center; Schweitzer, M. [Oak Ridge National Lab., TN (United States)

1994-03-01T23:59:59.000Z

405

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

406

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

407

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

4.2. Energy The California Energy Commission has analyzedmandate to reduce California's energy consumption. Over theEnd Use Surveys, California Energy Commission, 2002 [vi

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

408

Redesign of Electrical Installations to Maximize the Use of Photo Voltaic (PV) Cells at the End Use of Consumers in Kuwait  

E-Print Network (OSTI)

A new idea of redesigning the electrical installations inside residential premises is presented in this paper. The idea is based on having two separate circuits' installations. The first is A.C circuit which can be served by electric grid at standard operating voltage of 230 volts. While the second is D.C circuit being feed directly from the PV cells to meet the demand of all electrical appliances operated at tapered voltage between 12, 24 and 48 volts. The problem of unavailability of PV cell generation during the absence of sun is discussed and solved by introducing a smart interface between the power utility and the consumer having this micro generation PV cells. Smart bidirectional kWh energy meter is used to register the energy consumed by the consumer and the energy being produced by PV cells owned by the consumer himself. In this paper ten years were used to assess the advantages of using this method in Kuwait power systems. Besides the reduction in expansion cost for the power system, a significant release of system capacity was also assessed. Computer software was used to perform the load flow for typical days of the year to show clearly the behavior of the system under these new conditions. As a result of applying this new technique, generator units, transformers, over headlines and underground cables capacity were released. The voltage drop and energy losses through the power system network were reduced as result of reducing the current flow in them. A comparison between continuing to meet the expansion of the system in Kuwait with conventional electric power equipment and using new technique is presented in this paper.

Alatrash, J.; Mhaisen, N.; Ismail, Z.

2010-01-01T23:59:59.000Z

409

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,...

410

Final Environmental Impact Report: North Brawley Ten Megawatt...  

Open Energy Info (EERE)

Number NA DOI Not Provided Check for DOI availability: http:crossref.org Online Internet link for Final Environmental Impact Report: North Brawley Ten Megawatt Geothermal...

411

Water Sampling At Valley Of Ten Thousand Smokes Region Area ...  

Open Energy Info (EERE)

Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Water Sampling At Valley Of Ten Thousand Smokes Region Area (Keith, Et Al., 1992)...

412

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

413

Factors Influencing Water Heating Energy Use and Peak Demand in a Large Scale Residential Monitoring Study  

E-Print Network (OSTI)

A load research project by the Florida Power Corporation (FPC) is monitoring 200 residences in Central Florida, collecting detailed end-use load data. The monitoring is being performed to better estimate the impact of FPC's load control program, as well as obtain improved appliance energy consumption indexes and load profiles. A portion of the monitoring measures water heater energy use and demand in each home on a 15-minute basis.

Bouchelle, M. P.; Parker, D. S.; Anello, M. T.

2000-01-01T23:59:59.000Z

414

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

415

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

416

Electrical Energy Conservation and Peak Demand Reduction Potential for Buildings in Texas: Preliminary Results  

E-Print Network (OSTI)

This paper presents preliminary results of a study of electrical energy conservation and peak demand reduction potential for the building sector in Texas. Starting from 1980 building stocks and energy use characteristics, technical conservation potentials were calculated relative to frozen energy efficiency stock growth over the 1980-2000 period. The application of conservation supply methodology to Texas utilities is outlined, and then the energy use and peak demand savings, and their associated costs, are calculated using a prototypical building technique. Representative results are presented, for residential and commercial building types, as conservation supply curves for several end use categories; complete results of the study are presented in Ref. 1.

Hunn, B. D.; Baughman, M. L.; Silver, S. C.; Rosenfeld, A. H.; Akbari, H.

1985-01-01T23:59:59.000Z

417

Scoping Study for Demand Respose DFT II Project in Morgantown, WV  

Science Conference Proceedings (OSTI)

This scoping study describes the underlying data resources and an analysis tool for a demand response assessment specifically tailored toward the needs of the Modern Grid Initiatives Demonstration Field Test in Phase II in Morgantown, WV. To develop demand response strategies as part of more general distribution automation, automated islanding and feeder reconfiguration schemes, an assessment of the demand response resource potential is required. This report provides the data for the resource assessment for residential customers and describes a tool that allows the analyst to estimate demand response in kW for each hour of the day, by end-use, season, day type (weekday versus weekend) with specific saturation rates of residential appliances valid for the Morgantown, WV area.

Lu, Shuai; Kintner-Meyer, Michael CW

2008-06-06T23:59:59.000Z

418

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

419

Successful demand-side management  

Science Conference Proceedings (OSTI)

This article is a brief summary of a series of case studies of five publicly-owned utilities that are noted for their success with demand-side management. These utilities are: (1) city of Austin, Texas, (2) Burlington Electric Department in Vermont, (3) Sacramento Municipal Utility District in California, (4) Seattle City Light, and (5) Waverly Light and Power in Iowa. From these case studies, the authors identified a number of traits associated with a successful demand-side management program. These traits are: (1) high rates, (2) economic factors, (3) environmental awareness, (4) state emphasis on integrated resource planning/demand side management, (5) local political support, (6) large-sized utilities, and (7) presence of a champion.

Hadley, S. [Oak Ridge National Laboratory, TN (United States); Flanigan, T. [Results Center, Aspen, CO (United States)

1995-05-01T23:59:59.000Z

420

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.


421

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

422

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

423

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

percent of 2008 summer peak demand (FERC, 2008). Moreover,138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).non-coincident summer peak demand by 157 GW” by 2030, or 14–

Goldman, Charles

2010-01-01T23:59:59.000Z

424

Retail Demand Response in Southwest Power Pool  

E-Print Network (OSTI)

pricing tariffs have a peak demand reduction potential ofneed to reduce summer peak demand that is used to set demandcustomers and a system peak demand of over 43,000 MW. SPP’s

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

425

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

with total Statewide peak demand and on peak days isto examine the electric peak demand related to lighting inDaily) - TOU Savings - Peak Demand Charges - Grid Peak -Low

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

426

Tankless Demand Water Heaters | Department of Energy  

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

Demand Water Heaters Tankless Demand Water Heaters August 19, 2013 - 2:57pm Addthis Illustration of an electric demand water heater. At the top of the image, the heating unit is...

427

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

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

428

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

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

429

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

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

430

EIA projections of coal supply and demand  

SciTech Connect

Contents of this report include: EIA projections of coal supply and demand which covers forecasted coal supply and transportation, forecasted coal demand by consuming sector, and forecasted coal demand by the electric utility sector; and policy discussion.

Klein, D.E.

1989-10-23T23:59:59.000Z

431

Residential Electricity Demand in China -- Can Efficiency Reverse the Growth?  

SciTech Connect

The time when energy-related carbon emissions come overwhelmingly from developed countries is coming to a close. China has already overtaken the United States as the world's leading emitter of greenhouse gas emissions. The economic growth that China has experienced is not expected to slow down significantly in the long term, which implies continued massive growth in energy demand. This paper draws on the extensive expertise from the China Energy Group at LBNL on forecasting energy consumption in China, but adds to it by exploring the dynamics of demand growth for electricity in the residential sector -- and the realistic potential for coping with it through efficiency. This paper forecasts ownership growth of each product using econometric modeling, in combination with historical trends in China. The products considered (refrigerators, air conditioners, fans, washing machines, lighting, standby power, space heaters, and water heating) account for 90percent of household electricity consumption in China. Using this method, we determine the trend and dynamics of demandgrowth and its dependence on macroeconomic drivers at a level of detail not accessible by models of a more aggregate nature. In addition, we present scenarios for reducing residential consumption through efficiency measures defined at the product level. The research takes advantage of an analytical framework developed by LBNL (BUENAS) which integrates end use technology parameters into demand forecasting and stock accounting to produce detailed efficiency scenarios, thus allowing for a technologically realistic assessment of efficiency opportunities specifically in the Chinese context.

Letschert, Virginie; McNeil, Michael A.; Zhou, Nan

2009-05-18T23:59:59.000Z

432

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

433

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

434

Electric Utility Demand-Side Management 1997  

U.S. Energy Information Administration (EIA)

Electric Utility Demand-Side Management 1997 Executive Summary Background Demand-side management (DSM) programs consist of the planning, implementing, and monitoring ...

435

Retail Demand Response in Southwest Power Pool  

E-Print Network (OSTI)

Regulatory Commission (FERC) 2006. “Assessment of DemandRegulatory Commission (FERC) 2007. “Assessment of DemandRegulatory Commission (FERC) 2008a. “Wholesale Competition

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

436

EIA - Annual Energy Outlook 2009 - Electricity Demand  

Gasoline and Diesel Fuel Update (EIA)

data Rate of Electricity Demand Growth Slows, Following the Historical Trend Electricity demand fluctuates in the short term in response to business cycles, weather conditions,...

437

Demand Response as a System Reliability Resource  

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

Demand Response as a System Reliability Resource Title Demand Response as a System Reliability Resource Publication Type Report Year of Publication 2012 Authors Eto, Joseph H.,...

438

Home Network Technologies and Automating Demand Response  

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

electricity generation capacity to meet unrestrained future demand. To address peak electricity use Demand Response (DR) systems are being proposed to motivate reductions in...

439

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

440

Installation and Commissioning Automated Demand Response Systems  

E-Print Network (OSTI)

al: Installation and Commissioning Automated Demand ResponseConference on Building Commissioning: April 22 – 24, 2008al: Installation and Commissioning Automated Demand Response

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

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

Equity Capital Flows and Demand for REITs  

Science Conference Proceedings (OSTI)

This paper examines the shape of the market demand curve for ... Our results do not support a downward demand curve for ... Charleston, IL 61920, USA e-mail: ...

442

Option Value of Electricity Demand Response  

E-Print Network (OSTI)

Oakland CA, December. PJM Demand Side Response WorkingPrice Response Program a PJM Economic Load Response ProgramLoad Response Statistics PJM Demand Response Working Group

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

2005-01-01T23:59:59.000Z

443

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

29 5.6. Peak and hourly demand43 6.6. Peak and seasonal demandthe average percent of peak demand) significantly impact the

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

2008-01-01T23:59:59.000Z

444

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

445

Demand-Side Management Glossary  

Science Conference Proceedings (OSTI)

In recent years, demand-side management (DSM) programs have grown in significance within the U.S. electric power industry. Such rapid growth has resulted in new terms, standards, and vocabulary used by DSM professionals. This report is a first attempt to provide a consistent set of definitions for the expanding DSM terminology.

1992-11-01T23:59:59.000Z

446

Demand Dispatch — Intelligent Demand for a More Efficient Grid  

E-Print Network (OSTI)

This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference therein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed therein do not necessarily state or reflect those of the United States Government or any agency thereof. Demand Dispatch: Intelligent Demand for a More Efficient Grid

Keith Dodrill

2011-01-01T23:59:59.000Z

447

Fuel choice and aggregate energy demand in the commercial sector  

SciTech Connect

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

Cohn, S.

1978-12-01T23:59:59.000Z

448

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

E-Print Network (OSTI)

US 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 Approach Page 1 of 25 US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier

449

The alchemy of demand response: turning demand into supply  

Science Conference Proceedings (OSTI)

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

450

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

451

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

452

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

453

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

454

Demand Response and Risk Management  

Science Conference Proceedings (OSTI)

For several decades, power companies have deployed various types of demand response (DR), such as interruptible contracts, and there is substantial ongoing research and development on sophisticated mechanisms for triggering DR. In this white paper, EPRI discusses the increasing use of electricity DR in the power industry and how this will affect the practice of energy risk management. This paper outlines 1) characteristics of a common approach to energy risk management, 2) the variety of types of DR impl...

2008-12-18T23:59:59.000Z

455

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...

456

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

457

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

458

Questions and Answers - Is vacuum matter? What are ten things...  

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

Here is my top ten list of "Things That Are Not Matter": 1. Light 2. Sound 3. Heat 4. Energy 5. Gravity 6. Time 7. A Rainbow 8. Love 9. Happiness 10. A really good joke Author:...

459

Climatic Variability at Ten Stations Across the United States  

Science Conference Proceedings (OSTI)

Ten stations are chosen for a study of climatic variability in the continental United States, using as the main criteria good geographical distribution, long-period records (since before 1900), and available daily, monthly and annual values of ...

Kevin C. Vining; John F. Griffiths

1985-04-01T23:59:59.000Z

460

Ten scientists named Distinguished Members of Technical Staff  

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

02212012 Ten scientists named Distinguished Members of Technical Staff Anne M Stark, LLNL, (925) 422-9799, stark8@llnl.gov Printer-friendly From left: Dmitry Ryutov, John...

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

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

462

Demand Trading: Measurement, Verification, and Settlement (MVS)  

Science Conference Proceedings (OSTI)

With this report, EPRI's trilogy of publications on demand trading is complete. The first report (1006015), the "Demand Trading Toolkit," documented how to conduct demand trading based on price. The second report (1001635), "Demand Trading: Building Liquidity," focused on the problem of liquidity in the energy industry and developed the Demand Response Resource Bank concept for governing electricity markets based on reliability. The present report focuses on the emerging price/risk partnerships in electr...

2004-03-18T23:59:59.000Z

463

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

refers to “changes in electric usage by end-use customerschanges in customers’ electric usage patterns. Some types ofoff-peak usage is less costly for the electric system and

Goldman, Charles

2010-01-01T23:59:59.000Z

464

Effects of the drought on California electricity supply and demand  

E-Print Network (OSTI)

DEMAND . . . .Demand for Electricity and Power PeakDemand . . • . . ELECTRICITY REQUIREMENTS FOR AGRICULTUREResults . . Coriclusions ELECTRICITY SUPPLY Hydroelectric

Benenson, P.

2010-01-01T23:59:59.000Z

465

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

466

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

467

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

468

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

14 Peak Demand Baselinewinter morning electric peak demand in commercial buildings.California to reduce peak demand during summer afternoons,

Kiliccote, Sila

2010-01-01T23:59:59.000Z

469

Providing Reliability Services through Demand Response: A Prelimnary Evaluation of the Demand Response Capabilities of Alcoa Inc.  

Science Conference Proceedings (OSTI)

Demand response is the largest underutilized reliability resource in North America. Historic demand response programs have focused on reducing overall electricity consumption (increasing efficiency) and shaving peaks but have not typically been used for immediate reliability response. Many of these programs have been successful but demand response remains a limited resource. The Federal Energy Regulatory Commission (FERC) report, 'Assessment of Demand Response and Advanced Metering' (FERC 2006) found that only five percent of customers are on some form of demand response program. Collectively they represent an estimated 37,000 MW of response potential. These programs reduce overall energy consumption, lower green house gas emissions by allowing fossil fuel generators to operate at increased efficiency and reduce stress on the power system during periods of peak loading. As the country continues to restructure energy markets with sophisticated marginal cost models that attempt to minimize total energy costs, the ability of demand response to create meaningful shifts in the supply and demand equations is critical to creating a sustainable and balanced economic response to energy issues. Restructured energy market prices are set by the cost of the next incremental unit of energy, so that as additional generation is brought into the market, the cost for the entire market increases. The benefit of demand response is that it reduces overall demand and shifts the entire market to a lower pricing level. This can be very effective in mitigating price volatility or scarcity pricing as the power system responds to changing demand schedules, loss of large generators, or loss of transmission. As a global producer of alumina, primary aluminum, and fabricated aluminum products, Alcoa Inc., has the capability to provide demand response services through its manufacturing facilities and uniquely through its aluminum smelting facilities. For a typical aluminum smelter, electric power accounts for 30% to 40% of the factory cost of producing primary aluminum. In the continental United States, Alcoa Inc. currently owns and/or operates ten aluminum smelters and many associated fabricating facilities with a combined average load of over 2,600 MW. This presents Alcoa Inc. with a significant opportunity to respond in areas where economic opportunities exist to help mitigate rising energy costs by supplying demand response services into the energy system. This report is organized into seven chapters. The first chapter is the introduction and discusses the intention of this report. The second chapter contains the background. In this chapter, topics include: the motivation for Alcoa to provide demand response; ancillary service definitions; the basics behind aluminum smelting; and a discussion of suggested ancillary services that would be particularly useful for Alcoa to supply. Chapter 3 is concerned with the independent system operator, the Midwest ISO. Here the discussion examines the evolving Midwest ISO market structure including specific definitions, requirements, and necessary components to provide ancillary services. This section is followed by information concerning the Midwest ISO's classifications of demand response parties. Chapter 4 investigates the available opportunities at Alcoa's Warrick facility. Chapter 5 involves an in-depth discussion of the regulation service that Alcoa's Warrick facility can provide and the current interactions with Midwest ISO. Chapter 6 reviews future plans and expectations for Alcoa providing ancillary services into the market. Last, chapter 7, details the conclusion and recommendations of this paper.

Starke, Michael R [ORNL; Kirby, Brendan J [ORNL; Kueck, John D [ORNL; Todd, Duane [Alcoa; Caulfield, Michael [Alcoa; Helms, Brian [Alcoa

2009-02-01T23:59:59.000Z

470

Building Energy Software Tools Directory : Demand Response Quick...  

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

Demand Response Quick Assessment Tool Back to Tool Demand response quick assessment tool screenshot Demand response quick assessment tool screenshot Demand response quick...

471

Price-elastic demand in deregulated electricity markets  

E-Print Network (OSTI)

by the amount of electricity demand that is settled forward.unresponsive demand side, electricity demand has to be metxed percentage of overall electricity demand. The ISO, thus,

Siddiqui, Afzal S.

2003-01-01T23:59:59.000Z

472

Automated Demand Response Strategies and Commissioning Commercial Building Controls  

E-Print Network (OSTI)

Braun (Purdue). 2004. Peak demand reduction from pre-coolingthe average and maximum peak demand savings. The electricityuse charges, demand ratchets, peak demand charges, and other

Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Linkugel, Eric

2006-01-01T23:59:59.000Z

473

Potential For Energy, Peak Demand, and Water Savings in California Tomato Processing Facilities  

E-Print Network (OSTI)

Tomato processing is a major component of California's food industry. Tomato processing is extremely energy intensive, with the processing season coinciding with the local electrical utility peak period. Significant savings are possible in the electrical energy, peak demand, natural gas consumption, and water consumption of facilities. The electrical and natural gas energy usage and efficiency measures will be presented for a sample of California tomato plants. A typical end-use distribution of electrical energy in these plants will be shown. Results from potential electrical efficiency, demand response, and natural gas efficiency measures that have applications in tomato processing facilities will be presented. Additionally, water conservation measures and the associated savings will be presented. It is shown that an estimated electrical energy savings of 12.5%, electrical demand reduction of 17.2%, natural gas savings of 6.0%, and a fresh water usage reduction of 15.6% are achievable on a facility-wide basis.

Trueblood, A. J.; Wu, Y. Y.; Ganji, A. R.

2013-01-01T23:59:59.000Z

474

Demand Response Valuation Frameworks Paper  

Science Conference Proceedings (OSTI)

While there is general agreement that demand response (DR) is a valued component in a utility resource plan, there is a lack of consensus regarding how to value DR. Establishing the value of DR is a prerequisite to determining how much and what types of DR should be implemented, to which customers DR should be targeted, and a key determinant that drives the development of economically viable DR consumer technology. Most approaches for quantifying the value of DR focus on changes in utility system revenue requirements based on resource plans with and without DR. This ''utility centric'' approach does not assign any value to DR impacts that lower energy and capacity prices, improve reliability, lower system and network operating costs, produce better air quality, and provide improved customer choice and control. Proper valuation of these benefits requires a different basis for monetization. The review concludes that no single methodology today adequately captures the wide range of benefits and value potentially attributed to DR. To provide a more comprehensive valuation approach, current methods such as the Standard Practice Method (SPM) will most likely have to be supplemented with one or more alternative benefit-valuation approaches. This report provides an updated perspective on the DR valuation framework. It includes an introduction and four chapters that address the key elements of demand response valuation, a comprehensive literature review, and specific research recommendations.

Heffner, Grayson

2009-02-01T23:59:59.000Z

475

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

476

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

477

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.

478

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

479

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

480

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

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

Distillate Demand Strong in December 1999  

Gasoline and Diesel Fuel Update (EIA)

5% higher than in the prior year, due mainly to diesel demand growth, since warm weather kept heating oil demand from growing much. Last December, when stocks dropped below...

482

Solar in Demand | Department of Energy  

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

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...

483

Energy Basics: Tankless Demand Water Heaters  

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

only as needed and without the use of a storage tank. They don't produce the standby energy losses associated with storage water heaters. How Demand Water Heaters Work Demand...

484

Propane Demand by Sector - Energy Information Administration  

U.S. Energy Information Administration (EIA)

In order to understand markets you also have to look at supply and demand. First, demand or who uses propane. For the most part, the major components of propane ...

485

Travel Behavior and Demand Analysis and Prediction  

E-Print Network (OSTI)

and Demand Analysis and Prediction Konstadinos G. Goulias University of California Santa Barbara, Santa Barbara, CA, USA

Goulias, Konstadinos G

2007-01-01T23:59:59.000Z

486

Forecasting the demand for commercial telecommunications satellites  

Science Conference Proceedings (OSTI)

This paper summarizes the key elements of a forecast methodology for predicting demand for commercial satellite services and the resulting demand for satellite hardware and launches. The paper discusses the characterization of satellite services into more than a dozen applications (including emerging satellite Internet applications) used by Futron Corporation in its forecasts. The paper discusses the relationship between demand for satellite services and demand for satellite hardware

Carissa Bryce Christensen; Carie A. Mullins; Linda A. Williams

2001-01-01T23:59:59.000Z

487

The End-Use Technology Assessment Project: A Load-Shape Analysis of Ground Source Heat Pumps and Good Cents Homes  

Science Conference Proceedings (OSTI)

Interest is growing in end-use technology applications that promote overall energy efficiency through increased electricity use. This study will help utilities understand the impacts of such applications by providing load-shape information on ground source heat pumps as well as energy-efficient appliances promoted through Good Cents Homes programs. This report is available only to funders of Program 101A or 101.001. Funders may download this report at http://my.primen.com/Applications/DE/Community/index...

1995-05-27T23:59:59.000Z

488

Industrial sector end use. Energy Consumption Data Base (ECDB) for 1975 and 1976. Volume I. Summary of 1976 results. Final report  

SciTech Connect

This report is the summary document of a three-volume report. It contains an introduction followed by tables of data containing the following information: 1976 national energy consumption by industry fuel type, and end use; 1976 regional energy consumption by industry fuel type, and census division; 1976 regional energy consumption by industry fuel type, and federal regions; 1976 regional energy consumption by industry fuel type, and PAD district; 1976 state energy consumption by industry fuel type, and by state. (PLG)

1980-12-15T23:59:59.000Z

489

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.

490

Forecasting Uncertain Hotel Room Demand  

E-Print Network (OSTI)

Economic systems are characterized by increasing uncertainty in their dynamics. This increasing uncertainty is likely to incur bad decisions that can be costly in financial terms. This makes forecasting of uncertain economic variables an instrumental activity in any organization. This paper takes the hotel industry as a practical application of forecasting using the Holt-Winters method. The problem here is to forecast the uncertain demand for rooms at a hotel for each arrival day. Forecasting is part of hotel revenue management system whose objective is to maximize the revenue by making decisions regarding when to make rooms available for customers and at what price. The forecast approach discussed in this paper is based on quantitative models and does not incorporate management expertise. Even though, forecast results are found to be satisfactory for certain days, this is not the case for other arrival days. It is believed that human judgment is important when dealing with ...

Mihir Rajopadhye Mounir; Mounir Ben Ghaliay; Paul P. Wang; Timothy Baker; Craig V. Eister

2001-01-01T23:59:59.000Z

491

Forecasting demand of commodities after natural disasters  

Science Conference Proceedings (OSTI)

Demand forecasting after natural disasters is especially important in emergency management. However, since the time series of commodities demand after natural disasters usually has a great deal of nonlinearity and irregularity, it has poor prediction ... Keywords: ARIMA, Demand forecasting, EMD, Emergency management, Natural disaster

Xiaoyan Xu; Yuqing Qi; Zhongsheng Hua

2010-06-01T23:59:59.000Z

492

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

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

493

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

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

494

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

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

495

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

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

496

FINAL STAFF FORECAST OF 2008 PEAK DEMAND  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION FINAL STAFF FORECAST OF 2008 PEAK DEMAND STAFFREPORT June 2007 CEC-200 of the information in this paper. #12;Abstract This document describes staff's final forecast of 2008 peak demand demand forecasts for the respective territories of the state's three investor-owned utilities (IOUs

497

Leveraging gamification in demand dispatch systems  

Science Conference Proceedings (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

498

Ups and downs of demand limiting  

SciTech Connect

Electric power load management by limiting power demand can be used for energy conservation. Methods for affecting demand limiting, reducing peak usage in buildings, particularly usage for heating and ventilating systems, and power pricing to encourage demand limiting are discussed. (LCL)

Pannkoke, T.

1976-12-01T23:59:59.000Z

499

ORNL Residential Reference House Energy Demand model (ORNL-RRHED). Volume 4. Case studies  

Science Conference Proceedings (OSTI)

This report describes the use and structure of the ORNL Residential Reference House Energy Demand Model (RRHED). RRHED is a computer-based engineering-economic end-use simulation model which forecasts energy demand based on a detailed evaluation of how households use energy for particular appliances. The report is organized into four volumes. The first volume provides an overview of the modeling approach and gives a short summary of the material presented in the other three volumes. The second volume is a user reference guide which provides the details necessary for users of the model to run the code and make changes to fit their particular application. Volume 3 presents the basic theoretical rationale for the RRHED model structure. The last volume reports on the application of the model to the analysis of two different kinds of issues: one is the examination of conservation policy impacts and the other is the forecasting of electricity demand in a need for power assessment. The report has two major objectives. The first is to provide a reader with little background in end-use modeling with an introduction to how the RRHED model works. The second is to provide the details needed by a user of the model to understand not only the theory behind the model specification, but also the structure of the code. This information will allow for the modification of subroutines to fit particular applications.

Hamblin, D.M.; Thomas, B. Jr.; Maddigan, R.J.; Forman, C.W. Jr.; Bibo, L.J.; McKeehan, K.M.

1986-02-01T23:59:59.000Z

500

High Plains Severe Weather—Ten Years After  

Science Conference Proceedings (OSTI)

More than a decade ago, a study was published that identified a short list of precursor conditions for severe thunderstorms on the High Plains of the United States. The present study utilizes data from the summer months of ten convective seasons ...

John F. Weaver; Nolan J. Doesken

1991-09-01T23:59:59.000Z