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Note: This page contains sample records for the topic "total electricity demand" 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

"Table A16. Components of Total Electricity Demand by Census Region, Industry"  

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

6. Components of Total Electricity Demand by Census Region, Industry" 6. Components of Total Electricity Demand by Census Region, Industry" " Group, and Selected Industries, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," "," "," "," "," " " "," "," "," "," ","Sales and/or"," ","RSE" "SIC"," "," ","Transfers","Total Onsite","Transfers","Net Demand for","Row" "Code(a)","Industry Groups and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)","Factors"

2

Table A19. Components of Total Electricity Demand by Census Region and  

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

Components of Total Electricity Demand by Census Region and" Components of Total Electricity Demand by Census Region and" " Economic Characteristics of the Establishment, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)","Generation(c)","Offsite","Net Demand(d)","Factors" ,"Total United States" "RSE Column Factors:",0.5,1.4,1.3,1.9,0.5 "Value of Shipments and Receipts" "(million dollars)"

3

Table A26. Components of Total Electricity Demand by Census Region, Census Di  

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

Components of Total Electricity Demand by Census Region, Census Division, and" Components of Total Electricity Demand by Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)","Generation(c)","Offsite","Net Demand(d)","Factors" ,"Total United States" "RSE Column Factors:",0.5,2.1,1.2,2,0.4 "Value of Shipments and Receipts"

4

"Table A25. Components of Total Electricity Demand by Census Region, Census Division, Industry"  

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

Components of Total Electricity Demand by Census Region, Census Division, Industry" Components of Total Electricity Demand by Census Region, Census Division, Industry" " Group, and Selected Industries, 1994" " (Estimates in Million Kilowatthours)" " "," "," "," "," "," "," "," " " "," "," "," "," ","Sales and/or"," ","RSE" "SIC"," "," ","Transfers","Total Onsite","Transfers","Net Demand for","Row" "Code(a)","Industry Group and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)","Factors"

5

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

6

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)

7

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

8

EIA - Annual Energy Outlook 2008 - Electricity Demand  

Gasoline and Diesel Fuel Update (EIA)

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

9

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

10

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

Figure 34. Regional electricity cost duration curves in 2010especially focus on electricity costs and grid compositionrelatively higher electricity costs. If electricity demand

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

11

SUMMER 2007 ELECTRICITY SUPPLY AND DEMAND OUTLOOK  

E-Print Network (OSTI)

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

12

Electricity demand, GDP and employment: evidence from Italy  

Science Journals Connector (OSTI)

This paper applies time series methodologies to examine the causal relationship among electricity demand, real per capita GDP and total labor force for Italy from 1970 to 2009. After a brief introduction, a su...

Cosimo Magazzino

2014-03-01T23:59:59.000Z

13

Electricity Demand and Energy Consumption Management System  

E-Print Network (OSTI)

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

Sarmiento, Juan Ojeda

2008-01-01T23:59:59.000Z

14

Electricity demand analysis - unconstrained vs constrained scenarios  

Science Journals Connector (OSTI)

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

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

2003-01-01T23:59:59.000Z

15

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

Designing Markets for Electricity, Wiley-IEEE Press. CEC (in Major Drivers in U.S. Electricity Markets, NREL/CP-620-and fuel efficiency and electricity demand assumptions used

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

16

Electric Utility Demand-Side Evaluation Methodologies  

E-Print Network (OSTI)

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

Treadway, N.

17

Demand Response and Electric Grid Reliability  

E-Print Network (OSTI)

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

Wattles, P.

2012-01-01T23:59:59.000Z

18

Utility Sector Impacts of Reduced Electricity Demand  

SciTech Connect

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

Coughlin, Katie

2014-12-01T23:59:59.000Z

19

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

E-Print Network (OSTI)

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

Cappers, Peter

2009-01-01T23:59:59.000Z

20

Electricity demand and supply projections for Indian economy  

Science Journals Connector (OSTI)

The present paper deals with an econometric model to forecast future electricity requirements for various sectors of Indian economy. Following the analysis of time series of sectoral GDPs, number of consumers in various sectors and price indices of electricity, a logarithmic linear regression model has been developed to forecast long-term demand of electricity up to the year 2045. Using the historical GDP growth in various sectors and the corresponding electricity consumption for the period 1971-2005, it is predicted that the total electricity demand will be 5000 billion kWh, against a supply of 1500 billion kWh in the year 2045. This may lead to a disastrous situation for the country unless drastic policy measures are taken to improve the supply side as well as to reduce demand.

Subhash Mallah; N.K. Bansal

2009-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

Tool Improves Electricity Demand Predictions to Make More Room...  

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

Tool Improves Electricity Demand Predictions to Make More Room for Renewables Tool Improves Electricity Demand Predictions to Make More Room for Renewables October 3, 2011 -...

22

Table E13.1. Electricity: Components of Net Demand, 1998  

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

1. Electricity: Components of Net Demand, 1998;" 1. Electricity: Components of Net Demand, 1998;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Electricity Components;" " Unit: Million Kilowatthours." " ",," "," ",," " ,,,,"Sales and","Net Demand","RSE" "Economic",,,"Total Onsite","Transfers","for","Row" "Characteristic(a)","Purchases","Transfers In(b)","Generation(c)","Offsite","Electricity(d)","Factors" ,"Total United States"

23

New Zealand Energy Data: Electricity Demand and Consumption | OpenEI  

Open Energy Info (EERE)

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

24

What is a High Electric Demand Day?  

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

This presentation by T. McNevin of the New Jersey Bureau of Air Quality Planning was part of the July 2008 Webcast sponsored by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Weatherization and Intergovernmental Program Clean Energy and Air Quality Integration Initiative that was titled Role of Energy Efficiency and Renewable Energy in Improving Air Quality and Addressing Greenhouse Gas Reduction Goals on High Electric Demand Days.

25

Table 11.2 Electricity: Components of Net Demand, 2010;  

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

2 Electricity: Components of Net Demand, 2010; 2 Electricity: Components of Net Demand, 2010; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Electricity Components; Unit: Million Kilowatthours. Sales and Net Demand Economic Total Onsite Transfers for Characteristic(a) Purchases Transfers In(b) Generation(c) Offsite Electricity(d) Total United States Value of Shipments and Receipts (million dollars) Under 20 91,909 Q 1,406 194 93,319 20-49 86,795 81 2,466 282 89,060 50-99 90,115 215 2,593 1,115 91,808 100-249 124,827 347 11,375 5,225 131,324 250-499 116,631 2,402 24,079 5,595 137,516 500 and Over 225,242 6,485 91,741 20,770 302,699 Total 735,520 9,728 133,661 33,181 845,727 Employment Size Under 50

26

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network (OSTI)

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

Levy, Roger

2014-01-01T23:59:59.000Z

27

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network (OSTI)

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

Levy, Roger

2014-01-01T23:59:59.000Z

28

Table 11.1 Electricity: Components of Net Demand, 2010;  

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

1.1 Electricity: Components of Net Demand, 2010; 1.1 Electricity: Components of Net Demand, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Electricity Components; Unit: Million Kilowatthours. Total Sales and Net Demand NAICS Transfers Onsite Transfers for Code(a) Subsector and Industry Purchases In(b) Generation(c) Offsite Electricity(d) Total United States 311 Food 75,652 21 5,666 347 80,993 3112 Grain and Oilseed Milling 16,620 0 3,494 142 19,972 311221 Wet Corn Milling 7,481 0 3,213 14 10,680 31131 Sugar Manufacturing 1,264 0 1,382 109 2,537 3114 Fruit and Vegetable Preserving and Specialty Foods 9,258 0 336 66 9,528 3115 Dairy Products 9,585 2 38 22 9,602 3116 Animal Slaughtering and Processing 20,121 15 19 0 20,155 312 Beverage and Tobacco Products

29

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network (OSTI)

with residential electric resistance water heater solar system backup electric resistance water heaters. Anheaters require electric resistance backup water heaters.

Levy, Roger

2014-01-01T23:59:59.000Z

30

Electricity Markets Meet the Home through Demand Response Lazaros Gkatzikis  

E-Print Network (OSTI)

Electricity Markets Meet the Home through Demand Response Lazaros Gkatzikis CERTH, University Hegde, Laurent Massouli´e Technicolor Paris Research Lab Paris, France Abstract-- Demand response (DR the alternative option of dynamic demand adaptation. In this direction, demand response (DR) programs provide

31

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

32

Benefits of Demand Response in Electricity Markets and Recommendations...  

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

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...

33

Electricity demand as frequency controlled reserves, ENS (Smart...  

Open Energy Info (EERE)

ENS (Smart Grid Project) Jump to: navigation, search Project Name Electricity demand as frequency controlled reserves, ENS Country Denmark Coordinates 56.26392, 9.501785...

34

Electricity demand as frequency controlled reserves, ForskEL...  

Open Energy Info (EERE)

ForskEL (Smart Grid Project) Jump to: navigation, search Project Name Electricity demand as frequency controlled reserves, ForskEL Country Denmark Coordinates 56.26392,...

35

Topics in Residential Electric Demand Response.  

E-Print Network (OSTI)

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

Horowitz, Shira R.

2012-01-01T23:59:59.000Z

36

Price Responsive Demand in New York Wholesale Electricity Market using  

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

Price Responsive Demand in New York Wholesale Electricity Market using Price Responsive Demand in New York Wholesale Electricity Market using OpenADR Title Price Responsive Demand in New York Wholesale Electricity Market using OpenADR Publication Type Report LBNL Report Number LBNL-5557E Year of Publication 2012 Authors Kim, Joyce Jihyun, and Sila Kiliccote Date Published 06/2012 Publisher LBNL/NYSERDA Keywords commercial, demand response, dynamic pricing, mandatory hourly pricing, open automated demand response, openadr, pilot studies & implementation, price responsive demand Abstract In New York State, the default electricity pricing for large customers is Mandatory Hourly Pricing (MHP), which is charged based on zonal day-ahead market price for energy. With MHP, retail customers can adjust their building load to an economically optimal level according to hourly electricity prices. Yet, many customers seek alternative pricing options such as fixed rates through retail access for their electricity supply. Open Automated Demand Response (OpenADR) is an XML (eXtensible Markup Language) based information exchange model that communicates price and reliability information. It allows customers to evaluate hourly prices and provide demand response in an automated fashion to minimize electricity costs. This document shows how OpenADR can support MHP and facilitate price responsive demand for large commercial customers in New York City.

37

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

energy storage and demand management can complement solarwith energy storage to firm the resource, or solar thermaland solar generation. And demand response or energy storage

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

38

Photo-Ionic Cells: Two Solutions to Store Solar Energy and Generate Electricity on Demand  

Science Journals Connector (OSTI)

Photo-Ionic Cells: Two Solutions to Store Solar Energy and Generate Electricity on Demand ... potential of solar energy all over the world is many times larger than the current total primary energy demanded. ... The magnitudes of the free energies derived from formal potentials are detd. ...

Manuel A. Mndez; Pekka Peljo; Michel D. Scanlon; Heron Vrubel; Hubert H. Girault

2014-02-27T23:59:59.000Z

39

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

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

in U.S. Electricity Markets: Empirical Evidence in U.S. Electricity Markets: Empirical Evidence Demand Response in U.S. Electricity Markets: Empirical Evidence The work described in this paper was funded by the Office of Electricity Delivery and Energy Reliability, Permitting, Siting and Analysis of the U.S. Department of Energy under contract No. DE-AC02-05CH11231. The authors are solely responsible for any omissions or errors contained herein. Demand Response in U.S. Electricity Markets: Empirical Evidence More Documents & Publications Demand Response National Trends: Implications for the West? 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)

40

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network (OSTI)

widely differing control technologies, notification options,Electric Reliability Technology, LBNL, Joseph Eto E. Availability F. Technology Proposed Residential Large

Levy, Roger

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

Assumptions to the Annual Energy Outlook 2000 - Electricity Market Demand  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module (EMM) represents the planning, operations, and pricing of electricity in the United States. It is composed of four primary submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. In addition, nonutility generation and supply and electricity transmission and trade are represented in the planning and dispatching submodules. Electricity Market Module (EMM) represents the planning, operations, and pricing of electricity in the United States. It is composed of four primary submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. In addition, nonutility generation and supply and electricity transmission and trade are represented in the planning and dispatching submodules. Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. The major assumptions are summarized below.

42

Implications of Low Electricity Demand Growth  

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

Conference July 14, 2014 | Washington, DC Jim Diefenderfer, Director, Office of Electricity, Coal, Nuclear, & Renewables Analysis U.S. Energy Information Administration...

43

U.S. electric utility demand-side management 1995  

SciTech Connect

The US Electric Utility Demand-Side Management report is prepared by the Coal and Electric Data and Renewables Division; Office of Coal, Nuclear, Electric and Alternative Fuels; Energy Information Administration (EIA); US Department of Energy. The report presents comprehensive information on electric power industry demand-side management (DSM) activities in the US at the national, regional, and utility levels. The objective of the publication is to provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it relates to the US electric power industry. The first chapter, ``Profile: US Electric Utility Demand-Side Management``, presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions and costs attributable to DSM. 9 figs., 24 tabs.

NONE

1997-01-01T23:59:59.000Z

44

The Impact of Climate Change on Electricity Demand in Thailand  

E-Print Network (OSTI)

Climate change is expected to lead to changes in ambient temperature, wind speed, humidity, precipitation and cloud cover. As electricity demand is closely influenced by these climatic variables, there is likely to be ...

Parkpoom, Suchao Jake

2008-01-01T23:59:59.000Z

45

Incentive effects of paying demand response in wholesale electricity markets  

Science Journals Connector (OSTI)

Recently issued U.S. Federal Energy Regulatory Commission regulations require comparable treatment of demand reduction and generation in the wholesale electric market so that they are compensated at the same mark...

Hung-po Chao; Mario DePillis

2013-06-01T23:59:59.000Z

46

The residential demand for electricity in New England,  

E-Print Network (OSTI)

The residential demand for electricity, studied on the national level for many years, is here investigated on the regional level. A survey of the literature is first presented outlining past econometric work in the field ...

Levy, Paul F.

1973-01-01T23:59:59.000Z

47

Innovative and Progressive Electric Utility Demand-Side Management Strategies  

E-Print Network (OSTI)

to as Demand-Side Management (DSM) and are extremely rigorous in scope. Electric utilities have pursued many different DSM policies and strategies during the past decade. These programs have addressed various technologies and have included rebates for efficient...

Epstein, G. J.; Fuller, W. H.

48

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

problems, Electric Power Systems Research, 73(2): p. 169-problems, Electric Power Systems Research, 77(3-4): p. 212-decomposition, Electric Power Systems Research, 77(7): p.

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

49

Turkey opens electricity markets as demand grows  

SciTech Connect

Turkey's growing power market has attracted investors and project developers for over a decade, yet their plans have been dashed by unexpected political or financial crises or, worse, obstructed by a lengthy bureaucratic approval process. Now, with a more transparent retail electricity market, government regulators and investors are bullish on Turkey. Is Turkey ready to turn the power on? This report closely examine Turkey's plans to create a power infrastructure capable of providing the reliable electricity supplies necessary for sustained economic growth. It was compiled with on-the-ground research and extensive interview with key industrial and political figures. Today, hard coal and lignite account for 21% of Turkey's electricity generation and gas-fired plants account for 50%. The Alfin Elbistan-B lignite-fired plant has attracted criticism for its lack of desulfurization units and ash dam facilities that have tarnished the industry's image. A 1,100 MW hard-coal fired plant using supercritical technology is under construction. 9 figs., 1 tab.

McKeigue, J.; Da Cunha, A.; Severino, D. [Global Business Reports (United States)

2009-06-15T23:59:59.000Z

50

Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast  

E-Print Network (OSTI)

Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast Energy Demand ........................................................................ 28 Possible Future Trends for Plug-in Hybrid Electric Vehicles .............................................................. 23 Electricity Demand Growth in the West

51

U.S. electric utility demand-side management 1996  

SciTech Connect

The US Electric Utility Demand-Side Management report presents comprehensive information on electric power industry demand-side management (DSM) activities in the US at the national, regional, and utility levels. The objective of the publication is to provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it related to the US electric power industry. The first chapter, ``Profile: U.S. Electric Utility Demand-Side Management,`` presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions and costs attributable to DSM. 9 figs., 24 tabs.

NONE

1997-12-01T23:59:59.000Z

52

Sixth Northwest Conservation and Electric Power Plan Appendix H: Demand Response  

E-Print Network (OSTI)

Sixth Northwest Conservation and Electric Power Plan Appendix H: Demand Response Introduction..................................................................................................................................... 1 Demand Response in the Council's Fifth Power Plan......................................................................................................................... 3 Estimate of Potential Demand Response

53

Demand response in wholesale electricity markets: the choice of customer baseline  

Science Journals Connector (OSTI)

Given a hybrid electricity market structure, demand response (DR) in wholesale electricity markets depends ... counterfactual consumption levels that would have prevailed without demand-response programs. However...

Hung-po Chao

2011-02-01T23:59:59.000Z

54

Electrical power distribution control methods, electrical energy demand monitoring methods, and power management devices  

DOE Patents (OSTI)

Electrical power distribution control methods, electrical energy demand monitoring methods, and power management devices are described. In one aspect, an electrical power distribution control method includes providing electrical energy from an electrical power distribution system, applying the electrical energy to a load, providing a plurality of different values for a threshold at a plurality of moments in time and corresponding to an electrical characteristic of the electrical energy, and adjusting an amount of the electrical energy applied to the load responsive to an electrical characteristic of the electrical energy triggering one of the values of the threshold at the respective moment in time.

Chassin, David P. (Pasco, WA); Donnelly, Matthew K. (Kennewick, WA); Dagle, Jeffery E. (Richland, WA)

2006-12-12T23:59:59.000Z

55

Risk-based bidding of large electric utilities using Information Gap Decision Theory considering demand response  

Science Journals Connector (OSTI)

Abstract The present study presents a new risk-constrained bidding strategy formulation of large electric utilities in, presence of demand response programs. The considered electric utility consists of generation facilities, along with a retailer part, which is responsible for supplying associated demands. The total profit of utility comes from participating in day-ahead energy markets and selling energy to corresponding consumers via retailer part. Different uncertainties, such as market price, affect the profit of the utility. Therefore, here, attempts are made to make use of Information Gap Decision Theory (IGDT) to obtain a robust scheduling method against the unfavorable deviations of the market prices. Implementing demand response programs sounds attractive for the consumers through providing some incentives in one hand, and it improves the risk hedging capability of the utility on the other hand. The proposed method is applied to a test system and effect of demand response programs is investigated on the total profit of the utility.

M. Kazemi; B. Mohammadi-Ivatloo; M. Ehsan

2014-01-01T23:59:59.000Z

56

Demand or No Demand: Electrical Rates for Standard 90.1-2010  

SciTech Connect

ASHRAE is developing the 2010 version of Standard 90.1 with the goal of reaching 30% savings beyond the 2004 edition of the standard. Economics are used to inform the process of setting criteria and the assumed electricity rates are crucial to these calculations. Previously the committee used national average electrical rates in the criteria setting but recently a number of voices have been heard in support of using demand rates instead. This article explores the issues surrounding the use of a pure consumption rate vs. the use of demand rates and looks at the implications for HVAC equipment efficiency.

Jarnagin, Ronald E.; McBride, Merle F.; Trueman, Cedric; Liesen, Richard J.

2008-04-30T23:59:59.000Z

57

Electricity demand as frequency controlled reserves, ENS (Smart Grid  

Open Energy Info (EERE)

Electricity demand as frequency controlled reserves, ENS (Smart Grid Electricity demand as frequency controlled reserves, ENS (Smart Grid Project) Jump to: navigation, search Project Name Electricity demand as frequency controlled reserves, ENS Country Denmark Coordinates 56.26392°, 9.501785° 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":56.26392,"lon":9.501785,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

58

Progress towards Managing Residential Electricity Demand: Impacts of  

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

Progress towards Managing Residential Electricity Demand: Impacts of Progress towards Managing Residential Electricity Demand: Impacts of Standards and Labeling for Refrigerators and Air Conditioners in India Title Progress towards Managing Residential Electricity Demand: Impacts of Standards and Labeling for Refrigerators and Air Conditioners in India Publication Type Conference Paper Refereed Designation Unknown LBNL Report Number LBNL-2322E Year of Publication 2009 Authors McNeil, Michael A., and Maithili Iyer Date Published 06/2009 Keywords Air Conditioners, Appliance Efficiency, appliance energy efficiency, energy efficiency, greenhouse gas emissions, india, Labels, MEPS, refrigerators, Standards and labeling URL https://isswprod.lbl.gov/library/view-docs/public/output/rpt77250.PDF Refereed Designation Unknown Attachment Size

59

\\{HEMSs\\} and enabled demand response in electricity market: An overview  

Science Journals Connector (OSTI)

Abstract Traditional electricity grid offers demand side management (DSM) programs for industrial plants and commercial buildings; there is no such program for residential consumers because of the lack of effective automation tools and efficient information and communication technologies (ICTs). Smart Grid is, by definition, equipped with modern automation tools such as home energy management system (HEMS), and ICTs. HEMS is an intelligent system that performs planning, monitoring and control functions of the energy utilization within premises. It is intended to offer desirable demand response according to system conditions and price value signaled by the utility. HEMS enables smart appliances to counter demand response programs according to the comfort level and priority set by the consumer. Demand response can play a key role to ensure sustainable and reliable electricity supply by reducing future generation cost, electricity prices, CO2 emission and electricity consumption at peak times. This paper focuses on the review of \\{HEMSs\\} and enabled demand response (DR) programs in various scenarios as well as incorporates various DR architectures and models employed in the smart grid. A comprehensive case study along with simulations and numerical analysis has also been presented.

Aftab Ahmed Khan; Sohail Razzaq; Asadullah Khan; Fatima Khursheed; Owais

2015-01-01T23:59:59.000Z

60

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

Palm Springs solar insolation, and California electricityConcentrating Solar Power in California, NREL/SR-550-39291,generation from wind and solar in California could be very

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

Distributed Load Demand Scheduling in Smart Grid to Minimize Electricity Generation Cost  

E-Print Network (OSTI)

is to perform demand side management (DSM) [1], which aims at matching the consum- ers' electricity demand between electricity consumption and generation. On the consumption side, electric demand ramps upDistributed Load Demand Scheduling in Smart Grid to Minimize Electricity Generation Cost Siyu Yue

Pedram, Massoud

62

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

natural gas-fired power plant heat rates and generation,natural gas-fired power plant heat rates and generation,natural gas-fired power plants Total incremental generation

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

63

Climate, extreme heat, and electricity demand in California  

SciTech Connect

Climate projections from three atmosphere-ocean climate models with a range of low to mid-high temperature sensitivity forced by the Intergovernmental Panel for Climate Change SRES higher, middle, and lower emission scenarios indicate that, over the 21st century, extreme heat events for major cities in heavily air-conditioned California will increase rapidly. These increases in temperature extremes are projected to exceed the rate of increase in mean temperature, along with increased variance. Extreme heat is defined here as the 90 percent exceedance probability (T90) of the local warmest summer days under the current climate. The number of extreme heat days in Los Angeles, where T90 is currently 95 F (32 C), may increase from 12 days to as many as 96 days per year by 2100, implying current-day heat wave conditions may last for the entire summer, with earlier onset. Overall, projected increases in extreme heat under the higher A1fi emission scenario by 2070-2099 tend to be 20-30 percent higher than those projected under the lower B1 emission scenario, ranging from approximately double the historical number of days for inland California cities (e.g. Sacramento and Fresno), up to four times for previously temperate coastal cities (e.g. Los Angeles, San Diego). These findings, combined with observed relationships between high temperature and electricity demand for air-conditioned regions, suggest potential shortfalls in transmission and supply during T90 peak electricity demand periods. When the projected extreme heat and peak demand for electricity are mapped onto current availability, maintaining technology and population constant only for demand side calculations, we find the potential for electricity deficits as high as 17 percent. Similar increases in extreme heat days are suggested for other locations across the U.S. southwest, as well as for developing nations with rapidly increasing electricity demands. Electricity response to recent extreme heat events, such as the July 2006 heat wave in California, suggests that peak electricity demand will challenge current supply, as well as future planned supply capacities when population and income growth are taken into account.

Miller, N.L.; Hayhoe, K.; Jin, J.; Auffhammer, M.

2008-04-01T23:59:59.000Z

64

THE ROLE OF BUILDING TECHNOLOGIES IN REDUCING AND CONTROLLING PEAK ELECTRICITY DEMAND  

E-Print Network (OSTI)

LBNL-49947 THE ROLE OF BUILDING TECHNOLOGIES IN REDUCING AND CONTROLLING PEAK ELECTRICITY DEMAND? ..................................... 8 What are the seasonal aspects of electric peak demand?............................ 9 What because of the California electricity crisis (Borenstein 2001). Uncertainties surrounding the reliability

65

Stackelberg Game based Demand Response for At-Home Electric Vehicle Charging  

E-Print Network (OSTI)

1 Stackelberg Game based Demand Response for At-Home Electric Vehicle Charging Sung-Guk Yoon Member, which is called demand response. Under demand response, retailers determine their electricity prices cost solution and the result of the equal- charging scheme. Index Terms--demand response, electric

Bahk, Saewoong

66

Exponential smoothing with covariates applied to electricity demand forecast  

Science Journals Connector (OSTI)

Exponential smoothing methods are widely used as forecasting techniques in industry and business. Their usual formulation, however, does not allow covariates to be used for introducing extra information into the forecasting process. In this paper, we analyse an extension of the exponential smoothing formulation that allows the use of covariates and the joint estimation of all the unknowns in the model, which improves the forecasting results. The whole procedure is detailed with a real example on forecasting the daily demand for electricity in Spain. The time series of daily electricity demand contains two seasonal patterns: here the within-week seasonal cycle is modelled as usual in exponential smoothing, while the within-year cycle is modelled using covariates, specifically two harmonic explanatory variables. Calendar effects, such as national and local holidays and vacation periods, are also introduced using covariates. [Received 28 September 2010; Revised 6 March 2011, 2 October 2011; Accepted 16 October 2011

José D. Bermúdez

2013-01-01T23:59:59.000Z

67

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

68

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

69

Electric Water Heater Modeling and Control Strategies for Demand Response  

SciTech Connect

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

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

2012-07-22T23:59:59.000Z

70

Electricity Demand Evolution Driven by Storm Motivated Population Movement  

SciTech Connect

Managing the risks posed by climate change to energy production and delivery is a challenge for communities worldwide. Sea Level rise and increased frequency and intensity of natural disasters due to sea surface temperature rise force populations to move locations, resulting in changing patterns of demand for infrastructure services. Thus, Infrastructures will evolve to accommodate new load centers while some parts of the network are underused, and these changes will create emerging vulnerabilities. Combining climate predictions and agent based population movement models shows promise for exploring the universe of these future population distributions and changes in coastal infrastructure configurations. In this work, we created a prototype agent based population distribution model and developed a methodology to establish utility functions that provide insight about new infrastructure vulnerabilities that might result from these patterns. Combining climate and weather data, engineering algorithms and social theory, we use the new Department of Energy (DOE) Connected Infrastructure Dynamics Models (CIDM) to examine electricity demand response to increased temperatures, population relocation in response to extreme cyclonic events, consequent net population changes and new regional patterns in electricity demand. This work suggests that the importance of established evacuation routes that move large populations repeatedly through convergence points as an indicator may be under recognized.

Allen, Melissa R [ORNL; Fernandez, Steven J [ORNL; Fu, Joshua S [ORNL; Walker, Kimberly A [ORNL

2014-01-01T23:59:59.000Z

71

Sixth Northwest Conservation and Electric Power Plan Chapter 5: Demand Response  

E-Print Network (OSTI)

Sixth Northwest Conservation and Electric Power Plan Chapter 5: Demand Response Summary of Key.............................................................................................................. 1 Demand Response in the Fifth Power Plan........................................................................................... 3 Demand Response in the Sixth Power Plan

72

Large Consumer Electricity Acquisition Considering Time-of-Use Rates Demand Response Programs  

Science Journals Connector (OSTI)

The consumers try to obtain their electricity demand at minimum cost from different resources in restructured electricity markets. Hence more attention have been made on demand response programs (DRP) which aims ...

Sayyad Nojavan; Hadi Qesmati; Kazem Zare

2014-12-01T23:59:59.000Z

73

Influence of Air Conditioner Operation on Electricity Use and Peak Demand  

E-Print Network (OSTI)

Electricity demand due to occupant controlled room air conditioners in a large mater-metered apartment building is analyzed. Hourly data on the electric demand of the building and of individual air conditioners are used in analyses of annual...

McGarity, A. E.; Feuermann, D.; Kempton, W.; Norford, L. K.

1987-01-01T23:59:59.000Z

74

Demand responsive programs - an emerging resource for competitive electricity markets?  

SciTech Connect

The restructuring of regional electricity markets in the U.S. has been accompanied by numerous problems, including generation capacity shortages, transmission congestion, wholesale price volatility, and reduced system reliability. These problems have created significant new opportunities for technologies and business approaches that allow load serving entities and other aggregators, to control and manage the load patterns of their wholesale or retail end-users. These technologies and business approaches for manipulating end-user load shapes are known as Load Management or, more recently, Demand Responsive programs. Lawrence Berkeley National Laboratory (LBNL) is conducting case studies on innovative demand responsive programs and presents preliminary results for five case studies in this paper. These case studies illustrate the diversity of market participants and range of technologies and business approaches and focus on key program elements such as target markets, market segmentation and participation results; pricing scheme; dispatch and coordination; measurement, verification, and settlement; and operational results where available.

Heffner, Grayson C. Dr.; Goldman, Charles A.

2001-06-25T23:59:59.000Z

75

An Approach to Demand Response for Alleviating Power System Stress Conditions due to Electric Vehicle Penetration.  

E-Print Network (OSTI)

??Along with the growth of electricity demand and the penetration of intermittent renewable energy sources, electric power distribution networks will face more and more stress (more)

Shao, Shengnan

2011-01-01T23:59:59.000Z

76

Demand for Electric Power in Norway : Estimating price and substitution elasticities.  

E-Print Network (OSTI)

??The main goal of this master thesis is to estimate how the prices of electricity and heating oil affect the aggregate demand for electric power (more)

yan, Ola Hagen

2010-01-01T23:59:59.000Z

77

The potential contribution of small hydroelectric generation to meeting electrical demand on Vancouver Island.  

E-Print Network (OSTI)

??This work focuses on the electrical contribution small hydro generation can make to meeting Vancouver Island's electrical demand, today, and as further development proceeds. A (more)

Schuett, Matthew T.

2008-01-01T23:59:59.000Z

78

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

SciTech Connect

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

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

2009-08-01T23:59:59.000Z

79

Employing demand response in energy procurement plans of electricity retailers  

Science Journals Connector (OSTI)

Abstract This paper proposes a new framework in which demand response (DR) is incorporated as an energy resource of electricity retailers in addition to the commonly used forward contracts and pool markets. In this way, a stepwise reward-based DR is proposed as a real-time resource of the retailer. In addition, the unpredictable behavior of customers participating in the proposed reward-based DR is modeled through a scenario-based participation factor. The overall problem is formulated as a stochastic optimization approach in which pool prices and customers participation in DR are uncertain variables. The feasibility of the problem is evaluated on a realistic case of the Australian National Electricity Market (NEM) and solved using General Algebraic Modeling System (GAMS) software.

Nadali Mahmoudi; Mehdi Eghbal; Tapan K. Saha

2014-01-01T23:59:59.000Z

80

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

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

LBNL-2124E LBNL-2124E Demand Response in U.S. Electricity Markets: Empirical Evidence Principal Authors Peter Cappers a , Charles Goldman a , and David Kathan b a Lawrence Berkeley National Laboratory 1 Cyclotron Road, Berkeley, CA 94720 b Federal Energy Regulatory Commission, 888 First Street, NE, Washington, DC 20426, Energy Analysis Department Ernest Orlando Lawrence Berkeley National Laboratory 1 Cyclotron Road, MS 90R4000 Berkeley CA 94720-8136 Environmental Energy Technologies Division June 2009 http://eetd.lbl.gov/ea/EMS/EMS_pubs.html Pre-print version of the article to be published in Energy, forthcoming 2009. The work described in this paper was funded by the Office of Electricity Delivery and Energy Reliability, Permitting, Siting and Analysis of the U.S.

Note: This page contains sample records for the topic "total electricity demand" 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

California Natural Gas % of Total Electric Utility Deliveries...  

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

Electric Utility Deliveries (Percent) California Natural Gas % of Total Electric Utility Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

82

Customer Load Strategies for Demand Response in Bilateral Contracting of Electricity  

Science Journals Connector (OSTI)

Electricity markets are systems for affecting the purchase and sale of electricity using supply and demand to set energy prices. Electricity can be traded in organized markets or by negotiating forward bilateral ...

Fernando Lopes; Hugo Algarvio

2014-01-01T23:59:59.000Z

83

Using Compressed Air Efficiency Projects to Reduce Peak Industrial Electric Demands: Lessons Learned  

E-Print Network (OSTI)

"To help customers respond to the wildly fluctuating energy markets in California, Pacific Gas & Electric (PG&E) initiated an emergency electric demand reduction program in October 2000 to cut electric use during peak periods. One component...

Skelton, J.

84

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

SciTech Connect

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

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

2012-06-01T23:59:59.000Z

85

Table A39. Total Expenditures for Purchased Electricity and Steam  

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

9. Total Expenditures for Purchased Electricity and Steam" 9. Total Expenditures for Purchased Electricity and Steam" " by Type of Supplier, Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" ," Electricity",," Steam" ,,,,,"RSE" ,"Utility","Nonutility","Utility","Nonutility","Row" "Economic Characteristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors" ,"Total United States" "RSE Column Factors:",0.3,2,1.6,1.2

86

Climate, extreme heat, and electricity demand in California  

E-Print Network (OSTI)

demand responses to climate change: Methodology and application to the Commonwealth of Massachusetts.

Miller, N.L.

2008-01-01T23:59:59.000Z

87

Marginal Cost Pricing: An Efficient Tool to Ensure Electricity Demand Side Management  

Science Journals Connector (OSTI)

The constant adaptation between electricity supply and demand can be achieved in two ways : On the supply side, through the construction of additional facilities, and on the demand side, by implementing tariffs, ...

B. Lescoeur; J. B. Galland; E. Husson

1988-01-01T23:59:59.000Z

88

Duct Leakage Impacts on Airtightness, Infiltration, and Peak Electrical Demand in Florida Homes  

E-Print Network (OSTI)

return leak from the attic can increase cooling electrical demand by 100%. Duct repairs in a typical. electrically heated Florida home reduce winter peak demand by about 1.6 kW per house at about one-sixth the cost of building new electrical generation...

Cummings, J. B.; Tooley, J. J.; Moyer, N.

1990-01-01T23:59:59.000Z

89

The behavioral response to voluntary provision of an environmental public good: Evidence from residential electricity demand  

E-Print Network (OSTI)

residential electricity demand Grant D. Jacobsen a,n , Matthew J. Kotchen b,c , Michael P. Vandenbergh d online 25 February 2012 JEL classification: H41 Q42 G54 Keywords: Green electricity Voluntary environmental protection Carbon offset Renewable energy Moral licensing Residential electricity demand a b s t r

Kotchen, Matthew J.

90

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

E-Print Network (OSTI)

for 90% of household electricity consumption in China. Usinggives an annual electricity consumption of 12kWh assumingto look at is electricity consumption at the household

Letschert, Virginie

2010-01-01T23:59:59.000Z

91

A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of  

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

Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year ActualWeather Data Title A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year ActualWeather Data Publication Type Journal Year of Publication 2013 Authors Hong, Tianzhen, Wen-Kuei Chang, and Hung-Wen Lin Keywords Actual meteorological year, Building simulation, Energy use, Peak electricity demand, Typical meteorological year, Weather data Abstract Buildings consume more than one third of the world's total primary energy. Weather plays a unique and significant role as it directly affects the thermal loads and thus energy performance of buildings. The traditional simulated energy performance using Typical Meteorological Year (TMY) weather data represents the building performance for a typical year, but not necessarily the average or typical long-term performance as buildings with different energy systems and designs respond differently to weather changes. Furthermore, the single-year TMY simulations do not provide a range of results that capture yearly variations due to changing weather, which is important for building energy management, and for performing risk assessments of energy efficiency investments. This paper employs large-scale building simulation (a total of 3162 runs) to study the weather impact on peak electricity demand and energy use with the 30-year (1980 to 2009) Actual Meteorological Year (AMY) weather data for three types of office buildings at two design efficiency levels, across all 17 ASHRAE climate zones. The simulated results using the AMY data are compared to those from the TMY3 data to determine and analyze the differences. Besides further demonstration, as done by other studies, that actual weather has a significant impact on both the peak electricity demand and energy use of buildings, the main findings from the current study include: 1) annual weather variation has a greater impact on the peak electricity demand than it does on energy use in buildings; 2) the simulated energy use using the TMY3 weather data is not necessarily representative of the average energy use over a long period, and the TMY3 results can be significantly higher or lower than those from the AMY data; 3) the weather impact is greater for buildings in colder climates than warmer climates; 4) the weather impact on the medium-sized office building was the greatest, followed by the large office and then the small office; and 5) simulated energy savings and peak demand reduction by energy conservation measures using the TMY3 weather data can be significantly underestimated or overestimated. It is crucial to run multi-decade simulations with AMY weather data to fully assess the impact of weather on the long-term performance of buildings, and to evaluate the energy savings potential of energy conservation measures for new and existing buildings from a life cycle perspective.

92

On the impact of urban heat island and global warming on the power demand and electricity consumption of buildingsA review  

Science Journals Connector (OSTI)

Abstract Urban heat island and global warming increase significantly the ambient temperature. Higher temperatures have a serious impact on the electricity consumption of the building sector increasing considerably the peak and the total electricity demand. The present paper aims to collect, analyze and present in a comparative way existing studies investigating the impact of ambient temperature increase on electricity consumption. Analysis of eleven studies dealing with the impact of the ambient temperature on the peak electricity demand showed that for each degree of temperature increase, the increase of the peak electricity load varies between 0.45% and 4.6%. This corresponds to an additional electricity penalty of about 21 (10.4)W per degree of temperature increase and per person. In parallel, analysis of fifteen studies examining the impact of ambient temperature on the total electricity consumption, showed that the actual increase of the electricity demand per degree of temperature increase varies between 0.5% and 8.5%.

M. Santamouris; C. Cartalis; A. Synnefa; D. Kolokotsa

2014-01-01T23:59:59.000Z

93

Sweating it out: the response of summer electricity demand to increases in price.  

E-Print Network (OSTI)

??This study examines the own price elasticity of demand for electricity in the Greater Sacramento Area. Data corresponded to customer billing information from the Sacramento (more)

Davis, Zephaniah K.

2014-01-01T23:59:59.000Z

94

ELECTRICITY DEMAND AND SUPPLY PROJECTIONS IN IEA WORLD ENERGY SCENARIOS: HOW MUCH, HOW CLEAN?  

Science Journals Connector (OSTI)

Abstract (40-Word Limit): The presentation will highlight and discuss projections for electricity demand up to 2050 based on the recent publication Energy Technology Perspectives 2012:...

Frankl, Paolo

95

Evaluation of ground energy storage assisted electric vehicle DC fast charger for demand charge reduction and providing demand response  

Science Journals Connector (OSTI)

Abstract In 2012 there was approximately 2400 electric vehicle DC Fast Charging stations sold globally. According to Pike Research (Jerram and Gartner, 2012), it is anticipated that by 2020 there will be approximately 460,000 of them installed worldwide. A typical public DC fast charger delivers a maximum power output of 50kW which allows a typical passenger vehicle to be 80% charged in 1015min, compared with 68h for a 6.6kW AC level 2 charging unit. While DC fast chargers offer users the convenience of being able to rapidly charge their vehicle, the unit's high power demand has the potential to put sudden strain on the electricity network, and incur significant demand charges. Depending on the utility rate structure, a DC fast charger can experience annual demand charges of several thousand dollars. Therefore in these cases there is an opportunity to mitigate or even avoid the demand charges incurred by coupling the unit with an appropriately sized energy storage system and coordinating the way in which it integrates. This paper explores the technical and economical suitability of coupling a ground energy storage system with a DC fast charge unit for mitigation or avoidance of demand charges and lessening the impact on the local electricity network. This paper also discusses the concept of having the system participate in demand response programs in order to provide grid support and to further improve the economic suitability of an energy storage system.

Donald McPhail

2014-01-01T23:59:59.000Z

96

The Supply and Demand Models Based on Electricity Consumption  

Science Journals Connector (OSTI)

Analyzing how the supply and demand of a commodity changes as a function of its price is one of the many purposes of the field of economics. The supply and demand model of a commodity is also the most efficient a...

Zhaoguang Hu; Zheng Hu

2013-01-01T23:59:59.000Z

97

Trends in electricity demand and supply in the developing countries, 1980--1990  

SciTech Connect

This report provides an overview of trends concerning electricity demand and supply in the developing countries in the 1980--1990 period, with special focus on 13 major countries for which we have assembled consistent data series. We describe the linkage between electricity demand and economic growth, the changing sectoral composition of electricity consumption, and changes in the mix of energy sources for electricity generation. We also cover trends in the efficiency of utility electricity supply with respect to power plant efficiency and own-use and delivery losses, and consider the trends in carbon dioxide emissions from electricity supply.

Meyers, S.; Campbell, C.

1992-11-01T23:59:59.000Z

98

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

99

Economy and Electricity Demand Growth Linked but ƒƒƒ.  

Gasoline and Diesel Fuel Update (EIA)

Economy and Electricity Demand Economy and Electricity Demand Growth Linked but ... for International Utility Conference, Demand Trends Panel March 12, 2013 | London, UK by Adam Sieminski, Administrator U. S. electricity use and economic growth, 1950-2040 Adam Sieminski, EEI Demand Trends, March 12, 2013 2 -2% 0% 2% 4% 6% 8% 10% 12% 14% 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 Percent growth, 3-year rolling average Source: EIA, Annual Energy Outlook 2013 Early Release History Projections 2011 Electricity Use GDP 2.4% 0.9% 2011 - 2040 average Annual energy use of a new refrigerator, 1950-2008 Adam Sieminski, EEI Demand Trends, March 12, 2013 3 Kilowatthours per year Source: DOE / EERE - Building Technologies Office 0 200 400 600 800 1,000 1,200 1,400 1,600 1,800

100

THE CHALLENGES AND OPPORTUNITIES TO MEET THE WORKFORCE DEMAND IN THE ELECTRIC POWER AND ENERGY PROFESSION  

E-Print Network (OSTI)

, but also has become the backbone for our economic development. The world has witnessed electric power1 THE CHALLENGES AND OPPORTUNITIES TO MEET THE WORKFORCE DEMAND IN THE ELECTRIC POWER AND ENERGY and supply in the world in general, and in the US, in particular. The electric power and energy industry

Note: This page contains sample records for the topic "total electricity demand" 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

Prices in Wholesale Electricity Markets and Demand Response.  

E-Print Network (OSTI)

??Price determination for a wholesale electricity market has been a long-standing issue in energy systems modeling. From an economic perspective, the complication arises from determining (more)

Aketi, Venkata Sesha Praneeth

2014-01-01T23:59:59.000Z

102

Ancillary Service Revenue Opportunities from Electric Vehicles via Demand Response.  

E-Print Network (OSTI)

??Driven by a variety of factors including falling costs, environmental impacts, and state mandates, the integration of renewable energy on the U. S. electrical grid (more)

Moss, Brian

2011-01-01T23:59:59.000Z

103

Effects of the drought on California electricity supply and demand  

E-Print Network (OSTI)

ELECTRICITY SUPPLY Hydroelectric Energy Supply Thermal-question. Data on PG&E's hydroelectric resources and Pacific27 Table 28 Table 29 Hydroelectric Supply in California Fuel

Benenson, P.

2010-01-01T23:59:59.000Z

104

Singular value decomposition expansion for electrical demand analysis  

Science Journals Connector (OSTI)

......friction. Reactive power in an electric circuit is analogous to the...eigenvalue decomposition, the elementary factors are invariant under...invariant under three matrix elementary transformations on A, i...often much higher than the resistance in an electrical system......

FAN LI

2000-01-01T23:59:59.000Z

105

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

106

Electricity Demand-Side Management for an Energy Efficient Future in China: Technology Options and Policy Priorities  

E-Print Network (OSTI)

Electricity Demand-Side Management for an Energy Efficient Future in China: Technology Options sensitive impacts on electricity demand growth by different demand-side management (DSM) scenarios countries. The research showed that demand side management strategies could result in significant reduction

de Weck, Olivier L.

107

AN ECONOMETRIC ANALYSIS OF ZAMBIAN INDUSTRIAL ELECTRICITY DEMAND.  

E-Print Network (OSTI)

??The purpose of this thesis is twofold: to examine the electricity use in Zambias mining industry by focusing on own-price, cross price and index of (more)

Chama, Yoram Chama

2012-01-01T23:59:59.000Z

108

ASSESSMENT OF ELECTRICITY DEMAND IN IRAN'S INDUSTRIAL SECTOR USING DIFFERENT INTELLIGENT OPTIMIZATION TECHNIQUES  

Science Journals Connector (OSTI)

This study presents application of particle swarm optimization (PSO) and genetic algorithm (GA) methods to estimate electricity demand in Iran's industrial sectors, based on economic indicators. The economic indicators used in this study are number of ...

M. A. Behrang; E. Assareh; M. R. Assari; A. Ghanbarzadeh

2011-04-01T23:59:59.000Z

109

The Impacts of Utility-Sponsored Demand-Side Management Programs on Industrial Electricity Consumers  

E-Print Network (OSTI)

One of the most pressing issues in electric utility regulation today is the extent to which demand-side management (DSM) programs should be promoted by utilities. DSM refers to energy-efficiency or conservation measures, such as insulation, more...

Rosenblum, J. I.

110

Medium-term forecasting of demand prices on example of electricity prices for industry  

Science Journals Connector (OSTI)

In the paper, a method of forecasting demand prices for electric energy for the industry has been suggested. An algorithm of the forecast for 20062010 based on the data for 19972005 has been presented.

V. V. Kossov

2014-09-01T23:59:59.000Z

111

Report: Natural Gas Infrastructure Implications of Increased Demand from the Electric Power Sector  

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

This report examines the potential infrastructure needs of the U.S. interstate natural gas pipeline transmission system across a range of future natural gas demand scenarios that drive increased electric power sector natural gas use.

112

Issues Related to the Growth of Electricity in Global Energy Demand  

Science Journals Connector (OSTI)

Since the subject of this international conference is Global Energy Demand in Transition: The New Role of Electricity ... drive the evolution of the market shares of energy sources and uses (which are different,...

Marcelo Alonso

1995-01-01T23:59:59.000Z

113

Electricity Distribution Networks: Investment and Regulation, and Uncertain Demand  

E-Print Network (OSTI)

by the Department of Energy and Climate Change (DEEC) on an annual basis.6 5 Engineering Technical Report 115 (1988). 6 DECC Sub-national energy consumption statistics (http://www.decc.gov.uk/en/content... of non-domestic activity, which must be taken into account whilst forecasting non-domestic demand. 8 DECC Sub-national energy consumption statistics (http://www.decc.gov.uk/en/content...

Jamasb, Tooraj; Marantes, Cristiano

2011-01-31T23:59:59.000Z

114

Electric Demand Cost Versus Labor Cost: A Case Study  

E-Print Network (OSTI)

steel and glass. Pins, glass beads and headers are assembled manually and are put in a carbon tray. Carbon trays are put in furnaces (ovens) which are maintained at a constant temperature between 160Q-2000F and have an exothermic gas environment.... At this time, company registers its peak demand. Company keeps all furnaces on and keep them available for workers in case they will need it for their products. On average, no more than two furnaces will have same temperature and exothermic gas...

Agrawal, S.; Jensen, R.

115

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

E-Print Network (OSTI)

Energy Source Demand per Household Coal, Oil, Gas, Heat, Electricity Total Energy Source Demand Coal, Oil, Gas, Heat, Electricity Demography Japan

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

116

Solutions for Summer Electric Power Shortages: Demand Response andits Applications in Air Conditioning and Refrigerating Systems  

SciTech Connect

Demand response (DR) is an effective tool which resolves inconsistencies between electric power supply and demand. It further provides a reliable and credible resource that ensures stable and economical operation of the power grid. This paper introduces systematic definitions for DR and demand side management, along with operational differences between these two methods. A classification is provided for DR programs, and various DR strategies are provided for application in air conditioning and refrigerating systems. The reliability of DR is demonstrated through discussion of successful overseas examples. Finally, suggestions as to the implementation of demand response in China are provided.

Han, Junqiao; Piette, Mary Ann

2007-11-30T23:59:59.000Z

117

Univariate time-series forecasting of monthly peak demand of electricity in northern India  

Science Journals Connector (OSTI)

This study forecasts the monthly peak demand of electricity in the northern region of India using univariate time-series techniques namely Multiplicative Seasonal Autoregressive Integrated Moving Average (MSARIMA) and Holt-Winters Multiplicative Exponential Smoothing (ES) for seasonally unadjusted monthly data spanning from April 2000 to February 2007. In-sample forecasting reveals that the MSARIMA model outperforms the ES model in terms of lower root mean square error, mean absolute error and mean absolute percent error criteria. It has been found that ARIMA (2, 0, 0) (0, 1, 1)12 is the best fitted model to explain the monthly peak demand of electricity, which has been used to forecast the monthly peak demand of electricity in northern India, 15 months ahead from February 2007. This will help Northern Regional Load Dispatch Centre to make necessary arrangements a priori to meet the future peak demand.

Sajal Ghosh

2008-01-01T23:59:59.000Z

118

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

119

Integrated electricity and heating demand-side management for wind power integration in China  

Science Journals Connector (OSTI)

Abstract The wind power generation system will play a crucial role for developing the energy conservative, environmentally friendly, and sustainable electric power system in China. However, the intermittency and unpredictability of wind power has been an obstacle to the deployment of wind power generation, especially in the winter of northern China. In northern China, a combined heat and power (CHP) unit has been widely utilized as a heat and electricity source. Considering the flexible operation of CHP with introduction of electric heat pumps (EHPs), this paper proposes a new method of electricity and heating demand side management to facilitate the wind power integration with the purpose of energy conservation in a unit-commitment problem. The thermal characteristics of demand side such as the thermal inertia of buildings and thermal comfort of end users are taken into consideration. Moreover the distributed electric heat pumps (EHPs) widely used by city dwellers are introduced into the wind-thermal power system as the heating source and spinning reserve so as to increase the flexibility of heating and electricity supply. The simulation results show that the new method can integrate more wind power into power grid for electricity and heating demand to reduce the coal consumption.

Yulong Yang; Kai Wu; Hongyu Long; Jianchao Gao; Xu Yan; Takeyoshi Kato; Yasuo Suzuoki

2014-01-01T23:59:59.000Z

120

A demand responsive bidding mechanism with price elasticity matrix in wholesale electricity pools ; A demand responsive bidding mechanism with price elasticity matrix .  

E-Print Network (OSTI)

??In the past several decades, many demand-side participation features have been applied in the electricity power systems. These features, such as distributed generation, on-site storage (more)

Wang, Jiankang, Ph. D. Massachusetts Institute of Technology

2009-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

Statewide Electricity and Demand Capacity Savings from the Implementation of IECC Code in Texas: Analysis for Single-Family Residences  

E-Print Network (OSTI)

STATEWIDE ELECTRICITY AND DEMAND CAPACITY SAVINGS FROM THE IMPLEMENTATION OF IECC CODE IN TEXAS: ANALYSIS FOR SINGLE?FAMILY RESIDENCES 11th International Conference for Enhanced Building Operations New York City, October 18 ? 20, 2011 Hyojin...&M University System Statewide Electricity and Demand Savings from the IECC Code in TX 11th ICEBO Conference Oct. 18 ? 20, 2011 2 Outline Introduction Methodology Base?Case Building Results Summary Statewide Electricity and Demand Savings from the IECC...

Kim, H.; Baltazar, J.C.; Haberl, J.; Lewis, C.; Yazdani, B.

2011-01-01T23:59:59.000Z

122

Coordinating Regulation and Demand Response in Electric Power Grids: Direct and Price-Based Tracking Using Multirate Economic Model Predictive Control  

Science Journals Connector (OSTI)

?Based on Coordinating regulation and demand response in electric power grids using multirate model...

Haitham Hindi; Daniel Greene

2012-01-01T23:59:59.000Z

123

Further exploring the potential of residential demand response programs in electricity distribution  

Science Journals Connector (OSTI)

Abstract Smart grids play a key role in realizing climate ambitions. Boosting consumption flexibility is an essential measure in bringing the potential gains of smart grids to fruition. The collective scientific understanding of demand response programs argues that time-of-use tariffs have proven its merits. The findings upon which this conclusion rests are, however, primarily derived from studies covering energy-based time-of-use rates over fairly short periods of time. Hence, this empirical study set out with the intention of estimating the extent of response to a demand-based time-of-use electricity distribution tariff among Swedish single-family homes in the long term. The results show that six years after the implementation households still respond to the price signals of the tariff by cutting demand in peak hours and shifting electricity consumption from peak to off-peak hours. Studies conducted in the Nordic countries commonly include only homeowners and so another aim of the study was to explore the potential of demand response programs among households living in apartment buildings. The demand-based tariff proved to bring about similar, but not as marked, effects in rental apartments, whereas there are virtually no corresponding evidences of demand response in condominium apartments.

Cajsa Bartusch; Karin Alvehag

2014-01-01T23:59:59.000Z

124

Long-term electricity demand forecasting for power system planning using economic, demographic and climatic variables  

Science Journals Connector (OSTI)

The stochastic planning of power production overcomes the drawback of deterministic models by accounting for uncertainties in the parameters. Such planning accounts for demand uncertainties by using scenario sets and probability distributions. However, in previous literature, different scenarios were developed by either assigning arbitrary values or assuming certain percentages above or below a deterministic demand. Using forecasting techniques, reliable demand data can be obtained and inputted to the scenario set. This article focuses on the long-term forecasting of electricity demand using autoregressive, simple linear and multiple linear regression models. The resulting models using different forecasting techniques are compared through a number of statistical measures and the most accurate model was selected. Using Ontario's electricity demand as a case study, the annual energy, peak load and base load demand were forecasted up to the year 2025. In order to generate different scenarios, different ranges in the economic, demographic and climatic variables were used. [Received 16 October 2007; Revised 31 May 2008; Revised 25 October 2008; Accepted 1 November 2008

F. Chui; A. Elkamel; R. Surit; E. Croiset; P.L. Douglas

2009-01-01T23:59:59.000Z

125

Univariate forecasting of day-ahead hourly electricity demand in the northern grid of India  

Science Journals Connector (OSTI)

Short-term electricity demand forecasts (minutes to several hours ahead) have become increasingly important since the rise of the competitive energy markets. The issue is particularly important for India as it has recently set up a power exchange (PX), which has been operating on day-ahead hourly basis. In this study, an attempt has been made to forecast day-ahead hourly demand of electricity in the northern grid of India using univariate time-series forecasting techniques namely multiplicative seasonal ARIMA and Holt-Winters multiplicative exponential smoothing (ES). In-sample forecasts reveal that ARIMA models, except in one case, outperform ES models in terms of lower RMSE, MAE and MAPE criteria. We may conclude that linear time-series models works well to explain day-ahead hourly demand forecasts in the northern grid of India. The findings of the study will immensely help the players in the upcoming power market in India.

Sajal Ghosh

2009-01-01T23:59:59.000Z

126

Demand Reduction  

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

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

127

Statewide Electricity and Demand Capacity Savings from the Implementation of IECC Code in Texas: Analysis for Single-Family Residences  

E-Print Network (OSTI)

This paper presents estimates of the statewide electricity and electric demand savings achieved from the adoption of the International Energy Conservation Code (IECC) for single-family residences in Texas and includes the corresponding increase...

Kim, H.; Baltazar, J.C.; Haberl, J.

2011-01-01T23:59:59.000Z

128

Industrial-Load-Shaping: The Practice of and Prospects for Utility/Industry Cooperation to Manage Peak Electricity Demand  

E-Print Network (OSTI)

INDUSTRIAL-LOAD-SHAPI1IG: TIlE PRACTICE OF AND PROSPECTS FOR UTILITY/INDUSTRY COOPERATION TO MAUGE PEAK ELECTRICITY DEMAND Donald J. BuIes and David E. Rubin Consultants, Pacific Gas and Electric Company San Francisco, California Michael F.... Maniates Energy and Resources Group, University of California Berkeley, California ABSTRACT Load-management programs designed to reduce demand for electricity during peak periods are becoming increasingly important to electric utilities. For a gf...

Bules, D. J.; Rubin, D. E.; Maniates, M. F.

129

The Impact of Energy Efficiency and Demand Response Programs on the U.S. Electricity Market  

SciTech Connect

This study analyzes the impact of the energy efficiency (EE) and demand response (DR) programs on the grid and the consequent level of production. Changes in demand caused by EE and DR programs affect not only the dispatch of existing plants and new generation technologies, the retirements of old plants, and the finances of the market. To find the new equilibrium in the market, we use the Oak Ridge Competitive Electricity Dispatch Model (ORCED) developed to simulate the operations and costs of regional power markets depending on various factors including fuel prices, initial mix of generation capacity, and customer response to electricity prices. In ORCED, over 19,000 plant units in the nation are aggregated into up to 200 plant groups per region. Then, ORCED dispatches the power plant groups in each region to meet the electricity demands for a given year up to 2035. In our analysis, we show various demand, supply, and dispatch patterns affected by EE and DR programs across regions.

Baek, Young Sun [ORNL; Hadley, Stanton W [ORNL

2012-01-01T23:59:59.000Z

130

Demand-response (DR) programs, in which facilities reduce their electric loads in response to a utility signal, represent a  

E-Print Network (OSTI)

The Issue Demand-response (DR) programs, in which facilities reduce their electric loads (Figure 1). The testing covered four Lighting the Way to Demand ResponseLighting the Way to Demand Response California Energy Commission's Public Interest Energy Research Program Technical Brief PIER

131

Integrating Demand into the U.S. Electric Power System: Technical, Economic, and Regulatory Frameworks for Responsive Load  

E-Print Network (OSTI)

for Responsive/Adaptive Load by Jason W. Black Massachusetts Institute of Technology Submitted to the Engineering integration of demand response. Integrating demand into the US electricity system will allow the development, and market issues to determine a system structure that provides incentives for demand response. An integrated

de Weck, Olivier L.

132

Multicriteria decision making in electricity demand management: the case of Kuwait  

Science Journals Connector (OSTI)

Electricity demand in Kuwait has substantially increased over the years and this increase is attributed to population growth, increase in the number of buildings, and the extensive use of air-conditioning system during the very hot weather in the summer. The amount of electrical energy generated reached 48 444 308 megawatt hour (MWH) in 2007. Such growth calls for extensive investment in the continuous expansion of the existing power plants and constructing new ones. To rationalise the consumption of electricity, several conservation policies have to be implemented. In this work, we have attempted to diagnose such problem and solicit expert opinions in order to provide the proper remedies. Because the problem comprises several criteria that are subjective in nature, multicriteria decision-making approaches were suggested. The Analytical Hierarchy Process (AHP) was used as a decision tool to assess the different policies that could be used to bring about electricity conservation.

Mohammed Hajeeh

2010-01-01T23:59:59.000Z

133

A Preliminary Examination of the Supply and Demand Balance for Renewable Electricity  

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

A Preliminary Examination A Preliminary Examination of the Supply and Demand Balance for Renewable Electricity Blair Swezey, Jørn Aabakken, and Lori Bird Technical Report NREL/TP-670-42266 October 2007 NREL is operated by Midwest Research Institute ● Battelle Contract No. DE-AC36-99-GO10337 A Preliminary Examination of the Supply and Demand Balance for Renewable Electricity Blair Swezey, Jørn Aabakken, and Lori Bird Prepared under Task No. WF6N.1015 Technical Report NREL/TP-670-42266 October 2007 National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, Colorado 80401-3393 303-275-3000 * www.nrel.gov Operated for the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy by Midwest Research Institute * Battelle

134

Demand side management of electric car charging: Benefits for consumer and grid  

Science Journals Connector (OSTI)

Ireland is currently striving to source 10% of the energy required for its transport fleet from renewable energy sources by 2020. As part of the measures being implemented in order to help realise this ambitious target a number of Government schemes have been introduced to financially subsidise the purchase of alternative energy vehicles in an effort to achieve 10% EV (electric vehicle) penetration in the country's road fleet by 2020. The replacement of ICE (internal combustion engine) vehicles with EV equivalents poses challenges for grid operators while simultaneously offering opportunities in terms of distributed energy storage and flexible load. This paper examines how optimising the charging cycles of an electric car using DSM (Demand Side Management) based on a number of criteria could be used to achieve financial savings, increased demand on renewable energy, reduce demand on thermal generation plant, and reduce peak load demand. The results demonstrate that significant gains can be achieved using currently available market data which highlights the point that DSM can be implemented without any further technological advents.

P. Finn; C. Fitzpatrick; D. Connolly

2012-01-01T23:59:59.000Z

135

High Electric Demand Days: Clean Energy Strategies for Improving Air Quality  

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

This presentation by Art Diem of the State and Local Capacity Building Branch in the U.S. Environmental Protection Agency was part of the July 2008 Webcast sponsored by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Weatherization and Intergovernmental Program Clean Energy and Air Quality Integration Initiative that was titled Role of Energy Efficiency and Renewable Energy in Improving Air Quality and Addressing Greenhouse Gas Reduction Goals on High Electric Demand Days.

136

Effect of window type, size and orientation on the total energy demand for a building in Indian climatic conditions  

Science Journals Connector (OSTI)

Windows in a building allow daylight to enter a building space but simultaneously they also result in heat gains and losses affecting energy balance. This requires an optimisation of window area from the point of view of total energy demand viz., for lighting and cooling/heating. This paper is devoted to this kind of study for Indian climatic conditions, which are characterised by six climatic zones varying from extreme cold to hot, dry and humid conditions. Different types of windows have been considered because the optimised size will also depend on the thermo-optical parameters like heat transfer coefficient (U-value), solar heat gain coefficient (g), visual (?), and total transmittance (T) of the glazing in the window. It is observed that in a non-insulated building, cooling/heating energy demand far exceeds lighting energy demand, making the optimisation of window area a futile exercise from the point of view of total energy demand. Only for buildings with U-value below 0.6 W/m²K can optimisation be achieved. The optimised window area and the corresponding specific energy consumption have been calculated for different climates in India, for different orientations, and for three different advanced window systems.

Inderjeet Singh; N.K. Bansal

2004-01-01T23:59:59.000Z

137

An integrated assessment of global and regional water demands for electricity generation to 2095  

SciTech Connect

Electric power plants currently account for approximately one-half of the global industrial water withdrawal. While continued expansion of the electric sector seems likely into the future, the consequent water demands are quite uncertain, and will depend on highly variable water intensities by electricity technologies, at present and in the future. Using GCAM, an integrated assessment model of energy, agriculture, and climate change, we first establish lower-bound, median, and upper-bound estimates for present-day electric sector water withdrawals and consumption by individual electric generation technologies in each of 14 geopolitical regions, and compare them with available estimates of regional industrial or electric sector water use. We then explore the evolution of global and regional electric sector water use over the next century, focusing on uncertainties related to withdrawal and consumption intensities for a variety of electric generation technologies, rates of change of power plant cooling system types, and rates of adoption of a suite of water-saving technologies. Results reveal that the water withdrawal intensity of electricity generation is likely to decrease in the near term with capital stock turnover, as wet towers replace once-through flow cooling systems and advanced electricity generation technologies replace conventional ones. An increase in consumptive use accompanies the decrease in water withdrawal rates; however, a suite of water conservation technologies currently under development could compensate for this increase in consumption. Finally, at a regional scale, water use characteristics vary significantly based on characteristics of the existing capital stock and the selection of electricity generation technologies into the future.

Davies, Evan; Kyle, G. Page; Edmonds, James A.

2013-02-01T23:59:59.000Z

138

Sixth Northwest Conservation and Electric Power Plan Chapter 3: Electricity Demand Forecast  

E-Print Network (OSTI)

at a relatively slow pace, custom data centers (Google, etc.) are a relatively new end-use that has been seeing................................................................................................................... 7 Alternative Load Forecast Concepts been influenced by expected higher electricity prices that reflect a rapid rise in fuel prices

139

Statewide Emissions Reduction, Electricity and Demand Savings from the Implementation of Building-Energy-Codes in Texas  

E-Print Network (OSTI)

to the calculations. To estimate electric demand savings, the calculated statewide electric demand savings (MW) were then multiplied by the average capital cost of a natural gas combined cycle power plant, $1,165 per kW (Kaplan, 2008) using a 15% reserve margin... (Simulation adjustment3: Heating 72F, Cooling 75F) (b) Heat Pump House: 0.904 360 0.88 kW (Simulation adjustment3: 1.095 kW) HVAC System Type (a) Electric/Gas House: 0.594 (a) Electric/Gas House: 0.544 SLA= 0.00036 (a) Electric/Gas House: SEER 13...

Yazdani, B.; Haberl, J.; Kim, H.; Baltazar, J.C.; Zilbershtein, G.

2012-01-01T23:59:59.000Z

140

Projections up for total energy demand by IEA nations in 1990  

SciTech Connect

The author reviews the most recent IEA projections for energy demand to the year 2000 in IEA countries. These show that the expectations for 1990 are now higher than estimates made last year. Production of solid fuels is expected to increase from 814 million toe in 1983 to 1044 million toe in 1990 and 1345 million toe by 2000. Nearly all the increase is expected in the US, Canada and Australia.

Vielvoye, R.

1985-06-17T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

Dynamic Control of Electricity Cost with Power Demand Smoothing and Peak Shaving for Distributed Internet Data Centers  

E-Print Network (OSTI)

Dynamic Control of Electricity Cost with Power Demand Smoothing and Peak Shaving for Distributed a major part of their running costs. Modern electric power grid provides a feasible way to dynamically and efficiently manage the electricity cost of distributed IDCs based on the Locational Marginal Pricing (LMP

Rahman, A.K.M. Ashikur

142

Potential Energy Total electric potential energy, U, of a system of  

E-Print Network (OSTI)

Potential Energy Total electric potential energy, U, of a system of charges is obtained from of work done by the field, W*= -W. Bring q1 from , W *= 0 since no electric F yet #12;Potential Energy Total electric potential energy, U, of a system of charges is obtained from the work done by an external

Bertulani, Carlos A. - Department of Physics and Astronomy, Texas A&M University

143

Impact of plug-in hybrid electric vehicles on power systems with demand response and wind power.  

SciTech Connect

This paper uses a new unit commitment model which can simulate the interactions among plug-in hybrid electric vehicles (PHEVs), wind power, and demand response (DR). Four PHEV charging scenarios are simulated for the Illinois power system: (1) unconstrained charging, (2) 3-hour delayed constrained charging, (3) smart charging, and (4) smart charging with DR. The PHEV charging is assumed to be optimally controlled by the system operator in the latter two scenarios, along with load shifting and shaving enabled by DR programs. The simulation results show that optimally dispatching the PHEV charging load can significantly reduce the total operating cost of the system. With DR programs in place, the operating cost can be further reduced.

Wang, J.; Liu, C.; Ton, D.; Zhou, Y.; Kim, J.; Vyas, A. (Decision and Information Sciences); ( ES); (ED); (Kyungwon Univ.)

2011-07-01T23:59:59.000Z

144

Integrating demand into the U.S. electric power system : technical, economic, and regulatory frameworks for responsive load  

E-Print Network (OSTI)

The electric power system in the US developed with the assumption of exogenous, inelastic demand. The resulting evolution of the power system reinforced this assumption as nearly all controls, monitors, and feedbacks were ...

Black, Jason W. (Jason Wayne)

2005-01-01T23:59:59.000Z

145

Electricity demand-side management for an energy efficient future in China : technology options and policy priorities  

E-Print Network (OSTI)

The main objective of this research is to identify robust technology and policy options which achieve substantial reductions in electricity demand in China's Shandong Province. This research utilizes a scenario-based ...

Cheng, Chia-Chin

2005-01-01T23:59:59.000Z

146

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

E-Print Network (OSTI)

Laboratory. Berkeley. Demand Response Research Center,and Automated Demand Response in Wastewater TreatmentLaboratory. Berkeley. Demand Response Research Center,

McKane, Aimee

2010-01-01T23:59:59.000Z

147

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

E-Print Network (OSTI)

and Open Automated Demand Response. In Grid Interop Forum.Berkeley National Laboratory. Demand Response ResearchCenter, Demand Response Research Center PIER Team Briefing,

McKane, Aimee

2010-01-01T23:59:59.000Z

148

Quantifying Changes in Building Electricity Use, with Application to Demand Response  

E-Print Network (OSTI)

and techniques for demand response, Lawrence BerkeleyNational action plan on demand response, Prepared with the3] G. He?ner, Demand response valuation frameworks paper,

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

149

Load-side Demand Management in Buildings usingControlled Electric Springs  

E-Print Network (OSTI)

The concept of demand-side management for electricand simulation of demand-side management potential in urbanin smart grids, demand side management has been a keen topic

Soni, Jayantika; Krishnanand, KR; Panda, Sanjib

2014-01-01T23:59:59.000Z

150

LBNL-6280E A Fresh Look at Weather Impact on Peak Electricity Demand and  

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

280E 280E A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30- Year Actual Weather Data Tianzhen Hong 1 , Wen-kuei Chang 2 , Hung-Wen Lin 2 1 Environmental Energy Technologies Division 2 Green Energy and Environment Laboratories, Industrial Technology Research Institute, Taiwan, ROC May 2013 This work was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, the U.S.-China Clean Energy Research Center for Building Energy Efficiency, of the U.S. Department of Energy under Contract No. DE-AC02-

151

Managing Total Corporate Electricity/Energy Market Risks  

Science Journals Connector (OSTI)

This paper starts with a short history of the use of value-at-risk techniques in financial risk management. The specific and often unique risk management challenges faced by electricity companies are then desc...

Alex Henney; Greg Keers

2000-01-01T23:59:59.000Z

152

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

E-Print Network (OSTI)

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

Massachusetts at Amherst, University of

153

"Table A38. Total Expenditures for Purchased Electricity, Steam, and Natural Gas"  

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

8. Total Expenditures for Purchased Electricity, Steam, and Natural Gas" 8. Total Expenditures for Purchased Electricity, Steam, and Natural Gas" " by Type of Supplier, Census Region, Census Division, Industry Group," " and Selected Industries, 1994" " (Estimates in Million Dollars)" ,," Electricity",," Steam" ,,,,,,"RSE" "SIC",,"Utility","Nonutility","Utility","Nonutility","Row" "Code(a)","Industry Group and Industry","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors" ,,"Total United States"

154

Table A10. Total Inputs of Energy for Heat, Power, and Electricity...  

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

0. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Fuel Type, Industry Group, Selected Industries, and End Use, 1994:" " Part 2" " (Estimates in Trillion...

155

Chapter 21 - Case Study: Demand-Response and Alternative Technologies inElectricity Markets  

Science Journals Connector (OSTI)

Abstract The PJM wholesale electricity market has evolved to promote open competition between existing generation resources, new generation resources, demand-response, and alternative technologies to supply services to support reliable power grid operations. PJM has adapted market rules and procedures to accommodate smaller alternative resources while maintaining and enhancing stringent reliability standards for grid operation. Although the supply resource mix has tended to be less operationally flexible, the development of smart grid technologies, breakthroughs in storage technologies, microgrid applications, distributed supply resources, and smart metering infrastructure have the potential to make power transmission, distribution, and consumption more flexible than in the past. Competitive market signals in forward capacity markets and grid service markets have resulted in substantial investment in demand-response and alternative technologies to provide reliability services to the grid operator. This chapter discusses these trends and the market mechanisms by which both system and market operators can manage and leverage these changes to maintain the reliability of the bulk electric power system.

Andrew Ott

2014-01-01T23:59:59.000Z

156

Modeling of Electric Water Heaters for Demand Response: A Baseline PDE Model  

SciTech Connect

Demand response (DR)control can effectively relieve balancing and frequency regulation burdens on conventional generators, facilitate integrating more renewable energy, and reduce generation and transmission investments needed to meet peak demands. Electric water heaters (EWHs) have a great potential in implementing DR control strategies because: (a) the EWH power consumption has a high correlation with daily load patterns; (b) they constitute a significant percentage of domestic electrical load; (c) the heating element is a resistor, without reactive power consumption; and (d) they can be used as energy storage devices when needed. Accurately modeling the dynamic behavior of EWHs is essential for designing DR controls. Various water heater models, simplified to different extents, were published in the literature; however, few of them were validated against field measurements, which may result in inaccuracy when implementing DR controls. In this paper, a partial differential equation physics-based model, developed to capture detailed temperature profiles at different tank locations, is validated against field test data for more than 10 days. The developed model shows very good performance in capturing water thermal dynamics for benchmark testing purposes

Xu, Zhijie; Diao, Ruisheng; Lu, Shuai; Lian, Jianming; Zhang, Yu

2014-09-05T23:59:59.000Z

157

Abstract--Electrical Distribution Systems (EDS) are facing ever-increasing complexity due to fast growing demand and large  

E-Print Network (OSTI)

operation. As such Electrical Distribution Systems will require new planning strategies and tools, new1 Abstract-- Electrical Distribution Systems (EDS) are facing ever-increasing complexity due to fast growing demand and large amount of distributed energy resources integration. The conventional

Paris-Sud XI, Université de

158

Optimal Tariff Period Determination Cost of electricity generation is closely related to system demand. In general, the  

E-Print Network (OSTI)

Optimal Tariff Period Determination Cost of electricity generation is closely related to system setting is giving signal to customers the time variant cost of supplying electricity. Since the costs demand. In general, the generation cost is higher during system peak period, and vice versa. In Hong Kong

159

Statewide Electricity and Demand Capacity Savings from the International Energy Conservation Code (IECC) Adoption for Single-Family Residences in Texas (2002-2011)  

E-Print Network (OSTI)

This report is the continuation of the previous 2011 Statewide Electricity Savings report from code-compliant, single-family residences built between 2002 and 2009. Statewide electricity and electric demand savings achieved from the adoption...

Kim, H.; Baltazar, J. C.; Haberl, J. S.; Yazdani, B.

2013-01-01T23:59:59.000Z

160

"Table A46. Total Expenditures for Purchased Electricity, Steam, and Natural"  

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

6. Total Expenditures for Purchased Electricity, Steam, and Natural" 6. Total Expenditures for Purchased Electricity, Steam, and Natural" " Gas by Type of Supplier, Census Region, Industry Group, and Selected Industries," 1991 " (Estimates in Million Dollars)" ,," Electricity",," Steam",," Natural Gas" ,,"-","-----------","-","-----------","-","------------","-","RSE" "SIC",,"Utility","Nonutility","Utility","Nonutility","Utility","Transmission","Other","Row" "Code(a)","Industry Groups and Industry","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Supplier(b)","Pipelines","Supplier(d)","Factors"

Note: This page contains sample records for the topic "total electricity demand" 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

"Table A48. Total Expenditures for Purchased Electricity, Steam, and Natural"  

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

8. Total Expenditures for Purchased Electricity, Steam, and Natural" 8. Total Expenditures for Purchased Electricity, Steam, and Natural" " Gas by Type of Supplier, Census Region, and Economic Characteristics of the" " Establishment, 1991" " (Estimates in Million Dollars)" ," Electricity",," Steam",," Natural Gas" ,"-","-----------","-","-----------","-","------------","-----------","RSE" " ","Utility","Nonutility","Utility","Nonutility","Utility","Transmission","Other","Row" "Economic Characteristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Supplier(b)","Pipelines","Supplier(d)","Factors"," "

162

Table 16. Total Electricity Sales, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Electricity Sales, Projected vs. Actual Electricity Sales, Projected vs. Actual (billion kilowatt-hours) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 2364 2454 2534 2626 2708 2811 AEO 1983 2318 2395 2476 2565 2650 2739 3153 AEO 1984 2321 2376 2461 2551 2637 2738 3182 AEO 1985 2317 2360 2427 2491 2570 2651 2730 2808 2879 2949 3026 AEO 1986 2363 2416 2479 2533 2608 2706 2798 2883 2966 3048 3116 3185 3255 3324 3397 AEO 1987 2460 2494 2555 2622 2683 2748 2823 2902 2977 3363 AEO 1989* 2556 2619 2689 2760 2835 2917 2994 3072 3156 3236 3313 3394 3473 AEO 1990 2612 2689 3083 3488.0 3870.0 AEO 1991 2700 2762 2806 2855 2904 2959 3022 3088 3151 3214 3282 3355 3427 3496 3563 3632 3704 3776 3846 3916 AEO 1992 2746 2845 2858 2913 2975 3030 3087 3146 3209 3276 3345 3415 3483 3552 3625 3699 3774 3847 3921 AEO 1993 2803 2840 2893 2946 2998 3052 3104 3157 3214 3271 3327

163

Electricity demand as frequency controlled reserves, ForskEL (Smart Grid  

Open Energy Info (EERE)

ForskEL (Smart Grid ForskEL (Smart Grid Project) Jump to: navigation, search Project Name Electricity demand as frequency controlled reserves, ForskEL Country Denmark Coordinates 56.26392°, 9.501785° 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":56.26392,"lon":9.501785,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

164

Table A45. Total Inputs of Energy for Heat, Power, and Electricity Generation  

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Enclosed Floorspace, Percent Conditioned Floorspace, and Presence of Computer" " Controls for Building Environment, 1991" " (Estimates in Trillion Btu)" ,,"Presence of Computer Controls" ,," for Buildings Environment",,"RSE" "Enclosed Floorspace and"," ","--------------","--------------","Row" "Percent Conditioned Floorspace","Total","Present","Not Present","Factors" " "," " "RSE Column Factors:",0.8,1.3,0.9 "ALL SQUARE FEET CATEGORIES" "Approximate Conditioned Floorspace"

165

Table A31. Total Inputs of Energy for Heat, Power, and Electricity Generation  

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1991" " (Continued)" " (Estimates in Trillion Btu)",,,,"Value of Shipments and Receipts(b)" ,,,," (million dollars)" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," "," "," ",500,"Row" "Code(a)","Industry Groups and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors"

166

"2012 Total Electric Industry- Customers"  

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

Customers" Customers" "(Data from forms EIA-861- schedules 4A, 4B, 4D, EIA-861S and EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",6203726,842773,34164,5,7080668 "Connecticut",1454651,150435,4647,2,1609735 "Maine",703770,89048,2780,0,795598 "Massachusetts",2699141,389272,21145,2,3109560 "New Hampshire",601697,104978,3444,0,710119 "Rhode Island",435448,57824,1927,1,495200 "Vermont",309019,51216,221,0,360456 "Middle Atlantic",15727423,2215961,45836,26,17989246 "New Jersey",3455302,489943,12729,6,3957980 "New York",7010740,1038268,8144,6,8057158

167

A fuzzy chance-constrained program for unit commitment problem considering demand response, electric vehicle and wind power  

Science Journals Connector (OSTI)

Abstract As a form of renewable and low-carbon energy resource, wind power is anticipated to play an essential role in the future energy structure. Whereas, its features of time mismatch with power demand and uncertainty pose barriers for the power system to utilize it effectively. Hence, a novel unit commitment model is proposed in this paper considering demand response and electric vehicles, which can promote the exploitation of wind power. On the one hand, demand response and electric vehicles have the feasibility to change the load demand curve to solve the mismatch problem. On the other hand, they can serve as reserve for wind power. To deal with the unit commitment problem, authors use a fuzzy chance-constrained program that takes into account the wind power forecasting errors. The numerical study shows that the model can promote the utilization of wind power evidently, making the power system operation more eco-friendly and economical.

Ning Zhang; Zhaoguang Hu; Xue Han; Jian Zhang; Yuhui Zhou

2015-01-01T23:59:59.000Z

168

Review of real-time electricity markets for integrating Distributed Energy Resources and Demand Response  

Science Journals Connector (OSTI)

Abstract The high penetration of both Distributed Energy Resources (DER) and Demand Response (DR) in modern power systems requires a sequence of advanced strategies and technologies for maintaining system reliability and flexibility. Real-time electricity markets (RTM) are the non-discriminatory transaction platforms for providing necessary balancing services, where the market clearing (nodal or zonal prices depending on markets) is very close to real time operations of power systems. One of the primary functions of \\{RTMs\\} in modern power systems is establishing an efficient and effective mechanism for small DER and DR to participate in balancing market transactions, while handling their meteorological or intermittent characteristics, facilitating asset utilization, and stimulating their active responses. Consequently, \\{RTMs\\} are dedicated to maintaining the flexibility and reliability of power systems. This paper reviews advanced typical \\{RTMs\\} respectively in the North America, Australia and Europe, focusing on their market architectures and incentive policies for integrating DER and DR in electricity markets. In this paper, \\{RTMs\\} are classified into three groups: Group I applies nodal prices implemented by optimal power flow, which clears energy prices every 5min. Group II applies zonal prices, with the time resolution of 5-min. Group III is a general balancing market, which clears zonal prices intro-hourly. The various successful advanced RTM experiences have been summarized and discussed, which provides a technical overview of the present \\{RTMs\\} integrating DER and DR.

Qi Wang; Chunyu Zhang; Yi Ding; George Xydis; Jianhui Wang; Jacob stergaard

2015-01-01T23:59:59.000Z

169

Progress towards Managing Residential Electricity Demand: Impacts of Standards and Labeling for Refrigerators and Air Conditioners in India  

SciTech Connect

The development of Energy Efficiency Standards and Labeling (EES&L) began in earnest in India in 2001 with the Energy Conservation Act and the establishment of the Indian Bureau of Energy Efficiency (BEE). The first main residential appliance to be targeted was refrigerators, soon to be followed by room air conditioners. Both of these appliances are of critical importance to India's residential electricity demand. About 15percent of Indian households own a refrigerator, and sales total about 4 million per year, but are growing. At the same time, the Indian refrigerator market has seen a strong trend towards larger and more consumptive frost-free units. Room air conditioners in India have traditionally been sold to commercial sector customers, but an increasing number are going to the residential sector. Room air conditioner sales growth in India peaked in the last few years at 20percent per year. In this paper, we perform an engineering-based analysis using data specific to Indian appliances. We evaluate costs and benefits to residential and commercial sector consumers from increased equipment costs and utility bill savings. The analysis finds that, while the BEE scheme presents net benefits to consumers, there remain opportunities for efficiency improvement that would optimize consumer benefits, according to Life Cycle Cost analysis. Due to the large and growing market for refrigerators and air conditioners in India, we forecast large impacts from the standards and labeling program as scheduled. By 2030, this program, if fully implemented would reduce Indian residential electricity consumption by 55 TWh. Overall savings through 2030 totals 385 TWh. Finally, while efficiency levels have been set for several years for refrigerators, labels and MEPS for these products remain voluntary. We therefore consider the negative impact of this delay of implementation to energy and financial savings achievable by 2030.

McNeil, Michael A.; Iyer, Maithili

2009-05-30T23:59:59.000Z

170

"2012 Total Electric Industry- Revenue (Thousands Dollars)"  

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

Revenue (Thousands Dollars)" Revenue (Thousands Dollars)" "(Data from forms EIA-861- schedules 4A-D, EIA-861S and EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",7418025.1,6137400,3292222.3,37797.4,16885444.6 "Connecticut",2212594.3,1901294.3,451909.7,18679.5,4584477.8 "Maine",656822,467228,241624.4,0,1365674.3 "Massachusetts",3029291.6,2453106,2127180,17162,7626739.5 "New Hampshire",713388.2,598371.1,231041,0,1542800.3 "Rhode Island",449603.6,431951.9,98597.2,1955.9,982108.6 "Vermont",356325.4,285448.7,141870,0,783644.1 "Middle Atlantic",20195109.9,20394744.7,5206283.9,488944,46285082.4

171

"2012 Total Electric Industry- Sales (Thousand Megawatthours)"  

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

Sales (Thousand Megawatthours)" Sales (Thousand Megawatthours)" "(Data from forms EIA-861- schedules 4A, 4B, 4D, EIA-861S and EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",47207.696,44864.227,27817.984,566.173,120456.08 "Connecticut",12757.633,12976.05,3565.944,192.711,29492.338 "Maine",4480.736,4053.188,3027.135,0,11561.059 "Massachusetts",20313.469,17722.811,16927.205,349.839,55313.324 "New Hampshire",4439.208,4478.42,1952.633,0,10870.261 "Rhode Island",3121.367,3639.866,923.478,23.623,7708.334 "Vermont",2095.283,1993.892,1421.589,0,5510.764 "Middle Atlantic",132230.522,157278.208,69506.519,3910.06,362925.309

172

Demand-side management in smart grid operation considering electric vehicles load shifting and vehicle-to-grid support  

Science Journals Connector (OSTI)

Abstract Demand fluctuation in electric power systems is undesirable from many points of view; this has sparked an interest in demand-side strategies that try to establish mechanisms that allow for a flatter demand curve. Particularly interesting is load shifting, a strategy that considers the shifting of certain amounts of energy demand from some time periods to other time periods with lower expected demand, typically in response to price signals. In this paper, an optimization-based model is proposed to perform load shifting in the context of smart grids. In our model, we define agents that are responsible for load, generation and storage management; in particular, some of them are electric vehicle aggregators. An important feature of the proposed approach is the inclusion of electric vehicles with vehicle-to-grid capabilities; with this possibility, electric vehicles can provide certain services to the power grid, including load shifting and congestion management. Results are reported for a test system based on the IEEE 37-bus distribution grid; the effectiveness of the approach and the effect of the hourly energy prices on flattening the load curve are shown.

M.A. Lpez; S. de la Torre; S. Martn; J.A. Aguado

2015-01-01T23:59:59.000Z

173

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

E-Print Network (OSTI)

Total Energy Source Demand Coal, Oil, Gas, Heat, ElectricityEnergy Source Demand per Household Coal, Oil, Gas, Heat,ton of oil equivalent Considerable increases in demand for

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

174

Categorization of residential electricity consumption as a basis for the assessment of the impacts of demand response actions  

Science Journals Connector (OSTI)

Abstract In a smart(er) grid context, the existence of dynamic tariffs and bidirectional communications will simultaneously allow and require an active role from the end-user concerning electricity management. However, the residential end-user will not be always available to manage energy resources and decide, based on price signals and preferences/needs, the best response actions to implement or the best usage of the electricity produced locally. Therefore, energy management systems are required to monitor consumption/generation/storage and to make the best decisions according to input signals and the user's needs and preferences. The design of adequate algorithms to be implemented in those systems require the prior characterization of domestic electricity demand and categorization of loads, according to availability, typical usage patterns, working cycles and technical constraints. Automated demand response actions must be tailored and chosen according to this previous analysis of load characteristics. In this paper, a characterization of household electricity consumption is presented and an operational categorization of end-use loads is proposed. The existing potential for demand response to a diversified set of management actions is described and a tool to assess the impact of implementing several actions with different rates of penetration of energy management systems is presented. The results obtained show the potential savings for the end-user and expected changes in the load diagram with a decrease of the aggregated peak electricity demand and a smoothed valley.

Ana Soares; lvaro Gomes; Carlos Henggeler Antunes

2014-01-01T23:59:59.000Z

175

Beyond kWh and kW demand: Understanding the new real-time electric power  

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

Beyond kWh and kW demand: Understanding the new real-time electric power Beyond kWh and kW demand: Understanding the new real-time electric power measurement system in LBNL Building 90 Speaker(s): Alex McEachern Date: January 14, 2010 - 12:00pm Location: 90-3122 In the Summer of 2009, LBNL researchers installed end-use sub-metering equipment and associated Energy Information System (EIS) tools to characterize energy use and comfort in Building 90. Seven of 40 key electric loads were measured using advanced meters that make sophisticated real-time measurements of dozens of power flow parameters, power disturbances, and harmonics. The talk will review some electrical engineering fundamentals, how use and interpret data measured in building 90 in real-time. The real-time data available includes power, volt-amps, VAR's, unbalance voltage and current, voltage and current distortion,

176

An evaluation of total body electrical conductivity to estimate body composition of largemouth bass  

E-Print Network (OSTI)

Information about body composition of fish is important for the assessment and management of fish stocks. Measurement of total body electrical conductivity (TOBEC) recently has been used to estimate the body composition of several fish species in a...

Barziza, Daniel Eugene

2012-06-07T23:59:59.000Z

177

Table A36. Total Inputs of Energy for Heat, Power, and Electricity  

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

"Net","Residual","and Diesel",,,"and",,"Row" "Code(a)","End-Use Categories","Total","Electricity(b)","Fuel Oil","Fuel(c)","Natural Gas(d)","LPG","Breeze)","Other(e)","Factors" ,...

178

Table A10. Total Inputs of Energy for Heat, Power, and Electricity...  

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

,,,"Net","Residual","and Diesel",,,"Coal Coke",,"RSE" "SIC",,"Total","Electricity(b)","Fuel Oil","Fuel(c)","Natural Gas(d)","LPG","and Breeze)","Other(e)","Row"...

179

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

the country last July, while temperatures in July 2014 were closer to average. This led to a decrease in demand for electricity generation in July 2014, with total...

180

Demand side management of industrial electricity consumption: Promoting the use of renewable energy through real-time pricing  

Science Journals Connector (OSTI)

Abstract As the installed capacity of wind generation in Ireland continues to increase towards an overall goal of 40% of electricity from renewable sources by 2020, it is inevitable that the frequency of wind curtailment occurrences will increase. Using this otherwise discarded energy by strategically increasing demand at times that would otherwise require curtailment has the potential to reduce the installed capacity of wind required to meet the national 2020 target. Considering two industrial electricity consumers, this study analyses the potential for the implementation of price based demand response by an industrial consumer to increase their proportional use of wind generated electricity by shifting their demand towards times of low prices. Results indicate that while curtailing during peak price times has little or no benefit in terms of wind energy consumption, demand shifting towards low price times is likely to increase a consumers consumption of wind generation by approximately 5.8% for every 10% saved on the consumers average unit price of electricity.

Paddy Finn; Colin Fitzpatrick

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

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

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

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

182

Table A50. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

A50. Total Inputs of Energy for Heat, Power, and Electricity Generation" A50. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Census Region, Industry Group, Selected Industries, and Type of" " Energy-Management Program, 1994" " (Estimates in Trillion Btu)" ,,,," Census Region",,,"RSE" "SIC",,,,,,,"Row" "Code(a)","Industry Group and Industry","Total","Northeast","Midwest","South","West","Factors" ,"RSE Column Factors:",0.7,1.2,1.1,0.9,1.2 "20-39","ALL INDUSTRY GROUPS" ,"Participation in One or More of the Following Types of Programs",12605,1209,3303,6386,1706,2.9

183

Table A15. Total Inputs of Energy for Heat, Power, and Electricity Generation  

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," "," (million dollars)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",500,"Row" "Code(a)","Industry Group and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors" ,"RSE Column Factors:",0.6,1.3,1,1,0.9,1.2,1.2

184

Table A41. Total Inputs of Energy for Heat, Power, and Electricity  

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

A41. Total Inputs of Energy for Heat, Power, and Electricity" A41. Total Inputs of Energy for Heat, Power, and Electricity" " Generation by Census Region, Industry Group, Selected Industries, and Type of" " Energy Management Program, 1991" " (Estimates in Trillion Btu)" ,,," Census Region",,,,"RSE" "SIC","Industry Groups",," -------------------------------------------",,,,"Row" "Code(a)","and Industry","Total","Northeast","Midwest","South","West","Factors" ,"RSE Column Factors:",0.7,1.3,1,0.9,1.2 "20-39","ALL INDUSTRY GROUPS" ,"Participation in One or More of the Following Types of Programs",10743,1150,2819,5309,1464,2.6,,,"/WIR{D}~"

185

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

E-Print Network (OSTI)

Missing Link in the Electricity Value Chain Aimee McKane,Missing Link in the Electricity Value Chain Aimee McKane,grid reliability and lower electricity use during periods of

McKane, Aimee

2010-01-01T23:59:59.000Z

186

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

E-Print Network (OSTI)

Missing Link in the Electricity Value Chain Aimee McKane*,Missing Link in the Electricity Value Chain Aimee McKane,grid reliability and lower electricity use during periods of

McKane, Aimee

2010-01-01T23:59:59.000Z

187

" Row: NAICS Codes; Column: Electricity Components;"  

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

1. Electricity: Components of Net Demand, 1998;" 1. Electricity: Components of Net Demand, 1998;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Electricity Components;" " Unit: Million Kilowatthours." " "," ",,,,,," " " "," ",,,,"Sales and","Net Demand","RSE" "NAICS"," ",,,"Total Onsite","Transfers","for","Row" "Code(a)","Subsector and Industry","Purchases","Transfers In(b)","Generation(c)","Offsite","Electricity(d)","Factors" ,,"Total United States"

188

" Row: NAICS Codes; Column: Electricity Components;"  

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

1 Electricity: Components of Net Demand, 2002;" 1 Electricity: Components of Net Demand, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Electricity Components;" " Unit: Million Kilowatthours." " "," ",,,,,," " " "," ",,,"Total ","Sales and","Net Demand","RSE" "NAICS"," ",,"Transfers ","Onsite","Transfers","for","Row" "Code(a)","Subsector and Industry","Purchases"," In(b)","Generation(c)","Offsite","Electricity(d)","Factors" ,,"Total United States"

189

Where has Electricity Demand Growth Gon in PJM and What are the...  

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

economic conditions and environmental rules - New entry of combined cycle gas and demand response resources...will there be incentives for continued new entry? * Impending GHG...

190

E-Print Network 3.0 - aggregate electricity demand Sample Search...  

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

Distribution and Plants 11 Nordic TSOs' Action Plans in enhancing and monitoring Demand Response Summary: in Norway (draft) Nordel (2003): Statistical analysis of price response...

191

Time-of-use pricing and electricity demand response: evidence from a sample of Italian industrial customers  

Science Journals Connector (OSTI)

The introduction of real time pricing in many wholesale market as well as the liberalisation process involving the retail market poses the attention over the measurement of demand response to time differentiated price signals. This paper shows an example of how to estimate elasticities of substitution across time using a sample of Italian industrial customers facing time-of-use (TOU) pricing schemes. The model involves the estimation of a nested constant elasticity of substitution (CES) input demand function, which allows estimating substitutability of electricity usage across hourly intervals within a month and across different months.

Graziano Abrate

2008-01-01T23:59:59.000Z

192

The Effects of Residential Energy Efficiency on Electric Demand Response Programs  

Science Journals Connector (OSTI)

Design and efficiency of houses can affect the amount of peak load reduction available from a residential demand response program. Twenty-four houses were simulated with varying thermal integrity and air conditioner size during the summer cooling season ... Keywords: demand response, efficiency, residential, hvac, conservation

Ward Jewell

2014-01-01T23:59:59.000Z

193

Total  

Gasoline and Diesel Fuel Update (EIA)

Total Total .............. 16,164,874 5,967,376 22,132,249 2,972,552 280,370 167,519 18,711,808 1993 Total .............. 16,691,139 6,034,504 22,725,642 3,103,014 413,971 226,743 18,981,915 1994 Total .............. 17,351,060 6,229,645 23,580,706 3,230,667 412,178 228,336 19,709,525 1995 Total .............. 17,282,032 6,461,596 23,743,628 3,565,023 388,392 283,739 19,506,474 1996 Total .............. 17,680,777 6,370,888 24,051,665 3,510,330 518,425 272,117 19,750,793 Alabama Total......... 570,907 11,394 582,301 22,601 27,006 1,853 530,841 Onshore ................ 209,839 11,394 221,233 22,601 16,762 1,593 180,277 State Offshore....... 209,013 0 209,013 0 10,244 260 198,509 Federal Offshore... 152,055 0 152,055 0 0 0 152,055 Alaska Total ............ 183,747 3,189,837 3,373,584 2,885,686 0 7,070 480,828 Onshore ................ 64,751 3,182,782

194

Supplementary Information Potential for Electricity Generation from Renewable Resources and Levelized Cost of Electricity (LCOE)  

E-Print Network (OSTI)

Supplementary Information Potential for Electricity Generation from Renewable Resources and Levelized Cost of Electricity (LCOE) Electrical energy can be generated from renewable resources the potential to meet the worldwide demand of electricity and they contribute to the total generation

Suo, Zhigang

195

Table A11. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

1" 1" " (Estimates in Btu or Physical Units)" ,,,,"Distillate",,,"Coal" ,,,,"Fuel Oil",,,"(excluding" ,,"Net","Residual","and Diesel",,,"Coal Coke",,"RSE" ,"Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","and Breeze)","Other(d)","Row" "End-Use Categories","(trillion Btu)","(million kWh)","(1000 bbls)","(1000 bbls)","(billion cu ft)","(1000 bbls)","(1000 short tons)","(trillion Btu)","Factors" ,,,,,,,,,,, ,"Total United States"

196

Modeling demand for electric vehicles: the effect of car users' attitudes and perceptions  

E-Print Network (OSTI)

electric cars and petrol-driven ones and in particular which include the respondents' own cars to electric cars on vehicle preferences. Opinion and perception data are also collected to capture the impact) and currently, few charging stations and infrastructures are available. The electric car user is hence compelled

Bierlaire, Michel

197

Controlling market power and price spikes in electricity networks: Demand-side bidding  

Science Journals Connector (OSTI)

...controlled data set with...competition on transmission lines connecting...demand from outages are ignored. Other...losses in transmission and any line constraints...14 days of data by level...when the transmission lines...

Stephen J. Rassenti; Vernon L. Smith; Bart J. Wilson

2003-01-01T23:59:59.000Z

198

Interrelation Between the Accuracy of Prediction and Irregularity of Electric Energy Demand Curves  

Science Journals Connector (OSTI)

Results of a study of the dependence of the accuracy of prediction on daily and seasonal irregularity of demand curves are described. It is shown that in power systems characterized by high irregularity of the...

B. I. Makoklyuev; V. F. Ech

199

Table 6b. Relative Standard Errors for Total Electricity Consumption per  

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

b. Relative Standard Errors for Total Electricity Consumption per b. Relative Standard Errors for Total Electricity Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Electricity (thousand) Total Electricity Consumption (trillion Btu) Electricity Intensities (thousand Btu) Per Square Foot Per Effective Occupied Square Foot All Buildings 4 5 4 4 Building Floorspace (Square Feet) 1,001 to 5,000 5 6 6 6 5,001 to 10,000 4 9 9 9 10,001 to 25,000 5 7 5 5 25,001 to 50,000 7 10 10 10 50,001 to 100,000 7 12 8 8 100,001 to 200,000 9 13 10 10 200,001 to 500,000 10 13 11 11 Over 500,000 26 18 18 21 Principal Building Activity Education 8 9 6 6 Food Sales and Service 8 9 8 7 Health Care 14 12 12 9 Lodging 11 22 16 16 Mercantile and Service 5 7 7 7 Office 6 10 7 6 Public Assembly 7 12 28 30 Public Order and Safety 18 29 18 18 Religious Worship 10 10 11 11 Warehouse and Storage

200

Table A4. Total Inputs of Energy for Heat, Power, and Electricity Generation  

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

2" 2" " (Estimates in Trillion Btu)" " "," "," "," "," "," "," "," "," "," "," "," " " "," "," "," "," "," "," "," "," "," "," ","RSE" "SIC"," "," ","Net","Residual","Distillate"," "," "," ","Coke"," ","Row" "Code(a)","Industry Groups and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","LPG","Coal","and Breeze","Other(e)","Factors"

Note: This page contains sample records for the topic "total electricity demand" 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

Table A37. Total Inputs of Energy for Heat, Power, and Electricity  

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

2" 2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,,"Distillate",,,"(excluding" ,,,,"Fuel Oil",,,"Coal Coke",,"RSE" ,,"Net","Residual","and Diesel",,,"and",,"Row" "End-Use Categories","Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","Breeze)","Other(d)","Factors" "Total United States" "RSE Column Factors:","NF",0.4,1.6,1.5,0.7,1,1.6,"NF" "TOTAL INPUTS",15027,2370,414,139,5506,105,1184,5309,3 "Boiler Fuel","--","W",296,40,2098,18,859,"--",3.6

202

Table A11. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

2" 2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,,"Distillate",,,"(excluding" ,,,,"Fuel Oil",,,"Coal Coke",,"RSE" ,,"Net","Residual","and Diesel",,,"and",,"Row" "End-Use Categories","Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","Breeze)","Other(d)","Factors" ,"Total United States" "RSE Column Factors:"," NF",0.5,1.3,1.4,0.8,1.2,1.2," NF" "TOTAL INPUTS",16515,2656,441,152,6141,99,1198,5828,2.7 "Indirect Uses-Boiler Fuel"," --",28,313,42,2396,15,875," --",4

203

Total............................................................  

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

Total................................................................... Total................................................................... 111.1 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546

204

Solutions for Summer Electric Power Shortages: Demand Response and its Applications in Air Conditioning and Refrigerating Systems  

E-Print Network (OSTI)

for DR and demand side management, along with operationalresponse), DSM (demand side management), DR strategy, air

Han, Junqiao; Piette, Mary Ann

2008-01-01T23:59:59.000Z

205

Total...................  

Gasoline and Diesel Fuel Update (EIA)

4,690,065 52,331,397 2,802,751 4,409,699 7,526,898 209,616 1993 Total................... 4,956,445 52,535,411 2,861,569 4,464,906 7,981,433 209,666 1994 Total................... 4,847,702 53,392,557 2,895,013 4,533,905 8,167,033 202,940 1995 Total................... 4,850,318 54,322,179 3,031,077 4,636,500 8,579,585 209,398 1996 Total................... 5,241,414 55,263,673 3,158,244 4,720,227 8,870,422 206,049 Alabama ...................... 56,522 766,322 29,000 62,064 201,414 2,512 Alaska.......................... 16,179 81,348 27,315 12,732 75,616 202 Arizona ........................ 27,709 689,597 28,987 49,693 26,979 534 Arkansas ..................... 46,289 539,952 31,006 67,293 141,300 1,488 California ..................... 473,310 8,969,308 235,068 408,294 693,539 36,613 Colorado...................... 110,924 1,147,743

206

Table A52. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

2. Total Inputs of Energy for Heat, Power, and Electricity Generation by Employment Size" 2. Total Inputs of Energy for Heat, Power, and Electricity Generation by Employment Size" " Categories and Presence of General Technologies and Cogeneration Technologies, 1994" " (Estimates in Trillion Btu)" ,,,,"Employment Size(a)" ,,,,,,,,"RSE" ,,,,,,,"1000 and","Row" "General/Cogeneration Technologies","Total","Under 50","50-99","100-249","250-499","500-999","Over","Factors" "RSE Column Factors:",0.5,2,2.1,1,0.7,0.7,0.9 "One or More General Technologies Present",14601,387,781,2054,2728,3189,5462,3.1 " Computer Control of Building Environment (b)",5079,64,116,510,802,1227,2361,5

207

The structure of demand for electricity in the Gulf Cooperation Council countries  

SciTech Connect

Electricity is a vital ingredient for the economic and social advancement of all developing nations. The members of Gulf Cooperation Council (GCC) offer no exception. The quantity of electricity consumed in these countries has grown consistently since the 1970s. If past trends are extrapolated to the year 2000, the electricity consumption at the turn of the century will be at least 10-fold the level prevailing the 1970s.

Eltony, M.N.; Mohammad, Y.H.

1993-12-31T23:59:59.000Z

208

Converting 15-Minute Interval Electricity Load Data into Reduced Demand, Energy Reduction and Cash Flow  

E-Print Network (OSTI)

, store managers are intimidated. 5 So what are the solutions? A data acquisition system. Pro-active with alarming and demand-response. Is there staff to maintain and ensure a response? Passive. Acquire the data and then evaluate and assess... is not required, this will prevent the requirement for additional costs of installing an OAT sensor at the building and potentially adding costs to the datalogger hardware or configuration. If possible, it is best to use and on-site OAT sensor. If a demand-response...

Herrin, D. G.

209

Multi-objective dynamic economic emission dispatch of electric power generation integrated with game theory based demand response programs  

Science Journals Connector (OSTI)

Abstract The dynamic economic emission dispatch (DEED) of electric power generation is a multi-objective mathematical optimization problem with two objective functions. The first objective is to minimize all the fuel costs of the generators in the power system, whilst the second objective seeks to minimize the emissions cost. Both objective functions are subject to constraints such as load demand constraint, ramp rate constraint, amongst other constraints. In this work, we integrate a game theory based demand response program into the DEED problem. The game theory based demand response program determines the optimal hourly incentive to be offered to customers who sign up for load curtailment. The game theory model has in built mechanisms to ensure that the incentive offered the customers is greater than the cost of interruption while simultaneously being beneficial to the utility. The combined DEED and game theoretic demand response model presented in this work, minimizes fuel and emissions costs and simultaneously determines the optimal incentive and load curtailment customers have to perform for maximal power system relief. The developed model is tested on two test systems with industrial customers and obtained results indicate the practical benefits of the proposed model.

Nnamdi I. Nwulu; Xiaohua Xia

2015-01-01T23:59:59.000Z

210

Electric Demand Reduction for the U.S. Navy Public Works Center San Diego, California  

SciTech Connect

Pacific Northwest National Laboratory investigated the profitability of operating a Navy ship's generators (in San Diego) during high electricity price periods rather than the ships hooking up to the Base electrical system for power. Profitability is predicated on the trade-off between the operating and maintenance cost incurred by the Navy for operating the ship generators and the net profit associated with the sale of the electric power on the spot market. In addition, PNNL assessed the use of the ship's generators as a means to achieve predicted load curtailments, which can then be marketed to the California Independent System Operator.

Kintner-Meyer, Michael CW

2000-09-30T23:59:59.000Z

211

Floating offshore wind farms : demand planning & logistical challenges of electricity generation  

E-Print Network (OSTI)

Floating offshore wind farms are likely to become the next paradigm in electricity generation from wind energy mainly because of the near constant high wind speeds in an offshore environment as opposed to the erratic wind ...

Nnadili, Christopher Dozie, 1978-

2009-01-01T23:59:59.000Z

212

Quantifying Changes in Building Electricity Use, with Application to Demand Response  

E-Print Network (OSTI)

electric loads to deliver load following and regu- lation,6], and regulation/load following [7]), and as DR is used toload as a function of time-of-week and outdoor air temperature. Following

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

213

Total...................................................................  

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

15.2 15.2 7.8 1.0 1.2 3.3 1.9 For Two Housing Units............................. 0.9 Q N Q 0.6 N Heat Pump.................................................. 9.2 7.4 0.3 Q 0.7 0.5 Portable Electric Heater............................... 1.6 0.8 Q Q Q 0.3 Other Equipment......................................... 1.9 0.7 Q Q 0.7 Q Fuel Oil........................................................... 7.7 5.5 0.4 0.8 0.9 0.2 Steam or Hot Water System........................ 4.7 2.9 Q 0.7 0.8 N For One Housing Unit.............................. 3.3 2.9 Q Q Q N For Two Housing Units............................. 1.4 Q Q 0.5 0.8 N Central Warm-Air Furnace........................... 2.8 2.4 Q Q Q 0.2 Other Equipment......................................... 0.3 0.2 Q N Q N Wood..............................................................

214

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

SciTech Connect

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

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

1988-04-01T23:59:59.000Z

215

Table A4. Total Inputs of Energy for Heat, Power, and Electricity Generation  

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

1 " 1 " " (Estimates in Btu or Physical Units)" " "," "," "," "," "," "," "," "," ","Coke"," "," " " "," "," ","Net","Residual","Distillate","Natural Gas(d)"," ","Coal","and Breeze"," ","RSE" "SIC"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","LPG","(1000","(1000","Other(e)","Row" "Code(a)","Industry Groups and Industry","(trillion Btu)","(million kWh)","(1000 bbls)","(1000 bbls)","cu ft)","(1000 bbls)","short tons)","short tons)","(trillion Btu)","Factors"

216

Table A37. Total Inputs of Energy for Heat, Power, and Electricity  

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

1",,,,,,,"Coal" 1",,,,,,,"Coal" " (Estimates in Btu or Physical Units)",,,,,,,"(excluding" ,,,,"Distillate",,,"Coal Coke" ,,"Net",,"Fuel Oil",,,"and" ,,"Electricity(a)","Residual","and Diesel","Natural Gas",,"Breeze)",,"RSE" ,"Total","(million","Fuel Oil","Fuel","(billion","LPG","(1000 short","Other","Row" "End-Use Categories","(trillion Btu)","kWh)","(1000 bbls)","(1000 bbls)","cu ft)","(1000 bbls)","tons)","(trillion Btu)","Factors"

217

Table A36. Total Inputs of Energy for Heat, Power, and Electricity  

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

,,,,,,,,"Coal" ,,,,,,,,"Coal" " Part 1",,,,,,,,"(excluding" " (Estimates in Btu or Physical Units)",,,,,"Distillate",,,"Coal Coke" ,,,,,"Fuel Oil",,,"and" ,,,"Net","Residual","and Diesel","Natural Gas",,"Breeze)",,"RSE" "SIC",,"Total","Electricity(b)","Fuel Oil","Fuel","(billion","LPG","(1000 Short","Other","Row" "Code(a)","End-Use Categories","(trillion Btu)","(million kWh)","(1000 bbls)","(1000 bbls)","cu ft)","(1000 bbls)","tons)","(trillion Btu)","Factors",

218

Total..........................................................................  

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

7.1 7.1 19.0 22.7 22.3 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 2.1 0.6 Q 0.4 500 to 999........................................................... 23.8 13.6 3.7 3.2 3.2 1,000 to 1,499..................................................... 20.8 9.5 3.7 3.4 4.2 1,500 to 1,999..................................................... 15.4 6.6 2.7 2.5 3.6 2,000 to 2,499..................................................... 12.2 5.0 2.1 2.8 2.4 2,500 to 2,999..................................................... 10.3 3.7 1.8 2.8 2.1 3,000 to 3,499..................................................... 6.7 2.0 1.4 1.7 1.6 3,500 to 3,999..................................................... 5.2 1.6 0.8 1.5 1.4 4,000 or More.....................................................

219

Total..........................................................................  

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

0.7 0.7 21.7 6.9 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.6 Q Q 500 to 999........................................................... 23.8 9.0 4.2 1.5 3.2 1,000 to 1,499..................................................... 20.8 8.6 4.7 1.5 2.5 1,500 to 1,999..................................................... 15.4 6.0 2.9 1.2 1.9 2,000 to 2,499..................................................... 12.2 4.1 2.1 0.7 1.3 2,500 to 2,999..................................................... 10.3 3.0 1.8 0.5 0.7 3,000 to 3,499..................................................... 6.7 2.1 1.2 0.5 0.4 3,500 to 3,999..................................................... 5.2 1.5 0.8 0.3 0.4 4,000 or More.....................................................

220

Total..........................................................................  

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

25.6 25.6 40.7 24.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.9 1.0 500 to 999........................................................... 23.8 4.6 3.9 9.0 6.3 1,000 to 1,499..................................................... 20.8 2.8 4.4 8.6 5.0 1,500 to 1,999..................................................... 15.4 1.9 3.5 6.0 4.0 2,000 to 2,499..................................................... 12.2 2.3 3.2 4.1 2.6 2,500 to 2,999..................................................... 10.3 2.2 2.7 3.0 2.4 3,000 to 3,499..................................................... 6.7 1.6 2.1 2.1 0.9 3,500 to 3,999..................................................... 5.2 1.1 1.7 1.5 0.9 4,000 or More.....................................................

Note: This page contains sample records for the topic "total electricity demand" 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

Total..........................................................................  

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

4.2 4.2 7.6 16.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 1.0 0.2 0.8 500 to 999........................................................... 23.8 6.3 1.4 4.9 1,000 to 1,499..................................................... 20.8 5.0 1.6 3.4 1,500 to 1,999..................................................... 15.4 4.0 1.4 2.6 2,000 to 2,499..................................................... 12.2 2.6 0.9 1.7 2,500 to 2,999..................................................... 10.3 2.4 0.9 1.4 3,000 to 3,499..................................................... 6.7 0.9 0.3 0.6 3,500 to 3,999..................................................... 5.2 0.9 0.4 0.5 4,000 or More.....................................................

222

Total.........................................................................  

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

Floorspace (Square Feet) Floorspace (Square Feet) Total Floorspace 2 Fewer than 500.................................................. 3.2 Q 0.8 0.9 0.8 0.5 500 to 999.......................................................... 23.8 1.5 5.4 5.5 6.1 5.3 1,000 to 1,499.................................................... 20.8 1.4 4.0 5.2 5.0 5.2 1,500 to 1,999.................................................... 15.4 1.4 3.1 3.5 3.6 3.8 2,000 to 2,499.................................................... 12.2 1.4 3.2 3.0 2.3 2.3 2,500 to 2,999.................................................... 10.3 1.5 2.3 2.7 2.1 1.7 3,000 to 3,499.................................................... 6.7 1.0 2.0 1.7 1.0 1.0 3,500 to 3,999.................................................... 5.2 0.8 1.5 1.5 0.7 0.7 4,000 or More.....................................................

223

Total..........................................................................  

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

. . 111.1 20.6 15.1 5.5 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.4 500 to 999........................................................... 23.8 4.6 3.6 1.1 1,000 to 1,499..................................................... 20.8 2.8 2.2 0.6 1,500 to 1,999..................................................... 15.4 1.9 1.4 0.5 2,000 to 2,499..................................................... 12.2 2.3 1.7 0.5 2,500 to 2,999..................................................... 10.3 2.2 1.7 0.6 3,000 to 3,499..................................................... 6.7 1.6 1.0 0.6 3,500 to 3,999..................................................... 5.2 1.1 0.9 0.3 4,000 or More.....................................................

224

Total..........................................................................  

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

7.1 7.1 7.0 8.0 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.4 Q Q 0.5 500 to 999........................................................... 23.8 2.5 1.5 2.1 3.7 1,000 to 1,499..................................................... 20.8 1.1 2.0 1.5 2.5 1,500 to 1,999..................................................... 15.4 0.5 1.2 1.2 1.9 2,000 to 2,499..................................................... 12.2 0.7 0.5 0.8 1.4 2,500 to 2,999..................................................... 10.3 0.5 0.5 0.4 1.1 3,000 to 3,499..................................................... 6.7 0.3 Q 0.4 0.3 3,500 to 3,999..................................................... 5.2 Q Q Q Q 4,000 or More.....................................................

225

Total..........................................................  

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

.. .. 111.1 24.5 1,090 902 341 872 780 441 Total Floorspace (Square Feet) Fewer than 500...................................... 3.1 2.3 403 360 165 366 348 93 500 to 999.............................................. 22.2 14.4 763 660 277 730 646 303 1,000 to 1,499........................................ 19.1 5.8 1,223 1,130 496 1,187 1,086 696 1,500 to 1,999........................................ 14.4 1.0 1,700 1,422 412 1,698 1,544 1,348 2,000 to 2,499........................................ 12.7 0.4 2,139 1,598 Q Q Q Q 2,500 to 2,999........................................ 10.1 Q Q Q Q Q Q Q 3,000 or More......................................... 29.6 0.3 Q Q Q Q Q Q Heated Floorspace (Square Feet) None...................................................... 3.6 1.8 1,048 0 Q 827 0 407 Fewer than 500......................................

226

Total...................................................................  

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

2,033 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546 3,500 to 3,999................................................. 5.2 3,549 2,509 1,508

227

Total...........................................................  

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

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................... 3.2 1.9 0.9 Q Q Q 1.3 2.3 500 to 999........................................... 23.8 10.5 7.3 3.3 1.4 1.2 6.6 12.9 1,000 to 1,499..................................... 20.8 5.8 7.0 3.8 2.2 2.0 3.9 8.9 1,500 to 1,999..................................... 15.4 3.1 4.2 3.4 2.0 2.7 1.9 5.0 2,000 to 2,499..................................... 12.2 1.7 2.7 2.9 1.8 3.2 1.1 2.8 2,500 to 2,999..................................... 10.3 1.2 2.2 2.3 1.7 2.9 0.6 2.0 3,000 to 3,499..................................... 6.7 0.9 1.4 1.5 1.0 1.9 0.4 1.4 3,500 to 3,999..................................... 5.2 0.8 1.2 1.0 0.8 1.5 0.4 1.3 4,000 or More...................................... 13.3 0.9 1.9 2.2 2.0 6.4 0.6 1.9 Heated Floorspace

228

Total...........................................................  

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

14.7 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500.................................... 3.2 0.7 Q 0.3 0.3 0.7 0.6 0.3 Q 500 to 999........................................... 23.8 2.7 1.4 2.2 2.8 5.5 5.1 3.0 1.1 1,000 to 1,499..................................... 20.8 2.3 1.4 2.4 2.5 3.5 3.5 3.6 1.6 1,500 to 1,999..................................... 15.4 1.8 1.4 2.2 2.0 2.4 2.4 2.1 1.2 2,000 to 2,499..................................... 12.2 1.4 0.9 1.8 1.4 2.2 2.1 1.6 0.8 2,500 to 2,999..................................... 10.3 1.6 0.9 1.1 1.1 1.5 1.5 1.7 0.8 3,000 to 3,499..................................... 6.7 1.0 0.5 0.8 0.8 1.2 0.8 0.9 0.8 3,500 to 3,999..................................... 5.2 1.1 0.3 0.7 0.7 0.4 0.5 1.0 0.5 4,000 or More...................................... 13.3

229

Total................................................  

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

.. .. 111.1 86.6 2,522 1,970 1,310 1,812 1,475 821 1,055 944 554 Total Floorspace (Square Feet) Fewer than 500............................. 3.2 0.9 261 336 162 Q Q Q 334 260 Q 500 to 999.................................... 23.8 9.4 670 683 320 705 666 274 811 721 363 1,000 to 1,499.............................. 20.8 15.0 1,121 1,083 622 1,129 1,052 535 1,228 1,090 676 1,500 to 1,999.............................. 15.4 14.4 1,574 1,450 945 1,628 1,327 629 1,712 1,489 808 2,000 to 2,499.............................. 12.2 11.9 2,039 1,731 1,055 2,143 1,813 1,152 Q Q Q 2,500 to 2,999.............................. 10.3 10.1 2,519 2,004 1,357 2,492 2,103 1,096 Q Q Q 3,000 or 3,499.............................. 6.7 6.6 3,014 2,175 1,438 3,047 2,079 1,108 N N N 3,500 to 3,999.............................. 5.2 5.1 3,549 2,505 1,518 Q Q Q N N N 4,000 or More...............................

230

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

E-Print Network (OSTI)

EV market studies In the absenceof data on actual sales,EV, then we expect 16 to 18% annual of of light-duty vehicle salesEV experiments indicate there is still more than adequatepotential marketsfor electric vehicles to have , exceededthe former 1998CARB mandatefor sales

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

2001-01-01T23:59:59.000Z

231

ZONAL PRICING AND DEMAND-SIDE BIDDING IN THE NORWEGIAN ELECTRICITY MARKET  

E-Print Network (OSTI)

of the Program on Workable Energy Regulation (POWER). POWER is a program of the University of California Energy. University of California Energy Institute 2539 Channing Way Berkeley, California 94720-5180 www-ahead electricity market in Norway. We consider the hypothesis that generators are better able to exercise market

California at Berkeley. University of

232

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

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

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

2008-01-01T23:59:59.000Z

233

Genetic algorithm-based demand response scheme for electric vehicle charging  

Science Journals Connector (OSTI)

This paper presents a design and evaluates the performance of a charging task scheduler for electric vehicles, aiming at reducing the peak load and improving the service ratio in charging stations. Based on a consumption profile and the real-time task model consisting of actuation time, operation length, and deadline, the proposed scheduler fills the time table, by which the power controller turns on or off the electric connection switch to the vehicle on each time slot boundary. Genetic evolutions yield better results by making the initial population include both heuristic-generated schedules for fast convergence and randomly generated schedules for diversity loss compensation. Our heuristic scheme sequentially fills the time slots having lowest load for different orders such as deadline and operation length. The performance measurement result obtained from a prototype implementation reveals that our scheme can reduce the peak load for the given charging task sets by up to 4.9%, compared with conventional schemes.

Junghoon Lee; Gyung-Leen Park

2013-01-01T23:59:59.000Z

234

Modeling, Analysis, and Control of Demand Response Resources  

E-Print Network (OSTI)

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

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

235

Energy Conversion to Electricity  

Science Journals Connector (OSTI)

30 May 1974 research-article Energy Conversion to Electricity D. Clark...continuing growth in the demand for energy, and of electricity as the route...the electricity share of the total energy market and of the substitution of electricity...

1974-01-01T23:59:59.000Z

236

Linkages between demand-side management and congestion in the European electricity transmission system  

Science Journals Connector (OSTI)

Abstract We evaluate the possibility to reduce congestion in the transmission grid through large-scale implementation of demand-side management (DSM) in the form of load shifting for the EU-27 countries, Norway, and Switzerland for Year 2020. A linear, cost-minimising, dispatch model that includes a DC load-flow description of the transmission system and a general representation of load shifting is used. It is assumed that the EU Member States fulfil the targets for Year 2020 in their national renewable energy action plans. In the model calculations, a reference case without load shifting is compared with cases in which the load shifting is 5%, 10%, 15% or 20% of the load. The possibility to shift load in time is added exogenously and economic incentives for DSM are not evaluated. Three types of congestion are identified: peak-load-hour congestion, low-load-hour congestion and all-hour congestion. Peak-load-hour congestion is reduced as the DSM share of the load increases, whereas low-load-hour congestion, which is typically associated with a high level of wind generation, persists at all the DSM penetration levels investigated. We show that all-hour congestion occurs between systems that have large differences in supply structure, and that the impact of DSM on all-hour congestion is low.

Lisa Gransson; Joel Goop; Thomas Unger; Mikael Odenberger; Filip Johnsson

2014-01-01T23:59:59.000Z

237

Wind offering strategy in the Australian National Electricity Market: A two-step plan considering demand response  

Science Journals Connector (OSTI)

Abstract This paper proposes an energy offering strategy for wind power producers. A new trading plan is presented through which a wind power producer can employ demand response (DR) to maximize its profit. To consider DR, a new DR scheme is developed here. The proposed plan includes two steps: The first step takes place on a day-ahead basis. The corresponding decisions involve an initial offering schedule and preliminary DR arrangements for the following day. The second step coincides with the day of the energy delivery. A consecutive approach is proposed in which the wind power producer determines its final energy offer during each trading interval. Simultaneously, the required DR agreements for that interval are also confirmed. This approach is repeated until all periods of the day are covered. The proposed plan is formulated as a stochastic programming approach, where its feasibility is evaluated on a case of the Australian National Electricity Market (NEM).

Nadali Mahmoudi; Tapan K. Saha; Mehdi Eghbal

2015-01-01T23:59:59.000Z

238

Total plastic strain and electrical resistivity in high purity aluminum cyclically strained at 4.2 K  

E-Print Network (OSTI)

TOTAL PLASTIC STRAIN AND ELECTRICAL RESISTIVITY IN HIGH PURITY ALUMINUM CYCLICALLY STRAINED AT 4. 2 K A Thesis by JAMES TERENCE GEHAN Submitted to the Office of Graduate Studies of Texas ARM University in partial fulfillment... of the requirements for the degree of MASTER OF SCIENCE December 1988 Ulajor Subject: 1VIechanical Engineering TOTAL PLASTIC STRAIN AND ELECTRICAL RESISTIVITY IN HIGH PURITY ALUMINUM CYCLICALLY STRAINED AT 4. 2 K A Thesis by JAMES TERENCE GEHAN Approved...

Gehan, James Terence

2012-06-07T23:59:59.000Z

239

A computer-based total productive maintenance model for electric motors  

Science Journals Connector (OSTI)

The paper describes the development of a computer-based total productive maintenance (TPM) model to improve electrical motors readiness and uptime while reducing capital overhead. The TPM model includes the consideration of reactive, periodic, and predictive practices. The input data is processed and the generated report details a set of periodic recommendations providing guidelines on recommended actions and their frequency. The details about test results indicating the current condition of the motor as well estimated reactive, periodic, and predictive maintenance cost details are presented. Based on the historic data stored in its database, the model can predict potential problems prior to failure as well as prescribe periodic maintenance actions to maximise motor life. The TPM model will be a useful tool to predict the degradation in motor life due to deterioration in insulation, bearing, rotor bar and stator windings of the motor.

Aruna Muniswamy; Bhaskaran Gopalakrishnan; Subodh Chaudhari; Majid Jaridi; Ed Crowe; Deepak Gupta

2014-01-01T23:59:59.000Z

240

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

E-Print Network (OSTI)

B. Atanasiu (2006). Electricity Consumption and Efficiencywill see their electricity consumption rise significantly.the bulk of household electricity consumption in developing

Letschert, Virginie

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

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

242

A Hierarchical Demand Response Framework for Data Center Power Cost Optimization Under Real-World Electricity Pricing  

E-Print Network (OSTI)

1 A Hierarchical Demand Response Framework for Data Center Power Cost Optimization Under Real bills. Our focus is on a subset of this work that carries out demand response (DR) by modulating

Urgaonkar, Bhuvan

243

A Hierarchical Demand Response Framework for Data Center Power Cost Optimization Under Real-World Electricity Pricing  

E-Print Network (OSTI)

1 A Hierarchical Demand Response Framework for Data Center Power Cost Optimization Under Real for optimizing their utility bills. Our focus is on a subset of this work that carries out demand response (DR

Urgaonkar, Bhuvan

244

" Row: NAICS Codes; Column: Electricity Components;"  

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

1.1 Electricity: Components of Net Demand, 2010;" 1.1 Electricity: Components of Net Demand, 2010;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Electricity Components;" " Unit: Million Kilowatthours." " "," " " "," ",,,"Total ","Sales and","Net Demand" "NAICS"," ",,"Transfers ","Onsite","Transfers","for" "Code(a)","Subsector and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)" ,,"Total United States" 311,"Food",75652,21,5666,347,80993

245

" Row: NAICS Codes; Column: Electricity Components;"  

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

1.1 Electricity: Components of Net Demand, 2006;" 1.1 Electricity: Components of Net Demand, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Electricity Components;" " Unit: Million Kilowatthours." " "," " " "," ",,,"Total ","Sales and","Net Demand" "NAICS"," ",,"Transfers ","Onsite","Transfers","for" "Code(a)","Subsector and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)" ,,"Total United States" 311,"Food",73242,309,4563,111,78003

246

Novel effects of demand side management data on accuracy of electrical energy consumption modeling and long-term forecasting  

Science Journals Connector (OSTI)

Abstract Worldwide implementation of demand side management (DSM) programs has had positive impacts on electrical energy consumption (EEC) and the examination of their effects on long-term forecasting is warranted. The objective of this study is to investigate the effects of historical DSM data on accuracy of EEC modeling and long-term forecasting. To achieve the objective, optimal artificial neural network (ANN) models based on improved particle swarm optimization (IPSO) and shuffled frog-leaping (SFL) algorithms are developed for EEC forecasting. For long-term EEC modeling and forecasting for the U.S. for 20102030, two historical data types used in conjunction with developed models include (i) EEC and (ii) socio-economic indicators, namely, gross domestic product, energy imports, energy exports, and population for 19672009 period. Simulation results from IPSO-ANN and SFL-ANN models show that using socio-economic indicators as input data achieves lower mean absolute percentage error (MAPE) for long-term EEC forecasting, as compared with EEC data. Based on IPSO-ANN, it is found that, for the U.S. EEC long-term forecasting, the addition of DSM data to socio-economic indicators data reduces MAPE by 36% and results in the estimated difference of 3592.8 MBOE (5849.9TWh) in EEC for 20102030.

F.J. Ardakani; M.M. Ardehali

2014-01-01T23:59:59.000Z

247

Alternative Energy Futures: The Case for Electricity  

Science Journals Connector (OSTI)

...The per capita index of...the average per capita indices of...relative to GDP for total energy, electricity...electricity on the demand side are...Fig. 3. Per capita japan United...rela-States tive to GDP of total energy (cross hatch-ing...D _. demand for conventional...

Umberto Colombo

1982-08-20T23:59:59.000Z

248

Automated Demand Response Opportunities in Wastewater Treatment Facilities  

SciTech Connect

Wastewater treatment is an energy intensive process which, together with water treatment, comprises about three percent of U.S. annual energy use. Yet, since wastewater treatment facilities are often peripheral to major electricity-using industries, they are frequently an overlooked area for automated demand response opportunities. Demand response is a set of actions taken to reduce electric loads when contingencies, such as emergencies or congestion, occur that threaten supply-demand balance, and/or market conditions occur that raise electric supply costs. Demand response programs are designed to improve the reliability of the electric grid and to lower the use of electricity during peak times to reduce the total system costs. Open automated demand response is a set of continuous, open communication signals and systems provided over the Internet to allow facilities to automate their demand response activities without the need for manual actions. Automated demand response strategies can be implemented as an enhanced use of upgraded equipment and facility control strategies installed as energy efficiency measures. Conversely, installation of controls to support automated demand response may result in improved energy efficiency through real-time access to operational data. This paper argues that the implementation of energy efficiency opportunities in wastewater treatment facilities creates a base for achieving successful demand reductions. This paper characterizes energy use and the state of demand response readiness in wastewater treatment facilities and outlines automated demand response opportunities.

Thompson, Lisa; Song, Katherine; Lekov, Alex; McKane, Aimee

2008-11-19T23:59:59.000Z

249

2012,"Total Electric Power Industry","AK","Natural Gas",6,244.7,210.5  

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

TYPE_OF_PRODUCER","STATE_CODE","FUEL_SOURCE","GENERATORS","NAMEPLATE_CAPACITY TYPE_OF_PRODUCER","STATE_CODE","FUEL_SOURCE","GENERATORS","NAMEPLATE_CAPACITY (Megawatts)","SUMMER_CAPACITY (Megawatts)" 2012,"Total Electric Power Industry","AK","Natural Gas",6,244.7,210.5 2012,"Total Electric Power Industry","AK","Petroleum",4,4.8,4.8 2012,"Total Electric Power Industry","AK","Wind",1,24.6,24 2012,"Total Electric Power Industry","AK","All Sources",11,274.1,239.3 2012,"Total Electric Power Industry","AR","Coal",1,755,600 2012,"Total Electric Power Industry","AR","Natural Gas",1,22,20 2012,"Total Electric Power Industry","AR","All Sources",2,777,620

250

Definition: Demand Side Management | Open Energy Information  

Open Energy Info (EERE)

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

251

The Impact of Technological Change and Lifestyles on the Energy Demand  

E-Print Network (OSTI)

demand into a model of total private consumption. Private consumption is determined by economic variables of technological and socio- demographic variables on the demand for gasoline/diesel, heating and electricity. Key, households' electricity and heat consumption are growing rapidly despite of technological progress

Steininger, Karl W.

252

High-Performance with Solar Electric Reduced Peak Demand: Premier Homes Rancho Cordoba, CA- Building America Top Innovation  

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

This Building America Innovations profile describes Building America solar home research that has demonstrated the ability to reduce peak demand by 75%. Numerous field studies have monitored power production and system effectiveness.

253

Strategies for Demand Response in Commercial Buildings  

SciTech Connect

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

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

2006-06-20T23:59:59.000Z

254

Improvements in Test Protocols for Electric Vehicles to Determine Range and Total Energy Consumption  

Science Journals Connector (OSTI)

As electric vehicles have entered the market fairly recently, ... tested the same way as the ICE-driven cars with the exception that determining range is ... However, the current procedures address mainly primary...

Juhani Laurikko; Jukka Nuottimki

2013-01-01T23:59:59.000Z

255

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

256

The use of electrical resistance in the plant stem to measure plant response to soil moisture tension and evaporative demand  

E-Print Network (OSTI)

. . . . . . , . . . . . . ~. . . . . . . . . 30 10- Diurnal cotton plant stem electrical resistance readings as recorded simultaneously from three soil moisture levels. ~ 36 Flot 1-P (cotton), Diurnal cotton plant stem electrical resistance readings with soil moisture tension equal to 13... atsespheresl ~ ~ a ~ ~ ~ ~ ~ . ~ ~ ~ ~ ta ~ I ~ ~ ~ t ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ae ~ ~ ~ a ~ ~ t ~ ~ ~ ~ 37 13 ' Electrical resistance in the plant stem, and evapotrans- piration in non-irrigated and irrigated cotton plots during one diurnal period. . ~ 39 Plots...

Box, James E.

1956-01-01T23:59:59.000Z

257

Thermal Energy Storage for Electricity Peak-demand Mitigation: A Solution in Developing and Developed World Alike  

E-Print Network (OSTI)

N ATIONAL L ABORATORY Thermal Energy Storage for Electricity20, 2012. I. Dincer, On thermal energy storage systems andin research on cold thermal energy storage, International

DeForest, Nicholas

2014-01-01T23:59:59.000Z

258

Demand Response-Enabled Model Predictive HVAC Load Control in Buildings using Real-Time Electricity Pricing.  

E-Print Network (OSTI)

??A practical cost and energy efficient model predictive control (MPC) strategy is proposed for HVAC load control under dynamic real-time electricity pricing. The MPC strategy (more)

Avci, Mesut

2013-01-01T23:59:59.000Z

259

Hot Thermal Storage/Selective Energy System Reduces Electric Demand for Space Cooling As Well As Heating in Commercial Application  

E-Print Network (OSTI)

energy and off-peak electric resistance heating. Estimated energy and first cost savings, as compared with an all-electric VAV HVAC system, are: 30 to 50% in ductwork size and cost; 30% in fan energy; 25% in air handling equipment; 20 to 40% in utility...

Meckler, G.

1985-01-01T23:59:59.000Z

260

The Costs, Air Quality, and Human Health Effects of Meeting Peak Electricity Demand with Installed Backup Generators  

Science Journals Connector (OSTI)

E.G. thanks John Dawson, Rob Pinder, and Pavan Racherla for assistance with the PMCAMx model, and Janet Joseph, Peter Savio, and Gunnar Walmet from NYSERDA for useful information about backup generators and emergency demand response programs in New York City. ...

Elisabeth A. Gilmore; Lester B. Lave; Peter J. Adams

2006-10-21T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

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,

262

Demand-Side Management Expenditures and the Market Value of U.S. Electric Utilities: Strategic Investment or Disinvestment?  

Science Journals Connector (OSTI)

For over eighty years the vertically integrated suppliers of electricity in the United States have been assigned exclusive territorial (consumer) franchises and closely regulated. Both the legal monopolies and th...

Douglas A. Houston

1998-01-01T23:59:59.000Z

263

Table ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States  

Gasoline and Diesel Fuel Update (EIA)

ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States Year Primary Energy Electric Power Sector h,j Retail Electricity Total Energy g,h,i Coal Coal Coke Natural Gas a Petroleum Nuclear Fuel Biomass Total g,h,i,j Coking Coal Steam Coal Total Exports Imports Distillate Fuel Oil Jet Fuel b LPG c Motor Gasoline d Residual Fuel Oil Other e Total Wood and Waste f,g Prices in Dollars per Million Btu 1970 0.45 0.36 0.38 1.27 0.93 0.59 1.16 0.73 1.43 2.85 0.42 1.38 1.71 0.18 1.29 1.08 0.32 4.98 1.65 1975 1.65 0.90 1.03 2.37 3.47 1.18 2.60 2.05 2.96 4.65 1.93 2.94 3.35 0.24 1.50 2.19 0.97 8.61 3.33 1980 2.10 1.38 1.46 2.54 3.19 2.86 6.70 6.36 5.64 9.84 3.88 7.04 7.40 0.43 2.26 4.57 1.77 13.95 6.89 1985 2.03 1.67 1.69 2.76 2.99 4.61 7.22 5.91 6.63 9.01 4.30 R 7.62 R 7.64 0.71 2.47 4.93 1.91 19.05

264

Market and Policy Barriers for Demand Response Providing Ancillary Services in U.S. Markets  

E-Print Network (OSTI)

Wholesale Electricity Demand Response Program Comparison,J. (2009) Open Automated Demand Response Communicationsin Demand Response for Wholesale Ancillary Services.

Cappers, Peter

2014-01-01T23:59:59.000Z

265

Statewide Electrical Energy Cost Savings and Peak Demand Reduction from the IECC Code-Compliant, Single-Family Residences in Texas (2002-2009)  

E-Print Network (OSTI)

peaking plant (i.e., capacity savings), the calculated demand savings in MW were then multiplied by the average capital cost of natural gas combined cycle power plant, $1,165 per kW (Kaplan, 2008) using a 15% reserve margin (Faruqui et al. 2007... to the 2001 and 2006 IECC codes. 72?F Heating, 75?F CoolingSpace Temperature Set point (Simulation adjustment3: Heating 72F, Cooling 75F) (b) Heat Pump House: 0.904 360 0.88 kW (Simulation adjustment3: 1.095 kW) HVAC System Type (a) Electric/Gas...

Kim, H; Baltazar, J.C.; Haberl, J.

266

Demand Response - Policy | Department of Energy  

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

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

267

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

268

The Role of Demand Response in Default Service Pricing  

E-Print Network (OSTI)

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

Barbose, Galen; Goldman, Charles; Neenan, Bernie

2008-01-01T23:59:59.000Z

269

Control Strategy for Domestic Water Heaters during Peak Periods and its Impact on the Demand for Electricity  

Science Journals Connector (OSTI)

Because they store hot water, water heaters are easily-shifted loads that can be controlled to reduce peak demands. However, load shifting may have some detrimental consequences on the domestic hot water supply temperature if the heating element is deactivated for a long period of time. Furthermore, a new peak may be caused if a significant number of heaters are reactivated at the same time. This study presents a control strategy for water heaters that minimizes the pick-up demand when the heating elements are reactivated at the end of a load shifting period and that ensures, in all cases, the client's hot water supply. The study is based on a simulation model of a water heater that was experimentally validated and takes into account the diversity of the population's hot water withdrawal profile. More specifically, the data of 8,167 real water withdrawal profiles of several clients were input into the simulation model in order to evaluate the performance of water heaters under different operating conditions.

Alain Moreau

2011-01-01T23:59:59.000Z

270

Open Automated Demand Response for Small Commerical Buildings  

SciTech Connect

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

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

2009-05-01T23:59:59.000Z

271

Overview of Demand Side Response | Department of Energy  

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

and Energy Officials Need to Know High Electric Demand Days: Clean Energy Strategies for Improving Air Quality Demand Response in U.S. Electricity Markets: Empirical Evidence...

272

"2012 Total Electric Industry- Average Retail Price (cents/kWh)"  

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

Average Retail Price (cents/kWh)" Average Retail Price (cents/kWh)" "(Data from forms EIA-861- schedules 4A-D, EIA-861S and EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",15.713593,13.679941,11.83487,6.6759453,14.017926 "Connecticut",17.343298,14.652335,12.672933,9.6930118,15.54464 "Maine",14.658797,11.52742,7.9819499,".",11.812709 "Massachusetts",14.912724,13.841518,12.566635,4.9056852,13.78825 "New Hampshire",16.070168,13.36121,11.83228,".",14.192854 "Rhode Island",14.404061,11.867247,10.676724,8.2796427,12.740867 "Vermont",17.006075,14.316157,9.9796777,".",14.220244

273

Impact of a solar domestic hot water demand-side management program on an electric utility and its customers  

SciTech Connect

A methodology to assess the economic and environmental impacts of a large scale implementation of solar domestic hot water (SDHW) systems is developed. Energy, emission and demand reductions and their respective savings are quantified. It is shown that, on average, an SDHW system provides an energy reduction of about 3200 kWH, avoided emissions of about 2 tons and a capacity contribution of 0.7 kW to a typical Wisconsin utility that installs 5000 SDHW system. The annual savings from these reductions to utility is {dollar_sign}385,000, providing a return on an investment of over 20{percent}. It is shown that, on average, a consumer will save {dollar_sign}211 annually in hot water heating bills. 8 refs., 7 figs.

Trzeniewski, J.; Mitchell, J.W.; Klein, S.A.; Beckman, W.A.

1996-09-01T23:59:59.000Z

274

Energy and Demand Savings from Implementation Costs in Industrial Facilities  

E-Print Network (OSTI)

.g., natural gas) in each code [6]. Table 1. Energy Streams STREAM CODE Electrical Consumption EC Electrical Demand ED Other Electrical Fees EF Electricity E1 Natural Gas E2 L.P.G. E3 #1 Fuel Oil E4 #2 Fuel Oil E5 #4 Fuel Oil E6 #6 Fuel... that are widely scattered). Therefore, the correlations of implementation costs with electrical consumption and natural gas are also investigated in Tables 2 and 4, because they are highly important both nationally and in Texas. In fact, the total number...

Razinha, J. A.; Heffington, W. M.

275

Best practices and research for handling demand response security issues in the smart grid.  

E-Print Network (OSTI)

??When electricity demand is peak, utilities and other electric Independent Systems Operators (ISOs) keep electric generators on-line in order to meet the high demand. In (more)

Asavachivanthornkul, Prakarn

2010-01-01T23:59:59.000Z

276

Construction of a Demand Side Plant with Thermal Energy Storage  

E-Print Network (OSTI)

storage and its potential impact on the electric utilities and introduces the demand side plant concept....

Michel, M.

1989-01-01T23:59:59.000Z

277

Opportunities, Barriers and Actions for Industrial Demand Response in California  

E-Print Network (OSTI)

industrial demand response (DR) with energy efficiency (EE) to most effectively use electricity and natural gas

McKane, Aimee T.

2009-01-01T23:59:59.000Z

278

EV Project Electric Vehicle Charging Infrastructure Summary Report...  

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

Max electricity demand across all days Min electricity demand across all days Electricity demand on single calendar day with highest peak Charging Unit Usage Residential Level 2...

279

Equity Effects of Increasing-Block Electricity Pricing  

E-Print Network (OSTI)

Evidence from Residential Electricity Demand, Review ofLester D. The Demand for Electricity: A Survey, The BellResidential Demand for Electricity under Inverted Block

Borenstein, Severin

2008-01-01T23:59:59.000Z

280

Energy demand  

Science Journals Connector (OSTI)

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

Geoffrey Greenhalgh

1980-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

Behavioral Aspects in Simulating the Future US Building Energy Demand  

E-Print Network (OSTI)

Importance Total off- site energy demand (2030) 20% decreaseImportance Total off-site energy demand (2030) 20% decreaseImportance Total off-site energy demand (2030) 20% decrease

Stadler, Michael

2011-01-01T23:59:59.000Z

282

Flexible Demand Management under Time-Varying Prices  

E-Print Network (OSTI)

Day in a Typical Hourly Average Electricity Prices . . . . .on demand response to electricity price are mostly conductedassociated with electricity prices, local generation, and

Liang, Yong

2012-01-01T23:59:59.000Z

283

Automated Demand Response and Commissioning  

SciTech Connect

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

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

2005-04-01T23:59:59.000Z

284

Electric Utility Industrial Conservation Programs  

E-Print Network (OSTI)

Electrical Machinery and Equip. 7.0 3.3 3 7.6 3.0 10 7 0 10.8 100.0 90 11.9 100.0 353,5 4 * Total of 12 Industry Maximum Demand s is 832 MW. *..', Total of 12 Industry Annual Electricity Consumption is 2,981,090 Mlm. 723 ESL-IE-83-04-114 Proceedings... Electrical Machinery and Equip. 7.0 3.3 3 7.6 3.0 10 7 0 10.8 100.0 90 11.9 100.0 353,5 4 * Total of 12 Industry Maximum Demand s is 832 MW. *..', Total of 12 Industry Annual Electricity Consumption is 2,981,090 Mlm. 723 ESL-IE-83-04-114 Proceedings...

Norland, D. L.

1983-01-01T23:59:59.000Z

285

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

286

Modeling Electric Vehicle Benefits Connected to Smart Grids  

E-Print Network (OSTI)

the commercial building electricity costs distributed energydegradation costs electricity sales fixed electricity costsvariable electricity costs (energy and demand charges) EV

Stadler, Michael

2012-01-01T23:59:59.000Z

287

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

288

The business value of demand response for balance responsible parties.  

E-Print Network (OSTI)

?? By using IT-solutions, the flexibility on the demand side in the electrical systems could be increased. This is called demand response and is part (more)

Jonsson, Mattias

2014-01-01T23:59:59.000Z

289

Aggregator-Assisted Residential Participation in Demand Response Program.  

E-Print Network (OSTI)

??The demand for electricity of a particular location can vary significantly based on season, ambient temperature, time of the day etc. High demand can result (more)

Hasan, Mehedi

2012-01-01T23:59:59.000Z

290

Modeling, Analysis, and Control of Demand Response Resources.  

E-Print Network (OSTI)

??While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can plan an active role in (more)

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

291

Modeling, Analysis, and Control of Demand Response Resources.  

E-Print Network (OSTI)

?? While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can plan an active role (more)

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

292

Industrial Equipment Demand and Duty Factors  

E-Print Network (OSTI)

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

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

293

Harnessing the power of demand  

SciTech Connect

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

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

2008-03-15T23:59:59.000Z

294

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

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

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

295

U.S. Coal Supply and Demand  

Gasoline and Diesel Fuel Update (EIA)

U.S. Coal Supply and Demand > U.S. Coal Supply and Demand U.S. Coal Supply and Demand > U.S. Coal Supply and Demand U.S. Coal Supply and Demand 2010 Review (entire report also available in printer-friendly format ) Previous Editions 2009 Review 2008 Review 2007 Review 2006 Review 2005 Review 2004 Review 2003 Review 2002 Review 2001 Review 2000 Review 1999 Review Data for: 2010 Released: May 2011 Next Release Date: April 2012 Table 3. Electric Power Sector Net Generation, 2009-2010 (Million Kilowatthours) New England Coal 14,378 14,244 -0.9 Hydroelectric 7,759 6,861 -11.6 Natural Gas 48,007 54,680 13.9 Nuclear 36,231 38,361 5.9 Other (1) 9,186 9,063 -1.3 Total 115,559 123,210 6.6 Middle Atlantic Coal 121,873 129,935 6.6 Hydroelectric 28,793 26,463 -8.1 Natural Gas 89,808 104,341 16.2 Nuclear 155,140 152,469 -1.7

296

Cooperative Demand Response Using RepeatedGame for Price-Anticipating Buildings in Smart Grid  

E-Print Network (OSTI)

E. El-Saadany, A summary of demand response in electricityYang, and X. Guan, Optimal demand response scheduling withwith application to demand response, IEEE Transactions on

Ma, Kai; Hu, Guoqiang; Spanos, Costas J

2014-01-01T23:59:59.000Z

297

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

E-Print Network (OSTI)

2001. Electricity Demand Side Management Study: Review ofEpping/North Ryde Demand Side Management Scoping Study:Energy Agency Demand Side Management (IEA DSM) Programme:

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

2007-01-01T23:59:59.000Z

298

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

E-Print Network (OSTI)

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

299

Energy Efficiency Funds and Demand Response Programs - National Overview  

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

Funds and Demand Funds and Demand Response Programs - National Overview Charles Goldman Lawrence Berkeley National Laboratory November 2, 2006 Federal Utility Partnership Working Group San Francisco CA Overview of Talk * National Overview * Energy Efficiency Programs and Funds * Demand Response Programs and Funds * FEMP Resources on Public Benefit Funds *Suggestions for Federal Customers DSM Spending is increasing! * 2006 Utility DSM and Public Benefit spending is ~$2.5B$ - $1B for C&I EE programs * CA utilities account for 35% of total spending 0.0 0.5 1.0 1.5 2.0 2.5 3.0 1994 2000 2005 2006 Costs (in billion $) DSM Costs Load Management Gas EE Other States Electric EE California Electric EE EE Spending in 2006 (by State) $ Million < 1 (23) 1 - 10 (2) 11 - 50 (13) 51 - 100 (7) > 100 (5) 790 101 257

300

Demand Response (transactional control) - Energy Innovation Portal  

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

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

Note: This page contains sample records for the topic "total electricity demand" 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

EV Project Electric Vehicle Charging Infrastructure Summary Report...  

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

all days Percentage of charging units connected on single calendar day with peak electricity demand Charging Demand: Range of Aggregate Electricity Demand versus Time of Day...

302

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

E-Print Network (OSTI)

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

Sastry, S. Shankar

303

NCEP_Demand_Response_Draft_111208.indd  

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

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

304

Cogeneration System Size Optimization Constant Capacity and Constant Demand Models  

E-Print Network (OSTI)

known to the observer. Hence, the elements of W consists of the totality of outcomes that we associate with the states of nature Wj' Four basic outcomes are defined by the following relations: 1) Pc > Pd 2) Pc Hd 4) Hc Hd Where... and heat demand-there exist the following states of nature Wj: WI Hc > Hd and Pc > Pd w2 Hc > Hd and Pc Hd and Pc > Pd w4 Hc Hd and Pc < Pd where heat and electricity demands are expressed in power unit, i.e kWt and kWe, respectively...

Wong-Kcomt, J. B.; Turner, W. C.

305

Security and privacy in demand response systems in smart grid.  

E-Print Network (OSTI)

??Demand response programs are used in smart grid to improve stability of the electric grid and to reduce consumption of electricity and costs during peak (more)

Paranjpe, Mithila

2011-01-01T23:59:59.000Z

306

The Important Participants in Demand-Side Management: Power Consumers  

Science Journals Connector (OSTI)

Electric power consumers are the basis for demand-side management (DSM) practice. Increased power consumption efficiency...

Zhaoguang Hu; Xinyang Han; Quan Wen

2013-01-01T23:59:59.000Z

307

Configuring load as a resource for competitive electricity markets--Review of demand response programs in the U.S. and around the world  

E-Print Network (OSTI)

emergencies (see Table 2). Xcels Electric Reduction Savingsinstead, operated so that Xcel could avoid exceeding MAPPElectricity Cooperative Xcel Energy Investor-Owned Utility

Heffner, Grayson C.

2002-01-01T23:59:59.000Z

308

Building America Top Innovations Hall of Fame Profile … High-Performance with Solar Electric Reduced Peak Demand: Premier Homes Rancho Cordoba, CA  

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

95 homes in Premier Gardens are 95 homes in Premier Gardens are equipped with photovoltaic panels that take advantage of solar energy to offset peak power loads during the hottest part of the day. As the housing market continues to evolve toward zero net-energy ready homes, Building America research has provided essential guidance for integrating renewable energy systems with high-performance homes and showing how they align with utility peak-demand reduction interests. Solar photovoltaic technology is an attractive option for utilities because they can reduce reliance on fossil-fuel energy. More significantly, it reduces peak demand because systems produce the most power on sunny summer afternoons coincident with the highest demand for air conditioning. Photovoltaic systems have been a part of several research projects conducted by

309

"YEAR","MONTH","STATE","UTILITY CODE","UTILITY NAME","RESIDENTIAL PHOTOVOLTAIC ELECTRIC ENERGY SOLD BACK (MWh)","COMMERCIAL PHOTOVOLTAIC ELECTRIC ENERGY SOLD BACK (MWh)","INDUSTRIAL PHOTOVOLTAIC ELECTRIC ENERGY SOLD BACK (MWh)","TRANSPORTATION PHOTOVOLTAIC ELECTRIC ENERGY SOLD BACK (MWh)","TOTAL PHOTOVOLTAIC ELECTRIC ENERGY SOLD BACK (MWh)","RESIDENTIAL PHOTOVOLTAIC INSTALLED NET METERING CAPACITY (MW)","COMMERCIAL PHOTOVOLTAIC INSTALLED NET METERING CAPACITY (MW)","INDUSTRIAL PHOTOVOLTAIC INSTALLED NET METERING CAPACITY (MW)","TRANSPORTATION PHOTOVOLTAIC INSTALLED NET METERING CAPACITY (MW)","TOTAL PHOTOVOLTAIC INSTALLED NET METERING CAPACITY (MW)","RESIDENTIAL PHOTOVOLTAIC NET METERING CUSTOMER COUNT","COMMERCIAL PHOTOVOLTAIC NET METERING CUSTOMER COUNT","INDUSTRIAL PHOTOVOLTAIC NET METERING CUSTOMER COUNT","TRANSPORTATIONPHOTOVOLTAIC NET METERING CUSTOMER COUNT","TOTAL PHOTOVOLTAIC NET METERING CUSTOMER COUNT","RESIDENTIAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","COMMERCIAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","INDUSTRIAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","TRANSPORTATION WIND ELECTRIC ENERGY SOLD BACK (MWh)","TOTAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","RESIDENTIAL WIND INSTALLED NET METERING CAPACITY (MW)","COMMERCIAL WIND INSTALLED NET METERING CAPACITY (MW)","INDUSTRIAL WIND INSTALLED NET METERING CAPACITY (MW)","TRANSPORTATION WIND INSTALLED NET METERING CAPACITY (MW)","TOTAL WIND INSTALLED NET METERING CAPACITY (MW)","RESIDENTIAL WIND NET METERING CUSTOMER COUNT","COMMERCIAL WIND NET METERING CUSTOMER COUNT","INDUSTRIAL WIND NET METERING CUSTOMER COUNT","TRANSPORTATION WIND NET METERING CUSTOMER COUNT","TOTAL WIND NET METERING CUSTOMER COUNT","RESIDENTIAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","COMMERCIAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","INDUSTRIAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","TRANSPORTATION OTHER ELECTRIC ENERGY SOLD BACK (MWh)","TOTAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","RESIDENTIAL OTHER INSTALLED NET METERING CAPACITY (MW)","COMMERCIAL OTHER INSTALLED NET METERING CAPACITY (MW)","INDUSTRIAL OTHER INSTALLED NET METERING CAPACITY (MW)","TRANSPORTATION OTHER INSTALLED NET METERING CAPACITY (MW)","TOTAL OTHER INSTALLED NET METERING CAPACITY (MW)","RESIDENTIAL OTHER NET METERING CUSTOMER COUNT","COMMERCIAL OTHER NET METERING CUSTOMER COUNT","INDUSTRIAL OTHER NET METERING CUSTOMER COUNT","TRANSPORTATION OTHER NET METERING CUSTOMER COUNT","TOTAL OTHER NET METERING CUSTOMER COUNT","RESIDENTIAL TOTAL ENERGY SOLD BACK TO THE UTILITY (MWh)","COMMERCIAL TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","INDUSTRIAL TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","TRANSPORTATION TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","RESIDENTIAL TOTAL INSTALLED NET METERING CAPACITY (MW)","COMMERCIAL TOTAL INSTALLED NET METERING CAPACITY (MW)","INDUSTRIAL TOTAL INSTALLED NET METERING CAPACITY (MW)","TRANSPORTATION TOTAL INSTALLED NET METERING CAPACITY (MW)","TOTAL INSTALLED NET METERING CAPACITY (MW)","RESIDENTIAL TOTAL NET METERING CUSTOMER COUNT","COMMERCIAL TOTAL NET METERING CUSTOMER COUNT","INDUSTRIAL TOTAL NET METERING CUSTOMER COUNT","TRANSPORTATION TOTAL NET METERING CUSTOMER COUNT","TOTAL NET METERING CUSTOMER COUNT","RESIDENTIAL ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","COMMERCIAL ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","INDUSTRIAL ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","TRANSPORTATION ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","TOTAL ELECTRIC ENERGY SOLD BACK TO THE UTILITYFOR ALL STATES SERVED(MWh)","RESIDENTIAL INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","COMMERCIAL INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","INDUSTRIAL INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","TRANSPORTATION INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","RESIDENTIAL NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","COMMERCIAL NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","INDUSTRIAL NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","TRANSPORTATION NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","NET METERING CUSTOMER COUNT FOR ALL STATES SERVED"  

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

TRANSPORTATIONPHOTOVOLTAIC NET METERING CUSTOMER COUNT","TOTAL PHOTOVOLTAIC NET METERING CUSTOMER COUNT","RESIDENTIAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","COMMERCIAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","INDUSTRIAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","TRANSPORTATION WIND ELECTRIC ENERGY SOLD BACK (MWh)","TOTAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","RESIDENTIAL WIND INSTALLED NET METERING CAPACITY (MW)","COMMERCIAL WIND INSTALLED NET METERING CAPACITY (MW)","INDUSTRIAL WIND INSTALLED NET METERING CAPACITY (MW)","TRANSPORTATION WIND INSTALLED NET METERING CAPACITY (MW)","TOTAL WIND INSTALLED NET METERING CAPACITY (MW)","RESIDENTIAL WIND NET METERING CUSTOMER COUNT","COMMERCIAL WIND NET METERING CUSTOMER COUNT","INDUSTRIAL WIND NET METERING CUSTOMER COUNT","TRANSPORTATION WIND NET METERING CUSTOMER COUNT","TOTAL WIND NET METERING CUSTOMER COUNT","RESIDENTIAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","COMMERCIAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","INDUSTRIAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","TRANSPORTATION OTHER ELECTRIC ENERGY SOLD BACK (MWh)","TOTAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","RESIDENTIAL OTHER INSTALLED NET METERING CAPACITY (MW)","COMMERCIAL OTHER INSTALLED NET METERING CAPACITY (MW)","INDUSTRIAL OTHER INSTALLED NET METERING CAPACITY (MW)","TRANSPORTATION OTHER INSTALLED NET METERING CAPACITY (MW)","TOTAL OTHER INSTALLED NET METERING CAPACITY (MW)","RESIDENTIAL OTHER NET METERING CUSTOMER COUNT","COMMERCIAL OTHER NET METERING CUSTOMER COUNT","INDUSTRIAL OTHER NET METERING CUSTOMER COUNT","TRANSPORTATION OTHER NET METERING CUSTOMER COUNT","TOTAL OTHER NET METERING CUSTOMER COUNT","RESIDENTIAL TOTAL ENERGY SOLD BACK TO THE UTILITY (MWh)","COMMERCIAL TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","INDUSTRIAL TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","TRANSPORTATION TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","RESIDENTIAL TOTAL INSTALLED NET METERING CAPACITY (MW)","COMMERCIAL TOTAL INSTALLED NET METERING CAPACITY (MW)","INDUSTRIAL TOTAL INSTALLED NET METERING CAPACITY (MW)","TRANSPORTATION TOTAL INSTALLED NET METERING CAPACITY (MW)","TOTAL INSTALLED NET METERING CAPACITY (MW)","RESIDENTIAL TOTAL NET METERING CUSTOMER COUNT","COMMERCIAL TOTAL NET METERING CUSTOMER COUNT","INDUSTRIAL TOTAL NET METERING CUSTOMER COUNT","TRANSPORTATION TOTAL NET METERING CUSTOMER COUNT","TOTAL NET METERING CUSTOMER COUNT","RESIDENTIAL ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","COMMERCIAL ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","INDUSTRIAL ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","TRANSPORTATION ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","TOTAL ELECTRIC ENERGY SOLD BACK TO THE UTILITYFOR ALL STATES SERVED(MWh)","RESIDENTIAL INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","COMMERCIAL INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","INDUSTRIAL INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","TRANSPORTATION INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","RESIDENTIAL NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","COMMERCIAL NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","INDUSTRIAL NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","TRANSPORTATION NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","NET METERING CUSTOMER COUNT FOR ALL STATES SERVED"

310

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

311

Demand Response and Open Automated Demand Response  

E-Print Network (OSTI)

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

312

A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data  

E-Print Network (OSTI)

changes of HVAC source EUI between AMY and TMY3. (a) largeof total building source EUI. (a) large office, 90.1-2004a) changes in HVAC source EUI; (b) changes in total source

Hong, Tianzhen

2014-01-01T23:59:59.000Z

313

Electricity Monthly Update  

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

Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and...

314

Electricity Monthly Update  

Annual Energy Outlook 2012 (EIA)

Update November 28, 2012 Map of Electric System Selected for Daily Peak Demand was replaced with the correct map showing Selected Wholesale Electricity and Natural Gas Locations....

315

ELECTRIC  

Office of Legacy Management (LM)

you nay give us will be greatly uppreckted. VPry truly your23, 9. IX. Sin0j3, Mtinager lclectronics and Nuclear Physics Dept. omh , WESTINGHOUSE-THE NAT KING IN ELECTRICITY...

316

Demand Response Spinning Reserve Demonstration  

SciTech Connect

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

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

2007-05-01T23:59:59.000Z

317

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

318

How Can China Lighten Up? Urbanization, Industrialization and Energy Demand Scenarios  

E-Print Network (OSTI)

on the forecast of total energy demand. Based on this, weadjustment spurred energy demand for construction of newenergy services. Primary energy demand grew at an average

Aden, Nathaniel T.

2010-01-01T23:59:59.000Z

319

Total energy cycle assessment of electric and conventional vehicles: an energy and environmental analysis. Volume 2: appendices A-D to technical report  

SciTech Connect

This report compares the energy use, oil use and emissions of electric vehicles (EVs) with those of conventional, gasoline- powered vehicles (CVs) over the total life cycle of the vehicles. The various stages included in the vehicles` life cycles include vehicle manufacture, fuel production, and vehicle operation. Disposal is not included. An inventory of the air emissions associated with each stage of the life cycle is estimated. Water pollutants and solid wastes are reported for individual processes, but no comprehensive inventory is developed. Volume II contains additional details on the vehicle, utility, and materials analyses and discusses several details of the methodology.

NONE

1998-01-01T23:59:59.000Z

320

Total energy cycle assessment of electric and conventional vehicles: an energy and environmental analysis. Volume 4: peer review comments on technical report  

SciTech Connect

This report compares the energy use, oil use and emissions of electric vehicles (EVs) with those of conventional, gasoline-powered vehicles (CVs) over the total life cycle of the vehicles. The various stages included in the vehicles` life cycles include vehicle manufacture, fuel production, and vehicle operation. Disposal is not included. An inventory of the air emissions associated with each stage of the life cycle is estimated. Water pollutants and solid wastes are reported for individual processes, but no comprehensive inventory is developed. Volume IV includes copies of all the external peer review comments on the report distributed for review in July 1997.

NONE

1998-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

Annual Energy Outlook with Projections to 2025 - Market Trends- Electricity  

Gasoline and Diesel Fuel Update (EIA)

Electricity Demand and Supply Electricity Demand and Supply Annual Energy Outlook 2005 Market Trends - Electricity Demand and Supply Continued Growth in Electricity Use Is Expected in All Sectors Figure 66. Annual electricity sales by sector, 1970-2025 (billion kilowatthours). Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure data Total electricity sales are projected to increase at an average annual rate of 1.9 percent in the AEO2005 reference case, from 3,481 billion kilowatthours in 2003 to 5,220 billion kilowatthours in 2025 (Figure 66). From 2003 to 2025, annual growth in electricity sales is projected to average 1.6 percent in the residential sector, 2.5 percent in the commercial sector, and 1.3 percent in the industrial sector.

322

Commercial & Industrial Demand Response  

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

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

323

"State","Fossil Fuels",,,,,,"Nuclear Electric Power",,"Renewable Energy",,,,,,"Total Energy Production"  

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

P2. Energy Production Estimates in Trillion Btu, 2011 " P2. Energy Production Estimates in Trillion Btu, 2011 " "State","Fossil Fuels",,,,,,"Nuclear Electric Power",,"Renewable Energy",,,,,,"Total Energy Production" ,"Coal a",,"Natural Gas b",,"Crude Oil c",,,,"Biofuels d",,"Other e",,"Total" ,"Trillion Btu" "Alabama",468.671,,226.821,,48.569,,411.822,,0,,245.307,,245.307,,1401.191 "Alaska",33.524,,404.72,,1188.008,,0,,0,,15.68,,15.68,,1641.933 "Arizona",174.841,,0.171,,0.215,,327.292,,7.784,,107.433,,115.217,,617.734 "Arkansas",2.985,,1090.87,,34.087,,148.531,,0,,113.532,,113.532,,1390.004 "California",0,,279.71,,1123.408,,383.644,,25.004,,812.786,,837.791,,2624.553

324

The alchemy of demand response: turning demand into supply  

SciTech Connect

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

Rochlin, Cliff

2009-11-15T23:59:59.000Z

325

A Full Demand Response Model in Co-Optimized Energy and  

SciTech Connect

It has been widely accepted that demand response will play an important role in reliable and economic operation of future power systems and electricity markets. Demand response can not only influence the prices in the energy market by demand shifting, but also participate in the reserve market. In this paper, we propose a full model of demand response in which demand flexibility is fully utilized by price responsive shiftable demand bids in energy market as well as spinning reserve bids in reserve market. A co-optimized day-ahead energy and spinning reserve market is proposed to minimize the expected net cost under all credible system states, i.e., expected total cost of operation minus total benefit of demand, and solved by mixed integer linear programming. Numerical simulation results on the IEEE Reliability Test System show effectiveness of this model. Compared to conventional demand shifting bids, the proposed full demand response model can further reduce committed capacity from generators, starting up and shutting down of units and the overall system operating costs.

Liu, Guodong [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)

2014-01-01T23:59:59.000Z

326

Manuscript submitted to Electricity Journal 6/2/2006 Steven Letendre Richard Perez  

E-Print Network (OSTI)

Manuscript submitted to Electricity Journal 6/2/2006 Steven Letendre Richard Perez The Prometheus of the U.S. electric grid has become increasingly complex as it has been called upon to accommodate growth in total electricity consumption of 75%, accompanied by an increase in non-coincident peak demand in excess

Perez, Richard R.

327

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

328

Table A51. Number of Establishments by Sponsorship of Any Programs of Demand  

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

1. Number of Establishments by Sponsorship of Any Programs of Demand-Side Management through" 1. Number of Establishments by Sponsorship of Any Programs of Demand-Side Management through" " Electric Utility and Natural Gas Utility, by Industry Group and Selected Industries, 1994" ,," "," ",," "," ",," "," "," "," " ,," "," ","Any Programs"," "," ","Any Programs"," "," ",," " ,," "," of DSM Sponsored through Electric Utility(b)",,," of DSM Sponsored through Natural Gas Utility(c)",,,"RSE" "SIC"," ",,,,,,,,"Row" "Code(a)","Industry Group and Industry","Total","Sponsored","Not Sponsored","Don't Know","Sponsored","Not Sponsored","Don't Know","Factors"

329

A Dynamic household Alternative-fuel Vehicle Demand Model Using Stated and Revealed Transaction Information  

E-Print Network (OSTI)

Potential Demand for Electric Cars, Journal of Economrtricsand one large car) and one mini electric car. The two modelsscenarios: (i) a subcompact electric car is introduced to

Sheng, Hongyan

1999-01-01T23:59:59.000Z

330

Reliability implications of price responsive demand : a study of New England's power system  

E-Print Network (OSTI)

With restructuring of the traditional, vertically integrated electricity industry come new opportunities for electricity demand to actively participate in electricity markets. Traditional definitions of power system ...

Whitaker, Andrew C. (Andrew Craig)

2011-01-01T23:59:59.000Z

331

U.S. Coal Supply and Demand: 2001 Review  

Gasoline and Diesel Fuel Update (EIA)

U.S. Coal Supply and Demand: 2001 Review U.S. Coal Supply and Demand: 2001 Review 1 U.S. Coal Supply and Demand: 2001 Review (Revised 5/6/2002) 1 by Fred Freme U.S. Energy Information Administration 1 This article has been revised, deleting 17.6 millions short tons of coal consumed by the manufacturers of synthetic coal from the consumption of coal by "other industrial plants." This change was made because the synthetic coal those plants produced was primarily consumed in the electric sector and reported as coal, resulting in an overstating of total coal consumption. Overview With the dawning of a new century came the beginning of a new era in the coal industry. Instead of the traditional prac- tice of only buying and selling produced coal in the United

332

Response to changes in demand/supply  

E-Print Network (OSTI)

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

333

A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data  

E-Print Network (OSTI)

53: Total energy use in buildings evaluation and analysisTY. A design day for building load and energy estimation.Building and Environment, 1999; 34(4): 469-477. [5] Hong TZ,

Hong, Tianzhen

2014-01-01T23:59:59.000Z

334

ELECTRIC  

Office of Legacy Management (LM)

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

335

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"

336

Renewable Electricity Futures for the United States  

SciTech Connect

This paper highlights the key results from the Renewable Electricity (RE) Futures Study. It is a detailed consideration of renewable electricity in the United States. The paper focuses on technical issues related to the operability of the U. S. electricity grid and provides initial answers to important questions about the integration of high penetrations of renewable electricity technologies from a national perspective. The results indicate that the future U. S. electricity system that is largely powered by renewable sources is possible and the further work is warranted to investigate this clean generation pathway. The central conclusion of the analysis is that renewable electricity generation from technologies that are commercially available today, in combination with a more flexible electric system, is more than adequate to supply 80% of the total U. S. electricity generation in 2050 while meeting electricity demand on an hourly basis in every region of the United States.

Mai, Trieu; Hand, Maureen; Baldwin, Sam F.; Wiser , Ryan; Brinkman, G.; Denholm, Paul; Arent, Doug; Porro, Gian; Sandor, Debra; Hostick, Donna J.; Milligan, Michael; DeMeo, Ed; Bazilian, Morgan

2014-04-14T23:59:59.000Z

337

Graphical language for identification of control strategies allowing Demand Response  

E-Print Network (OSTI)

Graphical language for identification of control strategies allowing Demand Response David DA SILVA. This will allow the identification of the electric appliance availability for demand response control strategies to be implemented in terms of demand response for electrical appliances. Introduction An important part

Paris-Sud XI, Université de

338

D:\assumptions_2001\assumptions2002\currentassump\demand.vp  

Gasoline and Diesel Fuel Update (EIA)

2 2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Petroleum Market Module. . . . . . . . . . . . .

339

Home Network Technologies and Automating Demand Response  

SciTech Connect

Over the past several years, interest in large-scale control of peak energy demand and total consumption has increased. While motivated by a number of factors, this interest has primarily been spurred on the demand side by the increasing cost of energy and, on the supply side by the limited ability of utilities to build sufficient electricity generation capacity to meet unrestrained future demand. To address peak electricity use Demand Response (DR) systems are being proposed to motivate reductions in electricity use through the use of price incentives. DR systems are also be design to shift or curtail energy demand at critical times when the generation, transmission, and distribution systems (i.e. the 'grid') are threatened with instabilities. To be effectively deployed on a large-scale, these proposed DR systems need to be automated. Automation will require robust and efficient data communications infrastructures across geographically dispersed markets. The present availability of widespread Internet connectivity and inexpensive, reliable computing hardware combined with the growing confidence in the capabilities of distributed, application-level communications protocols suggests that now is the time for designing and deploying practical systems. Centralized computer systems that are capable of providing continuous signals to automate customers reduction of power demand, are known as Demand Response Automation Servers (DRAS). The deployment of prototype DRAS systems has already begun - with most initial deployments targeting large commercial and industrial (C & I) customers. An examination of the current overall energy consumption by economic sector shows that the C & I market is responsible for roughly half of all energy consumption in the US. On a per customer basis, large C & I customers clearly have the most to offer - and to gain - by participating in DR programs to reduce peak demand. And, by concentrating on a small number of relatively sophisticated energy consumers, it has been possible to improve the DR 'state of the art' with a manageable commitment of technical resources on both the utility and consumer side. Although numerous C & I DR applications of a DRAS infrastructure are still in either prototype or early production phases, these early attempts at automating DR have been notably successful for both utilities and C & I customers. Several factors have strongly contributed to this success and will be discussed below. These successes have motivated utilities and regulators to look closely at how DR programs can be expanded to encompass the remaining (roughly) half of the state's energy load - the light commercial and, in numerical terms, the more important residential customer market. This survey examines technical issues facing the implementation of automated DR in the residential environment. In particular, we will look at the potential role of home automation networks in implementing wide-scale DR systems that communicate directly to individual residences.

McParland, Charles

2009-12-01T23:59:59.000Z

340

National Action Plan on Demand Response  

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

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

Note: This page contains sample records for the topic "total electricity demand" 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

Demand response in future power systems management a conceptual framework and simulation tool.  

E-Print Network (OSTI)

??Mestrado em Engenharia Electrotcnica Sistemas Elctricos de Energia In competitive electricity markets with deep efficiency concerns, demand response gains significant importance. Moreover, demand response (more)

Faria, Pedro

2011-01-01T23:59:59.000Z

342

THE FUTURE DEMAND FOR ALTERNATIVE FUEL PASSENGER VEHICLES: A DIFFUSION OF INNOVATION APPROACH  

E-Print Network (OSTI)

.......................................................................................................... 5 2.1 AUTOMOBILE DEMAND MODELS.....................................................................................................................20 2.2.4 The Application of Diffusion Models to Automobile Demand.......................................................................................................................................36 3.1.5 Electric Vehicles

Levinson, David M.

343

Quantifying the Variable Effects of Systems with Demand Response Resources  

E-Print Network (OSTI)

Quantifying the Variable Effects of Systems with Demand Response Resources Anupama Kowli and George in the electricity industry. In particular, there is a new class of consumers, called demand response resources (DRRs

Gross, George

344

Research on the Demand Side Management Under Smart Grid  

Science Journals Connector (OSTI)

From the 1970 of the twentieth century demand side management has gradually become standardized management mode in electric power industry in developed ... coverage, full collection, full prepayment to demand-side

Litong Dong; Jun Xu; Haibo Liu; Ying Guo

2014-01-01T23:59:59.000Z

345

A Vision of Demand Response - 2016  

SciTech Connect

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

Levy, Roger

2006-10-15T23:59:59.000Z

346

What China Can Learn from International Experiences in Developing a Demand  

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

What China Can Learn from International Experiences in Developing a Demand What China Can Learn from International Experiences in Developing a Demand Response Program Title What China Can Learn from International Experiences in Developing a Demand Response Program Publication Type Conference Proceedings Year of Publication 2012 Authors Shen, Bo, Chun Chun Ni, Girish Ghatikar, and Lynn K. Price Conference Name ECEEE Summer Study on Energy Efficiency in Industry Date Published 06/2012 Conference Location Arnhem, the Netherlands Keywords china, demand response program, electricity, market sectors Abstract China has achieved remarkable economic growth over the last decade. To fuel the growth, China addeda total of 455 gigawatts of new generation capacity between 2006 and 2011, which is an increase of 76%in five years. Even so, this capacity does not meet the growing demand for electricity, and most ofChina's industrial sector is facing the worst power shortages since 2004. The Chinese government hasbeen managing the capacity shortfall through direct load control programs. While such mandatoryprograms have spared China from electricity outages, it does so at a high cost to the industrial sector.The load control program has significantly affected business operations and economic outputs, whilefailing to trigger greater energy efficiency improvement. Instead, it has led to a proliferation of dieselgenerators used by industrial facilities when electricity is not delivered, increasing diesel use andassociated air pollution.

347

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

348

Optimal Sizing of Energy Storage and Photovoltaic Power Systems for Demand Charge Mitigation (Poster)  

SciTech Connect

Commercial facility utility bills are often a strong function of demand charges -- a fee proportional to peak power demand rather than total energy consumed. In some instances, demand charges can constitute more than 50% of a commercial customer's monthly electricity cost. While installation of behind-the-meter solar power generation decreases energy costs, its variability makes it likely to leave the peak load -- and thereby demand charges -- unaffected. This then makes demand charges an even larger fraction of remaining electricity costs. Adding controllable behind-the-meter energy storage can more predictably affect building peak demand, thus reducing electricity costs. Due to the high cost of energy storage technology, the size and operation of an energy storage system providing demand charge management (DCM) service must be optimized to yield a positive return on investment (ROI). The peak demand reduction achievable with an energy storage system depends heavily on a facility's load profile, so the optimal configuration will be specific to both the customer and the amount of installed solar power capacity. We explore the sensitivity of DCM value to the power and energy levels of installed solar power and energy storage systems. An optimal peak load reduction control algorithm for energy storage systems will be introduced and applied to historic solar power data and meter load data from multiple facilities for a broad range of energy storage system configurations. For each scenario, the peak load reduction and electricity cost savings will be computed. From this, we will identify a favorable energy storage system configuration that maximizes ROI.

Neubauer, J.; Simpson, M.

2013-10-01T23:59:59.000Z

349

Electricity Markets  

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

Electricity Markets Electricity Markets Researchers in the electricity markets area conduct technical, economic, and policy analysis of energy topics centered on the U.S. electricity sector. Current research seeks to inform public and private decision-making on public-interest issues related to energy efficiency and demand response, renewable energy, electricity resource and transmission planning, electricity reliability and distributed generation resources. Research is conducted in the following areas: Energy efficiency research focused on portfolio planning and market assessment, design and implementation of a portfolio of energy efficiency programs that achieve various policy objectives, utility sector energy efficiency business models, options for administering energy efficiency

350

Hydrogen Energy Stations: Poly-Production of Electricity, Hydrogen, and Thermal Energy  

E-Print Network (OSTI)

Hydrogen and Electricity: Public-Private Partnershipand electricity demands. Foster Public-Private Partnershipand electricity demands. Foster Public-Private Partnership

Lipman, Timothy; Brooks, Cameron

2006-01-01T23:59:59.000Z

351

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

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

Shen, Bo

2013-01-01T23:59:59.000Z

352

Network-Driven Demand Side Management Website | Open Energy Informatio...  

Open Energy Info (EERE)

UtilityElectricity Service Costs) for this property. This task of the International Energy Agency is a broad, systematic examination of the potential for demand-side...

353

Reducing Peak Demand to Defer Power Plant Construction in Oklahoma  

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

costs and manage electric reliability under these conditions, OG&E is pursuing demand response strategies made possible by implementation of smart grid technologies, tools, and...

354

Automated demand response applied to a set of commercial facilities.  

E-Print Network (OSTI)

?? Commercial facility demand response refers to voluntary actions by customers that change their consumption of electric power in response to price signals, incentives, or (more)

Lincoln, Donald F.

2010-01-01T23:59:59.000Z

355

Demand Response National Trends: Implications for the West? ...  

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

National Trends: Implications for the West? Demand Response National Trends: Implications for the West? Committee on Regional Electric Power Cooperation. San Francisco, CA. March...

356

Automated demand response applied to a set of commercial buildings.  

E-Print Network (OSTI)

??Commercial facility demand response refers to voluntary actions by customers that change their consumption of electric power in response to price signals, incentives, or directions (more)

Lincoln, Donald

2010-01-01T23:59:59.000Z

357

A study of industrial equipment energy use and demand control.  

E-Print Network (OSTI)

??Demand and duty factors were measured for selected equipment [air compressors, electric furnaces, injection-molding machines, a welder, a granulator (plastics grinder), a sheet metal press (more)

Dooley, Edward Scott

2012-01-01T23:59:59.000Z

358

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Highlights: August 2011 Highlights: August 2011 Extreme heat in Texas, New Mexico, Colorado and Arizona drove significant increases in the retail sales of electricity in the Southwest. Wind generation increased in much of the United States, except the middle of the country where total generation declined. Bituminous coal stocks dropped 14% from August 2010. Key indicators Same Month 2010 Year to date Total Net Generation -1% 11% Residential Retail Price -6% 11% Cooling Degree-Days -3% 2% Natural Gas Price, Henry Hub -6% -9% Bituminous Coal Stocks -14% -14% Subbituminous Coal Stocks -10% -17% Heat wave drives record demand and wholesale prices in Texas A prolonged August heat wave in Texas stressed available generating capacity and produced very high wholesale prices in the Electric

359

Demand Response Valuation Frameworks Paper  

E-Print Network (OSTI)

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

Heffner, Grayson

2010-01-01T23:59:59.000Z

360

Furnace Blower Electricity: National and Regional Savings Potential  

E-Print Network (OSTI)

Currently, total electricity consumption of furnaces isthe total furnace electricity consumption and are primarilyto calculate the electricity consumption during cooling

Franco, Victor; Florida Solar Energy Center

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

U.S. Coal Supply and Demand: 1997 Review  

Gasoline and Diesel Fuel Update (EIA)

Western Western Interior Appalachian Energy Information Administration/ U.S. Coal Supply and Demand: 1997 Review 1 Figure 1. Coal-Producing Regions Source: Energy Information Administration, Coal Industry Annual 1996, DOE/EIA-0584(96) (Washington, DC, November 1997). U.S. Coal Supply and Demand: 1997 Review by B.D. Hong Energy Information Administration U.S. Department of Energy Overview U.S. coal production totaled a record high of 1,088.6 million short tons in 1997, up by 2.3 percent over the 1996 production level, according to preliminary data from the Energy Information Administration (Table 1). The electric power industry (utilities and independent power producers)-the dominant coal consumer-used a record 922.0 million short tons, up by 2.8 percent over 1996. The increase in coal use for

362

Smart (In-home) Power Scheduling for Demand Response on the Smart Grid  

E-Print Network (OSTI)

1 Smart (In-home) Power Scheduling for Demand Response on the Smart Grid Gang Xiong, Chen Chen consumption are part of demand response, which relies on varying price of electricity to reduce peak demand

Yener, Aylin

363

The Long View of Demand-Side Management Programs  

Science Journals Connector (OSTI)

One of the primary reasons that the electricity market failed in California during the 20002001 period was the lack of dynamic demand response to rising wholesale electricity prices. Had retail customers seen...

Ahmad Faruqui; Greg Wikler; Ingrid Bran

2003-01-01T23:59:59.000Z

364

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

365

Demand Controlled Ventilation and Classroom Ventilation  

E-Print Network (OSTI)

columnsindicatetheenergyandcostsavingsfor demandclasssize. (Theenergycosts ofclassroomventilationTotal Increase in Energy Costs ($) Increased State Revenue

Fisk, William J.

2014-01-01T23:59:59.000Z

366

Electric Power Annual 2011  

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

net internal demand, capacity resources, and capacity margins by North American Electric Reliability Corporation Region" "1999 through 2011 actual, 2012-2016 projected"...

367

Option Value of Electricity Demand Response  

E-Print Network (OSTI)

Operator (NYISO) and New York State Energy Research andhour National Energy Modeling System New York IndependentNYSERDA), January. New York State Energy Research and

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

2005-01-01T23:59:59.000Z

368

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network (OSTI)

implementation of advanced metering and rapidly expanding development of wind, solar, and clean energy

Levy, Roger

2014-01-01T23:59:59.000Z

369

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network (OSTI)

Smart Grid implementations may provide current, relevant information for calibrating potential renewable, outage management, and system operational benefits.

Levy, Roger

2014-01-01T23:59:59.000Z

370

Coordination of Energy Efficiency and Demand Response  

SciTech Connect

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

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

2010-01-29T23:59:59.000Z

371

Demand Response Assessment INTRODUCTION  

E-Print Network (OSTI)

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

372

Global energy demand to 2060  

SciTech Connect

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

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

1989-01-01T23:59:59.000Z

373

An Integrated Architecture for Demand Response Communications and Control  

E-Print Network (OSTI)

An Integrated Architecture for Demand Response Communications and Control Michael LeMay, Rajesh for the MGA and ZigBee wireless communications. Index Terms Demand Response, Advanced Meter Infrastructure. In principle this can be done with demand response techniques in which electricity users take measures

Gross, George

374

A Successful Implementation with the Smart Grid: Demand Response Resources  

E-Print Network (OSTI)

1 A Successful Implementation with the Smart Grid: Demand Response Resources Contribution of intelligent line switching, demand response resources (DRRs), FACTS devices and PMUs is key in the smart grid events as a result of voluntary load curtailments. Index Terms--Electricity Markets, Demand Response re

Gross, George

375

Demand Response Providing Ancillary A Comparison of Opportunities and  

E-Print Network (OSTI)

LBNL-5958E Demand Response Providing Ancillary Services A Comparison of Opportunities Government or any agency thereof or The Regents of the University of California. #12;Demand Response System Reliability, Demand Response (DR), Electricity Markets, Smart Grid Abstract Interest in using

376

Opportunities and Challenges for Data Center Demand Response  

E-Print Network (OSTI)

Opportunities and Challenges for Data Center Demand Response Adam Wierman Zhenhua Liu Iris Liu of renewable energy into the grid as well as electric power peak-load shaving: data center demand response. Data center demand response sits at the intersection of two growing fields: energy efficient data

Wierman, Adam

377

Towards Continuous Policy-driven Demand Response in Data Centers  

E-Print Network (OSTI)

Towards Continuous Policy-driven Demand Response in Data Centers David Irwin, Navin Sharma, and Prashant Shenoy University of Massachusetts, Amherst {irwin,nksharma,shenoy}@cs.umass.edu ABSTRACT Demand response (DR) is a technique for balancing electricity sup- ply and demand by regulating power consumption

Shenoy, Prashant

378

Towards continuous policy-driven demand response in data centers  

Science Journals Connector (OSTI)

Demand response (DR) is a technique for balancing electricity supply and demand by regulating power consumption instead of generation. DR is a key technology for emerging smart electric grids that aim to increase grid efficiency, while incorporating ... Keywords: blink, power, renewable energy, storage

David Irwin; Navin Sharma; Prashant Shenoy

2011-08-01T23:59:59.000Z

379

Coordination of Energy Efficiency and Demand Response  

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

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

380

Measuring the capacity impacts of demand response  

SciTech Connect

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

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

2009-07-15T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

Uranium 2009 resources, production and demand  

E-Print Network (OSTI)

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

Organisation for Economic Cooperation and Development. Paris

2010-01-01T23:59:59.000Z

382

Demand Response- Policy  

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

Since its inception, the Office of Electricity Delivery and Energy Reliability (OE) has been committed to modernizing the nation's electricity delivery infrastructure to assure consumers a robust,...

383

Demand response enabling technology development  

E-Print Network (OSTI)

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

2006-01-01T23:59:59.000Z

384

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

385

Cross-sector Demand Response  

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

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

386

Demand Response Programs for Oregon  

E-Print Network (OSTI)

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

387

Demand response enabling technology development  

E-Print Network (OSTI)

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

Arens, Edward; Auslander, David; Huizenga, Charlie

2008-01-01T23:59:59.000Z

388

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

389

Renewable Electricity Futures Study  

E-Print Network (OSTI)

Renewable Electricity Futures Study End-use Electricity Demand Volume 3 of 4 Volume 2 PDF Volume 3;Renewable Electricity Futures Study Edited By Hand, M.M. National Renewable Energy Laboratory Baldwin, S. U Sandor, D. National Renewable Energy Laboratory Suggested Citations Renewable Electricity Futures Study

390

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Highlights: February 2012 Highlights: February 2012 Warm temperatures across much of the U.S. led to lower retail sales of electricity during February 2012. Natural gas-fired generation increased in every region of the United States when compared to February 2011. Wholesale electricity prices remained in the low end of the annual range for most wholesale markets due to low demand and depressed natural gas prices Key Indicators Feb 2012 % Change from Feb. 2011 Total Net Generation (Thousand MWh) 310,298 -1.0% Residential Retail Price (cents/kWh) 11.55 3.9% Retail Sales (Thousand MWh) 285,684 -3.5% Heating Degree-Days 654 -12.0% Natural Gas Price, Henry Hub ($/MMBtu) 2.60 -38.1% Coal Stocks (Thousand Tons) 186,958 -13.6% Coal Consumption (Thousand Tons) 62,802 -14.6% Natural Gas Consumption

391

Demand Response In California  

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

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

392

Energy Demand Forecasting  

Science Journals Connector (OSTI)

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

S. C. Bhattacharyya

2011-01-01T23:59:59.000Z

393

Hydrogen and electricity: Parallels, interactions,and convergence  

E-Print Network (OSTI)

impacts of marginal electricity demand for CA hydrogenUS DOE, 2007. EIA. Electricity data. [cited 2007 March 2,F. Decarbonized hydrogen and electricity from natural gas.

Yang, Christopher

2008-01-01T23:59:59.000Z

394

Standby electricity consumption and saving potentials of Turkish households  

Science Journals Connector (OSTI)

Abstract The share of the residential sector currently accounts for about 25% of the national electricity consumption in Turkey. Due to increase in household income levels and decrease in the costs of appliances; significant increases in appliance ownerships and residential electricity consumption levels have been observed in recent years. Most domestic appliances continue consuming electricity when they are not performing their primary functions, i.e. at standby mode, which can constitute up 15% of the total household electricity consumption in some countries. Although the demand in Turkish residential electricity consumption is increasing, there are limited studies on the components of the residential electricity consumption and no studies specifically examining the extent and effects of standby electricity consumption using a surveying/measurement methodology. Thus, determining the share of standby electricity consumption in total home electricity use and the ways of reducing it are important issues in residential energy conservation strategies. In this study, surveys and standby power measurements are conducted at 260 households in Ankara, Turkey, to determine the amount, share, and saving potentials of the standby electricity consumption of Turkish homes. The survey is designed to gather information on the appliance properties, lights, electricity consumption behavior, economic and demographics of the occupants, and electricity bills. A total of 1746 appliances with standby power are measured in the surveyed homes. Using the survey and standby power measurements data, the standby, active, and lighting end-use electricity consumptions of the surveyed homes are determined. The average Turkish household standby power and standby electricity consumption are estimated as 22W and 95kWh/yr, respectively. It was also found that the standby electricity consumption constitutes 4% of the total electricity consumption in Turkish homes. Two scenarios are then applied to the surveyed homes to determine the potentials in reducing standby electricity consumption of the households.

Mustafa Cagri Sahin; Merih Aydinalp Koksal

2014-01-01T23:59:59.000Z

395

Distributed Solar Photovoltaics for Electric Vehicle Charging...  

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

DISTRIBUTED SOLAR PHOTOVOLTAICS FOR ELECTRIC VEHICLE CHARGING REGULATORY AND POLICY CONSIDERATIONS ABSTRACT Increasing demand for electric vehicle (EV) charging provides an...

396

Demand Response - Policy: More Information | Department of Energy  

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

Demand Response - Policy: More Information Demand Response - Policy: More Information Demand Response - Policy: More Information OE's commitment to ensuring non-wires options to modernize the nation's electricity delivery system includes ongoing support of a number of national and regional activities in support of demand response. The New England Demand Response Initiative (NEDRI), OE's initial endeavor to assist states with non-wire solutions, was created to develop a comprehensive, coordinated set of demand response programs for the New England regional power markets. NEDRI's goal was to outline workable market rules, public policies, and regulatory criteria to incorporate customer-based demand response resources into New England's electricity markets and power systems. NEDRI promoted best practices and coordinated

397

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

398

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

turbine NGST Natural gas steam turbine NWPP Northwest Powerfrom natural gas steam turbine (NGST) and natural gasNGST = Natural gas steam turbine; NWPP = Northwest Power

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

399

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

121]. Like other renewable resources and nuclear power, inhydro, nuclear, or renewable resources, and average GHGsupplied by each renewable resource and the capacity of

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

400

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

wind turbines, biomass, or geothermal power. By 2050, thebiomass, geothermal, and nuclear power plants arebiomass Nuclear, geothermal, and biomass power plants are

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

10 regions Illinois Colorado, Xcel Energy service area LADWPVehicle Charging in the Xcel Energy Colorado Servicecomprised 30% of LDVs in Xcel Energys Colorado service

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

402

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

2. Well-to-wheel vehicle GHG emissions rates as a functionplant type and average GHG emissions rates by scenario (Generation and average GHG emissions in 2050 for scenarios

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

403

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

Generation from wind and solar power plants can be highlygrid. When wind stops blowing, another power plant must bethan intermittent wind availability or uncertain power plant

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

404

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

Implementation Analysis (Preliminary Results), California Public Utilities Commission. NREL (2008) 20% Wind Energy

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

405

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

109 Figure 57. Assumed natural gas and coal prices in LEDGE-in Figure 57. The coal price stays relatively constantAssumed natural gas and coal prices in LEDGE-CA [152]. It

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

406

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

Biomass Geothermal Small Hydro Solar Wind Statewide CA-N CA-with a relatively small hydro resource require additionaldairy Photovoltaic Parabolic Small hydro Wind Hydro 1 Steam

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

407

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

IGCC Integrated gasification combined cycle IID ImperialCorporation NGCC Natural gas combined-cycle NGCT Natural gas79% from natural gas combined cycle (NGCC) power plants, and

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

408

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

near term. Local distribution infrastructure and reliabilityand distribution constraints, Reliability constraints,It does not depict reliability and distribution constraints,

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

409

Energy and Demand Savings from Implementation Costs in Industrial Facilities  

E-Print Network (OSTI)

, electrical consumption, demand and fees were tracked separately. The remaining data include only one energy stream (e.g., natural gas) in each code [6]. Table 1. Energy Streams STREAM CODE Electrical Consumption EC Electrical Demand ED Other... Electrical Fees EF Electricity E1 Natural Gas E2 L.P.G. E3 #1 Fuel Oil E4 #2 Fuel Oil E5 #4 Fuel Oil E6 #6 Fuel Oil E7 Coal E8 Wood E9 Paper E10 Other Gas E11 Other Energy E12 ESL-IE-00-04-17 Proceedings from the Twenty-second National...

Razinha, J. A.; Heffington, W. M.

410

Aviation fuel demand development in China  

Science Journals Connector (OSTI)

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

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

2014-01-01T23:59:59.000Z

411

Market and Policy Barriers for Demand Response Providing Ancillary Services  

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

Market and Policy Barriers for Demand Response Providing Ancillary Services Market and Policy Barriers for Demand Response Providing Ancillary Services in U.S. Markets Title Market and Policy Barriers for Demand Response Providing Ancillary Services in U.S. Markets Publication Type Report LBNL Report Number LBNL-6155E Year of Publication 2013 Authors Cappers, Peter, Jason MacDonald, and Charles A. Goldman Date Published 03/2013 Keywords advanced metering infrastructure, aggregators of retail customers, ancillary services, demand response, electric utility regulation, electricity market rules, electricity markets and policy group, energy analysis and environmental impacts department, institutional barriers, market and value, operating reserves, retail electricity providers, retail electricity tariffs, smart grid Attachment Size

412

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

413

Residential Demand Response  

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

that can store underutilized renewable or off peak electric energy for space and water heating. ETS systems store electric energy as heat in a well insulated brick core. Built-in...

414

Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

This page inTenTionally lefT blank 91 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules-electricity capacity planning, electricity fuel dispatching, electricity load and demand, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2012, DOE/EIA-M068(2012). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

415

Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 95 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules-electricity capacity planning, electricity fuel dispatching, electricity load and demand, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2011, DOE/EIA-M068(2011). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

416

Electricity Market Module  

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

Market Module Market Module This page inTenTionally lefT blank 101 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules-electricity capacity planning, electricity fuel dispatching, electricity load and demand, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2013, DOE/EIA-M068(2013). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

417

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

418

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

419

RTP Customer Demand Response  

Science Journals Connector (OSTI)

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

Steven Braithwait; Michael OSheasy

2002-01-01T23:59:59.000Z

420

World Energy Demand  

Science Journals Connector (OSTI)

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

Giovanni Petrecca

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

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

E-Print Network (OSTI)

2006b). Total U.S. Electricity Consumption Growth. fromprograms to reduce electricity consumption during peakof annual electricity consumption in households in five CEC

Peffer, Therese E.

2009-01-01T23:59:59.000Z

422

POWERTECH 2009, JUNE 28 -JULY 2, 2009, BUCHAREST, ROMANIA 1 Incorporation of Demand Response Resources in  

E-Print Network (OSTI)

POWERTECH 2009, JUNE 28 - JULY 2, 2009, BUCHAREST, ROMANIA 1 Incorporation of Demand Response, IEEE, Abstract--The use of demand-side resources, in general, and demand response resources (DRRs concerns. Integration of demand response resources in the competitive electricity markets impacts resource

Gross, George

423

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

424

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

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

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

425

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

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

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

426

Electric Drive Vehicle Infrastructure Deployment  

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

encourages off-peak energy * Smart Grid Integration o Charging stations with Demand Response, Time-of-Use Pricing, and AMI compatible with the modern electric grid * Help...

427

Changing Energy Demand Behavior: Potential of Demand-Side Management  

Science Journals Connector (OSTI)

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

Dr. Sylvia Breukers; Dr. Ruth Mourik

2013-01-01T23:59:59.000Z

428

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":""}]}

429

U.S. Coal Supply and Demand: 2003 Review  

Gasoline and Diesel Fuel Update (EIA)

3 Review 3 Review 1 U.S. Coal Supply and Demand: 2003 Review by Fred Freme U.S. Energy Information Administration Overview U.S. coal production fell for the second year in a row in 2003, declining by 24.8 million short tons to end the year at 1,069.5 million short tons according to preliminary data from the Energy Information Administration (Table 1), down 2.3 percent from the 2002 level of 1,094.3 million short tons. (Note: All percentage change calculations are done at the short ton level.) Total U.S. coal consumption rose in 2003, with all coal-consuming sectors increasing or remaining stable for the year. Coal consumption in the electric power sector increased by 2.4 percent. However, there were only slight gains in consumption by the other sectors. U.S. coal exports rose in 2003 for the first time in

430

Role of Context-Awareness for Demand Response Mechanisms  

Science Journals Connector (OSTI)

Recently due to major changes in the structure of electricity industry and the rising costs of power generation, many countries have realized the potential and benefits of smart metering systems and demand response

Pari Delir Haghighi; Shonali Krishnaswamy

2011-01-01T23:59:59.000Z

431

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

432

Serck standard packages for total energy  

Science Journals Connector (OSTI)

Although the principle of combined heat and power generation is attractive, practical problems have hindered its application. In the U.K. the scope for small scale combined heat and power (total energy) systems has been improved markedly by the introduction of new Electricity Board regulations which allow the operation of small a.c. generators in parallel with the mains low voltage supply. Following this change, Serck have developed a standard total energy unit, the CG100, based on the 2.25 1 Land Rover gas engine with full engine (coolant and exhaust gas) heat recovery. The unit incorporates an asynchronous generator, which utilising mains power for its magnetising current and speed control, offers a very simple means of generating electricity in parallel with the mains supply, without the need for expensive synchronising controls. Nominal output is 15 kW 47 kW heat; heat is available as hot water at temperatures up to 85C, allowing the heat output to be utilised directly in low pressure hot water systems. The CG100 unit can be used in any application where an appropriate demand exists for heat and electricity, and the annual utilisation will give an acceptable return on capital cost; it produces base load heat and electricity, with LPHW boilers and the mains supply providing top-up/stand-by requirements. Applications include residential use (hospitals, hotels, boarding schools, etc.), swimming pools and industrial process systems. The unit also operates on digester gas produced by anaerobic digestion of organic waste. A larger unit based on a six cylinder Ford engine (45 kWe output) is now available.

R. Kelcher

1984-01-01T23:59:59.000Z

433

TOTAL Full-TOTAL Full-  

E-Print Network (OSTI)

Conducting - Orchestral 6 . . 6 5 1 . 6 5 . . 5 Conducting - Wind Ensemble 3 . . 3 2 . . 2 . 1 . 1 Early- X TOTAL Full- Part- X TOTAL Alternative Energy 6 . . 6 11 . . 11 13 2 . 15 Biomedical Engineering 52 English 71 . 4 75 70 . 4 74 72 . 3 75 Geosciences 9 . 1 10 15 . . 15 19 . . 19 History 37 1 2 40 28 3 3 34

Portman, Douglas

434

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.

435

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.

436

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

437

Interoperability of Demand Response Resources Demonstration in NY  

SciTech Connect

The Interoperability of Demand Response Resources Demonstration in NY (Interoperability Project) was awarded to Con Edison in 2009. The objective of the project was to develop and demonstrate methodologies to enhance the ability of customer sited Demand Response resources to integrate more effectively with electric delivery companies and regional transmission organizations.

Wellington, Andre

2014-03-31T23:59:59.000Z

438

THE ROLE OFLOAD DEMAND ELASTICITY IN CONGESTION MANAGEMENTAND PRICING  

E-Print Network (OSTI)

THE ROLE OFLOAD DEMAND ELASTICITY IN CONGESTION MANAGEMENTAND PRICING EttoreBompard, Enrico that demand responsiveness can play in competitive electricity markets. Typically, the task of congestion and to determine transmission system usage charges. The actions of price responsive loads may be represented

Gross, George

439

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

440

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

Science Journals Connector (OSTI)

This study develops a spatially explicit, best-use framework to optimally allocate cellulosic biomass feedstocks to energy demands in transportation, electricity, and residential heating sectors, while minimizing total system costs and tracking greenhouse gas emissions. ... Steubing et al.(6) consider the optimal use of several biomass feedstocks to substitute fossil energy technologies in Europe, which is broader than the previously listed studies, but the authors use a ranking method to identify preferred allocation strategies with a nonspatial model. ... This study builds on these studies in developing a spatially explicit, best-use framework for model year 2020 that optimally allocates cellulosic biomass feedstocks to competing energy end uses (heating, transportation, electricity) based on minimizing total system costs. ...

Kimberley A. Mullins; Aranya Venkatesh; Amy L. Nagengast; Matt Kocoloski

2014-02-10T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

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

442

A proposed methodology for medium-range maximum demand anticipation and application  

Science Journals Connector (OSTI)

One to three years' anticipation of monthly and weekly peak demand is required to prepare maintenance schedules, develop power pooling agreements, select peaking capacity and provide data required by certain reliability coordinating centers. A total monthly forecast of the maximum demand is deduced and computed for the three years up to April 1981. This is accomplished for an important electrical network in Egypt. The anticipated maximum demand is executed for El-Mehalla El-Kubra city network. This network has an industrial and residential daily load characteristic. Direct monthly maximum demand forecasting is executed by separate treatment of weather-independent and weather-induced demand. The required forecast is derived by two methodologies: the probabilistic extrapolation-correlation, and that suggested by the authors. Daily and monthly data have been collected for more reliable determination of weather load models. Complete analysis, discussion and comments on the results are presented, and the results compared. This comparison reveals that an acceptable and reasonable percentage error is obtained on applying the proposed methodology.

M.S. Kandil; M.Helmy El-Maghraby; H. El-Dosouky

1981-01-01T23:59:59.000Z

443

FERC Presendation: Demand Response as Power System Resources, October 29,  

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

FERC Presendation: Demand Response as Power System Resources, FERC Presendation: Demand Response as Power System Resources, October 29, 2010 FERC Presendation: Demand Response as Power System Resources, October 29, 2010 Federal Energy Regulatory Commission (FERC) presentation on demand response as power system resources before the Electicity Advisory Committee, October 29, 2010 Demand Response as Power System Resources More Documents & Publications A National Forum on Demand Response: Results on What Remains to Be Done to Achieve Its Potential - Cost-Effectiveness Working Group Loads Providing Ancillary Services: Review of International Experience 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)

444

Rappahannock Electric Coop | Open Energy Information  

Open Energy Info (EERE)

Rappahannock Electric Cooperative) Rappahannock Electric Cooperative) Jump to: navigation, search Name Rappahannock Electric Coop Place Fredericksburg, Virginia Utility Id 40228 Utility Location Yes Ownership C NERC Location SERC Activity Distribution Yes Activity Retail Marketing Yes Alt Fuel Vehicle Yes Alt Fuel Vehicle2 Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] Energy Information Administration Form 826[2] SGIC[3] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Rappahannock Electric Cooperative Smart Grid Project was awarded $15,694,097 Recovery Act Funding with a total project value of $31,388,194. Utility Rate Schedules Grid-background.png COINCIDENT PEAK DEMAND RIDER Industrial

445

Bluestem Electric Coop Inc | Open Energy Information  

Open Energy Info (EERE)

Bluestem Electric Coop Inc Bluestem Electric Coop Inc Jump to: navigation, search Name Bluestem Electric Coop Inc Place Kansas Utility Id 23826 Utility Location Yes Ownership C NERC Location SPP NERC SPP Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Single-Phase General Service Demand Commercial Single-Phase Service Commercial Single-Phase Service Residential Single-Phase Time-of-Use Service Single-Phase Total Electric Service Single-phase Earth-Coupled Heat Pump Service Commercial Average Rates Residential: $0.1410/kWh Commercial: $0.1160/kWh Industrial: $0.2110/kWh

446

Total Imports  

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

Data Series: Imports - Total Imports - Crude Oil Imports - Crude Oil, Commercial Imports - by SPR Imports - into SPR by Others Imports - Total Products Imports - Total Motor Gasoline Imports - Finished Motor Gasoline Imports - Reformulated Gasoline Imports - Reformulated Gasoline Blended w/ Fuel Ethanol Imports - Other Reformulated Gasoline Imports - Conventional Gasoline Imports - Conv. Gasoline Blended w/ Fuel Ethanol Imports - Conv. Gasoline Blended w/ Fuel Ethanol, Ed55 & Ed55 Imports - Other Conventional Gasoline Imports - Motor Gasoline Blend. Components Imports - Motor Gasoline Blend. Components, RBOB Imports - Motor Gasoline Blend. Components, RBOB w/ Ether Imports - Motor Gasoline Blend. Components, RBOB w/ Alcohol Imports - Motor Gasoline Blend. Components, CBOB Imports - Motor Gasoline Blend. Components, GTAB Imports - Motor Gasoline Blend. Components, Other Imports - Fuel Ethanol Imports - Kerosene-Type Jet Fuel Imports - Distillate Fuel Oil Imports - Distillate F.O., 15 ppm Sulfur and Under Imports - Distillate F.O., > 15 ppm to 500 ppm Sulfur Imports - Distillate F.O., > 500 ppm to 2000 ppm Sulfur Imports - Distillate F.O., > 2000 ppm Sulfur Imports - Residual Fuel Oil Imports - Propane/Propylene Imports - Other Other Oils Imports - Kerosene Imports - NGPLs/LRGs (Excluding Propane/Propylene) Exports - Total Crude Oil and Products Exports - Crude Oil Exports - Products Exports - Finished Motor Gasoline Exports - Kerosene-Type Jet Fuel Exports - Distillate Fuel Oil Exports - Residual Fuel Oil Exports - Propane/Propylene Exports - Other Oils Net Imports - Total Crude Oil and Products Net Imports - Crude Oil Net Imports - Petroleum Products Period: Weekly 4-Week Avg.

447

Energy Demand Staff Scientist  

E-Print Network (OSTI)

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

Eisen, Michael

448

Energy Demand Modeling  

Science Journals Connector (OSTI)

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

S. L. Schwartz

1980-01-01T23:59:59.000Z

449

Calculation method for electricity end-use for residential lighting  

Science Journals Connector (OSTI)

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

Eva Rosenberg

2014-01-01T23:59:59.000Z

450

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

451

Energy demand simulation for East European countries  

Science Journals Connector (OSTI)

The analysis and created statistical models of energy consumption tendencies in the European Union (EU25), including new countries in transition, are presented. The EU15 market economy countries and countries in transition are classified into six clusters by relative indicators of Gross Domestic Product (GDP/P) and energy demand (W/P) per capita. The specified statistical models of energy intensity W/GDP non-linear stochastic tendencies have been discovered with respect to the clusters of classified countries. The new energy demand simulation models have been developed for the demand management in time??territory hierarchy in various scenarios of short-term and long-term perspective on the basis of comparative analysis methodology. The non-linear statistical models were modified to GDP, W/P and electricity (E/P) final consumption long-term forecasts for new associated East European countries and, as an example, for the Baltic Countries, including Lithuania.

Jonas Algirdas Kugelevicius; Algirdas Kuprys; Jonas Kugelevicius

2007-01-01T23:59:59.000Z

452

Demand response compensation, net Benefits and cost allocation: comments  

SciTech Connect

FERC's Supplemental Notice of Public Rulemaking addresses the question of proper compensation for demand response in organized wholesale electricity markets. Assuming that the Commission would proceed with the proposal ''to require tariff provisions allowing demand response resources to participate in wholesale energy markets by reducing consumption of electricity from expected levels in response to price signals, to pay those demand response resources, in all hours, the market price of energy for such reductions,'' the Commission posed questions about applying a net benefits test and rules for cost allocation. This article summarizes critical points and poses implications for the issues of net benefit tests and cost allocation. (author)

Hogan, William W.

2010-11-15T23:59:59.000Z

453

Managing Energy Demand With Standards and Information  

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

Managing Energy Demand With Standards and Information Managing Energy Demand With Standards and Information Speaker(s): Sebastien Houde Date: September 13, 2012 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Christopher Payne The goal of this talk is to discuss two interrelated research projects that aim to assess the welfare effects of energy policies that rely on standards and information. The first project focuses on the Energy Star certification program. Using unique micro-data on the US refrigerator market, I first show that consumers respond to certification in different ways. Some consumers appear to rely heavily on Energy Star and pay little attention to electricity costs, others are the reverse, and still others appear to be insensitive to both electricity costs and Energy Star. I then develop a

454

Modeling demand response and economic impact of advanced and smart metering  

Science Journals Connector (OSTI)

Advanced metering constitutes an essential component of communications between electricity suppliers and consumers. It may be possible to augment demand response by coupling Advanced Metering Infrastructure (AMI)...

Praneeth Aketi; Suvrajeet Sen

2014-09-01T23:59:59.000Z

455

Unexpected consequences of demand response : implications for energy and capacity price level and volatility .  

E-Print Network (OSTI)

??Historically, electricity consumption has been largely insensitive to short term spot market conditions, requiring the equating of supply and demand to occur almost exclusively through (more)

Levy, Tal Z. (Tal Ze'ev)

2014-01-01T23:59:59.000Z

456

Power system balancing with high renewable penetration : the potential of demand response .  

E-Print Network (OSTI)

??This study investigated the ability of responsive demand to stabilize the electrical grid when intermittent renewable resources are present. The WILMAR stochastic unit commitment model (more)

Critz, David Karl

2012-01-01T23:59:59.000Z

457

The Impact on Consumer Behavior of Energy Demand Side Management Programs Measurement Techniques and Methods.  

E-Print Network (OSTI)

??Much effort has gone into measuring the impact of Demand Side Management (DSM) programs on energy usage, particularly in regards to electric usage. However, there (more)

Pursley, Jeffrey L

2014-01-01T23:59:59.000Z

458

Evaluation of Conservation Voltage Reduction as a tool for demand side management.  

E-Print Network (OSTI)

??To ensure stability of the power grid, electricity supply and demand must remain in balance in real time. Traditionally utilities, call upon peaking power plants (more)

Dorrody, Ali

2014-01-01T23:59:59.000Z

459

Data centres power profile selecting policies for Demand Response: Insights of Green Supply Demand Agreement  

Science Journals Connector (OSTI)

Abstract Demand Response mechanisms serve to preserve the stability of the power grid by shedding the electricity load of the consumers during power shortage situations in order to match power generation to demand. Data centres have been identified as excellent candidates to participate in such mechanisms. Recently a novel supply demand agreement have been proposed to foster power adaptation collaboration between energy provider and data centres. In this paper, we analyse the contractual terms of this agreement by proposing and studying different data centres power profile selecting policies. To this end, we setup a discrete event simulation and analysed the power grids state of a German energy provider. We believe that our analysis provides insight and knowledge for any energy utility in setting up the corresponding demand supply agreements.

Robert Basmadjian; Lukas Mller; Hermann De Meer

2015-01-01T23:59:59.000Z

460

Ethanol Demand in United States Gasoline Production  

SciTech Connect

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

Hadder, G.R.

1998-11-24T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

Only tough choices in Meeting growing demand  

SciTech Connect

U.S. electricity demand is not growing very fast by international or historical standards. Yet meeting this relatively modest growth is proving difficult because investment in new capacity is expected to grow at an even slower pace. What is more worrisome is that a confluence of factors has added considerable uncertainties, making the investment community less willing to make the long-term commitments that will be needed during the coming decade.

NONE

2007-12-15T23:59:59.000Z

462

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

463

Warm Winters Held Heating Oil Demand Down While Diesel Grew  

Gasoline and Diesel Fuel Update (EIA)

8 8 Notes: To understand the inventory situation, we must look the balance between demand and supply that drives inventories up or down. First consider demand. Most of the remaining charts deal with total distillate demand. Total distillate demand includes both diesel and heating oil. These are similar products physically, and prior to the low sulfur requirements for on-road diesel fuel, were used interchangeably. But even today, low sulfur diesel can be used in the heating oil market, but low sulfur requirements keep heating oil from being used in the on-road transportation sector. The seasonal increases and decreases in stocks stem from the seasonal demand in heating oil shown as the bottom red line. Heating oil demand increases by more than 50 percent from its low point to its high

464

Decentralized demandsupply matching using community microgrids and consumer demand response: A scenario analysis  

Science Journals Connector (OSTI)

Abstract Developing countries constantly face the challenge of reliably matching electricity supply to increasing consumer demand. The traditional policy decisions of increasing supply and reducing demand centrally, by building new power plants and/or load shedding, have been insufficient. Locally installed microgrids along with consumer demand response can be suitable decentralized options to augment the centralized grid based systems and plug the demandsupply gap. The objectives of this paper are to: (1) develop a framework to identify the appropriate decentralized energy options for demandsupply matching within a community, and, (2) determine which of these options can suitably plug the existing demandsupply gap at varying levels of grid unavailability. A scenario analysis framework is developed to identify and assess the impact of different decentralized energy options at a community level and demonstrated for a typical urban residential community Vijayanagar, Bangalore in India. A combination of LPG based CHP microgrid and proactive demand response by the community is the appropriate option that enables the Vijayanagar community to meet its energy needs 24/7 in a reliable, cost-effective manner. The paper concludes with an enumeration of the barriers and feasible strategies for the implementation of community microgrids in India based on stakeholder inputs.

Kumudhini Ravindra; Parameshwar P. Iyer

2014-01-01T23:59:59.000Z

465

Reducing Peak Demand to Defer Power Plant Construction in Oklahoma  

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

Reducing Peak Demand to Defer Power Plant Construction in Oklahoma Reducing Peak Demand to Defer Power Plant Construction in Oklahoma Located in the heart of "Tornado Alley," Oklahoma Gas & Electric Company's (OG&E) electric grid faces significant challenges from severe weather, hot summers, and about 2% annual load growth. To better control costs and manage electric reliability under these conditions, OG&E is pursuing demand response strategies made possible by implementation of smart grid technologies, tools, and techniques from 2010-2012. The objective is to engage customers in lowering peak demand using smart technologies in homes and businesses and to achieve greater efficiencies on the distribution system. The immediate goal: To defer two 165 MW power plants currently planned for

466

Unlocking the potential for efficiency and demand response through advanced  

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

Unlocking the potential for efficiency and demand response through advanced Unlocking the potential for efficiency and demand response through advanced metering Title Unlocking the potential for efficiency and demand response through advanced metering Publication Type Conference Paper LBNL Report Number LBNL-55673 Year of Publication 2004 Authors Levy, Roger, Karen Herter, and John Wilson Conference Name 2004 ACEEE Summer Study on Energy Efficiency in Buildings Date Published 06/2004 Publisher ACEEE Conference Location Pacific Grove, CA Call Number California Energy Commission Keywords demand response, demand response and distributed energy resources center, demand response research center, energy efficiency demand response advanced metering, rate programs & tariffs Abstract Reliance on the standard cumulative kilowatt-hour meter substantially compromises energy efficiency and demand response programs. Without advanced metering, utilities cannot support time-differentiated rates or collect the detailed customer usage information necessary to (1) educate the customer to the economic value of efficiency and demand response options, or (2) distribute load management incentives proportional to customer contribution. These deficiencies prevent the customer feedback mechanisms that would otherwise encourage economically sound demand-side investments and behaviors. Thus, the inability to collect or properly price electricity usage handicaps the success of almost all efficiency and demand response options.

467

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.

468

U.S. Coal Supply and Demand: 2010 Year in Review - Energy Information  

Gasoline and Diesel Fuel Update (EIA)

U.S. Coal Supply and Demand: 2010 Year in Review U.S. Coal Supply and Demand: 2010 Year in Review Release Date: June 1, 2011 | Next Release Date: Periodically | full report Introduction Coal production in the United States in 2010 increased to a level of 1,085.3 million short tons according to preliminary data from the U.S. Energy Information Administration (EIA), an increase of 1.0 percent, or 10.4 million short tons above the 2009 level of 1,074.9 million short tons (Table 1). In 2010 U.S. coal consumption increased in all sectors except commercial and institutional while total coal stocks fell slightly for the year. Coal consumption in the electric power sector in 2010 was higher by 4.5 percent, while coking coal consumption increased by 37.9 percent and the other industrial sector increased by 7.1 percent. The commercial and

469

Optimal Planning and Operation of Smart Grids with Electric Vehicle Interconnection  

E-Print Network (OSTI)

index (1,2, 24) fixed electricity costs, $ macrogrid CO 2the commercial building, $ electricity costs, $ distributedcosts, $ variable electricity costs (energy and demand

Stadler, Michael

2012-01-01T23:59:59.000Z

470

DSM Electricity Savings Potential in the Buildings Sector in APP Countries  

E-Print Network (OSTI)

owned integrated hydro electricity utilities prevail,s Loading Order for Electricity Resources”, Staff Report,International Developments in Electricity Demand Management

McNeil, MIchael

2011-01-01T23:59:59.000Z

471

Guidelines for Marketing Demand-Side Management in the Commercial Sector  

E-Print Network (OSTI)

For the past decade, electric and gas utilities throughout the nation, not just in hot and humid climates, have promoted energy efficiency through a variety of demand-side management (DSM) programs. In 1984, the Electric Power Research Institute...

George, S. S.

1988-01-01T23:59:59.000Z

472

COMBINING DIVERSE DATA SOURCES FOR CEDSS, AN AGENT-BASED MODEL OF DOMESTIC ENERGY DEMAND  

E-Print Network (OSTI)

energy use covers the use of electricity, gas and oil within the home for space and water heating and electricalenergy demand. These exercises led us to focus on electrical

Gotts, Nicholas Mark; Polhill, Gary; Craig, Tony; Galan-Diaz, Carlos

2014-01-01T23:59:59.000Z

473

Demand Response and Variable Generation Integration Scoping Study  

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

Market and Policy Barriers for Demand Market and Policy Barriers for Demand Response Providing Ancillary Services in U.S. Electricity Markets Peter Cappers, Jason MacDonald, Charles Goldman April 2013 Report Summary 1 Energy Analysis Department  Electricity Markets and Policy Group Presentation Overview  Objectives and Approach  Wholesale and Retail Market Environments  Market and Policy Barrier Typology  Prototypical Regional Barrier Assessment 2 Energy Analysis Department  Electricity Markets and Policy Group A Role for Demand Response to Provide Ancillary Services  Increasing penetration of renewable energy generation in U.S. electricity markets means that bulk power system operators will need to manage the variable and uncertain nature of many renewable resources

474

Recovery Act: State Assistance for Recovery Act Related Electricity...  

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

carbon capture and storage, transmission lines, energy storage, smart grid, demand response equipment, and electric and hybrid-electric vehicles. View a full list of states...

475

Electric Power Research Institute Cooperation to Increase Energy...  

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

energy efficiency and promoting the widespread adoption of electric energy demand response programs in an effort to curtail energy use during peak periods. Electric Power...

476

Please cite this article in press as: Hughes L, Meeting residential space heating demand with wind-generated electricity, Renewable Energy (2009), doi:10.1016/j.renene.2009.11.014  

E-Print Network (OSTI)

, or compressed air (Blarke and Lund 2008). Energy suppliers are forced to go to these lengths when integrating. The benefits as well as the limitations of the approach are discussed in detail. Keywords: Energy storage- generated electricity, Renewable Energy (2009), doi:10.1016/j.renene.2009.11.014 ERG/200909 Meeting

Hughes, Larry

477

Modeling Electric Vehicle Benefits Connected to Smart Grids  

E-Print Network (OSTI)

costs EV battery degradation costs electricity sales fixedand sales, DER capital costs, fuel costs, demand response measures and EV

Stadler, Michael

2012-01-01T23:59:59.000Z

478

IEEE TRANSACTIONS ON SMART GRID, VOL. 5, NO. 2, MARCH 2014 861 An Optimal and Distributed Demand Response  

E-Print Network (OSTI)

of demand response management for the future smart grid that integrates plug-in electric vehicles for augmented Lagrangian. I. INTRODUCTION I N THE electricity market, demand response [1] is a mech- anism to manage users' consumption behavior under spe- cific supply conditions. The goal of demand response

Nehorai, Arye

479

Video-on-Demand Based on Delayed-Multicast: Algorithmic Support  

Science Journals Connector (OSTI)

...Article Video-on-Demand Based on Delayed-Multicast: Algorithmic Support N. Glinos...examine algorithmic issues related to the delayed multicast technique for video-on-demand delivery. We introduce the minimum total memory (MTM......

N. Glinos; D. B. Hoang; C. Nguyen; A. Symvonis

2004-01-01T23:59:59.000Z

480

Energy Demand Forecasting in China Based on Dynamic RBF Neural Network  

Science Journals Connector (OSTI)

A dynamic radial basis function (RBF) network model is proposed for energy demand forecasting in this paper. Firstly, we ... detail. At last, the data of total energy demand in China are analyzed and experimental...

Dongqing Zhang; Kaiping Ma; Yuexia Zhao

2011-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total electricity demand" 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

Understanding and Analysing Energy Demand  

Science Journals Connector (OSTI)

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

Subhes C. Bhattacharyya

2011-01-01T23:59:59.000Z

482

Opportunities for Automated Demand Response in Wastewater Treatment  

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

Opportunities for Automated Demand Response in Wastewater Treatment Opportunities for Automated Demand Response in Wastewater Treatment Facilities in California - Southeast Water Pollution Control Plant Case Study Title Opportunities for Automated Demand Response in Wastewater Treatment Facilities in California - Southeast Water Pollution Control Plant Case Study Publication Type Report LBNL Report Number LBNL-6056E Year of Publication 2012 Authors Olsen, Daniel, Sasank Goli, David Faulkner, and Aimee T. McKane Date Published 12/2012 Publisher CEC/LBNL Keywords market sectors, technologies Abstract This report details a study into the demand response potential of a large wastewater treatment facility in San Francisco. Previous research had identified wastewater treatment facilities as good candidates for demand response and automated demand response, and this study was conducted to investigate facility attributes that are conducive to demand response or which hinder its implementation. One years' worth of operational data were collected from the facility's control system, submetered process equipment, utility electricity demand records, and governmental weather stations. These data were analyzed to determine factors which affected facility power demand and demand response capabilities.

483

Demand Response: Load Management Programs  

E-Print Network (OSTI)

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

Simon, J.

2012-01-01T23:59:59.000Z

484

Marketing Demand-Side Management  

E-Print Network (OSTI)

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

O'Neill, M. L.

1988-01-01T23:59:59.000Z

485

Demand Charges | Open Energy Information  

Open Energy Info (EERE)

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

486

Assessment of Demand Response Resource  

E-Print Network (OSTI)

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

487

ERCOT Demand Response Paul Wattles  

E-Print Network (OSTI)

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

Mohsenian-Rad, Hamed

488

Pricing data center demand response  

Science Journals Connector (OSTI)

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

Zhenhua Liu; Iris Liu; Steven Low; Adam Wierman

2014-06-01T23:59:59.000Z

489

Is Demand-Side Management Economically Justified?  

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

7 7 Is Demand-Side Management Economically Justified? With billions of dollars being spent on demand-side management programs in the U.S. every year, the rationale for and performance of these programs are coming under increasing scrutiny. Three projects in the Energy Analysis Program are making significant contributions to the DSM debate. *Total Resource Cost Test Ratio = ratio of utility avoided costs (i.e., benefits) divided by total cost of program (i.e., Administrative Cost + Incentive Cost + Consumer Cost) In May, Joe Eto, Ed Vine, Leslie Shown, Chris Payne, and I released the first in a series of reports we authored from the Database on Energy Efficiency Programs (DEEP) project. The objective of DEEP is to document the measured cost and performance of utility-sponsored energy-efficiency

490

Demo Abstract: Toward Data-driven Demand-Response Optimization in a Campus Microgrid  

E-Print Network (OSTI)

Demo Abstract: Toward Data-driven Demand-Response Optimization in a Campus Microgrid Yogesh Simmhan-driven demand response optimization (DR) in the USC campus microgrid, as part of the Los An- geles Smart Grid of this project is to investigate techniques for demand-response optimization (DR) ­ cur- tailing the electricity

Prasanna, Viktor K.

491

Quantifying Benefits of Demand Response and Look-ahead Dispatch in Systems  

E-Print Network (OSTI)

Quantifying Benefits of Demand Response and Look-ahead Dispatch in Systems with Variable Resources Electric Energy System #12;#12;Quantifying Benefits of Demand Response and Look-ahead Dispatch in Systems benefits correspond to a real-world power system, as we use actual data on demand-response and wind

492

Residential Demand Response under Uncertainty Paul Scott and Sylvie Thiebaux and  

E-Print Network (OSTI)

Residential Demand Response under Uncertainty Paul Scott and Sylvie Thi´ebaux and Menkes van den stochastic optimisation in residential demand response. 1 Introduction Electricity consumption in residential participate in smart grid activities such as demand response where loads are shifted to times favourable

Thiébaux, Sylvie

493

The Influence of Demand Resource Response Time in Balancing Wind and Load  

Science Journals Connector (OSTI)

The integration of demand response resources into wholesale electricity markets facilitates the growth in wind power integration. Available demand resources have different capabilities in terms of response time, as demonstrated by the variety of programs ... Keywords: demand response, wind integration, power spectral density

Judith Cardell; Lindsay Anderson

2013-01-01T23:59:59.000Z

494

Demand-Side Load Scheduling Incentivized by Dynamic Energy Hadi Goudarzi, Safar Hatami, and Massoud Pedram  

E-Print Network (OSTI)

Demand-Side Load Scheduling Incentivized by Dynamic Energy Prices Hadi Goudarzi, Safar Hatami growth in electrical energy consumption under worst- case demand conditions [1]. To avoid expending 90089 {hgoudarz, shatami, pedram}@usc.edu Abstract--Demand response is an important part of the smart

Pedram, Massoud

495

State Residential Commercial Industrial Transportation Total  

Gasoline and Diesel Fuel Update (EIA)

schedules 4A-D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total 2012 Total Electric Industry- Average Retail Price (centskWh) (Data from...

496

Rappahannock Electric Coop | Open Energy Information  

Open Energy Info (EERE)

Rappahannock Electric Coop Rappahannock Electric Coop Place Fredericksburg, Virginia Utility Id 40228 Utility Location Yes Ownership C NERC Location SERC Activity Distribution Yes Activity Retail Marketing Yes Alt Fuel Vehicle Yes Alt Fuel Vehicle2 Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] Energy Information Administration Form 826[2] SGIC[3] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Rappahannock Electric Cooperative Smart Grid Project was awarded $15,694,097 Recovery Act Funding with a total project value of $31,388,194. Utility Rate Schedules Grid-background.png COINCIDENT PEAK DEMAND RIDER Industrial FARM, HOME AND CIVIC SERVICE SCHEDULE A Multi-Phase Residential

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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

498

ResourceTask Network Formulations for Industrial Demand Side Management of a Steel Plant  

Science Journals Connector (OSTI)

In the industrial demand side management (iDSM) or demand response (DR) grid-consumer interface, the electricity provider gives economic incentives to the industry to alter their electricity usage behavior and there are generally two approaches: ... It can be used as an important tool for industrial demand side management or demand response, a concept in which the plant adapts its operational behavior by changing the timing of electricity usage from on-peak to off-peak hours for the collective benefit of society. ...

Pedro M. Castro; Lige Sun; Iiro Harjunkoski

2013-08-13T23:59:59.000Z

499

Future scenarios and trends in energy generation in brazil: supply and demand and mitigation forecasts  

Science Journals Connector (OSTI)

Abstract The structure of the Brazilian energy matrix defines Brazil as a global leader in power generation from renewable sources. In 2011, the share of renewable sources in electricity production reached 88.8%, mainly due to the large national water potential. Although the Brazilian energy model presents a strong potential for expansion, the total energy that could be used with most current renewable technologies often outweighs the national demand. The current composition of the national energy matrix has outstanding participation of hydropower, even though the country has great potential for the exploitation of other renewable energy sources such as wind, solar and biomass. This document therefore refers to the trend of evolution of the Brazilian Energy Matrix and exposes possible mitigation scenarios, also considering climate change. The methodology to be used in the modeling includes the implementation of the LEAP System (Long-range Energy Alternatives Planning) program, developed by the Stockholm Environment Institute, which allows us to propose different scenarios under the definition of socioeconomic scenarios and base power developed in the context of the REGSA project (Promoting Renewable Electricity Generation in South America). Results envision future scenarios and trends in power generation in Brazil, and the projected demand and supply of electricity for up to 2030.

Jos Baltazar Salgueirinho Osrio De Andrade Guerra; Luciano Dutra; Norma Beatriz Camiso Schwinden; Suely Ferraz de Andrade

2014-01-01T23:59:59.000Z

500

Energy technologies and their impact on demand  

SciTech Connect

Despite the uncertainties, energy demand forecasts must be made to guide government policies and public and private-sector capital investment programs. Three principles can be identified in considering long-term energy prospects. First energy demand will continue to grow, driven by population growth, economic development, and the current low per capita energy consumption in developing countries. Second, energy technology advancements alone will not solve the problem. Energy-efficient technologies, renewable resource technologies, and advanced electric power technologies will all play a major role but will not be able to keep up with the growth in world energy demand. Third, environmental concerns will limit the energy technology choices. Increasing concern for environmental protection around the world will restrict primarily large, centralized energy supply facilities. The conclusion is that energy system diversity is the only solution. The energy system must be planned with consideration of both supply and demand technologies, must not rely on a single source of energy, must take advantage of all available technologies that are specially suited to unique local conditions, must be built with long-term perspectives, and must be able to adapt to change.

Drucker, H.

1995-06-01T23:59:59.000Z