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1

U.S. Regional Energy Demand Forecasts Using NEMS and GIS  

E-Print Network (OSTI)

LBNL-57955 U.S. Regional Energy Demand Forecasts Using NEMS and GIS Jesse A. Cohen, Jennifer L Efficiency and Renewable Energy, Office of Planning, Budget, and Analysis of the U.S. Department of Energy-57955 U.S. Regional Energy Demand Forecasts Using NEMS and GIS Prepared for the Office of Planning

2

Addressing Energy Demand through Demand Response: International...  

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

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

3

Addressing Energy Demand through Demand Response: International...  

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

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

4

Regional Differences in the Price-Elasticity of Demand for Energy  

DOE Green Energy (OSTI)

At the request of the National Renewable Energy Laboratory (NREL), the RAND Corporation examined the relationship between energy demand and energy prices with the focus on whether the relationships between demand and price differ if these are examined at different levels of data resolution. In this case, RAND compares national, regional, state, and electric utility levels of data resolution. This study is intended as a first step in helping NREL understand the impact that spatial disaggregation of data can have on estimating the impacts of their programs. This report should be useful to analysts in NREL and other national laboratories, as well as to policy nationals at the national level. It may help them understand the complex relationships between demand and price and how these might vary across different locations in the United States.

Bernstein, M. A.; Griffin, J.

2006-02-01T23:59:59.000Z

5

Addressing Energy Demand  

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

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

6

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

7

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

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

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

8

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

dependence in natural gas usage. January typically sees theindustrial fuels usage. Natural gas demand has been risinggas demands regionally, to account for variability in energy usage

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

2008-01-01T23:59:59.000Z

9

ENERGY DEMAND FORECAST METHODS REPORT  

E-Print Network (OSTI)

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

10

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

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

Shen, Bo

2013-01-01T23:59:59.000Z

11

CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST  

E-Print Network (OSTI)

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

12

Energy Demand | Open Energy Information  

Open Energy Info (EERE)

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

13

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

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

Goldman, Charles

2010-01-01T23:59:59.000Z

14

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

15

Energy Demand Staff Scientist  

E-Print Network (OSTI)

consumption per ton steel #12;Industrial Energy EfficiencyIndustrial Energy Efficiency Policy Analysis intensity trends and policy background · Focus on Industrial Energy Efficiency · Policy analysis PrimaryEnergy(Mtce) Commercial Buildings Residential Buildings Transportation Industry China 0 500 1,000 1

Knowles, David William

16

Coordination of Energy Efficiency and Demand Response  

Science Conference Proceedings (OSTI)

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

17

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.

18

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

19

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

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

Goldman, Charles

2010-01-01T23:59:59.000Z

20

Beyond Renewable Portfolio Standards: An Assessment of Regional Supply and Demand Conditions Affecting the Future of Renewable Energy in the West; Executive Summary  

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

National Renewable Energy Laboratory 15013 Denver West Parkway Golden, CO 80401 303-275-3000 * www.nrel.gov Beyond Renewable Portfolio Standards: An Assessment of Regional Supply and Demand Conditions Affecting the Future of Renewable Energy in the West Executive Summary David J. Hurlbut, Joyce McLaren, and Rachel Gelman National Renewable Energy Laboratory Prepared under Task No. AROE.2000 NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency & Renewable Energy Operated by the Alliance for Sustainable Energy, LLC This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. Technical Report NREL/TP-6A20-57830 August 2013 Contract No. DE-AC36-08GO28308

Note: This page contains sample records for the topic "regional energy 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

Beyond Renewable Portfolio Standards: An Assessment of Regional Supply and Demand Conditions Affecting the Future of Renewable Energy in the West  

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

(This page intentionally left blank) (This page intentionally left blank) National Renewable Energy Laboratory 15013 Denver West Parkway Golden, CO 80401 303-275-3000 * www.nrel.gov Beyond Renewable Portfolio Standards: An Assessment of Regional Supply and Demand Conditions Affecting the Future of Renewable Energy in the West David J. Hurlbut, Joyce McLaren, and Rachel Gelman National Renewable Energy Laboratory Prepared under Task No. AROE.2000 NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency & Renewable Energy Operated by the Alliance for Sustainable Energy, LLC This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. Technical Report NREL/TP-6A20-57830 August 2013 Contract No. DE-AC36-08GO28308

22

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"

23

Building Energy Software Tools Directory: Energy Demand Modeling  

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

Energy Demand Modeling Energy Demand Modeling The software is intended to be used for Energy Demand Modeling. This can be utilized from regional to national level. A Graphical User Interface of the software takes the input from the user in a quite logical and sequential manner. These input leads to output in two distinct form, first, it develops a Reference Energy System, which depicts the flow of energy from the source to sink with all the losses incorporated and second, it gives a MATLAB script file for advance post processing like graphs, visualization and optimizations to develop and evaluate the right energy mix policy frame work for a intended region. Keywords Reference Energy System, Software, GUI, Planning, Energy Demand Model EDM, Energy Policy Planning Validation/Testing

24

EIA - Annual Energy Outlook 2008 - Energy Demand  

Gasoline and Diesel Fuel Update (EIA)

Energy Demand Energy Demand Annual Energy Outlook 2008 with Projections to 2030 Energy Demand Figure 40. Energy use per capita and per dollar of gross domestic product, 1980-2030 (index, 1980 = 1). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 41. Primary energy use by fuel, 2006-2030 (quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. figure data Average Energy Use per Person Levels Off Through 2030 Because energy use for housing, services, and travel in the United States is closely linked to population levels, energy use per capita is relatively stable (Figure 40). In addition, the economy is becoming less dependent on energy in general. Energy intensity (energy use per 2000 dollar of GDP) declines by an average

25

Disaggregating regional energy supply/demand and flow data to 173 BEAs in support of export coal analysis. Final report  

SciTech Connect

This report documents the procedures and results of a study sponsored jointly by the US Department of Transportation and the US Department of Energy. The study was conducted to provide, Bureau of Economic Analysis (BEA)-level production/consumption data for energy materials for 1985 and 1990 in support of an analysis of transportation requirements for export coal. Base data for energy forecasts at the regional level were obtained from the Department of Energy, Energy Information Administration. The forecasts selected for this study are described in DOE/EIA's 1980 Annual Report to Congress, and are: 1985 Series, B, medium oil import price ($37.00/barrel); and 1990 Series B, medium oil import price ($41.00/barrel). Each forecast period is extensively described by approximately forty-three statistical tables prepared by EIA and made available to TERA for this study. This report provides sufficient information to enable the transportation analyst to appreciate the procedures employed by TERA to produce the BEA-level energy production/consumption data. The report presents the results of the procedures, abstracts of data tabulations, and various assumptions used for the preparation of the BEA-level data. The end-product of this effort was the BEA to BEA energy commodity flow data by more which serve as direct input to DOT's transportation network model being used for a detailed analysis of export coal transportation.

1981-06-01T23:59:59.000Z

26

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

E-Print Network (OSTI)

US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach Massimo www.cepe.ethz.ch #12;US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach Page 1 of 25 US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier

27

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

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

Shen, Bo

2013-01-01T23:59:59.000Z

28

Future demand for electricity in the Nassau--Suffolk region  

DOE Green Energy (OSTI)

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

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

1977-12-01T23:59:59.000Z

29

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

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

30

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

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

31

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

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

32

System Demand-Side Management: Regional results  

DOE Green Energy (OSTI)

To improve the Bonneville Power Administration's (Bonneville's) ability to analyze the value and impacts of demand-side programs, Pacific Northwest Laboratory (PNL) developed and implemented the System Demand-Side Management (SDSM) model, a microcomputer-based model of the Pacific Northwest Public Power system. This document outlines the development and application of the SDSM model, which is an hourly model. Hourly analysis makes it possible to examine the change in marginal revenues and marginal costs that accrue from the movement of energy consumption from daytime to nighttime. It also allows a more insightful analysis of programs such as water heater control in the context of hydroelectric-based generation system. 7 refs., 10 figs., 10 tabs.

Englin, J.E.; Sands, R.D.; De Steese, J.G.; Marsh, S.J.

1990-05-01T23:59:59.000Z

33

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

California Energy Demand Scenario Projections to 2050 RyanResearch Program California Energy Commission November 7,Chris Kavalec. California Energy Commission. CEC (2003a)

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

2008-01-01T23:59:59.000Z

34

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect

The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

2005-07-01T23:59:59.000Z

35

EIA - International Energy Outlook 2009-World Energy Demand and Economic  

Gasoline and Diesel Fuel Update (EIA)

World Energy and Economic Outlook World Energy and Economic Outlook International Energy Outlook 2009 Chapter 1 - World Energy Demand and Economic Outlook In the IEO2009 projections, total world consumption of marketed energy is projected to increase by 44 percent from 2006 to 2030. The largest projected increase in energy demand is for the non-OECD economies. Figure 10. World Marketed Energy Consumption, 1980-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 11. World Marketed Energy Consumption: OECD and Non-OECD, 1980-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 12. Marketed Energy Use by Region, 1990-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800.

36

EIA - International Energy Outlook 2008-World Energy Demand and Economic  

Gasoline and Diesel Fuel Update (EIA)

World Energy and Economic Outlook World Energy and Economic Outlook International Energy Outlook 2008 Chapter 1 - World Energy Demand and Economic Outlook In the IEO2008 projections, total world consumption of marketed energy is projected to increase by 50 percent from 2005 to 2030. The largest projected increase in energy demand is for the non-OECD economies. Figure 9. World Marketed EnergyConsumption, 1980-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 10. World Marketed Energy Consumption: OECD and Non-OECD, 1980-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 11. Marketed Energy Use in the Non-OECD Economies by Region, 1990-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800.

37

Assumptions to the Annual Energy Outlook 2002 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

38

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

39

Energy Basics: Tankless Demand Water Heaters  

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

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

40

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

and Demand Response Duke Energy is using the name Save-a-Energy Efficiency Division. Duke Energy describes all of itsPresident, and C.E.O. Duke Energy Kateri Callahan President

Goldman, Charles

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "regional energy 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

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

Gasoline and Diesel Fuel Update (EIA)

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

42

Definition: Peak Demand | Open Energy Information  

Open Energy Info (EERE)

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

43

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

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

44

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

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

45

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

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

46

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

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

47

Assisting Mexico in Developing Energy Supply and Demand Projections | Open  

Open Energy Info (EERE)

Assisting Mexico in Developing Energy Supply and Demand Projections Assisting Mexico in Developing Energy Supply and Demand Projections Jump to: navigation, search Name Assisting Mexico in Developing Energy Supply and Demand Projections Agency/Company /Organization Argonne National Laboratory Sector Energy Topics GHG inventory, Background analysis Resource Type Software/modeling tools Website http://www.dis.anl.gov/news/Me Country Mexico UN Region Latin America and the Caribbean References Assisting Mexico in Developing Energy Supply and Demand Projections[1] "CEEESA and the team of experts from Mexico analyzed the country's entire energy supply and demand system using CEEESA's latest version of the popular ENPEP-BALANCE software. The team developed a system representation, a so-called energy network, using ENPEP's powerful graphical user

48

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect

The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

2005-07-01T23:59:59.000Z

49

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

50

Residential sector: the demand for energy services  

Science Conference Proceedings (OSTI)

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

Not Available

1981-01-01T23:59:59.000Z

51

Driving Demand for Home Energy Improvements  

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

Driving Demand for Home Energy Improvements Driving Demand for Home Energy Improvements Title Driving Demand for Home Energy Improvements Publication Type Report Year of Publication 2010 Authors Fuller, Merrian C., Cathy Kunkel, Mark Zimring, Ian M. Hoffman, Katie L. Soroye, and Charles A. Goldman Tertiary Authors Borgeson, Merrian Pagination 136 Date Published 09/2010 Publisher LBNL City Berkeley Keywords electricity markets and policy group, energy analysis and environmental impacts department Abstract Policy makers and program designers in the U.S. and abroad are deeply concerned with the question of how to scale up energy efficiency to a level that is commensurate both to the energy and climate challenges we face, and to the potential for energy savings that has been touted for decades. When policy makers ask what energy efficiency can do, the answers usually revolve around the technical and economic potential of energy efficiency-they rarely hone in on the element of energy demand that matters most for changing energy usage in existing homes: the consumer. A growing literature is concerned with the behavioral underpinnings of energy consumption. We examine a narrower, related subject: How can millions of Americans be persuaded to divert valued time and resources into upgrading their homes to eliminate energy waste, avoid high utility bills, and spur the economy? With hundreds of millions of public dollars1 flowing into incentives, workforce training, and other initiatives to support comprehensive home energy improvements2, it makes sense to review the history of these programs and begin gleaning best practices for encouraging comprehensive home energy improvements. Looking across 30 years of energy efficiency programs that targeted the residential market, many of the same issues that confronted past program administrators are relevant today: How do we cost-effectively motivate customers to take action? Who can we partner with to increase program participation? How do we get residential efficiency programs to scale? While there is no proven formula-and only limited success to date with reliably motivating large numbers of Americans to invest in comprehensive home energy improvements, especially if they are being asked to pay for a majority of the improvement costs-there is a rich and varied history of experiences that new programs can draw upon. Our primary audiences are policy makers and program designers-especially those that are relatively new to the field, such as the over 2,000 towns, cities, states, and regions who are recipients of American Reinvestment and Recovery Act funds for clean energy programs. This report synthesizes lessons from first generation programs, highlights emerging best practices, and suggests methods and approaches to use in designing, implementing, and evaluating these programs. We examined 14 residential energy efficiency programs, conducted an extensive literature review, interviewed industry experts, and surveyed residential contractors to draw out these lessons.

52

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network (OSTI)

Total Annual Energy Usage Peak Electric Demand Power UsageSetpoint (C) Peak Electric Demand Power Usage Effective-Total Annual Energy Usage Peak Electric Demand Scenario

Shehabi, Arman

2010-01-01T23:59:59.000Z

53

Japan's Residential Energy Demand Outlook to 2030  

E-Print Network (OSTI)

for Energy Efficiency and Renewable Energy, Planning, Analysis, and Evaluation section in the U.S. Department section in the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. #12;ppaappeerr ttoo bbeeLBNL-292E Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards

54

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

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

Shen, Bo

2013-01-01T23:59:59.000Z

55

China End-Use Energy Demand Modeling  

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

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

56

Renewable Energy, Demand Response, Energy Efficiency, and Advanced...  

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

Renewable Energy, Demand Response, Energy Efficiency, and Advanced Energy Storage Infrastructure in UC San Diego's Microgrid Speaker(s): Byron Washom Date: August 14, 2008 -...

57

The Integration of Energy Efficiency, Renewable Energy, Demand...  

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

The Integration of Energy Efficiency, Renewable Energy, Demand Response and Climate Change: Challenges and Opportunities for Evaluators and Planners Title The Integration of Energy...

58

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity forecast is the combined product of the hard work and expertise of numerous staff members in the Demand the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast. Miguel Garcia

59

Transportation Demand Management (TDM) Encyclopedia | Open Energy  

Open Energy Info (EERE)

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

60

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

Note: This page contains sample records for the topic "regional energy 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

A residential energy demand system for Spain  

E-Print Network (OSTI)

Sharp price fluctuations and increasing environmental and distributional concerns, among other issues, have led to a renewed academic interest in energy demand. In this paper we estimate, for the first time in Spain, an ...

Labandeira Villot, Xavier

2005-01-01T23:59:59.000Z

62

BRYAN LOVELL Energy supply, demand and impact  

E-Print Network (OSTI)

BRYAN LOVELL Energy supply, demand and impact Now it is Britain's turn to think harder, says Brian both are true. Most predict that fossil fuels must remain a significant part of our energy supply, Britain has had a comfortable and profitable respite from anxieties about security of energy supply. Now

Cambridge, University of

63

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

64

Hydrogen demand, production, and cost by region to 2050.  

DOE Green Energy (OSTI)

This report presents an analysis of potential hydrogen (H{sub 2}) demand, production, and cost by region to 2050. The analysis was conducted to (1) address the Energy Information Administration's (EIA's) request for regional H{sub 2} cost estimates that will be input to its energy modeling system and (2) identify key regional issues associated with the use of H{sub 2} that need further study. Hydrogen costs may vary substantially by region. Many feedstocks may be used to produce H{sub 2}, and the use of these feedstocks is likely to vary by region. For the same feedstock, regional variation exists in capital and energy costs. Furthermore, delivery costs are likely to vary by region: some regions are more rural than others, and so delivery costs will be higher. However, to date, efforts to comprehensively and consistently estimate future H{sub 2} costs have not yet assessed regional variation in these costs. To develop the regional cost estimates and identify regional issues requiring further study, we developed a H{sub 2} demand scenario (called 'Go Your Own Way' [GYOW]) that reflects fuel cell vehicle (FCV) market success to 2050 and allocated H{sub 2} demand by region and within regions by metropolitan versus non-metropolitan areas. Because we lacked regional resource supply curves to develop our H{sub 2} production estimates, we instead developed regional H{sub 2} production estimates by feedstock by (1) evaluating region-specific resource availability for centralized production of H{sub 2} and (2) estimating the amount of FCV travel in the nonmetropolitan areas of each region that might need to be served by distributed production of H{sub 2}. Using a comprehensive H{sub 2} cost analysis developed by SFA Pacific, Inc., as a starting point, we then developed cost estimates for each H{sub 2} production and delivery method by region and over time (SFA Pacific, Inc. 2002). We assumed technological improvements over time to 2050 and regional variation in energy and capital costs. Although we estimate substantial reductions in H{sub 2} costs over time, our cost estimates are generally higher than the cost goals of the U.S. Department of Energy's (DOE's) hydrogen program. The result of our analysis, in particular, demonstrates that there may be substantial variation in H{sub 2} costs between regions: as much as $2.04/gallon gasoline equivalent (GGE) by the time FCVs make up one-half of all light-vehicle sales in the GYOW scenario (2035-2040) and $1.85/GGE by 2050 (excluding Alaska). Given the assumptions we have made, our analysis also shows that there could be as much as a $4.82/GGE difference in H{sub 2} cost between metropolitan and non-metropolitan areas by 2050 (national average). Our national average cost estimate by 2050 is $3.68/GGE, but the average H{sub 2} cost in metropolitan areas in that year is $2.55/GGE and that in non-metropolitan areas is $7.37/GGE. For these estimates, we assume that the use of natural gas to produce H{sub 2} is phased out. This phase-out reflects the desire of DOE's Office of Hydrogen, Fuel Cells and Infrastructure Technologies (OHFCIT) to eliminate reliance on natural gas for H{sub 2} production. We conducted a sensitivity run in which we allowed natural gas to continue to be used through 2050 for distributed production of H{sub 2} to see what effect changing that assumption had on costs. In effect, natural gas is used for 66% of all distributed production of H{sub 2} in this run. The national average cost is reduced to $3.10/GGE, and the cost in non-metropolitan areas is reduced from $7.37/GGE to $4.90, thereby reducing the difference between metropolitan and non-metropolitan areas to $2.35/GGE. Although the cost difference is reduced, it is still substantial. Regional differences are similarly reduced, but they also remain substantial. We also conducted a sensitivity run in which we cut in half our estimate of the cost of distributed production of H{sub 2} from electrolysis (our highest-cost production method). In this run, our national average cost estimate is reduced even further, to

Singh, M.; Moore, J.; Shadis, W.; Energy Systems; TA Engineering, Inc.

2005-10-31T23:59:59.000Z

65

Hydrogen demand, production, and cost by region to 2050.  

SciTech Connect

This report presents an analysis of potential hydrogen (H{sub 2}) demand, production, and cost by region to 2050. The analysis was conducted to (1) address the Energy Information Administration's (EIA's) request for regional H{sub 2} cost estimates that will be input to its energy modeling system and (2) identify key regional issues associated with the use of H{sub 2} that need further study. Hydrogen costs may vary substantially by region. Many feedstocks may be used to produce H{sub 2}, and the use of these feedstocks is likely to vary by region. For the same feedstock, regional variation exists in capital and energy costs. Furthermore, delivery costs are likely to vary by region: some regions are more rural than others, and so delivery costs will be higher. However, to date, efforts to comprehensively and consistently estimate future H{sub 2} costs have not yet assessed regional variation in these costs. To develop the regional cost estimates and identify regional issues requiring further study, we developed a H{sub 2} demand scenario (called 'Go Your Own Way' [GYOW]) that reflects fuel cell vehicle (FCV) market success to 2050 and allocated H{sub 2} demand by region and within regions by metropolitan versus non-metropolitan areas. Because we lacked regional resource supply curves to develop our H{sub 2} production estimates, we instead developed regional H{sub 2} production estimates by feedstock by (1) evaluating region-specific resource availability for centralized production of H{sub 2} and (2) estimating the amount of FCV travel in the nonmetropolitan areas of each region that might need to be served by distributed production of H{sub 2}. Using a comprehensive H{sub 2} cost analysis developed by SFA Pacific, Inc., as a starting point, we then developed cost estimates for each H{sub 2} production and delivery method by region and over time (SFA Pacific, Inc. 2002). We assumed technological improvements over time to 2050 and regional variation in energy and capital costs. Although we estimate substantial reductions in H{sub 2} costs over time, our cost estimates are generally higher than the cost goals of the U.S. Department of Energy's (DOE's) hydrogen program. The result of our analysis, in particular, demonstrates that there may be substantial variation in H{sub 2} costs between regions: as much as $2.04/gallon gasoline equivalent (GGE) by the time FCVs make up one-half of all light-vehicle sales in the GYOW scenario (2035-2040) and $1.85/GGE by 2050 (excluding Alaska). Given the assumptions we have made, our analysis also shows that there could be as much as a $4.82/GGE difference in H{sub 2} cost between metropolitan and non-metropolitan areas by 2050 (national average). Our national average cost estimate by 2050 is $3.68/GGE, but the average H{sub 2} cost in metropolitan areas in that year is $2.55/GGE and that in non-metropolitan areas is $7.37/GGE. For these estimates, we assume that the use of natural gas to produce H{sub 2} is phased out. This phase-out reflects the desire of DOE's Office of Hydrogen, Fuel Cells and Infrastructure Technologies (OHFCIT) to eliminate reliance on natural gas for H{sub 2} production. We conducted a sensitivity run in which we allowed natural gas to continue to be used through 2050 for distributed production of H{sub 2} to see what effect changing that assumption had on costs. In effect, natural gas is used for 66% of all distributed production of H{sub 2} in this run. The national average cost is reduced to $3.10/GGE, and the cost in non-metropolitan areas is reduced from $7.37/GGE to $4.90, thereby reducing the difference between metropolitan and non-metropolitan areas to $2.35/GGE. Although the cost difference is reduced, it is still substantial. Regional differences are similarly reduced, but they also remain substantial. We also conducted a sensitivity run in which we cut in half our estimate of the cost of distributed production of H{sub 2} from electrolysis (our highest-cost production method). In this run, our national average cost es

Singh, M.; Moore, J.; Shadis, W.; Energy Systems; TA Engineering, Inc.

2005-10-31T23:59:59.000Z

66

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

E-Print Network (OSTI)

step is to calculate energy service demand in each category,mainly determine the energy service demand while pricesthe energy source. In both energy service demand and energy

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

67

Electric power supply and demand 1979 to 1988 for the contiguous United States as projected by the Regional Electric Reliability Councils in their April 1, 1979 long-range coordinated planning reports to the Department of Energy  

SciTech Connect

Information concerning bulk electric power supply and demand is summarized and reviewed. Electric-utility power-supply systems are composed of power sources, transmission and distribution facilities, and users of electricity. In the United States there are three such systems of large geographic extent that together cover the entire country. Subjects covered are: energy forecasts, peak demand forecasts, generating-capacity forecasts, purchases and sales of capacity, and transmission. Extensive data are compiled in 17 tables. Information in two appendices includes a general description of the Regional Electric Reliability Councils and US generating capacity as of June 30, 1979. 3 figures, 17 tables.

Savage, N.; Graban, W.

1979-12-01T23:59:59.000Z

68

Transportation Energy: Supply, Demand and the Future  

E-Print Network (OSTI)

Transportation Energy: Supply, Demand and the Future http://www.uwm.edu/Dept/CUTS//2050/energy05.pdf Edward Beimborn Center for Urban Transportation Studies University of Wisconsin-Milwaukee Presentation to the District IV Conference Institute of Transportation Engineers June, 2005, updated September

Saldin, Dilano

69

Energy Demand (released in AEO2010)  

Reports and Publications (EIA)

Growth in U.S. energy use is linked to population growth through increases in demand for housing, commercial floorspace, transportation, manufacturing, and services. This affects not only the level of energy use, but also the mix of fuels and consumption by sector.

Information Center

2010-05-11T23:59:59.000Z

70

Letters: Energy demand prediction using GMDH networks  

Science Conference Proceedings (OSTI)

The electric power industry is in transition as it moves towards a competitive and deregulated environment. In this emerging market, traditional electric utilities as well as energy traders, power pools and independent system operators (ISOs) need the ... Keywords: Artificial neural networks, Energy demand, Forecasting, Group method of data handling (GMDH) networks, Self-organizing networks

Dipti Srinivasan

2008-12-01T23:59:59.000Z

71

Behavioral Aspects in Simulating the Future US Building Energy Demand  

E-Print Network (OSTI)

off- site energy demand (2030) 20% decrease to parameter 20%off-site energy demand (2030) 20% decrease to parameter 20%off-site energy demand (2030) 20% decrease to parameter 20%

Stadler, Michael

2011-01-01T23:59:59.000Z

72

EIA - Annual Energy Outlook 2009 - Energy Demand  

Gasoline and Diesel Fuel Update (EIA)

demand for renewable fuels increasing the fastestincluding E85 and biodiesel fuels for light-duty vehicles, biomass for co-firing at coal-fired electric power plants, and...

73

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

74

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

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

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

2008-01-01T23:59:59.000Z

75

Opportunities for Energy Efficiency and Demand Response in the...  

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

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

76

Response to several FOIA requests - Renewable Energy. Demand...  

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

Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. nepdg251500.pdf....

77

Energy Demands and Efficiency Strategies in Data Center Buildings  

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

Energy Demands and Efficiency Strategies in Data Center Buildings Title Energy Demands and Efficiency Strategies in Data Center Buildings Publication Type Thesis Year of...

78

South Korea-ANL Distributed Energy Resources and Demand Side...  

Open Energy Info (EERE)

Korea-ANL Distributed Energy Resources and Demand Side Management Jump to: navigation, search Name Distributed Energy Resources and Demand Side Management in South Korea Agency...

79

Modeling the residential demand for energy  

Science Conference Proceedings (OSTI)

Demand for energy is derived from the demand for services that appliances and energy together provide. This raises a number of serious econometric issues when estimating energy-demand functions: delineation of short-run and long-run household responses, specification of the price variable and in particular, the assumption that the model is recursive, or in other words, that the appliance choice equation and the energy consumption equation are uncorrelated. The dissertation utilizes a structural model of energy use whose theoretical underpinnings derive from the conditional logit model and an extension of that model to the joint-discrete/continuous case by Dubin and McFadden (1980). It uses the 1978 to 1979 National Interim Energy Comsumption Survey. Three appliance portfolio choices are analyzed; choice of water and space heating and central air-conditioning; choice of room air conditioners; and choice of clothes dryers, either as multinomial logit or binary probit choices. Results varied widely across the appliance choice considered; use of Hausman's test led to acceptance of the null hypothesis of orthogonality in some cases but not in others. Demand for electricity and natural gas tended to be price inelastic; however, estimated own-price effects differed considerably when disaggregated by appliance categories and across methods of estimation.

Kirby, S.N.

1983-01-01T23:59:59.000Z

80

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

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

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

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "regional energy 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

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":""}]}

82

U.S. Regional Demand Forecasts Using NEMS and GIS  

E-Print Network (OSTI)

Efficiency and Renewable Energy U.S. Department of Energyor consumption of energy in the U.S. Figure 2: The 13California Energy Commission 2002) U.S. Regional Energy

Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

2005-01-01T23:59:59.000Z

83

Impact of improved building thermal efficiency on residential energy demand  

SciTech Connect

The impact of improved building shell thermal efficiency on residential energy demand is explored in a theoretical framework. The important economic literature on estimating the price elasticity of residential energy demand is reviewed. The specification of the residential energy demand model is presented. The data used are described. The empirical estimation of the residential energy demand model is described. (MHR)

Adams, R.C.; Rockwood, A.D.

1983-04-01T23:59:59.000Z

84

Demand Management Institute (DMI) | Open Energy Information  

Open Energy Info (EERE)

Demand Management Institute (DMI) Demand Management Institute (DMI) Jump to: navigation, search Name Demand Management Institute (DMI) Address 35 Walnut Street Place Wellesley, Massachusetts Zip 02481 Sector Buildings Product Provides analysis for buildings on reducing energy use Website http://www.dmiinc.com/ Coordinates 42.3256508°, -71.2530294° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":42.3256508,"lon":-71.2530294,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

85

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

to Building Energy Management Systems (BEMS) to begin pre-a facility using Energy Management Control Systems (EMCS) orAct of 2007 energy management control systems The Energy

Shen, Bo

2013-01-01T23:59:59.000Z

86

Comparison of Demand Response Performance with an EnergyPlus...  

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

of Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building Title Comparison of Demand Response Performance with an EnergyPlus Model in a Low Energy...

87

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

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

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

88

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

services provided to the energy markets, Order 745 advancesin the wholesale energy market (both day-ahead and real-the capacity market is. The energy market does not feature

Shen, Bo

2013-01-01T23:59:59.000Z

89

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

is determined by the market energy price offered by themay be paid the spot market energy price. (e.g. PJM SRM, UKor the wholesale market price for energy. By codifying the

Shen, Bo

2013-01-01T23:59:59.000Z

90

Assumptions to the Annual Energy Outlook 2000 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The distinction between the two sets of manufacturing industries pertains to the level of modeling. The energy-intensive industries are modeled through the use of a detailed process flow accounting procedure, whereas the nonenergy-intensive and the nonmanufacturing industries are modeled with substantially less detail (Table 14). The Industrial Demand Module forecasts energy consumption at the four Census region levels; energy consumption at the Census Division level is allocated by using the SEDS24 data.

91

Draft Chapter 3: Demand-Side Resources | Department of Energy  

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

Draft Chapter 3: Demand-Side Resources Draft Chapter 3: Demand-Side Resources Utilities in many states have been implementing energy efficiency and load management programs...

92

Optimal Demand Response with Energy Storage Management  

E-Print Network (OSTI)

In this paper, we consider the problem of optimal demand response and energy storage management for a power consuming entity. The entity's objective is to find an optimal control policy for deciding how much load to consume, how much power to purchase from/sell to the power grid, and how to use the finite capacity energy storage device and renewable energy, to minimize his average cost, being the disutility due to load- shedding and cost for purchasing power. Due to the coupling effect of the finite size energy storage, such problems are challenging and are typically tackled using dynamic programming, which is often complex in computation and requires substantial statistical information of the system dynamics. We instead develop a low-complexity algorithm called Demand Response with Energy Storage Management (DR-ESM). DR-ESM does not require any statistical knowledge of the system dynamics, including the renewable energy and the power prices. It only requires the entity to solve a small convex optimization pr...

Huang, Longbo; Ramchandran, Kannan

2012-01-01T23:59:59.000Z

93

Coordination of Energy Efficiency and Demand Response  

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

044E 044E ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY Coordination of Energy Efficiency and Demand Response Charles Goldman, Michael Reid, Roger Levy and Alison Silverstein Environmental Energy Technologies Division January 2010 The work described in this report was funded by the Department of Energy Office of Electricity Delivery and Energy Reliability, Permitting, Siting and Analysis of the U.S. Department of Energy under Contract No. DE-AC02- 05CH11231. Disclaimer This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes

94

Univariate Modeling and Forecasting of Monthly Energy Demand Time Series  

E-Print Network (OSTI)

in this report. #12;i ABSTRACT These electricity demand forms and instructions ask load-serving entities and Instructions for Electricity Demand Forecasts. California Energy Commission, Electricity Supply Analysis.................................................................................................................................7 Form 1 Historic and Forecast Electricity Demand

Abdel-Aal, Radwan E.

95

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network (OSTI)

DX Cooling Total Annual Energy Usage Peak Electric DemandDX Cooling Total Annual Energy Usage Scenario Supply/ ReturnDX Cooling Total Annual Energy Usage Peak Electric Demand

Shehabi, Arman

2010-01-01T23:59:59.000Z

96

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

E-Print Network (OSTI)

Energy Outlook -A Projection up to 2030 under EnvironmentalEnergy Demand Outlook to 2030 Considering Energy EfficiencyEnergy Demand Outlook to 2030 Considering Energy Efficiency

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

97

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

E-Print Network (OSTI)

Japan Long-Term Energy Outlook -A Projection up to 2030Residential Energy Demand Outlook to 2030 Considering EnergyResidential Energy Demand Outlook to 2030 Considering Energy

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

98

The Role of Demand Resources In Regional Transmission Expansion Planning and Reliable Operations  

Science Conference Proceedings (OSTI)

Investigating the role of demand resources in regional transmission planning has provided mixed results. On one hand there are only a few projects where demand response has been used as an explicit alternative to transmission enhancement. On the other hand there is a fair amount of demand response in the form of energy efficiency, peak reduction, emergency load shedding, and (recently) demand providing ancillary services. All of this demand response reduces the need for transmission enhancements. Demand response capability is typically (but not always) factored into transmission planning as a reduction in the load which must be served. In that sense demand response is utilized as an alternative to transmission expansion. Much more demand response is used (involuntarily) as load shedding under extreme conditions to prevent cascading blackouts. The amount of additional transmission and generation that would be required to provide the current level of reliability if load shedding were not available is difficult to imagine and would be impractical to build. In a very real sense demand response solutions are equitably treated in every region - when proposed, demand response projects are evaluated against existing reliability and economic criteria. The regional councils, RTOs, and ISOs identify needs. Others propose transmission, generation, or responsive load based solutions. Few demand response projects get included in transmission enhancement plans because few are proposed. But this is only part of the story. Several factors are responsible for the current very low use of demand response as a transmission enhancement alternative. First, while the generation, transmission, and load business sectors each deal with essentially the same amount of electric power, generation and transmission companies are explicitly in the electric power business but electricity is not the primary business focus of most loads. This changes the institutional focus of each sector. Second, market and reliability rules have, understandably, been written around the capabilities and limitations of generators, the historic reliability resources. Responsive load limitations and capabilities are often not accommodated in markets or reliability criteria. Third, because of the institutional structure, demand response alternatives are treated as temporary solutions that can delay but not replace transmission enhancement. Financing has to be based on a three to five year project life as opposed to the twenty to fifty year life of transmission facilities. More can be done to integrate demand response options into transmission expansion planning. Given the societal benefits it may be appropriate for independent transmission planning organizations to take a more proactive role in drawing demand response alternatives into the resource mix. Existing demand response programs provide a technical basis to build from. Regulatory and market obstacles will have to be overcome if demand response alternatives are to be routinely considered in transmission expansion planning.

Kirby, Brendan J [ORNL

2006-07-01T23:59:59.000Z

99

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

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

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

2008-01-01T23:59:59.000Z

100

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

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

Goldman, Charles

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "regional energy 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

Tankless Demand Water Heaters | Department of Energy  

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

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

102

EIA - Annual Energy Outlook 2009 - Electricity Demand  

Gasoline and Diesel Fuel Update (EIA)

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

103

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

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

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

2008-01-01T23:59:59.000Z

104

Examining Synergies between Energy Management and Demand Response: A Case Study at Two California Industrial Facilities  

E-Print Network (OSTI)

and Demand Response History Energy Management Activities o #and Demand Response History Energy Management Activities

Olsen, Daniel

2013-01-01T23:59:59.000Z

105

U.S. Regional Demand Forecasts Using NEMS and GIS  

E-Print Network (OSTI)

residential and commercial electricity demand forecasts. The23 Electricity Demandand commercial electricity demand per census division from

Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

2005-01-01T23:59:59.000Z

106

Residential Demand Module of the National Energy Modeling ...  

U.S. Energy Information Administration (EIA)

Residential Demand Module of the National Energy Modeling System: Model Documentation 2013 November 2013 Independent Statistics & Analysis ...

107

Coordination of Energy Efficiency and Demand Response: A Resource...  

Open Energy Info (EERE)

Coordination of Energy Efficiency and Demand Response: A Resource of the National Action Plan for Energy Efficiency Jump to: navigation, search Tool Summary LAUNCH TOOL Name:...

108

Chapter 3 Demand-Side Resources | Department of Energy  

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

these resources result from one of two methods of reducing load: energy efficiency or demand response load management. The energy efficiency method designs and deploys...

109

Examining Synergies between Energy Management and Demand Response...  

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

Examining Synergies between Energy Management and Demand Response: A Case Study at Two California Industrial Facilities Title Examining Synergies between Energy Management and...

110

Poster: Thermal Energy Storage for Electricity Peak-demand Mitigation...  

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

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

111

Energy Efficiency/Demand Response/Smart Grid/Distribution ...  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration Independent Statistics & Analysis www.eia.gov Energy Efficiency/Demand Response/Smart Grid/Distribution ...

112

Assumptions to the Annual Energy Outlook 1999 - Industrial Demand...  

Gasoline and Diesel Fuel Update (EIA)

industrial.gif (5205 bytes) The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing...

113

Solar in Demand | Department of Energy  

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

in Demand Solar in Demand June 15, 2012 - 10:23am Addthis Kyle Travis, left and Jon Jackson, with Lighthouse Solar, install microcrystalline PV modules on top of Kevin Donovan's...

114

Demand Response - Policy | Department of Energy  

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

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

115

Propane Demand by Sector - Energy Information Administration  

U.S. Energy Information Administration (EIA)

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

116

EnergySolve Demand Response | Open Energy Information  

Open Energy Info (EERE)

EnergySolve Demand Response EnergySolve Demand Response Jump to: navigation, search Name EnergySolve Demand Response Place Somerset, New Jersey Product Somerset-based utility bill outsourcing company that provides electronic utility bill auditing, tariff analysis, late fee avoidance, and flexible bill payment solutions. Coordinates 45.12402°, -92.675379° 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":45.12402,"lon":-92.675379,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

117

Reducing Energy Demand in Buildings Through State Energy Codes  

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

Codes Assistance Project Codes Assistance Project Maureen Guttman, AIA Executive Director, BCAP Alliance to Save Energy 202-530-2211 mguttman@ase.org Tuesday, April 2, 2013 - Thursday, April 4, 2013 Reducing Energy Demand in Buildings Through State Energy Codes - Providing Technical Support and Assistance to States - 2 | Building Technologies Office eere.energy.gov Purpose & Objectives Problem Statement: Buildings = largest sector of energy consumption in America * Energy codes are a ready-made regulatory mechanism * States need support for implementation Impact of Project:

118

Reducing Energy Demand in Buildings Through State Energy Codes  

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

Codes Assistance Project Codes Assistance Project Maureen Guttman, AIA Executive Director, BCAP Alliance to Save Energy 202-530-2211 mguttman@ase.org Tuesday, April 2, 2013 - Thursday, April 4, 2013 Reducing Energy Demand in Buildings Through State Energy Codes - Providing Technical Support and Assistance to States - 2 | Building Technologies Office eere.energy.gov Purpose & Objectives Problem Statement: Buildings = largest sector of energy consumption in America * Energy codes are a ready-made regulatory mechanism * States need support for implementation Impact of Project:

119

Residential Energy Demand Reduction Analysis and Monitoring Platform - REDRAMP  

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

Dramatic Peak Residential Dramatic Peak Residential Demand Reduction in the Desert Southwest Yahia Baghzouz Center for Energy Research University of Nevada, Las Vegas Golden, CO Overview * Project description * Subdivision energy efficiency features * Home energy monitoring * Demand side management * Feeder loading * Battery Energy Storage System * Future Work Team Members Project Objective and Methodology * The main objective is to reduce peak power demand of a housing subdivision by 65% (compared to housing development that is built to conventional code). * This objective will be achieved by - Energy efficient home construction with roof- integrated PV system - Demand Side Management - Battery Energy Storage System Project schematic Diagram Project Physical Location: Las Vegas, NV Red Rock Hotel/Casino

120

Beyond Renewable Portfolio Standards: An Assessment of Regional Supply and Demand Conditions Affecting the Future of Renewable Energy in the West; Report and Executive Summary  

SciTech Connect

This study assesses the outlook for utility-scale renewable energy development in the West once states have met their renewable portfolio standard (RPS) requirements. In the West, the last state RPS culminates in 2025, so the analysis uses 2025 as a transition point on the timeline of RE development. Most western states appear to be on track to meet their final requirements, relying primarily on renewable resources located relatively close to the customers being served. What happens next depends on several factors including trends in the supply and price of natural gas, greenhouse gas and other environmental regulations, consumer preferences, technological breakthroughs, and future public policies and regulations. Changes in any one of these factors could make future renewable energy options more or less attractive.

Hurlbut, D. J.; McLaren, J.; Gelman, R.

2013-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "regional energy 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

Building Energy Software Tools Directory: Demand Response Quick Assessment  

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

Demand Response Quick Assessment Tool Demand Response Quick Assessment Tool Demand response quick assessment tool image The opportunities for demand reduction and cost savings with building demand responsive controls vary tremendously with building type and location. This assessment tool will predict the energy and demand savings, the economic savings, and the thermal comfort impact for various demand responsive strategies. Users of the tool will be asked to enter the basic building information such as types, square footage, building envelope, orientation, utility schedule, etc. The assessment tool will then use the prototypical simulation models to calculate the energy and demand reduction potential under certain demand responsive strategies, such as precooling, zonal temperature set up, and chilled water loop and air loop set points

122

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

Gasoline and Diesel Fuel Update (EIA)

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

123

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

for the most natural gas usage (33% and 51% of total demanddependence in natural gas usage, and consequently, Januarygas demand exhibits a strong winter peak in residential usage

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

2008-01-01T23:59:59.000Z

124

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

In Maximum demand, year 2050 electricity consumption reachesefficiency, year 2050 electricity consumption is 357 TWh,capita electricity consumption increases from 7,421 kWh/year

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

2008-01-01T23:59:59.000Z

125

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

both types of programs. Xcel Energy markets both energyEnergy Efficiency Marketing Xcel Energy Paul Suskie Chairman

Goldman, Charles

2010-01-01T23:59:59.000Z

126

Demand Response Energy Consulting LLC | Open Energy Information  

Open Energy Info (EERE)

Response Energy Consulting LLC Response Energy Consulting LLC Jump to: navigation, search Name Demand Response & Energy Consulting LLC Place Delanson, New York Zip NY 12053 Sector Efficiency Product Delanson-based demand response and energy efficiency consultants. Coordinates 42.748995°, -74.185794° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":42.748995,"lon":-74.185794,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

127

Behavioral Aspects in Simulating the Future US Building Energy Demand  

E-Print Network (OSTI)

USA, and published in the Conference Proceedings Structure of SBEAM Floor-space forecast to 2050 Gross demandUSA, and published in the Conference Proceedings Structure of SBEAM Floor-space forecast to 2050 Gross demandUSA, and published in the Conference Proceedings Relative Importance Total off- site energy demand (

Stadler, Michael

2011-01-01T23:59:59.000Z

128

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, Electricity Demography Japans population, an important factor in predicting residential energy demand as well

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

129

Demand Response and Smart Metering Policy Actions Since the Energy...  

Open Energy Info (EERE)

Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Officials Jump to: navigation, search Tool Summary LAUNCH TOOL Name:...

130

Residential Energy Demand Reduction Analysis and Monitoring Platform...  

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

Dramatic Peak Residential Demand Reduction in the Desert Southwest Yahia Baghzouz Center for Energy Research University of Nevada, Las Vegas Golden, CO Overview * Project...

131

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

Open Energy Info (EERE)

Side Management Website Jump to: navigation, search Name Network-Driven Demand Side Management Website Abstract This task of the International Energy Agency is a broad,...

132

1995 Demand-Side Managment - Energy Information Administration  

U.S. Energy Information Administration (EIA)

and more detailed data on energy savings, peak load reductions and costs attributable to DSM. Target Audience ... Profile: U.S. Electric Utility Demand-Side

133

Commercial Demand Module of the National Energy Modeling System ...  

U.S. Energy Information Administration (EIA)

Commercial Demand Module of the National Energy Modeling System: Model Documentation 2012 November 2012 . Independent Statistics & Analysis . www.eia.gov

134

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

Renewable energy spillage, operating costs and capacityfocused on renewable energy utilization, cost of operationssystem operating costs, renewable energy utilization,

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

135

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

Scale Renewable Energy Integration . . . . . . . . . . .Impacts of Renewable Energy Supply . . . . . . . . . . . . .1.3 Coupling Renewable Energy with Deferrable

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

136

Solar in Demand | Department of Energy  

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

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

137

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

Regulatory Commission [FERC] (2008). Assessment of DemandRegulatory Commission [FERC] (2009). A National AssessmentEIS EMCS EMS EPA ESCO ESPC FERC GE HVAC ISO ISO-NE kW kWh MW

Goldman, Charles

2010-01-01T23:59:59.000Z

138

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

function of real-time electricity prices (left) and windinflexible) demand and real-time prices. The case study inas a special case. The real-time price process is modeled as

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

139

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

140

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

energy scenarios to explore alternative energy pathways indo not include the alternative energy pathways (such asmodeling to investigate alternative energy supply strategies

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

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "regional energy 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

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)

142

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

Figure 16 Annual peak electricity demand by sector. Tableincludes an hourly electricity demand (i.e. power) profileof aggregating sectoral electricity demands into a statewide

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

2008-01-01T23:59:59.000Z

143

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

Table 22. Agricultural natural gas demand by planning area.23. Other sector natural gas demand by planning area.Projections Monthly natural gas demands are depicted in

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

2008-01-01T23:59:59.000Z

144

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

Gasoline and Diesel Fuel Update (EIA)

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

145

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

Gasoline and Diesel Fuel Update (EIA)

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

146

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

Gasoline and Diesel Fuel Update (EIA)

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

147

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

Gasoline and Diesel Fuel Update (EIA)

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

148

Assessment of Residential Energy Management Systems for Demand Response Applications  

Science Conference Proceedings (OSTI)

This Technical Update provides a description of what a residential energy management system comprises, with a focus on demand response applications. It includes findings from a survey of residential energy management system technology vendors; system pricing and availability; an overview of technology components and features; customer load monitoring and control capabilities; utility demand response control functions; communications protocols and technologies supported; and options for demand response si...

2009-12-22T23:59:59.000Z

149

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

same or better levels of energy services. This definitionSenior Vice President, Energy Services and Technology NewNational Association of Energy Service Companies Chuck Gray

Goldman, Charles

2010-01-01T23:59:59.000Z

150

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

to managing their energy usage. Greater customer willingnessto managing their energy usage. And greater customera net reduction in energy usage. 5 With sufficient advance

Goldman, Charles

2010-01-01T23:59:59.000Z

151

Regulation Services with Demand Response - Energy Innovation ...  

Biomass and Biofuels; Building Energy Efficiency; Electricity Transmission; Energy Analysis; Energy Storage; Geothermal; Hydrogen and Fuel Cell; ... (i.e. target ...

152

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

achieving all cost-effective energy efficiency by 2025. Thisinvestment in cost-effective energy efficiency. Coordinationto achieve all cost-effective energy efficiency by 2025. 1

Goldman, Charles

2010-01-01T23:59:59.000Z

153

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

control system energy management system U.S. Environmentalbuilding energy management systems (EMS) can deliversystem; EMS = energy management system; ISO = independent

Goldman, Charles

2010-01-01T23:59:59.000Z

154

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

of locational renewable energy production in each renewableto total renewable energy production, although accountingproduction data from the 2006 data set of the National Renewable Energy

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

155

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

Programs Integrated Energy Audit Provide engineeringtechnicians performed energy audits and provided advice to8 PG&Es Integrated Energy Audit, a program for businesses

Goldman, Charles

2010-01-01T23:59:59.000Z

156

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

what if wholesale market energy prices remain low or if CPPwith high prices in the real-time energy market. Nationalmarket prices and reliability circumstances, even though energy

Goldman, Charles

2010-01-01T23:59:59.000Z

157

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

forecasting for wind energy: Temperature dependence andlarge amounts of wind energy with a small electric system.Large scale integration of wind energy in the european power

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

158

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

1.2 Limitations to Large-Scale Renewable EnergyImpacts of Renewable Energy Supply . . . . . . . . . . . . .1.3 Coupling Renewable Energy with Deferrable

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

159

2012 SG Peer Review - Recovery Act: Enhanced Demand and Distribution Management Regional Demonstration - Craig Miller, NRECA  

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

Enhanced Distribution and Demand Management Enhanced Distribution and Demand Management Regional Demonstration Craig Miller Cooperative Research Network National Rural Electric Cooperative Association 8 June 2012 December 2008 Project Title Objective Life-cycle Funding ($K) $68 million with match Hardware: $43 million Research: $11.6 Co-op Labor: $13.4 Technical Scope * 23 Co-ops, Distributed Nationally * 275,000 components deployed * Meters & DR * Distribution Automation * Infrastructure * In home displays and web portals * Demand response over AMI * Prepaid metering * Interactive thermal storage * Electrical storage (20x10kWh, 1MWh 0.5MWh) * Renewable energy * Smart feeder switching * Conservation voltage reduction * Advanced metering infrastructure * Meter data management * Communications infrastructure * SCADA To advance the deployment of the smart grid

160

Proceedings of the Chinese-American symposium on energy markets and the future of energy demand  

SciTech Connect

The Symposium was organized by the Energy Research Institute of the State Economic Commission of China, and the Lawrence Berkeley Laboratory and Johns Hopkins University from the United States. It was held at the Johns Hopkins University Nanjing Center in late June 1988. It was attended by about 15 Chinese and an equal number of US experts on various topics related to energy demand and supply. Each presenter is one of the best observers of the energy situation in their field. A Chinese and US speaker presented papers on each topic. In all, about 30 papers were presented over a period of two and one half days. Each paper was translated into English and Chinese. The Chinese papers provide an excellent overview of the emerging energy demand and supply situation in China and the obstacles the Chinese planners face in managing the expected increase in demand for energy. These are matched by papers that discuss the energy situation in the US and worldwide, and the implications of the changes in the world energy situation on both countries. The papers in Part 1 provide historical background and discuss future directions. The papers in Part 2 focus on the historical development of energy planning and policy in each country and the methodologies and tools used for projecting energy demand and supply. The papers in Part 3 examine the pattern of energy demand, the forces driving demand, and opportunities for energy conservation in each of the major sectors in China and the US. The papers in Part 4 deal with the outlook for global and Pacific region energy markets and the development of the oil and natural gas sector in China.

Meyers, S. (ed.)

1988-11-01T23:59:59.000Z

Note: This page contains sample records for the topic "regional energy 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

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST forecast is the combined product of the hard work and expertise of numerous staff members in the Demand prepared the residential sector forecast. Mohsen Abrishami prepared the commercial sector forecast. Lynn

162

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

Director, Energy and Environmental Policy American ForestEnergy Efficiency Partnerships Roger Cooper Executive Vice President, Policy and Planning American

Goldman, Charles

2010-01-01T23:59:59.000Z

163

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

State Energy Research & Development Authority offers incentivesState Energy Research and Development Authority (NYSERDA) Existing Facilities Program offers incentives

Goldman, Charles

2010-01-01T23:59:59.000Z

164

Demand Responsive and Energy Efficient Control Technologies and Strategies in Commercial Buildings  

E-Print Network (OSTI)

Energy. Benefits of Demand Response in Electricity MarketsEnergy Efficiency and Demand Response?7 3.1.Demand Response in Commercial

Piette, Mary Ann; Kiliccote, Sila

2006-01-01T23:59:59.000Z

165

A Successful Case Study of Small Business Energy Efficiency and Demand Response with Communicating Thermostats  

E-Print Network (OSTI)

to everyone at the Demand Response Research Center, theEnergy Efficiency and Demand Response with CommunicatingEnergy Efficiency and Demand Response with Communicating

Herter, Karen

2010-01-01T23:59:59.000Z

166

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

E-Print Network (OSTI)

Energy EfficiencyandDemandResponseintheCalifornia1 4.0 EnergyEfficiencyandDemandResponse5 4.2. DemandResponse

Olsen, Daniel

2012-01-01T23:59:59.000Z

167

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network (OSTI)

Energy Resources and Demand Response under Uncertainty AfzalEnergy Resources and Demand Response under Uncertainty ?DER in conjunction with demand response (DR): the expected

Siddiqui, Afzal

2010-01-01T23:59:59.000Z

168

Demand Response and Smart Metering Policy Actions Since the Energy...  

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

Policy Actions Since the Energy Policy Act of 2005: A Summary for State Officials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A...

169

Strategies for reducing energy demand in the materials sector  

E-Print Network (OSTI)

This research answers a key question - can the materials sector reduce its energy demand by 50% by 2050? Five primary materials of steel, cement, aluminum, paper, and plastic, contribute to 50% or more of the final energy ...

Sahni, Sahil

2013-01-01T23:59:59.000Z

170

Response to several FOIA requests - Renewable Energy. Demand for Fossil  

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

Response to several FOIA requests - Renewable Energy. Demand for Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. nepdg_251_500.pdf. Demand for Fossil Fuels. Renewable sources of power. Demand for fossil fuels surely will overrun supply sooner or later, as indeed it already has in the casc of United States domestic oil drilling. Recognition also is growing that our air and land can no longer absorb unlimited quantities of waste from fossil fuel extraction and combustion. As that day draws nearer, policymakers will have no realistic alternative but to turn to sources of power that today make up a viable but small part of America's energy picture. And they will be

171

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

new technology and systems integration tools. Energy controland systems that support integration and coordination of energyand systems integration represent key building blocks for enabling greater coordination of energy

Goldman, Charles

2010-01-01T23:59:59.000Z

172

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

Gasoline and Diesel Fuel Update (EIA)

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

173

The National Energy Modeling System: An Overview 1998 - Commercial Demand  

Gasoline and Diesel Fuel Update (EIA)

COMMERCIAL DEMAND MODULE COMMERCIAL DEMAND MODULE blueball.gif (205 bytes) Floorspace Submodule blueball.gif (205 bytes) Energy Service Demand Submodule blueball.gif (205 bytes) Equipment Choice Submodule blueball.gif (205 bytes) Energy Consumption Submodule The commercial demand module (CDM) forecasts energy consumption by Census division for eight marketed energy sources plus solar thermal energy. For the three major commercial sector fuels, electricity, natural gas and distillate oil, the CDM is a "structural" model and its forecasts are built up from projections of the commercial floorspace stock and of the energy-consuming equipment contained therein. For the remaining five marketed "minor fuels," simple econometric projections are made. The commercial sector encompasses business establishments that are not

174

Ethanol Demand in United States Regional Production of Oxygenate-limited Gasoline  

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

5 5 Ethanol Demand in United States Regional Production of Oxygenate-limited Gasoline G. R. Hadder Center for Transportation Analysis Oak Ridge National Laboratory Oak Ridge, Tennessee August 2000 Prepared for Office of Fuels Development Office of Transportation Technologies U.S. Department of Energy Prepared by the OAK RIDGE NATIONAL LABORATORY Oak Ridge, Tennessee 37831 managed by UT-BATTELLE, LLC for the U. S. DEPARTMENT OF ENERGY under contract DE-AC05-00OR22725 iii TABLE OF CONTENTS LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi ACRONYMS AND ABBREVIATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix EXECUTIVE SUMMARY

175

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network (OSTI)

Optimal Control of Distributed Energy Resources and DemandRenewable Energy, former Distributed Energy Program of theOptimal Control of Distributed Energy Resources and Demand

Siddiqui, Afzal

2010-01-01T23:59:59.000Z

176

Regional Short-Term Energy Model (RSTEM) Overview  

Reports and Publications (EIA)

The Regional Short-Term Energy Model (RSTEM) utilizes estimated econometric relationships for demand, inventories and prices to forecast energy market outcomes across key sectors and selected regions throughout the United States.

Information Center

2009-04-16T23:59:59.000Z

177

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

by Sector Residential Peak Demand (MW) Commercial IndustrialTable 16. Non-coincident peak demand by sector. growth Avg.IEPR Projected non-coincident peak demand (MW) 3.1.2. Hourly

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

2008-01-01T23:59:59.000Z

178

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022  

E-Print Network (OSTI)

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022 AUGUST 2011 CEC-200-2011-011-SD CALIFORNIA or adequacy of the information in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast forecast. Bryan Alcorn and Mehrzad Soltani Nia prepared the industrial forecast. Miguel Garcia- Cerrutti

179

Assumptions to the Annual Energy Outlook 2001 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

180

Assumptions to the Annual Energy Outlook 2002 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

Note: This page contains sample records for the topic "regional energy 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

Energy Demand Modelling Introduction to the PhD project  

E-Print Network (OSTI)

Energy Demand Modelling Introduction to the PhD project Erika Zvingilaite Risø DTU System Analysis for optimization of energy systems Environmental effects Global externalities cost of CO2 Future scenarios for the Nordic energy systems 2010, 2020, 2030, 2040, 2050 (energy-production, consumption, emissions, net costs

182

Estimating disaggregated price elasticities in industrial energy demand  

Science Conference Proceedings (OSTI)

Econometric energy models are used to evaluate past policy experiences, assess the impact of future policies and forecast energy demand. This paper estimates an industrial energy demand model for the province of Ontario using a linear-logit specification for fuel type equations which are embedded in an aggregate energy demand equation. Short-term, long-term, own- and cross-price elasticities are estimated for electricity, natural gas, oil and coal. Own- and cross-price elasticities are disaggregated to show that overall price elasticities and the energy-constant price elasticities when aggregate energy use is held unchanged. These disaggregations suggest that a substantial part of energy conservation comes from the higher aggregate price of energy and not from interfuel substitution. 13 refs., 2 tabs.

Elkhafif, M.A.T. (Ontario Ministry of Energy, Toronto (Canada))

1992-01-01T23:59:59.000Z

183

U.S. Regional Demand Forecasts Using NEMS and GIS  

E-Print Network (OSTI)

Administration. 2004c. "Energy Glossary Website."http://www.eia.doe.gov/glossary/. Energy InformationGIS Appendix G. Glossary AEO : The Annual Energy Outlook,

Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

2005-01-01T23:59:59.000Z

184

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

E-Print Network (OSTI)

L ABORATORY Japans Residential Energy Demand Outlook tol i f o r n i a Japans Residential Energy Demand Outlook toParticularly in Japans residential sector, where energy

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

185

Estimating Demand Response Market Potential | Open Energy Information  

Open Energy Info (EERE)

Estimating Demand Response Market Potential Estimating Demand Response Market Potential Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Estimating Demand Response Market Potential Focus Area: Energy Efficiency, - Utility Topics: Socio-Economic Website: www.ieadsm.org/Files/Tasks/Task%20XIII%20-%20Demand%20Response%20Resou Equivalent URI: cleanenergysolutions.org/content/estimating-demand-response-market-pot Language: English Policies: "Deployment Programs,Regulations" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Demonstration & Implementation Regulations: Resource Integration Planning This resource presents demand response (DR) potential results from top-performing programs in the United States and Canada, as well as a DR

186

Assumptions to the Annual Energy Outlook - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumption to the Annual Energy Outlook Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions (see Figure 5). The Residential Demand Module also requires projections of available equipment and their installed costs over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

187

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

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2009 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 use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions (see Figure 5). The Residential Demand Module also requires projections of available equipment and their installed costs over the projection horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the projection horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

188

Assumptions to the Annual Energy Outlook 2002 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

189

Assumptions to the Annual Energy Outlook 2001 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

190

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

Gasoline and Diesel Fuel Update (EIA)

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

191

Assumptions to the Annual Energy Outlook - Transportation Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

192

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

Gasoline and Diesel Fuel Update (EIA)

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

193

Industrial Demand Module 1999, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. Crawford Honeycutt

1999-01-01T23:59:59.000Z

194

Industrial Demand Module 2005, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. C. Honeycutt

2005-05-01T23:59:59.000Z

195

Industrial Demand Module 2006, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. C. Honeycutt

2006-07-01T23:59:59.000Z

196

Industrial Demand Module 2009, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. C. Honeycutt

2009-05-20T23:59:59.000Z

197

Industrial Demand Module 2003, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2003-12-01T23:59:59.000Z

198

Industrial Demand Module 2007, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. C. Honeycutt

2007-03-21T23:59:59.000Z

199

Industrial Demand Module 2002, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2001-12-01T23:59:59.000Z

200

Industrial Demand Module 2001, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2000-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "regional energy 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

Industrial Demand Module 2008, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. C. Honeycutt

2008-06-01T23:59:59.000Z

202

Industrial Demand Module 2000, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2000-01-01T23:59:59.000Z

203

Industrial Demand Module 2004, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2004-02-01T23:59:59.000Z

204

Hydrogen Demand and Resource Assessment Tool | Open Energy Information  

Open Energy Info (EERE)

Hydrogen Demand and Resource Assessment Tool Hydrogen Demand and Resource Assessment Tool Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Hydrogen Demand and Resource Assessment Tool Agency/Company /Organization: National Renewable Energy Laboratory Sector: Energy Focus Area: Hydrogen, Transportation Topics: Technology characterizations Resource Type: Dataset, Software/modeling tools User Interface: Website Website: maps.nrel.gov/ Web Application Link: maps.nrel.gov/hydra Cost: Free Language: English References: http://maps.nrel.gov/hydra Logo: Hydrogen Demand and Resource Assessment Tool Use HyDRA to view, download, and analyze hydrogen data spatially and dynamically. HyDRA provides access to hydrogen demand, resource, infrastructure, cost, production, and distribution data. A user account is

205

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

event by paying higher real-time prices and still receivingvarying prices (e.g. , real-time prices, CPP) facilitatecorrelated with high prices in the real-time energy market.

Goldman, Charles

2010-01-01T23:59:59.000Z

206

Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California  

E-Print Network (OSTI)

your Power. (2008). "Demand Response Programs." RetrievedS. (2008). Automated Demand Response Results from Multi-Yearusing Open Automated Demand Response, California Energy

Lekov, Alex

2009-01-01T23:59:59.000Z

207

Demand Responsive and Energy Efficient Control Technologies and Strategies in Commercial Buildings  

E-Print Network (OSTI)

Contribution to Peak Demand?..5 3.potential to reduce peak demand in commercial buildingsbuildings contribution to peak demand and the use of energy

Piette, Mary Ann; Kiliccote, Sila

2006-01-01T23:59:59.000Z

208

Advanced Controls and Communications for Demand Response and Energy Efficiency in Commercial Buildings  

E-Print Network (OSTI)

for a large portion of summer peak demand. Research resultspotential to reduce peak demand in commercial buildingsbuildings contribution to peak demand and the use of energy

Kiliccote, Sila; Piette, Mary Ann; Hansen, David

2006-01-01T23:59:59.000Z

209

Swarm intelligence approaches to estimate electricity energy demand in Turkey  

Science Conference Proceedings (OSTI)

This paper proposes two new models based on artificial bee colony (ABC) and particle swarm optimization (PSO) techniques to estimate electricity energy demand in Turkey. ABC and PSO electricity energy estimation models (ABCEE and PSOEE) are developed ... Keywords: Ant colony optimization, Artificial bee colony, Electricity energy estimation, Particle swarm optimization, Swarm intelligence

Mustafa Servet K?Ran; Eren Zceylan; Mesut GNdZ; Turan Paksoy

2012-12-01T23:59:59.000Z

210

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

E-Print Network (OSTI)

OpportunitiesforEnergy EfficiencyandDemandResponseinAgricultural/WaterEnd?UseEnergyEfficiencyProgram. i1 4.0 EnergyEfficiencyandDemandResponse

Olsen, Daniel

2012-01-01T23:59:59.000Z

211

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 and brake, a lathe, a process chiller, and cooling tower pumps and fans] in two industrial plants. Demand factors for heavily loaded air compressors were found to be near 100 %, for lightly loaded centrifugal equipment (lathe, sheet metal shear and brake, and granulator) near 10 %, and for injection-molding machines near 50 %. The measured demand factors differ from those often estimated during energy surveys. Duty factors for some equipment were found to exceed 100 %, showing that some loads were on for longer periods than that indicated by plant personnel. Comparing a detailed summary of equipment rated loads to annual utility bills, when measurements are not available, can prevent over-estimation of the demand and duty factors for a plant. Raw unadjusted estimates of demand factors of 60 % or higher are often made, yet comparisons of rated loads to utility bills show that some equipment demand factors may be 50 % or less. This project tested a simple beacon alerting system, which used a blue strobe light to alert plant personnel when a preset demand limit had been reached. Tests of load shedding verified that the estimated demand savings of 50 kVA were realized (out of a total demand of almost 1200 kVA) when lighting and air conditioning loads were turned off.

Dooley, Edward Scott

2001-01-01T23:59:59.000Z

212

Examination of the Regional Supply and Demand Balance for Renewable...  

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

of Energy (U.S.) DSIRE Database of State Incentives for Renewables and Efficiency EIA Energy Information Administration ERCOT Electric Reliability Council of Texas EPA...

213

Global Energy Demand, Supply, Consequences, Opportunities  

E-Print Network (OSTI)

/Joule Population-Energy Equation Power = N x (GDP/N) x (Watts/GDP) C Emission Rate = Power x (Carbon/J) #12;d HVAC Onsite Power & Heat Natural Ventilation, Indoor Environment Building Materials Appliances Thermal · Building Materials Tenants · Lease space from Developer or Property Manager · Professional firms, retailers

Knowles, David William

214

Load Reduction, Demand Response and Energy Efficient Technologies and Strategies  

SciTech Connect

The Department of Energys (DOEs) Pacific Northwest National Laboratory (PNNL) was tasked by the DOE Office of Electricity (OE) to recommend load reduction and grid integration strategies, and identify additional demand response (energy efficiency/conservation opportunities) and strategies at the Forest City Housing (FCH) redevelopment at Pearl Harbor and the Marine Corps Base Hawaii (MCBH) at Kaneohe Bay. The goal was to provide FCH staff a path forward to manage their electricity load and thus reduce costs at these FCH family housing developments. The initial focus of the work was at the MCBH given the MCBH has a demand-ratchet tariff, relatively high demand (~18 MW) and a commensurate high blended electricity rate (26 cents/kWh). The peak demand for MCBH occurs in July-August. And, on average, family housing at MCBH contributes ~36% to the MCBH total energy consumption. Thus, a significant load reduction in family housing can have a considerable impact on the overall site load. Based on a site visit to the MCBH and meetings with MCBH installation, FCH, and Hawaiian Electric Company (HECO) staff, recommended actions (including a "smart grid" recommendation) that can be undertaken by FCH to manage and reduce peak-demand in family housing are made. Recommendations are also made to reduce overall energy consumption, and thus reduce demand in FCH family housing.

Boyd, Paul A.; Parker, Graham B.; Hatley, Darrel D.

2008-11-19T23:59:59.000Z

215

Examination of the Regional Supply and Demand Balance for Renewable Electricity in the United States through 2015: Projecting from 2009 through 2015 (Revised)  

SciTech Connect

This report examines the balance between the demand and supply of new renewable electricity in the United States on a regional basis through 2015. It expands on a 2007 NREL study that assessed the supply and demand balance on a national basis. As with the earlier study, this analysis relies on estimates of renewable energy supplies compared to demand for renewable energy generation needed to meet existing state renewable portfolio standard (RPS) policies in 28 states, as well as demand by consumers who voluntarily purchase renewable energy. However, it does not address demand by utilities that may procure cost-effective renewables through an integrated resource planning process or otherwise.

Bird, L.; Hurlbut, D.; Donohoo, P.; Cory, K.; Kreycik, C.

2010-06-01T23:59:59.000Z

216

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)"

217

"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"

218

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"

219

Assessment of Achievable Potential from Energy Efficiency and Demand  

Open Energy Info (EERE)

Assessment of Achievable Potential from Energy Efficiency and Demand Assessment of Achievable Potential from Energy Efficiency and Demand Response Programs in the United States (U.S.) (2010-2030) Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Assessment of Achievable Potential from Energy Efficiency and Demand Response Programs in the United States (U.S.) (2010-2030) Focus Area: Energy Efficiency, - Utility Topics: Policy Impacts Website: www.edisonfoundation.net/IEE/Documents/EPRI_AssessmentAchievableEEPote Equivalent URI: cleanenergysolutions.org/content/assessment-achievable-potential-energ Language: English Policies: Regulations Regulations: Mandates/Targets This report discusses the 2008 U.S. Energy Information Administration statistic that electricity consumption in the United States is predicted to

220

The National Energy Modeling System: An Overview 1998 - Residential Demand  

Gasoline and Diesel Fuel Update (EIA)

RESIDENTIAL DEMAND MODULE RESIDENTIAL DEMAND MODULE blueball.gif (205 bytes) Housing Stock Submodule blueball.gif (205 bytes) Appliance Stock Submodule blueball.gif (205 bytes) Technology Choice Submodule blueball.gif (205 bytes) Shell Integrity Submodule blueball.gif (205 bytes) Fuel Consumption Submodule The residential demand module (RDM) forecasts energy consumption by Census division for seven marketed energy sources plus solar thermal and geothermal energy. The RDM is a structural model and its forecasts are built up from projections of the residential housing stock and of the energy-consuming equipment contained therein. The components of the RDM and its interactions with the NEMS system are shown in Figure 5. NEMS provides forecasts of residential energy prices, population, and housing starts,

Note: This page contains sample records for the topic "regional energy 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

The Economics of Energy (and Electricity) Demand  

E-Print Network (OSTI)

% electrical efficiency might be able to deliver electrical heat using half the gas of gas fired boiler with 90% efficiency (p.152-153). An electric car uses around 15 kWh per 100 km, around 5 times less than the average fossil fuel car. This implies... that there is always a wide-range of observed efficiencies in the economy, with the average efficiency of the provision of an energy service being significantly less than the efficiency of the most efficient. Current new fossil fuel cars and gas boilers are 50...

Platchkov, Laura M.; Pollitt, Michael G.

222

Tankless or Demand-Type Water Heaters | Department of Energy  

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

Tankless or Demand-Type Water Heaters Tankless or Demand-Type Water Heaters Tankless or Demand-Type Water Heaters May 2, 2012 - 6:47pm Addthis Diagram of a tankless water heater. Diagram of a tankless water heater. How does it work? Tankless water heaters deliver hot water as it is needed, eliminating the need for storage tanks. Tankless water heaters, also known as demand-type or instantaneous water heaters, provide hot water only as it is needed. They don't produce the standby energy losses associated with storage water heaters, which can save you money. Here you'll find basic information about how they work, whether a tankless water heater might be right for your home, and what criteria to use when selecting the right model. Check out the Energy Saver 101: Water Heating infographic to learn if a tankless water heater is right for you.

223

EIA - International Energy Outlook 2009-World Energy Demand and Economic  

Gasoline and Diesel Fuel Update (EIA)

Liquid Fuels Liquid Fuels International Energy Outlook 2009 Chapter 2 - Liquid Fuels World liquids consumption in the IEO2009 reference case increases from 85 million barrels per day in 2006 to 107 million barrels per day in 2030. Unconventional liquids, at 13.4 million barrels per day, make up 12.6 percent of total liquids production in 2030. Figure 25. World Liquids Consumption by Region and Country Group, 2006 and 2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 26. World Liquids Supply in Three Cases, 2006 and 2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 27. World Production of Unconventional Liquid Fuels, 2006-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800.

224

EIA - Annual Energy Outlook 2008 - Natural Gas Demand  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Demand Natural Gas Demand Annual Energy Outlook 2008 with Projections to 2030 Natural Gas Demand Figure 72. Natural gas consumption by sector, 1990-2030 (trillion cubic feet). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 73. Total natural gas consumption, 1990-2030 (trillion cubic feet). Need help, contact the National Energy Information Center at 202-586-8800. figure data Fastest Increase in Natural Gas Use Is Expected for the Buildings Sectors In the reference case, total natural gas consumption increases from 21.7 trillion cubic feet in 2006 to a peak value of 23.8 trillion cubic feet in 2016, followed by a decline to 22.7 trillion cubic feet in 2030. The natural gas share of total energy consumption drops from 22 percent in 2006

225

Impact of selected energy conservation technologies on baseline demands  

SciTech Connect

This study is an application of the modeling and demand projection capability existing at Brookhaven National Laboratory to specific options in energy conservation. Baseline energy demands are modified by introducing successively three sets of conservation options. The implementation of improved building standards and the use of co-generation in industry are analyzed in detail and constitute the body of this report. Two further sets of energy demands are presented that complete the view of a low energy use, ''conservation'' scenario. An introduction to the report covers the complexities in evaluating ''conservation'' in view of the ways it is inextricably linked to technology, prices, policy, and the mix of output in the economy. The term as used in this report is narrowly defined, and methodologies are suggested by which these other aspects listed can be studied in the future.

Doernberg, A

1977-09-01T23:59:59.000Z

226

Energy Conservation and Commercialization in Gujarat: Report On Demand Side  

Open Energy Info (EERE)

Energy Conservation and Commercialization in Gujarat: Report On Demand Side Energy Conservation and Commercialization in Gujarat: Report On Demand Side Management (DSM) In Gujarat Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Energy Conservation and Commercialization in Gujarat: Report On Demand Side Management (DSM) In Gujarat Focus Area: Crosscutting Topics: Opportunity Assessment & Screening Website: eco3.org/wp-content/plugins/downloads-manager/upload/Report%20on%20Dem Equivalent URI: cleanenergysolutions.org/content/energy-conservation-and-commercializa Language: English Policies: "Deployment Programs,Financial Incentives,Regulations" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Technical Assistance Regulations: Resource Integration Planning

227

United States energy supply and demand forecasts 1979-1995  

SciTech Connect

Forecasts of U.S. energy supply and demand by fuel type and economic sector, as well as historical background information, are presented. Discussion and results pertaining to the development of current and projected marginal energy costs, and their comparison with market prices, are also presented.

Walton, H.L.

1979-01-01T23:59:59.000Z

228

Linking Continuous Energy Management and Open Automated Demand Response  

Science Conference Proceedings (OSTI)

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

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

2008-10-03T23:59:59.000Z

229

Retail Demand Response in Southwest Power Pool | Department of Energy  

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

Demand Response in Southwest Power Pool Demand Response in Southwest Power Pool Retail Demand Response in Southwest Power Pool In 2007, the Southwest Power Pool (SPP) formed the Customer Response Task Force (CRTF) to identify barriers to deploying demand response (DR) resources in wholesale markets and develop policies to overcome these barriers. One of the initiatives of this Task Force was to develop more detailed information on existing retail DR programs and dynamic pricing tariffs, program rules, and utility operating practices. This report describes the results of a comprehensive survey conducted by LBNL in support of the Customer Response Task Force and discusses policy implications for integrating legacy retail DR programs and dynamic pricing tariffs into wholesale markets in the SPP region.

230

Opportunities for Energy Efficiency and Demand Response in the California  

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

Opportunities for Energy Efficiency and Demand Response in the California Opportunities for Energy Efficiency and Demand Response in the California Cement Industry Title Opportunities for Energy Efficiency and Demand Response in the California Cement Industry Publication Type Report LBNL Report Number LBNL-4849E Year of Publication 2010 Authors Olsen, Daniel, Sasank Goli, David Faulkner, and Aimee T. McKane Date Published 12/2010 Publisher CEC/LBNL Keywords cement industry, cement sector, demand response, electricity use, energy efficiency, market sectors, mineral manufacturing, technologies Abstract This study examines the characteristics of cement plants and their ability to shed or shift load to participate in demand response (DR). Relevant factors investigated include the various equipment and processes used to make cement, the operational limitations cement plants are subject to, and the quantities and sources of energy used in the cement-making process. Opportunities for energy efficiency improvements are also reviewed. The results suggest that cement plants are good candidates for DR participation. The cement industry consumes over 400 trillion Btu of energy annually in the United States, and consumes over 150 MW of electricity in California alone. The chemical reactions required to make cement occur only in the cement kiln, and intermediate products are routinely stored between processing stages without negative effects. Cement plants also operate continuously for months at a time between shutdowns, allowing flexibility in operational scheduling. In addition, several examples of cement plants altering their electricity consumption based on utility incentives are discussed. Further study is needed to determine the practical potential for automated demand response (Auto-DR) and to investigate the magnitude and shape of achievable sheds and shifts.

231

Assumptions to the Annual Energy Outlook 2001 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

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

232

ADB-Methods and Tools for Energy Demand Projection | Open Energy  

Open Energy Info (EERE)

ADB-Methods and Tools for Energy Demand Projection ADB-Methods and Tools for Energy Demand Projection Jump to: navigation, search Tool Summary Name: Methods and Tools for Energy Demand Projection Agency/Company /Organization: Asian Development Bank Sector: Energy Topics: Pathways analysis Resource Type: Presentation, Software/modeling tools Website: cdm-mongolia.com/files/2_Methods_Hoseok_16May2010.pdf Cost: Free Methods and Tools for Energy Demand Projection Screenshot References: Methods and Tools for Energy Demand Projection[1] This article is a stub. You can help OpenEI by expanding it. References ↑ "Methods and Tools for Energy Demand Projection" Retrieved from "http://en.openei.org/w/index.php?title=ADB-Methods_and_Tools_for_Energy_Demand_Projection&oldid=398945" Categories:

233

A dynamic model of industrial energy demand in Kenya  

Science Conference Proceedings (OSTI)

This paper analyses the effects of input price movements, technology changes, capacity utilization and dynamic mechanisms on energy demand structures in the Kenyan industry. This is done with the help of a variant of the second generation dynamic factor demand (econometric) model. This interrelated disequilibrium dynamic input demand econometric model is based on a long-term cost function representing production function possibilities and takes into account the asymmetry between variable inputs (electricity, other-fuels and Tabour) and quasi-fixed input (capital) by imposing restrictions on the adjustment process. Variations in capacity utilization and slow substitution process invoked by the relative input price movement justifies the nature of input demand disequilibrium. The model is estimated on two ISIS digit Kenyan industry time series data (1961 - 1988) using the Iterative Zellner generalized least square method. 31 refs., 8 tabs.

Haji, S.H.H. [Gothenburg Univ. (Sweden)

1994-12-31T23:59:59.000Z

234

Energy demand and indoor climate of a traditional low-energy building in a hot climate.  

E-Print Network (OSTI)

?? Energy demand in the built environment is quite important. China holds a large population and the energy use in the building sector is about (more)

Li, Ang

2009-01-01T23:59:59.000Z

235

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

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

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

236

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

237

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

Gasoline and Diesel Fuel Update (EIA)

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

238

Assumptions to the Annual Energy Outlook - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumption to the Annual Energy Outlook Industrial Demand Module Table 17. Industry Categories Printer Friendly Version Energy-Intensive Manufacturing Nonenergy-Intensive Manufacturing Nonmanufacturing Industries Food and Kindred Products (NAICS 311) Metals-Based Durables (NAICS 332-336) Agricultural Production -Crops (NAICS 111) Paper and Allied Products (NAICS 322) Balance of Manufacturing (all remaining manufacturing NAICS) Other Agriculture Including Livestock (NAICS112- 115) Bulk Chemicals (NAICS 32B) Coal Mining (NAICS 2121) Glass and Glass Products (NAICS 3272) Oil and Gas Extraction (NAICS 211) Hydraulic Cement (NAICS 32731) Metal and Other Nonmetallic Mining (NAICS 2122- 2123) Blast Furnaces and Basic Steel (NAICS 331111) Construction (NAICS233-235)

239

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

Gasoline and Diesel Fuel Update (EIA)

industrial demand module (IDM) forecasts energy consumption for fuels and feedstocks for nine manufacturing industries and six nonmanufactur- ing industries, subject to delivered prices of energy and macroeconomic variables representing the value of output for each industry. The module includes industrial cogeneration of electricity that is either used in the industrial sector or sold to the electricity grid. The IDM structure is shown in Figure 7. industrial demand module (IDM) forecasts energy consumption for fuels and feedstocks for nine manufacturing industries and six nonmanufactur- ing industries, subject to delivered prices of energy and macroeconomic variables representing the value of output for each industry. The module includes industrial cogeneration of electricity that is either used in the industrial sector or sold to the electricity grid. The IDM structure is shown in Figure 7. Figure 7. Industrial Demand Module Structure Industrial energy demand is projected as a combination of “bottom up” characterizations of the energy-using technology and “top down” econometric estimates of behavior. The influence of energy prices on industrial energy consumption is modeled in terms of the efficiency of use of existing capital, the efficiency of new capital acquisitions, and the mix of fuels utilized, given existing capital stocks. Energy conservation from technological change is represented over time by trend-based “technology possibility curves.” These curves represent the aggregate efficiency of all new technologies that are likely to penetrate the future markets as well as the aggregate improvement in efficiency of 1994 technology.

240

U.S. Energy Demand, Offshore Oil Production and  

E-Print Network (OSTI)

;Summary of Conclusions. . . The global rate of production of oil is peaking now, coal will peak in 2U.S. Energy Demand, Offshore Oil Production and BP's Macondo Well Spill Tad Patzek, Petroleum that run the U.S. Complexity, models, risks Gulf of Mexico's oil and gas production Conclusions ­ p.3/4 #12

Patzek, Tadeusz W.

Note: This page contains sample records for the topic "regional energy 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

Assumptions to the Annual Energy Outlook 2001 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

242

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

rate California electricity consumption (GWh) Over two-thirds of total electricity demand is concentrated in the residential andrate N/A PG&E SMUD SCE LADWP SDGE BGP Other All CA 2005 IEPR Residential electricity

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

2008-01-01T23:59:59.000Z

243

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

forecast methods report. California Energy Commission, CEC-Chris Kavalec. California Energy Commission. CEC (2005d)Office, 5/12/2006. California Energy Advanced Energy

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

2008-01-01T23:59:59.000Z

244

Assumptions to the Annual Energy Outlook 2000 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions. The Residential Demand Module also requires projections of available equipment over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

245

Assumptions to the Annual Energy Outlook 1999 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

residential.gif (5487 bytes) residential.gif (5487 bytes) The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions. The Residential Demand Module also requires projections of available equipment over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

246

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

247

Construction of a Demand Side Plant with Thermal Energy Storage  

E-Print Network (OSTI)

Utility managements have two primary responsibilities. They must supply reliable electric service to meet the needs of their customers at the most efficient price possible while at the same time generating the maximum rate of return possible for their shareholders. Regulator hostility towards the addition of generating capacity has made it difficult for utilities to simultaneously satisfy both the needs of their ratepayers and the needs of their shareholders. Recent advances in thermal energy storage may solve the utilities' paradox. Residential thermal energy storage promises to provide the ratepayers significantly lower electricity rates and greater comfort levels. Utilities benefit from improved load factors, peak capacity additions at low cost, improved shareholder value (ie. a better return on assets), improved reliability, and a means of satisfying growing demand without the regulatory and litigious nightmares associated with current supply side solutions. This paper discusses thermal energy storage and its potential impact on the electric utilities and introduces the demand side plant concept.

Michel, M.

1989-01-01T23:59:59.000Z

248

Regionalized Global Energy Scenarios Meeting Stringent Climate Targets  

E-Print Network (OSTI)

to generate the energy supply mix that would meet given energy demands at lowest cost, assuming strongRegionalized Global Energy Scenarios Meeting Stringent Climate Targets ­ cost effective fuel in the energy system it is less costly to reduce CO2-emissions #12;Global energy system model #12;Global energy

249

Building Energy Software Tools Directory: Energy Demand Modeling  

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

and Renewable Energy EERE Home | Programs & Offices | Consumer Information Building Energy Software Tools Directory Search Search Help Building Energy Software Tools Directory...

250

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network (OSTI)

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

Piette, Mary Ann

2009-01-01T23:59:59.000Z

251

U.S. Propane Demand - Energy Information Administration  

U.S. Energy Information Administration (EIA)

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

252

STRATEGIC ENERGY INITIATIVE @ Winter 2005 Precarious energy situation demands strategic  

E-Print Network (OSTI)

energy solutions that could have a significant impact, especially in the southeastern U.S. Blowin of the oil it produced in 1970. -- Georgia Tech Strategic Energy Initiative and U.S. Dept. of Energy's Energy energy. At the U.S.Department of Energy-funded SolarThermal Test Facility on the main campus, Georgia

Sherrill, David

253

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

the entire forecast period, primarily because both weather-adjusted peak and electricity consumption were forecast. Keywords Electricity demand, electricity consumption, demand forecast, weather normalization, annual peak demand, natural gas demand, self-generation, conservation, California Solar Initiative. #12

254

Integrating Energy Efficiency and Demand Response into Utility Resource Plans  

Science Conference Proceedings (OSTI)

This report investigates the methods in which utilities integrate their supply-side and demand-side resources to meet their generating resource requirements. The major steps in developing a resource plan are reviewed, including the alternative methods currently employed. Finally, the report presents the results of a short survey that was administered to the advisors in Energy Utilization. The results show that methods are more sophisticated than 20 years ago, but more could be accomplished in ...

2013-01-14T23:59:59.000Z

255

Assumptions to the Annual Energy Outlook 2000 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

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

256

Experts Meeting: Behavioral Economics as Applied to Energy Demand Analysis and Energy Efficiency Programs  

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

Experts Meeting: Behavioral Economics Experts Meeting: Behavioral Economics as Applied to Energy Demand Analysis and Energy Efficiency Programs EIA Office of Energy Consumption and Efficiency Analysis July 17, 2013 | Washington, DC Meeting Agenda Jim Turnure, Director, Office of Energy Consumption and Efficiency Analysis July 17, 2013 2 * EIA WELCOME AND INTRODUCTION (15 minutes) * ORIENTATION/PRESENTATION: OVERVIEW OF EIA RESIDENTIAL AND COMMERCIAL DEMAND MODELS AND CURRENT METHODS FOR INCORPORATING ENERGY EFFICIENCY/EFFICIENCY PROGRAMS (30 minutes) * ORIENTATION/PRESENTATION: BEHAVIORAL ECONOMICS GENERAL OVERVIEW AND DISCUSSION (45 minutes) * EXPERTS ROUNDTABLE DISCUSSION/BRAINSTROMING: HOW CAN EIA BENEFIT FROM APPLICATION OF BEHAVIORAL ECONOMICS TO RESIDENTIAL AND COMMERCIAL ENERGY DEMAND MODELING?

257

Best Practices: Energy Savings Efficient energy use reduces Colorado State's total energy demand, decreases harmful  

E-Print Network (OSTI)

square foot on campus has flattened out. Students making a difference In 2004, Colorado State became one, decreases harmful emissions, and minimizes the cost of providing energy to the campus. As a result of energy conservation initiatives that have been implemented over the past 20 years, growth in the average demand per

258

Regional Energy Activity | Department of Energy  

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

in every region of the world. Important issue areas include regional and country-specific energy policies and practices, technology developments, market conditions, and trade and...

259

Fuel choice and aggregate energy demand in the commercial sector  

SciTech Connect

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

Cohn, S.

1978-12-01T23:59:59.000Z

260

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

E-Print Network (OSTI)

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

Letschert, Virginie

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "regional energy 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

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

262

The Baltics: Regional energy profiles  

SciTech Connect

However, all three Baltic Republics are heavily dependent on primary energy imports. Domestic energy sources in the Baltics are limited to oil shale mines in Estonia, small oil deposits in Lithuania, peat, and some very small hydroelectric power plants. A RBMK nuclear power station, similar to Chernobyl, operates at Snieckus in Lithuania, but the reactor fuel is also imported from Russia. However, Lithuania and Estonia are net exporters of electricity despite their reliance on primary fuels imports. The major power stations in these two Republics are the Ignalina Nuclear Power Station and the two thermal power plants at Narva in Estonia which are fueled by oil shale. The only oil refinery in the Baltics is also located in Lithuania, at Mazeikiai. This refinery has the capacity to satisfy the demand for selected refined products of the entire region, including the Kaliningrad oblast, a noncontiguous part of Russia. The Mazeikiai refinery has operated at only forty to sixty percent capacity since 1990 due to halts in crude oil supplies from Russia. The Baltic Republics also import one hundred percent of their coal and natural gas supplies. Russia is the main trading partner for all the Baltic states, accounting for more than half of their trade flow. Mutual trade within the Baltics has been surprisingly low. Other Baltic states contribute less than ten percent to each Republic`s exports or imports, even less than Belarus or Ukraine. Aside from Russia, Ukraine, and Belarus, only Kazakhstan contributes more than two percent to Baltics trade.

Not Available

1993-01-01T23:59:59.000Z

263

The Baltics: Regional energy profiles  

Science Conference Proceedings (OSTI)

However, all three Baltic Republics are heavily dependent on primary energy imports. Domestic energy sources in the Baltics are limited to oil shale mines in Estonia, small oil deposits in Lithuania, peat, and some very small hydroelectric power plants. A RBMK nuclear power station, similar to Chernobyl, operates at Snieckus in Lithuania, but the reactor fuel is also imported from Russia. However, Lithuania and Estonia are net exporters of electricity despite their reliance on primary fuels imports. The major power stations in these two Republics are the Ignalina Nuclear Power Station and the two thermal power plants at Narva in Estonia which are fueled by oil shale. The only oil refinery in the Baltics is also located in Lithuania, at Mazeikiai. This refinery has the capacity to satisfy the demand for selected refined products of the entire region, including the Kaliningrad oblast, a noncontiguous part of Russia. The Mazeikiai refinery has operated at only forty to sixty percent capacity since 1990 due to halts in crude oil supplies from Russia. The Baltic Republics also import one hundred percent of their coal and natural gas supplies. Russia is the main trading partner for all the Baltic states, accounting for more than half of their trade flow. Mutual trade within the Baltics has been surprisingly low. Other Baltic states contribute less than ten percent to each Republic's exports or imports, even less than Belarus or Ukraine. Aside from Russia, Ukraine, and Belarus, only Kazakhstan contributes more than two percent to Baltics trade.

Not Available

1993-01-01T23:59:59.000Z

264

Energy packet networks: smart electricity storage to meet surges in demand  

Science Conference Proceedings (OSTI)

When renewable energy is used either as a primary source, or as a back-up source to meet excess demand, energy storage becomes very useful. Simple examples of energy storage units include electric car batteries and uninterruptible power supplies. More ... Keywords: energy packet networks, network control of energy flow, on-demand energy dispatching, smart grid, store and forward energy, storing renewable energy

Erol Gelenbe

2012-03-01T23:59:59.000Z

265

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

Science Conference Proceedings (OSTI)

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

266

Advanced Control Technologies and Strategies Linking Demand Response and Energy Efficiency  

E-Print Network (OSTI)

demand shifting are thermal energy storage systems, whichlockout, pre-cooling, thermal energy storage, cooling loadlockout Pre-cooling Thermal energy storage Cooling

Kiliccote, Sila; Piette, Mary Ann

2005-01-01T23:59:59.000Z

267

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network (OSTI)

Solution Procedure for SDP Energy Prices We use electricityLondon for assistance with energy price modeling. Siddiquiof DER under uncertain energy prices with demand response

Siddiqui, Afzal

2010-01-01T23:59:59.000Z

268

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network (OSTI)

minimization Monthly peak demand management Daily time-of-Some tariff designs have peak demand charges that apply tothat may result in a peak demand that occurs in one month to

Piette, Mary Ann

2009-01-01T23:59:59.000Z

269

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

Dryer WH - Clothes Washer Clothes Washer WH - DishwasherDishwasher Water Heating Figure 7 Breakdown of residentialUEC Water Heating (WH) Dishwasher Advanced Energy Pathways -

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

2008-01-01T23:59:59.000Z

270

EIA - 2010 International Energy Outlook - World Energy Demand...  

Gasoline and Diesel Fuel Update (EIA)

about energy security and greenhouse gas emissions support the development of new nuclear generating capacity. World average capacity utilization rates have continued to rise...

271

Assumptions to the Annual Energy Outlook 1999 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

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

272

Industrial Demand Module 1998, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description ofthe NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in supportof its models (Public Law 94-385, section 57.b2). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

T. Crawford Honeycutt

1998-01-01T23:59:59.000Z

273

Forecasts of intercity passenger demand and energy use through 2000  

SciTech Connect

The development of national travel demand and energy-use forecasts for automobile and common-carrier intercity travel through the year 2000. The forecasts are driven by the POINTS (Passenger Oriented Intercity Network Travel Simulation) model, a model direct-demand model which accounts for competition among modes and destinations. Developed and used to model SMSA-to-SMSA business and nonbusiness travel, POINTS is an improvement over earlier direct demand models because it includes an explicit representation of cities' relative accessibilities and a utility maximizing behavorial multimodal travel function. Within POINTS, pathbuilding algorithms are used to determine city-pair travel times and costs by mode, including intramodal transfer times. Other input data include projections of SMSA population, public and private sector employment, and hotel and other retail receipts. Outputs include forecasts of SMSA-to-SMSA person trips and person-miles of travel by mode. For the national forecasts, these are expanded to represent all intercity travel (trips greater than 100 miles, one way) for two fuel-price cases. Under both cases rising fuel prices, accompanied by substantial reductions in model-energy intensities, result in moderate growth in total intercity passenger travel. Total intercity passenger travel is predicted to grow at approximately one percent per year, slightly fster than population growth, while air travel grows almost twice as fast as population. The net effect of moderate travel growth and substantial reduction in model energy intensities is a reduction of approximately 50 percent in fuel consumption by the intercity passenger travel market.

Kaplan, M.P.; Vyas, A.D.; Millar, M.; Gur, Y.

1982-01-01T23:59:59.000Z

274

ENERGY DEMAND AND CONSERVATION IN KENYA: INITIAL APPRAISAL  

E-Print Network (OSTI)

of Statistics d) Nairobi, Kenya. See also Estimates ofDEMAND AND CONSERVATION IN KENYA: INITIAL APPRAISAL LeeDemand and Conservation in Kenya: Initial Appraisal Lee

Schipper, Lee

2013-01-01T23:59:59.000Z

275

Electric grid planners: demand response and energy efficiency to ...  

U.S. Energy Information Administration (EIA)

Source: Form EIA-411, Coordinated Bulk Power Demand and Supply Report Note: All data are reported for time of summer peak, rather than overall demand.

276

Energy Use in the Australian Manufacturing Industry: An Analysis of Energy Demand Elasticity  

E-Print Network (OSTI)

Energy Use in the Australian Manufacturing Industry: An Analysis of Energy Demand Elasticity Chris in this paper. Energy consumption data was sourced from the Bureau of Resources and Energy Economics' Australian Energy Statistics publication. Price and income data were sourced from the Australian Bureau

277

Projecting household energy consumption within a conditional demand framework  

SciTech Connect

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Teotia, A.; Poyer, D.

1991-01-01T23:59:59.000Z

278

Projecting household energy consumption within a conditional demand framework  

Science Conference Proceedings (OSTI)

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Teotia, A.; Poyer, D.

1991-12-31T23:59:59.000Z

279

A critical review of single fuel and interfuel substitution residential energy demand models  

E-Print Network (OSTI)

The overall purpose of this paper is to formulate a model of residential energy demand that adequately analyzes all aspects of residential consumer energy demand behavior and properly treats the penetration of new technologies, ...

Hartman, Raymond Steve

1978-01-01T23:59:59.000Z

280

Japan's Long-term Energy Demand and Supply Scenario to 2050 ...  

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

Long-term Energy Demand and Supply Scenario to 2050 - Estimation for the Potential of Massive CO2 Mitigation Title Japan's Long-term Energy Demand and Supply Scenario to 2050 -...

Note: This page contains sample records for the topic "regional energy 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

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST  

E-Print Network (OSTI)

Policy Report, over the entire forecast period, primarily because both weather-adjusted peak and commercial sectors. Keywords Electricity demand, electricity consumption, demand forecast, weather normalization, annual peak demand, natural gas demand, self-generation, California Solar Initiative. #12;ii #12

282

Dynamic Controls for Energy Efficiency and Demand Response: Framework Concepts and a New Construction Study Case in New York  

E-Print Network (OSTI)

of Fully Automated Demand Response in Large Facilities.for Energy Efficiency and Demand Response, Proceedings ofAuthority (NYSERDA), the Demand Response Research Center (

Kiliccote, Sila; Piette, Mary Ann; Watson, David S.; Hughes, Glenn

2006-01-01T23:59:59.000Z

283

Worldwide transportation/energy demand, 1975-2000. Revised Variflex model projections  

SciTech Connect

The salient features of the transportation-energy relationships that characterize the world of 1975 are reviewed, and worldwide (34 countries) long-range transportation demand by mode to the year 2000 is reviewed. A worldwide model is used to estimate future energy demand for transportation. Projections made by the forecasting model indicate that in the year 2000, every region will be more dependent on petroleum for the transportation sector than it was in 1975. This report is intended to highlight certain trends and to suggest areas for further investigation. Forecast methodology and model output are described in detail in the appendices. The report is one of a series addressing transportation energy consumption; it supplants and replaces an earlier version published in October 1978 (ORNL/Sub-78/13536/1).

Ayres, R.U.; Ayres, L.W.

1980-03-01T23:59:59.000Z

284

Advanced Control Technologies and Strategies Linking Demand Response and Energy Efficiency  

E-Print Network (OSTI)

Electrical Peak Demands in Commercial Buildings Center for Analysis and Dissemination of Demonstrated Energy Technologies (CADDET), IEA/OECD Analyses

Kiliccote, Sila; Piette, Mary Ann

2005-01-01T23:59:59.000Z

285

Comfort-aware home energy management under market-based demand-response  

Science Conference Proceedings (OSTI)

To regulate energy consumption and enable Demand-Response programs, effective demand-side management at home is key and an integral part of the future Smart Grid. In essence, the home energy management is a mix between discrete appliance scheduling problem ... Keywords: demand-response, energy management, smart grid

Jin Xiao, Jian Li, Raouf Boutaba, James Won-Ki Hong

2012-10-01T23:59:59.000Z

286

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

SciTech Connect

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

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

2008-05-15T23:59:59.000Z

287

GRI baseline projection: Regional energy summary, 1991 edition. Topical report  

SciTech Connect

Results of the 1991 Edition of the GRI Baseline Projection for each of the eleven regions used in the Gas Research Institute (GRI) version of the DRI energy model are summarized. The 1991 edition of the projection is an internally consistent forecast of United States energy markets produced using results from GRI's Hydrocarbon Model in conjunction with the DRI Macroeconomic Model and the GRI/DRI Energy Model. The report discusses only those energy market concepts which are forecast on a regional basis in the Energy Model. Unless otherwise noted, all prices are reported in 1990 constant dollars. Transportation energy demand is not treated on a regional basis in the GRI/DRI Energy Model. For the purposes of the report, transportation energy demand was shared out to each region based on population.

Blanford, K.M.; McDonald, S.C.

1991-01-01T23:59:59.000Z

288

Model for Analysis of Energy Demand (MAED-2) | Open Energy Information  

Open Energy Info (EERE)

Website http:www-pub.iaea.orgMTCDp References MAED 21 "MAED model evaluates future energy demand based on medium- to long-term scenarios of socio-economic,...

289

Chapter 3: Demand-Side Resources | Department of Energy  

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

spent 14.7 billion on DSM programs between 1989 and 1999, an average of 1.3 billion per year. Chapter 3: Demand-Side Resources More Documents & Publications Chapter 3 Demand-Side...

290

Residual Fuel Demand - U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

In the 1986 to 1991 period, residual fuel oil demand declined only slightly both in absolute and as a percent of total product demand. While not shown, residual fuel ...

291

Regional Energy Profile Forum on Energy Preparedness  

Gasoline and Diesel Fuel Update (EIA)

Regional Energy Profile West Texas Intermediate Crude Oil Prices U.S. Crude Oil Inventory Outlook U.S. Distillate Inventory Outlook Distillate Stocks Low - Especially On East...

292

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

SciTech Connect

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

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

1984-10-01T23:59:59.000Z

293

Lake Region Electric Cooperative - Residential Energy Efficiency...  

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

Region Electric Cooperative - Residential Energy Efficiency Rebate Program Lake Region Electric Cooperative - Residential Energy Efficiency Rebate Program Eligibility Residential...

294

Southeast Regional Clean Energy Policy Analysis (Revised)  

SciTech Connect

More than half of the electricity produced in the southeastern states is fuelled by coal. Although the region produces some coal, most of the states depend heavily on coal imports. Many of the region's aging coal power facilities are planned for retirement within the next 20 years. However, estimates indicate that a 20% increase in capacity is needed over that time to meet the rapidly growing demand. The most common incentives for energy efficiency in the Southeast are loans and rebates; however, total public spending on energy efficiency is limited. The most common state-level policies to support renewable energy development are personal and corporate tax incentives and loans. The region produced 1.8% of the electricity from renewable resources other than conventional hydroelectricity in 2009, half of the national average. There is significant potential for development of a biomass market in the region, as well as use of local wind, solar, methane-to-energy, small hydro, and combined heat and power resources. Options are offered for expanding and strengthening state-level policies such as decoupling, integrated resource planning, building codes, net metering, and interconnection standards to support further clean energy development. Benefits would include energy security, job creation, insurance against price fluctuations, increased value of marginal lands, and local and global environmental paybacks.

McLaren, J.

2011-04-01T23:59:59.000Z

295

"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"

296

Optimal Technology Investment and Operation in Zero-Net-Energy Buildings with Demand Response  

E-Print Network (OSTI)

and achieve demand response. For example, on a hot August after- noon during the energy crisis, high demand-in trans- former used for everything from cell phones to computers could be up to 50 percent more efficient

297

Driving change : evaluating strategies to control automotive energy demand growth in China  

E-Print Network (OSTI)

As the number of vehicles in China has relentlessly grown in the past decade, the energy demand, fuel demand and greenhouse gas emissions associated with these vehicles have kept pace. This thesis presents a model to project ...

Bonde kerlind, Ingrid Gudrun

2013-01-01T23:59:59.000Z

298

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network (OSTI)

and Demand Response under Uncertainty F P t : wholesale natural gasdemand response and DER under uncertain electricity and natural gasand Demand Response under Uncertainty Energy Price Models We assume that the logarithms of the deseasonalized electricity and natural gas

Siddiqui, Afzal

2010-01-01T23:59:59.000Z

299

demand response - U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

EIA Survey Forms Facebook Twitter ... demand response June 14, 2012 California's electric power market faces challenges heading into summer. March 24, ...

300

EU-15 Gasoline & Distillate Demand - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

The European refining system is not well matched to its demand slate. Unlike the United States, Europe produces more gasoline than it can use, which ...

Note: This page contains sample records for the topic "regional energy 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

Coal supply/demand, 1980 to 2000. Task 3. Resource applications industrialization system data base. Final review draft. [USA; forecasting 1980 to 2000; sector and regional analysis  

SciTech Connect

This report is a compilation of data and forecasts resulting from an analysis of the coal market and the factors influencing supply and demand. The analyses performed for the forecasts were made on an end-use-sector basis. The sectors analyzed are electric utility, industry demand for steam coal, industry demand for metallurgical coal, residential/commercial, coal demand for synfuel production, and exports. The purpose is to provide coal production and consumption forecasts that can be used to perform detailed, railroad company-specific coal transportation analyses. To make the data applicable for the subsequent transportation analyses, the forecasts have been made for each end-use sector on a regional basis. The supply regions are: Appalachia, East Interior, West Interior and Gulf, Northern Great Plains, and Mountain. The demand regions are the same as the nine Census Bureau regions. Coal production and consumption in the United States are projected to increase dramatically in the next 20 years due to increasing requirements for energy and the unavailability of other sources of energy to supply a substantial portion of this increase. Coal comprises 85 percent of the US recoverable fossil energy reserves and could be mined to supply the increasing energy demands of the US. The NTPSC study found that the additional traffic demands by 1985 may be met by the railways by the way of improved signalization, shorter block sections, centralized traffic control, and other modernization methods without providing for heavy line capacity works. But by 2000 the incremental traffic on some of the major corridors was projected to increase very significantly and is likely to call for special line capacity works involving heavy investment.

Fournier, W.M.; Hasson, V.

1980-10-10T23:59:59.000Z

302

Secretary Bodman Meets with Regional Energy Ministers in Hungary |  

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

Regional Energy Ministers in Hungary Regional Energy Ministers in Hungary Secretary Bodman Meets with Regional Energy Ministers in Hungary March 17, 2006 - 3:44pm Addthis Emphasizes U.S. Support for Central European Energy Security BUDAPEST, HUNGARY - Secretary of Energy Samuel W. Bodman today participated in a regional energy meeting with ministers from Hungary, Czech Republic, Poland, Slovakia, Austria, Croatia and Romania. During the meeting, Secretary Bodman and the ministers discussed the importance of advancing sufficient, affordable, clean and reliable energy supplies to sustain global economic growth, accommodate heightened demand, and promote regional energy security. Traveling to Budapest from Moscow where he participated in the G8 Energy Ministerial, Secretary Bodman reaffirmed the G8 priorities

303

Category:Clean Energy Economy Regions | Open Energy Information  

Open Energy Info (EERE)

Clean Energy Economy Regions Jump to: navigation, search Clean Energy Economy Regions Category Pages in category "Clean Energy Economy Regions" The following 7 pages are in this...

304

Tankless Demand Water Heater Basics | Department of Energy  

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

Demand Water Heater Basics Demand Water Heater Basics Tankless Demand Water Heater Basics August 19, 2013 - 2:57pm Addthis Illustration of an electric demand water heater. At the top of the image, the heating unit is shown. Cold water flows in one end of a pipe, flows through and around several curved pipes over the heating elements, and out the other end as hot water. Beneath the heating unit, a typical sink setup is shown. The sink has two pipes coming out the bottom, one for the hot water line and one for the cold water line. Both pipes lead to the heating unit, which is installed in close proximity to the area of hot water use, and is connected to a power source (110 or 220 volts). Demand (tankless or instantaneous) water heaters have heating devices that are activated by the flow of water, so they provide hot water only as

305

Tankless Demand Water Heater Basics | Department of Energy  

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

Tankless Demand Water Heater Basics Tankless Demand Water Heater Basics Tankless Demand Water Heater Basics August 19, 2013 - 2:57pm Addthis Illustration of an electric demand water heater. At the top of the image, the heating unit is shown. Cold water flows in one end of a pipe, flows through and around several curved pipes over the heating elements, and out the other end as hot water. Beneath the heating unit, a typical sink setup is shown. The sink has two pipes coming out the bottom, one for the hot water line and one for the cold water line. Both pipes lead to the heating unit, which is installed in close proximity to the area of hot water use, and is connected to a power source (110 or 220 volts). Demand (tankless or instantaneous) water heaters have heating devices that are activated by the flow of water, so they provide hot water only as

306

Definition: Interruptible Load Or Interruptible Demand | Open Energy  

Open Energy Info (EERE)

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

307

Univariate modeling and forecasting of monthly energy demand time series using abductive and neural networks  

Science Conference Proceedings (OSTI)

Neural networks have been widely used for short-term, and to a lesser degree medium and long-term, demand forecasting. In the majority of cases for the latter two applications, multivariate modeling was adopted, where the demand time series is related ... Keywords: Abductive networks, Energy demand, Medium-term load forecasting, Neural networks, Time series forecasting, Univariate time series analysis

R. E. Abdel-Aal

2008-05-01T23:59:59.000Z

308

Survey and Forecast of Marketplace Supply and Demand for Energy-Efficient Lighting Products  

Science Conference Proceedings (OSTI)

Utility incentive programs have placed significant demands on the suppliers of certain types of energy-efficient lighting products--particularly compact fluorescent lamps and electronic ballasts. Two major federal programs may soon place even greater demands on the lighting industry. This report assesses the program-induced demand for efficient lighting products and their likely near-term supply.

1992-12-01T23:59:59.000Z

309

Impact of Temperature Trends on Short-Term Energy Demand, The (Released in the STEO September 1999)  

Reports and Publications (EIA)

The past few years have witnessed unusually warm weather, as evidenced by both mild winters and hot summers. The analysis shows that the 30-year norms--the basis of weather-related energy demand projections--donot reflect the warming trend or its regional and seasonal patterns.

Information Center

1999-09-01T23:59:59.000Z

310

LBNL/PUB-5482 Energy Efficiency Options for the New England Demand  

E-Print Network (OSTI)

LBNL/PUB-5482 Energy Efficiency Options for the New England Demand Response Initiative (NEDRI://eetd.lbl.gov/EA/EMP/ The work described in this study was funded by the Assistance Secretary of Energy Efficiency and Renewable00098 #12;Energy Efficiency Options for the New England Demand Response Initiative (NEDRI) ­ Framing

311

energy: Supply, Demand, and impacts CooRDinATinG LeAD AUThoR  

E-Print Network (OSTI)

240 chapter 12 energy: Supply, Demand, and impacts CooRDinATinG LeAD AUThoR Vincent C. Tidwell;energy: supply, demand, and impacts 241 · Delivery of electricity may become more vulnerable) in 2009, equal to 222 million BTUs per person (EIA 2010). Any change or disruption to the supply of energy

Kammen, Daniel M.

312

Large-Scale Integration of Deferrable Demand and Renewable Energy Sources  

E-Print Network (OSTI)

1 Large-Scale Integration of Deferrable Demand and Renewable Energy Sources Anthony Papavasiliou model for assessing the impacts of the large-scale integration of renewable energy sources. In order to accurately assess the impacts of renewable energy integration and demand response integration

Oren, Shmuel S.

313

ECOWAS Regional Centre for Renewable Energy and Energy Efficiency...  

Open Energy Info (EERE)

ECOWAS Regional Centre for Renewable Energy and Energy Efficiency (ECREEE) (Redirected from West African Regional Centre for Renewable Energy and Energy Efficiency (ECREEE)) Jump...

314

ECOWAS Regional Centre for Renewable Energy and Energy Efficiency...  

Open Energy Info (EERE)

ECOWAS Regional Centre for Renewable Energy and Energy Efficiency (ECREEE) Jump to: navigation, search Logo: Regional Centre for Renewable Energy and Energy Efficiency Name...

315

Tankless or Demand-Type Water Heaters | Department of Energy  

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

or Demand-Type Water Heaters May 2, 2012 - 6:47pm Addthis Diagram of a tankless water heater. Diagram of a tankless water heater. How does it work? Tankless water heaters deliver...

316

Chapter 3: Demand-Side Resources | Department of Energy  

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

spent 14.7 billion on DSM programs between 1989 and 1999, an average of 1.3 billion per year. Chapter 3: Demand-Side Resources More Documents & Publications Draft Chapter 3:...

317

Annual World Oil Demand Growth - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Following relatively small increases of 1.3 million barrels per day in 1999 and 0.8 million barrels per day in 2000, EIA is estimating world demand may grow by 1.5 ...

318

State and Regional policies that promote energy efficiency programs carried  

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

and Regional policies that promote energy efficiency programs and Regional policies that promote energy efficiency programs carried out by electric and gas utilities State and Regional policies that promote energy efficiency programs carried out by electric and gas utilities A report to the United States Congress Pursuant to section 139 of the energy policy act of 2005. March 2007 State and Regional policies that promote energy efficiency programs carried out by electric and gas utilities More Documents & Publications State and regional policies that promote energy efficiency programs carried out by electric and gas utilities 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)

319

State and regional policies that promote energy efficiency programs carried  

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

and regional policies that promote energy efficiency programs and regional policies that promote energy efficiency programs carried out by electric and gas utilities State and regional policies that promote energy efficiency programs carried out by electric and gas utilities A report to the United States Congress Pursuant to section 139 of the Energy Policy Act of 2005. March 2007 State and regional policies that promote energy efficiency programs carried out by electric and gas utilities More Documents & Publications State and Regional policies that promote energy efficiency programs carried out by electric and gas utilities 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)

320

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

Gasoline and Diesel Fuel Update (EIA)

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

Note: This page contains sample records for the topic "regional energy 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

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

Gasoline and Diesel Fuel Update (EIA)

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

322

Scenario Evaluation, Regionalization & Analysis (SERA) | Open Energy  

Open Energy Info (EERE)

Scenario Evaluation, Regionalization & Analysis (SERA) Scenario Evaluation, Regionalization & Analysis (SERA) Jump to: navigation, search Tool Summary Name: Scenario Evaluation, Regionalization & Analysis (SERA) Agency/Company /Organization: National Renewable Energy Laboratory Scenario Evaluation, Regionalization & Analysis (SERA) Screenshot Logo: Scenario Evaluation, Regionalization & Analysis (SERA) SERA (Scenario Evaluation, Regionalization & Analysis) is a geospatially and temporally oriented infrastructure analysis model that determines the optimal production and delivery scenarios for hydrogen, given resource availability and technology cost. Given annual H2 demands on a city-by-city basis, forecasts of feedstock costs, and a catalog of available hydrogen production and transportation technologies, the model generates

323

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network (OSTI)

Previous papers have discussed definitions of energyThis paper provides a framework linking continuous energyThe paper presents a framework about when energy is used,

Piette, Mary Ann

2009-01-01T23:59:59.000Z

324

Behavioral Aspects in Simulating the Future US Building Energy Demand  

E-Print Network (OSTI)

tech. selection Net energy consumption Service tech. cost &equip. selection Net energy consumption Service tech. cost &tech. selection Net energy consumption Service tech. cost &

Stadler, Michael

2011-01-01T23:59:59.000Z

325

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network (OSTI)

Heat DX Cooling Total Annual Energy Usage Peak Electricifier DX Cooling Total Annual Energy Usage Scenario Supply/ifier DX Cooling Total Annual Energy Usage Peak Electric

Shehabi, Arman

2010-01-01T23:59:59.000Z

326

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

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

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

327

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

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

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

328

Northeast Regional Biomass Energy Program  

DOE Green Energy (OSTI)

The Northeast Regional Biomass Program (NRBP) is entering its ninth year of operation. The management and the objectives have virtually remained unchanged and are stated as follows. The program conducted by NRBP has three basic features: (1) a state grant component that provides funds (with a 50 percent matching requirement) to each of the states in the region to strengthen and integrate the work of state agencies involved in biomass energy; (2) a series of technical reports and studies in areas that have been identified as being of critical importance to the development of biomass energy in the region; and (3) a continuous long range planning component with heavy private sector involvement that helps to identify activities necessary to spur greater development and use of biomass energy in the Northeast.

O'Connell, R.A.

1992-04-01T23:59:59.000Z

329

Northeast Regional Biomass Energy Program  

DOE Green Energy (OSTI)

The Northeast Regional Biomass Program (NRBP) is entering its ninth year of operation. The management and the objectives have virtually remained unchanged and are stated as follows. The program conducted by NRBP has three basic features: (1) a state grant component that provides funds (with a 50 percent matching requirement) to each of the states in the region to strengthen and integrate the work of state agencies involved in biomass energy; (2) a series of technical reports and studies in areas that have been identified as being of critical importance to the development of biomass energy in the region; and (3) a continuous long range planning component with heavy private sector involvement that helps to identify activities necessary to spur greater development and use of biomass energy in the Northeast.

O'Connell, R.A.

1992-02-01T23:59:59.000Z

330

Industrial Sector Energy Demand: Revisions for Non-Energy-Intensive Manufacturing (released in AEO2007)  

Reports and Publications (EIA)

For the industrial sector, EIAs analysis and projection efforts generally have focused on the energy-intensive industriesfood, bulk chemicals, refining, glass, cement, steel, and aluminumwhere energy cost averages 4.8 percent of annual operating cost. Detailed process flows and energy intensity indicators have been developed for narrowly defined industry groups in the energy-intensive manufacturing sector. The non-energy-intensive manufacturing industries, where energy cost averages 1.9 percent of annual operating cost, previously have received somewhat less attention, however. In AEO2006, energy demand projections were provided for two broadly aggregated industry groups in the non-energy-intensive manufacturing sector: metal-based durables and other non-energy-intensive. In the AEO2006 projections, the two groups accounted for more than 50 percent of the projected increase in industrial natural gas consumption from 2004 to 2030.

Information Center

2007-03-11T23:59:59.000Z

331

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network (OSTI)

optimized relative to the energy services begin delivered.energy is used, levels of services by energy using systems,energy efficiency and advances in controls and service level

Piette, Mary Ann

2009-01-01T23:59:59.000Z

332

Poster abstract: wireless sensor network characterization - application to demand response energy pricing  

Science Conference Proceedings (OSTI)

This poster presents latency and reliability characterization of wireless sensor network as applied to an advanced building control system for demand response energy pricing. A test network provided the infrastructure to extract round trip time and packet ... Keywords: advanced building control, demand response energy pricing

Nathan Ota; Dan Hooks; Paul Wright; David Auslander; Therese Peffer

2003-11-01T23:59:59.000Z

333

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network (OSTI)

cities, with electricity generation in some regions more reliant on fossil fuels while hydro- or nuclear-

Shehabi, Arman

2010-01-01T23:59:59.000Z

334

Modelling the Energy Demand of Households in a Combined  

E-Print Network (OSTI)

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

Steininger, Karl W.

335

Economic development and the structure of the demand for commerial energy  

E-Print Network (OSTI)

To deepen the understanding of the relation between economic development and energy demand, this study estimates the Engel curves that relate per-capita energy consumption in major economic sectors to per-capita GDP. Panel ...

Judson, Ruth A.

336

Economic development and the structure of the demand for commerial energy  

E-Print Network (OSTI)

To deepen understanding of the relation between economic development and energy demand, this study estimates the Engel curves that relate per-capita energy consumption in major economic sectors to per-capita GDP. Panel ...

Judson, Ruth A.; Schmalensee, Richard.; Stoker, Thomas M.

337

Residential energy demand modeling and the NIECS data base : an evaluation  

E-Print Network (OSTI)

The purpose of this report is to evaluate the 1978-79 National Interim Energy Consumption Survey (NIECS) data base in terms of its usefulness for estimating residential energy demand models based on household appliance ...

Cowing, Thomas G.

1982-01-01T23:59:59.000Z

338

Southeast Regional Clean Energy Policy Analysis | Department...  

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

Southeast Regional Clean Energy Policy Analysis Southeast Regional Clean Energy Policy Analysis This report covers the states that largely fall into the Southeastern Reliability...

339

ENERGY DEMAND AND CONSERVATION IN KENYA: INITIAL APPRAISAL  

E-Print Network (OSTI)

bound up in steel, paper, and other energy intensive goods.and residential energy use in the paper by McGranahan 1 eton energy use and the economy can be found in the paper by

Schipper, Lee

2013-01-01T23:59:59.000Z

340

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

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

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "regional energy 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

Future world energy demand driven by trends in developing ...  

U.S. Energy Information Administration (EIA)

EIA's International Energy Outlook 2013 (IEO2013) projects that growth in world energy use largely comes from countries outside of the Organization ...

342

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

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

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

343

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.

344

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

E-Print Network (OSTI)

equipment. Since electricity demand, is projected to exhibitfrom 44% in 2006. In electricity demand, its usage in plugRuns, Average Value) Electricity Demand Power/Electricity

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

345

Control and Optimization Meet the Smart Power Grid - Scheduling of Power Demands for Optimal Energy Management  

E-Print Network (OSTI)

The smart power grid aims at harnessing information and communication technologies to enhance reliability and enforce sensible use of energy. Its realization is geared by the fundamental goal of effective management of demand load. In this work, we envision a scenario with real-time communication between the operator and consumers. The grid operator controller receives requests for power demands from consumers, with different power requirement, duration, and a deadline by which it is to be completed. The objective is to devise a power demand task scheduling policy that minimizes the grid operational cost over a time horizon. The operational cost is a convex function of instantaneous power consumption and reflects the fact that each additional unit of power needed to serve demands is more expensive as demand load increases.First, we study the off-line demand scheduling problem, where parameters are fixed and known. Next, we devise a stochastic model for the case when demands are generated continually and sched...

Koutsopoulos, Iordanis

2010-01-01T23:59:59.000Z

346

National Action Plan on Demand Response, June 2010 | Department of Energy  

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

Action Plan on Demand Response, June 2010 Action Plan on Demand Response, June 2010 National Action Plan on Demand Response, June 2010 The Federal Energy Regulatory Commission (FERC) is required to develop the National Action Plan on Demand Response (National Action Plan) as outlined in section 529 of the Energy Independence and Security Act of 2007 (EISA), entitled "Electricity Sector Demand Response." This National Action Plan is designed to meet three objectives: Identify "requirements for technical assistance to States to allow them to maximize the amount of demand response resources that can be developed and deployed." Design and identify "requirements for implementation of a national communications program that includes broad-based customer education and support."

347

Energy and Emissions Long Term Outlook A Detailed Simulation of Energy Supply-Demand  

E-Print Network (OSTI)

The paper presents the results of a detailed, bottom-up modeling exercise of Mexicos energy markets. The Energy and Power Evaluation Program (ENPEP), the Wien Automatic System Planning (WASP) and the Energy Demand Model (MODEMA) were used to develop forecasts to 2025. Primary energy supply is projected to grow from 9,313 PJ (1999) to 13,130 PJ (2025). Mexicos crude oil production is expected to increase by 1 % annually to 8,230 PJ. As its domestic crude refining capacity becomes unable to meet the rising demand for petroleum products, imports of oil products will become increasingly important. The Mexican natural gas markets are driven by the strong demand for gas in the power generating and manufacturing industries which significantly outpaces projected domestic production. The result is a potential need for large natural gas imports that may reach approximately 46 % of total gas supplies by 2025. The long-term market outlook for Mexicos electricity industry shows a heavy reliance on naturalgas based generating technologies. Gas-fired generation is forecast to increase 26-fold eventually accounting for over 80 % of total generation by 2025. Alternative results for a constrained-gas scenario show a substantial shift to coal-based generation and the associated effects on the natural gas market. A renewables scenario investigates impacts of additional renewables for power generation (primarily wind plus some solar-photovoltaic). A nuclear scenario analyzes the impacts of additional nuclear power

Juan Quintanilla Martnez; Autnoma Mxico; Centro Mario Molina; Juan Quintanilla Martnez

2005-01-01T23:59:59.000Z

348

Regional Differences in Corn Ethanol Production: Profitability and Potential Water Demands  

E-Print Network (OSTI)

Through the use of a stochastic simulation model this project analyzes both the impacts of the expanding biofuels sector on water demand in selected regions of the United States and variations in the profitability of ethanol production due to location differences. Changes in consumptive water use in the Texas High Plains, Southern Minnesota, and the Central Valley of California, as impacted by current and proposed grain-based ethanol plants were addressed. In addition, this research assesses the potential impacts of technologies to reduce consumptive water use in the production of ethanol in terms of water usage and the economic viability of each ethanol facility. This research quantifies the role of corn ethanol production on water resource availability and identifies the alternative water pricing schemes at which ethanol production is no longer profitable. The results of this research show that the expansion of regional ethanol production and the resulting changes in the regional agricultural landscapes do relatively little to change consumptive water usage in each location. The California Central Valley has the highest potential for increased water usage with annual water usage in 2017 at levels 15% higher than historical estimates, whereas Southern Minnesota and the Texas High Plains are predicted to have increases of less than 5% during the same time period. Although water use by ethanol plants is extremely minor relative to consumptive regional agricultural water usage, technological adaptations by ethanol facilities have the potential to slightly reduce water usage and prove to be economically beneficial adaptations to make. The sensitivity of net present value (NPV) with respect to changes in water price is shown to be extremely inelastic, indicating that ethanol producers have the ability to pay significantly more for their fresh water with little impact on their 10 year economic performance.

Higgins, Lindsey M.

2009-05-01T23:59:59.000Z

349

Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California  

Science Conference Proceedings (OSTI)

This report summarizes the Lawrence Berkeley National Laboratory's research to date in characterizing energy efficiency and open automated demand response opportunities for industrial refrigerated warehouses in California. The report describes refrigerated warehouses characteristics, energy use and demand, and control systems. It also discusses energy efficiency and open automated demand response opportunities and provides analysis results from three demand response studies. In addition, several energy efficiency, load management, and demand response case studies are provided for refrigerated warehouses. This study shows that refrigerated warehouses can be excellent candidates for open automated demand response and that facilities which have implemented energy efficiency measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for open automated demand response (OpenADR) at little additional cost. These improved controls may prepare facilities to be more receptive to OpenADR due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.

Lekov, Alex; Thompson, Lisa; McKane, Aimee; Rockoff, Alexandra; Piette, Mary Ann

2009-05-11T23:59:59.000Z

350

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

Science Conference Proceedings (OSTI)

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

2013-05-22T23:59:59.000Z

351

Assessment of Commercial Building Automation and Energy Management Systems for Demand Response Applications  

Science Conference Proceedings (OSTI)

This Technical Update is an overview of commercial building automation and energy management systems with a focus on their capabilities (current and future), especially in support of demand response (DR). The report includes background on commercial building automation and energy management systems; a discussion of demand response applications in commercial buildings, including building loads and control strategies; and a review of suppliers building automation and energy management systems to support d...

2009-12-14T23:59:59.000Z

352

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

E-Print Network (OSTI)

Electricity and Natural Gas Demand in Japanese ResidentialWater Heating Natural Gas Demand Mtoe Actual Projection Mtoe

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

353

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

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

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

354

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network (OSTI)

lower RH upper RH UPS Waste Heat Humid- ifier DX Cooling Total Annual Energy Usage Peak Electriclower RH upper RH UPS Waste Heat Humid- ifier DX Cooling Total Annual Energy Usage Peak Electric

Shehabi, Arman

2010-01-01T23:59:59.000Z

355

Commercial Demand Module of the National Energy Modeling ...  

U.S. Energy Information Administration (EIA)

Commercial Buildings Energy Consumption Survey ... space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The market segment ...

356

ENERGY DEMAND AND CONSERVATION IN KENYA: INITIAL APPRAISAL  

E-Print Network (OSTI)

plants, at what energy intensity? hotel in a given year? toenergy use for key kinds of buildings; major tals. hotels~

Schipper, Lee

2013-01-01T23:59:59.000Z

357

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.

358

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

DOE Green Energy (OSTI)

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

359

Energy demand and conservation in Kenya: initial appraisal  

SciTech Connect

Ongoing research into the use and conservation of energy in Kenya is reported briefly. A partial accounting of energy use in Kenya is presented, and evidence that some energy conservation has been taking place is discussed. A fuller accounting for all commercial energy flows is both possible and desirable. The work presented should serve as a basis for further data collection and analysis in Kenya, and can be used as a model for similar efforts in other countries. The author intends to continue much of this energy accounting in Kenya in the latter half of 1980.

Schipper, L.

1980-03-01T23:59:59.000Z

360

Agent-based coordination techniques for matching supply and demand in energy networks  

Science Conference Proceedings (OSTI)

There is a lot of effort directed toward realizing the power network of the future. The future power network is expected to depend on a large number of renewable energy resources connected directly to the low and medium voltage power network. Demand ... Keywords: Supply and demand matching, market and non-market algorithms, multi-agent systems

Rashad Badawy; Benjamin Hirsch; Sahin Albayrak

2010-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "regional energy 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

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

E-Print Network (OSTI)

1 THE CHALLENGES AND OPPORTUNITIES TO MEET THE WORKFORCE DEMAND IN THE ELECTRIC POWER AND ENERGY PROFESSION Wanda Reder, S & C Electric Company, 6601 North Ridge Blvd., Chicago, IL 60626- 3997, USA Vahid, Iowa State University ABSTRACT There is a tremendous imbalance between engineering workforce demand

362

Transportation Energy Futures Series: Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future  

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

DEMAND DEMAND Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future TRANSPORTATION ENERGY FUTURES SERIES: Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future A Study Sponsored by U.S. Department of Energy Office of Energy Efficiency and Renewable Energy March 2013 Prepared by CAMBRIDGE SYSTEMATICS Cambridge, MA 02140 under subcontract DGJ-1-11857-01 Technical monitoring performed by NATIONAL RENEWABLE ENERGY LABORATORY Golden, Colorado 80401-3305 managed by Alliance for Sustainable Energy, LLC for the U.S. DEPARTMENT OF ENERGY Under contract DC-A36-08GO28308 This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their

363

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

364

Coordination of Energy Efficiency and Demand Response: A Resource of the  

Open Energy Info (EERE)

Coordination of Energy Efficiency and Demand Response: A Resource of the Coordination of Energy Efficiency and Demand Response: A Resource of the National Action Plan for Energy Efficiency Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Coordination of Energy Efficiency and Demand Response: A Resource of the National Action Plan for Energy Efficiency Focus Area: Energy Efficiency Topics: Policy, Deployment, & Program Impact Website: www.epa.gov/cleanenergy/documents/suca/ee_and_dr.pdf Equivalent URI: cleanenergysolutions.org/content/coordination-energy-efficiency-and-de Language: English Policies: "Regulations,Deployment Programs" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Retrofits Regulations: Energy Standards

365

Experts Meeting: Behavioral Economics as Applied to Energy Demand...  

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

methods associated with the modeling of changing energy markets for purposes of public information and policy analysis. - EIA uses the NEMS tool, a computer-based,...

366

Demand-Side Management and Energy Efficiency Revisited  

E-Print Network (OSTI)

of electricity consumption reported by utility n in year telectricity consumption due to energy e?ciency DSM expenditures across utilities and years

Auffhammer, Maximilian; Blumstein, Carl; Fowlie, Meredith

2007-01-01T23:59:59.000Z

367

Determining energy requirement for future water supply and demand alternatives.  

E-Print Network (OSTI)

??Water and energy are two inextricably linked resources. Each has the potential to limit the development of the other. There is a substantial body of (more)

Larsen, Sara Gaye

2010-01-01T23:59:59.000Z

368

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand...  

Annual Energy Outlook 2012 (EIA)

household.gif (5637 bytes) The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and...

369

Property:FlatDemandStructure | Open Energy Information  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:FlatDemandStructure Jump to: navigation, search This is a property of type Page. Pages using the property "FlatDemandStructure" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 0000827d-84d0-453d-b659-b86869323897 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 00101108-073b-4503-9cd4-01769611c26f + 00101108-073b-4503-9cd4-01769611c26f + 001361ca-50d2-49bc-b331-08755a2c7c7d + 001361ca-50d2-49bc-b331-08755a2c7c7d + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 001d1952-955c-411b-8ce4-3d146852a75e + 001d1952-955c-411b-8ce4-3d146852a75e +

370

Proposed Design for a Coupled Ground-Source Heat Pump/Energy Recovery Ventilator System to Reduce Building Energy Demand.  

E-Print Network (OSTI)

??The work presented in this thesis focuses on reducing the energy demand of a residential building by using a coupled ground-source heat pump/energy recovery ventilation (more)

McDaniel, Matthew Lee

2011-01-01T23:59:59.000Z

371

Discussion Paper Prepared for: Deploying Demand Side Energy Technologies workshop  

E-Print Network (OSTI)

The IEA study Energy Technology Perspectives 2006 (ETP 2006) demonstrates how energy technologies can contribute to a stabilization of CO2 emissions at todays level by 2050. The results of the scenario analysis showed that no fundamental technology breakthroughs are needed. Technologies that are available today or that are under development today will

Cecilia Tam; Dolf Gielen

2007-01-01T23:59:59.000Z

372

Demand Response and Smart Metering Policy Actions Since the Energy Policy  

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

and Smart Metering Policy Actions Since the Energy and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Officials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Officials This report represents a review of policy developments on demand response and other related areas such as smart meters and smart grid. It has been prepared by the Demand Response Coordinating Committ ee (DRCC) for the National Council on Electricity Policy (NCEP). The report focuses on State and Federal policy developments during the period from 2005 to mid-year 2008. It is an att empt to catalogue information on policy developments at both the federal and state level, both in the legislative and regulatory arenas. Demand Response and Smart Metering Policy Actions Since the Energy Policy

373

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

Gasoline and Diesel Fuel Update (EIA)

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

374

Saving Energy and Enabling Auto-Demand Response in Existing Buildings...  

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

Saving Energy and Enabling Auto-Demand Response in Existing Buildings and Plants Using Non-Invasive Retrofit Technologies Speaker(s): Harry Sim Date: April 7, 2011 - 12:00pm...

375

ZigBee Smart Energy Application Profile for Demand Response/Load...  

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

ZigBee Smart Energy Application Profile for Demand ResponseLoad Control and its implementation on a JAVA-based platform Speaker(s): John Lin Date: April 23, 2009 - 12:00pm...

376

Fact Sheet: U.S. and China Actions Matter for Global Energy Demand, for  

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

Fact Sheet: U.S. and China Actions Matter for Global Energy Demand, Fact Sheet: U.S. and China Actions Matter for Global Energy Demand, for Global Environmental Quality, and for the Challenge of Global Climate Change Fact Sheet: U.S. and China Actions Matter for Global Energy Demand, for Global Environmental Quality, and for the Challenge of Global Climate Change December 5, 2008 - 4:58pm Addthis The U.S. is committed to working together with China to tackle current energy challenges the world faces, including cultivating sufficient investment, the development and deployment of new energy technologies, and addressing greenhouse gas emissions from producing and using energy. Our cooperation spans power generation, efficient buildings, sustainable transportation, emissions-free nuclear power, and clean fossil fuels. The U.S. and China are the world's largest energy consumers and are

377

Fact Sheet: U.S. and China Actions Matter for Global Energy Demand, for  

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

S. and China Actions Matter for Global Energy Demand, S. and China Actions Matter for Global Energy Demand, for Global Environmental Quality, and for the Challenge of Global Climate Change Fact Sheet: U.S. and China Actions Matter for Global Energy Demand, for Global Environmental Quality, and for the Challenge of Global Climate Change December 5, 2008 - 4:58pm Addthis The U.S. is committed to working together with China to tackle current energy challenges the world faces, including cultivating sufficient investment, the development and deployment of new energy technologies, and addressing greenhouse gas emissions from producing and using energy. Our cooperation spans power generation, efficient buildings, sustainable transportation, emissions-free nuclear power, and clean fossil fuels. The U.S. and China are the world's largest energy consumers and are

378

India Energy Outlook: End Use Demand in India to 2020  

SciTech Connect

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

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

2009-03-30T23:59:59.000Z

379

An overview of energy supply and demand in China  

DOE Green Energy (OSTI)

Although China is a poor country, with much of its population still farming for basic subsistence in rural villages, China is rich in energy resources. With the world's largest hydropower potential, and ranking third behind the US and USSR in coal reserves, China is in a better position than many other developing countries when planning for its future energy development and self-sufficiency. China is now the third largest producer and consumer of commercial energy, but its huge populace dilutes this impressive aggregate performance into a per capita figure which is an order of magnitude below the rich industrialized nations. Despite this fact, it is still important to recognize that China's energy system is still one of the largest in the world. A system this size allows risk taking and can capture economies of scale. The Chinese have maintained rapid growth in energy production for several decades. In order to continue and fully utilize its abundant resources however, China must successfully confront development challenges in many areas. For example, the geographic distribution of consumption centers poorly matches the distribution of resources, which makes transportation a vital but often weak link in the energy system. Another example -- capital -- is scarce relative to labor, causing obsolete and inefficiently installed technology to be operated well beyond what would be considered its useful life in the West. Major improvements in industrial processes, buildings, and other energy-using equipment and practices are necessary if China's energy efficiency is to continue to improve. Chinese energy planners have been reluctant to invest in environmental quality at the expense of more tangible production quotas.

Liu, F.; Davis, W.B.; Levine, M.D.

1992-05-01T23:59:59.000Z

380

An overview of energy supply and demand in China  

DOE Green Energy (OSTI)

Although China is a poor country, with much of its population still farming for basic subsistence in rural villages, China is rich in energy resources. With the world`s largest hydropower potential, and ranking third behind the US and USSR in coal reserves, China is in a better position than many other developing countries when planning for its future energy development and self-sufficiency. China is now the third largest producer and consumer of commercial energy, but its huge populace dilutes this impressive aggregate performance into a per capita figure which is an order of magnitude below the rich industrialized nations. Despite this fact, it is still important to recognize that China`s energy system is still one of the largest in the world. A system this size allows risk taking and can capture economies of scale. The Chinese have maintained rapid growth in energy production for several decades. In order to continue and fully utilize its abundant resources however, China must successfully confront development challenges in many areas. For example, the geographic distribution of consumption centers poorly matches the distribution of resources, which makes transportation a vital but often weak link in the energy system. Another example -- capital -- is scarce relative to labor, causing obsolete and inefficiently installed technology to be operated well beyond what would be considered its useful life in the West. Major improvements in industrial processes, buildings, and other energy-using equipment and practices are necessary if China`s energy efficiency is to continue to improve. Chinese energy planners have been reluctant to invest in environmental quality at the expense of more tangible production quotas.

Liu, F.; Davis, W.B.; Levine, M.D.

1992-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "regional energy 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

EIA - Annual Energy Outlook 2009 - Natural Gas Demand  

Annual Energy Outlook 2012 (EIA)

at 202-586-8800. figure data Figure 72. Liquids production from gasification and oil shale, 2007-2030 (thousand barrels per day). Need help, contact the National Energy...

382

Power Sector Reforms in India: Demand Side and Renewable Energy...  

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

with EETD scientists on cooperative research? Get a job in EETD? Make my home more energy-efficient? Find a source within EETD for a news story I'm writing, shooting, or...

383

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

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

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

384

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

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

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

385

Comfort-Aware Home Energy Management Under Market-Based Demand-Response  

E-Print Network (OSTI)

pricing and consumption data in South Korea. Index Terms--smart grid, demand-response, energy management I-based pricing. In peak capping, each home is allocated an energy quota. In market-based pricing, the price-term viable way of regulating energy consumptions. We work with day-ahead market pricing in this paper

Boutaba, Raouf

386

A Successful Case Study of Small Business Energy Efficiency and Demand  

Open Energy Info (EERE)

A Successful Case Study of Small Business Energy Efficiency and Demand A Successful Case Study of Small Business Energy Efficiency and Demand Response with Communicating Thermostats Jump to: navigation, search Tool Summary LAUNCH TOOL Name: A Successful Case Study of Small Business Energy Efficiency and Demand Response with Communicating Thermostats Focus Area: Energy Efficiency Topics: Socio-Economic Website: drrc.lbl.gov/sites/drrc.lbl.gov/files/lbnl-2743e.pdf Equivalent URI: cleanenergysolutions.org/content/successful-case-study-small-business- Language: English Policies: Financial Incentives This report presents the results of a pilot study of 78 small commercial customers in the Sacramento Municipal Utility District. Participants were given a participation incentive and provided with both help in implementing energy efficiency measures for their buildings and an array of energy

387

Transportation Energy Futures Series: Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future  

SciTech Connect

Freight transportation demand is projected to grow to 27.5 billion tons in 2040, and to nearly 30.2 billion tons in 2050. This report describes the current and future demand for freight transportation in terms of tons and ton-miles of commodities moved by truck, rail, water, pipeline, and air freight carriers. It outlines the economic, logistics, transportation, and policy and regulatory factors that shape freight demand, the trends and 2050 outlook for these factors, and their anticipated effect on freight demand. After describing federal policy actions that could influence future freight demand, the report then summarizes the capabilities of available analytical models for forecasting freight demand. This is one in a series of reports produced as a result of the Transportation Energy Futures project, a Department of Energy-sponsored multi-agency effort to pinpoint underexplored strategies for reducing GHGs and petroleum dependence related to transportation.

Grenzeback, L. R.; Brown, A.; Fischer, M. J.; Hutson, N.; Lamm, C. R.; Pei, Y. L.; Vimmerstedt, L.; Vyas, A. D.; Winebrake, J. J.

2013-03-01T23:59:59.000Z

388

Retrofitting Existing Buildings for Demand Response & Energy Efficiency  

E-Print Network (OSTI)

heating or cooling load, and enables existing Building Management Systems to control fan speed) · Lighting ­ 20% (solution: Adura ALPS partnership) · Plug loads, data centers ­ remainder (solution: WTR partnership) · Plug loads, data centers ­ remainder (solution: WTR, WBM) Source: US Energy Information

California at Los Angeles, University of

389

Advanced Controls and Communications for Demand Response andEnergy Efficiency in Commercial Buildings  

SciTech Connect

Commercial buildings account for a large portion of summer peak demand. Research results show that there is significant potential to reduce peak demand in commercial buildings through advanced control technologies and strategies. However, a better understanding of commercial building's contribution to peak demand and the use of energy management and control systems is required to develop this demand response resource to its full potential. This paper discusses recent research results and new opportunities for advanced building control systems to provide demand response (DR) to improve electricity markets and reduce electric grid problems. The main focus of this paper is the role of new and existing control systems for HVAC and lighting in commercial buildings. A demand-side management framework from building operations perspective with three main features: daily energy efficiency, daily peak load management and event driven, dynamic demand response is presented. A general description of DR, its benefits, and nationwide potential in commercial buildings is outlined. Case studies involving energy management and control systems and DR savings opportunities are presented. The paper also describes results from three years of research in California to automate DR in buildings. Case study results and research on advanced buildings systems in New York are also presented.

Kiliccote, Sila; Piette, Mary Ann; Hansen, David

2006-01-17T23:59:59.000Z

390

Advanced Controls and Communications for Demand Response andEnergy Efficiency in Commercial Buildings  

SciTech Connect

Commercial buildings account for a large portion of summer peak demand. Research results show that there is significant potential to reduce peak demand in commercial buildings through advanced control technologies and strategies. However, a better understanding of commercial building's contribution to peak demand and the use of energy management and control systems is required to develop this demand response resource to its full potential. This paper discusses recent research results and new opportunities for advanced building control systems to provide demand response (DR) to improve electricity markets and reduce electric grid problems. The main focus of this paper is the role of new and existing control systems for HVAC and lighting in commercial buildings. A demand-side management framework from building operations perspective with three main features: daily energy efficiency, daily peak load management and event driven, dynamic demand response is presented. A general description of DR, its benefits, and nationwide potential in commercial buildings is outlined. Case studies involving energy management and control systems and DR savings opportunities are presented. The paper also describes results from three years of research in California to automate DR in buildings. Case study results and research on advanced buildings systems in New York are also presented.

Kiliccote, Sila; Piette, Mary Ann; Hansen, David

2006-01-17T23:59:59.000Z

391

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

E-Print Network (OSTI)

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

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

1985-01-01T23:59:59.000Z

392

Demand Responsive and Energy Efficient Control Technologies andStrategies in Commercial Buildings  

SciTech Connect

Commercial buildings account for a large portion of summer peak electric demand. Research results show that there is significant potential to reduce peak demand in commercial buildings through advanced control technologies and strategies. However, a better understanding of commercial buildings contribution to peak demand and the use of energy management and control systems is required to develop this demand response resource to its full potential. The main objectives of the study were: (1) To evaluate the size of contributions of peak demand commercial buildings in the U.S.; (2) To understand how commercial building control systems support energy efficiency and DR; and (3) To disseminate the results to the building owners, facility managers and building controls industry. In order to estimate the commercial buildings contribution to peak demand, two sources of data are used: (1) Commercial Building Energy Consumption Survey (CBECS) and (2) National Energy Modeling System (NEMS). These two sources indicate that commercial buildings noncoincidental peak demand is about 330GW. The project then focused on technologies and strategies that deliver energy efficiency and also target 5-10% of this peak. Based on a building operations perspective, a demand-side management framework with three main features: (1) daily energy efficiency, (2) daily peak load management and (3) dynamic, event-driven DR are outlined. A general description of DR, its benefits, and nationwide DR potential in commercial buildings are presented. Case studies involving these technologies and strategies are described. The findings of this project are shared with building owners, building controls industry, researchers and government entities through a webcast and their input is requested. Their input is presented in the appendix section of this report.

Piette, Mary Ann; Kiliccote, Sila

2006-09-01T23:59:59.000Z

393

The asymmetric effects of changes in price and income on energy and oil demand. Energy Journal 23(1  

E-Print Network (OSTI)

This paper estimates the effects on energy and oil demand of changes in income and oil prices, for 96 of the worlds largest countries, in per-capita terms. We examine three important issues: the asymmetric effects on demand of increases and decreases in oil prices; the asymmetric effects on demand of increases and decreases in income; and the different speeds of demand adjustment to changes in price and in income. Its main conclusions are the following: (1) OECD demand responds much more to increases in oil prices than to decreases; ignoring this asymmetric price response will bias downward the estimated response to income changes; (2) demands response to income decreases in many Non-OECD countries is not necessarily symmetric to its response to income increases; ignoring this asymmetric income response will bias the estimated response to income changes; (3) the speed of demand adjustment is faster to changes in income than to changes in price; ignoring this difference will bias upward the estimated response to income changes. Using correctly specified equations for energy and oil demand, the long-run response in demand for income growth is about 1.0 for Non-OECD Oil Exporters, Income Growers and perhaps all Non-OECD countries, and about 0.55 for OECD countries. These estimates for developing countries are significantly higher than current estimates used by the US Department of Energy. Our estimates for the OECD countries are also higher than those estimated recently by Schmalensee-Stoker-Judson (1998) and Holtz-Eakin and Selden (1995), who ignore the (asymmetric) effects of prices on demand. Higher responses to income changes, of course, will increase projections of energy and oil demand, and of carbon dioxide emissions.

Dermot Gately; Hillard G. Huntington; Dermot Gately; Hillard G. Huntington; Joyce Dargay; Lawrence Goulder; Mary Riddel; Shane Streifel

2002-01-01T23:59:59.000Z

394

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

E-Print Network (OSTI)

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

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

2013-01-01T23:59:59.000Z

395

Identification of Changes Needed in Supermarket Design for Energy Demand Reduction  

E-Print Network (OSTI)

Supermarkets use 3 percent of UK energy. To satisfy building regulations supermarket buildings are modeled in considerable detail. Lighting, occupancy, and small electrical energy impacts are included in this modeling. However, refrigeration energy is not, as it is classified as process energy rather than building related. Refrigeration energy, which can be very significant, is therefore currently unregulated and as a result, heat transfers related to refrigeration cabinets are typically not incorporated in modeling of the building at design stage. This paper explores the comparative energy demands of supermarket stores modeled, using a simple first order dynamic model, executed on Excel, and optimized firstly with, and secondly without, the cooling effect of refrigeration cabinets included in the model. A recently built supermarket is modeled. Results suggest that the energy demand of a new store could be reduced by 15 to 25 percent by improvement of the building envelope design with process energy included in the modeling.

Hill, F.; Edwards, R.; Levermore, G.

2012-01-01T23:59:59.000Z

396

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

SciTech Connect

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

NONE

1998-01-01T23:59:59.000Z

397

AWEA Wind Energy Regional Summit: Northeast | Department of Energy  

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

AWEA Wind Energy Regional Summit: Northeast AWEA Wind Energy Regional Summit: Northeast March 25, 2014 8:00AM EDT to March 26, 2014 5:00PM EDT Portland, Maine The AWEA Wind Energy...

398

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

Reports and Publications (EIA)

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

Information Center

2005-04-01T23:59:59.000Z

399

Modeling, Estimation, and Control in Energy Systems: Batteries & Demand Response  

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

Modeling, Modeling, Estimation, and Control in Energy Systems: Batteries & Demand Response Scott Moura Assistant Professor Civl & Environmental Engineering University of California, Berkeley EETD | LBNL Scott Moura | UC Berkeley Control, Batts, DR December 4, 2013 | Slide 1 Source: Vaclav Smil Estimates from Energy Transitions Scott Moura | UC Berkeley Control, Batts, DR December 4, 2013 | Slide 2 Energy Initiatives Denmark 50% wind penetration by 2025 Brazil uses 86% renewables China's aggressive energy/carbon intensity reduction EV Everywhere SunShot Green Button Zero emissions vehicle (ZEV) 33% renewables by 2020 Go Solar California Scott Moura | UC Berkeley Control, Batts, DR December 4, 2013 | Slide 3 Energy Systems of Interest Energy storage Smart Grids (e.g., batteries) (e.g., demand response) Scott Moura | UC Berkeley Control, Batts, DR December 4, 2013 | Slide 4 Energy

400

Geothermal Regions | Open Energy Information  

Open Energy Info (EERE)

Regions Regions Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Geothermal Regions RegionsMap2012.jpg Geothermal regions were outlined for the western United States (including Alaska and Hawaii) to identify geothermal areas, projects, and exploration trends for each region. These regions were developed based on the USGS physiographic regions (U.S. Geological Survey), and then adjusted to fit geothermal exploration parameters such as differences in geologic regime, structure, heat source, surface effects (weather, vegetation patterns, groundwater flow), and other relevant factors. The 21 regions can be seen outlined in red and overlain on the 2008 USGS Geothermal Favorability Map in Figure 1.[1] Add a new Geothermal Region List of Regions Area (km2) Mean MW

Note: This page contains sample records for the topic "regional energy 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

Federal Energy Management Program: Regional Super ESPC Saves Energy and  

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

Regional Super Regional Super ESPC Saves Energy and Dollars at NASA Johnson Space Center to someone by E-mail Share Federal Energy Management Program: Regional Super ESPC Saves Energy and Dollars at NASA Johnson Space Center on Facebook Tweet about Federal Energy Management Program: Regional Super ESPC Saves Energy and Dollars at NASA Johnson Space Center on Twitter Bookmark Federal Energy Management Program: Regional Super ESPC Saves Energy and Dollars at NASA Johnson Space Center on Google Bookmark Federal Energy Management Program: Regional Super ESPC Saves Energy and Dollars at NASA Johnson Space Center on Delicious Rank Federal Energy Management Program: Regional Super ESPC Saves Energy and Dollars at NASA Johnson Space Center on Digg Find More places to share Federal Energy Management Program:

402

Demand Response and Smart Metering Policy Actions Since the Energy Policy  

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 Page Edit with form History Facebook icon Twitter icon » Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Officials Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Officials Focus Area: Energy Efficiency, - Utility Topics: Socio-Economic Website: www.demandresponsesmartgrid.org/Resources/Documents/Final_NCEP_Report_ Equivalent URI: cleanenergysolutions.org/content/demand-response-and-smart-metering-po Language: English Policies: Regulations

403

Consensus forecast of U. S. energy supply and demand to the year 2000  

DOE Green Energy (OSTI)

Methods used in forecasting energy supply and demand are described, and recent forecasts are reviewed briefly. Forecasts to the year 2000 are displayed in tables and graphs and are used to prepare consensus forecasts for each form of fuel and energy supply. Fuel demand and energy use by consuming sector are tabulated for 1972 and 1975 for the various fuel forms. The distribution of energy consumption by use sector, as projected for the years 1985 and 2000 in the ERDA-48 planning report (Scenario V), is normalized to match the consensus energy supply forecasts. The results are tabulated listing future demand for each fuel and energy form by each major energy-use category. Recent estimates of U.S. energy resources are also reviewed briefly and are presented in tables for each fuel and energy form. The outlook for fossil fuel resources to the year 2040, as developed by the Institute for Energy Analysis at the Oak Ridge Associated Universities, is also presented.

Lane, J.A.

1976-02-01T23:59:59.000Z

404

Transportation Demand This  

Annual Energy Outlook 2012 (EIA)

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

405

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

Reports and Publications (EIA)

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

Information Center

2007-03-11T23:59:59.000Z

406

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

407

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)

2011-12-06T23:59:59.000Z

408

Utilization of Energy Efficiency and Demand Response as Resources for Transmission and Distribution Planning  

Science Conference Proceedings (OSTI)

EPRI began its Energy Efficiency Initiative in early 2007. Initiative research, which covers numerous topics associated with energy efficiency and demand management, is categorized into three areas: analytics, infrastructure, and devices. The project described in this report details the Initiatives analytics element, which deals with methods and tools for analyzing aspects of the use of energy efficiency as supply resource, including measurement and verification, inclusion in generation planning, emissi...

2008-02-05T23:59:59.000Z

409

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network (OSTI)

follows: EDemand t : electricity demand during day t (incost of reducing electricity demand (in $/MWh e ) HRDCost:maximum fraction of electricity demand to be met by demand

Siddiqui, Afzal

2010-01-01T23:59:59.000Z

410

Regional Systems Development for Geothermal Energy Resources Pacific Region  

Open Energy Info (EERE)

Systems Development for Geothermal Energy Resources Pacific Region Systems Development for Geothermal Energy Resources Pacific Region (California and Hawaii). Task 3: water resources evaluation. Topical report Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Report: Regional Systems Development for Geothermal Energy Resources Pacific Region (California and Hawaii). Task 3: water resources evaluation. Topical report Details Activities (1) Areas (1) Regions (0) Abstract: The fundamental objective of the water resources analysis was to assess the availability of surface and ground water for potential use as power plant make-up water in the major geothermal areas of California. The analysis was concentrated on identifying the major sources of surface and ground water, potential limitations on the usage of this water, and the

411

Gainesville Regional Utilities | Open Energy Information  

Open Energy Info (EERE)

Gainesville Regional Utilities Gainesville Regional Utilities Jump to: navigation, search Name Gainesville Regional Utilities Place Florida Utility Id 6909 Utility Location Yes Ownership M NERC Location FRCC NERC FRCC Yes Operates Generating Plant Yes Activity Generation Yes Activity Transmission Yes Activity Distribution Yes Activity Wholesale Marketing 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 Electric - Regular Service Residential Electric - Time-of-Use Service Residential General Service Demand Industrial General Service Non-Demand Commercial Large Power Service Industrial Average Rates

412

Hawaii Energy Strategy: Program guide. [Contains special sections on analytical energy forecasting, renewable energy resource assessment, demand-side energy management, energy vulnerability assessment, and energy strategy integration  

SciTech Connect

The Hawaii Energy Strategy program, or HES, is a set of seven projects which will produce an integrated energy strategy for the State of Hawaii. It will include a comprehensive energy vulnerability assessment with recommended courses of action to decrease Hawaii's energy vulnerability and to better prepare for an effective response to any energy emergency or supply disruption. The seven projects are designed to increase understanding of Hawaii's energy situation and to produce recommendations to achieve the State energy objectives of: Dependable, efficient, and economical state-wide energy systems capable of supporting the needs of the people, and increased energy self-sufficiency. The seven projects under the Hawaii Energy Strategy program include: Project 1: Develop Analytical Energy Forecasting Model for the State of Hawaii. Project 2: Fossil Energy Review and Analysis. Project 3: Renewable Energy Resource Assessment and Development Program. Project 4: Demand-Side Management Program. Project 5: Transportation Energy Strategy. Project 6: Energy Vulnerability Assessment Report and Contingency Planning. Project 7: Energy Strategy Integration and Evaluation System.

1992-09-01T23:59:59.000Z

413

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.

414

Regional Partnerships | Department of Energy  

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

Regional Regional Partnerships Regional Partnerships DOE's Regional Carbon Sequestration Partnerships Program DOE has created a network of seven Regional Carbon Sequestration Partnerships (RCSPs) to help develop the technology, infrastructure, and regulations to implement large-scale CO2 storage (also called carbon sequestration) in different regions and geologic formations within the Nation. Collectively, the seven RCSPs represent regions encompassing: 97 percent of coal-fired CO2 emissions; 97 percent of industrial CO2 emissions; 96 percent of the total land mass; and essentially all the geologic sequestration sites in the U.S. potentially available for carbon storage. We launched this initiative in 2003. It's being completed in phases (I, II, and III) and forms the centerpiece of national efforts to develop the

415

Regional Transmission Planning Webinar | Department of Energy  

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

Regional Transmission Planning Webinar Regional Transmission Planning Webinar Regional Transmission Planning Webinar May 29, 2013 11:00AM MDT Webinar The U.S. Department of Energy (DOE) Office of Indian Energy Policy and Programs, Office of Energy Efficiency and Renewable Energy Tribal Energy Program, and Western Area Power Administration (WAPA) are pleased to continue their sponsorship of the Tribal Renewable Energy Webinar Series. As part of a process to develop interconnection-based transmission plans for the Eastern and Western Interconnections and the Electric Reliability Council of Texas (ERCOT), the eight U.S. regional reliability organizations are expanding existing regional transmission planning activities and broadening stakeholder involvement. Hear about the status of the organizations' plans and evaluations of long-term regional transmission

416

Smart Grid Regional and Energy Storage Demonstration Projects...  

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

Regional and Energy Storage Demonstration Projects: Awards Smart Grid Regional and Energy Storage Demonstration Projects: Awards List of Smart Grid Regional and Energy Storage...

417

Regional Energy Deployment System (ReEDS) | Open Energy Information  

Open Energy Info (EERE)

Regional Energy Deployment System (ReEDS) Regional Energy Deployment System (ReEDS) (Redirected from Regional Energy Deployment System) Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Regional Energy Deployment System Agency/Company /Organization: NREL Sector: Energy Topics: Pathways analysis, Resource assessment Resource Type: Software/modeling tools User Interface: Desktop Application Website: www.nrel.gov/analysis/reeds/ OpenEI Keyword(s): EERE tool, Regional Energy Deployment System, ReEDS References: Regional Energy Deployment System (ReEDS) Web site[1] Regional Energy Deployment System (ReEDS) is a multiregional, multitimeperiod, Geographic Information System (GIS), and linear programming model of capacity expansion in the electric sector of the United States. The model, developed by NREL's Strategic Energy Analysis

418

Survey and forecast of marketplace supply and demand for energy- efficient lighting products  

SciTech Connect

The rapid growth in demand for energy-efficient lighting products has led to supply shortages for certain products. To understand the near-term (1- to 5-year) market for energy-efficient lighting products, a selected set of utilities and lighting product manufacturers were surveyed in early 1991. Two major U. S. government programs, EPA's Green Lights and DOE's Federal Relighting Initiative, were also examined to assess their effect on product demand. Lighting product manufacturers predicted significant growth through 1995. Lamp manufacturers indicated that compact fluorescent lamp shipments tripled between 1988 and 1991, and predicted that shipments would again triple, rising from 25 million units in 1991 to 72 million units in 1995. Ballast manufacturers predicted that demand for power-factorcorrected ballasts (both magnetic and electronic) would grow from 59.4 million units in 1991 to 71.1 million units in 1995. Electronic ballasts were predicted to grow from 11% of ballast demand in 1991 to 40% in 1995. Manufacturers projected that electronic ballast supply shortages would continue until late 1992. Lamp and ballast producers indicated that they had difficulty in determining what additional supply requirements might result due to demand created by utility programs. Using forecasts from 27 surveyed utilities and assumptions regarding the growth of U. S. utility lighting DSM programs, low, median, and high forecasts were developed for utility expenditures for lighting incentives through 1994. The projected median figure for 1992 was $316 million, while for 1994, the projected median figure was $547 million. The allocation of incentive dollars to various products and the number of units needed to meet utility-stimulated demand were also projected. To provide a better connection between future supply and demand, a common database is needed that captures detailed DSM program information including incentive dollars and unit-volume mix by product type.

Gough, A. (Lighting Research Inst., New York, NY (United States)); Blevins, R. (Plexus Research, Inc., Donegal, PA (United States))

1992-12-01T23:59:59.000Z

419

Water flows, energy demand, and market analysis of the informal water sector in Kisumu, Kenya  

E-Print Network (OSTI)

Analysis Water flows, energy demand, and market analysis of the informal water sector in Kisumu Available online xxxx Keywords: Informal water sector Water flows Developing countries Water market analysis to cope with popu- lation growth. Informal water businesses fulfill unmet water supply needs, yet little

Elimelech, Menachem

420

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network (OSTI)

than relying on central-station electricity generation and purchase of natural gas for heating and DER under uncertain electricity and natural gas prices · Section 5 summarizes the findings Control of Distributed Energy Resources and Demand Response under Uncertainty 3 · FPt: wholesale natural

Note: This page contains sample records for the topic "regional energy 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

Barriers to reducing energy demand in existing building stock -a perspective based on  

E-Print Network (OSTI)

Barriers to reducing energy demand in existing building stock - a perspective based on observation incentives for replacing the worst boilers, installing insulation funding for businesses and charities to push incentives, offer advice, develop new interventions building regs that apply to new boilers

Carletta, Jean

422

World Energy Consumption by Region, 1970-2020  

U.S. Energy Information Administration (EIA)

In the IEO2000 reference case, much of the growth in worldwide energy use is projected for the developing world. In particular, energy demand in developing Asia ...

423

Browse By Region | Open Energy Information  

Open Energy Info (EERE)

Categories Countries (211) States (51) Congressional Districts (437) Counties (3142) Cities (27937) Clean Energy Economy Regions (7) Programs (656) Tools (1483) Retrieved from...

424

Lake Region Electric Cooperative - Commercial Energy Efficiency...  

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

details Lake Region Electric Cooperative (LREC) offers grants to commercial customers for electric energy efficiency improvements, audits, and engineering and design assistance for...

425

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

SciTech Connect

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

Letschert, Virginie; McNeil, Michael A.

2008-05-13T23:59:59.000Z

426

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

SciTech Connect

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

Letschert, Virginie; McNeil, Michael A.

2008-05-13T23:59:59.000Z

427

Propane Sector Demand Shares  

U.S. Energy Information Administration (EIA)

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

428

Assessment of Achievable Potential from Energy Efficiency and Demand Response Programs in the U.S. (2010 - 2030)  

Science Conference Proceedings (OSTI)

This report documents the results of an exhaustive study to assess the achievable potential for electricity energy savings and peak demand reduction from energy efficiency and demand response programs through 2030. This achievable potential represents an estimated range of savings attainable through programs that encourage adoption of energy-efficient technologies, taking into consideration technical, economic, and market constraints.

2009-01-14T23:59:59.000Z

429

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

E-Print Network (OSTI)

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

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

2000-01-01T23:59:59.000Z

430

Web-based energy information systems for energy management and demand response in commercial buildings  

E-Print Network (OSTI)

download EMCS download Sub-metering Real-time Connectivityof diagnostic testing, sub-metering, and performancecoincident demand at sub-metering S Compare to historical

Motegi, Naoya; Piette, Mary Ann; Kinney, Satkartar; Herter, Karen

2003-01-01T23:59:59.000Z

431

Energy Demand and Emissions in Building in China: Scenarios and Policy Options  

E-Print Network (OSTI)

Recent rapid growth of energy use in China exerts great pressure on the energy supply and environment. This study provides scenarios of future energy development in buildings, including urban residential, rural residential and service sectors (not including transport), taking into account the most up-to-date data and recent policy discussions that will affect future economic, population, and energy supply trends. To understand the role of policy options including technology options and countermeasures, two scenarios were defined, which represent the range of plausible futures for energy development in buildings. This is also part of an energy and emission scenario study for the IPAC (Integrated Policy Assessment Model for China) modeling team. The results from quantitative analysis show that energy demand in buildings in China could increase quickly, as high as 666 million in 2030. However, policies and technologies could contribute a lot to energy demand savings, which could be 28% energy savings compared with the baseline scenario. There is still space for further energy savings if more advanced technologies could be fully diffused.

Kejun, J.; Xiulian, H.

2006-01-01T23:59:59.000Z

432

Regional Energy Deployment System (ReEDS) | Open Energy Information  

Open Energy Info (EERE)

Regional Energy Deployment System (ReEDS) Regional Energy Deployment System (ReEDS) Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Regional Energy Deployment System Agency/Company /Organization: NREL Sector: Energy Topics: Pathways analysis, Resource assessment Resource Type: Software/modeling tools User Interface: Desktop Application Website: www.nrel.gov/analysis/reeds/ OpenEI Keyword(s): EERE tool, Regional Energy Deployment System, ReEDS References: Regional Energy Deployment System (ReEDS) Web site[1] Regional Energy Deployment System (ReEDS) is a multiregional, multitimeperiod, Geographic Information System (GIS), and linear programming model of capacity expansion in the electric sector of the United States. The model, developed by NREL's Strategic Energy Analysis Center (SEAC), is designed to conduct analysis of the critical energy

433

Proceedings of the Northwest regional energy conference  

SciTech Connect

The conference was directed toward two main objectives. First, a major portion of the proceedings were to focus on the policies, programs, and priorities of the new US DOE, and their relationships to the Pacific Northwest region. Second, the conference was to explore specific energy issues of regional significance and provide an opportunity for regional feedback on energy policies. The 10 sessions of the conference are Keynote Session: Congress, and the National Energy Plan Sen. Henry Jackson; National Perspectives on Energy Issues (I): An Overview of the NEP, Programs and Priorities of DOE (Alvin Alm and NEP - Conservation and Solar Applications (Don Beattie); and Luncheon address - Alaska Energy Issues (Robert LeResche); National Perspectives on Energy Issues (II): Utility Rate Reform - National Provisions and Relationships to the Pacific Northwest (David Bardin) and Technology for Energy and Long Term Short Alternatives (Robert Thorne); Concurrent Interest Group Sessions: State and Local Roles in Energy Planning and Decision-Making and Industry and University Roles in DOE Research and Programs; Banquet address. The US Energy Future (James Schlesinger); Regional Perspectives on Energy Issues: DOE-X - Organization and Response to Regional Needs (Randall Hardy). What Comes After Number 13 (Sterling Munro), Hanford 1978 (Alex Fremling), and Low Head Hydro and Geothermal (Richard Wood); Lucheon address - The Washington Perspective on Energy (Dixie Lee Ray); Regional Power Planning (Panel); and Conference Wrap Up Session. (MCW)

Denman, A.S.; Comstock, D.R. (eds.)

1978-12-01T23:59:59.000Z

434

Kitchen Table Strategy: Home Inspectors Driving Demand for Home Energy Upgrades  

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

20/2012 20/2012 1 Benjamin Gromicko, InterNACHI "Kitchen Table" Strategy: Home Inspectors Driving Demand for Home Energy Upgrades 3/20/2012 2 Benjamin Gromicko, InterNACHI "Although the home performance industry's delivery of comprehensive energy and comfort improvements has been growing across the country, it continues to struggle in creating consumer attention and demand. Our industry's delivery timing is off. We are not yet engaging the homeowner at their sweet spot of making improvements -- right after they purchase a home! This is when they move most aggressively with all sorts of home improvement projects -- and, unfortunately, seldom with any concerns of energy use. I strongly believe the home inspection industry is in a prime position to educate new homeowners on the long-term

435

Calculating Energy and Demand Retrofit Savings for Victoria High School: Interim Report  

E-Print Network (OSTI)

As part of the LoanSTAR program, Victoria High School in Victoria, Texas underwent two retrofits: a) an absorption chiller was changed to an electric vapor compression chiller, and b) an EMCS system was installed after about 5 months in the post retrofit period. Moreover, retrofit savings calculation was complex since pre-retrofit data consisted of only monthly utility data while hourly monitored data are available for the post-retrofit period. This report describes the method in which we have performed retrofit energy and demand savings in Victoria High School. A previous report described the procedure adopted when no pre-retrofit data are available. We have only used Unnormalized Utility Bills Comparison ,or the Level-0 approach to determine electricity (energy and demand) and gas energy savings for VHS.

Liu, Y.; Reddy, T. A.; Katipamula, S.; Claridge, D. E.

1992-01-01T23:59:59.000Z

436

Optimal Technology Investment and Operation in Zero-Net-Energy Buildings with Demand Response  

Science Conference Proceedings (OSTI)

The US Department of Energy has launched the Zero-Net-Energy (ZNE) Commercial Building Initiative (CBI) in order to develop commercial buildings that produce as much energy as they use. Its objective is to make these buildings marketable by 2025 such that they minimize their energy use through cutting-edge energy-efficient technologies and meet their remaining energy needs through on-site renewable energy generation. We examine how such buildings may be implemented within the context of a cost- or carbon-minimizing microgrid that is able to adopt and operate various technologies, such as photovoltaic (PV) on-site generation, heat exchangers, solar thermal collectors, absorption chillers, and passive / demand-response technologies. We use a mixed-integer linear program (MILP) that has a multi-criteria objective function: the minimization of a weighted average of the building's annual energy costs and carbon / CO2 emissions. The MILP's constraints ensure energy balance and capacity limits. In addition, constraining the building's energy consumed to equal its energy exports enables us to explore how energy sales and demand-response measures may enable compliance with the CBI. Using a nursing home in northern California and New York with existing tariff rates and technology data, we find that a ZNE building requires ample PV capacity installed to ensure electricity sales during the day. This is complemented by investment in energy-efficient combined heat and power equipment, while occasional demand response shaves energy consumption. A large amount of storage is also adopted, which may be impractical. Nevertheless, it shows the nature of the solutions and costs necessary to achieve ZNE. For comparison, we analyze a nursing home facility in New York to examine the effects of a flatter tariff structure and different load profiles. It has trouble reaching ZNE status and its load reductions as well as efficiency measures need to be more effective than those in the CA case. Finally, we illustrate that the multi-criteria frontier that considers costs and carbon emissions in the presence of demand response dominates the one without it.

Stadler , Michael; Siddiqui, Afzal; Marnay, Chris; ,, Hirohisa Aki; Lai, Judy

2009-05-26T23:59:59.000Z

437

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

E-Print Network (OSTI)

New challenges of Japanese energy efficiency program by Topto 2030 Considering Energy Efficiency Standards Top-Runnerof Energy for Energy Efficiency and Renewable Energy,

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

438

Regional Energy Deployment System (ReEDS)  

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

Regional Energy Deployment Regional Energy Deployment System (ReEDS) Walter Short, Patrick Sullivan, Trieu Mai, Matthew Mowers, Caroline Uriarte, Nate Blair, Donna Heimiller, and Andrew Martinez Technical Report NREL/TP-6A20-46534 December 2011 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401 303-275-3000 * www.nrel.gov Contract No. DE-AC36-08GO28308 Regional Energy Deployment System (ReEDS) Walter Short, Patrick Sullivan, Trieu Mai, Matthew Mowers, Caroline Uriarte, Nate Blair, Donna Heimiller, and Andrew Martinez Prepared under Task Nos. DOCC.1014, SS10.2210,

439

Advanced Control Technologies and Strategies Linking Demand Response and Energy Efficiency  

E-Print Network (OSTI)

Fully Automated Demand Response Tests in Large Facilities.also provided through the Demand Response Research Center (of Fully Automated Demand Response in Large Facilities

Kiliccote, Sila; Piette, Mary Ann

2005-01-01T23:59:59.000Z

440

Advanced Controls and Communications for Demand Response and Energy Efficiency in Commercial Buildings  

E-Print Network (OSTI)

of Fully Automated Demand Response in Large FacilitiesNYSERDA) and the Demand Response Research Center (LLC Working Group 2 Demand Response Program Evaluation

Kiliccote, Sila; Piette, Mary Ann; Hansen, David

2006-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "regional energy 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

Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System  

Science Conference Proceedings (OSTI)

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. The NEMS Commercial Sector Demand Module is a simulation tool based upon economic and engineering relationships that models commercial sector energy demands at the nine Census Division level of detail for eleven distinct categories of commercial buildings. Commercial equipment selections are performed for the major fuels of electricity, natural gas, and distillate fuel, for the major services of space heating, space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The algorithm also models demand for the minor fuels of residual oil, liquefied petroleum gas, steam coal, motor gasoline, and kerosene, the renewable fuel sources of wood and municipal solid waste, and the minor services of office equipment. Section 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMS system. Section 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized in the model development process to this point. Section 3 also reviews alternative commercial sector modeling methodologies drawn from existing literature, providing a comparison to the chosen approach. Section 4 details the model structure, using graphics and text to illustrate model flows and key computations.

NONE

1998-01-01T23:59:59.000Z

442

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

SciTech Connect

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirements of the Energy Information Administration (EIA) to provide adequate documentation in support of its model. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

NONE

1998-01-01T23:59:59.000Z

443

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)

444

Program Strategies and Results for Californias Energy Efficiency and Demand Response Markets  

E-Print Network (OSTI)

Global Energy Partners provides a review of Californias strategic approach to energy efficiency and demand response implementation, with a focus on the industrial sector. The official role of the state, through the California Energy Commission (CEC), is presented along with special efforts being made in support of industrial end users. The interrelationship between the CEC and the California Public Utility Commission (CPUC) with regard to advancing demand side programs is highlighted. The specific cost recovery mechanisms put in place by the CPUC is discussed, including Californias experience with revenue decoupling, public purpose funds, and avoided cost calculations. Next, the role as energy efficiency (EE) and demand response (DR) program implementer played by each of the state Investor Owned Utilities (IOUs) is outlined. Each utility is responsible for serving major end use market segments with target programs designed to provide unique value. Within the industrial sector, there is special attention paid to the needs of the various sub-markets such as oil refining, agriculture, food processing, water and wastewater, manufacturing, and others. A review is presented of how EE and DR measures are selected, how incentive values are determined, which customers are eligible for programs, and how programs are evaluated to gage effectiveness. Lastly, mechanisms used by the IOUs to deliver industrial EE and DR incentive programs are discussed. This includes a review of core programs administered by the utilities as well as subcontracted programs administered by third party implementers and local government partners. Global Energy Partners will offer specific examples of program experience in the oil & gas, agriculture, and food processing sectors, and will also highlight program success within the emerging automated demand response market.

Ehrhard, R.; Hamilton, G.

2008-01-01T23:59:59.000Z

445

Ethanol Demand in United States Regional Production of Oxygenate-limited Gasoline  

DOE Green Energy (OSTI)

The Energy Policy Act of 1992 (the Act) outlined a national energy strategy that called for reducing the nation's dependency on petroleum imports. The Act directed the Secretary of Energy to establish a program to promote and expand the use of renewable fuels. The Office of Transportation Technologies (OTT) within the U.S. Department of Energy (DOE) has evaluated a wide range of potential fuels and has concluded that cellulosic ethanol is one of the most promising near-term prospects. Ethanol is widely recognized as a clean fuel that helps reduce emissions of toxic air pollutants. Furthermore, cellulosic ethanol produces less greenhouse gas emissions than gasoline or any of the other alternative transportation fuels being considered by DOE.

Hadder, G.R.

2000-08-01T23:59:59.000Z

446

Southeast Regional Clean Energy Policy Analysis (Revised)  

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

Southeast Regional Clean Southeast Regional Clean Energy Policy Analysis Revised Joyce McLaren Technical Report NREL/TP-6A20-49192 Revised April 2011 ERRATA SHEET NREL REPORT/PROJECT NUMBER: TP-6A20-49192 TITLE: Southeast Regional Clean Energy Policy Analysis AUTHOR(S): Joyce McLaren ORIGINAL PUBLICATION DATE: January 2011 DATE OF CORRECTIONS (MM/YYYY): 04/2011 The following figures and tables were replaced: Page vii, Figure ES-2 Page ix, Table ES-1 Page 12, Table 1 Page 20, Figure 10 Page 51, Table 11 Page 52, Figure 18 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401

447

Advanced Controls and Communications for Demand Response and Energy Efficiency in Commercial Buildings  

E-Print Network (OSTI)

all the test days and maximum demand savings for the bestin Table 4. Average Maximum Demand Demand Savings SavingsTable 4. Average and maximum demand savings results from

Kiliccote, Sila; Piette, Mary Ann; Hansen, David

2006-01-01T23:59:59.000Z

448

Assessment of Achievable Potential from Energy Efficiency and Demand Response Programs for the Tennessee Valley Authority  

Science Conference Proceedings (OSTI)

This report documents the results of a study to assess the achievable potential for electricity energy savings and peak demand reductions for the Tennessee Valley Authority (TVA) for 2010-2030. The approach involved applying the methodology and technology data developed for the Electric Power Research Institute (EPRI) National Study on the same subject (product number 1016987), adapted to the specific market sector characteristics of the Tennessee Valley. The efficient technologies and measures considere...

2010-03-24T23:59:59.000Z

449

Policy implications of the GRI Baseline Projection of US Energy Supply and Demand to 2010; 1991  

Science Conference Proceedings (OSTI)

The 1991 edition of the GRI Baseline Projection of U.S. Energy Supply and Demand is summarized. Three broad implications for the future of the natural gas industry are highlighted: the impact of the Middle East turmoil on the expected price of crude oil and the potentional for increased interfuel price competition between natural gas and petroleum in the mid-1990s if world oil prices return to lower levels.

Not Available

1990-12-01T23:59:59.000Z

450

The effects of regional climate change on space conditioning needs and the energy industry in the Great Lakes region  

Science Conference Proceedings (OSTI)

To date, studies of the effects of potential climate change on energy use and demand have been done on a macro scale or with coarse model data but, in reality, regional climate change effects will determine the actual behavior of energy users. The output from a 3-year simulation of the coupled NCAR CCM/MM4 regional climate modeling system is used to examine changes in average temperature and temperature variability on a regional scale, the impacts of such change on the need for space conditioning in the Great Lakes region, and the subsequent changes in energy demand. The NCAR modeling system uses general circulation model results to drive a more highly resolved mesoscale model to produce a detailed regional climate. A 3-year run of both base case and doubled CO{sub 2} climate for the United States has been produced. From these results, changes in heating and cooling degree days, and changes in consecutive days above or below various temperature thresholds were calculated. Heating and cooling energy use intensities that are representative of the residential building stock found in the region were used to convert climate data to energy demand. The implications for the energy industry are discussed. The model results indicate that the changed climate under doubled carbon dioxide conditions would have large impacts on energy use, although it is difficult to determine the balance between decreased heating needs and increased cooling needs. It was found that biases present in the temperature output of the modeling system are greater for the Great Lakes region than for the rest of the U.S. and limit the usefulness of the present data set for determining the effects of climate change on energy use in that area.

Fernau, M.E.; Maloney, E.D. [Argonne National Lab., IL (United States); Bates, G.T. [National Center for Atmospheric Research, Boulder, CO (United States)

1993-12-31T23:59:59.000Z

451

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

Science Conference Proceedings (OSTI)

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

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

1986-02-01T23:59:59.000Z

452

Regions in Energy Market Models  

DOE Green Energy (OSTI)

This report explores the different options for spatial resolution of an energy market model--and the advantages and disadvantages of models with fine spatial resolution. It examines different options for capturing spatial variations, considers the tradeoffs between them, and presents a few examples from one particular model that has been run at different levels of spatial resolution.

Short, W.

2007-02-01T23:59:59.000Z

453

Demand Side Energy Saving though Proper Construction Practices and Materials Selection  

E-Print Network (OSTI)

Energy consumed during the construction of buildings and structures, including the embodied energy of the concrete and other construction materials, represent a considerable percentage that may reach 40% of the total energy consumed during the whole service life of the structure. Reducing energy consumed in the construction practices along with reducing the embodied energy of concrete and building materials, therefore, are of major importance. Reducing concrete's embodied energy represents one of the major green features of buildings and an important tool to improve sustainability, save resources for coming generations and reduce greenhouse gas emissions. In this paper, different methods to reduce concrete's embodied energy are discussed and their effect on demand side energy are assessed. Using local materials, pozzolanic blended cements, fillers, along with specifying 56 days strength in design are discussed and assessed. Proper mix design, quality control and proper architectural design also affect and reduce embodied energy. Improving durability, regular maintenance and scheduled repair are essential to increase the expected service life of buildings and hence reduce overall resources consumption and reduce energy. These effects are discussed and quantified. Construction practices also consume considerable amount of energy. The effect of transporting, conveying, pouring, finishing and curing concrete on energy consumption are also discussed.

El-Hawary, M.

2010-01-01T23:59:59.000Z

454

A Successful Case Study of Small Business Energy Efficiency and Demand Response with Communicating Thermostats  

Science Conference Proceedings (OSTI)

This report documents a field study of 78 small commercial customers in the Sacramento Municipal Utility District service territory who volunteered for an integrated energy-efficiency/demand-response (EE-DR) program in the summer of 2008. The original objective for the pilot was to provide a better understanding of demand response issues in the small commercial sector. Early findings justified a focus on offering small businesses (1) help with the energy efficiency of their buildings in exchange for occasional load shed, and (2) a portfolio of options to meet the needs of a diverse customer sector. To meet these expressed needs, the research pilot provided on-site energy efficiency advice and offered participants several program options, including the choice of either a dynamic rate or monthly payment for air-conditioning setpoint control. Overall results show that pilot participants had energy savings of 20%, and the potential for an additional 14% to 20% load drop during a 100 F demand response event. In addition to the efficiency-related bill savings, participants on the dynamic rate saved an estimated 5% on their energy costs compared to the standard rate. About 80% of participants said that the program met or surpassed their expectations, and three-quarters said they would probably or definitely participate again without the $120 participation incentive. These results provide evidence that energy efficiency programs, dynamic rates and load control programs can be used concurrently and effectively in the small business sector, and that communicating thermostats are a reliable tool for providing air-conditioning load shed and enhancing the ability of customers on dynamic rates to respond to intermittent price events.

Herter, Karen; Wayland, Seth; Rasin, Josh

2009-08-12T23:59:59.000Z

455

Energy Department Announces Regional Winners of University Clean Energy  

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

Regional Winners of University Clean Regional Winners of University Clean Energy Business Competition Energy Department Announces Regional Winners of University Clean Energy Business Competition May 13, 2013 - 10:22am Addthis News Media Contact (202) 586-4940 WASHINGTON - Underscoring the Obama Administration's commitment to support the next generation of energy leaders, the U.S. Energy Department today announced the six regional winners of its National Clean Energy Business Plan Competition. The initiative inspires university teams across the country to create new businesses and commercialize promising energy technologies developed at U.S. universities and the National Laboratories. Today's regional finalists - Northwestern University, North Carolina A&T University, Purdue University, Brigham Young University, University of

456

Energy Department Announces Regional Winners of University Clean Energy  

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

Regional Winners of University Clean Regional Winners of University Clean Energy Business Competitions Energy Department Announces Regional Winners of University Clean Energy Business Competitions May 4, 2012 - 11:00am Addthis WASHINGTON, D.C. - Underscoring the Obama Administration's commitments to keep college affordable for American families and students and support the next generation of energy leaders, the U.S. Energy Department today announced the regional winners of its National Clean Energy Business Plan Competition. The initiative inspires university teams across the country to create new businesses and commercialize promising energy technologies developed at U.S. universities and the National Laboratories. Today's regional finalists - Northwestern University, University of Utah, University of Central Florida, MIT, Stanford University and Columbia

457

CONSULTANT REPORT DEMAND FORECAST EXPERT  

E-Print Network (OSTI)

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

458

Web-based energy information systems for energy management and demand response in commercial buildings  

E-Print Network (OSTI)

market Energy providers Target users Program manager (energy provider), energy manager (customer) Commercialization Data Access Trendmarket Energy service providers, utilities Target users Energy manager, operator Commercialization Data Access Trend

Motegi, Naoya; Piette, Mary Ann; Kinney, Satkartar; Herter, Karen

2003-01-01T23:59:59.000Z

459

Policy implications of the GRI baseline projection of US energy supply and demand to 2015, 1997  

SciTech Connect

The summary of the 1997 Edition of the GRI Baseline Projection of U.S. Energy Supply and Demand discusses the implications of the projection that are important for GRI strategic planning and scenario development, and for the gas industry. The projection indicates that with adequate technology advances, natural gas will play a major role in an increasingly competitive energy mix well into the next century. It is expected that the expansion in gas markets experienced over the last decade will continue over the long term.

NONE

1997-03-01T23:59:59.000Z

460

The Window Market in Texas: Opportunities for Energy Savings and Demand Reduction  

E-Print Network (OSTI)

The use of high performance windows represents a promising opportunity to reduce energy consumption and summer electrical demand in homes and commercial buildings in Texas and neighboring states. While low-e glass coatings and other energy efficiency features have become standard features in windows in states with building energy codes, their sales in the Texas market remain limited. This paper presents findings from a pilot energy efficiency program sponsored by American Electric Power Company (AEP). The Texas Window Initiative (TWI) has conducted over 160 on-site training sessions for hardware store sales personnel and builders across the AEP service areas in Texas over the past two years. Companion promotional activities have also been completed. The past one and a half years have witnessed a very significant increase in the market penetration of energy efficient windows in the AEP service area; from about 2.5% of total window sales in early 2000 to roughly 25% (according to preliminary data) by the end of 2001.1 Some of this increase is attributable to TWI's activities, although other factors may be responsible for a portion of this increase as well. The market for windows in Texas is described. TWI's approach to promoting energy efficient windows is reviewed. Initial impact estimates from TWI's activities are presented. The technical potential for energy savings and utility peak demand reduction from the installation of energy efficient windows in Texas is presented. The paper also provides some speculation on how the window market might be impacted by the adoption of building energy codes in Texas.

Zarnikau, J.; Campbell, L.

2002-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "regional energy 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

World Energy Consumption by Region, 1970-2020  

Gasoline and Diesel Fuel Update (EIA)

for the developing world. In particular, energy demand in developing Asia (including China, India, and South Korea, but excluding Australia, Japan, and New Zealand) and Central...

462

Web-based energy information systems for energy management and demand response in commercial buildings  

E-Print Network (OSTI)

2002). 2. Market Categorization Energy Information Systemsincreasing market for energy-related information services (Information Service area Allover US Service started Cost Target market Energy

Motegi, Naoya; Piette, Mary Ann; Kinney, Satkartar; Herter, Karen

2003-01-01T23:59:59.000Z

463

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

E-Print Network (OSTI)

economy, demography and energy prices, which implies thatgrowth, demography, energy prices, and climate on the futuredemand is determined by energy price indicators, taking into

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

464

Web-based energy information systems for energy management and demand response in commercial buildings  

E-Print Network (OSTI)

and Renewable Energy, Building Technologies Program, of theand Renewable Energy, Building Technologies Program, of theprogram managers and building energy managers by allowing

Motegi, Naoya; Piette, Mary Ann; Kinney, Satkartar; Herter, Karen

2003-01-01T23:59:59.000Z

465

Web-based energy information systems for energy management and demand response in commercial buildings  

E-Print Network (OSTI)

also known as EMS (Energy Management Systems), BMS (Buildingfacility operator or energy management systems, often wasteand Control Systems Energy Management Systems Environmental

Motegi, Naoya; Piette, Mary Ann; Kinney, Satkartar; Herter, Karen

2003-01-01T23:59:59.000Z

466

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

467

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

SciTech Connect

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

NONE

1995-03-01T23:59:59.000Z

468

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

Science Conference Proceedings (OSTI)

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

NONE

1997-01-01T23:59:59.000Z

469

Web-based energy information systems for energy management and demand response in commercial buildings  

E-Print Network (OSTI)

and benchmark energy use among a portfolio of sites by plotting energy-use data for multiple buildings and

Motegi, Naoya; Piette, Mary Ann; Kinney, Satkartar; Herter, Karen

2003-01-01T23:59:59.000Z

470

Optimal energy management of a micro-grid with renewable energy resources and demand response  

Science Conference Proceedings (OSTI)

With the introduction of smart energy grids and extensive penetration of renewable energy resources in distribution networks

2013-01-01T23:59:59.000Z

471

Electrical energy and demand savings from a geothermal heat pump energy savings performance contract at Ft. Polk, LA  

SciTech Connect

At Fort Polk, LA the space conditioning systems of an entire city (4,003 military family housing units) have been converted to geothermal heat pumps (GHP) under an energy savings performance contract. At the same time, other efficiency measures such as compact fluorescent lights (CFLs), low-flow hot water outlets, and attic insulation were installed. Pre- and post-retrofit data were taken at 15-minute intervals on energy flows through the electrical distribution feeders that serve the family housing areas of the post. 15-minute interval data was also taken on energy use from a sample of the residences. This paper summarizes the electrical energy and demand savings observed in this data. Analysis of feeder-level data shows that for a typical year, the project will result in a 25.6 million kWh savings in electrical energy use, or 32.4% of the pre-retrofit electrical consumption in family housing. Results from analysis of building-level data compare well with this figure. Analysis of feeder-level data also shows that the project has resulted in a reduction of peak electrical demand of 6,541 kW, which is 39.6% of the pre-retrofit peak electrical demand. In addition to these electrical savings, the facility is also saving an estimated 260,000 therms per year of natural gas. It should be noted that the energy savings presented in this document are the apparent energy savings observed in the monitored data, and are not to be confused with the contracted energy savings used as the basis for payments. To determine the contracted energy savings, the apparent energy savings may require adjustments for such things as changes in indoor temperature performance criteria, additions of ceiling fans, and other factors.

Shonder, J.A.; Hughes, P.J.

1997-06-01T23:59:59.000Z

472

Improving Regional Air Quality with Wind Energy  

DOE Green Energy (OSTI)

This model documentation is designed to assist State and local governments in pursuing wind energy purchases as a control measure under regional air quality plans. It is intended to support efforts to draft State Implementation Plans (SIPs), including wind energy purchases, to ensure compliance with the standard for ground-level ozone established under the Clean Air Act.

Not Available

2005-05-01T23:59:59.000Z

473

Mid-Atlantic Regional Wind Energy Institute  

DOE Green Energy (OSTI)

As the Department of Energy stated in its 20% Wind Energy by 2030 report, there will need to be enhanced outreach efforts on a national, state, regional, and local level to communicate wind development opportunities, benefits and challenges to a diverse set of stakeholders. To help address this need, PennFuture was awarded funding to create the Mid-Atlantic Regional Wind Energy Institute to provide general education and outreach on wind energy development across Maryland, Virginia, Delaware, Pennsylvania and West Virginia. Over the course of the two-year grant period, PennFuture used its expertise on wind energy policy and development in Pennsylvania and expanded it to other states in the Mid-Atlantic region. PennFuture accomplished this through reaching out and establishing connections with policy makers, local environmental groups, health and economic development organizations, and educational institutions and wind energy developers throughout the Mid-Atlantic region. PennFuture conducted two regional wind educational forums that brought together wind industry representatives and public interest organizations from across the region to discuss and address wind development in the Mid-Atlantic region. PennFuture developed the agenda and speakers in collaboration with experts on the ground in each state to help determine the critical issue to wind energy in each location. The sessions focused on topics ranging from the basics of wind development; model ordinance and tax issues; anti-wind arguments and counter points; wildlife issues and coalition building. In addition to in-person events, PennFuture held three webinars on (1) Generating Jobs with Wind Energy; (2) Reviving American Manufacturing with Wind Power; and (3) Wind and Transmission. PennFuture also created a web page for the institute (http://www.midatlanticwind.org) that contains an online database of fact sheets, research reports, sample advocacy letters, top anti-wind claims and information on how to address them, wind and wildlife materials and sample model ordinances. Video and presentations from each in-person meeting and webinar recordings are also available on the site. At the end of the two-year period, PennFuture has accomplished its goal of giving a unified voice and presence to wind energy advocates in the Mid-Atlantic region. We educated a broad range of stakeholders on the benefits of wind energy and gave them the tools to help make a difference in their states. We grew a database of over 500 contacts and hope to continue the discussion and work around the importance of wind energy in the region.

Courtney Lane

2011-12-20T23:59:59.000Z

474

Lake Region State College | Open Energy Information  

Open Energy Info (EERE)

College College Jump to: navigation, search Name Lake Region State College Facility Lake Region State College Sector Wind energy Facility Type Community Wind Facility Status In Service Owner Lake Region State College Developer Lake Region State College Energy Purchaser Lake Region State College Location Devils Lake ND Coordinates 48.166071°, -98.864529° 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":48.166071,"lon":-98.864529,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

475

Chapter 10, Peak Demand and Time-Differentiated Energy Savings Cross-Cutting Protocols: The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures  

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

0: Peak Demand and 0: Peak Demand and Time-Differentiated Energy Savings Cross-Cutting Protocols Frank Stern, Navigant Consulting Subcontract Report NREL/SR-7A30-53827 April 2013 The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures 10 - 1 Chapter 10 - Table of Contents 1 Introduction .............................................................................................................................2 2 Purpose of Peak Demand and Time-differentiated Energy Savings .......................................3 3 Key Concepts ..........................................................................................................................5 4 Methods of Determining Peak Demand and Time-Differentiated Energy Impacts ...............7

476

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

477

Intelligent energy management: impact of demand response and plug-in electric vehicles in a smart grid environment  

Science Conference Proceedings (OSTI)

Modernization of the power grid to meet the growing demand requires significant amount of operational, technological, and infrastructural overhaul. The Department of Energy's "Grid 2030" strategic vision outlines the action plan to alleviate the concerns ... Keywords: controlled charging, demand response, plug in hybrid electric vehicles, smart grid

Seshadri Srinivasa Raghavan; Alireza Khaligh

2012-03-01T23:59:59.000Z

478

Demand Responsive and Energy Efficient Control Technologies and Strategies in Commercial Buildings  

E-Print Network (OSTI)

12 Table 4. Average and Maximum Demand Savings Results fromall the test days and maximum demand savings for the best4. Table 4. Average and Maximum Demand Savings Results from

Piette, Mary Ann; Kiliccote, Sila

2006-01-01T23:59:59.000Z

479

Advanced Control Technologies and Strategies Linking Demand Response and Energy Efficiency  

E-Print Network (OSTI)

and M.A. Piette, J. Braun Peak Demand Reduction from Pre-to reduce Electrical Peak Demands in Commercial BuildingsManagement (Daily) - TOU - Peak Demand Charges - Grid Peak -

Kiliccote, Sila; Piette, Mary Ann

2005-01-01T23:59:59.000Z

480

Optimal Technology Investment and Operation in Zero-Net-Energy Buildings with Demand Response  

E-Print Network (OSTI)

electricity ($/kWh) demand ($/kW) natural gas 0.035 forelectricity ($/kWh) demand ($/kW) natural gas $/kWh $/thermnatural gas tariff combined with the almost constant demand

Stadler, Michael

2009-01-01T23:59:59.000Z