Powered by Deep Web Technologies
Note: This page contains sample records for the topic "type demand region" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

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

2

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

3

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...

4

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.

5

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

6

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

7

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

8

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

9

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

10

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)"

11

"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"

12

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"

13

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

14

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

15

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

16

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

17

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

18

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

19

"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"

20

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

Note: This page contains sample records for the topic "type demand region" 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

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

22

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

23

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

24

Region Type Checking for Core-Java  

E-Print Network (OSTI)

Region-based memory management offers several important advantages over garbage-collected heap, including real-time performance, better data locality and efficient use of limited memory. The concept of regions was first ...

Chin, Wei Ngan

25

Synoptic Weather Types for the Ross Sea Region, Antarctica  

Science Conference Proceedings (OSTI)

Synoptic classifications over the Southern Ocean in the Ross Sea region of Antarctica (50°S–Antarctic coast, 150°E–90°W) have been derived from NCEP reanalysis data (1979–2011), producing a set of six synoptic types for the region. These types ...

Lana Cohen; Sam Dean; James Renwick

2013-01-01T23:59:59.000Z

26

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

27

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 ...

28

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

30

File:Impacts of Regional Electricity Prices and Building Type...  

Open Energy Info (EERE)

History Share this page on Facebook icon Twitter icon File:Impacts of Regional Electricity Prices and Building Type on the Economics of Commercial PV Systems NREL 2012.pdf...

31

Demand Response Spinning Reserve  

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

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

32

Demand Response and Open Automated Demand Response Opportunities...  

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

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

33

Ergodic distribution for a fuzzy inventory model of type (s,S) with gamma distributed demands  

Science Conference Proceedings (OSTI)

In this study, a stochastic process (X(t)), which describes a fuzzy inventory model of type (s,S) is considered. Under some weak assumptions, the ergodic distribution of the process X(t) is expressed by a fuzzy renewal function U(x). Then, membership ... Keywords: Ergodic distribution, Fuzzy inventory model of type (s,S), Fuzzy renewal function, Gamma distribution with fuzzy parameter

Tahir Khaniyev; I. Burhan Turksen; Fikri Gokpinar; Basak Gever

2013-02-01T23:59:59.000Z

34

Regional load-curve models: QUERI's model long-run forecasts and sensitivity analysis. Volume 4. Final report. [Hourly demand in 32 US regions  

SciTech Connect

This report presents detailed forecasts of the hourly demand for electricity in 32 regions of the US through the year 2000. The forecasts are generated by a load curve model estimated by QUERI and described in Volume II of this report. Two primary sets of input assumptions for this model are utilized: one based on DRI's macro, regional and sectoral models is called the Baseline Scenario while the other, which is a projection of historical trends, is the Extrapolation Scenario. Under both assumptions, the growth rates of electricity are forecast to slow from historical levels. Load factors are generally projected to continue to decline; most regions are forecast to remain Summer peaking but this is rather sensitive to the choice of scenario. By considering other scenarios which are small perturbations of the Baseline assumptions, elasticities of average, peak and hourly loads are calculated. Different weather assumptions are also examined for the sensitivity of the load shapes to changes in the weather.

Engle, R.F.; Granger, C.W.J.; Ramanathan, R.

1981-09-01T23:59:59.000Z

35

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

36

Demand Trading: Building Liquidity  

Science Conference Proceedings (OSTI)

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

2002-11-27T23:59:59.000Z

37

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

38

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

39

On Demand Guarantees in Iran.  

E-Print Network (OSTI)

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

Ahvenainen, Laura

2009-01-01T23:59:59.000Z

40

Demand Response  

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

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

Note: This page contains sample records for the topic "type demand region" 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

Demand Response  

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

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

42

Demand Response Quick Assessment Tool (DRQAT)  

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

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

43

Retail Demand Response in Southwest Power Pool  

E-Print Network (OSTI)

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

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

44

Mass Market Demand Response  

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

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

45

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...

46

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...

47

Multiphase Saturation Equations, Change of Type and Inaccessible Regions  

E-Print Network (OSTI)

We identify a class of flux functions which give rise to conservation laws which are hyperbolic except along a codimension one subspace of state space. We show that a number of systems modelling porous medium flow can be regarded as perturbations of such systems, and describe the phenomenon of change of type for these perturbations.

Barbara Lee Keyfitz

1993-01-01T23:59:59.000Z

48

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

49

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

E-Print Network (OSTI)

concerns during system peak demand conditions, and failurerelative to national peak demand, was about 5.0% in 2006 [2]to a region’s summer peak demand (see Fig. 2). Demand

Cappers, Peter

2009-01-01T23:59:59.000Z

50

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

51

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

52

Demand Response as a System Reliability Resource  

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

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

53

Impacts of Regional Electricity Prices and Building Type on the Economics of Commercial Photovoltaic Systems  

DOE Green Energy (OSTI)

To identify the impacts of regional electricity prices and building type on the economics of solar photovoltaic (PV) systems, 207 rate structures across 77 locations and 16 commercial building types were evaluated. Results for expected solar value are reported for each location and building type. Aggregated results are also reported, showing general trends across various impact categories.

Ong, S.; Campbell, C.; Clark, N.

2012-12-01T23:59:59.000Z

54

Transportation Demand This  

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

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

55

demand | OpenEI  

Open Energy Info (EERE)

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

56

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

57

Automated Demand Response and Commissioning  

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

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

58

AEO2011: Coal Production by Region and Type This dataset comes...  

Open Energy Info (EERE)

by Region and Type This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is Table 140,...

59

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

60

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.

Note: This page contains sample records for the topic "type demand region" 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

Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

62

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.

63

AEO2011: Coal Production by Region and Type | OpenEI  

Open Energy Info (EERE)

by Region and Type by Region and Type Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is Table 140, and contains only the reference case. The unit of measurement in this dataset is million short tons. The data is broken down into northern Appalachia, central Appalachia, southern Appalachia, eastern interior, western interior, gulf, Dakota medium, western montana, Wyoming, Rocky Mountain, Arizona/New Mexico and Washington/Alaska. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO Coal Production EIA Data application/vnd.ms-excel icon AE2011: Coal Production by Region and Type- Reference Case (xls, 122.3 KiB)

64

AEO2011: Coal Minemouth Prices by Region and Type | OpenEI  

Open Energy Info (EERE)

Minemouth Prices by Region and Type Minemouth Prices by Region and Type Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is Table 141, and contains only the reference case. The dataset uses million short tons and the US Dollar. The data is broken down into northern Appalachia, central Appalachia, southern Appalachia, eastern interior, western interior, Gulf, Dakota medium, western Montana, Wyoming, Rocky Mountain, Arizona/New Mexico and Washington/Alaska. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO Coal Minemouth Prices EIA Data application/vnd.ms-excel icon AEO2011: Coal Minemouth Prices by Region and Type- Reference Case (xls, 121.6 KiB)

65

Demand Response  

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

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

66

Demand Response Programs, 6. edition  

Science Conference Proceedings (OSTI)

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

NONE

2007-10-15T23:59:59.000Z

67

Travel Demand Modeling  

SciTech Connect

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

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

2011-01-01T23:59:59.000Z

68

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

69

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

70

Thermophotovoltaic energy conversion system having a heavily doped n-type region  

DOE Patents (OSTI)

A thermophotovoltaic (TPV) energy conversion semiconductor device is provided which incorporates a heavily doped n-type region and which, as a consequence, has improved TPV conversion efficiency. The thermophotovoltaic energy conversion device includes an emitter layer having first and second opposed sides and a base layer in contact with the first side of the emitter layer. A highly doped n-type cap layer is formed on the second side of the emitter layer or, in another embodiment, a heavily doped n-type emitter layer takes the place of the cap layer.

DePoy, David M. (Clifton Park, NY); Charache, Greg W. (Clifton Park, NY); Baldasaro, Paul F. (Clifton Park, NY)

2000-01-01T23:59:59.000Z

71

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

72

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)

73

High Temperatures & Electricity Demand  

E-Print Network (OSTI)

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

74

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

75

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

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

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

76

" by Type of Supplier, Census Region, Census Division, Industry Group,"  

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

3. Average Prices of Purchased Electricity and Steam" 3. Average Prices of Purchased Electricity and Steam" " by Type of Supplier, Census Region, Census Division, Industry Group," " and Selected Industries, 1994" " (Estimates in Dollars per Physical Units)" ,," Electricity",," Steam" ,," (kWh)",," (million Btu)" ,,,,,,"RSE" "SIC",,"Utility","Nonutility","Utility","Nonutility","Row" "Code(a)","Industry Group and Industry","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors"

77

CO2 Monitoring for Demand Controlled Ventilation in Commercial...  

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

CO2 Monitoring for Demand Controlled Ventilation in Commercial Buildings Title CO2 Monitoring for Demand Controlled Ventilation in Commercial Buildings Publication Type Report Year...

78

Findings from the 2004 Fully Automated Demand Response Tests...  

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

the 2004 Fully Automated Demand Response Tests in Large Facilities Title Findings from the 2004 Fully Automated Demand Response Tests in Large Facilities Publication Type Report...

79

Assessing the Control Systems Capacity for Demand Response in...  

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

the Control Systems Capacity for Demand Response in California Industries Title Assessing the Control Systems Capacity for Demand Response in California Industries Publication Type...

80

Hawaiian Electric Company Demand Response Roadmap Project Final...  

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

Hawaiian Electric Company Demand Response Roadmap Project Final Report Title Hawaiian Electric Company Demand Response Roadmap Project Final Report Publication Type Report LBNL...

Note: This page contains sample records for the topic "type demand region" 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

LEED Demand Response Credit: A Plan for Research towards Implementatio...  

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

LEED Demand Response Credit: A Plan for Research towards Implementation Title LEED Demand Response Credit: A Plan for Research towards Implementation Publication Type Conference...

82

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...

83

Microgrid Dispatch for Macrogrid Peak-Demand Mitigation  

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

Dispatch for Macrogrid Peak-Demand Mitigation Title Microgrid Dispatch for Macrogrid Peak-Demand Mitigation Publication Type Conference Proceedings Refereed Designation Refereed...

84

building demand | OpenEI  

Open Energy Info (EERE)

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

85

Advanced Demand Responsive Lighting  

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

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

86

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...

87

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...

88

Assessment of Industrial Load for Demand Response across Western Interconnect  

SciTech Connect

Demand response (DR) has the ability to both increase power grid reliability and potentially reduce operating system costs. Understanding the role of demand response in grid modeling has been difficult due to complex nature of the load characteristics compared to the modeled generation and the variation in load types. This is particularly true of industrial loads, where hundreds of different industries exist with varying availability for demand response. We present a framework considering industrial loads for the development of availability profiles that can provide more regional understanding and can be inserted into analysis software for further study. The developed framework utilizes a number of different informational resources, algorithms, and real-world measurements to perform a bottom-up approach in the development of a new database with representation of the potential demand response resource in the industrial sector across the U.S. This tool houses statistical values of energy and demand response (DR) potential by industrial plant and geospatially locates the information for aggregation for different territories without proprietary information. This report will discuss this framework and the analyzed quantities of demand response for Western Interconnect (WI) in support of evaluation of the cost production modeling with power grid modeling efforts of demand response.

Alkadi, Nasr E [ORNL] [ORNL; Starke, Michael R [ORNL] [ORNL; Ma, Ookie [United States Department of Energy (DOE), Office of Efficiency and Renewable Energy (EERE)] [United States Department of Energy (DOE), Office of Efficiency and Renewable Energy (EERE)

2013-11-01T23:59:59.000Z

89

Demand Response and Open Automated Demand Response Opportunities...  

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

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

90

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

91

EIA - AEO2010 - Electricity Demand  

Gasoline and Diesel Fuel Update (EIA)

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

92

The peculiar motions of early-type galaxies in two distant regions - II. The spectroscopic data  

E-Print Network (OSTI)

We present the spectroscopic data for the galaxies studied in the EFAR project, which is designed to measure the properties and peculiar motions of early-type galaxies in two distant regions. We have obtained 1319 spectra of 714 early-type galaxies over 33 observing runs on 10 different telescopes. We describe the observations and data reductions used to measure redshifts, velocity dispersions and the Mgb and Mg2 Lick linestrength indices. Detailed simulations and intercomparison of the large number of repeat observations lead to reliable error estimates for all quantities. The measurements from different observing runs are calibrated to a common zeropoint or scale before being combined, yielding a total of 706 redshifts, 676 velocity dispersions, 676 Mgb linestrengths and 582 Mg2 linestrengths. The median estimated errors in the combined measurements are dcz=20 km/s, dsigma/sigma=9.1%, dMgb/Mgb=7.2% and dMg2=0.015 mag. Comparison of our measurements with published datasets shows no systematic errors in the redshifts or velocity dispersions and only small zeropoint corrections to bring our linestrengths onto the standard Lick system. We have assigned galaxies to physical clusters by examining the line-of-sight velocity distributions based on EFAR and ZCAT redshifts, together with the projected distributions on the sky. We derive mean redshifts and velocity dispersions for these clusters, which will be used in estimating distances and peculiar velocities and to test for trends in the galaxy population with cluster mass. The spectroscopic parameters presented here for 706 galaxies combine high quality data, uniform reduction and measurement procedures, and detailed error analysis. They form the largest single set of velocity dispersions and linestrengths for early-type galaxies published to date.

Gary Wegner; Matthew Colless; R. P. Saglia; Robert K. McMahan; Roger L. Davies; David Burstein; Glenn Baggley

1998-11-16T23:59:59.000Z

93

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

94

Demand Impacted by Weather  

U.S. Energy Information Administration (EIA)

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

95

Demand Trading Toolkit  

Science Conference Proceedings (OSTI)

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

2001-12-10T23:59:59.000Z

96

Are they equal yet. [Demand side management  

Science Conference Proceedings (OSTI)

Demand-side management (DSM) is considered an important tool in meeting the load growth of many utilities. Northwest regional and utility resource plans forecast demand-side resources to meet from one-half to two-thirds of additional electrical energy needs over the next 10 years. Numerous sources have stated that barriers, both regulatory and financial, exist to utility acquisition of demand-side resources. Regulatory actions are being implemented in Oregon to make demand-side investments competitive with supply-side investments. In 1989, the Oregon Public Utility Commission (PUC) took two actions regarding demand-side investments. The PUC's Order 89-1700 directed utilities to capitalize demand-side investments to properly match amortization expense with the multiyear benefits provided by DSM. The PUC also began an informal investigation concerning incentives for Oregon's regulated electric utilities to acquire demand-side resources.

Irwin, K.; Phillips-Israel, K.; Busch, E.

1994-05-15T23:59:59.000Z

97

Demand Response and Risk Management  

Science Conference Proceedings (OSTI)

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

2008-12-18T23:59:59.000Z

98

Electrical Demand Management  

E-Print Network (OSTI)

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

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

1983-01-01T23:59:59.000Z

99

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

100

Demand Dispatch-Intelligent  

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

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

Note: This page contains sample records for the topic "type demand region" 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

Automated Demand Response and Commissioning  

E-Print Network (OSTI)

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

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

2005-01-01T23:59:59.000Z

102

Demand Response Spinning Reserve Demonstration  

E-Print Network (OSTI)

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

2007-01-01T23:59:59.000Z

103

U.S. Propane Demand  

U.S. Energy Information Administration (EIA)

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

104

Demand Response Valuation Frameworks Paper  

E-Print Network (OSTI)

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

Heffner, Grayson

2010-01-01T23:59:59.000Z

105

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

106

Model documentation report: Short-term Integrated Forecasting System demand model 1985. [(STIFS)  

DOE Green Energy (OSTI)

The Short-Term Integrated Forecasting System (STIFS) Demand Model consists of a set of energy demand and price models that are used to forecast monthly demand and prices of various energy products up to eight quarters in the future. The STIFS demand model is based on monthly data (unless otherwise noted), but the forecast is published on a quarterly basis. All of the forecasts are presented at the national level, and no regional detail is available. The model discussed in this report is the April 1985 version of the STIFS demand model. The relationships described by this model include: the specification of retail energy prices as a function of input prices, seasonal factors, and other significant variables; and the specification of energy demand by product as a function of price, a measure of economic activity, and other appropriate variables. The STIFS demand model is actually a collection of 18 individual models representing the demand for each type of fuel. The individual fuel models are listed below: motor gasoline; nonutility distillate fuel oil, (a) diesel, (b) nondiesel; nonutility residual fuel oil; jet fuel, kerosene-type and naphtha-type; liquefied petroleum gases; petrochemical feedstocks and ethane; kerosene; road oil and asphalt; still gas; petroleum coke; miscellaneous products; coking coal; electric utility coal; retail and general industry coal; electricity generation; nonutility natural gas; and utility petroleum. The demand estimates produced by these models are used in the STIFS integrating model to produce a full energy balance of energy supply, demand, and stock change. These forecasts are published quarterly in the Outlook. Details of the major changes in the forecasting methodology and an evaluation of previous forecast errors are presented once a year in Volume 2 of the Outlook, the Methodology publication.

Not Available

1985-07-01T23:59:59.000Z

107

Two Types of Vertical Electrical Structures in Stratiform Precipitation Regions of Mesoscale Convective Systems  

Science Conference Proceedings (OSTI)

Electric field (E) soundings in the stratiform regions and transition zones of mesoscale convective systems (MCSs) are reported. Most of the E soundings were made during the 1991 Cooperative Oklahoma Profiler Studies (COPS-91). Multiple E ...

Thomas C. Marshall; W. David Rust

1993-11-01T23:59:59.000Z

108

A Pattern Recognition Technique for Distinguishing Surface and Cloud Types in the Polar Regions  

Science Conference Proceedings (OSTI)

Measurement of polar cloud cover is important because of its strong radiative influence on the energy balance of the snow and ice surface. Conventional satellite cloud detection schemes often fail in the polar regions because the visible and ...

Elizabeth Ebert

1987-10-01T23:59:59.000Z

109

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

110

Automated Demand Response and Commissioning  

E-Print Network (OSTI)

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

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

2005-01-01T23:59:59.000Z

111

Multi-commodity allocation for dynamic demands using pagerank vectors  

Science Conference Proceedings (OSTI)

We consider a variant of the contact process concerning multi-commodity allocation on networks. In this process, the demands for several types of commodities are initially given at some specified vertices and then the demands spread interactively on ...

Fan Chung; Paul Horn; Jacob Hughes

2012-06-01T23:59:59.000Z

112

Demand Response Database & Demo  

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

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

113

Tankless Demand Water Heaters  

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

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

114

Residential Sector Demand Module  

Reports and Publications (EIA)

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

Owen Comstock

2012-12-19T23:59:59.000Z

115

Industrial Demand Module  

Reports and Publications (EIA)

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

Kelly Perl

2013-05-14T23:59:59.000Z

116

Industrial Demand Module  

Reports and Publications (EIA)

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

Kelly Perl

2013-09-30T23:59:59.000Z

117

Residential Sector Demand Module  

Reports and Publications (EIA)

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

Owen Comstock

2013-11-05T23:59:59.000Z

118

U.S. Electric Utility Demand-Side Management  

Reports and Publications (EIA)

Final issue of this report. - Presents comprehensive information on electric power industry demand side management (DSM) activities in the United States at the national, regional, and utility levels.

Information Center

2002-12-01T23:59:59.000Z

119

Automated Demand Response Tests  

Science Conference Proceedings (OSTI)

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

2008-12-22T23:59:59.000Z

120

Automated Demand Response Tests  

Science Conference Proceedings (OSTI)

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

2009-03-30T23:59:59.000Z

Note: This page contains sample records for the topic "type demand region" 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

Draft for Public Comment Appendix A. Demand Forecast  

E-Print Network (OSTI)

Draft for Public Comment A-1 Appendix A. Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required component of the Council's Northwest Regional Conservation had a tradition of acknowledging the uncertainty of any forecast of electricity demand and developing

123

A Framework for Evaluating the Cost-effectiveness of Demand Response  

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

A Framework for Evaluating the Cost-effectiveness of Demand Response Title A Framework for Evaluating the Cost-effectiveness of Demand Response Publication Type Report Year of...

124

Demand Response in the West: Lessons for States and Provinces  

SciTech Connect

OAK-B135 This paper is submitted in fulfillment of DOE Grant No. DE-FG03-015F22369 on the experience of western states/provinces with demand response (DR) in the electricity sector. Demand-side resources are often overlooked as a viable option for meeting load growth and addressing the challenges posed by the region's aging transmission system. Western states should work together with utilities and grid operators to facilitate the further deployment of DR programs which can provide benefits in the form of decreased grid congestion, improved system reliability, market efficiency, price stabilization, hedging against volatile fuel prices and reduced environmental impacts of energy production. This report describes the various types of DR programs; provides a survey of DR programs currently in place in the West; considers the benefits, drawbacks and barriers to DR; and presents lessons learned and recommendations for states/provinces.

Douglas C. Larson; Matt Lowry; Sharon Irwin

2004-06-29T23:59:59.000Z

125

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

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

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

126

California Independent System Operator demand response & proxy demand resources  

Science Conference Proceedings (OSTI)

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

John Goodin

2012-01-01T23:59:59.000Z

127

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

128

Using Utility Load Data to Estimate Demand for Space Cooling and Potential for Shiftable Loads  

SciTech Connect

This paper describes a simple method to estimate hourly cooling demand from historical utility load data. It compares total hourly demand to demand on cool days and compares these estimates of total cooling demand to previous regional and national estimates. Load profiles generated from this method may be used to estimate the potential for aggregated demand response or load shifting via cold storage.

Denholm, P.; Ong, S.; Booten, C.

2012-05-01T23:59:59.000Z

129

Supply and demand of lube oils  

Science Conference Proceedings (OSTI)

Lube oil consumption in the world has reached about 40 million tonnes per year, of which 24 million tonnes is used outside the communist areas. There are large regional differences in annual consumption per head from one kilogramme (kg) in India to 35 kg in North America. A statistical analysis of historical data over twenty years in about ninety countries has lead to the conclusion that national income, measured as GDP per head, is the key determinant of total lube oil consumption per head. The functional relationship, however, is different in different countries. Starting from GDP projections until the year 2000, regional forecasts of lube oil demand have been made which show that the share of developing nations outside the communist area in world demand will grow. This will increase the regional imbalance between base oil capacity and demand.

Vlemmings, J.M.L.M.

1988-01-01T23:59:59.000Z

130

Demand Response In California  

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

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

131

Automated Demand Response Today  

Science Conference Proceedings (OSTI)

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

2012-03-29T23:59:59.000Z

132

United States lubricant demand  

Science Conference Proceedings (OSTI)

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

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

1988-01-01T23:59:59.000Z

133

Demand Response Valuation Frameworks Paper  

E-Print Network (OSTI)

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

Heffner, Grayson

2010-01-01T23:59:59.000Z

134

The San Diego Foundation Regional Focus 2050 Study  

E-Print Network (OSTI)

33 Figure 17.  Peak electricity demand forecasts of peak electricity demand in the region, which peak  temperature data and electricity demand as well as a 

2008-01-01T23:59:59.000Z

135

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

E-Print Network (OSTI)

size (average maximum demand) 84 , business type (SIC code),HECO customers’ average maximum demands was not available.to estimate the maximum demand (kW) of each customer.

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

2007-01-01T23:59:59.000Z

136

Demand Response and Storage Integration Study: Markets Report...  

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

and Background Tools and techniques have been developed to help characterize demand response (DR) resources Given diversity in types of DR programs and relative...

137

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

138

Transportation Demand Management Plan  

E-Print Network (OSTI)

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

139

Commercial Sector Demand Module  

Reports and Publications (EIA)

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

Kevin Jarzomski

2012-11-15T23:59:59.000Z

140

Commercial Sector Demand Module  

Reports and Publications (EIA)

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

Kevin Jarzomski

2013-10-10T23:59:59.000Z

Note: This page contains sample records for the topic "type demand region" 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

National Action Plan on Demand Response  

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

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

142

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":""}]}

143

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

144

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

145

Demand Forecast INTRODUCTION AND SUMMARY  

E-Print Network (OSTI)

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

146

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

147

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

148

On Demand Paging Using  

E-Print Network (OSTI)

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

Bluetooth Radios On; Yuvraj Agarwal; Rajesh K. Gupta

2003-01-01T23:59:59.000Z

149

Net Demand3 Production  

E-Print Network (OSTI)

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

J. Thijssen Llc

2011-01-01T23:59:59.000Z

150

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

151

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":""}]}

152

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

153

Ethanol Demand in United States Gasoline Production  

SciTech Connect

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

Hadder, G.R.

1998-11-24T23:59:59.000Z

154

Demand Response Valuation Frameworks Paper  

Science Conference Proceedings (OSTI)

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

Heffner, Grayson

2009-02-01T23:59:59.000Z

155

Dividends with Demand Response  

SciTech Connect

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

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

2003-10-31T23:59:59.000Z

156

Chinese demand drives global deforestation Chinese demand drives global deforestation  

E-Print Network (OSTI)

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

157

Estimating a Demand System with Nonnegativity Constraints: Mexican Meat Demand  

E-Print Network (OSTI)

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

Perloff, Jeffrey M.

158

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

159

Estimation of Demand Responses to Ramp Meters  

E-Print Network (OSTI)

Estimation of Demand Responses to Ramp Meters by Lei Zhang and David Levinson For the 3rd ICTTS different types of trips respond to ramp meters (work vs. non-work; short vs. long) A bill was passed to shut off ramp meters to study effectiveness in the Twin Cities in Spring 2000 The shut-off experiment

Levinson, David M.

160

Climate policy implications for agricultural water demand  

SciTech Connect

Energy, water and land are scarce resources, critical to humans. Developments in each affect the availability and cost of the others, and consequently human prosperity. Measures to limit greenhouse gas concentrations will inevitably exact dramatic changes on energy and land systems and in turn alter the character, magnitude and geographic distribution of human claims on water resources. We employ the Global Change Assessment Model (GCAM), an integrated assessment model to explore the interactions of energy, land and water systems in the context of alternative policies to limit climate change to three alternative levels: 2.5 Wm-2 (445 ppm CO2-e), 3.5 Wm-2 (535 ppm CO2-e) and 4.5 Wm-2 (645 ppm CO2-e). We explore the effects of two alternative land-use emissions mitigation policy options—one which taxes terrestrial carbon emissions equally with fossil fuel and industrial emissions, and an alternative which only taxes fossil fuel and industrial emissions but places no penalty on land-use change emissions. We find that increasing populations and economic growth could be anticipated to almost triple demand for water for agricultural systems across the century even in the absence of climate policy. In general policies to mitigate climate change increase agricultural demands for water still further, though the largest changes occur in the second half of the century, under both policy regimes. The two policies examined profoundly affected both the sources and magnitudes of the increase in irrigation water demands. The largest increases in agricultural irrigation water demand occurred in scenarios where only fossil fuel emissions were priced (but not land-use change emission) and were primarily driven by rapid expansion in bioenergy production. In these scenarios water demands were large relative to present-day total available water, calling into question whether it would be physically possible to produce the associated biomass energy. We explored the potential of improved water delivery and irrigation system efficiencies. These could potentially reduce demands substantially. However, overall demands remained high under our fossil-fuel-only tax policy. In contrast, when all carbon was priced, increases in agricultural water demands were smaller than under the fossil-fuel-only policy and were driven primarily by increased demands for water by non-biomass crops such as rice. Finally we estimate the geospatial pattern of water demands and find that regions such as China, India and other countries in south and east Asia might be expected to experience greatest increases in water demands.?

Chaturvedi, Vaibhav; Hejazi, Mohamad I.; Edmonds, James A.; Clarke, Leon E.; Kyle, G. Page; Davies, Evan; Wise, Marshall A.; Calvin, Katherine V.

2013-03-28T23:59:59.000Z

Note: This page contains sample records for the topic "type demand region" 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

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

162

ELECTRICITY DEMAND FORECAST COMPARISON REPORT  

E-Print Network (OSTI)

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

163

Overview of Demand Response  

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

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

164

EIA - AEO2010 - Natural Gas Demand  

Gasoline and Diesel Fuel Update (EIA)

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

165

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.

166

Resource allocation for demand surge mitigation during disaster response  

Science Conference Proceedings (OSTI)

Large-scale public health emergencies can result in an overwhelming demand for healthcare resources. Regional aid in the form of central stockpiles and resource redistribution can help mitigate the resulting demand surge. This paper discusses a resource ... Keywords: Decision support, Optimization, Pandemic flu, Resource allocation

Hina Arora; T. S. Raghu; Ajay Vinze

2010-12-01T23:59:59.000Z

167

Oxygenate Supply/Demand Balances  

Gasoline and Diesel Fuel Update (EIA)

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

168

Electric Demand Cost Versus Labor Cost: A Case Study  

E-Print Network (OSTI)

Electric Utility companies charge industrial clients for two things: demand and usage. Depending on type of business and hours operation, demand cost could be very high. Most of the operations scheduling in a plant is achieved considering labor cost. For small plants, it is quite possible that a decrease in labor could result in an increase in electric demand and cost or vice versa. In this paper two cases are presented which highlight the dependence of one on other.

Agrawal, S.; Jensen, R.

1998-04-01T23:59:59.000Z

169

U.S. electric utility demand-side management 1993  

SciTech Connect

This report presents comprehensive information on electric power industry demand-side management activities in the United States at the national, regional, and utility levels. Data is included for energy savings, peakload reductions, and costs.

NONE

1995-07-01T23:59:59.000Z

170

U.S. Electric Utility Demand-Side Management  

Reports and Publications (EIA)

Final issue of this report. - 1996 - Presents comprehensive information on electric power industry demand side management (DSM) activities in the United States at the national, regional, and utility levels.

Information Center

1997-12-01T23:59:59.000Z

171

The residential demand for electricity in New England,  

E-Print Network (OSTI)

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

Levy, Paul F.

1973-01-01T23:59:59.000Z

172

Mass Market Demand Response and Variable Generation Integration Issues: A  

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

Mass Market Demand Response and Variable Generation Integration Issues: A Mass Market Demand Response and Variable Generation Integration Issues: A Scoping Study Title Mass Market Demand Response and Variable Generation Integration Issues: A Scoping Study Publication Type Report Refereed Designation Unknown Year of Publication 2011 Authors Cappers, Peter, Andrew D. Mills, Charles A. Goldman, Ryan H. Wiser, and Joseph H. Eto Pagination 76 Date Published 10/2011 Publisher LBNL City Berkeley Keywords demand response, electricity markets and policy group, energy analysis and environmental impacts department, renewable generation integration, smart grid Abstract The penetration of renewable generation technology (e.g., wind, solar) is expected to dramatically increase in the United States during the coming years as many states are implementing policies to expand this sector through regulation and/or legislation. It is widely understood, though, that large scale deployment of certain renewable energy sources, namely wind and solar, poses system integration challenges because of its variable and often times unpredictable production characteristics (NERC, 2009). Strategies that rely on existing thermal generation resources and improved wind and solar energy production forecasts to manage this variability are currently employed by bulk power system operators, although a host of additional options are envisioned for the near future. Demand response (DR), when properly designed, could be a viable resource for managing many of the system balancing issues associated with integrating large-scale variable generation (VG) resources (NERC, 2009). However, demand-side options would need to compete against strategies already in use or contemplated for the future to integrate larger volumes of wind and solar generation resources. Proponents of smart grid (of which Advanced Metering Infrastructure or AMI is an integral component) assert that the technologies associated with this new investment can facilitate synergies and linkages between demand-side management and bulk power system needs. For example, smart grid proponents assert that system-wide implementation of advanced metering to mass market customers (i.e., residential and small commercial customers) as part of a smart grid deployment enables a significant increase in demand response capability.1 Specifically, the implementation of AMI allows electricity consumption information to be captured, stored and utilized at a highly granular level (e.g., 15-60 minute intervals in most cases) and provides an opportunity for utilities and public policymakers to more fully engage electricity customers in better managing their own usage through time-based rates and near-real time feedback to customers on their usage patterns while also potentially improving the management of the bulk power system. At present, development of time-based rates and demand response programs and the installation of variable generation resources are moving forward largely independent of each other in state and regional regulatory and policy forums and without much regard to the complementary nature of their operational characteristics.2 By 2020, the electric power sector is expected to add ~65 million advanced meters3 (which would reach ~47% of U.S. households) as part of smart grid and AMI4 deployments (IEE, 2010) and add ~40-80 GW of wind and solar capacity (EIA, 2010). Thus, in this scoping study, we focus on a key question posed by policymakers: what role can the smart grid (and its associated enabling technology) play over the next 5-10 years in helping to integrate greater penetration of variable generation resources by providing mass market customers with greater access to demand response opportunities? There is a well-established body of research that examines variable generation integration issues as well as demand response potential, but the nexus between the two has been somewhat neglected by the industry. The studies that have been conducted are informative concerning what could be accomplished with strong broad-based support for the expansion of demand response opportunities, but typically do not discuss the many barriers that stand in the way of reaching this potential. This study examines how demand side resources could be used to integrate wind and solar resources in the bulk power system, identifies barriers that currently limit the use of demand side strategies, and suggests several factors that should be considered in assessing alternative strategies that can be employed to integrate wind and solar resources in the bulk power system. It is difficult to properly gauge the role that DR could play in managing VG integration issues in the near future without acknowledging and understanding the entities and institutions that govern the interactions between variable generation and mass market customers (see Figure ES-1). Retail entities, like load-serving entities (LSE) and aggregators of retail customers (ARC), harness the demand response opportunities of mass market customers through tariffs (and DR programs) that are approved by state regulatory agencies or local governing entities (in the case of public power). The changes in electricity consumption induced by DR as well as the changes in electricity production due to the variable nature of wind and solar generation technologies is jointly managed by bulk power system operators. Bulk power system operators function under tariffs approved by the Federal Energy Regulatory Commission (FERC) and must operate their systems in accordance with rules set by regional reliability councils. These reliability rules are derived from enforceable standards that are set by the North American Electric Reliability Corporation (NERC) and approved by federal regulators. Thus, the role that DR can play in managing VG integration issues is contingent on what opportunities state and local regulators are willing to approve and how customers' response to the DR opportunities can be integrated into the bulk power system both electrically (due to reliability rules) and financially (due to market rules).

173

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

174

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

175

Scenario Analysis of Peak Demand Savings for Commercial Buildings with  

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

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

176

Unlocking the potential for efficiency and demand response through advanced  

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

Unlocking the potential for efficiency and demand response through advanced Unlocking the potential for efficiency and demand response through advanced metering Title Unlocking the potential for efficiency and demand response through advanced metering Publication Type Conference Paper LBNL Report Number LBNL-55673 Year of Publication 2004 Authors Levy, Roger, Karen Herter, and John Wilson Conference Name 2004 ACEEE Summer Study on Energy Efficiency in Buildings Date Published 06/2004 Publisher ACEEE Conference Location Pacific Grove, CA Call Number California Energy Commission Keywords demand response, demand response and distributed energy resources center, demand response research center, energy efficiency demand response advanced metering, rate programs & tariffs Abstract Reliance on the standard cumulative kilowatt-hour meter substantially compromises energy efficiency and demand response programs. Without advanced metering, utilities cannot support time-differentiated rates or collect the detailed customer usage information necessary to (1) educate the customer to the economic value of efficiency and demand response options, or (2) distribute load management incentives proportional to customer contribution. These deficiencies prevent the customer feedback mechanisms that would otherwise encourage economically sound demand-side investments and behaviors. Thus, the inability to collect or properly price electricity usage handicaps the success of almost all efficiency and demand response options.

177

Annual World Oil Demand Growth  

Gasoline and Diesel Fuel Update (EIA)

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

178

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.

179

Demand Response Valuation Frameworks Paper  

E-Print Network (OSTI)

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

Heffner, Grayson

2010-01-01T23:59:59.000Z

180

Demand Uncertainty and Price Dispersion.  

E-Print Network (OSTI)

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

Li, Suxi

2007-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "type demand region" 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

1995 Demand-Side Managment  

U.S. Energy Information Administration (EIA)

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

182

Rates and technologies for mass-market demand response  

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

Rates and technologies for mass-market demand response Rates and technologies for mass-market demand response Title Rates and technologies for mass-market demand response Publication Type Conference Paper LBNL Report Number LBNL-50626 Year of Publication 2002 Authors Herter, Karen, Roger Levy, John Wilson, and Arthur H. Rosenfeld Conference Name 2002 ACEEE Summer Study on Energy Efficiency in Buildings Conference Location Pacific Grove, CA Keywords demand response, demand response and distributed energy resources center, demand response research center, rate programs & tariffs Abstract Demand response programs are often quickly and poorly crafted in reaction to an energy crisis and disappear once the crisis subsides, ensuring that the electricity system will be unprepared when the next crisis hits. In this paper, we propose to eliminate the event-driven nature of demand response programs by considering demand responsiveness a component of the utility obligation to serve. As such, demand response can be required as a condition of service, and the offering of demand response rates becomes a requirement of utilities as an element of customer service. Using this foundation, we explore the costs and benefits of a smart thermostat-based demand response system capable of two types of programs: (1) a mandatory, system-operator controlled, contingency program, and (2) a voluntary, customer controlled, bill management program with rate-based incentives. Any demand response program based on this system could consist of either or both of these components. Ideally, these programs would be bundled, providing automatic load management through customer-programmed price response, plus up to 10 GW of emergency load shedding capability in California. Finally, we discuss options for and barriers to implementation of such a program in California.

183

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

184

Wireless Demand Response Controls for HVAC Systems  

E-Print Network (OSTI)

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

Federspiel, Clifford

2010-01-01T23:59:59.000Z

185

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

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

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

186

Installation and Commissioning Automated Demand Response Systems  

E-Print Network (OSTI)

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

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

2008-01-01T23:59:59.000Z

187

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

188

Strategies for Demand Response in Commercial Buildings  

E-Print Network (OSTI)

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

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

2006-01-01T23:59:59.000Z

189

Option Value of Electricity Demand Response  

E-Print Network (OSTI)

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

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

2005-01-01T23:59:59.000Z

190

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

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

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

191

Harnessing the power of demand  

Science Conference Proceedings (OSTI)

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

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

2008-03-15T23:59:59.000Z

192

China, India demand cushions prices  

SciTech Connect

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

Boyle, M.

2006-11-15T23:59:59.000Z

193

Estimating Costs and Efficiency of Storage, Demand, and Heat...  

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

| Chart credit ENERGY STAR Estimating the Cost and Energy Efficiency of a Solar Water Heater Diagram of a tankless water heater. Tankless or Demand-Type Water Heaters Water...

194

Opportunities for Automated Demand Response in Wastewater Treatment  

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

Opportunities for Automated Demand Response in Wastewater Treatment Opportunities for Automated Demand Response in Wastewater Treatment Facilities in California - Southeast Water Pollution Control Plant Case Study Title Opportunities for Automated Demand Response in Wastewater Treatment Facilities in California - Southeast Water Pollution Control Plant Case Study Publication Type Report LBNL Report Number LBNL-6056E Year of Publication 2012 Authors Olsen, Daniel, Sasank Goli, David Faulkner, and Aimee T. McKane Date Published 12/2012 Publisher CEC/LBNL Keywords market sectors, technologies Abstract This report details a study into the demand response potential of a large wastewater treatment facility in San Francisco. Previous research had identified wastewater treatment facilities as good candidates for demand response and automated demand response, and this study was conducted to investigate facility attributes that are conducive to demand response or which hinder its implementation. One years' worth of operational data were collected from the facility's control system, submetered process equipment, utility electricity demand records, and governmental weather stations. These data were analyzed to determine factors which affected facility power demand and demand response capabilities.

195

Demand Response for Ancillary Services  

Science Conference Proceedings (OSTI)

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

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

2013-01-01T23:59:59.000Z

196

China's Coal: Demand, Constraints, and Externalities  

Science Conference Proceedings (OSTI)

This study analyzes China's coal industry by focusing on four related areas. First, data are reviewed to identify the major drivers of historical and future coal demand. Second, resource constraints and transport bottlenecks are analyzed to evaluate demand and growth scenarios. The third area assesses the physical requirements of substituting coal demand growth with other primary energy forms. Finally, the study examines the carbon- and environmental implications of China's past and future coal consumption. There are three sections that address these areas by identifying particular characteristics of China's coal industry, quantifying factors driving demand, and analyzing supply scenarios: (1) reviews the range of Chinese and international estimates of remaining coal reserves and resources as well as key characteristics of China's coal industry including historical production, resource requirements, and prices; (2) quantifies the largest drivers of coal usage to produce a bottom-up reference projection of 2025 coal demand; and (3) analyzes coal supply constraints, substitution options, and environmental externalities. Finally, the last section presents conclusions on the role of coal in China's ongoing energy and economic development. China has been, is, and will continue to be a coal-powered economy. In 2007 Chinese coal production contained more energy than total Middle Eastern oil production. The rapid growth of coal demand after 2001 created supply strains and bottlenecks that raise questions about sustainability. Urbanization, heavy industrial growth, and increasing per-capita income are the primary interrelated drivers of rising coal usage. In 2007, the power sector, iron and steel, and cement production accounted for 66% of coal consumption. Power generation is becoming more efficient, but even extensive roll-out of the highest efficiency units would save only 14% of projected 2025 coal demand for the power sector. A new wedge of future coal consumption is likely to come from the burgeoning coal-liquefaction and chemicals industries. If coal to chemicals capacity reaches 70 million tonnes and coal-to-liquids capacity reaches 60 million tonnes, coal feedstock requirements would add an additional 450 million tonnes by 2025. Even with more efficient growth among these drivers, China's annual coal demand is expected to reach 3.9 to 4.3 billion tonnes by 2025. Central government support for nuclear and renewable energy has not reversed China's growing dependence on coal for primary energy. Substitution is a matter of scale: offsetting one year of recent coal demand growth of 200 million tonnes would require 107 billion cubic meters of natural gas (compared to 2007 growth of 13 BCM), 48 GW of nuclear (compared to 2007 growth of 2 GW), or 86 GW of hydropower capacity (compared to 2007 growth of 16 GW). Ongoing dependence on coal reduces China's ability to mitigate carbon dioxide emissions growth. If coal demand remains on a high growth path, carbon dioxide emissions from coal combustion alone would exceed total US energy-related carbon emissions by 2010. Within China's coal-dominated energy system, domestic transportation has emerged as the largest bottleneck for coal industry growth and is likely to remain a constraint to further expansion. China has a low proportion of high-quality reserves, but is producing its best coal first. Declining quality will further strain production and transport capacity. Furthermore, transporting coal to users has overloaded the train system and dramatically increased truck use, raising transportation oil demand. Growing international imports have helped to offset domestic transport bottlenecks. In the long term, import demand is likely to exceed 200 million tonnes by 2025, significantly impacting regional markets.

Aden, Nathaniel; Fridley, David; Zheng, Nina

2009-07-01T23:59:59.000Z

197

Demand Response Opportunities in Industrial Refrigerated Warehouses...  

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

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

198

Strategies for Demand Response in Commercial Buildings  

E-Print Network (OSTI)

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

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

2006-01-01T23:59:59.000Z

199

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

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

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

200

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

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

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "type demand region" 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

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

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

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

202

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

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

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

203

Pacific Northwest Demand Response Project Lee Hall, BPA Smart Grid Program Manager  

E-Print Network (OSTI)

, and challenging. Bonneville has previously reported to the Council on their role in the regional Smart Grid to reported to the Council on their role in the regional Smart Grid ich includes demand response in 10 to the Council on their role in the regional Smart Grid ich includes demand response in 10 participating

204

Effects of the drought on California electricity supply and demand  

E-Print Network (OSTI)

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

Benenson, P.

2010-01-01T23:59:59.000Z

205

Demand Response Research in Spain  

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

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

206

Winter Demand Impacted by Weather  

Gasoline and Diesel Fuel Update (EIA)

8 Notes: Heating oil demand is strongly influenced by weather. The "normal" numbers are the expected values for winter 2000-2001 used in EIA's Short-Term Energy Outlook. The chart...

207

Demand for money in China .  

E-Print Network (OSTI)

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

Zhang, Qing

2006-01-01T23:59:59.000Z

208

STEO December 2012 - coal demand  

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

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

209

Distillate Demand Strong Last Winter  

Gasoline and Diesel Fuel Update (EIA)

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

210

Thermal Mass and Demand Response  

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

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

211

Automated Demand Response and Commissioning  

E-Print Network (OSTI)

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

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

2005-01-01T23:59:59.000Z

212

Leslie Mancebo (7234) Transportation Demand &  

E-Print Network (OSTI)

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

Hammock, Bruce D.

213

Implementing Innovation in Planning Practice: The Case of Travel Demand Forecasting  

E-Print Network (OSTI)

Urban Travel Demand Forecasting Project. Institute ofTRB. Metropolitan Travel Forecasting: Current Practice andPurvis. Regional Travel Forecasting Model System for the San

Newmark, Gregory Louis

2011-01-01T23:59:59.000Z

214

Demand Response Spinning Reserve Demonstration  

Science Conference Proceedings (OSTI)

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

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

2007-05-01T23:59:59.000Z

215

DOE Hydrogen Analysis Repository: Hydrogen Demand and Infrastructure  

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

Hydrogen Demand and Infrastructure Deployment Hydrogen Demand and Infrastructure Deployment Project Summary Full Title: Geographically-Based Hydrogen Demand and Infrastructure Deployment Scenario Analysis Project ID: 189 Principal Investigator: Margo Melendez Keywords: Hydrogen fueling; infrastructure; fuel cell vehicles (FCV) Purpose This analysis estimates the spatial distribution of hydrogen fueling stations necessary to support the 5 million fuel cell vehicle scenario, based on demographic demand patterns for hydrogen fuel cell vehicles and strategy of focusing development on specific regions of the U.S. that may have high hydrogen demand. Performer Principal Investigator: Margo Melendez Organization: National Renewable Energy Laboratory (NREL) Address: 1617 Cole Blvd. Golden, CO 80401-3393 Telephone: 303-275-4479

216

Price Responsive Demand in New York Wholesale Electricity Market using  

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

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

217

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

218

Measuring Short-term Air Conditioner Demand Reductions for Operations and  

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

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

219

National Action Plan on Demand Response  

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

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

220

A National Forum on Demand Response: What Remains to Be Done to Achieve Its  

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

State and Regional Policy Assistance » Technical Assistance » Demand State and Regional Policy Assistance » Technical Assistance » Demand Response - Policy » A National Forum on Demand Response: What Remains to Be Done to Achieve Its Potential A National Forum on Demand Response: What Remains to Be Done to Achieve Its Potential In July 2011, the Federal Energy Regulatory Commission's (FERC) staff and the Department of Energy (DOE) jointly submitted to Congress a required "Implementation Proposal for the National Action Plan on Demand Response." The Implementation Proposal was for FERC's June 2010 National Action Plan for Demand Response. Part of the July 2011 Implementation Proposal called for a "National Forum" on demand response to be conducted by DOE and FERC. Given the rapid development of the demand response industry, DOE and FERC decided

Note: This page contains sample records for the topic "type demand region" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

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

Gasoline and Diesel Fuel Update (EIA)

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

222

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

Gasoline and Diesel Fuel Update (EIA)

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

223

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

224

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,

225

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

Gasoline and Diesel Fuel Update (EIA)

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

226

Demand Response and Open Automated Demand Response Opportunities for Data Centers  

E-Print Network (OSTI)

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

Mares, K.C.

2010-01-01T23:59:59.000Z

227

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

E-Print Network (OSTI)

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

Kiliccote, Sila

2010-01-01T23:59:59.000Z

228

Successful demand-side management  

Science Conference Proceedings (OSTI)

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

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

1995-05-01T23:59:59.000Z

229

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"

230

Winter Demand Impacted by Weather  

Gasoline and Diesel Fuel Update (EIA)

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

231

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

232

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

233

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

234

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.

235

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.

236

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.

237

Barrier Immune Radio Communications for Demand Response  

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

Barrier Immune Radio Communications for Demand Response Barrier Immune Radio Communications for Demand Response Title Barrier Immune Radio Communications for Demand Response Publication Type Report LBNL Report Number LBNL-2294e Year of Publication 2009 Authors Rubinstein, Francis M., Girish Ghatikar, Jessica Granderson, Paul Haugen, Carlos Romero, and David S. Watson Keywords technologies Abstract Various wireless technologies were field-tested in a six-story laboratory building to identify wireless technologies that can scale for future DR applications through very low node density power consumption, and unit cost. Data analysis included analysis of the signal-to-noise ratio (SNR), packet loss, and link quality at varying power levels and node densities. The narrowband technologies performed well, penetrating the floors of the building with little loss and exhibiting better range than the wideband technology. 900 MHz provided full coverage at 1 watt and substantially complete coverage at 500 mW at the test site. 900 MHz was able to provide full coverage at 100 mW with only one additional relay transmitter, and was the highest-performing technology in the study. 2.4 GHz could not provide full coverage with only a single transmitter at the highest power level tested (63 mW). However, substantially complete coverage was provided at 2.4 GHz at 63 mW with the addition of one repeater node.

238

Projecting market demand for residential heat pumps  

SciTech Connect

Primarily because of technological improvements and sharp increases in energy prices after the 1970s energy crises, the sale of residential electric heat pumps rose ninefold from 1970 to 1983. This report describes current and future market demand for heat pumps used for space heating and cooling. A three-step approach was followed. In the first step, the historical growth of residential electric heat pumps was analyzed, and factors that may have affected market growth were examined. Also examined were installation trends of heat pumps in new single-family and multifamily homes. A market segmentation analysis was used to estimate market size by categories. In the second step, several methods for forecasting future market demand were reviewed and evaluated to select the most suitable one for this study. The discrete-choice approach was chosen. In the third step, a market penetration model based on selected discrete-choice methods was developed to project heat pump demand in key market segments such as home type (single-family or multifamily), new or existing construction, and race-ethnic origin of household (black, Hispanic, or white).

Teotia, A.P.S.; Raju, P.S.; Karvelas, D.; Anderson, J.

1987-04-01T23:59:59.000Z

239

Demand Controlled Filtration in an Industrial Cleanroom  

SciTech Connect

In an industrial cleanroom, significant energy savings were realized by implementing two types of demand controlled filtration (DCF) strategies, one based on particle counts and one on occupancy. With each strategy the speed of the recirculation fan filter units was reduced to save energy. When the control was based on particle counts, the energy use was 60% of the baseline configuration of continuous fan operation. With simple occupancy sensors, the energy usage was 63% of the baseline configuration. During the testing of DCF, no complaints were registered by the operator of the cleanroom concerning processes and products being affected by the DCF implementation.

Faulkner, David; DiBartolomeo, Dennis; Wang, Duo

2007-09-01T23:59:59.000Z

240

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

Note: This page contains sample records for the topic "type demand region" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

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

242

Retail Demand Response in Southwest Power Pool  

E-Print Network (OSTI)

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

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

243

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

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

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

244

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...

245

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

246

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

247

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

248

EIA projections of coal supply and demand  

SciTech Connect

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

Klein, D.E.

1989-10-23T23:59:59.000Z

249

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

250

Electric Utility Demand-Side Management 1997  

U.S. Energy Information Administration (EIA)

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

251

Retail Demand Response in Southwest Power Pool  

E-Print Network (OSTI)

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

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

252

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,...

253

Home Network Technologies and Automating Demand Response  

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

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

254

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

255

Installation and Commissioning Automated Demand Response Systems  

E-Print Network (OSTI)

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

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

2008-01-01T23:59:59.000Z

256

Equity Capital Flows and Demand for REITs  

Science Conference Proceedings (OSTI)

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

257

Option Value of Electricity Demand Response  

E-Print Network (OSTI)

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

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

2005-01-01T23:59:59.000Z

258

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

259

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.

260

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.

Note: This page contains sample records for the topic "type demand region" 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

Water demand management in Kuwait  

E-Print Network (OSTI)

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

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

2006-01-01T23:59:59.000Z

262

Demand-Side Management Glossary  

Science Conference Proceedings (OSTI)

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

1992-11-01T23:59:59.000Z

263

Isospin and symmetry energy effects on nuclear fragment production in liquid-gas type phase transition region  

E-Print Network (OSTI)

We have demonstrated that the isospin of nuclei influences the fragment production during the nuclear liquid-gas phase transition. Calculations for Au197, Sn124, La124 and Kr78 at various excitation energies were carried out on the basis of the statistical multifragmentation model (SMM). We analyzed the behavior of the critical exponent tau with the excitation energy and its dependence on the critical temperature. Relative yields of fragments were classified with respect to the mass number of the fragments in the transition region. In this way, we have demonstrated that nuclear multifragmentation exhibits a 'bimodality' behavior. We have also shown that the symmetry energy has a small influence on fragment mass distribution, however, its effect is more pronounced in the isotope distributions of produced fragments.

N. Buyukcizmeci; R. Ogul; A. S. Botvina

2005-06-06T23:59:59.000Z

264

Isospin and symmetry energy effects on nuclear fragment production in liquid-gas type phase transition region  

E-Print Network (OSTI)

We have demonstrated that the isospin of nuclei influences the fragment production during the nuclear liquid-gas phase transition. Calculations for Au197, Sn124, La124 and Kr78 at various excitation energies were carried out on the basis of the statistical multifragmentation model (SMM). We analyzed the behavior of the critical exponent tau with the excitation energy and its dependence on the critical temperature. Relative yields of fragments were classified with respect to the mass number of the fragments in the transition region. In this way, we have demonstrated that nuclear multifragmentation exhibits a 'bimodality' behavior. We have also shown that the symmetry energy has a small influence on fragment mass distribution, however, its effect is more pronounced in the isotope distributions of produced fragments.

N. Buyukcizmeci; R. Ogul; A. S. Botvina

2004-12-31T23:59:59.000Z

265

ORNL/TM-2000/165 Ethanol Demand in United States  

E-Print Network (OSTI)

ORNL/TM-2000/165 Ethanol Demand in United States Regional Production of Oxygenate-limited Gasoline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 5. THE DEMAND FOR ETHANOL USED IN U.S. REGIONAL OXYGENATE- LIMITED GASOLINE PRODUCTON IN YEAR 2006+III, SUMMER WITH 3 PERCENT MAXIMUM MTBE . . . . . . . . . 54 5.4 PADD I+III, WINTER WITH 3 PERCENT MAXIMUM

266

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

267

Demand Dispatch — Intelligent Demand for a More Efficient Grid  

E-Print Network (OSTI)

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

Keith Dodrill

2011-01-01T23:59:59.000Z

268

The alchemy of demand response: turning demand into supply  

Science Conference Proceedings (OSTI)

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

Rochlin, Cliff

2009-11-15T23:59:59.000Z

269

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.

270

Water Utility Demand Management and the Financial, Social and Environmental  

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

Water Utility Demand Management and the Financial, Social and Environmental Water Utility Demand Management and the Financial, Social and Environmental Drivers Speaker(s): Allan J. Dietemann Date: February 19, 2004 - 12:00pm Location: Bldg. 90 Seminar Host/Point of Contact: Camilla Whitehead At Seattle Public Utilities, Al Dietemann leads a team of 11 persons with a budget of $5 million a year implementing cost-effective resource conservation measures. In 2003, the Seattle area used less water than was used in 1950 on an annual basis. Seattle's demand management programs have been successful in holding total regional water use constant in our service area, despite an annual growth in population served. During this seminar he will speak to the following issues: 1) Water utility demand management and the financial, social and environmental drivers. 2)

271

MODELING THE DEMAND FOR E85 IN THE UNITED STATES  

SciTech Connect

How demand for E85 might evolve in the future in response to changing economics and policies is an important subject to include in the National Energy Modeling System (NEMS). This report summarizes a study to develop an E85 choice model for NEMS. Using the most recent data from the states of Minnesota, North Dakota, and Iowa, this study estimates a logit model that represents E85 choice as a function of prices of E10 and E85, as well as fuel availability of E85 relative to gasoline. Using more recent data than previous studies allows a better estimation of non-fleet demand and indicates that the price elasticity of E85 choice appears to be higher than previously estimated. Based on the results of the econometric analysis, a model for projecting E85 demand at the regional level is specified. In testing, the model produced plausible predictions of US E85 demand to 2040.

Liu, Changzheng [ORNL] [ORNL; Greene, David L [ORNL] [ORNL

2013-10-01T23:59:59.000Z

272

Electricity demand as frequency controlled reserves, ENS (Smart Grid  

Open Energy Info (EERE)

Electricity demand as frequency controlled reserves, ENS (Smart Grid Electricity demand as frequency controlled reserves, ENS (Smart Grid Project) Jump to: navigation, search Project Name Electricity demand as frequency controlled reserves, ENS Country Denmark Coordinates 56.26392°, 9.501785° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":56.26392,"lon":9.501785,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

273

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":""}]}

274

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

275

U.S. Regional Demand Forecasts Using NEMS and GIS  

E-Print Network (OSTI)

h. Pacific i. MidAtlantic 4. Climate Zone shapefile a.must have a field with climate zone ID’s as an integer in apopulation forecasts and climate zone data. The model’s

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

2005-01-01T23:59:59.000Z

276

Regional Consumer Hydrogen Demand and Optimal Hydrogen Refueling Station Siting  

DOE Green Energy (OSTI)

Using a GIS approach to spatially analyze key attributes affecting hydrogen market transformation, this study proposes hypothetical hydrogen refueling station locations in select subregions to demonstrate a method for determining station locations based on geographic criteria.

Melendez, M.; Milbrandt, A.

2008-04-01T23:59:59.000Z

277

U.S. Regional Demand Forecasts Using NEMS and GIS  

E-Print Network (OSTI)

Figure 29: Residential electricity growth rate (percentage)Over Time The residential electricity growth rate indicatesFigure 29: Residential electricity growth rate (percentage)

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

2005-01-01T23:59:59.000Z

278

Petroleum products demand data revised at regional level ...  

U.S. Energy Information Administration (EIA)

A recent revision to petroleum product movements in the Petroleum ... The data revision involves movements of motor gasoline as reported to EIA by one or more survey ...

279

U.S. Regional Demand Forecasts Using NEMS and GIS  

E-Print Network (OSTI)

Forecasts Using NEMS and GIS National Climatic Data Center.with Changing Boundaries." Use of GIS to Understand Socio-Forecasts Using NEMS and GIS Appendix A. Map Results Gallery

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

2005-01-01T23:59:59.000Z

280

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...

Note: This page contains sample records for the topic "type demand region" 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

Q:\asufinal_0107_demand.vp  

Gasoline and Diesel Fuel Update (EIA)

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

282

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

283

Rates and technologies for mass-market demand response  

SciTech Connect

Demand response programs are often quickly and poorly crafted in reaction to an energy crisis and disappear once the crisis subsides, ensuring that the electricity system will be unprepared when the next crisis hits. In this paper, we propose to eliminate the event-driven nature of demand response programs by considering demand responsiveness a component of the utility obligation to serve. As such, demand response can be required as a condition of service, and the offering of demand response rates becomes a requirement of utilities as an element of customer service. Using this foundation, we explore the costs and benefits of a smart thermostat-based demand response system capable of two types of programs: (1) a mandatory, system-operator controlled, contingency program, and (2) a voluntary, customer controlled, bill management program with rate-based incentives. Any demand response program based on this system could consist of either or both of these components. Ideally, these programs would be bundled, providing automatic load management through customer-programmed price response, plus up to 10 GW of emergency load shedding capability in California. Finally, we discuss options for and barriers to implementation of such a program in California.

Herter, Karen; Levy, Roger; Wilson, John; Rosenfeld, Arthur

2002-07-21T23:59:59.000Z

284

Building Technologies Office: Integrated Predictive Demand Response  

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

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

285

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

Science Conference Proceedings (OSTI)

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

2004-03-18T23:59:59.000Z

286

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

287

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

288

Market and Policy Barriers for Demand Response Providing Ancillary Services  

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

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

289

Assessing the Control Systems Capacity for Demand Response in California  

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

the Control Systems Capacity for Demand Response in California the Control Systems Capacity for Demand Response in California Industries Title Assessing the Control Systems Capacity for Demand Response in California Industries Publication Type Report LBNL Report Number LBNL-5319E Year of Publication 2012 Authors Ghatikar, Girish, Aimee T. McKane, Sasank Goli, Peter L. Therkelsen, and Daniel Olsen Date Published 01/2012 Publisher CEC/LBNL Keywords automated dr, controls and automation, demand response, dynamic pricing, industrial controls, market sectors, openadr Abstract California's electricity markets are moving toward dynamic pricing models, such as real-time pricing, within the next few years, which could have a significant impact on an industrial facility's cost of energy use during the times of peak use. Adequate controls and automated systems that provide industrial facility managers real-time energy use and cost information are necessary for successful implementation of a comprehensive electricity strategy; however, little is known about the current control capacity of California industries. To address this gap, Lawrence Berkeley National Laboratory, in close collaboration with California industrial trade associations, conducted a survey to determine the current state of controls technologies in California industries. This study identifies sectors that have the technical capability to implement Demand Response (DR) and Automated Demand Response (Auto-DR). In an effort to assist policy makers and industry in meeting the challenges of real-time pricing, facility operational and organizational factors were taken into consideration to generate recommendations on which sectors Demand Response efforts should be focused. Analysis of the survey responses showed that while the vast majority of industrial facilities have semi- or fully automated control systems, participation in Demand Response programs is still low due to perceived barriers. The results also showed that the facilities that use continuous processes are good Demand Response candidates. When comparing facilities participating in Demand Response to those not participating, several similarities and differences emerged. Demand Response-participating facilities and non-participating facilities had similar timings of peak energy use, production processes, and participation in energy audits. Though the survey sample was smaller than anticipated, the results seemed to support our preliminary assumptions. Demonstrations of Auto-Demand Response in industrial facilities with good control capabilities are needed to dispel perceived barriers to participation and to investigate industrial subsectors suggested of having inherent Demand Response potential.

290

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)

291

Effects of the drought on California electricity supply and demand  

E-Print Network (OSTI)

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

Benenson, P.

2010-01-01T23:59:59.000Z

292

Automated Demand Response Opportunities in Wastewater Treatment Facilities  

E-Print Network (OSTI)

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

Thompson, Lisa

2008-01-01T23:59:59.000Z

293

Opportunities, Barriers and Actions for Industrial Demand Response in California  

E-Print Network (OSTI)

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

McKane, Aimee T.

2009-01-01T23:59:59.000Z

294

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

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

Kiliccote, Sila

2010-01-01T23:59:59.000Z

295

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

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

Kiliccote, Sila

2010-01-01T23:59:59.000Z

296

Automated Demand Response Technologies and Demonstration in New York City  

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

Technologies and Demonstration in New York City Technologies and Demonstration in New York City using OpenADR Title Automated Demand Response Technologies and Demonstration in New York City using OpenADR Publication Type Report LBNL Report Number LBNL-6470E Year of Publication 2013 Authors Kim, Joyce Jihyun, Sila Kiliccote, and Rongxin Yin Date Published 09/2013 Publisher LBNL/NYSERDA Abstract Demand response (DR) - allowing customers to respond to reliability requests and market prices by changing electricity use from their normal consumption pattern - continues to be seen as an attractive means of demand-side management and a fundamental smart-grid improvement that links supply and demand. Since October 2011, the Demand Response Research Center at Lawrence Berkeley National Laboratory and New York State Energy Research and Development Authority have conducted a demonstration project enabling Automated Demand Response (Auto-DR) in large commercial buildings located in New York City using Open Automated Demand Response (OpenADR) communication protocols. In particular, this project focuses on demonstrating how OpenADR can automate and simplify interactions between buildings and various stakeholders in New York State including the independent system operator, utilities, retail energy providers, and curtailment service providers. In this paper, we present methods to automate control strategies via building management systems to provide event-driven demand response, price response and demand management based on OpenADR signals. We also present cost control opportunities under day-ahead hourly pricing for large customers and Auto-DR control strategies developed for demonstration buildings. Lastly, we discuss the communication architecture and Auto-DR system designed for the demonstration project to automate price response and DR participation.

297

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...

298

Price-elastic demand in deregulated electricity markets  

E-Print Network (OSTI)

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

Siddiqui, Afzal S.

2003-01-01T23:59:59.000Z

299

Automated Demand Response Strategies and Commissioning Commercial Building Controls  

E-Print Network (OSTI)

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

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

2006-01-01T23:59:59.000Z

300

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

Note: This page contains sample records for the topic "type demand region" 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

Demand Side Bidding. Final Report  

SciTech Connect

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

Spahn, Andrew

2003-12-31T23:59:59.000Z

302

US electric utility demand-side management, 1994  

SciTech Connect

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

NONE

1995-12-26T23:59:59.000Z

303

Grid Integration of Aggregated Demand Response, Part 1: Load Availability  

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

Grid Integration of Aggregated Demand Response, Part 1: Load Availability Grid Integration of Aggregated Demand Response, Part 1: Load Availability Profiles and Constraints for the Western Interconnection Title Grid Integration of Aggregated Demand Response, Part 1: Load Availability Profiles and Constraints for the Western Interconnection Publication Type Report LBNL Report Number LBNL-6417E Year of Publication 2013 Authors Olsen, Daniel, Nance Matson, Michael D. Sohn, Cody Rose, Junqiao Han Dudley, Sasank Goli, Sila Kiliccote, Marissa Hummon, David Palchak, Paul Denholm, Jennie Jorgenson, and Ookie Ma Date Published 09/2013 Abstract Demand response (DR) has the potential to improve electric grid reliability and reduce system operation costs. However, including DR in grid modeling can be difficult due to its variable and non-traditional response characteristics, compared to traditional generation. Therefore, efforts to value the participation of DR in procurement of grid services have been limited. In this report, we present methods and tools for predicting demand response availability profiles, representing their capability to participate in capacity, energy, and ancillary services. With the addition of response characteristics mimicking those of generation, the resulting profiles will help in the valuation of the participation of demand response through production cost modeling, which informs infrastructure and investment planning.

304

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

305

Greater fuel diversity needed to meet growing US electricity demand  

Science Conference Proceedings (OSTI)

Electricity demand is growing in the USA. One way to manage the uncertainty is to diversity fuel sources. Fuel sources include coal, natural gas, nuclear and renewable energy sources. Tables show actual and planned generation projects by fuel types. 1 fig., 2 tabs.

Burt, B.; Mullins, S. [Industrial Info Resources (United States)

2008-01-15T23:59:59.000Z

306

Potential impacts of plug-in hybrid electric vehicles on regional power generation  

SciTech Connect

Simulations predict that the introduction of PHEVs could impact demand peaks, reduce reserve margins, and increase prices. The type of power generation used to recharge the PHEVs and associated emissions will depend upon the region and the timing of the recharge. (author)

Hadley, Stanton W.; Tsvetkova, Alexandra A.

2009-12-15T23:59:59.000Z

307

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

308

Distillate Demand Strong in December 1999  

Gasoline and Diesel Fuel Update (EIA)

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

309

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...

310

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...

311

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...

312

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 ...

313

Regional Reserve Margins  

Science Conference Proceedings (OSTI)

This report explores the status of reserve margins across the country. Reserve margins represent the margin of excess capacity compared to demand. It is commonly calculated as the fraction of unused capacity during the summer peak. Simple in concept, the numbers can be difficult to calculate because of changes in geographic boundaries between regions, different views of what capacity qualifies to be counted, and changes in estimates of demand. This report provides a comprehensive and consistently calcula...

2009-03-23T23:59:59.000Z

314

Travel Behavior and Demand Analysis and Prediction  

E-Print Network (OSTI)

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

Goulias, Konstadinos G

2007-01-01T23:59:59.000Z

315

Forecasting the demand for commercial telecommunications satellites  

Science Conference Proceedings (OSTI)

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

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

2001-01-01T23:59:59.000Z

316

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

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

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

317

Infrastructure Failure - Types and Frequency  

U.S. Energy Information Administration (EIA)

Infrastructure Failure - Types and Frequency. Small events that have no impact on supplies Events that require supply/demand responses Events that result in a ...

318

Forecasting demand of commodities after natural disasters  

Science Conference Proceedings (OSTI)

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

Xiaoyan Xu; Yuqing Qi; Zhongsheng Hua

2010-06-01T23:59:59.000Z

319

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

320

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

Note: This page contains sample records for the topic "type demand region" 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

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

322

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

323

FINAL STAFF FORECAST OF 2008 PEAK DEMAND  

E-Print Network (OSTI)

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

324

Leveraging gamification in demand dispatch systems  

Science Conference Proceedings (OSTI)

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

Benjamin Gnauk; Lars Dannecker; Martin Hahmann

2012-03-01T23:59:59.000Z

325

Ups and downs of demand limiting  

SciTech Connect

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

Pannkoke, T.

1976-12-01T23:59:59.000Z

326

Forecasting Uncertain Hotel Room Demand  

E-Print Network (OSTI)

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

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

2001-01-01T23:59:59.000Z

327

Demand Response and Variable Generation Integration Scoping Study  

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

Market and Policy Barriers for Demand Market and Policy Barriers for Demand Response Providing Ancillary Services in U.S. Electricity Markets Peter Cappers, Jason MacDonald, Charles Goldman April 2013 Report Summary 1 Energy Analysis Department  Electricity Markets and Policy Group Presentation Overview  Objectives and Approach  Wholesale and Retail Market Environments  Market and Policy Barrier Typology  Prototypical Regional Barrier Assessment 2 Energy Analysis Department  Electricity Markets and Policy Group A Role for Demand Response to Provide Ancillary Services  Increasing penetration of renewable energy generation in U.S. electricity markets means that bulk power system operators will need to manage the variable and uncertain nature of many renewable resources

328

Both Distillate Supply and Demand Reached Extraordinary Levels This Winter  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: This chart shows some critical differences in distillate supply and demand during this winter heating season, in comparison to the past two winters. Typically, distillate demand peaks during the winter months, but "new supply" (refinery production and net imports) cannot increase as much, so the remaining supply needed is drawn from inventories. This pattern is evident in each of the past two winter heating seasons. This winter, however, the pattern was very different, for several reasons: With inventories entering the season at extremely low levels, a "typical" winter stockdraw would have been nearly impossible, particularly in the Northeast, the region most dependent on heating oil. Demand reached near-record levels in December, as colder-than-normal

329

U.S. electric utility demand-side management 1996  

SciTech Connect

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

1997-12-01T23:59:59.000Z

330

U.S. electric utility demand-side management 1995  

SciTech Connect

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

1997-01-01T23:59:59.000Z

331

Evaluation of Representative Smart Grid Investment Project Technologies: Demand Response  

DOE Green Energy (OSTI)

This document is one of a series of reports estimating the benefits of deploying technologies similar to those implemented on the Smart Grid Investment Grant (SGIG) projects. Four technical reports cover the various types of technologies deployed in the SGIG projects, distribution automation, demand response, energy storage, and renewables integration. A fifth report in the series examines the benefits of deploying these technologies on a national level. This technical report examines the impacts of a limited number of demand response technologies and implementations deployed in the SGIG projects.

Fuller, Jason C.; Prakash Kumar, Nirupama; Bonebrake, Christopher A.

2012-02-14T23:59:59.000Z

332

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:

333

Measurement and Verification for Demand Response  

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

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

334

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":""}]}

335

Progress towards Managing Residential Electricity Demand: Impacts of  

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

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

336

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

337

Regional Workshop on Opportunities and Priorities for Low Carbon Green  

Open Energy Info (EERE)

Regional Workshop on Opportunities and Priorities for Low Carbon Green Regional Workshop on Opportunities and Priorities for Low Carbon Green Growth in Asia Jump to: navigation, search Tool Summary Name: Regional Workshop on Opportunities and Priorities for Low Carbon Green Growth in Asia Agency/Company /Organization: Asian Development Bank Institute Topics: Policies/deployment programs, Pathways analysis Resource Type: Workshop, Training materials Website: www.adbi.org/cd-roms/2010/08/27/4054.low.carbon.green.growth.asia/ UN Region: Central Asia, Eastern Asia, South-Eastern Asia References: ADB Regional Workshop[1] Contents "Concepts of Low Carbon Green Growth: Challenges and Current Status in the Asia Pacific Region Inside the Low Carbon Green Growth: Innovations in Green Energy Supply Demand Side Energy Efficiency Solutions: A Low Hanging

338

Battery resource assessment. Interim report No. 1. Battery materials demand scenarios  

DOE Green Energy (OSTI)

Projections of demand for batteries and battery materials between 1980 and 2000 are presented. The estimates are based on existing predictions for the future of the electric vehicle, photovoltaic, utility load-leveling, and existing battery industry. Battery demand was first computed as kilowatt-hours of storage for various types of batteries. Using estimates for the materials required for each battery, the maximum demand that could be expected for each battery material was determined.

Sullivan, D.

1980-12-01T23:59:59.000Z

339

Demand Response Opportunities and Enabling Technologies for Data Centers:  

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

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

340

Design and Operation of an Open, Interoperable Automated Demand Response  

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

Design and Operation of an Open, Interoperable Automated Demand Response Design and Operation of an Open, Interoperable Automated Demand Response Infrastructure for Commercial Buildings Title Design and Operation of an Open, Interoperable Automated Demand Response Infrastructure for Commercial Buildings Publication Type Journal Article LBNL Report Number LBNL-2340e Year of Publication 2009 Authors Piette, Mary Ann, Girish Ghatikar, Sila Kiliccote, David S. Watson, Edward Koch, and Dan Hennage Journal Journal of Computing Science and Information Engineering Volume 9 Issue 2 Keywords communication and standards, market sectors, openadr Abstract This paper describes the concept for and lessons from the development and field-testing of an open, interoperable communications infrastructure to support automated demand response (auto-DR). Automating DR allows greater levels of participation, improved reliability, and repeatability of the DR in participating facilities. This paper also presents the technical and architectural issues associated with auto-DR and description of the demand response automation server (DRAS), the client/server architecture-based middle-ware used to automate the interactions between the utilities or any DR serving entity and their customers for DR programs. Use case diagrams are presented to show the role of the DRAS between utility/ISO and the clients at the facilities.

Note: This page contains sample records for the topic "type demand region" 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

Rates and technologies for mass-market demand response  

Science Conference Proceedings (OSTI)

Demand response programs are often quickly and poorlycrafted in reaction to an energy crisis and disappear once the crisissubsides, ensuring that the electricity system will be unprepared whenthe next crisis hits. In this paper, we propose to eliminate theevent-driven nature of demand response programs by considering demandresponsiveness a component of the utility obligation to serve. As such,demand response can be required as a condition of service, and theoffering of demand response rates becomes a requirement of utilities asan element of customer service. Using this foundation, we explore thecosts and benefits of a smart thermostat-based demand response systemcapable of two types of programs: (1) a mandatory, system-operatorcontrolled, contingency program, and (2) a voluntary, customercontrolled, bill management program with rate-based incentives. Anydemand response program based on this system could consist of either orboth of these components. Ideally, these programs would be bundled,providing automatic load management through customer-programmed priceresponse, plus up to 10 GW of emergency load shedding capability inCalifornia. Finally, we discuss options for and barriers toimplementation of such a program in California.

Herter, Karen; Levy, Roger; Wilson, John; Rosenfeld, Arthur

2002-07-21T23:59:59.000Z

342

Retail Demand Response in Southwest Power Pool  

SciTech Connect

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. LBNL conducted a detailed survey of existing DR programs and dynamic pricing tariffs administered by SPP's member utilities. Survey respondents were asked to provide information on advance notice requirements to customers, operational triggers used to call events (e.g. system emergencies, market conditions, local emergencies), use of these DR resources to meet planning reserves requirements, DR resource availability (e.g. seasonal, annual), participant incentive structures, and monitoring and verification (M&V) protocols. Nearly all of the 30 load-serving entities in SPP responded to the survey. Of this group, fourteen SPP member utilities administer 36 DR programs, five dynamic pricing tariffs, and six voluntary customer response initiatives. These existing DR programs and dynamic pricing tariffs have a peak demand reduction potential of 1,552 MW. Other major findings of this study are: o About 81percent of available DR is from interruptible rate tariffs offered to large commercial and industrial customers, while direct load control (DLC) programs account for ~;;14percent. o Arkansas accounts for ~;;50percent of the DR resources in the SPP footprint; these DR resources are primarily managed by cooperatives. o Publicly-owned cooperatives accounted for 54percent of the existing DR resources among SPP members. For these entities, investment in DR is often driven by the need to reduce summer peak demand that is used to set demand charges for each distribution cooperative. o About 65-70percent of the interruptible/curtailable tariffs and DLC programs are routinely triggered based on market conditions, not just for system emergencies. Approximately, 53percent of the DR resources are available with less than two hours advance notice and 447 MW can be dispatched with less than thirty minutes notice. o Most legacy DR programs offered a reservation payment ($/kW) for participation; incentive payment levels ranged from $0.40 to $8.30/kW-month for interruptible rate tariffs and $0.30 to $4.60/kW-month for DLC programs. A few interruptible programs offered incentive payments which were explicitly linkedto actual load reductions during events; payments ranged from 2 to 40 cents/kWh for load curtailed.

Bharvirkar, Ranjit; Heffner, Grayson; Goldman, Charles

2009-01-30T23:59:59.000Z

343

Distributed Intelligent Automated Demand Response (DIADR) Building  

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

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

344

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

345

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

346

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.

347

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

SciTech Connect

Demand response is increasingly recognized as an essentialingredient to well functioning electricity markets. This growingconsensus was formalized in the Energy Policy Act of 2005 (EPACT), whichestablished demand response as an official policy of the U.S. government,and directed states (and their electric utilities) to considerimplementing demand response, with a particular focus on "price-based"mechanisms. The resulting deliberations, along with a variety of stateand regional demand response initiatives, are raising important policyquestions: for example, How much demand response is enough? How much isavailable? From what sources? At what cost? The purpose of this scopingstudy is to examine analytical techniques and data sources to supportdemand response market assessments that can, in turn, answer the secondand third of these questions. We focus on demand response for large(>350 kW), commercial and industrial (C&I) customers, althoughmany of the concepts could equally be applied to similar programs andtariffs for small commercial and residential customers.

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

2007-01-01T23:59:59.000Z

348

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

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

Marketing & Driving Demand: Social Media Tools & Strategies January 16, 2011 Maryanne Fuller (MF): Hi there. This is Maryanne Fuller from Lawrence Berkeley National Laboratory....

349

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

350

Wireless Demand Response Controls for HVAC Systems  

E-Print Network (OSTI)

Response Controls for HVAC Systems Clifford Federspiel,tests. Figure 5: Specific HVAC electric power consumptioncontrol, demand response, HVAC, wireless Executive Summary

Federspiel, Clifford

2010-01-01T23:59:59.000Z

351

Electric Utility Demand-Side Management  

U.S. Energy Information Administration (EIA)

Demand side management (DSM) activities in the electric power industry. The report presents a general discussion of DSM, its history, current issues, and a ...

352

Capitalize on Existing Assets with Demand Response  

E-Print Network (OSTI)

Industrial facilities universally struggle with escalating energy costs. EnerNOC will demonstrate how commercial, industrial, and institutional end-users can capitalize on their existing assets—at no cost and no risk. Demand response, the voluntary reduction of electric demand in response to grid instability, provides financial incentives to participating facilities that agree to conserve energy. With demand response, facilities also receive advance notice of potential blackouts and can proactively protect their equipment and machinery from sudden losses of power. A detailed case study, focusing on a sample industrial customer’s participation in demand response, will support the presentation.

Collins, J.

2008-01-01T23:59:59.000Z

353

Optimization of Demand Response Through Peak Shaving  

E-Print Network (OSTI)

Jul 5, 2013 ... Optimization of Demand Response Through Peak Shaving. G. Zakeri(g.zakeri *** at*** auckland.ac.nz) D. Craigie(David.Craigie ***at*** ...

354

Automated Demand Response Technology Demonstration Project for...  

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

Demonstration Project for Small and Medium Commercial Buildings Title Automated Demand Response Technology Demonstration Project for Small and Medium Commercial Buildings...

355

Integration of Demand Side Management, Distributed Generation...  

Open Energy Info (EERE)

Page Edit with form History Facebook icon Twitter icon Integration of Demand Side Management, Distributed Generation, Renewable Energy Sources, and Energy Storages:...

356

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

357

Discrete Choice Analysis: Hydrogen FCV Demand Potential  

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

Choice Analysis: H 2 FCV Demand Potential Cory Welch H 2 Scenario Analysis Workshop Washington, D.C. , January 31, 2007 2 Overview * Motivation for work * Methodology * Relative...

358

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

359

Electric Utility Demand-Side Management 1997  

U.S. Energy Information Administration (EIA)

DOE/EIA-0589(97) Distribution Category UC-950 U.S. Electric Utility Demand-Side Management 1997 December 1998 Energy Information Administration Office of Coal ...

360

Northwest Open Automated Demand Response Technology Demonstration...  

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

morning and summer afternoon peak electricity demand in commercial buildings the Seattle area. LBNL performed this demonstration for the Bonneville Power Administration (BPA)...

Note: This page contains sample records for the topic "type demand region" 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

Demand response participation in PJM wholesale markets  

Science Conference Proceedings (OSTI)

This paper provides an overview of demand response resource participation in PJM wholesale ancillary service markets which include: Day Ahead Scheduling Reserves, Synchronized Reserves and Regulation.

Peter L. Langbein

2012-01-01T23:59:59.000Z

362

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

3 3.0 Previous Experience with Demand Responsive Lighting11 4.3. Prevalence of Lighting13 4.4. Impact of Title 24 on Lighting

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

363

Home Network Technologies and Automating Demand Response  

E-Print Network (OSTI)

networks_in_the_home_the_new_growth_market.htm [12] NationalHome Network Technologies and Automating Demand Responsethe University of California. Home Network Technologies and

McParland, Charles

2010-01-01T23:59:59.000Z

364

Distillate Demand Strong in December 1999  

U.S. Energy Information Administration (EIA)

Total distillate demand includes both diesel and heating oil. These are similar products. Physically, diesel can be used in the heating oil market, but low sulfur ...

365

A Model of Household Demand for Activity Participation and Mobility  

E-Print Network (OSTI)

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

Golob, Thomas F.

1996-01-01T23:59:59.000Z

366

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

E-Print Network (OSTI)

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

Cappers, Peter

2009-01-01T23:59:59.000Z

367

Demand Response Opportunities in Industrial Refrigerated Warehouses in California  

E-Print Network (OSTI)

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

Goli, Sasank

2012-01-01T23:59:59.000Z

368

Results and commissioning issues from an automated demand response pilot  

E-Print Network (OSTI)

of Fully Automated Demand Response in Large Facilities"Management and Demand Response in Commercial Buildings", L Band Commissioning Issues from an Automated Demand Response.

Piette, Mary Ann; Watson, Dave; Sezgen, Osman; Motegi, Naoya

2004-01-01T23:59:59.000Z

369

Open Automated Demand Response for Small Commerical Buildings  

E-Print Network (OSTI)

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

Dudley, June Han

2009-01-01T23:59:59.000Z

370

Rates and technologies for mass-market demand response  

E-Print Network (OSTI)

Roger. 2002. Using Demand Response to Link Wholesale andfor advanced metering, demand response, and dynamic pricing.EPRI. 2001. Managing Demand-Response To Achieve Multiple

Herter, Karen; Levy, Roger; Wilson, John; Rosenfeld, Arthur

2002-01-01T23:59:59.000Z

371

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

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

Ghatikar, Girish

2010-01-01T23:59:59.000Z

372

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network (OSTI)

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

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

373

Direct versus Facility Centric Load Control for Automated Demand Response  

E-Print Network (OSTI)

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

Piette, Mary Ann

2010-01-01T23:59:59.000Z

374

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

375

Scenarios for Consuming Standardized Automated Demand Response Signals  

E-Print Network (OSTI)

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

Koch, Ed

2009-01-01T23:59:59.000Z

376

Dynamic Pricing, Advanced Metering, and Demand Response in Electricity Markets  

E-Print Network (OSTI)

the New England ISO Demand Response Collaborative, a NYSERDACEC Staff. Selected Demand Response Pilots in California:New Principles for Demand Response Planning, Electric Power

Borenstein, Severin; Jaske, Michael; Rosenfeld, Arthur

2002-01-01T23:59:59.000Z

377

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

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

Kiliccote, Sila

2010-01-01T23:59:59.000Z

378

Measurement and evaluation techniques for automated demand response demonstration  

E-Print Network (OSTI)

Development for Demand Response Calculation – Findings andManagement and Demand Response in Commercial Buildings. ”of Fully Automated Demand Response in Large Facilities. ”

Motegi, Naoya; Piette, Mary Ann; Watson, David S.; Sezgen, Osman; ten Hope, Laurie

2004-01-01T23:59:59.000Z

379

Open Automated Demand Response Communications Specification (Version 1.0)  

E-Print Network (OSTI)

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

Piette, Mary Ann

2009-01-01T23:59:59.000Z

380

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, ...

Note: This page contains sample records for the topic "type demand region" 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

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

55. Sample distribution of vehicle electricity demand forand distribution facilities that supply electricity demand.55. Sample distribution of vehicle electricity demand for

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

382

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

5. Average, minimum, and maximum demand reduction at eachshow the minimum and maximum demand reduction during the7. Average, minimum, and maximum demand reduction at each

Kiliccote, Sila

2010-01-01T23:59:59.000Z

383

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

384

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

E-Print Network (OSTI)

with Residential Electricity Demand in India's Future - How2008). The Boom of Electricity Demand in the residential2005). Forecasting Electricity Demand in Developing

Letschert, Virginie

2010-01-01T23:59:59.000Z

385

Climate, extreme heat, and electricity demand in California  

E-Print Network (OSTI)

warming and electricity demand: A study of California.Extreme Heat, and Electricity Demand in California Norman L.high temperature and electricity demand for air-conditioned

Miller, N.L.

2008-01-01T23:59:59.000Z

386

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

Statewide California Electricity Demand. [accessed June 22,fuel efficiency and electricity demand assumptions used into added vehicle electricity demand in the BAU (no IGCC)

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

387

Microgrid Dispatch for Macrogrid Peak-Demand Mitigation  

E-Print Network (OSTI)

Dispatch for Macrogrid Peak- Demand Mitigation NicholasDispatch for Macrogrid Peak-Demand Mitigation Nicholasdetermine whether the peak demand on the substation feeder

DeForest, Nicholas

2013-01-01T23:59:59.000Z

388

Effects of the drought on California electricity supply and demand  

E-Print Network (OSTI)

for Electricity and Power Peak Demand . . • . . ELECTRICITYby Major Utility Service Area Projected Peak Demand for1977 Historical Peak Demand by Utility Service Area Weather-

Benenson, P.

2010-01-01T23:59:59.000Z

389

Climate, extreme heat, and electricity demand in California  

E-Print Network (OSTI)

projected extreme heat and peak demand for electricity areadequately kept up with peak demand, and electricity supplytrend in aggregate peak demand in California is expected to

Miller, N.L.

2008-01-01T23:59:59.000Z

390

FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007 INTEGRATED Table of Contents General Instructions for Demand Forecast Submittals.............................................................................. 4 Protocols for Submitted Demand Forecasts

391

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

392

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

393

Robust Dynamic Traffic Assignment under Demand and Capacity Uncertainty  

E-Print Network (OSTI)

Assignment under Demand and Capacity Uncertainty ? Giuseppeworst-case sce- nario of demand and capacity con?gurations.uncertain demands and capacities are modeled as unknown-but-

Calafiore, Giuseppe; El Ghaoui, Laurent

2008-01-01T23:59:59.000Z

394

Rising Asian demand drives global coal consumption growth ...  

U.S. Energy Information Administration (EIA)

Global coal demand has almost doubled since 1980, driven by increases in Asia, where demand is up over 400% from 1980-2010. In turn, Asian demand is ...

395

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

Science Conference Proceedings (OSTI)

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

Not Available

1991-11-04T23:59:59.000Z

396

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

Science Conference Proceedings (OSTI)

The restructuring of regional and national electricity markets in the U.S. and around the world has been accompanied by numerous problems, including generation capacity shortages, transmission congestion, wholesale price volatility, and reduced system reliability. These problems have created new opportunities for technologies and business approaches that allow load serving entities and other aggregators to control and manage the load patterns of wholesale and retail end-users they serve. Demand Response Programs, once called Load Management, have re-emerged as an important element in the fine-tuning of newly restructured electricity markets. During the summers of 1999 and 2001 they played a vital role in stabilizing wholesale markets and providing a hedge against generation shortfalls throughout the U.S.A. Demand Response Programs include ''traditional'' capacity reservation and interruptible/curtailable rates programs as well as voluntary demand bidding programs offered by either Load Serving Entities (LSEs) or regional Independent System Operators (ISOs). The Lawrence Berkeley National Lab (LBNL) has been monitoring the development of new types of Demand Response Programs both in the U.S. and around the world. This paper provides a survey and overview of the technologies and program designs that make up these emerging and important new programs.

Heffner, Grayson C.

2002-09-01T23:59:59.000Z

397

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.

398

Pacific Northwest Regional Assessment of the Potential  

E-Print Network (OSTI)

, demand response and energy efficiency demand-side reductions. The fact that natural gas is the regionPacific Northwest Regional Assessment of the Potential Benefits of the Direct Use of Natural Gas) .........................42 Figure 1 Service Area Map of PNW Participating Natural Gas Utilities

399

Designing presentations for on-demand viewing  

Science Conference Proceedings (OSTI)

Increasingly often, presentations are given before a live audience, while simultaneously being viewed remotely and recorded for subsequent viewing on-demand over the Web. How should video presentations be designed for web access? How is video accessed ... Keywords: digital library, streaming media, video on-demand

Liwei He; Jonathan Grudin; Anoop Gupta

2000-12-01T23:59:59.000Z

400

INTEGRATION OF PV IN DEMAND RESPONSE  

E-Print Network (OSTI)

of the baseline defining a customer's load profile, and (2) PVs cannot be turned on at will for scheduled tests customers to curtail demand when needed to reduce risk of grid failure during times of peak loading load. The value of this credit may reach or exceed $100/kW/year [1] Demand response is typically

Perez, Richard R.

Note: This page contains sample records for the topic "type demand region" 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

A distributed approach to taming peak demand  

Science Conference Proceedings (OSTI)

A significant portion of all energy capacity is wasted in over-provisioning to meet peak demand. The current state-of-the-art in reducing peak demand requires central authorities to limit device usage directly, and are generally reactive. We apply techniques ...

Michael Sabolish; Ahmed Amer; Thomas M. Kroeger

2012-06-01T23:59:59.000Z

402

Note: The Newsvendor Model with Endogenous Demand  

Science Conference Proceedings (OSTI)

This paper considers a firm's price and inventory policy when it faces uncertain demand that depends on both price and inventory level. The authors extend the classic newsvendor model by assuming that expected utility maximizing consumers choose between ... Keywords: Demand Uncertainty, Fill Rate Competition, Inventory, Newsvendor Model, Pricing, Service Levels, Service Rate Competition

James D. Dana; Nicholas C. Petruzzi

2001-11-01T23:59:59.000Z

403

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

404

Forecasting Electricity Demand by Time Series Models  

Science Conference Proceedings (OSTI)

Electricity demand is one of the most important variables required for estimating the amount of additional capacity required to ensure a sufficient supply of energy. Demand and technological losses forecasts can be used to control the generation and distribution of electricity more efficiently. The aim of this paper is to utilize time series model

E. Stoimenova; K. Prodanova; R. Prodanova

2007-01-01T23:59:59.000Z

405

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.

406

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.

407

OECD Crude Oil v Product Demand Seasonal Patterns  

Gasoline and Diesel Fuel Update (EIA)

6 Notes: The answer lies in separating crude oil demand from product demand. Crude oil demand should be a better indicator of pressures on crude oil price than product demand....

408

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

409

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network (OSTI)

load and customer maximum demand are most commonly used as1) minimum and maximum amounts of demand reduction; (2)

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

410

Optimal Design of Demand-Responsive Feeder Transit Services  

E-Print Network (OSTI)

The general public considers Fixed-Route Transit (FRT) to be inconvenient while Demand-Responsive Transit (DRT) provides much of the desired flexibility with a door-to-door type of service. However, FRT is typically more cost efficient than DRT to deploy. Therefore, there is an increased interest in flexible transit services including all types of hybrid services that combine FRT and pure DRT. The demand-responsive feeder transit, also known as Demand-Responsive Connector (DRC), is a flexible transit service because it operates in a demand-responsive fashion within a service area and moves customers to/from a transfer point that connects to a FRT network. In this research we develop analytical models, validated by simulation, to design the DRC system. Feeder transit services are generally operated with a DRC policy which might be converted to a traditional FRT policy for higher demand. By using continuous approximations, we provide an analytical modeling framework to help planners and operators in their choice of the two policies. We compare utility functions of the two policies to derive rigorous analytical and approximate closed-form expressions of critical demand densities. They represent the switching conditions, that are functions of the parameters of each considered scenario, such as the geometry of the service area, the vehicle speed and also the weights assigned to each term contributing to the utility function: walking time, waiting time and riding time. We address the problem faced by planners in determining the optimal number of zones for dividing a service area. We develop analytical models representing the total cost functions balancing customer service quality and vehicle operating cost. We obtain close-form expressions for the FRT and approximation formulas for the DRC to determine the optimal number of zones. Finally we develop a real-case application with collected customer demand data and road network data of El Cenizo, Texas. With our analytical formulas, we obtain the optimal number of zones, and the times for switching FRT and DRC policies during a day. Simulation results considering the road network of El Cenizo demonstrate that our analytical formulas provide good estimates for practical use.

Li, Xiugang

2009-08-01T23:59:59.000Z

411

Review of Self-direct Demand Side Management (DSM) Programs  

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

Review of Self-direct Demand Side Management (DSM) Programs Review of Self-direct Demand Side Management (DSM) Programs Title Review of Self-direct Demand Side Management (DSM) Programs Publication Type Presentation Year of Publication 2012 Authors Borgeson, Merrian Keywords demand side resources: policy, electricity markets, electricity markets and policy group, energy analysis and environmental impacts department, energy efficiency, self direct programs, technical assistance Full Text LBNL recently provided technical assistance funded by DOE to the Public Utilities Commission of Ohio to inform their decision-making about changes to their existing self-direct program for commercial and industrial customers. Self-direct programs are usually targeted at large industrial customers with specialized needs or strong in-house energy engineering capacity. These programs are found in at least 24 states, and there is significant variety in how these programs are structured - with important implications for the additionality and reliability of the energy savings that result. LBNL reviewed existing programs and compared key elements of self-direct program design. For additional questions about this work, please contact Merrian Borgeson.

412

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

SciTech Connect

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

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

2001-06-25T23:59:59.000Z

413

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.

414

U.S. Coal Supply and Demand: 1997 Review  

Gasoline and Diesel Fuel Update (EIA)

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

415

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.

416

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.

417

FERC sees huge potential for demand response  

Science Conference Proceedings (OSTI)

The FERC study concludes that U.S. peak demand can be reduced by as much as 188 GW -- roughly 20 percent -- under the most aggressive scenario. More moderate -- and realistic -- scenarios produce smaller but still significant reductions in peak demand. The FERC report is quick to point out that these are estimates of the potential, not projections of what could actually be achieved. The main varieties of demand response programs include interruptible tariffs, direct load control (DLC), and a number of pricing schemes.

NONE

2010-04-15T23:59:59.000Z

418

Demand Controlled Ventilation and Classroom Ventilation  

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

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

419

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

420

Integrated Predictive Demand Response Controller Research Project |  

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

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

Note: This page contains sample records for the topic "type demand region" 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

Software demonstration: Demand Response Quick Assessment Tool  

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

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

422

NCEP_Demand_Response_Draft_111208.indd  

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

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

423

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

424

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

425

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

426

Demand response-enabled residential thermostat controls  

E-Print Network (OSTI)

from the utility. The electricity rates were generated basedat the different electricity rates and the user’s discomfortrates. Demand response measures have the effect of adding elasticity to the electricity

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

2008-01-01T23:59:59.000Z

427

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

428

Demand Response Enabled Appliance Development at GE  

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

Demand Response Enabled Appliance Development at GE Speaker(s): David Najewicz Date: June 12, 2009 - 12:00pm Location: 90-3122 Dave Najewicz of GE Consumer and Appliances will...

429

Automated Demand Response for Critical Peak Pricing  

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

Automated Demand Response for Critical Peak Pricing Speaker(s): Naoya Motegi Date: June 9, 2005 - 12:00pm Location: Bldg. 90 California utilities have been exploring the use of...

430

Wireless Demand Response Controls for HVAC  

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

Wireless Demand Response Controls for HVAC Speaker(s): Clifford Federspiel Date: June 22, 2006 - 12:00pm Location: 90-3148 Seminar HostPoint of Contact: Richard Diamond Peng Xu We...

431

Geographically Based Hydrogen Demand & Infrastructure Analysis (Presentation)  

DOE Green Energy (OSTI)

Presentation given at the 2006 DOE Hydrogen, Fuel Cells & Infrastructure Technologies Program Annual Merit Review in Washington, D.C., May 16-19, 2006, discusses potential future hydrogen demand and the infrastructure needed to support hydrogen vehicles.

Melendez, M.

2006-05-18T23:59:59.000Z

432

Software demonstration: Demand Response Quick Assessment Tool  

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

Software demonstration: Demand Response Quick Assessment Tool Speaker(s): Peng Xu Date: February 4, 2008 - 12:00pm Location: 90-3122 The potential for utilizing building thermal...

433

Volatile coal prices reflect supply, demand uncertainties  

SciTech Connect

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

Ryan, M.

2004-12-15T23:59:59.000Z

434

Demand response-enabled residential thermostat controls.  

E-Print Network (OSTI)

from the utility. The electricity rates were generated basedat the different electricity rates and the user’s discomfortrates. Demand response measures have the effect of adding elasticity to the electricity

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

2008-01-01T23:59:59.000Z

435

Essays on exchange rates and electricity demand  

E-Print Network (OSTI)

This thesis examines two important issues in economic development: exchange rates and electricity demand and addresses methodological issues of using time series and panel data analysis to investigate important policy ...

Li, Xiangming, 1966-

1999-01-01T23:59:59.000Z

436

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...

437

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

438

Better Buildings Neighborhood Program: Driving Demand  

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

even know they have. This section explains how you can use effective marketing to drive demand for energy upgrades in your community. Following the lead of many Better Buildings...

439

Residential Sector Demand Module 2000, Model Documentation  

Reports and Publications (EIA)

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.

John H. Cymbalsky

1999-12-01T23:59:59.000Z

440

Residential Sector Demand Module 2004, Model Documentation  

Reports and Publications (EIA)

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.

John H. Cymbalsky

2004-02-01T23:59:59.000Z

Note: This page contains sample records for the topic "type demand region" 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

Residential Sector Demand Module 2001, Model Documentation  

Reports and Publications (EIA)

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.

John H. Cymbalsky

2000-12-01T23:59:59.000Z

442

Residential Sector Demand Module 2002, Model Documentation  

Reports and Publications (EIA)

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.

John H. Cymbalsky

2001-12-01T23:59:59.000Z

443

Residential Sector Demand Module 2005, Model Documentation  

Reports and Publications (EIA)

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.

John H. Cymbalsky

2005-04-01T23:59:59.000Z

444

Residential Sector Demand Module 2003, Model Documentation  

Reports and Publications (EIA)

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.

John H. Cymbalsky

2003-01-01T23:59:59.000Z

445

Residential Sector Demand Module 2008, Model Documentation  

Reports and Publications (EIA)

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.

John H. Cymbalsky

2008-10-10T23:59:59.000Z

446

Residential Sector Demand Module 2006, Model Documentation  

Reports and Publications (EIA)

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.

John H. Cymbalsky

2006-03-01T23:59:59.000Z

447

Residential Sector Demand Module 2009, Model Documentation  

Reports and Publications (EIA)

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

John H. Cymbalsky

2009-05-01T23:59:59.000Z

448

Residential Sector Demand Module 1999, Model Documentation  

Reports and Publications (EIA)

This is the fifth edition of the Model Documentation Report: Residential Sector DemandModule of the National Energy Modeling System (NEMS). It reflects changes made to themodule over the past year for the Annual Energy Outlook 1999.

John H. Cymbalsky

1998-12-01T23:59:59.000Z

449

Residential Sector Demand Module 2007, Model Documentation  

Reports and Publications (EIA)

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.

John H. Cymbalsky

2007-04-26T23:59:59.000Z

450

Proceedings: Demand-Side Management Incentive Regulation  

Science Conference Proceedings (OSTI)

These proceedings provide background information on proposed regulatory incentive mechanisms to encourage utilities to develop demand-side management programs. Attendees discussed and analyzed various proposals and techniques and developed lists of key attributes that incentive mechanisms should have.

None

1990-05-01T23:59:59.000Z

451

Micro economics for demand-side management  

E-Print Network (OSTI)

This paper aims to interpret Demand-Side Management (DSM) activity and to point out its problems, adopting microeconomics as an analytical tool. Two major findings follow. first, the cost-benefit analysis currently in use ...

Kibune, Hisao

1991-01-01T23:59:59.000Z

452

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

453

Rapid increases in electricity demand challenge both ...  

U.S. Energy Information Administration (EIA)

... on April 1 was the steepest so far this year in SPP. The rate of increase in electricity demand peaked at 12.4% between 6 a.m. and 7 a.m. ...

454

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

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

for Marketing and Demand Creation (1.5 hr video) - EarthAid & Efficiency 2.0 Facebook Social Plug-ins YouTube Google Tools - Adwords & Web Optimizer *...

455

Measuring the capacity impacts of demand response  

Science Conference Proceedings (OSTI)

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

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

2009-07-15T23:59:59.000Z

456

Tri-State Demand Response Framework  

Science Conference Proceedings (OSTI)

This report provides the results of a demand response framework development project of Tri-State Generation and Transmission, a wholesale provider to a number of rural electric associations in the Rocky Mountain west. Tri-State has developed an assortment of planned demand response and energy shaping products and services designed to both shave peak and shift consumption to off-peak hours. The applications, networks, and devices that will be needed to support these needs will involve many ...

2013-03-28T23:59:59.000Z

457

OECD Crude "Demand" Remains Flat Between 1st and 2nd Quarters  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: As we enter the year 2000, we can expect crude oil demand to follow the usual pattern and remain relatively flat in OECD countries between first and second quarters. Note that for OECD, product demand is greater than crude use. These areas import products from outside the region. While product demand falls during the second and third quarters, crude inputs to refineries remain high enough to allow for some product stock building Additionally, purchases of crude oil exceed inputs to refineries for a time, allowing crude oil stocks to build as well in order to cover the shortfall between crude oil production and demand during the fourth and first quarters. Price can strengthen during the "weak product demand" summer months when the market feels stock building is inadequate to meet the

458

On demand responsiveness in additive cost sharing  

E-Print Network (OSTI)

Abstract. We propose two new axioms of demand responsiveness for additive cost sharing with variable demands. Group Monotonicity requires that if a group of agents increase their demands, not all of them pay less. Solidarity says that if agent i demands more, j should not pay more if k pays less. Both axioms are compatible in the partial responsibility theory postulating Strong Ranking, i.e., the ranking of cost shares should never contradict that of demands. The combination of Strong Ranking, Solidarity and Monotonicity characterizes the quasi-proportional methods, under which cost shares are proportional to ‘rescaled ’ demands. The alternative full responsibility theory is based on Separability, ruling out cross-subsidization when costs are additively separable. Neither the Aumann-Shapley nor the Shapley-Shubik method is group monotonic. On the other hand, convex combinations of “nearby ” …xed-path methods are group-monotonic: the subsidy-free serial method is the main example. No separable method meets Solidarity, yet restricting the axiom to submodular (or supermodular) cost functions leads to a characterization of the …xed-‡ow methods, containing the Shapley-Shubik and serial methods. JEL Classi…cation numbers: C 71, D 63.

Hervé Moulin; Yves Sprumont

2005-01-01T23:59:59.000Z

459

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

460

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

Note: This page contains sample records for the topic "type demand region" 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

Table 11.1 Electricity: Components of Net Demand, 2010;  

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

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

462

Table 11.2 Electricity: Components of Net Demand, 2010;  

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

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

463

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

464

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

465

Climate, extreme heat, and electricity demand in California  

SciTech Connect

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

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

2008-04-01T23:59:59.000Z

466

U.S. Coal Supply and Demand  

Gasoline and Diesel Fuel Update (EIA)

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

467

Changing fuel formulations will boost hydrogen demand  

SciTech Connect

Refinery demand in the U.S. for on-purpose hydrogen will continue to increase by 5-10 %/year, depending on the extent of implementation of the 1990 U.S. Clean Air Act Amendments (CAAA) and other proposed environmental legislation. Although the debate on the economic wisdom of the legislation still rages, it is evident that refiners likely will see a large upswing in hydrogen demand while existing hydrogen production may decline. To better understand the potential impact various reformulation scenarios may have on the refining industry, and specifically, on the demand for hydrogen, Texaco analyzed the hydrogen supply/demand scenario in great detail. Two cases were studied in this analysis: mild and severe reformulation. The mild reformulation case is based on current CAAA legislation along with minor modifications to automobile hardware. The severe case is based on a nationwide implementation of Phase 2 of the CAAA and California's proposed reformulated fuels. The paper discusses the current capacity balance; growth in demand; reformulated gasoline; steam methane reforming; and partial oxidation technology.

Simonsen, K.A.; O' Keefe, L.F. (Texaco Inc., White Plains, N.Y. (United States)); Fong, W.F. (Texaco Development Corp., White Plains, N.Y. (United States))

1993-03-22T23:59:59.000Z

468

Transmaterialization: technology and materials demand cycles  

SciTech Connect

Recently concern has risen worldwide regarding the issue of declining materials demand which has been termed dematerialization. A summary of the issues involved appears in the proceedings of the recent conference on metals demand published in Materials and Society (1986). Dematerialization refers to the constant decline in use of materials as a percentage of total production. Dematerialization implies a structural change in an economy, indicating a reduced demand for materials and, therefore, a decline in overall industrial growth. This paper proposes that, instead of dematerialization in the US material markets, the demand change that has been occurring can be more aptly described as transmaterialization. Transmaterialization implies a recurring industrial transformation in the way that economic societies use materials, a process that has occurred regularly or cyclically throughout history. Instead of a once and for all structural change as implied by dematerialization, transmaterialization suggests that minerals demand experiences phases in which old, lower-quality materials linked to mature industries undergo replacement periodically by higher-quality or technologically-more-appropriate materials. The latter, as of recent, tend to be lighter materials with more robust technical properties than those being replaced.

Waddell, L.M.; Labys, W.C.

1988-01-01T23:59:59.000Z

469

Demand response medium sized industry consumers (Smart Grid Project) | Open  

Open Energy Info (EERE)

response medium sized industry consumers (Smart Grid Project) response medium sized industry consumers (Smart Grid Project) Jump to: navigation, search Project Name Demand response medium sized industry consumers Country Denmark Headquarters Location Aarhus, Denmark Coordinates 56.162937°, 10.203921° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":56.162937,"lon":10.203921,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

470

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

471

Production Will Meet Demand Increase This Summer  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: Production must meet increases in demand this year. Last year, increased imports met most of the summer demand increase, and increases in stock draws met almost all of the remainder. Production did not increase much. But this year, inventories will not be available, and increased imports seem unlikely. Thus, increases in production will be needed to meet increased demand. Imports availability is uncertain this summer. Imports in 1999 were high, and with Phase II RFG product requirements, maintaining this level could be challenging since not all refineries exporting to the U.S. will be able to meet the new gasoline specifications. Stocks will also contribute little supply this summer. Last year's high gasoline stocks allowed for a stock draw that was 58 MB/D higher than

472

Wireless Demand Response Controls for HVAC Systems  

Science Conference Proceedings (OSTI)

The objectives of this scoping study were to develop and test control software and wireless hardware that could enable closed-loop, zone-temperature-based demand response in buildings that have either pneumatic controls or legacy digital controls that cannot be used as part of a demand response automation system. We designed a SOAP client that is compatible with the Demand Response Automation Server (DRAS) being used by the IOUs in California for their CPP program, design the DR control software, investigated the use of cellular routers for connecting to the DRAS, and tested the wireless DR system with an emulator running a calibrated model of a working building. The results show that the wireless DR system can shed approximately 1.5 Watts per design CFM on the design day in a hot, inland climate in California while keeping temperatures within the limits of ASHRAE Standard 55: Thermal Environmental Conditions for Human Occupancy.

Federspiel, Clifford

2009-06-30T23:59:59.000Z

473

Centralized and Decentralized Control for Demand Response  

Science Conference Proceedings (OSTI)

Demand response has been recognized as an essential element of the smart grid. Frequency response, regulation and contingency reserve functions performed traditionally by generation resources are now starting to involve demand side resources. Additional benefits from demand response include peak reduction and load shifting, which will defer new infrastructure investment and improve generator operation efficiency. Technical approaches designed to realize these functionalities can be categorized into centralized control and decentralized control, depending on where the response decision is made. This paper discusses these two control philosophies and compares their relative advantages and disadvantages in terms of delay time, predictability, complexity, and reliability. A distribution system model with detailed household loads and controls is built to demonstrate the characteristics of the two approaches. The conclusion is that the promptness and reliability of decentralized control should be combined with the predictability and simplicity of centralized control to achieve the best performance of the smart grid.

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

2011-04-29T23:59:59.000Z

474

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.

475

Electric Water Heater Modeling and Control Strategies for Demand Response  

Science Conference Proceedings (OSTI)

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

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

2012-07-22T23:59:59.000Z

476

Laboratory Testing of Demand-Response Enabled Household Appliances  

SciTech Connect

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

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

2013-10-01T23:59:59.000Z

477

Demand Response and Storage Integration Study: Markets Report Overview  

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

Andy Satchwell Andy Satchwell Scientific Engineering Associate Lawrence Berkeley National Laboratory National Association of Regulatory Utility Commissioners, ER&E Committee Meeting, July 24, 2012 Portland, OR Tools and Methods Working Group Energy Analysis and Environmental Impacts Department Outline of Presentation  Introduction and background: DR Estimation Tools and Methods Working Group  Working group members  Work plan  Identification of estimation tools and methods needs  Preliminary gap analysis  Next steps 2 Energy Analysis and Environmental Impacts Department Introduction and Background  Tools and techniques have been developed to help characterize demand response (DR) resources  Given diversity in types of DR programs and relative

478

Demand Responsive Lighting: A Scoping Study  

SciTech Connect

The objective of this scoping study is: (1) to identify current market drivers and technology trends that can improve the demand responsiveness of commercial building lighting systems and (2) to quantify the energy, demand and environmental benefits of implementing lighting demand response and energy-saving controls strategies Statewide. Lighting systems in California commercial buildings consume 30 GWh. Lighting systems in commercial buildings often waste energy and unnecessarily stress the electrical grid because lighting controls, especially dimming, are not widely used. But dimmable lighting equipment, especially the dimming ballast, costs more than non-dimming lighting and is expensive to retrofit into existing buildings because of the cost of adding control wiring. Advances in lighting industry capabilities coupled with the pervasiveness of the Internet and wireless technologies have led to new opportunities to realize significant energy saving and reliable demand reduction using intelligent lighting controls. Manufacturers are starting to produce electronic equipment--lighting-application specific controllers (LAS controllers)--that are wirelessly accessible and can control dimmable or multilevel lighting systems obeying different industry-accepted protocols. Some companies make controllers that are inexpensive to install in existing buildings and allow the power consumed by bi-level lighting circuits to be selectively reduced during demand response curtailments. By intelligently limiting the demand from bi-level lighting in California commercial buildings, the utilities would now have an enormous 1 GW demand shed capability at hand. By adding occupancy and light sensors to the remotely controllable lighting circuits, automatic controls could harvest an additional 1 BkWh/yr savings above and beyond the savings that have already been achieved. The lighting industry's adoption of DALI as the principal wired digital control protocol for dimming ballasts and increased awareness of the need to standardize on emerging wireless technologies are evidence of this transformation. In addition to increased standardization of digital control protocols controller capabilities, the lighting industry has improved the performance of dimming lighting systems over the last two years. The system efficacy of today's current dimming ballasts is approaching that of non-dimming program start ballasts. The study finds that the benefits of applying digital controls technologies to California's unique commercial buildings market are enormous. If California were to embark on an concerted 20 year program to improve the demand responsiveness and energy efficiency of commercial building lighting systems, the State could avoid adding generation capacity, improve the elasticity of the grid, save Californians billion of dollars in avoided energy charges and significantly reduce greenhouse gas emissions.

Rubinstein, Francis; Kiliccote, Sila

2007-01-03T23:59:59.000Z

479

Demand Responsive Lighting: A Scoping Study  

SciTech Connect

The objective of this scoping study is: (1) to identify current market drivers and technology trends that can improve the demand responsiveness of commercial building lighting systems and (2) to quantify the energy, demand and environmental benefits of implementing lighting demand response and energy-saving controls strategies Statewide. Lighting systems in California commercial buildings consume 30 GWh. Lighting systems in commercial buildings often waste energy and unnecessarily stress the electrical grid because lighting controls, especially dimming, are not widely used. But dimmable lighting equipment, especially the dimming ballast, costs more than non-dimming lighting and is expensive to retrofit into existing buildings because of the cost of adding control wiring. Advances in lighting industry capabilities coupled with the pervasiveness of the Internet and wireless technologies have led to new opportunities to realize significant energy saving and reliable demand reduction using intelligent lighting controls. Manufacturers are starting to produce electronic equipment--lighting-application specific controllers (LAS controllers)--that are wirelessly accessible and can control dimmable or multilevel lighting systems obeying different industry-accepted protocols. Some companies make controllers that are inexpensive to install in existing buildings and allow the power consumed by bi-level lighting circuits to be selectively reduced during demand response curtailments. By intelligently limiting the demand from bi-level lighting in California commercial buildings, the utilities would now have an enormous 1 GW demand shed capability at hand. By adding occupancy and light sensors to the remotely controllable lighting circuits, automatic controls could harvest an additional 1 BkWh/yr savings above and beyond the savings that have already been achieved. The lighting industry's adoption of DALI as the principal wired digital control protocol for dimming ballasts and increased awareness of the need to standardize on emerging wireless technologies are evidence of this transformation. In addition to increased standardization of digital control protocols controller capabilities, the lighting industry has improved the performance of dimming lighting systems over the last two years. The system efficacy of today's current dimming ballasts is approaching that of non-dimming program start ballasts. The study finds that the benefits of applying digital controls technologies to California's unique commercial buildings market are enormous. If California were to embark on an concerted 20 year program to improve the demand responsiveness and energy efficiency of commercial building lighting systems, the State could avoid adding generation capacity, improve the elasticity of the grid, save Californians billion of dollars in avoided energy charges and significantly reduce greenhouse gas emissions.

Rubinstein, Francis; Kiliccote, Sila

2007-01-03T23:59:59.000Z

480

Regional Workshop on Opportunities and Priorities for Low Carbon...  

Open Energy Info (EERE)

Region Inside the Low Carbon Green Growth: Innovations in Green Energy Supply Demand Side Energy Efficiency Solutions: A Low Hanging Fruit Managing the Technology for Low Carbon...

Note: This page contains sample records for the topic "type demand region" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

State and Regional Policy Assistance - Program Activities | Department...  

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

and long-terms needs of states, regions, and other organizations to implement policy and market solutions that bring about improved demand response, energy efficiency, renewable...

482

Automated Demand Response Strategies and Commissioning Commercial Building Controls  

E-Print Network (OSTI)

4 9 . Piette et at Automated Demand Response Strategies andDynamic Controls for Demand Response in New and ExistingFully Automated Demand Response Tests in Large Facilities"

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

2006-01-01T23:59:59.000Z

483

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

484

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

as 15-minute minimum and maximum demand values are provided.8. Hourly average and maximum demand savings of McKinstry on9. Hourly average and maximum demand savings of McKinstry on

Kiliccote, Sila

2010-01-01T23:59:59.000Z

485

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

if the customer’s maximum demand has exceeded 999 kilowattswhose meter indicates a maximum demand of 200 kW or greater2) the customer's maximum billing demand has exceeded 499

Ghatikar, Girish

2010-01-01T23:59:59.000Z

486

Open Automated Demand Response for Small Commerical Buildings  

E-Print Network (OSTI)

the average, minimum and maximum demand reduction for each Average, Minimum and Maximum Demand Reduction Based on 3/1016 Average, Minimum and Maximum Demand Reduction Based on

Dudley, June Han

2009-01-01T23:59:59.000Z

487

Open Automated Demand Response for Small Commerical Buildings  

E-Print Network (OSTI)

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

Dudley, June Han

2009-01-01T23:59:59.000Z

488

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

serves to partially fill off-peak demand troughs. If passivehigher before or after the peak demand hour when hydro powerare highest during off-peak demand hours, and are low at

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

489

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

490

Automated Demand Response Opportunities in Wastewater Treatment Facilities  

E-Print Network (OSTI)

power generators during peak demand periods. 13 Onsite powerit can be used during peak-demand periods. 15 Implementingtreatment loads from peak demand hours to off-peak hours is

Thompson, Lisa

2008-01-01T23:59:59.000Z

491

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

492

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

Non-vehicle demand load factor Natural gas price Carbon tax89). They increase with demand (and gross natural gas-firedelectricity demand and by changing natural gas price and CO

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

493

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.

494

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

E-Print Network (OSTI)

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

495

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

SciTech Connect

Recent forecasts of total electricity generating capacity and energy demand as well as for electricity produced from nuclear energy and hydroelectric power are presented in tables and graphs to the year 2000. A forecast of the distribution of type of fuel and energy source that will supply the future electricity demand is presented. Use of electricity by each major consuming sector is presented for 1975. Projected demands for electricity in the years 1985 and 2000, as allocated to consuming sectors, are derived and presented.

Lane, J.A.

1976-02-01T23:59:59.000Z

496

Installation and Commissioning Automated Demand Response Systems  

Science Conference Proceedings (OSTI)

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

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

2008-04-21T23:59:59.000Z

497

Patterns of crude demand: Future patterns of demand for crude oil as a func-  

E-Print Network (OSTI)

from the perspective of `peak oil', that is from the pers- pective of the supply of crude, and price#12;2 #12;Patterns of crude demand: Future patterns of demand for crude oil as a func- tion is given on the problems within the value chain, with an explanation of the reasons why the price of oil

Langendoen, Koen

498

Automated Demand Response Technology Demonstration Project for Small and  

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

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

499

Impacts of Energy Storage Systems in Addressing Regional Wind Penetration: Case Studies in NYISO and ERCOT  

Science Conference Proceedings (OSTI)

Optimal use of electric energy storage systems is expected to play a key role in supporting wind integration, relieving transmission and distribution (T&D) congestion, and improving the balance of supply and demand. However, there have been very limited assessments of what types and sizes of storage systems are optimal and what locations are the most promising. In 2009, an EPRI initial assessment of energy storage in ERCOT (EPRI report 1017824) recommended more regional market simulation studies to furth...

2010-12-23T23:59:59.000Z

500

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