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1

System Demand-Side Management: Regional results  

SciTech Connect (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

Tankless or Demand-Type Water Heaters | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

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.

3

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect (OSTI)

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

4

World oil demand’s shift toward faster growing and less price-responsive products and regions  

Science Journals Connector (OSTI)

Using data for 1971–2008, we estimate the effects of changes in price and income on world oil demand, disaggregated by product – transport oil, fuel oil (residual and heating oil), and other oil – for six groups of countries. Most of the demand reductions since 1973–74 were due to fuel-switching away from fuel oil, especially in the OECD; in addition, the collapse of the Former Soviet Union (FSU) reduced their oil consumption substantially. Demand for transport and other oil was much less price-responsive, and has grown almost as rapidly as income, especially outside the OECD and FSU. World oil demand has shifted toward products and regions that are faster growing and less price-responsive. In contrast to projections to 2030 of declining per-capita demand for the world as a whole – by the U.S. Department of Energy (DOE), International Energy Agency (IEA) and OPEC – we project modest growth. Our projections for total world demand in 2030 are at least 20% higher than projections by those three institutions, using similar assumptions about income growth and oil prices, because we project rest-of-world growth that is consistent with historical patterns, in contrast to the dramatic slowdowns which they project.

Joyce M. Dargay; Dermot Gately

2010-01-01T23:59:59.000Z

5

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)"

6

"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"

7

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"

8

Analysis of regional demand for natural gas by black and nonblack families  

SciTech Connect (OSTI)

This study examines long-term implications of a hypothetical 20% increase in the price of natural gas for black and nonblack families, by household, in the continental United States. The analysis focuses on four specific effects of such an increase: demand for natural gas, expenditure for natural gas, natural gas expenditure as a share of family income, and consumer surplus. Data are organized geographically to represent three sections of the continental United States - the northeastern states, the north central states, and the southern and western states. (The state groupings are identical to those represented in the country's census regions; the southern and western census regions were combined because of data limitations). The report presents demand equations that were used to estimate gas consumption and expenditure by average black and nonblack families in the three geographic areas. Models representing typical household types, each with a specific set of attributes, are then presented to show average base-year values for natural gas consumption and expenditure for two types of black and nonblack families - those that use natural gas for any purpose and only those that use it for space heating. (Base-period values are estimated using data from a DOE survey conducted in the years 1980 and 1981). The effects of a hypothetical 20% increase in the price of natural gas on the various household types were then estimated. Those effects are summarized. Families using natural gas for a any purpose in the north central states would experience the greatest long-term effects of a 20% price increase. Black families in those states would feel the effects more dramatically than nonblack families. The relative geographic effects of such a price increase change, however, when only those families that use natural gas for space heating are analyzed. 3 references, 4 figures, 18 tables.

Poyer, D.A.

1984-08-01T23:59:59.000Z

9

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...

Higgins, Lindsey M.

2010-07-14T23:59:59.000Z

10

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

SciTech Connect (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

11

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

SciTech Connect (OSTI)

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

12

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

Broader source: Energy.gov (indexed) [DOE]

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

13

Regional Differences in the Price-Elasticity of Demand for Energy  

SciTech Connect (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

14

"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"

15

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

16

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

17

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

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

18

Energy Demand Forecast for South East Asia Region: An Econometric Approach with Relation to the Energy Per Capita “Curve”  

Science Journals Connector (OSTI)

Based on the causality analysis completed for the ASEAN region, macroeconomic factors have a strong relation with increasing the power demand. The bi-directional relationship from energy causing the increase of e...

Nuki Agya Utama; Keiichi N. Ishihara; Tetsuo Tezuka…

2013-01-01T23:59:59.000Z

19

Formal Type Soundness for Cyclone's Region System Dan Grossman  

E-Print Network [OSTI]

management of Cyclone and its static typing discipline. The design incorporates several advance- mentsFormal Type Soundness for Cyclone's Region System Dan Grossman Greg Morrisett Trevor Jim Mike Hicks Yanling Wang James Cheney November 2001 Abstract Cyclone is a polymorphic, type-safe programming language

Hicks, Michael

20

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

SciTech Connect (OSTI)

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

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

Magnetoresistance of p-Type Si in the Hopping Region  

Science Journals Connector (OSTI)

The magnetoresistance in the hopping region of B-doped Si was found to be negative. This contrasts with the behavior in n-type Ge, where a positive magnetoresistance is characteristic of the hopping conduction region. No anisotropy is observed in fields up to 17 kG in the p-type Si. The resistance tends to saturate at about 15 kG. The change in dc resistance at that field is about 10% from the zero-field value.

M. Pollak and D. H. Watt

1963-02-15T23:59:59.000Z

22

Modeling regional transportation demand in China and the impacts of a national carbon constraint  

E-Print Network [OSTI]

Climate and energy policy in China will have important and uneven impacts on the country’s regionally heterogeneous transport system. In order to simulate these impacts, transport sector detail is added to a multi-sector, ...

Kishimoto, Paul

2015-01-30T23:59:59.000Z

23

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

Science Journals Connector (OSTI)

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

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

2014-02-10T23:59:59.000Z

24

Demand Response Programs for Oregon  

E-Print Network [OSTI]

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

25

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

Science Journals Connector (OSTI)

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

Inderjeet Singh; N.K. Bansal

2004-01-01T23:59:59.000Z

26

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

27

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

28

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

29

Demand Reduction  

Broader source: Energy.gov [DOE]

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

30

Mass Market Demand Response  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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,

31

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

SciTech Connect (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

32

Energy demand  

Science Journals Connector (OSTI)

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

Geoffrey Greenhalgh

1980-01-01T23:59:59.000Z

33

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

SciTech Connect (OSTI)

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.

Not Available

1981-06-01T23:59:59.000Z

34

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

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

35

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

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

36

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

37

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

38

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

39

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)

40

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)

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

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

42

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.

43

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

44

Coordination of Energy Efficiency and Demand Response  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

45

Some inferences on the role of lower positive charge region in facilitating different types of lightning  

E-Print Network [OSTI]

of lightning Amitabh Nag1 and Vladimir A. Rakov1 Received 24 November 2008; revised 22 January 2009; accepted 3'' the potential cloud-to-ground flash to an intracloud (or cloud-to-air) one. Assuming that the preliminary with the lower positive charge region, we qualitatively examine the inferred dependence of lightning type

Florida, University of

46

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

47

Demand Response Programs, 6. edition  

SciTech Connect (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

48

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

49

" 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"

50

Demand Response  

Broader source: Energy.gov (indexed) [DOE]

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

51

Demand Response and Open Automated Demand Response  

E-Print Network [OSTI]

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

52

The metal abundance of circumnuclear star forming regions in early type spirals. Spectrophotometric observations  

E-Print Network [OSTI]

We have obtained long-slit observations in the optical and near infrared of 12 circumnuclear HII regions (CNSFR) in the early type spiral galaxies NGC 2903, NGC 3351 and NGC 3504 with the aim of deriving their chemical abundances. Only for one of the regions, the [SIII] $\\lambda$ 6312 \\AA was detected providing, together with the nebular [SIII] lines at $\\lambda\\lambda$ 9069, 9532 \\AA, a value of the electron temperature of T$_e$([SIII])= 8400$^{+ 4650}_{-1250}$K. A semi-empirical method for the derivation of abundances in the high metallicity regime is presented. We obtain abundances which are comparable to those found in high metallicity disc HII regions from direct measurements of electron temperatures and consistent with solar values within the errors. The region with the highest oxygen abundance is R3+R4 in NGC 3504, 12+log(O/H) = 8.85, about 1.5 solar if the solar oxygen abundance is set at the value derived by Asplund et al. (2005), 12+log(O/H)$_{\\odot}$ = 8.66$\\pm$0.05. Region R7 in NGC 3351 has the lowest oxygen abundance of the sample, about 0.6 times solar. In all the observed CNSFR the O/H abundance is dominated by the O$^+$/H$^+$ contribution, as is also the case for high metallicity disc HII regions. For our observed regions, however, also the S$^+$/S$^{2+}$ ratio is larger than one, contrary to what is found in high metallicity disc HII regions for which, in general, the sulphur abundances are dominated by S$^{2+}$/H$^+$...

Angeles I. Diaz; Elena Terlevich; Marcelo Castellanos; Guillermo F. Hagele

2007-09-08T23:59:59.000Z

53

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.

54

Seasonal temperature variations and energy demand  

Science Journals Connector (OSTI)

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

Enrica De Cian; Elisa Lanzi; Roberto Roson

2013-02-01T23:59:59.000Z

55

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)

56

Water deuterium fractionation in the inner regions of two solar type protostars  

E-Print Network [OSTI]

The [HDO]/[H2O] ratio is a crucial parameter for probing the history of water formation. So far, it has been measured for only three solar type protostars and yielded different results, possibly pointing to a substantially different history in their formation. In the present work, we report new interferometric observations of the HDO 4 2,2 - 4 2,3 line for two solar type protostars, IRAS2A and IRAS4A, located in the NGC1333 region. In both sources, the detected HDO emission originates from a central compact unresolved region. Comparison with previously published interferometric observations of the H218$O 3 1,3 - 2 2,0 line shows that the HDO and H$_2$O lines mostly come from the same region. A non-LTE LVG analysis of the HDO and H218$O line emissions, combined with published observations, provides a [HDO]/[H2O] ratio of 0.3 - 8 % in IRAS2A and 0.5 - 3 % in IRAS4A. First, the water fractionation is lower than that of other molecules such as formaldehyde and methanol in the same sources. Second, it is similar t...

Taquet, Vianney; Ceccarelli, Cecilia; Neri, Roberto; Kahane, Claudine; Coutens, Audrey; Vastel, Charlotte

2013-01-01T23:59:59.000Z

57

Commercial & Industrial Demand Response  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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

58

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

59

Spatial Variation of Soil Type and Soil Moisture in the Regional Atmospheric Modeling System  

SciTech Connect (OSTI)

Soil characteristics (texture and moisture) are typically assumed to be initially constant when performing simulations with the Regional Atmospheric Modeling System (RAMS). Soil texture is spatially homogeneous and time-independent, while soil moisture is often spatially homogeneous initially, but time-dependent. This report discusses the conversion of a global data set of Food and Agriculture Organization (FAO) soil types to RAMS soil texture and the subsequent modifications required in RAMS to ingest this information. Spatial variations in initial soil moisture obtained from the National Center for Environmental Predictions (NCEP) large-scale models are also introduced. Comparisons involving simulations over the southeastern United States for two different time periods, one during warmer, more humid summer conditions, and one during cooler, dryer winter conditions, reveals differences in surface conditions related to increases or decreases in near-surface atmospheric moisture con tent as a result of different soil properties. Three separate simulation types were considered. The base case assumed spatially homogeneous soil texture and initial soil moisture. The second case assumed variable soil texture and constant initial soil moisture, while the third case allowed for both variable soil texture and initial soil moisture. The simulation domain was further divided into four geographically distinct regions. It is concluded there is a more dramatic impact on thermodynamic variables (surface temperature and dewpoint) than on surface winds, and a more pronounced variability in results during the summer period. While no obvious trends in surface winds or dewpoint temperature were found relative to observations covering all regions and times, improvement in surface temperatures in most regions and time periods was generally seen with the incorporation of variable soil texture and initial soil moisture.

Buckley, R.

2001-06-27T23:59:59.000Z

60

Energy and Security in Northeast Asia: Supply and Demand, Conflict and  

E-Print Network [OSTI]

3 Energy Policies and Energy Demand in Northeastissue of whether rising energy demand generates new securityoverall regional energy demand (Fesharaki, Sara Banaszak,

Fesharaki, Fereidun; Banaszak, Sarah; WU, Kang; Valencia, Mark J.; Dorian, James P.

1998-01-01T23:59:59.000Z

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.


61

Classification of Hepatitis C Virus Type 2 Isolates by Phylogenetic Analysis of Core and NS5 Regions  

Science Journals Connector (OSTI)

...Virus Type 2 Isolates by Phylogenetic Analysis of Core and NS5 Regions Mauro Pistello Fabrizio Maggi Claudia Fornai Alessandro Leonildi Antonietta Morrica Maria Linda Vatteroni Mauro Bendinelli Retrovirus Center and Virology Section Department of Biomedicine...

Mauro Pistello; Fabrizio Maggi; Claudia Fornai; Alessandro Leonildi; Antonietta Morrica; Maria Linda Vatteroni; Mauro Bendinelli

1999-06-01T23:59:59.000Z

62

A Survey on Privacy in Residential Demand Side Management Applications  

Science Journals Connector (OSTI)

Demand Side Management (DSM) is an auspicious concept for ... on privacy energy issues and potential solutions in Demand Response systems. For this we give an ... the BSI and indicate three technical types of Demand

Markus Karwe; Jens Strüker

2014-01-01T23:59:59.000Z

63

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

64

THE EXTENDED NARROW-LINE REGION OF TWO TYPE-I QUASI-STELLAR OBJECTS  

SciTech Connect (OSTI)

We investigate the narrow-line region (NLR) of two radio-quiet QSOs, PG1012+008 and PG1307+085, using high signal-to-noise spatially resolved long-slit spectra obtained with FORS1 at the Very Large Telescope. Although the emission is dominated by the point-spread function of the nuclear source, we are able to detect extended NLR emission out to several kiloparsec scales in both QSOs by subtracting the scaled central spectrum from outer spectra. In contrast to the nuclear spectrum, which shows a prominent blue wing and a broad line profile of the [O III] line, the extended emission reveals no clear signs of large-scale outflows. Exploiting the wide wavelength range, we determine the radial change of the gas properties in the NLR, i.e., gas temperature, density, and ionization parameter, and compare them with those of Seyfert galaxies and type-II QSOs. The QSOs have higher nuclear temperature and lower electron density than Seyferts, but show no significant difference compared to type-II QSOs, while the ionization parameter decreases with radial distance, similar to the case of Seyfert galaxies, For PG1012+008, we determine the stellar-velocity dispersion of the host galaxy. Combined with the black hole mass, we find that the luminous radio-quiet QSO follows the local M{sub BH}-{sigma}{sub *} relation of active galactic nuclei.

Oh, Semyeong; Woo, Jong-Hak [Astronomy Program, Department of Physics and Astronomy, Seoul National University, Seoul 151-742 (Korea, Republic of); Bennert, Vardha N. [Physics Department, California Polytechnic State University San Luis Obispo, CA 93407 (United States); Jungwiert, Bruno [Astronomical Institute, Academy of Sciences of the Czech Republic, Bocni II 1401/1a, CZ-141 31 Prague (Czech Republic); Haas, Martin [Astronomisches Institut, Ruhr-Universitaet Bochum, Universitaetsstrasse 150, D-44801 Bochum (Germany); Leipski, Christian [Max-Planck Institut fuer Astronomie, Koenigstuhl 17, D-69117 Heidelberg (Germany); Albrecht, Marcus, E-mail: smoh@astro.snu.ac.kr, E-mail: woo@astro.snu.ac.kr, E-mail: vbennert@calpoly.edu, E-mail: bruno@ig.cas.cz, E-mail: haas@astro.rub.de, E-mail: leipski@mpia-hd.mpg.de, E-mail: malbrecht@astro.uni-bonn.de [Argelander-Institut fuer Astronomie, Auf dem Huegel 71, 53121 Bonn (Germany)

2013-04-20T23:59:59.000Z

65

Paleocene benthonic foraminiferal biostratigraphy, paleobiogeography and paleoecology of Atlantic—Tethyan regions: Midway-type fauna  

Science Journals Connector (OSTI)

The stratigraphic, geographic and bathymetric distribution of some Paleocene benthonic foraminiferal assemblages have been studied in the Tethyan and circum-Atlantic regions within the framework of planktonic foraminiferal zones. Although some species appear to be restricted to either the Tethyan-European area or to the western Atlantic, the majority of species are amphi-Atlantic and Tethyan in distribution. The cosmopolitan distribution is attributed to more equitable climatic conditions (lower polar—equatorial thermal gradient) and warmer, more uniform thermal structure of the oceans and different paleogeographic and paleo-oceanographic conditions. Two main distinct depth-controlled benthonic foraminiferal assemblages (exclusive of the shallow-warm water Tethyan carbonate assemblage) have been recognized in the Paleocene. The continental shelf fauna, termed here the “Midway-type fauna” (MF) is characterized by species of Cibicidoides alleni (Plummer) = propria Brotzen, howelli (Toulmin), succedens (Brotzen), Anomalinoides [acuta (Plummer), midwayensis (Plummer)], Gavelinella [danica (Brotzen), neelyi (Jennings)], and Osangularia plummerae Brotzen, as well as various lagenids (nodosariids, lenticulinids, vaginulinids), polymorphinids and textulariids. A lower continental slope and abyssal plain fauna, termed here the “Velasco-type fauna” (VF), is characterized by, amongst others, Gavalinella [beccariiformis (White), rubiginosa (Cushman), velascoensis (Cushman)], Nuttallides truempy (Nuttall), Nuttallinella florealis (Cushman), velascoensisZ (Cushman)], (Cushman), Aragonia velascoensis (Cushman), nodosariids (N. velascoensis Cushman, Dentalina limbata d'Orbigny), various agglutinated forms [Gaudryina pyramidata Cushman, Tritaxia aspera (Cushman), Dorothia ex. gr. oxycona trinitatensis (Cushman and Renz)], and various gyroidinids and buliminids. Pleuriostomellids and stilostomellids are quantitatively rare and unimportant until the Middle—Late Eocene. This paper discusses the biostratigraphy and biogeography of the “Midway-type fauna”.

W.A. Berggren; Jane Aubert

1975-01-01T23:59:59.000Z

66

Advanced Demand Responsive Lighting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

67

Abstract 2322: The KIAA1549:BRAF fusion gene regulates mTOR signaling and gliomagenesis in a cell type- and brain region-specific manner.  

Science Journals Connector (OSTI)

...The KIAA1549:BRAF fusion gene regulates mTOR...gliomagenesis in a cell type- and brain region-specific...region- and cell type-specific growth...also observed in fusion BRAF-associated...The KIAA1549:BRAF fusion gene regulates mTOR...gliomagenesis in a cell type- and brain region-specific...

Aparna Kaul; Yi-Hsien Chen; Ryan J. Emnett; Sonika Dahiya; and David Gutmann

2013-08-14T23:59:59.000Z

68

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

69

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network [OSTI]

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

Shen, Bo

2013-01-01T23:59:59.000Z

70

Demand Response Valuation Frameworks Paper  

E-Print Network [OSTI]

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

Heffner, Grayson

2010-01-01T23:59:59.000Z

71

Demand Response Assessment INTRODUCTION  

E-Print Network [OSTI]

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

72

A Simulation Study of Demand Responsive Transit System Design  

E-Print Network [OSTI]

A Simulation Study of Demand Responsive Transit System Design Luca Quadrifoglio, Maged M. Dessouky changed the landscape for demand responsive transit systems. First, the demand for this type of transit experiencing increased usage for demand responsive transit systems. The National Transit Summaries and Trends

Dessouky, Maged

73

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network [OSTI]

these trends lead to declining natural gas consumption byNatural gas demand has been rising in California and this trendnatural gas demands regionally, to account for variability in energy usage trends

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

2008-01-01T23:59:59.000Z

74

Evidence of two different types of short term solar modulation of regional surface temperature and cloud  

E-Print Network [OSTI]

Recent work indicates that 27 day variations in cosmic ray flux during 2007 2009 are phase locked to 27 day variations in cloud and surface temperature at Shetland. Here we extend the study to other regions including Central England, US and Australia and to several other annual intervals that exhibit strong 27 day variation in cosmic ray flux and sunspot area. Band pass filtering was used to obtain 27 day components of daily maximum temperature in each region and 27 day components of cloud variation were determined, in Australia only, from solar exposure records. When cosmic ray flux is the dominant influence phase locked variations in surface temperature occur in each of the regions with, however, in phase or anti phase variation in different regions. Similar phase locking of 27 day variation in surface temperature to sunspot area variation occurs when sunspot activity is the dominant influence with indications that changes from in phase to anti phase variation are linked to flipping of sunspot activity from...

Edmonds, Ian

2014-01-01T23:59:59.000Z

75

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

76

Demand response enabling technology development  

E-Print Network [OSTI]

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

2006-01-01T23:59:59.000Z

77

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

78

Cross-sector Demand Response  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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

79

Demand response enabling technology development  

E-Print Network [OSTI]

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

Arens, Edward; Auslander, David; Huizenga, Charlie

2008-01-01T23:59:59.000Z

80

Automated Demand Response and Commissioning  

E-Print Network [OSTI]

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

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

2005-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "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

Genomic Imprinting Variations in the Mouse Type 3 Deiodinase Gene Between Tissues and Brain Regions  

E-Print Network [OSTI]

, tissues were dissected, immediately frozen on dry ice and stored at –70 C until further use. Brain regions were identified and harvested according to the mouse atlas by Paxinos (30). Animal procedures were approved by the Institutional Animal Care and Use... paternal, allele. This suggests that expression and associated alterations in chromatin facil- itate homologous recombination. The result is also con- sistent with observations that suggest the existence of epi- genetic boundaries that are associated with a...

Martinez, M. Elena; Charalambous, Marika; Saferali, Aabida; Fiering, Steven; Naumova, Anna K.; St. Germain, Donald; Ferguson-Smith, Anne C.; Hernandez, Arturo

2014-09-18T23:59:59.000Z

82

Demand Response In California  

Broader source: Energy.gov [DOE]

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

83

Energy Demand Forecasting  

Science Journals Connector (OSTI)

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

S. C. Bhattacharyya

2011-01-01T23:59:59.000Z

84

Building Energy Software Tools Directory: Demand Response Quick Assessment  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

85

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

Broader source: Energy.gov (indexed) [DOE]

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

86

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network [OSTI]

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

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

87

RTP Customer Demand Response  

Science Journals Connector (OSTI)

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

Steven Braithwait; Michael O’Sheasy

2002-01-01T23:59:59.000Z

88

World Energy Demand  

Science Journals Connector (OSTI)

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

Giovanni Petrecca

2014-01-01T23:59:59.000Z

89

A Foundation of Demand-Side Resource Management in Distributed Systems  

Science Journals Connector (OSTI)

The theoretical problems of demand-side management are examined in without regard to the type of resource whose demand is to be managed, and the Maximum Demand problem is identified and addressed in a ... resourc...

Shrisha Rao

2010-01-01T23:59:59.000Z

90

Neutralization Efficiency Is Greatly Enhanced by Bivalent Binding of an Antibody to Epitopes in the V4 Region and the Membrane-Proximal External Region within One Trimer of Human Immunodeficiency Virus Type 1 Glycoproteins  

Science Journals Connector (OSTI)

...External Region within One Trimer of Human Immunodeficiency Virus Type 1 Glycoproteins Published ahead of print on 12 May 2010. Pengcheng Wang Present address: Department of Microbiology and Immunology, Medical College of Jinan University, Guangzhou, Guangdong...

Pengcheng Wang; Xinzhen Yang

2010-05-12T23:59:59.000Z

91

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

92

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network [OSTI]

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

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

93

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network [OSTI]

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

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

94

Changing Energy Demand Behavior: Potential of Demand-Side Management  

Science Journals Connector (OSTI)

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

Dr. Sylvia Breukers; Dr. Ruth Mourik…

2013-01-01T23:59:59.000Z

95

Distribution Patterns of Metals Contamination in Sediments Based on Type Regional Development on the Intertidal Coastal Zones of the Persian Gulf, Iran  

Science Journals Connector (OSTI)

This study was performed to determine the variation of metals concentrations (Pb, Cd, Zn, and Cu) in surface sediments based on type region development from ten sites on the intertidal coastal zone of the Persian

Ali Kazemi; Alireza Riyahi Bakhtiari…

2012-01-01T23:59:59.000Z

96

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

97

Coordination of Energy Efficiency and Demand Response  

SciTech Connect (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

98

Demand Response In California  

Broader source: Energy.gov (indexed) [DOE]

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

99

Strategies for Demand Response in Commercial Buildings  

SciTech Connect (OSTI)

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

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

2006-06-20T23:59:59.000Z

100

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":""}]}

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

Demand Response - Policy: More Information | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

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

102

National Action Plan on Demand Response  

Broader source: Energy.gov (indexed) [DOE]

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

103

Introduction Potato Types and Uses The potato is native to the Andean region of South Potato varieties vary according to shape, flesh color  

E-Print Network [OSTI]

Introduction Potato Types and Uses The potato is native to the Andean region of South Potato, tuber type similar to the following examples: potatoes are the fourth most important food crop are planted each year for commercial production. The LongIWhite Skin: White Rose, Shepody potato is a member

Douches, David S.

104

Energy Demand Staff Scientist  

E-Print Network [OSTI]

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

Eisen, Michael

105

Energy Demand Modeling  

Science Journals Connector (OSTI)

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

S. L. Schwartz

1980-01-01T23:59:59.000Z

106

Demand Activated Manufacturing Architecture  

SciTech Connect (OSTI)

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

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

2001-02-07T23:59:59.000Z

107

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":""}]}

108

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

109

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

110

Utility Sector Impacts of Reduced Electricity Demand  

SciTech Connect (OSTI)

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

Coughlin, Katie

2014-12-01T23:59:59.000Z

111

Ethanol Demand in United States Gasoline Production  

SciTech Connect (OSTI)

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

112

Demand Response | Department of Energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

113

Understanding and Analysing Energy Demand  

Science Journals Connector (OSTI)

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

Subhes C. Bhattacharyya

2011-01-01T23:59:59.000Z

114

Transportation Demand This  

Gasoline and Diesel Fuel Update (EIA)

(VMT) per vehicle by fleet type stays constant over the forecast period based on the Oak Ridge National Laboratory fleet data. Fleet fuel economy for both conventional and...

115

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

116

Demand Response: Load Management Programs  

E-Print Network [OSTI]

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

Simon, J.

2012-01-01T23:59:59.000Z

117

Marketing Demand-Side Management  

E-Print Network [OSTI]

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

O'Neill, M. L.

1988-01-01T23:59:59.000Z

118

Demand Charges | Open Energy Information  

Open Energy Info (EERE)

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

119

Interoperability of Demand Response Resources Demonstration in NY  

SciTech Connect (OSTI)

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

Wellington, Andre

2014-03-31T23:59:59.000Z

120

Assessment of Demand Response Resource  

E-Print Network [OSTI]

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

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

ERCOT Demand Response Paul Wattles  

E-Print Network [OSTI]

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

Mohsenian-Rad, Hamed

122

Pricing data center demand response  

Science Journals Connector (OSTI)

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

Zhenhua Liu; Iris Liu; Steven Low; Adam Wierman

2014-06-01T23:59:59.000Z

123

Driving Demand for Home Energy Improvements  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

124

The San Diego Foundation Regional Focus 2050 Study  

E-Print Network [OSTI]

Regional Growth Forecast Reverse Osmosis Reactive organicenergy demand.   Reverse osmosis (RO) systems do not 

2008-01-01T23:59:59.000Z

125

Overview of Demand Response  

Broader source: Energy.gov (indexed) [DOE]

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

126

Mass Market Demand Response and Variable Generation Integration Issues: A  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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).

127

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

128

Scenario Analysis of Peak Demand Savings for Commercial Buildings with  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

129

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

130

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

131

Unlocking the potential for efficiency and demand response through advanced  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

132

Rates and technologies for mass-market demand response  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

133

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.

134

Forecasting intermittent demand by hyperbolic-exponential smoothing  

Science Journals Connector (OSTI)

Abstract Croston’s method is generally viewed as being superior to exponential smoothing when the demand is intermittent, but it has the drawbacks of bias and an inability to deal with obsolescence, where the demand for an item ceases altogether. Several variants have been reported, some of which are unbiased on certain types of demand, but only one recent variant addresses the problem of obsolescence. We describe a new hybrid of Croston’s method and Bayesian inference called Hyperbolic-Exponential Smoothing, which is unbiased on non-intermittent and stochastic intermittent demand, decays hyperbolically when obsolescence occurs, and performs well in experiments.

S.D. Prestwich; S.A. Tarim; R. Rossi; B. Hnich

2014-01-01T23:59:59.000Z

135

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network [OSTI]

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

Levy, Roger

2014-01-01T23:59:59.000Z

136

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

137

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network [OSTI]

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

Levy, Roger

2014-01-01T23:59:59.000Z

138

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

139

Barrier Immune Radio Communications for Demand Response  

E-Print Network [OSTI]

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

Rubinstein, Francis

2010-01-01T23:59:59.000Z

140

Home Network Technologies and Automating Demand Response  

E-Print Network [OSTI]

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

McParland, Charles

2010-01-01T23:59:59.000Z

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

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

142

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

143

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

144

Demand Responsive Lighting: A Scoping Study  

E-Print Network [OSTI]

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

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

145

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

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

Goldman, Charles

2010-01-01T23:59:59.000Z

146

China's Coal: Demand, Constraints, and Externalities  

E-Print Network [OSTI]

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

Aden, Nathaniel

2010-01-01T23:59:59.000Z

147

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network [OSTI]

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

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

148

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

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

Goldman, Charles

2010-01-01T23:59:59.000Z

149

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

150

Opportunities for Automated Demand Response in Wastewater Treatment  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

151

China's Coal: Demand, Constraints, and Externalities  

SciTech Connect (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

152

Harnessing the power of demand  

SciTech Connect (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

153

China, India demand cushions prices  

SciTech Connect (OSTI)

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

154

Honeywell Demonstrates Automated Demand Response Benefits for...  

Broader source: Energy.gov (indexed) [DOE]

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

155

Retail Demand Response in Southwest Power Pool  

E-Print Network [OSTI]

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

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

156

Automated Demand Response and Commissioning  

SciTech Connect (OSTI)

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

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

2005-04-01T23:59:59.000Z

157

Tissue site-specific enhancer function of the upstream regulatory region of human papillomavirus type 11 in cultured keratinocytes.  

Science Journals Connector (OSTI)

...in cultured cells after microinjection with DNA constructsa T-antigen expression with constructs: Cell type No. of pPT-1 pPPl pPT-11R % Positive Intensityb % Positive Intensity % Positive Intensity Host Larynx 3 4.7 ? 3.1 NDc 44.0 ? 22.1 30...

B M Steinberg; K J Auborn; J L Brandsma; L B Taichman

1989-02-01T23:59:59.000Z

158

Price Responsive Demand in New York Wholesale Electricity Market using  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

159

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

160

DOE Hydrogen Analysis Repository: Hydrogen Demand and Infrastructure  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

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

Measuring Short-term Air Conditioner Demand Reductions for Operations and  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

162

Simulating the impact of pricing policies on residential water demand: a Southern France case study  

E-Print Network [OSTI]

, with an estimated price elasticity of -0.2, is not yet very responsive to price variation. A regional water model water pricing. Keywords: demand elasticity, France, water pricing, residential water demand, simulationSimulating the impact of pricing policies on residential water demand: a Southern France case study

Paris-Sud XI, Université de

163

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

E-Print Network [OSTI]

Pacific Northwest Demand Response Project Lee Hall, BPA Smart Grid Program Manager February 14 utilities to invest in DR Regional situational analysis ďż˝ issues to address #12;Nationally ďż˝ Demand ResponseSource: FERC Demand Response & Advanced Metering Report, February 2011 Peak DR 65,000 MW 1,062 MW Peak DR

164

Building Energy Software Tools Directory: Energy Demand Modeling  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

165

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

Broader source: Energy.gov (indexed) [DOE]

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

166

Demand Response Research in Spain  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

167

Full Rank Rational Demand Systems  

E-Print Network [OSTI]

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

LaFrance, Jeffrey T; Pope, Rulon D.

2006-01-01T23:59:59.000Z

168

Demand Forecasting of New Products  

E-Print Network [OSTI]

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

Sun, Yu

169

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

170

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,

171

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

172

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

173

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].

174

Demand Response and Energy Efficiency  

E-Print Network [OSTI]

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

175

Demand Response Spinning Reserve Demonstration  

SciTech Connect (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

176

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.

177

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.

178

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

179

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

180

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.

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

National Action Plan on Demand Response  

Broader source: Energy.gov (indexed) [DOE]

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

182

Demand Response Projects: Technical and Market Demonstrations  

E-Print Network [OSTI]

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

183

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

184

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

185

The Role of Demand Response in Default Service Pricing  

SciTech Connect (OSTI)

In designing default service for competitive retail markets, demand response has been an afterthought at best. But that may be changing, as states that initiated customer choice in the past five to seven years reach an important juncture in retail market design and consider an RTP-type default service for large commercial and industrial customers. The authors describe the experience to date with RTP as a default service, focusing on its role as an instrument for cultivating price-responsive demand. (author)

Barbose, Galen; Goldman, Charles; Neenan, Bernie

2006-04-15T23:59:59.000Z

186

Industrial demand side management status report: Synopsis  

SciTech Connect (OSTI)

Industrial demand side management (DSM) programs, though not as developed or widely implemented as residential and commercial programs, hold the promise of significant energy savings-savings that will benefit industrial firms, utilities and the environment. This paper is a synopsis of a larger research report, Industrial Demand Side Management. A Status Report, prepared for the US Department of Energy. The report provides an overview of and rationale for DSM programs. Benefits and barriers are described, and data from the Manufacturing Energy Consumption Survey are used to estimate potential electricity savings from industrial energy efficiency measures. Overcoming difficulties to effective program implementation is worthwhile, since rough estimates indicate a substantial potential for electricity savings. The report categorizes types of DSM programs, presents several examples of each type, and explores elements of successful programs. Two in-depth case studies (of Boise Cascade and of Eli Lilly and Company) illustrate two types of effective DSM programs. Interviews with staff from state public utility commissions indicate the current thinking about the status and future of industrial DSM programs. Finally, the research report also includes a comprehensive bibliography, a description of technical assistance programs, and an example of a methodology for evaluating potential or actual savings from projects.

Hopkins, M.E.F.; Conger, R.L.; Foley, T.J.; Parker, J.W.; Placet, M.; Sandahl, L.J.; Spanner, G.E.; Woodruff, M.G.; Norland, D.

1995-08-01T23:59:59.000Z

187

Barrier Immune Radio Communications for Demand Response  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

188

Demand Controlled Filtration in an Industrial Cleanroom  

SciTech Connect (OSTI)

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

189

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.

190

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.

191

Facilitating Renewable Integration by Demand Response  

Science Journals Connector (OSTI)

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

Juan M. Morales; Antonio J. Conejo…

2014-01-01T23:59:59.000Z

192

Demand Response as a System Reliability Resource  

E-Print Network [OSTI]

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

Joseph, Eto

2014-01-01T23:59:59.000Z

193

Demand response-enabled residential thermostat controls.  

E-Print Network [OSTI]

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

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

2008-01-01T23:59:59.000Z

194

Value of Demand Response -Introduction Klaus Skytte  

E-Print Network [OSTI]

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

195

World Energy Use — Trends in Demand  

Science Journals Connector (OSTI)

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

Randy Hudson

1996-01-01T23:59:59.000Z

196

California Energy Demand Scenario Projections to 2050  

E-Print Network [OSTI]

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

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

2008-01-01T23:59:59.000Z

197

Balancing of Energy Supply and Residential Demand  

Science Journals Connector (OSTI)

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

Martin Bock; Grit Walther

2014-01-01T23:59:59.000Z

198

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"

199

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

200

Turkey's energy demand and supply  

SciTech Connect (OSTI)

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

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

International Oil Supplies and Demands  

SciTech Connect (OSTI)

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

Not Available

1991-09-01T23:59:59.000Z

202

International Oil Supplies and Demands  

SciTech Connect (OSTI)

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

Not Available

1992-04-01T23:59:59.000Z

203

Demand Response as a System Reliability Resource  

E-Print Network [OSTI]

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

Joseph, Eto

2014-01-01T23:59:59.000Z

204

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

205

Demand Response - Policy | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

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

206

Sandia National Laboratories: demand response inverter  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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

207

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

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

Goldman, Charles

2010-01-01T23:59:59.000Z

208

California Energy Demand Scenario Projections to 2050  

E-Print Network [OSTI]

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

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

2008-01-01T23:59:59.000Z

209

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

Broader source: Energy.gov (indexed) [DOE]

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

210

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

Broader source: Energy.gov (indexed) [DOE]

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

211

California Energy Demand Scenario Projections to 2050  

E-Print Network [OSTI]

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

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

2008-01-01T23:59:59.000Z

212

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":""}]}

213

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":""}]}

214

Water Utility Demand Management and the Financial, Social and Environmental  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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)

215

Retail Demand Response in Southwest Power Pool | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

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.

216

MODELING THE DEMAND FOR E85 IN THE UNITED STATES  

SciTech Connect (OSTI)

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; Greene, David L [ORNL

2013-10-01T23:59:59.000Z

217

Industrial demand side management: A status report  

SciTech Connect (OSTI)

This report provides an overview of and rationale for industrial demand side management (DSM) programs. Benefits and barriers are described, and data from the Manufacturing Energy Consumption Survey are used to estimate potential energy savings in kilowatt hours. The report presents types and examples of programs and explores elements of successful programs. Two in-depth case studies (from Boise Cascade and Eli Lilly and Company) illustrate two types of effective DSM programs. Interviews with staff from state public utility commissions indicate the current thinking about the status and future of industrial DSM programs. A comprehensive bibliography is included, technical assistance programs are listed and described, and a methodology for evaluating potential or actual savings from projects is delineated.

Hopkins, M.F.; Conger, R.L.; Foley, T.J. [and others

1995-05-01T23:59:59.000Z

218

Smart Buildings and Demand Response  

Science Journals Connector (OSTI)

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

2011-01-01T23:59:59.000Z

219

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

220

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

SciTech Connect (OSTI)

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

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

Regional Consumer Hydrogen Demand and Optimal Hydrogen Refueling Station Siting  

SciTech Connect (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

222

Method of Obtaining Consumer Welfare from Regional Travel Demand Models  

E-Print Network [OSTI]

sales or mcome taxes) Small (10) outlmes a practical methodfor refundmgrevenues from pncmg potsmes that comesclose to ach~ev-

Rodier, Caroline J.; Johnston, Robert A.

1998-01-01T23:59:59.000Z

223

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

224

Semiconductor systems utilizing materials that form rectifying junctions in both N and P-type doping regions, whether metallurgically or field induced, and methods of use  

DOE Patents [OSTI]

Disclosed are semiconductor systems, such as integrated circuits utilizing Schotky barrier and/or diffused junction technology, which semiconductor systems incorporate material(s) that form rectifying junctions in both metallurgically and/or field induced N and P-type doping regions, and methods of their use. Disclosed are Schottky barrier based inverting and non-inverting gate voltage channel induced semiconductor single devices with operating characteristics similar to multiple device CMOS systems and which can be operated as modulators, N and P-channel MOSFETS and CMOS formed therefrom, and (MOS) gate voltage controlled rectification direction and gate voltage controlled switching devices, and use of such material(s) to block parasitic current flow pathways. Simple demonstrative five mask fabrication procedures for inverting and non-inverting gate voltage channel induced semiconductor single devices with operating characteristics similar to multiple device CMOS systems are also presented.

Welch, James D. (10328 Pinehurst Ave., Omaha, NE 68124)

2000-01-01T23:59:59.000Z

225

The alchemy of demand response: turning demand into supply  

SciTech Connect (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

226

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

227

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

228

Market and Policy Barriers for Demand Response Providing Ancillary Services  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

229

On-Demand Based Wireless Resources Trading for Green Communications  

E-Print Network [OSTI]

The purpose of Green Communications is to reduce the energy consumption of the communication system as much as possible without compromising the quality of service (QoS) for users. An effective approach for Green Wireless Communications is On-Demand strategy, which scales power consumption with the volume and location of user demand. Applying the On-Demand Communications model, we propose a novel scheme -- Wireless Resource Trading, which characterizes the trading relationship among different wireless resources for a given number of performance metrics. According to wireless resource trading relationship, different wireless resources can be consumed for the same set of performance metrics. Therefore, to minimize the energy consumption for given performance metrics, we can trade the other type of wireless resources for the energy resource under the demanded performance metrics. Based on the wireless resource trading relationship, we derive the optimal energy-bandwidth and energy-time wireless resource trading ...

Cheng, Wenchi; Zhang, Hailin; Wang, Qiang

2011-01-01T23:59:59.000Z

230

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)

231

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

232

Assessment of Demand Response and Advanced Metering  

E-Print Network [OSTI]

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

Tesfatsion, Leigh

233

INTEGRATION OF PV IN DEMAND RESPONSE  

E-Print Network [OSTI]

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

Perez, Richard R.

234

Demand Side Management in Rangan Banerjee  

E-Print Network [OSTI]

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

Banerjee, Rangan

235

Assessing the Control Systems Capacity for Demand Response in California  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

236

Building Technologies Office: Integrated Predictive Demand Response  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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...

237

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

238

Incorporating Demand Response into Western Interconnection Transmission Planning  

E-Print Network [OSTI]

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

Satchwell, Andrew

2014-01-01T23:59:59.000Z

239

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

240

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

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

Automated Demand Response Technologies and Demonstration in New York City  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

242

Global energy demand to 2060  

SciTech Connect (OSTI)

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

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

1989-01-01T23:59:59.000Z

243

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

244

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

245

Modeling supermarket refrigeration energy use and demand  

SciTech Connect (OSTI)

A computer model has been developed that can predict the performance of supermarket refrigeration equipment to within 3% of field test measurements. The Supermarket Refrigeration Energy Use and Demand Model has been used to simulate currently available refrigerants R-12, R-502 and R-22, and is being further developed to address alternative refrigerants. This paper reports that the model is expected to be important in the design, selection and operation of cost-effective, high-efficiency refrigeration systems. It can profile the operation and performance of different types of compressors, condensors, refrigerants and display cases. It can also simulate the effects of store humidity and temperature on display cases; the efficiency of various floating head pressure setpoints, defrost alternatives and subcooling methods; the efficiency and amount of heat reclaim from refrigeration systems; and the influence of other variables such as store lighting and building design. It can also be used to evaluate operational strategies such as variable-speed drive or cylinder unloading for capacity control. Development of the model began in 1986 as part of a major effort, sponsored by the U.S. electric utility industry, to evaluate energy performance of then conventional single compressor and state-of-the-art multiplex refrigeration systems, and to characterize the contribution of a variety of technology enhancement features on system energy use and demand.

Blatt, M.H.; Khattar, M.K. (Electric Power Research Inst., Palo Alto, CA (US)); Walker, D.H. (Foster Miller Inc., Waltham, MA (US))

1991-07-01T23:59:59.000Z

246

On making energy demand and network constraints compatible in the last mile of the power grid  

Science Journals Connector (OSTI)

Abstract In the classical electricity grid power demand is nearly instantaneously matched by power supply. In this paradigm, the changes in power demand in a low voltage distribution grid are essentially nothing but a disturbance that is compensated for by control at the generators. The disadvantage of this methodology is that it necessarily leads to a transmission and distribution network that must cater for peak demand. So-called smart meters and smart grid technologies provide an opportunity to change this paradigm by using demand side energy storage to moderate instantaneous power demand so as to facilitate the supply-demand match within network limitations. A receding horizon model predictive control method can be used to implement this idea. In this paradigm demand is matched with supply, such that the required customer energy needs are met but power demand is moderated, while ensuring that power flow in the grid is maintained within the safe operating region, and in particular peak demand is limited. This enables a much higher utilisation of the available grid infrastructure, as it reduces the peak-to-base demand ratio as compared to the classical control methodology of power supply following power demand. This paper investigates this approach for matching energy demand to generation in the last mile of the power grid while maintaining all network constraints through a number of case studies involving the charging of electric vehicles in a typical suburban low voltage distribution network in Melbourne, Australia.

Iven Mareels; Julian de Hoog; Doreen Thomas; Marcus Brazil; Tansu Alpcan; Derek Jayasuriya; Valentin Müenzel; Lu Xia; Ramachandra Rao Kolluri

2014-01-01T23:59:59.000Z

247

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

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

248

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

249

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"

250

Regional water planning Milind Sohoni  

E-Print Network [OSTI]

of energy, capital and O&M ­ surface water: generally large investments, canals, pipelines ­ ground water demand for resources water, energy, firewood etc. · Need to meet demand with supply ­ Logistics efficiency, equity, sustainability #12;Regional View LOCATE: Farmland Villages Road/highways River/stream Dam

Sohoni, Milind

251

Demand Side Bidding. Final Report  

SciTech Connect (OSTI)

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

252

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

253

Demand Response Programs Oregon Public Utility Commission  

E-Print Network [OSTI]

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

254

Industrial Equipment Demand and Duty Factors  

E-Print Network [OSTI]

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

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

255

ConservationandDemand ManagementPlan  

E-Print Network [OSTI]

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

Abolmaesumi, Purang

256

Energy Demand Analysis at a Disaggregated Level  

Science Journals Connector (OSTI)

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

Subhes C. Bhattacharyya

2011-01-01T23:59:59.000Z

257

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:

258

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

259

Demand Response and Variable Generation Integration Scoping Study  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

260

U.S. electric utility demand-side management 1995  

SciTech Connect (OSTI)

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

NONE

1997-01-01T23:59:59.000Z

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

U.S. electric utility demand-side management 1996  

SciTech Connect (OSTI)

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

NONE

1997-12-01T23:59:59.000Z

262

Water supply and demand in an energy supply model  

SciTech Connect (OSTI)

This report describes a tool for water and energy-related policy analysis, the development of a water supply and demand sector in a linear programming model of energy supply in the United States. The model allows adjustments in the input mix and plant siting in response to water scarcity. Thus, on the demand side energy conversion facilities can substitute more costly dry cooling systems for conventional evaporative systems. On the supply side groundwater and water purchased from irrigators are available as more costly alternatives to unappropriated surface water. Water supply data is developed for 30 regions in 10 Western states. Preliminary results for a 1990 energy demand scenario suggest that, at this level of spatial analysis, water availability plays a minor role in plant siting. Future policy applications of the modeling system are discussed including the evaluation of alternative patterns of synthetic fuels development.

Abbey, D; Loose, V

1980-12-01T23:59:59.000Z

263

Decentralized demand management for water distribution  

E-Print Network [OSTI]

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

Zabolio, Dow Joseph

2012-06-07T23:59:59.000Z

264

Demand Responsive Lighting: A Scoping Study  

E-Print Network [OSTI]

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

265

Demand Response Resources in Pacific Northwest  

E-Print Network [OSTI]

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

266

Leveraging gamification in demand dispatch systems  

Science Journals Connector (OSTI)

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

Benjamin Gnauk; Lars Dannecker; Martin Hahmann

2012-03-01T23:59:59.000Z

267

Demand Response and Ancillary Services September 2008  

E-Print Network [OSTI]

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

268

THE STATE OF DEMAND RESPONSE IN CALIFORNIA  

E-Print Network [OSTI]

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

269

THE STATE OF DEMAND RESPONSE IN CALIFORNIA  

E-Print Network [OSTI]

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

270

Modeling Energy Demand Aggregators for Residential Consumers  

E-Print Network [OSTI]

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

Paris-Sud XI, Université de

271

Response to changes in demand/supply  

E-Print Network [OSTI]

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

272

Response to changes in demand/supply  

E-Print Network [OSTI]

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

273

Energy demand forecasting: industry practices and challenges  

Science Journals Connector (OSTI)

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

Mathieu Sinn

2014-06-01T23:59:59.000Z

274

Smart Buildings Using Demand Response March 6, 2011  

E-Print Network [OSTI]

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

Kammen, Daniel M.

275

Demand Response Valuation Frameworks Paper  

E-Print Network [OSTI]

in regions with organized energy markets (day-ahead or real-or bid into day-ahead energy markets then it might gainin capacity and energy markets are significant only in the

Heffner, Grayson

2010-01-01T23:59:59.000Z

276

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":""}]}

277

http://www.bea.gov/regional/rims/  

National Nuclear Security Administration (NNSA)

natural disasters, such as Hurricane Katrina; or of special events, such as national political conventions. RIMS II provides six types of multipliers: final-demand multipliers for...

278

Energy demand and population changes  

SciTech Connect (OSTI)

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

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

1980-12-01T23:59:59.000Z

279

Progress towards Managing Residential Electricity Demand: Impacts of  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

280

Cost-Efficiency in Water Management Through Demand Side Management and Integrated Planning  

Science Journals Connector (OSTI)

In the context of regional planning for efficient management of water and wastewater, it is crucial ... situation. This consists of measures for water demand side management, comparison of different scenarios of ...

Dr. Ing. Ralf Otterpohl

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.


281

Electricity demand analysis - unconstrained vs constrained scenarios  

Science Journals Connector (OSTI)

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

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

2003-01-01T23:59:59.000Z

282

Demand Response Opportunities and Enabling Technologies for Data Centers:  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

283

Measurement and Verification for Demand Response  

Broader source: Energy.gov (indexed) [DOE]

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

284

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

E-Print Network [OSTI]

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

Sastry, S. Shankar

285

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

E-Print Network [OSTI]

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

286

Design and Operation of an Open, Interoperable Automated Demand Response  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

287

FISHERY WASTE EFFLUENTS: A METHOD TO DETERMINE RELATIONSHIPS BETWEEN CHEMICAL OXYGEN DEMAND AND RESIDUE  

E-Print Network [OSTI]

FISHERY WASTE EFFLUENTS: A METHOD TO DETERMINE RELATIONSHIPS BETWEEN CHEMICAL OXYGEN DEMAND effluents, especially for total suspended and settleable solids, and oil and grease. The relationship between chemical oxygen demand and residue was determined on a limited number of samples from four types

288

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.

289

OUTDOOR RECREATION DEMAND AND EXPENDITURES: LOWER SNAKE RIVER RESERVOIRS  

E-Print Network [OSTI]

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

O'Laughlin, Jay

290

LEED Demand Response Credit: A Plan for Research towards Implementation  

E-Print Network [OSTI]

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

Kiliccote, Sila

2014-01-01T23:59:59.000Z

291

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

292

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

293

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

294

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

295

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

296

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

297

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

298

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

299

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

300

Modeling, Analysis, and Control of Demand Response Resources  

E-Print Network [OSTI]

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

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

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

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

302

Opportunities, Barriers and Actions for Industrial Demand Response in California  

E-Print Network [OSTI]

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

McKane, Aimee T.

2009-01-01T23:59:59.000Z

303

The Role of Demand Response in Default Service Pricing  

E-Print Network [OSTI]

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

Barbose, Galen; Goldman, Chuck; Neenan, Bernie

2006-01-01T23:59:59.000Z

304

The Role of Demand Response in Default Service Pricing  

E-Print Network [OSTI]

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

Barbose, Galen; Goldman, Charles; Neenan, Bernie

2008-01-01T23:59:59.000Z

305

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network [OSTI]

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

Piette, Mary Ann

2009-01-01T23:59:59.000Z

306

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network [OSTI]

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

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

307

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

308

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

309

Distributed Intelligent Automated Demand Response (DIADR) Building  

Broader source: Energy.gov (indexed) [DOE]

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,

310

The Retail Planning Problem under Demand Uncertainty.  

E-Print Network [OSTI]

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

Georgiadis, G.; Rajaram, K.

2012-01-01T23:59:59.000Z

311

Retail Demand Response in Southwest Power Pool  

E-Print Network [OSTI]

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

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

312

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

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

Goldman, Charles

2010-01-01T23:59:59.000Z

313

Distributed Automated Demand Response - Energy Innovation Portal  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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

314

Demand Response (transactional control) - Energy Innovation Portal  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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

315

Regulation Services with Demand Response - Energy Innovation...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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

316

Topics in Residential Electric Demand Response.  

E-Print Network [OSTI]

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

Horowitz, Shira R.

2012-01-01T23:59:59.000Z

317

Maximum-Demand Rectangular Location Problem  

E-Print Network [OSTI]

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

Manish Bansal

2014-10-01T23:59:59.000Z

318

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network [OSTI]

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

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

319

Basic Theory of Demand-Side Management  

Science Journals Connector (OSTI)

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

Zhaoguang Hu; Xinyang Han; Quan Wen

2013-01-01T23:59:59.000Z

320

Demand response at the Naval Postgraduate School .  

E-Print Network [OSTI]

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

Stouffer, Dean

2008-01-01T23:59:59.000Z

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

Demand response exchange in a deregulated environment .  

E-Print Network [OSTI]

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

Nguyen, DT

2012-01-01T23:59:59.000Z

322

Demand response exchange in a deregulated environment.  

E-Print Network [OSTI]

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

Nguyen, DT

2012-01-01T23:59:59.000Z

323

Geographically Based Hydrogen Demand and Infrastructure Rollout...  

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

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

324

Opportunities for Energy Efficiency and Demand Response in the California  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

325

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.

326

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.

327

FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007  

E-Print Network [OSTI]

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

328

Demand Response and Electric Grid Reliability  

E-Print Network [OSTI]

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

Wattles, P.

2012-01-01T23:59:59.000Z

329

DEMAND SIMULATION FOR DYNAMIC TRAFFIC ASSIGNMENT  

E-Print Network [OSTI]

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

Bierlaire, Michel

330

A Vision of Demand Response - 2016  

SciTech Connect (OSTI)

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

Levy, Roger

2006-10-15T23:59:59.000Z

331

SUMMER 2007 ELECTRICITY SUPPLY AND DEMAND OUTLOOK  

E-Print Network [OSTI]

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

332

Incorporating Demand Response into Western Interconnection Transmission Planning  

E-Print Network [OSTI]

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

Satchwell, Andrew

2014-01-01T23:59:59.000Z

333

Uranium 2009 resources, production and demand  

E-Print Network [OSTI]

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

Organisation for Economic Cooperation and Development. Paris

2010-01-01T23:59:59.000Z

334

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

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

335

Smart microgrid operational planning considering multiple demand response programs  

Science Journals Connector (OSTI)

Microgrid (MG) is one of the important blocks in the future smart distribution systems. The scheduling pattern of MGs affects distribution system operation. Also the optimal scheduling of MGs will result in reliable and economical operation of distribution system. In this paper an operational planning model of a MG which considers multiple demand response programs is proposed. In the proposed approach all types of loads can participate in demand response programs which will be considered in either energy or reserve scheduling. Also the renewable distributed generation uncertainty is covered by reserve provided by both Distributed Generations (DGs) and responsive loads. The novelty of this paper is the demand side participation in energy and reserve scheduling simultaneously. Furthermore the energy and reserve scheduling is proposed for day-ahead and real-time. The proposed model was tested on a typical MG system and the results show that running demand response programs will reduce total operation cost of MG and cause more efficient use of resources.

Alireza Zakariazadeh; Shahram Jadid

2014-01-01T23:59:59.000Z

336

Through Voluntary Conservation Regional Step-Down Plan  

E-Print Network [OSTI]

II. Regional Overview..................................................................................................................... 3 Wetland Habitat Types............................................................................................................... 3 Coastal Upland Habitat Types................................................................................................... 4

unknown authors

337

International Transportation Energy Demand Determinants (ITEDD...  

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

type Commercial Vehicle Sales Comm Sales by Technology Type Personal Vehicle Sales Private Sales by Technology Type Stock Accounting by Vehicle and Techn Type Policy...

338

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

E-Print Network [OSTI]

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

339

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.

340

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

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

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.

342

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.

343

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

SciTech Connect (OSTI)

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

344

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

E-Print Network [OSTI]

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

345

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

346

Health Care Demand, Empirical Determinants of  

Science Journals Connector (OSTI)

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

S.H. Zuvekas

2014-01-01T23:59:59.000Z

347

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

Science Journals Connector (OSTI)

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

Sajal Ghosh

2008-01-01T23:59:59.000Z

348

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

349

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

350

Level: National and Regional Data; Row: Values of Shipments and...  

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

2 Electricity: Components of Net Demand, 2006; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Electricity Components; Unit: Million...

351

NCEP_Demand_Response_Draft_111208.indd  

Broader source: Energy.gov (indexed) [DOE]

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

352

Solar in Demand | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

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

353

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

354

Demand Controlled Ventilation and Classroom Ventilation  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

355

China End-Use Energy Demand Modeling  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

356

Integrated Predictive Demand Response Controller Research Project |  

Broader source: Energy.gov (indexed) [DOE]

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

357

Software demonstration: Demand Response Quick Assessment Tool  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

358

Power Consumption Analysis of Architecture on Demand  

Science Journals Connector (OSTI)

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

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

359

Integration of Demand Side Management, Distributed Generation...  

Open Energy Info (EERE)

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

360

Capitalize on Existing Assets with Demand Response  

E-Print Network [OSTI]

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

Collins, J.

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "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

SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY  

Broader source: Energy.gov [DOE]

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

362

Global Energy: Supply, Demand, Consequences, Opportunities  

SciTech Connect (OSTI)

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

Arun Majumdar

2008-08-14T23:59:59.000Z

363

Volatile coal prices reflect supply, demand uncertainties  

SciTech Connect (OSTI)

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

364

Global Energy: Supply, Demand, Consequences, Opportunities  

ScienceCinema (OSTI)

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

Arun Majumdar

2010-01-08T23:59:59.000Z

365

Demand Controlled Ventilation and Classroom Ventilation  

E-Print Network [OSTI]

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

Fisk, William J.

2014-01-01T23:59:59.000Z

366

Transportation energy demand: Model development and use  

Science Journals Connector (OSTI)

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

Chris Kavalec

1998-06-01T23:59:59.000Z

367

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

368

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

369

Measuring the capacity impacts of demand response  

SciTech Connect (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

370

Real-Time Demand Side Energy Management  

E-Print Network [OSTI]

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

Victor, A.; Brodkorb, M.

2006-01-01T23:59:59.000Z

371

Electric Utility Demand-Side Evaluation Methodologies  

E-Print Network [OSTI]

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

Treadway, N.

372

Aviation fuel demand development in China  

Science Journals Connector (OSTI)

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

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

2014-01-01T23:59:59.000Z

373

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

Science Journals Connector (OSTI)

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

Argon Chen; Jakey Blue

2010-01-01T23:59:59.000Z

374

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

375

Changes in worldwide demand for metals (final). Open File report  

SciTech Connect (OSTI)

Worldwide demand for metals was analyzed to identify the important factors that explain differences in the level of demand among world countries. The per capita demand for steel, aluminum, copper, and total nonferrous metals was investigated for 40 to 50 countries over a 22-year period. These countries have been further grouped into four world regions for purposes of making generalizations about the importance of these factors for countries in different stages of development and with dissimilar levels of per capita gross domestic product (GDP). Intercountry and intertemporal differences are explained largely by differences in per capita GDP and changes over time in per capita GDP, oil real prices, and to a lesser extent, metal real prices. The trend in world consumption is dramatically different in the last decade than the previous one. In 1962-73, per capita consumption increased in all areas and consumption intensity (consumption divided by (GDP) increased in most areas). In 1973-84, per capita consumption fell in most areas and intensity fell dramatically, except in developing nations.

Faucett, J.G.; Chmelynski, H.J.

1986-08-01T23:59:59.000Z

376

Electricity Demand Evolution Driven by Storm Motivated Population Movement  

SciTech Connect (OSTI)

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

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

2014-01-01T23:59:59.000Z

377

National patterns of energy demand and expenditures by Hispanics  

SciTech Connect (OSTI)

This paper is based on ongoing research, at Argonne National Laboratory, being done for the Office of Minority Economic Impact (MI) of the US Department of Energy. Under its legislative mandate MI is required to assess the impact of government policy, programs, and actions on US minorities. In line with this mission Argonne is currently involved in characterizing and analyzing the patterns of energy demand and expenditures of minorities. A major barrier associated with this task is the availability of sufficient data. With the possible exception of blacks, analysis of the patterns of energy demand for most minority population categories is all but impossible because of small sample sizes. The major source of residential energy consumption data, the Residential Energy Consumption Survey, only collects data on 5000 to 7000 households. For many minority population categories, this number of observations make any meaningful statistical analysis at least at the regional Census level practically impossible, with any further refinement of the analysis becoming even more difficult. In this paper our primary purpose is to describe the patterns of energy demand for Hispanics and nonhispanics but ancillary to that briefly present one possible solution to the data availability problem.

Poyer, D.A.

1987-01-01T23:59:59.000Z

378

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

379

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.

380

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":""}]}

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

An Operational Model for Optimal NonDispatchable Demand Response  

E-Print Network [OSTI]

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

Grossmann, Ignacio E.

382

Climate, extreme heat, and electricity demand in California  

SciTech Connect (OSTI)

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

383

Electric Water Heater Modeling and Control Strategies for Demand Response  

SciTech Connect (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

384

Demand Response and Storage Integration Study: Markets Report Overview  

Broader source: Energy.gov (indexed) [DOE]

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

385

Organizing for demand-side management program implementation  

SciTech Connect (OSTI)

Organizing for the implementation of a demand-side management (DSM) program, is an exercise in planning and acquiring resources. However, the requirements for energy efficiency program implementation will vary and are dependent upon the type of mechanism employed in delivering the program. For example, commercial energy efficiency programs generally have three delivery mechanisms: rebate; direct installation; or DSM. For residential programs there are two unique methods, one a catalog program, which provides a source of purchasing energy efficient products, or a point-of-sale program, where rebates, in the form of coupons can be redeemed at the time of product purchase.

Obeiter, R.

1996-01-01T23:59:59.000Z

386

The Role of Demand Response in Default Service Pricing  

SciTech Connect (OSTI)

Dynamic retail electricity pricing, especially real-time pricing (RTP), has been widely heralded as a panacea for providing much-needed demand response in electricity markets. However, in designing default service for competitive retail markets, demand response often appears to be an afterthought. But that may be changing as states that initiated customer choice in the past 5-7 years reach an important juncture in retail market design. Most states with retail choice established an initial transitional period, during which utilities were required to offer a default or ''standard offer'' generation service, often at a capped or otherwise administratively-determined rate. Many retail choice states have reached, or are nearing, the end of their transitional period and several states have adopted an RTP-type default service for large commercial and industrial (C&I) customers. Are these initiatives motivated by the desire to induce greater demand response, or is RTP being called upon to serve a different role in competitive markets? Surprisingly, we found that in most cases, the primary reason for adopting RTP as the default service was not to encourage demand response, but rather to advance policy objectives related to the development of competitive retail markets. However, we also find that, if efforts are made in its design and implementation, default RTP service can also provide a solid foundation for developing price responsive demand, creating an important link between wholesale and retail market transactions. This paper, which draws from a lengthier report, describes the experience to date with default RTP in the U.S., identifying findings related to its actual and potential role as an instrument for cultivating price responsive demand [1]. For each of the five states currently with default RTP, we conducted a detailed review of the regulatory proceedings leading to its adoption. To further understand the intentions and expectations of those involved in its design and implementation, we also interviewed regulatory staff and utilities in each state, as well as eight of the most prominent competitive retail suppliers operating in these markets which, together, comprised about 60-65% of competitive C&I sales in the U.S. in 2004 [2].

Barbose, Galen; Goldman, Chuck; Neenan, Bernie

2006-03-10T23:59:59.000Z

387

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

388

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network [OSTI]

LABORATORY Coordination of Retail Demand Response withXXXXX Coordination of Retail Demand Response with MidwestAC02-05CH11231. Coordination of Retail Demand Response with

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

389

Analysis of Open Automated Demand Response Deployments in California  

E-Print Network [OSTI]

LBNL-6560E Analysis of Open Automated Demand Response Deployments in California and Guidelines The work described in this report was coordinated by the Demand Response Research. #12; #12;Abstract This report reviews the Open Automated Demand Response

390

PIER: Demand Response Research Center Director, Mary Ann Piette  

E-Print Network [OSTI]

1 PIER: Demand Response Research Center Director, Mary Ann Piette Program Development and Outreach Response Research Plan #12;2 Demand Response Research Center Objective Scope Stakeholders Develop, prioritize, conduct and disseminate multi- institutional research to facilitate Demand Response. Technologies

391

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

392

Demand Response Enabling Technologies and Approaches for Industrial Facilities  

E-Print Network [OSTI]

, there are also huge opportunities for demand response in the industrial sector. This paper describes some of the demand response initiatives that are currently active in New York State, explaining applicability of industrial facilities. Next, we discuss demand...

Epstein, G.; D'Antonio, M.; Schmidt, C.; Seryak, J.; Smith, C.

2005-01-01T23:59:59.000Z

393

LEED Demand Response Credit: A Plan for Research towards Implementation  

E-Print Network [OSTI]

DR’s growing role in demand-side management activities andhow DR fits with demand-side management activities, DRemissions rates The demand-side management (DSM) framework

Kiliccote, Sila

2014-01-01T23:59:59.000Z

394

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network [OSTI]

Data Collection for Demand-side Management for QualifyingPrepared by Demand-side Management Task Force of the4. Status of Demand Side Management in Midwest ISO 5.

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

395

Demand-Side Management and Energy Efficiency Revisited  

E-Print Network [OSTI]

EPRI). 1984. ”Demand Side Management. Vol. 1:Overview of Key1993. ”Industrial Demand-Side Management Programs: What’sJ. Kulick. 2004. ”Demand side management and energy e?ciency

Auffhammer, Maximilian; Blumstein, Carl; Fowlie, Meredith

2007-01-01T23:59:59.000Z

396

Commercial Fleet Demand for Alternative-Fuel Vehicles in California  

E-Print Network [OSTI]

Precursors of demand for alternative-fuel vehicles: resultsFLEET DEMAND FOR ALTERNATIVE-FUEL VEHICLES IN CALIFORNIA*Abstract—Fleet demand for alternative-fuel vehicles (‘AFVs’

Golob, Thomas F; Torous, Jane; Bradley, Mark; Brownstone, David; Crane, Soheila Soltani; Bunch, David S

1996-01-01T23:59:59.000Z

397

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network [OSTI]

ED2, September. CEC (2005b) Energy demand forecast methodsCalifornia Baseline Energy Demands to 2050 for Advancedof a baseline scenario for energy demand in California for a

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

2008-01-01T23:59:59.000Z

398

Behavioral Aspects in Simulating the Future US Building Energy Demand  

E-Print Network [OSTI]

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

Stadler, Michael

2011-01-01T23:59:59.000Z

399

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network [OSTI]

iv Chapter 5: National energy demand and potential energyAs Figure 1-2 shows, HVAC energy demand is comparable to thefor reducing this high energy demand reaches beyond

Shehabi, Arman

2010-01-01T23:59:59.000Z

400

Automated Demand Response Technology Demonstration Project for Small and  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

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

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

402

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

403

International Oil Supplies and Demands. Volume 1  

SciTech Connect (OSTI)

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

Not Available

1991-09-01T23:59:59.000Z

404

Energy demand simulation for East European countries  

Science Journals Connector (OSTI)

The analysis and created statistical models of energy consumption tendencies in the European Union (EU25), including new countries in transition, are presented. The EU15 market economy countries and countries in transition are classified into six clusters by relative indicators of Gross Domestic Product (GDP/P) and energy demand (W/P) per capita. The specified statistical models of energy intensity W/GDP non-linear stochastic tendencies have been discovered with respect to the clusters of classified countries. The new energy demand simulation models have been developed for the demand management in timeâ??territory hierarchy in various scenarios of short-term and long-term perspective on the basis of comparative analysis methodology. The non-linear statistical models were modified to GDP, W/P and electricity (E/P) final consumption long-term forecasts for new associated East European countries and, as an example, for the Baltic Countries, including Lithuania.

Jonas Algirdas Kugelevicius; Algirdas Kuprys; Jonas Kugelevicius

2007-01-01T23:59:59.000Z

405

International Oil Supplies and Demands. Volume 2  

SciTech Connect (OSTI)

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

Not Available

1992-04-01T23:59:59.000Z

406

Uranium 2014 resources, production and demand  

E-Print Network [OSTI]

Published every other year, Uranium Resources, Production, and Demand, or the "Red Book" as it is commonly known, is jointly prepared by the OECD Nuclear Energy Agency and the International Atomic Energy Agency. It is the recognised world reference on uranium and is based on official information received from 43 countries. It presents the results of a thorough review of world uranium supplies and demand and provides a statistical profile of the world uranium industry in the areas of exploration, resource estimates, production and reactor-related requirements. It provides substantial new information from all major uranium production centres in Africa, Australia, Central Asia, Eastern Europe and North America. Long-term projections of nuclear generating capacity and reactor-related uranium requirements are provided as well as a discussion of long-term uranium supply and demand issues. This edition focuses on recent price and production increases that could signal major changes in the industry.

Organisation for Economic Cooperation and Development. Paris

2014-01-01T23:59:59.000Z

407

DEMAND CONTROLLED VENTILATION AND CLASSROOM VENTILATION  

SciTech Connect (OSTI)

This document summarizes a research effort on demand controlled ventilation and classroom ventilation. The research on demand controlled ventilation included field studies and building energy modeling. Major findings included: ? The single-location carbon dioxide sensors widely used for demand controlled ventilation frequently have large errors and will fail to effectively control ventilation rates (VRs).? Multi-location carbon dioxide measurement systems with more expensive sensors connected to multi-location sampling systems may measure carbon dioxide more accurately.? Currently-available optical people counting systems work well much of the time but have large counting errors in some situations. ? In meeting rooms, measurements of carbon dioxide at return-air grilles appear to be a better choice than wall-mounted sensors.? In California, demand controlled ventilation in general office spaces is projected to save significant energy and be cost effective only if typical VRs without demand controlled ventilation are very high relative to VRs in codes. Based on the research, several recommendations were developed for demand controlled ventilation specifications in the California Title 24 Building Energy Efficiency Standards.The research on classroom ventilation collected data over two years on California elementary school classrooms to investigate associations between VRs and student illness absence (IA). Major findings included: ? Median classroom VRs in all studied climate zones were below the California guideline, and 40percent lower in portable than permanent buildings.? Overall, one additional L/s per person of VR was associated with 1.6percent less IA. ? Increasing average VRs in California K-12 classrooms from the current average to the required level is estimated to decrease IA by 3.4percent, increasing State attendance-based funding to school districts by $33M, with $6.2 M in increased energy costs. Further VR increases would provide additional benefits.? Confirming these findings in intervention studies is recommended. ? Energy costs of heating/cooling unoccupied classrooms statewide are modest, but a large portion occurs in relatively few classrooms.

Fisk, William J.; Mendell, Mark J.; Davies, Molly; Eliseeva, Ekaterina; Faulkner, David; Hong, Tienzen; Sullivan, Douglas P.

2014-01-06T23:59:59.000Z

408

Rice Supply, Demand and Related Government Programs.  

E-Print Network [OSTI]

, 1930-55 Year Weighted Year Weighted beginning average price beginning average price August per cwt. August per cwt. Dollars Dollars 'Includes an allowance for unredeemed loans. response to the strengthening of foreign demand, rice prices by 1952... 91 percent of the average parity price during 1935-54, with !he 4 years of World War I1 omitted. The elasticity of demand was assumed to be about -.2. The annually derived price based on the assumed elasticity and the percentage change in price...

Kincannon, John A.

1957-01-01T23:59:59.000Z

409

Demand Response Initiatives at CPS Energy  

E-Print Network [OSTI]

Demand Response Initiatives at CPS Energy Clean Air Through Energy Efficiency (CATEE) Conference December 17, 2013 ESL-KT-13-12-53 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 CPSE’s DR Program • DR... than the military bases and Toyota combined. • Schools & Universities contributed 6 MW’s of Demand Response in 2013. 2013 DR Participants Trinity University - $5,654 Fort Sam ISD - $18,860 Judson ISD - $45,540 Alamo Colleges - $98,222 UTSA - $168...

Luna, R.

2013-01-01T23:59:59.000Z

410

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

Broader source: Energy.gov (indexed) [DOE]

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

411

Overview of Demand Side Response | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

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

412

Robust Unit Commitment Problem with Demand Response and ...  

E-Print Network [OSTI]

Oct 29, 2010 ... sion, both Demand Response (DR) strategy and intermittent renewable ... Key Words: unit commitment, demand response, wind energy, robust ...

2010-10-31T23:59:59.000Z

413

National Action Plan on Demand Response | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

National Action Plan on Demand Response National Action Plan on Demand Response Presentation-given at the Federal Utility Partnership Working Group (FUPWG) Fall 2008...

414

ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES  

E-Print Network [OSTI]

ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES BY ANUPAMA SUNIL KOWLI B of consumers - called demand response resources (DRRs) - whose role has become increasingly important

Gross, George

415

The business value of demand response for balance responsible parties.  

E-Print Network [OSTI]

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

Jonsson, Mattias

2014-01-01T23:59:59.000Z

416

Aggregator-Assisted Residential Participation in Demand Response Program.  

E-Print Network [OSTI]

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

Hasan, Mehedi

2012-01-01T23:59:59.000Z

417

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network [OSTI]

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

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

418

BUILDINGS SECTOR DEMAND-SIDE EFFICIENCY TECHNOLOGY SUMMARIES  

E-Print Network [OSTI]

............................................................................................... 2 Demand-Side Efficiency Technologies I. Energy Management Systems (EMSsLBL-33887 UC-000 BUILDINGS SECTOR DEMAND-SIDE EFFICIENCY TECHNOLOGY SUMMARIES Jonathan G. Koomey

419

Modeling, Analysis, and Control of Demand Response Resources.  

E-Print Network [OSTI]

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

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

420

Modeling, Analysis, and Control of Demand Response Resources.  

E-Print Network [OSTI]

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

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

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

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

Energy Savers [EERE]

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

422

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

Broader source: Energy.gov (indexed) [DOE]

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

423

Chapter 3: Demand-Side Resources | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

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

424

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

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

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

425

Automation systems for Demand Response, ForskEL (Smart Grid Project) | Open  

Open Energy Info (EERE)

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

426

DOE Hydrogen Analysis Repository: HyDRA: Hydrogen Demand and Resource  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

HyDRA: Hydrogen Demand and Resource Analysis Tool HyDRA: Hydrogen Demand and Resource Analysis Tool Project Summary Full Title: HyDRA: Hydrogen Demand and Resource Analysis Tool Project ID: 220 Principal Investigator: Johanna Levene Brief Description: HyDRA has evolved from a basic display of spatial data to a repository of over 100 datasets with dynamic data, querying, and interoperability with other models and spatial data repositories and over 350 registered users. Keywords: Hydrogen infrastructure; wind; solar; biomass; coal; natural gas Purpose Facilitate regional and geographical analyses of resources, demand, and infrastructure relevant to the implementation of hydrogen production, delivery, and dispensing. Performer Principal Investigator: Johanna Levene Organization: National Renewable Energy Laboratory (NREL)

427

Assumptions to the Annual Energy Outlook 1999 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

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

428

Northwest Open Automated Demand Response Technology Demonstration Project  

SciTech Connect (OSTI)

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

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

2010-03-17T23:59:59.000Z

429

SHORT-RUN MONEY DEMAND Laurence Ball  

E-Print Network [OSTI]

SHORT-RUN MONEY DEMAND Laurence Ball Johns Hopkins University August 2002 I am grateful with Goldfeld's partial adjustment model. A key innovation is the choice of the interest rate in the money on "near monies" -- close substitutes for M1 such as savings accounts and money market mutual funds

Niebur, Ernst

430

Indianapolis Offers a Lesson on Driving Demand  

Broader source: Energy.gov [DOE]

Successful program managers know that understanding the factors that drive homeowners to make upgrades is critical to the widespread adoption of energy efficiency. What better place to learn about driving demand for upgrades than in Indianapolis, America's most famous driving city?

431

Senior Center Network Redesign Under Demand Uncertainty  

E-Print Network [OSTI]

Senior Center Network Redesign Under Demand Uncertainty Osman Y. ¨Ozaltin Department of Industrial of Massachusetts Boston, Boston, MA 02125-3393, USA, michael.johnson@umb.edu Andrew J. Schaefer Department. In response, we propose a two-echelon network of senior centers. We for- mulate a two-stage stochastic

Schaefer, Andrew

432

PUBLISH ON DEMAND Recasting the Textbook  

E-Print Network [OSTI]

of history helped students evaluate the sources of information and better understand the perspectives from which history is written? WHAT WE SET OUT TO DO We recast the history textbook as an edited on- demand- source documents and interactive technology. WHAT WE FOUND High school students accessed our database

Das, Rhiju

433

Energy technologies and their impact on demand  

SciTech Connect (OSTI)

Despite the uncertainties, energy demand forecasts must be made to guide government policies and public and private-sector capital investment programs. Three principles can be identified in considering long-term energy prospects. First energy demand will continue to grow, driven by population growth, economic development, and the current low per capita energy consumption in developing countries. Second, energy technology advancements alone will not solve the problem. Energy-efficient technologies, renewable resource technologies, and advanced electric power technologies will all play a major role but will not be able to keep up with the growth in world energy demand. Third, environmental concerns will limit the energy technology choices. Increasing concern for environmental protection around the world will restrict primarily large, centralized energy supply facilities. The conclusion is that energy system diversity is the only solution. The energy system must be planned with consideration of both supply and demand technologies, must not rely on a single source of energy, must take advantage of all available technologies that are specially suited to unique local conditions, must be built with long-term perspectives, and must be able to adapt to change.

Drucker, H.

1995-06-01T23:59:59.000Z

434

Industry continues to cut energy demand  

Science Journals Connector (OSTI)

The U.S.'s 10 most energy-intensive industries are continuing to reduce their energy demand, with the chemical industry emerging as a leader in industrial energy conservation, says the Department of Energy in a report to Congress.The chemical industry is ...

1981-01-12T23:59:59.000Z

435

Findings from the 2004 Fully Automated Demand Response Tests in Large  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

the 2004 Fully Automated Demand Response Tests in Large 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 LBNL Report Number LBNL-58178 Year of Publication 2005 Authors Piette, Mary Ann, David S. Watson, Naoya Motegi, and Norman Bourassa Date Published 10/18/2005 Keywords market sectors, technologies Abstract This report describes the results of the second season of research to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of time dependant activities that reduce or shift electricity use to improve electric grid reliability, manage electricity costs, and provide systems that encourage load shifting or shedding during times when the electric grid is near its capacity or electric prices are high. Demand Response is a subset of demand side management, which also includes energy efficiency and conservation. The overall goal of this research project was to support increased penetration of DR in large facilities through the use of automation and better understanding of DR technologies and strategies in large facilities. To achieve this goal, a set of field tests were designed and conducted. These tests examined the performance of Auto-DR systems that covered a diverse set of building systems, ownership and management structures, climate zones, weather patterns, and control and communication configurations.

436

A novel air-conditioning system for proactive power demand response to smart grid  

Science Journals Connector (OSTI)

Abstract Power demand response is considered as one of the most promising solutions in relieving the power imbalance of an electrical grid that results a series of critical problems to the gird and end-users. In order to effectively make use of the demand response potentials of buildings, this paper presents a novel air-conditioning system with proactive demand control for daily load shifting and real time power balance in the developing smart grid. This system consists of a chilled water storage system (CWS) and a temperature and humidity independent control (THIC) air-conditioning system, which can significantly reduce the storage volume of the chilled water tank and effectively enable a building with more flexibility in changing its electricity usage patterns. The power demand of the proposed air-conditioning system can be flexibly controlled as desired by implementing two types of demand response strategies: demand side bidding (DSB) strategy and demand as frequency controlled reserve (DFR) strategy, in respond to the day-ahead and hour-ahead power change requirements of the grid, respectively. Considerable benefits (e.g., energy and cost savings) can be achieved for both the electricity utilities and building owners under incentive pricing or tariffs. A case study is conducted in a simulation platform to demonstrate the application of the proposed system in an office building.

Chengchu Yan; Xue Xue; Shengwei Wang; Borui Cui

2014-01-01T23:59:59.000Z

437

Decentralized demand–supply matching using community microgrids and consumer demand response: A scenario analysis  

Science Journals Connector (OSTI)

Abstract Developing countries constantly face the challenge of reliably matching electricity supply to increasing consumer demand. The traditional policy decisions of increasing supply and reducing demand centrally, by building new power plants and/or load shedding, have been insufficient. Locally installed microgrids along with consumer demand response can be suitable decentralized options to augment the centralized grid based systems and plug the demand–supply gap. The objectives of this paper are to: (1) develop a framework to identify the appropriate decentralized energy options for demand–supply matching within a community, and, (2) determine which of these options can suitably plug the existing demand–supply gap at varying levels of grid unavailability. A scenario analysis framework is developed to identify and assess the impact of different decentralized energy options at a community level and demonstrated for a typical urban residential community – Vijayanagar, Bangalore in India. A combination of LPG based CHP microgrid and proactive demand response by the community is the appropriate option that enables the Vijayanagar community to meet its energy needs 24/7 in a reliable, cost-effective manner. The paper concludes with an enumeration of the barriers and feasible strategies for the implementation of community microgrids in India based on stakeholder inputs.

Kumudhini Ravindra; Parameshwar P. Iyer

2014-01-01T23:59:59.000Z

438

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

Gasoline and Diesel Fuel Update (EIA)

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

439

The Role of Demand Response Policy Forum Series  

E-Print Network [OSTI]

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

California at Davis, University of

440

Electricity Markets Meet the Home through Demand Response Lazaros Gkatzikis  

E-Print Network [OSTI]

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

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

Autonomous Demand Response in Heterogeneous Smart Grid Topologies  

E-Print Network [OSTI]

1 Autonomous Demand Response in Heterogeneous Smart Grid Topologies Hamed Narimani and Hamed-mails: narimani-hh@ec.iut.ac.ir and hamed@ee.ucr.edu Abstract--Autonomous demand response (DR) is scalable and has demand response systems in heterogeneous smart grid topologies. Keywords: Autonomous demand response

Mohsenian-Rad, Hamed

442

Climate, extreme heat, and electricity demand in California  

E-Print Network [OSTI]

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

Miller, N.L.

2008-01-01T23:59:59.000Z

443

Construction of a Demand Side Plant with Thermal Energy Storage  

E-Print Network [OSTI]

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

Michel, M.

1989-01-01T23:59:59.000Z

444

Global food demand and the sustainable intensification of agriculture  

Science Journals Connector (OSTI)

...analyzed crop demand (utilization...ZZQQhy2007 per capita real (inflation-adjusted) GDP (Table S1...nut oil, an energy dense commodity...future crop demand that we present...nation the mean per capita crop demands...per capita GDP). Crop Demand...

David Tilman; Christian Balzer; Jason Hill; Belinda L. Befort

2011-01-01T23:59:59.000Z

445

Opportunities, Barriers and Actions for Industrial Demand Response in California  

E-Print Network [OSTI]

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

McKane, Aimee T.

2009-01-01T23:59:59.000Z

446

Reducing Energy Demand: What Are the Practical Limits?  

Science Journals Connector (OSTI)

Reducing Energy Demand: What Are the Practical Limits? ... Global demand for energy could be reduced by up to 73% through practical efficiency improvements “passive systems”, the last technical components in each energy chain. ... This paper aims to draw attention to the opportunity for major reduction in energy demand, by presenting an analysis of how much of current global energy demand could be avoided. ...

Jonathan M. Cullen; Julian M. Allwood; Edward H. Borgstein

2011-01-12T23:59:59.000Z

447

AUTOMATION OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S.  

E-Print Network [OSTI]

AUTOMATION OF ENERGY DEMAND FORECASTING by Sanzad Siddique, B.S. A Thesis submitted to the Faculty OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S. Marquette University, 2013 Automation of energy demand of the energy demand forecasting are achieved by integrating nonlinear transformations within the models

Povinelli, Richard J.

448

The Differential Effects of Oil Demand and Supply Shocks on the Global Economy  

E-Print Network [OSTI]

We employ a set of sign restrictions on the generalized impulse responses of a Global VAR model, estimated for 38 countries/regions over the period 1979Q2.2011Q2, to discriminate between supply-driven and demand-driven oil-price shocks and to study...

Cashin, Paul; Mohaddes, Kamiar; Raissi, Maziar; Raissi, Mehdi

2012-11-01T23:59:59.000Z

449

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

SciTech Connect (OSTI)

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

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

2012-01-01T23:59:59.000Z

450

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

E-Print Network [OSTI]

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

Cappers, Peter

2014-01-01T23:59:59.000Z

451

A Cooperative Demand Response Scheme Using Punishment Mechanism and Application to Industrial Refrigerated Warehouses  

E-Print Network [OSTI]

Garcia, “Autonomous demand-side management based on game-and D. Dietrich, “Demand side management: Demand re- sponse,

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

2014-01-01T23:59:59.000Z

452

Data centres’ power profile selecting policies for Demand Response: Insights of Green Supply Demand Agreement  

Science Journals Connector (OSTI)

Abstract Demand Response mechanisms serve to preserve the stability of the power grid by shedding the electricity load of the consumers during power shortage situations in order to match power generation to demand. Data centres have been identified as excellent candidates to participate in such mechanisms. Recently a novel supply demand agreement have been proposed to foster power adaptation collaboration between energy provider and data centres. In this paper, we analyse the contractual terms of this agreement by proposing and studying different data centres’ power profile selecting policies. To this end, we setup a discrete event simulation and analysed the power grid’s state of a German energy provider. We believe that our analysis provides insight and knowledge for any energy utility in setting up the corresponding demand supply agreements.

Robert Basmadjian; Lukas Müller; Hermann De Meer

2015-01-01T23:59:59.000Z

453

Managing Energy Demand With Standards and Information  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Managing Energy Demand With Standards and Information Managing Energy Demand With Standards and Information Speaker(s): Sebastien Houde Date: September 13, 2012 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Christopher Payne The goal of this talk is to discuss two interrelated research projects that aim to assess the welfare effects of energy policies that rely on standards and information. The first project focuses on the Energy Star certification program. Using unique micro-data on the US refrigerator market, I first show that consumers respond to certification in different ways. Some consumers appear to rely heavily on Energy Star and pay little attention to electricity costs, others are the reverse, and still others appear to be insensitive to both electricity costs and Energy Star. I then develop a

454

Is Demand-Side Management Economically Justified?  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

7 7 Is Demand-Side Management Economically Justified? With billions of dollars being spent on demand-side management programs in the U.S. every year, the rationale for and performance of these programs are coming under increasing scrutiny. Three projects in the Energy Analysis Program are making significant contributions to the DSM debate. *Total Resource Cost Test Ratio = ratio of utility avoided costs (i.e., benefits) divided by total cost of program (i.e., Administrative Cost + Incentive Cost + Consumer Cost) In May, Joe Eto, Ed Vine, Leslie Shown, Chris Payne, and I released the first in a series of reports we authored from the Database on Energy Efficiency Programs (DEEP) project. The objective of DEEP is to document the measured cost and performance of utility-sponsored energy-efficiency

455

Home Network Technologies and Automating Demand Response  

SciTech Connect (OSTI)

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

McParland, Charles

2009-12-01T23:59:59.000Z

456

What is a High Electric Demand Day?  

Broader source: Energy.gov [DOE]

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

457

Only tough choices in Meeting growing demand  

SciTech Connect (OSTI)

U.S. electricity demand is not growing very fast by international or historical standards. Yet meeting this relatively modest growth is proving difficult because investment in new capacity is expected to grow at an even slower pace. What is more worrisome is that a confluence of factors has added considerable uncertainties, making the investment community less willing to make the long-term commitments that will be needed during the coming decade.

NONE

2007-12-15T23:59:59.000Z

458

ERCOT's Weather Sensitive Demand Response Pilot  

E-Print Network [OSTI]

ERCOT’s Weather Sensitive Demand Response Pilot CATEE 12-17-13 ESL-KT-13-12-21 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 Disclaimer The information contained in this report has been obtained from... Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 Weather Sensitive Loads Pilot CATEE 121313 - Tim Carter 713-646-5476 tim.carter@constellation.com4 Constellation's Integrated Power Products © 2013. Constellation Energy Resources, LLC...

Carter, T.

2013-01-01T23:59:59.000Z

459

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

E-Print Network [OSTI]

in significant energy and demand savings for refrigeratedbe modified to reduce energy demand during demand responsein refrigerated warehouse energy demand if they are not

Lekov, Alex

2009-01-01T23:59:59.000Z

460

Chinese Oil Demand: Steep Incline Ahead  

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

Chinese Oil Demand: Chinese Oil Demand: Steep Incline Ahead Malcolm Shealy Alacritas, Inc. April 7, 2008 Oil Demand: China, India, Japan, South Korea 0 2 4 6 8 1995 2000 2005 2010 Million Barrels/Day China South Korea Japan India IEA China Oil Forecast 0 2 4 6 8 10 12 14 16 18 2000 2005 2010 2015 2020 2025 2030 Million Barrels/Day WEO 2007 16.3 mbd 12.7 mbd IEA China Oil Forecasts 0 2 4 6 8 10 12 14 16 18 2000 2005 2010 2015 2020 2025 2030 Million Barrels/Day WEO 2007 WEO 2006 WEO 2004 WEO 2002 Vehicle Sales in China 0 2 4 6 8 10 1990 1995 2000 2005 2010 Million Vehicles/Year Vehicle Registrations in China 0 10 20 30 40 50 1990 1995 2000 2005 2010 Million Vehicles/Year Vehicle Density vs GDP per Capita 0 20 40 60 80 100 120 140 160 180 200 0 4,000 8,000 12,000 16,000 GDP per capita, 2005$ PPP Vehicles per thousand people Taiwan South Korea China Vehicle Density vs GDP per Capita

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

A hybrid inventory management system respondingto regular demand and surge demand  

SciTech Connect (OSTI)

This paper proposes a hybrid policy for a stochastic inventory system facing regular demand and surge demand. The combination of two different demand patterns can be observed in many areas, such as healthcare inventory and humanitarian supply chain management. The surge demand has a lower arrival rate but higher demand volume per arrival. The solution approach proposed in this paper incorporates the level crossing method and mixed integer programming technique to optimize the hybrid inventory policy with both regular orders and emergency orders. The level crossing method is applied to obtain the equilibrium distributions of inventory levels under a given policy. The model is further transformed into a mixed integer program to identify an optimal hybrid policy. A sensitivity analysis is conducted to investigate the impact of parameters on the optimal inventory policy and minimum cost. Numerical results clearly show the benefit of using the proposed hybrid inventory model. The model and solution approach could help healthcare providers or humanitarian logistics providers in managing their emergency supplies in responding to surge demands.

Mohammad S. Roni; Mingzhou Jin; Sandra D. Eksioglu

2014-06-01T23:59:59.000Z

462

Modelling future private car energy demand in Ireland  

Science Journals Connector (OSTI)

Targeted measures influencing vehicle technology are increasingly a tool of energy policy makers within the EU as a means of meeting energy efficiency, renewable energy, climate change and energy security goals. This paper develops the modelling capacity for analysing and evaluating such legislation, with a focus on private car energy demand. We populate a baseline car stock and car activity model for Ireland to 2025 using historical car stock data. The model takes account of the lifetime survival profile of different car types, the trends in vehicle activity over the fleet and the fuel price and income elasticities of new car sales and total fleet activity. The impacts of many policy alternatives may only be simulated by such a bottom-up approach, which can aid policy development and evaluation. The level of detail achieved provides specific insights into the technological drivers of energy consumption, thus aiding planning for meeting climate targets. This paper focuses on the methodology and baseline scenario. Baseline results for Ireland forecast a decline in private car energy demand growth (0.2%, compared with 4% in the period 2000–2008), caused by the relative growth in fleet efficiency compared with activity.

Hannah E. Daly; Brian P. Ó Gallachóir

2011-01-01T23:59:59.000Z

463

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

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

Goldman, Charles

2010-01-01T23:59:59.000Z

464

Regional Water Management: Adapting to Uncertain Water  

E-Print Network [OSTI]

Regional Water Management: Adapting to Uncertain Water Supply and Demand Jim Schneider, Ph · How Nebraska manages water · Dealing with uncertain water supplies: adaptive management #12;Regional-wide, systematic approach · Flexible--Adaptive Management Adaptive Manageme nt #12;Integrated Water Management

Nebraska-Lincoln, University of

465

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

Gasoline and Diesel Fuel Update (EIA)

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

466

Demand Response Opportunities in Industrial Refrigerated Warehouses in  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Response Opportunities in Industrial Refrigerated Warehouses in Response Opportunities in Industrial Refrigerated Warehouses in California Title Demand Response Opportunities in Industrial Refrigerated Warehouses in California Publication Type Conference Paper LBNL Report Number LBNL-4837E Year of Publication 2011 Authors Goli, Sasank, Aimee T. McKane, and Daniel Olsen Conference Name 2011 ACEEE Summer Study on Energy Efficiency in Industry Date Published 08/2011 Conference Location Niagara Falls, NY Keywords market sectors, openadr, refrigerated warehouses Abstract Industrial refrigerated warehouses that implemented energy efficiency measures and have centralized control systems can be excellent candidates for Automated Demand Response (Auto-DR) due to equipment synergies, and receptivity of facility managers to strategies that control energy costs without disrupting facility operations. Auto-DR utilizes OpenADR protocol for continuous and open communication signals over internet, allowing facilities to automate their Demand Response (DR). Refrigerated warehouses were selected for research because: They have significant power demand especially during utility peak periods; most processes are not sensitive to short-term (2-4 hours) lower power and DR activities are often not disruptive to facility operations; the number of processes is limited and well understood; and past experience with some DR strategies successful in commercial buildings may apply to refrigerated warehouses. This paper presents an overview of the potential for load sheds and shifts from baseline electricity use in response to DR events, along with physical configurations and operating characteristics of refrigerated warehouses. Analysis of data from two case studies and nine facilities in Pacific Gas and Electric territory, confirmed the DR abilities inherent to refrigerated warehouses but showed significant variation across facilities. Further, while load from California's refrigerated warehouses in 2008 was 360 MW with estimated DR potential of 45-90 MW, actual achieved was much less due to low participation. Efforts to overcome barriers to increased participation may include, improved marketing and recruitment of potential DR sites, better alignment and emphasis on financial benefits of participation, and use of Auto-DR to increase consistency of participation.

467

An evaluation of forecasting methods for aircraft non-routine maintenance material demand  

Science Journals Connector (OSTI)

Aircraft maintenance can be divided into routine and non-routine activities. Material demand associated with non-routine maintenance is typically intermittent or lumpy: it has a large variance in frequency and quantity. Consequently, this type of demand is hard to predict. This paper introduces a method to collect time series datasets for aircraft non-routine maintenance material demand. Non-routine material consumption is linked to scheduled maintenance tasks to gain insight in demand patterns. A structural part selection of the Boeing 737NG fleet of an aviation partner has been sampled to generate various test cases. Subsequently, various forecasting methods are applied to these test cases and evaluated using various accuracy metrics. For the small time series datasets associated with non-routine maintenance, exponentially weighted moving average (EMA) outperformed smoothing methods such as Croston's method (CR) and the Syntetos-Boylan approximation (SBA). To validate the practical applicability of EMA for non-routine maintenance material demand, the method has been applied and verified in the prediction of actual demand for a separate maintenance C-check.

Maarten Zorgdrager; Wim J.C. Verhagen; Richard Curran

2014-01-01T23:59:59.000Z

468

The Demand Side: Behavioral Patterns and Unpicked Low-Hanging Fruit  

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

The Demand Side: Behavioral Patterns and The Demand Side: Behavioral Patterns and Unpicked Low-Hanging Fruit James Sweeney Stanford University Director Precourt Energy Efficiency Center (NĂ©e: Precourt Institute for Energy Efficiency) Professor, Management Science and Engineering 6 Source: McKinsey & Co. Increased commercial space Gasoline Price Controls Compact Fluorescent Penetration LED: Traffic Lights, Task Lighting Appliance Energy Labeling Gasoline Rationing Much Incandescent Lighting Congestion Pricing Personal Computer Penetration Optimized Building Construction Overly Strict Building Standards Pigouvian Energy Tax Reduced Cost Decreased Energy Use "Smart" Regional Land Development Reformed Fuel Efficiency Standards Some Rail Rapid Transit Systems Efficient AC-DC Converters Halt SUV

469

Value of Demand Response: Quantities from Production Cost Modeling (Presentation)  

SciTech Connect (OSTI)

Demand response (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind and solar power generation. However, managed loads in grid models are limited by data availability and modeling complexity. This presentation focuses on the value of co-optimized DR resources to provide energy and ancillary services in a production cost model. There are significant variations in the availabilities of different types of DR resources, which affect both the operational savings as well as the revenue for each DR resource. The results presented include the system-wide avoided fuel and generator start-up costs as well as the composite revenue for each DR resource by energy and operating reserves. In addition, the revenue is characterized by the capacity, energy, and units of DR enabled.

Hummon, M.

2014-04-01T23:59:59.000Z

470

LNG demand, shipping will expand through 2010  

SciTech Connect (OSTI)

The 1990s, especially the middle years, have witnessed a dramatic turnaround in the growth of liquefied-natural-gas demand which has tracked equally strong natural-gas demand growth. This trend was underscored late last year by several annual studies of world LNG demand and shipping. As 1998 began, however, economic turmoil in Asian financial markets has clouded near-term prospects for LNG in particular and all energy in general. But the extent of damage to energy markets is so far unclear. A study by US-based Institute of Gas Technology, Des Plaines, IL, reveals that LNG imports worldwide have climbed nearly 8%/year since 1980 and account for 25% of all natural gas traded internationally. In the mid-1970s, the share was only 5%. In 1996, the most recent year for which complete data are available, world LNG trade rose 7.7% to a record 92 billion cu m, outpacing the overall consumption for natural gas which increased 4.7% in 1996. By 2015, says the IGT study, natural-gas use would surpass coal as the world`s second most widely used fuel, after petroleum. Much of this growth will occur in the developing countries of Asia where gas use, before the current economic crisis began, was projected to grow 8%/year through 2015. Similar trends are reflected in another study of LNG trade released at year end 1997, this from Ocean Shipping Consultants Ltd., Surrey, U.K. The study was done too early, however, to consider the effects of the financial problems roiling Asia.

True, W.R.

1998-02-09T23:59:59.000Z

471

The impact of demand-controlled and economizer ventilation strategies on energy use in buildings  

SciTech Connect (OSTI)

The overall objective of this work was to evaluate typical energy requirements associated with alternative ventilation control strategies for constant-air-volume (CAV) systems in commercial buildings. The strategies included different combinations of economizer and demand-controlled ventilation, and energy analyses were performed for four typical building types, eight alternative ventilation systems, and twenty US climates. Only single-zone buildings were considered so that simultaneous heating and cooling did not exist. The energy savings associated with economizer and demand-controlled ventilation strategies were found to be very significant for both heating and cooling. In general, the greatest savings in electrical usage for cooling with the addition of demand-controlled ventilation occur in situations where the opportunities for economizer cooling are less. This is true for warm and humid climates and for buildings that have relatively low internal gains (i.e., low occupant densities). As much as 20% savings in electrical energy for cooling were possible with demand-controlled ventilation. The savings in heating energy associated with demand-controlled ventilation were generally much larger but were strongly dependent upon the building type and occupancy schedule. Significantly greater savings were found for buildings with highly variable occupancy schedules and large internal gains (i.e., restaurants) as compared with office buildings. In some cases, the primary heating energy was virtually eliminated by demand-controlled ventilation as compared with fixed ventilation rates. For both heating and cooling, the savings associated with demand-controlled ventilation are dependent on the fixed minimum ventilation rate of the base case at design conditions.

Brandemuehl, M.J.; Braun, J.E.

1999-07-01T23:59:59.000Z

472

Barrier Immune Radio Communications for Demand Response  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

94E 94E Barrier Immune Radio Communications for Demand Response F. Rubinstein, G. Ghatikar, J. Granderson, D. Watson Lawrence Berkeley National Laboratory P. Haugen, C. Romero Lawrence Livermore National Laboratory February 2009 DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe

473

Gasoline demand in developing Asian countries  

SciTech Connect (OSTI)

This paper presents econometric estimates of motor gasoline demand in eleven developing countries of Asia. The price and GDP per capita elasticities are estimated for each country separately, and for several pooled combinations of the countries. The estimated elasticities for the Asian countries are compared with those of the OECD countries. Generally, one finds that the OECD countries have GDP elasticities that are smaller, and price elasticities that are larger (in absolute value). The price elasticities for the low-income Asian countries are more inelastic than for the middle-income Asian countries, and the GDP elasticities are generally more elastic. 13 refs., 6 tabs.

McRae, R. [Univ. of Calgary, Alberta (Canada)

1994-12-31T23:59:59.000Z

474

Property:GeothermalRegion | Open Energy Information  

Open Energy Info (EERE)

Property Name GeothermalRegion Property Name GeothermalRegion Property Type Page Pages using the property "GeothermalRegion" Showing 25 pages using this property. (previous 25) (next 25) A Abraham Hot Springs Geothermal Area + Northern Basin and Range Geothermal Region + Adak Geothermal Area + Alaska Geothermal Region + Aidlin Geothermal Facility + Holocene Magmatic Geothermal Region + Akun Strait Geothermal Area + Alaska Geothermal Region + Akutan Fumaroles Geothermal Area + Alaska Geothermal Region + Akutan Geothermal Project + Alaska Geothermal Region + Alum Geothermal Area + Walker-Lane Transition Zone Geothermal Region + Alum Geothermal Project + Walker-Lane Transition Zone Geothermal Region + Alvord Hot Springs Geothermal Area + Northwest Basin and Range Geothermal Region +

475

National Action Plan on Demand Response  

Broader source: Energy.gov (indexed) [DOE]

6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 ACTUAL FORECAST National Action Plan on Demand Response the feDeRal eneRgy RegulatoRy commission staff 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 National Action Plan on Demand Response THE FEDERAL ENERGY REGULATORY COMMISSION STAFF June 17, 2010 Docket No. AD09-10 Prepared with the support of The Brattle Group * GMMB * Customer Performance Group Definitive Insights * Eastern Research Group The opinions and views expressed in this staff report do not necessarily represent those of the Federal Energy Regulatory Commission, its Chairman, or individual Commissioners, and are not binding on the Commission.

476

Optimal Demand Response with Energy Storage Management  

E-Print Network [OSTI]

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

Huang, Longbo; Ramchandran, Kannan

2012-01-01T23:59:59.000Z

477

Strategic dynamic vehicle routing with spatio-temporal dependent demands  

E-Print Network [OSTI]

Dynamic vehicle routing problems address the issue of determining optimal routes for a set of vehicles, to serve a given set of demands that arrive sequentially in time. Traditionally, demands are assumed to be generated ...

Feijer, Diego (Diego Francisco Feijer Rovira)

2011-01-01T23:59:59.000Z

478

Demand Response Analysis in Smart Grids Using Fuzzy Clustering Model  

Science Journals Connector (OSTI)

This paper focuses on an analysis of demand response in a smart grid context, presenting the ... A fuzzy subtractive clustering method is applied to demand response on several domestic consumption scenarios and r...

R. Pereira; A. Fagundes; R. Melício…

2013-01-01T23:59:59.000Z

479

Optimization of Demand Response Through Peak Shaving , D. Craigie  

E-Print Network [OSTI]

Optimization of Demand Response Through Peak Shaving G. Zakeri , D. Craigie , A. Philpott , M. Todd for the demand response of such a consumer. We will establish a monotonicity result that indicates fuel supply

Todd, Michael J.

480

Quantifying the Variable Effects of Systems with Demand Response Resources  

E-Print Network [OSTI]

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

Gross, George

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481

Software components for demand side integration at a container terminal  

Science Journals Connector (OSTI)

Local energy management and demand response are established methods to raise energy ... in industrial enterprises the intelligent use of power demand draws significantly increased importance. Due to the ... energ...

Norman Ihle; Serge Runge; Claas Meyer-Barlag…

2014-11-01T23:59:59.000Z

482

Research on the Demand Side Management Under Smart Grid  

Science Journals Connector (OSTI)

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

Litong Dong; Jun Xu; Haibo Liu; Ying Guo

2014-01-01T23:59:59.000Z

483

Enhanced Oil Recovery to Fuel Future Oil Demands | GE Global...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

to Fuel Future Oil Demands Enhanced Oil Recovery to Fuel Future Oil Demands Trevor Kirsten 2013.10.02 I'm Trevor Kirsten and I lead a team of GE researchers that investigate a...

484

The Energy Demand Forecasting System of the National Energy Board  

Science Journals Connector (OSTI)

This paper presents the National Energy Board’s long term energy demand forecasting model in its present state of ... results of recent research at the NEB. Energy demand forecasts developed with the aid of this....

R. A. Preece; L. B. Harsanyi; H. M. Webster

1980-01-01T23:59:59.000Z

485

Competitive Technologies, Equipment Vintages and the Demand for Energy  

Science Journals Connector (OSTI)

Macroeconometric modelling of energy demand resorts to two approaches leading to models ... of view. The first approach specifies the demand of a group of consumers for a single form of energy, independent of the...

F. Carlevaro

1988-01-01T23:59:59.000Z

486

Forecasting Energy Demand Using Fuzzy Seasonal Time Series  

Science Journals Connector (OSTI)

Demand side energy management has become an important issue for energy management. In order to support energy planning and policy decisions forecasting the future demand is very important. Thus, forecasting the f...

?Irem Uçal Sar?; Ba¸sar Öztay¸si

2012-01-01T23:59:59.000Z

487

Indianapolis Offers a Lesson on Driving Demand | Department of...  

Broader source: Energy.gov (indexed) [DOE]

Indianapolis Offers a Lesson on Driving Demand Indianapolis Offers a Lesson on Driving Demand The flier for EcoHouse, with the headline 'Save energy, save money, improve your home'...

488

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

E-Print Network [OSTI]

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

Olsen, Daniel

2013-01-01T23:59:59.000Z

489

Analytical Frameworks to Incorporate Demand Response in Long-term Resource Planning  

E-Print Network [OSTI]

management system demand-side management energy efficiencyresource plans and demand side management (DSM) program

Satchwell, Andrew

2014-01-01T23:59:59.000Z

490

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

SciTech Connect (OSTI)

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

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

2008-04-30T23:59:59.000Z

491

Micro-Based Estimatesof Demand Functions for Local School Expenditures  

E-Print Network [OSTI]

demand functions from individual qualitative responses to a survey. This leads to estimates of income and price elasticities

Bergstrom, Ted; Rubinfeld, Daniel L.; Shapiro, Perry

1982-01-01T23:59:59.000Z

492

Maintaining Privacy in Data Rich Demand Response Applications  

Science Journals Connector (OSTI)

The paper introduces the privacy problem of demand response applications performed with the OpenADR standard. A...

Markus Karwe; Jens Strüker

2013-01-01T23:59:59.000Z

493

The Important Participants in Demand-Side Management: Power Consumers  

Science Journals Connector (OSTI)

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

Zhaoguang Hu; Xinyang Han; Quan Wen

2013-01-01T23:59:59.000Z

494

An Integrated Architecture for Demand Response Communications and Control  

E-Print Network [OSTI]

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

Gross, George

495

Factors Influencing Productivity and Operating Cost of Demand Responsive Transit  

E-Print Network [OSTI]

Factors Influencing Productivity and Operating Cost of Demand Responsive Transit Kurt Palmer Maged of the Americans with Disabilities Act in 1991 operating expenses for Demand Responsive Transit have more than and practices upon productivity and operating cost. ii #12;1 Introduction Demand Responsive Transit (DRT

Dessouky, Maged

496

Application of a Combination Forecasting Model in Logistics Parks' Demand  

Science Journals Connector (OSTI)

Logistics parks’ demand is an important basis of establishing the development policy of logistics industry and logistics infrastructure for planning. In order to improve the forecast accuracy of logistics parks’ demand, a combination forecasting ... Keywords: Logistics parks' demand, combine, simulated annealing algorithm, grey forecast model, exponential smoothing method

Chen Qin; Qi Ming

2010-05-01T23:59:59.000Z

497

A First Look at Colocation Demand Response Shaolei Ren  

E-Print Network [OSTI]

A First Look at Colocation Demand Response Shaolei Ren Florida International University Mohammad A. Islam Florida International University ABSTRACT Large data centers can participate in demand response, the existing research has only considered demand response by owner-operated data centers (e.g., Google

Ren, Shaolei

498

Examining Synergies between Energy Management and Demand Response: A  

E-Print Network [OSTI]

LBNL-5719E Examining Synergies between Energy Management and Demand Response: A Case Study at Two Summary #12;Introduction Energy Management · · · · · · · · · · #12;Demand Response #12;#12;Bentley Prince-Project Personnel Changes #12;Enablement of Demand Response Capabilities due to Energy Management Improvement

499

Retrofitting Existing Buildings for Demand Response & Energy Efficiency  

E-Print Network [OSTI]

Retrofitting Existing Buildings for Demand Response & Energy Efficiency www, enable demand response, improve productivity for older facilities. - Use technologies which minimize are notified by PG&E by 3pm the day prior to the critical event. - Customers with Auto-Demand Response enabled

California at Los Angeles, University of

500

Assessing the Control Systems Capacity for Demand Response in  

E-Print Network [OSTI]

LBNL-5319E Assessing the Control Systems Capacity for Demand Response in California Industries in this report was coordinated by the Demand Response Research Center and funded by the California Energy of the Demand Response Research Center Industrial Controls Experts Working Group: · Jim Filanc, Southern