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1

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

2

NEMS Freight Transportation Module Improvement Study  

Reports and Publications (EIA)

The U.S. Energy Information Administration (EIA) contracted with IHS Global, Inc. (IHS) to analyze the relationship between the value of industrial output, physical output, and freight movement in the United States for use in updating analytic assumptions and modeling structure within the National Energy Modeling System (NEMS) freight transportation module, including forecasting methodologies and processes to identify possible alternative approaches that would improve multi-modal freight flow and fuel consumption estimation.

2015-01-01T23:59:59.000Z

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

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

5

NEMS Freight Transportation Module Improvement Study  

Gasoline and Diesel Fuel Update (EIA)

and forecast accuracy. Challenges might include new skill development within EIA, contracting for additional commercial services, and possibly altering the manner in which NEMS...

6

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

7

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.

8

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.

9

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.

10

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

11

Modelling transport fuel demand  

Science Journals Connector (OSTI)

Transport fuels account for an increasing share of oil ... interest to study the economics of the transport fuel market and thereby to evaluate the efficiency of the price mechanism as an instrument of policy in ...

Thomas Sterner; Carol A. Dahl

1992-01-01T23:59:59.000Z

12

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.

13

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

14

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.

15

NEMS integrating module documentation report  

SciTech Connect (OSTI)

The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. energy markets for the midterm period. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to a variety of assumptions. The assumptions encompass macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, technology characteristics, and demographics. NEMS produces a general equilibrium solution for energy supply and demand in the U.S. energy markets on an annual basis through 2015. Baseline forecasts from NEMS are published in the Annual Energy Outlook. Analyses are also prepared in response to requests by the U.S. Congress, the DOE Office of Policy, and others. NEMS was first used for forecasts presented in the Annual Energy Outlook 1994.

NONE

1997-05-01T23:59:59.000Z

16

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

17

National Energy Modeling System (NEMS)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. through 2030. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. NEMS was designed and implemented by the Energy Information Administration (EIA) of the U.S. Department of Energy (DOE). NEMS can be used to analyze the effects of existing and proposed government laws and regulations related to energy production and use; the potential impact of new and advanced energy production, conversion, and consumption technologies; the impact and cost of greenhouse gas control; the impact of increased use of renewable energy sources; and the potential savings from increased efficiency of energy use; and the impact of regulations on the use of alternative or reformulated fuels. NEMS has also been used for a number of special analyses at the request of the Administration, U.S. Congress, other offices of DOE and other government agencies, who specify the scenarios and assumptions for the analysis. Modules allow analyses to be conducted in energy topic areas such as residential demand, industrial demand, electricity market, oil and gas supply, renewable fuels, etc.

18

China-Transportation Demand Management in Beijing: Mitigation...  

Open Energy Info (EERE)

Beijing: Mitigation of Emissions in Urban Transport Jump to: navigation, search Name Transportation Demand Management in Beijing - Mitigation of emissions in urban transport...

19

New city model to reduce demand for transportation  

Science Journals Connector (OSTI)

Managing demand for transportation can be a cost-effective alternative to increasing capacity. A demand management approach to transport services also has the potential to deliver better environmental outcomes, improved public health and stronger communities, and more prosperous and liveable cities The increased distance between places will have a direct impact on the demand of transportation. Public transport system (MRTS) is an answer to the growing traffic congestion. However, the question is; Is MRTS are the last resort? This paper will be an attempt to regularize the development scenario of the city and thus reducing the demand for transportation.

Sumant Sharma; Anoop Sharma; Ashwani Kumar

2011-01-01T23:59:59.000Z

20

China-Transportation Demand Management in Beijing: Mitigation of Emissions  

Open Energy Info (EERE)

China-Transportation Demand Management in Beijing: Mitigation of Emissions China-Transportation Demand Management in Beijing: Mitigation of Emissions in Urban Transport Jump to: navigation, search Name Transportation Demand Management in Beijing - Mitigation of emissions in urban transport Agency/Company /Organization Deutsche Gesellschaft fĂĽr Internationale Zusammenarbeit (GIZ) GmbH Sector Climate Focus Area Transportation Topics Low emission development planning, -LEDS, -NAMA Website http://www.tdm-beijing.org/ Program Start 2011 Program End 2014 Country China Eastern Asia References Transport Management in Beijing[1] Program Overview The project aims to improve transport demand management (TDM) in Beijing in order to manage the steadily increasing traffic density. The project provides capacity building for decision-makers and transport planners in

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


21

Energy demand and economic consequences of transport policy  

Science Journals Connector (OSTI)

Transport sector is a major consumer of energy. Concern of energy scarcity and price fluctuations enhanced significance of ... sector in national planning. This paper analyses energy demand for transport services...

J. B. Alam; Z. Wadud; J. B. Alam…

2013-09-01T23:59:59.000Z

22

EIA Buildings Analysis of Consumer Behavior in NEMS  

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

Buildings Analysis of Consumer Buildings Analysis of Consumer Behavior in NEMS Behavioral Economics Experts Meeting July 17, 2013 | Washington, DC David Peterson Buildings Energy Consumption and Efficiency Analysis Overview Behavioral Economics Experts Meeting, Washington DC, July 17, 2013 2 * NEMS Structure * Housing/floorspace and service demand in Residential Demand Module (RDM) and Commercial Demand Module (CDM) * Market share calculation for equipment in RDM and CDM * Price responses / elasticities * Distributed generation (DG) & combined heat and power (CHP) NEMS Structure Behavioral Economics Experts Meeting, Washington DC, July 17, 2013 3 * Represents energy supply, conversion, and demand in a unified, but modular system * Detailed structural and process models in most energy sectors

23

Multi-Path Transportation Futures Study: Vehicle Characterization and Scenario Analyses - Appendix E: Other NEMS-MP Results for the Base Case and Scenarios  

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

Appendix E: Other NEMS-MP Results Appendix E: Other NEMS-MP Results for the Base Case and Scenarios Energy Systems Division Availability of This Report This report is available, at no cost, at http://www.osti.gov/bridge. It is also available on paper to the U.S. Department of Energy and its contractors, for a processing fee, from: U.S. Department of Energy Office of Scientific and Technical Information P.O. Box 62

24

Energy Demand and Emission from Transport Sector in China  

Science Journals Connector (OSTI)

This paper aims to present a comprehensive overview of the current status and future trends of energy demand and emissions from transportation sector in China. ... a brief review of the national profile of energy

Yin Huang; Mengjun Wang

2013-01-01T23:59:59.000Z

25

Transportation Demand Management in Beijing - Mitigation of emissions in  

Open Energy Info (EERE)

Beijing - Mitigation of emissions in Beijing - Mitigation of emissions in urban transport Jump to: navigation, search Name Transportation Demand Management in Beijing - Mitigation of emissions in urban transport Agency/Company /Organization Deutsche Gesellschaft fĂĽr Internationale Zusammenarbeit (GIZ) GmbH Sector Climate Focus Area Transportation Topics Low emission development planning, -LEDS, -NAMA Website http://www.tdm-beijing.org/ Program Start 2011 Program End 2014 Country China Eastern Asia References Transport Management in Beijing[1] Program Overview The project aims to improve transport demand management (TDM) in Beijing in order to manage the steadily increasing traffic density. The project provides capacity building for decision-makers and transport planners in Beijing to enable them to calculate baselines and assess reduction

26

Overview of NEMS-H2, Version 1.0  

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

NEMS-H2, Version 1.0 NEMS-H2, Version 1.0 Frances Wood OnLocation, Inc., Energy Systems Consulting (fwood@onlocationinc.com) January 26, 2006 OnLocation, Inc., Energy Systems Consulting 2 Today's Presentation * Overview of NEMS-H2 Structure * Current Status * New Hydrogen Market Module (HMM) * Transportation Module Modifications * Preliminary Test Runs * Looking Ahead to Next Phase OnLocation, Inc., Energy Systems Consulting 3 NEMS Overview * The National Energy Modeling System (NEMS) was developed and is maintained by EIA - Annual Energy Outlook projections - Congressional as well as agency requests * NEMS has also been used extensively outside of EIA - Various National Laboratories studies - National Commission on Energy Policy - Program offices within DOE for R&D benefits estimation * Modular structure allows each sector to be represented by

27

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

28

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

29

Price Responsiveness in the AEO2003 NEMS Residential and Commercial Buildings Sector Models  

Reports and Publications (EIA)

This paper describes the demand responses to changes in energy prices in the Annual Energy Outlook 2003 versions of the Residential and Commercial Demand Modules of the National Energy Modeling System (NEMS). It updates a similar paper completed for the Annual Energy Outlook 1999 version of the NEMS.

2003-01-01T23:59:59.000Z

30

Sustainable Campus Transportation through Transit Partnership and Transportation Demand Management: A Case Study from the University of Florida  

E-Print Network [OSTI]

A. 2005. The impacts of transportation demand management andUnlimited access. Transportation 28 (3): 233–267. Cervero,transit. Journal of Public Transportation 3 (4):10–19. ???.

Bond, Alex; Steiner, Ruth

2006-01-01T23:59:59.000Z

31

Climate change mitigation and co-benefits of feasible transport demand policies in Beijing  

E-Print Network [OSTI]

i n f o Keywords: Climate change mitigation Transport demand management External costs Urban and potential impacts of travel demand management help to define policy instruments that mitigate the damaging. The paper investi- gates the role of demand elasticities and demonstrates that joint demand and supply-side

Kammen, Daniel M.

32

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

SciTech Connect (OSTI)

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

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

2013-03-01T23:59:59.000Z

33

Transport, energy and greenhouse gases: perspectives on demand limitation. Guest editorial  

Science Journals Connector (OSTI)

The current economic recession results in reduced industrial output and energy consumption, and thus reduces freight transport activity ... , but everything indicates that growth in transport demand should re-sta...

Charles Raux; Martin E. H. Lee-Gosselin

2010-05-01T23:59:59.000Z

34

A MODEL FOR THE FLEET SIZING OF DEMAND RESPONSIVE TRANSPORTATION SERVICES WITH TIME WINDOWS  

E-Print Network [OSTI]

A MODEL FOR THE FLEET SIZING OF DEMAND RESPONSIVE TRANSPORTATION SERVICES WITH TIME WINDOWS Marco a demand responsive transit service with a predetermined quality for the user in terms of waiting time models; Continuous approximation models; Paratransit services; Demand responsive transit systems. #12;3 1

Dessouky, Maged

35

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.

36

Harmony Search Algorithm for Transport Energy Demand Modeling  

Science Journals Connector (OSTI)

The transport sector is one of the major consumers of energy production throughout the world. Thus, the estimation of medium and long-term energy consumption based on socio-economic and transport related indic...

Halim Ceylan; Huseyin Ceylan

2009-01-01T23:59:59.000Z

37

Investigation of residential central air conditioning load shapes in NEMS  

SciTech Connect (OSTI)

This memo explains what Berkeley Lab has learned about how the residential central air-conditioning (CAC) end use is represented in the National Energy Modeling System (NEMS). NEMS is an energy model maintained by the Energy Information Administration (EIA) that is routinely used in analysis of energy efficiency standards for residential appliances. As part of analyzing utility and environmental impacts related to the federal rulemaking for residential CAC, lower-than-expected peak utility results prompted Berkeley Lab to investigate the input load shapes that characterize the peaky CAC end use and the submodule that treats load demand response. Investigations enabled a through understanding of the methodology by which hourly load profiles are input to the model and how the model is structured to respond to peak demand. Notably, it was discovered that NEMS was using an October-peaking load shape to represent residential space cooling, which suppressed peak effects to levels lower than expected. An apparent scaling down of the annual load within the load-demand submodule was found, another significant suppressor of the peak impacts. EIA promptly responded to Berkeley Lab's discoveries by updating numerous load shapes for the AEO2002 version of NEMS; EIA is still studying the scaling issue. As a result of this work, it was concluded that Berkeley Lab's customary end-use decrement approach was the most defensible way for Berkeley Lab to perform the recent CAC utility impact analysis. This approach was applied in conjunction with the updated AEO2002 load shapes to perform last year's published rulemaking analysis. Berkeley Lab experimented with several alternative approaches, including modifying the CAC efficiency level, but determined that these did not sufficiently improve the robustness of the method or results to warrant their implementation. Work in this area will continue in preparation for upcoming rulemakings for the other peak coincident end uses, commercial air conditioning and distribution transformers.

Hamachi LaCommare, Kristina; Marnay, Chris; Gumerman, Etan; Chan, Peter; Rosenquist, Greg; Osborn, Julie

2002-05-01T23:59:59.000Z

38

Solving a Dial-a-Ride Problem with a Hybrid Evolutionary Multi-objective Application to Demand Responsive Transport  

E-Print Network [OSTI]

to Demand Responsive Transport R´emy Chevrier,a , Arnaud Liefoogheb,c , Laetitia Jourdanb,c , Clarisse, 59650 Villeneuve d'Ascq, France Abstract Demand responsive transport allows customers to be carried to improve the quality of service, demand responsive transport needs more flexibility. This paper tries

Boyer, Edmond

39

Analysis and Representation of Miscellaneous Electric Loads in NEMS -  

Gasoline and Diesel Fuel Update (EIA)

Analysis and Representation of Miscellaneous Electric Loads in NEMS Analysis and Representation of Miscellaneous Electric Loads in NEMS Release date: January 6, 2014 Miscellaneous Electric Loads (MELs) comprise a growing portion of delivered energy consumption in residential and commercial buildings. Recently, the growth of MELs has offset some of the efficiency gains made through technology improvements and standards in major end uses such as space conditioning, lighting, and water heating. Miscellaneous end uses, including televisions, personal computers, security systems, data center servers, and many other devices, have continued to penetrate into building-related market segments. Part of this proliferation of devices and equipment can be attributed to increased service demand for entertainment, computing, and convenience appliances.

40

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

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

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

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


41

The National Energy Modeling System: An Overview 2000 - Overview of NEMS  

Gasoline and Diesel Fuel Update (EIA)

NEMS represents domestic energy markets by explicitly representing the economic decision making involved in the production, conversion, and consumption of energy products. Where possible, NEMS includes explicit representation of energy technologies and their characteristics. NEMS represents domestic energy markets by explicitly representing the economic decision making involved in the production, conversion, and consumption of energy products. Where possible, NEMS includes explicit representation of energy technologies and their characteristics. Since energy costs and availability and energy-consuming characteristics can vary widely across regions, considerable regional detail is included. Other details of production and consumption categories are represented to facilitate policy analysis and ensure the validity of the results. A summary of the detail provided in NEMS is shown below. Summary Table Major Assumptions Each module of NEMS embodies many assumptions and data to characterize the future production, conversion, or consumption of energy in the United States. Two major assumptions concern economic growth in the United States and world oil prices, as determined by world oil supply and demand.

42

Activity based travel demand models as a tool for evaluating sustainable transportation policies  

Science Journals Connector (OSTI)

India is in the course of an economic transition. The economic growth nurtured the life in the cities and cities have become a major livelihood destination for everyone. This migration of people contributed to the increased urbanization of Indian cities. The booming economy fostered the well-being and shaped the lifestyle of people in such a way that the dependency on private vehicle has become an unavoidable affair. Along with population growth, the increased vehicle ownership gave rise to overall spurt in travel demand. But the supply side lagged behind the demand adding to many of the transport related externalities such as accidents, congestion, pollution, inequity etc. The importance of sustainability is understood in the current urban transport scenario leading to the development and promotion of sustainable transport polices. The core agenda of these polices is to target the travel behavior of people and change the way they travel by creating a different travel environment. However, the impacts of many such policies are either unknown or complex. Hence, before adopting and implementing such policies, it is important for the decision makers to be aware of the impacts of them. The role of travel demand models comes here as they predict the future travel demand under different policy scenarios. This paper reviews the ability of travel demand models applied in India in analyzing the sustainable transport policies. The study found that the conventional model system in India, which is trip based four step aggregate methodology, is inadequate in analyzing the sustainable transport policies. A review of alternative approach, known as activity based travel demand modeling found that they are capable of handling such policies better than conventional models and are assistive to the decision makers in arriving at right mix of polices specific to the situations. Since there is no operational activity based travel demand model system developed in India, the study at the end envisaged a conceptual framework of an integrated activity based travel demand model based on the requirements identified from the review. This can potentially replace the existing travel demand models and can be used for planning applications once the modification & validation have been done according to the existing activity-travel behavior of individuals.

Manoj Malayath; Ashish Verma

2013-01-01T23:59:59.000Z

43

Mobility and Carbon: The Blind Side of Transport Fuel Demand in the  

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

Mobility and Carbon: The Blind Side of Transport Fuel Demand in the Mobility and Carbon: The Blind Side of Transport Fuel Demand in the Developed and Developing World Speaker(s): Lee Schipper Date: February 15, 2011 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Anita Estner James McMahon A new "Great Wall" has emerged in China, this one a string of miles of cars stuck in traffic. Emissions from road transport in developing countries are expected to rise sharply in the coming decades if current trends continue. Projections of passenger and freight activity, vehicle use, and CO2 emissions push up overall CO2 emissions by a factor of three in Latin American and five in Asia by 2030, even with fuel economy improvements. The increase in car use is in part a result of growing incomes and economic activity, but it also reflects the poor quality of transit and

44

Integrated NEMS and optoelectronics for sensor applications.  

SciTech Connect (OSTI)

This work utilized advanced engineering in several fields to find solutions to the challenges presented by the integration of MEMS/NEMS with optoelectronics to realize a compact sensor system, comprised of a microfabricated sensor, VCSEL, and photodiode. By utilizing microfabrication techniques in the realization of the MEMS/NEMS component, the VCSEL and the photodiode, the system would be small in size and require less power than a macro-sized component. The work focused on two technologies, accelerometers and microphones, leveraged from other LDRD programs. The first technology was the nano-g accelerometer using a nanophotonic motion detection system (67023). This accelerometer had measured sensitivity of approximately 10 nano-g. The Integrated NEMS and optoelectronics LDRD supported the nano-g accelerometer LDRD by providing advanced designs for the accelerometers, packaging, and a detection scheme to encapsulate the accelerometer, furthering the testing capabilities beyond bench-top tests. A fully packaged and tested die was never realized, but significant packaging issues were addressed and many resolved. The second technology supported by this work was the ultrasensitive directional microphone arrays for military operations in urban terrain and future combat systems (93518). This application utilized a diffraction-based sensing technique with different optical component placement and a different detection scheme from the nano-g accelerometer. The Integrated NEMS LDRD supported the microphone array LDRD by providing custom designs, VCSELs, and measurement techniques to accelerometers that were fabricated from the same operational principles as the microphones, but contain proof masses for acceleration transduction. These devices were packaged at the end of the work.

Czaplewski, David A.; Serkland, Darwin Keith; Olsson, Roy H., III; Bogart, Gregory R. (Symphony Acoustics, Rio Rancho, NM); Krishnamoorthy, Uma; Warren, Mial E.; Carr, Dustin Wade (Symphony Acoustics, Rio Rancho, NM); Okandan, Murat; Peterson, Kenneth Allen

2008-01-01T23:59:59.000Z

45

How to obtain the National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

The National Energy Modeling System (NEMS) NEMS is used by the modelers at the U. S. Energy Information Administration (EIA) who understand its structure and programming. NEMS has only been used by a few organizations outside of the EIA, because most people that requested NEMS found out that it was too difficult or rigid to use. NEMS is not typically used for state-level analysis and is poorly suited for application to other countries. However, many do obtain the model simply to use the data in its input files or to examine the source code.

2013-01-01T23:59:59.000Z

46

Overview of Options to Integrate Stationary Power Generation from Fuel Cells with Hydrogen Demand for the Transportation Sector  

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

Overview of Options to Integrate Stationary Overview of Options to Integrate Stationary Power Generation from Fuel Cells with Hydrogen Demand for the Transportation Sector Overview of Options to Integrate Stationary Overview of Options to Integrate Stationary Power Generation from Fuel Cells with Power Generation from Fuel Cells with Hydrogen Demand for the Transportation Hydrogen Demand for the Transportation Sector Sector Fred Joseck U.S. DOE Hydrogen Program Transportation and Stationary Power Integration Workshop (TSPI) Transportation and Stationary Power Transportation and Stationary Power Integration Workshop (TSPI) Integration Workshop (TSPI) Phoenix, Arizona October 27, 2008 2 Why Integration? * Move away from conventional thinking...fuel and power generation/supply separate * Make dramatic change, use economies of scale,

47

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

48

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

49

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].

50

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

51

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

52

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

53

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.

54

National Energy Modeling System (NEMS) | Open Energy Information  

Open Energy Info (EERE)

National Energy Modeling System (NEMS) National Energy Modeling System (NEMS) Jump to: navigation, search Tool Summary LAUNCH TOOL Name: National Energy Modeling System (NEMS) Agency/Company /Organization: Energy Information Administration Sector: Energy Focus Area: Economic Development Phase: Develop Goals Topics: Policies/deployment programs Resource Type: Software/modeling tools User Interface: Desktop Application Website: www.eia.gov/oiaf/aeo/overview/index.html OpenEI Keyword(s): EERE tool, National Energy Modeling System, NEMS Language: English References: The National Energy Modeling System: An Overview[1] Project the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and

55

Overview of NEMS-H2, Version 1.0  

Broader source: Energy.gov [DOE]

Presentation on Overview of NEMS-H2, Version 1.0 given by Frances Wood of OnLocation during the DOE Hydrogen Transition Analysis Workshop on January 26, 2006.

56

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

57

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

58

Assessment and Suggestions to Improve the Commercial Building Module of EIA-NEMS  

E-Print Network [OSTI]

use from the base case divided by the total change in lighting electricity use from the base case. VI LIST OF FIGURES Figure 1. Impact of lighting energy reduction on heating and cooling energy use in the large office building Figure 2. Impact...-South-Central) for the Commercial Sector Demand Module of NEMS. Units are in MBtu/sq.ft./year. E = Electricity NG = Natural Gas O = Other LA This was usually done by metering consumption before and after the retrofit and then analyzing the data to account for weather and changes...

O'Neal, D. L.; Reddy, T. A.; Sucher, B.

1996-01-01T23:59:59.000Z

59

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

60

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

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


61

Optimal Intercity Transportation Services with Heterogeneous Demand and Variable Fuel Price.  

E-Print Network [OSTI]

??In this thesis we examine how fuel price variation affects the optimal mix of services in intercity transportation. Towards this end, we make two main… (more)

Ryerson, Megan Smirti

2010-01-01T23:59:59.000Z

62

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

63

Assessing the impact of recent fare policy changes on public transport demand in London  

E-Print Network [OSTI]

Public transit agencies across the world have been moving towards electronic ticketing technology and to take advantage of the greater flexibility, have made changes in fare structure. Over the last decade, Transport for ...

Jain, Nihit

2011-01-01T23:59:59.000Z

64

Stochastic Dynamic Demand Inventory Models with Explicit Transportation Costs and Decisions  

E-Print Network [OSTI]

is the policy where several small loads will be dispatched as a single, combined load. From an inventory-modeling perspec- tive, the integrated inventory-transportation problems add dispatch quantities as decision variables to the stochastic dynamic inventory...): The vendor makes the inventory replen- ishment decisions on how much to order from the outside supplier. 2. Pure Outbound Transportation Models (PO): The collection depot makes the delivery schedules of order dispatches to the buyer(s). 3. Integrated...

Zhang, Liqing

2011-07-01T23:59:59.000Z

65

Appendix E: Other NEMS-MP results for the base case and scenarios.  

SciTech Connect (OSTI)

The NEMS-MP model generates numerous results for each run of a scenario. (This model is the integrated National Energy Modeling System [NEMS] version used for the Multi-Path Transportation Futures Study [MP].) This appendix examines additional findings beyond the primary results reported in the Multi-Path Transportation Futures Study: Vehicle Characterization and Scenario Analyses (Reference 1). These additional results are provided in order to help further illuminate some of the primary results. Specifically discussed in this appendix are: (1) Energy use results for light vehicles (LVs), including details about the underlying total vehicle miles traveled (VMT), the average vehicle fuel economy, and the volumes of the different fuels used; (2) Resource fuels and their use in the production of ethanol, hydrogen (H{sub 2}), and electricity; (3) Ethanol use in the scenarios (i.e., the ethanol consumption in E85 vs. other blends, the percent of travel by flex fuel vehicles on E85, etc.); (4) Relative availability of E85 and H2 stations; (5) Fuel prices; (6) Vehicle prices; and (7) Consumer savings. These results are discussed as follows: (1) The three scenarios (Mixed, (P)HEV & Ethanol, and H2 Success) when assuming vehicle prices developed through literature review; (2) The three scenarios with vehicle prices that incorporate the achievement of the U.S. Department of Energy (DOE) program vehicle cost goals; (3) The three scenarios with 'literature review' vehicle prices, plus vehicle subsidies; and (4) The three scenarios with 'program goals' vehicle prices, plus vehicle subsidies. The four versions or cases of each scenario are referred to as: Literature Review No Subsidies, Program Goals No Subsidies, Literature Review with Subsidies, and Program Goals with Subsidies. Two additional points must be made here. First, none of the results presented for LVs in this section include Class 2B trucks. Results for this class are included occasionally in Reference 1. They represent a small, though noticeable, segment of the 'LV plus 2B' market (e.g., a little more than 3% of today's energy use in that market). We generally do not include them in this discussion, simply because it requires additional effort to combine the NEMS-MP results for them with the results for the other LVs. (Where there is an exception, we will indicate so.) Second, where reference is made to E85, the ethanol content is actually 74%. The Energy Information Administration (EIA) assumes that, to address cold-starting issues, the percent of ethanol in E85 will vary seasonally. The EIA uses an annual average ethanol content of 74% in its forecasts. That assumption is maintained in the NEMS-MP scenario runs.

Plotkin, S. E.; Singh, M. K.; Energy Systems

2009-12-03T23:59:59.000Z

66

Composites for Aerospace and Transportation As the fuel costs and environment concerns continue to increase, so does the demand for composite  

E-Print Network [OSTI]

Composites for Aerospace and Transportation As the fuel costs and environment concerns continue to increase, so does the demand for composite materials for aerospace and transportation applications. Polymer composites are inherited lighter than their metallic counterparts resulting in significant weight reduction

Li, Mo

67

A sensitivity analysis of the treatment of wind energy in the AEO99 version of NEMS  

E-Print Network [OSTI]

other assumptions for wind power to determine which onesused in NEMS regarding wind power to determine their impact

Osborn, Julie G.; Wood, Frances; Richey, Cooper; Sanders, Sandy; Short, Walter; Koomey, Jonathan

2001-01-01T23:59:59.000Z

68

All-nanophotonic NEMS biosensor on a chip  

E-Print Network [OSTI]

Integrated chemical and biological sensors give advantages in cost, size and weight reduction and open new prospects for parallel monitoring and analysis. Biosensors based on nanoelectromechanical systems (NEMS) are the most attractive candidates for the integrated platform. However, actuation and transduction techniques (e.g. electrostatic, magnetomotive, thermal or piezoelectric) limit their operation to laboratory conditions. All-optical approach gives the possibility to overcome this problem, nevertheless, the existing schemes are either fundamentally macroscopic or excessively complicated and expensive in mass production. Here we propose a novel scheme of extremely compact NEMS biosensor monolithically integrated on a chip with all-nanophotonic transduction and actuation. It consists of the photonic waveguide and the nanobeam cantilever placed above the waveguide, both fabricated in the same CMOS-compatible process. Being in the near field of the strongly confined photonic mode, cantilever is efficiently...

Fedyanin, Dmitry Yu

2014-01-01T23:59:59.000Z

69

Toward Novel Hybrid Biomass, Coal, and Natural Gas Processes for Satisfying Current Transportation Fuel Demands, 1: Process Alternatives, Gasification Modeling, Process Simulation, and Economic Analysis  

Science Journals Connector (OSTI)

Toward Novel Hybrid Biomass, Coal, and Natural Gas Processes for Satisfying Current Transportation Fuel Demands, 1: Process Alternatives, Gasification Modeling, Process Simulation, and Economic Analysis ... This paper, which is the first part of a series of papers, introduces a hybrid coal, biomass, and natural gas to liquids (CBGTL) process that can produce transportation fuels in ratios consistent with current U.S. transportation fuel demands. ... Steady-state process simulation results based on Aspen Plus are presented for the seven process alternatives with a detailed economic analysis performed using the Aspen Process Economic Analyzer and unit cost functions obtained from literature. ...

Richard C. Baliban; Josephine A. Elia; Christodoulos A. Floudas

2010-07-19T23:59:59.000Z

70

Road Transport Elasticity: How Fuel Price Changes can Affect Traffic Demand on a Toll Motorway  

Science Journals Connector (OSTI)

Abstract The crisis beginning in late 2008 in Greece, and still in progress, led the Greek Government to undertake a particularly harsh program under the joint auspices of the International Monetary Fund (IMF), the European Union and the European Central Bank, aimed at restoring the primary budget surplus. The implementation of such a financial program has dramatically increased fuel taxes - about 82% for unleaded and 31% for diesel – also producing a serious impact on road traffic demand. Starting from the above framework, this paper describes the main outcomes of a study aimed at identifying, assessing and forecasting the effects of fuel prices and tax changes on traffic flows along a 365 km toll motorway corridor project connecting Athens to Tsakona, in the South-West of the Peloponnese.

Antonio Musso; Cristiana Piccioni; Michele Tozzi; Gilles Godard; Alexandre Lapeyre; Kostas Papandreou

2013-01-01T23:59:59.000Z

71

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

72

The state-of-the-art in air transportation demand and systems analysis : a report on the proceedings of a workshop sponsored by the Civil Aeronautics Board, Department of Transportation, and National Aeronautics and Space Administration (June 1975)  

E-Print Network [OSTI]

Introduction and summary: Forecasting air transportation demand has indeed become a complex and risky business in recent years, especially in view of unpredictable fuel prices, high inflation rates, a declining rate of ...

Taneja, Nawal K.

1975-01-01T23:59:59.000Z

73

Fuel-Mix, Fuel Efficiency, and Transport Demand Affect Prospects for Biofuels in Northern Europe  

Science Journals Connector (OSTI)

Consumption structure parameters describe how the four road transport processes are being consumed, such as, for example, the amount of car-sharing and private vehicle ownership per capita—and are based on country-specific trend extrapolation using data provided by national statistical agencies and other research institutions (13-17, 35). ... As Ohrogge et al. point out, although there are uncertainties in the pace of electric car development and market penetration, future strategies aimed at promoting bioelectricity instead of ethanol for substituting conventional fuels like gasoline in cars and promoting more diesel engines in heavier vehicles may be the best route to the goal of reducing petroleum consumption and CO2 emissions (69). ... In the case of Sweden, where forest operations are highly and efficiently mechanized, this stage consumes more fossil fuels than other elements of the wood supply chain (such as silviculture and logging operations). ...

Ryan M. Bright; Anders Hammer Strřmman

2010-02-17T23:59:59.000Z

74

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

75

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...

76

Nano-Electro-Mechanical (NEM) Relay Devices and Technology for Ultra-Low Energy Digital Integrated Circuits  

E-Print Network [OSTI]

Technology 3.1 Introduction Nano-electro-mechanical (NEM)improvements, a scaled nano-relay technology with optimizedNano-Electro-Mechanical (NEM) Relay Devices and Technology

Nathanael, Rhesa

2012-01-01T23:59:59.000Z

77

The National Energy Modeling System: An Overview 1998 - Overview of NEMS  

Gasoline and Diesel Fuel Update (EIA)

OVERVIEW OF NEMS OVERVIEW OF NEMS blueball.gif (205 bytes) Major Assumptions blueball.gif (205 bytes) NEMS Modular Structure blueball.gif (205 bytes) Integrating Module NEMS represents domestic energy markets by explicitly representing the economic decisionmaking involved in the production, conversion, and consumption of energy products. For example, the penetration of a new or advanced technology for electricity generation is projected only if the technology is deemed to be economic when considering the cost-minimizing mix of fuels over the life of the equipment. Since energy costs and availability and energy- consuming characteristics can vary widely across regions, considerable regional detail is included. Other details of production and consumption categories are represented to

78

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...

79

The National Energy Modeling System: An Overview 2000 - Transportation  

Gasoline and Diesel Fuel Update (EIA)

transportation demand module (TRAN) forecasts the consumption of transportation sector fuels by transportation mode, including the use of renewables and alternative fuels, subject to delivered prices of energy fuels and macroeconomic variables, including disposable personal income, gross domestic product, level of imports and exports, industrial output, new car and light truck sales, and population. The structure of the module is shown in Figure 8. transportation demand module (TRAN) forecasts the consumption of transportation sector fuels by transportation mode, including the use of renewables and alternative fuels, subject to delivered prices of energy fuels and macroeconomic variables, including disposable personal income, gross domestic product, level of imports and exports, industrial output, new car and light truck sales, and population. The structure of the module is shown in Figure 8. Figure 8. Transportation Demand Module Structure NEMS projections of future fuel prices influence the fuel efficiency, vehicle-miles traveled, and alternative-fuel vehicle (AFV) market penetration for the current fleet of vehicles. Alternative-fuel shares are projected on the basis of a multinomial logit vehicle attribute model, subject to State and Federal government mandates.

80

Recycling Guide: Reduce, Reuse, Recycle Recycling Information Call 301-496-7990 or visit the NEMS Website at http://www.nems.nih.gov  

E-Print Network [OSTI]

Recycling Guide: Reduce, Reuse, Recycle Recycling Information ­ Call 301-496-7990 or visit the NEMS in COMMINGLED bin Rinse food/beverage containers before recycling No Pyrex or Styrofoam Printer and Copier Toner Cartridges in TONER CARTRIDGE bin Recycle packaging material in appropriate bin NIH charities

Baker, Chris I.

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


81

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

SciTech Connect (OSTI)

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects. The NEMS Industrial Demand Model is a dynamic accounting model, bringing together the disparate industries and uses of energy in those industries, and putting them together in an understandable and cohesive framework. The Industrial Model generates mid-term (up to the year 2015) forecasts of industrial sector energy demand as a component of the NEMS integrated forecasting system. From the NEMS system, the Industrial Model receives fuel prices, employment data, and the value of industrial output. Based on the values of these variables, the Industrial Model passes back to the NEMS system estimates of consumption by fuel types.

NONE

1997-01-01T23:59:59.000Z

82

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

83

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

84

Workshop on Opportunities for Magnetism in MEMS/NEMS, April 16-17, 2010  

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

Opportunities for Magnetism in MEMS/NEMS Opportunities for Magnetism in MEMS/NEMS Argonne National Laboratory - April 16-17, 2010 Sponsored by NSF, NIST and Argonne National Laboratory Friday, April 16 13:00 Welcome and Introduction Chair: John Moreland 13:10 Pritiraj Mohanty Boston University "Study of Spin Dynamics using Nanomechanics" 13:50 T. Mitch Wallis NIST, Boulder "Measurement of the Einstein-de Haas Effect with a Microcantilever" 14:30 Albrecht Jander Oregon State University "Application of Torques to Nanostructures using Ferromagnetic Resonance" 15:10 Coffee Break Chair: Dennis Greywall 15:30 Rassul Karabalin Caltech "Next-Generation NEMS Functionality Enable by Advances in Novel Materials"

85

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

Gasoline and Diesel Fuel Update (EIA)

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

86

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

87

Assumptions to the Annual Energy Outlook 2001 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

88

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

89

Comparison of Bottom-Up and Top-Down Forecasts: Vision Industry Energy Forecasts with ITEMS and NEMS  

E-Print Network [OSTI]

of the Department of Energy's Office of Industrial Technologies, EIA extracted energy use infonnation from the Annual Energy Outlook (AEO) - 2000 (8) for each of the seven # The Pacific Northwest National Laboratory is operated by Battelle Memorial Institute...-6, 2000 NEMS The NEMS industrial module is the official forecasting model for EIA and thus the Department of Energy. For this reason, the energy prices and output forecasts used to drive the ITEMS model were taken from EIA's AEO 2000. Understanding...

Roop, J. M.; Dahowski, R. T

90

NEM modication prevents high-anity ATP binding to the rst nucleotide binding fold of the sulphonylurea receptor, SUR1  

E-Print Network [OSTI]

NEM modi¢cation prevents high-a¤nity ATP binding to the ¢rst nucleotide binding fold, UK Received 7 July 1999; received in revised form 11 August 1999 Abstract Pancreatic LL-cell ATP WWM 8-azido- [KK-32 P]ATP or 8-azido-[QQ-32 P]ATP was inhibited by NEM with Ki of 1.8 WWM and 2.4 WWM

Tucker, Stephen J.

91

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.

92

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,

93

Transportation  

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

Transportation Transportation Transportation of Depleted Uranium Materials in Support of the Depleted Uranium Hexafluoride Conversion Program Issues associated with transport of depleted UF6 cylinders and conversion products. Conversion Plan Transportation Requirements The DOE has prepared two Environmental Impact Statements (EISs) for the proposal to build and operate depleted uranium hexafluoride (UF6) conversion facilities at its Portsmouth and Paducah gaseous diffusion plant sites, pursuant to the National Environmental Policy Act (NEPA). The proposed action calls for transporting the cylinder at ETTP to Portsmouth for conversion. The transportation of depleted UF6 cylinders and of the depleted uranium conversion products following conversion was addressed in the EISs.

94

Transportation  

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

Health Risks » Transportation Health Risks » Transportation DUF6 Health Risks line line Accidents Storage Conversion Manufacturing Disposal Transportation Transportation A discussion of health risks associated with transport of depleted UF6. Transport Regulations and Requirements In the future, it is likely that depleted uranium hexafluoride cylinders will be transported to a conversion facility. For example, it is currently anticipated that the cylinders at the ETTP Site in Oak Ridge, TN, will be transported to the Portsmouth Site, OH, for conversion. Uranium hexafluoride has been shipped safely in the United States for over 40 years by both truck and rail. Shipments of depleted UF6 would be made in accordance with all applicable transportation regulations. Shipment of depleted UF6 is regulated by the

95

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

96

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

97

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

98

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

99

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

Gasoline and Diesel Fuel Update (EIA)

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

100

Transportation Efficiency Resources  

Broader source: Energy.gov [DOE]

Transportation efficiency reduces travel demand as measured by vehicle miles traveled (VMT). While transportation efficiency policies are often implemented under local governments, national and...

Note: This page contains sample records for the topic "nems transportation demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
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101

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...

102

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

103

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

SciTech Connect (OSTI)

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

NONE

1998-01-01T23:59:59.000Z

104

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.

105

Transportation  

Science Journals Connector (OSTI)

The romantic rides in Sandburg’s “eagle-car” changed society. On the one hand, motor vehicle transportation is an integral thread of society’s fabric. On the other hand, excess mobility fractures old neighborh...

David Hafemeister

2014-01-01T23:59:59.000Z

106

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. . . . . . . . . . . . .

107

http://tti.tamu.edu Multi-modal Transportation > Highway Transportation > Trucking > Railroad transportation > Public transit > Rural transportation > Rural transit > Freight  

E-Print Network [OSTI]

http://tti.tamu.edu Multi-modal Transportation > Highway Transportation > Trucking > Railroad transportation > Public transit > Rural transportation > Rural transit > Freight pipeline transportation >>> Transportation operat > Freight traffic > Commodities > Travel time > Travel demand > http

108

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

109

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

110

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.

111

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.

112

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.

113

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

114

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.

115

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

116

Transportation  

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

Due to limited parking, all visitors are strongly encouraged to: Due to limited parking, all visitors are strongly encouraged to: 1) car-pool, 2) take the Lab's special conference shuttle service, or 3) take the regular off-site shuttle. If you choose to use the regular off-site shuttle bus, you will need an authorized bus pass, which can be obtained by contacting Eric Essman in advance. Transportation & Visitor Information Location and Directions to the Lab: Lawrence Berkeley National Laboratory is located in Berkeley, on the hillside directly above the campus of University of California at Berkeley. The address is One Cyclotron Road, Berkeley, California 94720. For comprehensive directions to the lab, please refer to: http://www.lbl.gov/Workplace/Transportation.html Maps and Parking Information: On Thursday and Friday, a limited number (15) of barricaded reserved parking spaces will be available for NON-LBNL Staff SNAP Collaboration Meeting participants in parking lot K1, in front of building 54 (cafeteria). On Saturday, plenty of parking spaces will be available everywhere, as it is a non-work day.

117

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,

118

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

119

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

120

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

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


121

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...

122

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

123

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

124

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...

125

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

126

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

127

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

128

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.

129

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

130

Employing demand response in energy procurement plans of electricity retailers  

Science Journals Connector (OSTI)

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

Nadali Mahmoudi; Mehdi Eghbal; Tapan K. Saha

2014-01-01T23:59:59.000Z

131

Assumptions to the Annual Energy Outlook 2000 - Electricity Market Demand  

Gasoline and Diesel Fuel Update (EIA)

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

132

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.

133

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

134

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

135

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

136

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

137

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

138

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

139

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

140

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

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


141

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

142

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

143

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

144

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

145

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

146

14 - Graphene nanoelectromechanics (NEMS)  

Science Journals Connector (OSTI)

Abstract: The use of graphene in the development of nanoscale mechanical structures is reviewed. The recent development of graphene resonators and techniques used to fabricate and characterise them is described. Some applications in sensor technology are highlighted.

Z. Moktadir

2014-01-01T23:59:59.000Z

147

Warm Winters Held Heating Oil Demand Down While Diesel Grew  

Gasoline and Diesel Fuel Update (EIA)

8 8 Notes: To understand the inventory situation, we must look the balance between demand and supply that drives inventories up or down. First consider demand. Most of the remaining charts deal with total distillate demand. Total distillate demand includes both diesel and heating oil. These are similar products physically, and prior to the low sulfur requirements for on-road diesel fuel, were used interchangeably. But even today, low sulfur diesel can be used in the heating oil market, but low sulfur requirements keep heating oil from being used in the on-road transportation sector. The seasonal increases and decreases in stocks stem from the seasonal demand in heating oil shown as the bottom red line. Heating oil demand increases by more than 50 percent from its low point to its high

148

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

149

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

150

Impact of Competition on Quality of Service in Demand Responsive Transit  

E-Print Network [OSTI]

Impact of Competition on Quality of Service in Demand Responsive Transit Ferdi Grootenboers1@inrets.fr Abstract. Demand responsive transportation has the potential to pro- vide efficient public door-company, quality of service, auction 1 Introduction Demand-Responsive Transit (DRT) services are a form

de Weerdt, Mathijs

151

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

152

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

153

Demand Charges | Open Energy Information  

Open Energy Info (EERE)

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

154

A Summary Report Keeping pace with changing global markets, meeting world demand for a host  

E-Print Network [OSTI]

and Manitoba): cor- ridors, demand, energy, information, and people. Corridors and the big picture StewartA Summary Report Keeping pace with changing global markets, meeting world demand for a host, transportation infrastructure, ports, railroads, biofuels and agricultural byproducts, and transportation

Minnesota, University of

155

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

156

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

157

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

158

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

159

Dualmode transportation - impact on the electric grid  

E-Print Network [OSTI]

Continual increase in transport demand and uneven road capacity results in chaotic traffic congestion, brings with it high levels of air pollution, an elevated number of accidents, and an insatiable demand for oil to satisfy the motorized vehicles...

Azcarate Lara, Francisco Javier

2009-05-15T23:59:59.000Z

160

Dualmode transportation - impact on the electric grid  

E-Print Network [OSTI]

Continual increase in transport demand and uneven road capacity results in chaotic traffic congestion, brings with it high levels of air pollution, an elevated number of accidents, and an insatiable demand for oil to satisfy the motorized vehicles...

Azcarate Lara, Francisco Javier

2008-10-10T23:59:59.000Z

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


161

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

162

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

163

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

164

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

165

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

166

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

167

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

168

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

169

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

170

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

171

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

172

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

173

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

174

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

175

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

176

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

177

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

178

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)

179

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

180

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

SciTech Connect (OSTI)

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

NONE

1995-02-01T23:59:59.000Z

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


181

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

SciTech Connect (OSTI)

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

NONE

1994-08-01T23:59:59.000Z

182

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

SciTech Connect (OSTI)

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

NONE

1995-03-01T23:59:59.000Z

183

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

184

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

185

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,...

186

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

187

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

188

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

189

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

190

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

191

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

192

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.

193

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

194

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

195

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

196

Current Photovoltaics Applications—Transport  

Science Journals Connector (OSTI)

Most transport systems demand high reliability as personal safety is often at stake. System design and overall integrity is thus the primary requirement. These factors are to be considered in detail. Users will d...

P. R. Wolfe

1981-01-01T23:59:59.000Z

197

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...

198

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

199

Scalability and Evolutionary Dynamics of Air Transportation Networks in the United States  

E-Print Network [OSTI]

With the growing demand for air transportation and the limited ability to increase capacity at key points in the air transportation system, there are concerns that, in the future, the system will not scale to meet demand. ...

Bonnefoy, Philippe

2007-09-21T23:59:59.000Z

200

Residential and Transport Energy Use in India: Past Trend and Future Outlook  

E-Print Network [OSTI]

GDP per capita Transport Future outlook Drivers of Transport Energyenergy demand per passenger-km. Figure 20. Car Ownership and GDP

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

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


201

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

202

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

203

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

204

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

205

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

206

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

207

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

208

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

209

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

210

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

211

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

212

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"

213

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

214

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

215

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

216

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

217

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

218

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

219

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...

220

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,...

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


221

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

222

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

223

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...

224

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...

225

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

226

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

227

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

228

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

229

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

230

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.

231

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

232

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

Science Journals Connector (OSTI)

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

Nadali Mahmoudi; Tapan K. Saha; Mehdi Eghbal

2015-01-01T23:59:59.000Z

233

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...

234

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

235

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

236

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

237

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

238

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

239

Knowledge base for an autonomic transport layer  

Science Journals Connector (OSTI)

The accelerated development of Internet and mobile devices has lead to new QoS-demanding distributed applications and new QoS-providing communication services, particularly at the transport level. The diversity of transport services and underlying networks ... Keywords: autonomic computing, model-driven architecture, ontology-driven architecture, transport protocols

Ernesto Exposito; Christophe Chassot; Michel Diaz

2011-06-01T23:59:59.000Z

240

Transportation | Open Energy Information  

Open Energy Info (EERE)

Transportation Transportation Jump to: navigation, search Click to return to AEO2011 page AEO2011 Data From AEO2011 report . Market Trends From 2009 to 2035, transportation sector energy consumption grows at an average annual rate of 0.6 percent (from 27.2 quadrillion Btu to 31.8 quadrillion Btu), slower than the 1.2 percent average rate from 1975 to 2009. The slower growth is a result of changing demographics, increased LDV fuel economy, and saturation of personal travel demand.[1] References [1] ↑ 1.0 1.1 AEO2011 Transportation Sector Retrieved from "http://en.openei.org/w/index.php?title=Transportation&oldid=378906" What links here Related changes Special pages Printable version Permanent link Browse properties 429 Throttled (bot load) Error 429 Throttled (bot load)

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


241

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

242

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

243

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

244

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.

245

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

246

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

247

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

248

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

249

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

250

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

251

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

252

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

253

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

254

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

255

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

256

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

257

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

258

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

259

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.

260

Flexible system development strategies for the Chuo Shinkansen Maglev Project : dealing with uncertain demand and R&D outcomes  

E-Print Network [OSTI]

As a large-scale, long-term transportation project, the Chuo Shinkansen Maglev Project in Japan includes various uncertainties. Among them, two major uncertainties are identified in this thesis: the uncertainty of demand ...

Ishii, Masaki, S.M. Massachusetts Institute of Technology

2007-01-01T23:59:59.000Z

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


261

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

262

Robust transportation network design under user equilibrium  

E-Print Network [OSTI]

We address the problem of designing a transportation network in the presence of demand uncertainty, multiple origin-destination pairs and a budget constraint for the overall construction cost, under the behavioral assumption ...

Lu, Yun

2007-01-01T23:59:59.000Z

263

LEDSGP/Transportation Toolkit/Strategies/Avoid | Open Energy Information  

Open Energy Info (EERE)

LEDSGP/Transportation Toolkit/Strategies/Avoid LEDSGP/Transportation Toolkit/Strategies/Avoid < LEDSGP‎ | Transportation Toolkit‎ | Strategies(Redirected from Transportation Toolkit/Strategies/Avoid) Jump to: navigation, search LEDSGP Logo.png Transportation Toolkit Home Tools Training Contacts Avoid, Shift, Improve Framework The avoid, shift, improve (ASI) framework enables development stakeholders to holistically design low-emission transport strategies by assessing opportunities to avoid the need for travel, shift to less carbon-intensive modes, and improve on conventional technologies, infrastructure, and policies. Avoid Trips and Reduce Travel Demand Transportation Assessment Toolkit Bikes Spain licensed cropped.jpg Avoid trips taken and reduce travel demand by integrating land use planning, transport infrastructure planning, and transport demand

264

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

265

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

266

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

267

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

268

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

269

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

270

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

271

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

272

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

273

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

274

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

275

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

276

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

277

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

278

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

279

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

280

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

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


281

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

282

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

283

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

284

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

285

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

286

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

287

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

288

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,

289

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

290

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

291

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

292

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...

293

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...

294

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...

295

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

296

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

297

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

298

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

299

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

300

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

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


301

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

302

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...

303

The National Energy Modeling System: An Overview 1998 - Transportation  

Gasoline and Diesel Fuel Update (EIA)

TRANSPORTATION DEMAND MODULE TRANSPORTATION DEMAND MODULE blueball.gif (205 bytes) Fuel Economy Submodule blueball.gif (205 bytes) Regional Sales Submodule blueball.gif (205 bytes) Alternative-Fuel Vehicle Submodule blueball.gif (205 bytes) Light-Duty Vehicle Stock Submodule blueball.gif (205 bytes) Vehicle-Miles Traveled (VMT) Submodule blueball.gif (205 bytes) Light-Duty Vehicle Commercial Fleet Submodule blueball.gif (205 bytes) Commercial Light Truck Submodule blueball.gif (205 bytes) Air Travel Demand Submodule blueball.gif (205 bytes) Aircraft Fleet Efficiency Submodule blueball.gif (205 bytes) Freight Transport Submodule blueball.gif (205 bytes) Miscellaneous Energy Use Submodule The transportation demand module (TRAN) forecasts the consumption of transportation sector fuels by transportation mode, including the use of

304

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

305

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

306

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

307

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

308

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

309

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

310

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

311

Transportation Services  

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

Transportation Services Transporting nuclear materials within the United States and throughout the world is a complicated and sometimes highly controversial effort requiring...

312

Local Transportation  

E-Print Network [OSTI]

Local Transportation. Transportation from the Airport to Hotel. There are two types of taxi companies that operate at the airport: special and regular taxis (

313

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

314

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

315

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

316

Employer Based Travel Demand Management -Devising Options to Meet Employee Travel Needs  

E-Print Network [OSTI]

Employer Based Travel Demand Management - Devising Options to Meet Employee Travel Needs Bruce for presentation at the 2002 Annual Conference of the Canadian Institute of Transportation Engineers to be held May to Meet Employee Travel Needs Bruce Hellinga1 , Charles Lee2 , James Mallett3 , JoAnn Woodhall4 ABSTRACT

Hellinga, Bruce

317

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.

318

Chamber transport  

SciTech Connect (OSTI)

Heavy ion beam transport through the containment chamber plays a crucial role in all heavy ion fusion (HIF) scenarios. Here, several parameters are used to characterize the operating space for HIF beams; transport modes are assessed in relation to evolving target/accelerator requirements; results of recent relevant experiments and simulations of HIF transport are summarized; and relevant instabilities are reviewed. All transport options still exist, including (1) vacuum ballistic transport, (2) neutralized ballistic transport, and (3) channel-like transport. Presently, the European HIF program favors vacuum ballistic transport, while the US HIF program favors neutralized ballistic transport with channel-like transport as an alternate approach. Further transport research is needed to clearly guide selection of the most attractive, integrated HIF system.

OLSON,CRAIG L.

2000-05-17T23:59:59.000Z

319

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

320

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

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


321

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

322

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

323

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

324

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

325

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.

326

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

327

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

328

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

329

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

330

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...

331

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

332

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...

333

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

334

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

335

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

336

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

337

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

338

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

339

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.

340

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

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


341

Economic implications of natural gas vehicle technology in U.S. private automobile transportation  

E-Print Network [OSTI]

Transportation represents almost 28 percent of the United States' energy demand. Approximately 95 percent of U.S. transportation utilizes petroleum, the majority of which is imported. With significant domestic conventional ...

Kragha, Oghenerume Christopher

2010-01-01T23:59:59.000Z

342

The role of private participation in enhancing the Indian transport sector  

E-Print Network [OSTI]

The Indian transport sector, one of the largest transport networks in the world, faces some serious issues. These may be identified as follows: * Unmet demand for service and infrastructure * Conflicting responsibilities ...

Sharma, Nand, 1979-

2004-01-01T23:59:59.000Z

343

A Microscopic Traffic Simulation Model for Transportation Planning in Georgios Papageorgiou, Pantelis Damianou, Andreas Pitsilides  

E-Print Network [OSTI]

A Microscopic Traffic Simulation Model for Transportation Planning in Cyprus Georgios Papageorgiou. This paper presents the microscopic simulation model development of a major traffic network of Nicosia simulation model is developed and utilized for transportation planning. 1. Introduction The demand

Pitsillides, Andreas

344

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

345

Thermal Energy Transport in Nanostructured Materials  

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

Thermal Energy Transport in Nanostructured Materials Thermal Energy Transport in Nanostructured Materials Speaker(s): Ravi Prasher Date: August 25, 2008 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Ashok Gadgil World energy demand is expected to reach ~30 TW by 2050 from the current demand of ~13 TW. This requires substantial technological innovation. Thermal energy transport and conversion play a very significant role in more than 90% of energy technologies. All four modes of thermal energy transport, conduction, convection, radiation, and phase change (e.g. evaporation/boiling) are important in various energy technologies such as vapor compression power plants, refrigeration, internal combustion engines and building heating/cooling. Similarly thermal transport play a critical role in electronics cooling as the performance and reliability of

346

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.

347

Can Automotive Battery recycling Help Meet Lithium Demand?  

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

Gaines, Jennifer B. Dunn, and Christine James Gaines, Jennifer B. Dunn, and Christine James Center for Transportation Research Argonne National Laboratory Can Automotive Battery Recycling Help Meet Lithium Demand? ACS Meeting New Orleans, LA April 7-11, 2013 The submitted manuscript has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory ("Argonne"). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly

348

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":""}]}

349

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

350

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

351

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

352

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

353

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

354

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

355

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

356

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

357

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

358

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

359

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

360

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

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


361

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

362

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

363

Intelligent demand side energy management system for autonomous polygeneration microgrids  

Science Journals Connector (OSTI)

Autonomous polygeneration microgrids is a novel approach in addressing the needs of remote areas. These needs can include power, fuel for transportation in the form of hydrogen, potable water through desalination and space heating and cooling. This approach has been investigated technically and economically and has proved viable. Further research has taken place in the supervisory management of this topology using computational intelligence techniques like fuzzy logic, which has optimized the concept minimizing the sizes of the installed components. The optimal design of the system can meet, though, only the design principles and needs. In reality experience has shown that most autonomous power systems operate out of specifications very shortly after installation or after a couple of years new needs arise and it is not possible economic wise for the people to extend it. In these cases the microgrid would struggle to cover the increased needs and in the end fail, causing blackouts. A solution to this is partial load shedding in an intelligent manner. This paper presents a multi agent system for intelligent demand side management of the polygeneration microgrid topology which also includes grey prediction algorithms for better management. This approach can also be used for designing the optimal polygeneration microgrid for a given amount of an investment. The results show that the proposed intelligent demand side management system can address its design principles successfully and guaranty the most effective operation even in conditions near and over the limits of the design specification of the autonomous polygeneration microgrid.

George Kyriakarakos; Dimitrios D. Piromalis; Anastasios I. Dounis; Konstantinos G. Arvanitis; George Papadakis

2013-01-01T23:59:59.000Z

364

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

365

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

366

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

367

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

368

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

369

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

370

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

371

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":""}]}

372

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

373

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

374

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

375

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

376

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...

377

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...

378

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

379

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...

380

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

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


381

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

382

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

383

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

384

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

385

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

386

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

387

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....

388

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...

389

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...

390

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 -...

391

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

392

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?

393

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

394

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

395

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

396

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

397

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

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

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

398

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

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

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

399

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

400

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

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


401

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

402

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

403

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

404

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

405

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

406

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

407

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

408

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

409

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

410

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.

411

WIPP Transportation  

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

Transuranic Waste Transportation Container Documents Documents related to transuranic waste containers and packages. CBFO Tribal Program Information about WIPP shipments across...

412

Transportation Security  

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

Preliminary Draft - For Review Only 1 Transportation Security Draft Annotated Bibliography Review July 2007 Preliminary Draft - For Review Only 2 Work Plan Task * TEC STG Work...

413

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

414

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

415

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

416

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

417

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

418

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

419

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

420

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.

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


421

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

422

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

423

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

424

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.

425

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

426

International Energy Outlook 1999 - Transportation Energy Use  

Gasoline and Diesel Fuel Update (EIA)

transportation.gif (5350 bytes) transportation.gif (5350 bytes) Transportation energy use is projected to constitute more than half of the worldÂ’s oil consumption in 2020. Developing nations account for more than half the expected growth in transportation energy use in the IEO99 forecast. The International Energy Outlook 1999 (IEO99) presents a more detailed analysis than in previous years of the underlying factors conditioning long-term growth prospects for worldwide transportation energy demand. A nationÂ’s transportation system is generally an excellent indicator of its level of economic development. In many countries, personal travel still means walking or bicycling, and freight movement often involves domesticated animals. High rates of growth from current levels in developing countries such as China and India still leave their populations

427

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

428

EIA - The National Energy Modeling System: An Overview 2003  

Gasoline and Diesel Fuel Update (EIA)

The National Energy Modeling System: An Overview 2003 This report provides a summary description of the NEMS which was used to generate the projections of energy production, demand, imports, and prices through the year 2025 for the Annual Energy Outlook 2003. Preface Introduction Overview of NEMS Carbon Dioxide and Methane Emissions Macroeconomic Activity Module International Energy Module Residential Demand Module Commercial Demand Module Industrial Demand Module Transportation Demand Module Electricity Market Module Renewable Fuels Module Oil and Gas Supply Module Natural Gas Transmission and Distribution Module Petroleum Market Module Coal Market Module Bibliography Download the Report NEMS: An Overview 2003 Cover. Need help, contact the National Energy Information Center at 202-586-8800.

429

Transportation Market Distortions  

E-Print Network [OSTI]

of Highways, Volpe National Transportation Systems Center (Evaluating Criticism of Transportation Costing, VictoriaFrom Here: Evaluating Transportation Diversity, Victoria

Litman, Todd

2006-01-01T23:59:59.000Z

430

Sustainable fuel for the transportation sector  

Science Journals Connector (OSTI)

...gasoline and 6% of its diesel demand by converting...conversion to liquid fuels using the FT process...total current oil consumption of 13.8 Mbbl/d by...conversion of syngas to diesel is 100% selective...liquid hydrocarbon fuel. In our proposal...the transportation engine. Therefore, for coal...

Rakesh Agrawal; Navneet R. Singh; Fabio H. Ribeiro; W. Nicholas Delgass

2007-01-01T23:59:59.000Z

431

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

432

Controlling the bullwhip with transport capacity constraints  

Science Journals Connector (OSTI)

The bullwhip effect can be costly to companies in terms of capacity-on costs and stock-out costs. This paper examines the possibilities for controlling the bullwhip effect with transport capacity management in the supply chain. The goal is to examine how inventories and service levels react to transport capacity constraints in a simulated supply chain that is prone to the bullwhip effect. By controlling the transport capacities, the companies may be able to reduce the impacts of demand amplification and inventory variations. Thus, there may be significant practical implications of the findings for logistics managers in today's volatile business environments.

Jouni Juntunen; Jari Juga

2009-01-01T23:59:59.000Z

433

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

434

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

435

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

436

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

437

Energy Policy Act transportation rate study: Interim report on coal transportation  

SciTech Connect (OSTI)

The primary purpose of this report is to examine changes in domestic coal distribution and railroad coal transportation rates since enactment of the Clean Air Act Amendments of 1990 (CAAA90). From 1988 through 1993, the demand for low-sulfur coal increased, as a the 1995 deadline for compliance with Phase 1 of CAAA90 approached. The shift toward low-sulfur coal came sooner than had been generally expected because many electric utilities switched early from high-sulfur coal to ``compliance`` (very low-sulfur) coal. They did so to accumulate emissions allowances that could be used to meet the stricter Phase 2 requirements. Thus, the demand for compliance coal increased the most. The report describes coal distribution and sulfur content, railroad coal transportation and transportation rates, and electric utility contract coal transportation trends from 1979 to 1993 including national trends, regional comparisons, distribution patterns and regional profiles. 14 figs., 76 tabs.

NONE

1995-10-01T23:59:59.000Z

438

An Assessment of Future Demands for and Benefits of Public Transit Services in Tennessee  

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

2/55 2/55 An Assessment of Future Demands for and Benefits of Public Transit Services in Tennessee March 2002 Prepared by Frank Southworth David P. Vogt T. Randall Curlee Center for Transportation Analysis Oak Ridge National Laboratory P.O. Box 2008 Oak Ridge, TN 37831 Managed By UT-Battelle, Llc For The U. S. Department Of Energy Under Contract No. DE-AC05-00OR-22725 and Arun Chatterjee Frederick J. Wegmann Civil and Environmental Engineering Department The University of Tennessee Knoxville, TN 37996-2010 Prepared for Office of Public Transportation Tennessee Department of Transportation Nashville, TN 37243 i Contents Page Executive Summary vi 1. Introduction 1.1 1.1 Study Purpose 1.1 1.2 Report Organization and Content 1.2 1.3 Glossary of Terms Used 1.3 2. Transit Benefits Analysis Process 2.1

439

LEDSGP/Transportation Toolkit/Strategies | Open Energy Information  

Open Energy Info (EERE)

source source History View New Pages Recent Changes All Special Pages Semantic Search/Querying Get Involved Help Apps Datasets Community Login | Sign Up Search Page Edit History Facebook icon Twitter icon » LEDSGP/Transportation Toolkit/Strategies < LEDSGP‎ | Transportation Toolkit(Redirected from Transportation Toolkit/Strategies) Jump to: navigation, search LEDSGP Logo.png Transportation Toolkit Home Tools Training Contacts Avoid, Shift, Improve Framework The avoid, shift, improve (ASI) framework enables development stakeholders to holistically design low emissions transport strategies by assessing opportunities to avoid the need for travel, shift to less carbon-intensive modes, and improve on conventional technologies, infrastructure, and policies. Avoid Trips and Reduce Travel Demand

440

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.

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


441

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

442

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

443

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

444

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

445

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

446

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

447

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.

448

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

449

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

450

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

451

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...

452

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

453

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

454

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

455

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'...

456

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

457

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

458

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

459

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

460

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

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


461

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

462

Demand for hybrid car in Indian metro cities  

Science Journals Connector (OSTI)

The depleting stock of fossil fuels, environmental problems, and global warming are today's major concerns. Existing studies identify that transport sector is one of the major contributors towards these problems. Constant efforts in search of alternative, less polluting fuel are being made. Hybrid car technology uses the gasoline and electric technology to reduce air pollution, and save oil. From the field study it is observed that the people with conventional thinking, constituting about one-third of respondents, show more concern for environment. The variables leading to demand for hybrid cars could be energy efficiency, concern for environment, etc. Despite being price sensitive, Indian consumers are willing to pay a decent premium for acquiring this environment friendly car. This study is undertaken with the objective of analysing the scenario of hybrid car in India, and its market potential. The study conducts a questionnaire-based consumer survey based on demographic, economic, and desirable features in a hybrid car; using logit model and factor analysis for identifying variables useful for the study.

Debabrata Das; R. Srinivasan; Raj S. Dhankar

2011-01-01T23:59:59.000Z

463

Extrapolating Environmental Benefits from IGCC in NEMS  

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

August 2008 (April August 2008 (April 2009 Revision) DOE/NETL-402/080108 Water Requirements for Existing and Emerging Thermoelectric Plant Technologies Disclaimer This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference therein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or

464

NEMS Buildings Sector Working Group Meeting  

Gasoline and Diesel Fuel Update (EIA)

20 * Photovoltaic system cost path - Updated 2010 system costs based on Tracking the Sun IV (LBNL, 2011) * No change from AEO2012 for residential, 7% lower for commercial -...

465

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

466

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

467

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

468

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

469

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

470

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

471

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

472

Optimal Power Flow Based Demand Response Offer Price Optimization  

E-Print Network [OSTI]

Optimal Power Flow Based Demand Response Offer Price Optimization Zhen Qiu 1 Introduction-time energy balance. Demand response programs are offered by the utility companies to reduce the load response cost in exchange for load reduction. A considerable amount of papers have discussed the demand

Lavaei, Javad

473

A Successful Implementation with the Smart Grid: Demand Response Resources  

E-Print Network [OSTI]

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

Gross, George

474

Optimal demand response: problem formulation and deterministic case  

E-Print Network [OSTI]

Optimal demand response: problem formulation and deterministic case Lijun Chen, Na Li, Libin Jiang load through real-time demand response and purchases balancing power on the spot market to meet, optimal demand response reduces to joint scheduling of the procurement and consumption decisions

Low, Steven H.

475

Ris-R-1565(EN) Analyses of Demand Response  

E-Print Network [OSTI]

Risø-R-1565(EN) Analyses of Demand Response in Denmark Frits Møller Andersen Stine Grenaa Jensen. Larsen, Peter Meibom, Hans Ravn, Klaus Skytte, Mikael Togeby Title: Analyses of Demand Response and security of supply, the report describes demand response from a microeconomic perspective and provides

476

Optimal Demand Response Based on Utility Maximization in Power Networks  

E-Print Network [OSTI]

Optimal Demand Response Based on Utility Maximization in Power Networks Na Li, Lijun Chen different appliances including PHEVs and batteries and propose a demand response approach based on utility. The utility company can thus use dynamic pricing to coordinate demand responses to the benefit of the overall

Low, Steven H.

477

Date: June 12, 2007 To: Pacific Northwest Demand Response Project  

E-Print Network [OSTI]

Date: June 12, 2007 To: Pacific Northwest Demand Response Project From: Rich Sedano/RAP and Chuck, 2007 meeting of the Pacific Northwest Demand Response Project, we agreed to form three Working Groups for the evaluation of cost-effectiveness of Demand Response resources. One potential outcome would be for state

478

Examining Uncertainty in Demand Response Baseline Models and  

E-Print Network [OSTI]

LBNL-5096E Examining Uncertainty in Demand Response Baseline Models and Variability in Automated of California. #12;Examining Uncertainty in Demand Response Baseline Models and Variability in Automated.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR

479

Graphical language for identification of control strategies allowing Demand Response  

E-Print Network [OSTI]

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

Paris-Sud XI, Université de

480

Occupancy Based Demand Response HVAC Control Strategy Varick L. Erickson  

E-Print Network [OSTI]

Occupancy Based Demand Response HVAC Control Strategy Varick L. Erickson University of California an efficient demand response HVAC control strategy, actual room usage must be considered. Temperature and CO2 are used for simulations but not for predictive demand response strategies. In this paper, we develop

Cerpa, Alberto E.

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


481

Demand Response Providing Ancillary A Comparison of Opportunities and  

E-Print Network [OSTI]

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

482

Opportunities and Challenges for Data Center Demand Response  

E-Print Network [OSTI]

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

Wierman, Adam

483

Nordic TSOs' Action Plans in enhancing and monitoring Demand Response  

E-Print Network [OSTI]

Nordic TSOs' Action Plans in enhancing and monitoring Demand Response Nordel Market Committee.............................................................................................. 3 2. TSOS' ROLE IN ENHANCING DEMAND RESPONSE.............................. 3 3. ACTIONS TO ENSURE improvment ­ activate the energy efficiency actors 13 5. SYSTEMATIC MONITORING OF REALISED DEMAND RESPONSE 13

484

Optimal Demand Response Capacity of Automatic Lighting Control  

E-Print Network [OSTI]

1 Optimal Demand Response Capacity of Automatic Lighting Control Seyed Ataollah Raziei and Hamed-mails: razieis1@udayton.edu and hamed@ee.ucr.edu Abstract--Demand response programs seek to ad- just the normal prior studies have extensively studied the capacity of offering demand response in buildings

Mohsenian-Rad, Hamed

485

Towards Continuous Policy-driven Demand Response in Data Centers  

E-Print Network [OSTI]

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

Shenoy, Prashant

486

Opportunities for Demand Response in California Agricultural Irrigation: A  

E-Print Network [OSTI]

LBNL-6108E Opportunities for Demand Response in California Agricultural Irrigation: A Scoping Study was sponsored in part by the Demand Response Research Center which is funded by the California .................................. 2 Best Opportunities for Demand Response and Permanent Load Shifting Programs.............. 3

487

EnerNOC Inc. Commercial & Industrial Demand Response  

E-Print Network [OSTI]

© EnerNOC Inc. Commercial & Industrial Demand Response: An Overview of the Utility/Aggregator Business Model Pacific Northwest Demand Response Project April 28, 2011 #12;22 Agenda Introduction Ener #12;77 Whos EnerNOC? Market Leader in C&I Demand Response and Industrial Energy Efficiency More than

488

Fast Automated Demand Response to Enable the Integration of Renewable  

E-Print Network [OSTI]

LBNL-5555E Fast Automated Demand Response to Enable the Integration of Renewable Resources David S The work described in this report was coordinated by the Demand Response Research Center and funded ABSTRACT This study examines how fast automated demand response (AutoDR) can help mitigate grid balancing

489

Two Market Models for Demand Response in Power Networks  

E-Print Network [OSTI]

Two Market Models for Demand Response in Power Networks Lijun Chen, Na Li, Steven H. Low and John C-- In this paper, we consider two abstract market models for designing demand response to match power supply as oligopolistic markets, and propose distributed demand response algorithms to achieve the equilibria. The models

Low, Steven H.

490

Value of Demand Response Theoretical thoughts Klaus Skytte  

E-Print Network [OSTI]

Value of Demand Response ­ Theoretical thoughts Klaus Skytte Systems Analysis Department February 7 A B C MB C' B' DR q'load CP #12;Innovative tariffs · Intelligent demand response · Energy tariffs if the consumers are price elastic. · The value of DR also depends on the fuel and supply mix · Intelligent demand

491

Opportunities, Barriers and Actions for Industrial Demand Response in  

E-Print Network [OSTI]

LBNL-1335E Opportunities, Barriers and Actions for Industrial Demand Response in California A.T. Mc of Global Energy Partners. This work described in this report was coordinated by the Demand Response Demand Response in California. PIER Industrial/Agricultural/Water EndUse Energy Efficiency Program. CEC

492

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data in California and for climate zones within those areas. The staff California Energy Demand 2008-2018 forecast

493

Demand forecasting for multiple slow-moving items with short requests history and unequal demand variance  

Science Journals Connector (OSTI)

Modeling the lead-time demand for the multiple slow-moving inventory items in the case when the available requests history is very short is a challenge for inventory management. The classical forecasting technique, which is based on the aggregation of the stock keeping units to overcome the mentioned historical data peculiarity, is known to lead to very poor performance in many cases important for industrial applications. An alternative approach to the demand forecasting for the considered problem is based on the Bayesian paradigm, when the initially developed population-averaged demand probability distribution is modified for each item using its specific requests history. This paper follows this approach and presents a new model, which relies on the beta distribution as a prior for the request probability, and allows to account for disparity in variance of demand between different stock keeping units. To estimate the model parameters, a special computationally effective technique based on the generalized method of moments is developed. Simulation results indicate the superiority of the proposed model over the known ones, while the computational burden does not increase.

Alexandre Dolgui; Maksim Pashkevich

2008-01-01T23:59:59.000Z

494

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.

495

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.

496

Retail Demand Response in Southwest Power Pool  

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

LBNL-1470E LBNL-1470E Retail Demand Response in Southwest Power Pool Ranjit Bharvirkar, Grayson Heffner and Charles Goldman Lawrence Berkeley National Laboratory Environmental Energy Technologies Division January 2009 The work described in this report was funded by the Office of Electricity Delivery and Energy Reliability, Permitting, Siting and Analysis of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY 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

497

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

498

Coordination of Energy Efficiency and Demand Response  

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

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

499

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

Science Journals Connector (OSTI)

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

P. Finn; C. Fitzpatrick; D. Connolly

2012-01-01T23:59:59.000Z

500

Math 115 Excel Group Project 3 Worksheet Price Elasticity of Demand: U.S. Demand for Gasoline  

E-Print Network [OSTI]

Math 115 Excel Group Project 3 Worksheet Price Elasticity of Demand: U.S. Demand for Gasoline 1 for Gasoline 2 4. Consider the two price-demand graphs below. The labels give the x-value. Which graph for Gasoline 3 6. Jewelry This quote is from the article "Americans Snap Up Gold Jewelry as Metal's Price Sinks

Newberger, Florence