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1

National Energy Modeling System (NEMS)  

DOE Data Explorer (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.

2

Availability of the National Energy Modeling System (NEMS) Archive.  

U.S. Energy Information Administration (EIA)

Availability of the National Energy Modeling System (NEMS) Archive. NEMS has been developed primarily for use by the modelers at Energy Information

3

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

4

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

Reports and Publications (EIA)

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

T. Crawford Honeycutt

1999-01-01T23:59:59.000Z

5

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

Reports and Publications (EIA)

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

T. C. Honeycutt

2005-05-01T23:59:59.000Z

6

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

Reports and Publications (EIA)

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

T. C. Honeycutt

2006-07-01T23:59:59.000Z

7

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

Reports and Publications (EIA)

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

T. C. Honeycutt

2009-05-20T23:59:59.000Z

8

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

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2003-12-01T23:59:59.000Z

9

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

Reports and Publications (EIA)

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

T. C. Honeycutt

2007-03-21T23:59:59.000Z

10

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

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2001-12-01T23:59:59.000Z

11

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

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2000-12-01T23:59:59.000Z

12

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

Reports and Publications (EIA)

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

T. C. Honeycutt

2008-06-01T23:59:59.000Z

13

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

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2000-01-01T23:59:59.000Z

14

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

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2004-02-01T23:59:59.000Z

15

DOE Hydrogen Analysis Repository: NEMS-H2 (National Energy Modeling...  

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

economic aspects of hydrogen production, delivery, and consumption. Keywords: Energy prices; emissions; production; imports; energy consumption; economic Purpose NEMS projects...

16

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

Reports and Publications (EIA)

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

T. Crawford Honeycutt

1998-01-01T23:59:59.000Z

17

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

E-Print Network (OSTI)

and maintenance (O&M) costs, renewable energy productionrenewable energy technologies are modeled becomes critical. The structure of NEMS makes cost

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

2001-01-01T23:59:59.000Z

18

NEMS industrial module documentation report  

SciTech Connect

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 2010) 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 output of industrial activity. Based on the values of these variables, the Industrial Model passes back to the NEMS system estimates of consumption by fuel types.

1994-01-01T23:59:59.000Z

19

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

E-Print Network (OSTI)

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

20

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.

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

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

22

Learning and cost reductions for generating technologies in the national energy modeling system (NEMS)  

SciTech Connect

This report describes how Learning-by-Doing (LBD) is implemented endogenously in the National Energy Modeling System (NEMS) for generating plants. LBD is experiential learning that correlates to a generating technology's capacity growth. The annual amount of Learning-by-Doing affects the annual overnight cost reduction. Currently, there is no straightforward way to integrate and make sense of all the diffuse information related to the endogenous learning calculation in NEMS. This paper organizes the relevant information from the NEMS documentation, source code, input files, and output files, in order to make the model's logic more accessible. The end results are shown in three ways: in a simple spreadsheet containing all the parameters related to endogenous learning; by an algorithm that traces how the parameters lead to cost reductions; and by examples showing how AEO 2004 forecasts the reduction of overnight costs for generating technologies over time.

Gumerman, Etan; Marnay, Chris

2004-01-16T23:59:59.000Z

23

NEMS integrating module documentation report  

Science Conference Proceedings (OSTI)

The National Energy Modeling System (NEMS) is a computer modeling system that produces a general equilibrium solution for energy supply and demand in the US energy markets. The model achieves a supply and demand balance in the end-use demand regions, defined as the nine Census Divisions, by solving for the prices of each energy type such that the quantities producers are willing to supply equal the quantities consumers wish to consume. The system reflects market economics, industry structure, and energy policies and regulations that influence market behavior. The NEMS Integrating Module is the central integrating component of a complex modeling system. As such, a thorough understanding of its role in the modeling process can only be achieved by placing it in the proper context with respect to the other modules. To that end, this document provides an overview of the complete NEMS model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Not Available

1993-12-14T23:59:59.000Z

24

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

DOE Green Energy (OSTI)

Each year, the U.S. Department of Energy's Energy Information Administration (EIA) publishes a forecast of the domestic energy economy in the Annual Energy Outlook (AEO). During the forecast period of the AEO (currently through 2020), renewable energy technologies have typically not achieved significant growth. The contribution of renewable technologies as electric generators becomes more important, however, in scenarios analyzing greenhouse gas emissions reductions or significant technological advancements. We examined the economic assumptions about wind power used for producing forecasts with the National Energy Modeling System (NEMS) to determine their influence on the projected capacity expansion of this technology. This analysis should help illustrate to policymakers what types of issues may affect wind development, and improve the general understanding of the NEMS model itself. Figure 1 illustrates the model structure and factors relevant to wind deployment. We found that NEMS uses various cost multipliers and constraints to represent potential physical and economic limitations to growth in wind capacity, such as resource depletion, costs associated with rapid manufacturing expansion, and grid stability with high levels of capacity from intermittent resources. The model's flexibility allows the user to make alternative assumptions about the magnitude of these factors. While these assumptions have little effect on the Reference Case forecast for the 1999 edition of the AEO, they can make a dramatic difference when wind is more attractive, such as under a carbon permit trading system. With $100/ton carbon permits, the wind capacity projection for 2020 ranges from 15 GW in the unaltered model (AEO99 Reference Case) to 168 GW in the extreme case when all the multipliers and constraints examined in this study are removed. Furthermore, if modifications are made to the model allowing inter-regional transmission of electricity, wind capacity is forecast to reach 214 GW when all limitations are removed. The figures in the upper end of these ranges are not intended to be viewed as reasonable projections, but their magnitude illustrates the importance of the parameters governing the growth of wind capacity and resource availability in forecasts using NEMS. In addition, many uncertainties exist regarding these assumptions that potentially affect the growth of wind power. We suggest several areas in which to focus future research in order to better model the potential development of this resource. Because many of the assumptions related to wind in the model are also used for other renewable technologies, these suggestions could be applied to other renewable resources as well.

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

2001-01-01T23:59:59.000Z

25

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

E-Print Network (OSTI)

Comparisons are made of energy forecasts using results from the Industrial module of the National Energy Modeling System (NEMS) and an industrial economic-engineering model called the Industrial Technology and Energy Modeling System (ITEMS), a model developed for industrial energy analysis at the Pacific Northwest National Laboratory. Although the results are mixed, generally ITEMS show greater penetration of energy efficient technologies and thus lower energy use, even though the business as usual forecasts for ITEMS uses a higher discount rate than NEMS uses.

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

2000-04-01T23:59:59.000Z

26

NEMS integrating module documentation report  

Science Conference Proceedings (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

27

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

28

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

E-Print Network (OSTI)

Documentation Report: Wind Energy Submodule (WES). DOE/EIA-The Economic Value of Wind Energy at High Power System5 The Wind Energy Submodule (

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

2001-01-01T23:59:59.000Z

29

A SENSITIVITY ANALYSIS OF THE TREATMENT OF WIND ENERGY IN THE AEO99 VERSION OF NEMS  

E-Print Network (OSTI)

LBNL-44070 TP-28529 A SENSITIVITY ANALYSIS OF THE TREATMENT OF WIND ENERGY IN THE AEO99 VERSION and market penetration on the U.S. Department of Energy's Annual Energy Outlook (AEO) forecast for wind supply mix remains fairly steady, and renewable energy technologies such as wind do not achieve

30

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

E-Print Network (OSTI)

presents forecasts of energy supply, demand and pricesa reference case forecast with fossil fuel prices close toforecast for wind technologies. The AEO’s annual report of energy supply, demand, and prices

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

2001-01-01T23:59:59.000Z

31

U.S. Energy Information Administration NEMS Petroleum Market Model Documentation  

E-Print Network (OSTI)

This report was prepared by the U.S. Energy Information Administration, the independent statistical and analytical agency within

unknown authors

2012-01-01T23:59:59.000Z

32

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

E-Print Network (OSTI)

cost to further test the effects of the assumptions about wind energyEnergy Outlook 1999, December 1998. Although the cost of windcost of wind in the input file by half (before learning-by-doing and other factors are assessed) is tested, wind energy

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

2001-01-01T23:59:59.000Z

33

Appendix C: Map of NEMS Electricity Market Module Regions  

Annual Energy Outlook 2012 (EIA)

U.S. Energy Information Administration | Analysis of Impacts of a Clean Energy Standard as requested by Chairman Bingaman Appendix C: Map of NEMS Electricity Market Module Regions...

34

Appendix C. Map of NEMS Electricity Market Module Regions  

Gasoline and Diesel Fuel Update (EIA)

U.S. Energy Information Administration | Analysis of Impacts of a Clean Energy Standard as requested by Chairman Hall Appendix C. Map of NEMS Electricity Market Module Regions...

35

Overview of NEMS-H2, Version 1.0  

NLE Websites -- All DOE Office Websites (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

36

NEMS may be addressed to the following analysts:  

E-Print Network (OSTI)

This publication is on the WEB at: www.eia.doe.gov/oiaf/aeo/overview/index.html This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. PREFACE The National Energy Modeling System: An Overview provides a summary description of the National Energy Modeling System (NEMS), which was used to generate the forecasts of energy production, demand, imports, and prices through the year 2020 for the Annual Energy Outlook 2000 (AEO2000), (DOE/EIA-0383(2000)), released in November 1999. AEO2000 presents national forecasts of energy markets for five cases—a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The Overview presents a brief description of the methodology and scope of each of the component modules of NEMS. The model documentation reports listed in the appendix of this document

An Overview; Aeo Susan H. Holte

2000-01-01T23:59:59.000Z

37

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

38

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

E-Print Network (OSTI)

trend in the consumer market from personal computers (PCs) to mobile devices sparked a new era in computation that makes energy

Nathanael, Rhesa

2012-01-01T23:59:59.000Z

39

U.S. Energy Information Administration (EIA) - Pub  

Gasoline and Diesel Fuel Update (EIA)

NEMS - An Overview The National Energy Modeling System Component modules Annual Energy Outlook 2012 cases Appendix F: Regional Maps United States census divisions Electricity...

40

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect

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

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

2005-07-01T23:59:59.000Z

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

Investigation of residential central air conditioning load shapes in NEMS  

SciTech Connect

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

42

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect

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

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

2005-07-01T23:59:59.000Z

43

Nanotribology and nanomechanics of MEMS/NEMS and BioMEMS/BioNEMS materials and devices  

Science Conference Proceedings (OSTI)

The micro/nanoelectromechanical systems (MEMS/NEMS) need to be designed to perform expected functions typically in millisecond to picosecond range. Expected life of the devices for high speed contacts can vary from few hundred thousand to many billions ... Keywords: MEMS, NEMS, Nanomaterials characterization, Nanomechanics, Nanotechnology

Bharat Bhushan

2007-03-01T23:59:59.000Z

44

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.

45

Building Component Library | Open Energy Information  

Open Energy Info (EERE)

Building Component Library Building Component Library Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Building Component Library Agency/Company /Organization: NREL Sector: Energy Focus Area: Buildings Phase: Create a Vision, Evaluate Options, Develop Goals, Prepare a Plan Topics: Resource assessment, Technology characterizations Resource Type: Dataset Website: bcl.nrel.gov Cost: Free OpenEI Keyword(s): buildings, nrel, data, component Language: English Building Component Library Screenshot References: Buildings Component Library[1] The Building Component Library is a repository of building data used to create building energy models. The Building Component Library is a repository of building data used to create building energy models. The data are broken down into separate

46

U.S. Energy Information Administration (EIA) - Sector  

Gasoline and Diesel Fuel Update (EIA)

NEMS overview and brief description of cases NEMS overview and brief description of cases JUMP TO: The National Energy Modeling System | Component modules | Annual Energy Outlook 2013 cases The National Energy Modeling System Projections in the Annual Energy Outlook 2013 (AEO2013) are generated using the National Energy Modeling System (NEMS) [148], developed and maintained by the Office of Energy Analysis of the U.S. Energy Information Administration (EIA). In addition to its use in developing the Annual Energy Outlook (AEO) projections, NEMS is also used to complete analytical studies for the U.S. Congress, the Executive Office of the President, other offices within the U.S. Department of Energy (DOE), and other Federal agencies. NEMS is also used by other nongovernment groups, such as the Electric Power Research Institute, Duke University, and Georgia Institute

47

U.S. Energy Information Administration (EIA) - Sector  

Gasoline and Diesel Fuel Update (EIA)

NEMS overview and brief description of cases NEMS overview and brief description of cases On This Page The National Energy Modeling... Component modules Annual Energy Outlook 2011... The National Energy Modeling System The projections in the Annual Energy Outlook 2011 (AEO2011) are generated from the National Energy Modeling System (NEMS) [1], developed and maintained by the Office of Energy Analysis (OEA), formerly known as the Office Integrated Analysis and Forecasting (OIAF), of the U.S. Energy Information Administration (EIA) [2]. In addition to its use in developing the Annual Energy Outlook (AEO) projections, NEMS is also used to complete analytical studies for the U.S. Congress, the Executive Office of the President, other offices within the U.S. Department of Energy (DOE), and other Federal agencies. NEMS is also used by other nongovernment groups,

48

U.S. Energy Information Administration (EIA) - Sector  

Gasoline and Diesel Fuel Update (EIA)

NEMS overview and brief description of cases NEMS overview and brief description of cases JUMP TO: The National Energy Modeling System | Component modules | Annual Energy Outlook 2013 cases The National Energy Modeling System Projections in the Annual Energy Outlook 2013 (AEO2013) are generated using the National Energy Modeling System (NEMS) [148], developed and maintained by the Office of Energy Analysis of the U.S. Energy Information Administration (EIA). In addition to its use in developing the Annual Energy Outlook (AEO) projections, NEMS is also used to complete analytical studies for the U.S. Congress, the Executive Office of the President, other offices within the U.S. Department of Energy (DOE), and other Federal agencies. NEMS is also used by other nongovernment groups, such as the Electric Power Research Institute, Duke University, and Georgia Institute

49

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

E-Print Network (OSTI)

The National Energy Modeling System (NEMS) is a comprehensive, computer-based, energy-economy modeling system developed and maintained by the Department of Energy's Energy Information Administration (EIA). NEMS forecasts the national production, imports, conversion, consumption, and prices of energy out to 2015, subject to macroeconomic assumptions, world energy markets, resource availability and costs, technological developments, and behavioral and technological choice criteria. NEMS has nine program modules of which the Commercial Sector Demand (CSD) module is one. Currently the CSD module uses a matrix of Energy Use Intensities (EUls) gleaned from the 1989 CBECS database to model service demand per major fuel type for eight different geographic census divisions and eleven different building types.

O'Neal, D. L.

1996-01-01T23:59:59.000Z

50

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

51

Annual Energy Outlook 2013 - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Energy Information Administration ... Uranium fuel, nuclear reactors, ... About the National Energy Modeling System (NEMS)

52

Failure testing of active solar energy components  

SciTech Connect

Component and system reliability of active solar energy systems continue to be a major concern of designers, manufacturers, installers, and consumers. Six test loops were constructed and the Solar Energy Research Institute, in Golden, Colorado, to thermally cycle active solar energy system components. Drain valves, check valves, air vents, vacuum breakers, tempering valves, and polybutylene pipe were included in the testing. The test methods and results are discussed in this report. Test results show poor reliability of some of the components and limited performance from others. The results lead to a better understanding of certain failures in the field and present designers with realistic expectations for these components. Recommendations are given to improve component reliability and for further testing.

Farrington, R.B.

1984-07-01T23:59:59.000Z

53

The National Energy Modeling System: An Overview 2000 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. energy markets for the midterm period through 2020. 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). National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. energy markets for the midterm period through 2020. 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). The National Energy Modeling System: An Overview presents an overview of the structure and methodology of NEMS and each of its components. This chapter provides a description of the design and objectives of the system, followed by a chapter on the overall modeling structure and solution algorithm. The remainder of the report summarizes the methodology and scope of the component modules of NEMS. The model descriptions are intended for readers familiar with terminology from economics, operations research, and energy modeling. More detailed model documentation reports for all the NEMS modules are also available from EIA (Appendix, “Bibliography”).

54

Investigation of residential central air conditioning load shapes in NEMS  

E-Print Network (OSTI)

of Residential Central Air Conditioning Load Shapes in NEMSof Residential Central Air Conditioning Load Shapes in NEMSof Residential Central Air Conditioning Load Shapes in NEMS

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

2002-01-01T23:59:59.000Z

55

The National Energy Modeling System: An overview 1998  

Science Conference Proceedings (OSTI)

The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of US energy markets for the midterm period through 2020. 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, behavior and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. This report presents an overview of the structure and methodology of NEMS and each of its components. The first chapter provides a description of the design and objectives of the system, followed by a chapter on the overall modeling structure and solution algorithm. The remainder of the report summarizes the methodology and scope of the component modules of NEMS. The model descriptions are intended for readers familiar with terminology from economics, operations research, and energy modeling. 21 figs.

NONE

1998-02-01T23:59:59.000Z

56

Natural gas transmission and distribution model of the National Energy Modeling System  

SciTech Connect

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. From 1982 through 1993, the Intermediate Future Forecasting System (IFFS) was used by the EIA for its analyses, and the Gas Analysis Modeling System (GAMS) was used within IFFS to represent natural gas markets. Prior to 1982, the Midterm Energy Forecasting System (MEFS), also referred to as the Project Independence Evaluation System (PIES), was employed. NEMS was developed to enhance and update EIA`s modeling capability by internally incorporating models of energy markets that had previously been analyzed off-line. In addition, greater structural detail in NEMS permits the analysis of a broader range of energy issues. The time horizon of NEMS is the midterm period (i.e., through 2015). In order to represent the regional differences in energy markets, the component models of NEMS function at regional levels appropriate for the markets represented, with subsequent aggregation/disaggregation to the Census Division level for reporting purposes.

1997-02-01T23:59:59.000Z

57

EIA - The National Energy Modeling System: An Overview 2003-Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction The National Energy Modeling System: An Overview 2003 Introduction The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. energy markets for the midterm period through 2025. 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). The National Energy Modeling System: An Overview 2003 presents an overview of the structure and methodology of NEMS and each of its components. This chapter provides a description of the design and objectives of the system, followed by a chapter on the overall modeling structure and solution algorithm. The remainder of the report summarizes the methodology and scope of the component modules of NEMS. The model descriptions are intended for readers familiar with terminology from economics, operations research, and energy modeling. More detailed model documentation reports for all the NEMS modules are also available from EIA (Appendix, “Bibliography”).

58

The National Energy Modeling System: An overview  

Science Conference Proceedings (OSTI)

The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of US energy markets for the midterm period of 1990 to 2010. 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. This report presents an overview of the structure and methodology of NEMS and each of its components. The first chapter provides a description of the design and objectives of the system. The second chapter describes the modeling structure. The remainder of the report summarizes the methodology and scope of the component modules of NEMS. The model descriptions are intended for readers familiar with terminology from economics, operations research, and energy modeling. Additional background on the development of the system is provided in Appendix A of this report, which describes the EIA modeling systems that preceded NEMS. More detailed model documentation reports for all the NEMS modules are also available from EIA.

Not Available

1994-05-01T23:59:59.000Z

59

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

NLE Websites -- All DOE Office Websites (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

60

High-Voltage Insulators and Components - Energy Innovation Portal  

Vehicles and Fuels; Wind Energy; Partners (27) Visual ... Electrical component manufacturers can greatly reduce the profound difference between measured and ...

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

Incorporating uncertainty in vehicle miles traveled projections of the National Energy Modeling System.  

E-Print Network (OSTI)

??The National Energy Modeling System (NEMS) is a computational model that forecasts the production, consumption, and prices of energy in the United States. Although NEMS… (more)

Poetting, David Michael

2011-01-01T23:59:59.000Z

62

Vehicle Component Heat Dissipation Improvements - Energy ...  

Hydrogen and Fuel Cell; Hydropower, Wave and ... to cool electronics or other power components usually involve a set of thermally conductive fins ...

63

Property:Component Integration | Open Energy Information  

Open Energy Info (EERE)

Component Integration Component Integration Jump to: navigation, search This is a property of type String. The allowed values for this property are: Customer Assembled Factory Integrated Pages using the property "Component Integration" Showing 22 pages using this property. D Distributed Generation Study/10 West 66th Street Corp + Customer Assembled + Distributed Generation Study/615 kW Waukesha Packaged System + Factory Integrated + Distributed Generation Study/Aisin Seiki G60 at Hooligans Bar and Grille + Customer Assembled + Distributed Generation Study/Arrow Linen + Customer Assembled + Distributed Generation Study/Dakota Station (Minnegasco) + Customer Assembled + Distributed Generation Study/Elgin Community College + Customer Assembled + Distributed Generation Study/Emerling Farm + Factory Integrated +

64

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

DOE Green Energy (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

65

NREL's Building Component Library for Use with Energy Models  

DOE Data Explorer (OSTI)

The Building Component Library (BCL) is the U.S. Department of Energy’s comprehensive online searchable library of energy modeling building blocks and descriptive metadata. Novice users and seasoned practitioners can use the freely available and uniquely identifiable components to create energy models and cite the sources of input data, which will increase the credibility and reproducibility of their simulations. The BCL contains components which are the building blocks of an energy model. They can represent physical characteristics of the building such as roofs, walls, and windows, or can refer to related operational information such as occupancy and equipment schedules and weather information. Each component is identified through a set of attributes that are specific to its type, as well as other metadata such as provenance information and associated files. The BCL also contains energy conservation measures (ECM), referred to as measures, which describe a change to a building and its associated model. For the BCL, this description attempts to define a measure for reproducible application, either to compare it to a baseline model, to estimate potential energy savings, or to examine the effects of a particular implementation. The BCL currently contains more than 30,000 components and measures. A faceted search mechanism has been implemented on the BCL that allows users to filter through the search results using various facets. Facet categories include component and measure types, data source, and energy modeling software type. All attributes of a component or measure can also be used to filter the results.

66

Renewable: A key component of our global energy future  

DOE Green Energy (OSTI)

Inclusion of renewable energy sources in national and international energy strategies is a key component of a viable global energy future. The global energy balance is going to shift radically in the near future brought about by significant increases in population in China and India, and increases in the energy intensity of developing countries. To better understand the consequences of such global shifts in energy requirements and to develop appropriate energy strategies to respond to these shifts, we need to look at the factors driving choices among supply options by geopolitical consumers and the impact these factors can have on the future energy mix.

Hartley, D.

1995-12-31T23:59:59.000Z

67

Energy-Efficiency Labels and Standards: A Guidebook for Appliances, Equipment, and Lighting - 2nd Edition  

E-Print Network (OSTI)

Electrical Manufacturers’ Association (NEMA), 74t National Energy Modeling System (NEMS), 163 National impact analysis,

Wiel, Stephen; McMahon, James E.

2005-01-01T23:59:59.000Z

68

Renewable Portfolio Standards - Energy Efficiency Component | Department of  

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

Renewable Portfolio Standards - Energy Efficiency Component Renewable Portfolio Standards - Energy Efficiency Component Renewable Portfolio Standards - Energy Efficiency Component < Back Eligibility Investor-Owned Utility Municipal Utility Retail Supplier Program Info State Connecticut Program Type Energy Efficiency Resource Standard Provider Public Utilities Regulatory Authority Established in 1998 and subsequently revised several times, Connecticut's renewables portfolio standard (RPS) requires each electric supplier and each electric distribution company wholesale supplier to obtain at least 23% of its retail load by using renewable energy by January 1, 2020. Specific to energy efficiency, the RPS also requires each electric supplier and each electric distribution company wholesale supplier to obtain at least 4% of its retail load by using combined heat and power (CHP) systems

69

Data:720f8fd6-08e2-4501-b5e6-6f6a7c8d4a83 | Open Energy Information  

Open Energy Info (EERE)

until such time as the total rated generating capacity provided by all CGs under Net Energy Metering (NEM-S plus NEM-L) equals five percent (5%) of Bear Valley Electric Service...

70

Assumptions to the Annual Energy Outlook 2002 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20021 (AEO2002), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3 The National Energy Modeling System The projections in the AEO2002 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of

71

Assumptions to the Annual Energy Outlook 2001 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Outlook2001 Outlook2001 Supplemental Data to the AEO2001 NEMS Conference To Forecasting Home Page EIA Homepage Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20011 (AEO2001), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3 The National Energy Modeling System The projections in the AEO2001 were produced with the National Energy

72

Nanoelectromechanical (NEM) relays integrated with CMOS SRAM for improved stability and low leakage  

Science Conference Proceedings (OSTI)

We present a hybrid nanoelectromechanical (NEM)/CMOS static random access memory (SRAM) cell, in which the two pull-down transistors of a conventional CMOS six transistor (6T) SRAM cell are replaced with NEM relays. This SRAM cell utilizes the infinite ...

Soogine Chong; Kerem Akarvardar; Roozbeh Parsa; Jun-Bo Yoon; Roger T. Howe; Subhasish Mitra; H.-S. Philip Wong

2009-11-01T23:59:59.000Z

73

Model documentation Renewable Fuels Module of the National Energy Modeling System  

DOE Green Energy (OSTI)

This report documents the objectives, analaytical approach and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1996 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described.

NONE

1996-01-01T23:59:59.000Z

74

Annual Energy Outlook 96 Assumptions  

Gasoline and Diesel Fuel Update (EIA)

for for the Annual Energy Outlook 1996 January 1996 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 Introduction This paper presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 1996 (AEO96). In this context, assumptions include general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports listed in the Appendix. 1 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview. The National Energy Modeling System The projections

75

Boron injection/dilution capabilities in TRACB/NEM coupled code  

SciTech Connect

The coupled code TRAC-BF1/NEM is a thermal-hydraulic-neutronic code which allows transient simulations considering neutronic 3D and thermal-hydraulic process in multiple channels with one-dimensional geometry. TRAC-BF1 and NEM can be executed either in stand-alone mode, i.e. without coupling, as well as coupled. In stand-alone calculations NEM code is used without coupling and the thermal-hydraulic conditions (fuel temperature, moderator density and boron concentration) and xenon concentration for each node are taken from the SIMULATE3 output files. The NEM's source code has been modified to be able to read these conditions from external files when it is executed without being coupled. The coupling between TRAC-BF1 and NEM follows an integration scheme in which the thermal-hydraulic solution of TRAC-BF1 is sent to NEM to incorporate the feedback effects through the cross sections. TRAC-BF1 solves heat conduction equations inside of the heat structures using the 3D power distribution from NEM. The coupling is carried out through the communication protocol functions of PVM (Parallel Virtual Machine). The present article presents a study which constitutes an advance in the simulation of injection, transport and mix of boron in the reactor, increasing the capabilities of TRAC-BF1/NEM coupled code. This article shows the modifications introduced in the TRAC-BF1/NEM's source code to allow a more realistic simulation of boron injection transients. The qualification of these improvements in both codes is performed simulating a steady state of a generic BWR at nominal power. The results have been compared with SIMULATE3 which is used as a reference to obtain the cross sections through the SIMTAB methodology. (authors)

Jambrina, A.; Barrachina, T.; Miro, R.; Verdu, G. [Inst. for the Industrial, Radiophysical and Environmental Safety ISIRYM, Universitat Politecnica de Valencia UPV (Spain)

2012-07-01T23:59:59.000Z

76

CNT-based MEMS/NEMS gas ionizers for portable mass spectrometry applications  

E-Print Network (OSTI)

We report the fabrication and experimental characterization of a carbon nanotube (CNT)-based MEMS/NEMS electron impact gas ionizer with an integrated extractor gate for portable mass spectrometry. The ionizer achieves ...

Velasquez-Heller, Luis Fernand

77

Integrating Module of the National Energy Modeling System ...  

U.S. Energy Information Administration (EIA)

Chapter 3 describes the NEMS global data structure, used for inter-module communication, ... technologies, representations of renewable energy technologies, ...

78

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumptions to the Annual Energy Outlook 2006 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20061 (AEO2006), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview3, which is updated once every few years. The National Energy Modeling System

79

U.S. Regional Demand Forecasts Using NEMS and GIS  

E-Print Network (OSTI)

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

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

2005-01-01T23:59:59.000Z

80

U.S. Regional Demand Forecasts Using NEMS and GIS  

E-Print Network (OSTI)

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

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

2005-01-01T23:59:59.000Z

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

DAVID Fuel Cell Components SL | Open Energy Information  

Open Energy Info (EERE)

DAVID Fuel Cell Components SL Jump to: navigation, search Name DAVID Fuel Cell Components SL Place Madrid, Spain Zip 28010 Product DAVIDFCC is devoted to the research, manufacture...

82

Estimating the environmental and economic effects of widespread residential PV adoption using GIS and NEMS  

Science Conference Proceedings (OSTI)

This paper describes a study of the national effects of widespread adoption of grid-connected residential rooftop photovoltaic (PV) systems. A Geographic Information System (GIS) model is used to estimate potential PV system adoption and PV electricity generation and the National Energy Modeling System (NEMS) is used to estimate the national effects of PV electricity generation. Adoption is assumed to occur if levelized PV system cost is less than the local average retail electricity rate at the country level. An estimate of the current {open_quotes}best{close_quotes} scenario (defined by a 6.5% real interest rate, 30-year loan life, $6{sub 1994}/W system cost, and $4{sub 1994}/month voluntary premium) results in no adoption. Several scenarios designed to stimulate PV adoption are modeled. As an example, if PV system costs are instead assumed to be $3{sub 1994}/W, rooftop systems are found to be cost effective in 16% of detached single-family households in the U.S. by 2015 (assuming full adoption of 4-kW systems), this results in 82.1 TWh of annual PV electricity generation, 170 TWh of avoided electricity transmission, distribution, and generation losses, 6 Mt/a of avoided carbon emissions, 50 kt/a of avoided NOx emissions, and 27.3 GW of avoided electricity generating capacity in place.

Marnay, C.; Richey, R.C.; Mahler, S.A. [and others

1997-10-01T23:59:59.000Z

83

Building Component Library: An Online Repository to Facilitate Building Energy Model Creation; Preprint  

SciTech Connect

This paper describes the Building Component Library (BCL), the U.S. Department of Energy's (DOE) online repository of building components that can be directly used to create energy models. This comprehensive, searchable library consists of components and measures as well as the metadata which describes them. The library is also designed to allow contributors to easily add new components, providing a continuously growing, standardized list of components for users to draw upon.

Fleming, K.; Long, N.; Swindler, A.

2012-05-01T23:59:59.000Z

84

Building Component Library: An Online Repository to Facilitate Building Energy Model Creation; Preprint  

SciTech Connect

This paper describes the Building Component Library (BCL), the U.S. Department of Energy's (DOE) online repository of building components that can be directly used to create energy models. This comprehensive, searchable library consists of components and measures as well as the metadata which describes them. The library is also designed to allow contributors to easily add new components, providing a continuously growing, standardized list of components for users to draw upon.

Fleming, K.; Long, N.; Swindler, A.

2012-05-01T23:59:59.000Z

85

Annual Energy Outlook 2013 - Energy Information Administration  

U.S. Energy Information Administration (EIA)

About the National Energy Modeling System (NEMS) Retrospective Review for AEO2011; Thank You. We welcome your comments or suggestions (optional).

86

Supplement to the annual energy outlook 1995  

SciTech Connect

This section of the Supplement to the Annual Energy Outlook 1995 present the major assumptions of the modeling system used to generate the projections in the Annual Energy Outlook 1995 (AEO95). In this context, assumptions include general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports listed in Appendix B. A synopsis of the National Energy Modeling System (NEMS), the model components, and the interrelationships of the modules is presented. The NEMS is developed and maintained by the office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projection of domestic energy-economy markets in the midterm time period and perform policy analyses requested by various government agencies and the private sector.

Not Available

1995-02-01T23:59:59.000Z

87

Model documentation, Coal Market Module of the National Energy Modeling System  

Science Conference Proceedings (OSTI)

This report documents the objectives and the conceptual and methodological approach used in the development of the National Energy Modeling System`s (NEMS) Coal Market Module (CMM) used to develop the Annual Energy Outlook 1998 (AEO98). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of CMM`s two submodules. These are the Coal Production Submodule (CPS) and the Coal Distribution Submodule (CDS). CMM provides annual forecasts of prices, production, and consumption of coal for NEMS. In general, the CDS integrates the supply inputs from the CPS to satisfy demands for coal from exogenous demand models. The international area of the CDS forecasts annual world coal trade flows from major supply to major demand regions and provides annual forecasts of US coal exports for input to NEMS. Specifically, the CDS receives minemouth prices produced by the CPS, demand and other exogenous inputs from other NEMS components, and provides delivered coal prices and quantities to the NEMS economic sectors and regions.

NONE

1998-01-01T23:59:59.000Z

88

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

NLE Websites -- All DOE Office Websites (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"

89

Miracle Wind Power Components Manufacture Co Ltd | Open Energy...  

Open Energy Info (EERE)

Login | Sign Up Search Page Edit with form History Facebook icon Twitter icon Miracle Wind Power Components Manufacture Co Ltd Jump to: navigation, search Name Miracle Wind...

90

International Energy Module  

Reports and Publications (EIA)

Summarizes the overall structure of the International Energy Model and its interface with other NEMS modules, mathematical specifications of behavioral relationships, and data sources and estimation methods.

Adrian Geagla

2012-11-05T23:59:59.000Z

91

International Energy Module  

Reports and Publications (EIA)

Summarizes the overall structure of the International Energy Model and its interface with other NEMS modules, mathematical specifications of behavioral relationships, and data sources and estimation methods.

Adrian Geagla

2013-10-22T23:59:59.000Z

92

Non-destructive component separation using infrared radiant energy  

jar 42 and the combustion control device 44 of the embodiment of FIG. 3. An assembly 60 of components is disposed in the quartz bell jar 42 of FIG. 4.

93

Modeling Distributed Electricity Generation in the NEMS Buildings Models  

Reports and Publications (EIA)

This paper presents the modeling methodology, projected market penetration, and impact of distributed generation with respect to offsetting future electricity needs and carbon dioxide emissions in the residential and commercial buildings sector in the Annual Energy Outlook 2000 (AEO2000) reference case.

Erin Boedecker

2011-01-25T23:59:59.000Z

94

Surface Energy Components and Land Characteristics of a Rice Paddy  

Science Conference Proceedings (OSTI)

Many meteorological and air-quality models require land characteristics as inputs. A field experiment was conducted to study the surface energy budget of a rice paddy in Taiwan. During the day, the energy balance ratio measured by an eddy ...

Jeng-Lin Tsai; Ben-Jei Tsuang; Po-Sheng Lu; Ming-Hwi Yao; Yuan Shen

2007-11-01T23:59:59.000Z

95

2002 EIA Models Directory - Energy Information Administration  

U.S. Energy Information Administration (EIA)

The NEMS Residential Sector Demand Module is an integrated dynamic modeling system that projects residential energy demand by ... Energy Demand and Integration ...

96

Fusion: A necessary component of US energy policy  

SciTech Connect

US energy policy must ensure that its security, its economy, or its world leadership in technology development are not compromised by failure to meet the nation's electrical energy needs. Increased concerns over the greenhouse effect from fossil-fuel combustion mean that US energy policy must consider how electrical energy dependence on oil and coal can be lessened by conservation, renewable energy sources, and advanced energy options (nuclear fission, solar energy, and thermonuclear fusion). In determining how US energy policy is to respond to these issues, it will be necessary to consider what role each of the three advanced energy options might play, and to determine how these options can complement one another. This paper reviews and comments on the principal US studies and legislation that have addressed fusion since 1980, and then suggests a research, development, and demonstration program that is consistent with the conclusions of those prior authorities and that will allow us to determine how fusion technology can fit into a US energy policy that takes a balanced, long term view of US needs. 17 refs.

Correll, D.L. Jr.

1989-01-11T23:59:59.000Z

97

EIA - The National Energy Modeling System: An Overview 2003 - Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface The National Energy Modeling System: An Overview 2003 Preface The National Energy Modeling System: An Overview 2003 provides a summary description of the National Energy Modeling System (NEMS), which was used to generate the forecasts of energy production, demand, imports, and prices through the year 2025 for the Annual Energy Outlook 2003 (AEO2003), (DOE/EIA-0383(2003)), released in January 2003. AEO2003 presents national forecasts of energy markets for five primary cases—a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The Overview presents a brief description of the methodology and scope of each of the component modules of NEMS. The model documentation reports listed in the appendix of this document provide further details.

98

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7 7 1 (AEO2007), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant to formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports. 2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview 3 , which is updated once every few years. The National Energy Modeling System The projections in the AEO2007 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the long term and

99

Assumptions to the Annual Energy Outlook - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumption to the Annual Energy Outlook Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20041 (AEO2004), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview3, which is updated once every two years. The National Energy Modeling System The projections in the AEO2004 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the midterm time period and perform policy analyses requested by decisionmakers in the U.S. Congress, the Administration, including DOE Program Offices, and other government agencies.

100

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20031 (AEO2003), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3 The National Energy Modeling System The projections in the AEO2003 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the midterm time period and perform policy analyses requested by decisionmakers and analysts in the U.S. Congress, the Department of EnergyÂ’s Office of Policy and International Affairs, other DOE offices, and other government agencies.

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


101

The National Energy Modeling System: An Ocerview 2000 - Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface The National Energy Modeling System: An Overview provides a summary description of the National Energy Modeling System (NEMS), which was used to generate the forecasts of energy production, demand, imports, and prices through the year 2020 for the Annual Energy Outlook 2000 (AEO2000), (DOE/EIA-0383(2000)), released in November 1999. AEO2000 presents national forecasts of energy markets for five cases—a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The Overview presents a brief description of the methodology and scope of each of the component modules of NEMS. The model documentation reports listed in the appendix of this document provide further details.

102

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,

103

Model documentation: Natural gas transmission and distribution model of the National Energy Modeling System. Volume 1  

SciTech Connect

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of integrated Analysis and Forecasting of the Energy information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The methodology employed allows the analysis of impacts of regional capacity constraints in the interstate natural gas pipeline network and the identification of pipeline capacity expansion requirements. There is an explicit representation of core and noncore markets for natural gas transmission and distribution services, and the key components of pipeline tariffs are represented in a pricing algorithm. Natural gas pricing and flow patterns are derived by obtaining a market equilibrium across the three main elements of the natural gas market: the supply element, the demand element, and the transmission and distribution network that links them. The NGTDM consists of four modules: the Annual Flow Module, the Capacity F-expansion Module, the Pipeline Tariff Module, and the Distributor Tariff Module. A model abstract is provided in Appendix A.

NONE

1995-02-17T23:59:59.000Z

104

Rebuilding the Coal Model in the Energy Information Administration's National Energy Modeling System  

Science Conference Proceedings (OSTI)

The Energy Information Administration uses the National Energy Modeling System (NEMS) to forecast prices and quantities in energy markets. The coal model that the Energy Information Administration first used in NEMS contributed to convergence problems ... Keywords: GOVERNMENT-ENERGY POLICIES, NATURAL RESOURCES-ENERGY, PROGRAMMING--LINEAR

Melinda Hobbs; Michael Mellish; Frederic H. Murphy; Richard Newcombe; Reginald Sanders; Peter Whitman

2001-09-01T23:59:59.000Z

105

Modeling of battery energy storage in the National Energy Modeling System  

DOE Green Energy (OSTI)

The National Energy Modeling System (NEMS) developed by the U.S. Department of Energy`s Energy Information Administration is a well-recognized model that is used to project the potential impact of new electric generation technologies. The NEMS model does not presently have the capability to model energy storage on the national grid. The scope of this study was to assess the feasibility of, and make recommendations for, the modeling of battery energy storage systems in the Electricity Market of the NEMS. Incorporating storage within the NEMS will allow the national benefits of storage technologies to be evaluated.

Swaminathan, S.; Flynn, W.T.; Sen, R.K. [Sentech, Inc., Bethesda, MD (United States)

1997-12-01T23:59:59.000Z

106

Analysis & Projections - Analysis & Projections - U.S. Energy ...  

U.S. Energy Information Administration (EIA)

Annual Reports : International Energy Outlook. Released: July 25, 2013. ... (NEMS) used to generate the projections in the Annual Energy Outlook 2012, ...

107

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

Gasoline and Diesel Fuel Update (EIA)

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

108

Integrating Module of the National Energy Modeling System (INT)  

U.S. Energy Information Administration (EIA)

The National Energy Modeling System (NEMS) represents a general equilibrium solution of the interactions between the U.S. energy markets and the economy.

109

Assumptions to the Annual Energy Outlook 1999 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

link.gif (1946 bytes) link.gif (1946 bytes) bullet1.gif (843 bytes) Assumptions to the AEO99 bullet1.gif (843 bytes) Supplemental Tables to the AEO99 bullet1.gif (843 bytes) To Forecasting Home Page bullet1.gif (843 bytes) EIA Homepage introduction.gif (4117 bytes) This paper presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 19991 (AEO99), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3

110

Thermal Systems Process and Components Laboratory (Fact Sheet), NREL (National Renewable Energy Laboratory), Energy Systems Integration Facility (ESIF)  

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

Systems Process and Systems Process and Components Laboratory may include: * CSP technology developers * Utilities * Certification laboratories * Government agencies * Universities * Other National laboratories Contact Us If you are interested in working with NREL's Thermal Systems Process and Components Laboratory, please contact: ESIF Manager Carolyn Elam Carolyn.Elam@nrel.gov 303-275-4311 Thermal Systems Process and Components Laboratory The focus of the Thermal Systems Process and Components Laboratory at NREL's Energy Systems Integration Facility (ESIF) is to research, develop, test, and evaluate new techniques for thermal energy storage systems that are relevant to utility-scale concentrating solar power plants. The laboratory holds

111

A Comparison of a Hierarchy of Models for Determining Energy Balance Components over Vegetation Canopies  

Science Conference Proceedings (OSTI)

Several methods for estimating surface energy balance components over a vegetated surface are compared. These include Penman-Monteith, Deardorff, and multilayer canopy (CANWHT) models for evaporation. Measurements taken during the 1991 DOE-...

Christoph A. Vogel; Dennis D. Baldocchi; Ashok K. Luhar; K. Shankar Rao

1995-10-01T23:59:59.000Z

112

Model documentation: Renewable Fuels Module of the National Energy Modeling System  

SciTech Connect

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it related to the production of the 1994 Annual Energy Outlook (AEO94) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves two purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. The RFM consists of six analytical submodules that represent each of the major renewable energy resources -- wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. Of these six, four are documented in the following chapters: municipal solid waste, wind, solar and biofuels. Geothermal and wood are not currently working components of NEMS. The purpose of the RFM is to define the technological and cost characteristics of renewable energy technologies, and to pass these characteristics to other NEMS modules for the determination of mid-term forecasted renewable energy demand.

Not Available

1994-04-01T23:59:59.000Z

113

Assumptions to the Annual Energy Outlook 2000 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction This paper presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20001 (AEO2000), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3 The National Energy Modeling System The projections in the AEO2000 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the midterm time period and perform policy analyses requested by decisionmakers and analysts in the U.S. Congress, the Department of EnergyÂ’s Office of Policy, other DOE offices, and other government agencies.

114

A Symmetric Free Energy Based Multi-Component Lattice Boltzmann Method  

E-Print Network (OSTI)

We present a lattice Boltzmann algorithm based on an underlying free energy that allows the simulation of the dynamics of a multicomponent system with an arbitrary number of components. The thermodynamic properties, such as the chemical potential of each component and the pressure of the overall system, are incorporated in the model. We derived a symmetrical convection diffusion equation for each component as well as the Navier Stokes equation and continuity equation for the overall system. The algorithm was verified through simulations of binary and ternary systems. The equilibrium concentrations of components of binary and ternary systems simulated with our algorithm agree well with theoretical expectations.

Qun Li; A. J. Wagner

2007-04-26T23:59:59.000Z

115

Model documentation renewable fuels module of the National Energy Modeling System  

Science Conference Proceedings (OSTI)

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1995 Annual Energy Outlook (AEO95) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. The RFM consists of six analytical submodules that represent each of the major renewable energy resources--wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. The RFM also reads in hydroelectric facility capacities and capacity factors from a data file for use by the NEMS Electricity Market Module (EMM). The purpose of the RFM is to define the technological, cost and resource size characteristics of renewable energy technologies. These characteristics are used to compute a levelized cost to be competed against other similarly derived costs from other energy sources and technologies. The competition of these energy sources over the NEMS time horizon determines the market penetration of these renewable energy technologies. The characteristics include available energy capacity, capital costs, fixed operating costs, variable operating costs, capacity factor, heat rate, construction lead time, and fuel product price.

NONE

1995-06-01T23:59:59.000Z

116

EIA - The National Energy Modeling System: An Overview 2003-Overview of  

Gasoline and Diesel Fuel Update (EIA)

Overview of NEMS Overview of NEMS The National Energy Modeling System: An Overview 2003 Overview of NEMS 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. Summary of NEMS Detail Table. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Figure 1. Census Divisions. Need help, contact the National Energy Information Center at 202-586-8800. Figure 2. National Energy Modeling System. Need help, contact the National Energy Information Center at 202-586-8800. Since energy costs and availability and energy-consuming characteristics

117

CEERECEERE Center for Energy Efficiency and Renewable Energy at University of Massachusetts COMPONENT PERFORMANCECOMPONENT PERFORMANCE  

E-Print Network (OSTI)

CEERECEERE Center for Energy Efficiency and Renewable Energy at University of Massachusetts.D.ija, Ph.D. Center for Energy Efficiency and Renewable EnergyCenter for Energy Efficiency and Renewable Center for Energy Efficiency and Renewable Energy at University of Massachusetts INTRODUCTIONINTRODUCTION

Massachusetts at Amherst, University of

118

Step 5. Determine Crucial Components of the Energy Code: Scope and  

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

5. Determine Crucial Components of the Energy Code: Scope and 5. Determine Crucial Components of the Energy Code: Scope and Applicability, Format, Adoption Date, and Effective Date Description There are four crucial components that must be considered during the adoption process: scope and applicability, format, adoption date and effective date. The scope of a code dictates which requirements will be covered by the code while the format relates to the manner in which code requirements are presented. Based on the energy goals of a state or jurisdiction, the scope and format of a code will greatly influence which code is selected for adoption and the adoption process used. For example, if a jurisdiction wishes to include only the HVAC system in its local code, a national model code may be amended to reflect these changes or a locally

119

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

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

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

120

EIA - Annual Energy Outlook (AEO) 2013 Data Tables  

U.S. Energy Information Administration (EIA)

Levelized generation costs; Model documentation; Capital cost for electricity plants; About the National Energy Modeling System (NEMS) Retrospective Review for AEO2011;

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

Distributed generation capabilities of the national energy modeling system  

E-Print Network (OSTI)

Energy Information Administration Electricity Market Module of NEMS Geographic Information System(s) 10 9 (giga)watt 10 3 (kilo)watt Market Analysis

LaCommare, Kristina Hamachi; Edwards, Jennifer L.; Marnay, Chris

2003-01-01T23:59:59.000Z

122

EIA - The National Energy Modeling System: An Overview 2003-Report...  

Annual Energy Outlook 2012 (EIA)

Report Chapters The National Energy Modeling System: An Overview 2003 Report Chapters pdf image Preface pdf image Introduction pdf image Overview of NEMS pdf image Carbon Dioxide...

123

Model-Based Sensor Placement for Component Condition Monitoring and Fault Diagnosis in Fossil Energy Systems  

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

Sensor Placement for Sensor Placement for Component Condition Monitoring and Fault Diagnosis in Fossil Energy Systems Background Fossil fuel power plants generate approximately two-thirds of the world's total electricity and are expected to continue this important role in the years ahead. Increasing global energy demands, aging and inefficient power plants, and increasingly stricter emission requirements will require high levels of performance, available capacity, efficiency, and

124

Natural Gas Transmission and Distribution Model of the National Energy Modeling System. Volume 1  

Science Conference Proceedings (OSTI)

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic design, provides detail on the methodology employed, and describes the model inputs, outputs, and key assumptions. Subsequent chapters of this report provide: an overview of NGTDM; a description of the interface between the NEMS and NGTDM; an overview of the solution methodology of the NGTDM; the solution methodology for the Annual Flow Module; the solution methodology for the Distributor Tariff Module; the solution methodology for the Capacity Expansion Module; the solution methodology for the Pipeline Tariff Module; and a description of model assumptions, inputs, and outputs.

NONE

1998-01-01T23:59:59.000Z

125

Tensor force effects and high-momentum components in the nuclear symmetry energy  

E-Print Network (OSTI)

We analyze microscopic many-body calculations of the nuclear symmetry energy and its density dependence. The calculations are performed in the framework of the Brueckner-Hartree-Fock and the Self-Consistent Green's Functions methods. Within Brueckner-Hartree-Fock, the Hellmann-Feynman theorem gives access to the kinetic energy contribution as well as the contributions of the different components of the nucleon-nucleon interaction. The tensor component gives the largest contribution to the symmetry energy. The decomposition of the symmetry energy in a kinetic part and a potential energy part provides physical insight on the correlated nature of the system, indicating that neutron matter is less correlated than symmetric nuclear matter. Within the Self-Consistent Green's Function approach, we compute the momentum distributions and we identify the effects of the high momentum components in the symmetry energy. The results are obtained for the realistic interaction Argonne V18 potential, supplemented by the Urbana IX three-body force in the Brueckner-Hartree-Fock calculations.

Arianna Carbone; Artur Polls; Constança Providęncia; Arnau Rios; Isaac Vidańa

2013-08-06T23:59:59.000Z

126

The ENERGY STAR® Plant Label: A Valuable Component of Strategic Corporate Energy Management  

E-Print Network (OSTI)

ENERGY STAR is the national symbol for energy efficiency and environmental performance recognized by roughly 70% of the American people. In September 2006, the U.S. Environmental Protection Agency (EPA) extend the brand to industrial plants by awarding the first ENERGY STAR labels to plants that had demonstrated energy performance in the top quartile of energy efficiency using a sector-specific energy benchmarking and rating tool. Currently, four plant types are eligible to earn the ENERGY STAR: motor vehicle manufacturing, cement, petroleum refining, and wet corn milling. The US EPA has observed that energy performance rating and recognition systems can help to drive the improvement of both facility and sector energy efficiency. This paper describes the rationale for developing a rating and recognition program for industrial facilities, how the EPIs are developed, and process and requirements that have been established for awarding the ENERGY STAR label.

Tunnessen, W.

2008-01-01T23:59:59.000Z

127

Building Component Library: An Online Repository to Facilitate Building Energy Model Creation: Preprint  

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

Component Library: Component Library: An Online Repository to Facilitate Building Energy Model Creation Preprint Katherine Fleming, Nicholas Long, and Alex Swindler To be presented at the ACEEE Summer Study on Energy Efficiency in Buildings Pacific Grove, California August 12-17, 2012 Conference Paper NREL/CP-5500-54710 May 2012 NOTICE The submitted manuscript has been offered by an employee of the Alliance for Sustainable Energy, LLC (Alliance), a contractor of the US Government under Contract No. DE-AC36-08GO28308. Accordingly, the US Government and Alliance retain a nonexclusive royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for US Government purposes. This report was prepared as an account of work sponsored by an agency of the United States government.

128

The National Energy Modeling System The  

Gasoline and Diesel Fuel Update (EIA)

2000 2000 (AEO2000) are generated from the National Energy Modeling System (NEMS), developed and main- tained by the Office of Integrated Analysis and Fore- casting of the Energy Information Administration (EIA). In addition to its use in the development of the AEO projections, NEMS is also used in analytical studies for the U.S. Congress and other offices within the Department of Energy. The AEO forecasts are also used by analysts and planners in other govern- ment agencies and outside organizations. The projections in NEMS are developed with the use of a market-based approach to energy analysis. For each fuel and consuming sector, NEMS balances the energy supply and demand, accounting for the eco- nomic competition between the various energy fuels and sources. The time horizon of NEMS is the mid- term period, approximately 20 years in the future. In order to represent the regional differences

129

The effect of lighting system components on lighting quality, energy use, and life-cycle cost  

SciTech Connect

A computational method was developed to examine the effect of lamp, ballast, and fixture selection on the quality and quantity of illumination, energy consumption, and life-cycle cost of lighting systems. Applying this analysis to lighting layouts using different lamp/ballast/fixture combinations suggested that combinations with higher lumen outputs reduced the uniformity of the illuminance distribution at the workplace but did not reduce visibility levels. The use of higher lumen output lamp/ballast/fixture systems and higher efficiency components tended to reduce life-cycle costs as long as the premium cost of the components was not too high.

Rubinstein, F.; Clark, T.; Siminovitch, M.; Verderber, R.

1986-07-01T23:59:59.000Z

130

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.

131

Science and technology of piezoelectric/diamond heterostructures for monolithically integrated high performance MEMS/NEMS/CMOS devices.  

SciTech Connect

This paper describes the fundamental and applied science performed to integrate piezoelectric PbZr{sub x}Ti{sub 1-x}O{sub 3} and AlN films with a novel mechanically robust ultrananocrystalline diamond layer to enable a new generation of low voltage/high-performance piezoactuated hybrid piezoelectric/diamond MEMS/NEMS devices.

Auciello, O.; Sumant, A. V.; Hiller, J.; Kabius, B.; Ma, Z.; Srinivasan, S. (Center for Nanoscale Materials); ( MSD); (Univ. of Wisconsin at Madison); (INTEL)

2008-12-01T23:59:59.000Z

132

Components Makeover Gives Concentrating Solar Power a Boost (Fact Sheet), The Spectrum of Clean Energy Innovation  

DOE Green Energy (OSTI)

Parabolic trough technology is the most mature of the various concentrating solar power (CSP) options. But scientists at the National Renewable Energy Laboratory (NREL) continue to make advances on trough systems through innovative research on various components in industrial partnerships with Acciona Solar Power, SkyFuel, Schott Solar, and others. The results are leading to improved system efficiencies and lower costs for CSP plants.

Not Available

2010-12-01T23:59:59.000Z

133

An overview of component qualification using Bayesian statistics and energy methods.  

Science Conference Proceedings (OSTI)

The below overview is designed to give the reader a limited understanding of Bayesian and Maximum Likelihood (MLE) estimation; a basic understanding of some of the mathematical tools to evaluate the quality of an estimation; an introduction to energy methods and a limited discussion of damage potential. This discussion then goes on to presented a limited presentation as to how energy methods and Bayesian estimation are used together to qualify components. Example problems with solutions have been supplied as a learning aid. Bold letters are used to represent random variables. Un-bolded letter represent deterministic values. A concluding section presents a discussion of attributes and concerns.

Dohner, Jeffrey Lynn

2011-09-01T23:59:59.000Z

134

Learning and cost reductions for generating technologies in the national energy modeling system (NEMS)  

E-Print Network (OSTI)

of the combined cycle gas turbine - an experience curveTechnologies Combustion gas turbine, gas combined- cycle,Integrated Gas CC Gas/Oil Steam Turbine Existing CT Conv CT

Gumerman, Etan; Marnay, Chris

2004-01-01T23:59:59.000Z

135

Learning and cost reductions for generating technologies in the national energy modeling system (NEMS)  

E-Print Network (OSTI)

other than distributed generation. The cost reductionsWind Solar Thermal Photovoltaic Distributed Generation-Base Distributed Generation-Peak D Vintage PLANT TYPE C

Gumerman, Etan; Marnay, Chris

2004-01-01T23:59:59.000Z

136

Learning and cost reductions for generating technologies in the national energy modeling system (NEMS)  

E-Print Network (OSTI)

generation-peak, biomass, and advanced combustion turbineCombustion gas turbine, gas combined- cycle, conventional coal Biomass,Biomass plants change from Revolutionary to Evolutionary vintage, while the Advanced Combustion

Gumerman, Etan; Marnay, Chris

2004-01-01T23:59:59.000Z

137

Learning and cost reductions for generating technologies in the national energy modeling system (NEMS)  

E-Print Network (OSTI)

Integrated Gas CC Gas/Oil Steam Turbine Existing CT Conv CTGas Comb Cycle Gas/Oil Steam Turbine Existing CombustionGas Comb Cycle Gas/Oil Steam Turbine Existing Combustion

Gumerman, Etan; Marnay, Chris

2004-01-01T23:59:59.000Z

138

Learning and cost reductions for generating technologies in the national energy modeling system (NEMS)  

E-Print Network (OSTI)

a Mun Solid Waste Hydroelectric Pumped Storage Wind Dist.Geothermal Mun Solid Waste Hydroelectric Pumped Storage WindGeothermal Mun Solid Waste Hydroelectric Pumped Storage Wind

Gumerman, Etan; Marnay, Chris

2004-01-01T23:59:59.000Z

139

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

E-Print Network (OSTI)

Combustion Turbine/Diesel Nuclear Power Pumped Storage Fuel Cells Total Non-Renewable Renewable Technologies Conventional Hydropower Geothermal Municipal Solid Waste Wood and

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

2001-01-01T23:59:59.000Z

140

Learning and cost reductions for generating technologies in the national energy modeling system (NEMS)  

E-Print Network (OSTI)

steps for an example Combined Cycle plant. 1. Identify thean advanced natural gas combined cycle plant results in the2002. The economics of the combined cycle gas turbine - an

Gumerman, Etan; Marnay, Chris

2004-01-01T23:59:59.000Z

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

Learning and cost reductions for generating technologies in the national energy modeling system (NEMS)  

E-Print Network (OSTI)

Waste Hydroelectric Pumped Storage Wind Dist. Gen. BaseSolid Waste Hydroelectric Pumped Storage Wind Solar ThermalSolid Waste Hydroelectric Pumped Storage Wind Solar Thermal

Gumerman, Etan; Marnay, Chris

2004-01-01T23:59:59.000Z

142

The effects of variable speed and drive train component efficiencies on wind turbine energy capture  

SciTech Connect

A wind turbine rotor achieves optimal aerodynamic efficiency at a single tip-speed ratio (TSR). To maintain that optimal TSR and maximize energy capture in the stochastic wind environment, it is necessary to employ variable-speed operation. Conventional constant-speed wind turbines have, in the past, been converted into variable-speed turbines by attaching power electronics to the conventional induction generator and gearbox drive train. Such turbines have shown marginal, if any, improvement in energy capture over their constant-speed counterparts. These discrepancies have been shown to be the result of drive train components that are not optimized for variable-speed operation. Traditional drive trains and power electronic converters are designed to achieve maximum efficiency at full load and speed. However, the main energy producing winds operate the turbine at light load for long periods of time. Because of this, significant losses to efficiency occur. This investigation employs a quasi-static model to demonstrate the dramatic effect that component efficiency curves can have on overall annual energy capture.

Fingersh, L.J.; Robinson, M.C.

1998-05-01T23:59:59.000Z

143

Free energy of alternating two-component polymer brushes on cylindrical templates  

E-Print Network (OSTI)

We use computer simulations to investigate the stability of a two-component polymer brush de-mixing on a curved template into phases of different morphological properties. It has been previously shown via molecular dynamics simulations that immiscible chains having different length and anchored to a cylindrical template will phase separate into striped phases of different widths oriented perpendicularly to the cylindrical axis. We calculate free energy differences for a variety of stripe widths, and extract simple relationships between the sizes of the two polymers, N_1 and N_2, and the free energy dependence on the stripe width. We explain these relationships using simple physical arguments based upon previous theoretical work on the free energy of polymer brushes.

William L. Miller; Behnaz Bozorgui; Katherine Klymko; Angelo Cacciuto

2011-11-29T23:59:59.000Z

144

An Energy Based Fatigue Life Prediction Framework for In-Service Structural Components  

Science Conference Proceedings (OSTI)

An energy based fatigue life prediction framework has been developed for calculation of remaining fatigue life of in service gas turbine materials. The purpose of the life prediction framework is to account aging effect caused by cyclic loadings on fatigue strength of gas turbine engines structural components which are usually designed for very long life. Previous studies indicate the total strain energy dissipated during a monotonic fracture process and a cyclic process is a material property that can be determined by measuring the area underneath the monotonic true stress-strain curve and the sum of the area within each hysteresis loop in the cyclic process, respectively. The energy-based fatigue life prediction framework consists of the following entities: (1) development of a testing procedure to achieve plastic energy dissipation per life cycle and (2) incorporation of an energy-based fatigue life calculation scheme to determine the remaining fatigue life of in-service gas turbine materials. The accuracy of the remaining fatigue life prediction method was verified by comparison between model approximation and experimental results of Aluminum 6061-T6. The comparison shows promising agreement, thus validating the capability of the framework to produce accurate fatigue life prediction.

H. Ozaltun; M. H.H. Shen; T. George; C. Cross

2011-06-01T23:59:59.000Z

145

Free-Energy Component Analysis of 40 ProteinDNA Complexes: A Consensus View on the Thermodynamics  

E-Print Network (OSTI)

Free-Energy Component Analysis of 40 Protein­DNA Complexes: A Consensus View on the Thermodynamics. Computation of absolute binding free energies for systems of this complexity transiting from structural a computational first atlas of the free energy contributors to binding in 40 protein­DNA complexes representing

Jayaram, Bhyravabotla

146

Data:Ba6110db-d7e6-4920-9249-1ce9f48e3199 | Open Energy Information  

Open Energy Info (EERE)

Electric Member Corp Effective date: End date if known: Rate name: SCHEDULE NEM-14 NET ENERGY METERING SCHEDULE Sector: Description: Source or reference: Source Parent:...

147

Assumptions to the Annual Energy Outlook  

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 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 20). 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. The energy-intensive industries (food and kindred products, paper and allied products, bulk chemicals, glass and glass products, hydraulic cement, blast furnace and basic steel products, and aluminum) are modeled in considerable detail. Each industry is modeled as three separate but interrelated components consisting of the Process Assembly (PA) Component, the Buildings Component (BLD), and the Boiler/Steam/Cogenera- tion (BSC) Component. The BSC Component satisfies the steam demand from the PA and BLD Components. In some industries, the PA Component produces byproducts that are consumed in the BSC Component. For the manufacturing industries, the PA Component is separated into the major production processes or end uses.

148

Polarization components in $?^{0}$ photoproduction at photon energies up to 5.6 GeV  

E-Print Network (OSTI)

We present new data for the polarization observables of the final state proton in the $^{1}H(\\vec{\\gamma},\\vec{p})\\pi^{0}$ reaction. These data can be used to test predictions based on hadron helicity conservation (HHC) and perturbative QCD (pQCD). These data have both small statistical and systematic uncertainties, and were obtained with beam energies between 1.8 and 5.6 GeV and for $\\pi^{0}$ scattering angles larger than 75$^{\\circ}$ in center-of-mass (c.m.) frame. The data extend the polarization measurements data base for neutral pion photoproduction up to $E_{\\gamma}=5.6 GeV$. The results show non-zero induced polarization above the resonance region. The polarization transfer components vary rapidly with the photon energy and $\\pi^{0}$ scattering angle in c.m. frame. This indicates that HHC does not hold and that the pQCD limit is still not reached in the energy regime of this experiment.

W. Luo; E. J. Brash; R. Gilman; M. K. Jones; M. Meziane; L. Pentchev; C. F. Perdrisat; A. J. R. Puckett; V. Punjabi; F. R. Wesselmann; A. Ahmidouch; I. Albayrak; K. A. Aniol; J. Arrington; A. Asaturyan; O. Ates; H. Baghdasaryan; F. Benmokhtar; W. Bertozzi; L. Bimbot; P. Bosted; W. Boeglin; C. Butuceanu; P. Carter; S. Chernenko; M. E. Christy; M. Commisso; J. C. Cornejo; S. Covrig; S. Danagoulian; A. Daniel; A. Davidenko; D. Day; S. Dhamija; D. Dutta; R. Ent; S. Frullani; H. Fenker; E. Frlez; F. Garibaldi; D. Gaskell; S. Gilad; Y. Goncharenko; K. Hafidi; D. Hamilton; D. W. Higinbotham; W. Hinton; T. Horn; B. Hu; J. Huang; G. M. Huber; E. Jensen; H. Kang; C. Keppel; M. Khandaker; P. King; D. Kirillov; M. Kohl; V. Kravtsov; G. Kumbartzki; Y. Li; V. Mamyan; D. J. Margaziotis; P. Markowitz; A. Marsh; Y. Matulenko; J. Maxwell; G. Mbianda; D. Meekins; Y. Melnik; J. Miller; A. Mkrtchyan; H. Mkrtchyan; B. Moffit; O. Moreno; J. Mulholland; A. Narayan; Nuruzzaman; S. Nedev; E. Piasetzky; W. Pierce; N. M. Piskunov; Y. Prok; R. D. Ransome; D. S. Razin; P. E. Reimer; J. Reinhold; O. Rondon; M. Shabestari; A. Shahinyan; K. Shestermanov; S. Sirca; I. Sitnik; L. Smykov; G. Smith; L. Solovyev; P. Solvignon; I. I. Strakovsky; R. Subedi; R. Suleiman; E. Tomasi-Gustafsson; A. Vasiliev; M. Veilleux; S. Wood; Z. Ye; Y. Zanevsky; X. Zhang; Y. Zhang; X. Zheng; L. Zhu

2011-09-21T23:59:59.000Z

149

DOE/EIA-0581(2000) The National Energy Modeling System: An Overview  

Gasoline and Diesel Fuel Update (EIA)

NEMS NEMS represents domestic energy markets by ex- plicitly representing the economic decision making involved in the production, conversion, and con- sumption of energy products. Where possible, NEMS includes explicit representation of energy technolo- gies and their characteristics. Since energy costs and availability and en- ergy-consuming characteristics can vary widely across regions, considerable regional detail is in- cluded. Other details of production and consumption cate- gories are represented to facilitate policy analysis and en- sure the validity of the results. A summary of the detail provided in NEMS is shown below. 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 Energy Information Administration/The National Energy Modeling

150

A comparison of a hierarchy of models for determining energy balance components over vegetation canopies  

SciTech Connect

Several methods for estimating surface energy balance components over a vegetated surface are compared. These include Penman-Monteith, Deardorff, and multilayer canopy (CANWHT) models for evaporation. Measurements taken during the 1991 DOE-sponsored Boardman Area Regional Flux Experiment over a well-irrigated, closed wheat canopy are used in the comparison. The relative performance of each model is then evaluated. It is found that the Penman-Monteith approach using a simple parameterization for stomatal conductance performs best for evaporation flux. The Deardorff model is found to have the best relative performance for sensible heat, while the CANWHT model gives the best results for net radiation and soil heat flux. The Priestley-Taylor model for evaporation and a resistance-analog equation for sensible heat flux are also tested. 35 refs., 9 figs., 4 tabs.

Vogel, C.A.; Baldocchi, D.D.; Luhar, A.K.; Rao, K.S. [National Oceanic and Atmospheric Administration, Oak Ridge, TN (United States)

1995-10-01T23:59:59.000Z

151

Integrating Module of the National Energy Modeling System  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Dan Skelly

2010-06-01T23:59:59.000Z

152

Free Energy Component Analysis for Drug Design: A Case Study of HIV-1 Protease-Inhibitor Binding  

E-Print Network (OSTI)

Free Energy Component Analysis for Drug Design: A Case Study of HIV-1 Protease-Inhibitor Binding of the free energies of binding of protein-ligand complexes is presented. The method formulated involves developing molecular dynamics trajectories of the enzyme, the inhibitor, and the complex, followed by a free

Jayaram, Bhyravabotla

153

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

Science Conference Proceedings (OSTI)

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

NONE

1998-01-01T23:59:59.000Z

154

Modeling of Battery Energy Storage in the National Energy Modeling System  

E-Print Network (OSTI)

The National Energy Modeling System (NEMS) developed by the U.S. Department of Energy's Energy Information Administration is a well-recognized model that is used to project the potential impact of new electric generation technologies. The NEMS model does not presently have the capability to model energy storage on the national grid. The scope of this study was to assess the feasibility of, and make recommendations for, the modeling of battery energy storage systems in the Electricity Market Module of the NEMS. Incorporating storage within the NEMS will allow the national benefits of storage technologies to be evaluated. MODELING OF BATTERY ENERGY STORAGE IN THE CONTENTS NATIONAL ENERGY MODELING SYSTEM iv CONTENTS Acknowledgments Sandia National Laboratories (SNL) would like to acknowledge and thank Dr. Christine E. Platt of the U.S. Department of Energy's Office of Utility Technologies for the support and funding of this work. Thanks are also due to Paul C. Butler and Abbas A. Akhil...

Shiva Swaminathan; William T. Flynn; Rajat K. Sen

1997-01-01T23:59:59.000Z

155

Stack Components  

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

Stack Components Stack Components Nancy L. Garland Energy Efficiency and Renewable Energy Hydrogen, Fuel Cells and Infrastructure Technologies Program Fuel Cell Team FORS 5G-086 (202) 586-5673 nancy.garland@ee.doe.gov Stack Components F u e l P r o c e s s o r Bipolar Plate Cathode + Anode - Electrolyte H+ H+ HYDROGEN OXYGEN Example shown is for acidic electrolytes Bipolar Plate e - e - O 2 O 2 O 2 e - H+ Bipolar Plate Bipolar Plate Cathode + Anode - Electrolyte H+ H+ H+ H+ HYDROGEN OXYGEN Example shown is for acidic electrolytes Bipolar Plate Bipolar Plate e - e - e - e - O 2 O 2 O 2 O 2 O 2 O 2 e - e - H+ H+ Power Stack Component Barriers $10 Other Bipolar Plates Membranes Electrodes $25 $5 $5 Fuel Cell Power Systems $45/kW BARRIERS * Stack material cost/manufacturing * Durability * Electrode performance * Thermal and water management Stack Component Targets

156

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously derived supply curves, initial price paths and international regional supply and demand levels into NEMS. These quantities are not modeled directly in NEMS because NEMS is not an international model. Previous versions of the IEM adjusted these quantities after reading in initial values. In an attempt to more closely integrate the AEO2007 with the IEO2006 and the STEO some functionality was removed from the IEM. More analyst time was devoted to analyzing price relationships between marker crude oils and refined products. A new exogenous oil supply model, Generate World Oil Balances (GWOB), was also developed to incorporate actual investment occurring in the international oil market through 2015

157

Covariability of Components of Poleward Atmospheric Energy Transports on Seasonal and Interannual Timescales  

Science Conference Proceedings (OSTI)

Vertically integrated atmospheric energy and heat budgets are presented with a focus on the zonal mean transports and divergences of dry static energy, latent energy, their sum (the moist static energy), and the total (which includes kinetic ...

Kevin E. Trenberth; David P. Stepaniak

2003-11-01T23:59:59.000Z

158

The National Energy Modeling System: An Overview 1998 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

INTRODUCTION INTRODUCTION blueball.gif (205 bytes) Purpose of NEMS blueball.gif (205 bytes) Representations of Energy Market blueball.gif (205 bytes) Technology Representation blueball.gif (205 bytes) External Availability The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. energy markets for the midterm period through 2020. 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.

159

EIA-Assumptions to the Annual Energy Outlook - International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2007 International Energy Module The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously derived supply curves, initial price paths and international regional supply and demand levels into NEMS. These quantities are not modeled directly in NEMS because NEMS is not an international model. Previous versions of the IEM adjusted these quantities after reading in initial values. In an attempt to more closely integrate the AEO2007 with the IEO2006 and the STEO some functionality was removed from the IEM. More analyst time was devoted to analyzing price relationships between marker crude oils and refined products. A new exogenous oil supply model, Generate World Oil Balances (GWOB), was also developed to incorporate actual investment occurring in the international oil market through 2015 and resource assumptions through 2030. The GWOB model provides annual country level oil production detail for eight conventional and unconventional oils.

160

Integrating Module of the National Energy Modeling System 2007, Model Documentation  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Dan Skelly

2007-05-23T23:59:59.000Z

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

Integrating Module of the National Energy Modeling System 1995, Model Documentation  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Dan Skelly

1995-05-01T23:59:59.000Z

162

Integrating Module of the National Energy Modeling System 1997, Model Documentation  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Dan Skelly

1997-05-01T23:59:59.000Z

163

Integrating Module of the National Energy Modeling System 2004, Model Documentation  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Dan Skelly

2004-02-01T23:59:59.000Z

164

Integrating Module of the National Energy Modeling System 2001, Model Documentation  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Dan Skelly

2000-12-01T23:59:59.000Z

165

Integrating Module of the National Energy Modeling System 2009, Model Documentation  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Dan Skelly

2009-05-01T23:59:59.000Z

166

Integrating Module of the National Energy Modeling System 1999, Model Documentation  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Dan Skelly

1998-12-01T23:59:59.000Z

167

Integrating Module of the National Energy Modeling System 2000, Model Documentation  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Dan Skelly

1999-12-01T23:59:59.000Z

168

Integrating Module of the National Energy Modeling System 2008, Model Documentation  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Dan Skelly

2008-08-29T23:59:59.000Z

169

Integrating Module of the National Energy Modeling System 2002, Model Documentation  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Dan Skelly

2001-12-01T23:59:59.000Z

170

Integrating Module of the National Energy Modeling System 2005, Model Documentation  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Dan Skelly

2005-05-01T23:59:59.000Z

171

Integrating Module of the National Energy Modeling System 1996 Model Documentation - NOT PUBLISHED  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

172

Integrating Module of the National Energy Modeling System 2006, Model Documentation  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Dan Skelly

2006-06-01T23:59:59.000Z

173

Integrating Module of the National Energy Modeling System 1998 Model Documentation - NOT PUBLISHED  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

John Maples

2013-09-05T23:59:59.000Z

174

Components Makeover Gives Concentrating Solar Power a Boost (Fact Sheet), The Spectrum of Clean Energy Innovation, NREL (National Renewable Energy Laboratory)  

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

Components Makeover Gives Components Makeover Gives Concentrating Solar Power a Boost Parabolic trough technology is the most mature of the various concentrating solar power (CSP) options. But scientists at the National Renewable Energy Laboratory (NREL) continue to make advances on trough systems through innovative research on various components in industrial partnerships with Acciona Solar Power, SkyFuel, Schott Solar, and others. The results are leading to improved system efficiencies and lower costs for CSP plants. Space Frames for Lower Costs To maximize the overall efficiency of the conventional glass-mirror trough system, NREL worked with Acciona Solar Power-then known as Solargenix Energy-to improve vari- ous system components. A key focus was the structural framework that holds the mirrors

175

EIA - Assumptions to the Annual Energy Outlook 2010 - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2010 Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and

176

EIA - Assumptions to the Annual Energy Outlook 2008 - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2008 Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and Distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

177

EIA - Assumptions to the Annual Energy Outlook 2009 - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2009 Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

178

Assumptions to the Annual Energy Outlook - Natural Gas Transmission and  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumption to the Annual Energy Outlook Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and Distribution Model Regions. Having problems, call our National Energy Information Center at 202-586-8800 for help. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

179

Overview of NEMS-H2, Version 1.0 Frances Wood  

E-Print Network (OSTI)

International Energy: Gas Oil Electricity Natural Gas Transmission and Distribution Petroleum Refining Coal (grid-based electricity) · Each is represented by capital cost, non-fuel O&M costs, and energy sector to be represented by methodology and data that fit it best ­ Optimization techniques used

180

Origin of the high energy proton component below the geomagnetic cutoff in near earth orbit  

E-Print Network (OSTI)

The high flux proton component observed by AMS below the geomagnetic cutoff can be well accounted for by assuming these particles to be secondaries originating from the interaction of Cosmic Ray protons with the atmosphere. Simulation results are reported

L. Derome; M. Buenerd; A. Barrau; A. Bouchet; A. Menchaca-Rocha; T. Thuillier

2000-06-12T23:59:59.000Z

Note: This page contains sample records for the topic "nems energy components" 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: Natural Gas Transmission and Distribution Model of the National Energy Modeling System; Volume 1  

SciTech Connect

The Natural Gas Transmission and Distribution Model (NGTDM) is a component of the National Energy Modeling System (NEMS) used to represent the domestic natural gas transmission and distribution system. NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the Energy Information Administration (EIA) and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. This report documents the archived version of NGTDM that was used to produce the natural gas forecasts used in support of the Annual Energy Outlook 1994, DOE/EIA-0383(94). The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic design, provides detail on the methodology employed, and describes the model inputs, outputs, and key assumptions. It is intended to fulfill the legal obligation of the EIA to provide adequate documentation in support of its models (Public Law 94-385, Section 57.b.2). This report represents Volume 1 of a two-volume set. (Volume 2 will report on model performance, detailing convergence criteria and properties, results of sensitivity testing, comparison of model outputs with the literature and/or other model results, and major unresolved issues.) Subsequent chapters of this report provide: (1) an overview of the NGTDM (Chapter 2); (2) a description of the interface between the National Energy Modeling System (NEMS) and the NGTDM (Chapter 3); (3) an overview of the solution methodology of the NGTDM (Chapter 4); (4) the solution methodology for the Annual Flow Module (Chapter 5); (5) the solution methodology for the Distributor Tariff Module (Chapter 6); (6) the solution methodology for the Capacity Expansion Module (Chapter 7); (7) the solution methodology for the Pipeline Tariff Module (Chapter 8); and (8) a description of model assumptions, inputs, and outputs (Chapter 9).

NONE

1994-02-24T23:59:59.000Z

182

National Energy Modeling System (United States) | Open Energy Information  

Open Energy Info (EERE)

National Energy Modeling System (United States) National Energy Modeling System (United States) Jump to: navigation, search Tool Summary LAUNCH TOOL Name: National Energy Modeling System (United States) Focus Area: Biomass Topics: Policy, Deployment, & Program Impact Website: www.eia.gov/oiaf/aeo/overview/ Equivalent URI: cleanenergysolutions.org/content/national-energy-modeling-system-unite Language: English Policies: "Deployment Programs,Regulations" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Technical Assistance Regulations: Utility/Electricity Service Costs The National Energy Modeling System (NEMS) is a computer-based, energy-economy modelling system of the United States through 2030. NEMS

183

Data Collection for Current U.S. Wind Energy Projects: Component Costs, Financing, Operations, and Maintenance; January 2011 - September 2011  

DOE Green Energy (OSTI)

DNV Renewables (USA) Inc. (DNV) used an Operations and Maintenance (O&M) Cost Model to evaluate ten distinct cost scenarios encountered under variations in wind turbine component failure rates. The analysis considers: (1) a Reference Scenario using the default part failure rates within the O&M Cost Model, (2) High Failure Rate Scenarios that increase the failure rates of three major components (blades, gearboxes, and generators) individually, (3) 100% Replacement Scenarios that model full replacement of these components over a 20 year operating life, and (4) Serial Failure Scenarios that model full replacement of blades, gearboxes, and generators in years 4 to 6 of the wind project. DNV selected these scenarios to represent a broad range of possible operational experiences. Also in this report, DNV summarizes the predominant financing arrangements used to develop wind energy projects over the past several years and provides summary data on various financial metrics describing those arrangements.

Martin-Tretton, M.; Reha, M.; Drunsic, M.; Keim, M.

2012-01-01T23:59:59.000Z

184

U.S. Energy Information Administration (EIA) - Sector  

Gasoline and Diesel Fuel Update (EIA)

See most recent version of AEO See most recent version of AEO Annual Energy Outlook Products - Archive Annual Energy Outlook Supplement Tables Assumptions NEM System (NEMS): An Overview NEMS Retrospective Early Release HTML PDF HTML PDF HTML PDF HTML PDF HTML PDF HTML PDF 2013 2013 2013 2013 2012 2012 2012 2012 2012 2012 2011 2011 2011 2011 2011 2011 2011 2011 2010 2010 2010 2010 2010 2010 2010 2010 2010 2009 2009 2009 2009 2009 2009 2009 2009 2009 2008 2008 2008 2008 2008 2008 2009 2008 2008 2008 2008 2007 2007 2007 2007 2007

185

Identifying Opportunities for Swedish Component and Service Suppliers within the US Wind Energy Industry.  

E-Print Network (OSTI)

??This master thesis provides an overview of the US wind energy industry through an innovation system analysis thus covering both policy development as well as… (more)

Nachemson, Louise

2010-01-01T23:59:59.000Z

186

DISCOVERY OF AN EXTRA HARD SPECTRAL COMPONENT IN THE HIGH-ENERGY AFTERGLOW EMISSION OF GRB 130427A  

SciTech Connect

The extended high-energy gamma-ray (>100 MeV) emission which occurs after prompt gamma-ray bursts (GRBs) is usually characterized by a single power-law spectrum, which has been explained as the afterglow synchrotron radiation. The afterglow inverse Compton emission has long been predicted to be able to produce a high-energy component as well, but previous observations have not clearly revealed such a signature, probably due to the small number of >10 GeV photons even for the brightest GRBs known so far. In this Letter, we report on the Fermi Large Area Telescope observations of the >100 MeV emission from the very bright and nearby GRB 130427A. We characterize the time-resolved spectra of the GeV emission from the GRB onset to the afterglow phase. By performing time-resolved spectral fits of GRB 130427A, we found strong evidence of an extra hard spectral component that exists in the extended high-energy emission of this GRB. We argue that this hard component may arise from the afterglow inverse Compton emission.

Tam, Pak-Hin Thomas [Institute of Astronomy and Department of Physics, National Tsing Hua University, Hsinchu 30013, Taiwan (China); Tang Qingwen; Liu Ruoyu; Wang Xiangyu [School of Astronomy and Space Science, Nanjing University, Nanjing 210093 (China); Hou Shujin, E-mail: phtam@phys.nthu.edu.tw, E-mail: xywang@nju.edu.cn [Department of Astronomy and Institute of Theoretical Physics and Astrophysics, Xiamen University, Xiamen, Fujian 361005 (China)

2013-07-01T23:59:59.000Z

187

Impacts of Unconventional Gas Technology in the Annual Energy Outlook 2000  

Reports and Publications (EIA)

This paper describes the methodology used in the National Energy Modeling System (NEMS) to represent unconventional gas technologies and their impacts on projections in the Annual EnergyOutlook 2000 (AEO2000).

Information Center

2000-11-01T23:59:59.000Z

188

Estimation of land surface water and energy balance flux components and closure relation using conditional sampling  

E-Print Network (OSTI)

Models of terrestrial water and energy balance include numerical treatment of heat and moisture diffusion in the soil-vegetation-atmosphere continuum. These two diffusion and exchange processes are linked only at a few ...

Farhadi, Leila

2012-01-01T23:59:59.000Z

189

Results of scoping tests for open-cycle OTEC (ocean thermal energy conversion) components operating with seawater  

DOE Green Energy (OSTI)

This report presents comprehensive documentation of the experimental research conducted on open-cycle ocean thermal energy conversion (OC-OTEC) components operating with seawater as a working fluid. The results of this research are presented in the context of previous analysis and fresh-water testing; they provide a basis for understanding and predicting with confidence the performance of all components of an OC-OTEC system except the turbine. Seawater tests have confirmed the results that were obtained in fresh-water tests and predicted by the analytical models of the components. A sound technical basis has been established for the design of larger systems in which net power will be produced for the first time from OC-OTEC technology. Design and operation of a complete OC-OTEC system that produces power will provide sufficient confidence to warrant complete transfer of OC-OTEC technology to the private sector. Each components performance is described in a separate chapter written by the principal investigator responsible for technical aspects of the specific tests. Chapters have been indexed separately for inclusion on the data base.

Zangrando, F; Bharathan, D; Green, H J; Link, H F; Parsons, B K; Parsons, J M; Pesaran, A A [Solar Energy Research Inst., Golden, CO (USA); Panchal, C B [Argonne National Lab., IL (USA)

1990-09-01T23:59:59.000Z

190

EIA-Assumptions to the Annual Energy Outlook - National Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2007 National Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and Distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

191

Fatigue analysis of WECS (Wind Energy Conversion System) components using a rainflow counting algorithm  

Science Conference Proceedings (OSTI)

A rainflow counting algorithm'' has been incorporated into the LIFE2 fatigue/fracture analysis code for wind turbines. The count algorithm, with its associated pre- and post-count algorithms, permits the code to incorporate time-series data into its analysis scheme. After a description of the algorithms used here, their use is illustrated by the examination of stress-time histories from the Sandia 34-m Test Bed vertical axis wind turbine. The results of the rainflow analysis are compared and contrasted to previously reported predictions for the service lifetime of the fatigue critical component for this turbine. 14 refs., 8 figs., 3 tabs.

Sutherland, H.J.; Schluter, L.L.

1990-01-01T23:59:59.000Z

192

SINGLE- AND TWO-COMPONENT GAMMA-RAY BURST SPECTRA IN THE FERMI GBM-LAT ENERGY RANGE  

Science Conference Proceedings (OSTI)

Most Fermi gamma-ray burst spectra appear as either a broken power law extending to GeV energies or as a broken power with a separate GeV power-law component. Here we show that such spectra can be understood in terms of magnetically dominated relativistic jets where a dissipative photosphere produces the prompt MeV emission, which is extended into the GeV range by inverse Compton scattering in the external shock, with possible contributions from a reverse shock as well. The bulk Lorentz factors required in these models are in the range of 300-600, and the MeV-GeV time delays arise naturally. In some cases an optical flash and a sub-dominant thermal component are also present.

Veres, P.; Meszaros, P., E-mail: veresp@psu.edu, E-mail: nnp@astro.psu.edu [Department of Astronomy and Astrophysics, Department of Physics, and Center for Particle Astrophysics, 525 Davey Lab., Pennsylvania State University, University Park, PA 16802 (United States)

2012-08-10T23:59:59.000Z

193

Energy Saving Melting and Revert Reduction Technology (Energy SMARRT): Manufacturing Advanced Engineered Components Using Lost Foam Casting Technology  

SciTech Connect

This project was a subtask of Energy Saving Melting and Revert Reduction Technology (�¢����Energy SMARRT�¢���) Program. Through this project, technologies, such as computer modeling, pattern quality control, casting quality control and marketing tools, were developed to advance the Lost Foam Casting process application and provide greater energy savings. These technologies have improved (1) production efficiency, (2) mechanical properties, and (3) marketability of lost foam castings. All three reduce energy consumption in the metals casting industry. This report summarizes the work done on all tasks in the period of January 1, 2004 through June 30, 2011. Current (2011) annual energy saving estimates based on commercial introduction in 2011 and a market penetration of 97% by 2020 is 5.02 trillion BTU�¢����s/year and 6.46 trillion BTU�¢����s/year with 100% market penetration by 2023. Along with these energy savings, reduction of scrap and improvement in casting yield will result in a reduction of the environmental emissions associated with the melting and pouring of the metal which will be saved as a result of this technology. The average annual estimate of CO2 reduction per year through 2020 is 0.03 Million Metric Tons of Carbon Equivalent (MM TCE).

Harry Littleton; John Griffin

2011-07-31T23:59:59.000Z

194

Covariance statistics of turbulence velocity components for wind-energy-conversion system design-homogeneous, isotropic case  

DOE Green Energy (OSTI)

When designing a wind energy converison system (WECS), it may be necessary to take into account the distribution of wind across the disc of rotation. The specific engineering applications include structural strength, fatigue, and control. This wind distribution consists of two parts, namely that associated with the mean wind profile and that associated with the turbulence velocity fluctuation field. The work reported herein is aimed at the latter, namely the distribution of turbulence velocity fluctuations across the WECS disk of rotation. A theory is developed for the two-time covariance matrix for turbulence velocity vector components for wind energy conversion system (WECS) design. The theory is developed for homogeneous and iotropic turbulance with the assumption that Taylor's hypothesis is valid. The Eulerian turbulence velocity vector field is expanded about the hub of the WECS. Formulae are developed for the turbulence velocity vector component covariance matrix following the WECS blade elements. It is shown that upon specification of the turbulence energy spectrum function and the WECS rotation rate, the two-point, two-time covariance matrix of the turbulent flow relative to the WECS bladed elements is determined. This covariance matrix is represented as the sum of nonstationary and stationary contributions. Generalized power spectral methods are used to obtain two-point, double frequency power spectral density functions for the turbulent flow following the blade elements. The Dryden turbulence model is used to demonstrate the theory. A discussion of linear system response analysis is provided to show how the double frequency turbulence spectra might be used to calculate response spectra of a WECS to turbulent flow. Finally the spectrum of the component of turbulence normal to the WECS disc of rotation, following the blade elements, is compared with experimental results.

Fichtl, G.H.

1983-09-01T23:59:59.000Z

195

Ultrahigh heat flux plasma-facing components for magnetic fusion energy  

Science Conference Proceedings (OSTI)

Sandia and Ultramet partnered to design and test refractory metal plasma-facing components and heat exchangers for advanced, high-temperature power conversion systems. These devices consisted of high-temperature helium-to-helium and lithium-to-helium heat exchangers that operate with high efficiency due to the porous foam inserts used in the gas stream, which promote turbulence and provide extended surface area for enhanced convection. Single- and multi-channel helium panels and the Li-He heat exchanger were fabricated from either pure molybdenum, TZM, or tungsten. The design was carried out through an Ultramet subcontractor. The flow path was carefully tailored to minimize the pressure drop while maximizing the heat transfer. The single- and multi-channel helium panels were tested at Sandia's PMTF using an electron beam system and the closed helium flow loop. In 2006, a single-channel tungsten tube was successfully tested to an average heat flux of 14 MW/m{sup 2} with a localized peak of 22 MW/m{sup 2} along the axial centerline at the outer radius. Under this CRADA, multiple square-channel molybdenum components were successfully tested to heat flux levels approaching 8.5 MW/m{sup 2}. The three multi-channel prototypes experienced mechanical failure due to issues related to the design of the large unsupported span of the heated faceplates in combination with prototype material and braze selection. The Li-He heat exchanger was both designed and partially tested at the PMTF for helium and lithium flow.

Youchison, D. L.

2012-03-01T23:59:59.000Z

196

PV Standards Work: Photovoltaic System and Component Certification, Test Facility Accreditation, and Solar Photovoltaic Energy Systems International Standards  

DOE Green Energy (OSTI)

This paper discusses efforts led by two companies (PowerMark Corporation and Sunset Technologies Inc.) to support both U.S. domestic and international photovoltaic (PV) system and component certification and test facility accreditation programs and the operation of the International Electrotechnical Commission (IEC) Technical Committee 82 (TC-82) Photovoltaic Energy Systems. International and national PV certification/accreditation programs are successfully facilitating entry of only the highest quality PV products into the marketplace. Standards also continue to be a cornerstone for assuring global PV product conformity assessment, reducing non-tariff trade barriers, and ultimately improving PV products while lowering cost.

Basso, T. S.; Chalmers, S.; Barikmo, H. O.

2005-11-01T23:59:59.000Z

197

Impact of Component Sizing in Plug-In Hybrid Electric Vehicles for Energy Resource and Greenhouse Emissions Reduction  

Science Conference Proceedings (OSTI)

Widespread use of alternative hybrid powertrains currently appears inevitable and many opportunities for substantial progress remain. The necessity for environmentally friendly vehicles, in conjunction with increasing concerns regarding U.S. dependency on foreign oil and climate change, has led to significant investment in enhancing the propulsion portfolio with new technologies. Recently, plug-in hybrid electric vehicles (PHEVs) have attracted considerable attention due to their potential to reduce petroleum consumption and greenhouse gas (GHG) emissions in the transportation sector. PHEVs are especially appealing for short daily commutes with excessive stop-and-go driving. However, the high costs associated with their components, and in particular, with their energy storage systems have been significant barriers to extensive market penetration of PEVs. In the research reported here, we investigated the implications of motor/generator and battery size on fuel economy and GHG emissions in a medium duty PHEV. An optimization framework is proposed and applied to two different parallel powertrain configurations, pre-transmission and post-transmission, to derive the Pareto frontier with respect to motor/generator and battery size. The optimization and modeling approach adopted here facilitates better understanding of the potential benefits from proper selection of motor/generator and battery size on fuel economy and GHG emissions. This understanding can help us identify the appropriate sizing of these components and thus reducing the PHEV cost. Addressing optimal sizing of PHEV components could aim at an extensive market penetration of PHEVs.

Malikopoulos, Andreas [ORNL

2013-01-01T23:59:59.000Z

198

Reliability and maintainability study of select solar-energy-system components in the National Solar Data Network. Final subcontract report  

Science Conference Proceedings (OSTI)

This study reports on the reliability and maintainability of select solar energy system components evaluated in 16 solar heating and cooling systems over a one-year period. The systems evaluated were instrumented sites from the National Solar Data Network (NSDN). A complete description and system schematic for each site is provided. The study period was generally between October 1981 to October 1982. The report provides quantitative R and M data (e.g., Failure Rate and Mean Time Between Failures) on pumps, motors and fans from the selected NSDN sites, along with conclusions and recommendations based on comparative data for other components. In summary, pumps, valves, and heat exchangers in solar heating and cooling (SHAC) systems appear to be very reliable and show failure rates comparable to other mechanical system applications. Control systems typically used in SHAC systems appear to be the least reliable but still fall within the range of failures exhibited by other mechanical systems. Evidence suggests that piping leaks in SHAC systems occur at three times the rate of other mechanical systems. Recommendations are provided on other areas of research necessary to determine the useful life of SHAC system components. Finally, an appendix to this report describes actual failures encountered in the 16 systems evaluated.

Kendall, P.W.; Logee, T.L.; Raymond, M.G.

1983-06-01T23:59:59.000Z

199

Large-area low-temperature ultrananocrystaline diamond (UNCD) films and integration with CMOS devices for monolithically integrated diamond MEMD/NEMS-CMOS systems.  

SciTech Connect

Because of exceptional mechanical, chemical, and tribological properties, diamond has a great potential to be used as a material for the development of high-performance MEMS and NEMS such as resonators and switches compatible with harsh environments, which involve mechanical motion and intermittent contact. Integration of such MEMS/NEMS devices with complementary metal oxide semiconductor (CMOS) microelectronics will provide a unique platform for CMOS-driven commercial MEMS/NEMS. The main hurdle to achieve diamond-CMOS integration is the relatively high substrate temperatures (600-800 C) required for depositing conventional diamond thin films, which are well above the CMOS operating thermal budget (400 C). Additionally, a materials integration strategy has to be developed to enable diamond-CMOS integration. Ultrananocrystalline diamond (UNCD), a novel material developed in thin film form at Argonne, is currently the only microwave plasma chemical vapor deposition (MPCVD) grown diamond film that can be grown at 400 C, and still retain exceptional mechanical, chemical, and tribological properties comparable to that of single crystal diamond. We have developed a process based on MPCVD to synthesize UNCD films on up to 200 mm in diameter CMOS wafers, which will open new avenues for the fabrication of monolithically integrated CMOS-driven MEMS/NEMS based on UNCD. UNCD films were grown successfully on individual Si-based CMOS chips and on 200 mm CMOS wafers at 400 C in a MPCVD system, using Ar-rich/CH4 gas mixture. The CMOS devices on the wafers were characterized before and after UNCD deposition. All devices were performing to specifications with very small degradation after UNCD deposition and processing. A threshold voltage degradation in the range of 0.08-0.44V and transconductance degradation in the range of 1.5-9% were observed.

Sumant, A.V.; Auciello, O.; Yuan, H.-C; Ma, Z.; Carpick, R. W.; Mancini, D. C.; Univ. of Wisconsin; Univ. of Pennsylvania

2009-05-01T23:59:59.000Z

200

NEMS Measurement Science  

Science Conference Proceedings (OSTI)

... approximately one third of all nanotechnology R&D [1] and ... will focus on the measurement science needed for ... this work, all of these results will be ...

2012-12-21T23:59:59.000Z

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

VISION Model : description of model used to estimate the impact of highway vehicle technologies and fuels on energy use and carbon emissions to 2050.  

DOE Green Energy (OSTI)

The VISION model has been developed by the U.S. Department of Energy (DOE) to provide estimates of the potential energy use, oil use, and carbon emission impacts to 2050 of advanced light- and heavy-duty highway vehicle technologies and alternative fuels. DOE supports research of advanced transportation technologies (including fuels) and is frequently asked to provide estimates of the potential impacts of successful market penetration of these technologies, sometimes on a relatively quick-turnaround basis. VISION is a spreadsheet model in Microsoft Excel that can be used to respond rapidly to quick-turnaround requests, as well as for longer-term analyses. It uses vehicle survival and age-dependent usage characteristics to project total light and heavy vehicle stock, total vehicle miles of travel (VMT), and total energy use by technology and fuel type by year, given market penetration and vehicle energy efficiency assumptions developed exogenously. Total carbon emissions for on-highway vehicles by year are also estimated because life-cycle carbon coefficients for various fuels are included in VISION. VISION is not a substitute for the transportation component of the Energy Information Administration's (EIA's) National Energy Modeling System (NEMS). NEMS incorporates a consumer choice model to project market penetration of advanced vehicles and alternative fuels. The projections are made within the context of the entire U.S. economy. However, the NEMS model is difficult to use on a quick-turnaround basis and only makes projections to 2025. VISION complements NEMS with its relative ''user-friendliness'' and by extending the time frame of potential analysis. VISION has been used for a wide variety of purposes. For illustration, we have listed some of its most recent and current uses in Table 1.1. Figures 1.1-1.3 illustrate the results of some of those runs. These graphs are not actual model output, but they are based on model results. The main body of this report describes VISION's methodology and data sources. The methodology and data sources used in the light- and heavy-vehicle portions of the model are discussed separately. Some suggestions for future improvements to the model are made. Appendix A provides instructions on how to run the VISION model. Appendix B describes the procedure for updating the model with the latest EIA Annual Energy Outlook (AEO).

Singh, M.; Vyas, A.; Steiner, E.

2004-02-19T23:59:59.000Z

202

Component reliability testing  

SciTech Connect

Component and system reliability of active solare energy systems continues to be a major concern of designers, manufacturers, installers, and consumers. Six test loops were constructed at the Solar Energy Research Institute in Golden, Colorado, to thermally cycle active solar energy system components. Drain valves, check valves, air vents, vacuum breakers, tempering valves, and polybutylene pipe were included in the testing. Test results show poor reliabiity of some of the components and limited performance from others. The results lead to a better understanding of certain failures in the field and present designers with realistic expectations for these components.

Farrington, R.B.

1984-03-01T23:59:59.000Z

203

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

SciTech Connect

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) 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

204

Model documentation renewable fuels module of the National Energy Modeling System  

DOE Green Energy (OSTI)

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1997 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs. and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves three purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Finally, such documentation facilitates continuity in EIA model development by providing information sufficient to perform model enhancements and data updates as part of EIA`s ongoing mission to provide analytical and forecasting information systems.

NONE

1997-04-01T23:59:59.000Z

205

Argonne TDC: Superconductive Components, Inc.  

High-Performance Tailored Materials for Levitation Permanent Magnet Technologies Making materials to help advance flywheel energy storage. Superconductive Components ...

206

Annual Energy Outlook 2009 with Projections to 2030  

Science Conference Proceedings (OSTI)

The Annual Energy Outlook 2009 (AEO2009), prepared by the Energy Information Administration (EIA), presents long-term projections of energy supply, demand, and prices through 2030, based on results from EIA’s National Energy Modeling System (NEMS). EIA published an “early release” version of the AEO2009 reference case in December 2008.

None

2009-03-01T23:59:59.000Z

207

Components of an algebraic solution of the multichannel problem of low-energy n-${}^{12}$C scattering plus sub-threshold (${}^{13}$C) states  

E-Print Network (OSTI)

The effects of components in an assumed model interaction potential, as well as of the order to which its deformation is taken, upon resonances in the low-energy cross sections and upon sub-threshold bound states of the compound nucleus (${}^{13}$C) are discussed.

K Amos; L. Canton; G. Pisent; J. P. Svenne; D van der Knijff

2004-03-22T23:59:59.000Z

208

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.

209

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 23 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 International Energy Module The NEMS International Energy Module (IEM) simulates the interaction between U.S. and global petroleum markets. It uses assumptions of economic growth and expectations of future U.S. and world crude-like liquids production and consumption to estimate the effects of changes in U.S. liquid fuels markets on the international petroleum market. For each year of the forecast, the NEMS IEM computes world oil prices, provides a supply curve of world crude-like liquids, generates a worldwide oil supply- demand balance with regional detail, and computes quantities of crude oil and light and heavy petroleum products imported into

210

Assumptions to Annual Energy Outlook - Energy Information Administration  

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

Assumptions to AEO2013 Assumptions to AEO2013 Release Date: May 14, 2013 | Next Release Date: May 2014 | full report Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2013 [1] (AEO2013), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports [2]. The National Energy Modeling System Projections in the AEO2013 are generated using the NEMS, developed and maintained by the Office of Energy Analysis of the U.S. Energy Information Administration (EIA). In addition to its use in developing the Annual

211

Assumptions to Annual Energy Outlook - Energy Information Administration  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to AEO2012 Assumptions to AEO2012 Release Date: August 2, 2012 | Next Release Date: August 2013 | Full report Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2012 [1] (AEO2012), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports [2]. The National Energy Modeling System The projections in AEO2012 are generated using the NEMS, developed and maintained by the Office of Energy Analysis (OEA) of the U.S. Energy Information Administration (EIA). In addition to its use in developing the

212

Assumptions to the Annual Energy Outlook 2000 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Key Assumptions Key Assumptions The historical input data used to develop the HEM version for the AEO2000 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2000 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and transportation sectors as inputs to the disaggregation algorithm that results in the direct fuel expenditure analysis. Household end-use and personal transportation service consumption are obtained by HEM from the NEMS Residential and Transportation Demand Modules. Household disposable income is adjusted with forecasts of total disposable income from the NEMS Macroeconomic Activity Module.

213

Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Outlook Outlook 2010 Restrospective Review July 2011 www.eia.gov U.S. Depa rtment of Energy W ashington, DC 20585 This page inTenTionally lefT blank 3 U.S. Energy Information Administration | Annual Energy Outlook Retrospective Review While the integrated nature of NEMS may result in some feedback that slightly modifies the initial assumptions about world oil price and the macroeconomic growth environment, these feedbacks tend to be relatively small, so that the initial assumptions for world oil price and the macroeconomic growth environment largely determine the overall projection environ- ment. To the extent that this general environment deviates from the initial assumptions, the NEMS projection results will also deviate. Table 2 provides a summary of the percentage of years in

214

System, Stack and Component Design  

Science Conference Proceedings (OSTI)

Oct 17, 2011 ... Energy Conversion/Fuel Cells: System, Stack and Component Design ... In fuel cell mode it produces electricity and heat from hydrogen, and in ...

215

Annual Energy Outlook 2001-Appendix G: Major Assumptions for the Forecasts  

Gasoline and Diesel Fuel Update (EIA)

Forecasts Forecasts Summary of the AEO2001 Cases/ Scenarios - Appendix Table G1 bullet1.gif (843 bytes) Model Results (Formats - PDF, ZIP) - Appendix Tables - Reference Case - 1998 to 2020 bullet1.gif (843 bytes) Download Report - Entire AEO2001 (PDF) - AEO2001 by Chapters (PDF) bullet1.gif (843 bytes) Acronyms bullet1.gif (843 bytes) Contacts Related Links bullet1.gif (843 bytes) Assumptions to the AEO2001 bullet1.gif (843 bytes) Supplemental Data to the AEO2001 (Only available on the Web) - Regional and more detailed AEO 2001 Reference Case Results - 1998, 2000 to 2020 bullet1.gif (843 bytes) NEMS Conference bullet1.gif (843 bytes) Forecast Homepage bullet1.gif (843 bytes) EIA Homepage Appendix G Major Assumptions for the Forecasts Component Modules Major Assumptions for the Annual Energy Outlook 2001

216

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market “hubs.” The major assumptions used within the NGTDM are grouped into five general categories. They relate to (1) the classification of demand into core and noncore transportation service classes, (2) the pricing of transmission and distribution services, (3) pipeline and storage capacity expansion and utilization, and (4) the implementation of recent regulatory reform. A complete listing of NGTDM assumptions and in-depth methodology descriptions are presented in Model Documentation: Natural Gas Transmission and Distribution Model of the National Energy Modeling System, Model Documentation 2003, DOE/EIA- M062(2003) (Washington, DC, January 2003).

217

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 International Energy Module The NEMS International Energy Module (IEM) simulates the interaction between U.S. and global petroleum markets. It uses assumptions of economic growth and expectations of future U.S. and world crude-like liquids production and consumption to estimate the effects of changes in U.S. liquid fuels markets on the international petroleum market. For each year of the forecast, the NEMS IEM computes oil prices, provides a supply curve of world crude-like liquids, generates a worldwide oil supply- demand balance with regional detail, and computes quantities of crude oil and light and heavy petroleum products imported into the United States by export region. Changes in the oil price (WTI), which is defined as the price of light, low-sulfur crude oil delivered to Cushing, Oklahoma in

218

A Monte Carlo study to measure the energy spectra of the primary cosmic-ray components at the knee using a new Tibet AS core detector array  

E-Print Network (OSTI)

A new hybrid experiment has been started by AS{\\gamma} experiment at Tibet, China, since August 2011, which consists of a low threshold burst-detector-grid (YAC-II, Yangbajing Air shower Core array), the Tibet air-shower array (Tibet-III) and a large underground water Cherenkov muon detector (MD). In this paper, the capability of the measurement of the chemical components (proton, helium and iron) with use of the (Tibet-III+YAC-II) is investigated by means of an extensive Monte Carlo simulation in which the secondary particles are propagated through the (Tibet-III+YAC-II) array and an artificial neural network (ANN) method is applied for the primary mass separation. Our simulation shows that the new installation is powerful to study the chemical compositions, in particular, to obtain the primary energy spectrum of the major component at the knee.

The Tibet As? Collaboration; :; M. Amenomori; X. J. Bi; D. Chen; W. Y. Chen; S. W. Cui; Danzengluobu; L. K. Ding; X. H. Ding; C. F. Feng; Zhaoyang Feng; Z. Y. Feng; Q. B. Gou; H. W. Guo; Y. Q. Guo; H. H. He; Z. T. He; K. Hibino; N. Hotta; Haibing Hu; H. B. Hu; J. Huang; W. J. Li; H. Y. Jia; L. Jiang; F. Kajino; K. Kasahara; Y. Katayose; C. Kato; K. Kawata; Labaciren; G. M. Le; A. F. Li; C. Liu; J. S. Liu; H. Lu; X. R. Meng; K. Mizutani; K. Munakata; H. Nanjo; M. Nishizawa; M. Ohnishi; I. Ohta; S. Ozawa; X. L. Qian; X. B. Qu; T. Saito; T. Y. Saito; M. Sakata; T. K. Sako; J. Shao; M. Shibata; A. Shiomi; T. Shirai; H. Sugimoto; M. Takita; Y. H. Tan; N. Tateyama; S. Torii; H. Tsuchiya; S. Udo; H. Wang; H. R. Wu; L. Xue; Y. Yamamoto; Z. Yang; S. Yasue; A. F. Yuan; T. Yuda; L. M. Zhai; H. M. Zhang; J. L. Zhang; X. Y. Zhang; Y. Zhang; Yi Zhang; Ying Zhang; Zhaxisangzhu; X. X. Zhou

2013-03-12T23:59:59.000Z

219

A Monte Carlo study to measure the energy spectra of the primary cosmic-ray components at the knee using a new Tibet AS core detector array  

E-Print Network (OSTI)

A new hybrid experiment has been started by AS{\\gamma} experiment at Tibet, China, since August 2011, which consists of a low threshold burst-detector-grid (YAC-II, Yangbajing Air shower Core array), the Tibet air-shower array (Tibet-III) and a large underground water Cherenkov muon detector (MD). In this paper, the capability of the measurement of the chemical components (proton, helium and iron) with use of the (Tibet-III+YAC-II) is investigated by means of an extensive Monte Carlo simulation in which the secondary particles are propagated through the (Tibet-III+YAC-II) array and an artificial neural network (ANN) method is applied for the primary mass separation. Our simulation shows that the new installation is powerful to study the chemical compositions, in particular, to obtain the primary energy spectrum of the major component at the knee.

:,; Bi, X J; Chen, D; Chen, W Y; Cui, S W; Danzengluobu,; Ding, L K; Ding, X H; Feng, C F; Feng, Zhaoyang; Feng, Z Y; Gou, Q B; Guo, H W; Guo, Y Q; He, H H; He, Z T; Hibino, K; Hotta, N; Hu, Haibing; Hu, H B; Huang, J; Li, W J; Jia, H Y; Jiang, L; Kajino, F; Kasahara, K; Katayose, Y; Kato, C; Kawata, K; Labaciren,; Le, G M; Li, A F; Liu, C; Liu, J S; Lu, H; Meng, X R; Mizutani, K; Munakata, K; Nanjo, H; Nishizawa, M; Ohnishi, M; Ohta, I; Ozawa, S; Qian, X L; Qu, X B; Saito, T; Saito, T Y; Sakata, M; Sako, T K; Shao, J; Shibata, M; Shiomi, A; Shirai, T; Sugimoto, H; Takita, M; Tan, Y H; Tateyama, N; Torii, S; Tsuchiya, H; Udo, S; Wang, H; Wu, H R; Xue, L; Yamamoto, Y; Yang, Z; Yasue, S; Yuan, A F; Yuda, T; Zhai, L M; Zhang, H M; Zhang, J L; Zhang, X Y; Zhang, Y; Zhang, Yi; Zhang, Ying; Zhaxisangzhu,; Zhou, X X

2013-01-01T23:59:59.000Z

220

Modeling Interregional Transmission Congestion in the NationalEnergy Modeling System  

SciTech Connect

Congestion analysis using National Energy Modeling National Energy Modeling System (NEMS) or NEMS-derivatives, such as LBNL-NEMS, is subject to significant caveats because the generation logic inherent in NEMS limits the extent to which interregional transmission can be utilized and intraregional transmission is not represented at all. The EMM is designed primarily to represent national energy markets therefore regional effects may be simplified in ways that make congestion analysis harder. Two ways in particular come to mind. First, NEMS underutilizes the capability of the traditional electric grid as it builds the dedicated and detached grid. Second, it also undervalues the costs of congestion by allowing more transmission than it should, due to its use of a transportation model rather than a transmission model. In order to evaluate benefits of reduced congestion using LBNL-NEMS, Berkeley Lab identified three possible solutions: (1) implement true simultaneous power flow, (2) always build new plants within EMM regions even to serve remote load, and (3) the dedicated and detached grid should be part of the known grid. Based on these findings, Berkeley Lab recommends the following next steps: (1) Change the build logic that always places new capacity where it is needed and allow the transmission grid to be expanded dynamically. (2) The dedicated and detached grid should be combined with the traditional grid. (3) Remove the bias towards gas fired combine cycle and coal generation, which are the only types of generation currently allowed out of region. (4) A power flow layer should be embedded in LBNL-NEMS to appropriately model and limit transmission.

Gumerman, Etan; Chan, Peter; Lesieutre, Bernard; Marnay, Chris; Wang, Juan

2006-05-25T23:59:59.000Z

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

An energy-conserving two-temperature model of radiation damage in single-component and binary Lennard-Jones crystals  

SciTech Connect

Two-temperature models are used to represent the interaction between atoms and free electrons during thermal transients such as radiation damage, laser heating, and cascade simulations. In this paper, we introduce an energy-conserving version of an inhomogeneous finite reservoir two-temperature model using a Langevin thermostat to communicate energy between the electronic and atomic subsystems. This energy-conserving modification allows the inhomogeneous two-temperature model to be used for longer and larger simulations and simulations of small energy phenomena, without introducing nonphysical energy fluctuations that may affect simulation results. We test this model on the annealing of Frenkel defects. We find that Frenkel defect annealing is largely indifferent to the electronic subsystem, unless the electronic subsystem is very tightly coupled to the atomic subsystem. We also consider radiation damage due to local deposition of heat in two idealized systems. We first consider radiation damage in a large face-centered-cubic Lennard-Jones (LJ) single-component crystal that readily recrystallizes. Second, we consider radiation damage in a large binary glass-forming LJ crystal that retains permanent damage. We find that the electronic subsystem parameters can influence the way heat is transported through the system and have a significant impact on the number of defects after the heat deposition event. We also find that the two idealized systems have different responses to the electronic subsystem. The single-component LJ system anneals most rapidly with an intermediate electron-ion coupling and a high electronic thermal conductivity. If sufficiently damaged, the binary glass-forming LJ system retains the least permanent damage with both a high electron-ion coupling and a high electronic thermal conductivity. In general, we find that the presence of an electronic gas can affect short and long term material annealing.

Phillips, Carolyn L. [Applied Physics, University of Michigan, Ann Arbor, Michigan 48109 (United States); Crozier, Paul S. [Department of Multiscale Dynamic Materials Modeling, Sandia National Laboratories, P.O. Box 5800, MS 1322, Albuquerque, New Mexico 87185-1322 (United States)

2009-08-21T23:59:59.000Z

222

Assumptions to the Annual Energy Outlook 2013  

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

Introduction Introduction This page inTenTionally lefT blank 3 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2013 [1] (AEO2013), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports [2]. The National Energy Modeling System Projections in the AEO2013 are generated using the NEMS, developed and maintained by the Office of Energy Analysis of the U.S.

223

Ceramic Component Development Process Analysis  

SciTech Connect

The development of ceramic components and coatings is critical to the demonstration of advanced fossil energy systems. Ceramic components and coating will play critical role in hot-gas filtration, high- temperature heat exchangers, thermal barrier coatings, and the hot- section of turbines. Continuous-fiber composites (CFCC) are expected to play an increasing role in these applications. This program encompassed five technical areas related to ceramic component development for fossil energy systems.

Boss, D.; Sambasivan, S.; Kuehmann, C. [Northwestern Univ., Evanston, IL (United States). Basic Industrial Research Lab.; Faber, K. [Northwestern University, MEAS Materials Science & Engineering, Evanston, IL (United States)

1996-12-31T23:59:59.000Z

224

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

SciTech Connect

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

NONE

1998-01-01T23:59:59.000Z

225

Distributed generation capabilities of the national energy modeling system  

SciTech Connect

This report describes Berkeley Lab's exploration of how the National Energy Modeling System (NEMS) models distributed generation (DG) and presents possible approaches for improving how DG is modeled. The on-site electric generation capability has been available since the AEO2000 version of NEMS. Berkeley Lab has previously completed research on distributed energy resources (DER) adoption at individual sites and has developed a DER Customer Adoption Model called DER-CAM. Given interest in this area, Berkeley Lab set out to understand how NEMS models small-scale on-site generation to assess how adequately DG is treated in NEMS, and to propose improvements or alternatives. The goal is to determine how well NEMS models the factors influencing DG adoption and to consider alternatives to the current approach. Most small-scale DG adoption takes place in the residential and commercial modules of NEMS. Investment in DG ultimately offsets purchases of electricity, which also eliminates the losses associated with transmission and distribution (T&D). If the DG technology that is chosen is photovoltaics (PV), NEMS assumes renewable energy consumption replaces the energy input to electric generators. If the DG technology is fuel consuming, consumption of fuel in the electric utility sector is replaced by residential or commercial fuel consumption. The waste heat generated from thermal technologies can be used to offset the water heating and space heating energy uses, but there is no thermally activated cooling capability. This study consists of a review of model documentation and a paper by EIA staff, a series of sensitivity runs performed by Berkeley Lab that exercise selected DG parameters in the AEO2002 version of NEMS, and a scoping effort of possible enhancements and alternatives to NEMS current DG capabilities. In general, the treatment of DG in NEMS is rudimentary. The penetration of DG is determined by an economic cash-flow analysis that determines adoption based on the n umber of years to a positive cash flow. Some important technologies, e.g. thermally activated cooling, are absent, and ceilings on DG adoption are determined by some what arbitrary caps on the number of buildings that can adopt DG. These caps are particularly severe for existing buildings, where the maximum penetration for any one technology is 0.25 percent. On the other hand, competition among technologies is not fully considered, and this may result in double-counting for certain applications. A series of sensitivity runs show greater penetration with net metering enhancements and aggressive tax credits and a more limited response to lowered DG technology costs. Discussion of alternatives to the current code is presented in Section 4. Alternatives or improvements to how DG is modeled in NEMS cover three basic areas: expanding on the existing total market for DG both by changing existing parameters in NEMS and by adding new capabilities, such as for missing technologies; enhancing the cash flow analysis but incorporating aspects of DG economics that are not currently represented, e.g. complex tariffs; and using an external geographic information system (GIS) driven analysis that can better and more intuitively identify niche markets.

LaCommare, Kristina Hamachi; Edwards, Jennifer L.; Marnay, Chris

2003-01-01T23:59:59.000Z

226

Proposal for the Award of Two Contracts for the Technical Services for Work on Components of CERN Particle Accelerators and High Energy Physics Experiments  

E-Print Network (OSTI)

This document concerns the award of two contracts for the technical services for work on components of CERN particle accelerators and high energy physics experiments. Following a market survey carried out among 73 firms in fourteen Member States, a call for tenders (IT-3156/SPL) was sent on 4 November 2002 to three consortia in four Member States. By the closing date, CERN had received tenders from the three consortia. The Finance Committee is invited to agree to the negotiation of two contracts with: 1) the consortium SERCO FACILITIES MANAGEMENT (NL) - GERARD PERRIER INDUSTRIE (FR) - INEO ALPES (FR), the lowest bidder, for approximately 55% of the technical services for work on components of CERN particle accelerators and high energy physics experiments, for an initial period of five years and for a total amount not exceeding 37 435 270 euros (54 902 500 Swiss francs), subject to revision for inflation from 1 January 2005. The contract will include options for two one-year extensions beyond the initial five-...

2003-01-01T23:59:59.000Z

227

EIA - Assumptions to the Annual Energy Outlook 2008 - International Energy  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2008 International Energy Module The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously global and U.S.A. petroleum liquids supply and demand curves (1 curve per year; 2008-2030; approximated, isoelastic fit to previous NEMS results). These quantities are not modeled directly in NEMS. Previous versions of the IEM adjusted these quantities after reading in initial values. In an attempt to more closely integrate the AEO2008 with IEO2007 and the STEO some functionality was removed from IEM while a new algorithm was implemented. Based on the difference between U.S. total petroleum liquids production (consumption) and the expected U.S. total liquids production (consumption) at the current WTI price, curves for global petroleum liquids consumption (production) were adjusted for each year. According to previous operations, a new WTI price path was generated. An exogenous oil supply module, Generate World Oil Balances (GWOB), was also used in IEM to provide annual regional (country) level production detail for conventional and unconventional liquids.

228

Follow-up on the Department of Energy's Implementation of the Advanced Batteries and Hybrid Components Program Funded under the American Recovery and Reinvestment Act, OAS-RA-L-12-05  

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

Follow-up on the Department of Follow-up on the Department of Energy's Implementation of the Advanced Batteries and Hybrid Components Program Funded under the American Recovery and Reinvestment Act OAS-RA-L-12-05 July 2012 Department of Energy Washington, DC 20585 July 10, 2012 MEMORANDUM FOR THE DIRECTOR, NATIONAL ENERGY TECHNOLOGY LABORATORY FROM: Joanne Hill, Director Central Audits Division Office of Inspector General SUBJECT: INFORMATION: Audit Report on "Follow-up on the Department of Energy's Implementation of the Advanced Batteries and Hybrid Components Program Funded under the American Recovery and Reinvestment Act" BACKGROUND Under the American Recovery and Reinvestment Act of 2009, the Department of Energy's Advanced Batteries and Hybrid Components Program (Advanced Batteries Program) received

229

Assumptions to the Annual Energy Outlook 1999 - Natural Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by obtaining market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market “hubs.” The major assumptions used within the NGTDM are grouped into five general categories. They relate to (1) the classification of demand into core and noncore transportation service classes, (2) the pricing of transmission and distribution services, (3) pipeline and storage capacity expansion and utilization, (4) the implementation of recent regulatory reform, and (5) the implementation of provisions of the Climate Change Action Plan (CCAP). A complete listing of NGTDM assumptions and in-depth methodology descriptions are presented in Model Documentation Report: Natural Gas Transmission and Distribution Model of the National Energy Modeling System, DOE/EIA-MO62/1, January 1999.

230

Model documentation Coal Market Module of the National Energy Modeling System  

SciTech Connect

This report documents objectives and conceptual and methodological approach used in the development of the National Energy Modeling System (NEMS) Coal Market Module (CMM) used to develop the Annual Energy Outlook 1996 (AEO96). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of CMM`s three submodules: Coal Production Submodule, Coal Export Submodule, and Coal Distribution Submodule.

1996-04-30T23:59:59.000Z

231

Method of using infrared radiation for assembling a first component with a second component  

DOE Patents (OSTI)

A method of assembling a first component for assembly with a second component involves a heating device which includes an enclosure having a cavity for inserting a first component. An array of infrared energy generators is disposed within the enclosure. At least a portion of the first component is inserted into the cavity, exposed to infrared energy and thereby heated to a temperature wherein the portion of the first component is sufficiently softened and/or expanded for assembly with a second component.

Sikka, Vinod K. (Oak Ridge, TN); Whitson, Barry G. (Corryton, TN); Blue, Craig A. (Knoxville, TN)

1999-01-01T23:59:59.000Z

232

Heat treating of manufactured components  

DOE Patents (OSTI)

An apparatus for heat treating manufactured components using microwave energy and microwave susceptor material is disclosed. The system typically includes an insulating vessel placed within a microwave applicator chamber. A moderating material is positioned inside the insulating vessel so that a substantial portion of the exterior surface of each component for heat treating is in contact with the moderating material.

Ripley, Edward B. (Knoxville, TN)

2012-05-22T23:59:59.000Z

233

Custom Components - Microsystems Science, Technology, and Components  

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

Connectors area will help you optimize your choice of connectors for your requirements Passive RF Components Our Passive RF Components area will work with you to identify, specify...

234

International energy outlook 1996  

SciTech Connect

This International Energy Outlook presents historical data from 1970 to 1993 and EIA`s projections of energy consumption and carbon emissions through 2015 for 6 country groups. Prospects for individual fuels are discussed. Summary tables of the IEO96 world energy consumption, oil production, and carbon emissions projections are provided in Appendix A. The reference case projections of total foreign energy consumption and of natural gas, coal, and renewable energy were prepared using EIA`s World Energy Projection System (WEPS) model. Reference case projections of foreign oil production and consumption were prepared using the International Energy Module of the National Energy Modeling System (NEMS). Nuclear consumption projections were derived from the International Nuclear Model, PC Version (PC-INM). Alternatively, nuclear capacity projections were developed using two methods: the lower reference case projections were based on analysts` knowledge of the nuclear programs in different countries; the upper reference case was generated by the World Integrated Nuclear Evaluation System (WINES)--a demand-driven model. In addition, the NEMS Coal Export Submodule (CES) was used to derive flows in international coal trade. As noted above, foreign projections of electricity demand are now projected as part of the WEPS. 64 figs., 62 tabs.

NONE

1996-05-01T23:59:59.000Z

235

The National Energy Modeling System: An Overview 2000 - Macroeconomic  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic assessment at EIA involves several modes of analysis. The first type of analysis, used in forecasting the Annual Energy Outlook where energy prices change, uses kernel regression and response surface techniques to mimic the response of larger macroeconomic and industrial models. This mode of analysis requires a given economic baseline and then calculates the economic impacts of changing energy prices, calculated from the chosen growth path. The economic growth cases are derived from the larger core models and can reflect either high, low, or reference case growth assumptions. Analyzing economic impacts from energy price changes uses the macroeconomic activity module (MAM) within NEMS and provides a subset of the macroeconomic variables available in the larger core models. The composition of the subset is determined by the other energy modules in NEMS, as they use various macroeconomic concepts as assumptions to their particular energy model.

236

Annual energy outlook 1994: With projections to 2010  

Science Conference Proceedings (OSTI)

The Annual Energy Outlook 1994 (AEO94) presents the midterm energy forecasts of the Energy Information Administration (EIA). This year`s report presents projects and analyses of energy supply, demand, and prices through 2010, based for the first time on results from the National Energy Modeling System (NEMS). NEMS is the latest in a series of computer-based energy modeling systems used over the past 2 decades by EIA and its predecessor organization, the Federal Energy Administration, to analyze and forecast energy consumption and supply in the midterm period (about 20 years). Quarterly forecasts of energy supply and demand for 1994 and 1995 are published in the Short-Term Energy Outlook (February 1994). Forecast tables for 2000, 2005, and 2010 for each of the five scenarios examined in the AEO94 are provided in Appendices A through E. The five scenarios include a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices. Appendix F provides detailed comparisons of the AEO94 forecasts with those of other organizations. Appendix G briefly described the NEMS and the major AEO94 forecast assumptions. Appendix H summarizes the key results for the five scenarios.

Not Available

1994-01-01T23:59:59.000Z

237

International Energy Outlook 1999  

Gasoline and Diesel Fuel Update (EIA)

ieo99cvr.gif (8385 bytes) ieo99cvr.gif (8385 bytes) Preface This report presents international energy projections through 2020, prepared by the Energy Information Administration. The outlooks for major energy fuels are discussed, along with electricity, transportation, and environmental issues. The International Energy Outlook 1999 (IEO99) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2020. The report is an extension of EIAÂ’s Annual Energy Outlook 1999 (AEO99), which was prepared using the National Energy Modeling System (NEMS). U.S. projections appearing in IEO99 are consistent with those published in AEO99. IEO99 is provided as a statistical service to energy managers and analysts, both in government and in the private

238

The Distributive Impact Assessment Model (DIAM): Technology share component  

DOE Green Energy (OSTI)

The models described in this report are used to allocate total energy consumption in an energy end-use service area by fuel type (including electricity) within the Distributive Impact Assessment Model (DIAM) framework. The primary objective of the DIAM is to provide energy consumption and expenditure forecasts for different population categories that are consistent with the US Department of Energy (DOE) Energy Information Administration`s (EIA`s) National Energy Modeling System (NEMS) forecast, which is produced annually in the Annual Energy Outlook and periodically in support of DOE policy formulation and analysis. The models are multinominal logit models that have been estimated using EIA`s 1990 Residential Energy Consumption Survey. Three models were estimated: space heating share, water heating share, and cooking share. These models are used to allocate total end-use service consumption over different technologies defined by fuel type characteristics. For each of the end-use service categories, consumption shares are estimated for a subset of six fuel types: natural gas, electricity, liquid petroleum gas, fuel oil/kerosene, wood, and other fuel.

Poyer, D.A.; Earl, E.; Bonner, B.

1995-03-01T23:59:59.000Z

239

Assumptions to the Annual Energy Outlook 2001 - Footnotes  

Gasoline and Diesel Fuel Update (EIA)

Feedback Feedback Related Links Annual Energy Outlook2001 Supplemental Data to the AEO2001 NEMS Conference To Forecasting Home Page EIA Homepage FOOTNOTES [1] Energy Information Administration, Annual Energy Outlook 2001 (AEO2001), DOE/EIA-0383(2001), (Washington, DC, December 2000). [2] NEMS documentation reports are available on the EIA CD-ROM and the EIA Homepage (http://www.eia.gov/bookshelf.html). For ordering information on the CD-ROM, contact STAT-USA's toll free order number: 1-800-STAT-USA or by calling (202) 482-1986. [3] Energy Information Administration, The National Energy Modeling System: An Overview 2000, DOE/EIA-0581(2000), (Washington, DC, March 2000). [4] The underlying macroeconomic growth cases use Standard and PoorÂ’s DRI February 2000 T250200 and February TO250299 and TP250299.

240

Solar bowl component efficiencies  

Science Conference Proceedings (OSTI)

Battelle Pacific Northwest Laboratory has published two volumes on the economic evaluation of various proposed configurations and plant sizes for the four solar thermal technologies. These are the latest in a series of publications sponsored by the Department of Energy (DOE) on plant and operational costs and are more complete in that they include calculations of electrical output. These latest Battelle volumes use the 1976 solar data from Barstow, Calif., and by calculating or estimating the energy conversion efficiency of each element in the process from sun to electricity predict the output and cost of electricity from different plant sizes for each of the four technologies. In this paper a comparison is presented of the component efficiencies developed by Battelle and those of the solar bowl at Crosbyton, Tex.

O'Hair, E.A.; Green, B.L. (College of Engineering, Texas Tech. Univ., Lubbock, TX (United States))

1992-11-01T23:59:59.000Z

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

International Energy Outlook 2006  

Gasoline and Diesel Fuel Update (EIA)

6 6 (IEO2006) presents an assessment by the Energy Information Administra- tion (EIA) of the outlook for international energy mar- kets through 2030. U.S. projections appearing in IEO2006 are consistent with those published in EIA's Annual Energy Outlook 2006 (AEO2006), which was pre- pared using the National Energy Modeling System (NEMS). IEO2006 is provided as a service to energy managers and analysts, both in government and in the private sector. The projections are used by international agencies, Federal and State governments, trade associa- tions, and other planners and decisionmakers. They are published pursuant to the Department of Energy Orga- nization Act of 1977 (Public Law 95-91), Section 205(c). IEO2006 focuses exclusively on marketed energy. Non- marketed energy sources, which continue to play an important role in some developing countries, are not included

242

A New, Stochastic, Energy Model of the U.S. is Under Construction: SEDS and Its Industrial Structure  

E-Print Network (OSTI)

"A new energy model for the United States is currently being constructed by staff at five National Laboratories for the Office of Energy Efficiency and Renewable Energy at the Department of Energy. This new model, SEDS (Stochastic Energy Deployment Model), is designed to test the impact of DOE R&D on energy use in the economy. The “stochastic” part of this model will also allow examination of the risks associated with sudden oil shocks, imposition of carbon taxes or trading schemes, and other shocks to the energy economy. SEDS is organized by supply-side and demand-side sectors. The supply-side sectors include electricity, liquid fuels, natural gas, coal, and various renewable energy options. On the demand side, there are the usual suspects: industry, commercial buildings, residential buildings, and two transport sectors, light-duty vehicles and heavy-duty vehicles. The industrial sector is currently modeled as a single sector, using the latest Manufacturing Energy Consumption Survey (MECS) to calibrate energy consumption to end-use energy categories: boilers, process heating, electro-chemical processes, and other process requirements. As with the CIMS model, these process requirements have ancillary requirements – conveyance, motor drive, pumps, fans, and compressors – that all require certain classes of motors. Lighting and HVAC are considered separately from process requirements. The current version of SEDS, called SEDS-Lite, has technology detail in many sectors, but these are quite simple. The intent is to add detail over time: this year, we expect to add a pulp and paper sector and a iron and steel sector, pull these and petroleum refining out of the aggregate industrial sector, and add the non-manufacturing industrial component to the model. In future years, we expect the industrial detail to replicate CIMS. Our simulations with the industrial sector of SEDS-Lite will show how closely it tracks the NEMS forecasts. Other simulations will demonstrate how the stochastic component can be used to show industry"

Roop, J. M.

2009-05-01T23:59:59.000Z

243

Directory of energy information administration models 1995  

Science Conference Proceedings (OSTI)

This updated directory has been published annually; after this issue, it will be published only biennially. The Disruption Impact Simulator Model in use by EIA is included. Model descriptions have been updated according to revised documentation approved during the past year. This directory contains descriptions about each model, including title, acronym, purpose, followed by more detailed information on characteristics, uses, and requirements. Sources for additional information are identified. Included are 37 EIA models active as of February 1, 1995. The first group is the National Energy Modeling System (NEMS) models. The second group is all other EIA models that are not part of NEMS. Appendix A identifies major EIA modeling systems and the models within these systems. Appendix B is a summary of the `Annual Energy Outlook` Forecasting System.

NONE

1995-07-13T23:59:59.000Z

244

Directory of Energy Information Administration Models 1993  

SciTech Connect

This directory contains descriptions about each model, including the title, acronym, purpose, followed by more detailed information on characteristics, uses, and requirements. Sources for additional information are identified. Included in this directory are 35 EIA models active as of May 1, 1993. Models that run on personal computers are identified by ``PC`` as part of the acronym. EIA is developing new models, a National Energy Modeling System (NEMS), and is making changes to existing models to include new technologies, environmental issues, conservation, and renewables, as well as extend forecast horizon. Other parts of the Department are involved in this modeling effort. A fully operational model is planned which will integrate completed segments of NEMS for its first official application--preparation of EIA`s Annual Energy Outlook 1994. Abstracts for the new models will be included in next year`s version of this directory.

Not Available

1993-07-06T23:59:59.000Z

245

Women @ Energy: Carrie Milton | Department of Energy  

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

Carrie Milton Carrie Milton Women @ Energy: Carrie Milton March 28, 2013 - 10:15am Addthis Carrie Milton is an operations research analyst for the Office of Electricity, Coal, Nuclear, and Renewables Analysis at the U.S. Energy Information Administration. Carrie Milton is an operations research analyst for the Office of Electricity, Coal, Nuclear, and Renewables Analysis at the U.S. Energy Information Administration. Check out other profiles in the Women @ Energy series and share your favorites on Pinterest. Carrie Milton is an operations research analyst for the Office of Electricity, Coal, Nuclear, and Renewables Analysis at the U.S. Energy Information Administration. Her work involves incorporating collected data from multiple sources into the National Energy Modeling System (NEMS)

246

Model documentation, Renewable Fuels Module of the National Energy Modeling System  

DOE Green Energy (OSTI)

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the Annual Energy Outlook 1998 (AEO98) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. For AEO98, the RFM was modified in three principal ways, introducing capital cost elasticities of supply for new renewable energy technologies, modifying biomass supply curves, and revising assumptions for use of landfill gas from municipal solid waste (MSW). In addition, the RFM was modified in general to accommodate projections beyond 2015 through 2020. Two supply elasticities were introduced, the first reflecting short-term (annual) cost increases from manufacturing, siting, and installation bottlenecks incurred under conditions of rapid growth, and the second reflecting longer term natural resource, transmission and distribution upgrade, and market limitations increasing costs as more and more of the overall resource is used. Biomass supply curves were also modified, basing forest products supplies on production rather than on inventory, and expanding energy crop estimates to include states west of the Mississippi River using information developed by the Oak Ridge National Laboratory. Finally, for MSW, several assumptions for the use of landfill gas were revised and extended.

NONE

1998-01-01T23:59:59.000Z

247

Assumptions to the Annual Energy Outlook 2001 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Completed Copy in PDF Format Completed Copy in PDF Format Related Links Annual Energy Outlook2001 Supplemental Data to the AEO2001 NEMS Conference To Forecasting Home Page EIA Homepage Household Expenditures Module Key Assumptions The historical input data used to develop the HEM version for the AEO2001 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2001 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and

248

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

249

Annual Energy Outlook 2000  

Gasoline and Diesel Fuel Update (EIA)

Homepage Homepage Preface The Annual Energy Outlook 2000 (AEO2000) presents midterm forecasts of energy supply, demand, and prices through 2020 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA’s National Energy Modeling System (NEMS). The report begins with an “Overview” summarizing the AEO2000 reference case. The next section, “Legislation and Regulations,” describes the assumptions made with regard to laws that affect energy markets and discusses evolving legislative and regulatory issues. “Issues in Focus” discusses current energy issues—appliance standards, gasoline and diesel fuel standards, natural gas industry expansion, competitive electricity pricing, renewable portfolio standards, and carbon emissions. It is followed by the analysis of energy market trends.

250

Modeling Interregional Transmission Congestion in the National Energy Modeling System  

E-Print Network (OSTI)

Validating LBNL-NEMS Electricity Prices and Loads A directB. Appendix C. Validating NEMS Electricity Prices andcan lead to lower electricity prices and less frequent power

Gumerman, Etan; Chan, Peter; Lesieutre, Bernard; Marnay, Chris; Wang, Juan

2006-01-01T23:59:59.000Z

251

The National Energy Modeling System: An Overview 1998 - Appendix:  

Gasoline and Diesel Fuel Update (EIA)

APPENDIX: APPENDIX: BIBLIOGRAPHY The National Energy Modeling System is documented in a series of model documentation reports, available by contacting the National Energy Information Center (202/586-8800). Energy Information Administration, National Energy Modeling System Integrating Module Documentation Report, DOE/EIA-M057(97) (Washington, DC, May 1997). Energy Information Administration, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(97) (Washington, DC, December 1996). Energy Information Administration, Model Developer's Appendix to the Model Documentation Report: NEMS Macroeconomic Activity Module, DOE/EIA-M065A (Washington, DC, July 1994). Energy Information Administration, Documentation of the DRI Model of the

252

Annual energy outlook 1997 with projections to 2015  

Science Conference Proceedings (OSTI)

The Annual Energy Outlook 1997 (AEO97) presents midterm forecasts of energy supply, demand, and prices through 2015 prepared by the Energy Information Administration (EIA). These projections are based on results of EIA`s National Energy Modeling System (NEMS). This report begins with a summary of the reference case, followed by a discussion of the legislative assumptions and evolving legislative and regulatory issues. ``Issues in Focus`` discusses emerging energy issues and other topics of particular interest. It is followed by the analysis of energy market trends. The analysis in AEO97 focuses primarily on a reference case and four other cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. Forecast tables for these cases are provided in Appendixes A through C. Appendixes D and E present summaries of the reference case forecasts in units of oil equivalence and household energy expenditures. Twenty-three other cases explore the impacts of varying key assumptions in NEMS--generally, technology penetration, with the major results shown in Appendix F. Appendix G briefly describes NEMS and the major AEO97 assumptions, with a summary table. 114 figs., 22 tabs.

NONE

1996-12-01T23:59:59.000Z

253

Manufacturing complex silica aerogel target components  

SciTech Connect

Aerogel is a material used in numerous components in High Energy Density Physics targets. In the past these components were molded into the proper shapes. Artifacts left in the parts from the molding process, such as contour irregularities from shrinkage and density gradients caused by the skin, have caused LANL to pursue machining as a way to make the components.

Defriend Obrey, Kimberly Ann [Los Alamos National Laboratory; Day, Robert D [Los Alamos National Laboratory; Espinoza, Brent F [Los Alamos National Laboratory; Hatch, Doug [Los Alamos National Laboratory; Patterson, Brian M [Los Alamos National Laboratory; Feng, Shihai [Los Alamos National Laboratory

2008-01-01T23:59:59.000Z

254

A 6-Yr Climatology of Vertical Mean and Shear Components of Kinetic Energy for the Australian–South Pacific Jet Stream  

Science Conference Proceedings (OSTI)

The climatology of the kinetic energy associated with the subtropical jet over the Australian–South Pacific region is investigated for a 6-yr period, January 1985–December 1990, using monthly mean data. The total kinetic energy (TKE) is ...

Matthew D. Eastin; Dayton G. Vincent

1998-02-01T23:59:59.000Z

255

Software Component Integration Testing  

Science Conference Proceedings (OSTI)

... a combination of off-the-shelf components, with new components integrated to satisfy ... oriented, that is, it consists of objects with state and behavior. ...

2011-12-02T23:59:59.000Z

256

International Energy Outlook 2007  

Gasoline and Diesel Fuel Update (EIA)

7 7 (IEO2007) presents an assessment by the Energy Information Admin- istration (EIA) of the outlook for international energy markets through 2030. U.S. projections appearing in IEO2007 are consistent with those published in EIA's Annual Energy Outlook 2007 (AEO2007), which was pre- pared using the National Energy Modeling System (NEMS). IEO2007 is provided as a service to energy managers and analysts, both in government and in the private sector. The projections are used by international agencies, Federal and State governments, trade associa- tions, and other planners and decisionmakers. They are published pursuant to the Department of Energy Orga- nization Act of 1977 (Public Law 95-91), Section 205(c). Projections in IEO2007 are divided according to Organi- zation for Economic Cooperation and Development members (OECD) and non-members (non-OECD). There are

257

Annual Energy Outlook 2001  

Gasoline and Diesel Fuel Update (EIA)

Homepage Homepage Annual Energy Outlook 2001 With Projections to 2020 Preface The Annual Energy Outlook 2001 (AEO2001) presents midterm forecasts of energy supply, demand, and prices through 2020 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA’s National Energy Modeling System (NEMS). The report begins with an “Overview” summarizing the AEO2001 reference case. The next section, “Legislation and Regulations,” discusses evolving legislative and regulatory issues. “Issues in Focus” discusses the macroeconomic projections, world oil and natural gas markets, oxygenates in gasoline, distributed electricity generation, electricity industry restructuring, and carbon dioxide emissions. It is followed by the analysis of energy market trends.

258

International Energy Outlook 2006 - Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface International Energy Outlook 2006 Preface This report presents international energy projections through 2030, prepared by the Energy Information Administration, including outlooks for major energy fuels and associated carbon dioxide emissions. The International Energy Outlook 2006 (IEO2006) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2030. U.S. projections appearing in IEO2006 are consistent with those published in EIAÂ’s Annual Energy Outlook 2006 (AEO2006), which was prepared using the National Energy Modeling System (NEMS). IEO2006 is provided as a service to energy managers and analysts, both in government and in the private sector. The projections are used by international agencies, Federal and State governments, trade

259

EIA - The National Energy Modeling System: An Overview 2003-Macroeconomic  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module The National Energy Modeling System: An Overview 2003 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) links NEMS to the rest of the economy by providing projections of economic driver variables for use by the supply, demand, and conversion modules of NEMS. The derivation of the baseline macroeconomic forecast lays a foundation for the determination of the energy demand and supply forecast. MAM is used to present alternative macroeconomic growth cases to provide a range of uncertainty about the growth potential for the economy and its likely consequences for the energy system. MAM is also able to address the macroeconomic impacts associated with changing energy market conditions, such as alternative world oil price assumptions. Outside of the Annual Energy Outlook setting, MAM represents a system of linked modules which can assess the potential impacts on the economy of changes in energy events or policy proposals. These economic impacts then feed back into NEMS for an integrated solution. MAM consists of five modules:

260

Annual energy outlook 2005 with projections to 2025  

Science Conference Proceedings (OSTI)

The Annual Energy Outlook 2005 (AEO2005) presents midterm forecasts of energy supply, demand, and prices through 2025 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA's National Energy Modelling System (NEMS). The report begins with an 'Overview' summarizing the AEO2005 reference case. The next section, 'Legislation and Regulations', discusses evolving legislative and regulatory issues in the USA. Issues in Focus includes discussions on key energy market issues and examines their potential impacts. In particular, it includes a discussion of the world oil price assumptions used in the reference case and four alternative world oil price cases examined in AEO2005. 'Issues in Focus' is followed by 'Market Trends', which provides a summary of energy market trends in the AEO2005 forecast. The analysis in AEO2005 focuses primarily on a reference case, lower and higher economic growth cases, and four alternative oil price cases, a low world oil price case, an October oil futures case, and two high world oil price cases. Forecast tables for those cases are provided in Appendixes A through D. The major results for the alterative cases, which explore the impacts of varying key assumption in NEMS (such as rates of technology penetration), are summarized in Appendix E. Appendix F briefly describes NEMS and the alternative cases. 115 figs., 38 tabs., 8 apps.

NONE

2005-02-01T23:59:59.000Z

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


261

U.S. Energy Information Administration (EIA) - Source  

Gasoline and Diesel Fuel Update (EIA)

‹ Analysis & Projections ‹ Analysis & Projections AEO2013 Early Release Overview Release Date: December 5, 2012 | Full Report Release Date: Spring 2013 | Report Number: DOE/EIA-0383ER(2013) available in PDF Levelized Cost of New Generation Resources in the Annual Energy Outlook 2013 Release date: January 28, 2013 This paper presents average levelized costs for generating technologies that are brought on line in 20181 as represented in the National Energy Modeling System (NEMS) for the Annual Energy Outlook 2013 (AEO2013) Early Release Reference case.2 Both national values and the minimum and maximum values across the 22 U.S. regions of the NEMS electricity market module are presented. Levelized cost is often cited as a convenient summary measure of the overall competiveness of different generating technologies. It represents

262

U.S. Energy Information Administration (EIA) - Source  

Gasoline and Diesel Fuel Update (EIA)

available in PDF available in PDF Levelized Cost of New Generation Resources in the Annual Energy Outlook 2013 Release date: January 28, 2013 This paper presents average levelized costs for generating technologies that are brought on line in 20181 as represented in the National Energy Modeling System (NEMS) for the Annual Energy Outlook 2013 (AEO2013) Early Release Reference case.2 Both national values and the minimum and maximum values across the 22 U.S. regions of the NEMS electricity market module are presented. Levelized cost is often cited as a convenient summary measure of the overall competiveness of different generating technologies. It represents the per-kilowatthour cost (in real dollars) of building and operating a generating plant over an assumed financial life and duty cycle. Key inputs

263

Summary Impacts of Modeled Provisions of the 2003 Conference Energy Bill  

Reports and Publications (EIA)

This service report was undertaken at the February 2, 2004, request of Senator John Sununu to perform an assessment of the Conference Energy Bill of 2003. This report summarizes the CEB provisions that can be analyzed using the National Energy Modeling System (NEMS) and have the potential to affect energy consumption, supply, and prices. The impacts are estimated by comparing the projections with the CEB provisions to the AEO2004 Reference Case.

Andy Kydes

2004-02-01T23:59:59.000Z

264

International Energy Outlook 2001 - Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface picture of a printer Printer Friendly Version (PDF) This report presents international energy projections through 2020, prepared by the Energy Information Administration, including outlooks for major energy fuels and issues related to electricity, transportation, and the environment. The International Energy Outlook 2001 (IEO2001) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2020. The report is an extension of the EIAÂ’s Annual Energy Outlook 2001 (AEO2001), which was prepared using the National Energy Modeling System (NEMS). U.S. projections appearing in the IEO2001 are consistent with those published in the AEO2001. IEO2001 is provided as a statistical service to energy managers and analysts, both in

265

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

The International Energy Outlook 2005 (IEO2005) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2025. U.S. projections appearing in IEO2005 are consistent with those published in EIA's Annual Energy Outlook 2005 (AEO2005), which was prepared using the National Energy Modeling System (NEMS). The International Energy Outlook 2005 (IEO2005) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2025. U.S. projections appearing in IEO2005 are consistent with those published in EIA's Annual Energy Outlook 2005 (AEO2005), which was prepared using the National Energy Modeling System (NEMS). Table of Contents Projection Tables Reference Case High Economic Growth Case Low Economic Growth Case Reference Case Projections by End-Use Sector and Region Projections of Oil Production Capacity and Oil Production in Three Cases Projections of Nuclear Generating Capacity Highlights World Energy and Economic Outlook Outlook for World Energy Consumption World Economic Outlook Alternative Growth Cases

266

EIA - Assumptions to the Annual Energy Outlook 2009 - International Energy  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2009 International Energy Module Figure 2. World Oil Prices in three Cases, 1995-2030 (2006 dollars per barrel). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 3. OPEC Total Liquids Production in the Reference Case, 1995-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 4. Non-OPEC Total Liquids Production in the Reference Case, 1995-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. figure data The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously global and U.S.A. petroleum liquids

267

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

6 6 Assumptions to the Annual Energy Outlook 2006 This report presents major assumptions of NEMS that are used to generate the projections in the AEO2006. Contents (Complete Report) Download complete Report. Need help, contact the National Energy Information Center at 202-586-8800. Introduction Introduction Section to the Assumptions to the Annual Energy Outlook 2006 Report. Need help, contact the National Energy Information Center at 202-586-8800. Introduction Section to the Assumptions to the Annual Energy Outlook 2006 Report. Need help, contact the National Energy Information Center at 202-586-8800. Macroeconomic Activity Module Macroeconomic Activity Module Section to the Assumptions to the Annual Energy Outlook 2006 Report. Need help, contact the National Energy Information Center at 202-586-8800.

268

Energy Information Administration (EIA) - International Energy Outlook 2006  

Gasoline and Diesel Fuel Update (EIA)

International Energy Outlook 2006 International Energy Outlook 2006 International Energy Outlook 2006 The International Energy Outlook 2006 (IEO2006) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2030. U.S. projections appearing in IEO2006 are consistent with those published in EIA's Annual Energy Outlook 2006 (AEO2006), which was prepared using the National Energy Modeling System (NEMS). Projection Tables Appendix A: Reference Case Appendix B: High Economic Growth Case Appendix C: Low Economic Growth Case Appendix D: Reference Case Projections by End-Use Sector and Region Appendix E: Projections of Oil Production Capacity and Oil Production in Three Cases Appendix F: Reference Case Projections for Electricity Capacity and Generation by Fuel

269

Scenarios for Benefits Analysis of Energy Research, Development,Demonstration and Deployment  

SciTech Connect

For at least the last decade, evaluation of the benefits of research, development, demonstration, and deployment (RD3) by the U.S. Department of Energy has been conducted using deterministic forecasts that unrealistically presume we can precisely foresee our future 10, 25,or even 50 years hence. This effort tries, in a modest way, to begin a process of recognition that the reality of our energy future is rather one rife with uncertainty. The National Energy Modeling System (NEMS) is used by the Department of Energy's Office of Energy Efficiency and Renewable Energy (EE) and Fossil Energy (FE) for their RD3 benefits evaluation. In order to begin scoping out the uncertainty in these deterministic forecasts, EE and FE designed two futures that differ significantly from the basic NEMS forecast. A High Fuel Price Scenario and a Carbon Cap Scenario were envisioned to forecast alternative futures and the associated benefits. Ernest Orlando Lawrence Berkeley National Laboratory (LBNL) implemented these scenarios into its version of NEMS,NEMS-LBNL, in late 2004, and the Energy Information Agency created six scenarios for FE in early 2005. The creation and implementation of the EE-FE scenarios are explained in this report. Both a Carbon Cap Scenario and a High Fuel Price Scenarios were implemented into the NEMS-LBNL. EIA subsequently modeled similar scenarios using NEMS. While the EIA and LBNL implementations were in some ways rather different, their forecasts do not significantly diverge. Compared to the Reference Scenario, the High Fuel Price Scenario reduces energy consumption by 4 percent in 2025, while in the EIA fuel price scenario (known as Scenario 4) reduction from its corresponding reference scenario (known as Scenario 0) in 2025 is marginal. Nonetheless, the 4 percent demand reduction does not lead to other cascading effects that would significantly differentiate the two scenarios. The LBNL and EIA carbon scenarios were mostly identical. The only major difference was that LBNL started working with the AEO 2004NEMS code and EIA was using AEO 2005 NEMS code. Unlike the High Price Scenario the Carbon Cap scenario gives a radically different forecast than the Reference Scenario. NEMS-LBNL proved that it can handle these alternative scenarios. However, results are price inelastic (for both oil and natural gas prices) within the price range evaluated. Perhaps even higher price paths would lead to a distinctly different forecast than the Reference Scenario. On the other hand, the Carbon Cap Scenario behaves more like an alternative future. The future in the Carbon Cap Scenario has higher electricity prices, reduced driving, more renewable capacity, and reduced energy consumption. The next step for this work is to evaluate the EE benefits under each of the three scenarios. Comparing those three sets of predicted benefits will indicate how much uncertainty is inherent within this sort of deterministic forecasting.

Gumerman, Etan; Marnay, Chris

2005-09-07T23:59:59.000Z

270

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

2 2 The commercial module forecasts consumption by fuel 13 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 14 for eleven building categories 15 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

271

U.S. Energy Information Administration (EIA) - Sector  

Gasoline and Diesel Fuel Update (EIA)

NEMS overview and brief description of cases NEMS overview and brief description of cases Table E1. Summary of the AEO2012 cases Reference Baseline economic growth (2.5 percent per year from 2010 through 2035), oil price, and technology assumptions. Complete projection tables in Appendix A. Light, sweet crude oil prices rise to about $145 per barrel (2010 dollars) in 2035. Assumes RFS target to be met as soon as possible. Low Economic Growth Real GDP grows at an average annual rate of 2.0 percent from 2010 to 2035. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B.. High Economic Growth Real GDP grows at an average annual rate of 3.0 percent from 2010 to 2035. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B.

272

U.S. Energy Information Administration (EIA) - Sector  

Gasoline and Diesel Fuel Update (EIA)

NEMS overview and brief description of cases NEMS overview and brief description of cases Table E1. Summary of the AEO2011 cases Reference Baseline economic growth (2.7 percent per year from 2009 through 2035), world oil price, and technology assumptions. Complete projection tables in Appendix A. World light, sweet crude oil prices rise to about $125 per barrel by 2035 in year 2009 dollars. Assumes RFS target to be met as soon as possible. Fully integrated Low Economic Growth Real GDP grows at an average annual rate of 2.1 percent from 2009 to 2035. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B. Fully integrated High Economic Growth Real GDP grows at an average annual rate of 3.2 percent from 2009 to 2035. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B. Fully integrated

273

Beyond Generic Component Parameters  

Science Conference Proceedings (OSTI)

For flexible use in application contexts, software components should be parameterized, but also extended appropriately. Until now, there is no language mechanism to solve both problems uniformly. This paper presents a new concept, component hooks. Hooks ...

Uwe Aßmann

2002-06-01T23:59:59.000Z

274

International Energy Outlook - Table of Contents  

Gasoline and Diesel Fuel Update (EIA)

International Energy Outlook International Energy Outlook EIA Glossary International Energy Outlook 2004 Report #: DOE/EIA-0484(2004) Release date: April 2004 Next release date: July 2005 The International Energy Outlook 2004 (IEO2004) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2025. U.S.projections appearing in IEO2004 are consistent with those published in EIA's Annual Energy Outlook 2004 (AEO2004), which was prepared using the National Energy Modeling System (NEMS). Table of Contents Appendixes Highlights World Energy and Economic Outlook Outlook for Primary Energy Consumption Energy End Use Outlook for Carbon Dioxide Emissions World Economic Outlook Alternative Growth Case Trends in Energy Intensity

275

Modeling renewable portfolio standards for the annual energy outlook 1998 - electricity market module  

SciTech Connect

The Electricity Market Module (EMM) is the electricity supply component of the National Energy Modeling System (NEMS). The EMM represents the generation, transmission, and pricing of electricity. It consists of four submodules: the Electricity Capacity Planning (ECP) Submodule, the Electricity Fuel Dispatch (EFD) Submodule, the Electricity Finance and Pricing (EFP) Submodule, and the Load and Demand-Side Management (LDSM) Submodule. For the Annual Energy Outlook 1998 (AEO98), the EMM has been modified to represent Renewable Portfolio Standards (RPS), which are included in many of the Federal and state proposals for deregulating the electric power industry. A RPS specifies that electricity suppliers must produce a minimum level of generation using renewable technologies. Producers with insufficient renewable generating capacity can either build new plants or purchase {open_quotes}credits{close_quotes} from other suppliers with excess renewable generation. The representation of a RPS involves revisions to the ECP, EFD, and the EFP. The ECP projects capacity additions required to meet the minimum renewable generation levels in future years. The EFD determines the sales and purchases of renewable credits for the current year. The EFP incorporates the cost of building capacity and trading credits into the price of electricity.

1998-02-01T23:59:59.000Z

276

Reactor component automatic grapple  

DOE Patents (OSTI)

A grapple for handling nuclear reactor components in a medium such as liquid sodium which, upon proper seating and alignment of the grapple with the component as sensed by a mechanical logic integral to the grapple, automatically seizes the component. The mechanical logic system also precludes seizure in the absence of proper seating and alignment.

Greenaway, Paul R. (Bethel Park, PA)

1982-01-01T23:59:59.000Z

277

X-ray lasers and methods utilizing two component driving illumination provided by optical laser means of relatively low energy and small physical size  

DOE Patents (OSTI)

An X-ray laser (10), and related methodology, are disclosed wherein an X-ray laser target (12) is illuminated with a first pulse of optical laser radiation (14) of relatively long duration having scarcely enough energy to produce a narrow and linear cool plasma of uniform composition (38). A second, relatively short pulse of optical laser radiation (18) is uniformly swept across the length, from end to end, of the plasma (38), at about the speed of light, to consecutively illuminate continuously succeeding portions of the plasma (38) with optical laser radiation having scarcely enough energy to heat, ionize, and invert them into the continuously succeeding portions of an X-ray gain medium. This inventive double pulse technique results in a saving of more than two orders of magnitude in driving optical laser energy, when compared to the conventional single pulse approach.

Rosen, Mordecai D. (Berkeley, CA); Matthews, Dennis L. (El Granada, CA)

1991-01-01T23:59:59.000Z

278

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

SciTech Connect

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

NONE

1998-01-01T23:59:59.000Z

279

X-ray lasers and methods utilizing two component driving illumination provided by optical laser means of relatively low energy and small physical size  

DOE Patents (OSTI)

It is an object of this invention to provide an X-ray laser that is driven by an optical laser or lasers of relatively low energy and small physical size. Another object of this invention is to provide a method of driving an X-ray laser with an optical laser or lasers of relatively low energy and small physical size. Additional objects, advantages and novel features of the invention are set forth in part in the description included in this report. The objects and advantages of the invention may be realized and attained by means of the instrumentalities and combinations particularly pointed out in the appended claims. 8 figs.

Rosen, M.D.; Matthews, D.L.

1989-10-18T23:59:59.000Z

280

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

T T he 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 SEDS 25 data.

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

EIA - Assumptions to the Annual Energy Outlook 2010  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the Annual Energy Outlook 2010 This report summarizes the major assumptions used in the NEMS to generate the AEO2010 projections. Introduction Macroeconomic Activity Module International Energy Module Residential Demand Module Commercial Demand Module Industrial Demand Module Transportation Demand Module Electricity Market Module Oil and Gas Supply Module Natural Gas Transmission and Distribution Module Petroleum Market Module Coal Market Module Renewable Fuels Module PDF (GIF) Appendix A: Handling of Federal and Selected State Legislation and Regulation In the Annual Energy Outlook Past Assumptions Editions Download the Report Assumptions to the Annual Energy Outlook 2010 Report Cover. Need help, contact the National Energy Information Center at 202-586-8800.

282

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

283

Component Reliability Extensions for Fractal component model  

E-Print Network (OSTI)

that the model is an abstraction and, therefore, it may represent behavior not possible in the original program. Consequently, a model checker may then find errors that are not present in the program (i.e., false negatives, a component cannot be checked in isolation because it does not form a complete program (with the main method

284

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2006 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 SEDS27 data.

285

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2006 The NEMS Commercial Sector Demand Module generates forecasts 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.14

286

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2006 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

287

National Energy Modeling System: An Overview  

Gasoline and Diesel Fuel Update (EIA)

6) 6) Distribution Category UC-950 The National Energy Modeling System: An Overview March 1996 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the Department of Energy. The information contained herein should not be construed as advocating or reflecting any policy position of the Department of Energy or of any other organization. PREFACE The National Energy Modeling System: An Overview (Overview) provides a summary description of the National Energy Modeling System (NEMS), which was used to generate the forecasts of energy production, demand, imports, and prices through the year 2015 for the Annual Energy Outlook 1996 (AEO96), (DOE/EIA- 0383(96)), released in January

288

EIA - International Energy Outlook 2007 - Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface International Energy Outlook 2007 Preface This report presents international energy projections through 2030, prepared by the Energy Information Administration, including outlooks for major energy fuels and associated carbon dioxide emissions. The International Energy Outlook 2007 (IEO2007) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2030. U.S. projections appearing in IEO2007 are consistent with those published in EIAÂ’s Annual Energy Outlook 2007 (AEO2007), which was prepared using the National Energy Modeling System (NEMS). IEO2007 is provided as a service to energy managers and analysts, both in government and in the private sector. The projections are used by international agencies, Federal and State governments, trade

289

EIA - International Energy Outlook 2008-Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface International Energy Outlook 2008 Preface This report presents international energy projections through 2030, prepared by the Energy Information Administration, including outlooks for major energy fuels and associated carbon dioxide emissions. The International Energy Outlook 2008 (IEO2008) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2030. U.S. projections appearing in IEO2008 are consistent with those published in EIAÂ’s Annual Energy Outlook 2008 (AEO2008), which was prepared using the National Energy Modeling System (NEMS). IEO2008 is provided as a service to energy managers and analysts, both in government and in the private sector. The projections are used by international agencies, Federal and State governments, trade

290

Assumptions to the Annual Energy Outlook 2002 - Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2002, DOE/EIA- M068(2002) January 2002. 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

291

Assumptions to the Annual Energy Outlook 2001 - Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2001, DOE/EIA- M068(2001) January 2001. 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

292

Directory of Energy Information Administration Models 1994  

SciTech Connect

This directory revises and updates the 1993 directory and includes 15 models of the National Energy Modeling System (NEMS). Three other new models in use by the Energy Information Administration (EIA) have also been included: the Motor Gasoline Market Model (MGMM), Distillate Market Model (DMM), and the Propane Market Model (PPMM). This directory contains descriptions about each model, including title, acronym, purpose, followed by more detailed information on characteristics, uses and requirements. Sources for additional information are identified. Included in this directory are 37 EIA models active as of February 1, 1994.

Not Available

1994-07-01T23:59:59.000Z

293

EIA - Assumptions to the Annual Energy Outlook 2009  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the Annual Energy Outlook 2009 The Early Release for next year's Annual Energy Outlook will be presented at the John Hopkins Kenney Auditorium on December 14th This report summarizes the major assumptions used in the NEMS to generate the AEO2009 projections. Introduction Macroeconomic Activity Module International Energy Module Residential Demand Module Commercial Demand Module Industrial Demand Module Transportation Demand Module Electricity Market Module Oil and Gas Supply Module Natural Gas Transmission and Distribution Module Petroleum Market Module Coal Market Module Renewable Fuels Module PDF (GIF) Appendix A: Handling of Federal and Selected State Legislation and Regulation In the Annual Energy Outlook Past Assumptions Editions

294

Greenhouse Gas Initiatives - Analysis of McCain-Lieberman Bill S.280 ‘The ClimateStewardship and Innovation Act of 2007’ Using the National Energy Modeling System  

E-Print Network (OSTI)

Members of Congress have proposed a number of new aggressive plans for the reduction of greenhouse gases in the United States. Many of these proposals require reductions of 30% below current levels by 2020 and 60-80% reductions from current levels by 2050. While it is clear that achieving these proposed reductions will require major changes in U.S. energy infrastructure and technology implementation; it is only recently that quantitative analyses of the potential implications have become available. One of the critical questions to be addressed is the implications for various energy sources and technologies and the impact on energy prices to end users. This paper reports on the impacts of pending GHG legislation on energy supply, demand, and prices, and the technologies and market mechanisms that are likely to be employed to reduce CO2 emissions. The paper also reports on the results of analysis of GHG bills performed by SAIC using the National Energy Modeling System (NEMS). NEMS is an economy-wide, integrated energy model that analyzes energy supply, conversion, and demand. NEMS is used by the U.S. Energy Information Administration (EIA) to provide US energy market forecasts through 2030, and is the principal tool for the analysis of energy and greenhouse gas policies used by the U.S. government.

Ellsworth, C.

2008-01-01T23:59:59.000Z

295

Sustainable Energy Solutions Task 2.0: Wind Turbine Reliability and Maintainability Enhancement through System-wide Structure Health Monitoring and Modifications to Rotating Components  

DOE Green Energy (OSTI)

EXECUTIVE SUMARRY An evaluation of nondestructive structural health monitoring methods was completed with over 132 documents, 37 specifically about wind turbines, summarized into a technology matrix. This matrix lists the technology, what can be monitored with this technology, and gives a short summary of the key aspects of the technology and its application. Passive and active acoustic emission equipment from Physical Acoustics Corp. and Acellent Technologies have been evaluated and selected for use in experimental state loading and fatigue tests of composite wind turbine blade materials. Acoustic Emission (AE) and Active Ultrasonic Testing (AUT), were applied to composite coupons with both simulated and actual damage. The results found that, while composites are more complicated in nature, compared to metallic structures, an artificial neural network analysis could still be used to determine damage. For the AE system, the failure mode could be determined (i.e. fiber breakage, delamination, etc.). The Acellent system has been evaluated to work well with composite materials. A test-rig for reliability testing of the rotating components was constructed. The research on the types of bearings used in the wind turbines indicated that in most of the designs, the main bearings utilized to support the shaft are cylindrical roller bearings. The accelerated degradation testing of a population of bearings was performed. Vibration and acoustic emission data was collected and analyzed in order to identify a representative degradation signal for each bearing to identify the initiation of the degradation process in the bearings. Afterwards, the RMS of the vibration signal from degradation initiation up to the end of the useful life of the bearing was selected to predict the remaining useful life of the bearing. This step included fitting Autoregressive Moving Average (ARMA) models to the degradation signals and approximating the probability distribution function (PDF) of remaining useful life based on the results of Monte-Carlo simulation of the ARMA models. This step was performed for different percentages of the degradation signal of each bearing. The accuracy of the proposed approach then was assessed by comparing the actual life of the bearing and the estimated life of the bearing from the developed models. The results were impressive and indicated that the accuracy of the models improved as more data was utilized in developing the ARMA models (we get closer to the end of the life of the bearing).

Janet M Twomey, PhD

2010-04-30T23:59:59.000Z

296

Matter & Energy Solar Energy  

E-Print Network (OSTI)

See Also: Matter & Energy Solar Energy· Electronics· Materials Science· Earth & Climate Energy at the University of Illinois, the future of solar energy just got brighter. Although silicon is the industry Electronics Over 1.2 Million Electronics Parts, Components and Equipment. www.AlliedElec.com solar energy

Rogers, John A.

297

Extrapolating Environmental Benefits from IGCC in NEMS  

NLE Websites -- All DOE Office Websites (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

298

LLNL's NeMS: Network Mapping System  

High Performance Computing Innovation Center (Building 6475)located in LLNL's Livermore Valley Open Campus (LVOC) Seating is limited, Pre-registration ...

299

Integrating Program Component Executables  

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

Integrating Integrating Program Component Executables on Distributed Memory Architectures via MPH Chris Ding and Yun He Computational Research Division, Lawrence Berkeley National Laboratory University of California, Berkeley, CA 94720, USA chqding@lbl.gov, yhe@lbl.gov Abstract A growing trend in developing large and complex ap- plications on today's Teraflop computers is to integrate stand-alone and/or semi-independent program components into a comprehensive simulation package. One example is the climate system model which consists of atmosphere, ocean, land-surface and sea-ice. Each component is semi- independent and has been developed at different institu- tions. We study how this multi-component multi-executable application can run effectively on distributed memory archi- tectures. We identify five effective execution modes and de- velop the MPH library to support

300

EIA - Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

7 7 Assumptions to the Annual Energy Outlook 2007 This report summarizes the major assumptions used in the NEMS to generate the AEO2007 projections. Contents (Complete Report) Download complete Report. Need help, contact the National Energy Information Center at 202-586-8800. Introduction Introduction Section to the Assumptions to the Annual Energy Outlook 2007 Report. Need help, contact the National Energy Information Center at 202-586-8800. Introduction Section to the Assumptions to the Annual Energy Outlook 2007 Report. Need help, contact the National Energy Information Center at 202-586-8800. Macroeconomic Activity Module Macroeconomic Activity Module Section to the Assumptions to the Annual Energy Outlook 2007 Report. Need help, contact the National Energy Information Center at 202-586-8800.

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

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2006 The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2006, DOE/EIA- M068(2006). 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. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

302

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2006 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.

303

Assumptions to the Annual Energy Outlook - Household Expenditures Module  

Gasoline and Diesel Fuel Update (EIA)

Household Expenditures Module Household Expenditures Module Assumption to the Annual Energy Outlook Household Expenditures Module Figure 5. United States Census Divisions. Having problems, call our National Energy Information Center at 202-586-8800 for help. The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and demographic characteristics, and consumption and expenditures for fuels for various end-uses. These data are combined with NEMS forecasts of household disposable income, fuel consumption, and fuel expenditures by end-use and household type. The HEM disaggregation algorithm uses these combined results to forecast household fuel consumption and expenditures by income quintile and Census Division (see

304

International Energy Outlook - Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface International Energy Outlook 2004 Preface This report presents international energy projections through 2025, prepared by the Energy Information Administration, including outlooks for major energy fuels and issues related to electricity and the environment. The International Energy Outlook 2004 (IEO2004) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2025. U.S. projections appearing in IEO2004 are consistent with those published in EIAÂ’s Annual Energy Outlook 2004 (AEO2004), which was prepared using the National Energy Modeling System (NEMS). IEO2004 is provided as a service to energy managers and analysts, both in government and in the private sector. The projections are used by international agencies, Federal and State governments, trade associations, and other planners and decisionmakers. They are published pursuant to the Department of Energy Organization Act of 1977 (Public Law 95-91), Section 205(c). The IEO2004 projections are based on U.S. and foreign government laws in effect on October 1, 2003.

305

TransForum v9n1 - Drivetrain Electrification Components  

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

(TTR) parallel hybrid showing placement of component technologies Energy storage systems, power electronics, electric machines and gearboxes and control systems are the four main...

306

U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Policy Analysts Policy Analysts This page features the most requested EIA reports and features for policy analysts. If you can't find what you're looking for, please contact the EIA Information Center. Featured Links Responses to Congressional and other requests Congressional testimony Analysis papers from Annual Energy Outlook Financial data and analysis Environmental data and analysis National Energy Modeling System (NEMS) documentation Energy in Brief Maps Featured Reports Annual Energy Outlook International Energy Outlook Short-Term Energy Outlook The Availability and Price of Petroleum and Petroleum Products Produced in Countries Other Than Iran Potential Impacts of Reductions in Refinery Activity on Northeast Petroleum Product Markets Effect of Increased Natural Gas Exports on Domestic Energy Markets

307

EIA - Annual Energy Outlook 2008 - Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface Annual Energy Outlook 2008 with Projections to 2030 Preface The Annual Energy Outlook 2008 (AEO2008), prepared by the Energy Information Administration (EIA), presents long-term projections of energy supply, demand, and prices through 2030. The projections are based on results from EIA’s National Energy Modeling System (NEMS). EIA published an “early release” version of the AEO2008 reference case in December 2007; however, the Energy Independence and Security Act of 2007 (EISA2007), which was enacted later that month, will have a major impact on energy markets, and given the year-long life of AEO2008 and its use as a baseline for analyses of proposed policy changes, EIA decided to update the reference case to reflect the provisions of EISA2007.

308

EIA - International Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

International Energy Outlook 2007 International Energy Outlook 2007 The International Energy Outlook 2007 (IEO2007) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2030. U.S. projections appearing in IEO2007 are consistent with those published in EIA's Annual Energy Outlook 2007 (AEO2007), which was prepared using the National Energy Modeling System (NEMS). The report is also released in print. Projection Tables Appendix A. Reference Case Appendix B. High Economic Growth Case Appendix C. Low Economic Growth Case Appendix D. High World Oil Price Case Appendix E. Low World Oil Price Case Appendix F. Reference Case Projections by End Use Appendix G. Projections of Petroleum and Other Liquids Productions in Three Cases

309

Annual Energy Outlook 1998 Forecasts - Preface  

Gasoline and Diesel Fuel Update (EIA)

1998 With Projections to 2020 1998 With Projections to 2020 Annual Energy Outlook 1999 Report will be Available on December 9, 1998 Preface The Annual Energy Outlook 1998 (AEO98) presents midterm forecasts of energy supply, demand, and prices through 2020 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA's National Energy Modeling System (NEMS). The report begins with an “Overview” summarizing the AEO98 reference case. The next section, “Legislation and Regulations,” describes the assumptions made with regard to laws that affect energy markets and discusses evolving legislative and regulatory issues. “Issues in Focus” discusses three current energy issues—electricity restructuring, renewable portfolio standards, and carbon emissions. It is followed by the analysis

310

Annual Energy Outlook with Projections to 2025  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the nnual Energy Outlook Assumptions to the nnual Energy Outlook EIA Glossary Assumptions to the Annual Energy Outlook 2004 Report #: DOE/EIA-0554(2004) Release date: February 2004 Next release date:February 2005 The Assumptions to the Annual Energy Outlook presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook. Table of Contents Introduction Macroeconomic Activity Module International Energy Module Household Expenditures Module Residential Demand Module Commercial Demand Module Industrial Demand Module Transportation Demand Module Electricity Market Module Oil and Gas Supply Module Natural Gas Transmission and Distribution Module Petroleum Market Module Coal Market Module Renewable Fuels Module Appendix A Adobe Acrobat Logo

311

Ceramic component for electrodes  

SciTech Connect

A ceramic component suitable for preparing MHD generator electrodes having the compositional formula: Y.sub.x (Mg.sub.y Cr.sub.z).sub.w Al.sub.(1-w) O.sub.3 where x=0.9 to 1.05, y=0.02 to 0.2, z=0.8 to 1.05 and w=1.0 to 0.5. The component is resistant to the formation of hydration products in an MHD environment, has good electrical conductivity and exhibits a lower electrochemical corrosion rate than do comparable compositions of lanthanum chromite.

Marchant, David D. (Richland, WA); Bates, J. Lambert (Richland, WA)

1980-01-01T23:59:59.000Z

312

Components in the Pipeline  

Science Conference Proceedings (OSTI)

Scientists commonly describe their data processing systems metaphorically as software pipelines. These pipelines input one or more data sources and apply a sequence of processing steps to transform the data and create useful results. While conceptually simple, pipelines often adopt complex topologies and must meet stringent quality of service requirements that place stress on the software infrastructure used to construct the pipeline. In this paper we describe the MeDICi Integration Framework, which is a component-based framework for constructing complex software pipelines. The framework supports composing pipelines from distributed heterogeneous software components and provides mechanisms for controlling qualities of service to meet demanding performance, reliability and communication requirements.

Gorton, Ian; Wynne, Adam S.; Liu, Yan (Jenny); Yin, Jian

2011-02-24T23:59:59.000Z

313

EIA - Assumptions to the Annual Energy Outlook 2009 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumptions to the Annual Energy Outlook 2009 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2009 (AEO2009),1 including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 The National Energy Modeling System The projections in the AEO2009 were produced with the NEMS, which is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the long term and perform policy analyses requested by decisionmakers in the White House, U.S. Congress, offices within the Department of Energy, including DOE Program Offices, and other government agencies. The Annual Energy Outlook (AEO) projections are also used by analysts and planners in other government agencies and outside organizations.

314

EIA - Assumptions to the Annual Energy Outlook 2010 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumptions to the Annual Energy Outlook 2010 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2010 [1] (AEO2010), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports [2]. The National Energy Modeling System The projections in the AEO2010 were produced with the NEMS, which is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the long term and perform policy analyses requested by decisionmakers in the White House, U.S. Congress, offices within the Department of Energy, including DOE Program Offices, and other government agencies. The Annual Energy Outlook (AEO) projections are also used by analysts and planners in other government agencies and outside organizations.

315

Annual energy outlook 1995, with projections to 2010  

Science Conference Proceedings (OSTI)

The Annual Energy Outlook 1995 (AEO95) presents the midterm energy forecasts of the Energy Information Administration (EIA). This year`s report presents projections and analyses of energy supply, demand, and prices through 2010, based on results from the National Energy Modeling System (NEMS). Quarterly forecasts of energy supply and demand for 1995 and 1996 are published in the Short-Term Energy Outlook (February 1995). Forecast tables for the five cases examined in the AEO95 are provided in Appendixes A through C. Appendix A gives historical data and forecasts for selected years from 1992 through 2010 for the reference case. Appendix B presents two additional cases, which assume higher and lower economic growth than the reference case. Appendix C presents two cases that assume higher and lower world oil prices. Appendix D presents a summary of the forecasts in units of oil equivalence. Appendix E presents a summary of household energy expenditures. Appendix F provides detailed comparisons of the AEO95 forecasts with those of other organizations. Appendix G briefly describes NEMS and the major AEO95 forecast assumptions. Appendix H presents a stand-alone high electricity demand case. Appendix 1 provides a table of energy conversion factors and a table of metric conversion factors. 89 figs., 23 tabs.

NONE

1995-01-01T23:59:59.000Z

316

NREL: Learning - Advanced Vehicle Systems and Components  

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

Advanced Vehicle Systems and Components Advanced Vehicle Systems and Components Photo of a man checking out an advanced battery using testing equipment that includes a long metal tube on a table top. NREL's researchers test new batteries developed for hybrid electric vehicles. Credit: Warren Gretz Researchers and engineers at the NREL work closely with those in the automotive industry to develop new technologies, such as advanced batteries, for storing energy in cars, trucks, and buses. They also help to develop and test new technologies for using that energy more efficiently. And they work on finding new, energy-efficient ways to reduce the amount of fuel needed to heat and cool the interiors, or cabins, of vehicles. To help develop these new technologies, NREL's researchers are improving the efficiency of vehicle systems and components like these:

317

Hybrid solar lighting systems and components - Energy ...  

... (Lenoir City, TN), Earl; Dennis D. (Knoxville, TN), Beshears; David L. (Knoxville, TN), Maxey; Lonnie C. (Powell, TN), Jordan; John K. (Oak Ridge, TN), ...

318

EIA - Annual Energy Outlook 2014 Early Release  

Gasoline and Diesel Fuel Update (EIA)

Acronyms Acronyms List of Acronyms AEO Annual Energy Outlook LDV Light-duty vehicle AEO2013 Annual Energy Outlook 2013 LED Light emitting diode AEO20014 Annual Energy Outlook 2014 LNG Liquefied natural gas ATRA American Taxpayer Relief Act of 2012 LPG Liquefied petroleum gases bbl Barrels LRG Liquefied refinery gases Btu British thermal units MATS Mercury and Air Toxics Standards CAFE Corporate Average Fuel Economy MECS Manufacturing Energy Consumption Survey CAIR Clean Air Interstate Rule MMbbl/d Million barrels per day CO2 Carbon dioxide MMBtu Million Btu CTL Coal-to-liquids MMst Million short tons DOE U.S. Department of Energy NEMS National Energy Modeling System E85 Motor fuel containing up to 85% ethanol NGL Natural gas liquids

319

Assumptions to the Annual Energy Outlook 2013  

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

Demand Module Demand Module This page inTenTionally lefT blank 27 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 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

320

Assumptions to the Annual Energy Outlook 2013  

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

Industrial Demand Module Industrial Demand Module This page inTenTionally lefT blank 53 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Industrial Demand Module The NEMS Industrial Demand Module (IDM) estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 non-manufacturing industries. The manufacturing industries are subdivided further 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. The non-manufacturing industries are modeled with less detail because processes are simpler and there is less available data. The petroleum refining

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


321

EIA - Assumptions to the Annual Energy Outlook 2008 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumptions to the Annual Energy Outlook 2008 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20081 (AEO2008), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 The National Energy Modeling System The projections in the AEO2008 were produced with the NEMS, which is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the long term and perform policy analyses requested by decisionmakers in the White House, U.S. Congress, offices within the Department of Energy, including DOE Program Offices, and other government agencies. The AEO projections are also used by analysts and planners in other government agencies and outside organizations.

322

BNL CRCR LEAF Components  

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

A detailed description of the LEAF facility is given in Rev. Sci. Inst. 75, A detailed description of the LEAF facility is given in Rev. Sci. Inst. 75, 4359-4366 (2004), which can be found by following this link. Accelerator System Components The LEAF facility layout indicates the locations of the laser system, the RF components, the electron gun and the beam lines. RF System The modulator cabinet and S-band (2.856 GHz) klystron are located in the laser room. A copper waveguide carries the 15 MW RF pulse from the klystron to the electron gun in the accelerator vault. (A klystron is a high-power RF amplifier. You can visit the ALS MicroWorlds site for more information on klystrons and the principles of RF particle acceleration.) Electron Gun Accelerator and Beam Line 5 psec beam line The electron gun (link to picture) is located in the southwest corner of

323

Component for thermoelectric generator  

DOE Patents (OSTI)

In a thermoelectric generator, a component comprises a ceramic insulator, having over limited areas thereof, each area corresponding to a terminal end of thermoelectric wires, a coating of a first metal which adheres to the insulator, and an electrical thermoelectric junction including a second metal which wets said first metal and adheres to said terminal ends but does not wet said insulator, and a cloth composed of electrically insulating threads interlaced with thermoelectric wires.

Purdy, David L. (Indiana, PA)

1977-01-01T23:59:59.000Z

324

Geothermal component test facility  

DOE Green Energy (OSTI)

A description is given of the East Mesa geothermal facility and the services provided. The facility provides for testing various types of geothermal energy-conversion equipment and materials under field conditions using geothermal fluids from three existing wells. (LBS)

Not Available

1976-04-01T23:59:59.000Z

325

Analysis & Projections - U.S. Energy Information Administration (EIA) -  

Gasoline and Diesel Fuel Update (EIA)

Tables Tables Appendix C-Map of NEMS Electricity Market Module Regions Updates Scenario Case Data With Without HCES HCES Reference case Nuclear low cost Nuclear high cost Renewable low cost Renewable high cost Natural gas low cost Natural gas high cost Coal low cost Coal high cost See interactive table viewer Analysis of Impacts of a Clean Energy Standard as requested by Chairman Hall Release date: October 25, 2011 Introduction This report responds to a request from Chairman Ralph M. Hall for an analysis of the impacts of a Clean Energy Standard (CES). The request, as outlined in the letter included in Appendix A, sets out specific

326

Assumptions to the Annual Energy Outlook - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumption to the Annual Energy Outlook Petroleum Market Module Figure 8. Petroleum Administration for Defense Districts. Having problems, call our National Energy Information Center at 202-586-8800 for help. The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohols, ethers, and bioesters natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of U.S. refining

327

Progress in photovoltaic system and component improvements  

DOE Green Energy (OSTI)

The Photovoltaic Manufacturing Technology (PVMaT) project is a partnership between the US government (through the US Department of Energy [DOE]) and the PV industry. Part of its purpose is to conduct manufacturing technology research and development to address the issues and opportunities identified by industry to advance photovoltaic (PV) systems and components. The project was initiated in 1990 and has been conducted in several phases to support the evolution of PV industrial manufacturing technology. Early phases of the project stressed PV module manufacturing. Starting with Phase 4A and continuing in Phase 5A, the goals were broadened to include improvement of component efficiency, energy storage and manufacturing and system or component integration to bring together all elements for a PV product. This paper summarizes PV manufacturers` accomplishments in components, system integration, and alternative manufacturing methods. Their approaches have resulted in improved hardware and PV system performance, better system compatibility, and new system capabilities. Results include new products such as Underwriters Laboratories (UL)-listed AC PV modules, modular inverters, and advanced inverter designs that use readily available and standard components. Work planned in Phase 5A1 includes integrated residential and commercial roof-top systems, PV systems with energy storage, and 300-Wac to 4-kWac inverters.

Thomas, H.P.; Kroposki, B.; McNutt, P.; Witt, C.E. [National Renewable Energy Lab., Golden, CO (United States); Bower, W.; Bonn, R.; Hund, T.D. [Sandia National Labs., Albuquerque, NM (United States)

1998-07-01T23:59:59.000Z

328

Progress in photovoltaic system and component improvements  

SciTech Connect

The Photovoltaic Manufacturing Technology (PVMaT) project is a partnership between the US government (through the US Department of Energy [DOE]) and the PV industry. Part of its purpose is to conduct manufacturing technology research and development to address the issues and opportunities identified by industry to advance photovoltaic (PV) systems and components. The project was initiated in 1990 and has been conducted in several phases to support the evolution of PV industrial manufacturing technology. Early phases of the project stressed PV module manufacturing. Starting with Phase 4A and continuing in Phase 5A, the goals were broadened to include improvement of component efficiency, energy storage and manufacturing and system or component integration to bring together all elements for a PV product. This paper summarizes PV manufacturers` accomplishments in components, system integration, and alternative manufacturing methods. Their approaches have resulted in improved hardware and PV system performance, better system compatibility, and new system capabilities. Results include new products such as Underwriters Laboratories (UL)-listed AC PV modules, modular inverters, and advanced inverter designs that use readily available and standard components. Work planned in Phase 5A1 includes integrated residential and commercial roof-top systems, PV systems with energy storage, and 300-Wac to 4-kWac inverters.

Thomas, H.P.; Kroposki, B.; McNutt, P.; Witt, C.E. [National Renewable Energy Lab., Golden, CO (United States); Bower, W.; Bonn, R.; Hund, T.D. [Sandia National Labs., Albuquerque, NM (United States)

1998-08-01T23:59:59.000Z

329

The National Energy Modeling System: An Overview 2003  

Gasoline and Diesel Fuel Update (EIA)

3) 3) The National Energy Modeling System: An Overview 2003 March 2003 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. This publication is on the WEB at: www.eia.doe.gov/oiaf/aeo/overview/index.html The National Energy Modeling System: An Overview 2003 provides a summary description of the National En- ergy Modeling System (NEMS), which was used to generate the forecasts of energy production, demand, im- ports, and

330

Efficient independent component analysis  

E-Print Network (OSTI)

Independent component analysis (ICA) has been widely used for blind source separation in many fields such as brain imaging analysis, signal processing and telecommunication. Many statistical techniques based on M-estimates have been proposed for estimating the mixing matrix. Recently several nonparametric methods have been developed but in-depth analysis on asymptotic efficiency has not been available. We analyze ICA using semiparametric theories and propose a straightforward estimate based on the efficient score function by using B-spline approximations. The estimate is asymptotically efficient under moderate conditions and exhibits better performance than standard ICA methods in a variety of simulations.

Chen, Aiyou

2006-01-01T23:59:59.000Z

331

Assumptions to the Annual Energy Outlook 2013  

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

Demand Module Demand Module This page inTenTionally lefT blank 39 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2040. 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.

332

Adaptive kernel principal component analysis  

Science Conference Proceedings (OSTI)

An adaptive kernel principal component analysis (AKPCA) method, which has the flexibility to accurately track the kernel principal components (KPC), is presented. The contribution of this paper may be divided into two parts. First, KPC are recursively ... Keywords: Adaptive method, Kernel principal component, Kernel principal component analysis, Non-stationary data, Recursive algorithm

Mingtao Ding; Zheng Tian; Haixia Xu

2010-05-01T23:59:59.000Z

333

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumptions to the Annual Energy Outlook 2006 Figure 7. Oil and Gas Supply Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply on a regional basis (Figure 7). A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2006), (Washington, DC, 2006). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum Market Module. The OGSM simulates the activity of numerous firms that produce oil and natural

334

Energy Information Directory of the Energy Information Administration  

U.S. Energy Information Administration (EIA)

Naval Petroleum and Oil Shale Reserves; NE; NECA; NEED; NEIC; NEMA; NEMS; NERC; NETL; NGSA; NHA; NIULPE; NLGI; NMA; NOAA; North American Electric Reliability ...

335

EIA - The National Energy Modeling System: An Overview 2003-Residential  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module The National Energy Modeling System: An Overview 2003 Residential Demand Module Figure 5. Residential Demand Module Structure. Need help, contact the National Energy Information Center at 202-586-8800. Residential Demand Module Table. Need help, contact the National Energy Information Center at 202-586-8800. NEMS Residential Module Equipment Summary Table. Need help, contact the National Energy Information Center at 202-586-8800. Characteristics of Selected Equipment Table. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version The 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

336

Building Energy Software Tools Directory: Green Energy Compass  

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

Whole Building Analysis Energy Simulation Load Calculation Renewable Energy Retrofit Analysis SustainabilityGreen Buildings Codes & Standards Materials, Components, Equipment, &...

337

Browse wiki | Open Energy Information  

Open Energy Info (EERE)

who execute the applicable Standard Contract-NEM. An Eligible Customer Generator is a residential, commercial, industrial or agricultural Customer who uses a...

338

Macroeconomic Activity Module (Mam) 1998 (Kernel Regression), Model Documentation  

Reports and Publications (EIA)

The Macroeconomic Activity Module (MAM) serves two functions within the National Energy Modeling System (NEMS). First, it provides consistent sets of baselines macroeconomic variables (GDP and components, aggregate prices, interest rates, industrial output, housing starts, commercial floorspace, newcar sales, etc.) which are used by the supply, demand and conversion modules in reaching an energy market equilibrium. Second, it is designed to provide a feedback mechanism that alters the baseline variables during the course of an integrated NEMS run.

Ron Earley

1998-10-01T23:59:59.000Z

339

Spectral Components Analysis of Diffuse Emission Processes  

Science Conference Proceedings (OSTI)

We develop a novel method to separate the components of a diffuse emission process based on an association with the energy spectra. Most of the existing methods use some information about the spatial distribution of components, e.g., closeness to an external template, independence of components etc., in order to separate them. In this paper we propose a method where one puts conditions on the spectra only. The advantages of our method are: 1) it is internal: the maps of the components are constructed as combinations of data in different energy bins, 2) the components may be correlated among each other, 3) the method is semi-blind: in many cases, it is sufficient to assume a functional form of the spectra and determine the parameters from a maximization of a likelihood function. As an example, we derive the CMB map and the foreground maps for seven yeas of WMAP data. In an Appendix, we present a generalization of the method, where one can also add a number of external templates.

Malyshev, Dmitry; /KIPAC, Menlo Park

2012-09-14T23:59:59.000Z

340

Energy  

Site Map; Printable Version; Share this resource. Send a link to Full Size Image - Energy Innovation Portalto someone by E-mail; Share Full Size Image - Energy ...

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

Plug-In Hybrid Electric Vehicles - PHEV Modeling - Component Technologies  

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

Technologies Impact on Fuel Efficiency Technologies Impact on Fuel Efficiency One of the main objectives of the U.S. Department of Energy's (DOE's) Plug-in Hybrid Electric Vehicle (PHEV) R&D Plan (2.2Mb pdf) is to "determine component development requirements" through simulation analysis. Overall fuel efficiency is affected by component technologies from a component sizing and efficiency aspect. To properly define component requirements, several technologies for each of the main components (energy storage, engine and electric machines) are being compared at Argonne using PSAT. Per the R&D plan, several Li-ion battery materials are being modeled to evaluate their impacts on fuel efficiency and vehicle mass. Different Power to Energy ratios are being considered to understand the relative impact of power and energy.

342

U.S. Energy Information Administration | Annual Energy Outlook Retrospective Review  

Gasoline and Diesel Fuel Update (EIA)

Energy Information Administration | Annual Energy Outlook Retrospective Review Energy Information Administration | Annual Energy Outlook Retrospective Review Annual Energy Outlook Retrospective Review Table 2. Summary of the number o fover-estimated results between AEO Reference cases and realized Outcomes All AEOs NEMS AEOs Percent of Projections Over-Estimated Percent of Projections Over-Estimated Table 3. Gross Domestic Product, (Average Cumulative Growth) Actual vs. Projected 24% 37% Table 4. World Oil Prices, Actual vs. Projected 52% 24% Table 5. Total Petroleum Consumption, Actual vs. Projected 44% 61% Table 6. Domestic Crude Oil Production, Actual vs. Projected 59% 65% Table 7. Petroleum Net Imports, Actual vs. Projected 56% 61% Table 8. Natural Gas Wellhead Prices, Actual vs. Projected 54% 23% Table 9. Total Natural Gas Consumption, Actual vs. Projected

343

IPE Energy | Open Energy Information  

Open Energy Info (EERE)

Jump to: navigation, search Name IPE Energy Place Barueri, Sao Paulo, Brazil Sector Hydro, Services Product Sao Paulo-based hydro turbine and components, builderengineering...

344

Consistent Interaction Of Software Components  

Science Conference Proceedings (OSTI)

Constructing complex software systems by integrating different software components is a promising and challenging approach. With the functionality of software components given by models it is possible to ensure consistency of such models before implementation ...

Gregor Engels; Jochen M. Küuster; Luuk Groenwegen

2002-12-01T23:59:59.000Z

345

Argonne TDC: Superconductive Components, Inc.  

Unlocking the Potential of High-Temperature Superconductors . Superconductive Components, Inc. Columbus, Ohio. For bulk applications of high-temperature ...

346

Security Components and Mechanisms Group  

Science Conference Proceedings (OSTI)

Security Components and Mechanisms Group. Welcome. ... A security checklist is a document that contains instructions for securely configuring … ...

2013-01-17T23:59:59.000Z

347

Assumptions to the Annual Energy Outlook 2001 - Natural Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market

348

Assumptions to the Annual Energy Outlook 2002 - Natural Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market

349

Specifying and checking component usage  

Science Conference Proceedings (OSTI)

One of today's challenges is producing reliable software in the face of an increasing number of interacting components. Our system CHET lets developers define specifications describing how a component should be used and checks these specifications in ... Keywords: automata, components, finite-state, flow analysis, specifications, verification

Steven P. Reiss

2005-09-01T23:59:59.000Z

350

Process management using component thermal-hydraulic function classes  

DOE Patents (OSTI)

A process management expert system where following malfunctioning of a component, such as a pump, for determining system realignment procedures such as for by-passing the malfunctioning component with on-line speeds to maintain operation of the process at full or partial capacity or to provide safe shut down of the system while isolating the malfunctioning component. The expert system uses thermal-hydraulic function classes at the component level for analyzing unanticipated as well as anticipated component malfunctions to provide recommended sequences of operator actions. Each component is classified according to its thermal-hydraulic function, and the generic and component-specific characteristics for that function. Using the diagnosis of the malfunctioning component and its thermal hydraulic class, the expert system analysis is carried out using generic thermal-hydraulic first principles. One aspect of the invention employs a qualitative physics-based forward search directed primarily downstream from the malfunctioning component in combination with a subsequent backward search directed primarily upstream from the serviced component. Generic classes of components are defined in the knowledge base according to the three thermal-hydraulic functions of mass, momentum and energy transfer and are used to determine possible realignment of component configurations in response to thermal-hydraulic function imbalance caused by the malfunctioning component. Each realignment to a new configuration produces the accompanying sequence of recommended operator actions. All possible new configurations are examined and a prioritized list of acceptable solutions is produced.

Morman, James A. (Woodridge, IL); Wei, Thomas Y. C. (Downers Grove, IL); Reifman, Jaques (Western Springs, IL)

1999-01-01T23:59:59.000Z

351

Process management using component thermal-hydraulic function classes  

DOE Patents (OSTI)

A process management expert system where following malfunctioning of a component, such as a pump, for determining system realignment procedures such as for by-passing the malfunctioning component with on-line speeds to maintain operation of the process at full or partial capacity or to provide safe shut down of the system while isolating the malfunctioning component. The expert system uses thermal-hydraulic function classes at the component level for analyzing unanticipated as well as anticipated component malfunctions to provide recommended sequences of operator actions. Each component is classified according to its thermal-hydraulic function, and the generic and component-specific characteristics for that function. Using the diagnosis of the malfunctioning component and its thermal hydraulic class, the expert system analysis is carried out using generic thermal-hydraulic first principles. One aspect of the invention employs a qualitative physics-based forward search directed primarily downstream from the malfunctioning component in combination with a subsequent backward search directed primarily upstream from the serviced component. Generic classes of components are defined in the knowledge base according to the three thermal-hydraulic functions of mass, momentum and energy transfer and are used to determine possible realignment of component configurations in response to thermal-hydraulic function imbalance caused by the malfunctioning component. Each realignment to a new configuration produces the accompanying sequence of recommended operator actions. All possible new configurations are examined and a prioritized list of acceptable solutions is produced. 5 figs.

Morman, J.A.; Wei, T.Y.C.; Reifman, J.

1999-07-27T23:59:59.000Z

352

Explorations of Novel Energy Conversion and Storage Systems  

E-Print Network (OSTI)

alternative energy sources. Hydrogen has been investigated to become a major component of world energy solutions

Duffin, Andrew Mark

2010-01-01T23:59:59.000Z

353

From Multi-Component Gas Streams Opportunity  

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

Separation of CO Separation of CO 2 From Multi-Component Gas Streams Opportunity Research is active on the patent-pending technology, titled "Apparatus and Process for the Separation of Gases Using Supersonic Expansion and Oblique Shock Wave Compression." This technology is available for licensing and/or further collaborative research from the U.S. Department of Energy's National Energy Technology Laboratory. Overview The separation of a gaseous mixture into constituent gases has proven to be useful for a variety of industrial and commercial applications. Currently CO 2 can be separated from multi- component gas streams using compression and refrigeration techniques in order to condense the CO 2 out of a vapor phase so that it can be mechanically separated from the stream.

354

Fast-Tracking Drivetrain Electrification - Component Technology Development  

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

The four main components used in drivetrain electrification The four main components used in drivetrain electrification are energy storage systems, power electronics, electric machines/gearboxes, and control systems. Argonne is actively pursuing increased performance and efficiency of these components along with reducing manufacturing costs. Cost reduction is addressed by reducing materials cost/ quantity, reducing labor/processing steps, increasing performance for the same components, and optimizing efficiency for the same materials cost. Energy Storage System Components Argonne has partnered with Maxwell Technologies to investigate the benefits of actively combining high power density ultracapacitors via power electronics with high energy density Li-Ion (or other future chemistry) batteries. This combination potentially reduces the net ESS cost and provides full acceleration and braking power at low

355

Energy  

Science Conference Proceedings (OSTI)

Energy. Summary: Key metrologies/systems: Scanning tunneling microscopy and one- and two-photon photoemission/Model ...

2012-10-02T23:59:59.000Z

356

Energy  

Home. Site Map; Printable Version; Share this resource. About; Search; Categories (15) Advanced Materials; Biomass and Biofuels; Building Energy Efficiency ...

357

Assumptions to the Annual Energy Outlook  

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, sport utility vehicles and vans), commercial light trucks (8501-10,000 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.

358

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

359

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].

360

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

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

Analysis & Projections - U.S. Energy Information Administration (EIA) -  

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

Technical Workshop on Behavior Economics Presentations Technical Workshop on Behavior Economics Presentations November 15, 2013 About the workshop The U.S. Department of Energy's Energy Information Administration (EIA) conducted a technical workshop on July 17, 2013 in Washington, D.C. to assess recent methodological developments in the field of behavioral economics as applied to energy demand analysis and energy efficiency programs. This meeting supports the EIA goal of updating its analytic assumptions and methods associated with the modeling of changing energy markets for purposes of public information and policy analysis. The National Energy Modeling System (NEMS) is the primary technical system used by EIA for domestic, long term forecasting and analysis. Ultimate objectives include enhancing the quality of EIA products through improved consumer behavior

362

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.

363

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.

364

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,

365

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

366

Table 11.4 Electricity: Components of Onsite Generation, 2002  

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

4 Electricity: Components of Onsite Generation, 2002;" 4 Electricity: Components of Onsite Generation, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Onsite-Generation Components;" " Unit: Million Kilowatthours." " ",,,"Renewable Energy" ,,,"(excluding Wood",,"RSE" "Economic","Total Onsite",,"and",,"Row" "Characteristic(a)","Generation","Cogeneration(b)","Other Biomass)(c)","Other(d)","Factors" ,"Total United States" "RSE Column Factors:",0.8,0.8,1.1,1.4 "Value of Shipments and Receipts"

367

Table 11.3 Electricity: Components of Onsite Generation, 2002  

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

3 Electricity: Components of Onsite Generation, 2002;" 3 Electricity: Components of Onsite Generation, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Onsite-Generation Components;" " Unit: Million Kilowatthours." " "," ",,,"Renewable Energy",," " " "," ",,,"(excluding Wood",,"RSE" "NAICS"," ","Total Onsite",,"and",,"Row" "Code(a)","Subsector and Industry","Generation","Cogeneration(b)","Other Biomass)(c)","Other(d)","Factors" ,,"Total United States" ,"RSE Column Factors:",0.9,0.8,1.1,1.3

368

Heavy Water Components Test Reactor Decommissioning - Major Component Removal  

SciTech Connect

The Heavy Water Components Test Reactor (HWCTR) facility (Figure 1) was built in 1961, operated from 1962 to 1964, and is located in the northwest quadrant of the Savannah River Site (SRS) approximately three miles from the site boundary. The HWCTR facility is on high, well-drained ground, about 30 meters above the water table. The HWCTR was a pressurized heavy water test reactor used to develop candidate fuel designs for heavy water power reactors. It was not a defense-related facility like the materials production reactors at SRS. The reactor was moderated with heavy water and was rated at 50 megawatts thermal power. In December of 1964, operations were terminated and the facility was placed in a standby condition as a result of the decision by the U.S. Atomic Energy Commission to redirect research and development work on heavy water power reactors to reactors cooled with organic materials. For about one year, site personnel maintained the facility in a standby status, and then retired the reactor in place. In 1965, fuel assemblies were removed, systems that contained heavy water were drained, fluid piping systems were drained, deenergized and disconnected and the spent fuel basin was drained and dried. The doors of the reactor facility were shut and it wasn't until 10 years later that decommissioning plans were considered and ultimately postponed due to budget constraints. In the early 1990s, DOE began planning to decommission HWCTR again. Yet, in the face of new budget constraints, DOE deferred dismantlement and placed HWCTR in an extended surveillance and maintenance mode. The doors of the reactor facility were welded shut to protect workers and discourage intruders. The $1.6 billion allocation from the American Recovery and Reinvestment Act to SRS for site clean up at SRS has opened the doors to the HWCTR again - this time for final decommissioning. During the lifetime of HWCTR, 36 different fuel assemblies were tested in the facility. Ten of these experienced cladding failures as operational capabilities of the different designs were being established. In addition, numerous spills of heavy water occurred within the facility. Currently, radiation and radioactive contamination levels are low within HWCTR with most of the radioactivity contained within the reactor vessel. There are no known insults to the environment, however with the increasing deterioration of the facility, the possibility exists that contamination could spread outside the facility if it is not decommissioned. An interior panoramic view of the ground floor elevation taken in August 2009 is shown in Figure 2. The foreground shows the transfer coffin followed by the reactor vessel and control rod drive platform in the center. Behind the reactor vessel is the fuel pool. Above the ground level are the polar crane and the emergency deluge tank at the top of the dome. Note the considerable rust and degradation of the components and the interior of the containment building. Alternative studies have concluded that the most environmentally safe, cost effective option for final decommissioning is to remove the reactor vessel, steam generators, and all equipment above grade including the dome. Characterization studies along with transport models have concluded that the remaining below grade equipment that is left in place including the transfer coffin will not contribute any significant contamination to the environment in the future. The below grade space will be grouted in place. A concrete cover will be placed over the remaining footprint and the groundwater will be monitored for an indefinite period to ensure compliance with environmental regulations. The schedule for completion of decommissioning is late FY2011. This paper describes the concepts planned in order to remove the major components including the dome, the reactor vessel (RV), the two steam generators (SG), and relocating the transfer coffin (TC).

Austin, W.; Brinkley, D.

2010-05-05T23:59:59.000Z

369

Heavy Water Components Test Reactor Decommissioning - Major Component Removal  

SciTech Connect

The Heavy Water Components Test Reactor (HWCTR) facility (Figure 1) was built in 1961, operated from 1962 to 1964, and is located in the northwest quadrant of the Savannah River Site (SRS) approximately three miles from the site boundary. The HWCTR facility is on high, well-drained ground, about 30 meters above the water table. The HWCTR was a pressurized heavy water test reactor used to develop candidate fuel designs for heavy water power reactors. It was not a defense-related facility like the materials production reactors at SRS. The reactor was moderated with heavy water and was rated at 50 megawatts thermal power. In December of 1964, operations were terminated and the facility was placed in a standby condition as a result of the decision by the U.S. Atomic Energy Commission to redirect research and development work on heavy water power reactors to reactors cooled with organic materials. For about one year, site personnel maintained the facility in a standby status, and then retired the reactor in place. In 1965, fuel assemblies were removed, systems that contained heavy water were drained, fluid piping systems were drained, deenergized and disconnected and the spent fuel basin was drained and dried. The doors of the reactor facility were shut and it wasn't until 10 years later that decommissioning plans were considered and ultimately postponed due to budget constraints. In the early 1990s, DOE began planning to decommission HWCTR again. Yet, in the face of new budget constraints, DOE deferred dismantlement and placed HWCTR in an extended surveillance and maintenance mode. The doors of the reactor facility were welded shut to protect workers and discourage intruders. The $1.6 billion allocation from the American Recovery and Reinvestment Act to SRS for site clean up at SRS has opened the doors to the HWCTR again - this time for final decommissioning. During the lifetime of HWCTR, 36 different fuel assemblies were tested in the facility. Ten of these experienced cladding failures as operational capabilities of the different designs were being established. In addition, numerous spills of heavy water occurred within the facility. Currently, radiation and radioactive contamination levels are low within HWCTR with most of the radioactivity contained within the reactor vessel. There are no known insults to the environment, however with the increasing deterioration of the facility, the possibility exists that contamination could spread outside the facility if it is not decommissioned. An interior panoramic view of the ground floor elevation taken in August 2009 is shown in Figure 2. The foreground shows the transfer coffin followed by the reactor vessel and control rod drive platform in the center. Behind the reactor vessel is the fuel pool. Above the ground level are the polar crane and the emergency deluge tank at the top of the dome. Note the considerable rust and degradation of the components and the interior of the containment building. Alternative studies have concluded that the most environmentally safe, cost effective option for final decommissioning is to remove the reactor vessel, steam generators, and all equipment above grade including the dome. Characterization studies along with transport models have concluded that the remaining below grade equipment that is left in place including the transfer coffin will not contribute any significant contamination to the environment in the future. The below grade space will be grouted in place. A concrete cover will be placed over the remaining footprint and the groundwater will be monitored for an indefinite period to ensure compliance with environmental regulations. The schedule for completion of decommissioning is late FY2011. This paper describes the concepts planned in order to remove the major components including the dome, the reactor vessel (RV), the two steam generators (SG), and relocating the transfer coffin (TC).

Austin, W.; Brinkley, D.

2010-05-05T23:59:59.000Z

370

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2003, DOE/EIA-M068(2003) April 2003. 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. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

371

ESS 2012 Peer Review - Component Research for Redox Flow Batteries...  

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

Battelle for the Department of Energy Component Research for Redox Flow Batteries Tom Zawodzinski and Che-Nan (Josh) Sun With help from Jamie Lawton, Zhijiang Tang, Doug Aaron,...

372

Component framework for coupled integrated fusion plasma simulation  

Science Conference Proceedings (OSTI)

Successful simulation of the complex physics that affect magnetically confined fusion plasma remains an important target milestone towards the development of viable fusion energy. Major advances in the underlying physics formulations, mathematical modeling, ... Keywords: components, coupled simulation, framework, fusion

Wael R. Elwasif; David E. Bernholdt; Lee A. Berry; Donald B. Batchelor

2007-10-01T23:59:59.000Z

373

Energy efficient data centers  

E-Print Network (OSTI)

operators, reliable building energy benchmark informationbenchmark the relative energy intensity of the various load components in a data center, several different, and often confusing, building

Tschudi, William; Xu, Tengfang; Sartor, Dale; Koomey, Jon; Nordman, Bruce; Sezgen, Osman

2004-01-01T23:59:59.000Z

374

Transportation Sector Model of the National Energy Modeling System. Volume 1  

SciTech Connect

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model. The NEMS Transportation Model comprises a series of semi-independent models which address different aspects of the transportation sector. The primary purpose of this model is to provide mid-term forecasts of transportation energy demand by fuel type including, but not limited to, motor gasoline, distillate, jet fuel, and alternative fuels (such as CNG) not commonly associated with transportation. The current NEMS forecast horizon extends to the year 2010 and uses 1990 as the base year. Forecasts are generated through the separate consideration of energy consumption within the various modes of transport, including: private and fleet light-duty vehicles; aircraft; marine, rail, and truck freight; and various modes with minor overall impacts, such as mass transit and recreational boating. This approach is useful in assessing the impacts of policy initiatives, legislative mandates which affect individual modes of travel, and technological developments. The model also provides forecasts of selected intermediate values which are generated in order to determine energy consumption. These elements include estimates of passenger travel demand by automobile, air, or mass transit; estimates of the efficiency with which that demand is met; projections of vehicle stocks and the penetration of new technologies; and estimates of the demand for freight transport which are linked to forecasts of industrial output. Following the estimation of energy demand, TRAN produces forecasts of vehicular emissions of the following pollutants by source: oxides of sulfur, oxides of nitrogen, total carbon, carbon dioxide, carbon monoxide, and volatile organic compounds.

NONE

1998-01-01T23:59:59.000Z

375

A fine-grained component-level power measurement method  

Science Conference Proceedings (OSTI)

The ever growing energy consumption of computer systems have become a more and more serious problem in the past few years. Power profiling is a fundamental way for us to better understand where, when and how energy is consumed. This paper presents a ... Keywords: energy efficiency, fine-grained component-level power measurement method, computer system energy consumption, power profiling, direct measurement method, power dissipation synchronization, program phase, SPEC CPU2006 benchmarks, fine time granularity, memory management, architecture design

Zehan Cui; Yan Zhu; Yungang Bao; Mingyu Chen

2011-07-01T23:59:59.000Z

376

Energy  

Science Conference Proceedings (OSTI)

There has been a significant progress in converting solar energy using silicon technology to replace fossil fuels. However, its high cost of production has led ...

377

Energy  

Efficient, Low-cost Microchannel Heat Exchanger. Return to Marketing Summary. Skip footer navigation to end of page. ... Energy Innovation Portal on Facebook;

378

Energy  

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

Energy Energy Energy Express Licensing Accelerator-Driven Transmutation Of Spent Fuel Elements Express Licensing Acid-catalyzed dehydrogenation of amine-boranes Express Licensing Air Breathing Direct Methanol Fuel Cell Express Licensing Aligned Crystalline Semiconducting Film On A Glass Substrate And Method Of Making Express Licensing Anion-Conducting Polymer, Composition, And Membrane Express Licensing Apparatus for Producing Voltage and Current Pulses Express Licensing Biaxially oriented film on flexible polymeric substrate Express Licensing Corrosion Test Cell For Bipolar Plates Express Licensing Device for hydrogen separation and method Negotiable Licensing Durable Fuel Cell Membrane Electrode Assembly (MEA) Express Licensing Energy Efficient Synthesis Of Boranes Express Licensing

379

Energy  

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

energy, including Fundamental advances in nuclear fuels Nonproliferation safeguards Reactor concepts Reactor waste disposition Animation of new reactor concept for deep space...

380

APS beamline standard components handbook  

SciTech Connect

It is clear that most Advanced Photon Source (APS) Collaborative Access Team (CAT) members would like to concentrate on designing specialized equipment related to their scientific programs rather than on routine or standard beamline components. Thus, an effort is in progress at the APS to identify standard and modular components of APS beamlines. Identifying standard components is a nontrivial task because these components should support diverse beamline objectives. To assist with this effort, the APS has obtained advice and help from a Beamline Standardization and Modularization Committee consisting of experts in beamline design, construction, and operation. The staff of the Experimental Facilities Division identified various components thought to be standard items for beamlines, regardless of the specific scientific objective of a particular beamline. A generic beamline layout formed the basis for this identification. This layout is based on a double-crystal monochromator as the first optical element, with the possibility of other elements to follow. Pre-engineering designs were then made of the identified standard components. The Beamline Standardization and Modularization Committee has reviewed these designs and provided very useful input regarding the specifications of these components. We realize that there will be other configurations that may require special or modified components. This Handbook in its current version (1.1) contains descriptions, specifications, and pre-engineering design drawings of these standard components. In the future, the APS plans to add engineering drawings of identified standard beamline components. Use of standard components should result in major cost reductions for CATs in the areas of beamline design and construction.

Kuzay, T.M.

1992-01-01T23:59:59.000Z

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

Assumptions to the Annual Energy Outlook 1999 - Footnotes  

Gasoline and Diesel Fuel Update (EIA)

footnote.gif (3505 bytes) footnote.gif (3505 bytes) [1] Energy Information Administration, Annual Energy Outlook 1999 (AEO99), DOE/EIA-0383(99), (Washington, DC, December 1998). [2] NEMS documentation reports are available on the EIA CD-ROM and the EIA Homepage (http://www.eia.gov/bookshelf.html). For ordering information on the CD-ROM, contact STAT-USA's toll free order number: 1-800-STAT-USA or by calling (202) 482-1986. [3] Energy Information Administration, The National Energy Modeling System: An Overview 1998, DOE/EIA-0581(98), (Washington, DC, February 1998). [4] The underlying macroeconomic growth cases use DRI/McGraw-HillÂ’s August 1998 T250898 and February TO250298 and TP250298. [5] EIA, International Energy Outlook 1998, DOE/EIA-0484(98) (Washington DC, April 1998).

382

EIA - Assumptions to the Annual Energy Outlook 2009 - Renewable Fuels  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module Assumptions to the Annual Energy Outlook 2009 Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for projections of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind1. Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was one of the first electric generation technologies, to newer power systems using biomass, geothermal, LFG, solar, and wind energy.

383

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

384

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

385

Annual Energy Outlook with Projections to 2025- Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface Preface The Annual Energy Outlook 2004 (AEO2004) presents midterm forecasts of energy supply, demand, and prices through 2025 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA's National Energy Modeling System (NEMS). The report begins with an "Overview" summarizing the AEO2004 reference case. The next section, "Legislation and Regulations," discusses evolving legislation and regulatory issues. "Issues in Focus" includes discussions of future labor productivity growth; lower 48 natural gas depletion and productive capacity; natural gas supply options, with a focus on liquefied natural gas; natural gas demand for Canadian oil sands production; National Petroleum Council forecasts for natural gas; natural gas consumption in the industrial and electric power sectors; nuclear power plant construction costs; renewable electricity tax credits; and U.S. greenhouse gas intensity. It is followed by a discussion of "Energy Market Trends."

386

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

387

Analysis & Projections - U.S. Energy Information Administration (EIA) -  

Gasoline and Diesel Fuel Update (EIA)

Summary Table Summary Table Appendix B-Estimating Price Impacts of the BCES12 Small Retailer Exemption Appendix C-Map of NEMS Electricity Market Module Regions Appendix D-Request Letter and Bill Updates Scenario Case Data Reference case Clean energy standard Clean energy standard, constrained nuclear See interactive table viewer Analysis of the Clean Energy Standard Act of 2012 Release date: May 2, 2012 Background This report responds to a request from Senator Jeff Bingaman, Chairman of the Senate Committee on Energy and Natural Resources, for an analysis of the Clean Energy Standard (CES) Act of 2012. The request letter and the text of the proposed legislation are provided in Appendix D. The request

388

Supervised probabilistic principal component analysis  

Science Conference Proceedings (OSTI)

Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When labels of data are available, e.g., in a classification or regression task, ... Keywords: dimensionality reduction, principal component analysis, semi-supervised projection, supervised projection

Shipeng Yu; Kai Yu; Volker Tresp; Hans-Peter Kriegel; Mingrui Wu

2006-08-01T23:59:59.000Z

389

Performance of Solar Facade Components  

E-Print Network (OSTI)

of these products by developing and applying appropriate methods for assessment of durability, reliability materials · Daylighting products · Solar protection devices (e.g., blinds) · PV windows · Solar collector components are investigated. Physical models are further developed that allow component performance

390

Macroencapsulation Equivalency Guidance for Classified Weapon Components and NNSSWAC Compliance  

Science Conference Proceedings (OSTI)

The U.S. Department of Energy (DOE) complex has a surplus of classified legacy weapon components generated over the years with no direct path for disposal. The majority of the components have been held for uncertainty of future use or no identified method of sanitization or disposal. As more weapons are retired, there is an increasing need to reduce the amount of components currently in storage or on hold. A process is currently underway to disposition and dispose of the legacy/retired weapons components across the DOE complex.

Poling, J.

2012-05-15T23:59:59.000Z

391

System diagnostics using qualitative analysis and component functional classification  

DOE Patents (OSTI)

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system.

Reifman, Jaques (Lisle, IL); Wei, Thomas Y. C. (Downers Grove, IL)

1993-01-01T23:59:59.000Z

392

System diagnostics using qualitative analysis and component functional classification  

DOE Patents (OSTI)

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system. 5 figures.

Reifman, J.; Wei, T.Y.C.

1993-11-23T23:59:59.000Z

393

Process management using component thermal-hydraulic function classes  

DOE Patents (OSTI)

A process management expert system for a nuclear, chemical or other process is effective following malfunctioning of a component, such as a pump, for determining system realignment procedures such as for by-passing the malfunctioning component with on-line speeds to maintain operation of the process at full or partial capacity or to provide safe shut down of the system while isolating the malfunctioning component. The expert system uses thermal-hydraulic function classes at the component level for analyzing unanticipated as well as anticipated component malfunctions to provide recommended sequences of operator actions. Each component is classified according to its thermal-hydraulic function, and the generic and component-specific characteristics for that function. Using the diagnosis of the malfunctioning component and its thermal hydraulic class, the expert system analysis is carried out using generic thermal-hydraulic first principles. One aspect of the invention employs a qualitative physics-based forward search directed primarily downstream from the malfunctioning component in combination with a subsequent backward search directed primarily upstream from the serviced component. Generic classes of components are defined in the knowledge base according to the three thermal-hydraulic functions of mass, momentum and energy transfer and are used to determine possible realignment of component configurations in response to thermal-hydraulic function imbalance caused by the malfunctioning component. The search process is based upon mass, momentum and energy conservation principles so that qualitative thermal-hydraulic fundamental principles are satisfied for new system configurations. Each realignment to a new configuration produces the accompanying sequence of recommended operator actions. All possible new configurations are examined and a prioritized list of acceptable solutions is produced.

Morman, James A.; Wei, Thomas Y.C.; Reifman, Jaques

1997-12-01T23:59:59.000Z

394

Investigations into High Temperature Components and Packaging  

SciTech Connect

The purpose of this report is to document the work that was performed at the Oak Ridge National Laboratory (ORNL) in support of the development of high temperature power electronics and components with monies remaining from the Semikron High Temperature Inverter Project managed by the National Energy Technology Laboratory (NETL). High temperature electronic components are needed to allow inverters to operate in more extreme operating conditions as required in advanced traction drive applications. The trend to try to eliminate secondary cooling loops and utilize the internal combustion (IC) cooling system, which operates with approximately 105 C water/ethylene glycol coolant at the output of the radiator, is necessary to further reduce vehicle costs and weight. The activity documented in this report includes development and testing of high temperature components, activities in support of high temperature testing, an assessment of several component packaging methods, and how elevated operating temperatures would impact their reliability. This report is organized with testing of new high temperature capacitors in Section 2 and testing of new 150 C junction temperature trench insulated gate bipolar transistor (IGBTs) in Section 3. Section 4 addresses some operational OPAL-GT information, which was necessary for developing module level tests. Section 5 summarizes calibration of equipment needed for the high temperature testing. Section 6 details some additional work that was funded on silicon carbide (SiC) device testing for high temperature use, and Section 7 is the complete text of a report funded from this effort summarizing packaging methods and their reliability issues for use in high temperature power electronics. Components were tested to evaluate the performance characteristics of the component at different operating temperatures. The temperature of the component is determined by the ambient temperature (i.e., temperature surrounding the device) plus the temperature increase inside the device due the internal heat that is generated due to conduction and switching losses. Capacitors and high current switches that are reliable and meet performance specifications over an increased temperature range are necessary to realize electronics needed for hybrid-electric vehicles (HEVs), fuel cell (FC) and plug-in HEVs (PHEVs). In addition to individual component level testing, it is necessary to evaluate and perform long term module level testing to ascertain the effects of high temperature operation on power electronics.

Marlino, L.D.; Seiber, L.E.; Scudiere, M.B.; M.S. Chinthavali, M.S.; McCluskey, F.P.

2007-12-31T23:59:59.000Z

395

MIT and Energy Industries MIT Industry Brief  

E-Print Network (OSTI)

Computational Physics Atmospheric Aerosols and Air Chemistry Behavior of Nuclear Fuels Computational Materials Fracture Mechanics MEMS and NEMS Multifunctional Materials Nanomaterials (Particles, Wires

Polz, Martin

396

Building Energy Software Tools Directory: LISA  

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

Energy Simulation Load Calculation Renewable Energy Retrofit Analysis SustainabilityGreen Buildings Codes & Standards Materials, Components, Equipment, & Systems Other...

397

Building Energy Software Tools Directory: TAPS  

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

Energy Simulation Load Calculation Renewable Energy Retrofit Analysis SustainabilityGreen Buildings Codes & Standards Materials, Components, Equipment, & Systems Other...

398

Building Energy Software Tools Directory: Evergreen LED  

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

Energy Simulation Load Calculation Renewable Energy Retrofit Analysis SustainabilityGreen Buildings Codes & Standards Materials, Components, Equipment, & Systems...

399

Assumptions to the Annual Energy Outlook - Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumption to the Annual Energy Outlook Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2004, DOE/EIA- M068(2004). 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. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

400

U.S. Energy Information Administration (EIA) - Sector  

Gasoline and Diesel Fuel Update (EIA)

NEMS overview and brief description of cases NEMS overview and brief description of cases Table E1. Summary of the AEO2013 cases Case name Description Reference Real GDP grows at an average annual rate of 2.5 percent from 2011 to 2040. Crude oil prices rise to about $163 per barrel (2011 dollars) in 2040. Complete projection tables in Appendix A. Low Economic Growth Real GDP grows at an average annual rate of 1.9 percent from 2011 to 2040. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B. High Economic Growth Real GDP grows at an average annual rate of 2.9 percent from 2011 to 2040. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B. Low Oil Price Low prices result from a combination of low demand for petroleum and other liquids in the non-OECD nations and higher global supply. Lower demand is measured by lower economic growth relative to the Reference case. On the supply side, OPEC increases its market share to 49 percent, and the costs of other liquids production technologies are lower than in the Reference case.Light, sweet crude oil prices fall to $75 per barrel in 2040. Partial projection tables in Appendix C.

Note: This page contains sample records for the topic "nems energy components" from the National Library of EnergyBeta (NLEBeta).
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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

Assumptions to the Annual Energy Outlook 2000 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2000, DOE/EIA-M060(2000) January 2000. The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2000, DOE/EIA-M060(2000) January 2000. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of coal production, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

402

EIA - Assumptions to the Annual Energy Outlook 2008 - Electricity Market  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2008 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2008, DOE/EIA-M068(2008). 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. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

403

U.S. Energy Information Administration (EIA) - Sector  

Gasoline and Diesel Fuel Update (EIA)

NEMS overview and brief description of cases NEMS overview and brief description of cases Table E1. Summary of the AEO2013 cases Case name Description Reference Real GDP grows at an average annual rate of 2.5 percent from 2011 to 2040. Crude oil prices rise to about $163 per barrel (2011 dollars) in 2040. Complete projection tables in Appendix A. Low Economic Growth Real GDP grows at an average annual rate of 1.9 percent from 2011 to 2040. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B. High Economic Growth Real GDP grows at an average annual rate of 2.9 percent from 2011 to 2040. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B. Low Oil Price Low prices result from a combination of low demand for petroleum and other liquids in the non-OECD nations and higher global supply. Lower demand is measured by lower economic growth relative to the Reference case. On the supply side, OPEC increases its market share to 49 percent, and the costs of other liquids production technologies are lower than in the Reference case.Light, sweet crude oil prices fall to $75 per barrel in 2040. Partial projection tables in Appendix C.

404

Inherently Reliable Boiler Component Design  

Science Conference Proceedings (OSTI)

This report summarizes the lessons learned during the last decade in efforts to improve the reliability and availability of boilers used in the production of electricity. The information in this report can assist in component modifications and new boiler designs.

2003-03-31T23:59:59.000Z

405

Binder Formulations Utilizing Furanic Components  

This technology describes the use of furanic components derived from agricultural waste streams, such as hydroxylmethylfurfural (HMF).  When used in combination with a phenolic urethane resin and cured with a gaseous amine catalyst, the resulting ...

406

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

407

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

408

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.

409

EIA - AEO2010 - State renewable energy requirements and goals: Update  

Gasoline and Diesel Fuel Update (EIA)

State renewable energy requirements and goals: Update through 2009 State renewable energy requirements and goals: Update through 2009 Annual Energy Outlook 2010 with Projections to 2035 State renewable energy requirements and goals: Update through 2009 To the extent possible, AEO2010 incorporates the impacts of State laws requiring the addition of renewable generation or capacity by utilities doing business in the States. Currently, 30 States and the District of Columbia have enforceable RPS or similar laws (Table 2). Under such standards, each State determines its own levels of generation, eligible technologies, and noncompliance penalties. AEO2010 includes the impacts of all laws in effect as of September 2009 (with the exception of Hawaii, because NEMS provides electricity market projections for the continental United States only).

410

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.

411

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.

412

U.S. Energy Information Administration (EIA) - Source  

Gasoline and Diesel Fuel Update (EIA)

Levelized Cost of New Generation Resources in the Annual Energy Outlook Levelized Cost of New Generation Resources in the Annual Energy Outlook 2011 This paper presents average national levelized costs for generating technologies that are brought on line in 20161 as represented in the National Energy Modeling System (NEMS) as configured for the Annual Energy Outlook 2011 (AEO2011) reference case.2 Levelized cost is often cited as a convenient summary measure of the overall competiveness of different generating technologies. Levelized cost represents the present value of the total cost of building and operating a generating plant over an assumed financial life and duty cycle, converted to equal annual payments and expressed in terms of real dollars to remove the impact of inflation. Levelized cost reflects overnight capital cost,

413

Annual Energy Outlook 2006 with Projections to 2030  

Gasoline and Diesel Fuel Update (EIA)

6 6 (AEO2006), pre- pared by the Energy Information Administration (EIA), presents long-term forecasts of energy supply, demand, and prices through 2030. The projections are based on results from EIA's National Energy Modeling System (NEMS). The report begins with an "Overview" summarizing the AEO2006 reference case and comparing it with the AEO2005 reference case. The next section, "Leg- islation and Regulations," discusses evolving legisla- tion and regulatory issues, including recently enacted legislation and regulation, such as the Energy Policy Act of 2005, and some that are proposed. "Issues in Focus" includes a discussion of the basis of EIA's sub- stantial revision of the world oil price trend used in the projections. It also examines the following topics: implications of higher oil price expectations for eco- nomic growth; differences

414

The impacts on U.S. energy markets and the economy of reducing oil imports. Service report  

SciTech Connect

The General Accounting Office (GAO) has responded to a request from Representative John Kasich by requesting that the Energy Information Administration (EIA) use the National Energy Modeling System (NEMS) to estimate the cost to the U.S. economy of reducing oil imports. The analysis summarized by this paper focuses on two approaches toward a target reduction in oil imports: (1) a set of cases with alternative world crude oil price trajectories, and (2) two cases which investigates the use of an oil import fee.

1996-09-01T23:59:59.000Z

415

Energy  

Office of Legacy Management (LM)

..) ".. ..) ".. _,; ,' . ' , ,; Depar?.me.nt ,of.' Energy Washington; DC 20585 : . ' , - $$ o"\ ' ~' ,' DEC ?;$ ;y4,,, ~ ' .~ The Honorable John Kalwitz , 200 E. Wells Street Milwaukee, W~isconsin 53202, . . i :. Dear,Mayor 'Kalwitz: " . " Secretary of Energy Hazel' O'Leary has announceha new,approach 'to,openness in " the Department of Ene~rgy (DOE) and its communications with'the public. In -. support of~this initiative, we areipleased to forward the enclosed information related to the Milwaukee Ai.rport site in your jurisdiction that performed work, for DOE orits predecessor agencies. information; use, and retention. ., This information .is provided for your '/ ,' DOE's Formerly Utilized Sites Remedial:'Action~'Prog&is responsible for ,"'

416

Superplastic forming of stainless steel automotive components  

DOE Green Energy (OSTI)

Exhaust emission standards are governmentally controlled standards, which are increasingly stringent, forcing alternate strategies to meet these standards. One approach to improve the efficiency of the exhaust emission equipment is to decrease the time required to get the catalytic converter to optimum operating temperature. To accomplish this, automotive manufacturers are using double wall stainless steel exhaust manifolds to reduce heat loss of the exhaust gases to the converter. The current method to manufacture double wall stainless steel exhaust components is to use a low-cost alloy with good forming properties and extensively form, cut, assemble, and weld the pieces. Superplastic forming (SPF) technology along with alloy improvements has potential at making this process more cost effective. Lockheed Martin Energy Systems (LMES), Lawrence Livermore National Laboratory (LLNL) and USCAR Low Emission Partnership (LEP) worked under a Cooperative Research And Development Agreement (CRADA) to evaluate material properties, SPF behavior, and welding behavior of duplex stainless steel alloy for automotive component manufacturing. Battelle Pacific Northwest National Laboratory (PNNL) has a separate CRADA with the LEP to use SPF technology to manufacture a double wall stainless steel exhaust component. As a team these CRADAs developed and demonstrated a technical plan to accomplish making double wall stainless steel exhaust manifolds.

Bridges, B. [Lockheed Martin Energy Systems, Inc., Oak Ridge, TN (United States); Elmer, J. [Lawrence Livermore National Lab., CA (United States); Carol, L. [AC Delco Systems World Headquarters, Flint, MI (United States). USCAR Low Emissions Technology Research and Development Partnership

1997-02-06T23:59:59.000Z

417

Automated cleaning of electronic components  

SciTech Connect

Environmental and operator safety concerns are leading to the elimination of trichloroethylene and chlorofluorocarbon solvents in cleaning processes that remove rosin flux, organic and inorganic contamination, and particulates from electronic components. Present processes depend heavily on these solvents for manual spray cleaning of small components and subassemblies. Use of alternative solvent systems can lead to longer processing times and reduced quality. Automated spray cleaning can improve the quality of the cleaning process, thus enabling the productive use of environmentally conscious materials, while minimizing personnel exposure to hazardous materials. We describe the development of a prototype robotic system for cleaning electronic components in a spray cleaning workcell. An important feature of the prototype system is the capability to generate the robot paths and motions automatically from the CAD models of the part to be cleaned, and to embed cleaning process knowledge into the automatically programmed operations.

Drotning, W.; Meirans, L.; Wapman, W.; Hwang, Y.; Koenig, L.; Petterson, B.

1994-07-01T23:59:59.000Z

418

Progress in photovoltaic components and systems  

DOE Green Energy (OSTI)

The Photovoltaic Manufacturing Research and Development project is a government/industry partnership between the U.S. Department of Energy and members of the U.S. photovoltaic (PV) industry. The purpose of the project is to work with industry to improve manufacturing processes, reduce manufacturing costs, and improve the performance of PV products. This project is conducted through phased solicitations with industry participants selected through a competitive evaluation process. Starting in 1995, the two most recent solicitations include manufacturing improvements for balance-of-system (BOS) components, energy storage, and PV system design improvements. This paper surveys the work accomplished since that time, as well as BOS work currently in progress in the PV Manufacturing R&D project to identify areas of continued interest and product trends. Industry participants continue to work to improve inverters and to expand the features and capabilities of this key component. The industry also continues to advance fully integrated systems that meet standards for performance and safety. All participants included manufacturing improvements to reduce costs and improve reliability. Accomplishments of the project's participants are summarized to illustrate the product and manufacturing trends.

Thomas, H.; Kroposki, B.; Witt, C.; Bower, W.

2000-05-05T23:59:59.000Z

419

Progress in Photovoltaic Components and Systems  

DOE Green Energy (OSTI)

The Photovoltaic Manufacturing Research and Development project is a government/industry partnership between the US Department of Energy and members of the US photovoltaic (TV) industry. The purpose of the project is to work with industry to improve manufacturing processes, reduce manufacturing costs, and improve the performance of PV products. This project is conducted through phased solicitations with industry participants selected through a competitive evaluation process. Starting in 1995, the two most recent solicitations include manufacturing improvements for balance-of-system (BOS) components, energy storage, and PV system design improvements. This paper surveys the work accomplished since that time, as well as BOS work currently in progress in the PV Manufacturing R and D project to identify areas of continued interest and product trends. Industry participants continue to work to improve inverters and to expand the features and capabilities of this key component. The industry also continues to advance fully integrated systems that meet standards for performance and safety. All participants included manufacturing improvements to reduce costs and improve reliability. Accomplishments of the project's participants are summarized to illustrate the product and manufacturing trends.

THOMAS,H.; KROPOSKI,B.; WITT,C.; BOWER,WARD I.

2000-07-15T23:59:59.000Z

420

The National Energy Modeling System: An Overview 1998 - Carbon Emissions  

Gasoline and Diesel Fuel Update (EIA)

CARBON EMISSIONS CARBON EMISSIONS A part of the integrating module, the carbon emissions submodule (CEM) computes the carbon emissions due to the combustion of energy. The coefficients for carbon emissions are derived from Energy Information Administration, Emissions of Greenhouse Gases in the United States 1996, published in October 1997. The calculations account for the fact that some fossil fuels are used for nonfuel purposes, such as feedstocks, and thus the carbon in the fuel is sequestered in the end product. CEM also allows for several carbon policy evaluation options to be imposed within NEMS. Although none of the policy options are assumed in the Annual Energy Outlook 1998, the options can be used in special analyses to simulate potential market-based approaches to meet national carbon emission

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

EIA - Assumptions to the Annual Energy Outlook 2009 - Electricity Market  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2009 Electricity Market Module figure 6. Electricity Market Model Supply Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2009, DOE/EIA-M068(2009). Based on fuel prices and electricity demands provided by the other modules

422

U.S. Energy Information Administration (EIA) - Source  

Gasoline and Diesel Fuel Update (EIA)

available in PDF available in PDF Levelized Cost of New Generation Resources in the Annual Energy Outlook 2012 Release date: July 12, 2012 This paper presents average levelized costs for generating technologies that are brought on line in 20171 as represented in the National Energy Modeling System (NEMS) for the Annual Energy Outlook 2012 (AEO2012) reference case.2 Levelized cost is often cited as a convenient summary measure of the overall competiveness of different generating technologies. It represents the per-kilowatthour cost (in real dollars) of building and operating a generating plant over an assumed financial life and duty cycle. Key inputs to calculating levelized costs include overnight capital costs, fuel costs, fixed and variable operations and maintenance (O&M) costs, financing costs,

423

Assumptions to the Annual Energy Outlook 2002 - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has five submodules representing various renewable energy sources, biomass, geothermal, landfill gas, solar, and wind; a sixth renewable, conventional hydroelectric power, is represented in the Electricity Market Module (EMM).117 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration,

424

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

425

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.

426

Assumptions to the Annual Energy Outlook 2001 - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has five submodules representing various renewable energy sources, biomass, geothermal, landfill gas, solar, and wind; a sixth renewable, conventional hydroelectric power, is represented in the Electricity Market Module (EMM).112 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration,

427

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.

428

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

429

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

430

The CCSM4 Ocean Component  

Science Conference Proceedings (OSTI)

The ocean component of the Community Climate System Model version 4 (CCSM4) is described, and its solutions from the twentieth-century (20C) simulations are documented in comparison with observations and those of CCSM3. The improvements to the ...

Gokhan Danabasoglu; Susan C. Bates; Bruce P. Briegleb; Steven R. Jayne; Markus Jochum; William G. Large; Synte Peacock; Steve G. Yeager

2012-03-01T23:59:59.000Z

431

Automotive Component Product Development Enhancement  

E-Print Network (OSTI)

Optimization In an Integrated Concurrent Engineering Framework by Massimo Usan M. S. Aeronautical Engineering of the Requirements for the Degree of Master of Science in Engineering and Management at the Massachusetts Institute Engineering Systems Division #12;Automotive Component Product Development Enhancement Through Multi

432

Large Component Removal/Disposal  

Science Conference Proceedings (OSTI)

This paper describes the removal and disposal of the large components from Maine Yankee Atomic Power Plant. The large components discussed include the three steam generators, pressurizer, and reactor pressure vessel. Two separate Exemption Requests, which included radiological characterizations, shielding evaluations, structural evaluations and transportation plans, were prepared and issued to the DOT for approval to ship these components; the first was for the three steam generators and one pressurizer, the second was for the reactor pressure vessel. Both Exemption Requests were submitted to the DOT in November 1999. The DOT approved the Exemption Requests in May and July of 2000, respectively. The steam generators and pressurizer have been removed from Maine Yankee and shipped to the processing facility. They were removed from Maine Yankee's Containment Building, loaded onto specially designed skid assemblies, transported onto two separate barges, tied down to the barges, th en shipped 2750 miles to Memphis, Tennessee for processing. The Reactor Pressure Vessel Removal Project is currently under way and scheduled to be completed by Fall of 2002. The planning, preparation and removal of these large components has required extensive efforts in planning and implementation on the part of all parties involved.

Wheeler, D. M.

2002-02-27T23:59:59.000Z

433

Component-based LR parsing  

Science Conference Proceedings (OSTI)

A language implementation with proper compositionality enables a compiler developer to divide-and-conquer the complexity of building a large language by constructing a set of smaller languages. Ideally, these small language implementations should be ... Keywords: Component-based software development, LR parsing, Parser generator

Xiaoqing Wu; Barrett R. Bryant; Jeff Gray; Marjan Mernik

2010-04-01T23:59:59.000Z

434

MCFC component development at ANL.  

DOE Green Energy (OSTI)

Argonne National Laboratory is developing advanced cathode and electrolyte components for the molten carbonate fuel cell (MCFC). Working in support of the MCFC developers, the goal of this effort is to extend the life of the MCFC cell and to improve its performance.

Bloom, I.

1998-09-15T23:59:59.000Z

435

Integrity of neutron-absorbing components of LWR fuel systems  

Science Conference Proceedings (OSTI)

A study of the integrity and behavior of neutron-absorbing components of light-water (LWR) fuel systems was performed by Pacific Northwest Laboratory (PNL) and sponsored by the US Department of Energy (DOE). The components studies include control blades (cruciforms) for boiling-water reactors (BWRs) and rod cluster control assemblies for pressurized-water reactors (PWRs). The results of this study can be useful for understanding the degradation of neutron-absorbing components and for waste management planning and repository design. The report includes examples of the types of degradation, damage, or failures that have been encountered. Conclusions and recommendations are listed. 84 refs.

Bailey, W.J.; Berting, F.M.

1991-03-01T23:59:59.000Z

436

Dark Energy  

E-Print Network (OSTI)

After some remarks about the history and the mystery of the vacuum energy I shall review the current evidence for a cosmologically significant nearly homogeneous exotic energy density with negative pressure (`Dark Energy'). Special emphasis will be put on the recent polarization measurements by WMAP and their implications. I shall conclude by addressing the question: Do the current observations really imply the existence of a dominant dark energy component?

Norbert Straumann

2003-11-26T23:59:59.000Z

437

Field Comparisons of Direct and Component Measurements of Net Radiation under Clear Skies  

Science Conference Proceedings (OSTI)

Accurate measurements of net radiation are basic to all studies of the surface energy budget. In preparation for an energy budget experiment significant differences were found between direct and component measurement of net radiation, which ...

Claude E. Duchon; Gregory E. Wilk

1994-02-01T23:59:59.000Z

438

Renewable Energy Asia Group Ltd REA | Open Energy Information  

Open Energy Info (EERE)

Asia Group Ltd REA Jump to: navigation, search Name Renewable Energy Asia Group Ltd (REA) Place China Sector Wind energy Product Singaporean wind turbine component and system...

439

Residential energy gateway system in smart grid.  

E-Print Network (OSTI)

??This project discusses about the residential energy gateway in the Smart Grid. A residential energy gateway is a critical component in the Home Energy Management… (more)

Thirumurthy, Vinod Govindswamy

2010-01-01T23:59:59.000Z

440

,,,,,,"Coal Components",,,"Coke",,,"Electricity Components",,,,,,,,,,,,,,"Natural Gas Components",,,"Steam Components"  

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

2 Relative Standard Errors for Table 7.2;" 2 Relative Standard Errors for Table 7.2;" " Unit: Percents." ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"Selected Wood and Other Biomass Components" ,,,,,,"Coal Components",,,"Coke",,,"Electricity Components",,,,,,,,,,,,,,"Natural Gas Components",,,"Steam Components" " "," ",,,,,,,,,,,,,"Total",,,,,,,,,,,,,,,,,,,,,,,"Wood Residues",,,," " " "," "," ",,,,,"Bituminous",,,,,,"Electricity","Diesel Fuel",,,,,,"Motor",,,,,,,"Natural Gas",,,"Steam",,,," ",,,"and","Wood-Related","All"

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

,,,,,,"Coal Components",,,"Coke",,,"Electricity Components",,,,,,,,,,,,,,"Natural Gas Components",,,"Steam Components"  

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

Relative Standard Errors for Table 7.1;" Relative Standard Errors for Table 7.1;" " Unit: Percents." ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"Selected Wood and Other Biomass Components" ,,,,,,"Coal Components",,,"Coke",,,"Electricity Components",,,,,,,,,,,,,,"Natural Gas Components",,,"Steam Components" " "," ",,,,,,,,,,,,,"Total",,,,,,,,,,,,,,,,,,,,,,,"Wood Residues",,,," " " "," "," ",,,,,"Bituminous",,,,,,"Electricity","Diesel Fuel",,,,,,"Motor",,,,,,,"Natural Gas",,,"Steam",,,," ",,,"and","Wood-Related","All"

442

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface This report presents international energy projections through 2025, prepared by the Energy Information Administration, including outlooks for major energy fuels and associated carbon dioxide emissions. The International Energy Outlook 2005 (IEO2005) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2025. U.S. projections appearing in IEO2005 are consistent with those published in EIAÂ’s Annual Energy Outlook 2005 (AEO2005), which was prepared using the National Energy Modeling System (NEMS). Although the IEO typically uses the same reference case as the AEO, IEO2005 has adopted the October futures case from AEO2005 as its reference case for the United States. The October futures case, which has an assumption of higher world oil prices than the AEO2005 reference case, now appears to be a more likely projection. The reference case prices will be reconsidered for the next AEO. Based on information available as of July 2005, the AEO2006 reference case will likely reflect world oil prices higher than those in the IEO2005 reference case.

443

Infrared Debonding - Energy Innovation Portal  

Building Energy Efficiency; Electricity Transmission; ... Solar Thermal; Startup America; ... Benefits • Materials or components are not damaged or abraded, ...

444

Nonthermal effects in two component DT fusion reactors  

SciTech Connect

Net energy generation rates and f-factors are calculated for a variety of two component DT reactor configurations using a computer code that follows the energy distributions of the reactants and products explicitly, utilizing the Fokker--Planck approximation for low-angle Coulomb scattering and a transfer matrix for high-angle Coulomb, nuclear, and radiative processes. The relative importance of such non-thermal effects as alpha particle deposition, non- Maxwellian energy distributions for the target tritons and electrons, and the influence of high-angle Coulomb and nuclear scattering on the energy loss rate of the injected deuterons is explicitly assessed. (auth)

Weaver, T.A.; Chu, T.C.

1975-11-01T23:59:59.000Z

445

Household Vehicles Energy Consumption  

Reports and Publications (EIA)

This report provides newly available national and regional data and analyzes the nation's energy use by light-duty vehicles. This release represents the analytical component of the report, with a data component having been released in early 2005.

Mark Schipper

2005-11-30T23:59:59.000Z

446

Nuclear component horizontal seismic restraint  

DOE Patents (OSTI)

A nuclear component horizontal seismic restraint. Small gaps limit horizontal displacement of components during a seismic occurrence and therefore reduce dynamic loadings on the free lower end. The reactor vessel and reactor guard vessel use thicker section roll-forged rings welded between the vessel straight shell sections and the bottom hemispherical head sections. The inside of the reactor guard vessel ring forging contains local vertical dovetail slots and upper ledge pockets to mount and retain field fitted and installed blocks. As an option, the horizontal displacement of the reactor vessel core support cone can be limited by including shop fitted/installed local blocks in opposing alignment with the reactor vessel forged ring. Beams embedded in the wall of the reactor building protrude into apertures in the thermal insulation shell adjacent the reactor guard vessel ring and have motion limit blocks attached thereto to provide to a predetermined clearance between the blocks and reactor guard vessel ring.

Snyder, Glenn J. (Lynchburg, VA)

1988-01-01T23:59:59.000Z

447

Energy Sources | Department of Energy  

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

Renewable Energy Pilot Program Renewable Energy Pilot Program In June 2010, the Louisiana Public Service Commission (LPSC) unanimously approved a Renewable Energy Pilot Program for the state. The final implementation plan was adopted in November 2010. The goal of the pilot program is to determine whether a renewable portfolio standard is suitable for Louisiana. The pilot program has two major components: the Research Component and the Request for Proposal (RFP) Component. October 16, 2013 Renewable Energy Goal In May 2010, Oklahoma established a renewable energy goal for electric utilities operating in the state. The goal calls for 15% of the total installed generation capacity in Oklahoma to be derived from renewable sources by 2015. There are no interim targets, and the goal does not extend

448

The National Energy Modeling System: An Overview 1998 - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

NATURAL GAS TRANSMISSION AND DISTRIBUTION MODULE NATURAL GAS TRANSMISSION AND DISTRIBUTION MODULE blueball.gif (205 bytes) Annual Flow Submodule blueball.gif (205 bytes) Capacity Expansion Submodule blueball.gif (205 bytes) Pipeline Tariff Submodule blueball.gif (205 bytes) Distributor Tariff Submodule The natural gas transmission and distribution module (NGTDM) is the component of NEMS that represents the natural gas market. The NGTDM models the natural gas transmission and distribution network in the lower 48 States, which links suppliers (including importers) and consumers of natural gas. The module determines regional market-clearing prices for natural gas supplies (including border prices) and end-use consumption. The NGTDM has four primary submodules: the annual flow submodule, the capacity expansion submodule, the pipeline tariff submodule, and the

449

EERE Postdoctoral Research Awards: Application Components  

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

Application Components to someone by E-mail Share EERE Postdoctoral Research Awards: Application Components on Facebook Tweet about EERE Postdoctoral Research Awards: Application...

450

International energy outlook 1995, May 1995  

SciTech Connect

The International Energy Outlook 1995 (IEO95) presents an assessment by the Energy Information Administration (EIA) of the international energy market outlook through 2010. The report is an extension of the EIA`s Annual Energy Outlook 1995 (AEO95), which was prepared using the National Energy Modeling System (NEMS). US projections appearing in the IEO95 are consistent with those published in the AEO95. IEO95 is provided as a statistical service to energy managers and analysts, both in government and in the private sector. The projects are used by international agencies, Federal and State governments, trade associations, and other planners and decisionmakers. They are published pursuant to the Department of energy Organization Act of 1977 (Public Law 95-91), Section 295(c). The IEO95 projections are based on US and foreign government policies in effect on October 1, 1994. IEO95 displays projections according to six basic country groupings. The regionalization has changed since last year`s report. Mexico has been added to the Organization for Economic Cooperation and Development (OECD), and a more detailed regionalization has been incorporated for the remainder of the world, including the following subgroups: non-OECD Asia, Africa, Middle East, and Central and South America. China is included in non-OECD Asia. Eastern Europe and the former Soviet Union are combined in the EE/FSU subgroup.

NONE

1995-06-01T23:59:59.000Z

451

Virtual enterprise model for the electronic components business in the Nuclear Weapons Complex  

Science Conference Proceedings (OSTI)

The electronic components business within the Nuclear Weapons Complex spans organizational and Department of Energy contractor boundaries. An assessment of the current processes indicates a need for fundamentally changing the way electronic components are developed, procured, and manufactured. A model is provided based on a virtual enterprise that recognizes distinctive competencies within the Nuclear Weapons Complex and at the vendors. The model incorporates changes that reduce component delivery cycle time and improve cost effectiveness while delivering components of the appropriate quality.

Ferguson, T.J.; Long, K.S.; Sayre, J.A. [Sandia National Labs., Albuquerque, NM (United States); Hull, A.L. [Sandia National Labs., Livermore, CA (United States); Carey, D.A.; Sim, J.R.; Smith, M.G. [Allied-Signal Aerospace Co., Kansas City, MO (United States). Kansas City Div.

1994-08-01T23:59:59.000Z

452

Thermal Systems Process and Components Laboratory (Fact Sheet)  

DOE Green Energy (OSTI)

This fact sheet describes the purpose, lab specifications, applications scenarios, and information on how to partner with NREL's Thermal Systems Process and Components Laboratory at the Energy Systems Integration Facility. The focus of the Thermal Systems Process and Components Laboratory at NREL's Energy Systems Integration Facility (ESIF) is to research, develop, test, and evaluate new techniques for thermal energy storage systems that are relevant to utility-scale concentrating solar power plants. The laboratory holds test systems that can provide heat transfer fluids for the evaluation of heat exchangers and thermal energy storage devices. The existing system provides molten salt at temperatures up to 800 C. This unit is charged with nitrate salt rated to 600 C, but is capable of handling other heat transfer fluid compositions. Three additional test bays are available for future deployment of alternative heat transfer fluids such as hot air, carbon dioxide, or steam systems. The Thermal Systems Process and Components Laboratory performs pilot-scale thermal energy storage system testing through multiple charge and discharge cycles to evaluate heat exchanger performance and storage efficiency. The laboratory equipment can also be utilized to test instrument and sensor compatibility with hot heat transfer fluids. Future applications in the laboratory may include the evaluation of thermal energy storage systems designed to operate with supercritical heat transfer fluids such as steam or carbon dioxide. These tests will require the installation of test systems capable of providing supercritical fluids at temperatures up to 700 C.

Not Available

2011-10-01T23:59:59.000Z

453

EIA - Assumptions to the Annual Energy Outlook 2008 - Petroleum Market  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumptions to the Annual Energy Outlook 2008 Petroleum Market Module Figure 9. Petroleum Administration for Defense Districts. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Petroleum Market Module (PMM) projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, unfinished oil imports, other refinery inputs (including alcohols, ethers, bioesters, corn, biomass, and coal), natural gas plant liquids production, and refinery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic refineries. The PMM contains a linear programming (LP) representation of U.S. refining

454

Small Wind Energy Policy Making in the States: Lessons for a Shifting Energy Landscape.  

E-Print Network (OSTI)

??A key component of climate change policy is the promotion of alternative energy sources. Among renewable energy technologies wind energy represents an important source of… (more)

Wiener, Joshua G.

2009-01-01T23:59:59.000Z

455

Multi-component Removal in Flue Gas by Aqua Ammonia  

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

component Removal in Flue Gas by Aqua Ammonia component Removal in Flue Gas by Aqua Ammonia Opportunity The Department of Energy's National Energy Technology Laboratory is seeking licensing partners interested in implementing United States Patent Number 7,255,842 entitled "Multi-component Removal in Flue Gas by Aqua Ammonia." This patent discloses a method for the removal of potential environmental-impacting compounds from flue gas streams. The method oxidizes some or all of the acid precursors such as sulfur dioxide (SO 2 ) and nitric oxides (NO x ) into sulfur trioxide and nitrogen dioxide, respectively. Following this step, the gas stream is then treated with aqua ammonia or ammonium hydroxide to capture the compounds via chemical absorption through acid-base or neutralization reactions where a fertilizer is formed.

456

Failure Rate Data Analysis for High Technology Components  

SciTech Connect

Understanding component reliability helps designers create more robust future designs and supports efficient and cost-effective operations of existing machines. The accelerator community can leverage the commonality of its high-vacuum and high-power systems with those of the magnetic fusion community to gain access to a larger database of reliability data. Reliability studies performed under the auspices of the International Energy Agency are the result of an international working group, which has generated a component failure rate database for fusion experiment components. The initial database work harvested published data and now analyzes operating experience data. This paper discusses the usefulness of reliability data, describes the failure rate data collection and analysis effort, discusses reliability for components with scarce data, and points out some of the intersections between magnetic fusion experiments and accelerators.

L. C. Cadwallader

2007-07-01T23:59:59.000Z

457

Apparatus for microwave heat treatment of manufactured components  

DOE Patents (OSTI)

An apparatus for heat treating manufactured components using microwave energy and microwave susceptor material. Heat treating medium such as eutectic salts may be employed. A fluidized bed introduces process gases which may include carburizing or nitriding gases. The process may be operated in a batch mode or continuous process mode. A microwave heating probe may be used to restart a frozen eutectic salt bath.

Babcock & Wilcox Technical Services Y-12, LLC (Oak Ridge, TN)

2008-04-15T23:59:59.000Z

458

Methods for microwave heat treatment of manufactured components  

DOE Patents (OSTI)

An apparatus for heat treating manufactured components using microwave energy and microwave susceptor material. Heat treating medium such as eutectic salts may be employed. A fluidized bed introduces process gases which may include carburizing or nitriding gases. The process may be operated in a batch mode or continuous process mode. A microwave heating probe may be used to restart a frozen eutectic salt bath.

Ripley, Edward B. (Knoxville, TN)

2010-08-03T23:59:59.000Z