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Note: This page contains sample records for the topic "module estimates energy" 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
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1

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

2

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

3

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

he International Energy Module determines changes in the world oil price and the supply prices of crude he International Energy Module determines changes in the world oil price and the supply prices of crude oils and petroleum products for import to the United States in response to changes in U.S. import requirements. A market clearing method is used to determine the price at which worldwide demand for oil is equal to the worldwide supply. The module determines new values for oil production and demand for regions outside the United States, along with a new world oil price that balances supply and demand in the international oil market. A detailed description of the International Energy Module is provided in the EIA publication, Model Documentation Report: The International Energy Module of the National Energy Modeling System, DOE/EIA-M071(06), (Washington, DC, February 2006).

4

Module Handbook Specialisation Biomass Energy  

E-Print Network [OSTI]

Module Handbook Specialisation Biomass Energy 2nd Semester for the Master Programme REMA/EUREC Course 2008/2009 University of Zaragoza Specialisation Provider: Biomass Energy #12;Specialisation Biomass Energy, University of Zaragoza Modul: Introduction and Basic Concepts

Damm, Werner

5

Flywheel Energy Storage Module  

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

kWh/100 kW kWh/100 kW Flywheel Energy Storage Module * 100KWh - 1/8 cost / KWh vs. current State of the Art * Bonded Magnetic Bearings on Rim ID * No Shaft / Hub (which limits surface speed) * Flexible Motor Magnets on Rim ID * Develop Touch-down System for Earthquake Flying Rim Eliminate Shaft and Hub Levitate on Passive Magnetic Bearings Increase Rim Tip Speed Larger Diameter Thinner Rim Stores More Energy 4 X increase in Stored Energy with only 60% Increase in Weight Development of a 100 kWh/100 kW Flywheel Energy Storage Module High Speed, Low Cost, Composite Ring with Bore-Mounted Magnetics Current State of the Art Flywheel Limitations of Existing Flywheel * 15 Minutes of storage * Limited to Frequency Regulation Application * Rim Speed (Stored Energy) Limited by Hub Strain and Shaft Dynamics

6

State Energy Production Estimates  

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

State Energy Production Estimates 1960 Through 2012 2012 Summary Tables Table P1. Energy Production Estimates in Physical Units, 2012 Alabama 19,455 215,710 9,525 0 Alaska 2,052...

7

Alternative Energy Sources - An Interdisciplinary Module for...  

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

Alternative Energy Sources - An Interdisciplinary Module for Energy Education Alternative Energy Sources - An Interdisciplinary Module for Energy Education Below is information...

8

Photovoltaic Energy Technology Module | Open Energy Information  

Open Energy Info (EERE)

Photovoltaic Energy Technology Module Photovoltaic Energy Technology Module Jump to: navigation, search Tool Summary Name: Photovoltaic Energy Technology Module Agency/Company /Organization: World Bank Sector: Energy Focus Area: Renewable Energy, Solar Topics: Technology characterizations Website: web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTENERGY2/EXTRENENERGYTK/0,, References: Photovoltaic Energy Technology Module[1] Resources Portable Solar Photovoltaic Lanterns: Performance and Certification Specification, and Type Approval, ESMAP TECHNICAL PAPER 078 Testing of Storage Batteries used in Stand Alone Photovoltaic Power Systems, Test procedures and examples of test results Technical Specifications for Solar Home Systems (SHS), Rural Electrification and Renewable Energy Development (PV Component) Project

9

Energy Efficiency at Home - An Interdisciplinary Module for Energy...  

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

Efficiency at Home - An Interdisciplinary Module for Energy Education Energy Efficiency at Home - An Interdisciplinary Module for Energy Education Below is information about the...

10

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

11

Compact magnetic energy storage module  

DOE Patents [OSTI]

A superconducting compact magnetic energy storage module in which a plurality of superconducting toroids, each having a toroidally wound superconducting winding inside a poloidally wound superconducting winding, are stacked so that the flow of electricity in each toroidally wound superconducting winding is in a direction opposite from the direction of electrical flow in other contiguous superconducting toroids. This allows for minimal magnetic pollution outside of the module.

Prueitt, Melvin L. (Los Alamos, NM)

1994-01-01T23:59:59.000Z

12

Compact magnetic energy storage module  

DOE Patents [OSTI]

A superconducting compact magnetic energy storage module in which a plurality of superconducting toroids, each having a toroidally wound superconducting winding inside a poloidally wound superconducting winding, are stacked so that the flow of electricity in each toroidally wound superconducting winding is in a direction opposite from the direction of electrical flow in other contiguous superconducting toroids. This allows for minimal magnetic pollution outside of the module. 4 figures.

Prueitt, M.L.

1994-12-20T23:59:59.000Z

13

Module Handbook Specialisation Wind Energy  

E-Print Network [OSTI]

of Wind Turbines Module name: Wind potential, Aerodynamics & Loading of Wind Turbines Section Classes Evaluation of Wind Energy Potential Wind turbine Aerodynamics Static and dynamic Loading of Wind turbines Wind turbine Aerodynamics Static and dynamic Loading of Wind turbines Credit points 8 CP

Habel, Annegret

14

module 4 | Department of Energy  

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

module 4 module 4 HR5 TRANSITION BRIEFING module 4 More Documents & Publications Microsoft Word - Rev5functionalaccountabilityimplementationplan..doc Management (WFP) DEPARTMENT OF...

15

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

16

General Renewable Energy Technology Module | Open Energy Information  

Open Energy Info (EERE)

General Renewable Energy Technology Module General Renewable Energy Technology Module Jump to: navigation, search Tool Summary LAUNCH TOOL Name: General Renewable Energy Technology Module Agency/Company /Organization: World Bank Sector: Energy Focus Area: Renewable Energy Topics: Technology characterizations Website: web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTENERGY2/EXTRENENERGYTK/0,, References: General Renewable Energy Technology Module[1] Resource Generation and Transmission Interconnection Process Overview, PJM Manual, Transmission and Interconnection Planning Department, System Planning Division, PJM Interconnection, LLC References ↑ "General Renewable Energy Technology Module" Retrieved from "http://en.openei.org/w/index.php?title=General_Renewable_Energy_Technology_Module&oldid=328701

17

Wind Energy Technology Module | Open Energy Information  

Open Energy Info (EERE)

Wind Energy Technology Module Wind Energy Technology Module Jump to: navigation, search Tool Summary Name: Wind Energy Technology Module Agency/Company /Organization: World Bank Sector: Energy Focus Area: Renewable Energy, Wind Topics: Background analysis, Technology characterizations Website: web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTENERGY2/EXTRENENERGYTK/0,, Country: Russia, China Eastern Europe, Eastern Asia Coordinates: 54.5283298°, 112.9648819° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":54.5283298,"lon":112.9648819,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

18

Differential Turbo Coded Modulation with APP Channel Estimation  

E-Print Network [OSTI]

Differential Turbo Coded Modulation with APP Channel Estimation Sheryl L. Howard and Christian, iterative decoding. I. INTRODUCTION With the advent of turbo codes [1], [2] and iterative de- coding in very high noise/low signal- to-noise ratio (SNR) environments. Turbo trellis coded modulation (TTCM

Howard, Sheryl

19

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

20

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

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

Assumptions to the Annual Energy Outlook - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

22

Energy Expenditure Estimation DEMO Application  

E-Print Network [OSTI]

of accelerometry. An average smart phone contains an inertial sensor and today we hardly leave our home without itEnergy Expenditure Estimation DEMO Application Bozidara Cvetkovi´c1,2 , Simon Kozina1,2 , Bostjan://www.mps.si Abstract. The paper presents two prototypes for the estimation of hu- man energy expenditure during normal

Lu?trek, Mitja

23

Estimating Renewable Energy Costs  

Broader source: Energy.gov [DOE]

Some renewable energy measures, such as daylighting, passive solar heating, and cooling load avoidance, do not add much to the cost of a building. However, renewable energy technologies typically...

24

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.

25

Estimating Renewable Energy Costs | Department of Energy  

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

Estimating Renewable Energy Costs Estimating Renewable Energy Costs Estimating Renewable Energy Costs October 16, 2013 - 4:40pm Addthis Some renewable energy measures, such as daylighting, passive solar heating, and cooling load avoidance, do not add much to the cost of a building. However, renewable energy technologies typically require large, additional capital investments with savings accruing over the project's life. It is crucial that these systems are considered early on in the budgeting process. Early budget requests need to include a set of technologies that could be used to meet the project's design requirements and their associated implementation costs. The design team may respond with a different set of feasible technologies, but it is wise to have an existing placeholder in the budget. Federal agencies can continue to update the budget as decisions

26

Approved Module Information for ME4504, 2014/5 Module Title/Name: Renewable Energy Module Code: ME4504  

E-Print Network [OSTI]

turbine Renewable energy system design Renewable Energy Policy: UK and international perspectives ModuleApproved Module Information for ME4504, 2014/5 Module Title/Name: Renewable Energy Module Code: ME understanding of the origins and nature of renewable energy flows and their capture and conversion into useful

Neirotti, Juan Pablo

27

Assumptions to the Annual Energy Outlook 1999 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

28

Assumptions to the Annual Energy Outlook 2000 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

29

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.

30

Interface module for transverse energy input to dye laser modules  

DOE Patents [OSTI]

An interface module (10) for transverse energy input to dye laser modules is provided particularly for the purpose of delivering enhancing transverse energy beams (36) in the form of illumination bar (54) to the lasing zone (18) of a dye laser device, in particular to a dye laser amplifier (12). The preferred interface module (10) includes an optical fiber array (30) having a plurality of optical fibers (38) arrayed in a co-planar fashion with their distal ends (44) receiving coherent laser energy from an enhancing laser source (46), and their proximal ends (4) delivered into a relay structure (3). The proximal ends (42) of the optical fibers (38) are arrayed so as to be coplanar and to be aimed generally at a common point. The transverse energy beam array (36) delivered from the optical fiber array (30) is acted upon by an optical element array (34) to produce an illumination bar (54) which has a cross section in the form of a elongated rectangle at the position of the lasing window (18). The illumination bar (54) is selected to have substantially uniform intensity throughout.

English, Jr., Ronald E. (Tracy, CA); Johnson, Steve A. (Tracy, CA)

1994-01-01T23:59:59.000Z

31

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

32

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.

33

Energy use in optical modulators David A. B. Miller  

E-Print Network [OSTI]

Energy use in optical modulators David A. B. Miller Ginzton Laboratory, Stanford University, Nano particularly low energy for low-voltage electroabsorption modulators Optical modulators can offer low energy can usefully define an optical energy launch efficiency E , which is the ratio of the useful energy

Miller, David A. B.

34

Assumptions to the Annual Energy Outlook - International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumption to the Annual Energy Outlook International Energy Module Figure 2. World Oil Prices in three Cases, 1970-2025. Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure Data Figure 3. OPEC Oil Production in the Reference Case, 1970-2025. Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure Data Figure 4. Non-OPEC Production in the Reference Case, 1970-2025. Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure Data Table 4. Worldwide Oil Reserves as of January 1, 2002 (Billion Barrels) Printer Friendly Version Region Proved Oil Reserves Western Hemisphere 313.6 Western‘Europe 18.1 Asia-Pacific 38.7

35

Assumptions to the Annual Energy Outlook 2000 - International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module determines changes in the world oil price and the supply prices of crude oils and petroleum products for import to the United States in response to changes in U.S. import requirements. A market clearing method is used to determine the price at which worldwide demand for oil is equal to the worldwide supply. The module determines new values for oil production and demand for regions outside the United States, along with a new world oil price that balances supply and demand in the international oil market. A detailed description of the International Energy Module is provided in the EIA publication, Model Documentation Report: The International Energy Module of the National Energy Modeling System, DOE/EIA-M071(99), (Washington, DC, February 1999).

36

Biomass Energy Technology Module | Open Energy Information  

Open Energy Info (EERE)

Focus Area: Renewable Energy, Biomass Topics: Technology characterizations Website: web.worldbank.orgWBSITEEXTERNALTOPICSEXTENERGY2EXTRENENERGYTK0,, References: Biomass...

37

State energy data report 1994: Consumption estimates  

SciTech Connect (OSTI)

This document provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), operated by EIA. SEDS provides State energy consumption estimates to members of Congress, Federal and State agencies, and the general public, and provides the historical series needed for EIA`s energy models. Division is made for each energy type and end use sector. Nuclear electric power is included.

NONE

1996-10-01T23:59:59.000Z

38

Building Energy Software Tools Directory: Energy Estimation Software with  

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

Energy Estimation Software with Carbon Footprint Calculation Energy Estimation Software with Carbon Footprint Calculation Energy Estimation Software with Carbon Footprint Calculation logo. Energy Estimation Software for Fan and Pumping Applications estimates energy savings achieved when using a variable frequency drive instead of conventional control methods for fan and pumping applications. The results can be viewed in graphical format and text format and the software has built-in functions to generate an energy estimation report especially designed for consultants. The energy estimator software is available in two editions: Single System Edition This edition allows users to estimate energy savings for a single fan or pump system and generate a multi-page report based on the estimated savings. Project Edition This edition allows users to estimate energy savings of a single fan or

39

Model documentation coal market module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the approaches used in developing the Annual Energy Outlook 1995 (AEO95). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of the coal market module`s three submodules. These are the Coal Production Submodule (CPS), the Coal Export Submodule (CES), the Coal Expert Submodule (CES), and the Coal Distribution Submodule (CDS).

NONE

1995-03-01T23:59:59.000Z

40

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

Gasoline and Diesel Fuel Update (EIA)

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

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

Estimating Appliance and Home Electronic Energy Use | Department of Energy  

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

Estimating Appliance and Home Electronic Energy Use Estimating Appliance and Home Electronic Energy Use Estimating Appliance and Home Electronic Energy Use November 11, 2013 - 4:23pm Addthis Estimate the energy consumption and cost to operate an appliance when making a purchase. Investing in an energy-efficient product may save you money in the long run. | Photo courtesy of iStockphoto.com/wh1600. Estimate the energy consumption and cost to operate an appliance when making a purchase. Investing in an energy-efficient product may save you money in the long run. | Photo courtesy of iStockphoto.com/wh1600. If you're trying to decide whether to invest in a more energy-efficient appliance or you'd like to determine your electricity loads, you may want to estimate appliance energy consumption. Formula for Estimating Energy Consumption

42

Estimating Appliance and Home Electronic Energy Use | Department of Energy  

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

Estimating Appliance and Home Electronic Energy Use Estimating Appliance and Home Electronic Energy Use Estimating Appliance and Home Electronic Energy Use November 11, 2013 - 4:23pm Addthis Estimate the energy consumption and cost to operate an appliance when making a purchase. Investing in an energy-efficient product may save you money in the long run. | Photo courtesy of iStockphoto.com/wh1600. Estimate the energy consumption and cost to operate an appliance when making a purchase. Investing in an energy-efficient product may save you money in the long run. | Photo courtesy of iStockphoto.com/wh1600. If you're trying to decide whether to invest in a more energy-efficient appliance or you'd like to determine your electricity loads, you may want to estimate appliance energy consumption. Formula for Estimating Energy Consumption

43

GIZ Sourcebook Module 5h: Urban Transport and Energy Efficiency...  

Open Energy Info (EERE)

h: Urban Transport and Energy Efficiency Jump to: navigation, search Tool Summary LAUNCH TOOL Name: GIZ Sourcebook Module 5h: Urban Transport and Energy Efficiency AgencyCompany...

44

Modulated reconnection rate and energy conversion at the magnetopause under steady IMF conditions  

E-Print Network [OSTI]

Modulated reconnection rate and energy conversion at the magnetopause under steady IMF conditions L conversion across the dayside high-latitude magnetopause. The energy conversion is estimated during eleven describe a new method to determine the reconnection rate from the magnitude of the local energy conversion

California at Berkeley, University of

45

Interruption Cost Estimate Calculator | Open Energy Information  

Open Energy Info (EERE)

Interruption Cost Estimate Calculator Interruption Cost Estimate Calculator Jump to: navigation, search Tool Summary Name: Interruption Cost Estimate (ICE) Calculator Agency/Company /Organization: Freeman, Sullivan & Co. Sector: Energy Focus Area: Grid Assessment and Integration, Energy Efficiency Resource Type: Online calculator, Software/modeling tools User Interface: Website Website: icecalculator.com/ Country: United States Cost: Free Northern America References: [1] Logo: Interruption Cost Estimate (ICE) Calculator This calculator is a tool designed for electric reliability planners at utilities, government organizations or other entities that are interested in estimating interruption costs and/or the benefits associated with reliability improvements. About The Interruption Cost Estimate (ICE) Calculator is an electric reliability

46

Estimating wave energy from a wave record  

Science Journals Connector (OSTI)

This note is concerned with the calculation of wave energy from a time series record of wave heights. Various methods are used to estimate the wave energy. For wave records that contain a number of different ... ...

Sasithorn Aranuvachapun; John A. Johnson

1977-01-01T23:59:59.000Z

47

Retrofit Energy Savings Estimation Model | Open Energy Information  

Open Energy Info (EERE)

Retrofit Energy Savings Estimation Model Retrofit Energy Savings Estimation Model Jump to: navigation, search Tool Summary Name: Retrofit Energy Savings Estimation Model Agency/Company /Organization: Lawrence Berkeley National Laboratory Sector: Energy Focus Area: Buildings Topics: Resource assessment Resource Type: Software/modeling tools User Interface: Desktop Application Website: btech.lbl.gov/tools/resem/resem.htm Cost: Free Language: English References: Retrofit Energy Savings Estimation Model[1] Logo: Retrofit Energy Savings Estimation Model RESEM, the Retrofit Energy Savings Estimation Model, is a PC-based tool designed to allow Department of Energy (DOE) Institutional Conservation Program (ICP) staff and participants to reliably determine the energy savings directly caused by ICP-supported retrofit measures implemented in a

48

ESTIMATES OF ADDITIONAL ACHIEVABLE ENERGY SAVINGS  

E-Print Network [OSTI]

, as provided in the 2013 California Energy Efficiency Potential and Goals Study (2013 Potential Study 2013.1 The 2013 Potential Study estimated energy efficiency savings that could be realized through G. Brown Jr., Governor California Energy Commission DRAFT STAFF REPORT #12;CALIFORNIA ENERGY

49

State energy data report 1996: Consumption estimates  

SciTech Connect (OSTI)

The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the Combined State Energy Data System (CSEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining CSEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. CSEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public and (2) to provide the historical series necessary for EIA`s energy models. To the degree possible, energy consumption has been assigned to five sectors: residential, commercial, industrial, transportation, and electric utility sectors. Fuels covered are coal, natural gas, petroleum, nuclear electric power, hydroelectric power, biomass, and other, defined as electric power generated from geothermal, wind, photovoltaic, and solar thermal energy. 322 tabs.

NONE

1999-02-01T23:59:59.000Z

50

Estimating Appliance and Home Electronic Energy Use | Department of Energy  

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

Appliance and Home Electronic Energy Use Appliance and Home Electronic Energy Use Estimating Appliance and Home Electronic Energy Use November 11, 2013 - 4:23pm Addthis Estimate the energy consumption and cost to operate an appliance when making a purchase. Investing in an energy-efficient product may save you money in the long run. | Photo courtesy of iStockphoto.com/wh1600. Estimate the energy consumption and cost to operate an appliance when making a purchase. Investing in an energy-efficient product may save you money in the long run. | Photo courtesy of iStockphoto.com/wh1600. If you're trying to decide whether to invest in a more energy-efficient appliance or you'd like to determine your electricity loads, you may want to estimate appliance energy consumption. Formula for Estimating Energy Consumption

51

Integrated Module Heat Exchanger | Department of Energy  

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

Module Heat Exchanger Integrated Module Heat Exchanger 2012 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Program Annual Merit Review and Peer Evaluation Meeting...

52

Model documentation Coal Market Module of the National Energy Modeling System  

SciTech Connect (OSTI)

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.

NONE

1996-04-30T23:59:59.000Z

53

Model documentation Renewable Fuels Module of the National Energy Modeling System  

SciTech Connect (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

54

Improved diagnostic model for estimating wind energy  

SciTech Connect (OSTI)

Because wind data are available only at scattered locations, a quantitative method is needed to estimate the wind resource at specific sites where wind energy generation may be economically feasible. This report describes a computer model that makes such estimates. The model uses standard weather reports and terrain heights in deriving wind estimates; the method of computation has been changed from what has been used previously. The performance of the current model is compared with that of the earlier version at three sites; estimates of wind energy at four new sites are also presented.

Endlich, R.M.; Lee, J.D.

1983-03-01T23:59:59.000Z

55

How to Estimate the Economic Impacts from Renewable Energy |...  

Energy Savers [EERE]

How to Estimate the Economic Impacts from Renewable Energy How to Estimate the Economic Impacts from Renewable Energy U.S. Department of Energy Technical Assistance Project (TAP)...

56

Retrofit Energy Savings Estimation Model Reference Manual  

E-Print Network [OSTI]

Retrofit Energy Savings Estimation Model Reference Manual #12;#12;Retrofit Energy Savings commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does from the Department of Energy. Any conclusions or opinions expressed in this manual represent solely

57

Energy Policy 30 (2002) 477499 Photovoltaic module quality in  

E-Print Network [OSTI]

Energy Policy 30 (2002) 477­499 Photovoltaic module quality in the Kenyan solar home systems market purchases of clean decentralized photovoltaic technologies. Small amorphous-silicon modules dominate. This article analyzes market failure associated with photovoltaic module quality in the Kenyan SHS market

Kammen, Daniel M.

58

Density Estimation Trees in High Energy Physics  

E-Print Network [OSTI]

Density Estimation Trees can play an important role in exploratory data analysis for multidimensional, multi-modal data models of large samples. I briefly discuss the algorithm, a self-optimization technique based on kernel density estimation, and some applications in High Energy Physics.

Anderlini, Lucio

2015-01-01T23:59:59.000Z

59

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

Gasoline and Diesel Fuel Update (EIA)

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

60

Estimating pool energy requirements with a thermometer  

SciTech Connect (OSTI)

It is pointed out that there is a need for a simple method of estimating the energy required by a swimming pool. (This is the first step in determining the size of solar pool heaters for a specific application.) Previous methods for estimating pool energy requirements demand mathematical skills. The method proposed here requires only: (1) measurement of the average pool temperature; (2) an estimate of the pool volume; and (3) a knowledge of the desired temperature. Average temperature of the pool is measured using a weighted thermometer at different locations under various weather conditions. Step-by-step instructions complete with a table are provided. (MJJ)

Not Available

1980-04-01T23:59:59.000Z

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

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

62

Definition: PV module | Open Energy Information  

Open Energy Info (EERE)

Definition Definition Edit with form History Facebook icon Twitter icon » Definition: PV module Jump to: navigation, search Dictionary.png PV module A unit comprised of several PV cells, and the principal unit of a PV array; it is intended to generate direct current power under un-concentrated sunlight.[1][2] View on Wikipedia Wikipedia Definition A solar panel is a set of solar photovoltaic modules electrically connected and mounted on a supporting structure. A photovoltaic module is a packaged, connected assembly of photovoltaic cells. The solar module can be used as a component of a larger photovoltaic system to generate and supply electricity in commercial and residential applications. Each module is rated by its DC output power under standard test conditions (STC), and

63

Multiple Layer Graphene Optical Modulator - Energy Innovation...  

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

Materials Advanced Materials Find More Like This Return to Search Multiple Layer Graphene Optical Modulator Lawrence Berkeley National Laboratory Contact LBL About This...

64

Detailed Course Module Description | Department of Energy  

Energy Savers [EERE]

lists the course modules for building science courses offered at Cornell's Collaborator Sustainable Buildingi Practice course. coursemodule.pdf More Documents & Publications...

65

CHP Emissions Reduction Estimator | Open Energy Information  

Open Energy Info (EERE)

CHP Emissions Reduction Estimator CHP Emissions Reduction Estimator Jump to: navigation, search Tool Summary LAUNCH TOOL Name: CHP Emissions Reduction Estimator Agency/Company /Organization: United States Environmental Protection Agency Sector: Energy Focus Area: Buildings, Transportation, Industry Topics: GHG inventory, Co-benefits assessment Resource Type: Software/modeling tools User Interface: Spreadsheet Website: www.epa.gov/chp/basic/calculator.html Country: United States UN Region: Northern America CHP Emissions Reduction Estimator Screenshot References: http://www.epa.gov/chp/basic/calculator.html "This Emissions Estimator provides the amount of reduced emissions in terms of pounds of CO2, SO2, and NOX based on input from the User regarding the CHP technology being used. In turn the User will be provided with

66

Estimated United States Transportation Energy Use 2005  

SciTech Connect (OSTI)

A flow chart depicting energy flow in the transportation sector of the United States economy in 2005 has been constructed from publicly available data and estimates of national energy use patterns. Approximately 31,000 trillion British Thermal Units (trBTUs) of energy were used throughout the United States in transportation activities. Vehicles used in these activities include automobiles, motorcycles, trucks, buses, airplanes, rail, and ships. The transportation sector is powered primarily by petroleum-derived fuels (gasoline, diesel and jet fuel). Biomass-derived fuels, electricity and natural gas-derived fuels are also used. The flow patterns represent a comprehensive systems view of energy used within the transportation sector.

Smith, C A; Simon, A J; Belles, R D

2011-11-09T23:59:59.000Z

67

Assumptions to the Annual Energy Outlook 2001 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

68

Assumptions to the Annual Energy Outlook 2002 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

69

Order Module--THE CONTROL OF HAZARDOUS ENERGY (LOCKOUT/TAGOUT...  

Energy Savers [EERE]

Order Module--THE CONTROL OF HAZARDOUS ENERGY (LOCKOUTTAGOUT) FAMILIAR LEVEL Order Module--THE CONTROL OF HAZARDOUS ENERGY (LOCKOUTTAGOUT) FAMILIAR LEVEL The familiar level of...

70

SHARP Physics Modules Updated | Department of Energy  

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

Physics Modules Updated Physics Modules Updated SHARP Physics Modules Updated January 29, 2013 - 12:37pm Addthis PROTEUS Development The SHARP neutronics module, PROTEUS, includes neutron and gamma transport solvers, cross-section processing tools, and tools for depletion and fuel cycle analysis. Efforts in the second quarter focused on three major priorities: multi-physics integration, intermediate-fidelity tool development, and demonstrations of applicability. Integration of the second-order, discrete ordinates (Sn method) solver of PROTEUS with the latest version of the MOAB framework (which represents and evaluates mesh data) was initiated to enable its use for multi-physics analysis. With these updates, PROTEUS can obtain the mesh specification from the MOAB framework and store its data on the MOAB mesh representation so that MOAB

71

Design Considerations for a Universal Smart Energy Module for Energy Harvesting in Wireless  

E-Print Network [OSTI]

size and type harvester energy modules. Handling this complexity, discussing the problems, and giving]. Their goal is a cheap and easy circuit design for harvesting solar energy and storing it in a rechargeable NiDesign Considerations for a Universal Smart Energy Module for Energy Harvesting in Wireless Sensor

Turau, Volker

72

Table E6. Transportation Sector Energy Price Estimates, 2012  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

E6. Transportation Sector Energy Price Estimates, 2012 (Dollars per Million Btu) State Primary Energy Retail Electricity Total Energy Coal Natural Gas Petroleum Total Aviation...

73

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,

74

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,

75

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

76

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

77

Electrical and Energy Engineering Energy Information for modules taught in 201112.  

E-Print Network [OSTI]

Electrical and Energy Engineering Energy Information for modules taught in 201112. All programmes 1) BEng/MEng Electrical + Energy Eng-LC BEng/MEng All modules are compulsory Year Credits: 120 Total Systems0419509 20 1+2EE1A Circuits, Devices and Fields0419502 20 1+2EE1B Introduction to Electrical

Miall, Chris

78

Assumptions to the Annual Energy Outlook - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module Assumption to the Annual Energy Outlook 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).109 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, from hydroelectric power, which was an original source of electricity generation, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon low-cost energy storage.

79

Development of the Potential Energy Savings Estimation (PESE) Toolkit  

E-Print Network [OSTI]

This study has developed a prototype computer tool called the Potential Energy Savings Estimation (PESE) Toolkit. Baltazars methodology for potential energy savings estimation from EBCx/retrofit measures has been improved in several ways...

Liu, J.; Baltazar, J. C.; Claridge, D. E.

80

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.

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

Assumptions to the Annual Energy Outlook 2001 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module 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 2001, DOE/EIA-M060(2001) January 2001. 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

82

Assumptions to the Annual Energy Outlook 2002 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module 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 2002, DOE/EIA-M060(2002) (Washington, DC, January 2002). 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

83

Title of Document: LONGITUDINAL SPACE-CHARGE WAVES INDUCED BY ENERGY MODULATIONS  

E-Print Network [OSTI]

ABSTRACT Title of Document: LONGITUDINAL SPACE-CHARGE WAVES INDUCED BY ENERGY MODULATIONS Brian L. Modulations in energy or density can induce space-charge waves at low energies which could be problematic at higher energies. This thesis is a study of longitudinal space-charge waves induced by energy modulations

Anlage, Steven

84

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

85

Approved Module Information for ME2042, 2014/5 Module Title/Name: Energy Supply and Delivery Module Code: ME2042  

E-Print Network [OSTI]

to assess both technically and financially the potential for renewable energy sources in the UK. The module and sustainability. Ability to analyse and assess energy supply routes, especially efficiency. Ability to demonstrate to undertake background research and produce media briefing report on a given energy topic. Indicative Module

Neirotti, Juan Pablo

86

A Buildings Module for the Stochastic Energy Deployment System  

SciTech Connect (OSTI)

The U.S. Department of Energy (USDOE) is building a new long-range (to 2050) forecasting model for use in budgetary and management applications called the Stochastic Energy Deployment System (SEDS), which explicitly incorporates uncertainty through its development within the Analytica(R) platform of Lumina Decision Systems. SEDS is designed to be a fast running (a few minutes), user-friendly model that analysts can readily run and modify in its entirety through a visual programming interface. Lawrence Berkeley National Laboratory is responsible for implementing the SEDS Buildings Module. The initial Lite version of the module is complete and integrated with a shared code library for modeling demand-side technology choice developed by the National Renewable Energy Laboratory (NREL) and Lumina. The module covers both commercial and residential buildings at the U.S. national level using an econometric forecast of floorspace requirement and a model of building stock turnover as the basis for forecasting overall demand for building services. Although the module is fundamentally an engineering-economic model with technology adoption decisions based on cost and energy performance characteristics of competing technologies, it differs from standard energy forecasting models by including considerations of passive building systems, interactions between technologies (such as internal heat gains), and on-site power generation.

Lacommare, Kristina S H; Marnay, Chris; Stadler, Michael; Borgeson, Sam; Coffey, Brian; Komiyama, Ryoichi; Lai, Judy

2008-05-15T23:59:59.000Z

87

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.

88

Assumptions to the Annual Energy Outlook 2001 - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module 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 alcohol and ethers, 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 refining activities in three U.S. regions. This representation provides the marginal costs of production for a number of traditional and new petroleum products. The linear programming results are used to determine end-use product prices for

89

Assumptions to the Annual Energy Outlook 2002 - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module 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 alcohol and ethers, 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 refining activities in three U.S. regions. This representation provides the marginal costs of production for a number of traditional and new petroleum products. The linear programming results are used to determine end-use product prices for

90

Assumptions to the Annual Energy Outlook - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

91

Model documentation renewable fuels module of the National Energy Modeling System  

SciTech Connect (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

92

Additional Resources for Estimating Building Energy and Cost Savings to  

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

Additional Resources for Estimating Building Energy and Cost Additional Resources for Estimating Building Energy and Cost Savings to Reduce Greenhouse Gases Additional Resources for Estimating Building Energy and Cost Savings to Reduce Greenhouse Gases October 7, 2013 - 11:06am Addthis For evaluating greenhouse gas reduction strategies and estimating costs, the following information resources can help Federal agencies estimate energy and cost savings potential by building type. When deciding what resource to use for developing energy- and cost-savings estimates, a program should consider items detailed in Table 1. Table 1.Resources for Estimating Energy Savings Resource Items to consider Advanced Energy Retrofit Guides Based on representative building models of commercial buildings. Guidance available for a limited number of building types using the most common technologies.

93

Estimating the Potential Impact of Renewable Energy on the Caribbean  

E-Print Network [OSTI]

Estimating the Potential Impact of Renewable Energy on the Caribbean Job Sector Rebekah Shirley spur the creation of more jobs per unit of energy delivered locally than `business as usual' fossil with its Energy Efficiency (EE) and Renewable Energy (RE) campaign. We present a Green Jobs estimator which

Kammen, Daniel M.

94

Assumptions to the Annual Energy Outlook - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumption to the Annual Energy Outlook Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, imports, 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 2004, DOE/EIA-M060(2004) (Washington, DC, 2004). 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 capacity utilization of mines, mining capacity, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

95

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

SciTech Connect (OSTI)

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

96

"Order Module--DOE O 442.1, DEPARTMENT OF ENERGY EMPLOYEE CONCERNS...  

Office of Environmental Management (EM)

"Order Module--DOE O 442.1, DEPARTMENT OF ENERGY EMPLOYEE CONCERNS PROGRAM "Order Module--DOE O 442.1, DEPARTMENT OF ENERGY EMPLOYEE CONCERNS PROGRAM The familiar level of this...

97

Program Potential: Estimates of Federal Energy Cost Savings from Energy Efficient Procurement  

E-Print Network [OSTI]

24 Energy and Costsavings in Table 7: Annual energy and cost savings of waterwere used to derive energy and cost savings estimates:

Taylor, Margaret

2014-01-01T23:59:59.000Z

98

Towards Human Energy Expenditure Estimation Using Smart Phone Inertial Sensors  

E-Print Network [OSTI]

to reliably estimate energy expenditure (EE). Direct calorimetry [5] measures the heat produced by human bodyTowards Human Energy Expenditure Estimation Using Smart Phone Inertial Sensors Bozidara Cvetkovi´c1 human energy expenditure during sport and normal daily ac- tivities. The paper presents technical

Lu?trek, Mitja

99

Energy Efficiency at Home- An Interdisciplinary Module for Energy Education  

K-12 Energy Lesson Plans and Activities Web site (EERE)

Here you'll find an interdisciplinary approach to teaching energy education to middle school students

100

Assumptions to the Annual Energy Outlook 2000 - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module (RFM) consists of five distinct submodules that represent the major renewable energy technologies. Although it is described here, conventional hydroelectric is included in the Electricity Market Module (EMM) and is not part of the RFM. Similarly, ethanol modeling is included in the Petroleum Market Module (PMM). Some renewables, such as 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 require the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was an original source of electricity generation, to newer power systems using wind, solar, and geothermal energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon low-cost energy storage.

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

Assumptions to the Annual Energy Outlook 1999 - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

renewable.gif (4875 bytes) renewable.gif (4875 bytes) The NEMS Renewable Fuels Module (RFM) consists of five distinct submodules that represent the major renewable energy technologies. Although it is described here, conventional hydroelectric is included in the Electricity Market Module (EMM) and is not part of the RFM. Similarly, ethanol modeling is included in the Petroleum Market Module (PMM). Some renewables, such as 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 require the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was an original source of electricity generation, to newer power systems using wind, solar, and geothermal energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittence, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon low-cost energy storage.

102

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).

103

An Estimate of Residential Energy Savings From IECC Change Proposals  

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

An Estimate of Residential Energy Savings From IECC Change Proposals An Estimate of Residential Energy Savings From IECC Change Proposals Recommended for Approval at the ICC's Fall, 2009, Initial Action Hearings The U.S. Department of Energy (DOE) has established ambitious goals to improve the energy efficiency requirements of the International Energy Conservation Code (IECC) for residential buildings. DOE has established near- and long-term goals of 30% and 50% energy efficiency improvements, respectively, compared to the 2006 IECC. This report presents DOE's approach to calculating residential energy consumption for the purpose of estimating energy savings attributable to improvements in the code. This approach is then used to estimate the national average energy savings, relative to the 2006 IECC, resulting from the proposed improvements DOE submitted and supported for the 2012 IECC.

104

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

SciTech Connect (OSTI)

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

NONE

1998-01-01T23:59:59.000Z

105

Estimating Internal Wave Energy Fluxes in the Ocean  

Science Journals Connector (OSTI)

Energy flux is a fundamental quantity for understanding internal wave generation, propagation, and dissipation. In this paper, the estimation of internal wave energy fluxes ?u?p?? from ocean observations that may be sparse in either time or depth ...

Jonathan D. Nash; Matthew H. Alford; Eric Kunze

2005-10-01T23:59:59.000Z

106

2008 Status Report - Savings Estimates for the ENERGY STAR Voluntary  

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

Status Report - Savings Estimates for the ENERGY STAR Voluntary Status Report - Savings Estimates for the ENERGY STAR Voluntary Labeling Program Title 2008 Status Report - Savings Estimates for the ENERGY STAR Voluntary Labeling Program Publication Type Journal Article LBNL Report Number LBNL-56380 Year of Publication 2007 Authors Sanchez, Marla C., Carrie A. Webber, Richard E. Brown, and Gregory K. Homan Date Published 11/2007 Publisher Lawrence Berkeley National Laboratory ISBN Number LBNL-56380(2008) Keywords Enduse, Energy End-Use Forecasting, EUF Abstract ENERGY STAR is a voluntary labeling program designed to identify and promote energy-efficient products, buildings and practices. Operated jointly by the Environmental Protection Agency (EPA) and the U.S. Department of Energy (DOE), ENERGY STAR includes more than thirty products, spanning office equipment, residential heating and cooling equipment, commercial and residential lighting, home electronics, and major appliances. This report presents savings estimates for ENERGY STAR labeled products. We present estimates of energy, dollar, and carbon savings achieved by the program in the year 2007, what we expect in 2008, and provide savings forecasts for the periods 2008 to 2015 and 2008 to 2025. The forecast represents our best estimate of future ENERGY STAR savings. It is based on realistic ENERGY STAR unit sales for each of the products.

107

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

SciTech Connect (OSTI)

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

NONE

1995-03-01T23:59:59.000Z

108

Assumptions to the Annual Energy Outlook 2000 - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

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 alcohol and ethers, natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. 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 alcohol and ethers, 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 refining activities in three U.S. regions. This representation provides the marginal costs of production for a number of traditional and new petroleum products. The linear programming results are used to determine end-use product prices for each Census Division using the assumptions and methods described below.100

109

Assumptions to the Annual Energy Outlook 1999 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

coal.gif (4423 bytes) coal.gif (4423 bytes) 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, Model Documentation: Coal Market Module of the National Energy Modeling System, DOE/EIA-MO60. 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).

110

Numerical Wave Modeling and Wave Energy Estimation  

Science Journals Connector (OSTI)

In a rapidly evolving operational and research framework concerning the global energy resources, new frontiers have been set for ... the scientific community working on environmental and renewable energy issues. ...

G. Galanis; G. Zodiatis; D. Hayes

2013-01-01T23:59:59.000Z

111

Estimating Energy Savings in Compressed Air Systems  

E-Print Network [OSTI]

draw of the compressor was measured over a 4.5 hour interval during production. Based on the rated full load amps from the compressor nameplate, the full-load power (FLP) was calculated to be 52 kW. The no-load power draw (NLP1) of the compressor... for this compressor in load/unload control was: During the first seven hours, the #4 compressor was run in modulation control and then was switched to run in load/unload control with auto shutoff during the second seven hours. Compressors #1, #2 and #3 remained...

Schmidt, C.; Kissock, J. K.

2004-01-01T23:59:59.000Z

112

Analysis of photovoltaic module energy output under operating conditions in South Africa  

SciTech Connect (OSTI)

South Africa does not have any industry standard methodology to evaluate photovoltaic (PV) modules for energy production. The aim of this study is to characterize the energy production of PV modules deployed outdoors at the University of Port Elizabeth (UPE), Summerstrand, South Africa with the view of facilitating such a standard. The system developed for this study was designed to monitor the energy production of seven PV modules under normal operating conditions. An analysis of energy production of three of the PV modules under test, while operating under prevailing outdoor conditions, is given. Measured energy output is also compared with that predicted using an energy model.

Dyk, E.E. van; Meyer, E.L.; Scott, B.J.; O`Connor, D.A.; Wessels, J.B. [Univ. of Port Elizabeth (South Africa). Dept. of Physics

1997-12-31T23:59:59.000Z

113

Approved Module Information for EC211C, 2014/5 Module Title/Name: Estimation, Measurement & Scheduling Module Code: EC211C  

E-Print Network [OSTI]

practice and scheduling using planning and control tools and techniques to evaluate students? own work & Scheduling Module Code: EC211C School: Engineering and Applied Science Module Type: Standard Module New and practices of construction scheduling; * To develop an understanding of cost and time in construction

Neirotti, Juan Pablo

114

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

SciTech Connect (OSTI)

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

NONE

1995-02-01T23:59:59.000Z

115

Model documentation renewable fuels module of the National Energy Modeling System  

SciTech Connect (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

116

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

SciTech Connect (OSTI)

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

NONE

1994-08-01T23:59:59.000Z

117

Property:EstimatedTime | Open Energy Information  

Open Energy Info (EERE)

EstimatedTime EstimatedTime Jump to: navigation, search Property Name EstimatedTime Property Type Quantity Description An estimate of a particular chronological span, uses the Type:Epoch. Use this type to enumerate a length of time. The default unit is the year. Acceptable units (and their conversions) are: 8766 hours,hour,h,H,Hour,Hours,HOUR,HOURS 365.25 days,day,d,Day,Days,D,DAY,DAYS 52.17857 weeks,week,w,Week,Weeks,W,WEEK,WEEKS 12 months,month,m,Month,Months,M,MONTH,MONTHS 1 years,year,y,Year,Years,Y,YEAR,YEARS Subproperties This property has the following 35 subproperties: G GRR/Elements/14-CA-b.1 - NPDES Permit Application GRR/Elements/14-CA-b.12 - Were all EPA objections resolved GRR/Elements/14-CA-b.13 - NPDES Permit issued GRR/Elements/14-CA-b.3 - Is the application complete for the Regional Water Quality Control Board

118

Evaluation of an Incremental Ventilation Energy Model for Estimating  

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

Evaluation of an Incremental Ventilation Energy Model for Estimating Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation Title Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation Publication Type Report LBNL Report Number LBNL-5796E Year of Publication 2012 Authors Logue, Jennifer M., William J. N. Turner, Iain S. Walker, and Brett C. Singer Date Published 06/2012 Abstract Changing the rate of airflow through a home affects the annual thermal conditioning energy.Large-scale changes to airflow rates of the housing stock can significantly alter the energy consumption of the residential energy sector. However, the complexity of existing residential energy models hampers the ability to estimate the impact of policy changes on a state or nationwide level. The Incremental Ventilation Energy (IVE) model developed in this study was designed to combine the output of simple airflow models and a limited set of home characteristics to estimate the associated change in energy demand of homes. The IVE model was designed specifically to enable modelers to use existing databases of home characteristics to determine the impact of policy on ventilation at a population scale. In this report, we describe the IVE model and demonstrate that its estimates of energy change are comparable to the estimates of a well-validated, complex residential energy model when applied to homes with limited parameterization. Homes with extensive parameterization would be more accurately characterized by complex residential energy models. The demonstration included a range of home types, climates, and ventilation systems that cover a large fraction of the residential housing sector.

119

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

Estimating Total Energy Consumption and Emissions of Chinasof Chinas total energy consumption mix. However, accuratelyof Chinas total energy consumption, while others estimate

Fridley, David G.

2008-01-01T23:59:59.000Z

120

Derived Annual Estimates of Manufacturing Energy Consumption, 1974-1988  

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

Manufacturing > Derived Annual Estimates - Executive Summary Manufacturing > Derived Annual Estimates - Executive Summary Derived Annual Estimates of Manufacturing Energy Consumption, 1974-1988 Figure showing Derived Estimates Executive Summary This report presents a complete series of annual estimates of purchased energy used by the manufacturing sector of the U.S. economy, for the years 1974 to 1988. These estimates interpolate over gaps in the actual data collections, by deriving estimates for the missing years 1982-84 and 1986-87. For the purposes of this report, "purchased" energy is energy brought from offsite for use at manufacturing establishments, whether the energy is purchased from an energy vendor or procured from some other source. The actual data on purchased energy comes from two sources, the U.S. Department of Commerce Bureau of the Census's Annual Survey of Manufactures (ASM) and EIA's Manufacturing Energy Consumption Survey (MECS). The ASM provides annual estimates for the years 1974 to 1981. However, in 1982 (and subsequent years) the scope of the ASM energy data was reduced to collect only electricity consumption and expenditures and total expenditures for other purchased energy. In 1985, EIA initiated the triennial MECS collecting complete energy data. The series equivalent to the ASM is referred to in the MECS as "offsite-produced fuels." The completed annual series for 1974 to 1988 developed in this report links the ASM and MECS "offsite" series, estimating for the missing years. Estimates are provided for the manufacturing sector as a whole and at the two-digit Standard Industrial Classification (SIC) level for total energy consumption and for the consumption of individual fuels. There are no direct sources of data for the missing years (1982-1984 and 1986-1987). To derive consumption estimates, a comparison was made between the ASM, MECS, and other economic series to see whether there were any good predictors for the missing data. Various estimation schemes were analyzed to fill in the gaps in data after 1981 by trying to match known data for the 1974 to 1981 period.

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

Solar axions as an energy source and modulator of the Earth magnetic field  

E-Print Network [OSTI]

We show existence of strong negative correlation between the temporal variations of magnetic field toroidal component of the solar tachocline (the bottom of convective zone) and the Earth magnetic field (Y-component). The possibility that hypothetical solar axions, which can transform into photons in external electric or magnetic fields (the inverse Primakoff effect), can be the instrument by which the magnetic field of convective zone of the Sun modulates the magnetic field of the Earth is considered. We propose the axion mechanism of "solar dynamo-geodynamo" connection, where an energy of axions, which form in the Sun core, is modulated at first by the magnetic field of the solar tachocline zone (due to the inverse coherent Primakoff effect) and after that is absorbed in the liquid core of the Earth under influence of the terrestrial magnetic field, thereby playing the role of an energy source and a modulator of the Earth magnetic field. Within the framework of this mechanism new estimations of the strength of an axion coupling to a photon (ga_gamma about 5*10^-9 GeV^-1) and the axion mass (ma ~ 30 eV) have been obtained.

V. D. Rusov; E. P. Linnik; K. Kudela; S. Cht. Mavrodiev; T. N. Zelentsova; V. P. Smolyar; K. K. Merkotan

2010-08-16T23:59:59.000Z

122

Module: Emission Factors for Deforestation | Open Energy Information  

Open Energy Info (EERE)

Website: www.leafasia.orgtoolstechnical-guidance-series-emission-factors-defo Cost: Free Language: English Module: Emission Factors for Deforestation Screenshot Logo: Module:...

123

Module: Activity Data for Deforestation | Open Energy Information  

Open Energy Info (EERE)

Website: www.leafasia.orgtoolstechnical-guidance-series-activity-data-defores Cost: Free Language: English Module: Activity Data for Deforestation Screenshot Logo: Module:...

124

Assumptions to the Annual Energy Outlook 1999 - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

petroleum.gif (4999 bytes) petroleum.gif (4999 bytes) 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 alcohol and ethers, 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 refining activities in three U.S. regions. This representation provides the marginal costs of production for a number of traditional and new petroleum products. The linear programming results are used to determine end-use product prices for each Census Division using the assumptions and methods described below. 75

125

Order Module--THE CONTROL OF HAZARDOUS ENERGY (LOCKOUT/TAGOUT) FAMILIAR  

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

Order Module--THE CONTROL OF HAZARDOUS ENERGY (LOCKOUT/TAGOUT) Order Module--THE CONTROL OF HAZARDOUS ENERGY (LOCKOUT/TAGOUT) FAMILIAR LEVEL Order Module--THE CONTROL OF HAZARDOUS ENERGY (LOCKOUT/TAGOUT) FAMILIAR LEVEL The familiar level of this module is divided into two sections. In the first section, we will discuss the purpose of 29 CFR 1910.147 and the terms associated with the standard. In the second section, we will discuss the requirements in the standard. We have provided examples throughout the module to help familiarize you with the material. The examples will also help prepare you for the practice at the end of this module and the criterion test. Most of what you will need to know to complete this module is contained in the module. However, before continuing, you should obtain a copy of the standard. Copies of the standard are available at

126

Estimating climatological variability of solar energy production  

Science Journals Connector (OSTI)

Abstract A method is presented for estimating the climatological variability of yearly and monthly photovoltaic power production per 1kWp of installed power. This quantity is computed for a specified portfolio of sources on the basis of historical data. Its climatological variability is derived from a simulation of 33years of power production with hourly time step. Underlying meteorological variables are taken from the MERRA reanalysis for the years 19792011. Since the MERRA reanalysis is not a traditional data source for photovoltaic power modelling, various comparisons to available and more frequently used data sources are included. The method of estimation has the advantage of wide applicability due to the global coverage of the meteorological data.

Pavel Juru; Krytof Eben; Jaroslav Resler; Pavel Kr?; Ivan Kasanick; Emil Pelikn; Marek Brabec; Ji? Hoek

2013-01-01T23:59:59.000Z

127

EIA - Appendix B: Estimation Methodologies of Household Vehicles Energy  

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

If you have trouble viewing this page, contact the National Energy Informaiton Center at (202) 586-8800. Return to Energy Information Administration Home Page If you have trouble viewing this page, contact the National Energy Informaiton Center at (202) 586-8800. Return to Energy Information Administration Home Page EIA Home > Transportation Home Page > Appendix B Estimation MethodologiesIntroduction Appendix B Estimation Methodologies Introduction Statistics concerning vehicle miles traveled (VMT), vehicle fuel efficiency (given in terms of miles per gallon (MPG)), vehicle fuel consumption, and vehicle fuel expenditures are presented in this report. The methodology used to estimate these statistics relied on data from the 1993 Residential Energy Consumption Survey (RECS), the 1994 Residential Transportation Energy Consumption Survey (RTECS), the U.S. Environmental Protection Agency (EPA) fuel efficiency test results, the U.S. Bureau of Labor Statistics (BLS) retail pump price series, and the Lundberg Survey, Inc., price series for 1994.

128

Energy Balance Modulates Mouse Skin Tumor Promotion through Altered IGF-1R and EGFR Crosstalk  

Science Journals Connector (OSTI)

...and growth factor starved for...Results Dietary energy balance effects...malignant conversion (see also...that dietary energy balance modulated...steady-state growth factor signaling...Berger NA.Energy balance, host-related factors, and cancer...

Tricia Moore; Linda Beltran; Steve Carbajal; Stephen D. Hursting; and John DiGiovanni

2012-10-01T23:59:59.000Z

129

2007 Status Report - Savings Estimates for the ENERGY STAR Voluntary  

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

7 Status Report - Savings Estimates for the ENERGY STAR Voluntary 7 Status Report - Savings Estimates for the ENERGY STAR Voluntary Labeling Program Title 2007 Status Report - Savings Estimates for the ENERGY STAR Voluntary Labeling Program Publication Type Journal Article LBNL Report Number LBNL-56380 Year of Publication 2007 Authors Sanchez, Marla C., Carrie A. Webber, Richard E. Brown, and Gregory K. Homan Pagination 38 Date Published 03/2007 Publisher Lawrence Berkeley National Laboratory ISBN Number LBNL-56380(2007) Keywords Enduse, Energy End-Use Forecasting, EUF Abstract ENERGY STAR® is a voluntary labeling program designed to identify and promote energy-efficient products, buildings and practices. Operated jointly by the Environmental Protection Agency (EPA) and the U.S. Department of Energy (DOE), ENERGY STAR labels exist for more than thirty products, spanning office equipment, residential heating and cooling equipment, commercial and residential lighting, home electronics, and major appliances. This report presents savings estimates for a subset of ENERGY STAR labeled products. We present estimates of the energy, dollar and carbon savings achieved by the program in the year 2006, what we expect in 2007, and provide savings forecasts for two market penetration scenarios for the periods 2007 to 2015 and 2007 to 2025. The target market penetration forecast represents our best estimate of future ENERGY STAR savings. It is based on realistic market penetration goals for each of the products. We also provide a forecast under the assumption of 100 percent market penetration; that is, we assume that all purchasers buy ENERGY STAR-compliant products instead of standard efficiency products throughout the analysis period.

130

2005 Status Report - Savings Estimates for the ENERGY STAR Voluntary  

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

5 Status Report - Savings Estimates for the ENERGY STAR Voluntary 5 Status Report - Savings Estimates for the ENERGY STAR Voluntary Labeling Program Title 2005 Status Report - Savings Estimates for the ENERGY STAR Voluntary Labeling Program Publication Type Journal Article LBNL Report Number LBNL-56380 Year of Publication 2007 Authors Sanchez, Marla C., Carrie A. Webber, Richard E. Brown, and Gregory K. Homan Pagination 35 Date Published 03/2006 Publisher Lawrence Berkeley National Laboratory ISBN Number LBNL-56380(2005) Keywords Enduse, Energy End-Use Forecasting, EUF Abstract ENERGY STAR is a voluntary labeling program designed to identify and promote energy-efficient products, buildings and practices. Operated jointly by the Environmental Protection Agency (EPA) and the U.S. Department of Energy (DOE), Energy Star labels exist for more than forty products, spanning office equipment, residential heating and cooling equipment, commercial and residential lighting, home electronics, and major appliances. This report presents savings estimates for a subset of ENERGY STAR labeled products. We present estimates of the energy, dollar and carbon savings achieved by the program in the year 2004, what we expect in 2005, and provide savings forecasts for two market penetration scenarios for the periods 2005 to 2010 and 2005 to 2020. The target market penetration forecast represents our best estimate of future ENERGY STAR savings. It is based on realistic market penetration goals for each of the products. We also provide a forecast under the assumption of 100 percent market penetration; that is, we assume that all purchasers buy ENERGY STAR-compliant products instead of standard efficiency products throughout the analysis period.

131

2006 Status Report - Savings Estimates for the ENERGY STAR Voluntary  

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

6 Status Report - Savings Estimates for the ENERGY STAR Voluntary 6 Status Report - Savings Estimates for the ENERGY STAR Voluntary Labeling Program Title 2006 Status Report - Savings Estimates for the ENERGY STAR Voluntary Labeling Program Publication Type Journal Article LBNL Report Number LBNL-56380 Year of Publication 2007 Authors Sanchez, Marla C., Carrie A. Webber, Richard E. Brown, and Gregory K. Homan Pagination 38 Date Published March 2006 Publisher Lawrence Berkeley National Laboratory ISBN Number LBNL-56380(2006) Keywords Enduse, Energy End-Use Forecasting, EUF Abstract ENERGY STAR® is a voluntary labeling program designed to identify and promote energy-efficient products, buildings and practices. Operated jointly by the Environmental Protection Agency (EPA) and the U.S. Department of Energy (DOE), ENERGY STAR labels exist for more than thirty products, spanning office equipment, residential heating and cooling equipment, commercial and residential lighting, home electronics, and major appliances. This report presents savings estimates for a subset of ENERGY STAR labeled products. We present estimates of the energy, dollar and carbon savings achieved by the program in the year 2005, what we expect in 2006, and provide savings forecasts for two market penetration scenarios for the periods 2006 to 2015 and 2006 to 2025. The target market penetration forecast represents our best estimate of future ENERGY STAR savings. It is based on realistic market penetration goals for each of the products. We also provide a forecast under the assumption of 100 percent market penetration; that is, we assume that all purchasers buy ENERGY STAR-compliant products instead of standard efficiency products throughout the analysis period.

132

Energy-Efficient Modulation Design for Reliable Communication in Wireless Networks  

E-Print Network [OSTI]

Energy-Efficient Modulation Design for Reliable Communication in Wireless Networks Qing Chen transmit power scenarios. We have noted that variable power schemes can attain higher energy-efficiencies. The analysis of energy-efficient modulation design is also conducted in multi- hop linear networks

Gursoy, Mustafa Cenk

133

Uncertainty estimation improves energy measurement and verification procedures  

Science Journals Connector (OSTI)

Abstract Implementing energy conservation measures in buildings can reduce energy costs and environmental impacts, but such measures cost money to implement so intelligent investment strategies require the ability to quantify the energy savings by comparing actual energy used to how much energy would have been used in absence of the conservation measures (known as the baseline energy use). Methods exist for predicting baseline energy use, but a limitation of most statistical methods reported in the literature is inadequate quantification of the uncertainty in baseline energy use predictions. However, estimation of uncertainty is essential for weighing the risks of investing in retrofits. Most commercial buildings have, or soon will have, electricity meters capable of providing data at short time intervals. These data provide new opportunities to quantify uncertainty in baseline predictions, and to do so after shorter measurement durations than are traditionally used. In this paper, we show that uncertainty estimation provides greater measurement and verification (M&V) information and helps to overcome some of the difficulties with deciding how much data is needed to develop baseline models and to confirm energy savings. We also show that cross-validation is an effective method for computing uncertainty. In so doing, we extend a simple regression-based method of predicting energy use using short-interval meter data. We demonstrate the methods by predicting energy use in 17 real commercial buildings. We discuss the benefits of uncertainty estimates which can provide actionable decision making information for investing in energy conservation measures.

Travis Walter; Phillip N. Price; Michael D. Sohn

2014-01-01T23:59:59.000Z

134

Uncertainty Estimation Improves Energy Measurement and Verification Procedures  

SciTech Connect (OSTI)

Implementing energy conservation measures in buildings can reduce energy costs and environmental impacts, but such measures cost money to implement so intelligent investment strategies require the ability to quantify the energy savings by comparing actual energy used to how much energy would have been used in absence of the conservation measures (known as the baseline energy use). Methods exist for predicting baseline energy use, but a limitation of most statistical methods reported in the literature is inadequate quantification of the uncertainty in baseline energy use predictions. However, estimation of uncertainty is essential for weighing the risks of investing in retrofits. Most commercial buildings have, or soon will have, electricity meters capable of providing data at short time intervals. These data provide new opportunities to quantify uncertainty in baseline predictions, and to do so after shorter measurement durations than are traditionally used. In this paper, we show that uncertainty estimation provides greater measurement and verification (M&V) information and helps to overcome some of the difficulties with deciding how much data is needed to develop baseline models and to confirm energy savings. We also show that cross-validation is an effective method for computing uncertainty. In so doing, we extend a simple regression-based method of predicting energy use using short-interval meter data. We demonstrate the methods by predicting energy use in 17 real commercial buildings. We discuss the benefits of uncertainty estimates which can provide actionable decision making information for investing in energy conservation measures.

Walter, Travis; Price, Phillip N.; Sohn, Michael D.

2014-05-14T23:59:59.000Z

135

Estimating the rebound effect in US manufacturing energy consumption  

Science Journals Connector (OSTI)

The energy price shocks of the 1970s are usually assumed to have increased the search for new energy saving technologies where eventual gains in energy efficiencies will reduce the real per unit price of energy services and hence, the consumption of energy will rise and partially offset the initial reduction in the usage of energy sources. This is the rebound effect, which is estimated for the US manufacturing sector using time series data applying the dynamic OLS method (DOLS). When allowing for asymmetric price effects the rebound effect is found to be approximately 24% for the US manufacturing sector.

Jan Bentzen

2004-01-01T23:59:59.000Z

136

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 12 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module forecasts energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region forecast using the SEDS 27 data.

137

Estimating Marginal Residential Energy Prices in the Analysis of Proposed  

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

Marginal Residential Energy Prices in the Analysis of Proposed Marginal Residential Energy Prices in the Analysis of Proposed Appliance Energy Efficiency Standards Title Estimating Marginal Residential Energy Prices in the Analysis of Proposed Appliance Energy Efficiency Standards Publication Type Report LBNL Report Number LBNL-44230 Year of Publication 2000 Authors Chaitkin, Stuart, James E. McMahon, Camilla Dunham Whitehead, Robert D. Van Buskirk, and James D. Lutz Document Number LBNL-44230 Date Published March 1 Publisher Lawrence Berkeley National Laboratory City Berkeley Abstract Use of marginal energy prices, instead of average energy prices, represents a theoretically valuable and challenging refinement to the usual life-cycle cost analysis conducted for proposed appliance energy efficiency standards. LBNL developed a method to estimate marginal residential energy prices using a regression analysis based on a nationally representative sample of actual consumer energy bills. Based on the 1997 Residential Energy Consumption Survey (RECS), national mean marginal electricity prices were estimated to be 2.5% less than average electricity prices in the summer and 10.0% less than average prices in the non-summer months. For natural gas, marginal prices were 4.4% less than average prices in the winter and 15.3% less than average prices in the non-winter months.

138

Improved Coefficient Calculator for the California Energy Commission 6 Parameter Photovoltaic Module Model  

SciTech Connect (OSTI)

This paper describes an improved algorithm for calculating the six parameters required by the California Energy Commission (CEC) photovoltaic (PV) Calculator module model. Rebate applications in California require results from the CEC PV model, and thus depend on an up-to-date database of module characteristics. Currently, adding new modules to the database requires calculating operational coefficients using a general purpose equation solver - a cumbersome process for the 300+ modules added on average every month. The combination of empirical regressions and heuristic methods presented herein achieve automated convergence for 99.87% of the 5487 modules in the CEC database and greatly enhance the accuracy and efficiency by which new modules can be characterized and approved for use. The added robustness also permits general purpose use of the CEC/6 parameter module model by modelers and system analysts when standard module specifications are known, even if the module does not exist in a preprocessed database.

Dobos, A. P.

2012-05-01T23:59:59.000Z

139

Econometric Estimation of the Aggregate Impacts of Energy Efficiency  

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

Econometric Estimation of the Aggregate Impacts of Energy Efficiency Econometric Estimation of the Aggregate Impacts of Energy Efficiency Programs: Report on a California Pilot Study Speaker(s): Marvin J. Horowitz Date: February 26, 2013 - 2:00pm Location: 90-3075 Seminar Host/Point of Contact: Alan Sanstad The California Public Utilities Commission (CPUC) recently funded a study in which local area aggregated electricity and natural gas consumption in California from 2006 through 2010 were analyzed econometrically. Data were available to estimate electricity energy efficiency program impacts for two of the three large California investor-owned utilities. The findings indicate that net savings from these programs for the 2006-2010 period amounted to 11,391 GWh, or 7.3 percent of annual electricity consumption. This point estimate is 50 percent higher than the CPUC

140

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

SciTech Connect (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

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

The artificial neural network model to estimate the photovoltaic modul efficiency for all regions of the Turkey  

Science Journals Connector (OSTI)

Abstract Artificial neural network (ANN) is a useful tool that using estimates behavior of the most of engineering applications. In the present study, ANN model has been used to estimate the temperature, efficiency and power of the Photovoltaic module according to outlet air temperature and solar radiation. An experimental system consisted photovoltaic module, heating and cooling sub systems, proportional integral derivative (PID) control unit was designed and built. Tests were realized at the outdoors for the constant ambient air temperatures of photovoltaic module. To preserve ambient air temperature at the determined constant values as 10, 20, 30 and 40C, cooling and heating subsystems which connected PID control unit were used in the test apparatus. Ambient air temperature, solar radiation, back surface of the photovoltaic module temperature was measured in the experiments. Obtained data were used to estimate the photovoltaic module temperature, efficiency and power with using ANN approach for all 7 region of the Turkey. The study dealing with this paper not only will beneficial for the limited region but also in all region of Turkey which will be thought established of photovoltaic panels by the manufacturer, researchers and etc.

?lhan Ceylan; Engin Gedik; Okan Erkaymaz; Ali Etem Grel

2014-01-01T23:59:59.000Z

142

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

143

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 non-manufacturing industries. The manufacturing industries are further subdivided into the energy- intensive manufacturing industries and non-energy-intensive manufacturing industries (Table 6.1). The manufacturing industries are modeled through the use of a detailed process-flow or end-use accounting procedure, whereas the non- manufacturing industries are modeled with substantially less detail. The petroleum refining industry is not included in the Industrial Demand Module, as it is simulated separately in the Petroleum Market Module of NEMS. The Industrial Demand Module calculates energy consumption for the four Census Regions (see Figure 5) and disaggregates the energy consumption

144

Estimate Greenhouse Gas Emissions by Building Type | Department of Energy  

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

Estimate Greenhouse Gas Emissions by Building Type Estimate Greenhouse Gas Emissions by Building Type Estimate Greenhouse Gas Emissions by Building Type October 7, 2013 - 10:51am Addthis YOU ARE HERE Step 2 Starting with the programs contributing the greatest proportion of building greenhouse gas (GHG) emissions, the agency should next determine which building types operated by those programs use the most energy (Figure 1). Energy intensity is evaluated instead of emissions in this approach because programs may not have access to emissions data by building type. Figure 1 - An image of an organizational-type chart. A rectangle labeled 'Program 1' has lines pointing to three other rectangles below it labeled 'Building Type 1,' 'Building Type 2,' and 'Building Type 3.' Next to the building types it says, 'Step 2. Estimate emissions by building type.

145

EIA-Assumptions to the Annual Energy Outlook - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumptions to the Annual Energy Outlook 2007 Oil and Gas Supply Module 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

146

Order Module--THE CONTROL OF HAZARDOUS ENERGY (LOCKOUT/TAGOUT) FAMILIAR  

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

THE CONTROL OF HAZARDOUS ENERGY (LOCKOUT/TAGOUT) THE CONTROL OF HAZARDOUS ENERGY (LOCKOUT/TAGOUT) FAMILIAR LEVEL Order Module--THE CONTROL OF HAZARDOUS ENERGY (LOCKOUT/TAGOUT) FAMILIAR LEVEL The familiar level of this module is divided into two sections. In the first section, we will discuss the purpose of 29 CFR 1910.147 and the terms associated with the standard. In the second section, we will discuss the requirements in the standard. We have provided examples throughout the module to help familiarize you with the material. The examples will also help prepare you for the practice at the end of this module and the criterion test. Most of what you will need to know to complete this module is contained in the module. However, before continuing, you should obtain a copy of the standard. Copies of the standard are available at

147

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

148

Flat-Plate Photovoltaic Module Basics | Department of Energy  

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

Module Basics Module Basics Flat-Plate Photovoltaic Module Basics August 20, 2013 - 4:25pm Addthis Flat-plate photovoltaic (PV) modules are made of several components, including the front surface materials, encapsulant, rear surface, and frame. Front Surface Materials The front surface of a flat-plate PV module must have a high transmission in the wavelengths that can be used by the solar cells in the module. For example, for silicon solar cells, the top surface must have high transmission of light with wavelengths from 350 to 1200 nm. Also, reflection from the front surface should be minimal. An antireflection coating added to the top surface can greatly reduce the reflection of sunlight, and texturing of the surface can cause light that strikes the surface to stay within the cells. Unfortunately, these textured

149

Integrated Modules for Bioassay (IMBA) | Department of Energy  

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

Integrated Modules for Bioassay (IMBA) Integrated Modules for Bioassay (IMBA) Integrated Modules for Bioassay (IMBA) Current Central Registry Toolbox Version(s): IMBA ExpertTM USDOE Edition version 4.0.28 Code Owner: UK Health Protection Agency (HPA) Description: IMBA ExpertTM (IX) software suite comprises a series of independent modules (referred to as sub-modules) that implement the International Commission on Radiological Protection (ICRP) Publication 66, Human Respiratory Tract Model (HRTM) and the ICRP Publications 30 (series), 67, 68, 69, and 71 biokinetic models. In 2001, the United Kingdom (UK) National Radiological Protection Board (NRPB), whose functions were absorbed later into the UK Health Protection Agency (HPA), and ACJ & Associates Inc., began development of an interface (referred to as a shell) for the IMBA modules. This effort was funded in

150

Estimating Demand Response Market Potential | Open Energy Information  

Open Energy Info (EERE)

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

151

Dietary Energy Balance Modulation of Kras- and Ink4a/Arf+/?-Driven Pancreatic Cancer: The Role of Insulin-like Growth Factor-I  

Science Journals Connector (OSTI)

...research-article Research Articles Dietary Energy Balance Modulation of Kras- and Ink4a...we tested the hypothesis that dietary energy balance modulation impacts pancreatic...with IGF-I infusion. Thus, dietary energy balance modulation impacts spontaneous...

Laura M. Lashinger; Lauren M. Harrison; Audrey J. Rasmussen; Craig D. Logsdon; Susan M. Fischer; Mark J. McArthur; Stephen D. Hursting

2013-10-01T23:59:59.000Z

152

Order Module--NNSA OCCUPATIONAL RADIATION PROTECTION | Department of Energy  

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

Order Module--NNSA OCCUPATIONAL RADIATION PROTECTION Order Module--NNSA OCCUPATIONAL RADIATION PROTECTION Order Module--NNSA OCCUPATIONAL RADIATION PROTECTION The familiar level of this module is designed to provide the basic information to meet the requirements that are related to 10 CFR 835, "Occupational Radiation Protection," in the following DOE Functional Area Qualification Standards: DOE-STD-1177-2004, Emergency Management DOE-STD-1151-2002, Facility Representative DOE-STD-1146-2007, General Technical Base DOE-STD-1138-2007, Industrial Hygiene DOE-STD-1183-2007, Nuclear Safety Specialist DOE-STD-1174-2003, Radiation Protection DOE-STD-1175-2006, Senior Technical Safety Manager DOE-STD-1178-2004, Technical Program Manager DOE-STD-1155-2002, Transportation and Traffic Management DOE Order Self Study Modules - 10 CFR 835 Occupational Radiation Protection

153

"Order Module--DOE O 442.1, DEPARTMENT OF ENERGY EMPLOYEE CONCERNS PROGRAM  

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

"Order Module--DOE O 442.1, DEPARTMENT OF ENERGY EMPLOYEE CONCERNS "Order Module--DOE O 442.1, DEPARTMENT OF ENERGY EMPLOYEE CONCERNS PROGRAM "Order Module--DOE O 442.1, DEPARTMENT OF ENERGY EMPLOYEE CONCERNS PROGRAM The familiar level of this module is divided into two sections. In the first section, we will discuss the objectives, requirements, responsibilities, and definitions that are contained in the Order. In the second section, we will discuss the Guide. There is only one level of instruction for this Order. You will not be required to complete a practice for this module. Before continuing, you should obtain a copy of DOE O 442.1, DOE Employee Concerns Program, and its companion guide. Copies of these documents are available on the Office of Management and Administration's Web site at http://www.directives.doe.gov or though the course manager. It is not

154

Standard Review Plan (SRP) Modules | Department of Energy  

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

Quality Assurance » Standard Quality Assurance » Standard Review Plan (SRP) Modules Standard Review Plan (SRP) Modules Standard Review Plan - Critical Decision Handbook Overview Project Management Project Execution Plan Review Module (RM) Risk Management RM Integrated Project Team RM Earned Value Management System RM Acquisition Strategy RM Decommissioning Plan RM Site Transition Guidance Engineering and Design Conceptual Design RM Preliminary Design RM Final Design RM Construction Readiness RM Checkout, Testing, and Commissioning Plan RM Readiness Review RM Seismic Design Expectations Report Technology Readiness Assessment Report External Technical Review Report Preparation for Facility Operations RM Safety Safety Design Strategy RM Conceptual Safety Design RM Preliminary Safety Design RM Facility Disposition Safety Strategy RM

155

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

ABORATORY Estimating Total Energy Consumption and Emissionscomponent of Chinas total energy consumption mix. However,about 19% of Chinas total energy consumption, while others

Fridley, David G.

2008-01-01T23:59:59.000Z

156

Solar energy trapping with modulated silicon nanowire photonic crystals Guillaume Demsy and Sajeev John  

E-Print Network [OSTI]

Solar energy trapping with modulated silicon nanowire photonic crystals Guillaume Demésy and Sajeev by the American Institute of Physics. Related Articles Solar power conversion efficiency in modulated silicon utilizing multiple carrier generation via singlet exciton fission Appl. Phys. Lett. 101, 153507 (2012) Light

John, Sajeev

157

Integrating Photovoltaic Inverter Reliability into Energy Yield Estimation with Markov Models  

E-Print Network [OSTI]

Integrating Photovoltaic Inverter Reliability into Energy Yield Estimation with Markov Models of the inverters. Keywords-Photovoltaic energy conversion, Markov reliability models, utility-interactive inverters, energy yield estimation. I. INTRODUCTION Photovoltaic systems have gained prominence as economically

Liberzon, Daniel

158

Energy Savings Estimates and Cost Benefit Calculations for High Performance Relocatable Classrooms  

E-Print Network [OSTI]

1 Energy Savings Estimates and Cost Benefit Calculations for High Element 6, Project 2.1.2: Energy Savings Estimates and Cost Benefit Calculations for High Performance Hoeschele2 1 Environmental Energy Technologies Division Indoor Environment Department

159

Order Module--RADIATION PROTECTION PROGRAMS GUIDE | Department of Energy  

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

RADIATION PROTECTION PROGRAMS GUIDE RADIATION PROTECTION PROGRAMS GUIDE Order Module--RADIATION PROTECTION PROGRAMS GUIDE The familiar level of this module is designed to provide the basic information related to DOE G 441.1-1C, Radiation Protection Programs Guide, as required in DOE-STD-1174-2003, Radiation Protection Functional Area Qualification Standard, December 2003. Completion of this module also meets certain requirements associated with the DOE Facility Representative Program and the DOE Intern Program. The information contained in this module addresses specific requirements and as such does not include the entire text of the source document. Before continuing, you should obtain a copy of the Order. Copies of the DOE Directives are available at http://www.directives.doe.gov/ or through the course manager. In March

160

GIZ Sourcebook Module 4d: Natural Gas Vehicles | Open Energy...  

Open Energy Info (EERE)

d: Natural Gas Vehicles Jump to: navigation, search Tool Summary LAUNCH TOOL Name: GIZ Sourcebook Module 4d: Natural Gas Vehicles AgencyCompany Organization: GIZ ComplexityEase...

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

Modulation and Measurement of Time-Energy Entangled Photons  

E-Print Network [OSTI]

We describe a proof-of-principal experiment demonstrating a Fourier technique for measuring the shape of biphoton wavepackets. The technique is based on the use of synchronously driven fast modulators and slow (integrating) detectors.

Chinmay Belthangady; Shengwang Du; Chih-Sung Chuu; G. Y. Yin; S. E. Harris

2009-06-18T23:59:59.000Z

162

A Buildings Module for the Stochastic Energy Deployment System  

E-Print Network [OSTI]

F.W. Dodge 1991: Building Stock Database Methodology andEnd-Use Flow Maps for the Buildings Sector, D.B. Belzer,N ATIONAL L ABORATORY A Buildings Module for the Stochastic

Marnay, Chris

2008-01-01T23:59:59.000Z

163

Current-Induced Modulation of the Ocean Wave Spectrum and the Role of Nonlinear Energy Transfer  

Science Journals Connector (OSTI)

Numerical simulations were performed to investigate current-induced modulation of the spectral and statistical properties of ocean waves advected by idealized and realistic current fields. In particular, the role of nonlinear energy transfer ...

Hitoshi Tamura; Takuji Waseda; Yasumasa Miyazawa; Kosei Komatsu

2008-12-01T23:59:59.000Z

164

Project Profile: Sensible Heat, Direct, Dual-Media Thermal Energy Storage Module  

Broader source: Energy.gov [DOE]

Acciona Solar, under the Thermal Storage FOA, plans to develop a prototype thermal energy storage (TES) module with high efficiency. This project is looking at a packed or structured bed TES tank with molten salt flowing through it.

165

Dynamical systems in nanophotonics: From energy efficient modulators to light forces and optomechanics  

E-Print Network [OSTI]

We demonstrate novel device concepts based on rigorous design of the dynamics of resonant nanophotonic systems, such as dispersionless resonant switches and energy-efficient mo-dulator architectures, slow-light cells, and ...

Kaertner, Franz X.

166

Estimated United States Residential Energy Use in 2005  

SciTech Connect (OSTI)

A flow chart depicting energy flow in the residential sector of the United States economy in 2005 has been constructed from publicly available data and estimates of national energy use patterns. Approximately 11,000 trillion British Thermal Units (trBTUs) of electricity and fuels were used throughout the United States residential sector in lighting, electronics, air conditioning, space heating, water heating, washing appliances, cooking appliances, refrigerators, and other appliances. The residential sector is powered mainly by electricity and natural gas. Other fuels used include petroleum products (fuel oil, liquefied petroleum gas and kerosene), biomass (wood), and on-premises solar, wind, and geothermal energy. The flow patterns represent a comprehensive systems view of energy used within the residential sector.

Smith, C A; Johnson, D M; Simon, A J; Belles, R D

2011-12-12T23:59:59.000Z

167

Actual and Estimated Energy Savings Comparison for Deep Energy Retrofits in the Pacific Northwest  

SciTech Connect (OSTI)

Seven homes from the Pacific Northwest were selected to evaluate the differences between estimated and actual energy savings achieved from deep energy retrofits. The energy savings resulting from these retrofits were estimated, using energy modeling software, to save at least 30% on a whole-house basis. The modeled pre-retrofit energy use was trued against monthly utility bills. After the retrofits were completed, each of the homes was extensively monitored, with the exception of one home which was monitored pre-retrofit. This work is being conducted by Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy Building Technologies Program as part of the Building America Program. This work found many discrepancies between actual and estimated energy savings and identified the potential causes for the discrepancies. The differences between actual energy use and modeled energy use also suggest improvements to improve model accuracy. The difference between monthly whole-house actual and estimated energy savings ranged from 75% more energy saved than predicted by the model to 16% less energy saved for all the monitored homes. Similarly, the annual energy savings difference was between 36% and -14%, which was estimated based on existing monitored savings because an entire year of data is not available. Thus, on average, for all six monitored homes the actual energy use is consistently less than estimates, indicating home owners are saving more energy than estimated. The average estimated savings for the eight month monitoring period is 43%, compared to an estimated savings average of 31%. Though this average difference is only 12%, the range of inaccuracies found for specific end-uses is far greater and are the values used to directly estimate energy savings from specific retrofits. Specifically, the monthly post-retrofit energy use differences for specific end-uses (i.e., heating, cooling, hot water, appliances, etc.) ranged from 131% under-predicted to 77% over-predicted by the model with respect to monitored energy use. Many of the discrepancies were associated with occupant behavior which influences energy use, dramatically in some cases, actual versus modeled weather differences, modeling input limitations, and complex homes that are difficult to model. The discrepancy between actual and estimated energy use indicates a need for better modeling tools and assumptions. Despite the best efforts of researchers, the estimated energy savings are too inaccurate to determine reliable paybacks for retrofit projects. While the monitored data allows researchers to understand why these differences exist, it is not cost effective to monitor each home with the level of detail presented here. Therefore an appropriate balance between modeling and monitoring must be determined for more widespread application in retrofit programs and the home performance industry. Recommendations to address these deficiencies include: (1) improved tuning process for pre-retrofit energy use, which currently utilized broad-based monthly utility bills; (2) developing simple occupant-based energy models that better address the many different occupant types and their impact on energy use; (3) incorporating actual weather inputs to increase accuracy of the tuning process, which uses utility bills from specific time period; and (4) developing simple, cost-effective monitoring solutions for improved model tuning.

Blanchard, Jeremy; Widder, Sarah H.; Giever, Elisabeth L.; Baechler, Michael C.

2012-10-01T23:59:59.000Z

168

Alternative energy estimation from the shower lateral distribution function  

E-Print Network [OSTI]

The surface detector technique has been successfully used to detect cosmic ray showers for several decades. Scintillators or Cerenkov water tanks can be used to measure the number of particles and/or the energy density at a given depth in the atmosphere and reconstruct the primary particle properties. It has been shown that the experiment configuration and the resolution in reconstructing the core position determine a distance to the shower axis in which the lateral distribution function (LDF) of particles shows the least variation with respect to different primary particles type, simulation models and specific shapes of the LDF. Therefore, the signal at this distance (600 m for Haverah Park and 1000 m for Auger Observatory) has shown to be a good estimator of the shower energy. Revisiting the above technique, we show that a range of distances to the shower axis, instead of one single point, can be used as estimator of the shower energy. A comparison is done for the Auger Observatory configuration and the new estimator proposed here is shown to be a good and robust alternative to the standard single point procedure.

Vitor de Souza; Carlos O. Escobar; Joel Brito; Carola Dobrigkeit; Gustavo Medina-Tanco

2005-09-16T23:59:59.000Z

169

Statistical physics inspired energy-efficient coded-modulation for optical communications  

E-Print Network [OSTI]

constellation design. We demonstrate that statistical physics inspired energy-efficient (EE) signal an energy- efficient signal constellation design algorithm (EE- SCDA). In the absence of noise, the optimumStatistical physics inspired energy-efficient coded- modulation for optical communications Ivan B

Djordjevic, Ivan B.

170

COMPRESSED-AIR ENERGY STORAGE SYSTEMS FOR STAND-ALONE OFF-GRID PHOTOVOLTAIC MODULES  

E-Print Network [OSTI]

COMPRESSED-AIR ENERGY STORAGE SYSTEMS FOR STAND-ALONE OFF-GRID PHOTOVOLTAIC MODULES Dominique materials, flywheels, pumped hydro (PH), superconducting magnetic energy storage (SMES) and compressed air-grid alternative to the large-scale compressed air energy storage systems we propose to examine the viability

Deymier, Pierre

171

EK 131/132 module: Introduction to Wind Energy MW 3-5  

E-Print Network [OSTI]

EK 131/132 module: Introduction to Wind Energy MW 3-5 Course. This course provides an overview of wind turbine technology and energy concepts. The question of whether wind. Students will measure personal energy use and analyze wind turbine data from the Museum of Science's wind

172

Dietary Energy Balance Modulates Prostate Cancer Progression in Hi-Myc Mice  

Science Journals Connector (OSTI)

...research-article Research Articles Dietary Energy Balance Modulates Prostate Cancer...signaling may play a role in dietary energy balance effects on prostate...control and DIO diet groups show a mix of in situ and invasive adenocarcinomas...conducted to identify dietary energy balance-related changes in...

Jorge Blando; Tricia Moore; Stephen Hursting; Guiyu Jiang; Achinto Saha; Linda Beltran; Jianjun Shen; John Repass; Sara Strom; and John DiGiovanni

2011-12-01T23:59:59.000Z

173

Additional Resources for Estimating Building Energy and Cost Savings to Reduce Greenhouse Gases  

Broader source: Energy.gov [DOE]

For evaluating greenhouse gas reduction strategies and estimating costs, the following information resources can help Federal agencies estimate energy and cost savings potential by building type.

174

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

SciTech Connect (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

175

DEVELOPMENT OF A LOW COST INFERENTIAL NATURAL GAS ENERGY FLOW RATE PROTOTYPE RETROFIT MODULE  

SciTech Connect (OSTI)

In 1998, Southwest Research Institute began a multi-year project to develop a working prototype instrument module for natural gas energy measurement. The module will be used to retrofit a natural gas custody transfer flow meter for energy measurement, at a cost an order of magnitude lower than a gas chromatograph. Development and evaluation of the prototype energy meter in 2002-2003 included: (1) refinement of the algorithm used to infer properties of the natural gas stream, such as heating value; (2) evaluation of potential sensing technologies for nitrogen content, improvements in carbon dioxide measurements, and improvements in ultrasonic measurement technology and signal processing for improved speed of sound measurements; (3) design, fabrication and testing of a new prototype energy meter module incorporating these algorithm and sensor refinements; and (4) laboratory and field performance tests of the original and modified energy meter modules. Field tests of the original energy meter module have provided results in close agreement with an onsite gas chromatograph. The original algorithm has also been tested at a field site as a stand-alone application using measurements from in situ instruments, and has demonstrated its usefulness as a diagnostic tool. The algorithm has been revised to use measurement technologies existing in the module to measure the gas stream at multiple states and infer nitrogen content. The instrumentation module has also been modified to incorporate recent improvements in CO{sub 2} and sound speed sensing technology. Laboratory testing of the upgraded module has identified additional testing needed to attain the target accuracy in sound speed measurements and heating value.

E. Kelner; D. George; T. Morrow; T. Owen; M. Nored; R. Burkey; A. Minachi

2005-05-01T23:59:59.000Z

176

GAO Cost Estimating and Assessment Guide | Department of Energy  

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

Cost Estimating and Assessment Guide GAO Cost Estimating and Assessment Guide GAO 12-Step Estimating Process.pdf More Documents & Publications EIR SOP Septmebr 2010 Microsoft Word...

177

CORONAL MASS EJECTION MASS, ENERGY, AND FORCE ESTIMATES USING STEREO  

SciTech Connect (OSTI)

Understanding coronal mass ejection (CME) energetics and dynamics has been a long-standing problem, and although previous observational estimates have been made, such studies have been hindered by large uncertainties in CME mass. Here, the two vantage points of the Solar Terrestrial Relations Observatory (STEREO) COR1 and COR2 coronagraphs were used to accurately estimate the mass of the 2008 December 12 CME. Acceleration estimates derived from the position of the CME front in three dimensions were combined with the mass estimates to calculate the magnitude of the kinetic energy and driving force at different stages of the CME evolution. The CME asymptotically approaches a mass of 3.4 {+-} 1.0 Multiplication-Sign 10{sup 15} g beyond {approx}10 R{sub Sun }. The kinetic energy shows an initial rise toward 6.3 {+-} 3.7 Multiplication-Sign 10{sup 29} erg at {approx}3 R{sub Sun }, beyond which it rises steadily to 4.2 {+-} 2.5 Multiplication-Sign 10{sup 30} erg at {approx}18 R{sub Sun }. The dynamics are described by an early phase of strong acceleration, dominated by a force of peak magnitude of 3.4 {+-} 2.2 Multiplication-Sign 10{sup 14} N at {approx}3 R{sub Sun }, after which a force of 3.8 {+-} 5.4 Multiplication-Sign 10{sup 13} N takes effect between {approx}7 and 18 R{sub Sun }. These results are consistent with magnetic (Lorentz) forces acting at heliocentric distances of {approx}<7 R{sub Sun }, while solar wind drag forces dominate at larger distances ({approx}>7 R{sub Sun }).

Carley, Eoin P.; Gallagher, Peter T. [Astrophysics Research Group, School of Physics, Trinity College Dublin, Dublin 2 (Ireland); McAteer, R. T. James [Department of Astronomy, New Mexico State University, Las Cruces, NM 88003-8001 (United States)

2012-06-10T23:59:59.000Z

178

NREL-How to Estimate the Economic Impacts from Renewable Energy Webinar |  

Open Energy Info (EERE)

NREL-How to Estimate the Economic Impacts from Renewable Energy Webinar NREL-How to Estimate the Economic Impacts from Renewable Energy Webinar (Redirected from How to Estimate the Economic Impacts from Renewable Energy) Jump to: navigation, search Tool Summary LAUNCH TOOL Name: How to Estimate the Economic Impacts from Renewable Energy Agency/Company /Organization: National Renewable Energy Laboratory Sector: Energy Topics: Co-benefits assessment Resource Type: Webinar, Training materials Website: www.nrel.gov/applying_technologies/state_local_activities/webinar_2009 How to Estimate the Economic Impacts from Renewable Energy Screenshot References: How to Estimate the Economic Impacts from Renewable Energy[1] Logo: How to Estimate the Economic Impacts from Renewable Energy Sponsored by the U.S. Department of Energy Technical Assistance Project for

179

Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

180

A Novel Harmony Search Algorithm for One-Year-Ahead Energy Demand Estimation Using Macroeconomic Variables  

Science Journals Connector (OSTI)

In this paper we tackle a problem of one-year ahead energy demand estimation from macroeconomic variables. A modified Harmony ... the proposed approach in a real problem of Energy demand estimation in Spain, from...

Sancho Salcedo-Sanz

2014-01-01T23:59:59.000Z

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

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

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumptions to the Annual Energy Outlook 2007 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) 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, unfinished oil imports, other refinery inputs (including alcohols, ethers, and bioesters), 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

182

Self-oscillating modulators for direct energy conversion audio power amplifiers  

E-Print Network [OSTI]

Self-oscillating modulators for direct energy conversion audio power amplifiers Petar Ljusev1, Denmark Correspondence should be addressed to Petar Ljusev (pl@oersted.dtu.dk) ABSTRACT Direct energy conversion audio power amplifier represents total integration of switching-mode power supply and Class D

183

Elmore Model for Energy Estimation in RC Trees Quming Zhou and Kartik Mohanram  

E-Print Network [OSTI]

Elmore Model for Energy Estimation in RC Trees Quming Zhou and Kartik Mohanram Department This paper presents analysis methods for energy estimation in RC trees driven by time-varying voltage sources]: Design aids--simulation General Terms: Algorithms Keywords: Energy estimation, RC trees, interconnect. 1

Mohanram, Kartik

184

Dietary Modulation of Pancreatic Carcinogenesis: Calories and Energy Expenditure  

Science Journals Connector (OSTI)

...required in order for the HF corn oil diet to stimulate...administration & dosage Eating Energy Intake Female Lung Neoplasms...element of "net utilizable energy." Induction of MTs by...in rats fed HF and LF corn oil diets, restricted...independent of the level of energy intake." Thus, we were...

Theresa Craven-Giles; Anthony R. Tagliaferro; Anne M. Ronan; Karen J. Baumgartner; and B. D. Roebuck

1994-04-01T23:59:59.000Z

185

Capacity estimation and code design principles for continuous phase modulation (CPM)  

E-Print Network [OSTI]

is represented as Y n = Sn + Zn 1 < n < Ns. The received signal is processed by the demodulator to produce the 12 symbol likelihoods (n) = [Prob(Xn = 0);Prob(Xn = 1);:::;Prob(Xn = M 1)] for each discrete time instant n 2 [1;2;:::;Ns]. The M-ary CPM modulator... the properties of the channel make it easy to find the distribution that maximizes the mutual information. For channels with memory the information theoretic definition of capacity is maximum of limn!1 1N I(XN1 ; Y N1 ) , over all possible distributions...

Ganesan, Aravind

2004-09-30T23:59:59.000Z

186

Order Module--U.S. DEPARTMENT OF ENERGY ORDERS SELF-STUDY PROGRAM: GETTING  

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

Order Module--U.S. DEPARTMENT OF ENERGY ORDERS SELF-STUDY PROGRAM: Order Module--U.S. DEPARTMENT OF ENERGY ORDERS SELF-STUDY PROGRAM: GETTING STARTED Order Module--U.S. DEPARTMENT OF ENERGY ORDERS SELF-STUDY PROGRAM: GETTING STARTED This course was developed using the Criterion Referenced Instruction (CRI) method of training. That means the course contains only the information you need to perform your job. You will be shown the learning objectives at the beginning of the course. If you think you can demonstrate competency without additional instruction, you may complete the practice at any time. When you complete all of the practices successfully, you may ask the course manager for the criterion test. The familiar level requires that you understand and remember the material. The general level requires that you understand the applicability of the material. If you are unsure of the

187

Modulated power filter compensator for a small renewable wind energy.  

E-Print Network [OSTI]

??This paper has three sections, the first one is related to wind energy, the second is related to power filters used to mitigate the harmonics, (more)

Almadhi, Bassil

2015-01-01T23:59:59.000Z

188

NREL-How to Estimate the Economic Impacts from Renewable Energy Webinar |  

Open Energy Info (EERE)

NREL-How to Estimate the Economic Impacts from Renewable Energy Webinar NREL-How to Estimate the Economic Impacts from Renewable Energy Webinar Jump to: navigation, search Tool Summary LAUNCH TOOL Name: How to Estimate the Economic Impacts from Renewable Energy Agency/Company /Organization: National Renewable Energy Laboratory Sector: Energy Topics: Co-benefits assessment Resource Type: Webinar, Training materials Website: www.nrel.gov/applying_technologies/state_local_activities/webinar_2009 How to Estimate the Economic Impacts from Renewable Energy Screenshot References: How to Estimate the Economic Impacts from Renewable Energy[1] Logo: How to Estimate the Economic Impacts from Renewable Energy Sponsored by the U.S. Department of Energy Technical Assistance Project for state and local officials, this Webinar featured information for

189

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

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module Assumptions to the Annual Energy Outlook 2007 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 seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind.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 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. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon the availability of low-cost energy storage systems.

190

4052 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 57, NO. 10, OCTOBER 2009 Energy Planning for Progressive Estimation in  

E-Print Network [OSTI]

--Decentralized estimation, distributed estima- tion, energy scheduling and planning, incremental estimation, multi4052 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 57, NO. 10, OCTOBER 2009 Energy Planning energy planning algorithm for progressive estimation in multihop sensor networks. Unlike many iterative

Hua, Yingbo

191

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

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2007 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 2007, DOE/EIA- M068(2007). 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.

192

Software-related Energy Footprint of a Wireless Broadband Module  

E-Print Network [OSTI]

on the power consumption. This opens up for potential energy savings by creating better ap- plications Keywords 3G, Energy footprint, Power consumption, Wireless broad- band 1. INTRODUCTION The battery lifetime on performance with limited battery power, we need to employ every possible power saving mea- sure, including

193

Photon energy-modulated radiotherapy: Monte Carlo simulation and treatment planning study  

SciTech Connect (OSTI)

Purpose: To demonstrate the feasibility of photon energy-modulated radiotherapy during beam-on time. Methods: A cylindrical device made of aluminum was conceptually proposed as an energy modulator. The frame of the device was connected with 20 tubes through which mercury could be injected or drained to adjust the thickness of mercury along the beam axis. In Monte Carlo (MC) simulations, a flattening filter of 6 or 10 MV linac was replaced with the device. The thickness of mercury inside the device varied from 0 to 40 mm at the field sizes of 5 x 5 cm{sup 2} (FS5), 10 x 10 cm{sup 2} (FS10), and 20 x 20 cm{sup 2} (FS20). At least 5 billion histories were followed for each simulation to create phase space files at 100 cm source to surface distance (SSD). In-water beam data were acquired by additional MC simulations using the above phase space files. A treatment planning system (TPS) was commissioned to generate a virtual machine using the MC-generated beam data. Intensity modulated radiation therapy (IMRT) plans for six clinical cases were generated using conventional 6 MV, 6 MV flattening filter free, and energy-modulated photon beams of the virtual machine. Results: As increasing the thickness of mercury, Percentage depth doses (PDD) of modulated 6 and 10 MV after the depth of dose maximum were continuously increased. The amount of PDD increase at the depth of 10 and 20 cm for modulated 6 MV was 4.8% and 5.2% at FS5, 3.9% and 5.0% at FS10 and 3.2%-4.9% at FS20 as increasing the thickness of mercury from 0 to 20 mm. The same for modulated 10 MV was 4.5% and 5.0% at FS5, 3.8% and 4.7% at FS10 and 4.1% and 4.8% at FS20 as increasing the thickness of mercury from 0 to 25 mm. The outputs of modulated 6 MV with 20 mm mercury and of modulated 10 MV with 25 mm mercury were reduced into 30%, and 56% of conventional linac, respectively. The energy-modulated IMRT plans had less integral doses than 6 MV IMRT or 6 MV flattening filter free plans for tumors located in the periphery while maintaining the similar quality of target coverage, homogeneity, and conformity. Conclusions: The MC study for the designed energy modulator demonstrated the feasibility of energy-modulated photon beams available during beam-on time. The planning study showed an advantage of energy-and intensity modulated radiotherapy in terms of integral dose without sacrificing any quality of IMRT plan.

Park, Jong Min; Kim, Jung-in; Heon Choi, Chang; Chie, Eui Kyu; Kim, Il Han; Ye, Sung-Joon [Interdiciplinary Program in Radiation Applied Life Science, Seoul National University, Seoul, 110-744, Korea and Department of Radiation Oncology, Seoul National University Hospital, Seoul, 110-744 (Korea, Republic of); Interdiciplinary Program in Radiation Applied Life Science, Seoul National University, Seoul, 110-744 (Korea, Republic of); Department of Radiation Oncology, Seoul National University Hospital, Seoul, 110-744 (Korea, Republic of); Interdiciplinary Program in Radiation Applied Life Science, Seoul National University, Seoul, 110-744 (Korea, Republic of) and Department of Radiation Oncology, Seoul National University Hospital, Seoul, 110-744 (Korea, Republic of); Interdiciplinary Program in Radiation Applied Life Science, Seoul National University, Seoul, 110-744 (Korea, Republic of); Department of Radiation Oncology, Seoul National University Hospital, Seoul, 110-744 (Korea, Republic of) and Department of Intelligent Convergence Systems, Seoul National University, Seoul, 151-742 (Korea, Republic of)

2012-03-15T23:59:59.000Z

194

Non-data aided digital feedforward timing estimators for linear and nonlinear modulations  

E-Print Network [OSTI]

in Rx(1; ). For the square law estimator when there is no aliasing we have [20] ^ = 12 arg n ^ Rx(1; 0) o ; (3.6) Rx(k; ) = 1P Z 1=2 1=2 H(f)H(f + k=P)ej2 (f+k=P) df (3.7) = e j2 k T Z P=2T P=2T Hc(F)Hc(F + k=T)ej2 TF=P dF: 30 Consider... Control. 2 ( T=2;T=2]. (Our model is rather simple and we have not included e ects due to phase o set and multiplicative noise and other such e ects). Symbol timing recovery (STR) involves estimating this delay so that we can sample at the optimal sampling...

Sarvepalli, Pradeep Kiran

2004-09-30T23:59:59.000Z

195

Assumptions to the Annual Energy Outlook - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumption to the Annual Energy Outlook Oil and Gas Supply Module Figure 7. Oil and Gas Supply Model Regions. Having problems, call our National Energy Information Center at 202-586-8800 for help. Table 50. Crude Oil Technically Recoverable Resources (Billion barrels) Printer Friendly Version Crude Oil Resource Category As of January 1, 2002 Undiscovered 56.02 Onshore 19.33 Northeast 1.47 Gulf Coast 4.76 Midcontinent 1.12 Southwest 3.25 Rocky Moutain 5.73 West Coast 3.00 Offshore 36.69 Deep (>200 meter W.D.) 35.01 Shallow (0-200 meter W.D.) 1.69 Inferred Reserves 49.14 Onshore 37.78 Northeast 0.79 Gulf Coast 0.80 Midcontinent 3.73 Southwest 14.61 Rocky Mountain 9.91 West Coast 7.94

196

A qualitative examination of performance and energy yield of photovoltaic modules in southern Norway  

Science Journals Connector (OSTI)

Three different, commercially available photovoltaic modules have been monitored outdoors in the town of Grimstad, Norway. The present paper describes the experimental setup that was implemented, in particular details of the low-cost electronic loads. Results compare measured performance with manufacturer's data, and temperature measurements enable a comparison with performance at standard test condition temperature. Overall, the monocrystalline module performed best both regarding maximum efficiency and overall energy production, whereas the module based on triple junction amorphous silicon technology had the worst performance considering these criteria. The gross numbers of energy yield corresponding to measurements over a whole year show that photovoltaic technology could become a viable alternative also in a Northern country like Norway.

Ole-Morten Midtgard; Tor Oskar Stre; Georgi Yordanov; Anne Gerd Imenes; Chee Lim Nge

2010-01-01T23:59:59.000Z

197

Blower upkeep, energy savings estimated at $20,000/yr  

SciTech Connect (OSTI)

Vinyl chloride gas must be removed from operating vessels in a polymerization process at Occidental Chemical, Addis, LA. If left intact, the gases can polymerize and form deposits. Considered for this function were reciprocating and liquid ring type compressors. They were rejected, however, because of anticipated high valve maintenance and energy consumption. Since high reliability and leak-free performance are essential, two double-mechanical-sealed, positive displacement blowers were installed with water injection in 1980. The blowers are designed for those special applications where gas leak tightness is required or where continuous, high-pressure or vacuum, single-stage or two-stage is needed. The lobe-type blowers were selected by Occidental because they were considered to be best suited for the low-pressure differential operation. All internal surfaces are specially cleaned to reduce contamination and may be operated with non-hydrocarbon lubricants. A back-up seal on the drive shaft provides protection against leakage of process gas to the atmosphere. Maintenance and energy savings are estimated at $20,000/yr. The blowers were used with the water injection technique because previous experience vinyl chloride monomer indicated that there were major deposits inside the compressors and ring units. The blowers have provided contaminant-free (oil-free) monomer, and the water injection has prevented the polymerization material from sticking to the surfaces of the blowers. This has ensured practically trouble-free operation, and has greatly reduced maintenance and operation downtime, significantly reducing cost.

Diehl, R.; Powers, J.

1987-05-01T23:59:59.000Z

198

CONTROLLED PART-TO-SUBSTRATE MICRO-ASSEMBLY VIA ELECTROCHEMICAL MODULATION OF SURFACE ENERGY  

E-Print Network [OSTI]

the hydro- phobicity of the binding sites between micro-parts and substrates. Active assembly sites consistCONTROLLED PART-TO-SUBSTRATE MICRO-ASSEMBLY VIA ELECTROCHEMICAL MODULATION OF SURFACE ENERGY-2500, USA ABSTRACT A process designed for repeated parallel micro- assembly has been achieved by controlling

199

EIA-Assumptions to the Annual Energy Outlook - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumptions to the Annual Energy Outlook 2007 Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, imports, 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 2007, DOE/EIA-M060(2007) (Washington, DC, 2007). 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. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, and the cost of factor inputs (labor and fuel).

200

EIA - Assumptions to the Annual Energy Outlook 2010 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumptions to the Annual Energy Outlook 2010 Coal Market Module The NEMS Coal Market Module (CMM) provides projections of U.S. coal production, consumption, exports, imports, 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 2010, DOE/EIA-M060(2010) (Washington, DC, 2010). 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 projection. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, the cost of factor inputs (labor and fuel), and other mine supply costs.

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

EIA - Assumptions to the Annual Energy Outlook 2008 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumptions to the Annual Energy Outlook 2008 Coal Market Module The NEMS Coal Market Module (CMM) provides projections of U.S. coal production, consumption, exports, imports, 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 2008, DOE/EIA-M060(2008) (Washington, DC, 2008). 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 projection. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, and the cost of factor inputs (labor and fuel).

202

Impact of different macronutrient definitions and energy conversion factors on energy supply estimations  

Science Journals Connector (OSTI)

The magnitude of differences in energy supply using different definitions for carbohydrates and protein as well as different energy conversion factors was investigated. Food supply data for 19992001 from FAOSTAT were used for nine countries with different types of diets. Nutrient values were derived from USDA and the British food composition tables for three definitions of carbohydrate (total, available by difference, available as monosaccharide equivalents), three protein definitions (nitrogen (N)Jones factors, N6.25, sum of amino acids), fat, and two dietary fibre definitions (AOAC, non-starch polysaccharide). Then three sets of energy conversion factors were applied (Merrill & Watt, general Atwater with/without energy value for fibre, and gross energyGE). Using the same nutrient definitions, differences between general and specific Atwater factors accounted for 50320kJ/capita/day (1075kcal/capita/day) and for 2901500kJ/capita/day (70360kcal/capita/day) between GE and metabolizable energy supply calculations. Protein definitions have a minor impact on per capita energy supply values. They generate differences of less than 1%, or 4105kJ (125kcal), with N6.25 values providing the highest values, followed by Jones factors and the sum of amino acids. The largest differences observed in per capita energy supply calculations are due to carbohydrate definitions. Differences of 3.58% or 330780kJ/capita/day (80190kcal/capita/day) are observed between total and available carbohydrates as monosaccharide equivalents within the general Atwater system. Differences in energy supply between total and available carbohydrates could be minimized by applying an energy factor of 8kJ/g (2kcal/g) for dietary fibre, resulting in a higher energy supply of 100250kJ/capita/day (2560kcal/capita/day) or 12%. Differences in energy supply are less influenced by the energy factors as such than by the nutrient definition used, especially for carbohydrates. Differences in energy supply of up to 780kJ/capita/day (160kcal/capita/day) or 8% may be statistically relevant and might change research results, estimates of the dietary energy supply and consequently the estimation of the prevalence of undernourishment which may affect nutrition program and policies. Global harmonization of macronutrient definitions and energy factors is important to achieve unambiguous and comparable macronutrient and energy values among countries.

U.R Charrondiere; S Chevassus-Agnes; S Marroni; B Burlingame

2004-01-01T23:59:59.000Z

203

Parameter estimation of coupled water and energy balance models based on stationary constraints of surface states  

E-Print Network [OSTI]

[1] We use a conditional averaging approach to estimate the parameters of a land surface water and energy balance model and then use the estimated parameters to partition net radiation into latent, sensible, and ground ...

Sun, Jian

204

Development of an Outdoor Concentrating Photovoltaic Module Testbed, Module Handling and Testing Procedures, and Initial Energy Production Results  

SciTech Connect (OSTI)

This report addresses the various aspects of setting up a CPV testbed and procedures for handling and testing CPV modules.

Muller, M.

2009-09-01T23:59:59.000Z

205

EIA Report Estimates Growth of U.S. Energy Economy Through 2040 |  

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

EIA Report Estimates Growth of U.S. Energy Economy Through 2040 EIA Report Estimates Growth of U.S. Energy Economy Through 2040 EIA Report Estimates Growth of U.S. Energy Economy Through 2040 December 5, 2012 - 3:43pm Addthis EIA Report Estimates Growth of U.S. Energy Economy Through 2040 Matthew Loveless Matthew Loveless Data Integration Specialist, Office of Public Affairs What are the key facts? Crude oil, natural gas and renewable energy production are expected to grow rapidly. Net energy imports are expected to decline, as production grows faster than consumption. Editor's Note: This article was originally posted as part of the Energy Information Administration's (EIA) Today in Energy series. EIA has just issued its Annual Energy Outlook 2013 (AEO2013) Reference case, which highlights a growth in total U.S. energy production that

206

INVENTORY OF SOLAR RADIATION/SOLAR ENERGY SYSTEMS ESTIMATORS, MODELS, SITE-SPECIFIC DATA, AND PUBLICATIONS  

E-Print Network [OSTI]

INVENTORY OF SOLAR RADIATION/SOLAR ENERGY SYSTEMS ESTIMATORS, MODELS, SITE-SPECIFIC DATA, and Buildings Systems Integration Center National Renewable Energy Laboratory 8 July 2009 SOLAR SYSTEM POTENTIAL/calculators/PVWATTS/version1/ http://rredc.nrel.gov/solar/calculators/PVWATTS/version2/ Estimates the electrical energy

207

VTrack: Accurate, Energy-Aware Road Traffic Delay Estimation Using Mobile Phones  

E-Print Network [OSTI]

for travel time estimation using this sensor data that addresses two key challenges: energy consumptionVTrack: Accurate, Energy-Aware Road Traffic Delay Estimation Using Mobile Phones Arvind Thiagarajan the bat- tery quickly. In these cases, VTrack can use alternative, less energy-hungry but noisier sensors

Gummadi, Ramakrishna

208

Energy Planning for Progressive Estimation in Multihop Sensor Networks  

E-Print Network [OSTI]

routing tree establishment, transmission energy plan- ninglarge gap of energy between the single-hop tree and therouting tree finding and the transmis- sion energy planning

Huang, Yi; Hua, Yingbo

2009-01-01T23:59:59.000Z

209

State Energy Profiles and Estimates (SEDS) Report Archives  

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

States - U.S. Energy Information Administration (EIA) - U.S. Energy Information Administration (EIA) U.S. Energy Information Administration - EIA - Independent Statistics and...

210

Design and optimization of solid thermal energy storage modules for solar thermal power plant applications  

Science Journals Connector (OSTI)

Abstract Solid sensible heat storage is an attractive option for high-temperature storage applications in terms of investment and maintenance costs. Typical solid thermal energy storage systems use a heat transfer fluid to exchange heat as the fluid flows through a tubular heat exchanger embedded in the solid storage material. The modified lumped capacitance method is used with an effective heat transfer coefficient in a simplified analysis of the heat transfer in solid thermal energy storage systems for a solid cylindrical heat storage unit. The analytical solution was found using the Laplace transform method. The solution was then used to develop an optimization method for designing solid storage modules which uses the system requirements (released energy and fluid outlet temperature) as the constraint conditions and the storage module cost as the objective function for the optimization. Optimized results are then given for many kinds of system configurations.

Yongfang Jian; Quentin Falcoz; Pierre Neveu; Fengwu Bai; Yan Wang; Zhifeng Wang

2015-01-01T23:59:59.000Z

211

Energy Savings Estimates of Light Emitting Diodes in Niche Lighting Applications  

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

Savings Estimates of Light Emitting Diodes Savings Estimates of Light Emitting Diodes in Niche Lighting Applications Prepared for: Building Technologies Program Office of Energy Efficiency and Renewable Energy U.S. Department of Energy Prepared by: Navigant Consulting Inc. 1801 K Street, NW Suite 500 Washington DC, 20006 September 2008 * Department of Energy Washington, DC 20585 Energy Savings Estimates of Light Emitting Diodes in Niche Lighting Applications Released: September 2008 Revised: October 2008 This DOE report presents research findings for twelve different niche markets where LEDs are competing or poised to compete with traditional light sources (e.g., incandescent and fluorescent). Estimates of the energy saved due to current levels of LED market penetration as well as estimates of potential energy savings if these markets switched completely to LEDs

212

The Smart Grid: An Estimation of the Energy and Carbon Dioxide...  

Open Energy Info (EERE)

newspdfPNNL-19112Revision1Final.pdf Equivalent URI: cleanenergysolutions.orgcontentsmart-grid-estimation-energy-and-carb Language: English Policies: "Deployment...

213

Indian Country Solar Energy Potential Estimates & DOE IE Updates  

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

Pathways to Sustained Energy Pathways to Sustained Energy Development in Oklahoma Oklahoma Tribal Leader Forum - August 2012 Oklahoma City, Oklahoma 1 Office of Indian Energy Goals and Objectives * Promote Indian tribal energy development, efficiency and use * Reduce or stabilize energy costs * Enhance and strengthen Indian tribal energy and economic infrastructure relating to natural resource development and electrification * Bring electrical power and service to Indian land and the homes of tribal members Energy Policy Act of 2005, Title V, Sec. 502 2 Office of Indian Energy Programs 3 * START (Strategic Technical Assistance Response Teams) - Providing Expert Development Technical Assistance Directly to Tribal Staff/Leaders/Projects - Targeted energy development assistance - post feasibility & pre

214

Estimating the Benefits and Costs of Distributed Energy Technologies Workshop- Day 2 Presentations  

Broader source: Energy.gov [DOE]

On September 30 and October 1, 2014, the Department of Energy hosted a 2-day workshop on Estimating the Benefits and Costs of Distributed Energy Technologies. Presentations from Day 2 are available here.

215

Estimating the Benefits and Costs of Distributed Energy Technologies Workshop- Agenda and Summary  

Broader source: Energy.gov [DOE]

On September 30 and October 1, 2014, the Department of Energy hosted a 2-day workshop on Estimating the Benefits and Costs of Distributed Energy Technologies. The agenda and summaries are available here.

216

On Energy for Progressive and Consensus Estimation in Multihop Sensor Networks  

E-Print Network [OSTI]

energy and power plan- ning, multihop sensor networks, network with routing tree,with routing tree. Using the exact energy model and takingenergy planning algorithm for a progressive estimation method which exploits routing tree

Huang, Yi; Hua, Yingbo

2011-01-01T23:59:59.000Z

217

Estimating the Benefits and Costs of Distributed Energy Technologies Workshop- Day 1 Presentations  

Broader source: Energy.gov [DOE]

On September 30 and October 1, 2014, the Department of Energy hosted a 2-day workshop on Estimating the Benefits and Costs of Distributed Energy Technologies. Presentations from Day 1 are available here.

218

A tool to estimate materials and manufacturing energy for a product  

E-Print Network [OSTI]

This study proposes an easy-to-use methodology to estimate the materials embodied energy and manufacturing energy for a product. The tool requires as input the product's Bill of Materials and the knowledge on how these ...

Duque Ciceri, Natalia

219

Parameter estimation for energy balance models with memory  

Science Journals Connector (OSTI)

...model based on the energy balance of the Earth...climate dynamics. New York, NY: Springer...JA Coakley. 1981 Energy balance climate models...Climate sensitivity, energy balance models...Sciences, vol. 119. New York, NY: Springer...

2014-01-01T23:59:59.000Z

220

The Estimation of the Marine Main Diesel Engine Energy Balance  

Science Journals Connector (OSTI)

The basis of impact of energy device (marine main diesel engine) on its environment in terms of energy ... . Types of energy and exergy characterizing the marine main diesel engine are presented. The description ...

Z. Matuszak; G. Nicewicz

2014-01-01T23:59:59.000Z

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

Indian Country Solar Energy Potential Estimates & DOE IE Updates  

Office of Environmental Management (EM)

Pathways to Sustained Energy Development in Oklahoma Oklahoma Tribal Leader Forum - August 2012 Oklahoma City, Oklahoma 1 Office of Indian Energy Goals and Objectives * Promote...

222

PART 2. MATHEMATICAL MODELS IN POLLUTION CHAPTER V. MATHEMATICAL MODELS TO ESTIMATE THE ENERGY -  

E-Print Network [OSTI]

of the methodology introduced in a section 5.1, which was used to estimate the atmospheric pollution by the fuelPART 2. MATHEMATICAL MODELS IN POLLUTION CHAPTER V. MATHEMATICAL MODELS TO ESTIMATE THE ENERGY the necessary analysis from the point of view of estimating all the pollution effects in correlation

Baica, Malvina

223

Eigen-Inference for Energy Estimation of Multiple Sources  

E-Print Network [OSTI]

by overlaying the spectrum licensed to outdoors R. Couillet and M. Debbah are with the Alcatel-Lucent Chair techniques. Index Terms--Statistical inference, random matrix theory, power estimation, cognitive radio, G-estimation. I. INTRODUCTION At a time when radio resources become scarce, the alterna- tive offered by cognitive

224

Mandatory Photovoltaic System Cost Estimate | Department of Energy  

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

Mandatory Photovoltaic System Cost Estimate Mandatory Photovoltaic System Cost Estimate Mandatory Photovoltaic System Cost Estimate < Back Eligibility Utility Savings Category Solar Buying & Making Electricity Program Info State Colorado Program Type Line Extension Analysis Provider Colorado Public Utilities Commission At the request of a customer or a potential customer, Colorado electric utilities are required to conduct a cost comparison of a photovoltaic (PV) system to any proposed distribution line extension if the customer or potential customer provides the utility with load data (estimated monthly kilowatt-hour usage) requested by the utility to conduct the comparison, and if the customer's or potential customer's peak demand is estimated to be less than 25 kilowatts (kW). In performing the comparison analysis, the

225

Injection of a Phase Modulated Source into the Z-Beamlet Laser for Increased Energy Extraction.  

SciTech Connect (OSTI)

The Z-Beamlet laser has been operating at Sandia National Laboratories since 2001 to provide a source of laser-generated x-rays for radiography of events on the Z-Accelerator. Changes in desired operational scope have necessitated the increase in pulse duration and energy available from the laser system. This is enabled via the addition of a phase modulated seed laser as an alternative front-end. The practical aspects of deployment are discussed here.

Rambo, Patrick K.; Armstrong, Darrell J.; Schwarz, Jens; Smith, Ian C; Shores, Jonathon; Speas, Christopher; Porter, John L.

2014-11-01T23:59:59.000Z

226

Minimum energy decentralized estimation in a wireless sensor network with correlated sensor noises  

Science Journals Connector (OSTI)

Consider the problem of estimating an unknown parameter by a sensor network with a fusion center (FC). Sensor observations are corrupted by additive noises with an arbitrary spatial correlation. Due to bandwidth and energy limitation, each sensor is ... Keywords: decentralized estimation, energy efficiency, power control, wireless sensor networks

Alexey Krasnopeev; Jin-Jun Xiao; Zhi-Quan Luo

2005-09-01T23:59:59.000Z

227

JULY 2005 1 An estimate of tidal energy lost to turbulence at the Hawaiian Ridge  

E-Print Network [OSTI]

relation- ship between the energy in the semi-diurnal internal tide (E) and the depth of the ridge. This is roughly 15% of the energy estimated to be lost from the barotropic tide. 1. Introduction energy get removed from the ocean. Oceanic tides put energy into the ocean at a rate of 3.5 TW (Munk

Klymak, Jody M.

228

Estimating Internal Wave Energy Fluxes in the Ocean JONATHAN D. NASH  

E-Print Network [OSTI]

Estimating Internal Wave Energy Fluxes in the Ocean JONATHAN D. NASH College of Oceanic FE u p cgE is a fundamental quan- tity in internal wave energetics to identify energy sources, wave propagation, and energy sinks. Internal wave radiation transports energy from the boundaries

Kurapov, Alexander

229

Estimation of input energy in rocket-triggered lightning Vinod Jayakumar,1  

E-Print Network [OSTI]

the input power and energy, each per unit channel length and as a function of time, associated with return- lightning first stroke, based on the conversion of measured optical energy to total energy using energy., 2002] and measured current, I(t), at the channel base to estimate the input power per unit length, P

Florida, University of

230

Property:EstimatedTimeExplained | Open Energy Information  

Open Energy Info (EERE)

EstimatedTimeExplained EstimatedTimeExplained Jump to: navigation, search Property Name EstimatedTimeExplained Property Type Text Description An explanation of the accompanying time estimate, including any influential factors or variables. Subproperties This property has the following 40 subproperties: G GRR/Elements/14-CA-b.1 - NPDES Permit Application GRR/Elements/14-CA-b.10 - Did majority of RWQCB approve the permit GRR/Elements/14-CA-b.11 - EPA Review of Adopted Permit GRR/Elements/14-CA-b.12 - Were all EPA objections resolved GRR/Elements/14-CA-b.13 - NPDES Permit issued GRR/Elements/14-CA-b.2 - Review of application for completeness GRR/Elements/14-CA-b.3 - Is the application complete for the Regional Water Quality Control Board GRR/Elements/14-CA-b.4 - EPA review for completeness

231

Estimating material and energy intensities of urban areas  

E-Print Network [OSTI]

The objective of this thesis is to develop methods to estimate, analyze and visualize the resource intensity of urban areas. Understanding the resource consumption of the built environment is particularly relevant in cities ...

Quinn, David James, Ph. D. Massachusetts Institute of Technology

2012-01-01T23:59:59.000Z

232

ESTIMATING RISK TO CALIFORNIA ENERGY INFRASTRUCTURE FROM PROJECTED CLIMATE CHANGE  

E-Print Network [OSTI]

Change Scenarios and Sea Level Rise Estimates for theThe puzzle of global sea-level rise. Physics Today 55 (3):2009. The Impacts of Sea-Level Rise on the California Coast.

Sathaye, Jayant

2011-01-01T23:59:59.000Z

233

A Game-Theoretic Approach to Energy-Efficient Modulation in CDMA Networks with Delay Constraints  

E-Print Network [OSTI]

A game-theoretic framework is used to study the effect of constellation size on the energy efficiency of wireless networks for M-QAM modulation. A non-cooperative game is proposed in which each user seeks to choose its transmit power (and possibly transmit symbol rate) as well as the constellation size in order to maximize its own utility while satisfying its delay quality-of-service (QoS) constraint. The utility function used here measures the number of reliable bits transmitted per joule of energy consumed, and is particularly suitable for energy-constrained networks. The best-response strategies and Nash equilibrium solution for the proposed game are derived. It is shown that in order to maximize its utility (in bits per joule), a user must choose the lowest constellation size that can accommodate the user's delay constraint. Using this framework, the tradeoffs among energy efficiency, delay, throughput and constellation size are also studied and quantified. The effect of trellis-coded modulation on energy...

Meshkati, Farhad; Poor, H Vincent; Schwartz, Stuart C

2007-01-01T23:59:59.000Z

234

Intensity and energy modulated radiotherapy with proton beams: Variables affecting optimal prostate plan  

Science Journals Connector (OSTI)

Inverse planning for intensity- and energy-modulated radiotherapy (IEMRT) with proton beams involves the selection of (i) the relative importance factors to control the relative importance of the target and sensitive structures (ii) an appropriate energy resolution to achieve an acceptable depth modulation (iii) an appropriate beamlet width to modulate the beam laterally and (iv) a sufficient number of beams and their orientations. In this article we investigate the influence of these variables on the optimized dose distribution of a simulated prostate cancer IEMRT treatment. Good dose conformation for this prostate case was achieved using a constellation of I factors for the target rectum bladder and normal tissues of 500 50 15 and 1 respectively. It was found that for an active beam delivery system the energy resolution should be selected on the basis of the incident beams energy spread (? E ) and the appropriate energy resolution varied from 1 MeV at ? E =0.0? to ?5? MeV at ? E =2.0? MeV . For a passive beam delivery system the value of the appropriate depth resolution for inverse planning may not be critical as long as the value chosen is at least equal to one-half the FWHM of the primary beam Bragg peak. Results indicate that the dose grid element dimension should be equal to or no less than 70% of the beamlet width. For this prostate case we found that a maximum of three to four beam ports is required since there was no significant advantage to using a larger number of beams. However for a small number (?4) of beams the selection of beam orientations while having only a minor effect on target coverage strongly influenced the sensitive structure sparing and normal tissue integral dose.

Collins Yeboah; George A. Sandison; Alexei V. Chvetsov

2002-01-01T23:59:59.000Z

235

Wind Resource Estimation and Mapping at the National Renewable Energy Laboratory  

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

Resource Estimation and Resource Estimation and Mapping at the National Renewable Energy Laboratory April 1999 * NREL/CP-500-26245 M. Schwartz Presented at the ASES Solar '99 Conference Portland, Maine June 12-16, 1999 National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401-3393 NREL is a U.S. Department of Energy Laboratory Operated by Midwest Research Institute * * * * Battelle * * * * Bechtel

236

Property:EstimatedTimeHigh | Open Energy Information  

Open Energy Info (EERE)

EstimatedTimeHigh EstimatedTimeHigh Jump to: navigation, search Property Name EstimatedTimeHigh Property Type Quantity Description the high estimate of time required Use this type to enumerate a length of time. The default unit is the year. Acceptable units (and their conversions) are: 8766 hours,hour,h,H,Hour,Hours,HOUR,HOURS 365.25 days,day,d,Day,Days,D,DAY,DAYS 52.17857 weeks,week,w,Week,Weeks,W,WEEK,WEEKS 12 months,month,m,Month,Months,M,MONTH,MONTHS 1 years,year,y,Year,Years,Y,YEAR,YEARS Pages using the property "EstimatedTimeHigh" Showing 25 pages using this property. (previous 25) (next 25) 2 2-M Probe Survey + 3.422313e-4 years3 hours 0.125 days 0.0179 weeks 0.00411 months + A Acoustic Logs + 0.0881 years772.08 hours 32.17 days 4.596 weeks 1.057 months + Aerial Photography + 0.00548 years48 hours

237

Property:EstimatedCostHighUSD | Open Energy Information  

Open Energy Info (EERE)

EstimatedCostHighUSD EstimatedCostHighUSD Jump to: navigation, search Property Name EstimatedCostHighUSD Property Type Quantity Description the high estimate of cost in USD Use this type to express a monetary value in US Dollars. The default unit is one US Dollar. http://en.wikipedia.org/wiki/Area Acceptable units (and their conversions) are: 100 cent USD,cents USD,Cent USD,Cents USD .001 k USD,thousand USD,Thousand USD .000001 M USD,million USD,Million USD .000000001 T USD,trillion USD,Trillion USD Pages using the property "EstimatedCostHighUSD" Showing 25 pages using this property. (previous 25) (next 25) 2 2-M Probe Survey + 50050,000 centUSD 0.5 kUSD 5.0e-4 MUSD 5.0e-7 TUSD + A Acoustic Logs + 161,600 centUSD 0.016 kUSD 1.6e-5 MUSD 1.6e-8 TUSD + Aerial Photography + 2,360236,000 centUSD

238

Property:EstimatedCostLowUSD | Open Energy Information  

Open Energy Info (EERE)

EstimatedCostLowUSD EstimatedCostLowUSD Jump to: navigation, search Property Name EstimatedCostLowUSD Property Type Quantity Description the low estimate of cost in USD Use this type to express a monetary value in US Dollars. The default unit is one US Dollar. http://en.wikipedia.org/wiki/Area Acceptable units (and their conversions) are: 100 cent USD,cents USD,Cent USD,Cents USD .001 k USD,thousand USD,Thousand USD .000001 M USD,million USD,Million USD .000000001 T USD,trillion USD,Trillion USD Pages using the property "EstimatedCostLowUSD" Showing 25 pages using this property. (previous 25) (next 25) 2 2-M Probe Survey + 20020,000 centUSD 0.2 kUSD 2.0e-4 MUSD 2.0e-7 TUSD + A Acoustic Logs + 1100 centUSD 1.0e-3 kUSD 1.0e-6 MUSD 1.0e-9 TUSD + Aerial Photography + 100.3610,036 centUSD

239

Property:EstimatedCostMedianUSD | Open Energy Information  

Open Energy Info (EERE)

EstimatedCostMedianUSD EstimatedCostMedianUSD Jump to: navigation, search Property Name EstimatedCostMedianUSD Property Type Quantity Description the median estimate of cost in USD Use this type to express a monetary value in US Dollars. The default unit is one US Dollar. http://en.wikipedia.org/wiki/Area Acceptable units (and their conversions) are: 100 cent USD,cents USD,Cent USD,Cents USD .001 k USD,thousand USD,Thousand USD .000001 M USD,million USD,Million USD .000000001 T USD,trillion USD,Trillion USD Pages using the property "EstimatedCostMedianUSD" Showing 25 pages using this property. (previous 25) (next 25) 2 2-M Probe Survey + 30030,000 centUSD 0.3 kUSD 3.0e-4 MUSD 3.0e-7 TUSD + A Acoustic Logs + 4.62462 centUSD 0.00462 kUSD 4.62e-6 MUSD 4.62e-9 TUSD + Aerial Photography + 240.5424,054 centUSD

240

Property:EstimatedTimeMedian | Open Energy Information  

Open Energy Info (EERE)

EstimatedTimeMedian EstimatedTimeMedian Jump to: navigation, search Property Name EstimatedTimeMedian Property Type Quantity Description the median estimate of time required Use this type to enumerate a length of time. The default unit is the year. Acceptable units (and their conversions) are: 8766 hours,hour,h,H,Hour,Hours,HOUR,HOURS 365.25 days,day,d,Day,Days,D,DAY,DAYS 52.17857 weeks,week,w,Week,Weeks,W,WEEK,WEEKS 12 months,month,m,Month,Months,M,MONTH,MONTHS 1 years,year,y,Year,Years,Y,YEAR,YEARS Pages using the property "EstimatedTimeMedian" Showing 25 pages using this property. (previous 25) (next 25) 2 2-M Probe Survey + 2.281542e-4 years2 hours 0.0833 days 0.0119 weeks 0.00274 months + A Acoustic Logs + 0.044 years385.92 hours 16.08 days 2.297 weeks 0.528 months +

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

Property:EstimatedTimeLow | Open Energy Information  

Open Energy Info (EERE)

EstimatedTimeLow EstimatedTimeLow Jump to: navigation, search Property Name EstimatedTimeLow Property Type Quantity Description the low estimate of time required Use this type to enumerate a length of time. The default unit is the year. Acceptable units (and their conversions) are: 8766 hours,hour,h,H,Hour,Hours,HOUR,HOURS 365.25 days,day,d,Day,Days,D,DAY,DAYS 52.17857 weeks,week,w,Week,Weeks,W,WEEK,WEEKS 12 months,month,m,Month,Months,M,MONTH,MONTHS 1 years,year,y,Year,Years,Y,YEAR,YEARS Pages using the property "EstimatedTimeLow" Showing 25 pages using this property. (previous 25) (next 25) 2 2-M Probe Survey + 1.711157e-4 years1.5 hours 0.0625 days 0.00893 weeks 0.00205 months + A Acoustic Logs + 0.023 years201.36 hours 8.39 days 1.199 weeks 0.276 months + Aerial Photography + 2.737851e-4 years2.4 hours

242

ESTIMATION OF THE MEAN ENERGY OF MUONS IN MULTILAYER DETECTORS  

E-Print Network [OSTI]

The technique of muon mean energy determination in multilayer detectors is developed. The mean energy is measured by means of average small bursts $m$ i.e. the number of electrons and positrons generated by muons in the detecting layers of device via three basic processes --- creation of $e^+e^-$ pairs, $\\delta$-electrons and bremsestrahlung. The accuracy of the method is considered. Key words: muon energy, multilayer detectors.

T. T. BARNAVELI; Yu. G. VERBETSKY; I. V. KHALDEEVA; N. A. ERISTAVI

1995-05-30T23:59:59.000Z

243

Measuring Energy, Estimating Hamiltonians, and the Time-Energy Uncertainty Relation  

E-Print Network [OSTI]

Suppose that the Hamiltonian acting on a quantum system is unknown and one wants to determine what is the Hamiltonian. We show that in general this requires a time $\\Delta t$ which obeys the uncertainty relation $\\Delta t \\Delta H \\gtrsim 1$ where $\\Delta H$ is a measure of how accurately the unknown Hamiltonian must be estimated. We then apply this result to the problem of measuring the energy of an unknown quantum state. It has been previously shown that if the Hamiltonian is known, then the energy can in principle be measured in an arbitrarily short time. On the other hand we show that if the Hamiltonian is not known then an energy measurement necessarily takes a minimum time $\\Delta t$ which obeys the uncertainty relation $\\Delta t \\Delta E \\gtrsim 1$ where $\\Delta E$ is the precision of the energy measurement. Several examples are studied to address the question of whether it is possible to saturate these uncertainty relations. Their interpretation is discussed in detail.

Y. Aharonov; S. Massar; S. Popescu

2001-09-30T23:59:59.000Z

244

Arc Energy Estimations: Applications in Lightning-Induced Concrete Spall  

SciTech Connect (OSTI)

After lightning contacts a building, the possibility of a physical break in its conductive path to ground may exist. Given such a break, an electric field may develop across the gap until it exceeds the breakdown strength of the non-conducting, or dielectric, material. Breakdown subsequently occurs and energy is dissipated during the development of an arc channel. If the dielectric is concrete, a concern exists that the energy available for arc formation may be capable of launching pieces of spall into sensitive equipment. This paper discusses the mechanisms of energy dissipation in arc formation and quantifies the energy available for concrete spall.

Tully, L K; Ong, M M

2008-06-03T23:59:59.000Z

245

NISTIR 6045 Method for Estimating the Energy Efficiency Ratio of  

E-Print Network [OSTI]

to all electric units having rated cooling capacities less than 19 kW (65,000 Btu/h) and charged with Refrigerant 22. To estimate the EER(95) of one or more combinations that use the same condensing unit, a lab

Oak Ridge National Laboratory

246

Estimating the Cost and Energy Efficiency of a Solar Water Heater |  

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

Estimating the Cost and Energy Efficiency of a Solar Water Heater Estimating the Cost and Energy Efficiency of a Solar Water Heater Estimating the Cost and Energy Efficiency of a Solar Water Heater May 30, 2012 - 3:09pm Addthis Solar water heaters are more efficient the gas or electric heaters. | Chart credit ENERGY STAR Solar water heaters are more efficient the gas or electric heaters. | Chart credit ENERGY STAR What does this mean for me? Solar water heaters cost more to purchase and install but may save you money in the long run. Estimate the annual operating costs and compare several solar water heaters to determine whether it is worth investing in a more efficient system. Solar water heating systems usually cost more to purchase and install than conventional water heating systems. However, a solar water heater can

247

Estimating the Cost and Energy Efficiency of a Solar Water Heater |  

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

Estimating the Cost and Energy Efficiency of a Solar Water Heater Estimating the Cost and Energy Efficiency of a Solar Water Heater Estimating the Cost and Energy Efficiency of a Solar Water Heater May 30, 2012 - 3:09pm Addthis Solar water heaters are more efficient the gas or electric heaters. | Chart credit ENERGY STAR Solar water heaters are more efficient the gas or electric heaters. | Chart credit ENERGY STAR What does this mean for me? Solar water heaters cost more to purchase and install but may save you money in the long run. Estimate the annual operating costs and compare several solar water heaters to determine whether it is worth investing in a more efficient system. Solar water heating systems usually cost more to purchase and install than conventional water heating systems. However, a solar water heater can

248

An Observational Estimate of Inferred Ocean Energy Divergence KEVIN E. TRENBERTH AND JOHN T. FASULLO  

E-Print Network [OSTI]

An Observational Estimate of Inferred Ocean Energy Divergence KEVIN E. TRENBERTH AND JOHN T, in final form 25 September 2007) ABSTRACT Monthly net surface energy fluxes (FS) over the oceans are computed as residuals of the atmospheric energy budget using top-of-atmosphere (TOA) net radiation (RT

Fasullo, John

249

An Estimate of Tidal Energy Lost to Turbulence at the Hawaiian Ridge JODY M. KLYMAK  

E-Print Network [OSTI]

between the energy in the semidiurnal internal tide (E) and the depth-integrated dissipation (D. This is roughly 15% of the energy estimated to be lost from the barotropic tide. 1. Introduction One of the more. Oceanic tides put energy into the ocean at a rate of 3.5 TW Corresponding author address: J. Klymak

Kurapov, Alexander

250

Data-driven Techniques to Estimate Parameters in the Homogenized Energy Model for Shape Memory Alloys  

E-Print Network [OSTI]

, ferroelectric, and ferromagnetic materials. The energy origin of the model was originally investigated for SMA]. The original mod- els determined the equilibrium phase using the Gibbs energy to predict the mesoscopic (orData-driven Techniques to Estimate Parameters in the Homogenized Energy Model for Shape Memory

251

CONTEXT-BASED ENERGY ESTIMATOR: APPLICATION TO OBJECT SEGMENTATION ON THE TREE OF SHAPES  

E-Print Network [OSTI]

CONTEXT-BASED ENERGY ESTIMATOR: APPLICATION TO OBJECT SEGMENTATION ON THE TREE OF SHAPES Yongchao. A classical approach is to define an energy minimization framework, where interesting contours correspond to local minima of this energy. Active contours, graph cuts or minimum ratio cuts are instances of such ap

Paris-Sud XI, Université de

252

A Process Algebraic Framework for Estimating the Energy Consumption in Ad-hoc Wireless Sensor Networks  

E-Print Network [OSTI]

A Process Algebraic Framework for Estimating the Energy Consumption in Ad-hoc Wireless Sensor their connecti- vity properties and their performances in terms of energy consumption, throughput and other and the evaluation or esti- mation of energy consumption in ad-hoc WSNs. The frame- work is based on a variant

Rossi, Sabina

253

Order Module--U.S. DEPARTMENT OF ENERGY ORDERS SELF-STUDY PROGRAM: GETTING  

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

U.S. DEPARTMENT OF ENERGY ORDERS SELF-STUDY PROGRAM: U.S. DEPARTMENT OF ENERGY ORDERS SELF-STUDY PROGRAM: GETTING STARTED Order Module--U.S. DEPARTMENT OF ENERGY ORDERS SELF-STUDY PROGRAM: GETTING STARTED This course was developed using the Criterion Referenced Instruction (CRI) method of training. That means the course contains only the information you need to perform your job. You will be shown the learning objectives at the beginning of the course. If you think you can demonstrate competency without additional instruction, you may complete the practice at any time. When you complete all of the practices successfully, you may ask the course manager for the criterion test. The familiar level requires that you understand and remember the material. The general level requires that you understand the applicability of the material. If you are unsure of the

254

Indian Country Solar Energy Potential Estimates & DOE IE Updates  

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

Potential for Renewable Energy Potential for Renewable Energy Development on Tribal Lands October 2012 1 Introduction * The DOE Office of Indian Energy Policy and Programs (OI) requested ICF International (ICF) to identify areas within Tribal Lands that have a strong potential for renewable energy generation (solar and wind) as a source of Tribal revenue within the geographic area covered by the Western Electric Coordination Council (WECC) transmission grid * ICF used a combination of geospatial modeling and power flow modeling to identify sites where: - Conditions are optimal for solar or wind generation - Access to high-voltage transmission lines is favorable - Transmission upgrade costs would be minimal 2 Geospatial Analysis Phase I: Identify Potential Sites * Obtained GIS layers (e.g., wind/solar resources, transmission

255

Free energy differences : Representations, estimators, and sampling strategies  

E-Print Network [OSTI]

In this thesis we examine methodologies for determining free energy differences (FEDs) of phases via Monte Carlo simulation. We identify and address three generic issues that arise in FED calculations; the choice of representation, the choice...

Acharya, Arjun R

256

Turbulent kinetic energy balance as a tool for estimating vertical ...  

Science Journals Connector (OSTI)

Based on microstructure measurements in a simply shaped lake basin, the sources of ... Comparison with turbulent kinetic energy balances, performed in five other lakes, ...... pation (PB) is everywhere the same per unit area of sediment

1910-00-90T23:59:59.000Z

257

How to Estimate Energy Lost to Gravitational Waves (revised)  

E-Print Network [OSTI]

The energy--momentum radiated in gravitational waves by an isolated source is given by a formula of Bondi. This formula is highly non--local: the energy--momentum is not given as the integral of a well--defined local density. It has therefore been unclear whether the Bondi formula can be used to get information from gravity--wave measurements. In this note, we obtain, from local knowledge of the radiation field, a lower bound on the Bondi flux.

Adam D. Helfer

1993-07-19T23:59:59.000Z

258

Procedure for estimating fracture energy from fracture surface roughness  

DOE Patents [OSTI]

The fracture energy of a material is determined by first measuring the length of a profile of a section through a fractured surface of the material taken on a plane perpendicular to the mean plane of that surface, then determining the fractal dimensionality of the surface. From this, the yield strength of the material, and the Young's Modulus of that material, the fracture energy is calculated.

Williford, Ralph E. (Kennewick, WA)

1989-01-01T23:59:59.000Z

259

Using an ADCP to estimate turbulent kinetic energy dissipation rate in sheltered coastal waters  

Science Journals Connector (OSTI)

Turbulent microstructure and acoustic Doppler current profiler (ADCP) data were collected near Tacoma Narrows in Puget Sound, WA. Over 100 coincident microstructure profiles have been compared to ADCP estimates of turbulent kinetic energy ...

A. D. Greene; P. J. Hendricks; M. C. Gregg

260

ARM Best Estimate Data (ARMBE) Products for Climate Science for a Sustainable Energy Future (CSSEF)  

SciTech Connect (OSTI)

This data set was created for the Climate Science for a Sustainable Energy Future (CSSEF) model testbed project and is an extension of the hourly average ARMBE dataset to other extended facility sites and to include uncertainty estimates. Uncertainty estimates were needed in order to use uncertainty quantification (UQ) techniques with the data.

Riihimaki, Laura; Gaustad, Krista; McFarlane, Sally

2014-06-12T23:59:59.000Z

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

ESTIMATING DAMPING PARAMETERS IN MULTI-DEGREE-OF-FREEDOM VIBRATION SYSTEMS BY BALANCING ENERGY0  

E-Print Network [OSTI]

of Vibration and Acoustics, 131 (4) 041005, 2009 Measurement of damping forces, such as dry frictionESTIMATING DAMPING PARAMETERS IN MULTI-DEGREE-OF-FREEDOM VIBRATION SYSTEMS BY BALANCING ENERGY0 B@egr.msu.edu ABSTRACT A method of estimating damping parameters for multi- degree-of-freedom vibration systems

Feeny, Brian

262

ARM Best Estimate Data (ARMBE) Products for Climate Science for a Sustainable Energy Future (CSSEF)  

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

This data set was created for the Climate Science for a Sustainable Energy Future (CSSEF) model testbed project and is an extension of the hourly average ARMBE dataset to other extended facility sites and to include uncertainty estimates. Uncertainty estimates were needed in order to use uncertainty quantification (UQ) techniques with the data.

Laura Riihimaki; Krista Gaustad; Sally McFarlane

263

Evaluation of Thermal to Electrical Energy Conversion of High Temperature Skutterudite-Based Thermoelectric Modules  

Broader source: Energy.gov [DOE]

Discusses progress toward the fabrication of a skutterudite-based TE module and provides module performance data under operating conditions similar to those for automotive applications

264

Electrical power inverter having a phase modulated, twin-inverter, high frequency link and an energy storage module  

DOE Patents [OSTI]

The present invention provides an electrical power inverter method and apparatus, which includes a high frequency link, for converting DC power into AC power. Generally stated, the apparatus includes a first high frequency module which produces an AC voltage at a first output frequency, and a second high frequency inverter module which produces an AC voltage at a second output frequency that is substantially the same as the first output frequency. The second AC voltage is out of phase with the first AC voltage by a selected angular phase displacement. A mixer mixes the first and second output voltages to produce a high frequency carrier which has a selected base frequency impressed on the sidebands thereof. A rectifier rectifies the carrier, and a filter filters the rectified carrier. An output inverter inverts the filtered carrier to produce an AC line voltage at the selected base frequency. A phase modulator adjusts the relative angular phase displacement between the outputs of the first and second high frequency modules to control the base frequency and magnitude of the AC line voltage. 19 figs.

Pitel, I.J.

1987-02-03T23:59:59.000Z

265

Electrical power inverter having a phase modulated, twin-inverter, high frequency link and an energy storage module  

DOE Patents [OSTI]

The present invention provides an electrical power inverter method and apparatus, which includes a high frequency link, for converting DC power into AC power. Generally stated, the apparatus includes a first high frequency module which produces an AC voltage at a first output frequency, and a second high frequency inverter module which produces an AC voltage at a second output frequency that is substantially the same as the first output frequency. The second AC voltage is out of phase with the first AC voltage by a selected angular phase displacement. A mixer mixes the first and second output voltages to produce a high frequency carrier which has a selected base frequency impressed on the sidebands thereof. A rectifier rectifies the carrier, and a filter filters the rectified carrier. An output inverter inverts the filtered carrier to produce an AC line voltage at the selected base frequency. A phase modulator adjusts the relative angular phase displacement between the outputs of the first and second high frequency modules to control the base frequency and magnitude of the AC line voltage.

Pitel, Ira J. (Whippany, NJ)

1987-02-03T23:59:59.000Z

266

ESTIMATING THE ''DARK'' ENERGY CONTENT OF THE SOLAR CORONA  

SciTech Connect (OSTI)

The discovery of ubiquitous low-frequency (3-5 mHz) Alfvenic waves in the solar chromosphere (with Hinode/Solar Optical Telescope) and corona (with CoMP and SDO) has provided some insight into the non-thermal energy content of the outer solar atmosphere. However, many questions remain about the true magnitude of the energy flux carried by these waves. Here we explore the apparent discrepancy in the resolved coronal Alfvenic wave amplitude ({approx}0.5 km s{sup -1}) measured by the Coronal Multi-channel Polarimeter (CoMP) compared to those of the Hinode and the Solar Dynamics Observatory (SDO) near the limb ({approx}20 km s{sup -1}). We use a blend of observational data and a simple forward model of Alfvenic wave propagation to resolve this discrepancy and determine the Alfvenic wave energy content of the corona. Our results indicate that enormous line-of-sight superposition within the coarse spatio-temporal sampling of CoMP hides the strong wave flux observed by Hinode and SDO and leads to the large non-thermal line broadening observed. While this scenario has been assumed in the past, our observations with CoMP of a strong correlation between the non-thermal line broadening with the low-amplitude, low-frequency Alfvenic waves observed in the corona provide the first direct evidence of a wave-related non-thermal line broadening. By reconciling the diverse measurements of Alfvenic waves, we establish large coronal non-thermal line widths as direct signatures of the hidden, or ''dark'', energy content in the corona and provide preliminary constraints on the energy content of the wave motions observed.

McIntosh, Scott W. [High Altitude Observatory, National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307 (United States); De Pontieu, Bart, E-mail: mscott@ucar.edu [Lockheed Martin Solar and Astrophysics Lab, 3251 Hanover St., Org. A021S, Bldg. 252, Palo Alto, CA 94304 (United States)

2012-12-20T23:59:59.000Z

267

Methodology for estimating biomass energy potential and its application to Colombia  

Science Journals Connector (OSTI)

Abstract This paper presents a methodology to estimate the biomass energy potential and its associated uncertainty at a country level when quality and availability of data are limited. The current biomass energy potential in Colombia is assessed following the proposed methodology and results are compared to existing assessment studies. The proposed methodology is a bottom-up resource-focused approach with statistical analysis that uses a Monte Carlo algorithm to stochastically estimate the theoretical and the technical biomass energy potential. The paper also includes a proposed approach to quantify uncertainty combining a probabilistic propagation of uncertainty, a sensitivity analysis and a set of disaggregated sub-models to estimate reliability of predictions and reduce the associated uncertainty. Results predict a theoretical energy potential of 0.744 EJ and a technical potential of 0.059 EJ in 2010, which might account for 1.2% of the annual primary energy production (4.93 EJ).

Miguel Angel Gonzalez-Salazar; Mirko Morini; Michele Pinelli; Pier Ruggero Spina; Mauro Venturini; Matthias Finkenrath; Witold-Roger Poganietz

2014-01-01T23:59:59.000Z

268

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

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

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

269

Beam energy distribution influences on density modulation efficiency in seeded free-electron lasers  

E-Print Network [OSTI]

The beam energy spread at the entrance of undulator system is of paramount importance for efficient density modulation in high-gain seeded free-electron lasers (FELs). In this paper, the dependences of high harmonic micro-bunching in the high-gain harmonic generation (HGHG), echo-enabled harmonic generation (EEHG) and phase-merging enhanced harmonic generation (PEHG) schemes on the electron energy spread distribution are studied. Theoretical investigations and multi-dimensional numerical simulations are applied to the cases of uniform and saddle beam energy distributions and compared to a traditional Gaussian distribution. It shows that the uniform and saddle electron energy distributions significantly enhance the performance of HGHG-FELs, while they almost have no influence on EEHG and PEHG schemes. A numerical example demonstrates that, with about 84keV RMS uniform and/or saddle slice energy spread, the 30th harmonic radiation can be directly generated by a single-stage seeding scheme for a soft x-ray FEL f...

Wang, Guanglei; Deng, Haixiao; Zhang, Weiqing; Wu, Guorong; Dai, Dongxu; Wang, Dong; Zhao, Zhentang; Yang, Xueming

2015-01-01T23:59:59.000Z

270

Master thesis Solar Energy Meteorology Comparison of different methods to estimate cloud height for solar  

E-Print Network [OSTI]

Master thesis ­ Solar Energy Meteorology Comparison of different methods to estimate cloud height: · Interest in meteorology and solar energy · Experiences with data handling and analysis · Good programming for solar irradiance calculations In order to derive incoming solar irradiance at the earths surface

Peinke, Joachim

271

Optical Flow Estimation using Laplacian Mesh Energy Wenbin Li Darren Cosker Matthew Brown Rui Tang  

E-Print Network [OSTI]

Optical Flow Estimation using Laplacian Mesh Energy Wenbin Li Darren Cosker Matthew Brown Rui Tang.p.cosker,m.brown,r.tang}@bath.ac.uk Abstract In this paper we present a novel non-rigid optical flow algorithm for dense image correspondence and non-rigid registration. The algorithm uses a unique Laplacian Mesh Energy term to encourage local

Martin, Ralph R.

272

Progress In Electromagnetics Research B, Vol. 12, 259295, 2009 AN ESTIMATION OF SENSOR ENERGY CONSUMP-  

E-Print Network [OSTI]

Progress In Electromagnetics Research B, Vol. 12, 259­295, 2009 AN ESTIMATION OF SENSOR ENERGY University of Technology PO Box 218, Hawthorn, VIC 3122, Australia Abstract--A comprehensive energy model CONSUMP- TION M. N. Halgamuge, M. Zukerman, and K. Ramamohanarao ARC Special Research Center for Ultra

Halgamuge, Malka N.

273

A climatological estimate of incident solar energy in Tamaulipas, northeastern Mexico  

Science Journals Connector (OSTI)

Abstract An estimation of climatological fields of incident solar energy in Tamaulipas State, northeastern Mexico, is presented. Monthly mean evolution of solar energy in 7 automatic meteorological stations distributed along the State shows that the maximum values generally exceed 500200Wm?2 during fall-winter (NovFeb), and 700200Wm?2 during spring-summer (MayAug). An empirical model, which estimates the solar energy as function of other climatic variables (minimum temperature, maximum temperature, evaporation, and precipitation) recorded in 165 climatological conventional stations, is used to extend the climatological solar-energy estimate in the study area. The mean values of both measured and estimated solar energy are objectively mapped to fill the observation gaps and reduce the noise associated with inhomogeneous statistics and estimation errors. The highest values of solar energy ( ? 6.7 kWhm?2 during the summer and ? 4.0 kWhm?2 during the winter) are observed in the highlands, southwestern part of the State, whereas the lowest values ( ? 5.7 kWhm?2 during the summer and ? 2.8 kWhm?2 during the winter) are observed in the south-central part of the State.

David Rivas; Salomn Saleme-Vila; Rogelio Ortega-Izaguirre; Fabio Chal-Lara; Felipe Caballero-Briones

2013-01-01T23:59:59.000Z

274

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

SciTech Connect (OSTI)

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

NONE

1997-01-01T23:59:59.000Z

275

The DOE Slide Rule: An Energy Conservation Estimating Tool for Homebuilders  

E-Print Network [OSTI]

THE D.O.E. SLIDE RULE: ESTIMATING TOOL AN ENERGY CONSEF.VATION FOR HOMEBUILDERS STEVEN WINTER President Steven Winter Associates, Inc. New York, NY ADRIAN TULUCA . senior Associate Energy Group Steven Winter Associates, Inc. New York... for sale with R-19 insulation in the ceiling. After identifying potential homebuyer options to increase the ceiling insulation level (such as using R-22, R-30, or R-38 instead of R-19), a quick estimate is made of the energy savings that will result...

Winter, S.; Tuluca, A.

1984-01-01T23:59:59.000Z

276

Dietary Energy Balance Modulation of Kras- and Ink4a/Arf+/?-Driven Pancreatic Cancer: The Role of Insulin-like Growth Factor-I  

Science Journals Connector (OSTI)

...research-article Research Articles Dietary Energy Balance Modulation of Kras...the hypothesis that dietary energy balance modulation impacts pancreatic...States: why we need to stem the tide today. 2012[cited 2013...Demark-Wahnefried W, et alObesity, energy balance, and cancer: new opportunities...

Laura M. Lashinger; Lauren M. Harrison; Audrey J. Rasmussen; Craig D. Logsdon; Susan M. Fischer; Mark J. McArthur; and Stephen D. Hursting

2013-10-01T23:59:59.000Z

277

Study Estimates Energy Savings From Bringing All U.S. Homes Up to Code  

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

Study Estimates Energy Savings From Bringing All U.S. Homes Up to Code Study Estimates Energy Savings From Bringing All U.S. Homes Up to Code October 2013 October-November Special Focus: Energy Efficiency, Buildings, the Electric Grid Throughout October and November, EETD presents a special series of articles, research highlights, and social media posts addressing some of its recent research on energy efficiency and other buildings-related topics, and the electric grid. Tightening the envelope of homes should save energy by reducing the loss of heat when the exterior is cold, and the loss of cooled air when it is hot. Until now, it has not been clear for the current housing stock how much potential for energy savings exists in the U.S. stock of homes if all were brought up to codes requiring the tightening of the building envelope.

278

Estimation of annual energy output from a tidal barrage using two different methods  

Science Journals Connector (OSTI)

In recent years, there have been growing international challenges relating to climate change and global warming, with a conflict developing between the need to create a low-carbon economy and rapid depleting reserves of fossil fuels. In addition to these challenges there continues to be the added complexity of a significant global increase in energy demand. Marine renewable energy from tidal barrages is carbon-free and has the potential to make a significant contribution to energy supplies now and in the future. Therefore, it is appropriate to evaluate the total energy that can be extracted from such barrages. In this study two different methods are proposed to estimate the total annual energy output from a barrage, including a theoretical estimation based on the principle associated with tidal hydrodynamics, and a numerical estimation based on the solutions obtained from a 2D hydrodynamic model. The proposed Severn Barrage in the UK was taken as a case study, and these two methods were applied to estimate the potential annual energy output from the barrage. The predicted results obtained using the two methods indicate that the magnitude of the annual energy output would range from 13 to 16TWh, which is similar to the value of 15.6TWh reported by the Department of Energy and Climate Change, in the UK. Further investigations show that the total annual energy output would increase by about 15% if a higher discharge coefficient were to be adopted for the sluice gates, or if the turbine performance were to be improved. However, the estimated annual energy output could exceed the value of 16TWh if future technological advances in both sluice gate construction and turbine performance are included.

Junqiang Xia; Roger A. Falconer; Binliang Lin; Guangming Tan

2012-01-01T23:59:59.000Z

279

Summary and Presentations from Estimating the Benefits and Costs of Distributed Energy Technologies Workshop Now Available  

Broader source: Energy.gov [DOE]

Beginning on September 30, 2014, the Department of Energy hosted a two-day workshop on Estimating the Benefits and Costs of Distributed Energy Technologies in Washington DC. The purpose of the workshop was to foster discussion about the analytic challenges associated with valuing the diverse impacts of deploying distributed energy technologies. Many valuation studies have been published in recent years, using different methods and assumptions.

280

Estimate of Geothermal Energy Resource in Major U.S. Sedimentary Basins (Presentation), NREL (National Renewable Energy Laboratory)  

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

ESTIMATE OF GEOTHERMAL ENERGY RESOURCE IN ESTIMATE OF GEOTHERMAL ENERGY RESOURCE IN MAJOR U.S. SEDIMENTARY BASINS Colleen Porro and Chad Augustine April 24, 2012 National Renewable Energy Lab, Golden, CO NREL/PR-6A20-55017 NATIONAL RENEWABLE ENERGY LABORATORY Sedimentary Basin Geothermal WHAT IS SEDIMENTARY BASIN GEOTHERMAL? 2 Geothermal Energy from Sedimentary Rock - Using 'hot" geothermal fluids (>100 o C) produced from sedimentary basins to generate electricity - Advantages: * Reservoirs are porous, permeable, and well characterized * Known/proven temperature gradients from oil and gas well records * Drilling and reservoir fracturing techniques proven in sedimentary environment - Disadvantages: * Great depths required to encounter high temperatures * Emerging industry Photo by Warren Gretz, NREL/PIX 00450

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

Estimation of bremsstrahlung photon energy in the environment of high-energy electron accelerator using CaSO4:Dy based TL dosemeter  

Science Journals Connector (OSTI)

......Estimation of bremsstrahlung photon energy in the environment of high-energy electron accelerator using CaSO4...Mishra S. C. Quality control audit using TLDs for linear accelerators...Estimation of bremsstrahlung photon energy in the environment of high-energy......

A. K. Bakshi; M. K. Nayak; G. Haridas; S. Chatterjee; R. K. Kher

2008-01-01T23:59:59.000Z

282

14 - Estimating Water, Energy, andCarbon Footprints ofResidential Swimming Pools  

Science Journals Connector (OSTI)

Abstract This chapter demonstrates the development and application of a model as a tool to assess and compare the environmental impacts of residential swimming pools. To demonstrate the applicability and dependability of this model as an assessment, planning, and management tool, realistic scenarios were employed to estimate and compare water, energy, and carbon footprints of residential swimming pools located in Maricopa County (Phoenix metropolitan area, Arizona) and colder climates. The estimated water footprints of the modeled residential swimming pools range from 45m3/year to 185m3/year/pool, while the estimated energy footprints range between 2400 and 2800kWh/year/pool. The carbon footprint of the modeled pools was estimated to be 140050kgCO2e/year/pool. In the absence of direct measurements, development and utilization of simple models to assess and predict water consumption proves to be an invaluable instrument that should be part of a versatile water management toolkit.

Tyler Gallion; Tyler Harrison; Robert Hulverson; Kiril Hristovski

2014-01-01T23:59:59.000Z

283

DOE Order Self Study Modules - DOE O 442.1 Department of energy Employee Concerns Program  

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

2.1 2.1 DEPARTMENT OF ENERGY EMPLOYEE CONCERNS PROGRAM ALBUQUERQUE OPERATIONS OFFICE Change No: 0 DOE O 442.1 Level: Familiar Date: 6/15/01 1 DOE O 442.1 DOE EMPLOYEE CONCERNS PROGRAM FAMILIAR LEVEL _________________________________________________________________________ OBJECTIVES Given the familiar level of this module and the resources listed below, you will be able to perform the following: 1. State three examples of criteria that should be used to assess the significance of an employee's concern. 2. Describe three classifications of employee occupational safety and health concerns that are used for determining safety significance. 3. Discuss the objective of implementing DOE O 442.1, DOE Employee Concerns Program. 4. Discuss the four alternatives for processing concerns.

284

Numerical estimation model of energy conversion for small hybrid solarwind system  

Science Journals Connector (OSTI)

This article presents a numerical model which can estimate the energy conversions of separate and hybrid solarwind systems under variable weather. The model integrates the equations associated with the characteristics of photovoltaic generation, wind energy conversion, energy balance, and battery bank, and uses the local database for radiation, wind speed, and ambient temperature. Once the equation associated with the characteristics of load is given, the numerical model can estimate the monthly and yearly powers output of the separate and hybrid solarwind systems provided with different configurations. As a fundamental research, the presentations of daily profiles of solar radiation, wind energy, and ambient temperature are explained in detail, and the combination of the characteristics of wind energy conversion and battery bank is determined. The condition of hybrid action is shown, and the solutions are certain to be found. The operation strategies of separate and hybrid systems are also presented.

Shun Ching Lee

2012-01-01T23:59:59.000Z

285

2003 status report savings estimates for the energy star(R)voluntary labeling program  

SciTech Connect (OSTI)

ENERGY STAR(R) is a voluntary labeling program designed to identify and promote energy-efficient products, buildings and practices. Operated jointly by the Environmental Protection Agency (EPA) and the U.S. Department of Energy (DOE), ENERGY STAR labels exist for more than thirty products, spanning office equipment, residential heating and cooling equipment, commercial and residential lighting, home electronics, and major appliances. This report presents savings estimates for a subset of ENERGY STAR program activities, focused primarily on labeled products. We present estimates of the energy, dollar and carbon savings achieved by the program in the year 2002, what we expect in 2003, and provide savings forecasts for two market penetration scenarios for the period 2003 to 2020. The target market penetration forecast represents our best estimate of future ENERGY STAR savings. It is based on realistic market penetration goals for each of the products. We also provide a forecast under the assumption of 100 percent market penetration; that is, we assume that all purchasers buy ENERGY STAR-compliant products instead of standard efficiency products throughout the analysis period.

Webber, Carrie A.; Brown, Richard E.; McWhinney, Marla

2004-11-09T23:59:59.000Z

286

2002 status report: Savings estimates for the ENERGY STAR(R) voluntary labeling program  

SciTech Connect (OSTI)

ENERGY STAR [registered trademark] is a voluntary labeling program designed to identify and promote energy-efficient products, buildings and practices. Operated jointly by the Environmental Protection Agency (EPA) and the U.S. Department of Energy (DOE), ENERGY STAR labels exist for more than thirty products, spanning office equipment, residential heating and cooling equipment, commercial and residential lighting, home electronics, and major appliances. This report presents savings estimates for a subset of ENERGY STAR program activities, focused primarily on labeled products. We present estimates of the energy, dollar and carbon savings achieved by the program in the year 2001, what we expect in 2002, and provide savings forecasts for two market penetration scenarios for the period 2002 to 2020. The target market penetration forecast represents our best estimate of future ENERGY STAR savings. It is based on realistic market penetration goals for each of the products. We also provide a forecast under the assumption of 100 percent market penetration; that is, we assume that all purchasers buy ENERGY STAR-compliant products instead of standard efficiency products throughout the analysis period.

Webber, Carrie A.; Brown, Richard E.; McWhinney, Marla; Koomey, Jonathan

2003-03-03T23:59:59.000Z

287

2004 status report: Savings estimates for the Energy Star(R)voluntarylabeling program  

SciTech Connect (OSTI)

ENERGY STAR(R) is a voluntary labeling program designed toidentify and promote energy-efficient products, buildings and practices.Operated jointly by the Environmental Protection Agency (EPA) and theU.S. Department of Energy (DOE), ENERGY STAR labels exist for more thanthirty products, spanning office equipment, residential heating andcooling equipment, commercial and residential lighting, home electronics,and major appliances. This report presents savings estimates for a subsetof ENERGY STAR labeled products. We present estimates of the energy,dollar and carbon savings achieved by the program in the year 2003, whatwe expect in 2004, and provide savings forecasts for two marketpenetration scenarios for the periods 2004 to 2010 and 2004 to 2020. Thetarget market penetration forecast represents our best estimate of futureENERGY STAR savings. It is based on realistic market penetration goalsfor each of the products. We also provide a forecast under the assumptionof 100 percent market penetration; that is, we assume that all purchasersbuy ENERGY STAR-compliant products instead of standard efficiencyproducts throughout the analysis period.

Webber, Carrie A.; Brown, Richard E.; McWhinney, Marla

2004-03-09T23:59:59.000Z

288

Energy savings estimates and cost benefit calculations for high performance relocatable classrooms  

SciTech Connect (OSTI)

This report addresses the results of detailed monitoring completed under Program Element 6 of Lawrence Berkeley National Laboratory's High Performance Commercial Building Systems (HPCBS) PIER program. The purpose of the Energy Simulations and Projected State-Wide Energy Savings project is to develop reasonable energy performance and cost models for high performance relocatable classrooms (RCs) across California climates. A key objective of the energy monitoring was to validate DOE2 simulations for comparison to initial DOE2 performance projections. The validated DOE2 model was then used to develop statewide savings projections by modeling base case and high performance RC operation in the 16 California climate zones. The primary objective of this phase of work was to utilize detailed field monitoring data to modify DOE2 inputs and generate performance projections based on a validated simulation model. Additional objectives include the following: (1) Obtain comparative performance data on base case and high performance HVAC systems to determine how they are operated, how they perform, and how the occupants respond to the advanced systems. This was accomplished by installing both HVAC systems side-by-side (i.e., one per module of a standard two module, 24 ft by 40 ft RC) on the study RCs and switching HVAC operating modes on a weekly basis. (2) Develop projected statewide energy and demand impacts based on the validated DOE2 model. (3) Develop cost effectiveness projections for the high performance HVAC system in the 16 California climate zones.

Rainer, Leo I.; Hoeschele, Marc A.; Apte, Michael G.; Shendell, Derek G.; Fisk, Wlliam J.

2003-12-01T23:59:59.000Z

289

The Smart Grid: An Estimation of the Energy and Carbon Dioxide (CO2)  

Open Energy Info (EERE)

The Smart Grid: An Estimation of the Energy and Carbon Dioxide (CO2) The Smart Grid: An Estimation of the Energy and Carbon Dioxide (CO2) Benefits Jump to: navigation, search Tool Summary LAUNCH TOOL Name: The Smart Grid: An Estimation of the Energy and Carbon Dioxide (CO2) Benefits Focus Area: Crosscutting Topics: Market Analysis Website: energyenvironment.pnl.gov/news/pdf/PNNL-19112_Revision_1_Final.pdf Equivalent URI: cleanenergysolutions.org/content/smart-grid-estimation-energy-and-carb Language: English Policies: "Deployment Programs,Regulations,Financial Incentives" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Public-Private Partnerships Regulations: "Resource Integration Planning,Mandates/Targets,Enabling Legislation,Appliance & Equipment Standards and Required Labeling" is not in the list of possible values (Agriculture Efficiency Requirements, Appliance & Equipment Standards and Required Labeling, Audit Requirements, Building Certification, Building Codes, Cost Recovery/Allocation, Emissions Mitigation Scheme, Emissions Standards, Enabling Legislation, Energy Standards, Feebates, Feed-in Tariffs, Fuel Efficiency Standards, Incandescent Phase-Out, Mandates/Targets, Net Metering & Interconnection, Resource Integration Planning, Safety Standards, Upgrade Requirements, Utility/Electricity Service Costs) for this property.

290

End-use energy consumption estimates for U.S. commercial buildings, 1992  

SciTech Connect (OSTI)

An accurate picture of how energy is used in the nation`s stock of commercial buildings can serve a variety of program planning and policy needs of the US Department of Energy, utilities, and other groups seeking to improve the efficiency of energy use in the building sector. This report describes an estimation of energy consumption by end use based upon data from the 1992 Commercial Building Energy Consumption Survey (CBECS). The methodology used in the study combines elements of engineering simulations and statistical analysis to estimate end-use intensities for heating, cooling, ventilation, lighting, refrigeration, hot water, cooking, and miscellaneous equipment. Statistical Adjusted Engineering (SAE) models were estimated by building type. The nonlinear SAE models used variables such as building size, vintage, climate region, weekly operating hours, and employee density to adjust the engineering model predicted loads to the observed consumption (based upon utility billing information). End-use consumption by fuel was estimated for each of the 6,751 buildings in the 1992 CBECS. The report displays the summary results for 11 separate building types as well as for the total US commercial building stock. 4 figs., 15 tabs.

Belzer, D.B.; Wrench, L.E.

1997-03-01T23:59:59.000Z

291

Modulational instability of two pairs of counter-propagating waves and energy exchange in two-component media  

E-Print Network [OSTI]

Modulational instability of two pairs of counter-propagating waves and energy exchange in two-propagating waves in two-component media is considered within the framework of two generally nonintegrable coupled Sine-Gordon equations. We consider the dynamics of weakly nonlinear wave packets, and using

292

Estimating nonlinear QCD effects in ultrahigh energy neutrino events at IceCube  

Science Journals Connector (OSTI)

The number of ultrahigh energy events at IceCube is estimated, for the first time, taking into account nonlinear QCD effects in the neutrino-hadron cross section. We assume that the extragalactic neutrino flux is given by ??(E?)=?0E??2 and estimate the neutrino-hadron cross section using the dipole approach and a phenomenological model for the dipole-hadron cross section based on nonlinear QCD dynamics. We demonstrate that the nonlinear prediction is able to describe the current IceCube data and that the magnitude of the nonlinear effects is larger than 20% for visible energies of order of 2PeV and increases with the neutrino energy. Our main conclusion is that the nonlinear QCD effects are non-negligible and should be taken into account in the analysis of the number of ultrahigh energy events.

V.?P. Gonalves and D.?R. Gratieri

2014-09-11T23:59:59.000Z

293

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

SciTech Connect (OSTI)

Buildings represent an increasingly important component of China's total energy consumption mix. However, accurately assessing the total volume of energy consumed in buildings is difficult owing to deficiencies in China's statistical collection system and a lack of national surveys. Official statistics suggest that buildings account for about 19% of China's total energy consumption, while others estimate the proportion at 23%, rising to 30% over the next few years. In addition to operational energy, buildings embody the energy used in the in the mining, extraction, harvesting, processing, manufacturing and transport of building materials as well as the energy used in the construction and decommissioning of buildings. This embodied energy, along with a building's operational energy, constitutes the building's life-cycle energy and emissions footprint. This report first provides a review of international studies on commercial building life-cycle energy use from which data are derived to develop an assessment of Chinese commercial building life-cycle energy use, then examines in detail two cases for the development of office building operational energy consumption to 2020. Finally, the energy and emissions implications of the two cases are presented.

Fridley, David; Fridley, David G.; Zheng, Nina; Zhou, Nan

2008-03-01T23:59:59.000Z

294

Development of an energy-use estimation methodology for the revised Navy Manual MO-303  

SciTech Connect (OSTI)

The U.S. Navy commissioned Pacific Northwest Laboratory (PNL) to revise and/or update the Navy Utilities Targets Manual, NAVFAC MO-303 (U.S. Navy 1972b). The purpose of the project was to produce a current, applicable, and easy-to-use version of the manual for use by energy and facility engineers and staff at all Navy Public Works Centers (PWCs), Public Works Departments (PWDs), Engineering Field Divisions (EFDs), and other related organizations. The revision of the MO-303 manual involved developing a methodology for estimating energy consumption in buildings and ships. This methodology can account for, and equitably allocate, energy consumption within Navy installations. The analyses used to develop this methodology included developing end-use intensities (EUIs) from a vast collection of Navy base metering and billing data. A statistical analysis of the metering data, weather data, and building energy-use characteristics was used to develop appropriate EUI values for use at all Navy bases. A complete Navy base energy reconciliation process was also created for use in allocating all known energy consumption. Initial attempts to use total Navy base consumption values did not produce usable results. A parallel effort using individual building consumption data provided an estimating method that incorporated weather effects. This method produced a set of building EUI values and weather adjustments for use in estimating building energy use. A method of reconciling total site energy consumption was developed based on a {open_quotes}zero-sum{close_quotes} principle. This method provides a way to account for all energy use and apportion part or all of it to buildings and other energy uses when actual consumption is not known. The entire text of the manual was also revised to present a more easily read understood and usable document.

Richman, E.E.; Keller, J.M.; Wood, A.G.; Dittmer, A.L.

1995-01-01T23:59:59.000Z

295

Unbiased Estimate of Dark Energy Density from Type Ia Supernova Data  

Science Journals Connector (OSTI)

Type Ia supernovae (SNe Ia) are currently the best probes of the dark energy in the universe. To constrain the nature of dark energy, we assume a flat universe and that the weak energy condition is satisfied, and we allow the density of dark energy, ?X(z), to be an arbitrary function of redshift. Using simulated data from a space-based SN pencil-beam survey, we find that by optimizing the number of parameters used to parameterize the dimensionless dark energy density, f(z) = ?X(z)/?X(z = 0), we can obtain an unbiased estimate of both f(z) and the fractional matter density of the universe, ?m. A plausible SN pencil-beam survey (with a square degree field of view and for an observational duration of 1 yr) can yield about 2000 SNe Ia with 0 ? z ? 2. Such a survey in space would yield SN peak luminosities with a combined intrinsic and observational dispersion of ?(mint) = 0.16 mag. We find that for such an idealized survey, ?m can be measured to 10% accuracy, and the dark energy density can be estimated to ~20% to z ~ 1.5, and ~20%-40% to z ~ 2, depending on the time dependence of the true dark energy density. Dark energy densities that vary more slowly can be more accurately measured. For the anticipated Supernova/Acceleration Probe (SNAP) mission, ?m can be measured to 14% accuracy, and the dark energy density can be estimated to ~20% to z ~ 1.2. Our results suggest that SNAP may gain much sensitivity to the time dependence of the dark energy density and ?m by devoting more observational time to the central pencil-beam fields to obtain more SNe Ia at z > 1.2. We use both a maximum likelihood analysis and a Monte Carlo analysis (when appropriate) to determine the errors of estimated parameters. We find that the Monte Carlo analysis gives a more accurate estimate of the dark energy density than the maximum likelihood analysis.

Yun Wang; Geoffrey Lovelace

2001-01-01T23:59:59.000Z

296

An Estimate of the Thermodynamic Pressure in High-Energy Collisions  

E-Print Network [OSTI]

We introduce a novel approach to estimate the thermodynamic pressure from heavy-ion collisions based on recently measured higher-order moments of particle multiplicities by the STAR experiment. We start with fitting the experimental results in the most-central collisions. Then, we integrate them back to lower ones. For example, we find that the first-order moment, the mean multiplicity, is exactly reproduced from the integral of variance, the second-order moment. Therefore, the zero-order moment, the thermodynamic pressure, can be estimated from the integral of the mean multiplicity. the possible comparison between such a kind of pressure (deduced from the integral of particle multiplicity) and the lattice pressure and the relating of Bjorken energy density to the lattice energy density are depending on lattice QCD at finite baryon chemical potential and first-principle estimation of the formation time of the quark-gluon plasma (QGP).

Tawfik, Abdel Nasser

2015-01-01T23:59:59.000Z

297

Recoverable Resource Estimate of Identified Onshore Geopressured Geothermal Energy in Texas and Louisiana (Presentation), NREL (National Renewable Energy Laboratory)  

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

Recoverable Resource Estimate of Identified Recoverable Resource Estimate of Identified Onshore Geopressured Geothermal Energy in Texas and Louisiana AAPG 2012 Annual Convention and Exhibition Ariel Esposito and Chad Augustine April 24, 2012 NREL/PR-6A20-54999 2 * Geopressured Geothermal o Reservoirs characterized by pore fluids under high confining pressures and high temperatures with correspondingly large quantities of dissolved methane o Soft geopressure: Hydrostatic to 15.83 kPa/m o Hard geopressure: 15.83- 22.61 kPa/m (lithostatic pressure gradient) * Common Geopressured Geothermal Reservoir Structure o Upper thick low permeability shale o Thin sandstone layer o Lower thick low permeability shale * Three Potential Sources of Energy o Thermal energy (Temperature > 100°C - geothermal electricity generation)

298

Estimating the environmental impact of home energy visits and extent of behaviour change  

Science Journals Connector (OSTI)

Abstract The objective of this study was to estimate the environmental impact of a home energy visit programme, known as RE:NEW, that was delivered in London, in the United Kingdom. These home energy visits intended to encourage reductions in household carbon emissions and water consumption through the installation of small energy saving measures (such as radiator panels, in-home energy displays and low-flow shower heads), further significant energy saving measures (loft and cavity wall insulation) and behaviour change advice. The environmental impact of the programme was estimated in terms of carbon emissions abated and on average, for each household in the study, a visit led to an average carbon abatement of 146kgCO2. The majority of this was achieved through the installation of small energy saving measures. The impact of the visits on the installation of significant measures was negligible, as was the impact on behaviour change. Therefore, these visits did not overcome the barriers required to generate behaviour change or the barriers to the installation of more significant energy saving measures. Given this, a number of recommendations are proposed in this paper, which could increase the efficacy of these home energy visits.

Kristy Revell

2014-01-01T23:59:59.000Z

299

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. ???, XXXX, DOI:10.1029/, Refinements to flare energy estimates -a follow-up to "Energy  

E-Print Network [OSTI]

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. ???, XXXX, DOI:10.1029/, Refinements to flare energy , G. D. Holman 2 , and H. S. Hudson 3 Abstract. Emslie et al. [2004] reported estimates of the energy estimates - a follow-up to "Energy Partition in Two Solar Flare/CME Events" A. G. Emslie, 1 B. R. Dennis 2

California at Berkeley, University of

300

Program Potential: Estimates of Federal Energy Cost Savings from Energy Efficient Procurement  

E-Print Network [OSTI]

Freezers Commercial Steam Cookers b EnergyStar EnergyStarFreezers Com Steam Cookers Water-Cooled Ice Machines Pre-Printer CommercialSteamCookers CommercialCentralAir

Taylor, Margaret

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "module estimates energy" from the National Library of EnergyBeta (NLEBeta).
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We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Assumptions to the Annual Energy Outlook 2001 - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply. 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(2001), (Washington, DC, January 2001). 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 gas from domestic fields throughout the United States, acquire natural gas from foreign producers for resale in the United States, or sell U.S. gas to foreign consumers. OGSM encompasses domestic crude oil and natural gas supply by both

302

MHK Technologies/Small power take off module | Open Energy Information  

Open Energy Info (EERE)

power take off module power take off module < MHK Technologies Jump to: navigation, search << Return to the MHK database homepage Small power take off module.jpg Technology Profile Primary Organization Wavegen subsidiary of Voith Siemens Hydro Power Generation Technology Resource Click here Wave Technology Readiness Level Click here TRL 1 3 Discovery Concept Def Early Stage Dev Design Engineering Technology Description The 18 5kW power modules consist of a 5th generation Wells turbine valve and noise attenuator The complete modules weigh less than a tonne so installation or removal is easily achievable using a small mobile crane The modules are very simple and rugged the blades are fixed onto the rotor have no pitching mechanism no gearbox and have no contact with seawater

303

Assumptions to the Annual Energy Outlook 2002 - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply. 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(2002), (Washington, DC, January 2002). 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 gas from domestic fields throughout the United States, acquire natural gas from foreign producers for resale in the United States, or sell U.S. gas to foreign consumers. OGSM encompasses domestic crude oil and natural gas supply by both

304

Review of Photovoltaic Energy Production Using CdTe Thin-Film Modules: Extended Abstract Preprint  

SciTech Connect (OSTI)

CdTe has near-optimum bandgap, excellent deposition traits, and leads other technologies in commercial PV module production volume. Better understanding materials properties will accelerate deployment.

Gessert, T. A.

2008-09-01T23:59:59.000Z

305

Overview of the PV Module Model in PVWatts (Presentation)  

SciTech Connect (OSTI)

Overview of the PV module model. PVWatts module power estimates were compared with those using the Sandia model for three modules and data sets.

Marion, B.

2010-09-22T23:59:59.000Z

306

Integrated estimation of commercial sector end-use load shapes and energy use intensities  

SciTech Connect (OSTI)

The Southern California Edison Company (SCE) and the California Energy Commission (CEC) have contracted with Energy Analysis Program of the Applied Science Division at the Lawrence Berkeley Laboratory (LBL) to develop an integrated set of commercial sector load shapes (LS) and energy utilization indices (EUI) for use in forecasting electricity demand. The overall objectives of this project are to conduct detailed analyses of SCE data on commercial building characteristics, energy use, and whole-building load shapes, and, in conjunction with other data, to develop, test, and apply an integrated approach for the estimation of end-use LSs and EUIs. The project is one of the first attempts ever to combine simulation-based, prototypical building analyses with direct reconciliation to measured hourly load data.

Akbari, H.; Eto, J.; Turiel, I.; Heinemeier, K.; Lebot, B.; Nordman, B.; Rainer, L.

1989-01-01T23:59:59.000Z

307

Closing Data Gaps for LCA of Food Products: Estimating the Energy Demand of Food Processing  

Science Journals Connector (OSTI)

Closing Data Gaps for LCA of Food Products: Estimating the Energy Demand of Food Processing ... To quantify the environmental impacts arising from food production, environmental assessment tools such as life cycle assessment (LCA) should be applied. ... Most of the published LCAs on food are assessing primary agricultural products, e.g., refs 4 and 5, whereas the number of studies available on processed food is lower, e.g., refs 6?8. ...

Neus Sanjun; Franziska Stoessel; Stefanie Hellweg

2013-12-17T23:59:59.000Z

308

Estimating expected energy capture at potential wind turbine sites in Norway  

Science Journals Connector (OSTI)

To estimate the expected energy capture at potential wind turbine sites in Norway, a combination of low-cost wind monitoring, correlation and models are used. The wind monitoring, the correlation and the uncertainty of the method are described. Results from two cases are compared with predictions made with the model WASP. The results indicate that measurements are needed near potential wind turbine sites, until a high quality reference data set has been established, and models for complex terrain effects are validated.

T.A. Nygaard

1992-01-01T23:59:59.000Z

309

Detailed Course Module Description  

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

Course Module Description Course Module Description Module/Learning Objectives Level of Detail in Module by Audience Consumers Gen Ed/ Community College Trades 1. Energy Issues and Building Solutions High High High Learning Objectives: * Define terms of building science, ecological systems, economics of consumption * Relate building science perspective, ecology, social science * Explain historical energy and environmental issues related to buildings * Compare Site and source energy * Examine the health, safety and comfort issues in buildings * Examine the general context for building solutions (zero energy green home with durability as the goal) * Explain a basic overview of alternative energy (total solar flux) - do we have enough energy * Examine cash flow to homeowners

310

Estimating home energy decision parameters for a hybrid energyYeconomy policy model  

E-Print Network [OSTI]

-constrained world. Long-run simulations were created using CIMS, a hybrid energy-economy model supply submodel was built to simulate economies of scale in infrastructure. Capital costs, technology performance, infrastructure, fuel prices, and other conditions were varied in the simulations. All scenarios

311

Optimal estimation of free energies and stationary densities from multiple biased simulations  

E-Print Network [OSTI]

When studying high-dimensional dynamical systems such as macromolecules, quantum systems and polymers, a prime concern is the identification of the most probable states and their stationary probabilities or free energies. Often, these systems have metastable regions or phases, prohibiting to estimate the stationary probabilities by direct simulation. Efficient sampling methods such as umbrella sampling, metadynamics and conformational flooding have developed that perform a number of simulations where the system's potential is biased such as to accelerate the rare barrier crossing events. A joint free energy profile or stationary density can then be obtained from these biased simulations with weighted histogram analysis method (WHAM). This approach (a) requires a few essential order parameters to be defined in which the histogram is set up, and (b) assumes that each simulation is in global equilibrium. Both assumptions make the investigation of high-dimensional systems with previously unknown energy landscape ...

Wu, Hao

2013-01-01T23:59:59.000Z

312

Estimation methods review and analysis of offshore extreme wind speeds and wind energy resources  

Science Journals Connector (OSTI)

Abstract Offshore wind resources are more abundant and stronger and they blow more consistently than land-based wind resources. While gale force winds are easier to hit on the sea, the strong wind vibration and wind loads may exert severe damage and shock to wind turbines and wind power grids, even resulting in power grid collapse. Thus, to develop offshore wind power, apart from accurate quantitative wind energy potential assessments, it is necessary to effectively estimate extreme wind speeds. Toward this purpose, this paper investigates the current status of extreme wind speeds and wind energy assessment from literature review. It turns out that much work on wind energy estimation has been performed, whereas relatively little research involves extreme wind speeds, the main challenge stemming from the limited availability of derived extreme winds. Then a GH method based on artificial intelligence optimization algorithms is developed to re-analyze future samples of extreme wind speeds. On the basis of the re-analyzed extreme samples, as well as the Generalized Extreme Value (GEV) and Gumbel models optimized by Cuckoo Search (CS) and Chaotic Particle Swarm Optimization (CPSO) algorithms, the potential risks of extreme wind speeds are conducted based on 23-year (19902012) historic wind speeds. Thus, in terms of wind speeds, a comprehensive estimation for offshore wind energy is initially implemented in Bohai Rim, China. The assessment shows that the study areas have high-strength wind power but are rarely subjected to extreme wind speeds, which implies that it is suitable for wind farm construction.

Jianzhou Wang; Shanshan Qin; Shiqiang Jin; Jie Wu

2015-01-01T23:59:59.000Z

313

Estimation of Energy Baseline by Simulation for On-going Commissioning and Energy Saving Retrofit  

E-Print Network [OSTI]

if the building is closed. 0 100 200 300 400 500 0:00 4:00 8:00 12:00 16:00 20:00 0:00 4:00 8:00 12:00 16:00 20:00 0:00 Measured Simulated Cooling Load [kW] Fig. 7 Hourly-integrated cooling load 0 100 200 300 400 500 2005/8/6 2005/8/14 2005/8/22 2005.../8/30 2005/9/7 2005/9/15 2005/9/23 Simulated Estimated using Gas Consumption Daily-integrated Cooling Load [kW] Fig. 8 Daily-integrated cooling load 5.1 Models Of Equipments Used For Air-Conditioning System a) Gas Consumption of Gas-Fired Absorption...

Miyata, M.; Yoshida, H.; Asada, M.; Iwata, T.; Tanabe, Y.; Yanagisawa, T.

2006-01-01T23:59:59.000Z

314

Scintillation counter and wire chamber front end modules for high energy physics experiments  

SciTech Connect (OSTI)

This document describes two front-end modules developed for the proposed MIPP upgrade (P-960) experiment at Fermilab. The scintillation counter module was developed for the Plastic Ball detector time and charge measurements. The module has eight LEMO 00 input connectors terminated with 50 ohms and accepts negative photomultiplier signals in the range 0.25...1000 pC with the maximum input voltage of 4.0 V. Each input has a passive splitter with integration and differentiation times of {approx}20 ns. The integrated portion of the signal is digitized at 26.55 MHz by Analog Devices AD9229 12-bit pipelined 4-channel ADC. The differentiated signal is discriminated for time measurement and sent to one of the four TMC304 inputs. The 4-channel TMC304 chip allows high precision time measurement of rising and falling edges with {approx}100 ps resolution and has internal digital pipeline. The ADC data is also pipelined which allows deadtime-less operation with trigger decision times of {approx}4 {micro}s. The wire chamber module was developed for MIPP EMCal detector charge measurements. The 32-channel digitizer accepts differential analog signals from four 8-channel integrating wire amplifiers. The connection between wire amplifier and digitizer is provided via 26-wire twist-n-flat cable. The wire amplifier integrates input wire current and has sensitivity of 275 mV/pC and the noise level of {approx}0.013 pC. The digitizer uses the same 12-bit AD9229 ADC chip as the scintillator counter module. The wire amplifier has a built-in test pulser with a mask register to provide testing of the individual channels. Both modules are implemented as a 6Ux220 mm VME size board with 48-pin power connector. A custom europack (VME) 21-slot crate is developed for housing these front-end modules.

Baldin, Boris; DalMonte, Lou; /Fermilab

2011-01-01T23:59:59.000Z

315

Solar Energy Resource Assessment in Chile: Satellite Estimation and Ground Station Measurement  

Science Journals Connector (OSTI)

Abstract The progress from the last four years in solar energy resource assessment for Chile is reported, including measurements from a ground station network spanning from two to three years of data, and satellite estimations from the recently developed Chile-SR model including two full years of data. The model introduces different treatments for the meteorological variables and the effective cloud cover computations which allow estimation of the global horizontal irradiation on an hourly basis. The BRL model of diffuse radiation is then applied in order to estimate the diffuse fraction and diffuse irradiation, from which the Direct horizontal irradiation is then computed. Direct normal irradiation is computed by applying proper solar geometry corrections to the direct horizontal irradiation. The satellite estimation model was developed as an adaptation from Brazil-SR model, with an improved formulation for altitude-corrected atmospheric parameters, and a novel formulation for calculating effective cloud covers while at the same time detecting and differentiating it from snow covers and salt lakes. The model is validated by comparison with ground station data. The results indicate that there are high radiation levels throughout the country. In particular, northern Chile is endowed with one of the highest solar resources in the world, although the resource variability is higher than previously thought.

Rodrigo A. Escobar; Alberto Ortega; Cristin Corts; Alan Pinot; Enio Bueno Pereira; Fernando Ramos Martins; John Boland

2014-01-01T23:59:59.000Z

316

NREL Triples Previous Estimates of U.S. Wind Power Potential (Fact Sheet), The Spectrum of Clean Energy Innovation, NREL (National Renewable Energy Laboratory)  

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

Triples Previous Estimates of Triples Previous Estimates of U.S. Wind Power Potential The National Renewable Energy Laboratory (NREL) recently released new estimates of the U.S. potential for wind-generated electricity, using advanced wind mapping and validation techniques that triple previous estimates of the size of the nation's wind resources. The new study, conducted by NREL and AWS TruePower, finds that the contiguous 48 states have the potential to generate up to 37 million gigawatt-hours annually. In comparison, the total U.S. electricity generation from all sources was roughly 4 million gigawatt-hours in 2009. Detailed state-by-state estimates of wind energy potential for the United States show the estimated average wind speeds at an 80-meter height. The wind resource maps and estimates

317

Estimates of wind energy input to the Ekman layer in the Southern Ocean from surface drifter data  

E-Print Network [OSTI]

Estimates of wind energy input to the Ekman layer in the Southern Ocean from surface drifter data the contribution from the anticyclonic frequencies dominate the wind energy input. The latitudinal and seasonal variations of the wind energy input to the Ekman layer are closely related to the variations of the wind

Gille, Sarah T.

318

This paper introduces a methodology for estimation of energy consumption in peripherals such as audio and video devices.  

E-Print Network [OSTI]

ABSTRACT This paper introduces a methodology for estimation of energy consumption in peripherals such as audio and video devices. Peripherals can be responsible for significant amount of the energy consumption in current embedded systems. We introduce a cycle- accurate energy simulator and profiler capable

Simunic, Tajana

319

Dietary Energy Balance Modulation of Kras- and Ink4a/Arf+/?-Driven Pancreatic Cancer: The Role of Insulin-like Growth Factor-I  

Science Journals Connector (OSTI)

...provide 30% less total energy and 100% of all vitamins...approximately 30% more total energy, with 100% of vitamins...mice/diet) of dietary energy balance modulation, or...Sinai School of Medicine, New York, NY). Wild-type FVB...

Laura M. Lashinger; Lauren M. Harrison; Audrey J. Rasmussen; Craig D. Logsdon; Susan M. Fischer; Mark J. McArthur; and Stephen D. Hursting

2013-10-01T23:59:59.000Z

320

Dietary Energy Balance Modulation of Kras- and Ink4a/Arf+/?-Driven Pancreatic Cancer: The Role of Insulin-like Growth Factor-I  

Science Journals Connector (OSTI)

...factor and intracellular energy status signaling. We hypothesized...is responsive to dietary energy balance modulation in an...of body mass index among US adults, 1999-2010...Demark-Wahnefried W, et alObesity, energy balance, and cancer...

Laura M. Lashinger; Lauren M. Harrison; Audrey J. Rasmussen; Craig D. Logsdon; Susan M. Fischer; Mark J. McArthur; and Stephen D. Hursting

2013-10-01T23:59:59.000Z

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

Practical method for estimating wind characteristics at potential wind-energy-conversion sites  

SciTech Connect (OSTI)

Terrain features and variations in the depth of the atmospheric boundary layer produce local variations in wind, and these variations are not depicted well by standard weather reports. A method is developed to compute local winds for use in estimating the wind energy available at any potential site for a wind turbine. The method uses the terrain heights for an area surrounding the site and a series of wind and pressure reports from the nearest four or five national Weather Service stations. An initial estimate of the winds in the atmospheric boundary layer is made, then these winds are adjusted to satisfy the continuity equation. In this manner the flow is made to reflect the influences of the terrain and the shape of the boundary-layer top. This report describes in detail the methodology and results, and provides descriptions of the computer programs, instructions for using them, and complete program listings.

Endlich, R. M.; Ludwig, F. L.; Bhumralkar, C. M.; Estoque, M. A.

1980-08-01T23:59:59.000Z

322

Biomass Characteristics Index: A Numerical Approach in Palm Bio-Energy Estimation  

Science Journals Connector (OSTI)

Abstract In order to give a clear insight of the energy output estimation from the biomass, a comprehensive study on the physical properties of the biomass: bulk density and moisture content is crucial. A Biomass Characteristics Index (BCI) is proposed to represent the relationship between bulk density and moisture content. A numerical framework is developed to determine the BCI. This index is used to estimate the biomass bulk density and moisture content before the calorific value calculation. The classification of biomass according to its specific BCI can forecast the related bulk density and moisture content. Therefore, it reduces the hassle and time constraint to get those values through conventional empirical method. This will increase the overall biomass operational management efficiency.

Jiang Ping Tang; Hon Loong Lam; Mustafa Kamal Abdul Aziz; Noor Azian Morad

2014-01-01T23:59:59.000Z

323

NEMS Freight Transportation Module Improvement Study  

Reports and Publications (EIA)

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

2015-01-01T23:59:59.000Z

324

Remainder estimates for the Long Range Behavior of the van der Waals interaction energy  

E-Print Network [OSTI]

The van der Waals-London's law, for a collection of atoms at large separation, states that their interaction energy is pairwise attractive and decays proportionally to one over their distance to the sixth. The first rigorous result in this direction was obtained by Lieb and Thirring [LT], by proving an upper bound which confirms this law. Recently the van der Waals-London's law was proven under some assumptions by I.M. Sigal and the author [AS]. Following the strategy of [AS] and reworking the approach appropriately, we prove estimates on the remainder of the interaction energy. Furthermore, using an appropriate test function, we prove an upper bound for the interaction energy, which is sharp to leading order. For the upper bound, our assumptions are weaker, the remainder estimates stronger and the proof is simpler. The upper bound, for the cases it applies, improves considerably the upper bound of Lieb and Thirring. However, their bound is much more general. Here we consider only spinless Fermions.

Ioannis Anapolitanos

2014-10-21T23:59:59.000Z

325

Estimation of Building Parameters Using Simplified Energy Balance Model and Metered Whole Building Energy Use  

E-Print Network [OSTI]

to the difference between the total energy entering and leaving the system. That is, CV entering leaving air cond sol occ E C H E E E Q Q Q Q Q E E ? ? ? ? ? ? ? ? ? ? (1) where Qair, Qcond, Qsol, Qocc, and QE are building heat load components from air... is defined as (Shao, 2006): BL E C H E C H air cond sol occ E Q E E fE E E Q Q Q Q ? ? ? ? ? ? ? ? ? ? ? (2) where EE is the metered whole-building non-cooling electricity use. The multiplicative factor f represents a fraction of EE which...

Masuda, H.; Claridge, D.

2012-01-01T23:59:59.000Z

326

Outdoor PV Module Degradation of Current-Voltage Parameters: Preprint  

SciTech Connect (OSTI)

Photovoltaic (PV) module degradation rate analysis quantifies the loss of PV power output over time and is useful for estimating the impact of degradation on the cost of energy. An understanding of the degradation of all current-voltage (I-V) parameters helps to determine the cause of the degradation and also gives useful information for the design of the system. This study reports on data collected from 12 distinct mono- and poly-crystalline modules deployed at the National Renewable Energy Laboratory (NREL) in Golden, Colorado. Most modules investigated showed < 0.5%/year decrease in maximum power due to short-circuit current decline.

Smith, R. M.; Jordan, D. C.; Kurtz, S. R.

2012-04-01T23:59:59.000Z

327

The National Energy Modeling System: An Overview 1998 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

COAL MARKET MODULE COAL MARKET MODULE blueball.gif (205 bytes) Coal Production Submodule blueball.gif (205 bytes) Coal Distribution Submodule blueball.gif (205 bytes) Coal Export Component The coal market module (CMM) represents the mining, transportation, and pricing of coal, subject to end-use demand. Coal supplies are differentiated by heat and sulfur content. The CMM also determines the minimum cost pattern of coal supply to meet exogenously defined U.S. coal export demands as a part of the world coal market. Coal supply is projected on a cost-minimizing basis, constrained by existing contracts. Twelve different coal types are differentiated with respect to thermal grade, sulfur content, and underground or surface mining. The domestic production and distribution of coal is forecast for 13 demand regions and 11 supply

328

Order Module--DOE O 420.1B, FACILITY SAFETY | Department of Energy  

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

DOE O 420.1B, FACILITY SAFETY DOE O 420.1B, FACILITY SAFETY Order Module--DOE O 420.1B, FACILITY SAFETY To ensure that new DOE hazard category 1, 2, and 3 nuclear facilities are designed and constructed in a manner that ensures adequate protection to the public, workers, and the environment from nuclear hazards. To ensure that major modifications to hazard category 1, 2, and 3 nuclear facilities comply with the design and construction requirements for new hazard category 1, 2, and 3 nuclear facilities. To ensure that new DOE nuclear reactors comply with the requirements of DOE O 420.1B and the design requirements of DOE O 5480.30, Nuclear Reactor Safety Design Criteria. DOE Order Self Study Modules - DOE O 420.1B Facility Safety More Documents & Publications Order Module--DOE O 420.2B, SAFETY OF ACCELERATOR FACILITIES

329

A new approach to estimate commercial sector end-use load shapes and energy use intensities  

SciTech Connect (OSTI)

We discuss the application of an end-use load shape estimation technique to develop annual energy use intensities (EUIs) and hourly end-use load shapes (LSs) for commercial buildings in the Pacific Gas and Electric Company (PG&E) service territory. Results will update inputs for the commercial sector energy and peak demand forecasting models used by PG&E and the California Energy Commission (CEC). EUIs were estimated for 11 building types, up to 10 end uses, 3 fuel types, 2 building vintages, and up to 5 climate regions. The integrated methodology consists of two major parts. The first part is the reconciliation of initial end-use load-shape estimates with measured whole-building load data to produce intermediate EUIs and load shapes, using LBL`s End-use Disaggregation Algorithm, EDA. EDA is a deterministic hourly algorithm that relies on the observed characteristics of the measured hourly whole-building electricity use and disaggregates it into major end-use components. The end-use EUIs developed through the EDA procedure represent a snap-shot of electricity use by building type and end-use for two regions of the PG&E service territory, for the year that disaggregation is performed. In the second part of the methodology, we adjust the EUIs for direct application to forecasting models based on factors such as climatic impacts on space-conditioning EUIs, fuel saturation effects, building and equipment vintage, and price impacts. Core data for the project are detailed on-site surveys for about 800 buildings, mail surveys ({approximately}6000), load research data for over 1000 accounts, and hourly weather data for five climate regions.

Akbari, H.; Eto, J.; Konopacki, S.; Afzal, A.; Heinemeier, K.; Rainer, L.

1994-08-01T23:59:59.000Z

330

Estimate the fraction of the total transported energy (in the form of gasoline) in the Trans-Alaska Pipeline that is consumed in pumping.  

E-Print Network [OSTI]

Estimate the fraction of the total transported energy (in the form of gasoline) in the Trans m). So we can toss this out. Now estimate the energy content of gasoline: Many of you tried figuring

Nimmo, Francis

331

Efficient estimation of energy transfer efficiency in light-harvesting complexes  

E-Print Network [OSTI]

The fundamental physical mechanisms of energy transfer in photosynthetic complexes is not yet fully understood. In particular, the degree of efficiency or sensitivity of these systems for energy transfer is not known given their non-perturbative and non-Markovian interactions with proteins backbone and surrounding photonic and phononic environments. One major problem in studying light-harvesting complexes has been the lack of an efficient method for simulation of their dynamics in biological environments. To this end, here we revisit the second-order time-convolution (TC2) master equation and examine its reliability beyond extreme Markovian and perturbative limits. In particular, we present a derivation of TC2 without making the usual weak system-bath coupling assumption. Using this equation, we explore the long time behaviour of exciton dynamics of Fenna-Matthews-Olson (FMO) protein complex. Moreover, we introduce a constructive error analysis to estimate the accuracy of TC2 equation in calculating energy transfer efficiency, exhibiting reliable performance for environments with weak and intermediate memory and strength. Furthermore, we numerically show that energy transfer efficiency is optimal and robust for the FMO protein complex of green sulphur bacteria with respect to variations in reorganization energy and bath correlation time-scales.

Alireza Shabani; Masoud Mohseni; Herschel Rabitz; Seth Lloyd

2011-03-20T23:59:59.000Z

332

Using the fracture energies for the two films a first estimate of fracture toughness, K, can be found.  

E-Print Network [OSTI]

· Using the fracture energies for the two films a first estimate of fracture toughness, K, can be found. · Assumptions are made to estimate the crack area based on the fracture mode seen in the SEM. · The total crack length is assumed to be 3 times the contact radius, , at the fracture depth. · To find

Collins, Gary S.

333

Computational modeling of laser-plasma interactions: Pulse self-modulation and energy transfer between intersecting laser pulses  

Science Journals Connector (OSTI)

The nonlinear interaction of intense femtosecond laser pulses with a self-induced plasma channel in air and the energy transfer between two intersecting laser pulses were simulated using the finite-difference time-domain particle-in-cell method. Implementation of a simple numerical code enabled modeling of various phenomena, including pulse self-modulation in the spatiotemporal and spectral domains, conical emission, and energy transfer between two intersecting laser beams. The mechanism for energy transfer was found to be related to a plasma waveguide array induced by Moir patterns of the interfering electric fields. The simulation results provide a persuasive replication and explanation of previous experimental results, when carried out under comparable physical conditions, and lead to prediction of others. This approach allows us to further examine the effect of the laser and plasma parameters on the simulation results and to investigate the underlying physics.

Rotem Kupfer; Boris Barmashenko; Ilana Bar

2013-07-17T23:59:59.000Z

334

Assumptions to the Annual Energy Outlook 1999 - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

oil.gif (4836 bytes) oil.gif (4836 bytes) The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply. 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(99), (Washington, DC, January 1999). 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 gas from domestic fields throughout the United States, acquire natural gas from foreign producers for resale in the United States, or sell U.S. gas to foreign consumers. OGSM encompasses domestic crude oil and natural gas supply by both conventional and nonconventional recovery techniques. Nonconventional recovery includes enhanced oil recovery and unconventional gas recovery from tight gas formations, gas shale, and coalbeds. Foreign gas transactions may occur via either pipeline (Canada or Mexico) or transport ships as liquefied natural gas (LNG).

335

The National Energy Modeling System: An Overview 2000 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

coal market module (CMM) represents the mining, transportation, and pricing of coal, subject to end-use demand. Coal supplies are differentiated by heat and sulfur content. CMM also determines the minimum cost pattern of coal supply to meet exogenously defined U.S. coal export demands as a part of the world coal market. Coal supply is projected on a cost-minimizing basis, constrained by existing contracts. Twelve different coal types are differentiated with respect to thermal grade, sulfur content, and underground or surface mining. The domestic production and distribution of coal is forecast for 13 demand regions and 11 supply regions (Figures 19 and 20). coal market module (CMM) represents the mining, transportation, and pricing of coal, subject to end-use demand. Coal supplies are differentiated by heat and sulfur content. CMM also determines the minimum cost pattern of coal supply to meet exogenously defined U.S. coal export demands as a part of the world coal market. Coal supply is projected on a cost-minimizing basis, constrained by existing contracts. Twelve different coal types are differentiated with respect to thermal grade, sulfur content, and underground or surface mining. The domestic production and distribution of coal is forecast for 13 demand regions and 11 supply regions (Figures 19 and 20). Figure 19. Coal Market Module Demand Regions Figure 20. Coal Market Module Supply Regions

336

EFFECTIVE EFFICIENCY AND PERFORMANCE RATIO AS ENERGY RATING SYSTEM FOR PV MODULES Marko Topic1  

E-Print Network [OSTI]

conditions (STC) with one-sun irradiance (G0 = 1 kW/m2 , AM1.5 spectrum) and cell temperature (Tj) of 25 º irradiance, ambient temperature, and solar- incidence-angle distributions at the installation site daylight ambient temperature. Five PV modules are evaluated by both approaches in Ljubljana for different

Sites, James R.

337

Understanding the Temperature and Humidity Environment Inside a PV Module (Presentation), NREL (National Renewable Energy Laboratory)  

Broader source: Energy.gov [DOE]

This PowerPoint presentation was originally given by Michael Kempe of NREL in February 2013 detailing a project funded by the SunShot Initiative. Understanding the Temperature and Humidity Environment Inside a PV Module aims to show that by choosing humidity conditions that more closely match the use environment, one can minimize the uncertainty associated with moisture induced degradation modes.

338

Modulation of Adenylate Energy Charge During the Swarmer Cycle of Hyphomicrobium neptunium  

Science Journals Connector (OSTI)

...Academic Press, New York. 2. AtkInon, D. E. 1968. The energy charge of the adenylate...1979. Adenylate energy charge: A method...Academic Press, Inc., New York. 23. Lefson, E...nucleotide levels and energy charge in Arthrobacter...

Mary A. Emala; Ronald M. Weiner

1983-03-01T23:59:59.000Z

339

Table ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States  

Gasoline and Diesel Fuel Update (EIA)

ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States Year Primary Energy Electric Power Sector h,j Retail Electricity Total Energy g,h,i Coal Coal Coke Natural Gas a Petroleum Nuclear Fuel Biomass Total g,h,i,j Coking Coal Steam Coal Total Exports Imports Distillate Fuel Oil Jet Fuel b LPG c Motor Gasoline d Residual Fuel Oil Other e Total Wood and Waste f,g Prices in Dollars per Million Btu 1970 0.45 0.36 0.38 1.27 0.93 0.59 1.16 0.73 1.43 2.85 0.42 1.38 1.71 0.18 1.29 1.08 0.32 4.98 1.65 1975 1.65 0.90 1.03 2.37 3.47 1.18 2.60 2.05 2.96 4.65 1.93 2.94 3.35 0.24 1.50 2.19 0.97 8.61 3.33 1980 2.10 1.38 1.46 2.54 3.19 2.86 6.70 6.36 5.64 9.84 3.88 7.04 7.40 0.43 2.26 4.57 1.77 13.95 6.89 1985 2.03 1.67 1.69 2.76 2.99 4.61 7.22 5.91 6.63 9.01 4.30 R 7.62 R 7.64 0.71 2.47 4.93 1.91 19.05

340

Solar energy resource assessment in Chile: Satellite estimation and ground station measurements  

Science Journals Connector (OSTI)

Abstract The progress from the last four years in solar energy resource assessment for Chile is reported, including measurements from a ground station network spanning from two to three years of data, and satellite estimations from the recently developed Chile-SR model including two full years of data. The model introduces different procedures for the meteorological variables and the effective cloud cover computations that allow estimation of the global horizontal and diffuse irradiation on an hourly basis. Direct normal irradiation is computed by applying proper solar geometry corrections to the direct horizontal irradiation. The satellite estimation model was developed as an adaptation from Brazil-SR model, with an improved formulation for altitude-corrected atmospheric parameters, and a novel formulation for calculating effective cloud covers while at the same time detecting and differentiating it from snow covers and salt lakes. The model is validated by comparison with ground station data. The results indicate that there are high radiation levels throughout the country. In particular, northern Chile is endowed with one of the highest solar resources in the world.

Rodrigo A. Escobar; Cristin Corts; Alan Pino; Enio Bueno Pereira; Fernando Ramos Martins; Jos Miguel Cardemil

2014-01-01T23:59:59.000Z

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

Integrated estimation of commercial sector end-use load shapes and energy use intensities  

SciTech Connect (OSTI)

The Southern California Edison Company (SCE) and the California Energy Commission (CEC) have contracted with the Energy Analysis Program of the Applied Science Division at the Lawrence Berkeley Laboratory (LBL) to develop an integrated set of commercial sector load shapes (LS) and energy utilization indices (EUI) for use in forecasting electricity demand. The objectives of this project are to conduct detailed analyses of SCE data on commercial building characteristics, energy use, and whole-building load shapes; and in conjunction with other data, to develop, test, and apply an integrated approach for the estimation of end-use LSs and EUIs. The project represents one of the first attempts to combine simulation-based, prototypical building analyses with direct reconciliation to measured hourly load data. The project examined electricity and gas use for nine building types, including large offices, small offices, large retails, small retails, food stores, sitdown restaurants, fastfood restaurants, refrigerated warehouses, and non-refrigerated warehouses. For each building type, nine end uses were examined, including cooling, heating, ventilation, indoor lighting, outdoor lighting, miscellaneous equipment, water heating, cooking, and refrigeration. For the HVAC end uses (cooling, ventilation, and heating), separate analyses were performed for three climate zones: coastal, inland, and desert.

Akbari, H.; Eto, J.; Turiel, I.; Heinemeier, K.; Lebot, B.; Nordman, B.; Rainer, L.

1989-01-01T23:59:59.000Z

342

Estimation of the energy of the electron-photon component of cosmic rays on the basis of data for Cherenkov light from ultrahigh-energy extensive air showers  

Science Journals Connector (OSTI)

The energy fraction E em/E 0 dissipated to the electron-photon component of extensive air showers (EASs) for E 0=1015?1019 eV is estimated using data on Cherenkov r...

S. P. Knurenko; A. A. Ivanov; I. E. Sleptsov; A. V. Sabourov

2006-08-01T23:59:59.000Z

343

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Commercial Demand Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . . . 99 Petroleum Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Coal Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Renewable Fuels Module . . . . . . . . . . .

344

DOE Order Self Study Modules - 29 CFR 1910.147, The Control Of Hazardous Energy (Lockout/Tagout)  

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

CFR 1910.147 CFR 1910.147 Familiar Level June 2011 1 June 2011 29 CFR 1910.147 THE CONTROL OF HAZARDOUS ENERGY (LOCKOUT/TAGOUT) FAMILIAR LEVEL ___________________________________________________________________________ OBJECTIVES Given the familiar level of this module and the resources, you will be able to answer the following questions: 1. What is the purpose of implementing 29 CFR 1910.147? 2. What is the definition of the following terms?  authorized employee  hot tap  tagout  lockout  lockout device  energy isolating device  tagout device 3. What are the conditions that require a contractor to retrain employees in lockout/tagout procedures? 4. What are the contractor requirements for personnel lockout/tagout training, and what

345

Estimating the energy consumption and power demand of small power equipment in office buildings  

Science Journals Connector (OSTI)

Abstract Small power is a substantial energy end-use in office buildings in its own right, but also significantly contributes to internal heat gains. Technological advancements have allowed for higher efficiency computers, yet current working practices are demanding more out of digital equipment. Designers often rely on benchmarks to inform predictions of small power consumption, power demand and internal gains. These are often out of date and fail to account for the variability in equipment speciation and usage patterns in different offices. This paper details two models for estimating small power consumption in office buildings, alongside typical power demand profiles. The first model relies solely on the random sampling of monitored data, and the second relies on a bottom-up approach to establish likely power demand and operational energy use. Both models were tested through a blind validation demonstrating a good correlation between metered data and monthly predictions of energy consumption. Prediction ranges for power demand profiles were also observed to be representative of metered data with minor exceptions. When compared to current practices, which often rely solely on the use of benchmarks, both proposed methods provide an improved approach to predicting the operational performance of small power equipment in offices.

A.C. Menezes; A. Cripps; R.A. Buswell; J. Wright; D. Bouchlaghem

2014-01-01T23:59:59.000Z

346

DOE special projects: PLACE3S GIS MODULE [Final report  

SciTech Connect (OSTI)

PLACE3S (PLAnning for Community Energy, Economic and Environmental Sustainability) energy option matching module.

NONE

2002-07-31T23:59:59.000Z

347

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.

348

Estimates of Energy Consumption by Building Type and End Use at U.S. Army Installations  

E-Print Network [OSTI]

4. Figure 5-5. 1993 Electricity Consumption Estimates by EndkWh/ft ) 1993 Electricity Consumption Estimates by End Useof Total) 1993 Electricity Consumption Estimates by End Use

Konopacki, S.J.

2010-01-01T23:59:59.000Z

349

Energy Substrate Modulates Mitochondrial Structure and Oxidative Capacity in Cancer Cells  

Science Journals Connector (OSTI)

...and the effect that energy substrate type has...novel ratiometric green fluorescent protein...and the effect that energy substrate type has...lines incorporating green fluorescent protein...and the effect that energy substrate type has...novel ratiometric green fluorescent protein...

Rodrigue Rossignol; Robert Gilkerson; Robert Aggeler; Kunihiro Yamagata; S. James Remington; and Roderick A. Capaldi

2004-02-01T23:59:59.000Z

350

Spectral Energy Distributions and Age Estimates of 78 Star Clusters in M33  

E-Print Network [OSTI]

In this third paper of our series, we present CCD spectrophotometry of 78 star clusters that were detected by Chandar, Bianchi, & Ford in the nearby spiral galaxy M33. CCD images of M33 were obtained as a part of the BATC Color Survey of the sky in 13 intermediate-band filters from 3800 to 10000{\\AA}. By aperture photometry, we obtain the spectral energy distributions of these 78 star clusters. As Chandar, Bianchi, & Ford did, we estimate the ages of our sample clusters by comparing the photometry of each object with theoretical stellar population synthesis models for different values of metallicity. We find that the sample clusters formed continuously in M33 from $\\sim 3\\times10^6$ -- $10^{10}$ years. This conclusion is consistent with Chandar, Bianchi, & Ford. The results also show that, there are two peaks in cluster formation, at $\\sim 8\\times10^6$ and $\\sim 10^9$ years in these clusters.

Ma, J; Chen, J; Wu, H; Jiang, Z; Xue, S; Zhu, J; Ma, Jun; Zhou, Xu; Chen, Jiansheng; Wu, Hong; Jiang, Zhaoji; Xue, Suijian; Zhu, Jin

2002-01-01T23:59:59.000Z

351

Estimates of energy consumption by building type and end use at U.S. Army installations  

SciTech Connect (OSTI)

This report discusses the use of LBNL`s End-use Disaggregation Alogrithm (EDA) to 12 US Army installations nationwide in order to obtain annual estimates of electricity use for all major building types and end uses. The building types include barrack, dining hall, gymnasium, administration, vehicle maintenance, hospital, residential, warehouse, and misc. Up to 8 electric end uses for each type were considered: space cooling, ventilation (air handling units, fans, chilled and hot water pumps), cooking, misc./plugs, refrigeration, exterior and interior lighting, and process loads. Through building simulations, we also obtained estimates of natural gas space heating energy use. Average electricity use for these 12 installations and Fort Hood are: HVAC, misc., and indoor lighting end uses consumed the most electricity (28, 27, and 26% of total[3.8, 3.5, and 3.3 kWh/ft{sup 2}]). Refrigeration, street lighting, exterior lighting, and cooking consumed 7, 7, 3, and 2% of total (0.9, 0.9, 0.4, and 0.3 kWh/ft{sup 2})

Konopacki, S.J.; Akbari, H.

1996-08-01T23:59:59.000Z

352

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

18 Figure 6 Primary Energy Consumption by End-Use in24 Figure 7 Primary Energy Consumption by Fuel in Commercialbased on total primary energy consumption (source energy),

Fridley, David G.

2008-01-01T23:59:59.000Z

353

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

material intensity, energy intensity of materials, buildingtypes manufacturing energy intensity (how much energy itthe manufacturing energy intensity of each type of building

Fridley, David G.

2008-01-01T23:59:59.000Z

354

A quantum algorithm to efficiently sample the work distribution and to estimate the free energy of quantum systems  

E-Print Network [OSTI]

We present a new method to measure work and to efficiently sample its probability distribution with fixed precision. The method can be used to estimate free energies on a quantum computer. It is based on three facts: (i) The probability to detect work $w$ in the state $\\rho$ is $P(w)={\\rm tr}[\\rho \\,W(w)]$, where $W(w)$ are positive operators satisfying $\\int dw \\,W(w)=I$. As $W(w)$ define a POVM (positive operator valued measure), work measurement always reduces to a projective measurement performed at a single time on an enlarged system. (ii) Work can be estimated using a variant of the "phase estimation algorithm" which is such that work $w$ is detected as the outcome of the single time measurement with probability $P(w)$. (iii) The efficient sampling of $P(w)$ can be combined with fluctuation theorems to estimate differences between the free energy of quantum states.

Augusto J. Roncaglia; Federico Cerisola; Juan Pablo Paz

2014-09-12T23:59:59.000Z

355

A Game-Theoretic Approach to Energy-Efficient Modulation in CDMA Networks with Delay QoS Constraints  

E-Print Network [OSTI]

A game-theoretic framework is used to study the effect of constellation size on the energy efficiency of wireless networks for M-QAM modulation. A non-cooperative game is proposed in which each user seeks to choose its transmit power (and possibly transmit symbol rate) as well as the constellation size in order to maximize its own utility while satisfying its delay quality-of-service (QoS) constraint. The utility function used here measures the number of reliable bits transmitted per joule of energy consumed, and is particularly suitable for energy-constrained networks. The best-response strategies and Nash equilibrium solution for the proposed game are derived. It is shown that in order to maximize its utility (in bits per joule), a user must choose the lowest constellation size that can accommodate the user's delay constraint. This strategy is different from one that would maximize spectral efficiency. Using this framework, the tradeoffs among energy efficiency, delay, throughput and constellation size are ...

Meshkati, Farhad; Poor, H Vincent; Schwartz, Stuart C

2007-01-01T23:59:59.000Z

356

Characterization of HVAC operation uncertainty in EnergyPlus AHU modules.  

E-Print Network [OSTI]

??This study addresses 5 uncertainties that exist in the operation of HVAC systems, which will presumably affect the actual energy consumption of the HVAC system (more)

Sui, Di

2014-01-01T23:59:59.000Z

357

Energy efficient IM-DD OFDM-PON using dynamic SNR management and adaptive modulation  

Science Journals Connector (OSTI)

This paper describes the demonstration of an energy efficient orthogonal frequency division multiplexing passive optical network using the dynamic signal to noise ratio (SNR)...

Kimura, Hideaki; Asaka, Kota; Nakamura, Hirotaka; Kimura, Shunji; Yoshimoto, Naoto

2014-01-01T23:59:59.000Z

358

Electricity Market Module  

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

Market Module Market Module This page inTenTionally lefT blank 101 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 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, electricity load and demand, 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 2013, DOE/EIA-M068(2013). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

359

Corn phosphoglycolate phosphatase: Modulation of activity by pyridine nucleotides and adenylate energy charge  

Science Journals Connector (OSTI)

The activity of corn phosphoglycolate phosphatase (EC 3.1.3.18...in vitro, both by NADP(H) and adenylate energy charge. The Vmax of the enzyme is ... the light. At both pH, the adenylate energy charge alone has a...

P. Baldy; J. P. Jacquot; D. Lavergne; M. L. Champigny

1989-11-01T23:59:59.000Z

360

On Energy Harvesting Module for Scalable Cognitive Autonomous Nondestructive Sensing Network (SCANSn  

E-Print Network [OSTI]

energy harvesting from both solar and thermal sources to recharge the lithium-ion battery of the system, solar, thermal electric generator, battery charging, SHM 1. INTRODUCTION Structural Health Monitoring to the battery charger. Since the output voltages and currents of the solar and thermal energy harvesters vary

Ha, Dong S.

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

Order Module--DOE O 414.1D, QUALITY ASSURANCE | Department of Energy  

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

14.1D, QUALITY ASSURANCE 14.1D, QUALITY ASSURANCE Order Module--DOE O 414.1D, QUALITY ASSURANCE "To ensure that DOE, including NNSA, products and services meet or exceed customers' requirements and expectations. To achieve quality for all work based upon the following principles: All work, as defined in this Order, is conducted through an integrated and effective management system. Management support for planning, organization, resources, direction, and control is essential to quality assurance (QA). Performance and quality improvement require thorough, rigorous assessments and effective corrective actions. All personnel are responsible for achieving and maintaining quality. Risks and adverse mission impacts associated with work processes are minimized while maximizing reliability and performance of work products.

362

Order Module--DOE Order 422.1, CONDUCT OF OPERATIONS | Department of Energy  

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

422.1, CONDUCT OF OPERATIONS 422.1, CONDUCT OF OPERATIONS Order Module--DOE Order 422.1, CONDUCT OF OPERATIONS The general approach to implementing DOE O 422.1 is for contractors to develop, for DOE line management approval, documentation demonstrating implementation of the requirements in the contractor requirements document (CRD). DOE line management means the Federal officials such as Secretarial Officers and heads of field elements responsible for DOE facilities and operations. It is necessary to provide a conduct of operations matrix, which is a list of CRD requirements, citing the specific documentation that implements each item, or providing justification for each item that is not implemented. DOE line management must determine which facilities, other than hazard category 1, 2, and 3 nuclear facilities, require implementation

363

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

364

Review of Evaluation, Measurement and Verification Approaches Used to Estimate the Load Impacts and Effectiveness of Energy Efficiency Programs  

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

LBNL-3277E LBNL-3277E ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY Review of Evaluation, Measurement and Verification Approaches Used to Estimate the Load Impacts and Effectiveness of Energy Efficiency Programs Mike Messenger*, Ranjit Bharvirkar*, Bill Golemboski*, Charles A. Goldman**, Steven R. Schiller*** *Itron, Inc., **Lawrence Berkeley National Laboratory, ***Schiller Consulting, Inc. Environmental Energy Technologies Division April 2010 The work described in this report was funded by the Office of Electricity Delivery and Energy Reliability (OE); Permitting, Siting, and Analysis Division of the U.S. Department of Energy under Contract No. DE-AC02- 05CH11231. Disclaimer This document was prepared as an account of work sponsored by the United

365

A multilevel energy buffer and voltage modulator for grid-interfaced micro-inverters  

E-Print Network [OSTI]

Micro-inverters operating into the single-phase grid from solar photovoltaic (PV) panels or other low-voltage sources must buffer the twice-line-frequency variations between the energy sourced by the PV panel and that ...

Chen, Minjie

366

Climate Science for a Sustainable Energy Future Atmospheric Radiation Measurement Best Estimate (CSSEFARMBE)  

SciTech Connect (OSTI)

The Climate Science for a Sustainable Energy Future (CSSEF) project is working to improve the representation of the hydrological cycle in global climate models, critical information necessary for decision-makers to respond appropriately to predictions of future climate. In order to accomplish this objective, CSSEF is building testbeds to implement uncertainty quantification (UQ) techniques to objectively calibrate and diagnose climate model parameterizations and predictions with respect to local, process-scale observations. In order to quantify the agreement between models and observations accurately, uncertainty estimates on these observations are needed. The DOE Atmospheric Radiation Measurement (ARM) program takes atmospheric and climate related measurements at three permanent locations worldwide. The ARM VAP called the ARM Best Estimate (ARMBE) [Xie et al., 2010] collects a subset of ARM observations, performs quality control checks, averages them to one hour temporal resolution, and puts them in a standard format for ease of use by climate modelers. ARMBE has been widely used by the climate modeling community as a summary product of many of the ARM observations. However, the ARMBE product does not include uncertainty estimates on the data values. Thus, to meet the objectives of the CSSEF project and enable better use of this data with UQ techniques, we created the CSSEFARMBE data set. Only a subset of the variables contained in ARMBE is included in CSSEFARMBE. Currently only surface meteorological observations are included, though this may be expanded to include other variables in the future. The CSSEFARMBE VAP is produced for all extended facilities at the ARM Southern Great Plains (SGP) site that contain surface meteorological equipment. This extension of the ARMBE data set to multiple facilities at SGP allows for better comparison between model grid boxes and the ARM point observations. In the future, CSSEFARMBE may also be created for other ARM sites. As each site has slightly different instrumentation, this will require additional development to understand the uncertainty characterization associated with instrumentation at those sites. The uncertainty assignment process is implemented into the ARM programs new Integrated Software Development Environment (ISDE) so that many of the key steps can be used in the future to screen data based on ARM Data Quality Reports (DQRs), propagate uncertainties when transforming data from one time scale into another, and convert names and units into NetCDF Climate and Forecast (CF) standards. These processes are described in more detail in the following sections.

Riihimaki, Laura D.; Gaustad, Krista L.; McFarlane, Sally A.

2012-09-28T23:59:59.000Z

367

Estimating Energy Efficiency Technology Adoption Curve Elasticity with Respect to Government and Utility Deployment Program Indicators  

E-Print Network [OSTI]

Energy Efficiency Technology Adoption Curve Elasticity withEnvironmental Energy Technologies Division Ernest OrlandoEnergy, Building Technologies Office under Contract no. DE-

Van Buskirk, Robert

2014-01-01T23:59:59.000Z

368

Estimating Energy Efficiency Technology Adoption Curve Elasticity with Respect to Government and Utility Deployment Program Indicators  

E-Print Network [OSTI]

circles represent Energy Star market share data for statesdiamonds represent the Energy Star market share data foris assembled for Energy Star product markets covering all 50

Van Buskirk, Robert

2014-01-01T23:59:59.000Z

369

Methodological Issues in the Estimation of the Travel, Energy, and Air Quality Impacts of Telecommuting  

E-Print Network [OSTI]

have analyzed the air quality and energy impacts, but mostits travel, air quality, and energy impacts, and illustrateTHE TRAVEL, ENERGY, AND AIR QUALITY IMPACTS OF TELECOMMUTING

Mokhtarian, Patricia; Handy, Susan; Salomon, Ilan

1995-01-01T23:59:59.000Z

370

Energy savings estimates and cost benefit calculations for high performance relocatable classrooms  

E-Print Network [OSTI]

8: Annual HVAC Source Energy, Cost, and Savings ProjectionsStatewide HVAC Source Energy, Cost, and Savings Projections23 Table 8: Annual HVAC Source Energy, Cost, and Savings

Rainer, Leo I.; Hoeschele, Marc A.; Apte, Michael G.; Shendell, Derek G.; Fisk, William J.

2003-01-01T23:59:59.000Z

371

Nonlocal Modulation of Entangled Photons  

E-Print Network [OSTI]

We consider ramifications of the use of high speed light modulators to questions of correlation and measurement of time-energy entangled photons. Using phase modulators, we find that temporal modulation of one photon of an entangled pair, as measured by correlation in the frequency domain, may be negated or enhanced by modulation of the second photon. Using amplitude modulators we describe a Fourier technique for measurement of biphoton wave functions with slow detectors.

S. E. Harris

2008-08-06T23:59:59.000Z

372

Age Estimations of M31 Globular Clusters from Their Spectral Energy Distributions  

E-Print Network [OSTI]

This paper presents accurate spectral energy distributions (SEDs) of 16 M31 globular clusters (GCs) confirmed by spectroscopy and/or high spatial-resolution imaging, as well as 30 M31 globular cluster candidates detected by Mochejska et al. Most of these candidates have m_V > 18, deeper than previous searches, and these candidates have not yet been confirmed to be globular clusters. The SEDs of these clusters and candidates are obtained as part of the BATC Multicolor Survey of the Sky, in which the spectrophotometrically-calibrated CCD images of M31 in 13 intermediate-band filters from 4000 to 10000 A were observed. These filters are specifically designed to exclude most of the bright and variable night-sky emission lines including the OH forest. In comparison to the SEDs of true GCs, we find that some of the candidate objects are not GCs in M31. SED fits show that theoretical simple stellar population (SSP) models can fit the true GCs very well. We estimate the ages of these GCs by comparing with SSP models....

Ma, J; Chen, J; Fan, Z; Jiang, Z; Yang, Y; Zhou, X; Burstein, David; Chen, Jiansheng; Fan, Zhou; Jiang, Zhaoji; Ma, Jun; Yang, Yanbin; Zhou, Xu

2005-01-01T23:59:59.000Z

373

Spectral Energy Distributions and Age Estimates of 172 Globular Clusters in M31  

E-Print Network [OSTI]

In this paper we present CCD multicolor photometry for 172 globular clusters (GCs), taken from the Bologna catalog (Battistini et al. 1987), in the nearby spiral galaxy M31. The observations were carried out by using the National Astronomical Observatories 60/90 cm Schmidt Telescope in 13 intermediate-band filters, which covered a range of wavelength from 3800 to 10000A. This provides a multicolor map of M31 in pixels of 1.7"*1.7". By aperture photometry, we obtain the spectral energy distributions (SEDs) for these GCs. Using the relationship between the BATC intermediate-band system used for the observations and the UBVRI broad-band system, the magnitudes in the B and V bands are derived. The computed V and B-V are in agreement with the values given by Battistini et al. (1987) and Barmby et al. (2000). Finally, by comparing the photometry of each GC with theoretical stellar population synthesis models, we estimate ages of the sample GCs for different metallicities. The results show that nearly all our sample...

Jiang, L; Zhou, X; Chen, J; Wu, H; Jiang, Z; Jiang, Linhua; Ma, Jun; Zhou, Xu; Chen, Jiansheng; Wu, Hong; Jiang, Zhaoji

2003-01-01T23:59:59.000Z

374

Geopressured Geothermal Resource and Recoverable Energy Estimate for the Wilcox and Frio Formations, Texas (Presentation)  

SciTech Connect (OSTI)

An estimate of the total and recoverable geopressured geothermal resource of the fairways in the Wilcox and Frio formations is made using the current data available. The flow rate of water and methane for wells located in the geopressured geothermal fairways is simulated over a 20-year period utilizing the TOUGH2 Reservoir Simulator and research data. The model incorporates relative permeability, capillary pressure, rock compressibility, and leakage from the bounding shale layers. The simulations show that permeability, porosity, pressure, sandstone thickness, well spacing, and gas saturation in the sandstone have a significant impact on the percent of energy recovered. The results also predict lower average well production flow rates and a significantly higher production of natural gas relative to water than in previous studies done from 1975 to 1980. Previous studies underestimate the amount of methane produced with hot brine. Based on the work completed in this study, multiphase flow processes and reservoir boundary conditions greatly influence the total quantity of the fluid produced as well as the ratio of gas and water in the produced fluid.

Esposito, A.; Augustine, C.

2011-10-01T23:59:59.000Z

375

OpenPEOPLE D2.8 Ergonomic Page 1/37 Open Power and Energy Optimization Platform and Estimator  

E-Print Network [OSTI]

OpenPEOPLE D2.8­ Ergonomic Page 1/37 OpenPEOPLE Open Power and Energy Optimization Platform and Estimator Internal Deliverable 2.8 Ergonomics Document Manager Contributors Checked by Name Jonathan PONROY ergonomic for the OpenPEOPLE software platform. inria-00624000,version1-16Sep2011 #12;OpenPEOPLE D2

Paris-Sud XI, Université de

376

Energy Consumption Estimation for Room Air-conditioners Using Room Temperature Simulation with One-Minute Intervals  

E-Print Network [OSTI]

time can be known so that its energy consumption can be estimated accurately. In order to verify the simulation accuracy, an actual room equipped with a gas-engine heat pump (GHP) air-conditioning system is studied by both simulation and measurement...

Wang, F.; Yoshida, H.; Matsumoto, K.

2006-01-01T23:59:59.000Z

377

Adaptive algorithms for QCSE optical modulators Excitonic optical absorption at near band gap photon energies in III-V compound semiconductor  

E-Print Network [OSTI]

. Typically, such designs make use of simple rectangular potential wells in the AlGaAs/GaAs or InP/InGaAsP1 Adaptive algorithms for QCSE optical modulators Excitonic optical absorption at near band gap of the quantum well, the excitonic optical absorption strength and energy can be manipulated. This quantum

Levi, Anthony F. J.

378

Multiple Factors Affecting Cellular Redox Status and Energy Metabolism Modulate Hypoxia-Inducible Factor Prolyl Hydroxylase Activity In Vivo and In Vitro  

Science Journals Connector (OSTI)

...use of these cells allowed us to monitor GHO hydroxylation status without using proteasome inhibitors...found that MitoQ could not help us to distinguish between these...factors affecting cellular redox status and energy metabolism modulate hypoxia-inducible...

Yi Pan; Kyle D. Mansfield; Cara C. Bertozzi; Viktoriya Rudenko; Denise A. Chan; Amato J. Giaccia; M. Celeste Simon

2006-11-13T23:59:59.000Z

379

Energy Levels, Phase, and Amplitude Modulation of the Baroclinic Tide off Hawaii  

Science Journals Connector (OSTI)

Inverted echo sounder data from Station Aloha north of Oahu, Hawaii, are used to determine the absolute energy levels and time-varying nature of the first-mode baroclinic tide north of Hawaii. The semidiurnal tide amplitude and phase are ...

Stephen M. Chiswell

2002-09-01T23:59:59.000Z

380

A 900MHz RF Energy Harvesting Module TARIS Thierry, VIGNERAS Valrie  

E-Print Network [OSTI]

harvesting. Different types of source are considered among them are: wind, solar, vibration, temperature and everywhere". It is a decisive asset to address power saving and energy management challenges in WSN with the state of art. II. BUILDING BLOCK DESIGN AND CHARACTERISTICS Figure 1. Building blocks of the RF

Paris-Sud XI, Université de

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

Renewable Fuels Module This  

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

Fuels Module Fuels Module This page inTenTionally lefT blank 175 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 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 wind [1]. 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

382

Estimating the Opportunity Cost of REDD+: A Training Manual | Open Energy  

Open Energy Info (EERE)

Estimating the Opportunity Cost of REDD+: A Training Manual Estimating the Opportunity Cost of REDD+: A Training Manual Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Estimating the Opportunity Cost of REDD+: A Training Manual Agency/Company /Organization: World Bank Institute Sector: Land, Climate Focus Area: Forestry Resource Type: Guide/manual Website: wbi.worldbank.org/wbi/Data/wbi/wbicms/files/drupal-acquia/wbi/OppCosts Estimating the Opportunity Cost of REDD+: A Training Manual Screenshot References: Estimating the Opportunity Cost of REDD+: A Training Manual[1] "The manual shares hands-on experiences from field programs and presents the essential practical and theoretical steps, methods and tools to estimate the opportunity costs of REDD+ at the national level. The manual addresses the calculation of costs and benefits of the various land use

383

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.

384

2006 Status Report Savings Estimates for the ENERGY STAR(R) Voluntary Labeling Program  

E-Print Network [OSTI]

10,000 hours) than incandescent lamps (usually estimated atcurrent plus several future incandescent lamp purchases. Themany times longer than incandescent lamps, maintenance costs

Webber, Carrie A.; Brown, Richard E.; Sanchez, Marla; Homan, Gregory K.

2006-01-01T23:59:59.000Z

385

2007 Status Report: Savings Estimates for the ENERGY STAR(R) VoluntaryLabeling Program  

E-Print Network [OSTI]

10,000 hours) than incandescent lamps (usually estimated atcurrent plus several future incandescent lamp purchases. Themany times longer than incandescent lamps, maintenance costs

Sanchez, Marla; Webber, Carrie A.; Brown, Richard E.; Homan, Gregory K.

2007-01-01T23:59:59.000Z

386

2005 Status Report Savings Estimates for the ENERGY STAR(R) Voluntary Labeling Program  

E-Print Network [OSTI]

10,000 hours) than incandescent lamps (usually estimated atcurrent plus several future incandescent lamp purchases. Themany times longer than incandescent lamps, maintenance costs

Webber, Carrie A.; Brown, Richard E.; Sanchez, Marla

2006-01-01T23:59:59.000Z

387

Assumptions to the Annual Energy Outlook 2008  

Gasoline and Diesel Fuel Update (EIA)

8) 8) Release date: June 2008 Next release date: March 2009 Assumptions to the Annual Energy Outlook 2008 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Commercial Demand Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Natural Gas Transmission and Distribution Module. . . . . . . . . . . . . . . . . . . . . . 113 Petroleum Market Module

388

An Estimate of Energy Use in Laboratories, Cleanrooms, and Data Centers in New York  

E-Print Network [OSTI]

Andrews Program Manager New York State Energy Research andwork was supported by the New York State Energy Research andork. Energy Use by the High-tech Sector in New York Trillion

Mathew, Paul

2010-01-01T23:59:59.000Z

389

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

were used to calculate the energy mix in manufacturing,of Chinas total energy consumption mix. However, accuratelyof Chinas total energy consumption mix. However, accurately

Fridley, David G.

2008-01-01T23:59:59.000Z

390

Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation  

E-Print Network [OSTI]

associated change in energy demand of homes. The IVE modelmodels that calculate energy demand by solving a series ofand (b) the change in energy demand resulting in a change in

Logue, Jennifer M.

2014-01-01T23:59:59.000Z

391

A method to estimate the size and remaining market potential of the U.S. ESCO (energy service company) industry  

Science Journals Connector (OSTI)

Abstract This study presents a method to estimate the market investment potential for ESPC (energy-saving performance contracts) and annual blended energy savings remaining in buildings typically addressed by U.S. \\{ESCOs\\} (energy service companies). We define \\{ESCOs\\} as companies for whom performance-based contracting is a core business activity. The market potential analysis incorporates market penetration estimates provided by industry experts in late 2012, data on U.S. building stock typically addressed by ESCOs, and typical project investment costs from a database of 4000+projects. ESCO industry revenue growth significantly outpaced U.S. GDP (gross domestic product) growth during 20092011. We estimate that the remaining investment potential in facilities typically addressed by the ESCO industry ranges from ?$71 to $133 billion. Our analysis includes ESCO industry size and growth projections drawing on information from interviews with ESCO executives conducted in late 2012. The U.S. ESCO industry could grow in size from $6 billion in 2013 to ?$7.5 billion by 2014, but this growth is contingent on enabling policies. The U.S. ESCO industry is similar in size to the ESCO industries in Germany, France, and China. Our estimation approach could be adapted for other countries with the caveat that ESCO industry definitions and revenue reporting practices vary across countries.

Elizabeth Stuart; Peter H. Larsen; Charles A. Goldman; Donald Gilligan

2014-01-01T23:59:59.000Z

392

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

of Central Government Buildings. Available at: http://Energy Commission, PIER Building End-Use Energy Efficiencythe total lifecycle of a building such as petroleum and

Fridley, David G.

2008-01-01T23:59:59.000Z

393

PDSF Modules  

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

Modules Modules Modules Modules Approach to Managing The Environment Modules is a system which you can use to specify what software you want to use. If you want to use a particular software package loading its module will take care of the details of modifying your environment as necessary. The advantage of the modules approach is that the you are not required to explicitly specify paths for different executable versions and try to keep their related man paths and environment variables coordinated. Instead you simply "load" and "unload" specific modules to control your environment. Getting Started with Modules If you're using the standard startup files on PDSF then you're already setup for using modules. If the "module" command is not available, please

394

Macroeconomic Activity Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 19 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook2011 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module.

395

Estimates of Energy Consumption by Building Type and End Use at U.S. Army Installations  

E-Print Network [OSTI]

Irwin Fort Sill Yuma Pg Fort Bliss Fort Sam Houston FortEstimated H V A C EUIs at Fort Bliss Table 5-12. Annual DOE-Estimated Electricity Use at Fort Bliss [GWh/yr] Table 5-24.

Konopacki, S.J.

2010-01-01T23:59:59.000Z

396

Property:Number of Plants Included in Planned Estimate | Open Energy  

Open Energy Info (EERE)

Plants Included in Planned Estimate Plants Included in Planned Estimate Jump to: navigation, search Property Name Number of Plants Included in Planned Estimate Property Type String Description Number of plants included in the estimate of planned capacity per GEA Pages using the property "Number of Plants Included in Planned Estimate" Showing 21 pages using this property. A Alaska Geothermal Region + 3 + C Cascades Geothermal Region + 1 + Central Nevada Seismic Zone Geothermal Region + 4 + G Gulf of California Rift Zone Geothermal Region + 7 + H Hawaii Geothermal Region + 1 + Holocene Magmatic Geothermal Region + 4 + I Idaho Batholith Geothermal Region + 1 + N Northern Basin and Range Geothermal Region + 9 + Northern Rockies Geothermal Region + 0 + Northwest Basin and Range Geothermal Region + 6 +

397

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

398

Modulation of DNA loop lifetimes by the free energy of loop formation  

E-Print Network [OSTI]

Storage and retrieval of the genetic information in cells is a dynamic process that requires the DNA to undergo dramatic structural rearrangements. DNA looping is a prominent example of such a structural rearrangement that is essential for transcriptional regulation in both prokaryotes and eukaryotes, and the speed of such regulations affects the fitness of individuals. Here, we examine the in vitro looping dynamics of the classic Lac repressor gene-regulatory motif. We show that both loop association and loop dissociation at the DNA-repressor junctions depend on the elastic deformation of the DNA and protein, and that both looping and unlooping rates approximately scale with the looping J factor, which reflects the system's deformation free energy. We explain this observation by transition state theory and model the DNA-protein complex as an effective worm-like chain with twist. We introduce a finite protein-DNA binding interaction length, in competition with the characteristic DNA deformation length scale, ...

Chen, Yi-Ju; Mulligan, Peter; Spakowitz, Andrew J; Phillips, Rob

2015-01-01T23:59:59.000Z

399

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

400

2006 Status Report Savings Estimates for the ENERGY STAR(R) Voluntary Labeling Program  

E-Print Network [OSTI]

Technology. August. AHAM. 2002. Excel Spreadsheet: "development process through AHAM. Energy Star wattages are

Webber, Carrie A.; Brown, Richard E.; Sanchez, Marla; Homan, Gregory K.

2006-01-01T23:59:59.000Z

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


401

2007 Status Report: Savings Estimates for the ENERGY STAR(R) VoluntaryLabeling Program  

E-Print Network [OSTI]

Technology. August. AHAM. 2002. Excel Spreadsheet: "development process through AHAM. Energy Star wattages are

Sanchez, Marla; Webber, Carrie A.; Brown, Richard E.; Homan, Gregory K.

2007-01-01T23:59:59.000Z

402

Solar energy conversion via hot electron internal photoemission in metallic nanostructures: Efficiency estimates  

E-Print Network [OSTI]

Solar energy conversion via hot electron internal photoemission in metallic nanostructures://scitation.aip.org/termsconditions. Downloaded to ] IP: 131.215.44.236 On: Tue, 01 Apr 2014 22:46:10 #12;Solar energy conversion via hot electron for the construction of solar energy-conversion devices. Herein, we evaluate theoretically the energy-conversion

Atwater, Harry

403

Estimating electricity storage power rating and discharge duration for utility transmission and distribution deferral :a study for the DOE energy storage program.  

SciTech Connect (OSTI)

This report describes a methodology for estimating the power and energy capacities for electricity energy storage systems that can be used to defer costly upgrades to fully overloaded, or nearly overloaded, transmission and distribution (T&D) nodes. This ''sizing'' methodology may be used to estimate the amount of storage needed so that T&D upgrades may be deferred for one year. The same methodology can also be used to estimate the characteristics of storage needed for subsequent years of deferral.

Eyer, James M. (Distributed Utility Associates, Livermore, CA); Butler, Paul Charles; Iannucci, Joseph J., Jr. (,.Distributed Utility Associates, Livermore, CA)

2005-11-01T23:59:59.000Z

404

Technique for the Estimation of Surface Temperatures from Embedded Temperature Sensing for Rapid, High Energy Surface Deposition  

SciTech Connect (OSTI)

Temperature histories on the surface of a body that has been subjected to a rapid, high-energy surface deposition process can be di#14;fficult to determine, especially if it is impossible to directly observe the surface or attach a temperature sensor to it. In this report, we explore two methods for estimating the temperature history of the surface through the use of a sensor embedded within the body very near to the surface. First, the maximum sensor temperature is directly correlated with the peak surface temperature. However, it is observed that the sensor data is both delayed in time and greatly attenuated in magnitude, making this approach unfeasible. Secondly, we propose an algorithm that involves fitting the solution to a one-dimensional instantaneous energy solution problem to both the sensor data and to the results of a one-dimensional CVFEM code. This algorithm is shown to be able to estimate the surface temperature {+-}~20#14;{degrees}C.

Watkins, Tyson R.; Schunk, Peter Randall; Roberts, Scott A.

2014-07-01T23:59:59.000Z

405

Cost of capital estimation for energy efficiency projects through a cash flow beta approach  

Science Journals Connector (OSTI)

This paper presents a methodological framework for project beta estimation according to the Capital Asset Pricing Model (CAPM) when relevant ... monthly residential retail price data for electricity, natural gas,...

Gyrgy Andor; Marcell Dlk

2014-09-01T23:59:59.000Z

406

Indirect estimation of energy disposition by non-thermal electrons in solar flares  

Science Journals Connector (OSTI)

The broad-band EUV and microwave fluxes correlate strongly with hard X-ray fluxes in the impulsive phase of a solar flare. This note presents numerical aids for the estimation of the non-thermal electron fluxe...

H. S. Hudson; R. C. Canfield; S. R. Kane

1978-11-01T23:59:59.000Z

407

Measured and Parameterized Energy Fluxes Estimated for Atlantic Transects of R/V Polarstern  

Science Journals Connector (OSTI)

Sensible and latent heat fluxes were estimated from turbulence measurements gathered during several Atlantic Ocean transects of the research vessel (R/V) Polarstern. The inertial dissipation method was used to analyze the data. Resulting bulk ...

Karl Bumke; Michael Schlundt; John Kalisch; Andreas Macke; Henry Kleta

2014-02-01T23:59:59.000Z

408

T ti E St S tTetiaroa Energy Storage System Estimated ZBB Zinc Bromide Battery Performance and Costs  

E-Print Network [OSTI]

://rael.berkeley.edu 6Modeled 455kW gen set output power #12;Alte nati e Diesel Si ingAlternative Diesel Sizing://rael.berkeley.edu 1 #12;Island Load and DieselIsland Load and Diesel Generation Assumptions #12;Estimated Elect ical: Average daily energy use: 5,698 kWh d d 23 k Average power demand: 237 kW Peak power demand: 427 kW Load

Kammen, Daniel M.

409

Updated estimation of energy efficiencies of U.S. petroleum refineries.  

SciTech Connect (OSTI)

Evaluation of life-cycle (or well-to-wheels, WTW) energy and emission impacts of vehicle/fuel systems requires energy use (or energy efficiencies) of energy processing or conversion activities. In most such studies, petroleum fuels are included. Thus, determination of energy efficiencies of petroleum refineries becomes a necessary step for life-cycle analyses of vehicle/fuel systems. Petroleum refinery energy efficiencies can then be used to determine the total amount of process energy use for refinery operation. Furthermore, since refineries produce multiple products, allocation of energy use and emissions associated with petroleum refineries to various petroleum products is needed for WTW analysis of individual fuels such as gasoline and diesel. In particular, GREET, the life-cycle model developed at Argonne National Laboratory with DOE sponsorship, compares energy use and emissions of various transportation fuels including gasoline and diesel. Energy use in petroleum refineries is key components of well-to-pump (WTP) energy use and emissions of gasoline and diesel. In GREET, petroleum refinery overall energy efficiencies are used to determine petroleum product specific energy efficiencies. Argonne has developed petroleum refining efficiencies from LP simulations of petroleum refineries and EIA survey data of petroleum refineries up to 2006 (see Wang, 2008). This memo documents Argonne's most recent update of petroleum refining efficiencies.

Palou-Rivera, I.; Wang, M. Q. (Energy Systems)

2010-12-08T23:59:59.000Z

410

The Steam System Assessment Tool (SSAT): Estimating Steam System Energy, Cost, and Emission Savings  

E-Print Network [OSTI]

The U. S. Department of Energy's (DOE) Industrial Technology Program BestPractices Steam effort is developing a number of software tools to assist industrial energy users to improve the efficiency of their steam system. A major new Best...

Wright, A.; Bealing, C.; Eastwood, A.; Tainsh, R.; Hahn, G.; Harrell, G.

411

Urban energy consumption and related carbon emission estimation: a study at the sector scale  

Science Journals Connector (OSTI)

With rapid economic development and energy consumption growth, China has become the largest energy consumer in the world. Impelled by extensive international concern, there ... an urgent need to analyze the chara...

Weiwei Lu; Chen Chen; Meirong Su; Bin Chen; Yanpeng Cai

2013-12-01T23:59:59.000Z

412

On UHECR energy estimation algorithms based on the measurement of electromagnetic component parameters in EAS  

E-Print Network [OSTI]

Model calculations are performed of extensive air shower (EAS) component energies using a variety of hadronic interaction parameters. A conversion factor from electromagnetic component energy to the energy of ultra-high energy cosmic rays (UHECRs) and its model and primary mass dependence is studied. It is shown that model dependence of the factor minimizes under the necessary condition of the same maximum position and muon content of simulated showers.

A. A. Ivanov

2007-04-26T23:59:59.000Z

413

An Introduction to the Lighting Module of EcoAdvisor - An Online  

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

An Introduction to the Lighting Module of EcoAdvisor - An Online An Introduction to the Lighting Module of EcoAdvisor - An Online Interactive Training Software in Energy Efficiency Speaker(s): Joe Deringer Date: April 19, 2001 - 12:00pm Location: Bldg. 90 Seminar Host/Point of Contact: Kristina LaCommare The Lighting Energy Advisor (LEA) is an online module within EcoAdvisor. It takes a very different approach from most training courses and guidance materials about energy efficient lighting. LEA focuses on: - The balance of lighting quality, efficiency, and cost-effectiveness. - Design issues. - Estimates of lighting quality. - Visual, cost, and energy impacts of lighting design decisions. - Occupant productivity. This presentation will discuss the Phase 1 LEA Module much of which is now available online. We will also summarize more recent work, including work

414

Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

This page inTenTionally lefT blank 91 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 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, electricity load and demand, 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 2012, DOE/EIA-M068(2012). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

415

Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 95 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 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, electricity load and demand, 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 2011, DOE/EIA-M068(2011). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

416

Review of Evaluation, Measurement and Verification Approaches Used to Estimate the Load Impacts and Effectiveness of Energy Efficiency Programs  

SciTech Connect (OSTI)

Public and private funding for end-use energy efficiency actions is expected to increase significantly in the United States over the next decade. For example, Barbose et al (2009) estimate that spending on ratepayer-funded energy efficiency programs in the U.S. could increase from $3.1 billion in 2008 to $7.5 and 12.4 billion by 2020 under their medium and high scenarios. This increase in spending could yield annual electric energy savings ranging from 0.58% - 0.93% of total U.S. retail sales in 2020, up from 0.34% of retail sales in 2008. Interest in and support for energy efficiency has broadened among national and state policymakers. Prominent examples include {approx}$18 billion in new funding for energy efficiency programs (e.g., State Energy Program, Weatherization, and Energy Efficiency and Conservation Block Grants) in the 2009 American Recovery and Reinvestment Act (ARRA). Increased funding for energy efficiency should result in more benefits as well as more scrutiny of these results. As energy efficiency becomes a more prominent component of the U.S. national energy strategy and policies, assessing the effectiveness and energy saving impacts of energy efficiency programs is likely to become increasingly important for policymakers and private and public funders of efficiency actions. Thus, it is critical that evaluation, measurement, and verification (EM&V) is carried out effectively and efficiently, which implies that: (1) Effective program evaluation, measurement, and verification (EM&V) methodologies and tools are available to key stakeholders (e.g., regulatory agencies, program administrators, consumers, and evaluation consultants); and (2) Capacity (people and infrastructure resources) is available to conduct EM&V activities and report results in ways that support program improvement and provide data that reliably compares achieved results against goals and similar programs in other jurisdictions (benchmarking). The National Action Plan for Energy Efficiency (2007) presented commonly used definitions for EM&V in the context of energy efficiency programs: (1) Evaluation (E) - The performance of studies and activities aimed at determining the effects and effectiveness of EE programs; (2) Measurement and Verification (M&V) - Data collection, monitoring, and analysis associated with the calculation of gross energy and demand savings from individual measures, sites or projects. M&V can be a subset of program evaluation; and (3) Evaluation, Measurement, and Verification (EM&V) - This term is frequently seen in evaluation literature. EM&V is a catchall acronym for determining both the effectiveness of program designs and estimates of load impacts at the portfolio, program and project level. This report is a scoping study that assesses current practices and methods in the evaluation, measurement and verification (EM&V) of ratepayer-funded energy efficiency programs, with a focus on methods and practices currently used for determining whether projected (ex-ante) energy and demand savings have been achieved (ex-post). M&V practices for privately-funded energy efficiency projects (e.g., ESCO projects) or programs where the primary focus is greenhouse gas reductions were not part of the scope of this study. We identify and discuss key purposes and uses of current evaluations of end-use energy efficiency programs, methods used to evaluate these programs, processes used to determine those methods; and key issues that need to be addressed now and in the future, based on discussions with regulatory agencies, policymakers, program administrators, and evaluation practitioners in 14 states and national experts in the evaluation field. We also explore how EM&V may evolve in a future in which efficiency funding increases significantly, innovative mechanisms for rewarding program performance are adopted, the role of efficiency in greenhouse gas mitigation is more closely linked, and programs are increasingly funded from multiple sources often with multiple program administrators and in

Messenger, Mike; Bharvirkar, Ranjit; Golemboski, Bill; Goldman, Charles A.; Schiller, Steven R.

2010-04-14T23:59:59.000Z

417

The Role of Nuclear Modes in Coupled Electronic Systems: Quantum Coating, Vibronic Modulation, or Quantum- Dissipative Energy Flow?  

Science Journals Connector (OSTI)

The modulation of electronic dynamics by nuclear modes in a phthalocyanine dimer has been investigated by 2D-ES. Quantum-dissipative relaxation between the two excited states on 20 fs...

Christensson, Niklas; Bixner, Oliver; Milota, Franz; Hauer, Juergen; Kauffmann, Harald F

418

Performances of a thermal-storage module in a solar-energy power production perspective: A numerical assessment  

Science Journals Connector (OSTI)

A theoretical model has been developed to describe the cyclic behaviour of a latent-heat thermal-storage module. Attention has been focused on power production applications, where stability of the heat supply ...

C. Bellecci; M. Conti

419

"Order Module--DOE-STD-3009-94, PREPARATION GUIDE FOR U.S. DEPARTMENT OF ENERGY NONREACTOR NUCLEAR FACILITY  

Broader source: Energy.gov [DOE]

"The familiar level of this module is divided into three sections. The first section is an introduction to DOE-STD-3009-94. In the second section, we will introduce the 17 chapters of a documented...

420

Microsoft Word - Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation_Final2.docx  

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

XXXXX | Logue et al., Evaluation of an Incremental Ventilation Energy Model for Estimating XXXXX | Logue et al., Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation 1 Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation Jennifer M. Logue, William J. N. Turner, Iain S. Walker, and Brett C. Singer Environmental Energy Technologies Division June 2012 LBNL-5796E LBNL-XXXXX | Logue et al., Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation 2 Disclaimer This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor

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

Energy Estimation from the Angular Distribution of 20-GeV/c Pion Interactions in Photographic Emulsion  

Science Journals Connector (OSTI)

Interactions of 20-GeV/c negative pions in photographic emulsion have been analyzed in order to compare and test the methods of energy estimation commonly used in high-energy cosmic-ray investigations. The energy of each pion interaction has been determined from the angular distribution of the secondary particles using the median-angle, Castagnoli, Ech, and E(?) methods. The interactions have been divided into various groups according to the number Nh of evaporation prongs and the number ns of secondary particles. The median-angle, Castagnoli, and E(?) methods all overestimate the energy of the group with Nh?5 (ns?4) by factors of 1.5, 1.2, and 1.1, respectively. These same methods underestimate the energy of the group with Nh>5 (ns?4) by factors of 1.3, 2.0, and 2.3, respectively. The Ech method underestimates the energies of the groups with Nh?5 (ns?4) and Nh>5 (ns?4) by factors of 1.3 and 1.5, respectively. These underestimates by the Ech method become 0.9 and 1.0 if the general practice of including the effect of neutral secondaries to the Ech method is adopted. For all the various groupings of Nh and ns considered, the Ech method yields the most consistent and uniform results with the smallest standard deviations than any of the other three methods.

E. R. Goza; S. Krzywdzinski; C. O. Kim; J. N. Park

1970-11-01T23:59:59.000Z

422

Statistical Simulation to Estimate Uncertain Behavioral Parameters of Hybrid Energy-Economy Models  

E-Print Network [OSTI]

for their effect on output, energy demand, and, as a result, emissions. The model responses to these price changes are assumed to indicate likely market reactions to the extent that key parameters (price elasticities between functions. Policies that change energy prices, such as a tax on GHG emissions, can be simulated

423

Natural Gas Transmission and Distribution Module  

Gasoline and Diesel Fuel Update (EIA)

U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Natural Gas Transmission and Distribution Module The NEMS Natural Gas Transmission and...

424

Solar energy conversion via hot electron internal photoemission in metallic nanostructures: Efficiency estimates  

SciTech Connect (OSTI)

Collection of hot electrons generated by the efficient absorption of light in metallic nanostructures, in contact with semiconductor substrates can provide a basis for the construction of solar energy-conversion devices. Herein, we evaluate theoretically the energy-conversion efficiency of systems that rely on internal photoemission processes at metal-semiconductor Schottky-barrier diodes. In this theory, the current-voltage characteristics are given by the internal photoemission yield as well as by the thermionic dark current over a varied-energy barrier height. The Fowler model, in all cases, predicts solar energy-conversion efficiencies of <1% for such systems. However, relaxation of the assumptions regarding constraints on the escape cone and momentum conservation at the interface yields solar energy-conversion efficiencies as high as 1%10%, under some assumed (albeit optimistic) operating conditions. Under these conditions, the energy-conversion efficiency is mainly limited by the thermionic dark current, the distribution of hot electron energies, and hot-electron momentum considerations.

Leenheer, Andrew J.; Narang, Prineha; Atwater, Harry A., E-mail: haa@caltech.edu [Thomas J. Watson Laboratories of Applied Physics, California Institute of Technology, Pasadena, California 91125 (United States); Joint Center for Artificial Photosynthesis, Pasadena, California 91125 (United States); Lewis, Nathan S. [Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125 (United States); Joint Center for Artificial Photosynthesis, Pasadena, California 91125 (United States)

2014-04-07T23:59:59.000Z

425

Estimates of HE-LHC beam parameters at different injection energies  

SciTech Connect (OSTI)

A future upgrade to the LHC envisions increasing the top energy to 16.5 TeV and upgrading the injectors. There are two proposals to replace the SPS as the injector to the LHC. One calls for a superconducting ring in the SPS tunnel while the other calls for an injector (LER) in the LHC tunnel. In both scenarios, the injection energy to the LHC will increase. In this note we look at some of the consequences of increased injection energy to the beam dynamics in the LHC.

Sen, Tanaji; /Fermilab

2010-11-01T23:59:59.000Z

426

Liquid Fuels Market Module  

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

Liquid Fuels Market Module Liquid Fuels Market Module This page inTenTionally lefT blank 145 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Liquid Fuels Market Module The NEMS Liquid Fuels Market Module (LFMM) 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, esters, corn, biomass, and coal), natural gas plant liquids production, and refinery processing gain. In addition, the LFMM projects capacity expansion and fuel consumption at domestic refineries. The LFMM contains a linear programming (LP) representation of U.S. petroleum refining

427

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

rate of technology penetration and rate of intensity change,energy. In addition, the penetration rate of each end-use isinstalled base (i.e. penetration rate) for each end-use set

Fridley, David G.

2008-01-01T23:59:59.000Z

428

A Generalized Method for Estimation of Industrial Energy Savings from Capital and Behavioral Programs  

E-Print Network [OSTI]

methodology was developed to capture total energy savings. This model allows the separation of capital savings to yield savings uniquely attributable to the behavioral program. The intervention model and the resulting calculated savings were both validated...

Luneski, R. D.

2011-01-01T23:59:59.000Z

429

Estimation of the Energy and Capacity Savings in Texas from Appliance Efficiency Standards  

E-Print Network [OSTI]

The purpose of this presentation will be to assess the technical potential for energy and capacity savings in Texas by the year 2006 by the statewide adoption of minimum appliance efficiency standards equivalent to those recently adopted...

Verdict, M.

1986-01-01T23:59:59.000Z

430

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

431

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

of energy consumed from coal, coke, liquid fuels, naturalwas expressed in terms of coal equivalency. 2.1.8.1 Tnational fuel inputs of coal, natural gas and petroleum were

Fridley, David G.

2008-01-01T23:59:59.000Z

432

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7) 7) Release date: April 2007 Next release date: March 2008 Assumptions to the Annual Energy Outlook 2007 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Natural Gas Transmission and Distribution Module. . . . . . . . . . . . . . . . . . . . . . 107 Petroleum Market Module

433

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.

434

Influence of thermal zone assumptions on DOE-2 energy use estimations of a commercial building  

E-Print Network [OSTI]

heating and cooling energy consumption and the simulated values was only 3%. These results were found based on monthly energy data, and several iterations were performed to adjust the input file when major inconsistencies were found between... and Atmospheric Administration's Typical Meteorological Year (TMY) file and then "tuned" again. The ECM's were then modeled and ranked according to their cost effectiveness. This report shows one way of matching simulated data to monitored data...

Hinchey, Sharon Beth

1991-01-01T23:59:59.000Z

435

Development of method for estimation of world industrial energy consumption and its application  

Science Journals Connector (OSTI)

The energy balances published by the International Energy Agency (IEA) are one of the most valuable sources of energy statistics covering world energy supply and demand. However, some issues arise when these data are analyzed or used directly. Even when industrial energy consumption alone is examined, at least three types of issues are encountered: missing data, large amounts of misallocated data in some countries, and numerous unrealistic outliers in the time-series variations. When we deal with only a few regions, we can look at data one by one and modify them. In this case, we are going to overcome these issues with a systematic method because the data covers world including more than a hundred regions. This paper proposes a data reconciliation method to treat these issues, and describes its application to world industrial energy consumption. As a result of its application, we found that the three issues mentioned above seemed to be overcome. The degree of the reconciliation by region showed that OECD countries' degree tends to be smaller than those of non-OECD countries. However, not all of the OECD countries have low values and some countries, such as the United States, have high values.

Shinichiro Fujimori; Yuzuru Matsuoka

2011-01-01T23:59:59.000Z

436

Module Handbook Core Univ. of Oldenburg  

E-Print Network [OSTI]

· Mechanical and Electrical Systems of the WEC Content: Energy conversion process in Wind Turbines · Wind/EUREC Course 2008/2009 #12;EUREC Core Courses at University of Oldenburg, 1st Semester Wind Energy Module Module Description: Wind Energy Field: Core Oldenburg Courses: Wind Energy Wind Energy

Habel, Annegret

437

ENERGY-OPTIMISED CODED MODULATION FOR SHORT-RANGE WIRELESS COMMUNICATIONS ON NAKAGAMI-m FADING CHANNELS  

E-Print Network [OSTI]

of a transmission scheme which takes into account total energy consumption instead of transmission energy alone scheme which takes into account total energy consumption instead of transmission energy alone of a wireless communication link is sufficiently short, circuit energy consumption and transmission energy con

?ien, Geir E.

438

Module Configuration  

DOE Patents [OSTI]

A stand alone battery module including: (a) a mechanical configuration; (b) a thermal management configuration; (c) an electrical connection configuration; and (d) an electronics configuration. Such a module is fully interchangeable in a battery pack assembly, mechanically, from the thermal management point of view, and electrically. With the same hardware, the module can accommodate different cell sizes and, therefore, can easily have different capacities. The module structure is designed to accommodate the electronics monitoring, protection, and printed wiring assembly boards (PWAs), as well as to allow airflow through the module. A plurality of modules may easily be connected together to form a battery pack. The parts of the module are designed to facilitate their manufacture and assembly.

Oweis, Salah (Ellicott City, MD); D'Ussel, Louis (Bordeaux, FR); Chagnon, Guy (Cockeysville, MD); Zuhowski, Michael (Annapolis, MD); Sack, Tim (Cockeysville, MD); Laucournet, Gaullume (Paris, FR); Jackson, Edward J. (Taneytown, MD)

2002-06-04T23:59:59.000Z

439

Under Review for Publication in ASME J. Solar Energy Engineering SOL-12-1058 Life Estimation of Pressurized-Air Solar-Thermal Receiver Tubes  

E-Print Network [OSTI]

for a Brayton-cycle engine are challenging, and lack a large body of operational data unlike steam plants. WeUnder Review for Publication in ASME J. Solar Energy Engineering SOL-12-1058 Life Estimation estimates showed that the Brayton engine's turbine inlet temperature needs to be at least 1100 K

Tomkins, Andrew

440

LBNL-XXXXX | Logue et al., Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation  

E-Print Network [OSTI]

Impacts of Air Sealing and Mechanical Ventilation 1 Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation Jennifer M. Logue, William J. N for Estimating Impacts of Air Sealing and Mechanical Ventilation 2 Disclaimer This document was prepared

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

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,

442

Multiple regression analysis for the estimation of energy content of municipal solid waste  

Science Journals Connector (OSTI)

A regression equation is proposed to predict the Higher Heating Value (HHV) of Municipal Solid Waste (MSW) from the waste data of 86 cities of 35 countries. A mathematical model is developed, by using Statistical Package for Social Sciences (SPSS-10.0), to correlate the energy content of waste with the variables derived from its physical composition. Performance of the proposed multiple regression model is superior to available models. For validation, the proposed model is applied to the waste data of Jaipur City (India), nine cities of EEC countries and also to the MSW of USA. Energy content values obtained by proposed regression model and Modified Dulong's Equation (MDE) are closer to the measured mean energy content values for EEC countries compared to the values obtained by Khan's method. Objective of the paper is to propose a simple model, which can replace the lengthy MDE and which has universal applicability for the predication of HHVs.

G.D. Agrawal; A.P.S. Rathore; A.B. Gupta

2007-01-01T23:59:59.000Z

443

WRF wind simulation and wind energy production estimates forced by different reanalyses: Comparison with observed data for Portugal  

Science Journals Connector (OSTI)

Abstract The performance of the WRF mesoscale model in the wind simulation and wind energy estimates was assessed and evaluated under different initial and boundary forcing conditions. Due to the continuous evolution and progress in the development of reanalyses datasets, this work aims to compare an older, yet widely used, reanalysis (the NCEP-R2) with three recently released reanalyses datasets that represent the new generation of this type of data (ERA-Interim, NASA-MERRA and NCEP-CFSR). Due to its intensive use in wind energy assessment studies, the NCEP-GFS and NCEP-FNL analysis were also used to drive WRF and its results compared to those of the simulations driven by reanalyses. Six different WRF simulations were conducted and their results compared to measured wind data collected at thirteen wind measuring stations located in Portugal in areas of high wind energy potential. Based on the analysis and results presented in this work, it can be concluded that the new generation reanalyses are able to provide a considerable improvement in wind simulation when compared to the older reanalyses. Among all the initial and boundary conditions datasets tested here, ERA-Interim reanalysis is the one that likely provides the most realistic initial and boundary data, providing the best estimates of the local wind regimes and potential wind energy production. The NCEP-GFS and NCEP-FNL analyses seem to be the best alternatives to ERA-Interim, showing better results than all the other reanalyses datasets here tested, and can therefore be considered as valid alternatives to ERA-Interim, in particular for cases where reliable forcing data is needed for real-time applications due to its fast availability.

D. Carvalho; A. Rocha; M. Gmez-Gesteira; C. Silva Santos

2014-01-01T23:59:59.000Z

444

Assumptiions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . . . 99 Petroleum Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Coal Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Renewable Fuels Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Appendix A: Handling of Federal and Selected State Legislation

445

Assumptions to the Annual Energy Outlook 2013  

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

Energy Module Energy Module This page inTenTionally lefT blank 21 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 International Energy Module The LFMM 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 LFMM IEM computes BRENT and WTI prices, provides a supply curve of world crude-like liquids, and generates a worldwide oil supply- demand balance with regional detail. The IEM also provides, for each year of the projection period, endogenous and

446

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

447

ECOLOGICAL EFFICIENCY OF A PELAGIC MYSID SHRIMP; ESTIMATES FROM GROWTH, ENERGY BUDGET, AND MORTALITY STUDIES'  

E-Print Network [OSTI]

because, for example, there are losses involved in syn- thesizing macromolecules, in continually resyn of work. All energy that passes through a population is either lost as heat or passes on to another Metamysidopsis eZangata (Holmes) . Various aspects of the distribution, behavior, and pop- ulation biology

448

Estimates of Energy Consumption by Building Type and End Use at U.S. Army Installations  

E-Print Network [OSTI]

energy use intensity (EUI) by end use for major buildingare shown in Table 3-4. EDA_EUI j k u a l ) l A v a C j i jk annualihvaCii jjj x EDA_EUI ai,hvac,FtHood = EDA.EUIaniiu^

Konopacki, S.J.

2010-01-01T23:59:59.000Z

449

Control of Airborne Wind Energy Systems Based on Nonlinear Model Predictive Control & Moving Horizon Estimation  

E-Print Network [OSTI]

tethered to the ground at a high velocity across the wind direction. Power can be generated by a, the first option is considered. Because it involves a much lighter structure, a major advantage of powerControl of Airborne Wind Energy Systems Based on Nonlinear Model Predictive Control & Moving

450

Estimation and Mapping of Hurricane Turbulent Energy Using Airborne Doppler Measurements  

Science Journals Connector (OSTI)

Hurricane turbulent kinetic energy (TKE) was computed using airborne Doppler measurements from the NOAA WP-3D tail radars, and TKE data were retrieved for a variety of storms at different stages of their life cycle. The geometry of the radar ...

Sylvie Lorsolo; Jun A. Zhang; Frank Marks Jr.; John Gamache

2010-09-01T23:59:59.000Z

451

Estimation of viscosities of ternary silicate melts using the excess gibbs energy of mixing  

Science Journals Connector (OSTI)

A correlation to predict the viscosities of ternary silicates using the Gibbs energies of mixing of the silicate melts has been developed....2, FeO-MgO-SiO2, CaO-FeO-SiO2, CaO-MnO-SiO2, and CaO-MgO-SiO2. The good...

S. Seetharaman; Du Sichen; F. -Z. Ji

2000-02-01T23:59:59.000Z

452

Implementation of non-intrusive energy saving estimation for Volt/VAr control of smart distribution system  

Science Journals Connector (OSTI)

Abstract There has been a growing interest among power distribution utilities to explore smart grid technologies to improve the operational efficiency and reliability. As electricity distribution grid is evolving to become smart, energy demand reduction is one of the goals for the distribution utilities. In order to obtain this goal, utilities need to commit significant financial resources. Therefore, it became important to assess the benefit of new technologies such as Volt/VAr control (VVC). To compute the energy savings due to VVC implementation, existing algorithms are intrusive, and generally require altering the distribution system control settings and operating points, which is undesirable for system operator. On the other hand, these may require large amount of historical data. In this paper, implementation of a new non-intrusive energy saving estimation algorithm has been presented for integrated Volt/VAr control by Avista Utilities in Northwest USA. Developed algorithm utilizes measurements from smart distribution system. Develop algorithm allows studying the energy saving in long term as it requires no change in control settings of actual distribution system. Satisfactory results have been obtained and validated against field data from experiments on real feeders by Avista Utilities.

S. Chanda; F. Shariatzadeh; A. Srivastava; E. Lee; W. Stone; J. Ham

2014-01-01T23:59:59.000Z

453

Coal Market Module This  

Gasoline and Diesel Fuel Update (EIA)

51 51 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 Coal Market Module The NEMS Coal Market Module (CMM) provides projections of U.S. coal production, consumption, exports, imports, 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 2012, DOE/EIA-M060(2012) (Washington, DC, 2012). 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 projection. Forty-one separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations

454

Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

page intentionally left blank page intentionally left blank 153 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Coal Market Module The NEMS Coal Market Module (CMM) provides projections of U.S. coal production, consumption, exports, imports, 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 2011, DOE/EIA-M060(2011) (Washington, DC, 2011). 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 projection. Forty-one separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations

455

Abstract 966: Dietary energy balance modulates IGF-1R and EGFR signaling and crosstalk during tumor promotion  

Science Journals Connector (OSTI)

...for Cancer Research. 1 October 2014 meeting-abstract Molecular and...homeostasis of liver energy metabolism...to study the energy metabolism...homeostasis of liver energy metabolism. [abstract]. In: Proceedings...for Cancer Research; 2014 Apr...

Tricia Moore; Linda Beltran; Steve Carbajal; Guiyu Jiang; Tarlochan Bhatt; Stephen Hursting; and John DiGiovanni

2010-04-15T23:59:59.000Z

456

Analysis and estimation of the threshold for a microwave "pellicle mirror" parametric oscillator, via energy conservation  

E-Print Network [OSTI]

An experiment is proposed to observe the dynamical Casimir effect by means of two tandem, high Q, superconducting microwave cavities, which are separated from each other by only a very thin wall consisting of a flexible superconducting membrane that can be driven into motion by means of resonant "pump" microwaves injected into the left cavity. Degenerate "signal" and "idler" microwave signals can then be generated by the exponential amplification of vacuum fluctuations in the initially empty right cavity, above a certain threshold. The purpose of this paper is calculate the threshold for this novel kind of opto-mechanical parametric oscillation, using energy considerations.

Chiao, Raymond Y

2012-01-01T23:59:59.000Z

457

Transformation of potential energy surfaces for estimating isotopic shifts in anharmonic vibrational frequency calculations  

SciTech Connect (OSTI)

A transformation of potential energy surfaces (PES) being represented by multi-mode expansions is introduced, which allows for the calculation of anharmonic vibrational spectra of any isotopologue from a single PES. This simplifies the analysis of infrared spectra due to significant CPU-time savings. An investigation of remaining deviations due to truncations and the so-called multi-level approximation is provided. The importance of vibrational-rotational couplings for small molecules is discussed in detail. In addition, an analysis is proposed, which provides information about the quality of the transformation prior to its execution. Benchmark calculations are provided for a set of small molecules.

Meier, Patrick; Oschetzki, Dominik; Rauhut, Guntram, E-mail: rauhut@theochem.uni-stuttgart.de [Institut fr Theoretische Chemie, Universitt Stuttgart, Pfaffenwaldring 55, 70569 Stuttgart (Germany)] [Institut fr Theoretische Chemie, Universitt Stuttgart, Pfaffenwaldring 55, 70569 Stuttgart (Germany); Berger, Robert [Clemens-Schpf Institut fr Organische Chemie and Biochemie, Technische Universitt Darmstadt, Petersenstrasse 22, 64287 Darmstadt (Germany)] [Clemens-Schpf Institut fr Organische Chemie and Biochemie, Technische Universitt Darmstadt, Petersenstrasse 22, 64287 Darmstadt (Germany)

2014-05-14T23:59:59.000Z

458

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

459

Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

page intentionally left blank page intentionally left blank 167 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 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 wind [1]. 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

460

Evolution of the energy consumed by street lighting in Spain estimated with DMSP-OLS data  

E-Print Network [OSTI]

We present the results of the analysis of satellite imagery to study light pollution in Spain. Both calibrated and non-calibrated DMSP-OLS images were used. We describe the method to scale the non-calibrated DMSP-OLS images which allows us to use differential photometry techniques in order to study the evolution of the light pollution. Population data and DMSP-OLS satellite calibrated images for the year 2006 were compared to test the reliability of official statistics in public lighting consumption. We found a relationship between the population and the energy consumption which is valid for several regions. Finally the true evolution of the electricity consumption for street lighting in Spain from 1992 to 2010 was derived, it have been doubled in the last 18 years in most of the provinces.

de Miguel, Alejandro Snchez; Castao, Jos Gmez; Pascual, Sergio

2013-01-01T23:59:59.000Z

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


461

Evolution of the energy consumed by street lighting in Spain estimated with DMSP-OLS data  

Science Journals Connector (OSTI)

Abstract We present the results of the analysis of satellite imagery to study light pollution in Spain. Both calibrated and non-calibrated DMSP-OLS images were used. We describe the method to scale the non-calibrated DMSP-OLS images which allows us to use differential photometry techniques in order to study the evolution of the light pollution. Population data and DMSP-OLS satellite calibrated images for the year 2006 were compared to test the reliability of official statistics in public lighting consumption. We found a relationship between the population and the energy consumption which is valid for several regions. Finally the true evolution of the electricity consumption for street lighting in Spain from 1992 to 2010 was derived; it has been doubled in the last 18 years in most of the provinces.

Alejandro Snchez de Miguel; Jaime Zamorano; Jos Gmez Castao; Sergio Pascual

2014-01-01T23:59:59.000Z

462

Preliminary evaluation of the effectiveness of moisture removal and energy usage in pretreatment module of waste cooking oil for biodiesel production  

Science Journals Connector (OSTI)

Waste Cooking Oil (WCO) is a plausible low cost biodiesel feedstock but it exhibits few unfavorable parameters for conversion into biodiesel. One of the parameter is the presence of high moisture content which will inhibit or retard catalyst during the acid esterification or base transesterification causing lower purity and yield of biodiesel. This will effect the post processing and escalate production cost making WCO a not favorable biodiesel feedstock. Therefore, it is important to have an effective moisture removal method to reduce the moisture content below 0.05%wt or 500 ppm in WCO for an efficient biodiesel production. In this work, the effectiveness of moisture removal and the energy usage of a newly develop innovative pretreatment module has been evaluated and reported. Results show that the pretreatment module is able to reduce up to 85% to effectively reduce the moisture content to below 500ppm of the initial moisture content of WCO and only consume 157 Wh/l energy compared to conventional heating that consume 386 Wh/l and only remove 67.6% moisture in 2 hours.

K Palanisamy; M K Idlan; N Saifudin

2013-01-01T23:59:59.000Z

463

DOE Order Self Study Modules - DOE-STD-3009-94, Preparation Guide for U.S. Department of Energy Nonreactor Nuclear Facilities Documented Safety Analyses  

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

3009-94 3009-94 PREPARATION GUIDE FOR U.S. DEPARTMENT OF ENERGY NONREACTOR NUCLEAR FACILITY DOCUMENTED SAFETY ANALYSES DOE-STD-3009-94 Familiar Level June 2011 1 DOE-STD-3009-94 PREPARATION GUIDE FOR U.S. DEPARTMENT OF ENERGY NONREACTOR NUCLEAR FACILITY DOCUMENTED SAFETY ANALYSES FAMILIAR LEVEL _______________________________________________________________________________ OBJECTIVES Given the familiar level of this module and the resources listed below, you will be able to answer the following questions: 1. What are five general requirements for contractors who are responsible for a hazard category 1, 2, or 3 nuclear facility, as related to establishing a safety basis? 2. What actions must a contractor take when it is made aware of a potential inadequacy of

464

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

465

Photovoltaic concentrator module improvements study  

SciTech Connect (OSTI)

This report presents results of a project to design and fabricate an improved photovoltaic concentrator module. Using previous work as a baseline, this study conducted analyses and testing to select major module components and design features. The lens parquet and concentrator solar cell were selected from the highest performing, available components. A single 185X point-focus module was fabricated by the project team and tested at Sandia. Major module characteristics include a 6 by 4 compression-molded acrylic lens parquet (0.737 m{sup 2} area), twenty-four 0.2 ohms-cm, FZ, p-Si solar cells (1.56 cm{sup 2} area) soldered to ceramic substrates and copper heat spreaders, and an aluminized steel housing with corrugated bottom. This project marked the first attempt to use prismatic covers on solar cells in a high-concentration, point-focus application. Cells with 15 percent metallization were obtained, but problems with the fabrication and placement of prismatic covers on these cells lead to the decision not to use covers in the prototype module. Cell assembly fabrication, module fabrication, and module optical design activities are presented here. Test results are also presented for bare cells, cell assemblies, and module. At operating conditions of 981 watts/m{sup 2} DNI and an estimated cell temperature of 65{degrees}C, the module demonstrated an efficiency of 13.9 percent prior to stressed environmental exposure. 12 refs., 56 figs., 7 tabs.

Levy, S.L.; Kerschen, K.A. (Black and Veatch, Kansas City, MO (United States)); Hutchison, G. (Solar Kinetics, Inc., Dallas, TX (United States)); Nowlan, M.J. (Spire Corp., Bedford, MA (United States))

1991-08-01T23:59:59.000Z

466

A hybrid life-cycle inventory for multi-crystalline silicon PV module manufacturing in China  

Science Journals Connector (OSTI)

China is the world's largest manufacturer of multi-crystalline silicon photovoltaic (mc-Si PV) modules, which is a key enabling technology in the global transition to renewable electric power systems. This study presents a hybrid life-cycle inventory (LCI) of Chinese mc-Si PV modules, which fills a critical knowledge gap on the environmental implications of mc-Si PV module manufacturing in China. The hybrid LCI approach combines process-based LCI data for module and poly-silicon manufacturing plants with a 2007 China IO-LCI model for production of raw material and fuel inputs to estimate 'cradle to gate' primary energy use, water consumption, and major air pollutant emissions (carbon dioxide, methane, sulfur dioxide, nitrous oxide, and nitrogen oxides). Results suggest that mc-Si PV modules from China may come with higher environmental burdens that one might estimate if one were using LCI results for mc-Si PV modules manufactured elsewhere. These higher burdens can be reasonably explained by the efficiency differences in China's poly-silicon manufacturing processes, the country's dependence on highly polluting coal-fired electricity, and the expanded system boundaries associated with the hybrid LCI modeling framework. The results should be useful for establishing more conservative ranges on the potential 'cradle to gate' impacts of mc-Si PV module manufacturing for more robust LCAs of PV deployment scenarios.

Yuan Yao; Yuan Chang; Eric Masanet

2014-01-01T23:59:59.000Z

467

Approved Module Information for PD2003, 2014/5 Module Title/Name: Engineering Principles 2 Module Code: PD2003  

E-Print Network [OSTI]

to apply further engineering principles of mechanics, solid mechanics, energy systems and thermo-fluids and understanding of the fundamental engineering principles of mechanics, solid mechanics and thermo- fluidsApproved Module Information for PD2003, 2014/5 Module Title/Name: Engineering Principles 2 Module

Neirotti, Juan Pablo

468

Raising the Bar for Quality PV Modules  

Office of Energy Efficiency and Renewable Energy (EERE)

Since the development and codification of testing standards for PV modules requires a lengthy multiyear process, Department of Energys SunShot Initiative and National Renewable Energy Laboratory worked together on an accelerated schedule for nine months in 2013 to develop a voluntary standard that goes beyond current test protocols to qualify superior PV modules.

469

Oil and Gas Supply Module  

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

Oil and Gas Supply Module Oil and Gas Supply Module This page inTenTionally lefT blank 119 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Oil and Gas Supply Module The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze crude oil and natural gas exploration and development on a regional basis (Figure 8). The OGSM is organized into 4 submodules: Onshore Lower 48 Oil and Gas Supply Submodule, Offshore Oil and Gas Supply Submodule, Oil Shale Supply Submodule[1], and Alaska Oil and Gas Supply Submodule. 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(2011), (Washington, DC, 2011). The OGSM provides

470

Abstract 815: Dietary energy balance modulates skin tumor promotion through altered IGF-1R and EGFR crosstalk  

Science Journals Connector (OSTI)

...for Cancer Research 15 April 2013 meeting-abstract Molecular and...Washington, DC Abstract 1858: Development...biomarkers to assess energy metabolism...for Cancer Research, Frederick...biomarkers to assess energy metabolism in cancer. [abstract]. In: Proceedings...for Cancer Research; 2013 Apr...

Tricia Moore; Linda Beltran; Stephen Hursting; and John DiGiovanni

2011-04-15T23:59:59.000Z

471

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

472

ESTIMATE OF THE TOTAL MECHANICAL FEEDBACK ENERGY FROM GALAXY CLUSTER-CENTERED BLACK HOLES: IMPLICATIONS FOR BLACK HOLE EVOLUTION, CLUSTER GAS FRACTION, AND ENTROPY  

SciTech Connect (OSTI)

The total feedback energy injected into hot gas in galaxy clusters by central black holes can be estimated by comparing the potential energy of observed cluster gas profiles with the potential energy of non-radiating, feedback-free hot gas atmospheres resulting from gravitational collapse in clusters of the same total mass. Feedback energy from cluster-centered black holes expands the cluster gas, lowering the gas-to-dark-matter mass ratio below the cosmic value. Feedback energy is unnecessarily delivered by radio-emitting jets to distant gas far beyond the cooling radius where the cooling time equals the cluster lifetime. For clusters of mass (4-11) x 10{sup 14} M{sub sun}, estimates of the total feedback energy, (1-3) x 10{sup 63} erg, far exceed feedback energies estimated from observations of X-ray cavities and shocks in the cluster gas, energies gained from supernovae, and energies lost from cluster gas by radiation. The time-averaged mean feedback luminosity is comparable to those of powerful quasars, implying that some significant fraction of this energy may arise from the spin of the black hole. The universal entropy profile in feedback-free gaseous atmospheres in Navarro-Frenk-White cluster halos can be recovered by multiplying the observed gas entropy profile of any relaxed cluster by a factor involving the gas fraction profile. While the feedback energy and associated mass outflow in the clusters we consider far exceed that necessary to stop cooling inflow, the time-averaged mass outflow at the cooling radius almost exactly balances the mass that cools within this radius, an essential condition to shut down cluster cooling flows.

Mathews, William G.; Guo Fulai, E-mail: mathews@ucolick.org [University of California Observatories/Lick Observatory, Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA 95064 (United States)

2011-09-10T23:59:59.000Z

473

Neutrons from high?energy x?ray medical accelerators: An estimate of risk to the radiotherapy patient  

Science Journals Connector (OSTI)

The problem of neutrons produced by many of the high?energy x?ray therapy machines (10 MV and above) is reviewed and the possible risk their presence poses to radiotherapy patients is estimated. A review of the regulatory background containing a summary of the recommendations of the U. S. Council of State Governments (USCSG) and of the International Electro?Technical Commission (IEC) as well as an indication that recommendations will be forthcoming from the National Council on Radiation Protection (NCRP) and the International Commission of Radiological Protection (ICRP) is presented. The neutrons in question are produced by high?energy photons(x rays) incident on the various materials of the target flattening filter collimators and other essential components of the equipment. The neutron yield (per treatmentdose) increases rapidly as the megavoltage is increased from 10 to 20 MV but remains approximately constant above this. Measurements and calculations of the quantity quality and spatial distribution of these neutrons and their concomitant dose are summarized. Values of the neutrondose are presented as entrance dose midline dose (10?cm depth) and integral dose both within and outside of the treatment volume. These values are much less than the unavoidable photondoses which are largely responsible for treatment side effects. For typical equipment the average neutron integral dose from accelerator?produced neutrons is about 47 g?cGy (per treatment cGy) depending on the treatment plan. This translates into an average dose of neutrons [averaged over the body of a typical 70?kg (154 1b) patient] of 0.060.10 cGy for a treatment of 1000 cGy. Using these neutrondoses and the best available neutron risk coefficients it is estimated that 5010? 6 fatal malignancies per year due to the neutrons may follow a typical treatment course of 5000 rads of 25?MV x rays. This is only about 1/60th of the average incidence of malignancies for the general population. Thus the cancer risk to the radiotherapy patient from accelerator?produced neutrons poses an additional risk to the patient that is negligible in comparison.

Ravinder Nath; Edward R. Epp; John S. Laughlin; William P. Swanson; Victor P. Bond

1984-01-01T23:59:59.000Z

474

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.

475

Review of Evaluation, Measurement and Verification Approaches Used to Estimate the Load Impacts and Effectiveness of Energy Efficiency Programs  

E-Print Network [OSTI]

on future energy efficiency policy and market environment (on the energy efficiency policy and market environment overon future energy efficiency policy and market environment (

Messenger, Mike

2010-01-01T23:59:59.000Z

476

Silicon Photonics for Modulation, Switching, and Tuning  

Science Journals Connector (OSTI)

Thermal and electro-refractive silicon photonic modulators, switches, and tunable filters have been demonstrated with ultralow switching energies and high-speed operation. These...

Watts, Michael

477

Quantum modulation against electromagnetic interference  

E-Print Network [OSTI]

Periodic signals in electrical and electronic equipment can cause interference in nearby devices. Randomized modulation of those signals spreads their energy through the frequency spectrum and can help to mitigate electromagnetic interference problems. The inherently random nature of quantum phenomena makes them a good control signal. I present a quantum modulation method based on the random statistics of quantum light. The paper describes pulse width modulation schemes where a Poissonian light source acts as a random control that spreads the energy of the potential interfering signals. I give an example application for switching-mode power supplies and comment the further possibilities of the method.

Juan Carlos Garcia-Escartin

2014-11-26T23:59:59.000Z

478

Assumptions to the Annual Energy Outlook  

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 Census Division and prices for each energy source for each of the nine Census Divisions. The Residential Demand Module also requires projections of available equipment over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.