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1

NGNP: High Temperature Gas-Cooled Reactor Key Definitions, Plant Capabilities, and Assumptions  

SciTech Connect

This document provides key definitions, plant capabilities, and inputs and assumptions related to the Next Generation Nuclear Plant to be used in ongoing efforts related to the licensing and deployment of a high temperature gas-cooled reactor. These definitions, capabilities, and assumptions were extracted from a number of NGNP Project sources such as licensing related white papers, previously issued requirement documents, and preapplication interactions with the Nuclear Regulatory Commission (NRC).

Wayne Moe

2013-05-01T23:59:59.000Z

2

NGNP: High Temperature Gas-Cooled Reactor Key Definitions, Plant Capabilities, and Assumptions  

SciTech Connect

This document is intended to provide a Next Generation Nuclear Plant (NGNP) Project tool in which to collect and identify key definitions, plant capabilities, and inputs and assumptions to be used in ongoing efforts related to the licensing and deployment of a high temperature gas-cooled reactor (HTGR). These definitions, capabilities, and assumptions are extracted from a number of sources, including NGNP Project documents such as licensing related white papers [References 1-11] and previously issued requirement documents [References 13-15]. Also included is information agreed upon by the NGNP Regulatory Affairs group's Licensing Working Group and Configuration Council. The NGNP Project approach to licensing an HTGR plant via a combined license (COL) is defined within the referenced white papers and reference [12], and is not duplicated here.

Phillip Mills

2012-02-01T23:59:59.000Z

3

Science with the Square Kilometer Array: Motivation, Key Science Projects, Standards and Assumptions  

E-Print Network (OSTI)

The Square Kilometer Array (SKA) represents the next major, and natural, step in radio astronomical facilities, providing two orders of magnitude increase in collecting area over existing telescopes. In a series of meetings, starting in Groningen, the Netherlands (August 2002) and culminating in a `science retreat' in Leiden (November 2003), the SKA International Science Advisory Committee (ISAC), conceived of, and carried-out, a complete revision of the SKA science case (to appear in New Astronomy Reviews). This preface includes: (i) general introductory material, (ii) summaries of the key science programs, and (iii) a detailed listing of standards and assumptions used in the revised science case.

C. Carilli; S. Rawlings

2004-09-12T23:59:59.000Z

4

Preliminary Review of Models, Assumptions, and Key Data used in Performance Assessments and Composite Analysis at the Idaho National Laboratory  

SciTech Connect

This document is in response to a request by Ming Zhu, DOE-EM to provide a preliminary review of existing models and data used in completed or soon to be completed Performance Assessments and Composite Analyses (PA/CA) documents, to identify codes, methodologies, main assumptions, and key data sets used.

Arthur S. Rood; Swen O. Magnuson

2009-07-01T23:59:59.000Z

5

Housing  

Science Conference Proceedings (OSTI)

... NIST is located in Gaithersburg, Maryland, about 25 miles (40 kilometers) from the center of Washington, DC Housing arrangements have been ...

2010-10-05T23:59:59.000Z

6

AEO Assumptions  

Gasoline and Diesel Fuel Update (EIA)

for the for the Annual Energy Outlook 1997 December 1996 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 Energy Information Administration/Assumptions for the Annual Energy Outlook 1997 Contents Page Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Commercial Demand Module . . . . . . . . . . . . . . . . . .

7

Annual Energy Outlook 96 Assumptions  

Gasoline and Diesel Fuel Update (EIA)

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

8

EIA - Assumptions to the Annual Energy Outlook 2009 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

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

9

EIA - Assumptions to the Annual Energy Outlook 2010 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

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

10

EIA - Assumptions to the Annual Energy Outlook 2008 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

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

11

EIA - Assumptions to the Annual Energy Outlook 2009 - Coal Market...  

Annual Energy Outlook 2012 (EIA)

of mining equipment, the cost of factor inputs (labor and fuel), and other mine supply costs. The key assumptions underlying the coal production modeling are: As capacity...

12

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

13

Assumptions to the Annual Energy Outlook 2013  

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

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

14

Assumptions  

Gasoline and Diesel Fuel Update (EIA)

1 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Petroleum Market Module. . . . . . . . . . . . .

15

Assumptions  

Gasoline and Diesel Fuel Update (EIA)

to the to the Annual Energy Outlook 1998 December 1997 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Household Expenditures Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Oil and Gas Supply Module

16

Assumptions to the Annual Energy Outlook - Introduction  

Gasoline and Diesel Fuel Update (EIA)

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

17

Idaho National Engineering Laboratory installation roadmap assumptions document. Revision 1  

SciTech Connect

This document is a composite of roadmap assumptions developed for the Idaho National Engineering Laboratory (INEL) by the US Department of Energy Idaho Field Office and subcontractor personnel as a key element in the implementation of the Roadmap Methodology for the INEL Site. The development and identification of these assumptions in an important factor in planning basis development and establishes the planning baseline for all subsequent roadmap analysis at the INEL.

Not Available

1993-05-01T23:59:59.000Z

18

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

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

19

Assumptions to the Annual Energy Outlook 2013  

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

Macroeconomic Activity Module Macroeconomic Activity Module This page inTenTionally lefT blank 17 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents interactions between the U.S. economy and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP), is a key determinant of growth in the 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

20

House Shrews  

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

have a mouse problem each winter as the field mice enter from the 120 acres around the house. I read the answer in the archives on mouse house infestation. My question is are the...

Note: This page contains sample records for the topic "key assumptions housing" 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

Bat House  

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

House Name: gregory Location: NA Country: NA Date: NA Question: we live in o'fallon, il, (about 20 miles east of st.louis) and want to put a bat house in our backyard, but we...

22

Assumptions to Annual Energy Outlook - Energy Information Administration  

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

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

23

Assumptions to Annual Energy Outlook - Energy Information Administration  

Gasoline and Diesel Fuel Update (EIA)

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

24

Incremental housing at the receding suburban fringe  

E-Print Network (OSTI)

The years from 2005-2010 brought two major events that shook the basic assumptions underlying housing delivery in the United States of America. First, Hurricane Katrina and the catastrophic flooding of New Orleans that ...

Lamb, Zachary B

2010-01-01T23:59:59.000Z

25

The disciplined use of simplifying assumptions  

Science Conference Proceedings (OSTI)

Simplifying assumptions --- everyone uses them but no one's programming tool explicitly supports them. In programming, as in other kinds of engineering design, simplifying assumptions are an important method for dealing with complexity. Given a complex ...

Charles Rich; Richard C. Waters

1982-04-01T23:59:59.000Z

26

Postdoc Housing  

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

Housing Housing Postdoc Housing Point your career towards LANL: work with the best minds on the planet in an inclusive environment that is rich in intellectual vitality and opportunities for growth. Contact Email Housing in Los Alamos, nearby communities If you are interested in posting a housing opportunity, email the pertinent information to postdocprogram@lanl.gov. Housing listings will be posted for one month. If you wish for the listing to remain on the website longer, please contact the Postdoc Program Office by email. 12/18/2013 Available - Los Alamos, NM Rare top floor Iris Street Condo. Wake up & walk across the street to grab your morning bagel & latte. Stroll a bit further to enjoy the NM sunshine at the Ashley Pond! Spend your day in the heart of downtown, sweat it out

27

Student Housing  

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

Housing Housing Student Housing Point your career towards LANL: work with the best minds on the planet in an inclusive environment that is rich in intellectual vitality and opportunities for growth. If you are interested in posting a housing opportunity, email the pertinent information to Student Housing. Housing listings will be posted for two months. If you wish for the listing to remain on the website longer, please contact the Student Program Office by email. 01/09/2014 Available 1/10/2014 - Los Alamos, NM 35th Street Duplex - 3 Bedroom/1 bath; Very clean and very nice; All storm windows, furnace and water boiler were replaced in FY 2012; Kitchen and bathroom equipment was all replaced in FY2012 as well; Large fenced back yard with a storage shed; Within walking distance of Aspen Elementary

28

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,

29

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

30

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.

31

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

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2009 Residential Demand Module The NEMS Residential Demand Module projects future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions (see Figure 5). The Residential Demand Module also requires projections of available equipment and their installed costs over the projection horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the projection horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

32

Housing - TMS  

Science Conference Proceedings (OSTI)

July 7-11, 2013 Salt Lake Marriott Downtown at City Creek Salt Lake City, Utah . HOUSING. Salt Lake Marriott Downtown at City Creek 75 South West Temple

33

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

States. States. OGSM encompasses domestic crude oil and natural gas supply by both conventional and nonconventional recovery techniques. Nonconventional recovery includes unconventional gas recovery from low permeability formations of sandstone and shale, and coalbeds. Energy Information Administration/Assumptions to the Annual Energy Outlook 2007 93 Figure 7. Oil and Gas Supply Model Regions Source: Energy Information Administration, Office of Integrated Analysis and Forecasting. Report #:DOE/EIA-0554(2007) Release date: April 2007 Next release date: March 2008 Primary inputs for the module are varied. One set of key assumptions concerns estimates of domestic technically recoverable oil and gas resources. Other factors affecting the projection include the assumed

34

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Household Expenditures Module Household Expenditures Module 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. Key Assumptions The historical input data used to develop the HEM version for the AEO2003 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2003 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS).

35

Assumptions to the Annual Energy Outlook  

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 2003, DOE/EIA-M060(2003) (Washington, DC, January 2003). 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).

36

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

Gasoline and Diesel Fuel Update (EIA)

density, housing values, income values, and availability of deepwater ports. The production costs reflect assumed market prices entering the liquefaction facility for...

37

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

Gasoline and Diesel Fuel Update (EIA)

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

38

Assumptions to the Annual Energy Outlook 1999 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

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

39

Assumptions to the Annual Energy Outlook 2012  

U.S. Energy Information Administration (EIA)

Assumptions to the Annual Energy Outlook 2012 August 2012 www.eia.gov U.S. Department of Energy Washington, DC 20585

40

Assumptions to the Annual Energy Outlook 2000 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

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

Note: This page contains sample records for the topic "key assumptions housing" 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

House Wrens  

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

of Cook County Richard B. Ogilvie, President Roland F. Eisenbeis, Supt. of Conservation HOUSE WRENS Ten years ago this spring we moved and, of course, put up some nest boxes for...

42

House Wrens  

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

Wrens Name: Rebecca Location: NA Country: NA Date: NA Question: How long does a house wren live. I'm doing research on this bird I can't seem to find that much info. on it...

43

Arctic house  

E-Print Network (OSTI)

Currently available housing in the Arctic is limited to solutions that have been adapted from designs for less severe climates. This thesis has developed a new manner of residential construction designed specifically for ...

Turkel, Joel A. (Joel Abram), 1969-

1999-01-01T23:59:59.000Z

44

EIA - Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

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

45

House Snakes  

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

House Snakes House Snakes Name: LOIS Location: N/A Country: N/A Date: N/A Question: How do you get rid of snakes in a house? Do mothballs work? Replies: The snake is the most misunderstood and most abused of all animals. If you cannot overcome your abhorrence or fear of them, leave them alone. Do not kill them. They are valuable destroyers of mice, rats, gophers and many insects. Perhaps the following links could be of some assistance in keeping people from indiscriminately killing snakes? Snake-A-Way is the same product used by the pest control industry and currently the only registered snake repellent. Snake-A-Way links: http://www.animalrepellents.com/snakeinfo.html http://www.animalrepellents.com/ustudies/saw.html http://www.animalrepellents.com/editorials/naturel.html

46

Climate Action Planning Tool Formulas and Assumptions  

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

CLIMATE ACTION PLANNING TOOL FORMULAS AND ASSUMPTIONS Climate Action Planning Tool Formulas and Assumptions The Climate Action Planning Tool calculations use the following formulas and assumptions to generate the business-as-usual scenario and the greenhouse gas emissions reduction goals for the technology options. Business-as-Usual Scenario All Scope 1 (gas, oil, coal, fleet, and electricity) and Scope 2 calculations increase at a rate equal to the building growth rate. Scope 3 calculations (commuters and business travel) increase at a rate equal to the population growth rate. Assumptions New buildings will consume energy at the same rate (energy use intensity) as existing campus buildings. Fleet operations will be proportional to total building area.

47

Hierarchy of Mesoscale Flow Assumptions and Equations  

Science Conference Proceedings (OSTI)

The present research proposes a standard nomenclature for mesoscale meteorological concepts and integrates existing concepts of atmospheric space scales, flow assumptions, governing equations, and resulting motions into a hierarchy useful in ...

P. Thunis; R. Bornstein

1996-02-01T23:59:59.000Z

48

Sod Houses  

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

Houses Houses Nature Bulletin No. 620 December 3, 1960 Forest Preserve District of Cook County Daniel Ryan, President Roberts Mann, Conservation Editor David H. Thompson, Senior Naturalist SOD HOUSES In the 1860's and 70's, when pioneer settlers came to homestead free land on the vast lonely prairies of Kansas and Nebraska, they found a country that, except for fringes of cottonwoods and willows along the streams, was treeless. There was no rock and mighty little timber for building houses and barns. Lumber was very expensive and scarce. So was money. However, the prairies were thickly covered with short, drought- enduring buffalo and blue grama grasses. Some of the Indian tribes which not only hunted buffalo but also grew corn -- notably the Pawnee, Osage and Hidatsa -- had large earthlodges. They used sod in the walls and the conical or dome-like roofs had pole rafters covered with willow brush, slough hay, sod, and finally clay. So the homesteaders were inspired to build their homes with slabs of the remarkably thick and tough prairie sod: "Nebraska marble".

49

Open House  

Science Conference Proceedings (OSTI)

When the US housing market collapsed in 2008, so did the dreams of many middle- and lower-class Americans. Florida, California, Nevada, and Arizona were hit particularly hard, and not by a force of nature, but by the abstract and invisible hand of the ...

Jack Stenner; Patrick LeMieux

2011-08-01T23:59:59.000Z

50

Assumptions to the Annual Energy Outlook 2002 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

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

51

Assumptions to the Annual Energy Outlook 2001 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

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

52

Assumptions to the Annual Energy Outlook 2013  

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

Assumptions to the Annual Assumptions to the Annual Energy Outlook 2013 May 2013 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other Federal agencies. Table of Contents Introduction .................................................................................................................................................. 3

53

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.

54

SURF NIST Boulder - Housing  

Science Conference Proceedings (OSTI)

Housing. ... Students will be responsible for paying a housing deposit and rent which are covered by the subsistence allowance. ...

2012-12-17T23:59:59.000Z

55

Concordia Publishing House  

Science Conference Proceedings (OSTI)

... Nonprofit Category. Concordia Publishing House. man at ... cph.org. Concordia Publishing House (CPH) is the St. Louis, Mo ...

2011-11-22T23:59:59.000Z

56

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

57

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7), 7), (Washington, DC, January 2007). Key Assumptions The output of the U.S. economy, measured by GDP, is expected to increase by 2.9 percent between 2005 and 2030 in the reference case. Two key factors help explain the growth in GDP: the growth rate of nonfarm employment and the rate of productivity change associated with employment. As Table 3 indicates, for the Reference Case GDP growth slows down in each of the periods identified, from 3.0 percent between 2005 and 2010, to 2.9 percent between 2010 and 2020, to 2.8 percent in the between 2020 and 2030. In the near term from 2005 through 2010, the growth in nonfarm employment is low at 1.2 percent compared with 2.4 percent in the second half of the 1990s, while the economy is expected to experiencing relatively strong

58

1997 Housing Characteristics Tables Housing Unit Tables  

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

Million U.S. Households; 45 pages, 128 kb) Million U.S. Households; 45 pages, 128 kb) Contents Pages HC1-1a. Housing Unit Characteristics by Climate Zone, Million U.S. Households, 1997 4 HC1-2a. Housing Unit Characteristics by Year of Construction, Million U.S. Households, 1997 4 HC1-3a. Housing Unit Characteristics by Household Income, Million U.S. Households, 1997 4 HC1-4a. Housing Unit Characteristics by Type of Housing Unit, Million U.S. Households, 1997 3 HC1-5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 1997 3 HC1-6a. Housing Unit Characteristics by Type of Rented Housing Unit, Million U.S. Households, 1997 3 HC1-7a. Housing Unit Characteristics by Four Most Populated States, Million U.S. Households, 1997 4

59

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

60

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the Annual Energy Outlook 2004 Assumptions to the Annual Energy Outlook 2004 143 Appendix A: Handling of Federal and Selected State Legislation and Regulation in the Annual Energy Outlook Legislation Brief Description AEO Handling Basis Residential Sector A. National Appliance Energy Conservation Act of 1987 Requires Secretary of Energy to set minimum efficiency standards for 10 appliance categories a. Room Air Conditioners Current standard of 8.82 EER Federal Register Notice of Final Rulemaking, b. Other Air Conditioners (<5.4 tons) Current standard 10 SEER for central air conditioner and heat pumps, increasing to 12 SEER in 2006. Federal Register Notice of Final Rulemaking, c. Water Heaters Electric: Current standard .86 EF, incr easing to .90 EF in 2004. Gas: Curren

Note: This page contains sample records for the topic "key assumptions housing" 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

THE WHITE HOUSE | Department of Energy  

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

THE WHITE HOUSE THE WHITE HOUSE THE WHITE HOUSE More Documents & Publications THE WHITE HOUSE White House Mission Requests Memorandum...

62

KEY PERSONNEL  

National Nuclear Security Administration (NNSA)

APPENDIX J KEY PERSONNEL 07032013 TITLE NAME President Christopher C. Gentile Vice President, Operations Robin Stubenhofer Director, Sr. Program Management Rick Lavelock...

63

Key Outcomes:  

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

INDIAN COUNTRY ENERGY AND INFRASTRUCTURE WORKING GROUP ICEIWG Key Points & Action Items Inaugural Meeting Thursday, August 25, 2011 Renaissance Denver Hotel Denver, Colorado...

64

House Spiders  

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

Spiders Spiders Nature Bulletin No. 206-A November 13, 1965 Forest Preserve District of Cook County Seymour Simon, President Roland F. Eisenbeis, Supt. of Conservation HOUSE SPIDERS Nothing humiliates a housewife more than to spy a dusty streamer of cobwebs dangling from the ceiling when she has "company". With a cloth on the end of her broom, or a vacuum cleaner, she wages continual war on spiders. The spider itself frequently escapes by darting into a hide-away or dropping by a thread of silk to the floor where it may play "possum" until things have quieted down. But in basements, in unused rooms, in attics, between windows and screens, beneath porches, and in garages or other out buildings, many small spiders live their interesting lives.

65

Assumptions to Annual Energy Outlook - Energy Information Administrati...  

Annual Energy Outlook 2012 (EIA)

Assumptions to AEO2013 Release Date: May 14, 2013 | Next Release Date: May 2014 | full report Introduction This report presents the major assumptions of the National Energy...

66

Assumptions to the Annual Energy Outlook - Table 41  

Annual Energy Outlook 2012 (EIA)

> Forecasts >Assumptions to the Annual Energy Outlook> Download Report Assumption to the Annual Energy Outlook Adobe Acrobat Reader Logo Adobe Acrobat Reader is required for PDF...

67

Jurisdiction Members Contact Info Key Staffers  

E-Print Network (OSTI)

Relevant Jurisdiction Members Contact Info Key Staffers House Science, Space, and Technology, aeronautics, civil aviation, environment, and marine science · America COMPETES · Energy labs · National Science Foundation, including NCAR · National Aeronautics and Space Administration · National Weather

68

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

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

69

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2003, DOE/EIA-M068(2003) April 2003. Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

70

Housing policy in China  

E-Print Network (OSTI)

In the last three decades, the People's Republic of China (PRC) has managed to replace its welfare-based urban housing system with a market-based housing provision scheme. With such significant housing policy changes, the ...

Gao, Lu, S.M. Massachusetts Institute of Technology

2011-01-01T23:59:59.000Z

71

2012 ALS Open House  

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

House 2012 ALS Open House Print More than 6000 people came up the hill to see what is happening at Berkeley Lab during Open House on Saturday, October 13, and more than 1500 of...

72

California's Housing Problem  

E-Print Network (OSTI)

could not only improve Californias housing opportunitiesrequirements for education California Budget Project.Locked Out 2004: Californias Affordable Housing Crisis.

Kroll, Cynthia; Singa, Krute

2008-01-01T23:59:59.000Z

73

Assumptions to the Annual Energy Outlook 2000 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

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

74

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).

75

Key Documents  

Science Conference Proceedings (OSTI)

AOCS by-laws, code of ethics and anti trust policy established during our 100+ legacy. Key Documents AOCS History and Governance about us aocs committees contact us division council fats governing board history oils professionals science value cen

76

Assumptions to the Annual Energy Outlook 2013  

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

Demand Module Demand Module This page inTenTionally lefT blank 39 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2040. The definition of the commercial sector is consistent with EIA's State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial.

77

Assumptions to the Annual Energy Outlook  

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 each Census Division using the assumptions and methods described below.106

78

Assumptions to the Annual Energy Outlook - Contacts  

Gasoline and Diesel Fuel Update (EIA)

Contacts Contacts Assumption to the Annual Energy Outlook Contacts Specific questions about the information in this report may be directed to: Introduction Paul D. Holtberg 202/586-1284 Macroeconomic Activity Module Ronald F. Earley Yvonne Taylor 202/586-1398 202/586-1398 International Energy Module G. Daniel Butler 202/586-9503 Household Expenditures Module/ Residential Demand Module John H. Cymbalsky 202/586-4815 Commercial Demand Module Erin E. Boedecker 202/586-4791 Industrial Demand Module T. Crawford Honeycutt 202/586-1420 Transportation Demand Module John D. Maples 202/586-1757 Electricity Market Module Laura Martin 202/586-1494 Oil and Gas Supply Module/Natural Gas Transmission and Distribution Module Joseph Benneche 202/586-6132 Petroleum Market Module Bill Brown 202/586-8181

79

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

80

EIA-Assumptions to the Annual Energy Outlook - Macroeconomic Activity  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module Assumptions to the Annual Energy Outlook 2007 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. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2007), (Washington, DC, January 2007).

Note: This page contains sample records for the topic "key assumptions housing" 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 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

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

82

EIA - Assumptions to the Annual Energy Outlook 2009 - Macroeconomic  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module Assumptions to the Annual Energy Outlook 2010 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. A detailed description of the MAM is provided in the EIA publication, Model Document>ation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2009), (Washington, DC, January 2009).

83

Assumptions to the Annual Energy Outlook 2001 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

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

84

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).

85

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

86

EIA - Assumptions to the Annual Energy Outlook 2008 - Macroeconomic  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module Assumptions to the Annual Energy Outlook 2008 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. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2007), (Washington, DC, January 2007).

87

Assumptions to the Annual Energy Outlook 2001 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

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

88

EIA - Assumptions to the Annual Energy Outlook 2009 - Macroeconomic  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module Assumptions to the Annual Energy Outlook 2009 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. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2008), (Washington, DC, January 2008).

89

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7, DOE/EIA-M060(2007) (Washington, 7, 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).

90

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

91

Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Tools Tools Printable Version Share this resource Send a link to Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology to someone by E-mail Share Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Facebook Tweet about Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Twitter Bookmark Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Google Bookmark Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Delicious Rank Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Digg Find More places to share Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on AddThis.com...

92

Key Outcomes:  

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

Key Points & Action Items Key Points & Action Items Inaugural Meeting Thursday, August 25, 2011 Renaissance Denver Hotel Denver, Colorado Participants Tracey LeBeau, Director, Pilar Thomas, Deputy Director, and Brandt Petrasek, Special Assistant, Department of Energy, Office of Indian Energy Policy and Programs; Vice Chairman Ronald Suppah and Jim Manion, Confederated Tribes of the Warm Springs Reservation of Oregon; William Micklin, Ewiiaapaayp Band of Kumeyaay Indians; Councilman Barney Enos, Jr., Jason Hauter, Gila River Indian Community; Mato Standing High, Rosebud Sioux Tribe; R. Allen Urban, Yocha Dehe Wintun Nation; Glen Andersen, Scott Hendrick, Brooke Oleen, Jacquelyn Pless, Jim Reed and Julia Verdi, National Conference of State Legislatures-staff

93

Sixth Northwest Conservation and Electric Power Plan Chapter 2: Key Assumptions  

E-Print Network (OSTI)

PRICES The future prices of natural gas, coal, and oil have an important effect on the Council's power, is an important factor when considering the use of natural gas for electricity generation. Price volatility-sized homes. The cost of energy (natural gas, oil, and electricity) is expected to be significantly higher

94

1997 Housing Characteristics Tables Housing Unit Tables  

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

Percent of U.S. Households; 45 pages, 121 kb) Percent of U.S. Households; 45 pages, 121 kb) Contents Pages HC1-1b. Housing Unit Characteristics by Climate Zone, Percent of U.S. Households, 1997 4 HC1-2b. Housing Unit Characteristics by Year of Construction, Percent of U.S. Households, 1997 4 HC1-3b. Housing Unit Characteristics by Household Income, Percent of U.S. Households, 1997 4 HC1-4b. Housing Unit Characteristics by Type of Housing Unit, Percent of U.S. Households, 1997 3 HC1-5b. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, Percent of U.S. Households, 1997 3 HC1-6b. Housing Unit Characteristics by Type of Rented Housing Unit, Percent of U.S. Households, 1997 3 HC1-7b. Housing Unit Characteristics by Four Most Populated States, Percent of U.S. Households, 1997 4

95

House Retirement Timeline  

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

House Retirement House Retirement Timeline House is retiring December 20,2013 Fix your pipelines, move data and get help now! /house is POWERED OFF. 12/20/2013 Questions? Contact Kjiersten & Doug; consult@nersc.gov Office hours: MWThF 10:00-12:00 400-413 The link to /house will be permanently changed; all pipelines that have not removed /house dependencies will break. 11/15/2013 Your actions: Find anything that is still broken and let the developers know. Check houseHunter Continue data migration. We DO NOT GUARANTEE that you will be able to get data off /house after this date. 12/1/2013 Your action: Contact your group lead if you still need data /jgi/tools will no longer be in the default path 10/1/2013 Timeline & Important Dates The link to /house will be temporarily

96

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module 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. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2003), (Washington, DC, January 2003).

97

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

98

General model of quantum key distribution  

E-Print Network (OSTI)

A general mathematical framework for quantum key distribution based on the concepts of quantum channel and Turing machine is suggested. The security for its special case is proved. The assumption is that the adversary can perform only individual (in essence, classical) attacks. For this case an advantage of quantum key distribution over classical one is shown.

A. S. Trushechkin; I. V. Volovich

2005-04-20T23:59:59.000Z

99

Crested Flycatcher Bird House  

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

Crested Flycatcher Bird House Name: kristin Location: NA Country: NA Date: NA Question: What would be the best wood to use to build a house for a crested flycatcher? And what...

100

House Fly Ceiling  

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

NA Date: NA Question: We are a public library and have had a question regarding house flies. The question is "How high in the atmosphere can a house fly, fly? Replies:...

Note: This page contains sample records for the topic "key assumptions housing" 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

Texas House Tours Report  

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

house tour 1. A Decathlete will greet visitors at the site's en- trance, distributing tour books and introducing the SNAP House. 2. In the offi ce and entertainment cen- ter, a...

102

100% petroleum house  

E-Print Network (OSTI)

I am designing a Case Study House to be sponsored by Royal Dutch Shell which utilizes the by-product of oil extraction, petroleum gas, to produce a zero waste, 100% petroleum based house. The motivation of the Case Study ...

Costanza, David (David Nicholas)

2013-01-01T23:59:59.000Z

103

" Million Housing Units, Preliminary"  

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

the 2009 Residential Energy Consumption Survey." " Energy Information Administration 2009 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables" "Table...

104

" Million Housing Units, Final"  

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

Residential Energy Consumption Survey." " U.S. Energy Information Administration 2009 Residential Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary...

105

" Million Housing Units, Final...  

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

Residential Energy Consumption Survey." " U.S. Energy Information Administration 2009 Residential Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary...

106

Assumptions to the Annual Energy Outlook 2000 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

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

107

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).

108

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

Gasoline and Diesel Fuel Update (EIA)

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 2006, DOE/EIA-M060(2006) (Washington, DC, 2006). 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 2006, DOE/EIA-M060(2006) (Washington, DC, 2006). 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).

109

The Greening of Our House  

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

Greening of Our House (See also the Greening of the White House) The White House isn't the only building in the U.S. working toward a greener future. LBL's in-house energy...

110

BNL Biology Department - Open House  

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

Open House Open House in Biology is an annual event as part of BNL's Summer Sunday Tours in July and August. Have a look at pictures from past years: Open House 2001 Open House...

111

NREL: Housing Information  

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

Housing Information Housing Information Suggestions for where to start looking for short-term housing or apartments in the Golden, Colorado area are provided below. Short-term Housing Biz-Stay: Lakewood, Golden, Evergreen Housing Features: Short term furnished apartments to extended stay hotels Locations throughout the Lakewood-Golden-Evergreen area. Candlewood Suites 895 Tabor Street Golden, CO 80401 303-232-7171, ask for NREL rates or email Lisa.kennedy@ihg.com Housing Features: Pet friendly Free on-site laundry facilities All suites have kitchens Free high speed internet connections in all suites. University Housing Campus Village Apartments at the Auraria Campus University of Colorado Denver, Metro State College campus (May, June, July only) 318 Walnut St. Denver, CO 80204 303-573-5272

112

EIA - Assumptions to the Annual Energy Outlook 2010  

Gasoline and Diesel Fuel Update (EIA)

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

113

Assumptions to the Annual Energy Outlook - Macroeconomic Activity...  

Annual Energy Outlook 2012 (EIA)

Macroeconomic Activity Module Assumption to the Annual Energy Outlook Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the...

114

Affordable housing: Reducing the energy cost burden  

SciTech Connect

Residential energy expenditures are a key determinant of housing affordability, particularly for lower Income households. For years, federal, state and local governments and agencies have sought to defray energy expenses and Increase residential energy efficiency for low Income households through legislative and regulatory actions and programs. Nevertheless, household energy costs continue to place a major burden on lower Income families. This issue paper was written to help formulate national energy policy by providing the United States Department of Energy`s (DOE`s) Office of Energy Efficiency and Renewable Energy (EE) with Information to help define the affordable housing issue; Identify major drivers, key factors, and primary stakeholders shaping the affordable housing issue; and review how responding to this Issue may impact EE`s goals and objectives and Influence the strategic direction of the office. Typically, housing affordability is an Issue associated with lower income households. This issue paper adopts this perspective, but it is important to note that reducing energy utility costs can make {open_quotes}better{close_quote} housing affordable to any household regardless of income. As energy efficiency is improved throughout all sectors of the economy, special consideration must be given to low income households. Of all households, low income households are burdened the most by residential energy costs; their residences often are the least energy-efficient and have the greatest potential for efficiency improvements, but the occupants have the fewest resources to dedicate to conservation measures. This paper begins with a definition of {open_quotes}affordability{close_quotes} as it pertains to total housing costs and summarizes several key statistics related to housing affordability and energy use by lower income households.

Lee, A.D.; Chin, R.I.; Marden, C.L.

1995-01-01T23:59:59.000Z

115

Assumption-Commitment Support for CSP Model Checking  

E-Print Network (OSTI)

AVoCS 2006 Assumption-Commitment Support for CSP Model Checking Nick Moffat1 Systems Assurance using CSP. In our formulation, an assumption-commitment style property of a process SYS takes the form-Guarantee, CSP, Model Checking, Compositional Reasoning 1 Introduction The principle of compositional program

Paris-Sud XI, Université de

116

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

Gasoline and Diesel Fuel Update (EIA)

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

117

Recovery Act Open House  

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

Recovery Act Open House North Wind Environmental was one of three local small businesses that received Recovery Funding for projects at DOE's Idaho Site. Members of the community...

118

House Simulation Protocols Report  

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

Building America's House Simulation Protocols report is designed to assist researchers in tracking the progress of multiyear, whole-building energy reduction against research goals for new and...

119

" Million Housing Units, Final"  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.5 Household Demographics of U.S....

120

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.8 Household Demographics of Homes...

Note: This page contains sample records for the topic "key assumptions housing" 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

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.1 Household Demographics of U.S....

122

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.7 Household Demographics of U.S....

123

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.6 Household Demographics of U.S....

124

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.3 Household Demographics of U.S....

125

" Million Housing Units, Final"  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.4 Household Demographics of U.S....

126

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.11 Household Demographics of Homes...

127

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.10 Household Demographics of Homes...

128

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.9 Household Demographics of Homes...

129

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.2 Household Demographics of U.S....

130

" Million Housing Units, Final...  

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

0 Appliances in Homes in South Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"South Census Region" ,,,"South Atlantic Census Division",,,,,,"East South...

131

" Million Housing Units, Final...  

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

8 Home Appliances in Homes in Northeast Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"Northeast Census Region" ,,,"New England Census Division",,,"Middle...

132

Crypto Key Management Framework  

Science Conference Proceedings (OSTI)

... A Framework for Designing Cryptographic Key Management Systems ... A Framework for Designing Cryptographic Key Management Systems ...

2013-08-13T23:59:59.000Z

133

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

134

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

135

EIA - Assumptions to the Annual Energy Outlook 2009  

Gasoline and Diesel Fuel Update (EIA)

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

136

SLAC National Accelerator Laboratory - Lodging & Housing Information  

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

& Housing Information STANFORD GUEST HOUSE PHOTO: Stanford Guest House Front Facade This comfortable and convenient housing structure is located on SLAC's campus and is just a...

137

Notes 01. The fundamental assumptions and equations of lubrication theory  

E-Print Network (OSTI)

The fundamental assumption in Lubrication Theory. Derivation of thin film flow equations from Navier-Stokes equations. Importance of fluid inertia effects in thin film flows. Some fluid physical properties

San Andres, Luis

2009-01-01T23:59:59.000Z

138

Prognostic Evaluation of Assumptions Used by Cumulus Parameterizations  

Science Conference Proceedings (OSTI)

Using a spectral-type cumulus parameterization that includes moist downdrafts within a three-dimensional mesoscale model, various disparate closure assumptions are systematically tested within the generalized framework of dynamic control, static ...

Georg A. Grell

1993-03-01T23:59:59.000Z

139

Computational soundness for standard assumptions of formal cryptography  

E-Print Network (OSTI)

This implementation is conceptually simple, and relies only on general assumptions. Specifically, it can be thought of as a 'self-referential' variation on a well-known encryption scheme. 4. Lastly, we show how the ...

Herzog, Jonathan, 1975-

2004-01-01T23:59:59.000Z

140

LBL-34045 UC-1600 Residential HVAC Data, Assumptions and Methodology  

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

5 UC-1600 Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1 Francis X. Johnson, Richard E. Brown, James W. Hanford, Alan H. Sanstad and...

Note: This page contains sample records for the topic "key assumptions housing" 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

Assumptions to the Annual Energy Outlook 1999 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

bullet1.gif (843 bytes) Feedback link.gif (1946 bytes) bullet1.gif (843 bytes) Assumptions to the AEO99 bullet1.gif (843 bytes) Interactive Data Queries to the AEO99 bullet1.gif...

142

Pet House Sparrow  

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

Pet House Sparrow Pet House Sparrow Name: mary Location: N/A Country: N/A Date: N/A Question: I found a Baby House Sparrow and raised it. This Sparrow is a female and is about 5 months old and very tame. We are keeping this bird as a pet. We are interested in possibly breeding this bird and was wondering if you can mix breed the House Sparrow with a Finch or type of Sparrow that you could purchase at a pet store? What is the life expectancy of the House Sparrow? Replies: In the wild most small birds only live a year or two; well cared for in captivity they might be able to make it twice that long, but don't count on it. There are some records of exceptional life lengths for some species of small birds, 8 or 10 years, but I haven't heard of any for house sparrows. I don't think you would be able to cross breed house sparrows with any of the others, but I couldn't say for sure. Hybridization normally occurs only between very closely related species; I don't know enough about genetics.

143

ORNL Guest House  

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

The ORNL Guest House is located in the Oak Ridge National Laboratory campus, within 5 minutes by car to any part of the campus, High Flux Isotope Reactor (HFIR), Conference Center and short walk to the Spallation Neutron Source (SNS). The Guest House is a three story, 47 room, 71 bed facility (23 rooms with king beds and 24 rooms with 2 ex-long double beds). All rooms have a flat screen satellite TV, mini fridge, microwave, coffeemaker, iron & ironing board, and hair dryer. The entire Guest House has high speed wireless internet access with printing capabilities. The ORNL Guest House is located in the Oak Ridge National Laboratory campus, within 5 minutes by car to any part of the campus, High Flux Isotope Reactor (HFIR), Conference Center and short walk to the Spallation Neutron Source (SNS). The Guest House is a three story, 47 room, 71 bed facility (23 rooms with king beds and 24 rooms with 2 ex-long double beds). All rooms have a flat screen satellite TV, mini fridge, microwave, coffeemaker, iron & ironing board, and hair dryer. The entire Guest House has high speed wireless internet access with printing capabilities. ORNL Guest House Oak Ridge National Laboratory Address - 8640 Nano Center Drive Oak Ridge, Tn 37830 Phone: 865-576-8101 Fax: 865-576-8102 Operated by Paragon Hotel Company This Convenient and Modern Facility Offers:

144

Hood River Passive House  

Science Conference Proceedings (OSTI)

The Hood River Passive Project was developed by Root Design Build of Hood River Oregon using the Passive House Planning Package (PHPP) to meet all of the requirements for certification under the European Passive House standards. The Passive House design approach has been gaining momentum among residential designers for custom homes and BEopt modeling indicates that these designs may actually exceed the goal of the U.S. Department of Energy's (DOE) Building America program to reduce home energy use by 30%-50% (compared to 2009 energy codes for new homes). This report documents the short term test results of the Shift House and compares the results of PHPP and BEopt modeling of the project.

Hales, D.

2013-03-01T23:59:59.000Z

145

Principles of Passive House  

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

Principles of Passive House Principles of Passive House Speaker(s): Wolfgang Feist Date: November 1, 2010 - 12:00pm Location: 90-4133 Seminar Host/Point of Contact: Alan Meier The Passive House ("Passivhaus") concept is a rigorous, voluntary energy performance standard for buildings that reduces heating requirements by up to 90% and overall energy use by up to 80% over standard construction. Developed in Germany in the early 1990s and drawing on Super-insulated and Passive Solar ideas from North America and "Low Energy" European building standards, the concept of a building that could be practically constructed to maintain a comfortable interior climate without conventional heating or cooling systems was devised, tested and proven. The Passive House remains comfortable without large "active"

146

Indian Housing Training Conference  

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

This four-day conference will provide housing professionals with the tools to maintain good homes, build affordable homes, improve public safety, and provide essential building blocks to a healthy...

147

Bats in the House  

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

in the House Name: Michelle Location: NA Country: NA Date: NA Question: We are aware of having at least one and possibly more bats living in our attic. Recently (after they have...

148

Barn Swallow House  

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

Swallow House Name: Juli Location: NA Country: NA Date: NA Question: My father is building an "apartment" for barns and swallows to enjoy. He is wondering how large to drill the...

149

Jefferson Lab's Open House  

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

Currently, the date for Jefferson Lab's next Open House hasn't been announced. If you would like to be notified when a date has been set, you can subscribe to the Science Education...

150

" Million Housing Units, Final...  

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

the 2009 Poverty Guidelines for families published by the U.S. Department of Health and Human Services. 3Use of heating equipment for another housing unit also includes the use...

151

" Million Housing Units, Final...  

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

that do not contain a storage tank. The water is only heated as it passes through the heat exchanger. 3Use of a water heater for another housing unit also includes the use of...

152

" Million Housing Units, Final...  

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

that do not contain a storage tank. The water is only heated as it passes through the heat exchanger. 4Use of a water heater for another housing unit also includes the use of...

153

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC6.10 Space Heating in U.S. Homes in...

154

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC6.11 Space Heating in U.S. Homes in...

155

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC6.3 Space Heating in U.S. Homes, by...

156

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC6.4 Space Heating in U.S. Homes, by...

157

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC6.1 Space Heating in U.S. Homes, by...

158

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC6.7 Space Heating in U.S. Homes, by...

159

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC6.8 Space Heating in U.S. Homes in...

160

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC6.2 Space Heating in U.S. Homes, by...

Note: This page contains sample records for the topic "key assumptions housing" 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

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC6.9 Space Heating in U.S. Homes in...

162

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC6.6 Space Heating in U.S. Homes, by...

163

Atrium House solar revitalization  

E-Print Network (OSTI)

The idea behind the Atrium House Solar Revitalization project, may be briefly presented as: energy conserving, low rise, high density, related- to- the-sky residences. The proposed system consists of a reticulate grid - ...

Malamuceanu, Dan Roland

1984-01-01T23:59:59.000Z

164

" Million Housing Units, Final...  

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

5 Appliances in U.S. Homes, by Household Income, 2009" " Million Housing Units, Final" ,,"Household Income" ,"Total U.S.1 (millions)",,,"Below Poverty Line2" ,,"Less than...

165

" Million Housing Units, Final...  

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

3 Appliances in U.S. Homes, by Year of Construction, 2009" " Million Housing Units, Final" ,,"Year of Construction" ,"Total U.S.1 (millions)" ,,"Before 1940","1940 to 1949","1950...

166

" Million Housing Units, Final...  

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

6 Appliances in U.S. Homes, by Climate Region, 2009" " Million Housing Units, Final" ,,"Climate Region2" ,"Total U.S.1 (millions)" ,,"Very Cold","Mixed- Humid","Mixed-Dry"...

167

BUDGET KEY DATES  

Science Conference Proceedings (OSTI)

BUDGET KEY DATES. For Immediate Release: December 15, 2009. Contact: Diane Belford 301-975-8400. Budget Key Dates.

2013-06-16T23:59:59.000Z

168

Key worker housing : a demand analysis of middle-income workforce housing in eastern Massachusetts  

E-Print Network (OSTI)

The Boston Metropolitan Area is one of the most expensive places to live in the United States. In recent years studies have speculated that middle-income workers have had to endure increased commute times as they have moved ...

Sacks, Sean D

2005-01-01T23:59:59.000Z

169

Housing Characteristics, 1990  

DOE Green Energy (OSTI)

This report on energy consumption in the residential sector covers the following topics: housing trends 1980--1990, new housing trends, availability and usage of natural gas by households, changes in appliance usage (refrigerators, entertainment appliances, cooking appliances, convenience appliances), age of major household appliances and equipment, household energy conservation activities, demand-side management programs, and a portrait of households using solar or wood as a source of energy.

Not Available

1992-05-14T23:59:59.000Z

170

Shock absorbing battery housing  

SciTech Connect

A portable battery device is provided which dampens shock incident upon the battery device such that an electrical energizable apparatus connected to the battery device is subject to reduced shock whenever the battery device receives an impact. The battery device includes a battery housing of resilient shock absorbing material injection molded around an interconnecting structure which mechanically and electrically interconnects the battery housing to an electrically energizable apparatus.

McCartney, W.J.; Jacobs, J.D.; Keil, M.J.

1984-09-04T23:59:59.000Z

171

Standard assumptions and methods for solar heating and cooling systems analysis  

DOE Green Energy (OSTI)

A set of inputs, assumptions, analytical methods, and a reporting format is presented to help compare the results of residential and commercial solar system analyses being performed by different investigators. By the common use of load data, meteorological data, economic parameters, and reporting format, researchers examining, for example, two types of collectors may more easily compare their results. For residential heating and cooling systems, three locations were selected. The weather data chosen to characterize these cities are the Typical Meteorological Year (TMY). A house for each location was defined that is typical of new construction in that locale. Hourly loads for each location were calculated using a computerized load model that interacts with the system specified inputs characterizing each house. Four locations for commercial cooling analyses were selected from among the existing sites for which TMYs were available. A light commercial (nominal 25-ton cooling load) office building was defined and is used in all four locations. Hourly cooling and heating loads were computed for each city and are available on magnetic tape from the Solar Energy Research Insititute (SERI).

Leboeuf, C.M.

1980-01-01T23:59:59.000Z

172

2001 Housing Characteristics Detailed Tables  

U.S. Energy Information Administration (EIA)

2001 Residential Energy Consumption Survey-Housing Characteristics, 2001 Detailed Tables, Energy Information Administration

173

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.

174

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.

175

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

176

A Comparison of the Free Ride and CISK Assumptions  

Science Conference Proceedings (OSTI)

In a recent paper Fraedrich and McBride have studied the relation between the free ride and CISK (conditional instability of the second kind) assumptions in a well-known two-layer model. Here the comparison is extended to a more general case. ...

Torben Strunge Pedersen

1991-08-01T23:59:59.000Z

177

White House Champions of Change Recognizes Solar Innovator | Department of  

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

White House Champions of Change Recognizes Solar Innovator White House Champions of Change Recognizes Solar Innovator White House Champions of Change Recognizes Solar Innovator June 10, 2013 - 4:30pm Addthis Dr. Siva Sivananthan at the Sivananthan Laboratories in Bolingbrook, Illinois. | Photo courtesy of Megan Strand, UIC Dr. Siva Sivananthan at the Sivananthan Laboratories in Bolingbrook, Illinois. | Photo courtesy of Megan Strand, UIC Minh Le Minh Le Program Manager, Solar Program What are the key facts? Dr. Sivananthan, a 2009 SunShot Incubator awardee, was recently recognized by the White House as part of the Immigrant Innovator Champions of Change initiative. Dr. Sivananthan's solar research helps to advance the SunShot Initiative's goals of achieving cost-competitive solar by the end of the decade. Recently recognized by the White House, one awardee of the Energy

178

Argonne Open House 2009  

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

Argonne Open Argonne Open House 2009 Welcome Organization Visit Argonne Work with Argonne Contact us For Employees Site Map Help Join us on Facebook Follow us on Twitter NE on Flickr Celebrating the 70th Anniversary of Chicago Pile 1 (CP-1) Argonne OutLoud on Nuclear Energy Argonne Energy Showcase 2012 Argonne Open House 2009 Bookmark and Share THANK YOU! The Nuclear Engineering Division thanks all participants which contributed to make a success of the Open House event. Argonne opened its gates to the community on Saturday, August 29, from 9am to 4:30pm. NE actively participated in this event with activities inside and outside Building 208, the home of the Nuclear Engineering Division. Inside building 208 KEYWORDS: Nuclear Engineering; National Security; Environment, Safety and Health

179

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

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumptions to the Annual Energy Outlook 2009 Petroleum Market Module Figure 9., Petroleum Administration for Defense Districts. Need help, contact the National Energy Information Center at 202-586-8800. Table 11.1. Petroleum Product Categories. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Table 11.2. Year Round Gasoline Specifications by Petroleum Administration for Defense Districts. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Table 11.3. Gasolline Sulfur Content Assumptions, by Region and Gasoline Type, Parts per Million (PPM). Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version

180

Assumption Parish, Louisiana: Energy Resources | Open Energy Information  

Open Energy Info (EERE)

Assumption Parish, Louisiana: Energy Resources Assumption Parish, Louisiana: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 29.9232544°, -91.09694° 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":29.9232544,"lon":-91.09694,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

Note: This page contains sample records for the topic "key assumptions housing" 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

PROJECT MANGEMENT PLAN EXAMPLES Policy & Operational Decisions, Assumptions  

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

Policy & Operational Decisions, Assumptions Policy & Operational Decisions, Assumptions and Strategies Examples 1 & 2 Example 1 1.0 Summary The 322-M Metallurgical Laboratory is currently categorized as a Radiological Facility. It is inactive with no future DOE mission. In May of 1998 it was ranked Number 45 in the Inactive Facilities Risk Ranking database which the Facilities Decommissioning Division maintains. A short-term surveillance and maintenance program is in-place while the facility awaits final deactivation. Completion of the end points described in this deactivation project plan will place the 322-M facility into an End State that can be described as "cold and dark". The facility will be made passively safe requiring minimal surveillance and no scheduled maintenance.

182

Cost and Performance Assumptions for Modeling Electricity Generation Technologies  

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

Cost and Performance Cost and Performance Assumptions for Modeling Electricity Generation Technologies Rick Tidball, Joel Bluestein, Nick Rodriguez, and Stu Knoke ICF International Fairfax, Virginia Subcontract Report NREL/SR-6A20-48595 November 2010 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401 303-275-3000 * www.nrel.gov Contract No. DE-AC36-08GO28308 Cost and Performance Assumptions for Modeling Electricity Generation Technologies Rick Tidball, Joel Bluestein, Nick Rodriguez, and Stu Knoke ICF International Fairfax, Virginia NREL Technical Monitor: Jordan Macknick

183

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7, DOE/EIA- 7, 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. EMM Regions The supply regions used in EMM are based on the North American Electric Reliability Council regions and

184

Assumptions to the Annual Energy Outlook 2000 - Errata  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the Annual Energy Outlook 2000 Assumptions to the Annual Energy Outlook 2000 as of 4/4/2000 1. On table 20 "the fractional fuel efficiency change for 4-Speed Automatic" should be .045 instead of .030. On table 20 "the fractional fuel efficiency change for 5-Speed Automatic" should be .065 instead of .045. (Change made on 3/6/2000) 2. Table 28 should be labeled: "Alternative-Fuel Vehicle Attribute Inputs for Compact Cars for Two Stage Logit Model". (Change made on 3/6/2000) 3. The capital costs in Table 29 should read 1998 dollars not 1988 dollars. (Change made on 3/6/2000) 4. Table 37 changed the label "Year Available" to "First Year Completed." Changed the second sentence of Footnote 1 to read "these estimates are costs of new projects

185

Effects of internal gain assumptions in building energy calculations  

DOE Green Energy (OSTI)

The utilization of direct solar gains in buildings can be affected by operating profiles, such as schedules for internal gains, thermostat controls, and ventilation rates. Building energy analysis methods use various assumptions about these profiles. The effects of typical internal gain assumptions in energy calculations are described. Heating and cooling loads from simulations using the DOE 2.1 computer code are compared for various internal-gain inputs: typical hourly profiles, constant average profiles, and zero gain profiles. Prototype single-family-detached and multi-family-attached residential units are studied with various levels of insulation and infiltration. Small detached commercial buildings and attached zones in large commercial buildings are studied with various levels of internal gains. The results of this study indicate that calculations of annual heating and cooling loads are sensitive to internal gains, but in most cases are relatively insensitive to hourly variations in internal gains.

Christensen, C.; Perkins, R.

1981-01-01T23:59:59.000Z

186

House, home, and community : good models for graduate student housing  

E-Print Network (OSTI)

This thesis explores the planning and design of on-campus housing for graduate students in urban context. This study reviews the prevailing models of on-campus housing nationally and discusses the new concepts of future ...

Han, Jienan, 1978-

2004-01-01T23:59:59.000Z

187

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.

188

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

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2006 The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2006, DOE/EIA- M068(2006). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

189

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

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2008 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2008, DOE/EIA-M068(2008). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

190

Sod House Furnishings  

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

House Furnishings House Furnishings Nature Bulletin No. 666 February 10, 1962 Forest Preserve District of Cook County George W. Dunne, President Roland F. Eisenbeis, Supt. of Conservation SOD HOUSE FURNISHINGS Last year, after we issued Bulletin No. 620-A about the sod houses built by early settlers on the Great Plains, there were numerous requests for this one about the furnishings in those unique dwellings. If they seem meager and inadequate, bear in mind that, with rare exceptions, the pioneers were so poor that some had nothing but iron determination and courage. After the Civil War, ex-soldiers from both armies "pulled up stakes and lit out" for Nebraska, Kansas, or Texas. Under the Homestead Act of 1862, anyone who had not been a Rebel could "file" on and obtain, free, a quarter-section (160 acres) of "government land" -- public domain -- and, by paying $200, claim and pre-empt another. There were no restrictions on purchases from land companies, nor from the railroads that had been granted millions of acres.

191

Energy Housing Characteristics Tables RECS 2001  

U.S. Energy Information Administration (EIA)

Climate Zone PDF. Year of Construction PDF. Household Income PDF. Type of Housing Unit PDF. Type of Owner-Occupied Housing Unit PDF: Type of Rented Housing ...

192

Important notice about using /house  

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

Important notice about using house Important notice about using house July 6, 2012 (0 Comments) Description There have been a lot of issues recently with NFS hangs on the gpint...

193

The Future of Housing - TMS  

Science Conference Proceedings (OSTI)

May 20, 2008 ... From climate change to power deregulation and suburban sprawl to the rapid ... This presentation speaks directly to our future housing needs and ... using the 2007 Carnegie Mellon Solar Decathlon house as a case study.

194

Housing in the Gaithersburg Area  

Science Conference Proceedings (OSTI)

... NIST and Metro. http://www.higaithersburg.com/ Hyatt House Gaithersburg - 200 Skidmore Blvd. Gaithersburg, MD 20877 ...

195

White_House_0921.pdf | Department of Energy  

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

WhiteHouse0921.pdf WhiteHouse0921.pdf WhiteHouse0921.pdf More Documents & Publications THE WHITE HOUSE THE WHITE HOUSE WhiteHouseeconomicrpt021...

196

Passive retrofits for Navy housing  

DOE Green Energy (OSTI)

A project to assess and initiate passive solar energy retrofits to US Navy family housing is described. The current data base for Navy housing (ECOP), and its enhancement for passive solar purposes options proposed for Navy housing are explained. The analysis goals and methods to evaluate the retrofits are discussed. An educational package to explain the retrofits is described.

Hibbert, R.; Miles, C.; Jones, R.; Peck, C.; Anderson, J.; Jacobson, V.; Dale, A.M.

1985-01-01T23:59:59.000Z

197

President Obama Announces More Key Administration Posts | Department of  

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

President Obama Announces More Key Administration Posts President Obama Announces More Key Administration Posts President Obama Announces More Key Administration Posts November 29, 2011 - 4:34pm Addthis THE WHITE HOUSE Office of the Press Secretary FOR IMMEDIATE RELEASENovember 29, 2011 President Obama Announces More Key Administration Posts WASHINGTON, DC - Today, President Barack Obama announced his intent to nominate the following individuals to key Administration posts: Frederick "Rick" Barton - Assistant Secretary for Conflict and Stabilization Operations and Coordinator for Reconstruction and Stabilization, Department of State Arun Majumdar - Under Secretary of Energy, Department of Energy Marie F. Smith - Member, Social Security Advisory Board The President also announced his intent to appoint the following

198

Security proof of practical quantum key distribution schemes  

E-Print Network (OSTI)

This paper provides a security proof of the Bennett-Brassard (BB84) quantum key distribution protocol in practical implementation. To prove the security, it is not assumed that defects in the devices are absorbed into an adversary's attack. In fact, the only assumption in the proof is that the source is characterized. The proof is performed by lower-bounding adversary's Renyi entropy about the key before privacy amplification. The bound reveals the leading factors reducing the key generation rate.

Yodai Watanabe

2005-06-29T23:59:59.000Z

199

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

200

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

Note: This page contains sample records for the topic "key assumptions housing" 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

" Million U.S. Housing Units"  

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

3 Lighting Usage Indicators by Type of Housing Unit, 2005" " Million U.S. Housing Units" ,,"Type of Housing Unit" ,"Housing Units (millions)","Single-Family Units",,"Apartments in...

202

" Million U.S. Housing Units"  

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

3 Household Characteristics by Owner-Occupied Housing Unit, 2005" " Million U.S. Housing Units" ,," Owner-Occupied Housing Units (millions)","Type of Owner-Occupied Housing Unit"...

203

Fermilab Family Open House  

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

Sunday, February 9, 2014 Sunday, February 9, 2014 1:00–5:00 PM Directions to Fermilab This is a party for children who bring an adult with them to learn about the world of physics. (There's plenty for the grown-ups, too.) Events include: Watch Mr. Freeze's fabulous cryogenics show Explore physics concepts with hands-on activities Ask a scientist your physics questions. Take a tour! And more! The Open House is most appropriate for children in grades 3 and up. The event is free. Register only if you wish to go on a tour (minimum age 10). Otherwise, you do not have to register. You should pick up the tickets for the tours in the atrium on the day of the event. Tickets not picked up at least 10 minutes before a tour starts will be released. The Open House is co-supported by Fermilab Friends for Science Education and the Education Office.

204

Group key management  

SciTech Connect

This report describes an architecture and implementation for doing group key management over a data communications network. The architecture describes a protocol for establishing a shared encryption key among an authenticated and authorized collection of network entities. Group access requires one or more authorization certificates. The implementation includes a simple public key and certificate infrastructure. Multicast is used for some of the key management messages. An application programming interface multiplexes key management and user application messages. An implementation using the new IP security protocols is postulated. The architecture is compared with other group key management proposals, and the performance and the limitations of the implementation are described.

Dunigan, T.; Cao, C.

1997-08-01T23:59:59.000Z

205

Housing characteristics 1993  

Science Conference Proceedings (OSTI)

This report, Housing Characteristics 1993, presents statistics about the energy-related characteristics of US households. These data were collected in the 1993 Residential Energy Consumption Survey (RECS) -- the ninth in a series of nationwide energy consumption surveys conducted since 1978 by the Energy Information Administration of the US Department of Energy. Over 7 thousand households were surveyed, representing 97 million households nationwide. A second report, to be released in late 1995, will present statistics on residential energy consumption and expenditures.

NONE

1995-06-01T23:59:59.000Z

206

Flying Squirrels and Houses  

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

Flying Squirrels and Houses Flying Squirrels and Houses Name: Kathy Location: N/A Country: N/A Date: N/A Question: How do you get rid of flying squirrels in the attic of a Cape style home that has limited access to the attic? There is blown in insulation so we cannot see to the end of the house where we hear them, nor can a person crawl in to see anything. We have used d-con bars, mouse traps and have-a-heart traps in the crawl spaces we can reach, but have caught nothing. Replies: Place a statue of an owl near the entrance the squirrels are using. Owls are their motal enemies and this technique works for birds as well. Steve Sample You will not be able to solve this problem until you find the way they go in and out. Usually the easiest way is to look for light coming in from outside while in the dark attic, but if you can't see it that way do a thorough search of the outside. A flying squirrel does not need a very big hole, maybe 2" or less diameter. They go out at night so once you find the hole close it up at night while they are out. Good luck.

207

Energy Efficiency Standards for Manufactured Housing | Building...  

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

Regulations Determinations Federal Buildings Manufactured Housing Resource Center Energy Efficiency Standards for Manufactured Housing Section 413 of the Energy...

208

Before the House Transportation and Infrastructure Subcommittee...  

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

the House Transportation and Infrastructure Subcommittee on Economic Development, Public Buildings, and Emergency Management Before the House Transportation and Infrastructure...

209

Assumptions to the Annual Energy Outlook 2000 - Natural Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market “hubs.” The major assumptions used within the NGTDM are grouped into five general categories. They relate to (1) the classification of demand into core and noncore transportation service classes, (2) the pricing of transmission and distribution services, (3) pipeline and storage capacity expansion and utilization, (4) the implementation of recent regulatory reform, and (5) the implementation of provisions of the Climate Change Action Plan (CCAP). A complete listing of NGTDM assumptions and in-depth methodology descriptions are presented in Model Documentation: Natural Gas Transmission and Distribution Model of the National Energy Modeling System, Model Documentation 2000, DOE/EIA-M062(2000), January 2000.

210

Assumptions to the Annual Energy Outlook 2000 - Electricity Market Demand  

Gasoline and Diesel Fuel Update (EIA)

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

211

Assumptions to the Annual Energy Outlook 1999 - Natural Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

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

212

Unifying classical and quantum key distillation  

E-Print Network (OSTI)

Assume that two distant parties, Alice and Bob, as well as an adversary, Eve, have access to (quantum) systems prepared jointly according to a tripartite state ?ABE. In addition, Alice and Bob can use local operations and authenticated public classical communication. Their goal is to establish a key which is unknown to Eve. We initiate the study of this scenario as a unification of two standard scenarios: (i) key distillation (agreement) from classical correlations and (ii) key distillation from pure tripartite quantum states. Firstly, we obtain generalisations of fundamental results related to scenarios (i) and (ii), including upper bounds on the key rate, i.e., the number of key bits that can be extracted per copy of ?ABE. Moreover, based on an embedding of classical distributions into quantum states, we are able to find new connections between protocols and quantities in the standard scenarios (i) and (ii). Secondly, we study specific properties of key distillation protocols. In particular, we show that every protocol that makes use of pre-shared key can be transformed into an equally efficient protocol which needs no pre-shared key. This result is of practical significance as it applies to quantum key distribution (QKD) protocols, but it also implies that the key rate cannot be locked with information on Eves side. Finally, we exhibit an arbitrarily large separation between the key rate in the standard setting where Eve is equipped with quantum memory and the key rate in a setting where Eve is only given classical memory. This shows that assumptions on the nature of Eves memory are important in order to determine the correct security threshold in QKD. 1

Matthias Christ; Renato Renner

2008-01-01T23:59:59.000Z

213

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).

214

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).

215

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.

216

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)

217

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

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2009 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with 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.1

218

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

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2009 Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger aircraft, freight, rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

219

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

clothes drying, ceiling fans, coffee makers, spas, home security clothes drying, ceiling fans, coffee makers, spas, home security systems, microwave ovens, set-top boxes, home audio equipment, rechargeable electronics, and VCR/DVDs. In addition to the major equipment-driven end-uses, the average energy consumption per household is projected for other electric and nonelectric appliances. The module's output includes number Energy Information Administration/Assumptions to the Annual Energy Outlook 2007 19 Pacific East South Central South Atlantic Middle Atlantic New England West South Central West North Central East North Central Mountain AK WA MT WY ID NV UT CO AZ NM TX OK IA KS MO IL IN KY TN MS AL FL GA SC NC WV PA NJ MD DE NY CT VT ME RI MA NH VA WI MI OH NE SD MN ND AR LA OR CA HI Middle Atlantic New England East North Central West North Central Pacific West South Central East South Central

220

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

Gasoline and Diesel Fuel Update (EIA)

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

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


221

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

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2009 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2035. The definition of the commercial sector is consistent with 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 [1].

222

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

223

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

Gasoline and Diesel Fuel Update (EIA)

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

224

EIA - Assumptions to the Annual Energy Outlook 2010 - Petroleum Market  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumptions to the Annual Energy Outlook 2010 Petroleum Market Module The NEMS Petroleum Market Module (PMM) projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, unfinished oil imports, other refinery inputs (including alcohols, ethers, bioesters, corn, biomass, and coal), natural gas plant liquids production, and refinery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic refineries. Figure 9. Petroleum Administration for Defense Districts. The PMM contains a linear programming (LP) representation of U.S. refining activities in the five Petroleum Area Defense Districts (PADDs) (Figure 9),

225

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

226

Assumptions to the Annual Energy Outlook 1999 - Table 1  

Gasoline and Diesel Fuel Update (EIA)

Summary of AEO99 Cases Summary of AEO99 Cases Case Name Description Integration mode Reference Baseline economic growth, world oil price, and technology assumptions Fully Integrated Low Economic Growth Gross Domestic product grows at an average annual rate of 1.5 percent, compared to the reference case growth of 2.1 percent. Fully Integrated High Economic Growth Gross domestic product grows at an average annual rate of 2.6 percent, compared to the reference case growth of 2.1 percent. Fully Integrated Low World Oil Price World oil prices are $14.57 per barrel in 2020, compared to $22.73 per barrel in the reference case. Partially Integrated High World Oil Price World oil prices are $29.35 per barrel in 2020, compared to $22.73 per barrel in the reference case. Partially Integrated Residential: 1999 Technology

227

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

Gasoline and Diesel Fuel Update (EIA)

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

228

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

Gasoline and Diesel Fuel Update (EIA)

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

229

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.

230

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.

231

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

Gasoline and Diesel Fuel Update (EIA)

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

232

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

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2006 The 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).

233

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.

234

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

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2008 Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger aircraft, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

235

EIA - Assumptions to the Annual Energy Outlook 2010 - International Energy  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2010 International Energy Module Figure 2. World Oil Prices in Three Cases, 1995-2035 Figure 2. World Oil Prices in three Cases, 1995-2035 (2008 dollars per barrel). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 3. OPEC Total Liquids Production in the Reference Case, 1980-2035 Figure 3. OPEC Total Liquids Production in the Reference Case, 1995-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 4. Non-OPEC Total Liquids Production in the Reference Case, 1980-2035 Figure 4. Non-OPEC Total Liquids Production in the Reference Case, 1995-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800.

236

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

Gasoline and Diesel Fuel Update (EIA)

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

237

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

Gasoline and Diesel Fuel Update (EIA)

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

238

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

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2006 The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with 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.14

239

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.

240

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

Note: This page contains sample records for the topic "key assumptions housing" 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

Assumptions to the Annual Energy Outlook - Natural Gas Transmission and  

Gasoline and Diesel Fuel Update (EIA)

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

242

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

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2008 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with 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.1

243

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

Gasoline and Diesel Fuel Update (EIA)

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

244

Cost and Performance Assumptions for Modeling Electricity Generation Technologies  

Science Conference Proceedings (OSTI)

The goal of this project was to compare and contrast utility scale power plant characteristics used in data sets that support energy market models. Characteristics include both technology cost and technology performance projections to the year 2050. Cost parameters include installed capital costs and operation and maintenance (O&M) costs. Performance parameters include plant size, heat rate, capacity factor or availability factor, and plant lifetime. Conventional, renewable, and emerging electricity generating technologies were considered. Six data sets, each associated with a different model, were selected. Two of the data sets represent modeled results, not direct model inputs. These two data sets include cost and performance improvements that result from increased deployment as well as resulting capacity factors estimated from particular model runs; other data sets represent model input data. For the technologies contained in each data set, the levelized cost of energy (LCOE) was also evaluated, according to published cost, performance, and fuel assumptions.

Tidball, R.; Bluestein, J.; Rodriguez, N.; Knoke, S.

2010-11-01T23:59:59.000Z

245

Unifying classical and quantum key distillation  

E-Print Network (OSTI)

Assume that two distant parties, Alice and Bob, as well as an adversary, Eve, have access to (quantum) systems prepared jointly according to a tripartite state. In addition, Alice and Bob can use local operations and authenticated public classical communication. Their goal is to establish a key which is unknown to Eve. We initiate the study of this scenario as a unification of two standard scenarios: (i) key distillation (agreement) from classical correlations and (ii) key distillation from pure tripartite quantum states. Firstly, we obtain generalisations of fundamental results related to scenarios (i) and (ii), including upper bounds on the key rate. Moreover, based on an embedding of classical distributions into quantum states, we are able to find new connections between protocols and quantities in the standard scenarios (i) and (ii). Secondly, we study specific properties of key distillation protocols. In particular, we show that every protocol that makes use of pre-shared key can be transformed into an equally efficient protocol which needs no pre-shared key. This result is of practical significance as it applies to quantum key distribution (QKD) protocols, but it also implies that the key rate cannot be locked with information on Eve's side. Finally, we exhibit an arbitrarily large separation between the key rate in the standard setting where Eve is equipped with quantum memory and the key rate in a setting where Eve is only given classical memory. This shows that assumptions on the nature of Eve's memory are important in order to determine the correct security threshold in QKD.

Matthias Christandl; Artur Ekert; Michal Horodecki; Pawel Horodecki; Jonathan Oppenheim; Renato Renner

2006-08-25T23:59:59.000Z

246

President Obama Announces More Key Administration Posts | Department of  

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

President Obama Announces More Key Administration Posts President Obama Announces More Key Administration Posts President Obama Announces More Key Administration Posts April 17, 2009 - 12:00am Addthis WASHINGTON, DC - Today, President Barack Obama announced his intent to nominate the following individuals for key administration posts: Christine M. Griffin, Deputy Director of Office of Personnel Management; Kevin Concannon, Under Secretary for Food, Nutrition and Consumer Services, United States Department of Agriculture; Rajiv Shah, Under Secretary for Research, Education, and Economics, United States Department of Agriculture; Michael Nacht, Assistant Secretary of Defense (Global Strategic Affairs), Department of Defense; Mercedes Márquez, Assistant Secretary for Community Planning and Development, Department of Housing and

247

NCNR Summer School Housing Information  

Science Conference Proceedings (OSTI)

... 2010 NCNR/NSF Summer School Housing Information. Registration for the Summer School will be on May 9th, 2010 from 4-7 pm. ...

248

NCNR Summer School Housing Information  

Science Conference Proceedings (OSTI)

... 2008 NCNR/NSF Summer School Housing Information. Registration for the Summer School will be on June 22nd, 2008 from 4-7 pm. ...

249

NCNR Summer School Housing Information  

Science Conference Proceedings (OSTI)

... CHRNS Logo. Last modified 13-April-2011 by website owner: NCNR (attn: Jeff Krzywon). 2011 NCNR/NSF Summer School Housing Information. ...

250

Multifamily housing resources | ENERGY STAR  

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

manufacturing resources K-12 school resources Multifamily housing resources Restaurant resources Retail resources Senior care resources Small business resources State and...

251

DOE Announces More Key Administration Posts | Department of Energy  

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

More Key Administration Posts More Key Administration Posts DOE Announces More Key Administration Posts March 27, 2009 - 12:00am Addthis WASHINGTON, DC - Today, President Barack Obama announced his intent to nominate the following individuals to key administration posts: Ray Mabus, Secretary of the Navy, Department of Defense; Donald Remy, General Counsel of the Army, Department of Defense; J. Randolph Babbitt, Administrator, Federal Aviation Administration; Jose D. Riojas, Assistant Secretary for Operations, Security and Preparedness, Department of Veterans Affairs; John Trasviña, Assistant Secretary for Fair Housing and Equal Opportunity, Department of Housing and Urban Development; Lawrence E. Strickling, Assistant Secretary for Communications and Information, Department of Commerce; and Cathy Zoi, Assistant Secretary for Energy Efficiency and

252

The Key Agreement Schemes  

Science Conference Proceedings (OSTI)

... The three key derivation functions include KDF in Counter Mode, KDF in Feedback Mode, and KDF in Double-Pipeline Iteration Mode. ...

2013-04-23T23:59:59.000Z

253

Crypto Key Management Framework  

Science Conference Proceedings (OSTI)

... responsible to executive-level management (eg, the Chief Information Officer) for the ... entity information, keys, and metadata into a database used by ...

2013-08-15T23:59:59.000Z

254

A Graphical Approach to Diagnosing the Validity of the Conditional Independence Assumptions of a Bayesian Network Given Data  

SciTech Connect

Bayesian networks have attained widespread use in data analysis and decision making. Well studied topics include: efficient inference, evidence propagation, parameter learning from data for complete and incomplete data scenarios, expert elicitation for calibrating Bayesian network probabilities, and structure learning. It is not uncommon for the researcher to assume the structure of the Bayesian network or to glean the structure from expert elicitation or domain knowledge. In this scenario, the model may be calibrated through learning the parameters from relevant data. There is a lack of work on model diagnostics for fitted Bayesian networks; this is the contribution of this paper. We key on the definition of (conditional) independence to develop a graphical diagnostic method which indicates if the conditional independence assumptions imposed when one assumes the structure of the Bayesian network are supported by the data. We develop the approach theoretically and describe a Monte Carlo method to generate uncertainty measures for the consistency of the data with conditional independence assumptions under the model structure. We describe how this theoretical information and the data are presented in a graphical diagnostic tool. We demonstrate the approach through data simulated from Bayesian networks under different conditional independence assumptions. We also apply the diagnostic to a real world data set. The results indicate that our approach is a reasonable way of visualizing and inspecting the conditional independence assumption of a Bayesian network given data.

Walsh, Stephen J.; Whitney, Paul D.

2012-12-14T23:59:59.000Z

255

Cryptographic Key Management Workshop 2010  

Science Conference Proceedings (OSTI)

Cryptographic Key Management Workshop 2010. Purpose: ... Related Project(s): Cryptographic Key Management Project. Details: ...

2013-08-01T23:59:59.000Z

256

Terrace housing : providing quality in higher-density housing  

E-Print Network (OSTI)

The higher demand of higher-density housing in Bangkok due to the rapid growth of the economy and the use of high-performance materials and modern construction methods has changed the forms of housing from low-rise buildings ...

Atthakor, Songpol

1992-01-01T23:59:59.000Z

257

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.

258

EIA - Assumptions to the Annual Energy Outlook 2008 - Renewable Fuels  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module Assumptions to the Annual Energy Outlook 2008 Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for projections of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind1. Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was one of the first electric generation technologies, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. 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.

259

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

Gasoline and Diesel Fuel Update (EIA)

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

260

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

Note: This page contains sample records for the topic "key assumptions housing" 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

THE WHITE HOUSE  

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

WASHINGTON August 29, 1994 MEMORANDUM FOR CABINET MEMBER AND FULL-TIME EXECUTIVE BRANCH PRESIDENTIAL APPOINTEES FROM: LLOYD N. CUTLER SPECIAL COUNSEL TO THE PRESIDENT SUBJECT: Use of Company Aircraft and Accommodations As Presidential appointees, the actions we take reflect directly upon this Administration and on the President. We must therefore adhere strictly to the Standards of Ethical Conduct for Employees of the Executive Branch (Standards), 5. C.F.R. Part 2635. In addition, we must meet the even higher standard of avoiding conduct, however lawful, that public opinion regards as inappropriate for a Presidential appointee. In this spirit, the White House Chief of Staff has directed me to issue the following policy on the use, by Cabinet members and other full-time Executive Branch Presidential

262

The European Passive House Concept  

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

The European Passive House Concept The European Passive House Concept Speaker(s): Nabih Tahan Date: January 13, 2009 - 12:00pm Location: 90-3122 Nabih will describe the European Passive House concept and modern, home manufacturing methods in Austria. The Passive House is a European standard for a specific way to build a house that consumes very little energy, is comfortable and has a high indoor air quality. It is a cost effective method of building, where conventional heating systems are eliminated, and their cost is reinvested in super insulation, super air-tightness and heat recovery. Free heat generated from electrical and gas appliances and lighting is recycled through the heat recovery ventilator. This results in buildings that consume 80% to 90% less heating energy while constantly

263

House Report 108-576, FY 2005 House Report for Commerce ...  

Science Conference Proceedings (OSTI)

Taken from House Report 108-576, FY 2005 House Report for Commerce, Justice, and State Appropriations bill. SCIENTIFIC ...

2010-10-05T23:59:59.000Z

264

White House Mission Requests Memorandum | Department of Energy  

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

White House Mission Requests Memorandum White House Mission Requests Memorandum White House Mission Requests Memorandum More Documents & Publications THE WHITE HOUSE THE WHITE...

265

Optical key system  

Science Conference Proceedings (OSTI)

An optical key system comprises a battery-operated optical key and an isolated lock that derives both its operating power and unlock signals from the correct optical key. A light emitting diode or laser diode is included within the optical key and is connected to transmit a bit-serial password. The key user physically enters either the code-to-transmit directly, or an index to a pseudorandom number code, in the key. Such person identification numbers can be retained permanently, or ephemeral. When a send button is pressed, the key transmits a beam of light modulated with the password information. The modulated beam of light is received by a corresponding optical lock with a photovoltaic cell that produces enough power from the beam of light to operate a password-screen digital logic. In one application, an acceptable password allows a two watt power laser diode to pump ignition and timing information over a fiberoptic cable into a sealed engine compartment. The receipt of a good password allows the fuel pump, spark, and starter systems to each operate. Therefore, bypassing the lock mechanism as is now routine with automobile thieves is pointless because the engine is so thoroughly disabled.

Hagans, K.G.; Clough, R.E.

2000-04-25T23:59:59.000Z

266

Optical key system  

DOE Patents (OSTI)

An optical key system comprises a battery-operated optical key and an isolated lock that derives both its operating power and unlock signals from the correct optical key. A light emitting diode or laser diode is included within the optical key and is connected to transmit a bit-serial password. The key user physically enters either the code-to-transmit directly, or an index to a pseudorandom number code, in the key. Such person identification numbers can be retained permanently, or ephemeral. When a send button is pressed, the key transmits a beam of light modulated with the password information. The modulated beam of light is received by a corresponding optical lock with a photovoltaic cell that produces enough power from the beam of light to operate a password-screen digital logic. In one application, an acceptable password allows a two watt power laser diode to pump ignition and timing information over a fiberoptic cable into a sealed engine compartment. The receipt of a good password allows the fuel pump, spark, and starter systems to each operate. Therefore, bypassing the lock mechanism as is now routine with automobile thieves is pointless because the engine is so thoroughly disabled.

Hagans, Karla G. (Livermore, CA); Clough, Robert E. (Danville, CA)

2000-01-01T23:59:59.000Z

267

Demonstrating Modernism: Richard Neutra's Early Model Houses  

E-Print Network (OSTI)

88 Richard Neutra, Plywood Demonstration House, Los Angeles,Thomas Hines, Neutras All-Plywood House: A Design for anFigure 32. Richard Neutra, Plywood Demonstration House, Los

Peltakian, Danielle

2012-01-01T23:59:59.000Z

268

Million U.S. Housing Units Total...............................  

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

Attached 2 to 4 Units Table HC2.12 Home Electronics Usage Indicators by Type of Housing Unit, 2005 5 or More Units Mobile Homes Type of Housing Unit Housing Units (millions)...

269

Assumptions to the Annual Energy Outlook 2001 - Macroeconomic Activity  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module 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. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module

270

Assumptions to the Annual Energy Outlook 1999 - Macroeconomic Activity  

Gasoline and Diesel Fuel Update (EIA)

macroeconomic.gif (5367 bytes) macroeconomic.gif (5367 bytes) 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. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065, (Washington, DC, February 1994).

271

Assumptions to the Annual Energy Outlook 2002 - Macroeconomic Activity  

Gasoline and Diesel Fuel Update (EIA)

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. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module

272

Assumptions to the Annual Energy Outlook 2000 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

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. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065, (Washington, DC, February 1994), plus Macroeconomic Activity Module (MAM): Kernel Regression Documentation of the National Energy Modeling System 1999, DOE/EIA-M065(99), Washington, DC, 1999).

273

A Statistical Analysis of the Dependency of Closure Assumptions in Cumulus Parameterization on the Horizontal Resolution  

Science Conference Proceedings (OSTI)

Simulated data from the UCLA cumulus ensemble model are used to investigate the quasi-universal validity of closure assumptions used in existing cumulus parameterizations. A closure assumption is quasi-universally valid if it is sensitive neither ...

Kuan-Man Xu

1994-12-01T23:59:59.000Z

274

SR Key Facts  

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

Key Facts Savannah River Site Budget FY 2011 Budget Summary FY 2011 SRS EM Program Budget Summary FY 2012 Presidential Budget Request for SRS FY 2014 SRS EM Budget Presentation...

275

Key masking using biometry  

Science Conference Proceedings (OSTI)

We construct an abstract model based on a fundamental similarity property, which takes into account parametric dependencies and reflects a specific collection of requirements. We consider a method for masking a cryptographic key using biometry, which ...

A. L. Chmora

2011-06-01T23:59:59.000Z

276

Key Emergency Information  

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

Key Emergency Information What to Do if an Emergency Arises DOE is committed to public safety in the event an emergency arises. You will likely be made aware that an emergency is...

277

Comparison of risk-dominant scenario assumptions for several TRU waste facilities in the DOE complex  

Science Conference Proceedings (OSTI)

In order to gain a risk management perspective, the DOE Rocky Flats Field Office (RFFO) initiated a survey of other DOE sites regarding risks from potential accidents associated with transuranic (TRU) storage and/or processing facilities. Recently-approved authorization basis documents at the Rocky Flats Environmental Technology Site (RFETS) have been based on the DOE Standard 3011 risk assessment methodology with three qualitative estimates of frequency of occurrence and quantitative estimates of radiological consequences to the collocated worker and the public binned into three severity levels. Risk Class 1 and 2 events after application of controls to prevent or mitigate the accident are designated as risk-dominant scenarios. Accident Evaluation Guidelines for selection of Technical Safety Requirements (TSRs) are based on the frequency and consequence bin assignments to identify controls that can be credited to reduce risk to Risk Class 3 or 4, or that are credited for Risk Class 1 and 2 scenarios that cannot be further reduced. This methodology resulted in several risk-dominant scenarios for either the collocated worker or the public that warranted consideration on whether additional controls should be implemented. RFFO requested the survey because of these high estimates of risks that are primarily due to design characteristics of RFETS TRU waste facilities (i.e., Butler-type buildings without a ventilation and filtration system, and a relatively short distance to the Site boundary). Accident analysis methodologies and key assumptions are being compared for the DOE sites responding to the survey. This includes type of accidents that are risk dominant (e.g., drum explosion, material handling breach, fires, natural phenomena, external events, etc.), source term evaluation (e.g., radionuclide material-at-risk, chemical and physical form, damage ratio, airborne release fraction, respirable fraction, leakpath factors), dispersion analysis (e.g., meteorological assumptions, distance to receptors, plume meander, deposition, and other factors affecting the calculated {chi}/Q), dose assessments (specific activities, inhalation dose conversion factors, breathing rates), designated frequency of occurrence, and risk assignment per the DOE Standard 3011 methodology. Information from the sites is being recorded on a spreadsheet to facilitate comparisons. The first response from Westinghouse Safety Management Solutions for the Savannah River Site (SRS) also provided a detailed analysis of the major differences in methods and assumptions between RFETS and SRS, which forms much of the basis for this paper. Other sites responding to the survey include the Idaho National Engineering and Environmental Laboratory (INEEL), Hanford, and the Los Alamos National Laboratory (LANL).

Foppe, T.L. [Foppe and Associates, Inc., Golden, CO (United States); Marx, D.R. [Westinghouse Safety Management Solutions, Inc., Aiken, SC (United States)

1999-06-01T23:59:59.000Z

278

Building Technologies Office: Housing Innovation Awards  

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

Housing Innovation Housing Innovation Awards to someone by E-mail Share Building Technologies Office: Housing Innovation Awards on Facebook Tweet about Building Technologies Office: Housing Innovation Awards on Twitter Bookmark Building Technologies Office: Housing Innovation Awards on Google Bookmark Building Technologies Office: Housing Innovation Awards on Delicious Rank Building Technologies Office: Housing Innovation Awards on Digg Find More places to share Building Technologies Office: Housing Innovation Awards on AddThis.com... About Take Action to Save Energy Partner With DOE Activities Solar Decathlon Building America Home Energy Score Home Performance with ENERGY STAR Better Buildings Neighborhood Program Challenge Home Partner Log In Become a Partner Criteria Partner Locator

279

Building Technologies Office: House Simulation Protocols Report  

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

House Simulation House Simulation Protocols Report to someone by E-mail Share Building Technologies Office: House Simulation Protocols Report on Facebook Tweet about Building Technologies Office: House Simulation Protocols Report on Twitter Bookmark Building Technologies Office: House Simulation Protocols Report on Google Bookmark Building Technologies Office: House Simulation Protocols Report on Delicious Rank Building Technologies Office: House Simulation Protocols Report on Digg Find More places to share Building Technologies Office: House Simulation Protocols Report on AddThis.com... About Take Action to Save Energy Partner With DOE Activities Solar Decathlon Building America Research Innovations Research Tools Building Science Education Climate-Specific Guidance Solution Center

280

Total U.S. Housing Units.......................................  

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

Census Division Total Northeast Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Million U.S. Housing Units...

Note: This page contains sample records for the topic "key assumptions housing" 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

" Million U.S. Housing Units"  

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

3 Lighting Usage Indicators by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2...

282

Total U.S. Housing Units.................................  

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

Housing Units (millions) Single-Family Units Apartments in Buildings With-- Space Heating Usage Indicators Million U.S. Housing Units Detached Attached Energy Information...

283

Total U.S. Housing Units.......................................  

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

Census Division Total Midwest Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Million U.S. Housing Units...

284

Total U.S. Housing Units.......................................  

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

New York Florida Texas California Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics U.S. Housing Units...

285

Total U.S. Housing Units.......................................  

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

(millions) Census Division Total South Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Million U.S. Housing Units...

286

" Million U.S. Housing Units"  

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

7 Air-Conditioning Usage Indicators by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2...

287

Wind-Driven House Fire, Texas, 2009  

Science Conference Proceedings (OSTI)

Wind-Driven House Fire, Texas 2009. ... Selected Publications. Simulation of the Dynamics of a Wind-Driven Fire in a Ranch-Style House - Texas. ...

2012-02-08T23:59:59.000Z

288

White House Office of Manufacturing Policy  

Science Conference Proceedings (OSTI)

... and private, federal, state, and regional. The White House Office of ... has directed the Manufacturing Extension Partnership (MEP) housed within the ...

2011-12-12T23:59:59.000Z

289

Case Study 1 - Ventilation in Manufactured Houses  

Science Conference Proceedings (OSTI)

... Ventilation in Manufactured Houses. ... fan operation, an outdoor air intake duct installed on the forced-air return, and whole house exhaust with and ...

290

Whole-House Ventilation | Department of Energy  

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

air quality. There are four basic mechanical whole-house ventilation systems -- exhaust, supply, balanced, and energy recovery. Comparison of Whole-House Ventilation Systems...

291

Public housing renovation : an opportunity for a better housing environment  

E-Print Network (OSTI)

The central hypothesis of this study is that the current renovation program of public housing projects is based on a predominantly physical perspective. Understanding the administrative and implementation aspects of the ...

Jordn F., Pablo (Jordn Fuchs)

1984-01-01T23:59:59.000Z

292

,"Housing Units1","Average Square Footage Per Housing Unit",...  

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

the U.S. Department of Energy's Office of Energy and Efficiency and Renewable Energy (EERE). 5Rented includes households that occupy their primary housing unit without payment of...

293

Role of the DAPIA in the manufactured housing process  

SciTech Connect

This paper describes the function of Design Approval Primary Inspection Agencies (DAPIAs) and provides some insights into the design approval process for manufacturing housing units. DAPIAs play a key role in assuring that the designs for manufactured housing units are in compliance with HUD's Manufactured Housing Constructing and Safety Standards. There are five DAPIAs performing plan checks and design reviews for the manufacturing operating in the Pacific Northwest region. The costs to a manufacturer for DAPIA services ranges from $100 to $250 to approve modifications to existing designs and $700 to $1200 to approve a totally new design. Each DAPIA indicated that they would be willing to work with BPA in some way to assist manufacturers produce units which can achieve MCS levels. They would be available for energy design consultation on an informal basis. In addition they would be willing to consider formal certifications of MCS designs if BPA develops evaluation criteria which they can apply.

Balistocky, S.; Lee, A.D.; Onisko, S.A.

1986-02-01T23:59:59.000Z

294

HOUSINGS AND MOUNTINGS FOR CENTRIFUGES  

DOE Patents (OSTI)

A protective housing for a gas centrifuge comprises a slidable connection between flanges and framework portions for absorbing rotational energy in case of bursting of the rotor and a sealing means for sealing the rotor chamber.

Rushing, F.C.

1960-08-16T23:59:59.000Z

295

ARM - Key Science Questions  

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

govScienceKey Science Questions govScienceKey Science Questions Science Research Themes Research Highlights Journal Articles Collaborations Atmospheric System Research (ASR) ARM Science Team Meetings User Meetings Annual Meetings of the Atmospheric System Research (ASR) Science Team and Fall Working Groups Accomplishments Read about the 20 years of accomplishments (PDF, 696KB) from the ARM Program and user facility. Performance Metrics ASR Metrics 2009 2008 2007 2006 Key Science Questions The role of clouds and water vapor in climate change is not well understood; yet water vapor is the largest greenhouse gas and directly affects cloud cover and the propagation of radiant energy. In fact, there may be positive feedback between water vapor and other greenhouse gases. Carbon dioxide and other gases from human activities slightly warm the

296

Housing Characteristics, 1990. [Contains glossary  

DOE Green Energy (OSTI)

This report on energy consumption in the residential sector covers the following topics: housing trends 1980--1990, new housing trends, availability and usage of natural gas by households, changes in appliance usage (refrigerators, entertainment appliances, cooking appliances, convenience appliances), age of major household appliances and equipment, household energy conservation activities, demand-side management programs, and a portrait of households using solar or wood as a source of energy.

Not Available

1992-05-14T23:59:59.000Z

297

Key Research Results Achievement  

E-Print Network (OSTI)

daylighting options for specific spaces with sample design layouts · Various HVAC system types that achieve%energysavingsovercode.NREL developedthesimulationtoolsandledthe committeethatproducedtheguides. Key Result TheAdvanced school in Greensburg, Kansas, used many of the energy efficiency measures outlined in the Advanced Energy

298

Environmental Degradation Nuclear IX-Housing Form  

Science Conference Proceedings (OSTI)

ENVIRONMENTAL DEGRADATION OF MATERIALS IN NUCLEAR POWER SYSTEMSWATER REACTORS. HOUSING. RESERVATION FORM.

299

STARTLINK COMPOSITE HOUSING J. A. Hutchinson1  

E-Print Network (OSTI)

only the addition of insulation to build houses. With appropriate insulation, a Startlink house has that link together using bolts and snap-fit connection to build houses rapidly. The material is almost unknown in the industry yet has remarkable properties well suited to house building: lower thermal

Mottram, Toby

300

White House Conference on Global Climate Change  

SciTech Connect

President Clinton has directed the White House office on Environmental Policy to coordinate an interagency process to develop a plan to fulfill the commitment he made in his Earth Day address on April 21, 1993. This plan will become the cornerstone of the Climate Change Plan that will be completed shortly after the Rio Accord enters into force. The Office on Environmental Policy established the Interagency Climate Change Mitigation Group to draw on the expertise of federal agencies including the National Economic Council; the Council of Economic Advisors; the Office of Science and Technology Policy; the Office of Management and Budget; the National Security Council; the Domestic Policy Council; the Environmental Protection Agency; and the Departments of Energy, Transportation, Agriculture, Interior, Treasury, Commerce, and State. Working groups have been established to examine six key policy areas: energy demand, energy supply, joint implementation, methane and other gases, sinks, and transportation. The purpose of the White House Conference on Global Climate Change was to ``tap the real-world experiences`` of diverse participants and seek ideas and information for meeting the President`s goals. During the opening session, senior administration officials defined the challenge ahead and encouraged open and frank conversation about the best possible ways to meet it.

Not Available

1993-11-01T23:59:59.000Z

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


301

The self-sufficient solar house Freiburg  

SciTech Connect

The Fraunhofer Institute for Solar Energy Systems has built a Self-Sufficient Solar House (SSSH) in Freiburg, Germany. The aim of the project is to provide the entire energy demand for heating, domestic hot water, electricity and cooking by the sun. The combination of highly efficient solar systems with conventional means to save energy is the key to the successful operation of the house. With transparent insulation of building walls utilizing winter insulation the heating demand of the building is almost zero. Small size seasonal high energy storage is accomplished by electrolysis of water and pressurized storage of hydrogen and oxygen. The energy for electricity and hydrogen generation is supplied by solar cells. Hydrogen can be reconverted to electricity with a fuel cell or used for cooking. It also serves as a back-up for low temperature heat. There are provisions for short-term storage of electricity and optimal routing of energy. The SSSH is occupied by a family. An intensive measurement program is being carried out. The data are used for the validation of the dynamic simulation calculations, which formed the basis for planning the SSSH. 28 refs., 42 figs., 9 tabs.

Goetzberger, A.; Stahl, W.; Bopp, G.; Heinzel, A.; Voss, K. [Fraunhofer-Institut fuer Solare Energie Systeme, Frieburg (Germany)

1994-12-31T23:59:59.000Z

302

President Obama Announces More Key Administration Posts | Department of  

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

More Key Administration Posts More Key Administration Posts President Obama Announces More Key Administration Posts July 8, 2011 - 12:00am Addthis THE WHITE HOUSE Office of the Press Secretary WASHINGTON - Today, President Barack Obama announced his intent to nominate the following individuals to key Administration posts: Michael A. Hammer, Assistant Secretary for Public Affairs, Department of State Charles McConnell, Assistant Secretary for Fossil Energy, Department of Energy The President also announced his intent to appoint the following individuals to key Administration posts: Terry Guen, Member, Advisory Council on Historic Preservation Dorothy T. Lippert, Member, Advisory Council on Historic Preservation Rosemary A. Joyce, Member, Cultural Property Advisory Committee President Obama said, "Our nation will be greatly served by the talent and

303

AP Key Accomplishments  

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

Recent Key Accomplishments Recent Key Accomplishments Reduction of Carbon Dioxide Mechanistic insight into CO2 hydrogenation Rapid Transfer of Hydride Ion from a Ruthenium Complex to C1 Species in Water Reversible Hydrogen Storage using CO2 and a Proton-Switchable Iridium Catalyst in Aqueous Media Nickel(II) Macrocycles: Highly Efficient Electrocatalysts for the Selective Reduction of CO2 to CO Calculation of Thermodynamic Hydricities and the Design of Hydride Donors for CO2 Reduction Mechanisms for CO Production from CO2 Using Re(bpy)(CO)3X Catalysts Hydrogen Production Biomass-derived electrocatalytic composites for hydrogen evolution Hydrogen-Evolution Catalysts Based on NiMo Nitride Nanosheets Water Oxidation Enabling light-driven water oxidation via a low-energy RuIV=O intermediate

304

Ceramic tile expansion engine housing  

DOE Patents (OSTI)

An expandable ceramic tile housing for a high temperature engine is disclosed wherein each tile is independently supported in place in an interlocking matrix by retention mechanisms which mechanically couple the individual ceramic tiles to an outer metal support housing while maintaining thermal isolation of the metal housing from the ceramic tiles. The ceramic tiles are formed with either an octagonal front face portion and a square shank portion or a square front face portion with an octagonal shank portion. The length of the sides of the octagonal front face portion on one tile is equal to the length of the sides of the square front face portion of adjoining tiles to permit formation of an interlocking matrix. Fibrous ceramic sealing material may be placed between radial and tangential facing surfaces of adjacent tiles to limit radial gas flow there between. Labyrinth-sealed pressure-controlled compartments may be established between the tile housing and the outer metal support housing to control radial gas flow. 8 figures.

Myers, B.

1995-04-11T23:59:59.000Z

305

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

Analysis: Studies in Residential Energy Demand. AcademicHousing Characteristics 1987, Residential Energy ConsumptionHousing Characteristics 1990, Residential Energy Consumption

Johnson, F.X.

2010-01-01T23:59:59.000Z

306

Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results  

E-Print Network (OSTI)

light bulbs having designated usage level in the average house. (3) Refrigerator marketlight bulbs having designated usage level in the average house. (3) Refrigerator market

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

307

A Review of Electric Vehicle Cost Studies: Assumptions, Methodologies, and Results  

E-Print Network (OSTI)

assumptions Battery costs and capacities: Lead acid batteryElectricity cost Battery cost and capacity: Lead acidElectricity cost Battery cost and capacity: N i C d

Lipman, Timothy

1999-01-01T23:59:59.000Z

308

HVAC Improvements for Existing Houses  

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

HVAC Improvements for Existing Houses HVAC Improvements for Existing Houses Speaker(s): Chryséis Bovagnet Date: September 5, 2002 - 12:00pm Location: Bldg. 90 Many older houses in the US are either not well designed from a thermal point of view or have HVAC (Heating Ventilation and Air Conditioning) systems in need of repairs or improvements. The building envelopes tend to have poor insulation and lots of leakage, and the HVAC systems are inefficient. The cooling/heating equipment is often located outside of the conditioned space (e.g. in attics or crawlspaces) with ducts that leak and have poor insulation, which cause energy loss and bad occupant comfort on peak days or in extreme climates. We developed a series of retrofits that will allow us to reduce the energy consumption of residential HVAC

309

Amazing furnace-free house  

Science Conference Proceedings (OSTI)

A new 24,450 ft/sub 2/ house is described which has the following features: (1) 100% solar heating in a 6500 degree-day climate; (2) a greenhouse which never drops below 32/sup 0/F; (3) steady fresh air inflow; (4) building costs comparable to conventional homes of the same size; (5) roof solar collector and high temperature attic thermal storage; (6) a Solar Staircase which controls seasonal insolation; (7) a rock bin (100 ton) for low temperature storage; and (8) durability with low maintenance. The design features necessary to obtain the above criteria are discussed as well as the operation of the house for winter and summer use. An air moving system (fan plus ducts) is an essential part of the house. (MJJ)

Shurcliff, W.A.

1982-11-01T23:59:59.000Z

310

On-site Housing Rates | Staff Services  

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

Rates Rates Effective February 1, 2013 Rates for Occupancy < 30-Days Guest House* Single/Double: US $105.00/day Housekeeping service is provided on all working days. *Alternatives to the Guest House - When family-type accommodations are assigned to temporary or transient personnel, Guest House rates as set forth above will apply. The total will not exceed one months' rent for a unit occupied for 30 days or less. When such assignment is necessary due to lack of adequate Guest House accommodations, housekeeping service is provided on working days; for reservations staying seven days or less. Residence Houses Curie House: US $42.00/day Cavendish House: US $42.00/day Compton House: US $42.00/day Housekeeping service for all residence houses are provided three times per

311

Cryptographic Key Management Workshop 2012  

Science Conference Proceedings (OSTI)

Cryptographic Key Management Workshop 2012. Purpose: NIST is conducting a two-day Key Management Workshop on September 10-11. ...

2013-08-01T23:59:59.000Z

312

House Report 108-576, FY 2005 House Report for Commerce ...  

Science Conference Proceedings (OSTI)

*. Bookmark and Share. Taken from House Report 108-576, FY 2005 House Report for Commerce, Justice, and State Appropriations bill. ...

2010-10-05T23:59:59.000Z

313

Rising House Prices and Monetary Policy  

E-Print Network (OSTI)

Abstract. It is argued that the recent rise in house prices is the biggest nancial asset price boom in history. In this note, I look at how house prices are determined and how house price bubbles can occur. I discuss whether the recent increase in house prices is a bubble, whether monetary policy can cause a rise in the price of houses relative to other goods and what central banks should do in response to house price bubbles. Finally, I consider how central banks should take account of house prices in the price index used by central banks to measure ination. According to the Economist, the rise in housing prices in developed countries in the last ve years is the biggest bubble in history, with the total value of residential properties increasing by more than $30 trillion: an amount roughly equal to to developed countries combined annual GDPs. 1 This compares with the global stockmarket boom of the late 1990s where the ve-year increase was equal to about 80 percent of annual GDP. 2 1. How are House Prices Determined? Before proceeding with an analysis of the relationship between monetary policy and the house price boom, it is useful to consider how house prices are determined and how a house price bubble might arise. To keep matters simple, I abstract from uncertainty, depreciation and transactions costs. Consider a household deciding whether to rent or to buy a house in period t. If the household rents the house it pays the time-t rent, denoted by Q(t). If it purchases the house it pays the time-t house price, denoted by Ph (t). If it opted to purchase, rather than rent, then at the start of period t + 1 the household owns a house worth Ph (t + 1): The value to the household in period t of an amount Ph (t + 1) received in period t + 1

Anne Sibert

2005-01-01T23:59:59.000Z

314

Occupancy Simulation in Three Residential Research Houses  

Science Conference Proceedings (OSTI)

Three houses of similar floor plan are being compared for energy consumption. The first house is a typical builder house of 2400 ft2 (223 m2) in east Tennessee. The second house contains retrofits available to a home owner such as energy efficient appliances, windows and HVAC, as well as an insulated attic which contains HVAC duct work. The third house was built using optimum-value framing construction with photovoltaic modules and solar water heating. To consume energy researchers have set up appliances, lights, and plug loads to turn on and off automatically according to a schedule based on the Building America Research Benchmark Definition. As energy efficiency continues to be a focus for protecting the environment and conserving resources, experiments involving whole house energy consumption will be done. In these cases it is important to understand how to simulate occupancy so that data represents only house performance and not human behavior. The process for achieving automated occupancy simulation will be discussed. Data comparing the energy use of each house will be presented and it will be shown that the third house used 66% less and the second house used 36% less energy than the control house in 2010. The authors will discuss how energy prudent living habits can further reduce energy use in the third house by 23% over the average American family living in the same house.

Boudreaux, Philip R [ORNL; Gehl, Anthony C [ORNL; Christian, Jeffrey E [ORNL

2012-01-01T23:59:59.000Z

315

Evaluation of Affordable Prototype Houses at Two Levels of Energy Efficiency  

DOE Green Energy (OSTI)

Two high performance prototype houses were built in Carbondale, Colorado, as part of the U.S. Department of Energy's Building America (BA) Program. Each prototype was a 1256 ft2 (117 m2), 1-story, 3-bedroom house, and met the local requirements for affordable housing. The National Renewable Energy Laboratory (NREL) performed short-term field testing and DOE-2.2 simulations in support of this project at the end of December 2004. We also installed long-term monitoring equipment in one of the houses, and are currently tracking the performance of key building systems under occupied conditions. One of the houses (designated H1) included a package of cost-effective energy efficiency features that placed it well above the Energy Star level, targeting a Home Energy Rating System (HERS) score of 88-89. The other (designated H2) was a BA research house, targeting a HERS score of 94-95, and 45% whole-house energy savings compared to the BA Benchmark. Preliminary results from the field evaluation indicate that the energy savings for both houses will exceed the design targets established for the project, although the performance of certain building systems, including the ventilation and foundation systems, leave some room for improvement.

Hendron, R.; Barker, G.; Hancock, E.; Reeves, P.

2006-10-01T23:59:59.000Z

316

Before House Natural Resources Committee | Department of Energy  

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

House Natural Resources Committee Before House Natural Resources Committee Before House Natural Resources Committee By: Lauren Azar, Senoir Advisor to Secretary Chu Subject:...

317

Before House Subcommittee on Energy and Power - Committee on...  

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

House Subcommittee on Energy and Power - Committee on Energy and Commerce Before House Subcommittee on Energy and Power - Committee on Energy and Commerce Before House Subcommittee...

318

Statement of Patricia Hoffman before the United States House...  

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

before the United States House of Representatives House Appropriations Subcommittee on Energy and Water Development Statement of Patricia Hoffman before the United States House of...

319

Before the House Armed Services Subcommittee on Strategic Forces...  

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

House Armed Services Subcommittee on Strategic Forces Before the House Armed Services Subcommittee on Strategic Forces Before the House Armed Services Subcommittee on Strategic...

320

Before House Committee on Oversight and Government Reform | Department...  

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

House Committee on Oversight and Government Reform Before House Committee on Oversight and Government Reform Before House Committee on Oversight and Government Reform By: Secretary...

Note: This page contains sample records for the topic "key assumptions housing" 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

White House Initiative on Historically Black Colleges and Universities...  

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

White House Initiative on Historically Black Colleges and Universities White House Initiative on Historically Black Colleges and Universities How WHI-HBCU are ran White House...

322

Before the House Subcommittee on Energy and Power - Committee...  

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

the House Subcommittee on Energy and Power - Committee on Energy and Commerce Before the House Subcommittee on Energy and Power - Committee on Energy and Commerce Before the House...

323

Before House Subcommittee on Water and Power - Committee on Natural...  

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

House Subcommittee on Water and Power - Committee on Natural Resources Before House Subcommittee on Water and Power - Committee on Natural Resources Before House Subcommittee on...

324

Before the House Science and Technology Subcommittee on Energy...  

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

House Science and Technology Subcommittee on Energy and Environment Before the House Science and Technology Subcommittee on Energy and Environment Before the House Science and...

325

Before the Subcommittee on Energy and Power -- House Energy and...  

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

- House Energy and Commerce Committee Before the Subcommittee on Energy and Power -- House Energy and Commerce Committee Before the Subcommittee on Energy and Power -- House Energy...

326

Million U.S. Housing Units Total............................................................................  

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

Attached Attached 2 to 4 Units Table HC2.12 Home Electronics Usage Indicators by Type of Housing Unit, 2005 5 or More Units Mobile Homes Type of Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Home Electronics Usage Indicators Detached Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units Attached 2 to 4 Units Table HC2.12 Home Electronics Usage Indicators by Type of Housing Unit, 2005 5 or More Units Mobile Homes Type of Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Home Electronics Usage Indicators Detached Status of PC When Not in Use Left On..............................................................

327

California Housing Trends: Implications for Transportation Planning  

E-Print Network (OSTI)

Constraints 1997-2020, Department of Housing and Communitymore people means more housing needs. By 2020, the state ishousing on by the year 2010. Consequently by the year 2020,

Shirgaokar, Manish; Deakin, Elizabeth

2001-01-01T23:59:59.000Z

328

" Million U.S. Housing Units"  

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

"Table HC14.3 Household Characteristics by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division"...

329

" Million U.S. Housing Units"  

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

"Table HC10.3 Household Characteristics by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Household Characteristics",,"No...

330

Please transfer ALL data off /house  

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

Please transfer ALL data off house before 1212013 Please transfer ALL data off house September 3, 2013 by Kjiersten Fagnan (0 Comments) We are happy to announce that all the...

331

THE WHITE HOUSE | Department of Energy  

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

THE WHITE HOUSE THE WHITE HOUSE More Documents & Publications Progress Report on U.S.-China Energy Cooperation US-China clean energy report US-ChinaFactSheetElectricVehicles....

332

Advanced housing materials for extreme space applications  

Science Conference Proceedings (OSTI)

Thermal stresses have a significant impact on the mechanical integrity and performance of RF hybrid circuits. To minimize this impact, a series of spray deposited Si-Al alloys were evaluated for use in electronic housing applications. Current housings ...

Linda Del Castillo; James P. Hoffman; Gaj Birur

2011-03-01T23:59:59.000Z

333

The Malay house : rationale and change  

E-Print Network (OSTI)

The Malay house is defined and described in the Malaysian context . Underlying principles or rules that make up the house are derived from the analysis of its physical, spatial and functional elements and the variations ...

Wan Abidin, Wan Burhanuddin B

1981-01-01T23:59:59.000Z

334

Before the House Transportation and Infrastructure Subcommittee...  

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

Transportation and Infrastructure Subcommittee on Economic Development, Public Buildings, and Emergency Management Before the House Transportation and Infrastructure Subcommittee...

335

CAST SHOP TECHNOLOGY: V: Cast House Safety  

Science Conference Proceedings (OSTI)

TMS Logo. 1997 TMS Annual Meeting: Wednesday Session. CAST SHOP TECHNOLOGY: Session V: Cast House Safety. Sponsored by: LMD Aluminum...

336

US Commerce Secretary, White House Cybersecurity ...  

Science Conference Proceedings (OSTI)

Watch Webcast Today: US Commerce Secretary Gary Locke, White House Cybersecurity Coordinator Howard A. Schmidt to Visit Silicon Valley to ...

2011-01-11T23:59:59.000Z

337

White House Statement - 2000 Baldrige Awards  

Science Conference Proceedings (OSTI)

THE WHITE HOUSE Office of the Press Secretary. President Clinton Announces Winners of 2000 Baldrige Award. For Immediate ...

2011-07-13T23:59:59.000Z

338

US Commerce Secretary Gary Locke, White House ...  

Science Conference Proceedings (OSTI)

US Commerce Secretary Gary Locke, White House Cybersecurity Coordinator Howard A. Schmidt Announce Next Steps to Enhance Online ...

2011-01-10T23:59:59.000Z

339

House Report 109-118 NIST Appropriations  

Science Conference Proceedings (OSTI)

... House Report 109-118 - SCIENCE, STATE, JUSTICE, COMMERCE, AND RELATED AGENCIES APPROPRIATIONS BILL, FISCAL YEAR 2006. ...

2010-10-05T23:59:59.000Z

340

The Dow Chemical Company - NA System House ...  

Science Conference Proceedings (OSTI)

The Dow Chemical Company - NA System House - Wilmington. NVLAP Lab Code: 100210-0. Address and Contact Information: ...

2013-09-27T23:59:59.000Z

Note: This page contains sample records for the topic "key assumptions housing" 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

Sustainability: Economics, Lifecycle Analysis, Green House Gases ...  

Science Conference Proceedings (OSTI)

Report on Linking Transformational Materials and Processing for Energy and ... LIFECYCLE ANALYSIS, GREEN HOUSE GASES, AND CLIMATE CHANGE...

342

Solar energy systems for manufactured housing  

DOE Green Energy (OSTI)

The opportunities for solar energy utilization in manufactured housing such as mobile homes and modular homes are discussed. The general characteristics of the manufactured housing industry are described including market and prices. Special problems of the utilization of liquid heating collectors, air heating collectors, or passive types of solar heating systems in manufactured housing are considered. The market situation for solar energy in manufactured housing is discussed. The design of the Los Alamos Scientific Laboratory mobile/modular home is described.

Balcomb, J.D.

1976-01-01T23:59:59.000Z

343

Essays on the household-level effects of house price growth  

E-Print Network (OSTI)

Constructing measures of house price variance . . . . 2.4.4Flip That House? House Price Dynamics and Housing InvestmentHouse Price Data . . . . . . . . . . . . . . . . . . . . .

Sitgraves, Claudia Ayanna

2009-01-01T23:59:59.000Z

344

Edition Two, October 2009 Welcome to HOUSES!  

E-Print Network (OSTI)

, interpretation and analysis of the residential property market: Editorial ­ page 3 We all know that house prices for potential buyers. Feature article - House price indices - page 5 In each edition we focus on a contemporary topic of relevance to the property market. In this edition we describe how the different house price

Evans, Paul

345

Chicagoland Single-Family Housing Characterization  

Science Conference Proceedings (OSTI)

In this report, the PARR team identifies housing characteristics and energy use for fifteen housing types (groups) in the Chicagoland (Cook County, Illinois) region and specifies measure packages that provide an optimum level of energy savings based on a BEopt analysis. The analysis is based on assessor data and actual energy consumption data on 432,605 houses representing approximately 30% of the population.

Spanier, J.; Scheu, R.; Brand, L.; Yang, J.

2012-06-01T23:59:59.000Z

346

Puerto Rico House Tours Report  

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

team of Universidad de Puerto Rico is planning to present team of Universidad de Puerto Rico is planning to present the most interesting tour in Washington. The purpose and the message of the competition, the pride that the team has for their work, their house and their country are the elements that will be combined in order to give all the visitors an amazing and unique experience. The team will communicate through the tours the importance of renewable energy. The Delegation from Puerto Rico is going to show and explain their design in a accurate way, all the features and its benefits. The house tours will serve as a tool to persuade the people to believe in team's mission: To create societal consciousness about the sun as a technological, renewable, clean and feasible source of energy to satisfy present and

347

Remotely serviced filter and housing  

DOE Patents (OSTI)

A filter system for a hot cell comprises a housing adapted for input of air or other gas to be filtered, flow of the air through a filter element, and exit of filtered air. The housing is tapered at the top to make it easy to insert a filter cartridge holds the filter element while the air or other gas is passed through the filter element. Captive bolts in trunnion nuts are readily operated by electromechanical manipulators operating power wrenches to secure and release the filter cartridge. The filter cartridge is adapted to make it easy to change a filter element by using a master-slave manipulator at a shielded window station. 6 figs.

Ross, M.J.; Zaladonis, L.A.

1987-07-22T23:59:59.000Z

348

The self-sufficient solar house in Freiburg  

Science Conference Proceedings (OSTI)

The Fraunhofer Institute for Solar Energy Systems has built a completely self-sufficient solar house (SSSH) in Freiburg, Germany. The entire energy demand for heating, domestic hot water, electricity, and cooking is supplied by the sun. The combination of highly efficient solar systems with conventional means to save energy is the key to the successful operation of the house. Seasonal energy storage is accomplished by electrolysis of water and pressurized storage of hydrogen and oxygen. The energy for electricity and hydrogen generation is supplied by solar cells. Hydrogen can be reconverted to electricity with a fuel cell or using for cooking. It also serves as a back-up for low temperature heat. There are provisions for short term storage of electricity and optimal routing of energy. The SSSH is occupied by a family. An intensive measurement program is being carried out. The data are used for the validation of the dynamic simulation calculations, which formed the basis for planning the SSSH.

Stahl, W.; Voss, K.; Goetzberger, A. (Fraunhofer-Institut fuer Energiesysteme, Freiburg (Germany))

1994-01-01T23:59:59.000Z

349

Evergreen Sustainable Development Standard for Affordable Housing |  

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

Evergreen Sustainable Development Standard for Affordable Housing Evergreen Sustainable Development Standard for Affordable Housing Evergreen Sustainable Development Standard for Affordable Housing < Back Eligibility Low-Income Residential Savings Category Heating & Cooling Commercial Heating & Cooling Heating Home Weatherization Commercial Weatherization Sealing Your Home Cooling Appliances & Electronics Construction Design & Remodeling Ventilation Heat Pumps Commercial Lighting Lighting Water Heating Solar Buying & Making Electricity Program Info State District of Columbia Program Type Green Building Incentive Provider Housing Trust Fund The Washington State Department of Commerce created the Evergreen Sustainable Development Standard, a set of green building criteria that is required for any affordable housing project applying for state funds

350

House Report 107-218, TA Report Language  

Science Conference Proceedings (OSTI)

*. Bookmark and Share. Taken from House Report 107-218 FY 2003 Commerce, Justice, State Appropriations House Report. ...

2010-10-05T23:59:59.000Z

351

Heterogeneous Correlation Modeling Based on the Wavelet Diagonal Assumption and on the Diffusion Operator  

Science Conference Proceedings (OSTI)

This article discusses several models for background error correlation matrices using the wavelet diagonal assumption and the diffusion operator. The most general properties of filtering local correlation functions, with wavelet formulations, are ...

Olivier Pannekoucke

2009-09-01T23:59:59.000Z

352

Microwave Properties of Ice-Phase Hydrometeors for Radar and Radiometers: Sensitivity to Model Assumptions  

Science Conference Proceedings (OSTI)

A simplified framework is presented for assessing the qualitative sensitivities of computed microwave properties, satellite brightness temperatures, and radar reflectivities to assumptions concerning the physical properties of ice-phase ...

Benjamin T. Johnson; Grant W. Petty; Gail Skofronick-Jackson

2012-12-01T23:59:59.000Z

353

House Simulation Protocols Report | Department of Energy  

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

Residential Buildings » Building America » House Simulation Residential Buildings » Building America » House Simulation Protocols Report House Simulation Protocols Report This image shows a cover of a report titled Building America House Simulation Protocols. The Building America logo is shown in the lower left corner of the report cover. Building America's House Simulation Protocols report is designed to assist researchers in tracking the progress of multiyear, whole-building energy reduction against research goals for new and existing homes. These protocols are preloaded into BEopt and use a consistent approach for defining a reference building, so that all projects can be compared to each other. The steps involved in conducting performance analysis include: Defining the appropriate reference building Various climate regions, house sizes, and house ages require slightly

354

Whole-House Ventilation | Department of Energy  

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

Whole-House Ventilation Whole-House Ventilation Whole-House Ventilation May 30, 2012 - 2:37pm Addthis A whole-house ventilation system with dedicated ducting in a new energy-efficient home. | Photo courtesy of ©iStockphoto/brebca. A whole-house ventilation system with dedicated ducting in a new energy-efficient home. | Photo courtesy of ©iStockphoto/brebca. What does this mean for me? Whole-house ventilation is critical in an energy-efficient home to maintain adequate indoor air quality and comfort. The whole-house ventilation system you choose will depend upon your climate, budget, and the availability of experienced contractors in your area. Energy-efficient homes -- both new and existing -- require mechanical ventilation to maintain indoor air quality. There are four basic mechanical

355

Our Hand in Greening the White House  

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

Our Hand in Greening the White House (See also the Greening of Our House) "For as long as I live in the White House, I want Americans to see it not only as a symbol of clean government, but also a clean environment. We're going to identify what it takes to make the White House a model for efficiency and waste reduction, and then we're going to get the job done. . . Before I can ask you to do the best you can in your house, I ought to make sure I'm doing the best I can in my house." -President Bill Clinton, Earth Day, 1994 In an effort to provide leadership by example, the Greening of the White House project is bringing new technology, enlightened operations and management practices, and revised procurement procedures to the First Residence. Modern information technologies (e.g., multimedia) will make

356

Are American Homeowners Locked Their Houses? The Impact of Housing  

E-Print Network (OSTI)

U.S. policymakers are concerned that negative home equity arising from the severe housing market decline may be constraining geographic mobility and consequently serving as a factor in the nations persistently high unemployment rate. Indeed, the widespread drop in house prices since 2007 has increased the share of homeowners who are underwater on their mortgages. At the same time, migration across states and among homeowners has fallen sharply. Using a logistic regression framework to analyze data from the Internal Revenue Service on state-to-state migration between 2006 and 2009, the authors discover evidence that house lock decreases mobility but find it has a negligible impact on the national unemployment rate. A one-standard deviation increase in the share of underwater nonprime households in the origin state reduces the outflow of migrants from the origin to the destination state by 2.9 percent. When aggregated across the United States, this decrease in mobility reduces the national state-to-state migration rate by 0.05 percentage points, resulting in roughly 110,000 to 150,000 fewer individuals migrating across state lines in any given year. Assuming that all of these discouraged migrants were job-seekers who were previously unemployed before relocating and then found a job in their new state would reduce the nations unemployment rate by at most one-tenth of a percentage point in a given year. The cumulative effect over this period would yield an unemployment rate of 9.0 percent

Alicia Sasser Modestino; Julia Dennett

2011-01-01T23:59:59.000Z

357

Annual housing survey: 1978. United States and regions. Part F. Energy-related housing characteristics  

SciTech Connect

This report presents statistics on energy - related housing characteristics from the 1978 Annual Housing Survey for the United States by inside and outside standard metropolitan statistical areas. Tables provide data on fuel, fuel cost, heating, air conditioning, insulation, and transportation characteristics. In addition, they present figures on the income of families and individuals by energy - related housing characteristics; the value of owner - occupied housing units and the gross rent of renter - occupied housing units by energy - related housing characteristics; the monthly and yearly costs paid for utilities; and the number of rooms per housing unit by energy - related housing characteristics. Data on energy - related housing characteristics are also given for Black and Spanish heads of households. Appendices describe the geographic area classifications; provide definitions and explanations of the subjects covered in the report; and present information on sample design, estimation, and accuracy of the data. Area maps are included.

Not Available

1981-08-01T23:59:59.000Z

358

Before the Subcommittee on Energy -- House Science, Space, and Technology  

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

-- House Science, Space, and -- House Science, Space, and Technology Committee Before the Subcommittee on Energy -- House Science, Space, and Technology Committee Before the Subcommittee on Energy -- House Science, Space, and Technology Committee Testimony of Christopher Smith, Acting Assistant Secretary Before the Subcommittee on Energy -- House Science, Space, and Technology Committee More Documents & Publications Before the Subcommittee on Energy -- House Science, Space, and Technology Committee Before the Subcommittee on Environment and the Economy -- House Energy and Commerce Committee Before the Subcommittee on Energy -- House Science, Space, and Technology Committee Before the Subcommittee on Energy and Power -- House Energy and Commerce Committee Before the Subcommittees on Energy and Environment - House Committee on

359

TinyEARS: spying on house appliances with audio sensor nodes  

Science Conference Proceedings (OSTI)

Fine-grained awareness on how and where energy is spent is being increasingly recognized as the key to conserve energy. While several solutions to monitor the energy consumption patterns for commercial and industrial users exist, energy reporting systems ... Keywords: audio data classification, energy monitoring, house appliances, wireless audio sensor networks

Z. Cihan Taysi; M. Amac Guvensan; Tommaso Melodia

2010-11-01T23:59:59.000Z

360

Housing Innovation Awards at the Solar Decathlon  

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

Housing Innovation Awards at the Solar Decathlon Housing Innovation Awards at the Solar Decathlon Breakfast Presented by BASF Friday, October 4, 2013 8:30-10:30 a.m. Historic Hanger 244 Orange County Great Park in Irvine, CA Friday, October 4, 2013 8:30 AM-10:30 PM 2 | INNOVATION & INTEGRATION: Transforming the Energy Efficiency Market Buildings.Energy.gov Housing Innovation Awards Christine Barbour Master of Ceremonies 3 | INNOVATION & INTEGRATION: Transforming the Energy Efficiency Market Buildings.Energy.gov Housing Innovation Awards 4 | INNOVATION & INTEGRATION: Transforming the Energy Efficiency Market Buildings.Energy.gov Thank you for making the Housing Innovation Awards breakfast possible! Housing Innovation Awards 5 | INNOVATION & INTEGRATION: Transforming the Energy Efficiency Market Buildings.Energy.gov

Note: This page contains sample records for the topic "key assumptions housing" 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

All Electric Houses in Cold Climates  

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

Electric Houses Electric Houses in Cold Climates Duncan Prahl, RA IBACOS BA Tech Update, April 29, 2013 Denver CO All Electric Houses in Cold Climates Caveats About Me: * I'm an Architect * I love math and science, but I'm not going to marry it * My engineering skills are primarily based on osmosis and graphics * "Close enough is good enough" All Electric Houses in Cold Climates Utility Unbundling * True costs becoming "transparent" * Allows for next level of analysis * Cash flow, Total Cost of Ownership All Electric Houses in Cold Climates Martha's Vineyard Community Images courtesy South Mountain Company All Electric Houses in Cold Climates Specifications Building System Specification Below Slab R-20 extruded polystyrene (XPS) foam Foundation Walls R-20 poly iso foam

362

Housing Innovation Awards | Department of Energy  

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

Housing Innovation Awards Housing Innovation Awards Housing Innovation Awards Photo of a line of Housing Innovation Awards statues lined up on a table. The U.S. Department of Energy's Housing Innovation Awards recognize the very best in innovation on the path to zero net-energy ready homes. The awards, presented on October 4, 2013, at a breakfast ceremony during the U.S. Department of Energy (DOE) Solar Decathlon 2013 in Irvine, CA, showcase a number of the Building Technologies Office residential programs under one umbrella event. DOE Challenge Home Builder Awards Orange Arrow Presented to DOE Challenge Home builders who are leading a major housing industry transformation to zero net-energy ready homes. The DOE Challenge Home designation is the symbol of excellence in home building. Only a

363

Background on Quantum Key Distribution  

Science Conference Proceedings (OSTI)

... Background on Quantum Key Distribution. ... If someone, referred to by cryptographers as Eve, tries to eavesdrop on the transmission, she will not ...

2011-08-02T23:59:59.000Z

364

Building America Top Innovations Hall of Fame Profile … Moisture and Ventilation Solutions in Hot, Humid Climates: Florida Manufactured Housing  

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

Duct leakage was a key factor in moisture Duct leakage was a key factor in moisture damage in manufactured homes in humid climates. BUILDING AMERICA TOP INNOVATIONS HALL OF FAME PROFILE INNOVATIONS CATEGORY: 2. House-as-a-System Solutions 2.1 New Homes with Whole-House Packages Moisture and Ventilation Solutions in Hot, Humid Climates: Florida Manufactured Housing Research by Building America diagnosed the causes and prescribed a cure that dramatically reduced moisture problems in manufactured housing in Florida. In the late 1990s, Building America researchers at the Florida Solar Energy Center (FSEC) worked with manufactured home builders to diagnose moisture problems in homes in Florida. Moisture issues were so severe that in some homes researchers could push their fingers through the saturated drywall. Using a

365

Greening Project Status Report: The White House  

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

White House Prepared for the U.S. Department of Energy Federal Energy Management Program April 2001 Contents Page 1. Introduction......

366

Before the House Subcommittee on Investigations & Oversight ...  

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

& Oversight - Committee on Science, Space, and Technology Before the House Subcommittee on Investigations & Oversight - Committee on Science, Space, and Technology Testimony of...

367

Building Technologies Office: House Simulation Protocols Report  

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

Protocols Report This image shows a cover of a report titled "Building America House Simulation Protocols." The Building America logo is shown in the lower left corner of...

368

Improving air handler efficiency in houses  

E-Print Network (OSTI)

of different blade design and fan to housing clearances forimprovements, such as fan blade and cabinet design are hardequipment design (not putting large fans in small cabinets).

Walker, Iain S.

2004-01-01T23:59:59.000Z

369

PRELIMINARY DATA Housing Unit and Household Characteristics  

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

PRELIMINARY DATA Housing Unit and Household Characteristics RSE Column Factor: Total Households (million) Households With Fans (million) Percent of Households With Fans Number of...

370

U.S. Residential Housing Primary  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities >Table 7c Glossary U.S. Residential Housing Primary Page Last Revised: July 2009

371

" Million U.S. Housing Units"  

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

Consumption Survey. " " Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables" "Table HC8.4 Space Heating...

372

Building Magazine Article: A House & a Laboratory  

Science Conference Proceedings (OSTI)

... solar energy To 120/240 volT power anD pass ... Tw also installed a rubber membrane weather barrier system that helped seal the house. ...

2013-11-04T23:59:59.000Z

373

California Housing Trends: Implications for Transportation Planning  

E-Print Network (OSTI)

Publications Office, Sacramento, CA. Committee on HousingOffice of Research, Sacramento, CA, 1999. Elliott, J. ,Office of Research, Sacramento, CA. Senate Publications,

Shirgaokar, Manish; Deakin, Elizabeth

2001-01-01T23:59:59.000Z

374

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

Gasoline and Diesel Fuel Update (EIA)

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

375

Index Revision, House Price Risk, and the Market for House Price Derivatives  

E-Print Network (OSTI)

bias in repeat-sales home price indices. Freddie Mac workingpaper #0503. Index Revision, House Price Risk, and theMarket for House Price Derivatives Calhoun, C. A. (1996).

Deng, Yongheng; Quigley, John M.

2008-01-01T23:59:59.000Z

376

Exploring the enabling approach to housing through the Abuja Mass Housing Scheme  

E-Print Network (OSTI)

The magnitude of the housing problem in Nigeria is immense; the current deficit is around 12 to 16 million units. Government attempts to address housing availability has been a recurring theme throughout Nigeria's history. ...

Umoh, Nse (Nseabasi Effiong)

2012-01-01T23:59:59.000Z

377

On the use of the parabolic concentration profile assumption for a rotary desiccant dehumidifier  

SciTech Connect

The current work describes a model for a desiccant dehumidifier which uses a parabolic concentration profile assumption to model the diffusion resistance inside the desiccant particle. The relative merits of the parabolic concentration profile model compared with widely utilized rotary desiccant wheel models are discussed. The periodic steady-state parabolic concentration profile model developed is efficient and can accommodate a variety of materials. These features make it an excellent tool for design studies requiring repetitive desiccant wheel simulations. A quartic concentration profile assumption was also investigated which yielded a 2.8 percent average improvement in prediction error over the parabolic model.

Chant, E.E. [Univ. of Turabo, Gurabo (Puerto Rico); Jeter, S.M. [Georgia Inst. of Technology, Atlanta, GA (United States). George W. Woodruff School of Mechanical Engineering

1995-02-01T23:59:59.000Z

378

Sensitivity of Rooftop PV Projections in the SunShot Vision Study to Market Assumptions  

Science Conference Proceedings (OSTI)

The SunShot Vision Study explored the potential growth of solar markets if solar prices decreased by about 75% from 2010 to 2020. The SolarDS model was used to simulate rooftop PV demand for this study, based on several PV market assumptions--future electricity rates, customer access to financing, and others--in addition to the SunShot PV price projections. This paper finds that modeled PV demand is highly sensitive to several non-price market assumptions, particularly PV financing parameters.

Drury, E.; Denholm, P.; Margolis, R.

2013-01-01T23:59:59.000Z

379

Partnership in key exchange protocols  

Science Conference Proceedings (OSTI)

In this paper, we investigate the notion of partnership as found in security models for key exchange protocols. Several different approaches have been pursued to define partnership, with varying degrees of success. We aim to provide an overview and criticism ... Keywords: key exchange, partnership, session identifier

Kazukuni Kobara; Seonghan Shin; Mario Strefler

2009-03-01T23:59:59.000Z

380

Statement of Patricia Hoffman before the United States House of  

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

before the United States House of before the United States House of Representatives House Appropriations Subcommittee on Energy and Water Development Statement of Patricia Hoffman before the United States House of Representatives House Appropriations Subcommittee on Energy and Water Development Statement of Patricia Hoffman before the United States House of Representatives House Appropriations Subcommittee on Energy and Water Development to appear before you today to discuss the President's Fiscal Year (FY) 2012 budget request for the Department of Energy's (DOE) Office of Electricity Delivery and Energy Reliability (OE). Statement of Patricia Hoffman before the United States House of Representatives House Appropriations Subcommittee on Energy and Water Development More Documents & Publications

Note: This page contains sample records for the topic "key assumptions housing" 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

Biennial Assessment of the Fifth Power Plan Gas Turbine Power Plant Planning Assumptions  

E-Print Network (OSTI)

Biennial Assessment of the Fifth Power Plan Gas Turbine Power Plant Planning Assumptions October 17, 2006 Simple- and combined-cycle gas turbine power plants fuelled by natural gas are among the bulk-emission and efficient gas turbine technology made combined-cycle gas turbine power plants the "resource of choice

382

External review of the thermal energy storage (TES) cogeneration study assumptions. Final report  

DOE Green Energy (OSTI)

This report is to provide a detailed review of the basic assumptions made in the design, sizing, performance, and economic models used in the thermal energy storage (TES)/cogeneration feasibility studies conducted by Pacific Northwest Laboratory (PNL) staff. This report is the deliverable required under the contract.

Lai, B.Y.; Poirier, R.N. [Chicago Bridge and Iron Technical Services Co., Plainfield, IL (United States)

1996-08-01T23:59:59.000Z

383

Innovative Manufactured Housing Urban Design Demonstration Project  

Science Conference Proceedings (OSTI)

One quarter of the new houses sold in the United States in 1999 were manufactured homes, and manufactured housing represents an important and growing market for power producers. One niche market opportunity for manufactured homes is in urban areas. EPRI facilitated the completion of two limited demonstrations of energy efficient manufactured homes designed specifically for urban neighborhoods.

2000-10-05T23:59:59.000Z

384

Open house: interaction as critical reflection  

Science Conference Proceedings (OSTI)

This paper describes Open House, a networked art installation by Jack Stenner and Patrick LeMieux that allows visitors to telematically squat in a Florida home undergoing foreclosure after the U.S. housing collapse. Virtual markets transformed this otherwise ... Keywords: aesthetics, affect, body, immersion, installation, interaction, representation, subjectivity

Jack Stenner; Patrick LeMieux

2011-11-01T23:59:59.000Z

385

Edition Three, January 2010 Welcome to HOUSES!  

E-Print Network (OSTI)

, interpretation and analysis of the residential property market: Editorial ­ page 3 We all know that house prices to the property market. In this edition we look at the other sources available for monitoring house price movements across all or part of the UK other than the Halifax (Lloyds Banking Group) and Nationwide. Prices

Evans, Paul

386

Edition One, July 2009 Welcome to HOUSES!  

E-Print Network (OSTI)

- 15.7 % £152,49 7 - 15.9 % Source: Land Registry Price trends in East Midland cities mirror national trends Figures from the Land Registry suggest that the annual rates of house price decline in the cities, interpretation and analysis of the residential property market: Editorial ­ page 4 We all know that house prices

Evans, Paul

387

Edition Four, April 2010 Welcome to HOUSES!  

E-Print Network (OSTI)

, interpretation and analysis of the residential property market: Editorial ­ page 3 We all know that house prices between the various levels of survey inspection available.. Prices - page 8 Find out what's happening to house prices both nationally and regionally. Affordability - page 12 Can households afford to buy

Evans, Paul

388

Security of differential phase shift quantum key distribution against individual attacks  

E-Print Network (OSTI)

We derive a proof of security for the Differential Phase Shift Quantum Key Distribution (DPSQKD) protocol under the assumption that Eve is restricted to individual attacks. The security proof is derived by bounding the average collision probability, which leads directly to a bound on Eve's mutual information on the final key. The security proof applies to realistic sources based on pulsed coherent light. We then compare individual attacks to sequential attacks and show that individual attacks are more powerful.

Edo Waks; Hiroki Takesue; Yoshihisa Yamamoto

2005-08-15T23:59:59.000Z

389

On-site Housing | Staff Services  

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

On-site Housing On-site Housing Note: All guests wishing to stay on-site must be registered and approved in the BNL Guest Information System (GIS). Welcome to Brookhaven National Laboratory. BNL attracts more than 4,500 visiting scientists from all over the world each year to perform scientific research and work with our staff. To support our guests, there are 333 on-site housing units. These units are comprised of 66 family-style apartments, 39 efficiency apartments, 213 dormitory rooms, 13 Guest House rooms, and 2 year round private houses. Location: Hours of Operation: Research Support Building (400A), 20 Brookhaven Avenue Monday - Friday: 8:00 am to Midnight Reservations: (631) 344-2541 or 344-2551 Saturday: Closed* Fax: (631) 344-3098 Sunday: 4:00 pm to Midnight

390

Please transfer ALL data off /house  

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

Please transfer ALL data off /house before Please transfer ALL data off /house before 12/1/2013 Please transfer ALL data off house September 3, 2013 by Kjiersten Fagnan (0 Comments) We are happy to announce that all the file systems: /global/projectb, /global/dna and /webfs are available for use. We now strongly encourage users to begin the data transfer process from /house to the other file systems. House will retire on December 20, 2013! For more information on the best ways to transfer data and what each file system should be used for, check this page . Post your comment You cannot post comments until you have logged in. Login Here. Comments No one has commented on this page yet. RSS feed for comments on this page | RSS feed for all comments User Announcements Email announcement archive Subscribe via RSS

391

White House | OpenEI Community  

Open Energy Info (EERE)

White House White House Home Graham7781's picture Submitted by Graham7781(1992) Super contributor 16 August, 2013 - 12:21 New report from White House outlines largest problems facing United States energy grid energy grid OpenEI President Smart Grid United States White House Graham7781's picture Submitted by Graham7781(1992) Super contributor 30 August, 2012 - 15:16 Historic Fuel Standards auto fuel efficiency obama standards vehicle White House On Tuesday, Ray Lahood, Secretary of the U.S. Department of Transportation, and Lisa P. Jackson, Environmental Protection Agency Administrator, unveiled the joint effort, along with the Obama Administration, to create record fuel standards for vehicles built between 2017 and 2025. Syndicate content 429 Throttled (bot load) Error 429 Throttled (bot load)

392

DOE Solar Decathlon: Solar Decathlon House Tours  

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

House Tours House Tours Attending the U.S. Department of Energy Solar Decathlon isn't the only way to get a tour of a Solar Decathlon house. Many past competition houses are open to the public and offer tours year-round. To learn more about the Solar Decathlon houses from previous competitions that offer tours, select from the markers on the map below or choose from the links in the following tables. Screen reader users: click here for plain HTML Go to Google Maps Home Loading... Map Sat Ter Did you mean a different: Did you mean a different: Did you mean a different: Add Destination - Show options Hide options Get Directions Note: Public transit coverage may not be available in this area. Report a problem - Maps Labs - Help Google Maps ‎ ‎ - ©2014 Google ‎ - Terms of Use - Privacy

393

Energy efficient industrialized housing research program  

Science Conference Proceedings (OSTI)

This document describes the research work completed in five areas in fiscal year 1989. (1) The analysis of the US industrialized housing industry includes statistics, definitions, a case study, and a code analysis. (2) The assessment of foreign technology reviews the current status of design, manufacturing, marketing, and installation of industrialized housing primarily in Sweden and Japan. (3) Assessment of industrialization applications reviews housing production by climate zone, has a cost and energy comparison of Swedish and US housing, and discusses future manufacturing processes and emerging components. (4) The state of computer use in the industry is described and a prototype design tool is discussed. (5) Side by side testing of industrialized housing systems is discussed.

Berg, R.; Brown, G.Z.; Finrow, J.; Kellett, R.; McDonald, M.; McGinn, B.; Ryan, P.; Sekiguchi, Tomoko (Oregon Univ., Eugene, OR (USA). Center for Housing Innovation); Chandra, S.; Elshennawy, A.K.; Fairey, P.; Harrison, J.; Mazwell, L.; Roland, J.; Swart, W. (Florida Solar Energy Center, Cape Canaveral, FL (USA))

1989-12-01T23:59:59.000Z

394

OpenEI Community - White House  

Open Energy Info (EERE)

/0 en New report from White /0 en New report from White House outlines largest problems facing United States energy grid http://en.openei.org/community/blog/new-report-white-house-outlines-largest-problems-facing-united-states-energy-grid house-outlines-largest-problems-facing-united-states-energy-grid" target="_blank">read more http://en.openei.org/community/blog/new-report-white-house-outlines-largest-problems-facing-united-states-energy-grid#comments energy grid OpenEI President Smart Grid United States White House Fri, 16

395

Key Activities | Department of Energy  

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

Key Activities Key Activities Key Activities The Water Power Program conducts work in four key areas at the forefront of water power research. The Program is structured to help the United States meet its growing energy demands sustainably and cost-effectively by developing innovative renewable water power technologies, breaking down market barriers to deployment, building the infrastructure to test new technologies, and assessing water power resources for integration into our nation's grid. Research and Development Introduce and advance new marine and hydrokinetic technologies to provide sustainable and cost-effective renewable energy from the nation's waves, tides, currents, and ocean thermal gradients. Research and develop innovative hydropower technologies to sustainably tap our country's diverse water resources including rivers,

396

Key China Energy Statistics 2011  

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

1 Title Key China Energy Statistics 2011 Publication Type Chart Year of Publication 2012 Authors Levine, Mark D., David Fridley, Hongyou Lu, and Cecilia Fino-Chen Date Published...

397

Key China Energy Statistics 2012  

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

2 Title Key China Energy Statistics 2012 Publication Type Chart Year of Publication 2012 Authors Levine, Mark D., David Fridley, Hongyou Lu, and Cecilia Fino-Chen Date Published...

398

Cooling with a Whole House Fan | Department of Energy  

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

Cooling with a Whole House Fan Cooling with a Whole House Fan Cooling with a Whole House Fan May 30, 2012 - 6:54pm Addthis Whole house fan installed as part of a home retrofit project in California. | Photo courtesy of Lieko Earle, NREL. Whole house fan installed as part of a home retrofit project in California. | Photo courtesy of Lieko Earle, NREL. What does this mean for me? A whole-house fan may be sufficient to cool your house, at least for part of the year. In many climates, a whole-house fan can save you money and maintain comfort during the cooling season. How does it work? A whole-house fan works by pulling air in through windows and exhausting it through the attic and roof. Whole house cooling using a whole house fan can substitute for an air conditioner most of the year in most climates. Whole house fans combined

399

DOE Solar Decathlon: Where Are the Solar Decathlon Houses Now...  

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

Where Are the Solar Decathlon Houses Now? Since 2002, 72 houses have competed in the U.S. Department of Energy Solar Decathlon. These houses-now located throughout the United...

400

Technological rules and constraints affecting design of precast concrete housing  

E-Print Network (OSTI)

Precast concrete technology is of great importance in multifamily housing. This technology provides the possibility to the industrialize housing construction and thus enhance the availability and quality of houses. With ...

Nakamura, Takashi

1994-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "key assumptions housing" 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

Panel data analyses of urban economics and housing markets  

E-Print Network (OSTI)

The thesis looks three pertinent issues in Housing Market and Urban Economics literature with panel data- home sales and house price relationship, efficiency of housing market and commercial property taxation. For the first ...

Lee, Nai Jia

2009-01-01T23:59:59.000Z

402

President Obama Announces More Key Administration Posts | Department of  

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

January 23, 2012 - 8:28pm January 23, 2012 - 8:28pm Addthis THE WHITE HOUSE Office of the Press Secretary FOR IMMEDIATE RELEASE January 23, 2012 President Obama Announces More Key Administration Posts WASHINGTON - Today, President Barack Obama announced his intent to nominate the following individuals to key Administration posts: Erin C. Conaton - Under Secretary of Defense for Personnel and Readiness, Department of Defense Scott H. DeLisi - Ambassador to the Republic of Uganda, Department of State Deborah Delisle - Assistant Secretary for Elementary and Secondary Education, Department of Education Tracey Ann Jacobson - Ambassador to the Republic of Kosovo, Department of State James J. Jones - Assistant Administrator for Toxic Substances, Environmental Protection Agency Frank Kendall III - Under Secretary of Defense for Acquisition,

403

What is a low-energy house?  

Science Conference Proceedings (OSTI)

Traditionally, a ``low-energy`` house has been one that used little energy for space heating. But space heating typically accounts for less than half of the energy used by new US homes, and for low heating energy homes, space heating is often the third largest end use, behind water heating and appliances, and sometimes behind cooling. Low space heat alone cannot identify a low-energy house. To better understand the determinants of a low-energy house, we collected data on housing characteristics, incremental costs, and energy measurements from energy-efficient houses around the world and in a range of climates. We compare the energy required to provide thermal comfort as well as water heating, and other appliances. We do not have a single definition of a low-energy house, but through comparisons of actual buildings, we show how different definitions and quantitative indicators fail. In comparing the energy use of whole houses, weather normalization can be important, but for cases in which heating or cooling energy is surpassed by other end uses, other normalization methods must be used.

Litt, B.R.; Meier, A.K.

1994-08-01T23:59:59.000Z

404

Women and Housing Co-operatives in Nairobi, Kenya .  

E-Print Network (OSTI)

??This thesis examines the potential of housing co-operatives to provide adequate housing for women, focusing on the context of Nairobi, Kenya. The limitations of the (more)

Voellmecke, Lesley

2011-01-01T23:59:59.000Z

405

Before the Subcommittee on Environment and the Economy -- House...  

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

- House Energy and Commerce Committee Before the Subcommittee on Environment and the Economy -- House Energy and Commerce Committee Before the Subcommittee on Environment and the...

406

Before House Subcommittee on Oversight and Investigations - Committee...  

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

House Subcommittee on Oversight and Investigations - Committee on Energy and Commerce Before House Subcommittee on Oversight and Investigations - Committee on Energy and Commerce...

407

Before the House Energy and Commerce | Department of Energy  

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

Commerce Before the House Energy and Commerce Before the House Energy and Commerce By: Deputy Secretary Daniel Poneman Subject: H.R. 2054, Energy and Revenue Enrichment Act...

408

Before House Committee on Science, Space, and Technology | Department...  

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

Space, and Technology Before House Committee on Science, Space, and Technology Before House Committee on Science, Space, and Technology By: Peter Lyons Subject: Assessing America's...

409

White House Science Fair Recap | Department of Energy  

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

Speaks at Solar Impulse Press Conference Common Sense and The Next 30 Seconds White House Leadership Summit on Women, Climate and Energy Secretary Moniz at White House Women's...

410

Before House Committee on Oversight and Government Reform | Department...  

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

Oversight and Government Reform Before House Committee on Oversight and Government Reform Testimony of Daniel Poneman, Deputy Secretary of Energy Before House Committee on...

411

White_House_economic_rpt_0211.pdf | Department of Energy  

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

WhiteHouseeconomicrpt0211.pdf WhiteHouseeconomicrpt0211.pdf WhiteHouseeconomicrpt0211.pdf More Documents & Publications WhiteHouse0921.pdf THE WHITE HOUSE THE WHITE...

412

Before the House Science and Technology Committee | Department...  

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

Forward 1-27-10FinalTestimony(Majumdar).pdf More Documents & Publications Before the House Science, Space, and Technology Committee Before the House Subcommittee on...

413

Before the House Science, Space, and Technology Subcommittee...  

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

Investigations and Oversight Before the House Science, Space, and Technology Subcommittee on Investigations and Oversight Before the House Science, Space, and Technology...

414

Before the House Science and Technology Subcommittee on Oversight...  

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

on Oversight and Investigations Before the House Science and Technology Subcommittee on Oversight and Investigations Before the House Science and Technology Subcommittee on...

415

Before the House Veterans Affairs Committee | Department of Energy  

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

Veterans Affairs Committee Before the House Veterans Affairs Committee Before the House Veterans Affairs Committee By: Richard Kidd, Program Manager, FEMP Office of Energy...

416

Before the House Subcommittee on Investigations and Oversight...  

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

and Oversight Committee on Science, Space and Technology Before the House Subcommittee on Investigations and Oversight Committee on Science, Space and Technology Before the House...

417

Before the House Energy and Commerce Subcommittee on Oversight...  

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

Oversight and Investigations Before the House Energy and Commerce Subcommittee on Oversight and Investigations Before the House Energy and Commerce Subcommittee on Oversight and...

418

Before The Subcommittee on Oversight and Investigations - House...  

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

The Subcommittee on Oversight and Investigations - House Committee on Energy and Commerce Before The Subcommittee on Oversight and Investigations - House Committee on Energy and...

419

Before the Subcommittee on Environment and the Economy - House...  

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

the Economy - House Energy and Commerce Committee Before the Subcommittee on Environment and the Economy - House Energy and Commerce Committee Testimony of Ernest Moniz, Secretary...

420

Before House Subcommittee on Energy and Power and Subcommittee...  

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

House Subcommittee on Energy and Power and Subcommittee on Oversight and Investigations - Committee on Energy and Commerce Before House Subcommittee on Energy and Power and...

Note: This page contains sample records for the topic "key assumptions housing" 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

Before the Subcommittee on Energy - House Committee on Science...  

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

- House Committee on Science, Space and Technology Before the Subcommittee on Energy - House Committee on Science, Space and Technology Testimony of Adam Sieminiski, Administrator,...

422

Before the House Budget Committee | Department of Energy  

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

Repository 7-16-09FinalTestimony(kouts).pdf More Documents & Publications Before the House Budget Committee Before the Senate Budget Committee Before the House Science, Space,...

423

Before House Committee on Science, Space and Technology | Department...  

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

Space and Technology Before House Committee on Science, Space and Technology Before House Committee on Science, Space and Technology By: Secretary Steven Chu Subject: FY 2013...

424

Herbert Richardson: Before The U.S. House of Representatives...  

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

Richardson: Before The U.S. House of Representatives Committee on Energy and Commerce Subcommittee on Oversight and Investigations Herbert Richardson: Before The U.S. House of...

425

Before the House Energy and Commerce Committee | Department of...  

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

Committee Before the House Energy and Commerce Committee Before the House Energy and Commerce Committee By: Secretary Steven Chu Subject: American Clean Energy and Security Act of...

426

Testimony Before the House Appropriations Subcommittee on Energy...  

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

Testimony Before the House Appropriations Subcommittee on Energy and Water Development Testimony Before the House Appropriations Subcommittee on Energy and Water Development...

427

Before the House Science and Technology Subcommittee on Energy...  

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

Funding 7-23-09FinalTestimony(Hoffman).pdf More Documents & Publications Before the House Energy and Commerce Subcommittee on Energy and Environment Before the House...

428

Before the House Small Business Subcommittee on Contracting and...  

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

Subcommittee on Contracting and Technology Before the House Small Business Subcommittee on Contracting and Technology Before the House Small Business Subcommittee on Contracting...

429

Before the House Small Business Committee | Department of Energy  

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

Committee Before the House Small Business Committee Before the House Small Business Committee By: Larry James, Technology Transfer Program Manager, Office of Science Subject: SBIR...

430

Before the House Science and Technology Subcommittee on Investigations...  

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

on Investigations and Oversight Before the House Science and Technology Subcommittee on Investigations and Oversight Before the House Science and Technology Subcommittee on...

431

Testimony Before the House Natural Resources Subcommittee on...  

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

Natural Resources Subcommittee on Energy and Mineral Resources Testimony Before the House Natural Resources Subcommittee on Energy and Mineral Resources Testimony Before the House...

432

Hand-colored Wood Engraving of Custom House in Cincinnati  

Science Conference Proceedings (OSTI)

... and Measures (OWM) began providing standards of length, mass, and capacity to the custom-houses in the 1830s, the custom-house at Cincinnati ...

433

Before the Subcommittee on Oversight and Investigations - House...  

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

Oversight and Investigations - House Committee on Energy and Commerce Before the Subcommittee on Oversight and Investigations - House Committee on Energy and Commerce Testimony of...

434

Before the House Energy and Commerce Subcommittee on Energy and...  

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

& Publications Before the Senate Energy and Natural Resources Committee Before the House Energy and Commerce Subcommittee on Energy and Environment Before the House Energy and...

435

Before the Subcommittee on Strategic Forces - House Armed Services...  

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

Strategic Forces - House Armed Services Committee Before the Subcommittee on Strategic Forces - House Armed Services Committee Written Statement by David Huizenga, Senior Advisor...

436

Before the Subcommittee on Strategic Forces - House Armed Services...  

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

Forces - House Armed Services Committee Before the Subcommittee on Strategic Forces - House Armed Services Committee Testimony of Daniel B. Poneman, Deputy Secretary of Energy...

437

White House Honors Federal Agencies for Saving Taxpayers $133...  

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

House Honors Federal Agencies for Saving Taxpayers 133 Million in Energy Costs by Increasing Efficiency Measures White House Honors Federal Agencies for Saving Taxpayers 133...

438

Before the House Energy and Commerce Subcommittee on Energy and...  

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

Fuels and Vehicles EIAFinalTestimony(1).pdf More Documents & Publications Before the House Energy and Commerce Subcommittee on Energy and Environment Testimony Before the House...

439

Before Subcommittee on Water and Power - House Committee on Natural...  

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

Water and Power - House Committee on Natural Resources Before Subcommittee on Water and Power - House Committee on Natural Resources Testimony of Mark Gabriel, Administrator WAPA...

440

Before the House Energy and Commerce Subcommittee on Energy and...  

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

09FinalTestimony(Gruenspecht).pdf More Documents & Publications Testimony Before the House Energy and Commerce Subcommittee on Energy and Environment Testimony Before the House...

Note: This page contains sample records for the topic "key assumptions housing" 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

White House Council of Economic Advisers and Energy Department...  

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

White House Council of Economic Advisers and Energy Department Release New Report on Resiliency of Electric Grid During Natural Disasters White House Council of Economic Advisers...

442

Before the House Committee on Science, Space and Technology ...  

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

the House Committee on Science, Space and Technology Before the House Committee on Science, Space and Technology Statement Before the Committee on Science, Space and Technology,...

443

Before the House Science and Technology Committee | Department...  

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

Committee Before the House Science and Technology Committee Before the House Science and Technology Committee By: Secretary Steven Chu Subject: New Direction for Energy Research...

444

Before the House Science and Technology Subcommittee on Energy...  

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

9-10-09FinalTestimony(Gillo).pdf More Documents & Publications Before the House Science and Technology Subcommittee on Energy and Environment Before the House Science...

445

Before the House Subcommittee on Energy and Environment - Committee...  

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

Transportation Before the House Subcommittee on Energy and Environment - Committee on Science, Space, and Transportation Before the House Subcommittee on Energy and Environment -...

446

Testimony Before the House Subcommittee on Oversight and Investigation...  

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

House Subcommittee on Oversight and Investigations - Committee on Energy and Commerce Testimony Before the House Subcommittee on Oversight and Investigations - Committee on Energy...

447

Before the House Committee on Oversight and Government Reform...  

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

Oversight and Government Reform Before the House Committee on Oversight and Government Reform Before the Committee on Oversight and Government Reform, U.S. House of Representatives...

448

Testimony Before the House Energy and Commerce Subcommittee on...  

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

Energy and Commerce Subcommittee on Energy and Environment Testimony Before the House Energy and Commerce Subcommittee on Energy and Environment Before the House Energy and...

449

Before the House Natural Resources Subcommittee on Energy and...  

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

Energy and Mineral Resources Before the House Natural Resources Subcommittee on Energy and Mineral Resources Before the House Natural Resources Subcommittee on Energy and Mineral...

450

Before the House Science and Technology, Subcommittee on Energy...  

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

Technology, Subcommittee on Energy and Environment Before the House Science and Technology, Subcommittee on Energy and Environment Before the House Science and Technology,...

451

Testimony Before the House Energy & Water Development Committee...  

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

Reports Testimony Testimony Before the House Energy & Water Development Committee Testimony Before the House Energy & Water Development Committee Agency Financial Reports...

452

House Conference Report 106-1005, Face Page  

Science Conference Proceedings (OSTI)

... The managers on the part of the House and the Senate at the conference on the disagreeing votes of the two Houses on the amendment of the ...

2010-10-05T23:59:59.000Z

453

Solar Decathlon 2013: Designing the Houses of Today | Department...  

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

Designing the Houses of Today Solar Decathlon 2013: Designing the Houses of Today September 12, 2013 - 12:40pm Addthis The Southern California Institute of Architecture and...

454

Before the House Science and Technology Subcommittee on Energy...  

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

are here Home Before the House Science and Technology Subcommittee on Energy and Environment Before the House Science and Technology Subcommittee on Energy and Environment...

455

Before the House Committee on Science, Space, and Technology...  

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

Before the House Committee on Science, Space, and Technology Testimony of Ernest Moniz, Secretary of Energy Before the House Committee on Science, Space, and Technology...

456

Before the Subcommittee on Energy and Power - House Committee...  

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

on Energy and Power - House Committee on Energy and Commerce Testimony of Ernest Moniz, Secretary of Energy Before the Subcommittee on Energy and Power - House Committee on...

457

Join the STEM and Mentoring Interagency Open House Friday, January...  

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

Join the STEM and Mentoring Interagency Open House Friday, January 18, in Washington DC Join the STEM and Mentoring Interagency Open House Friday, January 18, in Washington DC...

458

Before the Subcommittee on Energy and Environment - House Committee...  

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

Environment - House Committee on Science, Space, and Technology Before the Subcommittee on Energy and Environment - House Committee on Science, Space, and Technology Testimony of...

459

U.S. Residential Housing Weather Adjusted Site Energy Consumption ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency > Residential Housing Energy Intensities > Table 1b Glossary U.S. Residential Housing Weather Adjusted ...

460

California Solar Initiative - Multi-Family Affordable Solar Housing...  

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

California Solar Initiative - Multi-Family Affordable Solar Housing (MASH) Program California Solar Initiative - Multi-Family Affordable Solar Housing (MASH) Program < Back...

Note: This page contains sample records for the topic "key assumptions housing" 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

On-site Housing Policies and Procedures | Staff Services  

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

in all apartments, Guest House rooms, Guest House lobby and dormitory lobbies. Computers with high speed internet connection are available in all dormitory lounges. Coin...

462

Paducah DUF6 Conversion Final EIS - Chapter 4: Environmental Impact Assessment Approach, Assumptions, and Methodology  

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

Paducah DUF Paducah DUF 6 Conversion Final EIS 4 ENVIRONMENTAL IMPACT ASSESSMENT APPROACH, ASSUMPTIONS, AND METHODOLOGY This EIS evaluates potential impacts on human health and the natural environment from building and operating a DUF 6 conversion facility at three alternative locations at the Paducah site and for a no action alternative. These impacts might be positive, in that they would improve conditions in the human or natural environment, or negative, in that they would cause a decline in those conditions. This chapter provides an overview of the methods used to estimate the potential impacts associated with the EIS alternatives, summarizes the major assumptions that formed the basis of the evaluation, and provides some background information on human health

463

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.

464

GRI baseline projection: Methodology and assumptions 1996 edition. Topical report, January-December 1995  

Science Conference Proceedings (OSTI)

The report documents the methodology employed in producing the 1996 Edition of the GRI Baseline Projection. DRI/McGraw-Hill`s Energy Group (DRI) maintains an energy modeling system for the Gas Research Institute (GRI) that is used to produce an annual projection of the supply and demand for energy by regions in the United States. The 1996 Edition of the GRI Baseline Projection is produced using several different models. The models analyze various pieces of the U.S. energy markets and their solutions are based on a framework of exogenous assumptions provided by GRI. The report describes the integration and solution procedures of the models and the assumptions used to produce the final projection results.

Rhodes, M.R.; Baxter, R.P.; Nottingham, R.P.

1996-04-01T23:59:59.000Z

465

GRI baseline projection: Methodology and assumptions 1995 edition. Topical report, January-December 1994  

SciTech Connect

The report documents the methodology employed in producing the 1995 Edition of the GRI Baseline Projection. DRI/McGraw-Hill`s Energy Group (DRI) maintains an energy modeling system for the Gas Research Institute (GRI) that is used to produce an annual projection of the supply and demand for energy by regions in the United States. The 1995 Edition of the GRI Baseline Projection is produced using several different models. The models analyze various pieces of the U.S. energy markets and their solutions are based on a framework of exogeneous assumptions provided by GRI. The report describes the integration and solution procedures of the models and the assumptions used to produce the final projection results.

Baxter, R.P.; Silveira, T.S.; Harshbarger, S.L.

1995-02-01T23:59:59.000Z

466

The Texas Solar D House  

E-Print Network (OSTI)

The Solar Decathlon provided a national forum for competition among fourteen university student teams, each of which designed, built, and operated a totally solar-powered home with a home office and their transportation needs using a solar-charged vehicle. The competition took place on the National Mall in Washington D.C., where each house was constructed and operated from September 18 to October 10, 2002. The competition consisted of ten contests focusing on energy production, energy-efficiency, design, thermal comfort, refrigeration, lighting, communication and transportation Professor Michael Garrison of the School of Architecture directed the University of Texas at Austin (UT) Solar Decathlon team along with Pliny Fisk, codirector of the non-profit Center for Maximum Potential Building Systems in Austin, Texas. The graduate student team developed a design that features an open building system using a reusable kit of parts that sits lightly on the land and forms the superstructure around a mobile utility environment. Our investigations suggest that progressive technologies offer solutions to the serious emerging challenges of energy efficiency and sustainable development and thereby become a strong design shaping force. These progressive technologies: photovoltaic (PV) power, passive solar heating, daylighting, natural ventilation, and solar hot water heating were integrated with concepts of affordability and energy conservation to help promote an ideology of sustainable architecture.

Garrison, M.

2004-01-01T23:59:59.000Z

467

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.

468

What We Talked About with the White House "Entrepreneur-in-Residence" |  

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

We Talked About with the White House We Talked About with the White House "Entrepreneur-in-Residence" What We Talked About with the White House "Entrepreneur-in-Residence" April 20, 2012 - 1:42pm Addthis Want more information on Apps for Energy? Signup at http://appsforenergy.challenge.gov. | Image by Hantz Leger. Want more information on Apps for Energy? Signup at http://appsforenergy.challenge.gov. | Image by Hantz Leger. Erin R. Pierce Erin R. Pierce Digital Communications Specialist, Office of Public Affairs What does this project do? Apps for Energy helps spur innovation and out-of-the-box thinking. Green Button's open data standards give developers the opportunity to impact the way millions use their utility data. Insights from developers and the general public play a key role in

469

Back to the Basics of Sustainability -- Houses of Bark and Energy of  

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

Back to the Basics of Sustainability -- Houses of Bark and Energy Back to the Basics of Sustainability -- Houses of Bark and Energy of Sunshine Back to the Basics of Sustainability -- Houses of Bark and Energy of Sunshine August 2, 2012 - 2:23pm Addthis With new pipes and controls, the natural gas kilns Highland Craftsmen uses to produce poplar bark shingles will operate about 40 percent more efficiently, saving the company $5,000 a year in energy costs. | Photo courtesy of Highland Craftsmen. With new pipes and controls, the natural gas kilns Highland Craftsmen uses to produce poplar bark shingles will operate about 40 percent more efficiently, saving the company $5,000 a year in energy costs. | Photo courtesy of Highland Craftsmen. Julie McAlpin Communications Liaison, State Energy Program What are the key facts? With funds from the State Energy Program, Highland Craftsmen

470

House Subcommittee on Strategic Forces of the Committee on Armed Services |  

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

House Subcommittee on Strategic Forces of the Committee on Armed House Subcommittee on Strategic Forces of the Committee on Armed Services House Subcommittee on Strategic Forces of the Committee on Armed Services January 31, 2007 - 10:15am Addthis Statement of Energy Secretary Samuel W. Bodman Madam Chairman and members of the subcommittee, I am pleased to appear before you to provide my assessment of the Department's progress in implementing Title 32 - the National Nuclear Security Administration Act. This is the first opportunity I have had to testify before this subcommittee specifically on this subject since assuming office as Secretary of Energy some two years ago. But this is a subject on which I have spent a considerable amount of time since my arrival at the Department. Let me begin by saying that the men and women of the NNSA complex are a key

471

House Passage of H.R. 5254 - The Refinery Permit Process Schedule Act |  

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

Passage of H.R. 5254 - The Refinery Permit Process Schedule Passage of H.R. 5254 - The Refinery Permit Process Schedule Act House Passage of H.R. 5254 - The Refinery Permit Process Schedule Act June 8, 2006 - 2:17pm Addthis Statement from Secretary Bodman WASHINGTON, DC - The following is a statement from the Secretary Samuel W. Bodman of the Department of Energy on the passage of House Resolution 5254, The Refinery Permit Process Schedule Act: "I commend the House of Representatives for their passage of this important piece of legislation. Expanding our nation's refining capacity is an important part of President Bush's four-point plan to confront high gasoline prices and is a key component to strengthening our nation's energy security. By increasing our nation's domestic refining capacity we can help grow our nation's economy and reduce our reliance on foreign sources

472

Order and chaos : articulating support, housing transformation  

E-Print Network (OSTI)

This thesis presents an exploration on the theme of order and chaos, as a formal and social phenomenon, particularly as it relates to housing. The work stems from an attraction to the messy vitality we find in certain ...

Boehm, William Hollister

1990-01-01T23:59:59.000Z

473

Advanced House Framing | Department of Energy  

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

can result in materials cost savings of up to 500 or 1,000 (for a 1,200- and 2,400-square-foot house, respectively), labor cost savings of between 3% and 5%, and annual heating...

474

" Million Housing Units, Final"  

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

Air Conditioning in U.S. Homes, by Housing Unit Type, 2009" Air Conditioning in U.S. Homes, by Housing Unit Type, 2009" " Million Housing Units, Final" ,,"Housing Unit Type" ,,"Single-Family Units",,"Apartments in Buildings With" ,"Total U.S.1 (millions)" ,," Detached"," Attached"," 2 to 4 Units","5 or More Units","Mobile Homes" "Air Conditioning" "Total Homes",113.6,71.8,6.7,9,19.1,6.9 "Air Conditioning Equipment" "Use Air Conditioning Equipment",94,61.1,5.6,6.3,15.2,5.8 "Have Air Conditioning Equipment But" "Do Not Use It",4.9,2.6,0.2,0.7,0.9,0.4 "Do Not Have Air Conditioning Equipment",14.7,8.1,0.9,2.1,3,0.7 "Type of Air Conditioning Equipment "

475

" Million Housing Units, Final"  

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

Household Demographics of U.S. Homes, by Housing Unit Type, 2009" Household Demographics of U.S. Homes, by Housing Unit Type, 2009" " Million Housing Units, Final" ,,"Housing Unit Type" ,,"Single-Family Units",,"Apartments in Buildings With" ,"Total U.S.1 (millions)" ,," Detached"," Attached"," 2 to 4 Units","5 or More Units","Mobile Homes" "Household Demographics" "Total Homes",113.6,71.8,6.7,9,19.1,6.9 "Number of Household Members" "1 Person",31.3,14.4,2.1,3.4,9.6,1.9 "2 Persons",35.8,24.2,1.9,2.5,5,2.1 "3 Persons",18.1,12.1,1.2,1.3,2.2,1.2 "4 Persons",15.7,11.5,1,1,1.5,0.8 "5 Persons",7.7,5.8,0.3,0.5,0.6,0.5

476

Advanced House Framing | Department of Energy  

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

Advanced House Framing Advanced House Framing Advanced House Framing April 13, 2012 - 7:57pm Addthis Two-story home using advanced framing techniques. Two-story home using advanced framing techniques. Advanced house framing means materials, labor, and heating and cooling cost savings because the approach: Uses less lumber and generates less waste than typical framing methods. Increases energy efficiency by replacing lumber with insulation material, resulting in a higher whole-wall R-value through reduced thermal bridging and increased insulation. How does it work? Advanced framing works structurally by aligning framing members directly over each other to transfer the load from roof trusses or rafters to second floor wall studs, to floor joists, to first floor studs to the foundation,

477

" Million Housing Units, Final"  

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

Fuels Used and End Uses in U.S. Homes, by Housing Unit Type, 2009" Fuels Used and End Uses in U.S. Homes, by Housing Unit Type, 2009" " Million Housing Units, Final" ,,"Housing Unit Type" ,,"Single-Family Units",,"Apartments in Buildings With" ,"Total U.S.1 (millions)" ,," Detached"," Attached"," 2 to 4 Units","5 or More Units","Mobile Homes" "Fuels Used and End Uses" "Total Homes",113.6,71.8,6.7,9,19.1,6.9 "Fuels Used for Any Use" "Electricity",113.6,71.8,6.7,9,19.1,6.9 "Natural Gas",69.2,45.6,4.7,6.1,11,1.8 "Propane/LPG",48.9,39.6,2.4,1.7,2,3.2 "Wood",13.1,11.4,0.3,0.2,0.5,0.7 "Fuel Oil",7.7,5.1,0.4,0.7,1.3,0.1

478

The House of the Future at MIT  

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

The House of the Future at MIT The House of the Future at MIT Speaker(s): Kent Larson Date: December 6, 2002 - 12:00pm Location: Bldg. 90 During this seminar, Professor Larson will discuss two related housing initiatives at MIT: Changing Places/Houses in The MIT Home of the Future Consortium. Change is accelerating, but the places we create are largely static and unresponsive. "Changing Places" is an MIT research consortium that explores how new technologies, materials, and strategies for design can make possible dynamic, evolving places that respond to the complexities of life. Open Source Building Alliance Providing individuals with choice creates competition and incentives for innovation. Mass-customization requires a modular component-based approach, which creates a pathway for new players to enter the $852

479

" Million U.S. Housing Units" ,,"2005...  

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

7 Air-Conditioning Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"...

480

City of Indianapolis- EcoHouse Project  

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

In June 2011, the City of Indianapolis announced the availability of the EcoHouse Project, an energy-efficiency loan program for medium- and low-income homeowners in Indianapolis. The Indianapolis...

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


481

The Passive House: A Sustainable Building Concept  

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

Passive House: A Sustainable Building Concept Speaker(s): Benjamin Krick Date: November 13, 2012 - 11:00am Location: 90-1099 Seminar HostPoint of Contact: Christian Kohler This...

482

White House Safety Datapalooza | Data.gov  

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

Resources Blogs Let's Talk Safety You are here Data.gov Communities Safety White House Safety Datapalooza Todd Park Todd Park, U.S. Chief Technology Officer, speaks at the...

483

The California Economy: Singing the Housing Blues  

E-Print Network (OSTI)

THECALIFORNIAECONOMY:SINGINGTHEHOUSING BLUESMany parts of the economy are doing better thantowards2007theentireeconomyisbeingthreatenedbythe

Thornberg, Christopher

2007-01-01T23:59:59.000Z

484

Tax policy, housing markets, and elderly homeowners  

E-Print Network (OSTI)

This dissertation consists of three essays studying the impact of tax policy on housing markets and elderly homeowners. Chapter One examines the potential lock-in effect of capital gains taxation on home sales, using the ...

Shan, Hui, Ph. D. Massachusetts Institute of Technology

2008-01-01T23:59:59.000Z

485

Whole-House Ventilation | Department of Energy  

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

into the house to be filtered to remove pollen and dust or dehumidified to provide humidity control Supply ventilation systems work best in hot or mixed climates. Because they...

486

Sustainable construction in Mexican housing markets  

E-Print Network (OSTI)

This thesis examines recent developments in Mexico's housing markets as an example of how sustainable construction is being adapted and applied in developing countries. The recognition that the construction, operation, and ...

Jung, Bomee

2007-01-01T23:59:59.000Z

487

Retrofitting the Southeast: The Cool Energy House  

Science Conference Proceedings (OSTI)

The Consortium for Advanced Residential Buildings has provided the technical engineering and building science support for a highly visible demonstration home in connection with the National Association of Home Builders' International Builders Show. The two previous projects, the Las Vegas net-zero ReVISION House and the 2011 VISION and ReVISION Houses in Orlando, met goals for energy efficiency, cost effectiveness, and information dissemination through multiple web-based venues. This project, which was unveiled at the 2012 International Builders Show in Orlando on February 9, is the deep energy retrofit Cool Energy House (CEH). The CEH began as a mid-1990s two-story traditional specification house of about 4,000 ft2 in the upscale Orlando suburb of Windermere.

Zoeller, W.; Shapiro, C.; Vijayakumar, G.; Puttagunta, S.

2013-02-01T23:59:59.000Z

488

Essays on annuitization and housing choice  

E-Print Network (OSTI)

Chapter 1 For most US households, labor income is the most important source of wealth and housing is the most important risky asset. A natural intuition is thus that households whose incomes covary relatively strongly with ...

Davidoff, Thomas, 1971-

2002-01-01T23:59:59.000Z

489

Million U.S. Housing Units Total...............................  

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

the Time... 2.8 0.6 Q Q Q Q N Table HC4.12 Home Electronics Usage Indicators by Renter-Occupied Housing Unit, 2005 Renter- Occupied...

490

On-site Housing Rates | Staff Services  

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

Rates Effective February 1, 2013 Rates for Occupancy < 30-Days Guest House* SingleDouble: 105.00 per day Housekeeping service is provided on all working days. *Alternatives to...

491

New urban housing in Seoul, Korea  

E-Print Network (OSTI)

For the last three decades, the capital city of Korea, Seoul, has experienced an explosive increase in population and rapid urbanization. This increase has led to a severe housing shortage in Seoul. The government responded ...

Lee, Kwanghyun, 1971-

2001-01-01T23:59:59.000Z

492

" Million Housing Units, Final"  

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

Appliances in U.S. Homes, by Housing Unit Type, 2009" Appliances in U.S. Homes, by Housing Unit Type, 2009" " Million Housing Units, Final" ,,"Housing Unit Type" ,,"Single-Family Units",,"Apartments in Buildings With" ,"Total U.S.1 (millions)" ,,,,,"5 or More Units","Mobile Homes" "Appliances",,"Detached","Attached","2 to 4 Units" "Total Homes",113.6,71.8,6.7,9,19.1,6.9 "Cooking Appliances" "Stoves (Units With Both" "an Oven and a Cooktop)" "Use a Stove",102.3,62.3,6.4,8.7,18.3,6.5 "1.",100.8,61,6.4,8.6,18.3,6.5 "2 or More",1.5,1.3,0.1,"Q","Q","Q" "Do Not Use a Stove",11.3,9.5,0.3,0.3,0.8,0.4

493

" Million Housing Units, Final"  

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

Water Heating in U.S. Homes, by Housing Unit Type, 2009" Water Heating in U.S. Homes, by Housing Unit Type, 2009" " Million Housing Units, Final" ,,"Housing Unit Type" ,,"Single-Family Units",,"Apartments in Buildings With" ,"Total U.S.1 (millions)" ,," Detached"," Attached"," 2 to 4 Units","5 or More Units","Mobile Homes" "Water Heating" "Total Homes",113.6,71.8,6.7,9,19.1,6.9 "Number of Storage Tank Water Heaters" 0,2.9,1.8,0.1,0.2,0.6,0.1 1,108.1,67.5,6.5,8.8,18.5,6.8 "2 or More",2.7,2.5,0.1,"Q","Q","Q" "Number of Tankless Water Heaters2" 0,110.4,69.5,6.5,8.9,18.6,6.8 1,3.1,2.2,0.2,0.2,0.5,"Q"

494

" Million Housing Units, Final"  

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

Space Heating in U.S. Homes, by Housing Unit Type, 2009" Space Heating in U.S. Homes, by Housing Unit Type, 2009" " Million Housing Units, Final" ,,"Housing Unit Type" ,,"Single-Family Units",,"Apartments in Buildings With" ,"Total U.S.1 (millions)" ,," Detached"," Attached"," 2 to 4 Units","5 or More Units","Mobile Homes" "Space Heating" "Total Homes",113.6,71.8,6.7,9,19.1,6.9 "Space Heating Equipment" "Use Space Heating Equipment",110.1,70.5,6.5,8.7,17.7,6.7 "Have Space Heating Equipment But Do " "Not Use It",2.4,0.8,0.2,0.2,1,0.1 "Do Not Have Space Heating Equipment",1.2,0.6,"Q",0.1,0.4,"Q"

495

2013 White House Tribal Nations Conference  

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

On Wednesday, November 13, President Obama will host the White House Tribal Nations Conference at the Department of the Interior. The conference will provide leaders from the 566 federally...

496

Achieving Sustainable Construction in Affordable Housing  

Science Conference Proceedings (OSTI)

An energy-efficient design and construction checklist and information sheets on energy-efficient design and construction are two products being developed. These products will help affordable housing providers take the first steps toward a whole-house approach to the design and implementation of energy-efficient construction practices. The checklist presents simple and clear guidance on energy improvements that can be readily addressed now by most affordable housing providers. The information sheets complement the checklist by providing installation instructions and material specifications that are accompanied by detailed graphics. The information sheets also identify benefits of recommended energy-efficiency measures and procedures including cost savings and impacts on health and comfort. This paper presents details on the checklist and information sheets and discusses their use in two affordable housing projects.

Barcik, M.K.; Creech, D.B.; Ternes, M.P.

1998-12-07T23:59:59.000Z

497

Energy efficient industrialized housing research program  

SciTech Connect

This is the second volume of a two volume report on energy efficient industrialized housing. Volume II contains support documentation for Volume I. The following items are included: individual trip reports; software bibliography; industry contacts in the US, Denmark, and Japan; Cost comparison of industrialized housing in the US and Denmark; draft of the final report on the systems analysis for Fleetwood Mobile Home Manufacturers. (SM)

Berg, R.; Brown, G.Z.; Finrow, J.; Kellett, R.; Mc Donald, M.; McGinn, B.; Ryan, P.; Sekiguchi, T. (Oregon Univ., Eugene, OR (USA). Center for Housing Innovation); Chandra, S.; Elshennawy, A.K.; Fairey, P.; Harrison, J.; Maxwell, L.; Roland, J.; Swart, W. (Florida Solar Energy Center, Cape Canaveral, FL (USA))

1989-01-01T23:59:59.000Z

498

EPAct Transportation Regulatory Activities: Key Terms  

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

Key Terms Key Terms to someone by E-mail Share EPAct Transportation Regulatory Activities: Key Terms on Facebook Tweet about EPAct Transportation Regulatory Activities: Key Terms on Twitter Bookmark EPAct Transportation Regulatory Activities: Key Terms on Google Bookmark EPAct Transportation Regulatory Activities: Key Terms on Delicious Rank EPAct Transportation Regulatory Activities: Key Terms on Digg Find More places to share EPAct Transportation Regulatory Activities: Key Terms on AddThis.com... Home About Covered Fleets Compliance Methods Alternative Fuel Petitions Resources Guidance Documents Statutes & Regulations Program Annual Reports Fact Sheets Newsletter Case Studies Workshops Tools Key Terms FAQs Key Terms The Energy Policy Act (EPAct) includes specific terminology related to

499

EPAct Transportation Regulatory Activities: Key Federal Statutes  

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

Key Key Federal Statutes to someone by E-mail Share EPAct Transportation Regulatory Activities: Key Federal Statutes on Facebook Tweet about EPAct Transportation Regulatory Activities: Key Federal Statutes on Twitter Bookmark EPAct Transportation Regulatory Activities: Key Federal Statutes on Google Bookmark EPAct Transportation Regulatory Activities: Key Federal Statutes on Delicious Rank EPAct Transportation Regulatory Activities: Key Federal Statutes on Digg Find More places to share EPAct Transportation Regulatory Activities: Key Federal Statutes on AddThis.com... Home About Contacts Covered Fleets Compliance Methods Alternative Fuel Petitions Resources Key Federal Statutes These are excerpts from federal statutes that established key Energy Policy Act (EPAct) transportation regulatory activities.

500

Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results  

E-Print Network (OSTI)

A comparison of national energy consumption by fuel typeenergy consumption in homes under differing assumptions, scenarios, and policies. At the national

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z