Powered by Deep Web Technologies
Note: This page contains sample records for the topic "assumptions housing stock" 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.


1

Comparing Wealth Effects: The Stock Market versus the Housing Market  

E-Print Network (OSTI)

MAREKET VERSUS THE HOUSING MARKET By Karl E. Case John M.Article ? Comparing Wealth E?ects: The Stock Market versusthe Housing Market Karl E. Case ? John M. Quigley † Robert

Case, Karl E.; Quigley, John M.; Shiller, Robert J.

2005-01-01T23:59:59.000Z

2

Disaster debris management and recovery of housing stock in San Francisco, CA  

E-Print Network (OSTI)

This thesis investigates the potential effects of a 7.2 magnitude earthquake in San Francisco City, particularly the implications on San Francisco's residential housing stock and impacts on the construction and demolition ...

Saiyed, Zahraa Nazim

2012-01-01T23:59:59.000Z

3

Expanding the housing supply through conversions of the existing stock  

E-Print Network (OSTI)

A large share of households remain poorly housed in the United States despite the steady improvement in overall housing conditions throughout the postwar period. Households that face the greatest difficulty in gaining ...

Pogharian, Sevag V. (Sevag Vasken)

1990-01-01T23:59:59.000Z

4

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

5

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,

6

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

7

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.

8

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.

9

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

10

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

11

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

12

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.

13

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

14

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

15

Jim Stock | Department of Energy  

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

Jim Stock Jim Stock About Us Jim Stock - Member - White House Council of Economic Advisers James H. Stock is a member of the Council of Economic Advisers and is responsible for offering the President objective advice on the formulation of economic policy. Stock was previously the Chief Economist for the Council of Economic Advisers. He is on leave from Harvard University where he is the Harold Hitchings Burbank Professor of Political Economy in the Department of Economics, with a dual appointment in the Harvard Kennedy School. Dr. Stock served as Chair of the Harvard Economics Department from 2006 to 2009 and has been a professor at Harvard continuously since 1983, with the exception of a two-year appointment at UC Berkeley from 1990 to 1991. His research focuses on macroeconomic forecasting, monetary policy, and

16

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.

17

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.

18

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

19

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

20

Supply/Demand Forecasts Begin to Show Stock Rebuilding  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: During 1999, we saw stock draws during the summer months, when we normally see stock builds, and very large stock draws during the winter of 1999/2000. Normally, crude oil production exceeds product demand in the spring and summer, and stocks build. These stocks are subsequently drawn down during the fourth and first quarters (dark blue areas). When the market is in balance, the stock builds equal the draws. During 2000, stocks have gradually built, but following the large stock draws of 1999, inventories needed to have been built more to get back to normal levels. As we look ahead using EIA's base case assumptions for OPEC production, non-OPEC production, and demand, we expect a more seasonal pattern for the next 3 quarters. But since we are beginning the year with

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

Fuel Ethanol Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 View History; U ...

22

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

23

Baldrige Stock Studies  

Science Conference Proceedings (OSTI)

Baldrige Stock Studies. From 1994 through 2004, the Baldrige Performance Excellence Program conducted studies around ...

2013-06-27T23:59:59.000Z

24

Second NIST Stock Investment Study "Quality Stocks" Yield ...  

Science Conference Proceedings (OSTI)

... Study Finds "Quality Stocks" Yield Big Payoff Second NIST Stock Investment Study February 1996 A second NIST stock investment study (the first ...

2013-09-11T23:59:59.000Z

25

Crude Oil Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

26

Lubricants Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

27

cutting stock problem  

Science Conference Proceedings (OSTI)

NIST. cutting stock problem. (classic problem). Definition: Find the best arrangement of shapes on rectangles to minimize ...

2013-08-23T23:59:59.000Z

28

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...

29

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...

30

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

31

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

32

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

33

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

34

Information flow between composite stock index and individual stocks  

E-Print Network (OSTI)

We investigate the strength and the direction of information transfer in the U.S. stock market between the composite stock price index of stock market and prices of individual stocks using the transfer entropy. Through the directionality of the information transfer, we find that individual stocks are influenced by the index of the market.

Kwon, Okyu

2007-01-01T23:59:59.000Z

35

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

36

Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

37

Stocks of Fuel Ethanol  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

38

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...

39

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

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2009 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIAÂ’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.1

40

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

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2009 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2035. The definition of the commercial sector is consistent with EIAÂ’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services [1].

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

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

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2006 The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIAÂ’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.14

42

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

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2008 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIAÂ’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.1

43

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

44

Stocks of Propane/Propylene  

U.S. Energy Information Administration (EIA)

Stocks held at natural gas processing plants are included in "Other Oils" and in totals. All stock levels are as of the end of the period.

45

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...

46

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...

47

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

48

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.

49

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.

50

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.

51

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.

52

stocked inventory.PDF  

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

08 08 AUDIT REPORT STOCKED INVENTORY AT THE SAVANNAH RIVER SITE U.S. DEPARTMENT OF ENERGY OFFICE OF INSPECTOR GENERAL OFFICE OF AUDIT SERVICES JUNE 2001 MEMORANDUM FOR THE SECRETARY FROM: Gregory H. Friedman (Signed) Inspector General SUBJECT: INFORMATION: Audit Report on "Stocked Inventory at the Savannah River Site" BACKGROUND The Department of Energy's (Department) management and operating contractor at the Savannah River Site, Westinghouse Savannah River Company (Westinghouse), is responsible for managing the majority of the Department's missions and associated stocked inventory at the site. As of March 2001, Westinghouse maintained about

53

Japanese coastal fishery stocks.  

E-Print Network (OSTI)

In United Nations Convention on the Law of the Sea (UNCLOS), it was enshrined that "States shall take measures which are designed, on the best scientific evidence available to the States concerned, to maintain or restore populations of harvested species at levels which can produce the maximum sustainable yield (MSY)". However considering the current status of scientific knowledge for the fishery target species in Japan, it is practical that MSY can be defined as the optimal yield under the proper fishery stock management (Japanese Fishery Agency 2012). In Japan, the allowable biological catch (ABC) is estimated for important coastal fishery stocks. The threshold level of stock (Blimit: the minimum stock biomass to ensure an appropriate amount of recruitment) is defined and if the biomass is above Blimit, ABC is calculated based on various reference points which ensure sustainable yields. If the biomass is below Blimit, tighter ABC is set to recover the stock. If the stock biomass is extremely low (below Bban), fishing moratorium or similar measure will be recommended.

Minoru Kanaiwa; Minoru Kanaiwa

2012-01-01T23:59:59.000Z

54

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

55

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.

56

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

57

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".

58

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

59

Distillate Stocks Expected  

Gasoline and Diesel Fuel Update (EIA)

4 4 Notes: So let's get to what you want to know. What do we expect this upcoming winter? When EIA's demand forecast is combined with its outlook for production and net imports, distillate stocks are projected to remain towards the lower end of the normal range. We are forecasting about an 11 million barrel build between the end of July 2001 and the end of November 2001, slightly more than the average over the past 5 years (10 million barrels), but less than the average of the last 10 years (15 ½ million barrels). If, however, economic incentives are high enough, distillate stocks could build more, resulting in a higher distillate stock level heading into the winter. Of course, the reverse is true as well, if for example, the distillate fuel refining spread declines substantially. Since 1994,

60

PAD District III Stocks  

Gasoline and Diesel Fuel Update (EIA)

4 4 Notes: PADD 3 (the Gulf Coast) inventories, at the end of July, stood at 33.5 million barrels and are well above the normal range for this time of year. Since we have a few months more to go until the beginning of the heating season, there is still time for the plentiful stocks in the Gulf Coast to find their way up into the Midwest. Thus, even though propane stocks in the Midwest are low, this could easily not be the case by the beginning of the heating season. One slight area of concern, however, is that the Texas Eastern Pipeline (TET) is experiencing brine problems due to heavy rains and record stock builds. To help alleviate the problem, some chemical companies are shifting their propane out of TET to other storage facilities. At this time we don't feel that this will negatively affect the propane market this

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

Propane/Propylene Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 View History; U ...

62

Naphtha for Petrochemical Feedstock Use Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 View History; U ...

63

Asphalt and Road Oil Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 View History; U ...

64

Crude Oil and Petroleum Products Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: 2007 2008 2009 2010 2011 2012 View History; U.S. 1,665,345 ...

65

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.

66

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

67

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

68

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

69

Rehabilitation for redevelopment : an approach to the conversion of old office buildings to housing  

E-Print Network (OSTI)

This thesis contends that the rehabilitation of existing building stock is a viable alternative to new construction in the production of housing. Principally, the thesis proposes that old office buildings, built between ...

Hellinghausen, D. Michael

1984-01-01T23:59:59.000Z

70

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

71

Results of Baldrige Winners' Common Stock Comparison ...  

Science Conference Proceedings (OSTI)

... Results of Baldrige Winners' Common Stock Comparison Third NIST Stock Investment Study February 1997 Methodology: A hypothetical sum was ...

2013-09-11T23:59:59.000Z

72

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

73

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

74

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

75

Reducing Life Cycle Impacts of the Existing Irish Housing Stock.  

E-Print Network (OSTI)

?? Abstract Despite the importance of addressing the challenges of the 2020 emissions reduction targets of both the European Union (EU) and Ireland, current residential… (more)

Famuyibo, Albert A.

2012-01-01T23:59:59.000Z

76

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.

77

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...

78

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.

79

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...

80

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...

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

Motor Gasoline Blending Components Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

82

Ethane/Ethylene Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

83

Reformulated GTAB Gasoline Blending Components Total Stocks Stocks ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

84

Crude Oil and Petroleum Products Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

85

Unfinished Oils - Naphthas and Lighter Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

86

Unfinished Oils - Heavy Gas Oils Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

87

Residual Fuel Oil Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

88

Normal Butane/Butylene Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

89

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).

90

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

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

91

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.

92

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

93

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...

94

Lubricants Refinery Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

95

Stocks of Distillate Fuel Oil  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

96

Stocks of Total Motor Gasoline  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

97

Stocks of Crude Oil, Commercial  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

98

Stock Mechanics: a classical approach  

E-Print Network (OSTI)

New theoretical approaches about forecasting stock markets are proposed. A mathematization of the stock market in terms of arithmetical relations is given, where some simple (non-differential, non-fractal) expressions are also suggested as general stock price formuli in closed forms which are able to generate a variety of possible price movements in time. A kind of mechanics is submitted to cover the price movements in terms of classical concepts. Where utilizing stock mechanics to grow the portfolios in real markets is also proven.

Tuncay, C

2005-01-01T23:59:59.000Z

99

California's Housing Problem  

E-Print Network (OSTI)

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

Kroll, Cynthia; Singa, Krute

2008-01-01T23:59:59.000Z

100

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.

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


101

Assumptions to the Annual Energy Outlook  

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

102

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

103

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

104

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

105

EIA - Assumptions to the Annual Energy Outlook 2008 - Residential...  

Gasoline and Diesel Fuel Update (EIA)

The end-use services for which equipment stocks are modeled include space conditioning (heating and cooling), water heating, refrigeration, freezers, dishwashers, clothes...

106

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...

107

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).

108

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).

109

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

110

Falling House Prices and Rising Time on the Market  

E-Print Network (OSTI)

Much of the current trouble in the housing market has been attributed to the fact that house price appreciation—strong for many years—is finally slowing; indeed, in many markets now, house prices are falling.The mere fact that falling house prices are considered newsworthy is interesting in its own right. In other asset markets, such as the stock and bond markets, prices routinely fluctuate up and down every day. In this Economic Letter I argue that the main reason for this difference reflects differences in the liquidity of houses and financial assets as investments. I review the ways in which residential real estate prices and liquidity vary over time and over different states of the economy, discuss the implications of this price and liquidity behavior

unknown authors

2008-01-01T23:59:59.000Z

111

Stock Market and Consumption: Evidence from China  

E-Print Network (OSTI)

A. 1992. Understanding Consumption. Cambridge, UK: CambridgeStock market wealth and consumption. The Journal of Economic139–146. Stock Market and Consumption: Evidence from China

Hau, Leslie C

2011-01-01T23:59:59.000Z

112

Average Stock Levels: Crude Market & Propane  

U.S. Energy Information Administration (EIA)

This graph shows that propane was not alone in experiencing excess supply in 1998 and extraordinary stock builds. Note that the graph shows average stock levels ...

113

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

114

Stocks of Residual Fuel Oil  

U.S. Energy Information Administration (EIA)

All stock levels are as of the end of the period. Data may not add to total due to independent rounding. Weekly data for RBOB with Ether, RBOB with Alcohol, ...

115

Buildings Stock Load Control  

E-Print Network (OSTI)

Researchers and practitioners have proposed a variety of solutions to reduce electricity consumption and curtail peak demand. This research focuses on electricity demand control by applying some strategies in existing building to reduce it during the extreme climate period. The first part of this paper presents the objectives of the study: ? to restrict the startup polluting manufacturing units (power station), ? to limit the environmental impacts (greenhouse emission), ? to reduce the transport and distribution electricity infrastructures The second part presents the approach used to rise the objectives : ? To aggregat the individual loads and to analyze the impact of different strategies from load shedding to reduce peak power demand by: ? Developing models of tertiary buildings stocks (Schools, offices, Shops, hotels); ? Making simulations for different load shedding strategies to calculate potential peak power saving. The third part is dedicated to the description of the developed models: An assembly of the various blocks of the library of simbad and simulink permit to model building. Finally the last part prensents the study results: Graphs and tables to see the load shedding strategies impacts.

Joutey, H. A.; Vaezi-Nejad, H.; Clemoncon, B.; Rosenstein, F.

2006-01-01T23:59:59.000Z

116

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...

117

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:...

118

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...

119

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

120

" 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...

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

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

122

" 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...

123

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...

124

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...

125

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

126

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

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2007 Commercial Demand Module The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIA's State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.12

127

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.

128

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...

129

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...

130

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

131

Stock Market and Consumption: Evidence from China  

E-Print Network (OSTI)

9] Funke, Norbert. 2004. Is there a stock market wealth e?ect in emerging markets? Economics Letters, 83, 417–21. [10]C. 1990. Has the stock market crash reduced consumer spend-

Hau, Leslie C

2011-01-01T23:59:59.000Z

132

Distillate Stocks Expected to Remain Low  

Gasoline and Diesel Fuel Update (EIA)

8 Notes: When EIA's demand forecast is combined with its outlook for production and net imports, distillate stocks are projected to remain low for the rest of the year. - Stocks...

133

Essays on predictability of stock returns  

E-Print Network (OSTI)

This thesis consists of three chapters exploring predictability of stock returns. In the first chapter, I suggest a new approach to analysis of stock return predictability. Instead of relying on predictive regressions, I ...

Rytchkov, Oleg

2007-01-01T23:59:59.000Z

134

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.

135

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...

136

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...

137

" 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....

138

" 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...

139

" 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....

140

" 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....

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

" 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....

142

" 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....

143

" 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....

144

" 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...

145

" 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...

146

" 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...

147

" 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....

148

" 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...

149

" 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...

150

Political Cycles and the Stock Market  

E-Print Network (OSTI)

forecast the stock market as controls for business cycle ?uctuations. After controlling for the dividend-price

Santa-Clara, Pedro; Valkanov, Rossen

2000-01-01T23:59:59.000Z

151

U.S. Total Stocks  

Annual Energy Outlook 2012 (EIA)

Show Data By: Product Stock Type Area Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 View History Crude Oil and Petroleum Products 1,806,501 1,817,459 1,817,679 1,817,508 1,820,533...

152

Stocking rate effects on intensive-early stocked Flint Hills bluestem range  

E-Print Network (OSTI)

Stocking rate effects on intensive-early stocked Flint Hills bluestem range CLENTON E. OWENSBY, ROBERT COCHRAN, AND ED F. SMITH Stocking rate effects on intensive-early stocked Kansas Flint Hills range- lands is limited to the first 2 1/ 2 months of the growing season in the Kansas Flint Hills. Grazing

Owensby, Clenton E.

153

Forecast Technical Document Growing Stock Volume  

E-Print Network (OSTI)

Forecast Technical Document Growing Stock Volume Forecasts A document describing how growing stock (`standing') volume is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Growing stock volume forecasts Background A forecast of standing volume (or

154

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

155

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...

156

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

157

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

158

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

159

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

160

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

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

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...

162

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...

163

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

164

Low Stocks Mean Tight Markets  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: Like those for other petroleum products, gasoline inventories have been running below normal. As of the latest weekly data, stocks are about 5% lower than the low end of the normal range for this time of year. Behind all of the low product inventories are low crude oil inventories. Recall that the crude market tightened in 1999 when OPEC cut back production. Demand was greater than supply and inventories were used to make up the difference. They have not yet recovered. Crude oil inventories are running about 7% below the low end of the normal range for this time of year. After last week's very large stock draw, it appears inventories are the lowest that they have been since December 1975. The U.S. inventory data will be an important price barometer to

165

Peoria Housing Authority(PHA) Weatherization Training Project  

Science Conference Proceedings (OSTI)

The DOE Weatherization Training Project's goal is to obtain a solid foundation of administrative and technical knowledge so the Peoria Housing Authority (PHA) can establish and implement a successful Weatherization Program by 2011. The DOE weatherization Training Project's two objectives are to (1) build PHA's capabilities by (2) developing its staff members capacities via the acquisition of weatherization skills and competencies. The impacts from this project include: (a) the improvement and expansion of PHA staff skills, (b) the overall enhancement of the quality of the PHA workforce, which will (c) foster employment, (d) the ability to properly weatherize PHA housing stock, tribal buildings, and tribal members houses, which will (e) result in reduced energy use, and (f) improved tribal and household economies.

Phillip Chrismon; Jason Dollarhide

2011-12-31T23:59:59.000Z

166

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.

167

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:

168

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

169

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"

170

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...

171

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...

172

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...

173

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...

174

" 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...

175

" 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...

176

" 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...

177

" 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...

178

" 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...

179

" 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...

180

" 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...

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

" 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...

182

" 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...

183

" 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...

184

" 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...

185

" 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...

186

" 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...

187

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

188

" 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...

189

" 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...

190

" 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"...

191

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

192

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

193

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

194

Distillate Stocks Expected to Remain Low  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: When EIA's demand forecast is combined with its outlook for production and net imports, distillate stocks are projected to remain low for the rest of the year. - Stocks are beginning at very low levels. The September 1 distillate fuel stock level (112 million barrels) is nearly 20% less than last year, and about 15% below the 10 year average for end of August levels. - But stocks on the East Coast, at 39.8 million barrels, are 39% behind year-ago levels, and about a similar percentage below end-of-August 10-year average levels. Over the last 10 years, the average stock build from the end of August through the end of November has been about 10 million barrels. We are forecasting about a 12 million barrel build, which does not reach the normal band. Forecast stocks peak at the end of November at 127 million

195

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

196

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

197

2001 Housing Characteristics Detailed Tables  

U.S. Energy Information Administration (EIA)

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

198

WILD RICE SALAD RECIPE 1 quart water, chicken stock or vegetable stock  

E-Print Network (OSTI)

WILD RICE SALAD RECIPE 1 quart water, chicken stock or vegetable stock 1 cup wild rice, rinsed Sea ground pepper to taste 4 tablespoons extra virgin olive oil 2 tablespoons buttermilk or plain low-fat

Blanchette, Robert A.

199

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

200

How Predictable Is The Chinese Stock Market?.  

E-Print Network (OSTI)

?? We analyze return predictability for the Chinese stock market, including the aggregate market portfolio and the components of the aggregate market, such as portfolios… (more)

Jiang, Fuwei

2011-01-01T23:59:59.000Z

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

Low Stocks Set Stage for Price Volatility  

Gasoline and Diesel Fuel Update (EIA)

left heating oil markets in a vulnerable position. Stocks began the winter of 199900 well above average. They deteriorated somewhat as low margins kept refiners from continuing...

202

Kerosene Bulk Terminal Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

203

Isobutane/Butylene Refinery Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

204

Crude Oil Refinery Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

205

Stocks of Kerosene-Type Jet Fuel  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

206

Petroleum Coke Refinery Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

207

Stocks of Motor Gasoline Blending Components  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

208

Gulf Coast (PADD 3) Total Stocks  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

209

Stocks of Motor Gasoline Blending Components, CBOB  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

210

Integer Solutions to Cutting Stock Problems  

E-Print Network (OSTI)

ting Stock Problem (CSP) that can be described as follows: find the most ... two integer linear programming models for the one-dimensional CSP differing in.

211

Measured Natural Cooling Enhancement of a While House Fan  

E-Print Network (OSTI)

An experimental study was carried out in the summer of 1991 to investigate the natural cooling potential of use of a whole house fan in Central Florida's hot and humid climate. The residential building, in Cocoa Beach, FL, is typical of much of the existing housing stock in Florida: a concrete block structure with R-11 ceiling insulation. The building was ventilated with all windows open during the three month summer test period (June- August). Air temperatures and relative humidity inside the home interior along with exterior meteorological conditions (insolation, wind speed, air temperature, relative humidity) were scanned every five seconds with integrated averages recorded on a multi-channel data logger every 15- minutes. The house was naturally ventilated during the first half of summer. After a significant period of pre-retrofit summer data had been collected characterizing the building's thermal response, a 24" whole house fan was installed. The house was then force ventilated during evening hours for the remainder of the summer to establish potential of whole-house fans to improve interior comfort conditions. The electrical consumption of the fan was measured at both available fan speeds. Measurements revealed that the building interior was 3 - 6°F cooler during the evening hours after the whole house fan was operated. However, data also showed that nighttime humidity levels rose: relative humidity increased from 74% to 83% during the nighttime period where fan-powered ventilation was used. Using the data results, an analysis was performed using Orlando, Florida TMY data to see how limits to whole house ventilation based on humidity and temperature conditions would affect the potential of such a cooling strategy.

Parker, D. S.

1994-01-01T23:59:59.000Z

212

Models for the two-dimensional two-stage cutting stock problem with multiple stock size  

Science Conference Proceedings (OSTI)

We consider a Two-Dimensional Cutting Stock Problem (2DCSP) where stock of different sizes is available, and a set of rectangular items has to be obtained through two-stage guillotine cuts. We propose and computationally compare three Mixed-Integer Programming ... Keywords: Computational experiments, Cutting stock problem, Mixed-integer programming models

Fabio Furini, Enrico Malaguti

2013-08-01T23:59:59.000Z

213

Intensive-Early Stocking and Season-Long Stocking of Kansas Flint Hills Range  

E-Print Network (OSTI)

Intensive-Early Stocking and Season-Long Stocking of Kansas Flint Hills Range ED F. SMITH AND CLENTON E. OWENSBY Highlight: Native Flint Hills bluestem range was stocked at twice the normal rate, 1 gains during the latter half of the growing season on Kansas Flint Hills range are barely one-half those

Owensby, Clenton E.

214

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

215

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

216

An analysis of residential energy consumption and expenditures by minority households by home type and housing vintage  

SciTech Connect

In this paper a descriptive analysis of the relationship between energy consumption, patterns of energy use, and housing stock variables is presented. The purpose of the analysis is to uncover evidence of variations in energy consumption and expenditures, and patterns of energy use between majority households (defines as households with neither a black nor Hispanic head of household), black households (defined as households with a black head of household), and Hispanic households (defined as households with a Hispanic head of household) between 1980 (time of the first DOE/EIA Residential Energy Consumption Survey, 1982a) and 1987 (time of the last DOE/EIA Residential Energy Consumption Survey, 1989a). The analysis is three-dimensional: energy consumption and expenditures are presented by time (1980 to 1987), housing vintage, and housing type. A comparative analysis of changes in energy variables for the three population groups -- majority, black, and Hispanic -- within and between specific housing stock categories is presented.

Poyer, D.A.

1992-01-01T23:59:59.000Z

217

An analysis of residential energy consumption and expenditures by minority households by home type and housing vintage  

SciTech Connect

In this paper a descriptive analysis of the relationship between energy consumption, patterns of energy use, and housing stock variables is presented. The purpose of the analysis is to uncover evidence of variations in energy consumption and expenditures, and patterns of energy use between majority households (defines as households with neither a black nor Hispanic head of household), black households (defined as households with a black head of household), and Hispanic households (defined as households with a Hispanic head of household) between 1980 (time of the first DOE/EIA Residential Energy Consumption Survey, 1982a) and 1987 (time of the last DOE/EIA Residential Energy Consumption Survey, 1989a). The analysis is three-dimensional: energy consumption and expenditures are presented by time (1980 to 1987), housing vintage, and housing type. A comparative analysis of changes in energy variables for the three population groups -- majority, black, and Hispanic -- within and between specific housing stock categories is presented.

Poyer, D.A.

1992-06-01T23:59:59.000Z

218

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

219

A quantum mechanical model for the relationship between stock price and stock ownership  

SciTech Connect

The trade of a fixed stock can be regarded as the basic process that measures its momentary price. The stock price is exactly known only at the time of sale when the stock is between traders, that is, only in the case when the owner is unknown. We show that the stock price can be better described by a function indicating at any moment of time the probabilities for the possible values of price if a transaction takes place. This more general description contains partial information on the stock price, but it also contains partial information on the stock owner. By following the analogy with quantum mechanics, we assume that the time evolution of the function describing the stock price can be described by a Schroedinger type equation.

Cotfas, Liviu-Adrian [Faculty of Economic Cybernetics, Statistics and Informatics, Academy of Economic Studies, 6 Piata Romana, 010374 Bucharest (Romania)

2012-11-01T23:59:59.000Z

220

A quantum mechanical model for the relationship between stock price and stock ownership  

E-Print Network (OSTI)

The trade of a fixed stock can be regarded as the basic process that measures its momentary price. The stock price is exactly known only at the time of sale when the stock is between traders, that is, only in the case when the owner is unknown. We show that the stock price can be better described by a function indicating at any moment of time the probabilities for the possible values of price if a transaction takes place. This more general description contains partial information on the stock price, but it also contains partial information on the stock owner. By following the analogy with quantum mechanics, we assume that the time evolution of the function describing the stock price can be described by a Schrodinger type equation.

Liviu-Adrian Cotfas

2012-07-14T23:59:59.000Z

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

222

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":""}]}

223

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.

224

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

225

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

226

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

227

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

228

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

229

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.

230

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

231

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

232

Iowa Refinery, Bulk Terminal, and Natural Gas Plant Stocks of ...  

U.S. Energy Information Administration (EIA)

Notes: Distillate stocks located in the Northeast Heating Oil Reserve are not included. Stocks are reported as of the last day of the month.

233

Oregon Refinery, Bulk Terminal, and Natural Gas Plant Stocks ...  

U.S. Energy Information Administration (EIA)

Notes: Distillate stocks located in the Northeast Heating Oil Reserve are not included. Stocks are reported as of the last day of the month.

234

Kentucky Refinery, Bulk Terminal, and Natural Gas Plant Stocks ...  

U.S. Energy Information Administration (EIA)

Notes: Distillate stocks located in the Northeast Heating Oil Reserve are not included. Stocks are reported as of the last day of the month.

235

Information Efficiency Comparison Between Shanghai and Hongkong Stock Markets.  

E-Print Network (OSTI)

??This thesis starts with the introduction of Shanghai stock market, Hong Kong stock market and efficient market hypothesis. It then tries to compare the information… (more)

Qu, Huan

2008-01-01T23:59:59.000Z

236

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.

237

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.

238

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.

239

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.

240

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 ...

Note: This page contains sample records for the topic "assumptions housing stock" 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 2000 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

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

242

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

243

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...

244

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.

245

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 ...

246

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...

247

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

248

A quantum model for the stock market  

E-Print Network (OSTI)

Beginning with several basic hypotheses of quantum mechanics, we give a new quantum model in econophysics. In this model, we define wave functions and operators of the stock market to establish the Schr\\"odinger equation for the stock price. Based on this theoretical framework, an example of a driven infinite quantum well is considered, in which we use a cosine distribution to simulate the state of stock price in equilibrium. After adding an external field into the Hamiltonian to analytically calculate the wave function, the distribution and the average value of the rate of return are shown.

Chao Zhang; Lu Huang

2010-09-24T23:59:59.000Z

249

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

250

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

251

" 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...

252

" 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"...

253

,"Crude Oil and Petroleum Products Total Stocks Stocks by Type"  

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

Total Stocks Stocks by Type" Total Stocks Stocks by Type" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Crude Oil and Petroleum Products Total Stocks Stocks by Type",6,"Monthly","9/2013","1/15/1956" ,"Release Date:","11/27/2013" ,"Next Release Date:","Last Week of December 2013" ,"Excel File Name:","pet_stoc_typ_a_ep00_sae_mbbl_m.xls" ,"Available from Web Page:","http://www.eia.gov/dnav/pet/pet_stoc_typ_a_ep00_sae_mbbl_m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.gov"

254

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.

255

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

256

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.

257

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...

258

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...

259

Name Address Place Zip Sector Product Stock Symbol Year founded Number  

Open Energy Info (EERE)

Address Place Zip Sector Product Stock Symbol Year founded Number Address Place Zip Sector Product Stock Symbol Year founded Number of employees Number of employees Telephone number Website Coordinates Region ABS Alaskan Inc Van Horn Rd Fairbanks Alaska Gateway Solar Wind energy Marine and Hydrokinetic Solar PV Solar thermal Wind Hydro Small scale wind turbine up to kW and solar systems distributor http www absak com United States AER NY Kinetics LLC PO Box Entrance Avenue Ogdensburg Marine and Hydrokinetic United States AW Energy Lars Sonckin kaari Espoo FI Marine and Hydrokinetic http www aw energy com Finland AWS Ocean Energy formerly Oceanergia Redshank House Alness Point Business Park Alness Ross shire IV17 UP Marine and Hydrokinetic http www awsocean com United Kingdom Able Technologies Audubon Road Englewood Marine and Hydrokinetic http

260

Ohio Distillate Fuel Oil Stocks at Refineries, Bulk Terminals, and ...  

U.S. Energy Information Administration (EIA)

Ohio Distillate Fuel Oil Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

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

Wisconsin Propane and Propylene Stocks at Refineries, Bulk ...  

U.S. Energy Information Administration (EIA)

Wisconsin Propane and Propylene Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

262

Michigan Finished Motor Gasoline Stocks at Refineries, Bulk ...  

U.S. Energy Information Administration (EIA)

Michigan Finished Motor Gasoline Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

263

An efficient CMAC neural network for stock index forecasting  

Science Conference Proceedings (OSTI)

Stock index forecasting is one of the major activities of financial firms and private investors in making investment decisions. Although many techniques have been developed for predicting stock index, building an efficient stock index forecasting model ... Keywords: Back-propagation neural network, Cerebellar model articulation controller, Neural network, Stock index forecasting, Support vector regression

Chi-Jie Lu; Jui-Yu Wu

2011-11-01T23:59:59.000Z

264

Long-term Stock Market Forecasting using Gaussian Processes  

E-Print Network (OSTI)

Address3 email4 Abstract5 Forecasting stock market prices is an attractive topic to researchers from6 to analyze18 and forecast stock prices and index changes. The accuracy of these techniques is still an19-term predictions in stock prices.32 33 1.2 Motivation34 In stock market, investors need long-term forecasting

de Freitas, Nando

265

Alaska Prices, Sales Volumes & Stocks - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Prices, Sales Volumes & Stocks by State Area: Period: Download Series History: Definitions, Sources ...

266

Colorado Propane and Propylene Stocks at Refineries, Bulk ...  

U.S. Energy Information Administration (EIA)

Colorado Propane and Propylene Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

267

Colorado Finished Motor Gasoline Stocks at Refineries, Bulk ...  

U.S. Energy Information Administration (EIA)

Colorado Finished Motor Gasoline Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

268

South Dakota Distillate Fuel Oil Stocks at Refineries, Bulk ...  

U.S. Energy Information Administration (EIA)

South Dakota Distillate Fuel Oil Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

269

South Dakota Propane and Propylene Stocks at Refineries, Bulk ...  

U.S. Energy Information Administration (EIA)

South Dakota Propane and Propylene Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

270

Distillate Stocks Expected to Remain Low  

U.S. Energy Information Administration (EIA)

When EIA’s demand forecast is combined with its outlook for production and net imports, distillate stocks are projected to remain low for the rest of the year.

271

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.

272

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.

273

Assumptions to the Annual Energy Outlook 2000 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

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

274

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.

275

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).

276

Macroeconomic determinants of the stock market movements: empirical evidence from the Saudi stock market.  

E-Print Network (OSTI)

??This dissertation investigates the long run and short run relationships between Saudi stock market returns and eight macroeconomic variables. We investigate the ability of these… (more)

Alshogeathri, Mofleh Ali Mofleh

2011-01-01T23:59:59.000Z

277

Crude Oil Total Stocks Stocks by Type - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

278

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)

279

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.

280

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

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


281

EIA - Assumptions to the Annual Energy Outlook 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.

282

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

283

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

284

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),

285

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

286

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

287

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

288

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

289

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.

290

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.

291

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

292

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).

293

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).

294

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

295

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.

296

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.

297

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).

298

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.

299

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

300

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).

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

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

302

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

303

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

304

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

305

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.

306

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

307

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

308

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).

309

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

310

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).

311

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).

312

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

313

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

314

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

315

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. ...

316

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. ...

317

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. ...

318

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...

319

Restaurant Industry Stock Price Forecasting Model Utilizing Artificial Neural Networks to Combine Fundamental and Technical Analysis.  

E-Print Network (OSTI)

??Stock price forecasting is a classic problem facing analysts. Forcasting models have been developed for predicting individual stocks and stock indices around the world and… (more)

Dravenstott, Ronald W.

2012-01-01T23:59:59.000Z

320

Towards a Very Low Energy Building Stock: Modeling the US Commercial...  

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

Towards a Very Low Energy Building Stock: Modeling the US Commercial Building Stock to Support Policy and Innovation Planning Title Towards a Very Low Energy Building Stock:...

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

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

322

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.

323

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.

324

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

325

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).

326

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.

327

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

328

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).

329

Property:StockSymbol | Open Energy Information  

Open Energy Info (EERE)

StockSymbol StockSymbol Jump to: navigation, search This is a property of type String. Pages using the property "StockSymbol" Showing 25 pages using this property. (previous 25) (next 25) A A.O. Smith + AOS + AAON + AAON + Alterra Power + MGMXF + Ameresco, Inc. + AMRC + Applied Materials + AMAT + Archer Daniels Midland + ADM + Autodesk + ADSK + C China Integrated Energy + CBEH + E EEMAP, Inc. + N/A + EnerNOC + ENOC + Evergreen Solar, Inc. + ESLR + ExxonMobil + XOM + G General Electric + GE + Geothermal Resources Council + Geothermal Resources Council + Goodwill Instrument + TPE 2423 + GreenShift Corporation + GERS.OB + Gulfsands Petroleum + AIM:GPX + H Helix Wind Corp. + HLXW + I ICF International + NASDAQ:ICFI + J Johnson Controls + JCI + M Molycorp Inc. + MCP +

330

U.S. Crude Oil Stocks  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: U.S. crude oil stocks stood at about 289 million barrels on September 8, according to EIA's latest survey. This puts them about 24 million barrels below the level seen at the same time last year. Current market conditions do not suggest much improvement in the near term. We probably ended last month (August 2000) with the lowest level for end-of-August crude oil stocks (289 million barrels) in the United States since 1976, when crude oil inputs to refineries were about 2 million barrels per day less than today. However, by EIA data, we have seen (at least slightly) lower crude stocks in recent months, including an end-December 1999 level of 284 million barrels. The American Petroleum Institute (API), which also surveys petroleum supply and demand

331

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

332

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

333

Air Exchange Rates in New Energy-Efficient Manufactured Housing  

E-Print Network (OSTI)

During the 1989-1990 heating season, Pacific Northwest Laboratory, for the Bonneville Power Administration, measured the ventilation characteristics of 139 newly constructed energy-efficient manufactured homes and a control sample of 35 newer manufactured homes. A standard door fan pressurization technique was used to estimate shell leakiness, and a passive perfluorocarbon tracer technique was used to estimate overall air exchange rates. A measurement of the designated whole-house exhaust system flow rate was taken as well as an occupant and structure survey. The energy-efficient manufactured homes have very low air exchange rates, significantly lower than either existing manufactured homes or site-built homes. The standard deviation of the effective leakage area for this sample of homes is small (25% to 30% of the mean), indicating that the leakiness of manufactured housing stock can be confidently characterized by the mean value. There is some indication of increased ventilation due to the energy-efficient whole-house ventilation specification, but not directly related to the operation of the wholehouse system. The mechanical systems as installed and operated do not provide the intended ventilation; consequently indoor air quality could possibly be adversely impacted and moisture/condensation in the living space is a potential problem.

Hadley, D. L.; Bailey, S. A.

1990-01-01T23:59:59.000Z

334

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

335

Housing Stock Characterization Study: An Innovative Approach to Measuring Retrofit Impact  

Science Conference Proceedings (OSTI)

A residential energy efficiency retrofit loan program depends on a self-sustaining finance option and optimized retrofit measures that recoup their unsubsidized costs through energy bill savings alone within the useful life of the retrofit. A first step in evaluating retrofit options is to measure and verify their energy savings. This report evaluates Orlando Utilities Commission (OUC) residential energy-efficiency demand side management (DSM) programs to assess their relative energy and economic performance.

Jones, P.; Taylor, N.; Kipp, J.

2012-09-01T23:59:59.000Z

336

Modeling Space Heating Demand in Massachusetts’ Housing Stock and the Implications for Climate Change Mitigation Policy.  

E-Print Network (OSTI)

??This research examines variation in average household energy consumption for space heating in municipalities in Massachusetts in order to explore the magnitude of variation among… (more)

Robinson, Nathan H.

2011-01-01T23:59:59.000Z

337

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...

338

Low Distillate Stocks Set Stage for Price Volatility  

U.S. Energy Information Administration (EIA)

This distillate price spike is a classic response to a local supply and demand imbalance that began as a result of low distillate stocks. Low distillate stocks in the ...

339

U.S. Distillate Stocks - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Slide 5 of 27. Distillate Stocks. This slide shows the average U.S. distillate stock pattern -- building in the summer and fall, then being drawn down through the ...

340

Jiangsu FAW Foundry Stock Co Ltd | Open Energy Information  

Open Energy Info (EERE)

FAW Foundry Stock Co Ltd Jump to: navigation, search Name Jiangsu FAW Foundry Stock Co Ltd Place Wuxi, Jiangsu Province, China Sector Wind energy Product Wuxi-based JV set up...

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

Propane/Propylene Natural Gas Processing Plant Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 View History; U ...

342

Residual Fuel Oil Bulk Terminal Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 View History; U ...

343

Policy Consequences of Better Stock Estimates in Pacific Halibut Fisheries  

E-Print Network (OSTI)

the effect of halibut price, stock biomass, on the amount ofbiomass over time. The measurement equa- equation tions include a priceprice The is catch in determined equation area storage describes the effect of effort and stock biomass

Berck, Peter; Johns, Grace

1985-01-01T23:59:59.000Z

344

Demonstrating Modernism: Richard Neutra's Early Model Houses  

E-Print Network (OSTI)

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

Peltakian, Danielle

2012-01-01T23:59:59.000Z

345

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)...

346

Ohio Refinery, Bulk Terminal, and Natural Gas Plant Stocks of ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Distillate stocks ...

347

Michigan Refinery, Bulk Terminal, and Natural Gas Plant Stocks of ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Distillate stocks ...

348

Idaho Refinery, Bulk Terminal, and Natural Gas Plant Stocks of ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Distillate stocks ...

349

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

350

Fear and its implications for stock markets  

E-Print Network (OSTI)

The value of stocks indices, and other assets, are examples of stochastic processes that drop and raise in unpredictable ways. In this paper, we discuss certain asymmetries in short term price movements that can not be attributed to a long term increasing trend. These empirical asymmetries predict that price drops in stock indices on a relatively short time scale are more common than the corresponding price raises, and we present several empirical examples of such asymmetries. Furthermore, a simple model is introduced with the aim of explaining these facts. The prime idea is to introduce occasional, short periods of dropping stock prices that are synchronized for all stocks of the index. These collective negative price movements are imagined to be triggered by external factors in our society that create fear for the future among the investors. In the model this is parameterized by a ``fear factor'' defining how often such events take place. It is demonstrated that such a simple fear factor model can reproduce...

Simonsen, I; Jensen, M H; Donangelo, R; Sneppen, K; Simonsen, Ingve; Ahlgren, Peter Toke Heden; Jensen, Mogens H.; Donangelo, Raul; Sneppen, Kim

2006-01-01T23:59:59.000Z

351

West Coast (PADD 5) Total Stocks  

U.S. Energy Information Administration (EIA)

Stock Type: Area: Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 View History; Crude Oil and Petroleum Products: 148,209: 144,699: 141,778: 140,755: 140,174: 142,146: 1981 ...

352

A new Loan-Stock Financial Instrument  

E-Print Network (OSTI)

A new financial instrument (a new kind of a loan) is introduced. The loan-stock instrument (LSI) combines fixed rate instruments (loans, etc.) with other financial instruments that have higher volatilities and returns (stocks, mutual funds, currencies, derivatives, options, etc.). This new loan depends on the value of underlying security (for example, stock) in such a way that when underlying security increases, the value of loan decreases and backwards. The procedure to create a risk free portfolio and a technique to fairly price the LSI is described. The philosophy behind this procedure is quite similar to the Black-Scholes formalism in option theory. Creation of the risk free portfolio is possible because the change in the underlying security offsets the change in the value of the loan (or the amount that the borrower has to repay). The new financial instrument takes an advantage of the fact that on average the stock market grows in time. It is beneficial for both the borrower and the lender. The LSI is more attractive for the borrower than the traditional loan is due to the decrease in the amount that has to be repaid. This attractiveness constitutes the benefit for the lender in terms of the market share among the borrowers. In addition, the lender can charge the extra premium.

Alexander Morozovsky; Rajan Narasimhan; Yuri Kholodenko

2000-07-01T23:59:59.000Z

353

Game Analysis of the Evolution of Artificial Stock Market  

Science Conference Proceedings (OSTI)

In this paper, we build the participators’ logistic model of the game model in artificial stock market. The participators are three types: flexible agent, semi-flexible agent and rigidity agent. Then, we set up the game model in artificial stock ... Keywords: Artificial stock market, Game model, Agent

She Zhenyu; Yan Bo

2010-12-01T23:59:59.000Z

354

Using Neural Networks to Forecast Stock Market Prices Ramon Lawrence  

E-Print Network (OSTI)

Using Neural Networks to Forecast Stock Market Prices Ramon Lawrence Department of Computer Science on the application of neural networks in forecasting stock market prices. With their ability to discover patterns. Section 3 covers current analytical and computer methods used to forecast stock market prices

Lawrence, Ramon

355

Upgrade energy building standards and develop rating system for existing low-income housing  

SciTech Connect

The city of Memphis Division of Housing and Community Development (HCD) receives grant funding each year from the U.S. Department of Housing and Urban Development (HUD) to provide local housing assistance to low-income residents. Through the years, HCD has found that many of the program recipients have had difficulty in managing their households, particularly in meeting monthly financial obligations. One of the major operating costs to low-income households is the utility bill. Furthermore, HCD`s experience has revealed that many low-income residents are simply unaware of ways to reduce their utility bill. Most of the HCD funds are distributed to low-income persons as grants or no/low interest loans for the construction or rehabilitation of single-family dwellings. With these funds, HCD builds 80 to 100 new houses and renovates about 500 homes each year. Houses constructed or renovated by HCD must meet HUD`s minimum energy efficiency standards. While these minimum standards are more than adequate to meet local building codes, they are not as aggressive as the energy efficiency standards being promoted by the national utility organizations and the home building industry. Memphis Light, Gas and Water (MLGW), a city-owned utility, has developed an award-winning program named Comfort Plus which promotes energy efficiency{open_quote} in new residential construction. Under Comfort Plus, MLGW models house plans on computer for a fee and recommends cost-effective alterations which improve the energy efficiency of the house. If the builder agrees to include these recommendations, MLGW will certify the house and guarantee a maximum annual heating/cooling bill for two years. While the Comfort Plus program has received recognition in the new construction market, it does not address the existing housing stock.

Muller, D.; Norville, C. [Memphis and Shelby County Div. of Planning and Development, TN (United States)

1993-07-01T23:59:59.000Z

356

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

357

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

358

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...

359

" 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...

360

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...

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

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...

362

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...

363

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...

364

" 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...

365

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

366

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

367

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 ...

368

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...

369

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 ...

Jordán F., Pablo (Jordán Fuchs)

1984-01-01T23:59:59.000Z

370

,"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...

371

Do Firms Choose Their Stock Liquidity? A Study of Innovative Firms and Their Stock Liquidity ?  

E-Print Network (OSTI)

We ask whether firms can choose, or at least influence, their stock liquidity. We analyze a sample of firms that, we hypothesize, will value stock liquidity more than other firms – innovative firms that primarily hold intangible assets and expect to raise capital from the stock market. Consistent with their reliance on equity markets, we find that innovative firms have higher liquidity and that they take a variety of actions (e.g., frequent earnings guidance, stock splits etc) that help keep their stock more liquid. Maintaining liquidity appears to be less of a concern when innovative firms have greater access to other sources of capital. Given their low leverage, there is greater reliance on monitoring by large equity-holders and incentive contracts to help resolve agency issues, rather than banks or other creditors: consistent with the greater institutional ownership, higher likelihood of blockholders, and more incentivized CEO compensation contracts in these firms. The marginal impact on firm value (Tobin’s Q) of a plausibly exogenous increase in liquidity (e.g., following decimalization of stock prices) is greater for innovative firms, especially when CEOs have strong incentive contracts. Innovative activity tends to increase in the wake of such liquidity enhancements.

Nishant Dass; Vikram N; Steven Chong Xiao; Nikunj Kapadia; Simi Kedia; Pete Kyle; Er Ljungqvist

2012-01-01T23:59:59.000Z

372

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

373

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

374

Tebian Electric Apparatus Stock Co Ltd TBEA | Open Energy Information  

Open Energy Info (EERE)

Tebian Electric Apparatus Stock Co Ltd TBEA Tebian Electric Apparatus Stock Co Ltd TBEA Jump to: navigation, search Name Tebian Electric Apparatus Stock Co Ltd (TBEA) Place Changji, Xinjiang Autonomous Region, China Zip 831100 Sector Solar Product TBEA makes transformer products and aluminium foil, and also solar energy equipment. References Tebian Electric Apparatus Stock Co Ltd (TBEA)[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Tebian Electric Apparatus Stock Co Ltd (TBEA) is a company located in Changji, Xinjiang Autonomous Region, China . References ↑ "Tebian Electric Apparatus Stock Co Ltd (TBEA)" Retrieved from "http://en.openei.org/w/index.php?title=Tebian_Electric_Apparatus_Stock_Co_Ltd_TBEA&oldid=352059

375

NATIONAL ENERGY POLICY Taking Stock A  

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

Taking Stock Taking Stock A merica's current energy challeng- es can be met with rapidly im- proving technology, dedicated leadership, and a comprehensive approach to our energy needs. Our challenge is clear-we must use tech- nology to reduce demand for energy, re- pair and maintain our energy infrastruc- ture, and increase energy supply. Today, the United States remains the world's undisput- ed technological leader; but recent events have demonstrated that we have yet to inte- grate 21st-century technology into an ener- gy plan that is focused on wise energy use, production, efficiency, and conservation. Prices today for gasoline, heating oil, and natural gas are dramatically higher than they were only a year ago. In Califor- nia, homeowners, farmers, and businesses face soaring electricity prices, rolling

376

Maximum entropy distribution of stock price fluctuations  

E-Print Network (OSTI)

The principle of absence of arbitrage opportunities allows obtaining the distribution of stock price fluctuations by maximizing its information entropy. This leads to a physical description of the underlying dynamics as a random walk characterized by a stochastic diffusion coefficient and constrained to a given value of the expected volatility, taking in this way into account the information provided by the existence of an option market. This model is validated by a comprehensive comparison with observed distributions of both price return and diffusion coefficient. Expected volatility is the only parameter in the model and can be obtained by analysing option prices. We give an analytic formulation of the probability density function for price returns which can be used to extract expected volatility from stock option data. This distribution is of high practical interest since it should be preferred to a Gaussian when dealing with the problem of pricing derivative financial contracts.

Bartiromo, Rosario

2011-01-01T23:59:59.000Z

377

Environmental Degradation Nuclear IX-Housing Form  

Science Conference Proceedings (OSTI)

ENVIRONMENTAL DEGRADATION OF MATERIALS IN NUCLEAR POWER SYSTEMS—WATER REACTORS. HOUSING. RESERVATION FORM.

378

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

379

Transfer Entropy Analysis of the Stock Market  

E-Print Network (OSTI)

In terms of transfer entropy, we investigated the strength and the direction of information transfer in the US stock market. Through the directionality of the information transfer, the more influential company between the correlated ones can be found and also the market leading companies are selected. Our entropy analysis shows that the companies related with energy industries such as oil, gas, and electricity influence the whole market.

Baek, S K; Kwon, O; Moon, H T; Baek, Seung Ki; Jung, Woo-Sung; Kwon, Okyu; Moon, Hie-Tae

2005-01-01T23:59:59.000Z

380

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

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

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

382

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

383

“Taken from House Conference Report 108-10 FY 2003 ...  

Science Conference Proceedings (OSTI)

... in this title or from actions taken for the care ... earned in a single year from such stocks. ... enforcement and vessel monitoring, stock assessments--data ...

2012-05-29T23:59:59.000Z

384

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

385

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

386

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

387

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

388

Low Gasoline Stocks Indicate Increased Odds of Spring Volatility  

Gasoline and Diesel Fuel Update (EIA)

We cannot just focus on distillate. Gasoline will likely be our next We cannot just focus on distillate. Gasoline will likely be our next major concern. Gasoline stock levels have fallen well below the typical band for this time of year, primarily for the same reason distillate stocks fell to low levels -- namely relatively low production due to low margins. At the end of January, total gasoline inventories were almost 13 million barrels (6%) below the low end of the normal band. While gasoline stocks are generally not as important a supply source to the gasoline market this time of year as are distillate stocks to the distillate market, gasoline stocks still are needed. Gasoline stocks are usually used to help meet gasoline demand during February and March as refiners go through maintenance and turnarounds, but we do not have the

389

Last-Minute Energy Saving Stocking Stuffers | Department of Energy  

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

Last-Minute Energy Saving Stocking Stuffers Last-Minute Energy Saving Stocking Stuffers Last-Minute Energy Saving Stocking Stuffers December 23, 2013 - 12:13pm Addthis There are all sorts of small energy-efficient presents available for stuffing stockings this year. | Photo courtesy of ©iStockphoto.com/DNY59 There are all sorts of small energy-efficient presents available for stuffing stockings this year. | Photo courtesy of ©iStockphoto.com/DNY59 Christina Stowers Communications Specialist in the Office of Weatherization and Intergovernmental Program How can I participate? Keep an eye out for these small, energy saving gifts as you do your last minute shopping this year. Looking for some last minute stocking stuffers to complement the holiday gifts you've purchased for your loved ones? We covered a few

390

Low Distillate Stocks Set Stage for Price Volatility  

Gasoline and Diesel Fuel Update (EIA)

Along with the recent rise in crude oil prices, low stocks of Along with the recent rise in crude oil prices, low stocks of distillate fuels left markets in a vulnerable position. As we went into our two biggest distillate demand months, January and February, U.S. distillate stocks were very low -- particularly on the East and Gulf Coasts. The East Coast is the primary heating oil region, and it depends heavily on production from the Gulf Coast as well. Distillate stocks in the U.S. and Europe were in surplus supply as recently as October, but distillate stocks did not build as they usually do during the late fall, and declined more sharply than usual in December. December stocks closed well below the normal range. The unusual drawdown, in contrast to the more normal building pattern, resulted in distillate inventory levels about 3 million barrels lower than the very low

391

Distillate Stocks Are Important Part of Northeast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

1 of 15 1 of 15 Notes: Why do stocks matter in the Northeast? Stocks are normally an important part of PADD 1 winter distillate supply. Over the last 5 years, they provided about 15% of supply during the peak winter months of January and February. One of the biggest stock draws we have seen was in January 1994, when a prolonged severe cold spell required 666 MB/D of stocks, covering almost 36% of demand for that month. PADD 1 refineries meet about 25% of demand during January and February, and other PADDs -- mostly PADD 3 -- supply 45-50% of the regionÂ’s needs. Imports generally supply about as much as stocks during the peak months, with most of the product coming from Canada, the Virgin Islands and Venezuela. Percentages do not tell the whole story. Stocks supply close to 300

392

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

393

The investigation of the market disequilibrium in the stock market.  

E-Print Network (OSTI)

??This thesis investigated stock market disequilibrium focusing on two topics: the impact of multiple market makers on the market disequilibrium at the market microstructure level,… (more)

Park, Jin Suk

2013-01-01T23:59:59.000Z

394

Normal Butane/Butylene Refinery Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

395

NIST 2002 Stock Study of Malcolm Baldrige National Quality ...  

Science Conference Proceedings (OSTI)

... Stock Purchases. December 2, 2002 Close. Price, $ Invested, Price, $ Value, % Change. 11/2/92. CitiGroup (AT&T Universal Card Services). 44.125 ...

2011-07-14T23:59:59.000Z

396

U.S. Motor Gasoline Blending Components Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

397

East Coast (PADD 1) Crude Oil Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

398

East Coast (PADD 1) Liquefied Petroleum Gases Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

399

Stocks by Type - Rocky Mountain (PADD 4) CBOB Gasoline Blending ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

400

Rocky Mountain (PADD 4) Crude Oil Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

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

Stocks of Reformulated Gasoline - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

402

Table 3.4 Petroleum Stocks (Million Barrels)  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration / Monthly Energy Review October 2013 47 Table 3.4 Petroleum Stocks (Million Barrels) Crude Oila Distillate

403

Stocks of Total Crude Oil and Petroleum Products (Excl. SPR)  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

404

U.S. Renewable Diesel Fuel Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

405

Residuum Refinery Stocks by Type - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

406

U.S. Asphalt and Road Oil Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

407

Crude Oil Non-SPR Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

408

Conventional Gasoline Blended Bulk Terminal Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

409

U.S. Crude Oil Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

410

East Coast (PADD 1) Total Stocks - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

411

Stocks of Distillate Fuel Oil 15 ppm Sulfur and Under  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

412

Stocks of Total Crude Oil and Petroleum Products (Including SPR)  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

413

PADD 1 Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

414

Ethane/Ethylene Natural Gas Processing Plant Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

415

Stocks of SPR Crude Oil - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

416

Midwest (PADD 2) Total Stocks - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

417

MTBE Pipeline Stocks by Type - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

418

Crude Oil Tank Farms and Pipelines Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

419

Kerosene-Type Jet Fuel Refinery Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

420

Asphalt and Road Oil Bulk Terminal Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

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

Stocks of Distillate Fuel Oil - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

422

Crude Oil Strategic Petroleum Reserve Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

423

Crude Oil Alaskan in Transit Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

424

Crude Oil and Petroleum Products Bulk Terminal Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

425

Midwest (PADD 2) Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

426

Jefferson Lab Science Series - The Physics of Stock Car Racing...  

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

Archive Next Video (Understanding Flight) Understanding Flight The Physics of Stock Car Racing from a NASCAR Champion's Perspective Dr. Scott Winters - Lawrence Livermore...

427

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

of supply when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Stocks are normally an important part of PADD 1...

428

Cushing, Oklahoma Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

429

Stocks of Total Motor Gasoline - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

430

U.S. Ethane/Ethylene Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

431

Refinery Grade Butane Bulk Terminal Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

432

Isobutane/Butylene Bulk Terminal Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

433

U.S. Refinery Grade Butane Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

434

Midwest (PADD 2) Refinery Grade Butane Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

435

Gulf Coast (PADD 3) Refinery Grade Butane Stocks at Bulk ...  

U.S. Energy Information Administration (EIA)

Gulf Coast (PADD 3) Refinery Grade Butane Stocks at Bulk Terminals (Thousand Barrels) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 2005: 935: ...

436

Chapter 3. Fossil-Fuel Stocks for Electricity Generation  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration/Electric Power Monthly June 2012 69 Chapter 3. Fossil-Fuel Stocks for Electricity Generation

437

Stocks of Motor Gasoline RBOB with Alcohol Blending Components  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

438

Stocks of Finished Motor Gasoline - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

439

Stocks of All Other Motor Gasoline Blending Components  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

440

Distillate Stocks Are Important Part of East Coast Winter Supply  

U.S. Energy Information Administration (EIA)

One of the biggest stock draws we have seen was in January 1994, ... and if cold weather increases demand, resupply from these sources can take several weeks. ...

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

Stocks of Conventional Gasoline Blended with Fuel Ethanol  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

442

U.S. Propane Stocks - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Even if the near-record corn crop boosts dryer demand higher than expected, or 10 percent colder weather than normal occurs, stocks should be adequate for winter ...

443

5. Petroleum Stocks: Causes and Effects of Lower Inventories  

U.S. Energy Information Administration (EIA)

Energy Information Administration / Petroleum 1996: Issues and Trends 85 Stocks are needed to keep petroleum supplies moving smoothly from wellhead to ...

444

Hybrid Kansei-SOM model using risk management and company assessment for stock trading  

Science Conference Proceedings (OSTI)

Risk management and stock assessment are key methods for stock trading decisions. In this paper, we present a new stock trading method using Kansei evaluation integrated with a Self-Organizing Map model for improvement of a stock trading system. The ... Keywords: Hybrid intelligent trading system, Investment risk, Kansei evaluation, Risk management, Self-Organizing Map, Stock trading system

Hai V. Pham, Eric W. Cooper, Thang Cao, Katsuari Kamei

2014-01-01T23:59:59.000Z

445

Air Tightness of New U.S. Houses: A Preliminary Report  

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

Tightness of New U.S. Houses: A Preliminary Report Tightness of New U.S. Houses: A Preliminary Report Title Air Tightness of New U.S. Houses: A Preliminary Report Publication Type Report LBNL Report Number LBNL-48671 Year of Publication 2002 Authors Sherman, Max H., and Nance Matson Abstract Most dwellings in the United States are ventilated primarily through leaks in the building shell (i.e., infiltration) rather than by whole-house mechanical ventilation systems. Consequently, quantification of envelope air-tightness is critical to determining how much energy is being lost through infiltration and how much infiltration is contributing toward ventilation requirements. Envelope air tightness and air leakage can be determined from fan pressurization measurements with a blower door. Tens of thousands of unique fan pressurization measurements have been made of U.S. dwellings over the past decades. LBNL has collected the available data on residential infiltration into its Residential Diagnostics Database, with support from the U.S. Department of Energy. This report documents the envelope air leakage section of the LBNL database, with particular emphasis on new construction. The work reported here is an update of similar efforts carried out a decade ago, which used available data largely focused on the housing stock, rather than on new construction. The current effort emphasizes shell tightness measurements made on houses soon after they are built. These newer data come from over two dozen datasets, including over 73,000 measurements spread throughout a majority of the U.S. Roughly one-third of the measurements are for houses identified as energy-efficient through participation in a government or utility program. As a result, the characteristics reported here provide a quantitative estimate of the impact that energy-efficiency programs have on envelope tightness in the US, as well as on trends in construction.

446

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 in‡ation. 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

447

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

448

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:...

449

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...

450

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...

451

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...

452

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...

453

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...

454

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...

455

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...

456

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...

457

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...

458

Recent Trends in Crude Oil Stock Levels  

Gasoline and Diesel Fuel Update (EIA)

J J J J J J J J J J J J J J J J J J J J J J J J J J J J J J J J J 0 280 300 320 340 360 380 400 420 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 Average Range: 1993-1995 Recent Trends in Crude Oil Stock Levels by Aileen A. Bohn Energy Information Administration (EIA) data for March 1996 primary inventories of crude oil were the lowest recorded in almost 20 years. Crude oil inventories, which were generally on a downward trend since the beginning of 1995, fell below the average range in July 1995 and have yet to recover (Figure FE1). On September 27, 1996, crude oil stocks registered 303 million barrels, compared to a normal range of nearly 311 to 332 million barrels for September. 1 Low crude oil inventories can cause price volatility in crude oil markets. 2 When inventories are low, refiners resort to

459

Northern Gulf of Mexico Continental Shelf Stock  

E-Print Network (OSTI)

waters from 20 to 200m deep in the northern Gulf from the U.S.-Mexican border to the Florida Keys (Figure 1). Both “coastal ” and “offshore ” ecotypes of bottlenose dolphins occur in the Gulf of Mexico (Hersh and Duffield 1990; LeDuc and Curry 1998). The Continental Shelf Stock probably consists of a mixture of both the coastal and offshore ecotypes. The offshore and coastal ecotypes are genetically distinct using both mitochondrial and nuclear markers (Hoelzel et al. 1998). In the northwestern Atlantic, Torres et al. (2003) found a statistically significant break in the distribution of the ecotypes at 34 km from shore. The offshore ecotype was found exclusively seaward of 34km and in waters deeper than 34 m. Within 7.5km of shore, all animals were of the coastal ecotype. The continental shelf is much wider in the Gulf of Mexico so these results may not apply. The continental shelf stock range may extend into Mexican and Cuban territorial waters; however, there are no available estimates of either abundance or mortality from those countries. A stranded dolphin from the Florida Panhandle was rehabilitated and released over the shelf off western Florida, and traveled into the Atlantic Ocean (Wells et al. 1999). The bottlenose dolphins inhabiting waters <20m deep in

Bottlenose Dolphin (tursiops Truncatus Truncatus

2012-01-01T23:59:59.000Z

460

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

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

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

462

" 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"...

463

" 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...

464

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...

465

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....

466

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

467

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

468

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...

469

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 ...

470

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

471

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

472

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

473

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

474

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

475

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 ...

476

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

477

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

478

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

479

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

480

Paper Millionaires: How Valuable is Stock to a Stockholder Who is Restricted from Selling it?  

E-Print Network (OSTI)

this is because taking additional stock market risk helpsrisk of the restricted stock by taking o?setting positionsuse his illiquid stock as collateral for taking a net short

Kahl, Matthias; Liu, Jun; Longstaff, Francis A

2001-01-01T23:59:59.000Z

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

U.S. Atlantic and Gulf of Mexico Marine Mammal Stock Assessments -2012  

E-Print Network (OSTI)

iv U.S. Atlantic and Gulf of Mexico Marine Mammal Stock Assessments - 2012 Volume 1 Gordon T Atlantic Stock __________________________________104 Gulf Of Mexico Cetacean Species Sperm Whale (Physeter macrocephalus): Northern Gulf of Mexico Stock _______________________________112 Bryde's Whale (Balaenoptera

482

Table 2. U.S. Biodiesel Production, Sales, and Stocks  

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

U.S. Biodiesel Production, Sales, and Stocks U.S. Biodiesel Production, Sales, and Stocks (million gallons) Period 2011 January 35 22 9 17 4 February 40 27 13 17 1 March 60 41 17 19 2 April 71 47 22 21 2 May 77 50 27 23 2 June 81 62 24 19 (4)

483

Uranium Stocks in Slovenia for Nuclear Power Author: Matic Suhodolcan  

E-Print Network (OSTI)

Seminar Uranium Stocks in Slovenia for Nuclear Power Plant NEK Author: Matic Suhodolcan Supervisor and that reopening would make sense. We try to calculate the years of operating NEK only with uranium ore for reprocessing fuel. #12;Uranium Stocks in Slovenia for Slovenian Nuclear Power Plant NEK Matic Suhodolcan FMF 2

Prosen, TomaÂ?

484

Time Series Analysis and Forecasting in Stock Market Investments  

E-Print Network (OSTI)

Time Series Analysis and Forecasting in Stock Market Investments Ted Chi-Wei Fung Department and forecasting have been used as methods to help precisely on the task of stock market prediction by using past data. This paper will discuss three different models to create a time series analysis and forecast

Zanibbi, Richard

485

Value-Added Stock Loan Participation Program | Department of Energy  

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

Value-Added Stock Loan Participation Program Value-Added Stock Loan Participation Program Value-Added Stock Loan Participation Program < Back Eligibility Agricultural Savings Category Bioenergy Solar Buying & Making Electricity Wind Maximum Rebate RFA provides up to 45% of the loan up to $40,000 of loan principal Program Info Start Date 1994 State Minnesota Program Type State Loan Program Provider Minnesota Department of Agriculture The Value-Added Stock Loan Participation Program was created in 1994 and is designed to help farmers finance the purchase of stock in certain types of cooperative, limited liability company, or limited liability partnership that will produce a "value-added agricultural product." This may include wind energy and anaerobic-digestion cooperatives if they meet the

486

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: Stocks are important in the Northeast because they are the nearest source of supply when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Stocks are normally an important part of East Coast winter distillate supply. Over the last 10 years, they provided about 15% of supply during the peak winter months of January and February. One of the biggest stock draws we have seen was in January 1994, when a prolonged severe cold spell required 666,000 barrels per day of stocks, covering almost 36% of demand for that month. On average, stocks supply the East Coast with about 260,000 barrels per day on average in January and 280,000 barrels per day in February. Those supplies represent draws of about 8 million barrels in one month.

487

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

8 8 Notes: Why do stocks matter in the Northeast? They are the nearest source of supply when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Stocks are normally an important part of PADD 1 winter distillate supply. Over the last 10 years, they provided about 15% of supply during the peak winter months of January and February. One of the biggest stock draws we have seen was in January 1994, when a prolonged severe cold spell required 666 MB/D of stocks, covering almost 36% of demand for that month. Stocks supply the East Coast with about 260 MB/D on average in January and 280 MB/D in February. Those supplies represent draws of about 8 million barrels in one month. PADD 1 refineries meet about 25% of demand during January and

488

Distillate Stocks Are Important Part of Northeast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

The weather alone was not enough to cause the price spike. The low The weather alone was not enough to cause the price spike. The low stocks left the area vulnerable to sudden changes in the market, such as the weather change. Why do stocks matter in the Northeast? Stocks are normally an important part of PADD 1 winter distillate supply. Over the last 5 years, PADD 1 stocks provided about 15% of supply during the peak winter months of January and February. They are the closest source of supply to the consumer. PADD 1 depends on about 60% of its supply from distant sources such as the Gulf Coast or imports, which can take several weeks to travel to the Northeast. Even product from East Coast refineries, if capacity is available, may take a week before it is produced and delivered to the regions needing new supply. Thus, stocks must be able

489

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

Stocks are normally an important part of East Coast winter Stocks are normally an important part of East Coast winter distillate supply, since they are the nearest source when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Over the last 10 years, stocks have provided about 15% of supply during the peak winter months of January and February. On average, stocks supply the East Coast with about 260 thousand barrels per day in January and 280 in February. Those supplies represent draws of about 8 million barrels in one month. In addition, East Coast refineries meet about 25% of demand during January and February, and other regions -- mostly the Gulf Coast -- supply 40-50% of the region's needs. Imports generally supply about as much as stocks during the peak

490

Recovery May Require Holding Stocks Level in February and March  

Gasoline and Diesel Fuel Update (EIA)

have dropped back as new supplies are appearing, but we still have dropped back as new supplies are appearing, but we still have nearly a month of winter ahead of us. Stocks cannot drop much farther. February 4 stock levels were just above the lowest month-end levels ever seen for PADD 1, which occurred in April 1996. For stocks to recover to the low end of the normal range, they would have to stay level in February in March, when normally they would be used to meet demand. Keeping stocks level would require finding supply to substitute for the average stock drops of 290 thousand barrels per day (8 million barrels) in February and 210 thousand barrels per day (6 million barrels) in March. If all of that supply were to come from imports, we would have to see distillate imports into PADD 1 double from their average levels of 7

491

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

492

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

493

BOTTLENOSE DOLPHIN (Tursiops truncatus): Northern Gulf of Mexico Oceanic Stock  

E-Print Network (OSTI)

Thirty-eight stocks have been provisionally identified for Gulf of Mexico bottlenose dolphins (Waring et al. 2001). Gulf of Mexico inshore habitat has been separated into 33 bay, sound and estuarine stocks. Three northern Gulf of Mexico coastal stocks include nearshore waters from the shore to the 20 m isobath. The continental shelf stock encompasses waters from 20 to 200 m deep. The Gulf of Mexico oceanic stock encompasses the waters from the 200 m isobath to the seaward extent of the U.S. Exclusive Economic Zone (EEZ; Figure 1). Both “coastal/nearshore ” and “offshore ” ecotypes of bottlenose dolphins (Hersh and Duffield 1990) occur in the Gulf of Mexico (LeDuc and Curry 1998). The offshore and nearshore ecotypes are genetically distinct using both mitochondrial and nuclear markers (Hoelzel et al. 1998). In the northwestern Atlantic, Torres et al. (2003) found a statistically significant break in the distribution of the ecotypes at 34 km from shore. The offshore ecotype was found exclusively seaward of 34 km and in waters deeper than 34 m. Within 7.5 km of shore, all animals were of the coastal ecotype. If the distribution of ecotypes found by Torres et al. (2003) is similar in the northern Gulf of Mexico, the oceanic stock consists of the offshore ecoptype. Based on research currently being conducted on bottlenose dolphins in the Gulf of Mexico, as well as the western North Atlantic Ocean, the structure of these stocks is uncertain, but appears to be complex. The multi-disciplinary research programs conducted over the last two decades (e.g., Wells 1994) are beginning to shed light on stock structures of bottlenose dolphins, though additional analyses are needed before stock structures can be elaborated on in the Gulf of Mexico. As research is completed, it may be necessary to revise all the stocks of bottlenose dolphins in the Gulf of Mexico. POPULATION SIZE Estimates of abundance were derived through the application of distance sampling

Stock Definition; Geographic Range

2003-01-01T23:59:59.000Z

494

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

495

U.S. Propane Total Stocks  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: U.S. inventories of propane benefited from a late pre-season build that pushed inventories to over 65 million barrels by early November 2000, the second highest peak pre-heating season level since 1986. Although propane inventories were expected to remain within the normal range for the duration of the 2000-01 heating season, cold weather in November and December, along with recently high natural gas prices that discouraged propane production from gas processing, resulted in stocks falling below the normal range by the end of December. However, if the weather remains seasonally normal, and the recent decline in natural gas prices holds, EIA expects the propane inventory drawdown to slow. This is reflected in the data for January 19, which showed a draw of only 2.1 million barrels, compared to more than twice that

496

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

497

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

498

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

499

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

500

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