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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

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

2

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

3

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

4

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,

5

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

6

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.

7

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.

8

Housing  

Science Journals Connector (OSTI)

A large part of the worlds energy consumption is used in the housing and transport sectors. Any reduction in their energy consumption, for the same quality of product or service, is highly worthwhile. Housing...

Christian Ng; Marcel H. Van de Voorde

2014-01-01T23:59:59.000Z

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

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

11

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.

12

Houses undergoing psychoanalysis :  

E-Print Network [OSTI]

The objective of this thesis is to explore the relationship between the self and the house. In approaching the subject, my assumptions were that the basic condition of the house-self relationship is of tension and animosity ...

Palmon, Ruth, 1970-

2002-01-01T23:59:59.000Z

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

Comparison of the effects of floor and cage housing on the performance of five strains and crosses of egg production stocks  

E-Print Network [OSTI]

strains, found average hen housed product, on of 176 eggs for birds housed on the floor compared with 154 eggs foz compaxable b'rds in layaway batteries. The xesponse differences among stxains were incons'stent. Rowevex, Millex (19/6) reported moxe... of suz'vivors while the caged pullets showed signif icantly lower mox tality and heavier eggs, Consistent significant differences could not be demonstrated for the traits studied, namely the production index and sexual maturity. Francis {19...

Bailey, Bernice Boyce

2012-06-07T23:59:59.000Z

16

Jim Stock | Department of Energy  

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

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

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 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.

19

Key Assumptions Policy Issues  

E-Print Network [OSTI]

11/13/2014 1 Key Assumptions and Policy Issues RAAC Steering Committee November 17, 2014 Portland Supply Limitations 8 Withi h B l i8. Within-hour Balancing 9. Capacity and Energy Values for Wind/Solar t b it d d li d· Thermal: must be sited and licensed · Wind/solar: must be sited and licensed · EE

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

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

22

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

23

Section 25: Future State Assumptions  

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

the Compliance Certification Application (CCA), Chapter 6.0, Section 6.2 and Appendices SCR and MASS (U.S. DOE 1996). Many of these future state assumptions were derived from the...

24

Energy House  

Broader source: Energy.gov [DOE]

Students learn about energy conservation and efficiency by using various materials to insulate a cardboard house.

25

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

26

The case for micro-apartment housing in growing urban centers  

E-Print Network [OSTI]

Taking an analytical approach, this thesis will address how the unmet housing need of urban single-person households can be rectified by the introduction of micro-apartments. The existing housing stock has been built largely ...

Shore, Zachary, S.M. Massachusetts Institute of Technology

2014-01-01T23:59:59.000Z

27

Postdoc Housing  

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

28

Student Housing  

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

29

Meadowlark House  

Office of Energy Efficiency and Renewable Energy (EERE)

This poster describes the energy efficiency features and sustainable materials used in the Greensburg GreenTown Chain of Eco-Homes Meadowlark House in Greensburg, Kansas.

30

House Snakes  

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

31

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

Gasoline and Diesel Fuel Update (EIA)

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

32

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

Gasoline and Diesel Fuel Update (EIA)

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

33

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

Gasoline and Diesel Fuel Update (EIA)

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

34

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

Gasoline and Diesel Fuel Update (EIA)

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

35

Developing Alaskan Sustainable Housing  

Office of Energy Efficiency and Renewable Energy (EERE)

The Association of Alaska Housing Authorities is holding a 3-day training event for housing developmentprofessionals titled Developing Alaskan Sustainable Housing (DASH). This is a unique...

36

Sod Houses  

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

37

stocked inventory.PDF  

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

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

38

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.

39

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.

40

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.

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

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.

42

Assumptions to the Annual Energy Outlook 2013  

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

Act of 2006 (AB32) AB32 established a comprehensive, multi-year program to reduce Green House Gas (GHG) emissions in California, including a cap-and-trade program. In...

43

Climate Action Planning Tool Formulas and Assumptions  

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

44

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

45

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,

46

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

47

On the performance of the base-stock inventory system under a compound Erlang demand distribution  

Science Journals Connector (OSTI)

Abstract In this paper, we propose a new method for determining the optimal base-stock level in a single echelon inventory system where the demand is a compound Erlang process and the lead-time is constant. The demand inter-arrival follows an Erlang distribution and the demand size follows a Gamma distribution. The stock is controlled according to a continuous review base-stock policy where unfilled demands are backordered. The optimal base-stock level is derived based on a minimization of the total expected inventory cost. A numerical investigation is conducted to analyze the performance of the inventory system with respect to the different system parameters and also to show the outperformance of the approach that is based on the compound Erlang demand assumption as compared to the classical Newsboy approach. This work allows insights to be gained on stock control related issues for both slow and fast moving stock keeping units.

S. Saidane; M.Z. Babai; M.S. Aguir; O. Korbaa

2013-01-01T23:59:59.000Z

48

IPA Derivatives for Make-to-Stock Production-Inventory Systems With Backorders Under the (R,r) Policy  

E-Print Network [OSTI]

IPA Derivatives for Make-to-Stock Production-Inventory Systems With Backorders Under the (R Infinitesimal Perturbation Analysis (IPA) in the class of Make-to Stock (MTS) production-inventory systems regularity assumptions. The paper then analyzes the SFM counterpart and derives closed-form IPA derivative

49

House Spiders  

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

50

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.

51

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

52

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

53

Preliminary Assumptions for Natural Gas Peaking  

E-Print Network [OSTI]

Preliminary Assumptions for Natural Gas Peaking Technologies Gillian Charles and Steve Simmons GRAC, Reciprocating Engines Next steps 2 #12;Definitions Baseload Energy: power generated (or conserved) across a period of time to serve system demands for electricity Peaking Capacity: capability of power generating

54

Preliminary Assumptions for Natural Gas Peaking  

E-Print Network [OSTI]

Preliminary Assumptions for Natural Gas Peaking Technologies Gillian Charles GRAC 2/27/14 #12;Today Vernon, WA PSE Klamath Generation Peakers June 2002 (2) 54 MW P&W FT8 Twin- pac 95 MW Klamath, OR IPP; winter-only PPA w/ PSE Dave Gates Generating Station Jan 2011 (3) P&W SWIFTPAC 150 MW Anaconda, MT North

55

Empirically Revisiting the Test Independence Assumption  

E-Print Network [OSTI]

Empirically Revisiting the Test Independence Assumption Sai Zhang, Darioush Jalali, Jochen Wuttke}@cs.washington.edu ABSTRACT In a test suite, all the test cases should be independent: no test should affect any other test's result, and running the tests in any order should produce the same test results. Techniques such as test

Ernst, Michael

56

Stocking Rate Decisions  

E-Print Network [OSTI]

to predict potential forage shortfalls, determine the im- pact of the decision on finances and other ranch re- sources, and make any necessary adjustments before the forage resource is harmed or financial problems occur. Through adequate planning and periodic... rates with limited knowledge of future forage and market conditions. But they can use past records, experience and range surveys to make realistic projections of forage and market conditions (Figure 3). Then, the planned stock- ing rate should...

White, Larry D.; McGinty, Allan

1999-02-15T23:59:59.000Z

57

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

58

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

59

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.

60

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

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

Stocks, bonds and the  

Science Journals Connector (OSTI)

In this paper, we investigate the relative performance of stocks and bonds for various investment horizons on the French market. We use a new matched block bootstrap approach to take account of estimation risk. Furthermore, in the light of non-normality of returns, we use two different risk approaches as inputs in portfolio optimization: the traditional variance, and a downside risk measure, the semi-variance. Our results suggest that an investor should avoid bonds in the long run due to the time diversification effect.

Gilles Sanfilippo

2003-01-01T23:59:59.000Z

62

House Retirement Timeline  

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

63

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).

64

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

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

65

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.

66

Radon in Syrian houses  

Science Journals Connector (OSTI)

A nationwide investigation of radon levels in Syrian houses was carried out during the period 1991 - 1993. Passive radon diffusion dosemeters using polycarbonate detectors were distributed in houses all over Syria. Detectors were subjected to electrochemical etching to reveal latent tracks of alpha particles. The mean radon concentration in Syrian houses was found to be with some values several times higher. This investigation indicated that there were a few houses in Syria that require remedial action. Most houses that have high levels of radon were found in the southern area, especially in the Damascus governorate. The study also indicated that radon concentrations were higher in old houses built from mud with no tiling.

I Othman; M Hushari; G Raja; A Alsawaf

1996-01-01T23:59:59.000Z

67

Manufacturing Energy and Carbon Footprint Definitions and Assumptions, October 2012  

Broader source: Energy.gov [DOE]

Definitions of parameters and table of assumptions for the Manufacturing Energy and Carbon Footprint

68

Pacific Housing | Open Energy Information  

Open Energy Info (EERE)

Housing Jump to: navigation, search Name: Pacific Housing Place: Sacramento, CA Website: http:www.pacifichousing.com References: Pacific Housing1 Information About Partnership...

69

Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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...

70

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

71

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

72

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

73

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.

74

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

75

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

76

" Million Housing Units, Final...  

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

2 Fuels Used and End Uses in U.S. Homes, by OwnerRenter Status, 2009" " Million Housing Units, Final" ,,,,"Housing Unit Type" ,,,,"Single-Family Units",,,,"Apartments in Buildings...

77

" Million Housing Units, Final...  

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

2 Household Demographics of U.S. Homes, by OwnerRenter Status, 2009" " Million Housing Units, Final" ,,,,"Housing Unit Type" ,,,,"Single-Family Units",,,,"Apartments in Buildings...

78

Insulator for laser housing  

DOE Patents [OSTI]

The present invention provides a heat-resistant electrical insulator adapted for joining laser housing portions, which insulator comprises: an annulus; a channel in the annulus traversing the circumference and length of the housing; at least two ports, each communicating with the channel and an outer surface of the housing; and an attachment for securely attaching each end of the annulus to a laser housing member.

Duncan, David B. (Auburn, CA)

1992-01-01T23:59:59.000Z

79

Insulator for laser housing  

DOE Patents [OSTI]

The present invention provides a heat-resistant electrical insulator adapted for joining laser housing portions, which insulator comprises: an annulus; a channel in the annulus traversing the circumference and length of the housing; at least two ports, each communicating with the channel and an outer surface of the housing; and an attachment for securely attaching each end of the annulus to a laser housing member. 3 figs.

Duncan, D.B.

1992-12-29T23:59:59.000Z

80

EcoHouse Program Overview  

Broader source: Energy.gov [DOE]

Provides an overview of the Indianapolis Better Buildings program, the EcoHouse program, and Indianapolis Neighborhood Housing partnership (INHP).

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

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).

82

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).

83

NREL: Housing Information  

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

84

Persistent collective trend in stock markets  

Science Journals Connector (OSTI)

Empirical evidence is given for a significant difference in the collective trend of the share prices during the stock index rising and falling periods. Data on the Dow Jones Industrial Average and its stock components are studied between 1991 and 2008. Pearson-type correlations are computed between the stocks and averaged over stock pairs and time. The results indicate a general trend: whenever the stock index is falling the stock prices are changing in a more correlated manner than in case the stock index is ascending. A thorough statistical analysis of the data shows that the observed difference is significant, suggesting a constant fear factor among stockholders.

Emeric Balogh; Ingve Simonsen; Blint Zs. Nagy; Zoltn Nda

2010-12-13T23:59:59.000Z

85

2010 Manufacturing Energy and Carbon Footprints: Definitions and Assumptions  

Broader source: Energy.gov [DOE]

This 13-page document provides definitions and assumptions used in the Manufacturing Energy and Carbon Footprints (MECS 2010)

86

" Million Housing Units, Final...  

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

1 Space Heating in U.S. Homes in West Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"West Census Region" ,,,"Mountain Census Division",,,"Pacific...

87

" Million Housing Units, Final...  

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

0 Household Demographics of Homes in South Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"South Census Region" ,,,"South Atlantic Census...

88

" Million Housing Units, Final...  

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

0 Fuels Used and End Uses in Homes in South Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"South Census Region" ,,,"South Atlantic Census...

89

" Million Housing Units, Final...  

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

1 Household Demographics of Homes in West Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"West Census Region" ,,,"Mountain Census Division",,,"Pacific...

90

" Million Housing Units, Final...  

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

HC.1.11 Fuels Used and End Uses in Homes in West Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"West Census Region" ,,,"Mountain Census...

91

" Million Housing Units, Final...  

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

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

92

" Million Housing Units, Final...  

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

8 Space Heating in U.S. Homes in Northeast Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"Northeast Census Region" ,,,"New England Census...

93

" Million Housing Units, Final...  

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

9 Household Demographics of Homes in Midwest Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"Midwest Census Region" ,,,"East North Central Census...

94

" Million Housing Units, Final...  

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

9 Space Heating in U.S. Homes in Midwest Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"Midwest Census Region" " ",,,"East North Central Census...

95

" Million Housing Units, Final...  

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

9 Fuels Used and End Uses in Homes in Midwest Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"Midwest Census Region" ,,,"East North Central Census...

96

HOUSE PASSES ENERGY BILLS  

Science Journals Connector (OSTI)

Among the dissimilarities, the House bill would require that, by 2020, utilities generate 15% of their electricity from renewable sourceswind, solar, and hydropower. ...

JEFF JOHNSON

2007-08-13T23:59:59.000Z

97

Thermal Insulation of Houses  

Science Journals Connector (OSTI)

... THE Thermal Insulation (Dwellings) Bill which Mr. G. Nabarro introduced into the House of Commons on ... , sponsored by members of both major political parties, extends the principle of the Thermal Insulation (Industrial Buildings) Act of July 1957 to all new dwelling houses built in the ...

1958-02-22T23:59:59.000Z

98

Multiple pump housing  

DOE Patents [OSTI]

A fluid delivery system includes a first pump having a first drive assembly, a second pump having a second drive assembly, and a pump housing. At least a portion of each of the first and second pumps are located in the housing.

Donoho, II, Michael R. (Edelstein, IL); Elliott, Christopher M. (Metamora, IL)

2010-03-23T23:59:59.000Z

99

" Million U.S. Housing Units"  

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

0 Home Appliances Usage Indicators by Type of Housing Unit, 2005" " Million U.S. Housing Units" ,,"Type of Housing Unit" ," Housing Units (millions) ","Single-Family...

100

Quantum Brownian motion model for stock markets  

E-Print Network [OSTI]

We investigate the relevance between quantum open systems and stock markets. A Quantum Brownian motion model is proposed for studying the interaction between the Brownian system and the reservoir, i.e., the stock index and the entire stock market. Based on the model, we investigate the Shanghai Stock Exchange of China from perspective of quantum statistics, and thereby examine the behaviors of the stock index violating the efficient market hypothesis, such as fat-tail phenomena and non-Markovian features. Our interdisciplinary works thus help to discovery the underlying quantum characteristics of stock markets and develop new research fields of econophysics.

Meng, Xiangyi; Guo, Hong

2014-01-01T23:59:59.000Z

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.


101

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

102

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.

103

Peoria Housing Authority(PHA) Weatherization Training Project  

SciTech Connect (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

104

Developing Alaskan Sustainable Housing Training  

Broader source: Energy.gov [DOE]

Hosted by the Association of Alaska Housing Authorities (AAHA), this three-day training event covers strategies and technical issues related to sustainable housing development.

105

Pet House Sparrow  

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

106

ORNL Guest House  

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

107

Stocking Rate: The Key Grazing Management Decision  

E-Print Network [OSTI]

Stocking rate is the most important grazing management decision a rancher makes. This publication covers all the factors involved in determining an appropriate stocking rate, including rainfall and forage production, range condition, and the forage...

Lyons, Robert K.; Machen, Richard V.

2001-07-19T23:59:59.000Z

108

Privacy Threats in Online Stock Quotes  

Science Journals Connector (OSTI)

Stock traders reveal information about their pending trades by their selection of stock performance data to retrieve from the web. Potentially malicious quote publishers have access to this information, and ca...

Peter Williams

2008-01-01T23:59:59.000Z

109

Essays on macroeconomic risks and stock prices  

E-Print Network [OSTI]

In this thesis, I study the relationship between macroeconomic risks and asset prices. In the first chapter, I establish that inflation risk is priced in the cross-section of stock returns: stocks that have low returns ...

Duarte, Fernando Manuel

2011-01-01T23:59:59.000Z

110

Islamic Finance Bulletin Conventional Stock Markets 2  

E-Print Network [OSTI]

by about 6 percent. There were signs of revival in the Tunisian economy after Qatar extended a USD 1- lar increased from oil importers, and as #12;StockMarkets Table 2: Evolution of Islamic Stock Markets

Meju, Max

111

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

112

Principles of Passive House  

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

113

Cost Effective Sustainable Housing.  

E-Print Network [OSTI]

??Cost Effective Sustainable Housing The topic of research which was discussed throughout this study was an analysis of sustainable development between single-family and multi-family structures. (more)

Morton, Joshua

2009-01-01T23:59:59.000Z

114

" Million Housing Units, Final...  

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

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

115

" Million Housing Units, Final...  

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

3 Space Heating 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...

116

" Million Housing Units, Final...  

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

5 Fuels Used and End Uses in U.S. Homes, by Household Income, 2009" " Million Housing Units, Final" ,,"Household Income" ,"Total U.S.1 (millions)",,,"Below Poverty Line2"...

117

" Million Housing Units, Final...  

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

7 Space Heating in U.S. Homes, by Census Region, 2009" " Million Housing Units, Final" ,,"Census Region" ,"Total U.S.1 (millions)" ,,"Northeast","Midwest","South","West" "Space...

118

" Million Housing Units, Final...  

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

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

119

" Million Housing Units, Final...  

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

4 Space Heating in U.S. Homes, by Number of Household Members, 2009" " Million Housing Units, Final" ,,"Number of Household Members" ,"Total U.S.1 (millions)" ,,,,,,"5 or More...

120

" Million Housing Units, Final...  

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

6 Space Heating 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"...

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

Houses for Dorchester  

E-Print Network [OSTI]

The intent of this thesis is to develop a design for thirty units of housing responding to the development objectives of the Nuestra Comunidad Development Corporation (NCDC) in the Upham Corner district of Dorchester. It ...

Chalmers, Thomas C. (Thomas Clark)

1987-01-01T23:59:59.000Z

122

Indian Housing Training Conference  

Broader source: Energy.gov [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...

123

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.

124

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

125

MONITORED GEOLOGIC REPOSITORY LIFE CYCLE COST ESTIMATE ASSUMPTIONS DOCUMENT  

SciTech Connect (OSTI)

The purpose of this assumptions document is to provide general scope, strategy, technical basis, schedule and cost assumptions for the Monitored Geologic Repository (MGR) life cycle cost (LCC) estimate and schedule update incorporating information from the Viability Assessment (VA) , License Application Design Selection (LADS), 1999 Update to the Total System Life Cycle Cost (TSLCC) estimate and from other related and updated information. This document is intended to generally follow the assumptions outlined in the previous MGR cost estimates and as further prescribed by DOE guidance.

R.E. Sweeney

2001-02-08T23:59:59.000Z

126

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

127

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

SciTech Connect (OSTI)

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

128

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

SciTech Connect (OSTI)

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

129

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

130

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

131

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

132

Idaho National Engineering Laboratory installation roadmap assumptions document. Revision 1  

SciTech Connect (OSTI)

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

133

Argonne Open House 2009  

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

134

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

135

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

136

THE WHITE HOUSE | Department of Energy  

Energy Savers [EERE]

THE WHITE HOUSE THE WHITE HOUSE THE WHITE HOUSE More Documents & Publications FACT SHEET: U.S.-China Clean Energy Cooperation Announcements US-China Clean Energy Cooperation...

137

THE WHITE HOUSE | Department of Energy  

Office of Environmental Management (EM)

THE WHITE HOUSE THE WHITE HOUSE THE WHITE HOUSE More Documents & Publications Audit Report: IG-0473 Lapse Documents Inspection Report: IG-0397...

138

Sod House Furnishings  

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

139

Controlling House Sparrows  

E-Print Network [OSTI]

T he English or house sparrow is a very common resident in urban and suburban areas. Introduced from Europe, the sparrow has spread over the entire United States and is found almost everywhere in Texas. It is an aggressive, adaptable bird that nests...

Texas Wildlife Services

2008-04-15T23:59:59.000Z

140

Housing services Zinfandel Hall  

E-Print Network [OSTI]

resources, the library, and the Internet. The Community has its own dining hall, swimming pools, study roomsHousing services Zinfandel Hall (707) 664-2541 Fax: (707) 664-4158 e-mail: ssu hall suites and campus apartments, all located just seconds from the main campus classroom buildings

Ravikumar, B.

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

White House honors Los Alamos  

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

White House honors Los Alamos physicist's early career work July 10, 2009 Los Alamos, New Mexico, July 10, 2009-The White House today announced that Los Alamos National Laboratory...

142

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

143

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

144

Queens College Louis Armstrong House  

E-Print Network [OSTI]

Queens College Louis Armstrong House Louis Armstrong House Museum "From a humble, two-room shack Armstrong. Armstrong lived for nearly three decades in the modest, brick-fronted Corona, Queens home that today is the Louis Armstrong House Museum, which is partnered with Queens College, and open

Rosen, Jay

145

Which Reduces Vehicle Travel More: Jobs-Housing Balauce or Retail-Housing Mixing?  

E-Print Network [OSTI]

More: Jobs-Housing Balance or Retail-Housing Mixing? 2. TheMore: Jobs-Housing Balauce or Retail-Housing Mixing? Robertto housing or bringing retail and consumer services closer

Cervero, Robert; Duncan, Michael

2008-01-01T23:59:59.000Z

146

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

147

Fermilab Family Open House  

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

148

Bachelor Project StockHome -Web Application  

E-Print Network [OSTI]

Bachelor Project StockHome - Web Application User interface for a financial analysis tool Gilad and assisting us during dark times. Last but not least, I would like to thank my friends who spent those long . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 iii #12;Gilad Geron StockHome - Web Application A Technologies 31 A.1 Ruby

Lanza, Michele

149

TRAWLING AND THE STOCKS OF FISH  

Science Journals Connector (OSTI)

... before the Royal Society of Arts on January 27 on Trawling and the Stocks of Fish, Dr. E. S. Russell, director of fishery investigations, Ministry of Agriculture ... manner the problems which will confront us after the War in connexion with the national fish stocks of Great Britain and those of our near neighbours. In a summary of ...

1943-03-20T23:59:59.000Z

150

Housing characteristics 1993  

SciTech Connect (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

151

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

152

COMPARING ALASKA'S OIL PRODUCTION TAXES: INCENTIVES AND ASSUMPTIONS1  

E-Print Network [OSTI]

1 COMPARING ALASKA'S OIL PRODUCTION TAXES: INCENTIVES AND ASSUMPTIONS1 Matthew Berman In a recent analysis comparing the current oil production tax, More Alaska Production Act (MAPA, also known as SB 21 oil prices, production rates, and costs. He noted that comparative revenues are highly sensitive

Pantaleone, Jim

153

Reasoning by Assumption: Formalisation and Analysis of Human Reasoning Traces  

E-Print Network [OSTI]

for the traces acquired in experiments undertaken. 1 Introduction Practical reasoning processes are often not limited to single reasoning steps, but extend to traces or trajectories of a number of interrelated by assumption'. This (non-deductive) practical reasoning pattern in- volves a number of interrelated reasoning

Treur, Jan

154

Flying Squirrels and Houses  

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

155

Systematic analysis of group identification in stock markets  

Science Journals Connector (OSTI)

We propose improved methods to identify stock groups using the correlation matrix of stock price changes. By filtering out the marketwide effect and the random noise, we construct the correlation matrix of stock groups in which nontrivial high correlations between stocks are found. Using the filtered correlation matrix, we successfully identify the multiple stock groups without any extra knowledge of the stocks by the optimization of the matrix representation and the percolation approach to the correlation-based network of stocks. These methods drastically reduce the ambiguities while finding stock groups using the eigenvectors of the correlation matrix.

Dong-Hee Kim and Hawoong Jeong

2005-10-25T23:59:59.000Z

156

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":""}]}

157

PROJECT MANGEMENT PLAN EXAMPLES Policy & Operational Decisions, Assumptions  

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

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.

158

Cost and Performance Assumptions for Modeling Electricity Generation Technologies  

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

159

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

160

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

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

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

162

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

163

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.

164

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

165

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.

166

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.

167

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.

168

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

169

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 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

170

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

171

,"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"

172

The 2005 Solar D House  

E-Print Network [OSTI]

. UT Solar D House This isnt the only technology that makes life easier in this house. Besides a bevy of energy efficient appliances and lighting, which reduce energy costs, theres so much more. Even the appliances contribute, with features...-profit, where the house will be used as a learning center for low-income families as transitional housing. As part of their mission statement, the UT SolarD Team hopes to inspire the Austin public about the benefits of solar-powered, energy...

Garrison, M.

2006-01-01T23:59:59.000Z

173

Political Risk and Stock Market Development  

Science Journals Connector (OSTI)

This article examines empirically the relationship between political instability and stock market development in a small capital market (the Greek capital market). We measure socio-political instability by con...

Costas Siriopoulos; Dimitrios Asteriou

1998-01-01T23:59:59.000Z

174

Credit Conditions and Stock Return Predictability  

E-Print Network [OSTI]

This dissertation examines stock return predictability with aggregate credit conditions. The aggregate credit conditions are empirically measured by credit standards (Standards) derived from the Federal Reserve Board's Senior Loan Officer Opinion...

Park, Heungju

2012-10-19T23:59:59.000Z

175

Skewness in individual stocks at different investment  

Science Journals Connector (OSTI)

This paper examines the (a)symmetry of several individual stock returns at different investment horizons: daily, weekly and monthly. While some asymmetries are observed in daily returns, they disappear almost completely in weekly and monthly returns. The explanation for this fact lies in the convergence to normality that takes place when the investment horizon increases. These features allow one to question several financial models; in particular, they question the preference for positive skewness as a factor for investments in stock markets.

Amado Peir

2002-01-01T23:59:59.000Z

176

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

177

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

178

Diversion assumptions for high-powered research reactors  

SciTech Connect (OSTI)

This study deals with diversion assumptions for high-powered research reactors -- specifically, MTR fuel; pool- or tank-type research reactors with light-water moderator; and water, beryllium, or graphite reflectors, and which have a power level of 25 MW(t) or more. The objective is to provide assistance to the IAEA in documentation of criteria and inspection observables related to undeclared plutonium production in the reactors described above, including: criteria for undeclared plutonium production, necessary design information for implementation of these criteria, verification guidelines including neutron physics and heat transfer, and safeguards measures to facilitate the detection of undeclared plutonium production at large research reactors.

Binford, F.T.

1984-01-01T23:59:59.000Z

179

THE WHITE HOUSE  

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

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

180

Information House Committee on Transportation  

E-Print Network [OSTI]

. The energy efficiency and environmental advantage of rail over trucks are well established in terms Information For the House Committee on Transportation House Committee with the Port of Houston ranking as the largest port in the US in terms of import tonnage. The Gulf

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

Viable Algae in House Dust  

Science Journals Connector (OSTI)

... two culture media: Bristol8 and modified Chu No. 10 (ref. 9). Viable algae were cultured from all the dust samples taken from forty -one homes. In these ... 1). Samples from three commercial producers of house dust allergenic extract also revealed viable algae (Table 2). In general, the algal organisms found in house dust used in ...

I. LEONARD BERNSTEIN; ROBERT S. SAFFERMAN

1970-08-22T23:59:59.000Z

182

Software and House Requirements Engineering  

E-Print Network [OSTI]

a requirements engineer who puts her knowledge of software construction together with her creativity to come upSoftware and House Requirements Engineering: Lessons Learned in Combatting Requirements Creep creativity to try to come up with a plan for a house that will meet the customer's requirements. The customer

Berry, Daniel M.

183

The European Passive House Concept  

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

184

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.

185

Assumptions to the Annual Energy Outlook 2000 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

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

186

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.

187

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).

188

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.

189

The contour method cutting assumption: error minimization and correction  

SciTech Connect (OSTI)

The recently developed contour method can measure 2-D, cross-sectional residual-stress map. A part is cut in two using a precise and low-stress cutting technique such as electric discharge machining. The contours of the new surfaces created by the cut, which will not be flat if residual stresses are relaxed by the cutting, are then measured and used to calculate the original residual stresses. The precise nature of the assumption about the cut is presented theoretically and is evaluated experimentally. Simply assuming a flat cut is overly restrictive and misleading. The critical assumption is that the width of the cut, when measured in the original, undeformed configuration of the body is constant. Stresses at the cut tip during cutting cause the material to deform, which causes errors. The effect of such cutting errors on the measured stresses is presented. The important parameters are quantified. Experimental procedures for minimizing these errors are presented. An iterative finite element procedure to correct for the errors is also presented. The correction procedure is demonstrated on experimental data from a steel beam that was plastically bent to put in a known profile of residual stresses.

Prime, Michael B [Los Alamos National Laboratory; Kastengren, Alan L [ANL

2010-01-01T23:59:59.000Z

190

Multi-Family Housing Loans and Grants  

Broader source: Energy.gov [DOE]

Multi-family housing programs offer rural rental housing loans to provide affordable multi-family rental housing for very low-, low-, and moderate-income families, the elderly, and persons with...

191

PPPL Open House | Princeton Plasma Physics Lab  

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

June 1, 2013, 9:00am to 4:00pm Open House at Princeton Plasma Physics Laboratory PPPL Open House Hot Plasma, Cool Science: Princeton Plasma Physics Lab Open House on June 1 Mark...

192

Open House | Princeton Plasma Physics Lab  

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

Contact Us Open House PPPL Open House Saturday, June 1 9 a.m. to 4 p.m. Princeton Plasma Physics Laboratory 100 Stellarator Road Princeton, NJ, 08540 OPEN HOUSE PROGRAM BOOKLET...

193

Building Technologies Office: House Simulation Protocols Report  

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

194

Building Technologies Office: Housing Innovation Awards  

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

195

" Million U.S. Housing Units"  

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

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

196

" Million U.S. Housing Units"  

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

0 Home Appliances Usage Indicators by Year of Construction, 2005" " Million U.S. Housing Units" ,,"Year of Construction" ,"Housing Units (millions)" ,,"Before 1940","1940 to...

197

Better Buildings Challenge Expands to Multifamily Housing  

Broader source: Energy.gov [DOE]

The U.S. Departments of Energy and Housing and Urban Development expanded the Better Buildings Challenge to multifamily housing such as apartments and condominiums.

198

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

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

CDD or More and Less than 4,000 HDD Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

199

Before the House Subcommittee on Investigations & Oversight ...  

Energy Savers [EERE]

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

200

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

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
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201

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

202

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

203

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.

204

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.

205

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

206

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).

207

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).

208

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

209

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.

210

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.

211

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).

212

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.

213

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

214

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).

215

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

216

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

217

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

218

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

219

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.

220

Assumptions to the Annual Energy Outlook - International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

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

Note: This page contains sample records for the topic "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

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

222

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).

223

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

224

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).

225

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).

226

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

227

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)

228

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.

229

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

230

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.

231

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

232

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

233

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),

234

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

235

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

236

Public housing renovation : an opportunity for a better housing environment  

E-Print Network [OSTI]

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

Jordn F., Pablo (Jordn Fuchs)

1984-01-01T23:59:59.000Z

237

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

E-Print Network [OSTI]

In the wake of the next large-scale earthquake in the city of San Francisco, an expected 85,000 households are expected to become uninhabitable and beyond repair, leaving thousands of residents with immediate needs for ...

Saiyed, Zahraa N.

238

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 +

239

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

240

Engineer in the White House  

Science Journals Connector (OSTI)

... of Staff at the White House is a powerful figure. The present incumbent, Mr John Sununu, has the distinction of having himself run for elected office and of being ...

John Maddox

1990-03-08T23:59:59.000Z

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.


241

White House Tribal Nations Conference  

Broader source: Energy.gov [DOE]

On December 5, 2012, President Obama will host representatives invited from each of the 566 federally recognized American Indian tribes, and Alaska Native Villages, at the 2012 White House Tribal...

242

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

243

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).

244

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.

245

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

246

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).

247

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.

248

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.

249

Rangeland Drought Management for Texans: Stocking Rate and Grazing Management  

E-Print Network [OSTI]

This publication explains how stocking rates and grazing management decisions can help a ranch survive a drought. To deal with drought, a rancher must monitor forage supply and demand; use a conservative stocking rate and keep it flexible...

Hart, Charles R.; Carpenter, Bruce B.

2001-05-03T23:59:59.000Z

250

Predicting stock returns and assessing prediction performance  

Science Journals Connector (OSTI)

......found that in the USA, 47% of investments were made by households with an average annual turnover of over 75% of stocks held...effects in data from the USA, the UK, France, Germany and Japan, and conclude that data snooping is not a major problem......

Rose Baker; Alexander Belgorodskiy

2007-10-01T23:59:59.000Z

251

Wild oil prices, but brave stock markets! The case of GCC stock markets  

Science Journals Connector (OSTI)

Using a vector autoregression (VAR) analysis, this paper investigates the effect of the sharp increase in oil prices on stock market returns for five Gulf ... to 24 May, 2005. During this period oil price has bee...

Bashar Abu Zarour

252

Market Maker Inventories and Stock Prices Terrence Hendershott  

E-Print Network [OSTI]

complement past returns when predicting return reversals. A portfolio long high-inventory/low-return stocks and short low-inventory/high-return stocks yields 1.05% over the following 5 days. Order imbalancesMarket Maker Inventories and Stock Prices Terrence Hendershott U.C. Berkeley Mark S. Seasholes U

Kearns, Michael

253

Assessment of the eel stock in Sweden, spring 2012  

E-Print Network [OSTI]

Assessment of the eel stock in Sweden, spring 2012 Aqua reports 2012:9 First post-evaluation of the Swedish Eel Management Plan Willem Dekker #12;Assessment of the eel stock in Sweden, spring 2012 First: Dekker, W. (2012). Assessment of the eel stock in Sweden, spring 2012. First post

254

On the self-similarity assumption in dynamic models for large eddy simulations  

E-Print Network [OSTI]

that the present formulation of the DP is usually incompatible with its under- lying self-similarity assumption SSAOn the self-similarity assumption in dynamic models for large eddy simulations Daniele Carati eddy simulations and their underlying self-similarity assumption is discussed. The interpretation

Van Den Eijnden, Eric

255

HVAC Improvements for Existing Houses  

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

256

Aluminium in-use stocks in the state of Connecticut  

Science Journals Connector (OSTI)

The in-use stock of aluminium in the State of Connecticut, USA, has been established by an extensive bottom-up study. For year 2000, the results are a total stock of 1.21.4Tg Al, or 360400kg Al per capita. The per capita stock amount is similar to that derived in a recent study in Japan. Infrastructure & buildings contains nearly 60% of the total stock, and transportation vehicles nearly 40%. The aluminium in equipment of various kinds amounts to only about 2% of the total, and packaging stock is less than 1%.

Korinti Recalde; Jinlong Wang; T.E. Graedel

2008-01-01T23:59:59.000Z

257

On-site Housing Rates | Staff Services  

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

258

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

259

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

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

260

NATIONAL ENERGY POLICY Taking Stock A  

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

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

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

Energy Savers [EERE]

House Natural Resources Subcommittee on Water and Power Before the House Natural Resources Subcommittee on Water and Power Before the House Natural Resources Subcommittee on Water...

262

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

Energy Savers [EERE]

the House Natural Resources Subcommittee on Water and Power Before the House Natural Resources Subcommittee on Water and Power Before the House Natural Resources Subcommittee on...

263

2014 Housing Innovation Awards DOE Challenge Home Application...  

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

2014 Housing Innovation Awards DOE Challenge Home Application 2014 Housing Innovation Awards DOE Challenge Home Application The U.S. Department of Energy's Housing Innovation...

264

Building America Whole-House Solutions for New Homes: Affordable...  

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

New Homes: Affordable Cold Climate Infill Housing with Hybrid Insulation Approach Building America Whole-House Solutions for New Homes: Affordable Cold Climate Infill Housing with...

265

Building America Whole-House Solutions for Existing Homes: Islip...  

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

Islip Housing Authority Energy Efficiency Turnover Protocols, Islip, New York Building America Whole-House Solutions for Existing Homes: Islip Housing Authority Energy Efficiency...

266

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

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

House Committee on Science, Space, and Technology Before House Committee on Science, Space, and Technology Before House Committee on Science, Space, and Technology By: Peter Lyons...

267

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

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

the House Science, Space, and Technology Committee Before the House Science, Space, and Technology Committee Before the House Science, Space, and Technology Committee By: David...

268

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

Energy Savers [EERE]

House Science and Technology Committee Before the House Science and Technology Committee Before the House Science and Technology Committee By: Arun Majumdar, Director Advanced...

269

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

Office of Environmental Management (EM)

House Committee on Science, Space and Technology Before House Committee on Science, Space and Technology Before House Committee on Science, Space and Technology By: Secretary...

270

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

Office of Environmental Management (EM)

House Science and Technology Committee Before the House Science and Technology Committee Before the House Science and Technology Committee By: Warren F. Miller Jr., Assistant...

271

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

Office of Environmental Management (EM)

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...

272

Just Suppose: Housing Subsidies for Low Income Renters  

E-Print Network [OSTI]

bonds Low-income housing tax credit Homeowner Multifamilybonds Low-income housing tax credit Fiscal year Fiscal yearthe Low Income Housing Tax Credit (LIHTC) program to provide

Quigley, John M.

2007-01-01T23:59:59.000Z

273

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

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

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...

274

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

Office of Environmental Management (EM)

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...

275

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

276

Kevin Smith Sutherland House 234  

E-Print Network [OSTI]

Kevin Smith Sutherland House 234 PMB 3342 Nashville, TN 37235 January 27, 2010 Mr. Scott at Kevin.m.smith@vanderbilt.edu or by phone at (543)3843909. Thank you for your consideration. Sincerely, Kevin Smith The cover letter needs to be in business letter format...this includes

Bordenstein, Seth

277

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

278

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

Gasoline and Diesel Fuel Update (EIA)

... 13.2 10.2 0.6 0.3 1.1 1.1 Table HC2.10 Home Appliances Usage Indicators by Type of Housing Unit, 2005 Housing Units (millions) Single-Family Units...

279

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

280

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

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

Lockout housing and sleeve for safety valve  

SciTech Connect (OSTI)

This patent describes apparatus for use in a subsurface valve. It comprises a lockout housing; and a lockout sleeve.

Dickson, R.L.; Davis, G.R.

1992-07-07T23:59:59.000Z

282

Inside the White House: Solar Panels  

Broader source: Energy.gov [DOE]

Go inside the White House and learn about the installation of solar panels on the roof of the residence.

283

Federal Housing Administration's Energy Efficient Mortgage Program  

Broader source: Energy.gov [DOE]

Describes the U.S. Department of Housing and Urban Development Energy Efficient Mortgage Program which helps homebuyers or homeowners save money on utility bills by enabling them to finance the cost of adding energy efficiency features to new or existing housing. Authors: U.S. Department of Housing and Urban Development

284

White House Forum on Minorites in Energy  

Broader source: Energy.gov [DOE]

On November 13, 2013, the Department of Energy and the White House Office of Science and Technology Policy, the Council for Environmental Quality, and the White House Office of Public Engagement co-hosted the White House Forum on Minorities in Energy. The event included the announcement of the Ambassadors for the Minorities in Energy Initiative.

285

Last-Minute Energy Saving Stocking Stuffers | Department of Energy  

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

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

286

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

287

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 region’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

288

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

289

Puerto Rico House Tours Report  

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

290

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

291

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 using an overhead crane. The 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.

Ross, Maurice J. (Pocatello, ID); Zaladonis, Larry A. (Idaho Falls, ID)

1988-09-27T23:59:59.000Z

292

Evergreen Sustainable Development Standard for Affordable Housing |  

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

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

293

New Developments in Hog Houses and Equipment.  

E-Print Network [OSTI]

for the central house are the half-monitor and the gable-roof. The half-monitor house should be set lengthwise east and west so that the windows face south, while the gable-roof house should be set lengthwise north and south so that the rays of the sun... will shine through the sky-light windows on the east side in the morning, and those on the west side in the afternoon. The central house is better adapted for one who is in the hog business on a larger scale than the average. This house permits a number...

Hale, Fred; Smith, H. P. (Harris Pearson)

1933-01-01T23:59:59.000Z

294

Status of the eel stock in Sweden in 2011  

E-Print Network [OSTI]

Status of the eel stock in Sweden in 2011 Willem Dekker Håkan Wickström Jan Andersson Aqua reports of the eel stock in Sweden in 2011 By Willem Dekker, Håkan Wickström & Jan Andersson October 2011 SLU: Dekker, W., Wickström, H. & Andersson, J. (2011). Status of the eel stock in Sweden in 2011. Aqua reports

295

The house of the future  

ScienceCinema (OSTI)

Learn what it will take to create tomorrow's net-zero energy home as scientists reveal the secrets of cool roofs, smart windows, and computer-driven energy control systems. The net-zero energy home: Scientists are working to make tomorrow's homes more than just energy efficient -- they want them to be zero energy. Iain Walker, a scientist in the Lab's Energy Performance of Buildings Group, will discuss what it takes to develop net-zero energy houses that generate as much energy as they use through highly aggressive energy efficiency and on-site renewable energy generation. Talking back to the grid: Imagine programming your house to use less energy if the electricity grid is full or price are high. Mary Ann Piette, deputy director of Berkeley Lab's building technology department and director of the Lab's Demand Response Research Center, will discuss how new technologies are enabling buildings to listen to the grid and automatically change their thermostat settings or lighting loads, among other demands, in response to fluctuating electricity prices. The networked (and energy efficient) house: In the future, your home's lights, climate control devices, computers, windows, and appliances could be controlled via a sophisticated digital network. If it's plugged in, it'll be connected. Bruce Nordman, an energy scientist in Berkeley Lab's Energy End-Use Forecasting group, will discuss how he and other scientists are working to ensure these networks help homeowners save energy.

None

2010-09-01T23:59:59.000Z

296

Automatic stock market trading based on Technical Analysis.  

E-Print Network [OSTI]

?? The theory of technical analysis suggests that future stock price developement can be foretold by analyzing historical price fluctuations and identifying repetitive patterns. A (more)

Larsen, Fredrik

2007-01-01T23:59:59.000Z

297

Whole-House Ventilation | Department of Energy  

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

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

298

Our Hand in Greening the White House  

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

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

299

House Simulation Protocols Report | Department of Energy  

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

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

300

Housing Archetype Analysis for Home Energy-Efficient Retrofit in the Great Lakes Region  

SciTech Connect (OSTI)

This project report details activities and results of the 'Market Characterization' project undertaken by the Cost Effective Energy Retrofit (CEER) team targeted toward the DOE goal of achieving 30%-50% reduction in existing building energy use. CEER consists of members from the Dow Chemical Company, Michigan State University, Ferris State University and Habitat for Humanity Kent County. The purpose of this market characterization project was to identify housing archetypes which are dominant within Great Lakes region and therefore offer significant potential for energy-efficient retrofit research and implementation due to the substantial number of homes possessing similar characteristics. Understanding the characteristics of housing groups referred to as 'archetypes' by vintage, style, and construction characteristics can allow research teams to focus their retrofit research and develop prescriptive solutions for those structure types which are prevalent and offer high potential uptake within a region or market. Key research activities included; literature review, statistical analysis of national and regional data of the American Housing Survey (AHS) collected by the U.S. Census Bureau, analysis of Michigan specific data, development of a housing taxonomy of architectural styles, case studies of two local markets (i.e., Ann Arbor and Grand Rapids in Michigan) and development of a suggested framework (or process) for characterizing local markets. In order to gain a high level perspective, national and regional data from the U.S. Census Bureau was analyzed using cross tabulations, multiple regression models, and logistic regression to characterize the housing stock and determine dominant house types using 21 variables.

Kim, S. K.; Mrozowski, T.; Harrell-Seyburn, A.; Ehrlich, N.; Hembroff, L.; Bieburn, B.; Mazor, M.; McIntyre, A.; Mutton, C.; Parsons, G.; Syal, M. G.; Wilkinson, R.

2014-09-01T23:59:59.000Z

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.


301

Big meter data analysis of the energy efficiency potential in Stockholm's building stock  

Science Journals Connector (OSTI)

Abstract The City of Stockholm is making substantial efforts towards meeting its climate change commitments including a GHG emission target of 3tonnes per capita by 2020 and making its new eco-district Stockholm Royal Seaport a candidate of Clinton Climate Initiative's Climate Positive Program. Towards achieving these policies, this study evaluated the energy efficiency potential in the city, in collaboration with the district heating and electricity utility Fortum. Drawing on their vast billing meter data on the housing stock in Stockholm, a new understanding of energy use in the city emerged. Analysis of the energy efficiency potential of different building vintages revealed that the retrofitting potential of the building stock to current building codes would reduce heating energy use by one third. In terms of market segmentation, the greatest reduction potential in total energy was found to be for buildings constructed between 1946 and 1975. This is due to the large number of buildings constructed during that era and their poor energy performance. However, the least energy-efficient buildings were those built between 1926 and 1945 in contradiction to commonly held beliefs. These findings indicate the need for a shift in public policy towards the buildings with highest retrofitting potential.

Hossein Shahrokni; Fabian Levihn; Nils Brandt

2014-01-01T23:59:59.000Z

302

The Absent House: The Ecological House of Puerto Rico  

High Performance Buildings Database

Vega Alta, PR The Absent House takes advantage of the benevolent climate of the humid tropics of Puerto Rico to play with the ambiguity of interior and exterior spaces. Main spaces include: a kitchenette and master bathroom suite; a guest tower with a bedroom, bathroom, and small library; an open, public pavilion for cooking, dining, and porch activities; a bathroom for visitors; an infrastructure pavilion for electricity and water consumption management; and an organic garden. The Patio of the Sun and the Stars, the most important s

303

OIKOS 101: 499504, 2003 Do seedlings in gaps interact? A field test of assumptions in ESS  

E-Print Network [OSTI]

OIKOS 101: 499­504, 2003 Do seedlings in gaps interact? A field test of assumptions in ESS seed seedlings in gaps interact? A field test of assumptions in ESS seed size models. ­ Oikos 101: 499­504. ESS for the occupancy of `safe sites' or vegetation gaps. If mortality rates are high and/or frequency-independent, ESS

Silvertown, Jonathan

304

Granular Matter 4(3) (2002) How good is the equipartition assumption for the transport  

E-Print Network [OSTI]

Granular Matter 4(3) (2002) How good is the equipartition assumption for the transport properties of a granular mixture? Meheboob Alam (1) , Stefan Luding (1;2) ? Abstract Kinetic-theory, with the assumption of equipar- tition of granular energy, suggests that the pressure and viscosity of a granular mixture vary

Luding, Stefan

305

Impact of assumption of log-normal distribution on monthly rainfall estimation from TMI  

E-Print Network [OSTI]

The log-normal assumption for the distribution of the rain rates used for the estimation of monthly rain totals proposed in Wilheit et al 1991 was examined. Since the log-normal assumption was originally used for the SSM/I, it is now necessary to re...

Lee, Dong Heon

2012-06-07T23:59:59.000Z

306

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

307

Oil, economic growth and strategic petroleum stocks  

Science Journals Connector (OSTI)

Abstract An examination of over 40 years of data reveals that oil price shocks are invariably followed by 23 years of weak economic growth and weak economic growth is almost always preceded by an oil price shock. This paper reviews why the price-inelastic demand and supply of oil cause oil price shocks and why oil price shocks reduce economic growth through dislocations of labor and capital. This paper also reviews the current state of oil-supply security noting that previous episodes of supply instability appear to have become chronic conditions. While new unconventional oil production technologies have revitalized North American oil production, there are significant barriers to a world-wide uptake of these technologies. Strategic petroleum stocks could provide a large measure of protection to the world economy during an oil supply disruption if they are used promptly and in sufficient volume to prevent large oil-price spikes. Despite the large volume of world-wide emergency reserves, their effectiveness in protecting world economies is not assured. Strategic oil stocks have not been used in sufficient quantity or soon enough to avoid the economic downturns that followed past oil supply outages. In addition, the growth of U.S. oil production has reduced the ability of the U.S. Strategic Petroleum Reserve to protect the economy following a future oil supply disruption. The policy implications of these findings are discussed.

Carmine Difiglio

2014-01-01T23:59:59.000Z

308

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

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

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

309

A new scenario framework for climate change research: The concept of Shared Climate Policy Assumptions  

SciTech Connect (OSTI)

The paper presents the concept of shared climate policy assumptions as an important element of the new scenario framework. Shared climate policy assumptions capture key climate policy dimensions such as the type and scale of mitigation and adaptation measures. They are not specified in the socio-economic reference pathways, and therefore introduce an important third dimension to the scenario matrix architecture. Climate policy assumptions will have to be made in any climate policy scenario, and can have a significant impact on the scenario description. We conclude that a meaningful set of shared climate policy assumptions is useful for grouping individual climate policy analyses and facilitating their comparison. Shared climate policy assumptions should be designed to be policy relevant, and as a set to be broad enough to allow a comprehensive exploration of the climate change scenario space.

Kriegler, Elmar; Edmonds, James A.; Hallegatte, Stephane; Ebi, Kristie L.; Kram, Tom; Riahi, Keywan; Winkler, Harald; Van Vuuren, Detlef

2014-04-01T23:59:59.000Z

310

Conditional correlations and volatility spillovers between crude oil and stock index returns  

Science Journals Connector (OSTI)

This paper investigates the conditional correlations and volatility spillovers between the crude oil and financial markets, based on crude oil returns and stock index returns. Daily returns from 2 January 1998 to 4 November 2009 of the crude oil spot, forward and futures prices from the WTI and Brent markets, and the FTSE100, NYSE, Dow Jones and S&P500 stock index returns, are analysed using the CCC model of Bollerslev (1990), VARMA-GARCH model of Ling and McAleer (2003), VARMA-AGARCH model of McAleer, Hoti, and Chan (2008), and DCC model of Engle (2002). Based on the CCC model, the estimates of conditional correlations for returns across markets are very low, and some are not statistically significant, which means the conditional shocks are correlated only in the same market and not across markets. However, the DCC estimates of the conditional correlations are always significant. This result makes it clear that the assumption of constant conditional correlations is not supported empirically. Surprisingly, the empirical results from the VARMA-GARCH and VARMA-AGARCH models provide little evidence of volatility spillovers between the crude oil and financial markets. The evidence of asymmetric effects of negative and positive shocks of equal magnitude on the conditional variances suggests that VARMA-AGARCH is superior to VARMA-GARCH and CCC.

Chia-Lin Chang; Michael McAleer; Roengchai Tansuchat

2013-01-01T23:59:59.000Z

311

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)

312

Fish Stocks Rainer Froese, IFM-GEOMAR, Kiel, Germany  

E-Print Network [OSTI]

Fish Stocks Rainer Froese, IFM-GEOMAR, Kiel, Germany Daniel Pauly, University of British Columbia and consisting of four elements (species names, location, time, and source). Catches The fish (or other aquatic organisms) of a given stock killed during a certain period by the operation of fishing gear. This definition

Pauly, Daniel

313

Petrale Sole Stock Assessment Review (STAR) Panel Report  

E-Print Network [OSTI]

constituted a major uncertainty in the assessment (Figure 1), as did the appropriate natural mortality ratePetrale Sole Stock Assessment Review (STAR) Panel Report Hotel Deca, Seattle, Washington 20-24 June Leipzig PFMC Groundfish Advisory Subpanel (GAP) Stock Assessment Team (STAT) Melissa Haltuch NMFS

314

UCSF FOUNDATION DONATION OF SECURITIES: STOCKS AND MUTAL FUNDS  

E-Print Network [OSTI]

-over- UCSF FOUNDATION DONATION OF SECURITIES: STOCKS AND MUTAL FUNDS GIFT TO CURRENT ACCOUNT Thank you for your interest in making a gift of stocks or mutual fund shares to the UCSF Foundation. We Foundation of your donation. Broker Instructions -- Credit to: State Street Bank & Trust, DTC #997, UCSF

Yamamoto, Keith

315

UCSF FOUNDATION DONATION OF SECURITIES: STOCKS AND MUTAL FUNDS  

E-Print Network [OSTI]

-over- UCSF FOUNDATION DONATION OF SECURITIES: STOCKS AND MUTAL FUNDS GIFT TO ENDOWMENT ACCOUNT Thank you for your interest in making a gift of stocks or mutual funds shares to the UCSF Foundation. We to notify UCSF Foundation of your donation. · Broker Instructions -- Credit to: State Street Bank & Trust

Yamamoto, Keith

316

"Why Are Some Firms More Innovative? Knowledge Inputs, Knowledge Stocks,  

E-Print Network [OSTI]

"Why Are Some Firms More Innovative? Knowledge Inputs, Knowledge Stocks, and the Role of Global, Exporting, Knowledge and Technological Change Abstract Why do some firms create more knowledge than others stock of knowledge. But there is very little empirical evidence on production functions for new ideas

Sadoulet, Elisabeth

317

Detecting Stock Market Manipulation using Supervised Learning Algorithms  

E-Print Network [OSTI]

suspicious transactions in relation to market manipulation in stock market. We use a case studyDetecting Stock Market Manipulation using Supervised Learning Algorithms Koosha Golmohammadi, Osmar,Chile ddiaz@unegocios.cl Abstract-- Market manipulation remains the biggest concern of investors in today

Zaiane, Osmar R.

318

Housing Innovation Awards at the Solar Decathlon  

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

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

319

All Electric Houses in Cold Climates  

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

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

320

Housing Innovation Awards | Department of Energy  

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

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

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

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

322

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

323

Value-Added Stock Loan Participation Program | Department of Energy  

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

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

324

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.

325

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

326

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

327

Use of naphthenic base stocks in engine oil formulations  

SciTech Connect (OSTI)

The use of naphthenic base stocks in the formulation of engine oils has always been restricted due to certain physico-chemical properties (i.e. low oxidation stability, high volatility, great variation of the viscosity with the temperature) as well as the limited availability of this type of base oil in many parts of the world. This paper summarizes the experimental results followed in the development of a crankcase engine oil formulation SAE 40, API SF/CC with maximum usage of a naphthenic base stock MVIN-170 combined with HVI stocks and conventional additive technologies. The physico-chemical characterization of the MVIN-170 base stock, a conventional processed napthenic oil that Maraven (affiliate of PDVSA) commercializes from Isla Refinery of Curazao, is presented and compared with other napthenic oils coming from other crude sources of processes and with parafinic base stocks of equivalent viscosity.

Josefina, V.C.M.; Armando, I.R.

1988-01-01T23:59:59.000Z

328

On the stock control performance of intermittent demand estimators  

Science Journals Connector (OSTI)

The purpose of this paper is to assess the empirical stock control performance of intermittent demand estimation procedures. The forecasting methods considered are the simple moving average, single exponential smoothing, Croston's method and a new method recently developed by the authors of this paper. We first discuss the nature of the empirical demand data set (3000 stock keeping units) and we specify the stock control model to be used for experimentation purposes. Performance measures are then selected to report customer service level and stock volume differences. The out-of-sample empirical comparison results demonstrate the superior stock control performance of the new intermittent demand forecasting method and enable insights to be gained into the empirical utility of the other estimators.

Aris A. Syntetos; John E. Boylan

2006-01-01T23:59:59.000Z

329

Moldy Assumptions  

E-Print Network [OSTI]

sustainability movements. 2 Despite these noble intentions, using human responsibility as a base for architecture

Heully, Gustave Paul

2012-01-01T23:59:59.000Z

330

,"U.S. Refinery, Bulk Terminal, and Natural Gas Plant Stocks...  

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

Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)","U.S. Gasoline Blending Components Stocks at Refineries, Bulk Terminals, and Natural Gas Plants...

331

2014 House Nuclear Cleanup Caucus Oak Ridge  

Office of Environmental Management (EM)

2014 House Nuclear Cleanup Caucus Oak Ridge August 16, 2014 Sue Cange Acting Manager Oak Ridge Office of Environmental Management Oak Ridge Site Specific Advisory Board Annual...

332

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

Gasoline and Diesel Fuel Update (EIA)

Single-Family Units Apartments in Buildings With-- Table HC3.10 Home Appliances Usage Indicators by Owner-Occupied Housing Unit, 2005 Home Appliances Usage Indicators...

333

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

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

Single-Family Units Apartments in Buildings With-- Table HC4.10 Home Appliances Usage Indicators by Renter-Occupied Housing Unit, 2005 Home Appliances Usage Indicators...

334

Testimony before the House Appropriations Committee, Subcommittee...  

National Nuclear Security Administration (NNSA)

... Testimony before the House Appropriations Committee, Subcommittee on Energy and Water Congressional Testimony Mar 4, 2010 Administrator Thomas D'Agostino As Prepared for...

335

Science to return to the White House  

Science Journals Connector (OSTI)

... Senators and Congressmen that he wants Congress to pass a bill to establish a small science policy ... policy office in the White House, headed by a ...

Colin Norman

1975-06-05T23:59:59.000Z

336

Fayette Country, Pennsylvania, Housing Market Analysis  

Broader source: Energy.gov [DOE]

This is a document from the Fayette County Housing Consortium posted to the website of the U.S. Department of Energy's Better Buildings Neighborhood Program.

337

Islip Housing Authority Energy Efficiency Turnover Protocols...  

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

outlets, wires, and lighting; sealing around the bath exhaust fan housing and ducts boots; replacing entry door weather stripping; caulking around entry door frame and windows;...

338

Solar energy, conservation, and rental housing  

SciTech Connect (OSTI)

Renters must pay the majority of energy costs either directly or in their rents. They have limited financial and legal abilities to make improvements necessary to increase substantially the energy efficiency of rental housing. This report discusses the problem of how to increase investments in energy conservation and solar energy devices for rental housing, which constitutes over one-third of US housing. As background, this report characterizes the rental-housing market, including owners' decision-making criteria. Federal, state, and local policies that affect energy-related investments in rental housing are described. Programs are divided into five major categories: (1) programs for tenants, (2) financial incentives for owners, (3) leasing of solar energy equipment, (4) mediation between tenants and landlords, and (5) regulation. The report concludes that energy and conservation programs aimed at the residential sector must disaggregate owner-occupied housing from rental housing for maximum effect. No one program is advocated since local rental-housing markets differ substantially. For improvements greater than no-cost or low-cost items, programs must be directed at rental-housing owners and not only at tenants.

Levine, A.; Raab, J.

1981-03-01T23:59:59.000Z

339

Slideshow of the White House Energy Datapalooza  

Broader source: Energy.gov [DOE]

This post included photo's from the Energy Datapalooza hosted jointly by the White House Office of Technology-Policy and the Department of Energy.

340

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

E-Print Network [OSTI]

stock, household size, fuel prices and household income.needed by the model. Fuel price projections are implementedand Exogenous Drivers Fuel Prices Income Household Size

Johnson, F.X.

2010-01-01T23:59:59.000Z

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.


341

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

E-Print Network [OSTI]

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

Deng, Yongheng; Quigley, John M.

2008-01-01T23:59:59.000Z

342

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

343

Statement of Patricia Hoffman before the United States House of  

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

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

344

CBE UFAD cost analysis tool: Life cycle cost model, issues and assumptions  

E-Print Network [OSTI]

Building Maintenance and Repair Cost Reference. WhitestoneJ. Wallis and H. Lin. 2008. CBE UFAD Cost Analysis Tool:UFAD First Cost Model, Issues and Assumptions. Center for

Webster, Tom; Benedek, Corinne; Bauman, Fred

2008-01-01T23:59:59.000Z

345

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

Science Journals Connector (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

346

Behavioral Assumptions Underlying California Residential Sector Energy Efficiency Programs (2009 CIEE Report)  

Broader source: Energy.gov [DOE]

This paper examines the behavioral assumptions that underlie Californias residential sector energy efficiency programs and recommends improvements that will help to advance the states ambitious greenhouse gas reduction goals.

347

Length measurement of a moving rod by a single observer without assumptions concerning its magnitude  

E-Print Network [OSTI]

We extend the results presented by Weinstein concerning the measurement of the length of a moving rod by a single observer, without making assumptions concerning the distance between the moving rod and the observer who measures its length.

Bernhard Rothenstein; Ioan Damian

2005-07-03T23:59:59.000Z

348

Assumptions about the U.S., the EU, NATO, and their Impact on the Transatlantic Agenda  

Science Journals Connector (OSTI)

I propose in this paper to discuss, from an American perspective, the assumptions and assertions that influence the way that I look at foreign policy events at the end of this decade. I will conclude with a fe...

Stanley Sloan

2000-01-01T23:59:59.000Z

349

White House | OpenEI Community  

Open Energy Info (EERE)

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

350

DOE Solar Decathlon: Solar Decathlon House Tours  

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

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

351

On-site Housing | Staff Services  

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

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

352

Please transfer ALL data off /house  

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

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

353

OpenEI Community - White House  

Open Energy Info (EERE)

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

354

Cooling with a Whole House Fan | Department of Energy  

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

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

355

Technological rules and constraints affecting design of precast concrete housing  

E-Print Network [OSTI]

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

Nakamura, Takashi

1994-01-01T23:59:59.000Z

356

White_House_0921.pdf | Department of Energy  

Office of Environmental Management (EM)

WhiteHouse0921.pdf WhiteHouse0921.pdf WhiteHouse0921.pdf More Documents & Publications EA-0921: Finding of No Significant Impact whmissionstatus.pdf Environmental Leaders,...

357

Weblog Analysis for Predicting Correlations in Stock Price Evolutions Milad Kharratzadeh1  

E-Print Network [OSTI]

method which combines information from the weblog data and histor- ical stock prices. Through simulation strategies based on company sec- tors or historical stock prices. This suggests that the method- ology has evolution of stock prices and whether this is complementary to the information embedded in historical stock

Coates, Mark

358

Trading Puts and CDS on Stocks with Short Sale Ban Sophie Xiaoyan Ni and Jun Pan  

E-Print Network [OSTI]

not perform differently from the middle group. Within the sample of banned stocks with CDS traded and using in banned stocks and the trading of options and CDS. Within the sample of banned stocks with exchange traded options, stocks whose put-call ratios are in the top quintile underperform the middle group by 2.13% and 4

Gabrieli, John

359

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

7 7 Notes: 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 MB/D in January and 280 MB/D 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 months,

360

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: 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

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

PADD 1 (East Coast) Heating Oil Stocks Low  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: The East Coast (PADD 1) is the primary heating oil region, and it depends heavily on production from the Gulf Coast (PADD 3) as well. The biggest decline in U.S. stocks has taken place in the heating oil markets of PADD 1 (East Coast), which consumed 86 percent of the nation’s heating oil in 1998. It also is the region with the largest volume of heating oil stocks. PADD 1 was down over 8.4 million barrels on January 21 from the 5-year average stock level for end of January PADD 3, which supplies PADD 1, was down 4.6 million barrels from its 5-year January ending levels. During the week ending January 21, weather in New England was nearly 20% colder than normal for this time of year. This cold weather on top of low stocks was pushing prices up, with

362

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","B100 Production",,"Sales of B100",,"Sales of B100 Included in Biodiesel Blends",,"Ending Stocks of B100",,"B100 Stock Change" 2011 "January",35.355469,,21.760435,,9.397668,,16.705962,,3.900173 "February",40.342355,,27.263997,,13.027514,,17.367083,,0.661121 "March",59.59017,,40.879532,,16.804541,,19.178192,,1.811109 "April",71.0517,,47.320311,,21.819273,,21.000047,,1.821855 "May",77.196652,,49.520679,,27.20637,,23.448551,,2.448504 "June",81.39104,,61.776718,,23.965853,,19.302451,,-4.1461 "July",91.679738,,65.997152,,22.388332,,22.956565,,3.654114

363

The More Important Price Indicator This Year is Low Stocks  

Gasoline and Diesel Fuel Update (EIA)

6 of 6 6 of 6 Notes: Crude prices this year at the beginning of the second quarter are likely to be higher -- not lower -- as a result of the current shortfall in crude oil production relative to demand on top of low stocks. OECD stocks of crude oil and products plunged steeply in 1999. By year end, they were below the low levels at end December 1996 -- OPEC's stated target. This does not take into consideration the growth in demand that these stocks must help supply. EIA expects OECD stocks to stay very low throughout the year 2000. The projection shows end March levels remain well below those seen at the end of the first quarter 1996. The build during the summer will not be adequate to make up for the draws, resulting in a net draw of over 300 thousand barrels in an already tight market.

364

Forecasting Volatility in Stock Market Using GARCH Models  

E-Print Network [OSTI]

Forecasting volatility has held the attention of academics and practitioners all over the world. The objective for this master's thesis is to predict the volatility in stock market by using generalized autoregressive ...

Yang, Xiaorong

2008-01-01T23:59:59.000Z

365

The impact of political risk for testing Taiwan's stock market  

Science Journals Connector (OSTI)

This paper examines the vital role of political risk in stock trading. In Taiwan, the Kuomintang (KMT) Government has always been stable, since 1949, but the Progressive Party (DPP) has replaced KMI, and made huge impacts. I adopt the weighted attribute-adjustment methodology to measure the political risk variables, construct a multifactor model to link the political risk induced by Taiwan's first governmental change in May 1999, and analyse its influence on Taiwan's stock market trading. The results show that the political risk induced by governmental change resulted in a crisis of illiquidity in Taiwan's stock market. After the governmental change, the worsening situation in the domestic economy and the populace's lack of faith in the government were the key factors resulting in a serious shrinkage in Taiwan's stock trading.

Lie-Huey Wang

2003-01-01T23:59:59.000Z

366

Stock, Energy and Currency Effects on the Asymmetric Wheat Market  

Science Journals Connector (OSTI)

The purpose of this paper is to explore the effects of financial and currency indicators on wheat futures prices. The results suggest that the stock market, and particularly the S&P 500, positively influence the ...

Nikolaos Sariannidis

2011-05-01T23:59:59.000Z

367

Revised Propane Stock Levels for 6/7/13  

Gasoline and Diesel Fuel Update (EIA)

Revised Propane Stock Levels for 6713 Release Date: June 19, 2013 Following the release of the Weekly Petroleum Status Report (WPSR) for the week ended June 7, 2013, EIA...

368

Advisory on the reporting error in the combined propane stocks...  

Gasoline and Diesel Fuel Update (EIA)

Advisory on the reporting error in the combined propane stocks for PADDs 4 and 5 Release Date: June 12, 2013 The U.S. Energy Information Administration issued the following...

369

NONLINEARITY AND MARKET EFFICIENCY IN GCC STOCK MARKETS  

E-Print Network [OSTI]

): Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates (UAE), using three robust and highly regarded nonlinearity tests. In addition, the Efficient Market Hypothesis (EMH) was tested in this dissertation for the GCC stock markets using...

Alharbi, Abdullah M. H.

2009-07-31T23:59:59.000Z

370

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: 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

371

Low-Cost Ventilation in Production Housing - Building America...  

Energy Savers [EERE]

Low-Cost Ventilation in Production Housing - Building America Top Innovation Low-Cost Ventilation in Production Housing - Building America Top Innovation This drawing shows simple...

372

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

Energy Savers [EERE]

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

373

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

Energy Savers [EERE]

Testimony Testimony Before the House Energy & Water Development Committee Testimony Before the House Energy & Water Development Committee February 29, 2012 Fiscal Year 2013...

374

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

Energy Savers [EERE]

House Natural Resources Committee Before the Subcommittee on Water and Power - House Natural Resources Committee Testimony of Christopher M. Turner, Administrator SWPA Before the...

375

Testimony Before the House Appropriations Subcommittee on Energy...  

Energy Savers [EERE]

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

376

Before the House Budget Committee | Department of Energy  

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

the House Budget Committee Before the House Budget Committee By: Matt Rogers, Senior Advisor to the Secretary Subject: An Examination of the Economy and Recovery Act...

377

Senior Advisor Huizenga's Written Statement before the House...  

Office of Environmental Management (EM)

House Armed Services Subcommittee on Strategic Forces (April 17, 2012) Senior Advisor Huizenga's Written Statement before the House Armed Services Subcommittee on Strategic Forces...

378

Building America Whole-House Solutions for Existing Homes: Cascade...  

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

Building America Whole-House Solutions for Existing Homes: Cascade Apartments - Deep Energy Multifamily Retrofit (Fact Sheet) Building America Whole-House Solutions for Existing...

379

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

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

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

380

Energy Department Announces Winners of Housing Innovation Awards...  

Energy Savers [EERE]

Energy Department Announces Winners of Housing Innovation Awards Energy Department Announces Winners of Housing Innovation Awards October 25, 2013 - 1:21pm Addthis The Energy...

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

Advanced Envelope Research for Factory Built Housing, Phase 3...  

Energy Savers [EERE]

Advanced Envelope Research for Factory Built Housing, Phase 3-Design Development and Prototyping Advanced Envelope Research for Factory Built Housing, Phase 3-Design Development...

382

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

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

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

383

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

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

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

384

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

Office of Environmental Management (EM)

Science and Technology Committee Before the House Science and Technology Committee Before the House Science and Technology Committee By: Secretary Steven Chu Subject: Department of...

385

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

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

Science, Space, and Technology Committee Before the House Science, Space, and Technology Committee Before the House Science, Space, and Technology Committee By: Dr. Arun Majumdar,...

386

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

Office of Environmental Management (EM)

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

387

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

Energy Savers [EERE]

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

388

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

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

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

389

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

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

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

390

Building America Whole-House Solutions for New Homes: Hydronic...  

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

Building America Whole-House Solutions for New Homes: Hydronic Heating Coil Versus Propane Furnace (Fact Sheet) Building America Whole-House Solutions for New Homes: Hydronic...

391

Building America Whole-House Solutions for New Homes: Insight...  

Energy Savers [EERE]

Building America Whole-House Solutions for New Homes: Hydronic Heating Coil Versus Propane Furnace (Fact Sheet) Building America Whole-House Solutions for New Homes: S & A...

392

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

Office of Environmental Management (EM)

Job Creation and Regulatory Affairs - House Committee on Oversight and Governmant Reform Presentation: DOE Loan Programs Before the House Science, Space, and Technology...

393

White House Office of Science and Technology Policy Summer 2014...  

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

White House Office of Science and Technology Policy Summer 2014 Internship Program Application Period White House Office of Science and Technology Policy Summer 2014 Internship...

394

Secretary Moniz's Remarks at the White House Tribal Nations Conference...  

Energy Savers [EERE]

White House Tribal Nations Conference -- As Delivered Secretary Moniz's Remarks at the White House Tribal Nations Conference -- As Delivered December 3, 2014 - 3:25pm Addthis Dr....

395

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

Office of Environmental Management (EM)

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

396

White House honors Los Alamos physicist's early career work  

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

White House honors physicist's early career work White House honors Los Alamos physicist's early career work Ivan Vitev has received a prestigious Presidential Early Career Award...

397

White House Highlights New DOE Measures to Advance Renewable...  

Energy Savers [EERE]

White House Highlights New DOE Measures to Advance Renewable Energy Deployment and Increase Energy Efficiency White House Highlights New DOE Measures to Advance Renewable Energy...

398

Tribal Leaders Provide White House with Input on Bolstering Climate...  

Energy Savers [EERE]

Tribal Leaders Provide White House with Input on Bolstering Climate Resilience Tribal Leaders Provide White House with Input on Bolstering Climate Resilience January 7, 2015 -...

399

Join a White House Google+ Hangout with Energy Secretary Moniz...  

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

Join a White House Google+ Hangout with Energy Secretary Moniz & EPA Administrator McCarthy Join a White House Google+ Hangout with Energy Secretary Moniz & EPA Administrator...

400

Secretary Moniz's Remarks at the White House Energy Datapalooza...  

Office of Environmental Management (EM)

Secretary Moniz's Remarks at the White House Energy Datapalooza -- As Delivered Secretary Moniz's Remarks at the White House Energy Datapalooza -- As Delivered May 28, 2014 -...

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

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

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

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

402

Secretary Moniz at White House Women's Leadership Summit on Climate...  

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

Secretary Moniz at White House Women's Leadership Summit on Climate and Energy Secretary Moniz at White House Women's Leadership Summit on Climate and Energy Addthis Speakers...

403

White House Forum on Minorities in Energy | Department of Energy  

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

White House Forum on Minorities in Energy White House Forum on Minorities in Energy Addthis 1 of 13 Secretary Moniz, Ambassadors of the Minorities in Energy Initiative, and...

404

White House Meeting Honors New Superior Energy Performance Members...  

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

White House Meeting Honors New Superior Energy Performance Members White House Meeting Honors New Superior Energy Performance Members December 13, 2013 - 11:39am Addthis New...

405

White House Leadership Summit on Women, Climate and Energy |...  

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

White House Leadership Summit on Women, Climate and Energy White House Leadership Summit on Women, Climate and Energy Addthis Topic Energy Efficiency Energy Usage Science &...

406

White House Spotlights Solar Innovation as Summit Registration...  

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

White House Spotlights Solar Innovation as Summit Registration Continues White House Spotlights Solar Innovation as Summit Registration Continues April 23, 2014 - 10:38am Addthis...

407

2014 HAC Rural Housing Conference: Retool, Rebuild, Renew  

Broader source: Energy.gov [DOE]

The biennial HAC Rural Housing Conference brings together stakeholders in the field of rural affordable housing from local nonprofits, federal agencies, Congress, state and local governments, and...

408

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

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

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

409

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

Office of Environmental Management (EM)

The Subcommittee on Water and Power - House Committee on Natural Resources Before The Subcommittee on Water and Power - House Committee on Natural Resources Testimony of Elliot E....

410

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

Office of Environmental Management (EM)

The Subcommittee on Water and Power - House Committee on Natural Resources Before The Subcommittee on Water and Power - House Committee on Natural Resources Testimony of Mark A....

411

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

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

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

412

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

Office of Environmental Management (EM)

the Subcommittee on Water and Power - House Natural Resources Committee Before the Subcommittee on Water and Power - House Natural Resources Committee Testimony of William K....

413

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

Office of Environmental Management (EM)

House Natural Resources Committee Before the Subcommittee on Water and Power - House Natural Resources Committee Testimony of Kenneth E. Legg, Administrator SEPA...

414

Before The Subcommittee on Water and Power - House Energy and...  

Office of Environmental Management (EM)

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

415

Native Learning Center Second Annual Indian Housing Training...  

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

Native Learning Center Second Annual Indian Housing Training Conference Native Learning Center Second Annual Indian Housing Training Conference September 10, 2014 12:00PM EDT to...

416

Los Angeles County's Green Idea House Achieves Efficient Goals...  

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

Los Angeles County's Green Idea House Achieves Efficient Goals Los Angeles County's Green Idea House Achieves Efficient Goals Photo of an energy-efficient home with modern...

417

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

Office of Environmental Management (EM)

on Energy -- House Science, Space, and Technology Committee Testimony of Christopher Smith, Acting Assistant Secretary Before the Subcommittee on Energy -- House Science, Space,...

418

Energy Department Announces Winners of Housing Innovation Awards...  

Energy Savers [EERE]

Energy Department Announces Winners of Housing Innovation Awards Energy Department Announces Winners of Housing Innovation Awards October 25, 2013 - 12:00am Addthis The Energy...

419

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

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

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

420

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

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

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

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

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

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

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

422

Polyfluoroalkyl chemicals in house dust  

SciTech Connect (OSTI)

We developed a high throughput analytical method using on-line solid phase extraction coupled with isotope dilution high-performance liquid chromatography-tandem mass spectrometry (on-line SPE-HPLC-MS/MS) to simultaneously determine the concentrations of 17 polyfluoroalkyl chemicals (PFCs) in house dust. The sample preparation includes dispersion of the dust samples in 0.1 M formic acid:MeOH (1:1), followed by agitation and filtration, addition of the isotope-labeled internal standard solution to the filtrate, and analysis by on-line SPE-HPLC-MS/MS. The limits of quantitation were <4.0 ng/g. The method accuracies ranged between 73.2% and 100.2% for the different analytes at two spike levels. We confirmed the validity of the method by analyzing 39 household dust samples collected in 2004. Of the 17 PFCs measured, 6 of them-perfluorobutane sulfonate (PFBuS), N-ethyl-perfluorooctane sulfonamide, 2-(N-ethyl-perfluorooctane sulfonamido) acetic acid (Et-PFOSA-AcOH), 2-(N-methyl-perfluorooctane sulfonamido) ethanol (Me-PFOSA-EtOH), perfluorohexane sulfonate (PFHxS), and perfluorooctane sulfonate (PFOS)-had detection frequencies >70%. We detected PFOS, PFBuS, and PFHxS at the highest median concentration, followed by Et-PFOSA-AcOH and Me-PFOSA-EtOH.

Kato, Kayoko [Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, 4770 Buford Hwy., Mailstop F53, Atlanta, GA 30341 (United States)] [Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, 4770 Buford Hwy., Mailstop F53, Atlanta, GA 30341 (United States); Calafat, Antonia M., E-mail: acalafat@cdc.gov [Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, 4770 Buford Hwy., Mailstop F53, Atlanta, GA 30341 (United States); Needham, Larry L. [Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, 4770 Buford Hwy., Mailstop F53, Atlanta, GA 30341 (United States)] [Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, 4770 Buford Hwy., Mailstop F53, Atlanta, GA 30341 (United States)

2009-07-15T23:59:59.000Z

423

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

Gasoline and Diesel Fuel Update (EIA)

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

424

Mobile-component housing and solar energy: the possibilities  

SciTech Connect (OSTI)

The possibilities for acceptance of PV among different modes of housing construction are considered. The focus is on that form of housing production defined as mobile-component housing, a type of housing built in a factory to a single national construction standard. The first section describes the structure of the manufactured housing industry. It provides definitions and terminology necessary to a discussion of mobile-component housing. It then reviews the production activity and approach, distribution, consumer and financing for this mode of housing. The second section presents the product characteristics of mobile-component housing. The third section reviews solar technologies, and discusses their relation to mobile-component housing. The fourth section focuses specifically on factors influencing receptivity to solar by the mobile-component housing industry. The conclusion summarizes the analysis as it relates to the possibilities for photovoltaics in mobile-component housing.

Nutt-Powell, T.E.; Furlong, M.

1980-04-01T23:59:59.000Z

425

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

SciTech Connect (OSTI)

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

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

2013-01-01T23:59:59.000Z

426

" Million Housing Units, Final"  

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

Air Conditioning in U.S. Homes, by Housing Unit Type, 2009" Air Conditioning in U.S. Homes, by Housing Unit Type, 2009" " Million Housing Units, Final" ,,"Housing Unit Type" ,,"Single-Family Units",,"Apartments in Buildings With" ,"Total U.S.1 (millions)" ,," Detached"," Attached"," 2 to 4 Units","5 or More Units","Mobile Homes" "Air Conditioning" "Total Homes",113.6,71.8,6.7,9,19.1,6.9 "Air Conditioning Equipment" "Use Air Conditioning Equipment",94,61.1,5.6,6.3,15.2,5.8 "Have Air Conditioning Equipment But" "Do Not Use It",4.9,2.6,0.2,0.7,0.9,0.4 "Do Not Have Air Conditioning Equipment",14.7,8.1,0.9,2.1,3,0.7 "Type of Air Conditioning Equipment "

427

" Million Housing Units, Final"  

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

Household Demographics of U.S. Homes, by Housing Unit Type, 2009" Household Demographics of U.S. Homes, by Housing Unit Type, 2009" " Million Housing Units, Final" ,,"Housing Unit Type" ,,"Single-Family Units",,"Apartments in Buildings With" ,"Total U.S.1 (millions)" ,," Detached"," Attached"," 2 to 4 Units","5 or More Units","Mobile Homes" "Household Demographics" "Total Homes",113.6,71.8,6.7,9,19.1,6.9 "Number of Household Members" "1 Person",31.3,14.4,2.1,3.4,9.6,1.9 "2 Persons",35.8,24.2,1.9,2.5,5,2.1 "3 Persons",18.1,12.1,1.2,1.3,2.2,1.2 "4 Persons",15.7,11.5,1,1,1.5,0.8 "5 Persons",7.7,5.8,0.3,0.5,0.6,0.5

428

Advanced House Framing | Department of Energy  

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

Advanced House Framing Advanced House Framing Advanced House Framing April 13, 2012 - 7:57pm Addthis Two-story home using advanced framing techniques. Two-story home using advanced framing techniques. Advanced house framing means materials, labor, and heating and cooling cost savings because the approach: Uses less lumber and generates less waste than typical framing methods. Increases energy efficiency by replacing lumber with insulation material, resulting in a higher whole-wall R-value through reduced thermal bridging and increased insulation. How does it work? Advanced framing works structurally by aligning framing members directly over each other to transfer the load from roof trusses or rafters to second floor wall studs, to floor joists, to first floor studs to the foundation,

429

" Million Housing Units, Final"  

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

Fuels Used and End Uses in U.S. Homes, by Housing Unit Type, 2009" Fuels Used and End Uses in U.S. Homes, by Housing Unit Type, 2009" " Million Housing Units, Final" ,,"Housing Unit Type" ,,"Single-Family Units",,"Apartments in Buildings With" ,"Total U.S.1 (millions)" ,," Detached"," Attached"," 2 to 4 Units","5 or More Units","Mobile Homes" "Fuels Used and End Uses" "Total Homes",113.6,71.8,6.7,9,19.1,6.9 "Fuels Used for Any Use" "Electricity",113.6,71.8,6.7,9,19.1,6.9 "Natural Gas",69.2,45.6,4.7,6.1,11,1.8 "Propane/LPG",48.9,39.6,2.4,1.7,2,3.2 "Wood",13.1,11.4,0.3,0.2,0.5,0.7 "Fuel Oil",7.7,5.1,0.4,0.7,1.3,0.1

430

The House of the Future at MIT  

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

The House of the Future at MIT The House of the Future at MIT Speaker(s): Kent Larson Date: December 6, 2002 - 12:00pm Location: Bldg. 90 During this seminar, Professor Larson will discuss two related housing initiatives at MIT: Changing Places/Houses in The MIT Home of the Future Consortium. Change is accelerating, but the places we create are largely static and unresponsive. "Changing Places" is an MIT research consortium that explores how new technologies, materials, and strategies for design can make possible dynamic, evolving places that respond to the complexities of life. Open Source Building Alliance Providing individuals with choice creates competition and incentives for innovation. Mass-customization requires a modular component-based approach, which creates a pathway for new players to enter the $852

431

Tax policy, housing markets, and elderly homeowners  

E-Print Network [OSTI]

This dissertation consists of three essays studying the impact of tax policy on housing markets and elderly homeowners. Chapter One examines the potential lock-in effect of capital gains taxation on home sales, using the ...

Shan, Hui, Ph. D. Massachusetts Institute of Technology

2008-01-01T23:59:59.000Z

432

Housing Innovation Awards at the Solar Decathlon  

Broader source: Energy.gov [DOE]

Housing Innovation Awards at the Solar Decathlon, U.S. Department of Energy, Breakfast presented by BASF, Friday, October 4, 2013 8:30-10:30 a.m. Historic Hanger 244 Orange County Great Park in Irvine, CA.

433

Redefining the edge : housing on Chicago's waterfront  

E-Print Network [OSTI]

This thesis proposes an approach to the design of urban housing which uses the public realm to reconcile the various desires of the city for continuous, accessible fabric, the developer for property value raising enhancements, ...

Montalto, Anthony Olindo

1995-01-01T23:59:59.000Z

434

City of Indianapolis- EcoHouse Project  

Broader source: Energy.gov [DOE]

In June 2011, the City of Indianapolis announced the availability of the EcoHouse Project, an energy-efficiency loan program for medium- and low-income homeowners in Indianapolis. The Indianapolis...

435

Environmental control for confinement livestock housing  

SciTech Connect (OSTI)

Advantages and disadvantages of mechanical ventilation systems for livestock housing are discussed. Various principles involved in environmental control are reviewed. The design, operation, maintenance, and management of the equipment needed for environmental control are discussed. (JGB)

Jones, D.D.; Friday, W.H.; DeForest, S.S.

1980-06-01T23:59:59.000Z

436

The BLOOMhouse:Zero Net Energy Housing  

E-Print Network [OSTI]

site within a different climatic zone, and client context. Recognizing that consumers look to Solar Decathlon entries for ideas of how to integrate renewable energy technologies into their own homes this house will serve as a working example...

Garrison, M.; Krepart, R.; Randall, S.; Novoselac, A.

437

Achieving Sustainable Construction in Affordable Housing  

SciTech Connect (OSTI)

An energy-efficient design and construction checklist and information sheets on energy-efficient design and construction are two products being developed. These products will help affordable housing providers take the first steps toward a whole-house approach to the design and implementation of energy-efficient construction practices. The checklist presents simple and clear guidance on energy improvements that can be readily addressed now by most affordable housing providers. The information sheets complement the checklist by providing installation instructions and material specifications that are accompanied by detailed graphics. The information sheets also identify benefits of recommended energy-efficiency measures and procedures including cost savings and impacts on health and comfort. This paper presents details on the checklist and information sheets and discusses their use in two affordable housing projects.

Barcik, M.K.; Creech, D.B.; Ternes, M.P.

1998-12-07T23:59:59.000Z

438

Retrofitting the Southeast: The Cool Energy House  

SciTech Connect (OSTI)

The Consortium for Advanced Residential Buildings has provided the technical engineering and building science support for a highly visible demonstration home in connection with the National Association of Home Builders' International Builders Show. The two previous projects, the Las Vegas net-zero ReVISION House and the 2011 VISION and ReVISION Houses in Orlando, met goals for energy efficiency, cost effectiveness, and information dissemination through multiple web-based venues. This project, which was unveiled at the 2012 International Builders Show in Orlando on February 9, is the deep energy retrofit Cool Energy House (CEH). The CEH began as a mid-1990s two-story traditional specification house of about 4,000 ft2 in the upscale Orlando suburb of Windermere.

Zoeller, W.; Shapiro, C.; Vijayakumar, G.; Puttagunta, S.

2013-02-01T23:59:59.000Z

439

Available Housing Listings July 20, 2012  

E-Print Network [OSTI]

Available Housing Listings July 20, 2012 The Fire Pit - A Cultural Drop-In Centre 1120 3rd Ave, burns lake and vanderhoof. for more information and to obtain an application, visit the website at www

Northern British Columbia, University of

440

Available Housing Listings July 13, 2012  

E-Print Network [OSTI]

Available Housing Listings July 13, 2012 The Fire Pit - A Cultural Drop-In Centre 1120 3rd Ave, burns lake and vanderhoof. for more information and to obtain an application, visit the website at www

Northern British Columbia, University of

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

2013 White House Tribal Nations Conference  

Broader source: Energy.gov [DOE]

On Wednesday, November 13, President Obama will host the White House Tribal Nations Conference at the Department of the Interior. The conference will provide leaders from the 566 federally...

442

Elements of an Energy-Efficient House  

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

ability of a material to resist heat transfer, and the lower the value, the faster the heat loss. For example, a typical house in New York might have insulation of R-11 in the...

443

Housing for single-parent families  

E-Print Network [OSTI]

This thesis poses the question of how we are to house the family of the future. The concept of the strictly nuclear family as a backbone of our civilization is disintegrating under the onslaught of careers, of divorce, of ...

Johnson, Katrina Rae

1986-01-01T23:59:59.000Z

444

Order and chaos : articulating support, housing transformation  

E-Print Network [OSTI]

This thesis presents an exploration on the theme of order and chaos, as a formal and social phenomenon, particularly as it relates to housing. The work stems from an attraction to the messy vitality we find in certain ...

Boehm, William Hollister

1990-01-01T23:59:59.000Z

445

Edition Three, January 2010 Welcome to HOUSES!  

E-Print Network [OSTI]

13 Can households afford to buy the house of their dreams? Can households keep up with their mortgage quarter of 2009. While +0.1% isn't much growth we can join France, Germany, US and Japan in positive

Evans, Paul

446

" Million Housing Units, Final"  

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

Appliances in U.S. Homes, by Housing Unit Type, 2009" Appliances in U.S. Homes, by Housing Unit Type, 2009" " Million Housing Units, Final" ,,"Housing Unit Type" ,,"Single-Family Units",,"Apartments in Buildings With" ,"Total U.S.1 (millions)" ,,,,,"5 or More Units","Mobile Homes" "Appliances",,"Detached","Attached","2 to 4 Units" "Total Homes",113.6,71.8,6.7,9,19.1,6.9 "Cooking Appliances" "Stoves (Units With Both" "an Oven and a Cooktop)" "Use a Stove",102.3,62.3,6.4,8.7,18.3,6.5 "1.",100.8,61,6.4,8.6,18.3,6.5 "2 or More",1.5,1.3,0.1,"Q","Q","Q" "Do Not Use a Stove",11.3,9.5,0.3,0.3,0.8,0.4

447

" Million Housing Units, Final"  

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

Water Heating in U.S. Homes, by Housing Unit Type, 2009" Water Heating in U.S. Homes, by Housing Unit Type, 2009" " Million Housing Units, Final" ,,"Housing Unit Type" ,,"Single-Family Units",,"Apartments in Buildings With" ,"Total U.S.1 (millions)" ,," Detached"," Attached"," 2 to 4 Units","5 or More Units","Mobile Homes" "Water Heating" "Total Homes",113.6,71.8,6.7,9,19.1,6.9 "Number of Storage Tank Water Heaters" 0,2.9,1.8,0.1,0.2,0.6,0.1 1,108.1,67.5,6.5,8.8,18.5,6.8 "2 or More",2.7,2.5,0.1,"Q","Q","Q" "Number of Tankless Water Heaters2" 0,110.4,69.5,6.5,8.9,18.6,6.8 1,3.1,2.2,0.2,0.2,0.5,"Q"

448

" Million Housing Units, Final"  

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

Space Heating in U.S. Homes, by Housing Unit Type, 2009" Space Heating in U.S. Homes, by Housing Unit Type, 2009" " Million Housing Units, Final" ,,"Housing Unit Type" ,,"Single-Family Units",,"Apartments in Buildings With" ,"Total U.S.1 (millions)" ,," Detached"," Attached"," 2 to 4 Units","5 or More Units","Mobile Homes" "Space Heating" "Total Homes",113.6,71.8,6.7,9,19.1,6.9 "Space Heating Equipment" "Use Space Heating Equipment",110.1,70.5,6.5,8.7,17.7,6.7 "Have Space Heating Equipment But Do " "Not Use It",2.4,0.8,0.2,0.2,1,0.1 "Do Not Have Space Heating Equipment",1.2,0.6,"Q",0.1,0.4,"Q"

449

2014 White House Tribal Nations Conference  

Broader source: Energy.gov [DOE]

President Obama will host the 2014 White House Tribal Nations Conference at the Capital Hilton in Washington, DC. The conference will provide leaders from the 566 federally recognized tribes the opportunity to interact directly with the President and members of the White House Council on Native American Affairs. Each federally recognized tribe will be invited to send one representative to the conference. Additional details about the conference will be released at a later date.

450

Stock option fraud detection and an analysis for its reasons: Arabic Republic of Egypt case  

Science Journals Connector (OSTI)

This paper investigates how stock option turned from an incentive for good management to a tool of management fraud. The objective of this paper is accomplished through studying the stock option phenomenon in the Arab Republic of Egypt (ARE). Stock option grants data are obtained from all firms that have stock option grants and listed in the Egyptian stock market. The empirical study covers the period from 2006 through 2009. Detecting stock option fraud and distinguishing between control and fraud firms was done through calculating the cumulative abnormal returns before and after stock option grants. Results of this research reveal that the incidence of stock option fraud is higher in unscheduled option grants compared to scheduled ones. These results strongly support that the reason of stock option fraud in ARE is dating games rather than news announcements manipulation.

Zakia M. Alaa Eldeen; Ahmed F. Elbayoumi

2013-01-01T23:59:59.000Z

451

Keynote Address: Ali Zaidi, the White House Domestic Policy Council  

Broader source: Energy.gov [DOE]

Keynote address by Ali Zaidi, Deputy Director for Energy Policy, the White House Domestic Policy Council.

452

USER SATISFACTION WITH INNOVATIVE COOLING RETROFITS IN SACRAMENTO PUBLIC HOUSING  

E-Print Network [OSTI]

and a housing authority have been retrofitting their buildings with evaporative coolers, ground-source heatpumps

Diamond, Richard

453

"ENDING STOCKS OF CRUDE OIL (excluding SPR)"  

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

ENDING STOCKS OF CRUDE OIL (excluding SPR)" ENDING STOCKS OF CRUDE OIL (excluding SPR)" "Sourcekey","WCESTP11","WCESTP11","WCESTP21","WCESTP21","WCESTP31","WCESTP31","WCESTP41","WCESTP41","WCESTP51","WCESTP51","WCESTUS1","WCESTUS1" "Date","Weekly East Coast (PADD 1) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly East Coast (PADD 1) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Midwest (PADD 2) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Midwest (PADD 2) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Gulf Coast (PADD 3) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Gulf Coast (PADD 3) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Rocky Mountain (PADD 4) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Rocky Mountain (PADD 4) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly West Coast (PADD 5) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly West Coast (PADD 5) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly U.S. Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly U.S. Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)"

454

Campus Recreation at Sonoma State University RELEASE OF LIABILITY -PROMISE NOT TO SUE ASSUMPTION OF  

E-Print Network [OSTI]

Campus Recreation at Sonoma State University RELEASE OF LIABILITY - PROMISE NOT TO SUE ASSUMPTION OF RISK - AGREEMENT TO PAY CLAIMS PERMISSION TO USE VISUAL LIKENESS Activities: a) USE OF SSU RECREATION RECREATION PROGRAMS. Effective Locations and Time Periods: a) RECREATION CENTER: DURING HOURS OF OPERATION

Ravikumar, B.

455

Cognitive Assessment Models with Few Assumptions, and Connections with Nonparametric IRT  

E-Print Network [OSTI]

Cognitive Assessment Models with Few Assumptions, and Connections with Nonparametric IRT Brian of the monotonicity conditions discussed in Section 4. #12;Abstract In recent years, as cognitive theories of learning" on student achievement relative to theory-driven lists of examinee skills, beliefs and other cognitive

Junker, Brian

456

Draft -F. Nicoud 1 About the zero Mach number assumption in  

E-Print Network [OSTI]

Draft - F. Nicoud 1 About the zero Mach number assumption in the calculation of thermoacoustic as the the flame forcing ('Rayleigh') term. Besides, the net effect of the non zero Mach number terms the frequency of oscillation and growth rate are modified when the Mach number is not zero. It is demonstrated

Nicoud, Franck

457

Models of transcription factor binding: Sensitivity of activation functions to model assumptions  

E-Print Network [OSTI]

on statistical physics, a Markov-chain model and a computational simulation. Comparison of these models suggests for cooperativity. The simulation model suggests that direct interactions between TFs are unlikely to be the main in this contribution, the assumption of the cell being a well stirred reactor makes a qualitative difference

Kent, University of

458

Distillate Stocks are Low - Especially on the East Coast  

Gasoline and Diesel Fuel Update (EIA)

8 8 Notes: Distillate stocks are normally built during the summer for use during the winter as shown by the normal band. Currently, stocks are very low for this time of year. This graph shows East Coast inventories, which at the end of August, were well below the normal band (over 9 million barrels or 19% below the low end of the band). The East Coast is about 31% lower than its 10-year average level for this time of year. We focus on the East Coast (PADD 1 ) because this a region in which heating oil is a major winter fuel. Furthermore, the East Coast consumes almost 2/3 of the nation's heating oil (high sulfur distillate). December 1999 was the turning point. Stocks were well within the normal range through November 1999, but in December, they dropped below the

459

Has Oil Price Predicted Stock Returns for Over a Century?  

Science Journals Connector (OSTI)

Abstract This paper contributes to the debate on the role of oil prices in predicting stock returns. The novelty of the paper is that it considers monthly time-series historical data that span over 150 years (1859:10-2013:12) and applies a predictive regression model that accommodates three salient features of the data, namely, a persistent and endogenous oil price, and model heteroskedasticity. Three key findings are unraveled: First, oil price predicts US stock returns. Second, in-sample evidence is corroborated by out-sample evidence of predictability. Third, both positive and negative oil price changes are important predictors of US stock returns, with negative changes relatively more important. Our results are robust to the use of different estimators and choice of in-sample periods.

Paresh Kumar Narayan; Rangan Gupta

2014-01-01T23:59:59.000Z

460

Table 38. Coal Stocks at Coke Plants by Census Division  

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

Coal Stocks at Coke Plants by Census Division Coal Stocks at Coke Plants by Census Division (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 38. Coal Stocks at Coke Plants by Census Division (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Census Division June 30, 2013 March 31, 2013 June 30, 2012 Percent Change (June 30) 2013 versus 2012 Middle Atlantic w w w w East North Central 1,313 1,177 1,326 -1.0 South Atlantic w w w w East South Central w w w w U.S. Total 2,500 2,207 2,295 8.9 w = Data withheld to avoid disclosure. Note: Total may not equal sum of components because of independent rounding. Source: U.S. Energy Information Administration (EIA), Form EIA-5, 'Quarterly Coal Consumption and Quality Report - Coke Plants.'

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

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

Gasoline and Diesel Fuel Update (EIA)

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

462

Paducah DUF6 Conversion Final EIS - Chapter 4: Environmental Impact Assessment Approach, Assumptions, and Methodology  

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

Paducah DUF Paducah DUF 6 Conversion Final EIS 4 ENVIRONMENTAL IMPACT ASSESSMENT APPROACH, ASSUMPTIONS, AND METHODOLOGY This EIS evaluates potential impacts on human health and the natural environment from building and operating a DUF 6 conversion facility at three alternative locations at the Paducah site and for a no action alternative. These impacts might be positive, in that they would improve conditions in the human or natural environment, or negative, in that they would cause a decline in those conditions. This chapter provides an overview of the methods used to estimate the potential impacts associated with the EIS alternatives, summarizes the major assumptions that formed the basis of the evaluation, and provides some background information on human health

463

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

SciTech Connect (OSTI)

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

Phillip Mills

2012-02-01T23:59:59.000Z

464

Greenbuilt Retrofit Test House Final Report  

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

Greenbuilt Retrofit Test House Greenbuilt Retrofit Test House Final Report B. Sparn, K. Hudon, L. Earle, C. Booten, and P. C. Tabares-Velasco National Renewable Energy Laboratory G. Barker and C. E. Hancock Mountain Energy Partnership Technical Report NREL/TP-5500-54009 October 2012 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 15013 Denver West Parkway Golden, Colorado 80401 303-275-3000 * www.nrel.gov Contract No. DE-AC36-08GO28308 Greenbuilt Retrofit Test House Final Report B. Sparn, K. Hudon, L. Earle, C. Booten, and P. C. Tabares-Velasco National Renewable Energy Laboratory G. Barker and C. E. Hancock

465

The smartest house in Los Alamos  

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

The Smartest House In Los Alamos The Smartest House In Los Alamos Community Connections: Our link to Northern New Mexico Communities Latest Issue:Dec. 2013 - Jan. 2014 All Issues » submit The smartest house in Los Alamos The first project in the United States to demonstrate how "smart grid" technology could provide residential customers with a significant amount of their electricity from renewable resources is open and getting ready for visitors. October 1, 2012 dummy image Read our archives Contacts Editor Linda Anderman Email Community Programs Office Kurt Steinhaus Email The first project in the United States to demonstrate how "smart grid" technology could provide residential customers with a significant amount of their electricity from renewable resources is open and getting ready for

466

House Care Co Ltd | Open Energy Information  

Open Energy Info (EERE)

House Care Co Ltd House Care Co Ltd Jump to: navigation, search Name House Care Co Ltd Place Tokyo, Tokyo, Japan Zip 163-1431 Sector Solar Product Japanese insulation and roofing installer which also distributes and installs solar roofing systems. Coordinates 35.670479°, 139.740921° 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":35.670479,"lon":139.740921,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

467

University of Colorado House Tours Report  

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

HOUSE TOURS BRIEF CONTEST REPORT HOUSE TOURS BRIEF CONTEST REPORT This report summarizes the strategy of the CU Solar Decathlon Team for addressing the Hours Tours portion of the 2005 Solar Decathlon Competition. Brochures The CU Team is designing one brochure for the General Public and one for the Competition Judges. Both of these 18"x 24" handouts will fold into 10 sections like a compact map. On the inside of the brochures will appear a color rendering of the North, South, East and West facades of the house, in addition to a floor plan. The brochures will also include a detailed map that will explain various aspects of the CU Solar Decathlon Home and site plan. The content of each brochure will be audience appropriate. Each of the ten sections will contain 250-500 words of text, as well as pictures, diagrams,

468

NH House Committee_April27 2005  

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

Mercury Control Mercury Control Technology R&D Program for Coal-Fired Boilers Working Session of the New Hampshire House Science, Technology, & Energy Committee April 26, 2005 Concord, New Hampshire Thomas J. Feeley, III thomas.feeley@netl.doe.gov National Energy Technology Laboratory NH House Committee_April 2005 Mercury Control Technology Field Testing Program Performance/Cost Objectives * Have technologies ready for commercial demonstration by 2007 for all coals * Reduce "uncontrolled" Hg emissions by 50-70% * Reduce cost by 25-50% compared to baseline cost estimates Baseline Costs: $50,000 - $70,000 / lb Hg Removed 2000 Year Cost NH House Committee_April 2005 Stages of Mercury Control Technology Development DOE RD&D Model Lab/Bench/Pilot-Scale Testing Field Testing

469

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

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2007 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules-electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2007, DOE/EIA- M068(2007). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

470

E-Print Network 3.0 - analogous fish stocks Sample Search Results  

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

fish stocks Search Powered by Explorit Topic List Advanced Search Sample search results for: analogous fish stocks Page: << < 1 2 3 4 5 > >> 1 2008 Status of U.S. Fisheries...

471

Variation of mitochondrial control region sequences of Steller sea lions: the three-stock hypothesis  

E-Print Network [OSTI]

into regions and stocks to examine structure at different spatial scales. F- and ?-statistics were computed for all pairwise comparisons of rookeries, regions and stocks. Significant (PAlaska to California...

Baker, Alyson Renee

2004-09-30T23:59:59.000Z

472

Clustering of Japanese stock returns by recursive modularity optimization for efficient portfolio diversification  

Science Journals Connector (OSTI)

......Toyota. Some major automobile parts suppliers that...relations with specific automobile companies mentioned...comprises stocks of Electric Appliances: Canon...Chemical (Ch) and Electric Appliances (EA) stocks...components suppliers for automobile companies and other......

Takashi Isogai

2014-07-01T23:59:59.000Z

473

" Million Housing Units, Final"  

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

2 Household Demographics of U.S. Homes, by Owner/Renter Status, 2009" 2 Household Demographics of U.S. Homes, by Owner/Renter Status, 2009" " Million Housing Units, Final" ,,,,"Housing Unit Type" ,,,,"Single-Family Units",,,,"Apartments in Buildings With" ,"Total U.S.1 (millions)",,,"Detached",,"Attached",,"2 to 4 Units",,"5 or More Units",,"Mobile Homes" "Household Demographics",,"Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent" "Total Homes",113.6,76.5,37.1,63.2,8.6,3.9,2.8,1.5,7.6,2.3,16.8,5.5,1.4 "Number of Household Members"

474

" Million Housing Units, Final"  

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

2 Televisions in U.S. Homes, by Owner/Renter Status, 2009" 2 Televisions in U.S. Homes, by Owner/Renter Status, 2009" " Million Housing Units, Final" ,,,,"Housing Unit Type" ,,,,"Single-Family Units",,,,"Apartments in Buildings With" ,,,,"Detached",,"Attached",,"2 to 4 Units",,"5 or More Units",,"Mobile Homes" ,"Total U.S.1 (millions)" ,,"Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent" "Televisions" "Total Homes",113.6,76.5,37.1,63.2,8.6,3.9,2.8,1.5,7.6,2.3,16.8,5.5,1.4 "Televisions" "Number of Televisions"

475

Multifamily Housing: Looking for Energy Solutions  

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

operating operating costs, increase resident satisfaction, and enhance the value of your properties. Turn to an ENERGY STAR ® Service and Product Provider Partner ENERGY STAR Service and Product Providers (SPPs) have the experience and tools to implement energy-efficient strategies that are right for you. Following the U.S. Environmental Protection Agency's (EPA) Guidelines for Energy Management, a proven strategy developed from ENERGY STAR partner successes, SPPs can help your organization gain control of energy consumption and costs. Energy Efficiency Benefits the Multifamily Housing Industry, Your Tenants, and the Environment ENERGY STAR SPPs can help multifamily housing owners and managers reap the financial and environmental benefits of superior energy

476

" Million Housing Units, Final"  

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

2 Air Conditioning in U.S. Homes, by Owner/Renter Status, 2009" 2 Air Conditioning in U.S. Homes, by Owner/Renter Status, 2009" " Million Housing Units, Final" ,,,,"Housing Unit Type" ,,,,"Single-Family Units",,,,"Apartments in Buildings With" ,,,,"Detached",,"Attached",,"2 to 4 Units",,"5 or More Units",,"Mobile Homes" ,"Total U.S.1 (millions)" "Air Conditioning",,"Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent" "Total Homes",113.6,76.5,37.1,63.2,8.6,3.9,2.8,1.5,7.6,2.3,16.8,5.5,1.4 "Air Conditioning Equipment"

477

" Million Housing Units, Final"  

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

2 Space Heating in U.S. Homes, by Owner/Renter Status, 2009" 2 Space Heating in U.S. Homes, by Owner/Renter Status, 2009" " Million Housing Units, Final" ,,,,"Housing Unit Type" ,,,,"Single-Family Units",,,,"Apartments in Buildings With" ,,,,"Detached",,"Attached",,"2 to 4 Units",,"5 or More Units",,"Mobile Homes" ,"Total U.S.1 (millions)" ,,"Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent" "Space Heating" "Total Homes",113.6,76.5,37.1,63.2,8.6,3.9,2.8,1.5,7.6,2.3,16.8,5.5,1.4 "Space Heating Equipment"

478

" Million Housing Units, Final"  

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

2 Appliances in U.S. Homes, by Owner/Renter Status, 2009" 2 Appliances in U.S. Homes, by Owner/Renter Status, 2009" " Million Housing Units, Final" ,,,,"Housing Unit Type" ,,,,"Single-Family Units",,,,"Apartments in Buildings With" ,"Total U.S.1 (millions)",,,"Detached",,"Attached",,"2 to 4 Units",,"5 or More Units",,"Mobile Homes" "Appliances",,"Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent" "Total Homes",113.6,76.5,37.1,63.2,8.6,3.9,2.8,1.5,7.6,2.3,16.8,5.5,1.4 "Cooking Appliances" "Stoves (Units With Both"

479

2014 Building America House Simulation Protocols  

SciTech Connect (OSTI)

As BA has grown to include a large and diverse cross-section of the home building and retrofit industries, it has become more important to develop accurate, consistent analysis techniques to measure progress towards the program's goals. The House Simulation Protocol (HSP) document provides guidance to program partners and managers so they can compare energy savings for new construction and retrofit projects. The HSP provides the program with analysis methods that are proven to be effective and reliable in investigating the energy use of advanced energy systems and of entire houses.

Wilson, E.; Engebrecht-Metzger, C.; Horowitz, S.; Hendron, R.

2014-03-01T23:59:59.000Z

480

Low-Income Housing Tax Credits  

Science Journals Connector (OSTI)

Abstract The Low-Income Housing Tax Credit (LIHTC) programme is the primary subsidy mechanism used to support the development of rental housing for low-income households in the United States. The programme adds about 1300 projects and 91000 units per year. These projects are privately owned. The owners of the projects receive tax credits each year for 10 years in exchange for a commitment to maintain the units at affordable rents for occupancy by low-income households for a period of at least 15 years. The programme is proving to be popular with developers, but it is vulnerable to fluctuations in credit markets.

K. McClure

2012-01-01T23:59:59.000Z

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

"Table HC3.1 Housing Unit Characteristics by Owner-Occupied Housing Unit, 2005"  

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

Housing Unit Characteristics by Owner-Occupied Housing Unit, 2005" Housing Unit Characteristics by Owner-Occupied Housing Unit, 2005" " Million Housing Units" ,," Owner-Occupied Housing Units (millions)","Type of Owner-Occupied Housing Unit" ,"U.S. Housing Units (millions" ,,,"Single-Family Units",,"Apartments in Buildings With--" "Housing Unit Characteristics",,,"Detached","Attached","2 to 4 Units","5 or More Units","Mobile Homes" "Total",111.1,78.1,64.1,4.2,1.8,2.3,5.7 "Census Region and Division" "Northeast",20.6,13.4,10.4,1.4,1,0.3,0.4 "New England",5.5,3.8,3.1,"Q",0.3,"Q","Q" "Middle Atlantic",15.1,9.6,7.3,1.3,0.6,"Q","Q"

482

"Table HC4.1 Housing Unit Characteristics by Renter-Occupied Housing Unit, 2005"  

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

Housing Unit Characteristics by Renter-Occupied Housing Unit, 2005" Housing Unit Characteristics by Renter-Occupied Housing Unit, 2005" " Million Housing Units" ,," Renter-Occupied Housing Units (millions)","Type of Renter-Occupied Housing Unit" ,"U.S. Housing Units (millions" ,,,"Single-Family Units",,"Apartments in Buildings With--" "Housing Unit Characteristics",,,"Detached","Attached","2 to 4 Units","5 or More Units","Mobile Homes" "Total",111.1,33,8,3.4,5.9,14.4,1.2 "Census Region and Division" "Northeast",20.6,7.2,0.8,0.9,1.6,3.8,"Q" "New England",5.5,1.7,0.2,"Q",0.6,0.9,"Q" "Middle Atlantic",15.1,5.5,0.7,0.9,1,2.9,"Q"

483

SWAMP Project Trip report Quantification of Carbon Stocks and Emissions  

E-Print Network [OSTI]

1 SWAMP Project Trip report Quantification of Carbon Stocks and Emissions from the Mangrove Forests University Corvallis, Oregon, USA. #12;2 1. Introduction Funding for this project came from a grant, Washington DC. This intensive study is part of the Sustainable Wetlands Adaptation and Mitigation Program

Tullos, Desiree

484

ALASKAN WOOD FROGS STOCK UP ON SOLUTES TO SURVIVE  

E-Print Network [OSTI]

Inside JEB i ALASKAN WOOD FROGS STOCK UP ON SOLUTES TO SURVIVE Outwardly, the tiny wood frog, Rana these wood frogs, which are native to Alaska, Canada and the northern USA, to unravel their secrets. Costanzo tolerance in a northern population of the wood frog. J. Exp. Biol. 216, 3461-3473. Nicola Stead THE GENETICS

Besansky, Nora J.

485

Terrorism, country attributes, and the volatility of stock returns  

Science Journals Connector (OSTI)

Abstract This study investigates the interplay between terrorism and finance, focusing on the stock return volatility of American firms targeted by terrorist attacks. We find terrorism risk is an important factor in explaining the volatility of stock returns, which should be taken into account when modelling volatility. Using a volatility event-study approach and a new bootstrapping technique, we find volatility increases on the day of the attack and remain significant for at least fifteen days following the day of the attack. Cross-sectional analysis of the abnormal volatility indicates that the impact of terrorist attacks differs according to the country characteristics in which the incident occurred. We find that firms operating in wealthier, or more democratic countries, face greater volatility in stock returns relative to firms operating in developing countries. Firm exposure varies with the nature of country location, with country wealth and level of democracy playing an important role in explaining the likelihood of a terrorist attack. Our results show that despite significant terrorist events this past decade, stock markets in developed countries have not taken terrorist risk into sufficient consideration.

Naceur Essaddam; John M. Karagianis

2014-01-01T23:59:59.000Z

486

LACTATION VS. IMPROVED GROWTH IN STOCK ALBINO RATS  

Science Journals Connector (OSTI)

...MIui UNVnERSITY OF ILLINOIS DINOSAUR TENDONS WHn1n...attributable to lack of milk production by the mothers. It is...stock diet. Cod-liver oil given in addition to...attention to possible cumulative deficiencies in such...carry on for three months field exploration, shore collecting...

Arthur H. Smith; William E. Anderson

1929-07-26T23:59:59.000Z

487

Mining The Stock Market: Which Measure Is Best ? [Extended Abstract  

E-Print Network [OSTI]

in history), production capacities, population statistics, and sales amounts. Since the data sets occurring the price of the stock at the beginning of an operational day. Every time series is assigned to one out of 102 clusters (e.g. ``Computers (Hardware)'', ``Oil and Gas'', etc). Assuming this classification

488

I. Introduction The Stock Assessment Improvement Plan (SAIP) is the  

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of fish- eries management systems. The resulting review (Appen- dix 7) contained ten recommendations are addressed in detail in Section II, along with other factors that define NMFS' stock assess- ment mandate. Section III provides background informa- tion on requirements for conducting assessments

489

iSTOCK PHOTO Oklahoma State University's innovation  

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AND INDIVIDUALS TO OFFER INNOVATIVE WAYS TO REDUCE THE COST OF ENERGY. FOR MORE INFORMATION, VISIT IGSHPAiSTOCK PHOTO FALL 2013 52 Oklahoma State University's innovation in geothermal production technology is a green option that provides long-term cost savings and production efficiency. The ground

490

A discussion of stock market speculation by Pierre-Joseph Proudhon  

E-Print Network [OSTI]

thought that the publication of a compilation of stock market transactions2 did not merit his signatureA discussion of stock market speculation by Pierre-Joseph Proudhon Nice #12;2 A discussion of stock market speculation by Pierre-Joseph Proudhon Abstract The object

Boyer, Edmond

491

On the relationship between world oil prices and GCC stock markets  

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On the relationship between world oil prices and GCC stock markets Mohamed El Hedi Arouri Associate ABSTRACT We provide comprehensive evidence on the relationship between oil prices and stock mar- kets to be more sensitive to negative than to positive oil shocks. Keywords: oil prices, stock markets, GCC

Paris-Sud XI, Université de

492

Market impact and trading protocols of hidden orders in stock markets Esteban Moro,1, 2  

E-Print Network [OSTI]

Market impact and trading protocols of hidden orders in stock markets Esteban Moro,1, 2 Javier study the market impact of trading orders. We are specifically interested in large trading orders market member codes using data from the Spanish Stock Market and the London Stock Exchange. We find

493

Housing Price Dynamics in Time and Space: Predictability, Liquidity and Investor Returns  

E-Print Network [OSTI]

C. A. (1996). OFHEO house price indexes: HPI technicalsense of elevated housing prices. Federal Reserve Bank ofJ. E. (1991). Measuring prices in retransaction housing

Hwang, Min; Quigley, John M.

2010-01-01T23:59:59.000Z

494

Holistic revitalization in small post-industrial cities : tools for urban housing development  

E-Print Network [OSTI]

For generations, housing programs have sought to utilize redevelopment projects to accomplish broader community revitalization goals. Contemporary affordable housing practice embodies this idea in large housing development ...

Beam, Jeffrey (Jeffrey J.)

2009-01-01T23:59:59.000Z

495

The "Mortgage Consensus and the Housing Bubble: Revisiting the Post-Fordism Debate  

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Consensus and the Housing Bubble Wyly, Elvin, and JasonConsensus and the Housing Bubble References Amin, Ash.Consensus and the Housing Bubble Jones-Correa, Michael.

Flores Jr., Luis

2014-01-01T23:59:59.000Z

496

Illinois Institute of Technology Housing & Residential Services  

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Illinois Institute of Technology Housing & Residential Services Student Guide to 20102011 & assemble beds, etc); · Remove posters, paper, tape, sticky tack, etc from all surfaces; · Wipe clean all walls and furniture; · If living in an apartment, wipe clean the kitchen appliances, cabinets

Heller, Barbara

497

Biotechnology regulation: White House holds the ring  

Science Journals Connector (OSTI)

... House Office of Science and Technology Policy (OSTP) says, in a major statement on biotechnology regulation*, that the Recombinant DNA Advisory Committee (RAC) of the National Institutes of ... research, and endorses the actions of the Environmental Protection Agency in moving to regulate industrial biotechnology.

Tim Beardsley

1985-01-10T23:59:59.000Z

498

House Rejects Southern Idaho Power Line  

Science Journals Connector (OSTI)

The House of Representatives has refused to go along with the Bonneville Power Administration's plans to build a power transmission line into southern Idaho, where Monsanto hopes to use part of the power in a planned expansion of its elemental phosphorus ...

1964-06-22T23:59:59.000Z

499

1 Old Faculty Club 2 Boyd House  

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, Visitor Center 23 Carpenter Hall 24 Carson Engineering Center 25 Devon Energy Hall 26 Felgar Hall 27 Swim Center 76 Cross Center 77 OCCE Cross Center Main 78 Coats Hall, Law 79 Sam Noble Oklahoma MuseumCAMPUS MAP 1 Old Faculty Club 2 Boyd House 3 Whitehand Hall 4 Catlett Music Center 5 Fred Jones Jr

Xue, Ming

500

Bachelor Thesis Future sustainable terraced houses  

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Cardiff University August 4, 2014 #12;Colophon Title: Future sustainable residential buildings in Cardiff a first introduction about sustainability in the building sector. Collecting data about the future climateBachelor Thesis Future sustainable terraced houses in Cardiff Karin Ernst University of Twente

Vellekoop, Michel