National Library of Energy BETA

Sample records for bottom-up energy end-use

  1. Bottom-Up Energy Analysis System - Methodology and Results

    SciTech Connect (OSTI)

    McNeil, Michael A.; Letschert, Virginie E.; Stephane, de la Rue du Can; Ke, Jing

    2012-06-15

    The main objective of the development of BUENAS is to provide a global model with sufficient detail and accuracy for technical assessment of policy measures such as energy efficiency standards and labeling (EES&L) programs. In most countries where energy efficiency policies exist, the initial emphasis is on household appliances and lighting. Often, equipment used in commercial buildings, particularly heating, air conditioning and ventilation (HVAC) is also covered by EES&L programs. In the industrial sector, standards and labeling generally covers electric motors and distribution transformers, although a few more types of industrial equipment are covered by some programs, and there is a trend toward including more of them. In order to make a comprehensive estimate of the total potential impacts, development of the model prioritized coverage of as many end uses commonly targeted by EES&L programs as possible, for as many countries as possible.

  2. Bottom-Up Energy Analysis System (BUENAS) | Open Energy Information

    Open Energy Info (EERE)

    Lawrence Berkeley National Laboratory Sector: Energy Focus Area: Buildings, Energy Efficiency Topics: Baseline projection, - Macroeconomic, Pathways analysis Resource Type:...

  3. Bottom-Up Cost Analysis of a High Concentration PV Module; NREL (National Renewable Energy Laboratory)

    SciTech Connect (OSTI)

    Horowitz, K.; Woodhouse, M.; Lee, H.; Smestad, G.

    2015-04-13

    We present a bottom-up model of III-V multi-junction cells, as well as a high concentration PV (HCPV) module. We calculate $0.65/Wp(DC) manufacturing costs for our model HCPV module design with today’s capabilities, and find that reducing cell costs and increasing module efficiency offer the promising pathways for future cost reductions. Cell costs could be significantly reduced via an increase in manufacturing scale, substrate reuse, and improved manufacturing yields. We also identify several other significant drivers of HCPV module costs, including the Fresnel lens primary optic, module housing, thermal management, and the receiver board. These costs could potentially be lowered by employing innovative module designs.

  4. Energy End-Use Intensities in Commercial Buildings 1989 -- Executive...

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

    9 Energy End-Use Intensities > Executive Summary Executive Summary Energy End Uses Ranked by Energy Consumption, 1989 Energy End Uses Ranked by Energy Consumption, 1989 Source:...

  5. Assessment of Historic Trend in Mobility and Energy Use in India Transportation Sector Using Bottom-up Approach

    SciTech Connect (OSTI)

    Zhou, Nan; McNeil, Michael A.

    2009-05-01

    Transportation mobility in India has increased significantly in the past decades. From 1970 to 2000, motorized mobility (passenger-km) has risen by 888%, compared with an 88% population growth (Singh,2006). This contributed to many energy and environmental issues, and an energy strategy incorporates efficiency improvement and other measures needs to be designed. Unfortunately, existing energy data do not provide information on driving forces behind energy use and sometime show large inconsistencies. Many previous studies address only a single transportation mode such as passenger road travel; did not include comprehensive data collection or analysis has yet been done, or lack detail on energy demand by each mode and fuel mix. The current study will fill a considerable gap in current efforts, develop a data base on all transport modes including passenger air and water, and freight in order to facilitate the development of energy scenarios and assess significance of technology potential in a global climate change model. An extensive literature review and data collection has been done to establish the database with breakdown of mobility, intensity, distance, and fuel mix of all transportation modes. Energy consumption was estimated and compared with aggregated transport consumption reported in IEA India transportation energy data. Different scenarios were estimated based on different assumptions on freight road mobility. Based on the bottom-up analysis, we estimated that the energy consumption from 1990 to 2000 increased at an annual growth rate of 7% for the mid-range road freight growth case and 12% for the high road freight growth case corresponding to the scenarios in mobility, while the IEA data only shows a 1.7% growth rate in those years.

  6. India Energy Outlook: End Use Demand in India to 2020

    SciTech Connect (OSTI)

    de la Rue du Can, Stephane; McNeil, Michael; Sathaye, Jayant

    2009-03-30

    Integrated economic models have been used to project both baseline and mitigation greenhouse gas emissions scenarios at the country and the global level. Results of these scenarios are typically presented at the sectoral level such as industry, transport, and buildings without further disaggregation. Recently, a keen interest has emerged on constructing bottom up scenarios where technical energy saving potentials can be displayed in detail (IEA, 2006b; IPCC, 2007; McKinsey, 2007). Analysts interested in particular technologies and policies, require detailed information to understand specific mitigation options in relation to business-as-usual trends. However, the limit of information available for developing countries often poses a problem. In this report, we have focus on analyzing energy use in India in greater detail. Results shown for the residential and transport sectors are taken from a previous report (de la Rue du Can, 2008). A complete picture of energy use with disaggregated levels is drawn to understand how energy is used in India and to offer the possibility to put in perspective the different sources of end use energy consumption. For each sector, drivers of energy and technology are indentified. Trends are then analyzed and used to project future growth. Results of this report provide valuable inputs to the elaboration of realistic energy efficiency scenarios.

  7. Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Cement Sector

    SciTech Connect (OSTI)

    Sathaye, J.; Xu, T.; Galitsky, C.

    2010-08-15

    Adoption of efficient end-use technologies is one of the key measures for reducing greenhouse gas (GHG) emissions. How to effectively analyze and manage the costs associated with GHG reductions becomes extremely important for the industry and policy makers around the world. Energy-climate (EC) models are often used for analyzing the costs of reducing GHG emissions for various emission-reduction measures, because an accurate estimation of these costs is critical for identifying and choosing optimal emission reduction measures, and for developing related policy options to accelerate market adoption and technology implementation. However, accuracies of assessing of GHG-emission reduction costs by taking into account the adoption of energy efficiency technologies will depend on how well these end-use technologies are represented in integrated assessment models (IAM) and other energy-climate models.

  8. Healthcare Energy End-Use Monitoring

    SciTech Connect (OSTI)

    Sheppy, M.; Pless, S.; Kung, F.

    2014-08-01

    NREL partnered with two hospitals (MGH and SUNY UMU) to collect data on the energy used for multiple thermal and electrical end-use categories, including preheat, heating, and reheat; humidification; service water heating; cooling; fans; pumps; lighting; and select plug and process loads. Additional data from medical office buildings were provided for an analysis focused on plug loads. Facility managers, energy managers, and engineers in the healthcare sector will be able to use these results to more effectively prioritize and refine the scope of investments in new metering and energy audits.

  9. Healthcare Energy End-Use Monitoring | Department of Energy

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

    Healthcare Energy End-Use Monitoring Healthcare Energy End-Use Monitoring NREL partnered with two hospitals (MGH and SUNY UMU) to collect data on the energy used for multiple thermal and electrical end-use categories, including preheat, heating, and reheat; humidification; service water heating; cooling; fans; pumps; lighting; and select plug and process loads. Additional data from medical office buildings were provided for an analysis focused on plug loads. Facility managers, energy managers,

  10. Alternative Strategies for Low Pressure End Uses | Department of Energy

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

    Alternative Strategies for Low Pressure End Uses Alternative Strategies for Low Pressure End Uses This tip sheet outlines alternative strategies for low-pressure end uses as a pathway to reduced compressed air energy costs. COMPRESSED AIR TIP SHEET #11 PDF icon Alternative Strategies for Low Pressure End Uses (August 2004) More Documents & Publications Eliminate Inappropriate Uses of Compressed Air Compressed Air System Control Strategies Engineer End Uses for Maximum Efficiency

  11. Energy End-Use Intensities in Commercial Buildings

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

    Estimates The end-use estimates had two main sources: the 1989 Commercial Buildings Energy Consumption Survey (CBECS) and the Facility Energy Decision Screening (FEDS) system....

  12. Energy End-Use Intensities in Commercial Buildings 1989

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

    1989 Energy End-Use Intensities Overview Full Report Tables National estimates and analysis of energy consumption by fuel (electricity, natural gas, fuel oil, and district...

  13. End-Use Sector Flowchart | Department of Energy

    Office of Environmental Management (EM)

    End-Use Sector Flowchart End-Use Sector Flowchart This system of energy intensity indicators for total energy covers the economy as a whole and each of the major end-use sectors-transportation, industry, commercial and residential-identified in Figure 1. By clicking on any of the boxes with the word "Sector" in the title will reveal the more detailed structure within that sector. PDF icon End-Use Sector Flowchart More Documents & Publications Barriers to Industrial Energy

  14. Distribution Infrastructure and End Use | Department of Energy

    Office of Environmental Management (EM)

    Distribution Infrastructure and End Use Distribution Infrastructure and End Use The expanded Renewable Fuel Standard (RFS2) created under the Energy Independence and Security Act (EISA) of 2007 requires 36 billion gallons of biofuels to be blended into transportation fuel by 2022. Meeting the RFS2 target introduces new challenges for U.S. infrastructure, as modifications will be needed to transport and deliver renewable fuels that are not compatible with existing petroleum infrastructure. The

  15. Energy end-use intensities in commercial buildings

    SciTech Connect (OSTI)

    Not Available

    1994-09-01

    This report examines energy intensities in commercial buildings for nine end uses: space heating, cooling, ventilation, lighting, water heating, cooking, refrigeration, office equipment, and other. The objective of this analysis was to increase understanding of how energy is used in commercial buildings and to identify targets for greater energy efficiency which could moderate future growth in demand. The source of data for the analysis is the 1989 Commercial Buildings Energy Consumption survey (CBECS), which collected detailed data on energy-related characteristics and energy consumption for a nationally representative sample of approximately 6,000 commercial buildings. The analysis used 1989 CBECS data because the 1992 CBECS data were not yet available at the time the study was initiated. The CBECS data were fed into the Facility Energy Decision Screening (FEDS) system, a building energy simulation program developed by the US Department of Energy`s Pacific Northwest Laboratory, to derive engineering estimates of end-use consumption for each building in the sample. The FEDS estimates were then statistically adjusted to match the total energy consumption for each building. This is the Energy Information Administration`s (EIA) first report on energy end-use consumption in commercial buildings. This report is part of an effort to address customer requests for more information on how energy is used in buildings, which was an overall theme of the 1992 user needs study. The end-use data presented in this report were not available for publication in Commercial Buildings Energy Consumption and Expenditures 1989 (DOE/EIA-0318(89), Washington, DC, April 1992). However, subsequent reports on end-use energy consumption will be part of the Commercial Buildings Energy Consumption and Expenditures series, beginning with a 1992 data report to be published in early 1995.

  16. Engineer End Uses for Maximum Efficiency | Department of Energy

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

    Engineer End Uses for Maximum Efficiency Engineer End Uses for Maximum Efficiency This tip sheet outlines steps to ensure the efficiency of compressed air end-use applications....

  17. United States Industrial Sector Energy End Use Analysis

    SciTech Connect (OSTI)

    Shehabi, Arman; Morrow, William R.; Masanet, Eric

    2012-05-11

    The United States Department of Energy’s (DOE) Energy Information Administration (EIA) conducts the Manufacturing Energy Consumption Survey (MECS) to provide detailed data on energy consumption in the manufacturing sector. The survey is a sample of approximately 15,000 manufacturing establishments selected from the Economic Census - Manufacturing Sector. MECS provides statistics on the consumption of energy by end uses (e.g., boilers, process, electric drives, etc.) disaggregated by North American Industry Classification System (NAICS) categories. The manufacturing sector (NAICS Sector 31-33) consists of all manufacturing establishments in the 50 States and the District of Columbia. According to the NAICS, the manufacturing sector comprises establishments engaged in the mechanical, physical, or chemical transformation of materials, substances, or components into new products. The establishments are physical facilities such as plants, factories, or mills. For many of the sectors in the MECS datasets, information is missing because the reported energy use is less than 0.5 units or BTUs, or is withheld to avoid disclosing data for individual establishments, or is withheld because the standard error is greater than 50%. We infer what the missing information likely are using several approximations techniques. First, much of the missing data can be easily calculated by adding or subtracting other values reported by MECS. If this is not possible (e.g. two data are missing), we look at historic MECS reports to help identify the breakdown of energy use in the past and assume it remained the same for the current MECS. Lastly, if historic data is also missing, we assume that 3 digit NAICS classifications predict energy use in their 4, 5, or 6 digit NAICS sub-classifications, or vice versa. Along with addressing data gaps, end use energy is disaggregated beyond the specified MECS allocations using additional industry specific energy consumption data. The result is a completed table of energy end use by sector with mechanical drives broken down by pumps, fans, compressed air, and drives.

  18. Development of Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Iron and Steel Sector

    SciTech Connect (OSTI)

    Xu, T.T.; Sathaye, J.; Galitsky, C.

    2010-09-30

    Adoption of efficient end-use technologies is one of the key measures for reducing greenhouse gas (GHG) emissions. With the working of energy programs and policies on carbon regulation, how to effectively analyze and manage the costs associated with GHG reductions become extremely important for the industry and policy makers around the world. Energy-climate (EC) models are often used for analyzing the costs of reducing GHG emissions (e.g., carbon emission) for various emission-reduction measures, because an accurate estimation of these costs is critical for identifying and choosing optimal emission reduction measures, and for developing related policy options to accelerate market adoption and technology implementation. However, accuracies of assessing of GHG-emission reduction costs by taking into account the adoption of energy efficiency technologies will depend on how well these end-use technologies are represented in integrated assessment models (IAM) and other energy-climate models. In this report, we first conduct brief overview on different representations of end-use technologies (mitigation measures) in various energy-climate models, followed by problem statements, and a description of the basic concepts of quantifying the cost of conserved energy including integrating non-regrets options. A non-regrets option is defined as a GHG reduction option that is cost effective, without considering their additional benefits related to reducing GHG emissions. Based upon these, we develop information on costs of mitigation measures and technological change. These serve as the basis for collating the data on energy savings and costs for their future use in integrated assessment models. In addition to descriptions of the iron and steel making processes, and the mitigation measures identified in this study, the report includes tabulated databases on costs of measure implementation, energy savings, carbon-emission reduction, and lifetimes. The cost curve data on mitigation measures are available over time, which allows an estimation of technological change over a decade-long historical period. In particular, the report will describe new treatment of technological change in energy-climate modeling for this industry sector, i.e., assessing the changes in costs and energy-savings potentials via comparing 1994 and 2002 conservation supply curves. In this study, we compared the same set of mitigation measures for both 1994 and 2002 -- no additional mitigation measure for year 2002 was included due to unavailability of such data. Therefore, the estimated potentials in total energy savings and carbon reduction would most likely be more conservative for year 2002 in this study. Based upon the cost curves, the rate of change in the savings potential at a given cost can be evaluated and be used to estimate future rates of change that can be the input for energy-climate models. Through characterizing energy-efficiency technology costs and improvement potentials, we have developed and presented energy cost curves for energy efficiency measures applicable to the U.S. iron and steel industry for the years 1994 and 2002. The cost curves can change significantly under various scenarios: the baseline year, discount rate, energy intensity, production, industry structure (e.g., integrated versus secondary steel making and number of plants), efficiency (or mitigation) measures, share of iron and steel production to which the individual measures can be applied, and inclusion of other non-energy benefits. Inclusion of other non-energy benefits from implementing mitigation measures can reduce the costs of conserved energy significantly. In addition, costs of conserved energy (CCE) for individual mitigation measures increase with the increases in discount rates, resulting in a general increase in total cost of mitigation measures for implementation and operation with a higher discount rate. In 1994, integrated steel mills in the U.S. produced 55.

  19. Residential Lighting End-Use Consumption | Department of Energy

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

    Information Resources Publications Market Studies Residential Lighting End-Use Consumption Residential Lighting End-Use Consumption The U.S. DOE Residential Lighting ...

  20. End Use and Fuel Certification | Department of Energy

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

    End Use and Fuel Certification End Use and Fuel Certification Breakout Session 2: Frontiers and Horizons Session 2-B: End Use and Fuel Certification John Eichberger, Vice President of Government Relations, National Association for Convenience Stores PDF icon b13_eichberger_2-b.pdf More Documents & Publications Biofuels Market Opportunities High Octane Fuels Can Make Better Use of Renewable Transportation Fuels Making Better Use of Ethanol as a Transportation Fuel With "Renewable Super

  1. Energy End-Use Intensities in Commercial Buildings1992 -- Overview...

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

    in the way that variables such as building age and employment density could interact with the engineering estimates of end-use consumption. The SAE equations were...

  2. Energy End-Use Intensities in Commercial Buildings 1995 - Index...

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

    End-Use Analyst Contact: Joelle Michaels joelle.michaels@eia.doe.gov CBECS Manager URL: http:www.eia.govconsumptioncommercialdataarchivecbecscbec-eu1.html separater bar If...

  3. End use energy consumption data base: transportation sector

    SciTech Connect (OSTI)

    Hooker, J.N.; Rose, A.B.; Greene, D.L.

    1980-02-01

    The transportation fuel and energy use estimates developed a Oak Ridge National Laboratory (ORNL) for the End Use Energy Consumption Data Base are documented. The total data base contains estimates of energy use in the United States broken down into many categories within all sectors of the economy: agriculture, mining, construction, manufacturing, commerce, the household, electric utilities, and transportation. The transportation data provided by ORNL generally cover each of the 10 years from 1967 through 1976 (occasionally 1977 and 1978), with omissions in some models. The estimtes are broken down by mode of transport, fuel, region and State, sector of the economy providing transportation, and by the use to which it is put, and, in the case of automobile and bus travel, by the income of the traveler. Fuel types include natural gas, motor and aviation gasoline, residual and diesel oil, liuqefied propane, liquefied butane, and naphtha- and kerosene-type jet engine fuels. Electricity use is also estimated. The mode, fuel, sector, and use categories themselves subsume one, two, or three levels of subcategories, resulting in a very detailed categorization and definitive accounting.

  4. Healthcare Energy: Using End-Use Data to Inform Decisions | Department of

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

    Energy Using End-Use Data to Inform Decisions Healthcare Energy: Using End-Use Data to Inform Decisions The Building Technologies Office conducted a healthcare energy end-use monitoring project in partnership with two hospitals. See below for ideas about how to use end-use data to inform decisions in your facility. The relative magnitude of the energy consumption of different end uses can be a starting point for prioritizing energy investments and action, whether the scope under

  5. Energy End-Use Intensities in Commercial Buildings

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

    as buildings of the 1980's. In this section, intensities are based upon the entire building stock, not just those buildings using a particular fuel for a given end use. This...

  6. The Bottom-Up Approach forThermoelectric Nanocomposites, plusƒ |

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

    Department of Energy The Bottom-Up Approach forThermoelectric Nanocomposites, plusƒ The Bottom-Up Approach forThermoelectric Nanocomposites, plusƒ Contains an overview of the synthetic strategies for preparing bulk nanocomposite TE materials using a two-step bottom-up approach and associated experimental and theoretical results. PDF icon nolas.pdf More Documents & Publications Innovative Nano-structuring Routes for Novel Thermoelectric Materials;Phonon Blocking & DOS Engineering

  7. Energy End-Use Intensities in Commercial Buildings1995 -- Overview...

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

    by the Commercial Buildings Energy Consumption Survey (CBECS) and (2) building energy simulations provided by the Facility Energy Decision Screening (FEDS) system. The...

  8. Energy End-Use Intensities in Commercial Buildings1995 -- Tables

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

    model using survey data from the 1995 commercial buildings energy consumption survey and building energy simulations provided by the Facility Energy Decision Screening system....

  9. End-use Breakdown: The Building Energy Modeling Blog

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

    Modeling Blog en EnergyPlus Logo Debuts on Revit Toolbar http:energy.goveerebuildingsarticlesenergyplus-logo-debuts-revit-toolbar

  10. Energy End-Use Intensities in Commercial Buildings

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

    Active Solar: As an energy source, energy from the sun collected and stored using mechanical pumps or fans to circulate heat-laden fluids or air between solar collectors and the...

  11. Energy End-Use Intensities in Commercial Buildings

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

    2. Energy Use in Commercial Buildings The purpose of this section is to provide an overview of how energy was used in commercial buildings. Focusing on 1989 buildings, the section...

  12. Energy End-Use Intensities in Commercial Buildings

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

    Intensities The purpose of this section is to provide information on how energy was used for space conditioning--heating, cooling, and ventilation--in commercial...

  13. Energy End-Use Intensities in Commercial Buildings 1989 data...

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

    Buildings Energy Consumption Survey. Divider Bar To View andor Print Reports (requires Adobe Acrobat Reader) - Download Adobe Acrobat Reader If you experience any difficulties,...

  14. Energy End-Use Intensities in Commercial Buildings 1992

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

    Energy Consumption Survey. divider line To View andor Print Reports (requires Adobe Acrobat Reader) - Download Adobe Acrobat Reader If you experience any difficulties,...

  15. End-use Breakdown: The Building Energy Modeling Blog | Department of Energy

    Office of Environmental Management (EM)

    End-use Breakdown: The Building Energy Modeling Blog End-use Breakdown: The Building Energy Modeling Blog RSS Welcome to the Building Technologies Office's Building Energy Modeling blog. February 19, 2016 Trimble's recent acquisition of Sefaira and its pairing with SketchUp is a good sign for the BEM industry. Image credit: Sefaira. DOE. A Good Sign for the Building Energy Modeling Industry If you are a BEM professional, know a BEM professional, or even follow one on LinkedIn or Twitter, you've

  16. A new class of high ZT doped bulk nanothermoelectrics through bottom-up

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

    synthesis | Department of Energy new class of high ZT doped bulk nanothermoelectrics through bottom-up synthesis A new class of high ZT doped bulk nanothermoelectrics through bottom-up synthesis Reports on synthesis of large quantities of p- and n-type nanocrystals then sintered into bulk samples with high power factors and low thermal conductivity through impurity doping and nanostructuring PDF icon ramanath.pdf More Documents & Publications Nano-structures Thermoelectric Materals -

  17. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    1 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Residual and Natural Gas(d) LPG and Coke and Breeze) NAICS Total Electricity(b) Fuel Oil Diesel Fuel(c) (billion NGL(e) (million Other(f) Code(a) End Use (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) (trillion Btu) Total United States

  18. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    2 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal NAICS Net Residual and LPG and (excluding Coal Code(a) End Use Total Electricity(b) Fuel Oil Diesel Fuel(c) Natural Gas(d) NGL(e) Coke and Breeze) Other(f) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 15,658 2,850 251 129 5,512 79 1,016 5,820 Indirect Uses-Boiler Fuel --

  19. Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    7 End Uses of Fuel Consumption, 2006; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Demand Residual and Natural Gas(c) LPG and Coke and Breeze) for Electricity(a) Fuel Oil Diesel Fuel(b) (billion NGL(d) (million End Use (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) Total United States TOTAL FUEL CONSUMPTION 977,338 40 22 5,357 21

  20. Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    Next MECS will be conducted in 2010 Table 5.8 End Uses of Fuel Consumption, 2006; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal Net Demand Residual and LPG and (excluding Coal End Use for Electricity(a) Fuel Oil Diesel Fuel(b) Natural Gas(c) NGL(d) Coke and Breeze) Total United States TOTAL FUEL CONSUMPTION 3,335 251 129 5,512 79 1,016 Indirect Uses-Boiler Fuel 84 133 23 2,119 8 547

  1. Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    5 End Uses of Fuel Consumption, 2006; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Residual and Natural Gas(c) LPG and Coke and Breeze) Total Electricity(a) Fuel Oil Diesel Fuel(b) (billion NGL(d) (million Other(e) End Use (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) (trillion Btu) Total United States TOTAL FUEL CONSUMPTION

  2. Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    6 End Uses of Fuel Consumption, 2006; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal Net Residual and LPG and (excluding Coal End Use Total Electricity(a) Fuel Oil Diesel Fuel(b) Natural Gas(c) NGL(d) Coke and Breeze) Other(e) Total United States TOTAL FUEL CONSUMPTION 15,658 2,850 251 129 5,512 79 1,016 5,820 Indirect Uses-Boiler Fue -- 41 133 23 2,119 8 547 -- Conventional Boiler Use 41 71 17

  3. Assembly of a Molecular Needle, from the Bottom Up

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

    Assembly of a Molecular Needle, from the Bottom Up Assembly of a Molecular Needle, from the Bottom Up Print Wednesday, 21 December 2005 00:00 Many pathogenic bacteria use a specialized secretion system to inject virulence proteins directly into the cells they infect. The injected proteins, by mimicking host-cell mechanisms, can then subvert normal cellular function. The type III secretion system (TTSS) is a sophisticated protein complex with an overall shape similar to a hypodermic needle. More

  4. Hierarchical Three-Dimensional Microbattery Electrodes Combining Bottom-Up

    Office of Scientific and Technical Information (OSTI)

    Self-Assembly and Top-Down Micromachining (Journal Article) | SciTech Connect Hierarchical Three-Dimensional Microbattery Electrodes Combining Bottom-Up Self-Assembly and Top-Down Micromachining Citation Details In-Document Search Title: Hierarchical Three-Dimensional Microbattery Electrodes Combining Bottom-Up Self-Assembly and Top-Down Micromachining Authors: Gerasopoulos, K ; Pomerantseva, Ekaterina ; McCarthy, M ; Brown, A ; Wang, Chunsheng ; Culver, J N ; Ghodssi, Reza Publication Date:

  5. Table B19. Energy End Uses, Number of Buildings and Floorspace, 1999

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

    9. Energy End Uses, Number of Buildings and Floorspace, 1999" ,"Number of Buildings (thousand)",,,,,,"Total Floorspace (million square feet)" ,"All Buildings","Energy Used For (more than one may apply)",,,,,"All Buildings","Energy Used For (more than one may apply)" ,,"Space Heating","Cooling","Water Heating","Cooking","Manufact-uring",,"Space

  6. Energy Demand: Limits on the Response to Higher Energy Prices in the End-Use Sectors (released in AEO2007)

    Reports and Publications (EIA)

    2007-01-01

    Energy consumption in the end-use demand sectorsresidential, commercial, industrial, and transportationgenerally shows only limited change when energy prices increase. Several factors that limit the sensitivity of end-use energy demand to price signals are common across the end-use sectors. For example, because energy generally is consumed in long-lived capital equipment, short-run consumer responses to changes in energy prices are limited to reductions in the use of energy services or, in a few cases, fuel switching; and because energy services affect such critical lifestyle areas as personal comfort, medical services, and travel, end-use consumers often are willing to absorb price increases rather than cut back on energy use, especially when they are uncertain whether price increases will be long-lasting. Manufacturers, on the other hand, often are able to pass along higher energy costs, especially in cases where energy inputs are a relatively minor component of production costs. In economic terms, short-run energy demand typically is inelastic, and long-run energy demand is less inelastic or moderately elastic at best.

  7. Assembly of a Molecular Needle, from the Bottom Up

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

    Assembly of a Molecular Needle, from the Bottom Up Print Many pathogenic bacteria use a specialized secretion system to inject virulence proteins directly into the cells they infect. The injected proteins, by mimicking host-cell mechanisms, can then subvert normal cellular function. The type III secretion system (TTSS) is a sophisticated protein complex with an overall shape similar to a hypodermic needle. More than twenty unique types of proteins are required for its assembly, most of which are

  8. Assembly of a Molecular Needle, from the Bottom Up

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

    Assembly of a Molecular Needle, from the Bottom Up Print Many pathogenic bacteria use a specialized secretion system to inject virulence proteins directly into the cells they infect. The injected proteins, by mimicking host-cell mechanisms, can then subvert normal cellular function. The type III secretion system (TTSS) is a sophisticated protein complex with an overall shape similar to a hypodermic needle. More than twenty unique types of proteins are required for its assembly, most of which are

  9. Assembly of a Molecular Needle, from the Bottom Up

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

    Assembly of a Molecular Needle, from the Bottom Up Print Many pathogenic bacteria use a specialized secretion system to inject virulence proteins directly into the cells they infect. The injected proteins, by mimicking host-cell mechanisms, can then subvert normal cellular function. The type III secretion system (TTSS) is a sophisticated protein complex with an overall shape similar to a hypodermic needle. More than twenty unique types of proteins are required for its assembly, most of which are

  10. Assembly of a Molecular Needle, from the Bottom Up

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

    Assembly of a Molecular Needle, from the Bottom Up Print Many pathogenic bacteria use a specialized secretion system to inject virulence proteins directly into the cells they infect. The injected proteins, by mimicking host-cell mechanisms, can then subvert normal cellular function. The type III secretion system (TTSS) is a sophisticated protein complex with an overall shape similar to a hypodermic needle. More than twenty unique types of proteins are required for its assembly, most of which are

  11. Bottom-up graphene nanoribbon field-effect transistors

    SciTech Connect (OSTI)

    Bennett, Patrick B.; Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720 ; Pedramrazi, Zahra; Madani, Ali; Chen, Yen-Chia; Crommie, Michael F.; Materials Sciences Division, Lawrence Berkeley National Laboratories, Berkeley, California 94720 ; Oteyza, Dimas G. de; Centro de Física de Materiales CSIC Chen, Chen; Fischer, Felix R.; Materials Sciences Division, Lawrence Berkeley National Laboratories, Berkeley, California 94720 ; Bokor, Jeffrey; Materials Sciences Division, Lawrence Berkeley National Laboratories, Berkeley, California 94720

    2013-12-16

    Recently developed processes have enabled bottom-up chemical synthesis of graphene nanoribbons (GNRs) with precise atomic structure. These GNRs are ideal candidates for electronic devices because of their uniformity, extremely narrow width below 1?nm, atomically perfect edge structure, and desirable electronic properties. Here, we demonstrate nano-scale chemically synthesized GNR field-effect transistors, made possible by development of a reliable layer transfer process. We observe strong environmental sensitivity and unique transport behavior characteristic of sub-1?nm width GNRs.

  12. Table 2.3 Manufacturing Energy Consumption for Heat, Power, and Electricity Generation by End Use, 2006

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

    Manufacturing Energy Consumption for Heat, Power, and Electricity Generation by End Use, 2006 End-Use Category Net Electricity 1 Residual Fuel Oil Distillate Fuel Oil LPG 2 and NGL 3 Natural Gas Coal 4 Total 5 Million Kilowatthours Million Barrels Billion Cubic Feet Million Short Tons Indirect End Use (Boiler Fuel) 12,109 21 4 2 2,059 25 – – Conventional Boiler Use 12,109 11 3 2 1,245 6 – – CHP 6 and/or Cogeneration Process – – 10 1 (s) 814 19 – – Direct End Use All Process Uses 657,810

  13. The Value of End-Use Energy Efficiency in Mitigation of U.S. Carbon Emissions

    SciTech Connect (OSTI)

    Kyle, G. Page; Smith, Steven J.; Clarke, Leon E.; Kim, Son H.; Wise, Marshall A.

    2007-11-27

    This report documents a scenario analysis exploring the value of advanced technologies in the U.S. buildings, industrial, and transportation sectors in stabilizing atmospheric greenhouse gas concentrations. The analysis was conducted by staff members of Pacific Northwest National Laboratory (PNNL), working at the Joint Global Change Research Institute (JGCRI) in support of the strategic planning process of the U.S. Department of Energy (U.S. DOE) Office of Energy Efficiency and Renewable Energy (EERE). The conceptual framework for the analysis is an integration of detailed buildings, industrial, and transportation modules into MiniCAM, a global integrated assessment model. The analysis is based on three technology scenarios, which differ in their assumed rates of deployment of new or presently available energy-saving technologies in the end-use sectors. These technology scenarios are explored with no carbon policy, and under two CO2 stabilization policies, in which an economic price on carbon is applied such that emissions follow prescribed trajectories leading to long-term stabilization of CO2 at roughly 450 and 550 parts per million by volume (ppmv). The costs of meeting the emissions targets prescribed by these policies are examined, and compared between technology scenarios. Relative to the reference technology scenario, advanced technologies in all three sectors reduce costs by 50% and 85% for the 450 and 550 ppmv policies, respectively. The 450 ppmv policy is more stringent and imposes higher costs than the 550 ppmv policy; as a result, the magnitude of the economic value of energy efficiency is four times greater for the 450 ppmv policy than the 550 ppmv policy. While they substantially reduce the costs of meeting emissions requirements, advanced end-use technologies do not lead to greenhouse gas stabilization without a carbon policy. This is due mostly to the effects of increasing service demands over time, the high consumption of fossil fuels in the electricity sector, and the use of unconventional feedstocks in the liquid fuel refining sector. Of the three end-use sectors, advanced transportation technologies have the greatest potential to reduce costs of meeting carbon policy requirements. Services in the buildings and industrial sectors can often be supplied by technologies that consume low-emissions fuels such as biomass or, in policy cases, electricity. Passenger transportation, in contrast, is especially unresponsive to climate policies, as the fuel costs are small compared to the time value of transportation and vehicle capital and operating costs. Delaying the transition from reference to advanced technologies by 15 years increases the costs of meeting 450 ppmv stabilization emissions requirements by 21%, but the costs are still 39% lower than the costs assuming reference technology. The report provides a detailed description of the end-use technology scenarios and provides a thorough analysis of the results. Assumptions are documented in the Appendix.

  14. Bottom-Up Energy Analysis System (BUENAS) | Open Energy Information

    Open Energy Info (EERE)

    can be done about it: The Potential of Efficiency in the Residential Sector Residential Electricity Demand in China -Can Efficiency Reverse the Growth? Best Available Technology...

  15. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    Next MECS will be conducted in 2010 Table 5.3 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Demand Residual and Natural Gas(d) LPG and Coke and Breeze) NAICS for Electricity(b) Fuel Oil Diesel Fuel(c) (billion NGL(e) (million Code(a) End Use (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons)

  16. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    4 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal NAICS Net Demand Residual and LPG and (excluding Coal Code(a) End Use for Electricity(b) Fuel Oil Diesel Fuel(c) Natural Gas(d) NGL(e) Coke and Breeze) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 3,335 251 129 5,512 79 1,016 Indirect Uses-Boiler Fuel 84 133 23

  17. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    SciTech Connect (OSTI)

    McKone, Thomas E.; Lobscheid, A.B.

    2006-06-01

    This study assesses for California how increasing end-use electrical energy efficiency from installing residential insulation impacts exposures and disease burden from power-plant pollutant emissions. Installation of fiberglass attic insulation in the nearly 3 million electricity-heated homes throughout California is used as a case study. The pollutants nitrous oxides (NO{sub x}), sulfur dioxide (SO{sub 2}), fine particulate matter (PM2.5), benzo(a)pyrene, benzene, and naphthalene are selected for the assessment. Exposure is characterized separately for rural and urban environments using the CalTOX model, which is a key input to the US Environmental Protection Agency (EPA) Tool for the Reduction and Assessment of Chemicals and other environmental Impacts (TRACI). The output of CalTOX provides for urban and rural populations emissions-to-intake factors, which are expressed as an individual intake fraction (iFi). The typical iFi from power plant emissions are on the order of 10{sup -13} (g intake per g emitted) in urban and rural regions. The cumulative (rural and urban) product of emissions, population, and iFi is combined with toxic effects factors to determine human damage factors (HDFs). HDF are expressed as disability adjusted life years (DALYs) per kilogram pollutant emitted. The HDF approach is applied to the insulation case study. Upgrading existing residential insulation to US Department of Energy (DOE) recommended levels eliminates over the assmned 50-year lifetime of the insulation an estimated 1000 DALYs from power-plant emissions per million tonne (Mt) of insulation installed, mostly from the elimination of PM2.5 emissions. In comparison, the estimated burden from the manufacture of this insulation in DALYs per Mt is roughly four orders of magnitude lower than that avoided.

  18. Bottoms Up. [report on the Defense Department] (Journal Article) | SciTech

    Office of Scientific and Technical Information (OSTI)

    Connect Bottoms Up. [report on the Defense Department] Citation Details In-Document Search Title: Bottoms Up. [report on the Defense Department] The [open quotes]Bottoms Up Review[close quotes] was the Pentagon's ongoing reevaluation of the dangers faced by the United States and the forces needed to deal with those dangers. Its purpose was [open quotes]to define the strategy, force structure, modernization programs, industrial base, and infrastucture needed to meet new dangers and seize new

  19. Bottom Up and Country Led: A New Framework for Climate Action...

    Open Energy Info (EERE)

    transition strategically to low-carbon economic development while bolstering their resilience to the effects of climate change." References "Bottom Up and Country Led: A New...

  20. Control Limits for Building Energy End Use Based on Engineering Judgment, Frequency Analysis, and Quantile Regression

    SciTech Connect (OSTI)

    Henze, G. P.; Pless, S.; Petersen, A.; Long, N.; Scambos, A. T.

    2014-02-01

    Approaches are needed to continuously characterize the energy performance of commercial buildings to allow for (1) timely response to excess energy use by building operators; and (2) building occupants to develop energy awareness and to actively engage in reducing energy use. Energy information systems, often involving graphical dashboards, are gaining popularity in presenting energy performance metrics to occupants and operators in a (near) real-time fashion. Such an energy information system, called Building Agent, has been developed at NREL and incorporates a dashboard for public display. Each building is, by virtue of its purpose, location, and construction, unique. Thus, assessing building energy performance is possible only in a relative sense, as comparison of absolute energy use out of context is not meaningful. In some cases, performance can be judged relative to average performance of comparable buildings. However, in cases of high-performance building designs, such as NREL's Research Support Facility (RSF) discussed in this report, relative performance is meaningful only when compared to historical performance of the facility or to a theoretical maximum performance of the facility as estimated through detailed building energy modeling.

  1. Assessment of U.S. Electric End-Use Energy Efficiency Potential

    SciTech Connect (OSTI)

    Gellings, Clark W.; Wikler, Greg; Ghosh, Debyani

    2006-11-15

    Demand-side management holds significant potential to reduce growth in U.S. energy consumption and peak demand, and in a cost-effective manner. But significant policy interventions will be required to achieve these benefits. (author)

  2. Understanding Superconducting Magnetic Energy Storage (SMES) technology, applications, and economics, for end-use workshop

    SciTech Connect (OSTI)

    Ferraro, R.J.; McConnell, B.W.

    1993-06-01

    The overall objective of this project was to determine the state-of-the-art and to what extent existing SMES is a viable option in meeting the needs of utilities and their customers for improving electric service power quality. By defining and analyzing SMES electrical/mechanical performance characteristics, and comparing SMES application benefits with competitive stored energy systems, industry will be able to determine SMES unique applications and potential market penetration. Building on this information base, it would also be possible to evaluate the impact of high temperature superconductors (77 K and 20-35 K) on SMES technology applications. The authors of this report constructed a network of industry contacts and research consultants that were used to collect, update, and analyze ongoing SMES R&D and marketing activities in industries, utilities, and equipment manufacturers. These key resources were utilized to assemble performance characteristics on existing SMES, battery, capacitor, flywheel, and high temperature superconductor (HTS) stored energy technologies. From this information, preliminary stored energy system comparisons were accomplished. In this way, the electric load needs would be readily comparable to the potential solutions and applications offered by each aforementioned energy storage technology.

  3. Energy balances in the production and end-use of methanol derived from coal

    SciTech Connect (OSTI)

    1980-12-10

    Analysis is performed for three combinations of fuels, specifically: net petroleum gain (petroleum only); net premium fuel gain (natural gas and petroleum); and net energy gain (includes all fuels; does not include free energy from sun). The base case selected for evaluation was that of an energy-efficient coal-to-methanol plant located in Montana/Wyoming and using the Lurgi conversion process. The following variations of the base coal-methanol case are also analyzed: gasoline from coal with methanol as an intermediate step (Mobil-M); and methanol from coal (Texaco gasification process). For each process, computations are made for the product methanol as a replacement for unleaded gasoline in a conventional spark ignition engine and as a chemical feedstock. For the purpose of the energy analysis, computations are made for three situations regarding mileage of methanol/ gasoline compared to that of regular unleaded gasoline: mileage of the two fuels equal, mileage 4 percent better with gasohol, and mileage 4 percent worse with gasohol. The standard methodology described for the base case applies to all of the variations.

  4. Table 3.6 Consumer Expenditure Estimates for Energy by End-Use Sector, 1970-2010 (Million Dollars )

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

    Consumer Expenditure Estimates for Energy by End-Use Sector, 1970-2010 (Million Dollars 1) Year Residential Commercial Industrial Transportation Natural Gas 2 Petroleum Retail Electricity 3 Total 4 Natural Gas 2 Petroleum 5 Retail Electricity 3 Total 6,7 Coal Natural Gas 2 Petroleum 5 Biomass 8 Retail Electricity 3 Total 7,9 Petroleum 5 Total 7,10 1970 5,272 4,186 10,352 20,112 1,844 1,440 7,319 10,678 2,082 2,625 6,069 366 5,624 16,691 35,327 35,379 1971 5,702 4,367 11,589 21,934 2,060 1,574

  5. An integrated top-down and bottom-up strategy for characterization protein isoforms and modifications

    SciTech Connect (OSTI)

    Wu, Si; Tolic, Nikola; Tian, Zhixin; Robinson, Errol W.; Pasa-Tolic, Ljiljana

    2011-04-15

    Bottom-up and top-down strategies are two commonly used methods for mass spectrometry (MS) based protein identification; each method has its own advantages and disadvantages. In this chapter, we describe an integrated top-down and bottom-up approach facilitated by concurrent liquid chromatography-mass spectrometry (LC-MS) analysis and fraction collection for comprehensive high-throughput intact protein profiling. The approach employs a high resolution reversed phase (RP) LC separation coupled with LC eluent fraction collection and concurrent on-line MS with a high field (12 Tesla) Fourier-transform ion cyclotron resonance (FTICR) mass spectrometer. Protein elusion profiles and tentative modified protein identification are made using detected intact protein mass in conjunction with bottom-up protein identifications from the enzymatic digestion and analysis of corresponding LC fractions. Specific proteins of biological interest are incorporated into a target ion list for subsequent off-line gas-phase fragmentation that uses an aliquot of the original collected LC fraction, an aliquot of which was also used for bottom-up analysis.

  6. Piezoresistive characterization of bottom-up, n-type silicon microwires undergoing bend deformation

    SciTech Connect (OSTI)

    McClarty, Megan M.; Oliver, Derek R. E-mail: Derek.Oliver@umanitoba.ca; Bruce, Jared P.; Freund, Michael S. E-mail: Derek.Oliver@umanitoba.ca

    2015-01-12

    The piezoresistance of silicon has been studied over the past few decades in order to characterize the material's unique electromechanical properties and investigate their wider applicability. While bulk and top-down (etched) micro- and nano-wires have been studied extensively, less work exists regarding bottom-up grown microwires. A facile method is presented for characterizing the piezoresistance of released, phosphorus-doped silicon microwires that have been grown, bottom-up, via a chemical vapour deposition, vapour-liquid-solid process. The method uses conductive tungsten probes to simultaneously make electrical measurements via direct ohmic contact and apply mechanical strain via bend deformation. These microwires display piezoresistive coefficients within an order of magnitude of those expected for bulk n-type silicon; however, they show an anomalous response at degenerate doping concentrations (?10{sup 20?}cm{sup ?3}) when compared to lower doping concentrations (?10{sup 17?}cm{sup ?3}), with a stronger piezoresistive coefficient exhibited for the more highly doped wires. This response is postulated to be due to the different growth mechanism of bottom-up microwires as compared to top-down.

  7. Top-down and bottom-up definitions of human failure events in human reliability analysis

    SciTech Connect (OSTI)

    Boring, Ronald Laurids

    2014-10-01

    In the probabilistic risk assessments (PRAs) used in the nuclear industry, human failure events (HFEs) are determined as a subset of hardware failures, namely those hardware failures that could be triggered by human action or inaction. This approach is top-down, starting with hardware faults and deducing human contributions to those faults. Elsewhere, more traditionally human factors driven approaches would tend to look at opportunities for human errors first in a task analysis and then identify which of those errors is risk significant. The intersection of top-down and bottom-up approaches to defining HFEs has not been carefully studied. Ideally, both approaches should arrive at the same set of HFEs. This question is crucial, however, as human reliability analysis (HRA) methods are generalized to new domains like oil and gas. The HFEs used in nuclear PRAs tend to be top-down—defined as a subset of the PRA—whereas the HFEs used in petroleum quantitative risk assessments (QRAs) often tend to be bottom-up—derived from a task analysis conducted by human factors experts. The marriage of these approaches is necessary in order to ensure that HRA methods developed for top-down HFEs are also sufficient for bottom-up applications.

  8. End-use taxes: Current EIA practices

    SciTech Connect (OSTI)

    Not Available

    1994-08-17

    There are inconsistencies in the EIA published end-use price data with respect to Federal, state, and local government sales and excise taxes; some publications include end-use taxes and others do not. The reason for including these taxes in end-use energy prices is to provide consistent and accurate information on the total cost of energy purchased by the final consumer. Preliminary estimates are made of the effect on prices (bias) reported in SEPER (State Energy Price and Expenditure Report) resulting from the inconsistent treatment of taxes. EIA has undertaken several actions to enhance the reporting of end-use energy prices.

  9. Energy balances in the production and end use of alcohols derived from biomass. A fuels-specific comparative analysis of alternate ethanol production cycles

    SciTech Connect (OSTI)

    Not Available

    1980-10-01

    Considerable public interest and debate have been focused on the so-called energy balance issue involved in the conversion of biomass materials into ethanol for fuel use. This report addresses questions of net gains in premium fuels that can be derived from the production and use of ethanol from biomass, and shows that for the US alcohol fuel program, energy balance need not be a concern. Three categories of fuel gain are discussed in the report: (1) Net petroleum gain; (2) Net premium fuel gain (petroleum and natural gas); and (3) Net energy gain (for all fuels). In this study the investment of energy (in the form of premium fuels) in alcohol production includes all investment from cultivating, harvesting, or gathering the feedstock and raw materials, through conversion of the feedstock to alcohol, to the delivery to the end-user. To determine the fuel gains in ethanol production, six cases, encompassing three feedstocks, five process fuels, and three process variations, have been examined. For each case, two end-uses (automotive fuel use and replacement of petrochemical feedstocks) were scrutinized. The end-uses were further divided into three variations in fuel economy and two different routes for production of ethanol from petrochemicals. Energy requirements calculated for the six process cycles accounted for fuels used directly and indirectly in all stages of alcohol production, from agriculture through distribution of product to the end-user. Energy credits were computed for byproducts according to the most appropriate current use.

  10. Power applications of high-temperature superconductivity: Variable speed motors, current switches, and energy storage for end use

    SciTech Connect (OSTI)

    Hawsey, R.A. [Oak Ridge National Lab., TN (United States); Banerjee, B.B.; Grant, P.M. [Electric Power Research Inst., Palo Alto, CA (United States)

    1996-08-01

    The objective of this project is to conduct joint research and development activities related to certain electric power applications of high-temperature superconductivity (HTS). The new superconductors may allow development of an energy-efficient switch to control current to variable speed motors, superconducting magnetic energy storage (SMES) systems, and other power conversion equipment. Motor types that were considered include induction, permanent magnet, and superconducting ac motors. Because it is impractical to experimentally alter certain key design elements in radial-gap motors, experiments were conducted on an axial field superconducting motor prototype using 4 NbTi magnets. Superconducting magnetic energy storage technology with 0.25--5 kWh stored energy was studied as a viable solution to short duration voltage sag problems on the customer side of the electric meter. The technical performance characteristics of the device wee assembled, along with competing technologies such as active power line conditioners with storage, battery-based uninterruptible power supplies, and supercapacitors, and the market potential for SMES was defined. Four reports were prepared summarizing the results of the project.

  11. Enhancing Bottom-up and Top-down Proteomic Measurements with Ion Mobility Separations

    SciTech Connect (OSTI)

    Baker, Erin Shammel; Burnum-Johnson, Kristin E.; Ibrahim, Yehia M.; Orton, Daniel J.; Monroe, Matthew E.; Kelly, Ryan T.; Moore, Ronald J.; Zhang, Xing; Theberge, Roger; Costello, Catherine E; Smith, Richard D.

    2015-07-03

    Proteomic measurements with greater throughput, sensitivity and additional structural information enhance the in-depth characterization of complex mixtures and targeted studies with additional information and higher confidence. While liquid chromatography separation coupled with mass spectrometry (LC-MS) measurements have provided information on thousands of proteins in different sample types, the additional of another rapid separation stage providing structural information has many benefits for analyses. Technical advances in ion funnels and multiplexing have enabled ion mobility separations to be easily and effectively coupled with LC-MS proteomics to enhance the information content of measurements. Herein, we report on applications illustrating increased sensitivity, throughput, and structural information by utilizing IMS-MS and LC-IMS-MS measurements for both bottom-up and top-down proteomics measurements.

  12. The National Fuel End-Use Efficiency Field Test: Energy Savings and Performance of an Improved Energy Conservation Measure Selection Technique

    SciTech Connect (OSTI)

    Ternes, M.P.

    1991-01-01

    The performance of an advanced residential energy conservation measure (ECM) selection technique was tested in Buffalo, New York, to verify the energy savings and program improvements achieved from use of the technique in conservation programs and provide input into determining whether utility investments in residential gas end-use conservation are cost effective. The technique analyzes a house to identify all ECMs that are cost effective in the building envelope, space-heating system, and water-heating system. The benefit-to-cost ratio (BCR) for each ECM is determined and cost-effective ECMs (BCR > 1.0) are selected once interactions between ECMs are taken into account. Eighty-nine houses with the following characteristics were monitored for the duration of the field test: occupants were low-income, houses were single-family detached houses but not mobile homes, and primary space- and water-heating systems were gas-fired. Forty-five houses received a mix of ECMs as selected by the measure selection technique (audit houses) and 44 served as a control group. Pre-weatherization data were collected from January to April 1988 and post-weatherization data were collected from December 1988 to April 1989. Space- and waterheating gas consumption and indoor temperature were monitored weekly during the two winters. A house energy consumption model and regression analysis were employed to normalize the space-heating energy savings to average outdoor temperature conditions and a 68 F indoor temperature. Space and water-heating energy savings for the audit houses were adjusted by the savings for the control houses. The average savings of 257 therms/year for the audit houses was 17% of the average pre-weatherization house gas consumption and 78% of that predicted. Average space-heating energy savings was 252 therms/year (25% of pre-weatherization space-heating energy consumption and 85% of the predicted value) and average water-heating savings was 5 therms/year (2% of pre-weatherization water-heating energy consumption and 17% of predicted). The overall BCR for the ECMs was 1.24 using the same assumptions followed in the selection technique: no administration cost, residential fuel costs, real discount rate of 0.05, and no fuel escalation. A weatherization program would be cost effective at an administration cost less than $335/house. On average, the indoor temperature increased in the audit houses by 0.5 F following weatherization and decreased in the control houses by 0.1 F. The following conclusions regarding the measure selection technique were drawn from the study: (1) a significant cost-effective level of energy savings resulted, (2) space-heating energy savings and total installation costs were predicted with reasonable accuracy, indicating that the technique's recommendations are justified, (3) effectiveness improved from earlier versions and can continue to be improved, and (4) a wider variety of ECMs were installed compared to most weatherization programs. An additional conclusion of the study was that a significant indoor temperature take-back effect had not occurred.

  13. Table 3.4 Consumer Price Estimates for Energy by End-Use Sector, 1970-2010 (Dollars per Million Btu)

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

    Consumer Price Estimates for Energy by End-Use Sector, 1970-2010 (Dollars 1 per Million Btu) Year Residential Commercial Industrial Transportation Natural Gas 2 Petroleum Retail Electricity 3 Total 4 Natural Gas 2 Petroleum 5 Retail Electricity 3 Total 6,7 Coal Natural Gas 2 Petroleum 5 Biomass 8 Retail Electricity 3 Total 7,9 Petroleum 5 Total 7,10 1970 1.06 1.54 6.51 2.10 0.75 0.90 [R] 6.09 1.97 0.45 0.38 0.98 1.59 2.99 0.84 2.31 2.31 1971 1.12 1.59 6.80 2.24 .80 1.02 6.44 2.15 .50 .41 1.05

  14. Biomass Resource Allocation among Competing End Uses

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

    Biomass Resource Allocation among Competing End Uses Emily Newes, Brian Bush, Daniel Inman, Yolanda Lin, Trieu Mai, Andrew Martinez, David Mulcahy, Walter Short, Travis Simpkins, and Caroline Uriarte National Renewable Energy Laboratory Corey Peck Lexidyne, LLC Technical Report NREL/TP-6A20-54217 May 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

  15. Benchmarking Non-Hardware Balance-of-System (Soft) Costs for U.S. Photovoltaic Systems, Using a Bottom-Up Approach and Installer Survey - Second Edition

    SciTech Connect (OSTI)

    Friedman, B.; Ardani, K.; Feldman, D.; Citron, R.; Margolis, R.; Zuboy, J.

    2013-10-01

    This report presents results from the second U.S. Department of Energy (DOE) sponsored, bottom-up data-collection and analysis of non-hardware balance-of-system costs -- often referred to as 'business process' or 'soft' costs -- for U.S. residential and commercial photovoltaic (PV) systems. In service to DOE's SunShot Initiative, annual expenditure and labor-hour-productivity data are analyzed to benchmark 2012 soft costs related to (1) customer acquisition and system design (2) permitting, inspection, and interconnection (PII). We also include an in-depth analysis of costs related to financing, overhead, and profit. Soft costs are both a major challenge and a major opportunity for reducing PV system prices and stimulating SunShot-level PV deployment in the United States. The data and analysis in this series of benchmarking reports are a step toward the more detailed understanding of PV soft costs required to track and accelerate these price reductions.

  16. Biomass Resource Allocation among Competing End Uses

    SciTech Connect (OSTI)

    Newes, E.; Bush, B.; Inman, D.; Lin, Y.; Mai, T.; Martinez, A.; Mulcahy, D.; Short, W.; Simpkins, T.; Uriarte, C.; Peck, C.

    2012-05-01

    The Biomass Scenario Model (BSM) is a system dynamics model developed by the U.S. Department of Energy as a tool to better understand the interaction of complex policies and their potential effects on the biofuels industry in the United States. However, it does not currently have the capability to account for allocation of biomass resources among the various end uses, which limits its utilization in analysis of policies that target biomass uses outside the biofuels industry. This report provides a more holistic understanding of the dynamics surrounding the allocation of biomass among uses that include traditional use, wood pellet exports, bio-based products and bioproducts, biopower, and biofuels by (1) highlighting the methods used in existing models' treatments of competition for biomass resources; (2) identifying coverage and gaps in industry data regarding the competing end uses; and (3) exploring options for developing models of biomass allocation that could be integrated with the BSM to actively exchange and incorporate relevant information.

  17. Conservative and dissipative force field for simulation of coarse-grained alkane molecules: A bottom-up approach

    SciTech Connect (OSTI)

    Trément, Sébastien; Rousseau, Bernard, E-mail: bernard.rousseau@u-psud.fr [Laboratoire de Chimie-Physique, UMR 8000 CNRS, Université Paris-Sud, Orsay (France)] [Laboratoire de Chimie-Physique, UMR 8000 CNRS, Université Paris-Sud, Orsay (France); Schnell, Benoît; Petitjean, Laurent; Couty, Marc [Manufacture Française des Pneumatiques MICHELIN, Centre de Ladoux, 23 place des Carmes, 63000 Clermont-Ferrand (France)] [Manufacture Française des Pneumatiques MICHELIN, Centre de Ladoux, 23 place des Carmes, 63000 Clermont-Ferrand (France)

    2014-04-07

    We apply operational procedures available in the literature to the construction of coarse-grained conservative and friction forces for use in dissipative particle dynamics (DPD) simulations. The full procedure rely on a bottom-up approach: large molecular dynamics trajectories of n-pentane and n-decane modeled with an anisotropic united atom model serve as input for the force field generation. As a consequence, the coarse-grained model is expected to reproduce at least semi-quantitatively structural and dynamical properties of the underlying atomistic model. Two different coarse-graining levels are studied, corresponding to five and ten carbon atoms per DPD bead. The influence of the coarse-graining level on the generated force fields contributions, namely, the conservative and the friction part, is discussed. It is shown that the coarse-grained model of n-pentane correctly reproduces self-diffusion and viscosity coefficients of real n-pentane, while the fully coarse-grained model for n-decane at ambient temperature over-predicts diffusion by a factor of 2. However, when the n-pentane coarse-grained model is used as a building block for larger molecule (e.g., n-decane as a two blobs model), a much better agreement with experimental data is obtained, suggesting that the force field constructed is transferable to large macro-molecular systems.

  18. Table 5.1 End Uses of Fuel Consumption, 2010;

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

    5.1 End Uses of Fuel Consumption, 2010; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Residual and Natural Gas(d) LPG and Coke and Breeze) NAICS Total Electricity(b) Fuel Oil Diesel Fuel(c) (billion NGL(e) (million Other(f) Code(a) End Use (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) (trillion Btu) Total United States

  19. Table 5.2 End Uses of Fuel Consumption, 2010;

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

    2 End Uses of Fuel Consumption, 2010; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal NAICS Net Residual and LPG and (excluding Coal Code(a) End Use Total Electricity(b) Fuel Oil Diesel Fuel(c) Natural Gas(d) NGL(e) Coke and Breeze) Other(f) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 14,228 2,437 79 130 5,211 69 868 5,435 Indirect Uses-Boiler Fuel -- 27

  20. Table 5.3 End Uses of Fuel Consumption, 2010;

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

    3 End Uses of Fuel Consumption, 2010; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Demand Residual and Natural Gas(d) LPG and Coke and Breeze) NAICS for Electricity(b) Fuel Oil Diesel Fuel(c) (billion NGL(e) (million Code(a) End Use (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) Total United States 311 - 339 ALL

  1. Table 5.4 End Uses of Fuel Consumption, 2010;

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

    4 End Uses of Fuel Consumption, 2010; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal NAICS Net Demand Residual and LPG and (excluding Coal Code(a) End Use for Electricity(b) Fuel Oil Diesel Fuel(c) Natural Gas(d) NGL(e) Coke and Breeze) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 2,886 79 130 5,211 69 868 Indirect Uses-Boiler Fuel 44 46 19

  2. Table 5.5 End Uses of Fuel Consumption, 2010;

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

    5 End Uses of Fuel Consumption, 2010; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Residual and Natural Gas(c) LPG and Coke and Breeze) Total Electricity(a) Fuel Oil Diesel Fuel(b) (billion NGL(d) (million Other(e) End Use (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) (trillion Btu) Total United States TOTAL FUEL CONSUMPTION

  3. Table 5.6 End Uses of Fuel Consumption, 2010;

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

    6 End Uses of Fuel Consumption, 2010; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal Net Residual and LPG and (excluding Coal End Use Total Electricity(a) Fuel Oil Diesel Fuel(b) Natural Gas(c) NGL(d) Coke and Breeze) Other(e) Total United States TOTAL FUEL CONSUMPTION 14,228 2,437 79 130 5,211 69 868 5,435 Indirect Uses-Boiler Fuel -- 27 46 19 2,134 10 572 -- Conventional Boiler Use -- 27 20 4 733

  4. Table 5.7 End Uses of Fuel Consumption, 2010;

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

    7 End Uses of Fuel Consumption, 2010; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Demand Residual and Natural Gas(c) LPG and Coke and Breeze) for Electricity(a) Fuel Oil Diesel Fuel(b) (billion NGL(d) (million End Use (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) Total United States TOTAL FUEL CONSUMPTION 845,727 13 22 5,064 18

  5. Table 5.8 End Uses of Fuel Consumption, 2010;

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

    8 End Uses of Fuel Consumption, 2010; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal Net Demand Residual and LPG and (excluding Coal End Use for Electricity(a) Fuel Oil Diesel Fuel(b) Natural Gas(c) NGL(d) Coke and Breeze) Total United States TOTAL FUEL CONSUMPTION 2,886 79 130 5,211 69 868 Indirect Uses-Boiler Fuel 44 46 19 2,134 10 572 Conventional Boiler Use 44 20 4 733 3 72 CHP

  6. Vehicle Technologies Office: Biofuels End-Use Research | Department of

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

    Energy Alternative Fuels » Vehicle Technologies Office: Biofuels End-Use Research Vehicle Technologies Office: Biofuels End-Use Research Biofuels offer Americans viable domestic, environmentally sustainable alternatives to gasoline and diesel. Learn about the basics, benefits, and issues to consider related to biodiesel and ethanol on the Alternative Fuels Data Center. The Vehicle Technologies Office supports research to increase our knowledge of the effects of biofuels on engines and

  7. Preliminary CBECS End-Use Estimates

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

    For the past three CBECS (1989, 1992, and 1995), we used a statistically-adjusted engineering (SAE) methodology to estimate end-use consumption. The core of the SAE methodology...

  8. Realizing Building End-Use Efficiency with Ermerging Technologies

    Broader source: Energy.gov [DOE]

    Information about the implementation of emerging technologies to maximize end-use efficiency in buildings.

  9. Office Buildings - End-Use Equipment

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

    Information Administration, 2003 Commercial Buildings Energy Consumption Survey. More computers, dedicated servers, printers, and photocopiers were used in office buildings than in...

  10. Constructing Ordered Sensitized Heterojunctions: Bottom-Up Electrochemical Synthesis of p-Type Semiconductors in Oriented n-TiO2 Nanotube Arrays

    SciTech Connect (OSTI)

    Wang, Q.; Zhu, K.; Neale, N. R.; Frank. A. J.

    2009-01-01

    Fabrication of efficient semiconductor-sensitized bulk heterojunction solar cells requires the complete filling of the pore system of one semiconductor (host) material with nanoscale dimensions (<100 nm) with a different semiconductor (guest) material. Because of the small pore size and electrical conductivity of the host material, it is challenging to employ electrochemical approaches to fill the entire pore network. Typically, during the electrochemical deposition process, the guest material blocks the pores of the host, precluding complete pore filling. We describe a general synthetic strategy for spatially controlling the growth of p-type semiconductors in the nanopores of electrically conducting n-type materials. As an illustration of this strategy, we report on the facile electrochemical deposition of p-CuInSe{sub 2} in nanoporous anatase n-TiO{sub 2} oriented nanotube arrays and nanoparticle films. We show that by controlling the ambipolar diffusion length the p-type semiconductors can be deposited from the bottom-up, resulting in complete pore filling.

  11. The Reality and Future Scenarios of Commercial Building Energy Consumption in China

    SciTech Connect (OSTI)

    Zhou, Nan; Lin, Jiang

    2007-08-01

    While China's 11th Five Year Plan called for a reduction of energy intensity by 2010, whether and how the energy consumption trend can be changed in a short time has been hotly debated. This research intends to evaluate the impact of a variety of scenarios of GDP growth, energy elasticity and energy efficiency improvement on energy consumption in commercial buildings in China using a detailed China End-use Energy Model. China's official energy statistics have limited information on energy demand by end use. This is a particularly pertinent issue for building energy consumption. The authors have applied reasoned judgments, based on experience of working on Chinese efficiency standards and energy related programs, to present a realistic interpretation of the current energy data. The bottom-up approach allows detailed consideration of end use intensity, equipment efficiency, etc., thus facilitating assessment of potential impacts of specific policy and technology changes on building energy use. The results suggest that: (1) commercial energy consumption in China's current statistics is underestimated by about 44%, and the fuel mix is misleading; (2) energy efficiency improvements will not be sufficient to offset the strong increase in end-use penetration and intensity in commercial buildings; (3) energy intensity (particularly electricity) in commercial buildings will increase; (4) different GDP growth and elasticity scenarios could lead to a wide range of floor area growth trajectories , and therefore, significantly impact energy consumption in commercial buildings.

  12. CBECS 1989 - Energy End-use Intensities in Commercial Buildings...

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

    the sampling error is nonzero and unknown for the particular sample chosen, the sample design permits sampling errors to be estimated. Due to the complexity of the sample design,...

  13. End-Use Sector Flowcharts, Energy Intensity Indicators

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

    Economy Transportation Sector Commercial Sector Residential Sector Electric Power Sector Industrial Sector Manufacturing NAICS 311-339 Food, Beverages, & Tobacco NAICS 311/312 Textile Mills and Products NAICS 313/314 Apparel & Leather Products NAICS 315/316 Wood Products NAICS 321 Paper NAICS 322 Printing & Related Support NAICS 323 Petroleum & Coal Products NAICS 324 Chemicals NAICS 325 Plastics & Rubber Products NAICS 326 Nonmetallic Mineral Products NAICS 327 Primary

  14. Energy End-Use Intensities in Commercial Buildings

    Gasoline and Diesel Fuel Update (EIA)

    and stored using mechanical pumps or fans to circulate heat-laden fluids or air between solar collectors and the building. Examples include the use of solar collectors for water...

  15. Energy Information Administration - Table 2. End Uses of Fuel...

    Gasoline and Diesel Fuel Update (EIA)

    -- -- -- Net Electricity 74 79 76 Residual Fuel Oil 19 * 11 Natural Gas 369 329 272 Machine Drive -- -- -- Net Electricity 68 86 77 Notes 1. The North American Industry...

  16. Energy End-Use Intensities in Commercial Buildings

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

    lighting intensities per lighted square foot-hour (Figure 23). * Food service and health care buildings had the highest water-heating intensities per square foot--more than...

  17. Energy End-Use Intensities in Commercial Buildings 1992 - Index...

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

    Author Contact: Joelle.Michaels@eia.doe.gov Joelle Michaels CBECS Survey Manager URL: http:www.eia.govconsumptioncommercialdataarchivecbecscbecs1d.html separater bar...

  18. End-Use Opportunity Analysis from Progress Indicator Results for ASHRAE Standard 90.1-2013

    SciTech Connect (OSTI)

    Hart, Philip R.; Xie, YuLong

    2015-02-05

    This report and an accompanying spreadsheet (PNNL 2014a) compile the end use building simulation results for prototype buildings throughout the United States. The results represent he energy use of each edition of ASHRAE Standard 90.1, Energy Standard for Buildings Except Low-Rise Residential Buildings (ASHRAE 2004, 2007, 2010, 2013). PNNL examined the simulation results to determine how the remaining energy was used.

  19. Refining and End Use Study of Coal Liquids

    SciTech Connect (OSTI)

    1997-10-01

    This report summarizes revisions to the design basis for the linear programing refining model that is being used in the Refining and End Use Study of Coal Liquids. This revision primarily reflects the addition of data for the upgrading of direct coal liquids.

  20. GridLAB-D Technical Support Document: Residential End-Use Module Version 1.0

    SciTech Connect (OSTI)

    Taylor, Zachary T.; Gowri, Krishnan; Katipamula, Srinivas

    2008-07-31

    1.0 Introduction The residential module implements the following end uses and characteristics to simulate the power demand in a single family home: • Water heater • Lights • Dishwasher • Range • Microwave • Refrigerator • Internal gains (plug loads) • House (heating/cooling loads) The house model considers the following four major heat gains/losses that contribute to the building heating/cooling load: 1. Conduction through exterior walls, roof and fenestration (based on envelope UA) 2. Air infiltration (based on specified air change rate) 3. Solar radiation (based on CLTD model and using tmy data) 4. Internal gains from lighting, people, equipment and other end use objects. The Equivalent Thermal Parameter (ETP) approach is used to model the residential loads and energy consumption. The following sections describe the modeling assumptions for each of the above end uses and the details of power demand calculations in the residential module.

  1. Electricity end-use efficiency: Experience with technologies, markets, and policies throughout the world

    SciTech Connect (OSTI)

    Levine, M.D.; Koomey, J.; Price, L.; Geller, H.; Nadel, S.

    1992-03-01

    In its August meeting in Geneva, the Energy and Industry Subcommittee (EIS) of the Policy Response Panel of the Intergovernmental Panel on Climate Change (IPCC) identified a series of reports to be produced. One of these reports was to be a synthesis of available information on global electricity end-use efficiency, with emphasis on developing nations. The report will be reviewed by the IPCC and approved prior to the UN Conference on Environment and Development (UNCED), Brazil, June 1992. A draft outline for the report was submitted for review at the November 1991 meeting of the EIS. This outline, which was accepted by the EIS, identified three main topics to be addressed in the report: status of available technologies for increasing electricity end-use efficiency; review of factors currently limiting application of end-use efficiency technologies; and review of policies available to increase electricity end-use efficiency. The United States delegation to the EIS agreed to make arrangements for the writing of the report.

  2. Driving Biofuels End Use: BETO/VTO Collaborations

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

    Driving Biofuels End Use: BETO/VTO Collaborations BETO FY 2015 Peer Review Kevin Stork EERE Vehicle Technologies Office March 26, 2015 Alexandria, Virginia 2 * Transportation is responsible for 66% of U.S. petroleum usage * 27% of GHG emissions * On-Road vehicles responsible for 85% of transportation petroleum usage Oil Dependency is Dominated by Vehicles * 16.0M LDVs sold in 2014. * 240 million light-duty vehicles on the road in the U.S * 10-15 years for annual sales penetration * 10-15 years

  3. Detailed End Use Load Modeling for Distribution System Analysis

    SciTech Connect (OSTI)

    Schneider, Kevin P.; Fuller, Jason C.

    2010-04-09

    The field of distribution system analysis has made significant advances in the past ten years. It is now standard practice when performing a power flow simulation to use an algorithm that is capable of unbalanced per-phase analysis. Recent work has also focused on examining the need for time-series simulations instead of examining a single time period, i.e., peak loading. One area that still requires a significant amount of work is the proper modeling of end use loads. Currently it is common practice to use a simple load model consisting of a combination of constant power, constant impedance, and constant current elements. While this simple form of end use load modeling is sufficient for a single point in time, the exact model values are difficult to determine and it is inadequate for some time-series simulations. This paper will examine how to improve simple time invariant load models as well as develop multi-state time variant models.

  4. Renewable Electricity Futures Study Volume 3: End-Use Electricity Demand

    Broader source: Energy.gov [DOE]

    This volume details the end-use electricity demand and efficiency assumptions. The projection of electricity demand is an important consideration in determining the extent to which a predominantly renewable electricity future is feasible. Any scenario regarding future electricity use must consider many factors, including technological, sociological, demographic, political, and economic changes (e.g., the introduction of new energy-using devices; gains in energy efficiency and process improvements; changes in energy prices, income, and user behavior; population growth; and the potential for carbon mitigation).

  5. Residential applliance data, assumptions and methodology for end-use forecasting with EPRI-REEPS 2.1

    SciTech Connect (OSTI)

    Hwang, R.J,; Johnson, F.X.; Brown, R.E.; Hanford, J.W.; Kommey, J.G.

    1994-05-01

    This report details the data, assumptions and methodology for end-use forecasting of appliance energy use in the US residential sector. Our analysis uses the modeling framework provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which was developed by the Electric Power Research Institute. In this modeling framework, appliances include essentially all residential end-uses other than space conditioning end-uses. We have defined a distinct appliance model for each end-use based on a common modeling framework provided in the REEPS software. This report details our development of the following appliance models: refrigerator, freezer, dryer, water heater, clothes washer, dishwasher, lighting, cooking and miscellaneous. Taken together, appliances account for approximately 70% of electricity consumption and 30% of natural gas consumption in the US residential sector. Appliances are thus important to those residential sector policies or programs aimed at improving the efficiency of electricity and natural gas consumption. This report is primarily methodological in nature, taking the reader through the entire process of developing the baseline for residential appliance end-uses. Analysis steps documented in this report include: gathering technology and market data for each appliance end-use and specific technologies within those end-uses, developing cost data for the various technologies, and specifying decision models to forecast future purchase decisions by households. Our implementation of the REEPS 2.1 modeling framework draws on the extensive technology, cost and market data assembled by LBL for the purpose of analyzing federal energy conservation standards. The resulting residential appliance forecasting model offers a flexible and accurate tool for analyzing the effect of policies at the national level.

  6. 1999 Commercial Buildings Characteristics--End-Use Equipment

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

    586-8800. Energy Information Administration Commercial Buildings Energy Consumption Survey Cooling Equipment Packaged air conditioning units were the predominant type of cooling...

  7. Residential Lighting End-Use Consumption Study: Estimation Framework and Initial Estimates

    SciTech Connect (OSTI)

    Gifford, Will R.; Goldberg, Miriam L.; Tanimoto, Paulo M.; Celnicker, Dane R.; Poplawski, Michael E.

    2012-12-01

    The U.S. DOE Residential Lighting End-Use Consumption Study is an initiative of the U.S. Department of Energy’s (DOE’s) Solid-State Lighting Program that aims to improve the understanding of lighting energy usage in residential dwellings. The study has developed a regional estimation framework within a national sample design that allows for the estimation of lamp usage and energy consumption 1) nationally and by region of the United States, 2) by certain household characteristics, 3) by location within the home, 4) by certain lamp characteristics, and 5) by certain categorical cross-classifications (e.g., by dwelling type AND lamp type or fixture type AND control type).

  8. Lawrence Berkeley National Laboratory (LBNL) | Open Energy Information

    Open Energy Info (EERE)

    drug Off-grid LED lighting Resources LBNL Tools BEST-Cement for China Benchmarking and Energy Saving Tool Bottom-Up Energy Analysis System (BUENAS) Climate Change Mitigation in...

  9. Technology data characterizing water heating in commercial buildings: Application to end-use forecasting

    SciTech Connect (OSTI)

    Sezgen, O.; Koomey, J.G.

    1995-12-01

    Commercial-sector conservation analyses have traditionally focused on lighting and space conditioning because of their relatively-large shares of electricity and fuel consumption in commercial buildings. In this report we focus on water heating, which is one of the neglected end uses in the commercial sector. The share of the water-heating end use in commercial-sector electricity consumption is 3%, which corresponds to 0.3 quadrillion Btu (quads) of primary energy consumption. Water heating accounts for 15% of commercial-sector fuel use, which corresponds to 1.6 quads of primary energy consumption. Although smaller in absolute size than the savings associated with lighting and space conditioning, the potential cost-effective energy savings from water heaters are large enough in percentage terms to warrant closer attention. In addition, water heating is much more important in particular building types than in the commercial sector as a whole. Fuel consumption for water heating is highest in lodging establishments, hospitals, and restaurants (0.27, 0.22, and 0.19 quads, respectively); water heating`s share of fuel consumption for these building types is 35%, 18% and 32%, respectively. At the Lawrence Berkeley National Laboratory, we have developed and refined a base-year data set characterizing water heating technologies in commercial buildings as well as a modeling framework. We present the data and modeling framework in this report. The present commercial floorstock is characterized in terms of water heating requirements and technology saturations. Cost-efficiency data for water heating technologies are also developed. These data are intended to support models used for forecasting energy use of water heating in the commercial sector.

  10. Biogas end-use in the European community

    SciTech Connect (OSTI)

    Constant, M.; Naveau, H.; Nyns, E.J. ); Ferrero, G.L.

    1989-01-01

    In Europe over the past few years the generation of biogas for energy and environmental purposes has been gaining in importance. Industrial wastewaters, cattle manure, sewage sludges, urban wastes, crop residues, algae and aquatic biomass are all typical of the materials being utilized. In contrast to the extensive inventory of biomethanation processes which has been carried out within the EEC, until recently a detailed, up-to-date investigation of the end-sues of biogas had not been undertaken. To supply the necessary information, the Commission of the European Communities and the Belgian Science Policy Office jointly entrusted a study to the Unit of Bioengineering at the Catholic University of Louvain, Belgium. This book is record of the study and has the following key features: it gives a broad overview of the ongoing use of biogas in Europe; it summarizes available data on storage, purification and engines using biogas; it draws several conclusions concerning the technical and economic viability of the processes; it discusses the problems of using biogas; and it outlines recommendations and future R and D and demonstration projects in the field.

  11. Residential and Transport Energy Use in India: Past Trend and Future Outlook

    SciTech Connect (OSTI)

    de la Rue du Can, Stephane; Letschert, Virginie; McNeil, Michael; Zhou, Nan; Sathaye, Jayant

    2009-03-31

    The main contribution of this report is to characterize the underlying residential and transport sector end use energy consumption in India. Each sector was analyzed in detail. End-use sector-level information regarding adoption of particular technologies was used as a key input in a bottom-up modeling approach. The report looks at energy used over the period 1990 to 2005 and develops a baseline scenario to 2020. Moreover, the intent of this report is also to highlight available sources of data in India for the residential and transport sectors. The analysis as performed in this way reveals several interesting features of energy use in India. In the residential sector, an analysis of patterns of energy use and particular end uses shows that biomass (wood), which has traditionally been the main source of primary energy used in households, will stabilize in absolute terms. Meanwhile, due to the forces of urbanization and increased use of commercial fuels, the relative significance of biomass will be greatly diminished by 2020. At the same time, per household residential electricity consumption will likely quadruple in the 20 years between 2000 and 2020. In fact, primary electricity use will increase more rapidly than any other major fuel -- even more than oil, in spite of the fact that transport is the most rapidly growing sector. The growth in electricity demand implies that chronic outages are to be expected unless drastic improvements are made both to the efficiency of the power infrastructure and to electric end uses and industrial processes. In the transport sector, the rapid growth in personal vehicle sales indicates strong energy growth in that area. Energy use by cars is expected to grow at an annual growth rate of 11percent, increasing demand for oil considerably. In addition, oil consumption used for freight transport will also continue to increase .

  12. Residential sector end-use forecasting with EPRI-Reeps 2.1: Summary input assumptions and results

    SciTech Connect (OSTI)

    Koomey, J.G.; Brown, R.E.; Richey, R.

    1995-12-01

    This paper describes current and projected future energy use by end-use and fuel for the U.S. residential sector, and assesses which end-uses are growing most rapidly over time. The inputs to this forecast are based on a multi-year data compilation effort funded by the U.S. Department of Energy. We use the Electric Power Research Institute`s (EPRI`s) REEPS model, as reconfigured to reflect the latest end-use technology data. Residential primary energy use is expected to grow 0.3% per year between 1995 and 2010, while electricity demand is projected to grow at about 0.7% per year over this period. The number of households is expected to grow at about 0.8% per year, which implies that the overall primary energy intensity per household of the residential sector is declining, and the electricity intensity per household is remaining roughly constant over the forecast period. These relatively low growth rates are dependent on the assumed growth rate for miscellaneous electricity, which is the single largest contributor to demand growth in many recent forecasts.

  13. Current Status and Future Scenarios of Residential Building Energy Consumption in China

    SciTech Connect (OSTI)

    Zhou, Nan; Nishida, Masaru; Gao, Weijun

    2008-12-01

    China's rapid economic expansion has propelled it into the ranks of the largest energy consuming nation in the world, with energy demand growth continuing at a pace commensurate with its economic growth. Even though the rapid growth is largely attributable to heavy industry, this in turn is driven by rapid urbanization process, by construction materials and equipment produced for use in buildings. Residential energy is mostly used in urban areas, where rising incomes have allowed acquisition of home appliances, as well as increased use of heating in southern China. The urban population is expected to grow by 20 million every year, accompanied by construction of 2 billion square meters of buildings every year through 2020. Thus residential energy use is very likely to continue its very rapid growth. Understanding the underlying drivers of this growth helps to identify the key areas to analyze energy efficiency potential, appropriate policies to reduce energy use, as well as to understand future energy in the building sector. This paper provides a detailed, bottom-up analysis of residential building energy consumption in China using data from a wide variety of sources and a modeling effort that relies on a very detailed characterization of China's energy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecast the future outlook for the critical period extending to 2020, based on assumptions of likely patterns of economic activity, availability of energy services, technology improvement and energy intensities.

  14. Comparative Analysis of Modeling Studies on China's Future Energy and Emissions Outlook

    SciTech Connect (OSTI)

    Zheng, Nina; Zhou, Nan; Fridley, David

    2010-09-01

    The past decade has seen the development of various scenarios describing long-term patterns of future Greenhouse Gas (GHG) emissions, with each new approach adding insights to our understanding of the changing dynamics of energy consumption and aggregate future energy trends. With the recent growing focus on China's energy use and emission mitigation potential, a range of Chinese outlook models have been developed across different institutions including in China's Energy Research Institute's 2050 China Energy and CO2 Emissions Report, McKinsey & Co's China's Green Revolution report, the UK Sussex Energy Group and Tyndall Centre's China's Energy Transition report, and the China-specific section of the IEA World Energy Outlook 2009. At the same time, the China Energy Group at Lawrence Berkeley National Laboratory (LBNL) has developed a bottom-up, end-use energy model for China with scenario analysis of energy and emission pathways out to 2050. A robust and credible energy and emission model will play a key role in informing policymakers by assessing efficiency policy impacts and understanding the dynamics of future energy consumption and energy saving and emission reduction potential. This is especially true for developing countries such as China, where uncertainties are greater while the economy continues to undergo rapid growth and industrialization. A slightly different assumption or storyline could result in significant discrepancies among different model results. Therefore, it is necessary to understand the key models in terms of their scope, methodologies, key driver assumptions and the associated findings. A comparative analysis of LBNL's energy end-use model scenarios with the five above studies was thus conducted to examine similarities and divergences in methodologies, scenario storylines, macroeconomic drivers and assumptions as well as aggregate energy and emission scenario results. Besides directly tracing different energy and CO{sub 2} savings potential back to the underlying strategies and combination of efficiency and abatement policy instruments represented by each scenario, this analysis also had other important but often overlooked findings.

  15. "End Use","for Electricity(a)","Fuel Oil","Diesel Fuel(b)","Natural...

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

    8 Relative Standard Errors for Table 5.8;" " Unit: Percents." ,,,"Distillate" ,,,"Fuel Oil",,,"Coal" ,"Net Demand","Residual","and",,"LPG and","(excluding Coal" "End Use","for...

  16. ,"U.S. Distillate Fuel Oil and Kerosene Sales by End Use"

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

    Distillate Fuel Oil and Kerosene Sales by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

  17. ,"New Mexico Sales of Distillate Fuel Oil by End Use"

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

    Sales of Distillate Fuel Oil by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Sales of Distillate Fuel Oil by End Use",13,"Annual",2014,"6/30/1984" ,"Release Date:","12/22/2015" ,"Next Release Date:","Last Week of November 2016" ,"Excel

  18. ,"Nebraska Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Nebraska Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  19. ,"Nevada Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Nevada Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  20. ,"New Hampshire Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Hampshire Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  1. ,"New Jersey Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Jersey Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  2. ,"New Mexico Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  3. ,"New York Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New York Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  4. ,"North Carolina Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Carolina Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  5. ,"North Dakota Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  6. ,"Oklahoma Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  7. ,"Pennsylvania Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  8. ,"Rhode Island Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Rhode Island Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  9. ,"South Carolina Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","South Carolina Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  10. ,"South Dakota Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","South Dakota Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  11. ,"U.S. Adjusted Sales of Distillate Fuel Oil by End Use"

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

    Distillate Fuel Oil by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Adjusted Sales of Distillate Fuel Oil by End Use",13,"Annual",2014,"6/30/1984" ,"Release Date:","12/22/2015" ,"Next Release Date:","Last Week of November 2016" ,"Excel File

  12. ,"U.S. Adjusted Sales of Residual Fuel Oil by End Use"

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

    Residual Fuel Oil by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Adjusted Sales of Residual Fuel Oil by End Use",8,"Annual",2014,"6/30/1984" ,"Release Date:","12/22/2015" ,"Next Release Date:","Last Week of November 2016" ,"Excel File

  13. ,"Utah Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  14. ,"West Virginia Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","West Virginia Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  15. ,"Wisconsin Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Wisconsin Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  16. ,"Alabama Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alabama Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  17. ,"Arizona Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Arizona Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  18. ,"Connecticut Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Connecticut Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  19. ,"Delaware Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Delaware Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  20. ,"Georgia Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Georgia Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  1. ,"Idaho Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Idaho Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  2. ,"Kansas Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  3. ,"Kentucky Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  4. ,"Louisiana Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  5. ,"Maryland Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Maryland Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  6. ,"Mississippi Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Mississippi Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  7. ,"Missouri Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Missouri Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  8. ,"Montana Natural Gas Consumption by End Use"

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

    Consumption by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Consumption by End Use",6,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  9. MARKAL-MACRO: A linked model for energy-economy analysis

    SciTech Connect (OSTI)

    Manne, A.S.; Wene, C.O.

    1992-02-01

    MARKAL-MACRO is an experiment in model linkage for energy and economy analysis. This new tool is intended as an improvement over existing methods for energy strategy assessment. It is designed specifically for estimating the costs and analyzing the technologies proposed for reducing environmental risks such as global climate change or regional air pollution. The greenhouse gas debate illustrates the usefulness of linked energy-economy models. A central issue is the coupling between economic growth, the level of energy demands, and the development of an energy system to supply these demands. The debate is often connected with alternative modeling approaches. The competing philosophies may be labeled ``top-down macroeconomic`` and ``bottom-up engineering`` perspectives. MARKAL is a systems engineering (physical process) analysis built on the concept of a Reference Energy System (RES). MARKAL is solved by means of dynamic linear programming. In most applications, the end use demands are fixed, and an economically efficient solution is obtained by minimizing the present value of energy system`s costs throughout the planning horizon. MACRO is a macroeconomic model with an aggregated view of long-term economic growth. The basis input factors of production are capital, labor and individual forms of energy. MACRO is solved by nonlinear optimization.

  10. MARKAL-MACRO: A linked model for energy-economy analysis

    SciTech Connect (OSTI)

    Manne, A.S. ); Wene, C.O. Chalmers Univ. of Tech., Goeteborg )

    1992-02-01

    MARKAL-MACRO is an experiment in model linkage for energy and economy analysis. This new tool is intended as an improvement over existing methods for energy strategy assessment. It is designed specifically for estimating the costs and analyzing the technologies proposed for reducing environmental risks such as global climate change or regional air pollution. The greenhouse gas debate illustrates the usefulness of linked energy-economy models. A central issue is the coupling between economic growth, the level of energy demands, and the development of an energy system to supply these demands. The debate is often connected with alternative modeling approaches. The competing philosophies may be labeled top-down macroeconomic'' and bottom-up engineering'' perspectives. MARKAL is a systems engineering (physical process) analysis built on the concept of a Reference Energy System (RES). MARKAL is solved by means of dynamic linear programming. In most applications, the end use demands are fixed, and an economically efficient solution is obtained by minimizing the present value of energy system's costs throughout the planning horizon. MACRO is a macroeconomic model with an aggregated view of long-term economic growth. The basis input factors of production are capital, labor and individual forms of energy. MACRO is solved by nonlinear optimization.

  11. "Table B25. Energy End Uses, Floorspace for Non-Mall Buildings...

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

    may apply)" ,,"Space Heating","Cooling","Water Heating","Cooking","Manu- facturing" "All ...5378,4653,4631,1926,"Q" "District Chilled Water ......",2853,2734,2853,2655,1274,"Q" ...

  12. Energy for 500 Million Homes: Drivers and Outlook for Residential Energy Consumption in China

    SciTech Connect (OSTI)

    Zhou, Nan; McNeil, Michael A.; Levine, Mark

    2009-06-01

    China's rapid economic expansion has propelled it to the rank of the largest energy consuming nation in the world, with energy demand growth continuing at a pace commensurate with its economic growth. The urban population is expected to grow by 20 million every year, accompanied by construction of 2 billion square meters of buildings every year through 2020. Thus residential energy use is very likely to continue its very rapid growth. Understanding the underlying drivers of this growth helps to identify the key areas to analyze energy efficiency potential, appropriate policies to reduce energy use, as well as to understand future energy in the building sector. This paper provides a detailed, bottom-up analysis of residential building energy consumption in China using data from a wide variety of sources and a modelling effort that relies on a very detailed characterization of China's energy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecast the future outlook for the critical period extending to 2020, based on assumptions of likely patterns of economic activity, availability of energy services, technology improvement and energy intensities. From this analysis, we can conclude that Chinese residential energy consumption will more than double by 2020, from 6.6 EJ in 2000 to 15.9 EJ in 2020. This increase will be driven primarily by urbanization, in combination with increases in living standards. In the urban and higher income Chinese households of the future, most major appliances will be common, and heated and cooled areas will grow on average. These shifts will offset the relatively modest efficiency gains expected according to current government plans and policies already in place. Therefore, levelling and reduction of growth in residential energy demand in China will require a new set of more aggressive efficiency policies.

  13. Assembly of a Molecular Needle, from the Bottom Up

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

    Genetic sequencing studies seem to indicate that type III secretion systems come from a common ancestor foreign to the bacteria. Crystallographic studies such as the one by Yip...

  14. Assembly of a Molecular Needle, from the Bottom Up

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

    in gram-negative bacteria (e.g. Yersinia, Shigella, Salmonella, Pseudomonas, and E. coli), which are all characterized by a double-membrane cell wall. The needle complex spans...

  15. Assembly of a Molecular Needle, from the Bottom Up

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

    micrograph of the needle complex. The TTSS needle complex is found in gram-negative bacteria (e.g. Yersinia, Shigella, Salmonella, Pseudomonas, and E. coli), which are all...

  16. Assembly of a Molecular Needle, from the Bottom Up

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

    Inset: Electron micrograph of the needle complex. The TTSS needle complex is found in gram-negative bacteria (e.g. Yersinia, Shigella, Salmonella, Pseudomonas, and E. coli),...

  17. Engineer End Uses for Maximum Efficiency; Industrial Technologies Program (ITP) Compressed Air Tip Sheet #10 (Fact Sheet)

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

    0 * August 2004 Industrial Technologies Program Suggested Actions * Review compressed air end uses and determine the required level of air pressure. * Review the compressed air end uses' original confgurations to determine whether manufacturing processes have evolved in such a way that those end uses are no longer necessary or can be reconfgured more effciently. References From Compressed Air Challenge Âź (CAC): The Compressed Air System Best Practices Manual, Guidelines for Selecting a

  18. ,"U.S. Adjusted Distillate Fuel Oil and Kerosene Sales by End Use"

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

    Distillate Fuel Oil and Kerosene Sales by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Residential",4,"Annual",2014,"6/30/1984" ,"Data 2","Commercial",10,"Annual",2014,"6/30/1984" ,"Data

  19. ,"U.S. Distillate Fuel Oil and Kerosene Sales by End Use"

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

    Distillate Fuel Oil and Kerosene Sales by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Residential",4,"Annual",2014,"6/30/1984" ,"Data 2","Commercial",10,"Annual",2014,"6/30/1984" ,"Data

  20. Evaluating Energy Efficiency Policies with Energy-Economy Models

    SciTech Connect (OSTI)

    Mundaca, Luis; Neij, Lena; Worrell, Ernst; McNeil, Michael A.

    2010-08-01

    The growing complexities of energy systems, environmental problems and technology markets are driving and testing most energy-economy models to their limits. To further advance bottom-up models from a multidisciplinary energy efficiency policy evaluation perspective, we review and critically analyse bottom-up energy-economy models and corresponding evaluation studies on energy efficiency policies to induce technological change. We use the household sector as a case study. Our analysis focuses on decision frameworks for technology choice, type of evaluation being carried out, treatment of market and behavioural failures, evaluated policy instruments, and key determinants used to mimic policy instruments. Although the review confirms criticism related to energy-economy models (e.g. unrealistic representation of decision-making by consumers when choosing technologies), they provide valuable guidance for policy evaluation related to energy efficiency. Different areas to further advance models remain open, particularly related to modelling issues, techno-economic and environmental aspects, behavioural determinants, and policy considerations.

  1. Table 3. Top five retailers of electricity, with end use sectors...

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

    3,"WGL Energy Services, Inc.","Investor-owned",1270636,59707,1210929,0,0 4,"Direct Energy Business Marketing, LLC","Investor-owned",1208043,0,839195,220720,148128 5,"Direct Energy ...

  2. 1980 survey and evaluation of utility conservation, load management, and solar end-use projects. Volume 3: utility load management projects. Final report

    SciTech Connect (OSTI)

    Not Available

    1982-01-01

    The results of the 1980 survey of electric utility-sponsored energy conservation, load management, and end-use solar energy conversion projects are described. The work is an expansion of a previous survey and evaluation and has been jointly sponsored by EPRI and DOE through the Oak Ridge National Laboratory. There are three volumes and a summary document. Each volume presents the results of an extensive survey to determine electric utility involvement in customer-side projects related to the particular technology (i.e., conservation, solar, or load management), selected descriptions of utility projects and results, and first-level technical and economic evaluations.

  3. Target Allocation Methodology for China's Provinces: Energy Intensity in the 12th FIve-Year Plan

    SciTech Connect (OSTI)

    Ohshita, Stephanie; Price, Lynn

    2011-03-21

    Experience with China's 20% energy intensity improvement target during the 11th Five-Year Plan (FYP) (2006-2010) has shown the challenges of rapidly setting targets and implementing measures to meet them. For the 12th FYP (2011-2015), there is an urgent need for a more scientific methodology to allocate targets among the provinces and to track physical and economic indicators of energy and carbon saving progress. This report provides a sectoral methodology for allocating a national energy intensity target - expressed as percent change in energy per unit gross domestic product (GDP) - among China's provinces in the 12th FYP. Drawing on international experience - especially the European Union (EU) Triptych approach for allocating Kyoto carbon targets among EU member states - the methodology here makes important modifications to the EU approach to address an energy intensity rather than a CO{sub 2} emissions target, and for the wider variation in provincial energy and economic structure in China. The methodology combines top-down national target projections and bottom-up provincial and sectoral projections of energy and GDP to determine target allocation of energy intensity targets. Total primary energy consumption is separated into three end-use sectors - industrial, residential, and other energy. Sectoral indicators are used to differentiate the potential for energy saving among the provinces. This sectoral methodology is utilized to allocate provincial-level targets for a national target of 20% energy intensity improvement during the 12th FYP; the official target is determined by the National Development and Reform Commission. Energy and GDP projections used in the allocations were compared with other models, and several allocation scenarios were run to test sensitivity. The resulting allocations for the 12th FYP offer insight on past performance and offer somewhat different distributions of provincial targets compared to the 11th FYP. Recommendations for reporting and monitoring progress on the targets, and methodology improvements, are included.

  4. Public Meeting: Physical Characterization of Smart and Grid-Connected Commercial and Residential Building End-Use Equipment and Appliances

    Office of Energy Efficiency and Renewable Energy (EERE)

    These documents contain slide decks presented at the Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances public meeting held on April 30, 2014.

  5. July 11 Public Meeting: Physical Characterization of Grid-Connected Commercial And Residential Building End-Use Equipment And Appliances

    Broader source: Energy.gov [DOE]

    These documents contain the three slide decks presented at the public meeting on the Physical Characterization of Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances, held on July 11, 2014 in Washington, DC.

  6. Table 3. Top five retailers of electricity, with end use sectors...

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

    NewEnergy, Inc","Investor-owned",469721,0,296950,149198,23573 4,"TransCanada Power Marketing, Ltd.","Investor-owned",301970,0,0,301970,0 5,"Direct Energy Business ...

  7. Table 3. Top five retailers of electricity, with end use sectors...

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

    3,"PECO Energy Co","Investor-owned",11394476,8577010,2270505,546961,0 4,"Talen Energy Marketing, LLC","Investor-owned",10381698,1509992,5324011,3260638,287057 5,"PPL ...

  8. Table 3. Top five retailers of electricity, with end use sectors...

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

    Energy LLC - (MT)","Investor-owned",5974533,2398528,3120726,455279,0 2,"Talen Energy Marketing, LLC","Investor-owned",2202299,0,131400,2070899,0 3,"Flathead Electric ...

  9. Energy by State | Open Energy Information

    Open Energy Info (EERE)

    per ) Compare By: US States Sector End-Use Sectors Electric Power Sector Energy Source, Consumption Coal Geothermal Energy Hydroelectric Power Natural Gas Nuclear Energy...

  10. Microsoft Word - Major end uses front page v2 2015-03-31.docx

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

    ... and manufacturer information. - Provide a relative ... and clothes dryers in 2015 * ENERGY STAR continues to ... (HHV) of the fuel. **Electricity consumption is for ...

  11. Table 3. Top five retailers of electricity, with end use sectors...

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

    Maine" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"NextEra Energy Power Marketing","Investor-owned",19844...

  12. The use of negotiated agreements to improve efficiency of end-use appliances: First results from the European experience

    SciTech Connect (OSTI)

    Bertoldi, P.; Bowie, R.; Hagen, L.

    1998-07-01

    The European Union is pursuing measures to improve end-use equipment efficiency through a variety of policy instruments, in particular for domestic appliances. One of the most effective methods to achieve market transformation is through minimum efficiency performance standards (MEPS). However, after the difficulties and controversy following the adoption of legislation for MEPS for domestic refrigerators/freezers, a new policy instrument, i.e. negotiated agreements by manufacturers, has been investigated and tested for two type of appliances: domestic washing machines and TVs and VCRs. Based on the positive experience of the above two agreements, other products (e.g. dryers, dishwasher, electric water heaters, etc.) will be the subject of future negotiated agreements. Based on the results of the two negotiated agreements, this paper describes the energy efficiency potential, the procedures, and the advantages and disadvantages of negotiated agreements compared to legislated mandatory for MEPS, as developed in the European context. The paper concludes that negotiated agreements are a viable policy option, which allow flexibility in the implementation of the efficiency targets and therefore the adoption of cost-effective solutions for manufacturers. In addition, negotiated agreements can be implemented more quickly compared to mandatory MEPS and they allow a closer monitoring of the results. The main question asked in the paper is whether the negotiated agreements can deliver the results in the long term compared to what could be achieved through legislation. The European experience indicates that this instrument can deliver the results and that it offer a number of advantages compared to MEPS.

  13. Table 3. Top five retailers of electricity, with end use sectors...

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

    NewEnergy, Inc","Investor-owned",3073373,0,2140922,923167,9284 5,"TransCanada Power Marketing, Ltd.","Investor-owned",2374650,0,0,2374650,0 " ","Total sales, top five ...

  14. Table 3. Top five retailers of electricity, with end use sectors...

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

    4,"Niagara Mohawk Power Corp.","Investor-owned",13152596,8914956,3220135,1017505,0 5,"Direct Energy Business Marketing, LLC","Investor-owned",8604263,0,4198880,4405383,0 " ...

  15. Table 3. Top five retailers of electricity, with end use sectors...

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

    3,"United Illuminating Co","Investor-owned",1771412,1179978,547455,43979,0 4,"TransCanada Power Marketing, Ltd.","Investor-owned",1347975,0,0,1347975,0 5,"Direct Energy ...

  16. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Michigan" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"DTE Electric Company","Investor-owned",42272312,15273084,16715877,10283351,0 2,"Consumers Energy Co","Investor-owned",32556015,12792609,11117015,8646391,0 3,"First Energy Solutions

  17. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Carolina" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"Duke Energy Carolinas, LLC","Investor-owned",55301813,20601105,22341733,12351570,7405 2,"Duke Energy Progress - (NC)","Investor-owned",36886571,15249396,13425824,8211351,0 3,"Virginia Electric & Power

  18. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Ohio" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"First Energy Solutions Corp.","Investor-owned",49437270,14024133,21080138,14272628,60371 2,"Ohio Power Co","Investor-owned",19142615,10834999,3492174,4815442,0 3,"DPL Energy

  19. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Texas" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"Reliant Energy Retail Services","Investor-owned",39511303,17784060,3813963,17913280,0 2,"TXU Energy Retail Co LP","Investor-owned",37916867,22545174,5383121,9988572,0 3,"City of San Antonio -

  20. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Hampshire" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"Public Service Co of NH","Investor-Owned",3772359,2488177,1149989,134193,0 2,"Constellation NewEnergy, Inc","Investor-Owned",978706,0,577347,401359,0 3,"Integrys Energy Services, Inc.","Investor-Owned",789158,3122,786036,0,0

  1. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Illinois" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"Constellation NewEnergy, Inc","Investor-owned",19729300,869767,12641305,5509689,708539 2,"Commonwealth Edison Co","Investor-owned",18295340,9548453,7883890,862997,0 3,"Homefield

  2. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Indiana" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"Duke Energy Indiana Inc","Investor-owned",28003070,9183527,8450462,10369081,0 2,"Northern Indiana Pub Serv Co","Investor-owned",16798335,3444738,3992698,9339677,21222 3,"Indiana Michigan Power

  3. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Iowa" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"MidAmerican Energy Co","Investor-owned",20217549,5829442,5195709,9192398,0 2,"Interstate Power and Light Co","Investor-owned",14586595,3939183,3951419,6695993,0 3,"Board of Water Electric &

  4. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Kansas" "megawatthours" ,"Entity","Type of Provider","All Sectors","Residential","Commercial","Industrial","Transportation" 1,"Westar Energy Inc","Investor-owned",9826375,3409863,4433462,1983050,0 2,"Kansas Gas & Electric Co","Investor-owned",9669223,3113287,3132064,3423872,0 3,"Kansas City Power & Light

  5. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Maryland" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"Baltimore Gas & Electric Co","Investor-owned",11968295,8967015,2846423,154857,0 2,"WGL Energy Services, Inc.","Investor-owned",7553788,1092845,6460943,0,0 3,"Potomac Electric Power

  6. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Jersey" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"Public Service Elec & Gas Co","Investor-owned",19192403,11493325,6936055,763023,0 2,"Jersey Central Power & Lt Co","Investor-owned",9947655,7417321,2298350,231984,0 3,"Direct Energy Business Marketing,

  7. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Carolina" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"South Carolina Electric&Gas Company","Investor-owned",21371090,7571438,7799857,5999795,0 2,"Duke Energy Carolinas, LLC","Investor-owned",20566058,6313640,5619965,8632453,0 3,"South Carolina Public Service

  8. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Dakota" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"Northern States Power Co - Minnesota","Investor-owned",2040726,725505,980503,334718,0 2,"NorthWestern Energy - (SD)","Investor-owned",1564096,579570,690191,294335,0 3,"Black Hills Power

  9. Microsoft Word - Major end uses front page v2 2015-03-31.docx

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

    4 APPENDIX C EIA - Technology Forecast Updates - Residential and Commercial Building Technologies - Reference Case Presented to: U.S. Energy Information Administration Prepared by: Navigant Consulting, Inc. 1200 19th Street, NW, Suite 700 Washington, D.C. 20036 And SAIC 8301 Greensboro Drive McLean, VA 22102 December 19, 2012 Confidential and Proprietary, ©2012 Navigant Consulting, Inc. Do not distribute or copy Final DISCLAIMER This presentation was prepared as an account of work sponsored by

  10. Microsoft Word - Major end uses front page v2 2015-03-31.docx

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

    5 APPENDIX D EIA - Technology Forecast Updates - Residential and Commercial Building Technologies - Advanced Case Presented to: U.S. Energy Information Administration Prepared by: Navigant Consulting, Inc. 1200 19th Street, NW, Suite 700 Washington, D.C. 20036 And SAIC 8301 Greensboro Drive McLean, VA 22102 December 19, 2012 Confidential and Proprietary, ©2012 Navigant Consulting, Inc. Do not distribute or copy Advanced Case Final DISCLAIMER This presentation was prepared as an account of work

  11. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Florida" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"Florida Power & Light Co","Investor-owned",103058588,54074164,45932938,2963404,88082 2,"Duke Energy Florida, Inc","Investor-owned",36615990,18507962,14901674,3206354,0 3,"Tampa Electric Co","Investor-owned",18417662,8469567,7921282,2026813,0

  12. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Total sales, top five providers" "Nevada" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"Nevada Power Co","Investor-owned",21184405,9012407,4576328,7587394,8276 2,"Sierra Pacific Power Co","Investor-owned",8151543,2369781,2963657,2818105,0 3,"Shell Energy North America (US),

  13. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Washington" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"Puget Sound Energy Inc","Investor-owned",21208609,10769101,9205670,1229556,4282 2,"City of Seattle - (WA)","Public",9457191,3137668,5261681,1057188,654 3,"Bonneville Power Administration","Federal",7222335,0,833256,6389079,0

  14. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    Wyoming" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"PacifiCorp","Investor-owned",9553734,1092932,1538409,6922393,0 2,"Powder River Energy Corp","Cooperative",2633437,215755,912786,1504896,0 3,"Cheyenne Light Fuel & Power Co","Investor-owned",1100543,269296,549520,281727,0

  15. Renewable Electricity Futures Study. Volume 3: End-Use Electricity Demand

    SciTech Connect (OSTI)

    Hostick, D.; Belzer, D.B.; Hadley, S.W.; Markel, T.; Marnay, C.; Kintner-Meyer, M.

    2012-06-01

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).

  16. Renewable Electricity Futures Study. Volume 3. End-Use Electricity Demand

    SciTech Connect (OSTI)

    Hostick, Donna; Belzer, David B.; Hadley, Stanton W.; Markel, Tony; Marnay, Chris; Kintner-Meyer, Michael

    2012-06-15

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%–90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT). Learn more at the RE Futures website. http://www.nrel.gov/analysis/re_futures/

  17. Researching Energy Use in Hospitals

    Broader source: Energy.gov [DOE]

    Historically, when hospital facility and energy managers have compared alternative energy efficiency investments for various end-use systems, their benchmarks have been limited to end-use estimates...

  18. Table 10.9 Photovoltaic Cell and Module Shipments by Sector and End Use, 1989-2010 (Peak Kilowatts )

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

    Photovoltaic Cell and Module Shipments by Sector and End Use, 1989-2010 (Peak Kilowatts 1 ) Year By Sector By End Use Total Residential Commercial 3 Industrial 4 Electric Power 5 Other 6 Grid-Connected 2 Off-Grid 2 Centralized 7 Distributed 8 Domestic 9 Non-Domestic 10 Total Shipments of Photovoltaic Cells and Modules 11<//td> 1989 1,439 6,057 [R] 3,993 785 551 [12] 1,251 [12] 2,620 8,954 12,825 1990 1,701 8,062 [R] 2,817 826 432 [12] 469 [12] 3,097 10,271 13,837 1991 3,624 5,715 [R] 3,947

  19. " Row: End Uses;"

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

    HVAC (e)",280,3,5,417,5,5,6.6 " Facility Lighting",212,"--","--","--","--","--",1.1 " ... HVAC (e)",41,2,3,68,1,"*",6.4 " Facility Lighting",33,"--","--","--","--","--",1.3 " Other ...

  20. " Row: End Uses;"

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

    HVAC (f)",285,4,4,378,5,2 " Facility Lighting",215,"--","--","--","--","--" " Other ... HVAC (f)",38,3,3,57,1,"*" " Facility Lighting",29,"--","--","--","--","--" " Other ...

  1. " Row: End Uses;"

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

    HVAC (f)",236,"Q",4,306,4,3 " Facility Lighting",177,"--","--","--","--","--" " Other ... HVAC (f)",29,"Q",3,45,1,"Q" " Facility Lighting",22,"--","--","--","--","--" " Other ...

  2. " Row: End Uses;" " ...

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

    ...,79355,1,1,392,1,"*","--",5.7 " Facility Lighting","--",61966,"--","--","--","--","--","--...707,"*",1,57,"*","*","--",7.2 " Facility Lighting","--",9494,"--","--","--","--","--","--"...

  3. " Row: End Uses;" " ...

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

    ..."--",271,4,6,403,4,4,"--",5.7 " Facility Lighting","--",211,"--","--","--","--","--","--",... *","--",7.2 " Facility Lighting","--",32,"--","--","--","--","--","--",1...

  4. " Row: End Uses;"

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

    HVAC (f)",83480,1,1,367,1,"*" " Facility Lighting",62902,"--","--","--","--","--" " Other ... (f)",11142,"*","*",56,"*","*" " Facility Lighting",8470,"--","--","--","--","--" " Other ...

  5. " Row: End Uses;" " ...

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

    ...f)","--",265,4,4,378,5,2,"--" " Facility Lighting","--",198,"--","--","--","--","--","--" ...f)","--",34,3,3,57,1,"*","--" " Facility Lighting","--",26,"--","--","--","--","--","--" " ...

  6. " Row: End Uses;" " ...

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

    ..."--",77768,1,1,367,1,"*","--" " Facility Lighting","--",58013,"--","--","--","--","--","--...,9988,"*","*",56,"*","*","--" " Facility Lighting","--",7651,"--","--","--","--","--","--" ...

  7. " Row: End Uses;" " ...

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

    ...","--",222,"Q",4,306,4,3,"--" " Facility Lighting","--",165,"--","--","--","--","--","--" ...","--",26,"Q",3,45,1,"Q","--" " Facility Lighting","--",20,"--","--","--","--","--","--" " ...

  8. " Row: End Uses;"

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

    (f)",69090,"*",1,297,1,"*" " Facility Lighting",51946,"--","--","--","--","--" " Other ... (f)",8543,"*",1,43,"*","*" " Facility Lighting",6524,"--","--","--","--","--" " Other ...

  9. " Row: End Uses;"

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

    (e)",81980,1,1,406,1,"*",6.6 " Facility Lighting",62019,"--","--","--","--","--",1.1 " ...)",12126,"*",1,66,"*","*",6.4 " Facility Lighting",9668,"--","--","--","--","--",1.3 " ...

  10. " Row: End Uses;" " ...

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

    ..."--",262,3,5,417,5,5,"--",6.6 " Facility Lighting","--",196,"--","--","--","--","--","--",..."--",38,2,3,68,1,"*","--",6.4 " Facility Lighting","--",30,"--","--","--","--","--","--",1...

  11. " Row: End Uses;" " ...

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

    ...,76840,1,1,406,1,"*","--",6.6 " Facility Lighting","--",57460,"--","--","--","--","--","--...241,"*",1,66,"*","*","--",6.4 " Facility Lighting","--",8831,"--","--","--","--","--","--"...

  12. " Row: End Uses;"

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

    ... 1, 2, and 4 fuel oils and Nos. 1, 2, and 4" "diesel fuels." " (c) 'Natural Gas' ... gas brokers, marketers," "and any marketing subsidiaries of utilities." " (d) ...

  13. " Row: End Uses;" " ...

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

    ... 1, 2, and 4 fuel oils and Nos. 1, 2, and 4" "diesel fuels." " (c) 'Natural Gas' ... gas brokers, marketers," "and any marketing subsidiaries of utilities." " (d) ...

  14. Table 2.6 Household End Uses: Fuel Types, Appliances, and Electronics, Selected Years, 1978-2009

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

    6 Household End Uses: Fuel Types, Appliances, and Electronics, Selected Years, 1978-2009 Appliance Year Change 1978 1979 1980 1981 1982 1984 1987 1990 1993 1997 2001 2005 2009 1980 to 2009 Total Households (millions) 77 78 82 83 84 86 91 94 97 101 107 111 114 32 Percent of Households<//td> Space Heating - Main Fuel 1 Natural Gas 55 55 55 56 57 55 55 55 53 52 55 52 50 -5 Electricity 2 16 17 18 17 16 17 20 23 26 29 29 30 35 17 Liquefied Petroleum Gases 4 5 5 4 5 5 5 5 5 5 5 5 5 0 Distillate

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

    Gasoline and Diesel Fuel Update (EIA)

    of Energy, U.S. Energy Information Administration. 6. U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Residential Lighting End-Use Consumption...

  16. Commercial Buildings Energy Consumption and Expenditures 1992

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

    Distribution Category UC-950 Commercial Buildings Energy Consumption and Expenditures 1992 April 1995 Energy Information Adminstration Office of Energy Markets and End Use U.S....

  17. Quadrennial Energy Review Second Installment Electricity: Generation...

    Energy Savers [EERE]

    Quadrennial Energy Review Second Installment Electricity: Generation to End-Use ... Ernest Moniz, United States Secretary of Energy As United States Secretary of Energy, Dr. ...

  18. The Boom of Electricity Demand in the Residential Sector in the Developing World and the Potential for Energy Efficiency

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2008-05-13

    With the emergence of China as the world's largest energy consumer, the awareness of developing country energy consumption has risen. According to common economic scenarios, the rest of the developing world will probably see an economic expansion as well. With this growth will surely come continued rapid growth in energy demand. This paper explores the dynamics of that demand growth for electricity in the residential sector and the realistic potential for coping with it through efficiency. In 2000, only 66% of developing world households had access to electricity. Appliance ownership rates remain low, but with better access to electricity and a higher income one can expect that households will see their electricity consumption rise significantly. This paper forecasts developing country appliance growth using econometric modeling. Products considered explicitly - refrigerators, air conditioners, lighting, washing machines, fans, televisions, stand-by power, water heating and space heating - represent the bulk of household electricity consumption in developing countries. The resulting diffusion model determines the trend and dynamics of demand growth at a level of detail not accessible by models of a more aggregate nature. In addition, the paper presents scenarios for reducing residential consumption through cost-effective and/or best practice efficiency measures defined at the product level. The research takes advantage of an analytical framework developed by LBNL (BUENAS) which integrates end use technology parameters into demand forecasting and stock accounting to produce detailed efficiency scenarios, which allows for a realistic assessment of efficiency opportunities at the national or regional level. The past decades have seen some of the developing world moving towards a standard of living previously reserved for industrialized countries. Rapid economic development, combined with large populations has led to first China and now India to emerging as 'energy giants', a phenomenon that is expected to continue, accelerate and spread to other countries. This paper explores the potential for slowing energy consumption and greenhouse gas emissions in the residential sector in developing countries and evaluates the potential of energy savings and emissions mitigation through market transformation programs such as, but not limited to Energy Efficiency Standards and Labeling (EES&L). The bottom-up methodology used allows one to identify which end uses and regions have the greatest potential for savings.

  19. Historical Monthly Energy Review

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

    73-92) Distribution Category UC-950 Historical Monthly Energy Review 1973-1992 Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy...

  20. 2014-04-30 Public Meeting Presentation Slides: Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances

    Office of Energy Efficiency and Renewable Energy (EERE)

    These documents contain slide decks presented at the Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances public meeting held on April 30, 2014.

  1. 2014-04-30 Public Meeting Agenda: Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances

    Broader source: Energy.gov [DOE]

    This document is the agenda for the Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances public meeting being held on April 30, 2014.

  2. Agenda for Public Meeting on the Physical Characterization of Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances

    Broader source: Energy.gov [DOE]

    Download the agenda below for the July 11 Public Meeting on the Physical Characterization of Grid-Connected Commercial and  Residential Buildings End-Use Equipment and Appliances.

  3. Peru-GEF Nationally Appropriate Mitigation Actions in the Energy...

    Open Energy Info (EERE)

    (Redirected from UNDP-Peru GEF Nationally Appropriate Mitigation Actions in the Energy Generation and End-Use Sectors)...

  4. Assessment of Energy Use in Multibuilding Facilities

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

    CBECS asked for district steam or district hot water piped into the building. Source: Energy Information Administration, Office of Energy Markets and End Use, 1979, 1983, 1986 and...

  5. Buildings and Energy in the 1980s

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

    Air Conditioning: See Energy End Use, Cooling. Authorization Form: A form signed by the respondent authorizing energy supplier companies that serve the building to release...

  6. Commercial Buildings Energy Consumption Survey (CBECS) - U.S. Energy

    Gasoline and Diesel Fuel Update (EIA)

    Information Administration (EIA) Estimation of Energy End-use Consumption CBECS 2012 - Release date: March 18, 2016 2012 CBECS The energy end-use consumption tables for the 2012 CBECS provide estimates of the amount of electricity, natural gas, fuel oil, and district heat used for ten end uses: space heating, cooling, ventilation, water heating, lighting, cooking, refrigeration, computing (including servers), office equipment, and other uses. Although details vary by energy source, there are

  7. Table 10.7 Solar Thermal Collector Shipments by Market Sector, End Use, and Type, 2001-2009 (Thousand Square Feet)

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

    Solar Thermal Collector Shipments by Market Sector, End Use, and Type, 2001-2009 (Thousand Square Feet) Year and Type By Market Sector By End Use Total Residential Commercial 1 Industrial 2 Electric Power 3 Other 4 Pool Heating Water Heating Space Heating Space Cooling Combined Heating 5 Process Heating Electricity Generation Total Shipments 6<//td> 2001 Total 10,125 1,012 17 1 35 10,797 274 70 0 12 34 2 11,189 Low 7 9,885 987 12 0 34 10,782 42 61 0 0 34 0 10,919 Medium 8 240 24 5 0 1 16

  8. Monthly Energy Review - March 2010

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

    March 31, 2010 DOEEIA-0035(201003) Monthly Energy Review March 2010 U.S. Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy...

  9. Monthly Energy Review - May 2010

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

    May 27, 2010 DOEEIA-0035(201005) Monthly Energy Review May 2010 U.S. Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington,...

  10. Monthly Energy Review - April 2010

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

    April 30, 2010 DOEEIA-0035(201004) Monthly Energy Review April 2010 U.S. Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy...

  11. Monthly Energy Review - May 2010

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

    June 30, 2010 DOEEIA-0035(201006) Monthly Energy Review June 2010 U.S. Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy...

  12. Monthly Energy Review - July 2010

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

    July 30, 2010 DOEEIA-0035(201007) Monthly Energy Review July 2010 U.S. Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy...

  13. Monthly Energy Review - February 2010

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

    February 26, 2010 DOEEIA-0035(201002) Monthly Energy Review February 2010 U.S. Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy...

  14. Bottom-up, decision support system development : a wetlandsalinity management application in California's San Joaquin Valley

    SciTech Connect (OSTI)

    Quinn, Nigel W.T.

    2006-05-10

    Seasonally managed wetlands in the Grasslands Basin ofCalifornia's San Joaquin Valley provide food and shelter for migratorywildfowl during winter months and sport for waterfowl hunters during theannual duck season. Surface water supply to these wetland contain saltwhich, when drained to the San Joaquin River during the annual drawdownperiod, negatively impacts downstream agricultural riparian waterdiverters. Recent environmental regulation, limiting discharges salinityto the San Joaquin River and primarily targeting agricultural non-pointsources, now addresses return flows from seasonally managed wetlands.Real-time water quality management has been advocated as a means ofmatching wetland return flows to the assimilative capacity of the SanJoaquin River. Past attempts to build environmental monitoring anddecision support systems to implement this concept have failed forreasons that are discussed in this paper. These reasons are discussed inthe context of more general challenges facing the successfulimplementation of environmental monitoring, modelling and decisionsupport systems. The paper then provides details of a current researchand development project which will ultimately provide wetland managerswith the means of matching salt exports with the available assimilativecapacity of the San Joaquin River, when fully implemented. Manipulationof the traditional wetland drawdown comes at a potential cost to thesustainability of optimal wetland moist soil plant habitat in thesewetlands - hence the project provides appropriate data and a feedback andresponse mechanism for wetland managers to balance improvements to SanJoaquin River quality with internally-generated information on the healthof the wetland resource. The author concludes the paper by arguing thatthe architecture of the current project decision support system, whencoupled with recent advances in environmental data acquisition, dataprocessing and information dissemination technology, holds significantpromise to address some of the problems described earlier in the paperthat have limited past efforts to improve Basin water qualitymanagement.

  15. Estimates of U.S. Commercial Building Electricity Intensity Trends: Issues Related to End-Use and Supply Surveys

    SciTech Connect (OSTI)

    Belzer, David B.

    2004-09-04

    This report examines measurement issues related to the amount of electricity used by the commercial sector in the U.S. and the implications for historical trends of commercial building electricity intensity (kWh/sq. ft. of floor space). The report compares two (Energy Information Administration) sources of data related to commercial buildings: the Commercial Building Energy Consumption Survey (CBECS) and the reporting by utilities of sales to commercial customers (survey Form-861). Over past two decades these sources suggest significantly different trend rates of growth of electricity intensity, with the supply (utility)-based estimate growing much faster than that based only upon the CBECS. The report undertakes various data adjustments in an attempt to rationalize the differences between these two sources. These adjustments deal with: 1) periodic reclassifications of industrial vs. commercial electricity usage at the state level and 2) the amount of electricity used by non-enclosed equipment (non-building use) that is classified as commercial electricity sales. In part, after applying these adjustments, there is a good correspondence between the two sources over the the past four CBECS (beginning with 1992). However, as yet, there is no satisfactory explanation of the differences between the two sources for longer periods that include the 1980s.

  16. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    6 Reference case Table A19. Energy-related carbon dioxide emissions by end use (million metric tons) Energy Information Administration / Annual Energy Outlook 2015 Table A19. Energy-related carbon dioxide emissions by end use (million metric tons) Sector and end use Reference case Annual growth 2013-2040 (percent) 2012 2013 2020 2025 2030 2035 2040 Residential Space heating ........................................................ 228 293 248 236 228 218 207 -1.3% Space cooling

  17. Energy Use in China: Sectoral Trends and Future Outlook

    SciTech Connect (OSTI)

    Zhou, Nan; McNeil, Michael A.; Fridley, David; Lin, Jiang; Price,Lynn; de la Rue du Can, Stephane; Sathaye, Jayant; Levine, Mark

    2007-10-04

    This report provides a detailed, bottom-up analysis ofenergy consumption in China. It recalibrates official Chinese governmentstatistics by reallocating primary energy into categories more commonlyused in international comparisons. It also provides an analysis of trendsin sectoral energy consumption over the past decades. Finally, itassesses the future outlook for the critical period extending to 2020,based on assumptions of likely patterns of economic activity,availability of energy services, and energy intensities. The followingare some highlights of the study's findings: * A reallocation of sectorenergy consumption from the 2000 official Chinese government statisticsfinds that: * Buildings account for 25 percent of primary energy, insteadof 19 percent * Industry accounts for 61 percent of energy instead of 69percent * Industrial energy made a large and unexpected leap between2000-2005, growing by an astonishing 50 percent in the 3 years between2002 and 2005. * Energy consumption in the iron and steel industry was 40percent higher than predicted * Energy consumption in the cement industrywas 54 percent higher than predicted * Overall energy intensity in theindustrial sector grew between 2000 and 2003. This is largely due tointernal shifts towards the most energy-intensive sub-sectors, an effectwhich more than counterbalances the impact of efficiency increases. *Industry accounted for 63 percent of total primary energy consumption in2005 - it is expected to continue to dominate energy consumption through2020, dropping only to 60 percent by that year. * Even assuming thatgrowth rates in 2005-2020 will return to the levels of 2000-2003,industrial energy will grow from 42 EJ in 2005 to 72 EJ in 2020. * Thepercentage of transport energy used to carry passengers (instead offreight) will double from 37 percent to 52 percent between 2000 to 2020,.Much of this increase is due to private car ownership, which willincrease by a factor of 15 from 5.1 million in 2000 to 77 million in2020. * Residential appliance ownership will show signs of saturation inurban households. The increase in residential energy consumption will belargely driven by urbanization, since rural homes will continue to havelow consumption levels. In urban households, the size of appliances willincrease, but its effect will be moderated by efficiency improvements,partially driven by government standards. * Commercial energy increaseswill be driven both by increases in floor space and by increases inpenetration of major end uses such as heating and cooling. Theseincreases will be moderated somewhat, however, by technology changes,such as increased use of heat pumps. * China's Medium- and Long-TermDevelopment plan drafted by the central government and published in 2004calls for a quadrupling of GDP in the period from 2000-2020 with only adoubling in energy consumption during the same period. A bottom-upanalysis with likely efficiency improvements finds that energyconsumption will likely exceed the goal by 26.12 EJ, or 28 percent.Achievements of these goals will there fore require a more aggressivepolicy of encouraging energy efficiency.

  18. April 30 Public Meeting: Physical Characterization of Smart and Grid-Connected Commercial and Residential Building End-Use Equipment and Appliances

    Broader source: Energy.gov [DOE]

    These documents contain slide decks presented at the Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances public meeting held on April 30, 2014. The first document includes the first presentation from the meeting: DOE Vision and Objectives. The second document includes all other presentations from the meeting: Terminology and Definitions; End-User and Grid Services; Physical Characterization Framework; Value, Benefits & Metrics.

  19. Manufacturing Consumption of Energy 1994

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

    2(94) Distribution Category UC-950 Manufacturing Consumption of Energy 1994 December 1997 Energy Information Administration Office of Energy Markets and End Use U.S. Department of...

  20. U.S. Renewable Energy Policy and Industry

    SciTech Connect (OSTI)

    Zhou, Ella

    2015-10-01

    From 2005 to 2014, wind and solar power generation has seen an almost tenfold increase in the United States. Such rapid development is the result of a variety of federal and state, top-down and bottom-up drivers, as well as the macro-environment of cost-reduction globally and early adoption in Europe. This presentation, prepared for a meeting with China National Renewable Energy Center and National Energy Administration (of China), is a summary of some of the key drivers for renewable energy deployment in the United States.

  1. Buildings and Energy in the 80's -- Overview

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

    Total Residential and Commercial Primary Consumption by Type of Building Sources: Energy Information Administration, Office of Energy Markets and End Use, EIA-457 of the 1980...

  2. The Global Energy Challenge (Conference) | SciTech Connect

    Office of Scientific and Technical Information (OSTI)

    conversion of energy from chemical fuel, sunlight, and heat to electricity or hydrogen as an energy carrier and finally to end uses like transportation, lighting, and...

  3. U.S. Energy Information Administration (EIA) - Ap

    Gasoline and Diesel Fuel Update (EIA)

    and the number of producing facilities Consumption & Efficiency view all Residential Energy Consumption Survey Household end use consumption of energy and expenditures Commercial...

  4. Buildings and Energy in the 80's -- Detailed Tables

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

    Total Residential and Commercial Primary Consumption by Type of Building Sources: Energy Information Administration, Office of Energy Markets and End Use, EIA-457 of the 1980...

  5. CBECS - Buildings and Energy in the 1980's - Detailed Tables

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

    Total Residential and Commercial Primary Consumption by Type of Building Sources: Energy Information Administration, Office of Energy Markets and End Use, EIA-457 of the 1980...

  6. U.S. Energy Information Administration (EIA) - Ap

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

    (2) Congressional & other requests (1) consumption (8) demand (1) end-use (1) energy (2) Energy Perspectives (5) exports (7) Extended Policies Case (1) forecast (1)...

  7. ,"Total Fuel Oil Consumption (trillion Btu)",,,,,"Fuel Oil Energy...

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

    A. Fuel Oil Consumption (Btu) and Energy Intensities by End Use for All Buildings, 2003" ,"Total Fuel Oil Consumption (trillion Btu)",,,,,"Fuel Oil Energy Intensity (thousand Btu...

  8. Manufacturing consumption of energy 1991

    SciTech Connect (OSTI)

    Not Available

    1994-12-01

    This report provides estimates on energy consumption in the manufacturing sector of the US economy. These estimates are based on data from the 1991 Manufacturing Energy Consumption Survey (MECS). This survey--administered by the Energy End Use and Integrated Statistics Division, Office of Energy Markets and End Use, Energy Information Administration (EIA)--is the most comprehensive source of national-level data on energy-related information for the manufacturing industries.

  9. National Energy Efficiency Evaluation, Measurement and Verification (EM&V) Standard: Scoping Study of Issues and Implementation Requirements

    SciTech Connect (OSTI)

    Schiller Consulting, Inc.; Schiller, Steven R.; Goldman, Charles A.; Galawish, Elsia

    2011-02-04

    This report is a scoping study that identifies issues associated with developing a national evaluation, measurement and verification (EM&V) standard for end-use, non-transportation, energy efficiency activities. The objectives of this study are to identify the scope of such a standard and define EM&V requirements and issues that will need to be addressed in a standard. To explore these issues, we provide and discuss: (1) a set of definitions applicable to an EM&V standard; (2) a literature review of existing guidelines, standards, and 'initiatives' relating to EM&V standards as well as a review of 'bottom-up' versus 'top-down' evaluation approaches; (3) a summary of EM&V related provisions of two recent federal legislative proposals (Congressman Waxman's and Markey's American Clean Energy and Security Act of 2009 and Senator Bingaman's American Clean Energy Leadership Act of 2009) that include national efficiency resource requirements; (4) an annotated list of issues that that are likely to be central to, and need to be considered when, developing a national EM&V standard; and (5) a discussion of the implications of such issues. There are three primary reasons for developing a national efficiency EM&V standard. First, some policy makers, regulators and practitioners believe that a national standard would streamline EM&V implementation, reduce costs and complexity, and improve comparability of results across jurisdictions; although there are benefits associated with each jurisdiction setting its own EM&V requirements based on their specific portfolio and evaluation budgets and objectives. Secondly, if energy efficiency is determined by the US Environmental Protection Agency to be a Best Available Control Technology (BACT) for avoiding criteria pollutant and/or greenhouse gas emissions, then a standard can be required for documenting the emission reductions resulting from efficiency actions. The third reason for a national EM&V standard is that such a standard is likely to be required as a result of future federal energy legislation that includes end-use energy efficiency, either as a stand-alone energy-efficiency resource standard (EERS) or as part of a clean energy or renewable energy standard. This study is focused primarily on this third reason and thus explores issues associated with a national EM&V standard if energy efficiency is a qualifying resource in federal clean energy legislation. Developing a national EM&V standard is likely to be a lengthy process; this study focuses on the critical first step of identifying the issues that must be addressed in a future standard. Perhaps the most fundamental of these issues is 'how good is good enough?' This has always been the fundamental issue of EM&V for energy efficiency and is a result of the counter-factual nature of efficiency. Counter-factual in that savings are not measured, but estimated to varying degrees of accuracy by comparing energy consumption after a project (program) is implemented with what is assumed to have been the consumption of energy in the absence of the project (program). Therefore, the how good is good enough question is a short version of asking how certain does one have to be of the energy savings estimate that results from EM&V activities and is that level of certainty properly balanced against the amount of effort (resources, time, money) that is utilized to obtain that level of certainty. The implication is that not only should energy efficiency investments be cost-effective, but EM&V investments should consider risk management principles and thus also balance the costs and value of information derived from EM&V (EM&V should also be cost-effective).

  10. China Energy and Emissions Paths to 2030

    SciTech Connect (OSTI)

    Fridley, David; Zheng, Nina; Zhou, Nan; Ke, Jing; Hasanbeigi, Ali; Morrow, Bill; Price, Lynn

    2011-01-14

    After over two decades of staggering economic growth and soaring energy demand, China has started taking serious actions to reduce its economic energy and carbon intensity by setting short and medium-term intensity reduction targets, renewable generation targets and various supporting policies and programs. In better understanding how further policies and actions can be taken to shape China's future energy and emissions trajectory, it is important to first identify where the largest opportunities for efficiency gains and emission reduction lie from sectoral and end-use perspectives. Besides contextualizing China's progress towards reaching the highest possible efficiency levels through the adoption of the most advanced technologies from a bottom-up perspective, the actual economic costs and benefits of adopting efficiency measures are also assessed in this study. This study presents two modeling methodologies that evaluate both the technical and economic potential of raising China's efficiency levels to the technical maximum across sectors and the subsequent carbon and energy emission implications through 2030. The technical savings potential by efficiency measure and remaining gap for improvements are identified by comparing a reference scenario in which China continues the current pace of with a Max Tech scenario in which the highest technically feasible efficiencies and advanced technologies are adopted irrespective of costs. In addition, from an economic perspective, a cost analysis of selected measures in the key industries of cement and iron and steel help quantify the actual costs and benefits of achieving the highest efficiency levels through the development of cost of conserved energy curves for the sectors. The results of this study show that total annual energy savings potential of over one billion tonne of coal equivalent exists beyond the expected reference pathway under Max Tech pathway in 2030. CO2 emissions will also peak earlier under Max Tech, though the 2020s is a likely turning point for both emission trajectories. Both emission pathways must meet all announced and planned policies, targets and non-fossil generation targets, or an even wider efficiency gap will exist. The savings potential under Max Tech varies by sector, but the industrial sector appears to hold the largest energy savings and emission reduction potential. The primary source of savings is from electricity rather than fuel, and electricity savings are magnified by power sector decarbonization through increasing renewable generation and coal generation efficiency improvement. In order to achieve the maximum energy savings and emission reduction potential, efficiency improvements and technology switching must be undertaken across demand sectors as well as in the growing power sector. From an economic perspective, the cost of conserved energy analysis indicates that nearly all measures for the iron and steel and cement industry are cost-effective. All 23 efficiency measures analyzed for the cement industry are cost-effective, with combined CO2 emission reduction potential of 448 Mt CO2. All of the electricity savings measures in the iron and steel industry are cost-effective, but the cost-effective savings potential for fuel savings measures is slightly lower than total technical savings potential. The total potential savings from these measures confirm the magnitude of savings in the scenario models, and illustrate the remaining efficiency gap in the cement and iron and steel industries.

  11. Energy Efficiency Program Impact Evaluation Guide

    Broader source: Energy.gov [DOE]

    This Energy Efficiency Program Impact Evaluation Guide describes and provides guidance on approaches for determining and documenting energy and non-energy benefits resulting from end-use energy efficiency programs and portfolios of programs.

  12. Tax Credits, Rebates & Savings | Department of Energy

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

    end-use customers. This information must be provided to customers quarterly "in plain English." Electricity suppliers must also file a copy of their energy source disclosure...

  13. Buildings and Energy in the 1980s

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

    Energy Sources and End Uses Energy is an important but often unnoticed contributor to the high levels of productivity and quality of life enjoyed by U.S. residents. Energy is used...

  14. Energy Intensity Indicators: Overview of Concepts

    Broader source: Energy.gov [DOE]

    The Energy Intensity Indicators website reports changes in energy intensity in the United States since 1970. The website discusses, and presents data for, energy intensity trends by major end-use...

  15. Energy Intensity Indicators: Coverage

    Broader source: Energy.gov [DOE]

    This system of energy intensity indicators for total energy covers the economy as a whole and each of the major end-use sectors—transportation, industry, commercial, and residential, as well as the electric power sector. These sectors are shown in Figure 1. More detail for some of these sectors can be obtained by accessing the file "End-Use Sector Flowchart" below Figure 1.

  16. Buildings Energy Data Book

    Buildings Energy Data Book [EERE]

    Most Popular Tables PDFXLS 1.1.1 U.S. Residential and Commercial Buildings Total Primary Energy Consumption PDFXLS 3.1.1 Commercial Primary Energy Consumption, by Year and Fuel Type PDFXLS 1.1.3 Buildings Share of U.S. Primary Energy Consumption PDFXLS 3.1.4 2010 Commercial Energy End-Use Splits, by Fuel Type PDFXLS 2.1.1 Residential Primary Energy Consumption, by Year and Fuel Type PDFXLS 3.1.5 2015 Commercial Energy End-Use Splits, by Fuel Type PDFXLS 3.2.1 Total Commercial Floorspace and

  17. Assumption to the Annual Energy Outlook 2014 - Commercial Demand...

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

    chosen to meet the projected service demands for the seven major end uses. Once technologies are chosen, the energy consumed by the equipment stock (both existing and purchased...

  18. Fuel Mix and Emissions Disclosure | Department of Energy

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

    end-use customers. This information must be provided to customers quarterly "in plain English." Electricity suppliers must also file a copy of their energy source disclosure...

  19. Deep Energy Retrofit Performance Metric Comparison: Eight California...

    Office of Scientific and Technical Information (OSTI)

    the home were performed and the homes were monitored for total and individual end-use energy consumption for approximately one year. Annual performance in site and source...

  20. Consumption & Efficiency - U.S. Energy Information Administration...

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

    larger shares of electricity generation oil... Btu January to November 2015 2014 2013 2012 End-Use ... Source: U.S. Energy Information Administration, Monthly ...

  1. Price Elasticities for Energy Use in Buildings of the United...

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

    end uses in the Electricity Price Doubled case 10 ... 2014 U.S. Energy Information Administration | Price ... is cut in half between 2015 and 2040)......

  2. Manufacturing Energy and Carbon Footprints (2010 MECS) | Department of

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

    Energy Manufacturing Energy and Carbon Footprints (2010 MECS) Manufacturing Energy and Carbon Footprints (2010 MECS) Energy and carbon footprints map energy use and carbon emissions in manufacturing from energy supply to end use. The footprints show where energy is used and lost-and the associated greenhouse gases (GHGs) that are emitted. Each footprint visualizes the flow of energy (in the form of fuel, electricity, or steam) to major end uses in manufacturing, including boilers, power

  3. Energy-Water Overview

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

    Emerging Issues and Challenges DOE/EIA 2010 Energy Conference Mike Hightower Sandia National Laboratories mmhight@sandia.gov, 505-844-5499 Energy and Water are ... Interdependent Water for Energy and Energy for Water Energy and power production require water: * Thermoelectric cooling * Hydropower * Energy minerals extraction/mining * Fuel Production (fossil fuels, H 2 , biofuels) * Emission control Water production, processing, distribution, and end-use require energy: * Pumping * Conveyance and

  4. Buildings and Energy in the 1980's

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

    sum to totals. * See "Glossary" for definition of terms used in this report. Source: Energy Information Administration, Office of Energy Markets and End Use, Form EIA-457 of the...

  5. Energy Signal Tool for Decision Support in Building Energy Systems...

    Office of Scientific and Technical Information (OSTI)

    different from expected (red and yellow lights) or approximately the same as expected (green light). Which light to display for a given energy end use is determined by comparing...

  6. Manufacturing Consumption of Energy 1994

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

    A9. Total Inputs of Energy for Heat, Power, and Electricity Generation by Fuel Type, Census Region, and End Use, 1994: Part 1 (Estimates in Btu or Physical Units) See footnotes at...

  7. S U M M A R I E S U.S. Energy Information Administration | State...

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

    End-Use Sectors a Fossil Fuels Nuclear Electric Power Renewable Energy e Net Interstate Flow of Electricity f Net Electricity Imports g Residential Commercial Industrial b...

  8. U.S. States - U.S. Energy Information Administration (EIA) -...

    Gasoline and Diesel Fuel Update (EIA)

    End-Use Sectors a Fossil Fuels Nuclear Electric Power Renewable Energy e Net Interstate Flow of Electricity f Net Electricity Imports g Residential Commercial Industrial b...

  9. International energy outlook 2006

    SciTech Connect (OSTI)

    2006-06-15

    This report presents international energy projections through 2030, prepared by the Energy Information Administration. After a chapter entitled 'Highlights', the report begins with a review of world energy and economic outlook, followed by energy consumption by end-use sector. The next chapter is on world oil markets. Natural gas, world coal market and electricity consumption and supply are then discussed. The final chapter covers energy-related carbon dioxide emissions.

  10. Estimate of Cost-Effective Potential for Minimum Efficiency Performance Standards in 13 Major World Economies Energy Savings, Environmental and Financial Impacts

    SciTech Connect (OSTI)

    Letschert, Virginie E.; Bojda, Nicholas; Ke, Jing; McNeil, Michael A.

    2012-07-01

    This study analyzes the financial impacts on consumers of minimum efficiency performance standards (MEPS) for appliances that could be implemented in 13 major economies around the world. We use the Bottom-Up Energy Analysis System (BUENAS), developed at Lawrence Berkeley National Laboratory (LBNL), to analyze various appliance efficiency target levels to estimate the net present value (NPV) of policies designed to provide maximum energy savings while not penalizing consumers financially. These policies constitute what we call the “cost-effective potential” (CEP) scenario. The CEP scenario is designed to answer the question: How high can we raise the efficiency bar in mandatory programs while still saving consumers money?

  11. Energy

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

    Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Fuel Cycle Defense Waste Management Programs Advanced Nuclear Energy Nuclear

  12. Energy

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

    2 - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Fuel Cycle Defense Waste Management Programs Advanced Nuclear Energy Nuclear

  13. Energy

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

    3 - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Fuel Cycle Defense Waste Management Programs Advanced Nuclear Energy Nuclear

  14. The Global Energy Challenge (Conference) | SciTech Connect

    Office of Scientific and Technical Information (OSTI)

    New routes are needed for the efficient conversion of energy from chemical fuel, sunlight, and heat to electricity or hydrogen as an energy carrier and finally to end uses...

  15. Buildings and Energy in the 1980's (TABLES)

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

    sum to totals. * See "Glossary" for definition of terms used in this report. Source: Energy Information Administration, Office of Energy Markets and End Use, Form EIA-788 of the...

  16. Manufacturing Energy Consumption Survey (MECS) - U.S. Energy Information

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

    Administration (EIA) U. S. Census Regions and Divisions: census map About the MECS Survey forms Maps MECS Terminology Archives Features First 2010 Data Press Release 2010 Data Brief Other End Use Surveys Commercial Buildings - CBECS Residential - RECS Transportation DOE Uses MECS Data Manufacturing Energy and Carbon Footprints Associated Analysis Manufacturing Energy Sankey Diagrams Manufacturing Energy Flows Tool

  17. Energy

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

    national energy security by developing energy sources with limited impacts on environment improving efficiency and reliability of nation's energy infrastructure Research...

  18. Healthcare Energy: Massachusetts General Hospital Gray Building

    Broader source: Energy.gov [DOE]

    The Building Technologies Office conducted a healthcare energy end-use monitoring project in partnership with two hospitals. This page contains highlights from monitoring at the Gray Building at Massachusetts General Hospital.

  19. U.S. Energy Information Administration | State Energy Data 2013: Consumption

    Gasoline and Diesel Fuel Update (EIA)

    15 Section 7. Total Energy T O T A L E N E R G Y The preceding sections of this documentation describe how the U. S. Energy Information Administration (EIA) arrives at state end-use consumption estimates by individual energy source in the State Energy Data System (SEDS). This section describes how all energy sources are added in Btu to create total energy consumption and end-use consumption estimates. Total Energy Consumption Total energy consumption by state is defined in SEDS as the sum of all

  20. High-Energy Permanent Magnets for Hybrid Vehicles and Alternative Energy Uses

    SciTech Connect (OSTI)

    Hadjipanayis, George C.; McCallum, William R.; Sellmyer, David J.; Harris, Vincent; Carpenter, Everett E.; Liu, Jinfang

    2013-12-17

    The report summarizes research undertaken by a multidisciplinary team aimed at the development of the next generation high-energy permanent magnets. The principal approach was relied on bottom-up fabrication of anisotropic nanocomposite magnets. Our efforts resulted in further development of the theoretical concept and fabrication principles for the nanocomposites and in synthesis of a range of rare-earth-based hard magnetic nanoparticles. Even though we did not make a breakthrough in the assembly of these hard magnetic particles with separately prepared Fe(Co) nanoparticles and did not obtain a compact nanocomposite magnet, our performed research will help to direct the future efforts, in particular, towards nano-assembly via coating, when the two phases which made the nanocomposite are first organized in core-shell-structured particles. Two other approaches were to synthesize (discover) new materials for the traditional singe-material magnets and the nanocomposite magnets. Integrated theoretical and experimental efforts lead to a significant advance in nanocluster synthesis technique and yielded novel rare-earth-free nanostructured and nanocomposite materials. Examination of fifteen R-Fe-X alloy systems (R = rare earth), which have not been explored earlier due to various synthesis difficulties reveal several new ferromagnetic compounds. The research has made major progress in bottom-up manufacturing of rare-earth-containing nanocomposite magnets with superior energy density and open new directions in development of higher-energy-density magnets that do not contain rare earths. The advance in the scientific knowledge and technology made in the course of the project has been reported in 50 peer-reviewed journal articles and numerous presentations at scientific meetings.

  1. ENERGY

    Office of Environmental Management (EM)

    U.S. Department of ENERGY Department of Energy Quadrennial Technology Review-2015 Framing Document http://energy.gov/qtr 2015-01-13 Page 2 The United States faces serious energy-linked challenges as well as substantial energy opportunities. Disruptions, both natural and man-made, threaten our aging energy infrastructure; global patterns of energy use are changing our climate; and our nation's dependence on foreign sources of energy comes at a significant cost to our economy. We need clean,

  2. SUSTAINABLE DEVELOPMENT IN KAZAKHASTAN: USING OIL AND GAS PRODUCTION BY-PRODUCT SULFUR FOR COST-EFFECTIVE SECONDARY END-USE PRODUCTS.

    SciTech Connect (OSTI)

    KALB, P.D.; VAGIN, S.; BEALL, P.W.; LEVINTOV, B.L.

    2004-09-25

    The Republic of Kazakhstan is continuing to develop its extensive petroleum reserves in the Tengiz region of the northeastern part of the Caspian Sea. Large quantities of by-product sulfur are being produced as a result of the removal of hydrogen sulfide from the oil and gas produced in the region. Lack of local markets and economic considerations limit the traditional outlets for by-product sulfur and the buildup of excess sulfur is a becoming a potential economic and environmental liability. Thus, new applications for re-use of by-product sulfur that will benefit regional economies including construction, paving and waste treatment are being developed. One promising application involves the cleanup and treatment of mercury at a Kazakhstan chemical plant. During 19 years of operation at the Pavlodar Khimprom chlor-alkali production facility, over 900 tons of mercury was lost to the soil surrounding and beneath the buildings. The Institute of Metallurgy and Ore Benefication (Almaty) is leading a team to develop and demonstrate a vacuum-assisted thermal process to extract the mercury from the soil and concentrate it as pure, elemental mercury, which will then be treated using the Sulfur Polymer Stabilization/Solidification (SPSS) process. The use of locally produced sulfur will recycle a low-value industrial by-product to treat hazardous waste and render it safe for return to the environment, thereby helping to solve two problems at once. SPSS chemically stabilizes mercury to mercuric sulfide, which has a low vapor pressure and low solubility, and then physically encapsulates the material in a durable, monolithic solid sulfur polymer matrix. Thus, mercury is placed in a solid form very much like stable cinnabar, the form in which it is found in nature. Previous research and development has shown that the process can successfully encapsulate up to 33 wt% mercury in the solid form, while still meeting very strict regulatory standards for leachable mercury (0.025 mg/l in the Toxicity Characteristic Leaching Procedure). The research and development to deploy Kazakhstan recycled sulfur for secondary applications described in this paper is being conducted with support from the International Science and Technology Center (ISTC) and the U.S. Department of Energy Initiatives for Proliferation Prevention (DOE IPP).

  3. Energy

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

    Energy /newsroom/_assets/images/energy-icon.png Energy Research into alternative forms of energy, and improving and securing the power grid, is a major national security imperative. Health Space Computing Energy Earth Materials Science Technology The Lab All The Grid Modernization Initiative represents a comprehensive DOE effort to help shape the future of our nation's grid and solve the challenges of integrating conventional and renewable sources with energy storage and smart buildings. Los

  4. " Row: End Uses within NAICS Codes;"

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

    (g)",69090,"*",1,297,1,"*" ," Facility Lighting",51946,"--","--","--","--","--" ," Other ... (g)",6192,"*","*",32,"*","*" ," Facility Lighting",6082,"--","--","--","--","--" ," Other ...

  5. " Row: End Uses within NAICS Codes;"

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

    HVAC (g)",236,"Q",4,306,4,3 ," Facility Lighting",177,"--","--","--","--","--" ," Other ... (g)",21,"*","Q",33,"*","*" ," Facility Lighting",21,"--","--","--","--","--" ," Other ...

  6. " Row: End Uses within NAICS Codes;"

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

    ...)","--",265,4,4,378,5,2,"--" ," Facility Lighting","--",198,"--","--","--","--","--","--" ...--",21,"*","*",30,1,"*","--" ," Facility Lighting","--",18,"--","--","--","--","--","--" ...

  7. " Row: End Uses within NAICS Codes;"

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

    ...--",77768,1,1,367,1,"*","--" ," Facility Lighting","--",58013,"--","--","--","--","--","--...6036,"*","*",29,"*","*","--" ," Facility Lighting","--",5291,"--","--","--","--","--","--" ...

  8. " Row: End Uses within NAICS Codes;"

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

    (g)",83480,1,1,367,1,"*" ," Facility Lighting",62902,"--","--","--","--","--" ," Other ... (g)",6217,"*","*",29,"*","*" ," Facility Lighting",5472,"--","--","--","--","--" ," Other ...

  9. " Row: End Uses within NAICS Codes;"

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

    (f)",84678,1,1,392,1,"*",5.7 ," Facility Lighting",66630,"--","--","--","--","--",1 ," ...,5402,"*","*",26,"*","*",2.2 ," Facility Lighting",4785,"--","--","--","--","--",1 ," ...

  10. " Row: End Uses within NAICS Codes;"

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

    ...",64945,"*",1,297,1,"*","--" ," Facility Lighting","--",48453,"--","--","--","--","--","--...5949,"*","*",32,"*","*","--" ," Facility Lighting","--",5809,"--","--","--","--","--","--" ...

  11. " Row: End Uses within NAICS Codes;"

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

    (g)",81980,1,1,406,1,"*",6.6 ," Facility Lighting",62019,"--","--","--","--","--",1.1 ," ...5037,"*","*",36,"*","*",11.3 ," Facility Lighting",4826,"--","--","--","--","--",1.3 ," ...

  12. " Row: End Uses within NAICS Codes;"

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

    ...79355,1,1,392,1,"*","--",5.7 ," Facility Lighting","--",61966,"--","--","--","--","--","--...,"*","*",26,"*","*","--",2.2 ," Facility Lighting","--",4492,"--","--","--","--","--","--"...

  13. " Row: End Uses within NAICS Codes;"

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

    (g)",280,3,5,417,5,5,6.6 ," Facility Lighting",212,"--","--","--","--","--",1.1 ," ...g)",17,"*","*",37,1,"*",11.3 ," Facility Lighting",16,"--","--","--","--","--",1.3 ," ...

  14. " Row: End Uses within NAICS Codes;"

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

    (f)",289,4,6,403,4,4,5.7 ," Facility Lighting",227,"--","--","--","--","--",1 ," Other ... (f)",18,1,1,26," *"," *",2.2 ," Facility Lighting",16,"--","--","--","--","--",1 ," Other ...

  15. " Row: End Uses within NAICS Codes;"

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

    ...,"--",222,"Q",4,306,4,3,"--" ," Facility Lighting","--",165,"--","--","--","--","--","--" ...",20,"*","Q",33,"*","*","--" ," Facility Lighting","--",20,"--","--","--","--","--","--" ...

  16. " Row: End Uses within NAICS Codes;"

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

    ...--",271,4,6,403,4,4,"--",5.7 ," Facility Lighting","--",211,"--","--","--","--","--","--",... *"," *","--",2.2 ," Facility Lighting","--",15,"--","--","--","--","--","--",1 ...

  17. " Row: End Uses within NAICS Codes;"

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

    ...--",262,3,5,417,5,5,"--",6.6 ," Facility Lighting","--",196,"--","--","--","--","--","--",...6,"*","*",37,1,"*","--",11.3 ," Facility Lighting","--",15,"--","--","--","--","--","--",1...

  18. " Row: End Uses within NAICS Codes;"

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

    HVAC (g)",285,4,4,378,5,2 ," Facility Lighting",215,"--","--","--","--","--" ," Other ... (g)",21,"*","*",30,1,"*" ," Facility Lighting",19,"--","--","--","--","--" ," Other ...

  19. " Row: End Uses within NAICS Codes;"

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

    ...76840,1,1,406,1,"*","--",6.6 ," Facility Lighting","--",57460,"--","--","--","--","--","--..."*","*",36,"*","*","--",11.3 ," Facility Lighting","--",4526,"--","--","--","--","--","--"...

  20. End-Use Taxes: Current EIA Practices

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

    However, many States levy taxes on aviation fuel, as shown in Table B3 in Appendix B, based on information obtained from State TaxationRevenue Offices. The use of the national...

  1. Alabama Natural Gas Consumption by End Use

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

    534,779 598,514 666,712 615,407 634,678 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 10,163 10,367 12,389 12,456 10,055 1983-2014 Plant Fuel 6,441 6,939 6,616 6,804 6,462 1983-2014 Pipeline & Distribution Use 22,124 23,091 25,349 22,166 18,688 1997-2014 Volumes Delivered to Consumers 496,051 558,116 622,359 573,981 599,473 640,707 1997-2015 Residential 42,215 36,582 27,580 35,059 38,971 31,794 1967-2015 Commercial 27,071 25,144 21,551 25,324 27,515 24,519 1967-2015 Industrial 144,938

  2. Alaska Natural Gas Consumption by End Use

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

    333,312 335,458 343,110 332,298 327,428 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 211,918 208,531 214,335 219,190 219,451 1983-2014 Plant Fuel 37,316 35,339 37,397 36,638 36,707 1983-2014 Pipeline & Distribution Use 3,284 3,409 3,974 544 309 1997-2014 Volumes Delivered to Consumers 80,794 88,178 87,404 75,926 70,960 70,027 1997-2015 Residential 18,714 20,262 21,380 19,215 17,734 18,468 1967-2015 Commercial 15,920 19,399 19,898 18,694 17,925 19,281 1967-2015 Industrial 6,408 6,769

  3. Arizona Natural Gas Consumption by End Use

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

    330,914 288,802 332,068 332,073 307,946 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 19 17 12 4 3 1983-2014 Pipeline & Distribution Use 15,447 13,158 12,372 12,619 13,484 1997-2014 Volumes Delivered to Consumers 315,448 275,627 319,685 319,450 294,459 336,195 1997-2015 Residential 37,812 38,592 34,974 39,692 32,397 34,215 1967-2015 Commercial 31,945 32,633 31,530 32,890 30,456 30,537 1967-2015 Industrial 19,245 21,724 22,657 22,153 22,489 19,991 1997-2015 Vehicle Fuel 2,015 1,712

  4. Arkansas Natural Gas Consumption by End Use

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

    244,193 271,515 284,076 296,132 282,120 268,453 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 4,091 5,340 6,173 6,599 6,605 6,452 1983-2014 Plant Fuel 489 529 423 622 797 871...

  5. Louisiana Natural Gas Consumption by End Use

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

    17,378 117,825 109,098 112,861 116,396 123,498 2001-2015 Residential 1,292 1,202 1,354 1,531 2,380 3,756 1989-2015 Commercial 1,804 1,902 2,214 2,286 2,789 2,970 1989-2015 Industrial 77,300 80,789 78,022 79,787 81,870 85,489 2001-2015 Vehicle Fuel 5 5 4 5 4 5 2010-2015 Electric Power 36,977 33,927 27,504 29,252 29,353 31,279

  6. Maine Natural Gas Consumption by End Use

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

    NA NA NA NA NA NA 2001-2015 Residential 46 45 46 136 232 298 1989-2015 Commercial 409 425 415 569 779 961 1989-2015 Industrial NA NA NA NA NA NA 2001-2015 Vehicle Fuel 0 0 0 0 0 0 2010-2015 Electric Power 1,132 1,839 1,538 2,483 1,813 1,42

  7. Maryland Natural Gas Consumption by End Use

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

    12,233 10,397 9,762 12,704 16,455 18,593 2001-2015 Residential 1,624 1,557 1,518 3,820 6,137 8,243 1989-2015 Commercial 2,900 2,967 2,932 4,663 5,844 6,571 1989-2015 Industrial 1,118 906 1,131 1,242 1,266 1,302 2001-2015 Vehicle Fuel 20 20 19 20 19 20 2010-2015 Electric Power 6,571 4,947 4,162 2,959 3,188 2,45

  8. Massachusetts Natural Gas Consumption by End Use

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

    31,404 31,673 25,692 29,699 31,148 36,395 2001-2015 Residential 2,619 2,442 2,465 5,784 9,387 12,553 1989-2015 Commercial 3,912 3,873 4,066 7,399 9,210 10,044 1989-2015 Industrial 2,219 2,286 2,507 3,055 4,108 4,110 2001-2015 Vehicle Fuel 70 70 67 70 67 70 2010-2015 Electric Power 22,583 23,001 16,586 13,391 8,375 9,618

  9. Michigan Natural Gas Consumption by End Use

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

    39,804 37,730 38,018 55,280 71,432 87,181 2001-2015 Residential 5,722 6,026 6,164 16,846 29,138 36,400 1989-2015 Commercial 5,155 5,500 5,306 9,388 13,375 18,235 1989-2015 Industrial 11,349 11,437 11,698 13,570 14,366 15,847 2001-2015 Vehicle Fuel 34 34 33 34 33 34 2010-2015 Electric Power 17,544 14,732 14,817 15,441 14,519 16,664

  10. Minnesota Natural Gas Consumption by End Use

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

    22,461 22,087 22,872 27,097 35,845 NA 2001-2015 Residential 2,322 2,587 2,362 5,207 10,741 18,067 1989-2015 Commercial 2,540 2,910 2,786 5,206 8,381 12,550 1989-2015 Industrial 10,321 10,272 11,305 13,280 13,605 NA 2001-2015 Vehicle Fuel 4 4 4 4 4 4 2010-2015 Electric Power 7,274 6,314 6,416 3,400 3,113 5,725

  11. Mississippi Natural Gas Consumption by End Use

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

    45,832 43,363 NA 37,302 NA 40,203 2001-2015 Residential 466 428 512 796 NA 2,377 1989-2015 Commercial 785 889 NA 1,277 NA 1,725 1989-2015 Industrial 9,730 9,838 9,911 11,304 10,334 10,524 2001-2015 Vehicle Fuel 2 2 2 2 2 2 2010-2015 Electric Power 34,848 32,206 26,810 23,923 25,741 25,574

  12. Montana Natural Gas Consumption by End Use

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

    ,334 NA 3,662 4,787 7,811 9,316 2001-2015 Residential 381 377 494 1,042 2,634 3,260 1989-2015 Commercial 597 584 689 1,158 2,508 3,107 1989-2015 Industrial 1,438 NA 1,709 1,873 2,004 2,173 2001-2015 Vehicle Fuel 0 0 0 0 0 0 2010-2015 Electric Power 918 803 770 714 666 777

  13. Nebraska Natural Gas Consumption by End Use

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

    10,715 9,420 8,366 9,672 13,194 16,498 2001-2015 Residential 790 684 667 1,053 2,858 5,497 1989-2015 Commercial 1,223 1,010 932 1,558 2,619 3,974 1989-2015 Industrial 7,440 6,832 6,257 7,056 7,553 6,885 2001-2015 Vehicle Fuel 5 5 5 5 5 5 2010-2015 Electric Power 1,257 890 505 W 160 137

  14. Nevada Natural Gas Consumption by End Use

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

    24,653 NA NA 22,739 NA 30,673 2001-2015 Residential 1,108 1,176 1,215 1,440 4,172 7,264 1989-2015 Commercial 1,598 1,709 1,662 1,970 3,091 4,015 1989-2015 Industrial 1,165 NA NA 1,182 NA 1,200 2001-2015 Vehicle Fuel 60 60 58 60 58 60 2010-2015 Electric Power 20,722 22,904 20,109 18,088 15,282 18,13

  15. Colorado Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    8,936 19,060 19,128 22,856 40,791 49,929 2001-2015 Residential 2,725 2,476 3,036 5,976 16,679 23,229 1989-2015 Commercial 1,568 1,456 1,694 2,859 6,789 9,397 1989-2015 Industrial 4,997 4,987 4,790 5,823 7,640 8,931 2001-2015 Vehicle Fuel 27 27 26 27 26 27 2010-2015 Electric Power 9,620 10,114 9,582 8,172 9,658 8,346

  16. Florida Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    124,560 126,037 118,468 114,127 106,003 105,637 2001-2015 Residential 833 634 632 1,081 1,216 1,440 1989-2015 Commercial 4,734 4,651 4,441 5,003 5,214 5,660 1989-2015 Industrial 7,672 7,362 7,385 7,997 7,774 8,933 2001-2015 Vehicle Fuel 18 18 17 18 17 18 2010-2015 Electric Power 111,305 113,372 105,993 100,028 91,782 89,5

  17. Georgia Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    58,820 54,742 49,172 52,445 55,858 56,505 2001-2015 Residential 3,662 3,731 3,794 5,873 10,248 11,943 1989-2015 Commercial 2,164 2,274 2,417 3,159 4,695 5,185 1989-2015 Industrial 12,955 12,710 12,244 13,714 13,291 13,391 2001-2015 Vehicle Fuel 99 99 96 99 96 99 2010-2015 Electric Power 39,940 35,927 30,621 29,598 27,527 25,8

  18. Hawaii Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    243 240 233 240 228 251 2001-2015 Residential 45 43 41 44 44 47 1989-2015 Commercial 159 156 153 152 148 167 1989-2015 Industrial 38 41 37 43 36 36 2001-2015 Vehicle Fuel 1 1 1 1 1 1 2010-2015 Electric Power -- -- -- -- -- --

  19. Idaho Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    6,426 NA 6,838 NA NA 13,715 2001-2015 Residential 464 359 638 995 3,624 4,740 1989-2015 Commercial 625 583 694 1,066 2,068 2,719 1989-2015 Industrial 2,094 NA 2,564 NA NA 3,403 2001-2015 Vehicle Fuel 13 13 13 13 13 13 2010-2015 Electric Power 3,230 3,645 2,930 2,500 2,240 2,840

  20. Illinois Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    5,724 42,537 43,969 57,973 NA 107,844 2001-2015 Residential 7,939 7,946 8,021 18,056 35,960 50,744 1989-2015 Commercial 7,162 7,573 7,821 12,312 NA 24,179 1989-2015 Industrial 19,474 19,033 19,312 21,016 24,322 25,140 2001-2015 Vehicle Fuel 29 29 28 29 28 29 2010-2015 Electric Power 11,120 7,957 8,788 6,560 7,008 7,753

  1. Indiana Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    3,339 43,297 39,873 48,080 59,575 72,031 2001-2015 Residential 2,234 2,242 2,432 5,799 11,746 16,881 1989-2015 Commercial 2,324 2,749 2,784 4,720 6,409 8,381 1989-2015 Industrial 28,293 28,167 26,713 28,848 29,980 33,462 2001-2015 Vehicle Fuel 2 2 2 2 2 2 2010-2015 Electric Power 10,486 10,138 7,942 8,711 11,439 13,305

  2. Iowa Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    19,248 18,504 17,814 21,170 NA 32,191 2001-2015 Residential 1,171 1,036 1,260 2,268 5,686 8,921 1989-2015 Commercial 1,567 1,468 1,716 3,156 NA 6,246 1989-2015 Industrial 13,445 13,635 13,086 14,826 14,751 15,399 2001-2015 Vehicle Fuel 2 2 1 2 1 2 2010-2015 Electric Power 3,063 2,364 1,750 918 530 1,623

  3. Kansas Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    7,191 NA 11,628 12,195 NA 24,751 2001-2015 Residential 1,147 1,061 1,075 1,701 NA 8,698 1989-2015 Commercial 1,492 NA 1,164 1,755 2,731 4,161 1989-2015 Industrial 11,127 9,693 7,725 8,738 8,919 11,086 2001-2015 Vehicle Fuel 1 1 1 1 1 1 2010-2015 Electric Power 3,425 2,353 1,662 W W 804

  4. Kentucky Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    6,787 15,592 15,333 18,190 21,975 22,413 2001-2015 Residential 858 849 845 1,565 3,977 5,585 1989-2015 Commercial 1,139 1,152 1,154 1,709 2,925 3,570 1989-2015 Industrial 8,478 8,791 8,464 8,840 9,759 9,943 2001-2015 Vehicle Fuel 2 2 2 2 2 2 2010-2015 Electric Power 6,310 4,798 4,867 6,074 5,312 3,312

  5. Massachusetts Natural Gas Consumption by End Use

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

    432,297 449,194 416,350 421,001 418,526 1997-2014 Pipeline & Distribution Use 3,827 4,657 3,712 2,759 6,258 1997-2014 Volumes Delivered to Consumers 428,471 444,537 412,637 418,241 412,268 434,781 1997-2015 Residential 125,602 129,217 115,310 116,867 126,902 125,463 1967-2015 Commercial 72,053 81,068 73,040 99,781 105,801 105,809 1967-2015 Industrial 44,239 47,590 43,928 46,677 45,581 46,186 1997-2015 Vehicle Fuel 735 760 761 699 820 831 1988-2015 Electric Power 185,842 185,903 179,598

  6. Michigan Natural Gas Consumption by End Use

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

    46,748 776,466 790,642 814,635 850,974 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 6,626 5,857 7,428 7,248 5,948 1983-2014 Plant Fuel 1,684 1,303 1,174 1,071 1,152 1983-2014 Pipeline & Distribution Use 24,904 23,537 20,496 18,713 19,347 1997-2014 Volumes Delivered to Consumers 713,533 745,769 761,544 787,603 824,527 NA 1997-2015 Residential 304,330 318,004 276,778 334,211 354,713 319,680 1967-2015 Commercial 152,350 163,567 144,609 171,519 186,413 172,156 1967-2015 Industrial 143,351

  7. Minnesota Natural Gas Consumption by End Use

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

    422,968 420,770 422,263 467,874 473,310 1997-2014 Pipeline & Distribution Use 15,465 15,223 12,842 11,626 12,657 1997-2014 Volumes Delivered to Consumers 407,503 405,547 409,421 456,247 460,653 NA 1997-2015 Residential 122,993 125,160 109,103 139,897 146,647 119,119 1967-2015 Commercial 89,963 94,360 83,174 105,937 110,905 93,865 1967-2015 Industrial 158,457 157,776 159,947 160,732 173,556 NA 1997-2015 Vehicle Fuel 14 7 7 41 49 32 1988-2015 Electric Power 36,076 28,244 57,190 49,640 29,496

  8. Mississippi Natural Gas Consumption by End Use

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

    438,733 433,538 494,016 420,594 412,979 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 10,388 2,107 3,667 2,663 1,487 1983-2014 Plant Fuel 1,155 1,042 1,111 1,103 1,310 1983-2014 Pipeline & Distribution Use 28,117 28,828 48,497 23,667 19,787 1997-2014 Volumes Delivered to Consumers 399,073 401,561 440,741 393,161 390,396 NA 1997-2015 Residential 27,152 24,303 19,572 25,185 28,358 NA 1967-2015 Commercial 21,179 20,247 17,834 19,483 22,195 NA 1967-2015 Industrial 115,489 112,959 111,995

  9. Missouri Natural Gas Consumption by End Use

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

    280,181 272,583 255,875 276,967 296,605 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 0 0 0 0 * 1984-2014 Pipeline & Distribution Use 5,820 7,049 4,973 5,626 6,184 1997-2014 Volumes Delivered to Consumers 274,361 265,534 250,902 271,341 290,421 271,116 1997-2015 Residential 107,389 102,545 83,106 106,446 115,512 102,814 1967-2015 Commercial 61,194 62,304 54,736 64,522 72,919 65,595 1967-2015 Industrial 65,554 63,053 62,516 63,212 67,115 65,349 1997-2015 Vehicle Fuel 7 6 6 42 49 31

  10. Montana Natural Gas Consumption by End Use

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

    72,025 78,217 73,399 79,670 78,010 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 3,265 2,613 3,845 3,845 1,793 1983-2014 Plant Fuel 800 604 612 645 657 1983-2014 Pipeline & Distribution Use 7,442 6,888 6,979 6,769 4,126 1997-2014 Volumes Delivered to Consumers 60,517 68,113 61,963 68,410 71,435 NA 1997-2015 Residential 20,875 21,710 19,069 20,813 21,379 18,772 1967-2015 Commercial 20,459 22,336 19,205 20,971 21,549 NA 1967-2015 Industrial 18,478 19,386 18,319 19,352 22,084 NA 1997-2015

  11. Nebraska Natural Gas Consumption by End Use

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

    168,944 171,777 158,757 173,376 172,749 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 331 287 194 194 62 1983-2014 Plant Fuel 0 0 0 0 0 1983-2014 Pipeline & Distribution Use 7,329 9,270 7,602 6,949 7,066 1997-2014 Volumes Delivered to Consumers 161,284 162,219 150,961 166,233 165,620 149,107 1997-2015 Residential 40,132 39,717 31,286 41,229 42,147 33,830 1967-2015 Commercial 31,993 32,115 26,503 32,214 32,407 28,474 1967-2015 Industrial 85,180 86,128 85,439 88,140 86,878 82,326

  12. Nevada Natural Gas Consumption by End Use

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

    59,251 249,971 273,502 272,965 252,097 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 4 3 4 3 3 1988-2014 Pipeline & Distribution Use 2,992 4,161 6,256 4,954 4,912 1997-2014 Volumes Delivered to Consumers 256,256 245,807 267,242 268,008 247,182 NA 1997-2015 Residential 39,379 40,595 37,071 41,664 35,135 36,592 1967-2015 Commercial 29,475 30,763 28,991 31,211 29,105 29,614 1967-2015 Industrial 10,728 11,080 11,299 13,209 14,324 NA 1997-2015 Vehicle Fuel 837 591 589 597 701 682 1988-2015

  13. Ohio Natural Gas Consumption by End Use

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

    784,293 823,548 842,959 912,403 1,000,231 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 773 781 836 1,079 4,247 1983-2014 Plant Fuel 0 0 127 202 468 1983-2014 Pipeline & Distribution Use 15,816 14,258 9,559 10,035 12,661 1997-2014 Volumes Delivered to Consumers 767,704 808,509 832,437 901,087 982,855 949,865 1997-2015 Residential 283,703 286,132 250,871 297,361 320,568 289,683 1967-2015 Commercial 156,407 161,408 145,482 168,233 183,105 169,515 1967-2015 Industrial 269,287 268,034

  14. Oklahoma Natural Gas Consumption by End Use

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

    675,727 655,919 691,661 658,569 640,607 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 39,489 40,819 43,727 45,581 50,621 1983-2014 Plant Fuel 23,238 24,938 27,809 32,119 36,231 1983-2014 Pipeline & Distribution Use 30,611 30,948 32,838 41,813 45,391 1997-2014 Volumes Delivered to Consumers 582,389 559,215 587,287 539,056 508,363 544,200 1997-2015 Residential 65,429 61,387 49,052 66,108 69,050 59,675 1967-2015 Commercial 41,822 40,393 36,106 44,238 46,986 42,383 1967-2015 Industrial

  15. Oregon Natural Gas Consumption by End Use

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

    239,325 199,419 215,830 240,418 220,076 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 31 39 44 44 25 1983-2014 Pipeline & Distribution Use 6,394 5,044 4,554 4,098 3,686 1997-2014 Volumes Delivered to Consumers 232,900 194,336 211,232 236,276 216,365 233,523 1997-2015 Residential 40,821 46,604 43,333 46,254 41,185 37,930 1967-2015 Commercial 27,246 30,359 28,805 30,566 28,377 26,502 1967-2015 Industrial 55,822 56,977 57,506 57,372 56,522 54,931 1997-2015 Vehicle Fuel 183 144 144 154 181

  16. Pennsylvania Natural Gas Consumption by End Use

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

    879,365 965,742 1,037,979 1,121,696 1,203,418 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 19,805 46,784 79,783 115,630 112,847 1983-2014 Plant Fuel 881 963 2,529 9,200 11,602 1983-2014 Pipeline & Distribution Use 47,470 51,220 37,176 37,825 36,323 1997-2014 Volumes Delivered to Consumers 811,209 866,775 918,490 959,041 1,042,647 1,078,193 1997-2015 Residential 223,642 219,446 197,313 231,861 254,816 242,098 1967-2015 Commercial 141,699 141,173 126,936 149,114 159,636 156,887

  17. Tennessee Natural Gas Consumption by End Use

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

    257,443 264,231 277,127 279,441 303,996 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 214 231 335 335 142 1983-2014 Plant Fuel 148 145 150 142 128 1983-2014 Pipeline & Distribution Use 10,081 11,655 9,880 6,660 5,913 1997-2014 Volumes Delivered to Consumers 247,000 252,200 266,762 272,304 297,814 306,194 1997-2015 Residential 74,316 67,190 53,810 71,241 78,385 67,951 1967-2015 Commercial 56,194 52,156 44,928 53,888 57,427 53,995 1967-2015 Industrial 94,320 106,522 105,046 110,475

  18. Texas Natural Gas Consumption by End Use

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

    3,574,398 3,693,905 3,850,331 4,021,851 4,088,445 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 157,751 147,268 163,325 198,208 213,481 1983-2014 Plant Fuel 151,818 155,358 171,359 178,682 184,723 1983-2014 Pipeline & Distribution Use 79,817 85,549 138,429 294,316 274,451 1997-2014 Volumes Delivered to Consumers 3,185,011 3,305,730 3,377,217 3,350,645 3,415,789 3,589,916 1997-2015 Residential 226,445 199,958 169,980 207,148 234,520 199,288 1967-2015 Commercial 188,796 184,475 161,273

  19. Utah Natural Gas Consumption by End Use

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

    219,213 222,227 223,039 247,285 242,457 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 22,022 23,209 28,165 28,165 25,336 1983-2014 Plant Fuel 1,616 3,063 3,031 5,996 4,782 1983-2014 Pipeline & Distribution Use 10,347 11,374 12,902 13,441 14,061 1997-2014 Volumes Delivered to Consumers 185,228 184,581 178,941 199,684 198,278 187,452 1997-2015 Residential 66,087 70,076 59,801 70,491 62,458 58,177 1967-2015 Commercial 38,461 40,444 35,363 41,398 38,156 35,552 1967-2015 Industrial 32,079

  20. Vermont Natural Gas Consumption by End Use

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

    8,443 8,611 8,191 9,602 10,678 1997-2014 Pipeline & Distribution Use 16 53 114 89 124 1997-2014 Volumes Delivered to Consumers 8,428 8,558 8,077 9,512 10,554 NA 1997-2015 Residential 3,078 3,214 3,012 3,415 3,826 3,754 1980-2015 Commercial 2,384 2,479 2,314 4,748 4,830 NA 1980-2015 Industrial 2,909 2,812 2,711 1,303 1,858 NA 1997-2015 Vehicle Fuel 1 3 3 3 3 3 1997-2015 Electric Power 55 49 38 44 36 19

  1. Virginia Natural Gas Consumption by End Use

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

    375,421 373,444 410,106 418,506 419,615 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 6,121 7,206 8,408 8,408 7,252 1983-2014 Pipeline & Distribution Use 10,091 13,957 9,443 8,475 7,424 1997-2014 Volumes Delivered to Consumers 359,208 352,281 392,255 401,623 404,939 NA 1997-2015 Residential 88,157 79,301 70,438 85,702 92,817 83,512 1967-2015 Commercial 68,911 64,282 60,217 68,126 72,164 67,597 1967-2015 Industrial 62,243 66,147 71,486 75,998 81,040 NA 1997-2015 Vehicle Fuel 142 267 266

  2. Washington Natural Gas Consumption by End Use

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

    285,726 264,589 264,540 318,292 307,021 1997-2014 Lease and Plant Fuel 1967-1992 Pipeline & Distribution Use 7,587 6,644 9,184 10,144 8,933 1997-2014 Volumes Delivered to Consumers 278,139 257,945 255,356 308,148 298,088 NA 1997-2015 Residential 75,554 85,393 79,892 83,365 78,750 71,818 1967-2015 Commercial 51,335 56,487 53,420 55,805 54,457 49,906 1967-2015 Industrial 71,280 76,289 78,196 80,889 79,439 NA 1997-2015 Vehicle Fuel 436 510 512 418 491 524 1988-2015 Electric Power 79,535 39,265

  3. Alabama Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    56,930 54,897 50,117 49,292 50,501 54,716 2001-2015 Residential 702 694 671 934 2,031 3,411 1989-2015 Commercial 1,088 1,131 1,174 1,513 2,317 2,366 1989-2015 Industrial 15,749 15,311 14,897 15,292 15,100 15,670 2001-2015 Vehicle Fuel 19 19 18 19 18 19 2010-2015 Electric Power 39,373 37,742 33,356 31,534 31,034 33,249

  4. Alaska Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    3,931 3,785 4,473 5,317 6,929 7,958 2001-2015 Residential 493 527 1,033 1,422 2,306 2,670 1989-2015 Commercial 713 766 1,253 1,451 2,103 2,558 1989-2015 Industrial 359 375 323 348 354 393 2001-2015 Vehicle Fuel 1 1 1 1 1 1 2010-2015 Electric Power 2,365 2,116 1,863 2,096 2,164 2,336

  5. Arizona Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    38,296 42,499 35,461 29,557 25,804 30,415 2001-2015 Residential 1,056 971 1,072 1,334 3,107 6,609 1989-2015 Commercial 1,758 1,654 1,714 1,918 3,014 4,130 1989-2015 Industrial 1,468 1,457 1,417 1,572 1,844 1,988 2001-2015 Vehicle Fuel 173 173 167 173 167 173 2010-2015 Electric Power 33,842 38,244 31,091 24,561 17,672 17,515

  6. Arkansas Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    22,018 21,854 17,958 14,702 18,552 22,561 2001-2015 Residential 557 514 546 731 2,155 3,933 1989-2015 Commercial 2,308 2,444 2,571 3,048 3,863 4,724 1989-2015 Industrial 6,345 6,370 6,286 6,790 7,098 7,148 2001-2015 Vehicle Fuel 3 3 3 3 3 3 2010-2015 Electric Power 12,805 12,523 8,552 4,130 5,434 6,754

  7. California Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    92,918 199,015 189,292 186,757 195,837 235,282 2001-2015 Residential 19,107 17,560 17,188 19,412 44,802 73,730 1989-2015 Commercial 15,962 16,537 15,250 16,321 26,389 29,820 1989-2015 Industrial 70,121 71,776 66,196 64,699 63,799 67,213 2001-2015 Vehicle Fuel 1,408 1,408 1,363 1,408 1,363 1,408 2010-2015 Electric Power 86,319 91,733 89,295 84,917 59,484 63,111

  8. Tennessee Natural Gas Consumption by End Use

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

    19,267 17,907 18,246 18,807 24,268 29,015 2001-2015 Residential 1,032 1,028 1,163 1,982 4,847 7,765 1989-2015 Commercial 2,060 2,125 2,259 3,080 4,707 5,273 1989-2015 Industrial 8,573 8,743 8,683 9,162 9,248 9,813 2001-2015 Vehicle Fuel 9 9 8 9 8 9 2010-2015 Electric Power 7,594 6,002 6,133 4,574 5,458 6,1

  9. Texas Natural Gas Consumption by End Use

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

    329,042 332,621 291,178 276,726 267,183 307,656 2001-2015 Residential 6,189 4,587 5,116 5,934 9,793 24,772 1989-2015 Commercial 10,630 9,295 9,558 10,313 12,553 17,584 1989-2015 Industrial 130,522 132,785 125,076 128,958 134,340 141,897 2001-2015 Vehicle Fuel 300 300 290 300 290 300 2010-2015 Electric Power 181,401 185,654 151,139 131,222 110,207 123,103

  10. Ohio Natural Gas Consumption by End Use

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

    50,025 48,583 46,019 55,863 74,007 88,545 2001-2015 Residential 5,084 4,792 4,741 12,359 22,384 31,154 1989-2015 Commercial 4,753 4,790 4,535 9,220 12,881 16,455 1989-2015 Industrial 19,742 19,354 18,786 20,416 22,796 23,708 2001-2015 Vehicle Fuel 30 30 29 30 29 30 2010-2015 Electric Power 20,417 19,618 17,928 13,838 15,918 17,199

  11. Oklahoma Natural Gas Consumption by End Use

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

    45,577 43,618 38,010 34,185 42,019 50,354 2001-2015 Residential 1,271 1,095 1,169 1,308 2,614 6,999 1989-2015 Commercial 1,553 1,502 1,509 1,638 2,339 4,093 1989-2015 Industrial 12,322 13,036 15,155 14,917 16,551 16,204 2001-2015 Vehicle Fuel 34 34 33 34 33 34 2010-2015 Electric Power 30,396 27,950 20,143 16,289 20,482 23,024

  12. Oregon Natural Gas Consumption by End Use

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

    17,872 17,582 18,287 18,493 25,529 28,283 2001-2015 Residential 860 841 1,217 1,804 5,854 7,090 1989-2015 Commercial 968 948 1,217 1,552 3,444 4,307 1989-2015 Industrial 4,016 4,163 4,085 4,375 4,834 5,261 2001-2015 Vehicle Fuel 15 15 15 15 15 15 2010-2015 Electric Power 12,013 11,616 11,754 10,746 11,382 11,609

  13. Pennsylvania Natural Gas Consumption by End Use

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

    74,666 73,764 67,203 78,980 87,069 96,515 2001-2015 Residential 4,230 4,143 4,892 11,789 18,582 24,976 1989-2015 Commercial 4,493 4,751 5,319 10,093 13,175 15,188 1989-2015 Industrial 17,977 17,360 17,224 18,923 19,211 20,699 2001-2015 Vehicle Fuel 31 31 30 31 30 31 2010-2015 Electric Power 47,934 47,480 39,738 38,145 36,071 35,62

  14. Wyoming Natural Gas Consumption by End Use

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

    4,559 4,334 4,513 4,917 7,317 9,112 2001-2015 Residential 250 205 313 415 1,468 2,262 1989-2015 Commercial 401 283 478 537 1,585 2,273 1989-2015 Industrial 3,906 3,844 3,720 3,963 4,262 4,575 2001-2015 Vehicle Fuel 2 2 2 2 2 2 2010-2015 Electric Power W W W W W W

  15. California Natural Gas Consumption by End Use

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

    2,273,128 2,153,186 2,403,494 2,415,571 2,344,977 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 64,931 44,379 51,154 49,846 54,288 1983-2014 Plant Fuel 2,370 2,253 2,417 2,834 2,361 1983-2014 Pipeline & Distribution Use 9,741 10,276 12,906 10,471 22,897 1997-2014 Volumes Delivered to Consumers 2,196,086 2,096,279 2,337,017 2,352,421 2,265,431 2,257,216 1997-2015 Residential 494,890 512,565 477,931 481,773 397,489 404,869 1967-2015 Commercial 247,997 246,141 253,148 254,845 237,675

  16. Colorado Natural Gas Consumption by End Use

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

    501,350 466,680 443,750 467,798 480,747 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 66,083 78,800 76,462 71,105 74,402 1983-2014 Plant Fuel 25,090 28,265 29,383 25,806 30,873 1983-2014 Pipeline & Distribution Use 14,095 13,952 10,797 9,107 8,451 1997-2014 Volumes Delivered to Consumers 396,083 345,663 327,108 361,779 367,021 NA 1997-2015 Residential 131,224 130,116 115,695 134,936 132,106 125,433 1967-2015 Commercial 57,658 55,843 51,795 58,787 58,008 NA 1967-2015 Industrial 114,295

  17. Connecticut Natural Gas Consumption by End Use

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

    199,426 230,036 229,156 234,475 235,205 1997-2014 Pipeline & Distribution Use 6,739 6,302 4,747 4,381 4,698 1997-2014 Volumes Delivered to Consumers 192,687 223,734 224,409 230,094 230,507 250,527 1997-2015 Residential 42,729 44,719 41,050 46,802 51,193 51,857 1967-2015 Commercial 40,656 44,832 42,346 46,418 51,221 53,378 1967-2015 Industrial 24,117 26,258 26,932 29,965 28,371 25,943 1997-2015 Vehicle Fuel 41 27 27 46 54 44 1988-2015 Electric Power 85,144 107,897 114,054 106,863 99,668

  18. Delaware Natural Gas Consumption by End Use

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

    54,825 79,715 101,676 95,978 100,776 1997-2014 Lease and Plant Fuel 1967-1992 Pipeline & Distribution Use 140 464 1,045 970 1,040 1997-2014 Volumes Delivered to Consumers 54,685 79,251 100,630 95,008 99,736 99,543 1997-2015 Residential 10,126 10,030 8,564 10,197 11,316 10,501 1967-2015 Commercial 12,193 10,478 10,034 11,170 11,882 11,189 1967-2015 Industrial 7,983 19,760 28,737 32,154 31,004 33,127 1997-2015 Vehicle Fuel 1 1 1 1 1 1 1988-2015 Electric Power 24,383 38,984 53,295 41,487 45,534

  19. Florida Natural Gas Consumption by End Use

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

    1,158,452 1,217,689 1,328,463 1,225,676 1,231,957 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 4,512 4,896 6,080 5,609 6,551 1983-2014 Plant Fuel 0 0 0 0 272 1983-2014 Pipeline & Distribution Use 22,798 13,546 16,359 12,494 3,468 1997-2014 Volumes Delivered to Consumers 1,131,142 1,199,247 1,306,024 1,207,573 1,221,666 NA 1997-2015 Residential 18,744 16,400 14,366 15,321 16,652 14,777 1967-2015 Commercial 54,065 53,532 54,659 59,971 62,646 NA 1967-2015 Industrial 76,522 85,444 98,144

  20. Georgia Natural Gas Consumption by End Use

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

    530,030 522,897 615,771 625,283 652,230 1997-2014 Pipeline & Distribution Use 8,473 10,432 10,509 7,973 6,977 1997-2014 Volumes Delivered to Consumers 521,557 512,466 605,262 617,310 645,253 683,796 1997-2015 Residential 138,671 113,335 97,664 121,629 134,438 117,523 1967-2015 Commercial 60,153 56,602 51,918 57,195 59,039 53,581 1967-2015 Industrial 146,737 144,940 146,481 157,982 160,821 157,407 1997-2015 Vehicle Fuel 915 1,097 1,104 998 1,171 1,194 1988-2015 Electric Power 175,082 196,492

  1. Hawaii Natural Gas Consumption by End Use

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

    2,627 2,619 2,689 2,855 2,928 1997-2014 Pipeline & Distribution Use 2 2 3 1 1 2004-2014 Volumes Delivered to Consumers 2,625 2,616 2,687 2,853 2,927 2,929 1997-2015 Residential 509 486 481 582 583 572 1980-2015 Commercial 1,777 1,768 1,850 1,873 1,931 1,908 1980-2015 Industrial 339 362 355 388 401 442 1997-2015 Vehicle Fuel 0 0 0 10 12 7 1997-2015 Electric Power -- -- -- -- -- --

  2. Idaho Natural Gas Consumption by End Use

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

    83,326 82,544 89,004 104,783 91,514 1997-2014 Lease and Plant Fuel 1967-1992 Pipeline & Distribution Use 7,679 5,201 5,730 5,940 3,867 1997-2014 Volumes Delivered to Consumers 75,647 77,343 83,274 98,843 87,647 NA 1997-2015 Residential 23,975 26,666 23,924 27,370 24,616 22,963 1967-2015 Commercial 15,033 16,855 15,838 18,485 16,963 16,171 1967-2015 Industrial 24,195 25,392 29,781 27,996 28,046 NA 1997-2015 Vehicle Fuel 69 131 132 133 156 152 1988-2015 Electric Power 12,375 8,299 13,599

  3. Illinois Natural Gas Consumption by End Use

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

    966,678 986,867 940,367 1,056,826 1,092,999 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 50 101 122 122 70 1983-2014 Plant Fuel 4,559 4,917 4,896 4,917 288 1983-2014 Pipeline & Distribution Use 19,864 21,831 24,738 26,936 30,263 1997-2014 Volumes Delivered to Consumers 942,205 960,018 910,611 1,024,851 1,062,377 NA 1997-2015 Residential 416,570 418,143 360,891 452,602 479,465 399,446 1967-2015 Commercial 198,036 215,605 188,099 230,820 246,273 NA 1967-2015 Industrial 281,406 278,498

  4. Indiana Natural Gas Consumption by End Use

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

    573,866 630,669 649,921 672,751 710,838 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 283 433 506 506 177 1983-2014 Pipeline & Distribution Use 8,679 10,259 7,206 7,428 7,025 1997-2014 Volumes Delivered to Consumers 564,904 619,977 642,209 664,817 703,637 712,946 1997-2015 Residential 138,415 132,094 115,522 144,496 156,639 133,876 1967-2015 Commercial 75,883 75,995 66,663 82,596 90,915 78,491 1967-2015 Industrial 289,314 326,573 344,678 356,690 375,647 373,191 1997-2015 Vehicle Fuel

  5. Iowa Natural Gas Consumption by End Use

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

    311,075 306,909 295,183 326,140 330,433 1997-2014 Pipeline & Distribution Use 11,042 10,811 10,145 11,398 12,650 1997-2014 Volumes Delivered to Consumers 300,033 296,098 285,038 314,742 317,784 NA 1997-2015 Residential 68,376 67,097 55,855 72,519 76,574 62,032 1967-2015 Commercial 51,674 51,875 43,767 56,592 57,438 NA 1967-2015 Industrial 167,423 167,233 168,907 173,545 172,718 174,199 1997-2015 Vehicle Fuel 0 0 0 15 18 11 1988-2015 Electric Power 12,560 9,893 16,509 13,702 11,035 17,518

  6. Kansas Natural Gas Consumption by End Use

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

    75,184 279,724 262,316 283,177 285,969 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 13,461 12,781 17,017 17,110 14,851 1983-2014 Plant Fuel 2,102 2,246 2,268 2,189 1,983 1983-2014 Pipeline & Distribution Use 24,305 23,225 19,842 22,586 22,588 1997-2014 Volumes Delivered to Consumers 235,316 241,473 223,188 241,292 246,547 NA 1997-2015 Residential 67,117 65,491 50,489 68,036 71,126 NA 1967-2015 Commercial 31,799 32,117 25,452 33,198 36,512 NA 1967-2015 Industrial 108,484 113,356

  7. Kentucky Natural Gas Consumption by End Use

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

    32,099 223,034 225,924 229,983 254,244 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 5,626 5,925 6,095 6,095 4,388 1983-2014 Plant Fuel 772 278 641 280 278 1983-2014 Pipeline & Distribution Use 13,708 12,451 8,604 7,157 8,426 1997-2014 Volumes Delivered to Consumers 211,993 204,380 210,584 216,451 241,151 249,968 1997-2015 Residential 54,391 50,696 43,065 54,208 57,589 47,712 1967-2015 Commercial 36,818 34,592 30,771 37,422 40,033 34,308 1967-2015 Industrial 101,497 103,517 105,554

  8. Louisiana Natural Gas Consumption by End Use

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

    1,354,641 1,420,264 1,482,343 1,396,261 1,460,031 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 59,336 80,983 54,463 57,549 58,034 1983-2014 Plant Fuel 40,814 42,633 42,123 34,179 30,527 1983-2014 Pipeline & Distribution Use 46,892 51,897 49,235 36,737 45,762 1997-2014 Volumes Delivered to Consumers 1,207,599 1,244,752 1,336,521 1,267,795 1,325,708 1,361,733 1997-2015 Residential 45,516 39,412 31,834 38,820 44,392 36,580 1967-2015 Commercial 27,009 25,925 26,294 28,875 31,209 30,656

  9. Maine Natural Gas Consumption by End Use

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

    7,575 71,690 68,266 64,091 60,661 1997-2014 Pipeline & Distribution Use 1,753 2,399 762 844 1,300 1997-2014 Volumes Delivered to Consumers 75,821 69,291 67,504 63,247 59,362 NA 1997-2015 Residential 1,234 1,409 1,487 1,889 2,357 2,605 1967-2015 Commercial 5,830 6,593 7,313 8,146 9,030 9,795 1967-2015 Industrial 28,365 27,734 30,248 32,308 24,121 NA 1997-2015 Vehicle Fuel 1 1 1 * 1 1 1997-2015 Electric Power 40,392 33,555 28,456 20,904 23,853 17,447

  10. Maryland Natural Gas Consumption by End Use

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

    212,020 193,986 208,946 197,356 207,527 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 0 0 0 0 1 1983-2014 Pipeline & Distribution Use 6,332 6,065 7,397 4,125 6,327 1997-2014 Volumes Delivered to Consumers 205,688 187,921 201,550 193,232 201,199 205,407 1997-2015 Residential 83,830 77,838 70,346 83,341 90,542 81,592 1967-2015 Commercial 67,555 67,505 64,146 71,145 74,843 69,307 1967-2015 Industrial 23,371 21,220 17,626 13,989 14,734 14,635 1997-2015 Vehicle Fuel 203 222 221 201 236 240

  11. Utah Natural Gas Consumption by End Use

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

    11,359 11,750 10,440 10,855 20,739 27,782 2001-2015 Residential 1,623 1,545 1,320 2,002 8,290 12,265 1989-2015 Commercial 1,168 1,157 1,170 1,474 4,732 6,881 1989-2015 Industrial 2,777 2,788 2,757 2,969 3,120 3,612 2001-2015 Vehicle Fuel 22 22 22 22 22 22 2010-2015 Electric Power 5,768 6,238 5,171 4,387 4,575 5,002

  12. Vermont Natural Gas Consumption by End Use

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

    NA 544 566 NA 1,024 1,168 2001-2015 Residential 87 73 79 164 288 393 1989-2015 Commercial NA 318 336 522 557 586 1989-2015 Industrial NA 153 150 NA 178 188 2001-2015 Vehicle Fuel 0 0 0 0 0 0 2010-2015 Electric Power 0 0 1 0 1

  13. Virginia Natural Gas Consumption by End Use

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

    40,769 37,648 33,817 27,516 36,489 44,149 2001-2015 Residential 1,491 1,442 1,913 3,395 6,309 7,966 1989-2015 Commercial 2,656 2,587 3,658 4,647 6,019 6,065 1989-2015 Industrial 7,530 7,435 6,116 7,701 7,582 7,259 2001-2015 Vehicle Fuel 21 21 20 21 20 21 2010-2015 Electric Power 29,071 26,163 22,109 11,752 16,558 22,839

  14. Connecticut Natural Gas Consumption by End Use

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

    27,870 20,353 15,426 14,745 16,786 17,440 2001-2015 Residential 8,998 4,902 2,172 1,368 1,120 997 1989-2015 Commercial 7,504 4,556 2,676 2,295 2,379 2,512 1989-2015 Industrial...

  15. ,"Texas Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcustxm.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  16. ,"Maine Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcusmem.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  17. ,"Indiana Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcusinm.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  18. ,"Ohio Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcusohm.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  19. ,"Michigan Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcusmim.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  20. ,"Massachusetts Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcusmam.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  1. ,"Vermont Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcusvtm.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  2. ,"Alaska Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcusakm.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  3. ,"Washington Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcuswam.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  4. ,"Arkansas Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcusarm.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  5. ,"Colorado Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcuscom.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  6. ,"Virginia Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcusvam.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  7. ,"California Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcuscam.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  8. ,"Wyoming Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcuswym.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  9. ,"Iowa Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcusiam.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  10. ,"Oregon Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcusorm.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  11. ,"Florida Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcusflm.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  12. ,"Minnesota Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcusmnm.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  13. ,"Illinois Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcusilm.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  14. ,"Hawaii Natural Gas Consumption by End Use"

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

    Date:","1292016" ,"Next Release Date:","2292016" ,"Excel File Name:","ngconssumdcushim.xls" ,"Available from Web Page:","http:www.eia.govdnavng...

  15. Wisconsin Natural Gas Consumption by End Use

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

    372,898 393,734 402,656 442,544 462,627 1997-2014 Pipeline & Distribution Use 2,973 2,606 1,780 2,803 3,629 1997-2014 Volumes Delivered to Consumers 369,924 391,128 400,876 439,741 458,999 454,450 1997-2015 Residential 123,618 129,445 112,554 142,985 150,409 126,685 1967-2015 Commercial 82,204 87,040 76,949 99,434 107,003 90,195 1967-2015 Industrial 121,408 126,856 124,338 136,034 141,661 136,264 1997-2015 Vehicle Fuel 56 60 59 100 117 96 1988-2015 Electric Power 42,639 47,727 86,975 61,188

  16. Wyoming Natural Gas Consumption by End Use

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

    50,106 156,455 153,333 149,820 135,678 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 34,459 39,114 33,826 32,004 21,811 1983-2014 Plant Fuel 27,104 28,582 29,157 27,935 25,782 1983-2014 Pipeline & Distribution Use 20,807 17,898 16,660 15,283 14,990 1997-2014 Volumes Delivered to Consumers 67,736 70,862 73,690 74,597 73,096 72,765 1997-2015 Residential 12,915 13,283 11,502 13,640 13,269 11,942 1967-2015 Commercial 11,153 11,680 10,482 12,013 12,188 12,498 1967-2015 Industrial 43,059

  17. ,"Tennessee Natural Gas Consumption by End Use"

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

    ...575,20337,5751,4289,10219,,77 37605,31833,12804,8138,10610,,281 37636,37778,15336,9595,11144,,1704 37667,37692,15713,10236,11487,,256 37695,27915,10227,7187,10262,,239 ...

  18. Missouri Natural Gas Consumption by End Use

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

    1,873 1,770 3,351 8,236 1989-2015 Commercial 1,960 2,021 2,299 2,254 3,585 5,631 1989-2015 Industrial 4,605 4,716 4,376 4,527 4,939 5,585 2001-2015 Vehicle Fuel 4 4 4 4 4 4...

  19. Washington Natural Gas Consumption by End Use

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

    1,649 2,519 4,019 9,599 1989-2015 Commercial 2,287 1,996 1,902 2,709 3,462 5,744 1989-2015 Industrial 5,770 5,477 5,625 5,921 6,680 NA 2001-2015 Vehicle Fuel 38 42 42 40 42 40...

  20. Wisconsin Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    22,344 25,107 23,388 23,582 29,271 38,844 2001-2015 Residential 2,478 2,475 2,308 2,498 6,080 11,070 1989-2015 Commercial 2,842 2,782 2,964 2,867 4,985 7,776 1989-2015 Industrial...

  1. Delaware Natural Gas Consumption by End Use

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

    8,917 8,330 7,939 2001-2015 Residential 703 270 181 163 166 157 1989-2015 Commercial 735 403 410 375 409 432 1989-2015 Industrial 3,037 2,819 2,561 2,669 2,636 2,448 2001-2015...

  2. The Global Energy Challenge

    ScienceCinema (OSTI)

    Crabtree, George

    2010-01-08

    The expected doubling of global energy demand by 2050 challenges our traditional patterns of energy production, distribution and use.   The continued use of fossil fuels raises concerns about supply, security, environment and climate.  New routes are needed for the efficient conversion of energy from chemical fuel, sunlight, and heat to electricity or hydrogen as an energy carrier and finally to end uses like transportation, lighting, and heating. Opportunities for efficient new energy conversion routes based on nanoscale materials will be presented, with emphasis on the sustainable energy technologies they enable.

  3. Healthcare Energy: Spotlight on Medical Equipment | Department of Energy

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

    Medical Equipment Healthcare Energy: Spotlight on Medical Equipment The Building Technologies Office conducted a healthcare energy end-use monitoring project in partnership with two hospitals. Additional plug load data from medical office buildings were provided by Mazzetti, Inc. See below for a few highlights from monitoring large medical imaging equipment and medical office building plug loads. Graphic showing the average weekday energy use of a CT machine. Graph showing average weekday energy

  4. Motor Energy Savings Potential Report | Department of Energy

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

    Motor Energy Savings Potential Report Motor Energy Savings Potential Report This report describes the current state of motor technology and estimates opportunities for energy savings through application of more advanced technologies in a variety of residential and commercial end uses. The objectives of this report were to characterize the state and type of motor technologies used in residential and commercial appliances and equipment and to identify opportunities to reduce the energy consumption

  5. Impacts of Temperature Variation on Energy Demand in Buildings (released in AEO2005)

    Reports and Publications (EIA)

    2005-01-01

    In the residential and commercial sectors, heating and cooling account for more than 40% of end-use energy demand. As a result, energy consumption in those sectors can vary significantly from year to year, depending on yearly average temperatures.

  6. LARGE INDUSTRIAL FACILITIES BY STATE | Department of Energy

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

    Number of Large Energy User Manufacturing Facilities by Sector and State (with Industrial Energy Consumption by State and Manufacturing Energy Consumption by Sector) More Documents & Publications U.S. Manufacturing Energy Use and Greenhouse Gas Emissions Analysis Energy Use Loss and Opportunities Analysis: U.S. Manufacturing & Mining End-Use Sector Flowchart

  7. U.S. Energy Information Administration | Annual Coal Report 2013

    Gasoline and Diesel Fuel Update (EIA)

    U.S. Coal Consumption by End Use Sector, Census Division, and State, 2013 and 2012 (thousand short tons) U.S. Energy Information Administration | Annual Coal Report 2013 Table 26. U.S. Coal Consumption by End Use Sector, Census Division, and State, 2013 and 2012 (thousand short tons) U.S. Energy Information Administration | Annual Coal Report 2013 2013 2012 Total Census Division and State Electric Power 1 Other Industrial Coke Commercial and Institutional Electric Power 1 Other Industrial Coke

  8. U.S. Energy Information Administration | Annual Coal Report 2013

    Gasoline and Diesel Fuel Update (EIA)

    Average Price of Coal Delivered to End Use Sector by Census Division and State, 2013 and 2012 (dollars per short ton) U.S. Energy Information Administration | Annual Coal Report 2013 Table 34. Average Price of Coal Delivered to End Use Sector by Census Division and State, 2013 and 2012 (dollars per short ton) U.S. Energy Information Administration | Annual Coal Report 2013 2013 2012 Annual Percent Change Census Division and State Electric Power 1 Other Industrial Coke Commercial and

  9. A National Perspective on Energy and Industry

    Gasoline and Diesel Fuel Update (EIA)

    Using EIA's Energy Consumption Surveys to Analyze Energy Programs and Policies Steven Nadel American Council for an Energy-Efficient Economy EIA 2008 Energy Conference, April 7-8, 2008 The American Council for an Energy Efficient Economy (ACEEE) * Non-profit (501c (3)) dedicated to advancing energy efficiency through research and dissemination. * ~25 staffers in Washington DC, Delaware, Michigan and Wisconsin * Focus on End-Use Efficiency in Industry, Buildings, Utilities, Transportation, &

  10. Trends in Renewable Energy Consumption and Electricity

    Reports and Publications (EIA)

    2012-01-01

    Presents a summary of the nation’s renewable energy consumption in 2010 along with detailed historical data on renewable energy consumption by energy source and end-use sector. Data presented also includes renewable energy consumption for electricity generation and for non-electric use by energy source, and net summer capacity and net generation by energy source and state. The report covers the period from 2006 through 2010.

  11. Energy

    Office of Legacy Management (LM)

    ..) ".. _,; ,' . ' , ,; Depar?.me.nt ,of.' Energy Washington; DC 20585 : . ' , - $$ o"\ ' ~' ,' DEC ?;$ ;y4,,, ~ ' .~ The Honorable John Kalwitz , 200 E. Wells Street Milwaukee, W~isconsin 53202, . . i :. Dear,Mayor 'Kalwitz: " . " Secretary of Energy Hazel' O'Leary has announceha new,approach 'to,openness in " the Department of Ene~rgy (DOE) and its communications with'the public. In -. support of~this initiative, we areipleased to forward the enclosed information

  12. Issues in International Energy Consumption Analysis: Canadian Energy Demand

    Reports and Publications (EIA)

    2015-01-01

    The residential sector is one of the main end-use sectors in Canada accounting for 16.7% of total end-use site energy consumption in 2009 (computed from NRCan 2012. pp, 4-5). In this year, the residential sector accounted for 54.5% of buildings total site energy consumption. Between 1990 and 2009, Canadian household energy consumption grew by less than 11%. Nonetheless, households contributed to 14.6% of total energy-related greenhouse gas emissions in Canada in 2009 (computed from NRCan 2012). This is the U.S. Energy Information Administration’s second study to help provide a better understanding of the factors impacting residential energy consumption and intensity in North America (mainly the United States and Canada) by using similar methodology for analyses in both countries.

  13. Healthcare Energy: Spotlight on Fans and Pumps | Department of Energy

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

    Fans and Pumps Healthcare Energy: Spotlight on Fans and Pumps Chilled water pumps at a central plant. Image by Warren Gretz, NREL/06196 Chilled water pumps at a central plant. Image by Warren Gretz, NREL/06196 The Building Technologies Office conducted a healthcare energy end-use monitoring project in partnership with two hospitals. See below for a few highlights from monitoring fan and pump energy use. Fans At the Massachusetts General Hospital (MGH) Gray Building, supply, return/exhaust, and

  14. Energy

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

    M onthly Energy Re< view Ila A a m 0 II 8 IIIW *g U In this issue: New data on nuclear electricity in Eastern Europe (Table 10.4) 9'Ij a - Ordering Information This publication...

  15. Manufacturing Energy and Carbon Footprints (2006 MECS)

    Broader source: Energy.gov [DOE]

    Energy and Carbon Footprints provide a mapping of energy from supply to end use in manufacturing. They show us where energy is used and lost—and where greenhouse gases (GHGs) are emitted. Footprints are available below for 15 manufacturing sectors (representing 94% of all manufacturing energy use) and for U.S. manufacturing as a whole. Analysis of these footprints is also available in the U.S. Manufacturing Energy Use and Greenhouse Gas Emissions Analysis report.

  16. State energy data report 1994: Consumption estimates

    SciTech Connect (OSTI)

    1996-10-01

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

  17. Petroleum: An energy profile, 1999

    SciTech Connect (OSTI)

    1999-07-01

    This report prepared by the Energy Information Administration covers the following topics: petroleum production and end-use sectors; resources and reserves; exploration and production; LPG sources and processing; motor gasoline octane enhancement; constructing pipelines; the strategic petroleum reserve; imports and exports; marketing; district descriptions and maps; and refinery processes and facilities. 33 figs., 7 tabs.

  18. Energy Intensity Indicators: Indicators for Major Sectors

    Broader source: Energy.gov [DOE]

    This system of energy intensity indicators for total energy covers the economy as a whole and each of the major end-use sectors—transportation, industry, commercial, and residential, as well as the electric power sector. These sectors are shown in Figure 1.

  19. Assessing Internet energy intensity: A review of methods and results

    SciTech Connect (OSTI)

    Coroama, Vlad C.; Hilty, Lorenz M.; Empa, Swiss Federal Laboratories for Materials Science and Technology, Lerchenfeldstr. 5, 9014 St. Gallen; Centre for Sustainable Communications, KTH Royal Institute of Technology, Lindstedtsvägen 5, 100 44 Stockholm

    2014-02-15

    Assessing the average energy intensity of Internet transmissions is a complex task that has been a controversial subject of discussion. Estimates published over the last decade diverge by up to four orders of magnitude — from 0.0064 kilowatt-hours per gigabyte (kWh/GB) to 136 kWh/GB. This article presents a review of the methodological approaches used so far in such assessments: i) top–down analyses based on estimates of the overall Internet energy consumption and the overall Internet traffic, whereby average energy intensity is calculated by dividing energy by traffic for a given period of time, ii) model-based approaches that model all components needed to sustain an amount of Internet traffic, and iii) bottom–up approaches based on case studies and generalization of the results. Our analysis of the existing studies shows that the large spread of results is mainly caused by two factors: a) the year of reference of the analysis, which has significant influence due to efficiency gains in electronic equipment, and b) whether end devices such as personal computers or servers are included within the system boundary or not. For an overall assessment of the energy needed to perform a specific task involving the Internet, it is necessary to account for the types of end devices needed for the task, while the energy needed for data transmission can be added based on a generic estimate of Internet energy intensity for a given year. Separating the Internet as a data transmission system from the end devices leads to more accurate models and to results that are more informative for decision makers, because end devices and the networking equipment of the Internet usually belong to different spheres of control. -- Highlights: • Assessments of the energy intensity of the Internet differ by a factor of 20,000. • We review top–down, model-based, and bottom–up estimates from literature. • Main divergence factors are the year studied and the inclusion of end devices. • We argue against extending the Internet system boundary beyond data transmission. • Decision-makers need data that differentiates between end devices and transmission.

  20. Hawaii energy strategy project 2: Fossil energy review. Task 2: Fossil energy in Hawaii

    SciTech Connect (OSTI)

    Breazeale, K.; Yamaguchi, N.D.; Keeville, H.

    1993-12-01

    In Task 2, the authors establish a baseline for evaluating energy use in Hawaii, and examine key energy and economic indicators. They provide a detailed look at fossil energy imports by type, current and possible sources of oil, gas and coal, quality considerations, and processing/transformation. They present time series data on petroleum product consumption by end-use sector, though they caution the reader that the data is imperfect. They discuss fuel substitutability to identify those end-use categories that are most easily switched to other fuels. They then define and analyze sequential scenarios of fuel substitution in Hawaii and their impacts on patterns of demand. They also discuss energy security--what it means to Hawaii, what it means to neighboring economies, whether it is possible to achieve energy security. 95 figs., 48 tabs.

  1. Healthcare Energy: Spotlight on Chiller Plants | Department of Energy

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

    Chiller Plants Healthcare Energy: Spotlight on Chiller Plants The Building Technologies Office conducted a healthcare energy end-use monitoring project in partnership with two hospitals. See below for a few highlights from monitoring chiller plant energy. Image of a chiller plant. Chiller Energy Annual site energy use intensities (EUIs) for chiller energy were estimated to be 27.7 kBtu/ft2-yr for the the Massachusetts General Hospital (MGH) Gray Building and 26.8 kBtu/ft2-yr for the State

  2. Understanding Manufacturing Energy and Carbon Footprints, October 2012

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

    Understanding Manufacturing Energy and Carbon Footprints The Manufacturing Energy and Carbon Footprints map energy use and carbon emissions from energy supply to end use. Footprints are published for 15 manufacturing sectors (representing 94% of all manufacturing energy use) and for U.S. manufacturing as a whole. These sectors are described in more detail in the document Manufacturing Energy and Carbon Footprint Scope. Manufacturing Energy and Carbon Footprint Sectors: All Manufacturing

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

    Gasoline and Diesel Fuel Update (EIA)

    intensity Energy intensity (measured both by energy use per capita and by energy use per dollar of GDP) declines in the AEO2015 Reference case over the projection period (Figure 19). While a portion of the decline results from a small shift from energy-intensive to nonenergy-intensive manufacturing, most of it results from changes in other sectors. figure data Increasing energy efficiency reduces the energy intensity of many residential end uses between 2013 and 2040. Total energy consumption

  4. Manufacturing Energy and Carbon Footprints (2006 MECS) | Department of

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

    Energy Manufacturing Energy and Carbon Footprints (2006 MECS) Manufacturing Energy and Carbon Footprints (2006 MECS) Energy and Carbon Footprints provide a mapping of energy from supply to end use in manufacturing. They show us where energy is used and lost-and where greenhouse gases (GHGs) are emitted. Footprints are available below for 15 manufacturing sectors (representing 94% of all manufacturing energy use) and for U.S. manufacturing as a whole. Analysis of these footprints is also

  5. Tools | Department of Energy

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

    Below are links to tools that assist users with project planning and analysis. Spectrally Enhanced Lighting Spectrally Enhanced Lighting (SEL) is a cost-effective, low-risk design method for achieving significant energy savings by shifting lamp color from the warmer to the cooler (whiter) end of the color spectrum, more closely matching daylight. Residential Lighting Usage Estimate Tool The Residential Lighting Usage Estimate Tool is a companion to the report, "Residential Lighting End-Use

  6. Databases | Department of Energy

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

    Combined Heat & Power Deployment » Databases Databases DOE has supported the development of several combined heat and power (CHP) and distributed energy databases that have proven to be "go-to" resources for end users. These resources include an installation database that tracks CHP projects in all end-use sectors for all 50 states, as well as a database of regulatory requirements for small electric generators. A searchable database of CHP project profiles compiled by the DOE CHP

  7. ENERGY INFORMATION CLEARINGHOUSE

    SciTech Connect (OSTI)

    Ron Johnson

    2003-10-01

    Alaska has spent billions of dollars on various energy-related activities over the past several decades, with projects ranging from smaller utilities used to produce heat and power in rural Alaska to huge endeavors relating to exported resources. To help provide information for end users, utilities, decision makers, and the general public, the Institute of Northern Engineering at UAF established an Energy Information Clearinghouse accessible through the worldwide web in 2002. This clearinghouse contains information on energy resources, end use technologies, policies, related environmental issues, emerging technologies, efficiency, storage, demand side management, and developments in Alaska.

  8. EERE's 2016 Budget | Department of Energy

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

    About Us » Budget » EERE's 2016 Budget EERE's 2016 Budget The Office of Energy Efficiency and Renewable Energy (EERE) is the U.S. government's primary clean energy technology organization. EERE works with many of America's best innovators and businesses to support high-impact applied research, development, demonstration, and deployment (RDD&D) activities in sustainable transportation, renewable power, and end-use energy efficiency. EERE implements a range of strategies aimed at reducing

  9. Energy Intensity Indicators: Caveats and Cautions | Department of Energy

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

    Caveats and Cautions Energy Intensity Indicators: Caveats and Cautions This website contains a diverse collection of indicators that track changes in energy intensity at the national and end-use sector levels (after taking into account other explanatory factors). Indicators are based on readily available and publicly accessible data, although some of this data has been interpolated between published years, or extrapolated beyond the last published year. To help facilitate the appropriate

  10. EIA Energy Efficiency-Table 1b. Fuel Consumption for Selected...

    Gasoline and Diesel Fuel Update (EIA)

    b Page Last Modified: May 2010 Table 1b. End Uses of Fuel Consumption (Site Energy) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) MECS Survey Years NAICS Subsector...

  11. EIA Energy Efficiency-Table 2b. Primary Fuel Consumption for...

    Gasoline and Diesel Fuel Update (EIA)

    b Page Last Modified: May 2010 Table 2b. End Uses of Fuel Consumption (Primary 1 Energy) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) MECS Survey Years NAICS...

  12. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

    Gasoline and Diesel Fuel Update (EIA)

    Modified: May 2010 Table 2b. End Uses of Fuel Consumption (Primary 1 Energy) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) Note: The Btu conversion factors used for...

  13. Overview of energy-conservation research opportunities

    SciTech Connect (OSTI)

    Hopp, W.J.; Hauser, S.G.; Hane, G.J.; Gurwell, W.E.; Bird, S.P.; Cliff, W.C.; Williford, R.E.; Williams, T.A.; Ashton, W.B.

    1981-12-01

    This document is a study of research opportunities that are important to developing advanced technologies for efficient energy use. The study's purpose is to describe a wide array of attractive technical areas from which specific research and development programs could be implemented. Research areas are presented for potential application in each of the major end-use sectors. The study develops and applies a systematic approach to identifying and screening applied energy conservation research opportunities. To broadly cover the energy end-use sectors, this study develops useful information relating to the areas where federally-funded applied research will most likely play an important role in promoting energy conservation. This study is not designed to produce a detailed agenda of specific recommended research activities. The general information presented allows uniform comparisons of disparate research areas and as such provides the basis for formulating a cost-effective, comprehensive federal-applied energy conservation research strategy. Chapter 2 discusses the various methodologies that have been used in the past to identify research opportunities and details the approach used here. In Chapters 3, 4, and 5 the methodology is applied to the buildings, transportation, and industrial end-use sectors and the opportunities for applied research in these sectors are discussed.Chapter 6 synthesizes the results of the previous three chapters to give a comprehensive picture of applied energy conservation research opportunities across all end-use sectors and presents the conclusions to the report.

  14. Bottoms-Up In-Situ Vitrification Of Hard-to-Treat Buried Mixed Wastes, CRADA Final Report ORNL99-0543

    SciTech Connect (OSTI)

    Spalding, B. P. [ORNL] [ORNL; Farrar, Lawrence [Montec Research] [Montec Research

    2000-01-01

    This Phase I project was designed to demonstrate feasibility of in situ waste destruction and vitrification technology as a means of remediating hard-to-treat buried radioactive and hazardous wastes and focused on proving viability of the concentric graphite arc melter technique as a robust, safe, and economic tool for use as the IWDV process heat source. Oak Ridge National Laboratory provided technical support to Montec Research including the volatile behavior of elements during silicate melting operations and temperature viscosity modeling of silicate melts. Further research will be needed to develop this technology into a competitive remediation technique

  15. Home Energy Saver v.2.0

    Energy Science and Technology Software Center (OSTI)

    2008-09-01

    A web-based residential energy calculator. Provides customized estimates of residential energy use, energy bills, and CO2 emissions, based on building description information provided by the user. Energy use is estimated by end-use and device, using engineering models. Space heating and cooling use is based on the DOE-2.1E building simulation model. Other end-uses (water heating, appliances, lighting, and miscellaneous equipment) are based on engineering models developed by LBNL. Users can estimate their household carbon footprint andmore » compare it to average vaules for their neighborhood and other regions, displayed using the Google Maps API. Energy bills can be calculated using either average energy price data or actual utility tariffs (including time-of-use) contained in the LBNL Tariff Analysis Project (TAP). HES includes a link to the TAP energy bill calculator web service. The HES software also includes extensive default input data for required user inputs.« less

  16. U.S. Energy Information Administration (EIA) - Data

    Gasoline and Diesel Fuel Update (EIA)

    Find statistics on energy consumption and efficiency across all fuel sources. + EXPAND ALL Residential Energy Consumption Survey data Household characteristics Release Date: March 28, 2011 Survey data for occupied primary housing units. Residential Energy Consumption Survey (RECS) Home energy use & costs Release Date: January, 2013 Energy consumption and expenditures by end uses by fuel. Residential Energy Consumption Survey (RECS) Detailed household microdata Release Date: February, 2013

  17. Barriers to Industrial Energy Efficiency - Report to Congress, June 2015 |

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

    Department of Energy Barriers to Industrial Energy Efficiency - Report to Congress, June 2015 Barriers to Industrial Energy Efficiency - Report to Congress, June 2015 This report examines barriers that impede the adoption of energy efficient technologies and practices in the industrial sector, and identifies successful examples and opportunities to overcome these barriers. Three groups of energy efficiency technologies and measures were examined: industrial end-use energy efficiency,

  18. 2010 Manufacturing Energy and Carbon Footprints: Scope | Department of

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

    Energy Scope 2010 Manufacturing Energy and Carbon Footprints: Scope This five-page document provides detailed descriptions of the manufacturing sectors examined in the Energy and Carbon Footprints (MECS 2010) PDF icon Scope of the Manufacturing Energy and Carbon Footprints (MECS 2010) More Documents & Publications Manufacturing Energy and Carbon Footprints Scope End-Use Sector Flowchart U.S. Manufacturing Energy Use and Greenhouse Gas Emissions Analysis

  19. Energy Intensity Changes by Sector, 1985-2011 - Alternative Measures by

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

    Type of Energy | Department of Energy Changes by Sector, 1985-2011 - Alternative Measures by Type of Energy Energy Intensity Changes by Sector, 1985-2011 - Alternative Measures by Type of Energy Further insight with regard to the comparison of intensity changes by sector can be gained by looking at how they differ with respect to different definitions of energy use. Source energy attributes all the energy used for electricity generation and transmission to the specific end-use sector,

  20. Estimates of US biomass energy consumption 1992

    SciTech Connect (OSTI)

    Not Available

    1994-05-06

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass-derived primary energy used by the US economy. It presents estimates of 1991 and 1992 consumption. The objective of this report is to provide updated estimates of biomass energy consumption for use by Congress, Federal and State agencies, biomass producers and end-use sectors, and the public at large.

  1. The Standard Energy Efficiency Database Platform

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

    SEED: The Standard Energy Efficiency Database Platform Bill Prindle Bill Prindle ICF International William.prindle@icfi.com 202-492-9698 2 | Building Technologies Office eere.energy.gov Purpose & Objectives Problem Statement: Data invisibility is a fundamental barrier in building end-use markets. Measuring and recognizing efficiency in U.S. buildings requires standardizing our energy data infrastructure via software conventions. Impact of Project: SEED is intended to provide public agencies

  2. Wind Vision | Department of Energy

    Office of Environmental Management (EM)

    Wind Vision Wind Vision Wind Vision Introduction U.S. Wind Power Impacts Roadmap Download Wind Vision: A New Era for Wind Power in the United States The Wind Vision report updates the Department of Energy's 2008 20% Wind Energy by 2030 through analysis of scenarios of wind power supplying 10% of national end-use electricity demand by 2020, 20% by 2030, and 35% by 2050. With more than 4.5% of the nation's electricity supplied by wind energy today, the Department of Energy has collaborated with

  3. Wind Vision | Department of Energy

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

    Wind Vision Wind Vision Wind Vision Introduction U.S. Wind Power Impacts Roadmap Download Wind Vision: A New Era for Wind Power in the United States The Wind Vision report updates the Department of Energy's 2008 20% Wind Energy by 2030 through analysis of scenarios of wind power supplying 10% of national end-use electricity demand by 2020, 20% by 2030, and 35% by 2050. With more than 4.5% of the nation's electricity supplied by wind energy today, the Department of Energy has collaborated with

  4. Wind Vision | Department of Energy

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

    Wind Vision Wind Vision Wind Vision Introduction U.S. Wind Power Impacts Roadmap Download Wind Vision: A New Era for Wind Power in the United States The Wind Vision report updates the Department of Energy's 2008 20% Wind Energy by 2030 through analysis of scenarios of wind power supplying 10% of national end-use electricity demand by 2020, 20% by 2030, and 35% by 2050. With more than 4.5% of the nation's electricity supplied by wind energy today, the Department of Energy has collaborated with

  5. Healthcare Energy: Spotlight on Lighting and Other Electric Loads |

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

    Department of Energy Lighting and Other Electric Loads Healthcare Energy: Spotlight on Lighting and Other Electric Loads Compact fluorescent, light-emitting diode, and energy-saving incandescent light bulbs. | Image by Dennis Schroeder/NREL 19469 Compact fluorescent, light-emitting diode, and energy-saving incandescent light bulbs. | Image by Dennis Schroeder/NREL 19469 The Building Technologies Office conducted a healthcare energy end-use monitoring project in partnership with two

  6. Residential Energy Consumption Survey (RECS) - Analysis & Projections -

    Gasoline and Diesel Fuel Update (EIA)

    U.S. Energy Information Administration (EIA) How does EIA estimate energy consumption and end uses in U.S. homes? RECS 2009 - Release date: March 28, 2011 EIA administers the Residential Energy Consumption Survey (RECS) to a nationally representative sample of housing units. Specially trained interviewers collect energy characteristics on the housing unit, usage patterns, and household demographics. This information is combined with data from energy suppliers to these homes to estimate

  7. Understanding the 2014 Manufacturing Energy and Carbon Footprints

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

    Understanding the 2010 Manufacturing Energy and Carbon Footprints The Manufacturing Energy and Carbon Footprints map energy use and combustion greenhouse gas (GHG) emissions from energy supply to end use. Footprints are published for 15 manufacturing sectors (representing 95% of all manufacturing energy use and 94% of U.S. manufacturing combustion GHG emissions) and for U.S. manufacturing as a whole (NAICS 31 - 33). These sectors are described in more detail in the document 2010 Manufacturing

  8. Pump Selection Considerations | Department of Energy

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

    Selection Considerations Pump Selection Considerations This tip sheet outlines important pump selection considerations, including fluid properties and pumping system end use requirements. PUMPING SYSTEMS TIP SHEET #2 PDF icon Pump Selection Considerations (October 2005) More Documents & Publications Select an Energy-Efficient Centrifugal Pump Pumping System Assessment Tool Overview Conduct an In-Plant Pumping System Survey

  9. Energy Efficiency Services Sector: Workforce Size and Expectations for Growth

    SciTech Connect (OSTI)

    Goldman, Charles; Fuller, Merrian C.; Stuart, Elizabeth; Peters, Jane S.; McRae, Marjorie; Albers, Nathaniel; Lutzenhiser, Susan; Spahic, Mersiha

    2010-03-22

    The energy efficiency services sector (EESS) is poised to become an increasingly important part of the U.S. economy. Climate change and energy supply concerns, volatile and increasing energy prices, and a desire for greater energy independence have led many state and national leaders to support an increasingly prominent role for energy efficiency in U.S. energy policy. The national economic recession has also helped to boost the visibility of energy efficiency, as part of a strategy to support economic recovery. We expect investment in energy efficiency to increase dramatically both in the near-term and through 2020 and beyond. This increase will come both from public support, such as the American Recovery and Reinvestment Act (ARRA) and significant increases in utility ratepayer funds directed toward efficiency, and also from increased private spending due to codes and standards, increasing energy prices, and voluntary standards for industry. Given the growing attention on energy efficiency, there is a concern among policy makers, program administrators, and others that there is an insufficiently trained workforce in place to meet the energy efficiency goals being put in place by local, state, and federal policy. To understand the likelihood of a potential workforce gap and appropriate response strategies, one needs to understand the size, composition, and potential for growth of the EESS. We use a bottom-up approach based upon almost 300 interviews with program administrators, education and training providers, and a variety of EESS employers and trade associations; communications with over 50 sector experts; as well as an extensive literature review. We attempt to provide insight into key aspects of the EESS by describing the current job composition, the current workforce size, our projections for sector growth through 2020, and key issues that may limit this growth.

  10. Calendar Year 2007 Program Benefits for U.S. EPA Energy Star Labeled Products: Expanded Methodology

    SciTech Connect (OSTI)

    Sanchez, Marla; Homan, Gregory; Lai, Judy; Brown, Richard

    2009-09-24

    This report provides a top-level summary of national savings achieved by the Energy Star voluntary product labeling program. To best quantify and analyze savings for all products, we developed a bottom-up product-based model. Each Energy Star product type is characterized by product-specific inputs that result in a product savings estimate. Our results show that through 2007, U.S. EPA Energy Star labeled products saved 5.5 Quads of primary energy and avoided 100 MtC of emissions. Although Energy Star-labeled products encompass over forty product types, only five of those product types accounted for 65percent of all Energy Star carbon reductions achieved to date, including (listed in order of savings magnitude)monitors, printers, residential light fixtures, televisions, and furnaces. The forecast shows that U.S. EPA?s program is expected to save 12.2 Quads of primary energy and avoid 215 MtC of emissions over the period of 2008?2015.

  11. Energy Videos

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

    Energy Videos Energy

  12. Energy-Efficiency and Air-Pollutant Emissions-Reduction Opportunities for the Ammonia Industry in China

    SciTech Connect (OSTI)

    Ma, Ding; Hasanbeigi, Ali; Chen, Wenying

    2015-06-01

    As one of the most energy-intensive and polluting industries, ammonia production is responsible for significant carbon dioxide (CO2) and air-pollutant emissions. Although many energy-efficiency measures have been proposed by the Chinese government to mitigate greenhouse gas emissions and improve air quality, lack of understanding of the cost-effectiveness of such improvements has been a barrier to implementing these measures. Assessing the costs, benefits, and cost-effectiveness of different energy-efficiency measures is essential to advancing this understanding. In this study, a bottom-up energy conservation supply curve model is developed to estimate the potential for energy savings and emissions reductions from 26 energy-efficiency measures that could be applied in China’s ammonia industry. Cost-effective implementation of these measures saves a potential 271.5 petajoules/year for fuel and 5,443 gigawatt-hours/year for electricity, equal to 14% of fuel and 14% of electricity consumed in China’s ammonia industry in 2012. These reductions could mitigate 26.7 million tonnes of CO2 emissions. This study also quantifies the co-benefits of reducing air-pollutant emissions and water use that would result from saving energy in China’s ammonia industry. This quantitative analysis advances our understanding of the cost-effectiveness of energy-efficiency measures and can be used to augment efforts to reduce energy use and environmental impacts.

  13. Energy 101: Geothermal Energy | Department of Energy

    Office of Environmental Management (EM)

    Geothermal Energy Energy 101: Geothermal Energy

  14. Proceedings of the DOE chemical energy storage and hydrogen energy systems contracts review

    SciTech Connect (OSTI)

    Not Available

    1980-02-01

    Sessions were held on electrolysis-based hydrogen storage systems, hydrogen production, hydrogen storage systems, hydrogen storage materials, end-use applications and system studies, chemical heat pump/chemical energy storage systems, systems studies and assessment, thermochemical hydrogen production cycles, advanced production concepts, and containment materials. (LHK)

  15. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    0 2005 Energy End-Use Expenditures for an Average Household, by Region ($2010) Northeast Midwest South West National Space Heating 1,050 721 371 352 575 Air-Conditioning 199 175 456 262 311 Water Heating 373 294 313 318 320 Refrigerators 194 145 146 154 157 Other Appliances and Lighting 827 665 715 716 725 Total (1) 2,554 1,975 1,970 1,655 2,003 Note(s): 1) Due to rounding, end-uses do not sum to totals. Source(s): EIA, 2005 Residential Energy Consumption Survey, Oct. 2008, Table US-15; EIA,

  16. Supplement to the Annual Energy Outlook 1993

    SciTech Connect (OSTI)

    Not Available

    1993-02-17

    The Supplement to the Annual Energy Outlook 1993 is a companion document to the Energy Information Administration`s (EIA) Annual Energy Outlook 1993 (AEO). Supplement tables provide the regional projections underlying the national data and projections in the AEO. The domestic coal, electric power, commercial nuclear power, end-use consumption, and end-use price tables present AEO forecasts at the 10 Federal Region level. World coal tables provide data and projections on international flows of steam coal and metallurgical coal, and the oil and gas tables provide the AEO oil and gas supply forecasts by Oil and Gas Supply Regions and by source of supply. All tables refer to cases presented in the AEO, which provides a range of projections for energy markets through 2010.

  17. Barriers to Industrial Energy Efficiency - Report to Congress, June 2015

    SciTech Connect (OSTI)

    2015-06-01

    This report examines barriers that impede the adoption of energy efficient technologies and practices in the industrial sector, and identifies successful examples and opportunities to overcome these barriers. Three groups of energy efficiency technologies and measures were examined: industrial end-use energy efficiency, industrial demand response, and industrial combined heat and power. This report also includes the estimated economic benefits from hypothetical Federal energy efficiency matching grants, as directed by the Act.

  18. Barriers to Industrial Energy Efficiency - Study (Appendix A), June 2015

    SciTech Connect (OSTI)

    2015-06-01

    This study examines barriers that impede the adoption of energy efficient technologies and practices in the industrial sector, and identifies successful examples and opportunities to overcome these barriers. Three groups of energy efficiency technologies and measures were examined: industrial end-use energy efficiency, industrial demand response, and industrial combined heat and power. This study also includes the estimated economic benefits from hypothetical Federal energy efficiency matching grants, as directed by the Act.

  19. Energy-consumption and carbon-emission analysis of vehicle and component manufacturing.

    SciTech Connect (OSTI)

    Sullivan, J. L.; Burnham, A.; Wang, M.; Energy Systems

    2010-10-12

    A model is presented for calculating the environmental burdens of the part manufacturing and vehicle assembly (VMA) stage of the vehicle life cycle. The approach is bottom-up, with a special focus on energy consumption and CO{sub 2} emissions. The model is applied to both conventional and advanced vehicles, the latter of which include aluminum-intensive, hybrid electric, plug-in hybrid electric and all-electric vehicles. An important component of the model, a weight-based distribution function of materials and associated transformation processes (casting, stamping, etc.), is developed from the United States Council for Automotive Research Generic Vehicle Life Cycle Inventory Study. As the approach is bottom-up, numerous transformation process data and plant operational data were extracted from the literature for use in representing the many operations included in the model. When the model was applied to conventional vehicles, reliable estimates of cumulative energy consumption (34 GJ/vehicle) and CO{sub 2} emission (2 tonnes/vehicle) were computed for the VMA life-cycle stage. The numerous data sets taken from the literature permitted the development of some statistics on model results. Because the model explicitly includes a greater coverage of relevant manufacturing processes than many earlier studies, our energy estimates are on the higher end of previously published values. Limitations of the model are also discussed. Because the material compositions of conventional vehicles within specific classes (cars, light duty trucks, etc.) are sensibly constant on a percent-by-weight basis, the model can be reduced to a simple linear form for each class dependent only on vehicle weight. For advanced vehicles, the material/transformation process distribution developed above needs to be adjusted for different materials and components. This is particularly so for aluminum-intensive and electric-drive vehicles. In fact, because of their comparatively high manufacturing energy, batteries required for an electric vehicle can significantly add to the energy burden of the VMA stage. Overall, for conventional vehicles, energy use and CO{sub 2} emissions from the VMA stage are about 4% of their total life-cycle values. They are expected to be somewhat higher for advanced vehicles.

  20. Disaggregated analysis of US energy consumption in the 1990s: Evidence of the effects of the internet and rapid economic growth

    SciTech Connect (OSTI)

    Murtishaw, Scott; Schipper, Lee

    2001-07-01

    This paper decomposes US energy use from 1988 to 1998 and attributes the changes in energy use to three underlying factors: activity, structure, and intensity. For this study we use a bottom-up methodology, by separately decomposing delivered energy use in six sectors: travel, freight, manufacturing industries, non-manufacturing industries, residential, and services. The most commonly used indicator of energy efficiency in the total economy, the ratio of energy consumed to unit of GDP (E/GDP) created can often be misleading. The rapid decline in the E/GDP ratio in recent years has been used to support assertions that the Internet and information technologies in general have enabled improvements in energy efficiencies. However, our disaggregate analysis suggests that energy intensities on average are falling more slowly than ever before while actual energy use increased faster than at any time since 1970. The decline in the E/GDP ratio in the mid-to late 1990s owes much more to structural changes in the demand for energy services than to falling energy intensities.

  1. Documentation of Calculation Methodology, Input data, and Infrastructure for the Home Energy Saver Web Site

    SciTech Connect (OSTI)

    Pinckard, Margaret J.; Brown, Richard E.; Mills, Evan; Lutz, James D.; Moezzi, Mithra M.; Atkinson, Celina; Bolduc, Chris; Homan, Gregory K.; Coughlin, Katie

    2005-07-13

    The Home Energy Saver (HES, http://HomeEnergySaver.lbl.gov) is an interactive web site designed to help residential consumers make decisions about energy use in their homes. This report describes the underlying methods and data for estimating energy consumption. Using engineering models, the site estimates energy consumption for six major categories (end uses); heating, cooling, water heating, major appliances, lighting, and miscellaneous equipment. The approach taken by the Home Energy Saver is to provide users with initial results based on a minimum of user input, allowing progressively greater control in specifying the characteristics of the house and energy consuming appliances. Outputs include energy consumption (by fuel and end use), energy-related emissions (carbon dioxide), energy bills (total and by fuel and end use), and energy saving recommendations. Real-world electricity tariffs are used for many locations, making the bill estimates even more accurate. Where information about the house is not available from the user, default values are used based on end-use surveys and engineering studies. An extensive body of qualitative decision-support information augments the analytical results.

  2. International energy outlook 1999

    SciTech Connect (OSTI)

    1999-03-01

    This report presents international energy projections through 2020, prepared by the Energy Information Administration. The outlooks for major energy fuels are discussed, along with electricity, transportation, and environmental issues. The report begins with a review of world trends in energy demand. The historical time frame begins with data from 1970 and extends to 1996, providing readers with a 26-year historical view of energy demand. The IEO99 projections covers a 24-year period. The next part of the report is organized by energy source. Regional consumption projections for oil, natural gas, coal, nuclear power, and renewable energy (hydroelectricity, geothermal, wind, solar, and other renewables) are presented in the five fuel chapters, along with a review of the current status of each fuel on a worldwide basis. The third part of the report looks at energy consumption in the end-use sectors, beginning with a chapter on energy use for electricity generation. New to this year`s outlook are chapters on energy use in the transportation sector and on environmental issues related to energy consumption. 104 figs., 87 tabs.

  3. 2007 Estimated International Energy Flows

    SciTech Connect (OSTI)

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

    2011-03-10

    An energy flow chart or 'atlas' for 136 countries has been constructed from data maintained by the International Energy Agency (IEA) and estimates of energy use patterns for the year 2007. Approximately 490 exajoules (460 quadrillion BTU) of primary energy are used in aggregate by these countries each year. While the basic structure of the energy system is consistent from country to country, patterns of resource use and consumption vary. Energy can be visualized as it flows from resources (i.e. coal, petroleum, natural gas) through transformations such as electricity generation to end uses (i.e. residential, commercial, industrial, transportation). These flow patterns are visualized in this atlas of 136 country-level energy flow charts.

  4. Abstract

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

    based on a bottom-up approach both from the traditional definition of energy-economic-engineering modeling, the "integrated assessment" model methodology, and from a pragmatic...

  5. Energy manager design for microgrids

    SciTech Connect (OSTI)

    Firestone, Ryan; Marnay, Chris

    2005-01-01

    On-site energy production, known as distributed energy resources (DER), offers consumers many benefits, such as bill savings and predictability, improved system efficiency, improved reliability, control over power quality, and in many cases, greener electricity. Additionally, DER systems can benefit electric utilities by reducing congestion on the grid, reducing the need for new generation and transmission capacity, and offering ancillary services such as voltage support and emergency demand response. Local aggregations of distributed energy resources (DER) that may include active control of on-site end-use energy devices can be called microgrids. Microgrids require control to ensure safe operation and to make dispatch decisions that achieve system objectives such as cost minimization, reliability, efficiency and emissions requirements, while abiding by system constraints and regulatory rules. This control is performed by an energy manager (EM). Preferably, an EM will achieve operation reasonably close to the attainable optimum, it will do this by means robust to deviations from expected conditions, and it will not itself incur insupportable capital or operation and maintenance costs. Also, microgrids can include supervision over end-uses, such as curtailing or rescheduling certain loads. By viewing a unified microgrid as a system of supply and demand, rather than simply a system of on-site generation devices, the benefits of integrated supply and demand control can be exploited, such as economic savings and improved system energy efficiency.

  6. Residential Energy Consumption Survey (RECS) - Analysis & Projections -

    Gasoline and Diesel Fuel Update (EIA)

    U.S. Energy Information Administration (EIA) EIA household energy use data now includes detail on 16 States RECS 2009 - Release date: March 28, 2011 EIA is releasing new benchmark estimates for home energy use for the year 2009 that include detailed data for 16 States, 12 more than in past EIA residential energy surveys. EIA has conducted the Residential Energy Consumption Survey (RECS) since 1978 to provide data on home energy characteristics, end uses of energy, and expenses for the four

  7. Refrigeration Playbook: Natural Refrigerants; Selecting and Designing Energy-Efficient Commercial Refrigeration Systems That Use Low Global Warming Potential Refrigerants

    SciTech Connect (OSTI)

    Nelson, Caleb; Reis, Chuck; Nelson, Eric; Armer, James; Arthur, Rob; Heath, Richard; Rono, James; Hirsch, Adam; Doebber, Ian

    2015-03-01

    This report provides guidance for selecting and designing energy efficient commercial refrigeration systems using low global warming potential refrigerants. Refrigeration systems are generally the largest energy end use in a supermarket type building, often accounting for more than half of a building's energy consumption.

  8. U.S. Department of Energy Energy Savings Assessment (ESA) Overview of the Pumping System Assessment Tool (PSAT)

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

    S. Department of Energy Energy Savings Assessment (ESA) Overview of the Pumping System Assessment Tool (PSAT) Date: December 15, 2008 By: Don Casada Diagnostic Solutions, LLC doncasada@diagsol.com 865-938-0965 Motor-driven equipment is a dominant electricity consumer Industrial motor systems: - are the single largest electrical end use category in the American economy - account for 25% of all U.S. electrical sales Pumps are the largest industrial user of motor-driven electrical energy Fluid

  9. Energy Signal Tool for Decision Support in Building Energy Systems

    SciTech Connect (OSTI)

    Henze, G. P.; Pavlak, G. S.; Florita, A. R.; Dodier, R. H.; Hirsch, A. I.

    2014-12-01

    A prototype energy signal tool is demonstrated for operational whole-building and system-level energy use evaluation. The purpose of the tool is to give a summary of building energy use which allows a building operator to quickly distinguish normal and abnormal energy use. Toward that end, energy use status is displayed as a traffic light, which is a visual metaphor for energy use that is either substantially different from expected (red and yellow lights) or approximately the same as expected (green light). Which light to display for a given energy end use is determined by comparing expected to actual energy use. As expected, energy use is necessarily uncertain; we cannot choose the appropriate light with certainty. Instead, the energy signal tool chooses the light by minimizing the expected cost of displaying the wrong light. The expected energy use is represented by a probability distribution. Energy use is modeled by a low-order lumped parameter model. Uncertainty in energy use is quantified by a Monte Carlo exploration of the influence of model parameters on energy use. Distributions over model parameters are updated over time via Bayes' theorem. The simulation study was devised to assess whole-building energy signal accuracy in the presence of uncertainty and faults at the submetered level, which may lead to tradeoffs at the whole-building level that are not detectable without submetering.

  10. U.S. Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions,

  11. New Mexico Sales of Distillate Fuel Oil by End Use

    Gasoline and Diesel Fuel Update (EIA)

    09,709 554,352 574,557 608,490 621,430 669,923 1984-2014 Residential 55 46 37 27 72 53 1984-2014 Commercial 11,030 9,435 9,609 9,145 9,112 12,114 1984-2014 Industrial 33,804 24,429 27,110 31,316 32,029 32,917 1984-2014 Oil Company 9,871 1,705 2,127 5,857 11,218 27,016 1984-2014 Farm 11,278 14,821 10,955 12,816 15,784 11,752 1984-2014 Electric Power 4,321 4,000 1,689 5,155 4,816 3,826 1984-2014 Railroad 245 1,780 1,707 19,123 38,543 45,446 1984-2014 Vessel Bunkering 0 0 0 0 0 0 1984-2014

  12. Alabama Sales of Distillate Fuel Oil by End Use

    Gasoline and Diesel Fuel Update (EIA)

    987,571 1,038,133 1,094,359 1,132,711 1,047,981 1,027,777 1984-2014 Residential 3,971 4,895 432 750 639 722 1984-2014 Commercial 39,802 46,009 48,475 46,654 30,536 27,874 1984-2014 Industrial 90,659 77,542 81,120 120,347 77,119 65,322 1984-2014 Oil Company 0 328 1,035 2,640 2,929 2,985 1984-2014 Farm 17,882 19,881 24,518 24,503 24,651 20,459 1984-2014 Electric Power 8,276 10,372 22,490 9,375 6,514 10,071 1984-2014 Railroad 44,546 42,465 97,177 125,439 63,570 56,873 1984-2014 Vessel Bunkering

  13. Texas Sales of Distillate Fuel Oil by End Use

    Gasoline and Diesel Fuel Update (EIA)

    ,329,790 5,693,270 6,373,078 6,688,629 6,914,481 7,837,118 1984-2014 Residential 67 28 127 102 16 59 1984-2014 Commercial 136,419 100,886 184,312 173,303 142,268 132,601 1984-2014 Industrial 189,981 197,024 233,292 241,601 240,179 270,760 1984-2014 Oil Company 210,865 316,523 541,640 736,186 679,737 886,957 1984-2014 Farm 201,769 207,183 243,170 216,915 190,572 222,849 1984-2014 Electric Power 19,495 15,646 23,156 20,022 20,706 24,700 1984-2014 Railroad 429,026 467,128 498,006 483,096 504,823

  14. Distribution Category UC-98 Consumption End-Use A Comparison...

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

    buildings) as well as a list of large buildings in each metropolitan area. MECS is based upon a comprehensive list of manufactures that is maintained by the Census Bureau for...

  15. Florida Sales of Distillate Fuel Oil by End Use

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

    840,100 2,027,012 1,914,621 1,918,039 2,023,650 2,038,923 1984-2014 Residential 1,551 1,820 1,085 572 451 728 1984-2014 Commercial 126,292 113,313 100,791 104,860 113,873 110,082 1984-2014 Industrial 36,512 43,088 35,652 32,087 31,458 42,894 1984-2014 Oil Company 236 2,255 4,038 4,359 4,427 3,802 1984-2014 Farm 86,642 204,866 109,177 103,325 122,563 98,418 1984-2014 Electric Power 31,161 43,675 35,577 16,137 16,244 12,182 1984-2014 Railroad 33,651 42,353 46,461 66,711 93,844 92,435 1984-2014

  16. West Virginia Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    33 5,114 4,922 4,914 6,180 6,835 2001-2015 Residential 419 244 339 387 1,242 2,132 1989-2015 Commercial 796 981 876 1,107 1,547 1,923 1989-2015 Industrial 1,903 1,746 1,834 1,677...

  17. New Hampshire Natural Gas Consumption by End Use

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

    NA NA NA NA NA NA 2001-2015 Residential 146 147 148 242 657 854 1989-2015 Commercial 221 226 232 377 823 1,017 1989-2015 Industrial NA NA NA NA NA NA 2001-2015 Vehicle Fuel 6 6 6 6 6 6 2010-2015 Electric Power 4,211 4,622 3,922 3,375 3,795 2,706

  18. New Jersey Natural Gas Consumption by End Use

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

    47,857 46,260 NA NA 56,469 63,409 2001-2015 Residential 5,478 4,422 4,498 9,214 16,149 22,163 1989-2015 Commercial 7,486 8,431 NA NA 11,186 13,623 1989-2015 Industrial 4,256 4,032 4,128 4,370 4,611 4,249 2001-2015 Vehicle Fuel 19 19 19 19 19 19 2010-2015 Electric Power 30,618 29,355 29,675 24,677 24,504 23,354

  19. District of Columbia Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    984 1,037 1,072 1,740 2,437 2,907 2001-2015 Residential 242 240 253 520 911 1,335 1989-2015 Commercial 657 711 736 1,135 1,443 1,487 1989-2015 Industrial 0 0 0 0 0 0 2001-2015 Vehicle Fuel 86 86 83 86 83 86 2010-2015 Electric Power -- -- -- -- -- --

  20. New Hampshire Natural Gas Consumption by End Use

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

    0,378 69,978 72,032 54,028 57,017 1997-2014 Pipeline & Distribution Use 247 202 27 67 81 1997-2014 Volumes Delivered to Consumers 60,131 69,776 72,004 53,961 56,936 NA 1997-2015 Residential 6,738 6,955 6,422 7,185 7,755 7,587 1980-2015 Commercial 8,406 8,890 8,130 9,204 9,412 9,327 1980-2015 Industrial 6,022 7,083 7,007 7,866 8,456 NA 1997-2015 Vehicle Fuel 28 37 37 62 73 60 1988-2015 Electric Power 38,937 46,812 50,408 29,644 31,240 42,67

  1. New Jersey Natural Gas Consumption by End Use

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

    54,458 660,743 652,060 682,247 762,200 1997-2014 Pipeline & Distribution Use 5,359 5,655 4,603 5,559 5,070 1997-2014 Volumes Delivered to Consumers 649,099 655,088 647,457 676,688 757,130 NA 1997-2015 Residential 219,141 213,630 191,371 226,195 247,742 237,164 1967-2015 Commercial 181,480 191,808 174,641 171,797 202,201 NA 1967-2015 Industrial 49,269 49,865 54,785 61,468 61,494 NA 1997-2015 Vehicle Fuel 150 191 191 195 229 222 1988-2015 Electric Power 199,059 199,594 226,469 217,032 245,464

  2. New Mexico Natural Gas Consumption by End Use

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

    41,137 246,418 243,961 245,502 246,178 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 49,070 47,556 47,696 47,018 49,406 1983-2014 Plant Fuel 35,289 38,331 37,195 33,121 35,269 1983-2014 Pipeline & Distribution Use 8,597 7,067 7,467 8,782 8,561 1997-2014 Volumes Delivered to Consumers 148,181 153,464 151,602 156,581 152,942 NA 1997-2015 Residential 35,253 34,299 32,515 36,024 32,370 34,036 1967-2015 Commercial 25,155 25,035 24,898 26,790 25,688 26,262 1967-2015 Industrial 16,779 20,500

  3. New York Natural Gas Consumption by End Use

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

    1,198,127 1,217,324 1,223,036 1,273,263 1,345,315 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 573 498 423 375 541 1983-2014 Pipeline & Distribution Use 15,122 18,836 17,610 16,819 24,923 1997-2014 Volumes Delivered to Consumers 1,182,432 1,197,990 1,205,004 1,256,070 1,319,852 1,322,592 1997-2015 Residential 390,491 393,825 357,709 416,357 458,313 450,815 1967-2015 Commercial 287,389 291,118 270,232 300,776 320,168 309,481 1967-2015 Industrial 75,475 75,162 74,133 79,776 84,255

  4. North Carolina Natural Gas Consumption by End Use

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

    304,148 307,804 363,945 440,175 453,212 1997-2014 Pipeline & Distribution Use 7,978 7,322 5,436 4,029 3,877 1997-2014 Volumes Delivered to Consumers 296,169 300,481 358,510 436,146 449,335 NA 1997-2015 Residential 74,520 61,644 56,511 69,654 75,178 NA 1967-2015 Commercial 56,225 49,898 48,951 55,271 59,945 NA 1967-2015 Industrial 92,321 99,110 102,151 109,662 107,904 105,096 1997-2015 Vehicle Fuel 32 30 30 71 83 62 1988-2015 Electric Power 73,072 89,799 150,866 201,489 206,226 268,925

  5. North Dakota Natural Gas Consumption by End Use

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

    66,395 72,463 72,740 81,593 83,330 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 3,753 3,200 4,595 6,486 8,683 1983-2014 Plant Fuel 4,294 5,473 5,887 6,707 5,736 1983-2014 Pipeline & Distribution Use 13,745 13,575 15,619 14,931 14,604 1997-2014 Volumes Delivered to Consumers 44,603 50,214 46,639 53,469 54,307 55,321 1997-2015 Residential 10,536 10,937 9,594 12,085 12,505 10,606 1967-2015 Commercial 10,302 10,973 10,364 13,236 13,999 12,334 1967-2015 Industrial 23,762 28,303 26,680

  6. Rhode Island Natural Gas Consumption by End Use

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

    94,110 100,455 95,476 85,537 88,673 1997-2014 Lease and Plant Fuel 1967-1992 Pipeline & Distribution Use 1,468 1,003 1,023 1,087 2,824 1997-2014 Volumes Delivered to Consumers 92,642 99,452 94,452 84,450 85,849 90,207 1997-2015 Residential 16,942 16,864 15,883 18,221 19,724 19,522 1967-2015 Commercial 10,458 10,843 10,090 11,633 13,178 11,734 1967-2015 Industrial 8,033 7,462 7,841 8,161 8,008 8,751 1997-2015 Vehicle Fuel 87 85 85 73 86 89 1988-2015 Electric Power 57,122 64,198 60,553 46,362

  7. South Carolina Natural Gas Consumption by End Use

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

    220,235 229,497 244,850 232,297 231,863 1997-2014 Pipeline & Distribution Use 3,452 3,408 3,416 2,529 2,409 1997-2014 Volumes Delivered to Consumers 216,783 226,089 241,434 229,768 229,454 NA 1997-2015 Residential 32,430 26,851 22,834 28,642 31,862 27,171 1967-2015 Commercial 24,119 22,113 21,416 23,862 25,380 NA 1967-2015 Industrial 73,397 76,973 81,165 83,730 83,330 NA 1997-2015 Vehicle Fuel 7 9 9 18 21 16 1988-2015 Electric Power 86,830 100,144 116,010 93,516 88,861 135,239

  8. South Dakota Natural Gas Consumption by End Use

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

    72,563 73,605 70,238 81,986 79,964 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 562 594 866 916 827 1983-2014 Plant Fuel 0 0 0 2012-2014 Pipeline & Distribution Use 5,806 6,692 6,402 6,888 5,221 1997-2014 Volumes Delivered to Consumers 66,195 66,320 62,969 74,182 73,917 73,755 1997-2015 Residential 12,815 12,961 10,742 13,920 14,213 11,638 1967-2015 Commercial 11,025 11,101 9,330 12,151 12,310 10,497 1967-2015 Industrial 40,755 40,668 40,432 44,039 44,205 44,683 1997-2015 Vehicle Fuel

  9. West Virginia Natural Gas Consumption by End Use

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

    13,179 115,361 129,753 142,082 150,766 1997-2014 Lease and Plant Fuel 1967-1998 Lease Fuel 11,348 15,571 21,569 28,682 27,853 1983-2014 Plant Fuel 810 1,153 1,812 3,429 6,776 1983-2014 Pipeline & Distribution Use 21,589 21,447 31,913 29,578 29,160 1997-2014 Volumes Delivered to Consumers 79,432 77,189 74,459 80,393 86,978 NA 1997-2015 Residential 27,021 25,073 22,538 26,514 28,257 24,975 1967-2015 Commercial 24,907 24,094 22,634 24,252 24,101 22,584 1967-2015 Industrial 26,023 25,443 26,926

  10. U.S. Adjusted Sales of Kerosene by End Use

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

    Area: U.S. East Coast (PADD 1) New England (PADD 1A) Connecticut Maine Massachusetts New Hampshire Rhode Island Vermont Central Atlantic (PADD 1B) Delaware District of Columbia Maryland New Jersey New York Pennsylvania Lower Atlantic (PADD 1C) Florida Georgia North Carolina South Carolina Virginia West Virginia Midwest (PADD 2) Illinois Indiana Iowa Kansas Kentucky Michigan Minnesota Missouri Nebraska North Dakota Ohio Oklahoma South Dakota Tennessee Wisconsin Gulf Coast (PADD 3) Alabama

  11. New Mexico Natural Gas Consumption by End Use

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

    11,371 12,236 10,219 10,795 14,369 19,223 2001-2015 Residential 830 864 854 1,282 3,863 6,379 1989-2015 Commercial 1,029 1,121 1,106 1,689 3,294 4,321 1989-2015 Industrial 1,382 1,437 1,348 1,479 1,616 1,575 2001-2015 Vehicle Fuel 16 16 15 16 15 16 2010-2015 Electric Power 8,114 8,798 6,895 6,330 5,581 6,933

  12. North Dakota Natural Gas Consumption by End Use

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

    2,929 3,396 3,600 4,063 5,168 5,845 2001-2015 Residential 170 147 200 513 1,069 1,713 1989-2015 Commercial 308 294 321 667 1,214 1,808 1989-2015 Industrial 1,954 2,463 2,646 2,883 2,885 2,324 2001-2015 Vehicle Fuel 0 0 0 0 0 0 2010-2015 Electric Power 497 492 433 W W W

  13. Rhode Island Natural Gas Consumption by End Use

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

    8,254 8,371 4,837 6,216 7,643 6,847 2001-2015 Residential 430 397 385 1,038 1,591 1,903 1989-2015 Commercial 258 249 244 624 1,007 1,106 1989-2015 Industrial 658 681 694 683 704 750 2001-2015 Vehicle Fuel 7 7 7 7 7 7 2010-2015 Electric Power 6,902 7,037 3,507 3,864 4,334 3,08

  14. South Dakota Natural Gas Consumption by End Use

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

    5,249 5,045 4,529 4,893 6,660 8,123 2001-2015 Residential 188 221 226 473 1,162 1,996 1989-2015 Commercial 304 314 315 571 1,127 1,564 1989-2015 Industrial 3,541 3,566 3,469 3,452 3,849 3,907 2001-2015 Vehicle Fuel 0 0 0 0 0 0 2010-2015 Electric Power 1,216 943 519 396 521 6

  15. U.S. Natural Gas Consumption by End Use

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

    Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2010 2011 2012 2013 2014 2015 View History Total Consumption 24,086,797 24,477,425 25,538,487 26,155,071 26,698,068 27,472,867 1949-2015 Lease and Plant Fuel 1,285,627 1,322,588 1,396,273 1,483,085 1,500,181 1,580,997 1930-2015 Lease Fuel 916,797 938,340 987,957 1,068,289 1,074,943 1983-2014 Plant Fuel 368,830 384,248 408,316 414,796

  16. ,"U.S. Natural Gas Consumption by End Use"

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

    9,"Monthly","122015","1151973" ,"Release Date:","2292016" ,"Next Release Date:","3312016" ,"Excel File Name:","ngconssumdcunusm.xls" ,"Available from Web Page:","http:...

  17. District of Columbia Natural Gas Consumption by End Use

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

    33,251 32,862 28,561 32,743 34,057 1997-2014 Pipeline & Distribution Use 213 1,703 1,068 1,434 1,305 1997-2014 Volumes Delivered to Consumers 33,038 31,159 27,493 31,309 32,751 29,157 1997-2015 Residential 13,608 12,386 11,260 13,214 14,242 12,371 1980-2015 Commercial 18,547 16,892 15,363 17,234 17,498 15,793 1980-2015 Industrial 0 0 0 0 0 0 1997-2015 Vehicle Fuel 883 879 870 861 1,011 993 1988-2015 Electric Power -- 1,003 W -- -- --

  18. Gulf of Mexico Natural Gas Consumption by End Use

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

    Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2009 2010 2011 2012 2013 2014 View History Total Consumption 103,976 108,490 101,217 93,985 95,207 93,855 1999-2014 Lease Fuel 103,976 108,490 101,217 93,985 95,207 93,855 1999-2014 Plant Fuel 0 2014-2014

  19. U.S. Sales of Kerosene by End Use

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

    Area: U.S. East Coast (PADD 1) New England (PADD 1A) Connecticut Maine Massachusetts New Hampshire Rhode Island Vermont Central Atlantic (PADD 1B) Delaware District of Columbia Maryland New Jersey New York Pennsylvania Lower Atlantic (PADD 1C) Florida Georgia North Carolina South Carolina Virginia West Virginia Midwest (PADD 2) Illinois Indiana Iowa Kansas Kentucky Michigan Minnesota Missouri Nebraska North Dakota Ohio Oklahoma South Dakota Tennessee Wisconsin Gulf Coast (PADD 3) Alabama

  20. Louisiana Sales of Distillate Fuel Oil by End Use

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

    514,474 1,744,771 1,873,769 1,488,986 1,405,392 1,375,580 1984-2014 Residential 1,036 140 34 53 84 89 1984-2014 Commercial 59,689 38,695 39,659 36,840 17,590 21,197 1984-2014 Industrial 21,826 26,063 20,770 33,052 31,744 33,670 1984-2014 Oil Company 243,789 319,394 364,261 245,303 183,801 178,810 1984-2014 Farm 42,624 44,027 49,985 48,462 40,785 46,134 1984-2014 Electric Power 4,321 4,775 5,464 2,733 4,610 4,826 1984-2014 Railroad 18,345 25,425 32,515 28,110 39,578 45,790 1984-2014 Vessel