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  1. DOE Releases Electricity Subsector Cybersecurity Risk Management...

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

    Releases Electricity Subsector Cybersecurity Risk Management Process (RMP) Guideline DOE Releases Electricity Subsector Cybersecurity Risk Management Process (RMP) Guideline May ...

  2. Integrating Electricity Subsector

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

    Integrating Electricity Subsector Failure Scenarios into a Risk Assessment Methodology 3002001181 | DEC 2013 Program Leads Jason D. Christopher Technical Lead, Cyber Security Capabilities & Risk Management Department of Energy (DOE), Office of Electricity Delivery and Energy Reliability (OE) Annabelle Lee Senior Technical Executive, Cyber Security Electric Power Research Institute (EPRI) For more information on the DOE's cyber security risk management programs, please contact

  3. Notice of Publication of Electricity Subsector Cybersecurity...

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

    Publication of Electricity Subsector Cybersecurity Risk Management Process: Federal Register Notice Volume 77, No. 100 - May 23, 2012 Notice of Publication of Electricity Subsector...

  4. Electricity Subsector Cybersecurity Capability Maturity Model...

    Office of Environmental Management (EM)

    and prioritize their actions and investments to improve cybersecurity, combines ... 2013 - Wednesday, June 5, 2013 Oil and Natural Gas Subsector Cybersecurity Capability ...

  5. Electricity Subsector Cybersecurity Capability Maturity Model...

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

    The Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Version 1.1, which allows electric utilities and grid operators to assess their cybersecurity...

  6. Oil and Natural Gas Subsector Cybersecurity Capability Maturity...

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

    The Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) is a ... Oil and Natural Gas Subsector C2M2 v1.1 (February 2014) (1.82 MB) More Documents & ...

  7. Oil and Natural Gas Subsector Cybersecurity Capability Maturity...

    Office of Environmental Management (EM)

    Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) Oil and Natural ...

  8. Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model

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

    (ONG-C2M2) | Department of Energy Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) The Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) was established as a result of the Administration's efforts to improve electricity subsector cybersecurity capabilities, and to

  9. ELECTRICITY SUBSECTOR CYBERSECURITY RISK MANAGEMENT PROCESS

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

    CYBERSECURITY RISK MANAGEMENT PROCESS U.S. Department of Energy May 2012 DOE/OE-0003 Acknowledgments This electricity subsector cybersecurity Risk Management Process (RMP) guideline was developed by the Department of Energy (DOE), in collaboration with the National Institute of Standards and Technology (NIST) and the North American Electric Reliability Corporation (NERC). Members of industry and utility-specific trade groups were included in authoring this guidance designed to be meaningful and

  10. Electricity Subsector Cybersecurity Capability Maturity Model v. 1.1.

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

    (February 2014) | Department of Energy Subsector Cybersecurity Capability Maturity Model v. 1.1. (February 2014) Electricity Subsector Cybersecurity Capability Maturity Model v. 1.1. (February 2014) The Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Version 1.1, which allows electric utilities and grid operators to assess their cybersecurity capabilities and prioritize their actions and investments to improve cybersecurity, combines elements from existing

  11. Electricity Subsector Cybersecurity Capability Maturity Model v. 1.1.

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

    (February 2014) | Department of Energy Subsector Cybersecurity Capability Maturity Model v. 1.1. (February 2014) Electricity Subsector Cybersecurity Capability Maturity Model v. 1.1. (February 2014) The Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Version 1.1, which allows electric utilities and grid operators to assess their cybersecurity capabilities and prioritize their actions and investments to improve cybersecurity, combines elements from existing

  12. DOE Releases Electricity Subsector Cybersecurity Risk Management Process

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

    (RMP) Guideline | Department of Energy Electricity Subsector Cybersecurity Risk Management Process (RMP) Guideline DOE Releases Electricity Subsector Cybersecurity Risk Management Process (RMP) Guideline May 23, 2012 - 9:30am Addthis News Media Contact: (202) 586-4940 For Immediate Release: May 23, 2012 Department of Energy Releases Electricity Subsector Cybersecurity Risk Management Process (RMP) Guideline Public-Private Sector Collaboration Produces Guidance to Help Electric Utilities

  13. Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model

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

    (February 2014) | Department of Energy Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (February 2014) Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (February 2014) The Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) is a derivative of the Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Version 1.1. The ES-C2M2 was developed in support of a White House initiative led by the Department of

  14. Table B-1: Analytical Results Statistical Mean Upper Confidence

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

    .1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments; Unit: Physical Units or Btu. Coke and Shipments Net Residual Distillate Natural Gas(e) LPG and Coal Breeze of Energy Sources NAICS Total(b) Electricity(c) Fuel Oil Fuel Oil(d) (billion NGL(f) (million (million Other(g) Produced Onsite(h) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million

  15. Originally Released: July 2009

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

    Coke and Shipments Net Residual Distillate Natural Gas(e) LPG and Coal Breeze of Energy Sources NAICS Total(b) Electricity(c) Fuel Oil Fuel Oil(d) (billion NGL(f) (million (million Other(g) Produced Onsite(h) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) (trillion Btu) Total United States 311 Food 1,186 73,440 4 3 620 1 7 * 105 * 3112 Grain and Oilseed Milling 318 15,464 * * 117 * 5 0 29 *

  16. Originally Released: July 2009

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

    Coke and Shipments Net Residual Distillate Natural Gas(e) LPG and Coal Breeze of Energy Sources NAICS Total(b) Electricity(c) Fuel Oil Fuel Oil(d) (billion NGL(f) (million (million Other(g) Produced Onsite(h) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) (trillion Btu) Total United States 311 Food 1,186 73,440 4 3 620 1 7 * 105 * 3112 Grain and Oilseed Milling 318 15,464 * * 117 * 5 0 29 *

  17. Originally Released: July 2009

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

    1.2 First Use of Energy for All Purposes (Fuel and Nonfuel), 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments; Unit: Trillion Btu. Shipments NAICS Net Residual Distillate LPG and Coke and of Energy Sources Code(a) Subsector and Industry Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Total United States 311 Food 1,186 251 26 16 638 3 147 1 105 * 3112 Grain and Oilseed Milling 318 53 2 1 120

  18. Table 1.1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2010;

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

    1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments; Unit: Physical Units or Btu. Coke and Shipments Net Residual Distillate Natural Gas(e) LPG and Coal Breeze of Energy Sources NAICS Total(b) Electricity(c) Fuel Oil Fuel Oil(d) (billion NGL(f) (million (million Other(g) Produced Onsite(h) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million

  19. Table 1.2 First Use of Energy for All Purposes (Fuel and Nonfuel), 2010

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

    2 First Use of Energy for All Purposes (Fuel and Nonfuel), 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments; Unit: Trillion Btu. Shipments NAICS Net Residual Distillate LPG and Coke and of Energy Sources Code(a) Subsector and Industry Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Total United States 311 Food 1,162 257 12 23 583 8 182 2 96 * 3112 Grain and Oilseed Milling 355 56 * 1 123 Q

  20. Integrating Electricity Subsector Failure Scenarios into a Risk Assessment

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

    Methodology (December 2013) | Department of Energy Integrating Electricity Subsector Failure Scenarios into a Risk Assessment Methodology (December 2013) Integrating Electricity Subsector Failure Scenarios into a Risk Assessment Methodology (December 2013) The nation's power system consists of both legacy and next generation technologies. New grid technologies are introducing millions of novel, intelligent components to the electric grid that communicate in much more advanced ways than in

  1. Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) |

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

    Department of Energy Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) The Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) was established as a result of the Administration's efforts to improve electricity subsector cybersecurity capabilities, and to understand the cybersecurity posture of the energy

  2. OIL AND NATURAL GAS SUBSECTOR CYBERSECURITY CAPABILITY MATURITY MODEL (ONG-C2M2)

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

    OIL AND NATURAL GAS SUBSECTOR CYBERSECURITY CAPABILITY MATURITY MODEL (ONG-C2M2) Version 1.1 February 2014 Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model Version 1.1 iii TABLE OF CONTENTS Acknowledgments ......................................................................................................................................... v 1. Introduction

  3. Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments;

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

    Coke and Shipments Net Residual Distillate Natural LPG and Coal Breeze of Energy Sources NAICS Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Gas(e) NGL(f) (million (million Other(g) Produced Onsite(h) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) short tons) short tons) (trillion Btu) (trillion Btu) Total United States RSE Column Factors: 0.9 1 1.2 1.8 1 1.6 0.8 0.9 1.2 0.4 311 Food 1,123 67,521 2 3 567 1 8 * 89 0 311221 Wet

  4. table1.1_02

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

    Coke and Shipments Net Residual Distillate Natural LPG and Coal Breeze of Energy Sources RSE NAICS Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Gas(e) NGL(f) (million (million Other(g) Produced Onsite(h) Row Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) short tons) short tons) (trillion Btu) (trillion Btu) Factors Total United States RSE Column Factors: 0.9 1 1.2 1.8 1 1.6 0.8 0.9 1.2 0.4 311 Food 1,123 67,521 2 3 567 1 8 *

  5. table1.2_02

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

    2 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments; Unit: Trillion Btu. Shipments RSE NAICS Net Residual Distillate Natural LPG and Coke and of Energy Sources Row Code(a) Subsector and Industry Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Factors Total United States RSE Column Factors: 0.9 1 1.2 1.8 1 1.6 0.8 0.9 1.2 0.4 311 Food 1,123 230

  6. Notice of Publication of Electricity Subsector Cybersecurity Risk Management Process: Federal Register Notice Volume 77, No. 100- May 23, 2012

    Broader source: Energy.gov [DOE]

    This serves as public notification of the publication, by the Department of Energy (DOE) of the Electricity Subsector Cybersecurity Risk Management Process guideline. The guideline describes a risk...

  7. Current and future industrial energy service characterizations. Volume III. Energy data on 15 selected states' manufacturing subsector

    SciTech Connect (OSTI)

    Krawiec, F.; Thomas, T.; Jackson, F.; Limaye, D.R.; Isser, S.; Karnofsky, K.; Davis, T.D.

    1980-11-01

    An examination is made of the current and future energy demands, and uses, and cost to characterize typical applications and resulting services in the US and industrial sectors of 15 selected states. Volume III presents tables containing data on selected states' manufacturing subsector energy consumption, functional uses, and cost in 1974 and 1976. Alabama, California, Illinois, Indiana, Louisiana, Michigan, Missouri, New Jersey, New York, Ohio, Oregon, Pennsylvania, Texas, West Virginia, and Wisconsin were chosen as having the greatest potential for replacing conventional fuel with solar energy. Basic data on the quantities, cost, and types of fuel and electric energy purchased by industr for heat and power were obtained from the 1974 and 1976 Annual Survey of Manufacturers. The specific indutrial energy servic cracteristics developed for each selected state include. 1974 and 1976 manufacturing subsector fuels and electricity consumption by 2-, 3-, and 4-digit SIC and primary fuel (quantity and relative share); 1974 and 1976 manufacturing subsector fuel consumption by 2-, 3-, and 4-digit SIC and primary fuel (quantity and relative share); 1974 and 1976 manufacturing subsector average cost of purchsed fuels and electricity per million Btu by 2-, 3-, and 4-digit SIC and primary fuel (in 1976 dollars); 1974 and 1976 manufacturing subsector fuels and electric energy intensity by 2-, 3-, and 4-digit SIC and primary fuel (in 1976 dollars); manufacturing subsector average annual growth rates of (1) fuels and electricity consumption, (2) fuels and electric energy intensity, and (3) average cost of purchased fuels and electricity (1974 to 1976). Data are compiled on purchased fuels, distillate fuel oil, residual ful oil, coal, coal, and breeze, and natural gas. (MCW)

  8. table3.2

    Gasoline and Diesel Fuel Update (EIA)

    ... NAICS Code(a) Subsector and Industry Total Net Electricity(b... RSE Row Factors Table 3.2 Fuel Consumption, 2002; Level: ... of Energy Markets and End Use, Energy Consumption ...

  9. Integrating Electricity Subsector

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

    ... gangs Recreational Criminals Hackers 4 http:www.safetyissues.comsitecybercrimeciarevealshackerattacksonutilities.html?print 4-6 Table 4-1 (Continued) Electric Sector ...

  10. "Code(a)","Subsector and Industry","Source(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Natural Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)"

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

    1.4 Relative Standard Errors for Table 1.4;" " Unit: Percents." ,,"Any",,,,,,,,,"Shipments" "NAICS",,"Energy","Net","Residual","Distillate",,"LPG and",,"Coke and",,"of Energy Sources" "Code(a)","Subsector and Industry","Source(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Natural

  11. "Code(a)","Subsector and Industry","Source(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Natural Gas(e)","NGL(f)","Coal","and Breeze","Other(g)"

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

    3.4 Relative Standard Errors for Table 3.4;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," ",," " " "," ","Any" "NAICS"," ","Energy","Net","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and

  12. "Code(a)","Subsector and Industry","Source(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","NGL(e)","Coal","and Breeze","Other(f)"

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

    2.4 Relative Standard Errors for Table 2.4;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," ",," " " "," ","Any Combustible" "NAICS"," ","Energy","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and

  13. "Code(a)","Subsector and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","and Breeze","Other(e)"

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

    9 Relative Standard Errors for Table 7.9;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," "," " " "," " "NAICS"," "," ",,"Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and

  14. ELECTRICITY SUBSECTOR CYBERSECURITY CAPABILITY MATURITY MODEL...

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

    ... Credentials are issued for personnel and other entities that require access to assets ... Credentials are periodically reviewed to ensure that they are associated with the correct ...

  15. ELECTRICITY SUBSECTOR CYBERSECURITY RISK MANAGEMENT PROCESS

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

    by the Department of Energy (DOE), in collaboration ... to be meaningful and tailored for the electricity sector. ... by other legislation, regulation, policies, programmatic ...

  16. Electricity Subsector Cybersecurity Capability Maturity Model...

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

    Sector Cybersecurity Framework Implementation Guidance (January 2015) The Electricity Journal: Cybersecurity and the Smarter Grid CEDS Fact Sheets Cybersecurity Procurement...

  17. Electricity Subsector Cybersecurity Capability Maturity Model...

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

    Facilitated self-evaluations provide organizations with an opportunity to conduct ES-C2M2 evaluations with the aid of experienced facilitators in a one-day structured walk-through. ...

  18. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    0.5 Number of Establishments with Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Residual Fuel Oil(b) Alternative Energy Sources(c) Coal Coke NAICS Total Establishments Not Electricity Natural Distillate and Code(a) Selected Subsectors and Industry Consuming Residual Fuel Oil(d Switchable Switchable Receipts(e) Gas Fuel Oil Coal LPG Breeze Other(f) Total United States 311 Food

  19. Level: National Data; Row: NAICS Codes; Column: Levels of Price Difference;

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

    6 Percent of Establishments by Levels of Price Difference that Would Cause Fuel Switching from Coal to a Less Expensive Substitute, 2010; Level: National Data; Row: NAICS Codes; Column: Levels of Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided Substitute Total United States

  20. Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable;

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

    1 Reasons that Made Natural Gas Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Billion cubic feet. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS Natural Gas Unswitchable Capable of Using Adversely Affects Alternative Environmenta Contract Storage for Another Columns F, G, Code(a) Subsector and Industry Consumed as a FueNatural Gas Fuel Use Another Fuel the

  1. Released: December 2015

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

    4 Percent of Establishments by Levels of Price Difference that Would Cause Fuel Switching from Electricity to a Less Expensive Substitute, 2010; Level: National Data; Row: NAICS Codes; Column: Levels of Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided Substitute Total United

  2. Released: December 2015

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

    5 Percent of Establishments by Levels of Price Difference that Would Cause Fuel Switching from Natural Gas to a Less Expensive Substitute, 2010; Level: National Data; Row: NAICS Codes; Column: Levels of Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided Substitute Total United

  3. Released: December 2015

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

    8 Percent of Establishments by Levels of Price Difference that Would Cause Fuel Switching from Distillate Fuel Oil to a Less Expensive Substitute, 2010; Level: National Data; Row: NAICS Codes; Column: Levels of Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided Substitute Total

  4. Released: December 2015

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

    9 Percent of Establishments by Levels of Price Difference that Would Cause Fuel Switching from Residual Fuel Oil to a Less Expensive Substitute, 2010; Level: National Data; Row: NAICS Codes; Column: Levels of Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided Substitute Total

  5. Released: June 2010

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

    4 Percent of Establishments by Levels of Lowest Price Difference that Would Cause Fuel Switching from Electricity to a Less Expensive Substitute, 2006; Level: National Data; Row: NAICS Codes; Column: Levels of Lowest Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided Substitute

  6. Released: June 2010

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

    5 Percent of Establishments by Levels of Lowest Price Difference that Would Cause Fuel Switching from Natural Gas to a Less Expensive Substitute, 2006; Level: National Data; Row: NAICS Codes; Column: Levels of Lowest Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided Substitute

  7. Released: June 2010

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

    6 Percent of Establishments by Levels of Lowest Price Difference that Would Cause Fuel Switching from Coal to a Less Expensive Substitute, 2006; Level: National Data; Row: NAICS Codes; Column: Levels of Lowest Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided Substitute Total

  8. Released: June 2010

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

    7 Percent of Establishments by Levels of Lowest Price Difference that Would Cause Fuel Switching from LPG to a Less Expensive Substitute, 2006; Level: National Data; Row: NAICS Codes; Column: Levels of Lowest Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided Substitute Total

  9. Released: June 2010

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

    8 Percent of Establishments by Levels of Lowest Price Difference that Would Cause Fuel Switching from Distillate Fuel Oil to a Less Expensive Substitute, 2006; Level: National Data; Row: NAICS Codes; Column: Levels of Lowest Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided

  10. Released: June 2010

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

    9 Percent of Establishments by Levels of Lowest Price Difference that Would Cause Fuel Switching from Residual Fuel Oil to a Less Expensive Substitute, 2006; Level: National Data; Row: NAICS Codes; Column: Levels of Lowest Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided

  11. Table 10.24 Reasons that Made Distillate Fuel Oil Unswitchable, 2006;

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

    4 Reasons that Made Distillate Fuel Oil Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Million barrels. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS Distillate Fuel Oil Unswitchable Distillate Capable of Using Adversely Affects Alternative Environmenta Contract Storage for Another Columns F, G, Code(a) Subsector and Industry Consumed as a Fue Fuel Oil Fuel Use

  12. Table 10.25 Reasons that Made Residual Fuel Oil Unswitchable, 2006;

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

    5 Reasons that Made Residual Fuel Oil Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Million barrels. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS Residual Fuel Oil Unswitchable ResiduaCapable of Using Adversely Affects Alternative Environmental Contract Storage for Another Columns F, G, Code(a) Subsector and Industry Consumed as a Fue Fuel Oil Fuel Use

  13. Level: National and Regional Data; Row: NAICS Codes, Value of Shipments and Employment Sizes;

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

    6 Capability to Switch Electricity to Alternative Energy Sources, 2010; Level: National and Regional Data; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Million Kilowatthours. Coal Coke NAICS Total Not Natural Distillate Residual and Code(a) Selected Subsectors and Industry Receipts(c) Switchable Switchable Gas Fuel Oil Fuel Oil Coal LPG Breeze Other(d) Total United States 311 Food 75,673 2,403 70,987 666 1,658 Q 406 Q Q 141 3112 Grain and Oilseed

  14. Other States Natural Gas Coalbed Methane, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    August 2009 Revised: October 2009 Next MECS will be conducted in 2010 Table 3.5 Selected Byproducts in Fuel Consumption, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Trillion Btu. Waste Blast Pulping Liquor Oils/Tars NAICS Furnace/Coke Petroleum or Wood Chips, and Waste Code(a) Subsector and Industry Total Oven Gases Waste Gas Coke Black Liquor Bark Materials Total United States 311 Food 10 0 3 0 0 7 Q 3112 Grain and Oilseed Milling 7 0 1 0 0 6 *

  15. Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes;

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

    0 Capability to Switch Coal to Alternative Energy Sources, 2006; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Thousand Short Tons. NAICS Total Not Electricity Natural Distillate Residual Code(a) Subsector and Industry Consumed(c) Switchable Switchable Receipts(d) Gas Fuel Oil Fuel Oil LPG Other(e) Total United States 311 Food 6,603 1,013 5,373 27 981 303 93 271 86 3112 Grain and Oilseed Milling 5,099 658 4,323

  16. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    3 Number of Establishments with Capability to Switch LPG to Alternative Energy Sources, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke NAICS Total Establishments Not Electricity Natural Distillate Residual and Code(a) Selected Subsectors and Industry Consuming LPG(d) Switchable Switchable Receipts(e) Gas Fuel Oil Fuel Oil Coal Breeze Other(f) Total United States 311 Food 4,039 600 2,860 356 221 Q W 0 0 16 3112 Grain and Oilseed Milling

  17. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    3 Number of Establishments with Capability to Switch Natural Gas to Alternative Energy Sources, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Natural Gas(b) Alternative Energy Sources(c) Coal Coke NAICS Total Establishments Not Electricity Distillate Residual and Code(a) Selected Subsectors and Industry Consuming Natural Gas(d Switchable Switchable Receipts(e) Fuel Oil Fuel Oil Coal LPG Breeze Other(f) Total United States 311 Food 10,373 1,667

  18. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    7 Number of Establishments with Capability to Switch Electricity to Alternative Energy Sources, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke NAICS Total Establishments Not Natural Distillate Residual and Code(a) Selected Subsectors and Industry with Electricity Receipts(d Switchable Switchable Gas Fuel Oil Fuel Oil Coal LPG Breeze Other(e) Total United States 311 Food 13,265 765 11,829 482 292 Q Q 51 Q Q 3112 Grain and Oilseed

  19. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    9 Number of Establishments with Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke NAICS Total Establishments Not Electricity Natural Residual and Code(a) Selected Subsectors and Industry Consuming Distillate Fuel Oil(d Switchable Switchable Receipts(e) Gas Fuel Oil Coal LPG Breeze Other(f) Total United States 311 Food 2,416 221 2,115 82 160 Q 0 Q 0 30 3112 Grain and

  20. Table 2.1 Nonfuel (Feedstock) Use of Combustible Energy, 2010;

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

    1 Nonfuel (Feedstock) Use of Combustible Energy, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Residual Distillate Natural Gas(c) LPG and Coal and Breeze NAICS Total Fuel Oil Fuel Oil(b) (billion NGL(d) (million (million Other(e) Code(a) Subsector and Industry (trillion Btu) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States 311 Food 10 * * 4 Q 0 0 2 3112 Grain and

  1. Table 3.6 Selected Wood and Wood-Related Products in Fuel Consumption, 2010;

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

    Table 3.6 Selected Wood and Wood-Related Products in Fuel Consumption, 2010; Level: National and Regional Data; Row: Selected NAICS Codes; Column: Energy Sources; Unit: Trillion Btu. Wood Residues and Wood-Related Pulping Liquor Wood Byproducts and NAICS or Biomass Agricultural Harvested Directly from Mill Paper-Related Code(a) Subsector and Industry Black Liquor Total(b) Waste(c) from Trees(d) Processing(e) Refuse(f) Total United States 311 Food 0 44 43 * * 1 311221 Wet Corn Milling 0 1 1 0 0 0

  2. Table 7.6 Quantity of Purchased Energy Sources, 2010;

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

    6 Quantity of Purchased Energy Sources, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Residual Distillate Natural Gas(c) LPG and Coal and Breeze NAICS Total Electricity Fuel Oil Fuel Oil(b) (billion NGL(d) (million (million Other(e) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States 311 Food 1,108 75,652 2 4

  3. Table 7.9 Expenditures for Purchased Energy Sources, 2010;

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

    9 Expenditures for Purchased Energy Sources, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Million U.S. Dollars. NAICS Residual Distillate LPG and Coke Code(a) Subsector and Industry Total Electricity Fuel Oil Fuel Oil(b) Natural Gas(c) NGL(d) Coal and Breeze Other(e) Total United States 311 Food 10,111 5,328 130 431 3,391 150 442 29 210 3112 Grain and Oilseed Milling 2,130 932 2 12 673 Q 294 0 158 311221 Wet Corn Milling 1,002 352 1 5 296 1 239 0 107

  4. Originally Released: August 2009

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

    August 2009 Revised: October 2009 Next MECS will be conducted in 2010 Table 3.5 Selected Byproducts in Fuel Consumption, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Trillion Btu. Waste Blast Pulping Liquor Oils/Tars NAICS Furnace/Coke Petroleum or Wood Chips, and Waste Code(a) Subsector and Industry Total Oven Gases Waste Gas Coke Black Liquor Bark Materials Total United States 311 Food 10 0 3 0 0 7 Q 3112 Grain and Oilseed Milling 7 0 1 0 0 6 *

  5. Originally Released: July 2009

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

    1 Nonfuel (Feedstock) Use of Combustible Energy, 2006 Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources Unit: Physical Units or Btu. Coke Residual Distillate Natural Gas(c) LPG and Coal and Breeze NAICS Total Fuel Oil Fuel Oil(b) (billion NGL(d) (million (million Other(e) Code(a) Subsector and Industry (trillion Btu) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States 311 Food 3 0 * 2 * 0 * * 3112 Grain and Oilseed

  6. Originally Released: July 2009

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

    2 Nonfuel (Feedstock) Use of Combustible Energy, 2006 Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources Unit: Trillion Btu. NAICS Residual Distillate LPG and Coke Code(a) Subsector and Industry Total Fuel Oil Fuel Oil(b) Natural Gas(c) NGL(d) Coal and Breeze Other(e) Total United States 311 Food 3 0 * 2 * 0 * * 3112 Grain and Oilseed Milling 3 0 * 2 * 0 0 * 311221 Wet Corn Milling * 0 0 0 0 0 0 * 31131 Sugar Manufacturing * 0 * 0 * 0 * 0 3114 Fruit and Vegetable

  7. Originally Released: July 2009

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

    1 Fuel Consumption, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources Unit: Physical Units or Btu Coke Net Residual Distillate Natural Gas(d) LPG and Coal and Breeze NAICS Total Electricity(b) Fuel Oil Fuel Oil(c) (billion NGL(e) (million (million Other(f) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States 311 Food 1,186 73,440 4 3 618 1 7 * 107

  8. Originally Released: July 2009

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

    2 Fuel Consumption, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources Unit: Trillion Btu. NAICS Net Residual Distillate LPG and Coke Code(a) Subsector and Industry Total Electricity(b) Fuel Oil Fuel Oil(c) Natural Gas(d) NGL(e) Coal and Breeze Other(f) Total United States 311 Food 1,186 251 26 16 635 3 147 1 107 3112 Grain and Oilseed Milling 317 53 2 1 118 * 114 0 30 311221 Wet Corn Milling 179 23 * * 52 * 95 0 9 31131 Sugar Manufacturing 82 3 9 1 18 * 31 1 20

  9. Originally Released: July 2009

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

    4.1 Offsite-Produced Fuel Consumption, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Residual Distillate Natural Gas(d) LPG and Coal and Breeze NAICS Total Electricity(b) Fuel Oil Fuel Oil(c) (billion NGL(e) (million (million Other(f) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States 311 Food 1,124 73,551 4 3

  10. Originally Released: July 2009

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

    2 Offsite-Produced Fuel Consumption, 2006 Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources Unit: Trillion Btu. NAICS Residual Distillate LPG and Coke Code(a) Subsector and Industry Total Electricity(b) Fuel Oil Fuel Oil(c) Natural Gas(d) NGL(e) Coal and Breeze Total United States 311 Food 1,124 251 26 16 635 3 147 1 3112 Grain and Oilseed Milling 316 53 2 1 118 * 114 0 311221 Wet Corn Milling 179 23 * * 52 * 95 0 31131 Sugar Manufacturing 67 3 9 1 18 * 31 1 3114 Fruit

  11. Table 3. Annual commercial spent fuel discharges and burnup

    Gasoline and Diesel Fuel Update (EIA)

    1 Nonfuel (Feedstock) Use of Combustible Energy, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Residual Distillate Natural Gas(c) LPG and Coal and Breeze NAICS Total Fuel Oil Fuel Oil(b) (billion NGL(d) (million (million Other(e) Code(a) Subsector and Industry (trillion Btu) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States 311 Food 10 * * 4 Q 0 0 2 3112 Grain and

  12. Table 35. U.S. Coal Consumption at Manufacturing Plants by North American Industry Classification System (NAICS) Code

    Gasoline and Diesel Fuel Update (EIA)

    1 Fuel Consumption, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Net Residual Distillate Natural Gas(d) LPG and Coal and Breeze NAICS Total Electricity(b) Fuel Oil Fuel Oil(c) (billion NGL(e) (million (million Other(f) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States 311 Food 1,158 75,407 2 4 563 1 8 * 99

  13. Integrating Electricity Subsector Failure Scenarios into a Risk...

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

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  14. "Code(a)","Subsector and Industry","Source(b)","Electricity(c...

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

    ... " NFNo applicable RSE rowcolumn factor." " * Estimate less than 0.5." " ... of a purchase or transfer and consumed onsite for the" "production of heat and power. ...

  15. RSE Table 1.1 Relative Standard Errors for Table 1.1

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

    Oil","Fuel Oil(d)","Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)" ,,"Total United States" 311,"Food",4,5,25,20,5,27,6,0,10,0 311221," Wet Corn ...

  16. RSE Table 1.2 Relative Standard Errors for Table 1.2

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

    Oil","Fuel Oil(d)","Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)" ,,"Total United States" 311,"Food",4,5,25,20,5,27,6,0,10,0 311221," Wet Corn ...

  17. Released: July 2009

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

    Oil","Fuel Oil(d)","Natural Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)" ,,"Total United States" 311,"Food",5.5,4.1,21.5,13.1,7.1,15.7,1.1,0,36.5,0 3112," Grain ...

  18. Released: July 2009

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

    Oil","Fuel Oil(d)","Natural Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)" ,,"Total United States" 311,"Food",5.5,4.1,21.5,13.1,7.1,15.6,1.1,0,36.5,0 3112," Grain ...

  19. Microsoft Word - ClearPathIV_Exercise Summary Report_Public Release...

    Energy Savers [EERE]

    ... Center Electricity Subsector Coordinating Council Association International Partners Israel National Emergency Management Authority Natural Resources Canada Pontificia ...

  20. Okmulgee Extended Facility

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

    (ONG-C2M2) | Department of Energy Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) The Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) was established as a result of the Administration's efforts to improve electricity subsector cybersecurity capabilities, and to

  1. EIA Energy Efficiency-Table 1d. Nonfuel Consumption (Site Energy...

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

    d Page Last Modified: May 2010 Table 1d. Nonfuel Consumption (Site Energy) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) MECS Survey Years NAICS Subsector and...

  2. EAC Recommendations for DOE Action Regarding Implementing Effective...

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

    DOE Responses to EAC Work Products - June 2014 Electricity Advisory Committee Meeting Presentations June 2013 - Wednesday, June 5, 2013 Electricity Subsector Cybersecurity ...

  3. Plastics and Rubber Products (2010 MECS) | Department of Energy

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

    The energy pathway-from primary sources (fuel, steam, and electricity) to facility end use-is shown ... of energy use or compare energy consumption across manufacturing subsectors. ...

  4. Static Sankey Diagram Full Sector Manufacturing | Department...

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

    consumption across manufacturing subsectors. The U.S. Manufacturing diagram below shows the fuel, steam and electricity ... Applied energy (applied toward direct production or end use ...

  5. Energy Analysis by Sector | Department of Energy

    Office of Environmental Management (EM)

    flows to major energy end uses in manufacturing and line colors indicate fuel, steam, electricity, and applied or lost ... compare energy consumption across manufacturing subsectors. ...

  6. Petroleum Refining (2010 MECS) | Department of Energy

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

    The energy pathway-from primary sources (fuel, steam, and electricity) to facility end use-is shown ... of energy use or compare energy consumption across manufacturing subsectors. ...

  7. Glass and Glass Products (2010 MECS) | Department of Energy

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

    The energy pathway-from primary sources (fuel, steam, and electricity) to facility end use-is shown ... of energy use or compare energy consumption across manufacturing subsectors. ...

  8. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

    Gasoline and Diesel Fuel Update (EIA)

    2009. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 418 435 457 312 Beverage and Tobacco Product Manufacturing 134 116 125 313 Textile...

  9. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

    Gasoline and Diesel Fuel Update (EIA)

    Dollars) MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 430 468 552 312 Beverage and Tobacco Product Manufacturing 98 120 131 313 Textile...

  10. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

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

    2009. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 417 444 526 312 Beverage and Tobacco Product Manufacturing 114 128 144 313 Textile...

  11. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

    Gasoline and Diesel Fuel Update (EIA)

    Dollars ) MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 431 447 473 312 Beverage and Tobacco Product Manufacturing 122 96 109 313 Textile...

  12. " Row: NAICS Codes; Column: Energy Sources...

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

    and",,"Coke"," ","Row" "Code(a)","Subsector and ... 324,"Petroleum and Coal ... Division, Form EIA-810, 'Monthly Refinery Report' for 2002.

  13. " Row: NAICS Codes; Column: Energy Sources...

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

    Energy Sources","Row" "Code(a)","Subsector and ... 324,"Petroleum and Coal ... Division, Form EIA-810, 'Monthly Refinery Report' for 2002.

  14. "RSE Table C3.1. Relative Standard Errors for Table C3.1;...

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

    ... and Office of Oil and Gas, Petroleum" "Supply Division, Form EIA-810, 'Monthly Refinery Report' for 1998." ... and",,"Coke"," " "Code(a)","Subsector and ...

  15. Reducing Cyber Risk to Critical Infrastructure: NIST Framework...

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

    Cyber Community C Voluntary Program Electricity Subsector Cybersecurity Risk Management ... November 3, 2015 National Critical Infrastructure Security and Resilience Month: Improving ...

  16. The ARRA EAP Energy Assurance Planning Bulletin

    Office of Environmental Management (EM)

    the recently completed Electricity Subsector Cybersecurity Capability Maturity Model. ... Richard Reed, Vice President of Preparedness and Resilience Strategy for the American Red ...

  17. table1.3_02.xls

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

    3 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources and Shipments; Unit: Trillion Btu. Shipments RSE Economic Net Residual Distillate Natural LPG and Coke and of Energy Sources Row Characteristic(a) Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Factors Total United States RSE Column Factors: 0.8 0.9 1.4 2.7 0.8 0.6 2 1.4 1.1

  18. Table 1.3 First Use of Energy for All Purposes (Fuel and Nonfuel), 2010;

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

    1.3 First Use of Energy for All Purposes (Fuel and Nonfuel), 2010; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources and Shipments; Unit: Trillion Btu. Shipments Economic Net Residual Distillate LPG and Coke and of Energy Sources Characteristic(a) Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Total United States Value of Shipments and Receipts (million dollars) Under 20 1,169 314 6

  19. OMB CEQ Joint Statement_1.pdf

    Office of Environmental Management (EM)

    OIL AND NATURAL GAS SUBSECTOR CYBERSECURITY CAPABILITY MATURITY MODEL (ONG-C2M2) Version 1.1 February 2014 Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model Version 1.1 iii TABLE OF CONTENTS Acknowledgments ......................................................................................................................................... v 1. Introduction

  20. Level: National Data; Row: General Energy-Management Activities within NAICS Codes;

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

    Next MECS will be fielded in 2015 Table 8.1 Number of Establishments by Participation in General Energy-Management Activities, 2010; Level: National Data; Row: General Energy-Management Activities within NAICS Codes; Column: Participation and Source of Assistance; Unit: Establishment Counts. NAICS Code(a) Energy-Management Activity No Participation Participation(b) In-house Utility/Energy Suppler Product/Service Provider Federal Program State/Local Program Don't Know Total United States 311 -

  1. EIA Energy Efficiency-Table 4b. Value of Production by Selected...

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

    b Page Last Modified: May 2010 Table 4b. Value of Production 1 by Selected Industries, 1998, 2002, and 2006 (Billion 2000 Dollars ) MECS Survey Years NAICS Subsector and Industry...

  2. EIA Energy Efficiency-Table 4a. Value of Shipments by Selected...

    Gasoline and Diesel Fuel Update (EIA)

    Table 4a Page Last Modified: May 2010 Table 4a. Value of Shipments1 by Selected Industries, 1998, 2002, and 2006 (Billion 2000 Dollars ) MECS Survey Years NAICS Subsector and...

  3. EIA Energy Efficiency-Table 3d. Value Added by Selected Industries...

    Gasoline and Diesel Fuel Update (EIA)

    d Page Last Modified: May 2010 Table 3d. Value Added1 by Selected Industries, 1998, 2002, and 2006 (Current Brillion Dollars) MECS Survey Years NAICS Subsector and Industry 1998...

  4. EIA Energy Efficiency-Table 3a. Value of Shipments by Selected...

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

    a Page Last Modified: May 2010 Table 3a. Value of Shipments 1 by Selected Industries, 1998, 2002, and 2006 (Current Billion Dollars) MECS Survey Years NAICS Subsector and Industry...

  5. EIA Energy Efficiency-Table 4d. Value Added by Selected Industries...

    Gasoline and Diesel Fuel Update (EIA)

    d Page Last Modified: May 2010 Table 4d. Value Added1 by Selected Industries, 1998, 2002, and 2006 (Billion 2000 Dollars 2) MECS Survey Years NAICS Subsector and Industry 1998 2002...

  6. 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...

  7. EIA Energy Efficiency-Table 4f. Industrial Production Indexes...

    Gasoline and Diesel Fuel Update (EIA)

    f Page Last Modified: May 2010 Table 4f. Industrial Production Indexes by Selected Industries, 1998, 2002, and 2006 (2000 100) MECS Survey Years NAICS Subsector and Industry 1998...

  8. Table 1c. Off-Site Produced Energy (Site Energy)For Selected...

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

    c Page Last Modified: May 2010 Table 1c. Off-Site Produced Energy (Site Energy) for Selected Industries, 1998, 2002 and 2006 (Trillion Btu) MECS Survey Years NAICS Subsector and...

  9. EIA Energy Efficiency-Table 4e. Gross Output by Selected Industries...

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

    e Page Last Modified: May 2010 Table 4e. Gross Output1by Selected Industries, 1998, 2002, and 2006 (Billion 2000 Dollars 2) MECS Survey Years NAICS Subsector and Industry 1998 2002...

  10. EIA Energy Efficiency-Table 3e. Gross Output by Selected Industries...

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

    e Page Last Modified: May 2010 Table 3e. Gross Output1 by Selected Industries, 1998, 2002, and 2006 (Current Billion Dollars) MECS Survey Years NAICS Subsector and Industry 1998...

  11. New Report Charts Dynamic, Steady Growth of the U.S. Solar Jobs...

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

    Rounding out the top three largest subsectors is the sales and distribution industry -- which has grown to more than 16,000 skilled workers. With public and private innovation ...

  12. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

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    Table 6. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 429 456 539 312 Beverage and Tobacco Product Manufacturing 103 104 125 313 Textile...

  13. DYNAMIC MANUFACTURING ENERGY FLOWS TOOL (2010, UNITS: TRILLION...

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

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  14. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

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    Sept 2009. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 430 448 472 312 Beverage and Tobacco Product Manufacturing 121 96 109 313 Textile...

  15. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

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    Table 2. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 428 460 537 312 Beverage and Tobacco Product Manufacturing 102 106 124 313 Textile...

  16. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

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

    2009. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 97.3 102.6 107.9 312 Beverage and Tobacco Product Manufacturing 109.0 90.0 99.4...

  17. New Draft of Cybersecurity Risk Management Process (RMP) Guideline Now Available for Public Comment (March 2012)

    Broader source: Energy.gov [DOE]

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  18. Economic and Environmental Impacts of Increased US Exports of...

    Energy Savers [EERE]

    ... Finally, we examine the impacts on the use of CNG in the transport sector. The CES virtually eliminates the use of CNG or LNG in the heavy duty truck sub-sector as shown in Figure ...

  19. PowerPoint Presentation

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

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  20. Testimony of Gerry Cauley, President and Chief Executive Officer

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

    ... As NERC's CEO, I am a member of the ESCC, which coordinates policy-related activities and initiatives to improve the reliability and resilience of the Electricity Sub-sector. The ...

  1. Market Report for the Industrial Sector, 2009

    SciTech Connect (OSTI)

    Sastri, Bhima; Brueske, Sabine; de los Reyes, Pamela; Jamison, Keith; Justiniano, Mauricio; Margolis, Nancy; Monfort, Joe; Raghunathan, Anand; Sabouni, Ridah

    2009-07-01

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  2. Research Highlight

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

    and for divided sub-sectors (DF1 and DF2) in dust-free sector. Also PR estimated rain rate profiles with standard errors in dusty and dust-free sectors for both case and...

  3. Cybersecurity Risk Management Process (RMP) | Department of Energy

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

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  4. table8.1_02.xls

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

    1 Number of Establishments by Participation in Energy-Management Activity, 2002 Level: National Data; Row: Energy-Management Activities within NAICS Codes; Column: Participation and Source of Financial Support for Activity; Unit: Establishment Counts. RSE NAICS Row Code(a) Energy-Management Activity No Participation Participation(b) In-house Other Don't Know Factors Total United States RSE Column Factors: 0.9 1.4 0.9 0.9 1 311 - 339 ALL MANUFACTURING INDUSTRIES Participation in One or More of

  5. Level: National Data; Row: Specific Energy-Management Activities within NAICS Codes;

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

    Next MECS will be conducted in 2010 Table 8.4 Number of Establishments by Participation in Specific Energy-Management Activities, 2006; Level: National Data; Row: Specific Energy-Management Activities within NAICS Codes; Column: Participation; Unit: Establishment Counts. NAICS Code(a) Energy-Management Activity No Participation Participation(b) Don't Know Not Applicable Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES Full-Time Energy Manager (c) 159,258 9,922 25,553 -- Set Goals for

  6. Level: National Data; Row: Specific Energy-Management Activities within NAICS Codes;

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

    Next MECS will be fielded in 2015 Table 8.4 Number of Establishments by Participation in Specific Energy-Management Activities, 2010; Level: National Data; Row: Specific Energy-Management Activities within NAICS Codes; Column: Participation; Unit: Establishment Counts. NAICS Code(a) Energy-Management Activity No Participation Participation(b) Don't Know No Steam Used Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES Full-Time Energy Manager (c) 142,267 12,536 15,365 -- Set Goals for

  7. Energy Emergency Energy Emergency Preparedness Quarterly Preparedness...

    Energy Savers [EERE]

    ... about the RMP, or the ES-C2M2 at http:energy.govsitesprodfilesElectricity%20Subsector% 20Cybersecurity%20Capabilities%20Maturity%20Model%20%28ES-C2M2%29%20-%20May%202012.pdf. ...

  8. QTR Webinar: Chapter 8 - Industry and Manufacturing | Department of Energy

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

    Webinar: Chapter 8 - Industry and Manufacturing QTR Webinar: Chapter 8 - Industry and Manufacturing Background The U.S. industrial sector accounts for approximately one-third of the overall energy consumption and associated carbon emissions in the U.S. About four-fifths of end-use industrial energy is consumed by the manufacturing sub-sector, which produces goods ranging from fundamental commodities to sophisticated final-use products. Many of these products have a significant energy and carbon

  9. Recommendations on U. S. Grid Security - EAC 2011 | Department of Energy

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

    on U. S. Grid Security - EAC 2011 Recommendations on U. S. Grid Security - EAC 2011 Recommendations from the Electricity Advisory Committee on actions to be taken by the Department of Energy to compliment the North American Electric Reliability Corporation's (NERC's) Critical Infrastructure Strategic Roadmap developed by the Electricity Sub-Sector Coordinating Council and approved by the NERC Board of Trustees in November 2010. EAC Recommendations on U. S. Grid Security Oct 2011.pdf (110.71 KB)

  10. Roadmap to Achieve Energy Delivery Systems Cybersecurity

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

    Roadmap to Achieve Energy Delivery Systems Cybersecurity ii Acknowledgements The Energy Sector Control Systems Working Group (ESCSWG) developed this roadmap in support of the Electricity Sub-sector Coordinating Council, Oil and Natural Gas Sector Coordinating Council, and the Government Coordinating Council for Energy under the Critical Infrastructure Partnership Advisory Council (CIPAC) Framework; the roadmap has been approved for release by these councils. The ESCSWG members volunteered their

  11. Industry sector analysis: The market for renewable energy resources (the Philippines). Export trade information

    SciTech Connect (OSTI)

    Cannon, E.; Miranda, A.L.

    1990-08-01

    The market survey covers the renewable energy resources market in the Philippines. Sub-sectors covered include biomass, solar energy, photovoltaic cells, windmills, and mini-hydro systems. The analysis contains statistical and narrative information on projected market demand, end-users; receptivity of Philippine consumers to U.S. products; the competitive situation, and market access (tariffs, non-tariff barriers, standards, taxes, distribution channels). It also contains key contact information.

  12. " Row: NAICS Codes; Column: Energy Sources;"

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

    2 Offsite-Produced Fuel Consumption, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Trillion Btu." "NAICS",,,,,,"Residual","Distillate",,,"LPG and",,,"Coke" "Code(a)","Subsector and Industry","Total",,"Electricity(b)",,"Fuel Oil","Fuel Oil(c)","Natural

  13. " Row: NAICS Codes; Column: Energy Sources;"

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

    2 Offsite-Produced Fuel Consumption, 2010;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Trillion Btu." "NAICS",,,,"Residual","Distillate",,"LPG and",,"Coke" "Code(a)","Subsector and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural

  14. Energy Intensity Indicators: Overview of Concepts | Department of Energy

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

    Overview of Concepts Energy Intensity Indicators: Overview of Concepts 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 sectors, associated subsector for the economy as whole (economywide). Following the conventions used by the Department of Energy's Energy Information Administration, the four major end-use sectors are 1) residential, 2) commercial,

  15. Energy-Related Carbon Dioxide Emissions in U.S. Manufacturing

    Reports and Publications (EIA)

    2006-01-01

    Based on the Manufacturing Energy Consumption Survey (MECS) conducted by the U.S. Department of Energy, Energy Information Administration (EIA), this paper presents historical energy-related carbon dioxide emission estimates for energy-intensive sub-sectors and 23 industries. Estimates are based on surveys of more than 15,000 manufacturing plants in 1991, 1994, 1998, and 2002. EIA is currently developing its collection of manufacturing data for 2006.

  16. 2016 Animal Responses to Light Meeting Report | Department of Energy

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

    U.S. Department of Energy (DOE), as the Sector-Specific Agency for the Energy Sector, has worked closely with government and industry partners to develop the 2015 Energy Sector-Specific Plan (SSP). DOE conducted much of this work in collaboration with the Energy Sector Coordinating Councils (SCCs) and the Energy Government Coordinating Council (GCC). The Energy SCCs represent the interests of the Electricity and Oil and Natural Gas Subsectors; the Energy GCC represents government at various

  17. RSE Table 10.12 Relative Standard Errors for Table 10.12

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

    2 Relative Standard Errors for Table 10.12;" " Unit: Percents." ,,"LPG",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,"and" "Code(a)","Subsector and

  18. RSE Table 10.13 Relative Standard Errors for Table 10.13

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

    3 Relative Standard Errors for Table 10.13;" " Unit: Percents." ,,"LPG(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,"and" "Code(a)","Subsector and

  19. RSE Table 7.6 Relative Standard Errors for Table 7.6

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

    6 Relative Standard Errors for Table 7.6;" " Unit: Percents." " "," " " "," ",,,,,,,,," " "NAICS"," "," ",,"Residual","Distillate","Natural ","LPG and",,"Coke" "Code(a)","Subsector and Industry","Total","Electricity","Fuel Oil","Fuel

  20. RSE Table 8.2 Relative Standard Errors for Table 8.2

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

    2 Relative Standard Errors for Table 8.2;" " Unit: Percents." " "," ",,"Computer Control of Building Wide Evironment(c)",,,"Computer Control of Processes or Major Energy-Using Equipment(d)",,,"Waste Heat Recovery",,,"Adjustable - Speed Motors",,,"Oxy - Fuel Firing" " "," " "NAICS"," " "Code(a)","Subsector and

  1. Released: June 2010

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

    3 Relative Standard Errors for Table 10.13;" " Unit: Percents." ,,"LPG(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,"and" "Code(a)","Subsector and

  2. Released: March 2013

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

    3 Electricity: Components of Onsite Generation, 2010;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Onsite-Generation Components;" " Unit: Million Kilowatthours." " "," ",,,"Renewable Energy" " "," ",,,"(excluding Wood" "NAICS"," ","Total Onsite",,"and" "Code(a)","Subsector and

  3. Released: October 2009

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

    3 Electricity: Components of Onsite Generation, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Onsite-Generation Components;" " Unit: Million Kilowatthours." " "," ",,,"Renewable Energy" " "," ",,,"(excluding Wood" "NAICS"," ","Total Onsite",,"and" "Code(a)","Subsector and

  4. Cybersecurity Capability Maturity Model (C2M2) Program | Department of

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

    Energy Program Cybersecurity Capability Maturity Model (C2M2) Program Cybersecurity Capability Maturity Model (C2M2) Program The Cybersecurity Capability Maturity Model (C2M2) program is a public-private partnership effort that was established as a result of the Administration's efforts to improve electricity subsector cybersecurity capabilities, and to understand the cybersecurity posture of the grid. The C2M2 helps organizations-regardless of size, type, or industry-evaluate, prioritize,

  5. Cybersecurity Risk Management Process (RMP) Guideline - Final (May 2012) |

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

    Department of Energy Risk Management Process (RMP) Guideline - Final (May 2012) Cybersecurity Risk Management Process (RMP) Guideline - Final (May 2012) This electricity subsector cybersecurity Risk Management Process (RMP) guideline was developed by the Department of Energy, in collaboration with the National Institute of Standards and Technology (NIST) and the North American Electric Reliability Corporation (NERC). The RMP is written with the goal of enabling organizations- regardless of

  6. DOE Releases Maturity Model to Better Protect the Nation's Grid from

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

    Cybersecurity Threats | Department of Energy Maturity Model to Better Protect the Nation's Grid from Cybersecurity Threats DOE Releases Maturity Model to Better Protect the Nation's Grid from Cybersecurity Threats May 31, 2012 - 4:32pm Addthis The Electricity Subsector Cybersecurity Capability Maturity Model, which allows electric utilities and grid operators to assess their cybersecurity capabilities and prioritize their actions and investments to improve cybersecurity, combines elements

  7. 2006 Update of Business Downtime Costs

    SciTech Connect (OSTI)

    Hinrichs, Mr. Doug; Goggin, Mr. Michael

    2007-01-01

    The objective of this paper is to assess the downtime cost of power outages to businesses in the commercial and industrial sectors, updating and improving upon studies that have already been published on this subject. The goal is to produce a study that, relative to existing studies, (1) applies to a wider set of business types (2) reflects more current downtime costs, (3) accounts for the time duration factor of power outages, and (4) includes data on the costs imposed by real outages in a well-defined market. This study examines power outage costs in 11 commercial subsectors and 5 industrial subsectors, using data on downtime costs that was collected in the 1990's. This study also assesses power outage costs for power outages of 20 minutes, 1 hour, and 4 hours duration. Finally, this study incorporates data on the costs of real power outages for two business subsectors. However, the current limited state of data availability on the topic of downtime costs means there is room to improve upon this study. Useful next steps would be to generate more recent data on downtime costs, data that covers outages shorter than 20 minutes duration and longer than 4 hours duration, and more data that is based on the costs caused by real-world outages. Nevertheless, with the limited data that is currently available, this study is able to generate a clear and detailed picture of the downtime costs that are faced by different types of businesses.

  8. Class of supersymmetric solitons with naked singularities

    SciTech Connect (OSTI)

    Cvetic, M.; Youm, D. )

    1995-02-15

    We study vacuum domain walls in a class of four-dimensional [ital N]=1 supergravity theories where along with the matter field, forming the wall, there is more than one dilaton,'' each respecting SU(1,1) symmetry in their subsector. We find [ital supersymmetric] (planar, static) walls, interpolating between a Minkowski vacuum and a new class of supersymmetric vacua which have a naked (planar) singularity. Although such walls correspond to idealized configurations, i.e., they correspond to planar configurations of infinite extent, they provide the first example of supersymmetric classical solitons with naked singularities.

  9. Bandwidth Study on Energy Use and Potential Energy Saving Opportunities in U.S. Chemical Manufacturing

    SciTech Connect (OSTI)

    Sabine Brueske, Caroline Kramer, Aaron Fisher

    2015-06-01

    Energy bandwidth studies of U.S. manufacturing sectors can serve as foundational references in framing the range (or bandwidth) of potential energy savings opportunities. This bandwidth study examines energy consumption and potential energy savings opportunities in U.S. chemical manufacturing. The study relies on multiple sources to estimate the energy used in the production of 74 individual chemicals, representing 57% of sector-wide energy consumption. Energy savings opportunities for individual chemicals and for 15 subsectors of chemicals manufacturing are based on technologies currently in use or under development; these potential savings are then extrapolated to estimate sector-wide energy savings opportunity.

  10. " Row: NAICS Codes; Column: Energy-Consumption Ratios;"

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

    1 Consumption Ratios of Fuel, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy-Consumption Ratios;" " Unit: Varies." ,,,,"Consumption" ,,,"Consumption","per Dollar" ,,"Consumption","per Dollar","of Value" "NAICS",,"per Employee","of Value Added","of Shipments" "Code(a)","Subsector and Industry","(million

  11. "RSE Table N13.3. Relative Standard Errors for Table N13.3;"

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

    3. Relative Standard Errors for Table N13.3;" " Unit: Percents." " "," ","Total of" "NAICS"," ","Sales and","Utility","Nonutility" "Code(a)","Subsector and Industry","Transfers Offsite","Purchaser(b)","Purchaser(c)" ,,"Total United States" , 311,"Food",8,9,0 311221," Wet Corn Milling",0,0,0 312,"Beverage and Tobacco

  12. 311221," Wet Corn Milling",0,0,0,0,0

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

    1.1 Relative Standard Errors for Table 11.1;" " Unit: Percents." " "," " " "," ",,,"Total ","Sales and","Net Demand" "NAICS"," ",,"Transfers ","Onsite","Transfers","for" "Code(a)","Subsector and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)" ,,"Total

  13. 3219," Other Wood Products",0,0,0

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

    5 Relative Standard Errors for Table 11.5;" " Unit: Percents." " "," " " "," ","Total of" "NAICS"," ","Sales and","Utility","Nonutility" "Code(a)","Subsector and Industry","Transfers Offsite","Purchaser(b)","Purchaser(c)" ,,"Total United States" 311,"Food",25,34,35 311221," Wet Corn Milling",29,40,7

  14. RSE Table 10.10 Relative Standard Errors for Table 10.10

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

    0 Relative Standard Errors for Table 10.10;" " Unit: Percents." ,,"Coal",,,"Alternative Energy Sources(b)" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual" "Code(a)","Subsector and Industry","Consumed(c)","Switchable","Switchable","Receipts(d)","Gas","Fuel

  15. RSE Table 10.11 Relative Standard Errors for Table 10.11

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

    1 Relative Standard Errors for Table 10.11;" " Unit: Percents." ,,"Coal(b)",,,"Alternative Energy Sources(c)" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual" "Code(a)","Subsector and Industry","Consumed(d)","Switchable","Switchable","Receipts(e)","Gas","Fuel

  16. RSE Table 2.1 Relative Standard Errors for Table 2.1

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

    2.1 Relative Standard Errors for Table 2.1;" " Unit: Percents." " "," " " "," " "NAICS"," "," ","Residual","Distillate","Natural ","LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","and

  17. RSE Table 7.9 Relative Standard Errors for Table 7.9

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

    9 Relative Standard Errors for Table 7.9;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," ",," " " "," " "NAICS"," "," ",,"Residual","Distillate","Natural ","LPG and",,"Coke"," " "Code(a)","Subsector and

  18. RSE Table N2.1 and N2.2. Relative Standard Errors for Tables N2.1 and N2.2

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

    N2.1 and N2.2. Relative Standard Errors for Tables N2.1 and N2.2;" " Unit: Percents." " "," " "NAICS"," "," ","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","and Breeze","Other(e)"

  19. RSE Table N3.1 and N3.2. Relative Standard Errors for Tables N3.1 and N3.2

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

    N3.1 and N3.2. Relative Standard Errors for Tables N3.1 and N3.2;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," ",," " "NAICS"," "," ","Net","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and

  20. RSE Table N4.1 and N4.2. Relative Standard Errors for Tables N4.1 and N4.2

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

    N4.1 and N4.2. Relative Standard Errors for Tables N4.1 and N4.2;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," ",," " "NAICS"," "," ",,"Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and

  1. Released: August 2009

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

    5 Relative Standard Errors for Table 3.5;" " Unit: Percents." ,,,,,,,,"Waste",," " ,,,"Blast",,,"Pulping Liquor",,"Oils/Tars" "NAICS",,,"Furnace/Coke",,"Petroleum","or","Wood Chips,","and Waste" "Code(a)","Subsector and Industry","Total","Oven Gases","Waste Gas","Coke","Black

  2. Released: February 2010

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

    2 Relative Standard Errors for Table 8.2;" " Unit: Percents." ,,,"Computer Control of Building Wide Evironment(c)",,,"Computer Control of Processes or Major Energy-Using Equipment(d)",,,"Waste Heat Recovery",,,"Adjustable - Speed Motors",,,"Oxy - Fuel Firing",,,," " "NAICS" "Code(a)","Subsector and Industry","Establishments(b)","In Use(e)","Not in

  3. Released: July 2009

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

    1 Relative Standard Errors for Table 2.1, 2006;" " Unit: Percents." " "," " " "," " "NAICS"," "," ","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","and

  4. Released: July 2009

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

    2 Relative Standard Errors for Table 3.2, 2006;" " Unit: Percents." " "," " "NAICS"," "," ","Net","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","NGL(e)","Coal","and

  5. Released: June 2010

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

    1 Relative Standard Errors for Table 10.11;" " Unit: Percents." ,,"Coal(b)",,,"Alternative Energy Sources(c)" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual" "Code(a)","Subsector and Industry","Consumed(d)","Switchable","Switchable","Receipts(e)","Gas","Fuel

  6. Released: March 2013

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

    5 Electricity: Sales to Utility and Nonutility Purchasers, 2010;" " Level: National and Regional Data; " " Row: NAICS Codes;" " Column: Utility and Nonutility Purchasers;" " Unit: Million Kilowatthours." " "," " " "," ","Total of" "NAICS"," ","Sales and","Utility","Nonutility" "Code(a)","Subsector and Industry","Transfers

  7. Released: October 2009

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

    5 Electricity: Sales to Utility and Nonutility Purchasers, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes;" " Column: Utility and Nonutility Purchasers;" " Unit: Million Kilowatthours." " "," " " "," ","Total of" "NAICS"," ","Sales and","Utility","Nonutility" "Code(a)","Subsector and Industry","Transfers

  8. Cybersecurity Capability Maturity Model (February 2014) | Department of

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

    Energy (February 2014) Cybersecurity Capability Maturity Model (February 2014) The Cybersecurity Capability Maturity Model (C2M2) was derived from the Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Version 1.1 by removing sector-specific references and terminology. The ES-C2M2 was developed in support of a White House initiative led by the Department of Energy (DOE), in partnership with the Department of Homeland Security (DHS), and in collaboration with private- and

  9. Energy Efficiency Services Sector: Workforce Education and Training Needs

    SciTech Connect (OSTI)

    Goldman, Charles A.; Peters, Jane S.; Albers, Nathaniel; Stuart, Elizabeth; Fuller, Merrian C.

    2010-03-19

    This report provides a baseline assessment of the current state of energy efficiency-related education and training programs and analyzes training and education needs to support expected growth in the energy efficiency services workforce. In the last year, there has been a significant increase in funding for 'green job' training and workforce development (including energy efficiency), through the American Recovery and Reinvestment Act (ARRA). Key segments of the energy efficiency services sector (EESS) have experienced significant growth during the past several years, and this growth is projected to continue and accelerate over the next decade. In a companion study (Goldman et al. 2009), our research team estimated that the EESS will increase two- to four-fold by 2020, to 220,000 person-years of employment (PYE) (low-growth scenario) or up to 380,000 PYE (high-growth scenario), which may represent as many as 1.3 million individuals. In assessing energy efficiency workforce education and training needs, we focus on energy-efficiency services-related jobs that are required to improve the efficiency of residential and nonresidential buildings. Figure ES-1 shows the market value chain for the EESS, sub-sectors included in this study, as well as the types of market players and specific occupations. Our assessment does not include the manufacturing, wholesale, and retail distribution subsectors, or energy efficiency-focused operations and maintenance performed by facility managers.

  10. Constructing vulnerabilty and protective measures indices for the enhanced critical infrastructure protection program.

    SciTech Connect (OSTI)

    Fisher, R. E.; Buehring, W. A.; Whitfield, R. G.; Bassett, G. W.; Dickinson, D. C.; Haffenden, R. A.; Klett, M. S.; Lawlor, M. A.; Decision and Information Sciences; LANL

    2009-10-14

    The US Department of Homeland Security (DHS) has directed its Protective Security Advisors (PSAs) to form partnerships with the owners and operators of assets most essential to the Nation's well being - a subclass of critical infrastructure and key resources (CIKR) - and to conduct site visits for these and other high-risk assets as part of the Enhanced Critical Infrastructure Protection (ECIP) Program. During each such visit, the PSA documents information about the facility's current CIKR protection posture and overall security awareness. The primary goals for ECIP site visits (DHS 2009) are to: (1) inform facility owners and operators of the importance of their facilities as an identified high-priority CIKR and the need to be vigilant in light of the ever-present threat of terrorism; (2) identify protective measures currently in place at these facilities, provide comparisons of CIKR protection postures across like assets, and track the implementation of new protective measures; and (3) enhance existing relationships among facility owners and operators; DHS; and various Federal, State, local tribal, and territorial partners. PSAs conduct ECIP visits to assess overall site security; educate facility owners and operators about security; help owners and operators identify gaps and potential improvements; and promote communication and information sharing among facility owners and operators, DHS, State governments, and other security partners. Information collected during ECIP visits is used to develop metrics; conduct sector-by-sector and cross-sector vulnerability comparisons; identify security gaps and trends across CIKR sectors and subsectors; establish sector baseline security survey results; and track progress toward improving CIKR security through activities, programs, outreach, and training (Snyder 2009). The data being collected are used in a framework consistent with the National Infrastructure Protection Plan (NIPP) risk criteria (DHS 2009). The NIPP

  11. Exploring the Potential Business Case for Synergies Between Natural Gas and Renewable Energy

    SciTech Connect (OSTI)

    Cochran, J.; Zinaman, O.; Logan, J.; Arent, D.

    2014-02-01

    Natural gas and renewable energy each contribute to economic growth, energy independence, and carbon mitigation, sometimes independently and sometimes collectively. Often, natural gas and renewables are considered competitors in markets, such as those for bulk electricity. This paper attempts to address the question, 'Given near- and long-term needs for abundant, cleaner energy sources and decarbonization, how can more compelling business models be created so that these two domestic forms of energy work in greater concert?' This paper explores revenue opportunities that emerge from systems-level perspectives in 'bulk energy' (large-scale electricity and natural gas production, transmission, and trade) and four 'distribution edge' subsectors: industrial, residential, commercial, and transportation end uses.

  12. 2008 Industrial Technologies Market Report, May 2009

    SciTech Connect (OSTI)

    Energetics; DOE

    2009-07-01

    The industrial sector is a critical component of the U.S. economy, providing an array of consumer, transportation, and national defense-related goods we rely on every day. Unlike many other economic sectors, however, the industrial sector must compete globally for raw materials, production, and sales. Though our homes, stores, hospitals, and vehicles are located within our borders, elements of our goods-producing industries could potentially be moved offshore. Keeping U.S. industry competitive is essential to maintaining and growing the U.S. economy. This report begins with an overview of trends in industrial sector energy use. The next section of the report focuses on some of the largest and most energy-intensive industrial subsectors. The report also highlights several emerging technologies that could transform key segments of industry. Finally, the report presents policies, incentives, and drivers that can influence the competitiveness of U.S. industrial firms.

  13. Public Interest Energy Research (PIER) Program. Final Project Report. California Energy Balance Update and Decomposition Analysis for the Industry and Building Sectors

    SciTech Connect (OSTI)

    de la Rue du Can, Stephane; Hasanbeigi, Ali; Sathaye, Jayant

    2010-12-01

    This report on the California Energy Balance version 2 (CALEB v2) database documents the latest update and improvements to CALEB version 1 (CALEB v1) and provides a complete picture of how energy is supplied and consumed in the State of California. The CALEB research team at Lawrence Berkeley National Laboratory (LBNL) performed the research and analysis described in this report. CALEB manages highly disaggregated data on energy supply, transformation, and end-use consumption for about 40 different energy commodities, from 1990 to 2008. This report describes in detail California's energy use from supply through end-use consumption as well as the data sources used. The report also analyzes trends in energy demand for the "Manufacturing" and "Building" sectors. Decomposition analysis of energy consumption combined with measures of the activity driving that consumption quantifies the effects of factors that shape energy consumption trends. The study finds that a decrease in energy intensity has had a very significant impact on reducing energy demand over the past 20 years. The largest impact can be observed in the industry sector where energy demand would have had increased by 358 trillion British thermal units (TBtu) if subsectoral energy intensities had remained at 1997 levels. Instead, energy demand actually decreased by 70 TBtu. In the "Building" sector, combined results from the "Service" and "Residential" subsectors suggest that energy demand would have increased by 264 TBtu (121 TBtu in the "Services" sector and 143 TBtu in the "Residential" sector) during the same period, 1997 to 2008. However, energy demand increased at a lesser rate, by only 162 TBtu (92 TBtu in the "Services" sector and 70 TBtu in the "Residential" sector). These energy intensity reductions can be indicative of energyefficiency improvements during the past 10 years. The research presented in this report provides a basis for developing an energy-efficiency performance index to measure

  14. How Can China Lighten Up? Urbanization, Industrialization and Energy Demand Scenarios

    SciTech Connect (OSTI)

    Aden, Nathaniel T.; Zheng, Nina; Fridley, David G.

    2009-07-01

    Urbanization has re-shaped China's economy, society, and energy system. Between 1990 and 2007 China added 290 million new urban residents, bringing the total urbanization rate to 45%. This population adjustment spurred energy demand for construction of new buildings and infrastructure, as well as additional residential use as rural biomass was replaced with urban commercial energy services. Primary energy demand grew at an average annual rate of 10% between 2000 and 2007. Urbanization's effect on energy demand was compounded by the boom in domestic infrastructure investment, and in the export trade following World Trade Organization (WTO) accession in 2001. Industry energy consumption was most directly affected by this acceleration. Whereas industry comprised 32% of 2007 U.S. energy use, it accounted for 75% of China's 2007 energy consumption. Five sub-sectors accounted for 78% of China's industry energy use in 2007: iron and steel, energy extraction and processing, chemicals, cement, and non-ferrous metals. Ferrous metals alone accounted for 25% of industry and 18% of total primary energy use. The rapid growth of heavy industry has led China to become by far the world's largest producer of steel, cement, aluminum, and other energy-intensive commodities. However, the energy efficiency of heavy industrial production continues to lag world best practice levels. This study uses scenario analysis to quantify the impact of urbanization and trade on industrial and residential energy consumption from 2000 to 2025. The BAU scenario assumed 67% urbanization, frozen export amounts of heavy industrial products, and achievement of world best practices by 2025. The China Lightens Up (CLU) scenario assumed 55% urbanization, zero net exports of heavy industrial products, and more aggressive efficiency improvements by 2025. The five dominant industry sub-sectors were modeled in both scenarios using a LEAP energy end-use accounting model. The results of this study show that a CLU

  15. Industrial sector energy conservation programs in the People`s Republic of China during the seventh five-year plan (1986--1990)

    SciTech Connect (OSTI)

    Liu Zhiping; Sinton, J.E.; Yang Fuqiang; Levine, M.D.; Ting, M.K.

    1994-09-01

    The impetus at the national level to invest in energy conservation is quite strong and has long been reflected not only in official pronouncements, but also in the investments and organizational activities of the Chinese government. In the early 1980s the central government began a program of direct investments in industrial energy conservation that continues to the present. In addition, concurrently established governmental and quasi-governmental agencies have pursued conservation through administrative and educational measures. In Section 2 of this paper the authors outline the policies and institutions that supported China`s program of energy conservation investments in the Sixth and Seventh Five-Year Plans (FYPs) (1981--1985 and 1986--1990). In Section 3 they describe examples of the types of conservation projects pursued in four industrial subsectors: ferrous metals manufacturing; non-ferrous metals mining and manufacturing; chemicals manufacturing; and building materials manufacturing. Section 4 presents a simple methodology for comparing the costs of energy conservation to those of energy supply. Further discussion points out the applicability and limitations of this methodology to State Planning Commission published statistical material on the overall results of energy conservation investments. Though problematic, such analysis indicates that energy conservation investments were probably substantially cheaper than investments in equivalent energy supply would have been. They end with a discussion of some of the difficulties encountered in carrying out the conservation investment programs.

  16. Mitigation of carbon dioxide from the Indonesia energy system

    SciTech Connect (OSTI)

    Adi, A.C.; Nurrohim, A.; Hidajat, M.N.

    1996-12-31

    Energy consumption in Indonesia is growing fast in line with the development of national economy. During (1990 - 1993) the emission of CO{sub 2} gas coming from energy sector increased from 150 million tones to 200 million tones in 1993. Whereas, the total methane emission from the oil, gas and coal sub-sector reached 550 kilo tones in 1991 and increased to 670 kilo tones in 1994. This amount of CO{sub 2} and Methane from energy sector was 26% and 10 % respectively of the total emission of Indonesia. Based on the last two decades of Indonesia`s economic growth experience, as a developing country this high economic growth rate of Indonesia in the future will be kept until reaching the newly industrialized country level, which is more than 6% annually in the next decade. This high growth rate economic projection will also added the level of GHG emission in the future. As a developing country Indonesia is one of the fast growing countries. The GDP growth in the year 1995 was more than 7 percent, therefore growth rate of energy consumption in this country also rose following the economic growth.

  17. Energy use and CO2 emissions of China’s industrial sector from a global perspective

    SciTech Connect (OSTI)

    Zhou, Sheng; Kyle, G. Page; Yu, Sha; Clarke, Leon E.; Eom, Jiyong; Luckow, Patrick W.; Chaturvedi, Vaibhav; Zhang, Xiliang; Edmonds, James A.

    2013-07-10

    The industrial sector has accounted for more than 50% of China’s final energy consumption in the past 30 years. Understanding the future emissions and emissions mitigation opportunities depends on proper characterization of the present-day industrial energy use, as well as industrial demand drivers and technological opportunities in the future. Traditionally, however, integrated assessment research has handled the industrial sector of China in a highly aggregate form. In this study, we develop a technologically detailed, service-oriented representation of 11 industrial subsectors in China, and analyze a suite of scenarios of future industrial demand growth. We find that, due to anticipated saturation of China’s per-capita demands of basic industrial goods, industrial energy demand and CO2 emissions approach a plateau between 2030 and 2040, then decrease gradually. Still, without emissions mitigation policies, the industrial sector remains heavily reliant on coal, and therefore emissions-intensive. With carbon prices, we observe some degree of industrial sector electrification, deployment of CCS at large industrial point sources of CO2 emissions at low carbon prices, an increase in the share of CHP systems at industrial facilities. These technological responses amount to reductions of industrial emissions (including indirect emission from electricity) are of 24% in 2050 and 66% in 2095.

  18. Energy structures and environmental futures

    SciTech Connect (OSTI)

    Haugland, T.; Bergesen, H.O.; Roland, K.

    1998-11-01

    Energy is not only a basis for modern society, but also a product of it. This book is a study of the close and ever-changing relationship between the energy sector and the society that surrounds it. At the end of the twentieth century this relationship faces two fundamental challenges: First, the national confinement of modern energy systems is undermined by technological progress, making long-distance trade increasingly attractive, and by the broad trend towards economic internationalization in general and political integration in Europe in particular. Second, the risk of climate change may lead governments and publics to demand a profound restructuring of the entire energy sector. The purpose is to analyze how these two fundamental challenges, and the connection between them, can affect future energy developments in Europe. The analysis must be rooted in a firm understanding of the past. The first part of the book is therefore devoted to a systematic description and analysis of the energy sector in Europe as it has developed over the past twenty-five years, by major subsectors and with examples from the most important countries. Part 1 discusses trends and policies related to energy demand, energy sector developments in oil, coal, natural gas, and electricity, achievements and challenges in the environment, and the role of international policy bodies. Part 2 forecasts future developments in 1995--2020, by discussing the following: Paths for future developments; National rebound scenario; Liberalization and trade; Liberalization versus national rebound; and Environmental futures.

  19. Analysis of Long-range Clean Energy Investment Scenarios forEritrea, East Africa

    SciTech Connect (OSTI)

    Van Buskirk, Robert D.

    2004-05-07

    We discuss energy efficiency and renewable energy investments in Eritrea from the strategic long-term economic perspective of meeting Eritrea's sustainable development goals and reducing greenhouse gas emissions. Energy efficiency and renewable energy are potentially important contributors to national productive capital accumulation, enhancement of the environment, expansion of energy services, increases in household standard of living, and improvements in health. In this study we develop a spreadsheet model for calculating some of the national benefits and costs of different levels of investment in energy efficiency and renewable energy. We then present the results of the model in terms of investment demand and investment scenario curves. These curves express the contribution that efficiency and renewable energy projects can make in terms of reduced energy sector operating expenses, and reduced carbon emissions. We provide demand and supply curves that show the rate of return, the cost of carbon emissions reductions vs. supply, and the evolution of the marginal carbon emissions per dollar of GDP for different investment levels and different fuel-type subsectors.

  20. Current and future industrial energy service characterizations

    SciTech Connect (OSTI)

    Krawiec, F.; Thomas, T.; Jackson, F.; Limaye, D.R.; Isser, S.; Karnofsky, K.; Davis, T.D.

    1980-10-01

    Current and future energy demands, end uses, and cost used to characterize typical applications and resultant services in the industrial sector of the United States and 15 selected states are examined. A review and evaluation of existing industrial energy data bases was undertaken to assess their potential for supporting SERI research on: (1) market suitability analysis, (2) market development, (3) end-use matching, (3) industrial applications case studies, and (4) identification of cost and performance goals for solar systems and typical information requirements for industrial energy end use. In reviewing existing industrial energy data bases, the level of detail, disaggregation, and primary sources of information were examined. The focus was on fuels and electric energy used for heat and power purchased by the manufacturing subsector and listed by 2-, 3-, and 4-digit SIC, primary fuel, and end use. Projections of state level energy prices to 1990 are developed using the energy intensity approach. The effects of federal and state industrial energy conservation programs on future industrial sector demands were assessed. Future end-use energy requirements were developed for each 4-digit SIC industry and were grouped as follows: (1) hot water, (2) steam (212 to 300/sup 0/F, each 100/sup 0/F interval from 300 to 1000/sup 0/F, and greater than 1000/sup 0/F), and (3) hot air (100/sup 0/F intervals). Volume I details the activities performed in this effort.

  1. New trends in industrial energy efficiency in the Mexico iron and steel industry

    SciTech Connect (OSTI)

    Ozawa, Leticia; Martin, Nathan; Worrell, Ernst; Price, Lynn; Sheinbaum, Claudia

    1999-07-31

    Energy use in the Mexican industrial sector experienced important changes in the last decade related to changes in the Mexican economy. In previous studies, we have shown that a real change in energy-intensity was the most important factor in the overall decline of energy use and CO2 emissions in the Mexican industrial sector. Real changes in energy intensity were explained by different factors, depending on the industrial sub-sector. In this paper, we analyze the factors that influenced energy use in the Mexican iron and steel industry, the largest energy consuming and energy-intensive industry in the country. To understand the trends in this industry we used a decomposition analysis based on physical indicators to decompose the changes in intra-sectoral structural changes and efficiency improvements. Also, we use a structure-efficiency analysis for international comparisons, considering industrial structure and the best available technology. In 1995, Mexican iron and steel industry consumed 17.7 percent of the industrial energy consumption. Between 1970 and 1995, the steel production has increased with an annual growth rate of 4.7 percent, while the specific energy consumption (SEC) has decreased from 28.4 to 23.8 GJ/tonne of crude steel. This reduction was due to energy efficiency improvements (disappearance of the open hearth production, increase of the share of the continuous casting) and to structural changes as well (increase of the share of scrap input in the steelmaking).

  2. Profile of the chemicals industry in California: Californiaindustries of the future program

    SciTech Connect (OSTI)

    Galitsky, Christina; Worrell, Ernst

    2004-06-01

    -specific energy-efficiency. An important element of the SIOF-program is the preparation of R&D roadmaps for each of the selected industries. The roadmap will help to identify priority needs for the participating industries to meet their energy challenges. The roadmap effort builds on the roadmaps developed by DOE, and on the conditions specific for the industry in California. Key to the successful preparation of a roadmap in the selected industries is the development of a profile of the industries. The profile provides a basis for the participants in the roadmap-effort, especially as the structure of the industries in California can be different than in the nation. The sector profiles describe the current economic and energy situation of these industries in California, the processes and energy uses, and the potential future developments in each industry. The profiles are an integral part of the roadmap, to help working group partners to evaluate the industry's R&D needs for their industry in California. In this report, we focus on the chemicals industry. The industry is an important economic factor in the state, providing over 82,300 jobs directly, and more in indirect employment. Value of shipments in 2001 was just under $25.7 Billion, or 6% of all manufacturing in California. There are over 1,500 chemical plants in California, of which 52% are pharmaceutical companies. Many companies operate chemical plants in California. The industry consumes 8% of the electricity and 5% of the natural gas in California. In this report, we start with a description of the chemical industry in the United States and California. This is followed by a discussion of the energy consumption and energy intensity of the Californian chemical industry. Chapter 3 focuses on the main sub-sectors. For each of the sub-sectors a general process description is provided in Chapter 4. Based on this analysis, in Chapter 5, we discuss potential technology developments that can contribute to further improving the

  3. Addressing an Uncertain Future Using Scenario Analysis

    SciTech Connect (OSTI)

    Siddiqui, Afzal S.; Marnay, Chris

    2006-12-15

    nature, such as the Energy Information Administration's (EIA's) National Energy Modeling System (NEMS). NEMS is the source of the influential Annual Energy Outlook whose business-as-usual (BAU) case, the Reference Case, forms the baseline for most of the U.S. energy policy discussion. NEMS is an optimizing model because: 1. it iterates to an equilibrium among modules representing the supply, demand, and energy conversion subsectors; and 2. several subsectoral models are individually solved using linear programs (LP). Consequently, it is deeply rooted in the recent past and any effort to simulate the consequences of a major regime shift as depicted in Figure 1 must come by applying an exogenously specified scenario. And, more generally, simulating futures that lie outside of our recent historic experience, even if they do not include regime switches suggest some form of scenario approach. At the same time, the statistical validity of scenarios that deviate significantly outside the ranges of historic inputs should be questioned.

  4. Constructing a resilience index for the Enhanced Critical Infrastructure Protection Program

    SciTech Connect (OSTI)

    Fisher, R. E.; Bassett, G. W.; Buehring, W. A.; Collins, M. J.; Dickinson, D. C.; Eaton, L. K.; Haffenden, R. A.; Hussar, N. E.; Klett, M. S.; Lawlor, M. A.; Millier, D. J.; Petit, F. D.; Peyton, S. M.; Wallace, K. E.; Whitfield, R. G.; Peerenboom, J P

    2010-10-14

    component of the risk management framework and infrastructure protection. This shift in focus toward resilience complements the analysis of protective measures by taking into account the three other phases of risk management: mitigation, response, and recovery (Figure 1). Thus, the addition of a robust resilience index (RI) to the established PMI/VI provides vital information to owners/operators throughout the risk management process. Combining a pre-incident focus with a better understanding of resilience, as well as potential consequences from damaged CIKR, allows owners/operators to better understand different ways to decrease risk by (1) increasing physical security measures to prevent an incident, (2) supplementing redundancy to mitigate the effects of an incident, and (3) enhancing emergency action and business continuity planning to increase the effectiveness of recovery procedures. Information provided by the RI methodology is also used by facility owners/operators to better understand how their facilities compare to similar sector/subsector sites and to help them make risk-based decisions. This report provides an overview of the RI methodology developed to estimate resilience and provide resilience comparisons for sectors and subsectors. The information will be used to (1) assist DHS in analyzing existing response and recovery methods and programs at facilities and (2) identify potential ways to increase resilience. The RI methodology is based on principles of Appreciative Inquiry, which is 'the coevolutionary search for the best in people, their organizations, and the relevant world around them' (Cooperrider et al. 2005). Appreciative Inquiry identifies the best of 'what is' and helps to envision 'what might be.' The ECIP program and the RI represent a new model (using Appreciative Inquiry principles) for information sharing between government and industry (Fisher and Petit 2010). A 'dashboard' display, which provides an interactive tool - rather than a static

  5. Assessing the Control Systems Capacity for Demand Response in California Industries

    SciTech Connect (OSTI)

    Ghatikar, Girish; McKane, Aimee; Goli, Sasank; Therkelsen, Peter; Olsen, Daniel

    2012-01-18

    good control capabilities are needed to dispel perceived barriers to participation and to investigate industrial subsectors suggested of having inherent Demand Response potential.

  6. SCENARIOS FOR MEETING CALIFORNIA'S 2050 CLIMATE GOALS California's Carbon Challenge Phase II Volume I: Non-Electricity Sectors and Overall Scenario Results

    SciTech Connect (OSTI)

    Wei, Max; Greenblatt, Jeffrey; Donovan, Sally; Nelson, James; Mileva, Ana; Johnston, Josiah; Kammen, Daniel

    2014-06-01

    This study provides an updated analysis of long-term energy system scenarios for California consistent with the State meeting its 2050 climate goal, including detailed analysis and assessment of electricity system build-out, operation, and costs across the Western Electricity Coordinating Council (WECC) region. Four key elements are found to be critical for the State to achieve its 2050 goal of 80 percent greenhouse (GHG) reductions from the 1990 level: aggressive energy efficiency; clean electricity; widespread electrification of passenger vehicles, building heating, and industry heating; and large-scale production of low-carbon footprint biofuels to largely replace petroleum-based liquid fuels. The approach taken here is that technically achievable energy efficiency measures are assumed to be achieved by 2050 and aggregated with the other key elements mentioned above to estimate resultant emissions in 2050. The energy and non-energy sectors are each assumed to have the objective of meeting an 80 percent reduction from their respective 1990 GHG levels for the purposes of analysis. A different partitioning of energy and non-energy sector GHG greenhouse reductions is allowed if emission reductions in one sector are more economic or technically achievable than in the other. Similarly, within the energy or non-energy sectors, greater or less than 80 percent reduction from 1990 is allowed for sub-sectors within the energy or non-energy sectors as long as the overall target is achieved. Overall emissions for the key economy-wide scenarios are considered in this report. All scenarios are compliant or nearly compliant with the 2050 goal. This finding suggests that multiple technical pathways exist to achieve the target with aggressive policy support and continued technology development of largely existing technologies.

  7. Energy-Efficiency Improvement Opportunities for the Textile Industry

    SciTech Connect (OSTI)

    China Energy Group; Hasanbeigi, Ali

    2010-09-29

    The textile industry is one of the most complicated manufacturing industries because it is a fragmented and heterogeneous sector dominated by small and medium enterprises (SMEs). Energy is one of the main cost factors in the textile industry. Especially in times of high energy price volatility, improving energy efficiency should be a primary concern for textile plants. There are various energy-efficiency opportunities that exist in every textile plant, many of which are cost-effective. However, even cost-effective options often are not implemented in textile plants mostly because of limited information on how to implement energy-efficiency measures, especially given the fact that a majority of textile plants are categorized as SMEs and hence they have limited resources to acquire this information. Know-how on energy-efficiency technologies and practices should, therefore, be prepared and disseminated to textile plants. This guidebook provides information on energy-efficiency technologies and measures applicable to the textile industry. The guidebook includes case studies from textile plants around the world and includes energy savings and cost information when available. First, the guidebook gives a brief overview of the textile industry around the world, with an explanation of major textile processes. An analysis of the type and the share of energy used in different textile processes is also included in the guidebook. Subsequently, energy-efficiency improvement opportunities available within some of the major textile sub-sectors are given with a brief explanation of each measure. The conclusion includes a short section dedicated to highlighting a few emerging technologies in the textile industry as well as the potential for the use of renewable energy in the textile industry.

  8. Fossil Fuel Carbon Dioxide Emissions Data and Data Plots from Project Vulcan

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

    Gurney, Kevin

    The Vulcan Project is a NASA/DOE funded effort under the North American Carbon Program (NACP) to quantify North American fossil fuel carbon dioxide (CO2) emissions at space and time scales much finer than has been achieved in the past. The purpose is to aid in quantification of the North American carbon budget, to support inverse estimation of carbon sources and sinks, and to support the demands posed by higher resolution CO2 observations (in situ and remotely sensed). The detail and scope of the Vulcan CO2 inventory has also made it a valuable tool for policymakers, demographers, social scientists and the public at large. The Vulcan project has achieved the quantification of the 2002 U.S. fossil fuel CO2 emissions at the scale of individual factories, powerplants, roadways and neighborhoods on an hourly basis. The entire inventory was built on a common 10 km x 10 km grid to facilitate atmospheric modeling. In addition to improvement in space and time resolution, Vulcan is quantified at the level of fuel type, economic sub-sector, and county/state identification. Explore the Vulcan website for the Vulcan gridded data, methodological details, publications, plots and analysis.[Taken from "About Project Vulcan" at http://www.purdue.edu/eas/carbon/vulcan/index.php]Also, see the peer-reviewed paper that provides a "core" description for this project: Gurney, K.R., D. Mendoza, Y. Zhou, M Fischer, S. de la Rue du Can, S. Geethakumar, C. Miller (2009) The Vulcan Project: High resolution fossil fuel combustion CO2 emissions fluxes for the United States, Environ. Sci. Technol., 43, doi:10.1021/es900,806c.

  9. Analysis of energy use in building services of the industrial sector in California: A literature review and a preliminary characterization

    SciTech Connect (OSTI)

    Akbari, H.; Borgers, T.; Gadgil, A.; Sezgen, O.

    1991-04-01

    Energy use patterns in many of California's fastest-growing industries are not typical of those in the mix of industries elsewhere in the US. Many California firms operate small and medium-sized facilities, often in buildings used simultaneously or interchangeably for commercial (office, retail, warehouse) and industrial activities. In these industrial subsectors, the energy required for building services'' to provide occupant comfort and necessities (lighting, HVAC, office equipment, computers, etc.) may be at least as important as the more familiar process energy requirements -- especially for electricity and on-peak demand. In this report, published or unpublished information on energy use for building services in the industrial sector have been compiled and analyzed. Seven different sources of information and data relevant to California have been identified. Most of these are studies and/or projects sponsored by the Department of Energy, the California Energy Commission, and local utilities. The objectives of these studies were diverse: most focused on industrial energy use in general, and, in one case, the objective was to analyze energy use in commercial buildings. Only one of these studies focused directly on non-process energy use in industrial buildings. Our analysis of Northern California data for five selected industries shows that the contribution of total electricity consumption for lighting ranges from 9.5% in frozen fruits to 29.1% in instruments; for air-conditioning, it ranges from nonexistent in frozen fruits to 35% in instrument manufacturing. None of the five industries selected had significant electrical space heating. Gas space heating ranges from 5% in motor vehicles facilities to more than 58% in the instrument manufacturing industry. 15 refs., 15 figs., 9 tabs.

  10. Chapter 9, Land and Bioenergy in Scientific Committee on Problems of the Environment (SCOPE), Bioenergy & Sustainability: bridging the gaps.

    SciTech Connect (OSTI)

    Woods J, Lynd LR; Laser, M; Batistella M, De Castro D; Kline, Keith L; Faaij, Andre

    2015-01-01

    In this chapter we address the questions of whether and how enough biomass could be produced to make a material contribution to global energy supply on a scale and timeline that is consistent with prominent low carbon energy scenarios. We assess whether bioenergy provision necessarily conflicts with priority ecosystem services including food security for the world s poor and vulnerable populations. In order to evaluate the potential land demand for bioenergy, we developed a set of three illustrative scenarios using specified growth rates for each bioenergy sub-sector. In these illustrative scenarios, bioenergy (traditional and modern) increases from 62 EJ/yr in 2010 to 100, 150 and 200 EJ/yr in 2050. Traditional bioenergy grows slowly, increasing by between 0.75% and 1% per year, from 40 EJ/yr in 2010 to 50 or 60 EJ/ yr in 2050, continuing as the dominant form of bioenergy until at least 2020. Across the three scenarios, total land demand is estimated to increase by between 52 and 200 Mha which can be compared with a range of potential land availability estimates from the literature of between 240 million hectares to over 1 billion hectares. Biomass feedstocks arise from combinations of residues and wastes, energy cropping and increased efficiency in supply chains for energy, food and materials. In addition, biomass has the unique capability of providing solid, liquid and gaseous forms of modern energy carriers that can be transformed into analogues to existing fuels. Because photosynthesis fixes carbon dioxide from the atmosphere, biomass supply chains can be configured to store at least some of the fixed carbon in forms or ways that it will not be reemitted to the atmosphere for considerable periods of time, so-called negative emissions pathways. These attributes provide opportunities for bioenergy policies to promote longterm and sustainable options for the supply of energy for the foreseeable future.

  11. Improving the behavioral realism of global integrated assessment models: An application to consumers’ vehicle choices

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    McCollum, David L.; Wilson, Charlie; Pettifor, Hazel; Ramea, Kalai; Krey, Volker; Riahi, Keywan; Bertram, Christoph; Lin, Zhenhong; Edelenbosch, Oreane Y.; Fujisawa, Sei

    2016-05-03

    A large body of transport sector-focused research recognizes the complexity of human behavior in relation to mobility. Yet, global integrated assessment models (IAMs), which are widely used to evaluate the costs, potentials, and consequences of different greenhouse gas emission trajectories over the medium-to-long term, typically represent behavior and the end use of energy as a simple rational choice between available alternatives, even though abundant empirical evidence shows that real-world decision making is more complex and less routinely rational. This paper demonstrates the value of incorporating certain features of consumer behavior in IAMs, focusing on light-duty vehicle (LDV) purchase decisions. Anmore » innovative model formulation is developed to represent heterogeneous consumer groups with varying preferences for vehicle novelty, range, refueling/recharging availability, and variety. The formulation is then implemented in the transport module of MESSAGE-Transport, a global IAM, although it also has the generic flexibility to be applied in energy-economy models with varying set-ups. Comparison of conventional and behaviorally-realistic model runs with respect to vehicle purchase decisions shows that consumer preferences may slow down the transition to alternative fuel (low-carbon) vehicles. Consequently, stronger price-based incentives and/or non-price based measures may be needed to transform the global fleet of passenger vehicles, at least in the initial market phases of novel alternatives. Otherwise, the mitigation burden borne by other transport sub-sectors and other energy sectors could be higher than previously estimated. Moreover, capturing behavioral features of energy consumers in global IAMs increases their usefulness to policy makers by allowing a more realistic assessment of a more diverse suite of policies.« less

  12. Inflation in maximal gauged supergravities

    SciTech Connect (OSTI)

    Kodama, Hideo; Nozawa, Masato

    2015-05-18

    We discuss the dynamics of multiple scalar fields and the possibility of realistic inflation in the maximal gauged supergravity. In this paper, we address this problem in the framework of recently discovered 1-parameter deformation of SO(4,4) and SO(5,3) dyonic gaugings, for which the base point of the scalar manifold corresponds to an unstable de Sitter critical point. In the gauge-field frame where the embedding tensor takes the value in the sum of the 36 and 36’ representations of SL(8), we present a scheme that allows us to derive an analytic expression for the scalar potential. With the help of this formalism, we derive the full potential and gauge coupling functions in analytic forms for the SO(3)×SO(3)-invariant subsectors of SO(4,4) and SO(5,3) gaugings, and argue that there exist no new critical points in addition to those discovered so far. For the SO(4,4) gauging, we also study the behavior of 6-dimensional scalar fields in this sector near the Dall’Agata-Inverso de Sitter critical point at which the negative eigenvalue of the scalar mass square with the largest modulus goes to zero as the deformation parameter s approaches a critical value s{sub c}. We find that when the deformation parameter s is taken sufficiently close to the critical value, inflation lasts more than 60 e-folds even if the initial point of the inflaton allows an O(0.1) deviation in Planck units from the Dall’Agata-Inverso critical point. It turns out that the spectral index n{sub s} of the curvature perturbation at the time of the 60 e-folding number is always about 0.96 and within the 1σ range n{sub s}=0.9639±0.0047 obtained by Planck, irrespective of the value of the η parameter at the critical saddle point. The tensor-scalar ratio predicted by this model is around 10{sup −3} and is close to the value in the Starobinsky model.

  13. 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

  14. Community Wind: Once Again Pushing the Envelope of Project Finance

    SciTech Connect (OSTI)

    bolinger, Mark A.

    2011-01-18

    financed by an intrastate offering of both debt and equity, (4) a 6 MW project in Washington state that taps into New Markets Tax Credits using an 'inverted' or 'pass-through' lease structure, and (5) a 9 MW project in Oregon that combines a variety of state and federal incentives and loans with unconventional equity from high-net-worth individuals. In most cases, these are first-of-their-kind structures that could serve as useful examples for other projects - both community and commercial wind alike. This report describes each of these innovative new financing structures in some detail, using a case-study approach. The purpose is twofold: (1) to disseminate useful information on these new financial structures, most of which are widely replicable; and (2) to highlight the recent policy changes - many of them temporary unless extended - that have facilitated this innovation. Although the community wind market is currently only a small sub-sector of the U.S. wind market - as defined here, less than 2% of the overall market at the end of 2009 (Wiser and Bolinger 2010) - its small size belies its relevance to the broader market. As such, the information provided in this report has relevance beyond its direct application to the community wind sector. The next two sections of this report briefly summarize how most community wind projects in the U.S. have been financed historically (i.e., prior to this latest wave of innovation) and describe the recent federal policy changes that have enabled a new wave of financial innovation to occur, respectively. Section 4 contains brief case studies of how each of the five projects mentioned above were financed, noting the financial significance of each. Finally, Section 5 concludes by distilling a number of general observations or pertinent lessons learned from the experiences of these five projects.

  15. Business Case for Energy Efficiency in Support of Climate Change Mitigation, Economic and Societal Benefits in China

    SciTech Connect (OSTI)

    McNeil, Michael A.; Bojda, Nicholas; Ke, Jing; Qin, Yining; de la Rue du Can, Stephane; Fridley, David; Letschert, Virginie E.; McMahon, James E.

    2011-08-18

    This study seeks to provide policymakers and other stakeholders with actionable information towards a road map for reducing energy consumption cost-effectively. We focus on individual end use equipment types (hereafter referred to as appliance groups) that might be the subject of policies - such as labels, energy performance standards, and incentives - to affect market transformation in the short term, and on high-efficiency technology options that are available today. As the study title suggests, the high efficiency or Business Case scenario is constructed around a model of cost-effective efficiency improvement. Our analysis demonstrates that a significant reduction in energy consumption and emissions is achievable at net negative cost, that is, as a profitable investment for consumers. Net savings are calculated assuming no additional costs to energy consumption such as carbon taxes. Savings relative to the base case as calculated in this way is often referred to as 'economic savings potential'. Chinese energy demand has grown dramatically over the last few decades. While heavy industry still plays a dominant role in greenhouse gas emissions, demand from residential and commercial buildings has also seen rapid growth in percentage terms. In the residential sector this growth is driven by internal migration from the countryside to cities. Meanwhile, income in both urban and rural subsectors allows ownership of major appliances. While residences are still relatively small by U.S. or European standards, nearly all households own a refrigerator, a television and an air conditioner. In the future, ownership rates are not expected to grow as much as in other developing countries, because they are already close to saturation. However, the gradual turnover of equipment in the world's largest consumer market provides a huge opportunity for greenhouse gas mitigation. In addition to residences, commercial floor space has expanded rapidly in recent years, and construction

  16. Control Systems Security Center Comparison Study of Industrial Control System Standards against the Control Systems Protection Framework Cyber-Security Requirements

    SciTech Connect (OSTI)

    Robert P. Evans

    2005-09-01

    Cyber security standards, guidelines, and best practices for control systems are critical requirements that have been delineated and formally recognized by industry and government entities. Cyber security standards provide a common language within the industrial control system community, both national and international, to facilitate understanding of security awareness issues but, ultimately, they are intended to strengthen cyber security for control systems. This study and the preliminary findings outlined in this report are an initial attempt by the Control Systems Security Center (CSSC) Standard Awareness Team to better understand how existing and emerging industry standards, guidelines, and best practices address cyber security for industrial control systems. The Standard Awareness Team comprised subject matter experts in control systems and cyber security technologies and standards from several Department of Energy (DOE) National Laboratories, including Argonne National Laboratory, Idaho National Laboratory, Pacific Northwest National Laboratory, and Sandia National Laboratories. This study was conducted in two parts: a standard identification effort and a comparison analysis effort. During the standard identification effort, the Standard Awareness Team conducted a comprehensive open-source survey of existing control systems security standards, regulations, and guidelines in several of the critical infrastructure (CI) sectors, including the telecommunication, water, chemical, energy (electric power, petroleum and oil, natural gas), and transportation--rail sectors and sub-sectors. During the comparison analysis effort, the team compared the requirements contained in selected, identified, industry standards with the cyber security requirements in ''Cyber Security Protection Framework'', Version 0.9 (hereafter referred to as the ''Framework''). For each of the seven sector/sub-sectors listed above, one standard was selected from the list of standards identified