National Library of Energy BETA

Sample records for dsm programs number

  1. International DSM and DSM program evaluation: An INDEEP assessment

    SciTech Connect (OSTI)

    Vine, E.

    1995-04-01

    This paper discusses the current level of demand-side management (DSM) occurring in selected European countries and reviews the availability of information on DSM programs and program evaluation. Next, thirteen European DSM programs are compared by examining such factors as: motivations for program implementation, marketing methods, participation rates, total energy savings, and program costs. The transfer of DSM program results and experiences found in these case studies is also discussed, as well as the lessons learned during the design, implementation, and evaluation of these programs. This paper represents a preliminary assessment of the state of DSM and DSM program evaluation in Europe. The findings from this work also represent the first steps in a joint international effort to compile and analyze the measured results of energy efficiency programs in a consistent and comprehensive fashion. The authors find that these programs represent cost-effective resources: the cost of energy saved by the programs ranged from a low of 0.0005 ECUs/kWh (0.01 {cents}/kWh) to a high of 0.077 ECUs/kWh (9.7 {cents}/kWh), with an average cost of 0.027 ECUs/kWh (3.3 {cents}/kWh). Weighted by energy savings, the average cost of energy saved by the programs was 0.014 ECUs/kWh (1.8 {cents}/kWh).

  2. Handbook of evaluation of utility DSM programs

    SciTech Connect (OSTI)

    Hirst, E.; Reed, J.; Bronfman, B.; Fitzpatrick, G.; Hicks, E.; Hirst, E.; Hoffman, M.; Keating, K.; Michaels, H.; Nadel, S.; Peters, J.; Reed, J.; Saxonis, W.; Schoen, A.; Violette, D.

    1991-12-01

    Program evaluation has become a central issue in the world of utility integrated resource planning. The DSM programs that utilities were operating to meet federal requirements or to improve customer relations are now becoming big business. DSM is being considered an important resource in a utility`s portfolio of options. In the last five years, the amount of money that utilities have invested in DSM has grown exponentially in most regulatory jurisdictions. Market analysts are now talking about DSM being a $30 billion industry by the end of the decade. If the large volume of DSM-program investments was not enough to highlight the importance of evaluation, then the introduction of regulatory incentives has really focused the spotlight. This handbook was developed through a process that involved many of those people who represent the diverse constituencies of DSM-program evaluation. We have come to recognize the many technical disciplines that must be employed to evaluate DSM programs. An analysis might start out based on the principles of utility load research to find out what happened, but a combination of engineering and statistical methods must be used to ``triangulate`` an estimate of what would have happened without the program. The difference, of course, is that elusive but prized result of evaluation: what happened as the direct result of the DSM program. Technical performance of DSM measures is not the sole determinant of the answer, either. We also recognize the importance of such behavioral attributes of DSM as persistence and free ridership. Finally, DSM evaluation is meaningless without attention to planning an approach, communicating results to relevant decision-makers, and focusing as much on the process as the impacts of the program. These topics are all covered in this handbook.

  3. Commercial and Industrial DSM Program Overview | Department of...

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

    Commercial and Industrial DSM Program Overview Commercial and Industrial DSM Program Overview Presentation provides an overview of PEPCO and Delmarva Power's demand side management...

  4. Electric-utility DSM programs: Terminology and reporting formats

    SciTech Connect (OSTI)

    Hirst, E. ); Sabo, C. )

    1991-10-01

    The number, scope, effects, and costs of electric-utility demand-site management programs are growing rapidly in the United States. Utilities, their regulators, and energy policy makers need reliable information on the costs of, participation in, and energy and load effects of these programs to make informed decisions. In particular, information is needed on the ability of these programs to cost-effectively provide energy and capacity resources that are alternatives to power plants. This handbook addresses the need for additional and better information in two ways. First, it discusses the key concepts associated with DSM-program types, participation, energy and load effects, and costs. Second, the handbook offers definitions and a sample reporting form for utility DSM programs. The primary purpose in developing these definitions and this form is to encourage consistency in the collection and reporting of data on DSM programs. To ensure that the discussions, reporting formats, and definitions will be useful and used, development of this handbook was managed by a committee, with membership from electric utilities, state regulatory commissions, and the US Department of Energy. Also, this data-collection form was pretested by seven people from six utilities, who completed the form for nine DSM programs.

  5. Handbook of evaluation of utility DSM programs. [Demand-Side Management (DSM)

    SciTech Connect (OSTI)

    Hirst, E.; Reed, J.; Bronfman, B.; Fitzpatrick, G.; Hicks, E.; Hirst, E.; Hoffman, M.; Keating, K.; Michaels, H.; Nadel, S.; Peters, J.; Reed, J.; Saxonis, W.; Schoen, A.; Violette, D.

    1991-12-01

    Program evaluation has become a central issue in the world of utility integrated resource planning. The DSM programs that utilities were operating to meet federal requirements or to improve customer relations are now becoming big business. DSM is being considered an important resource in a utility's portfolio of options. In the last five years, the amount of money that utilities have invested in DSM has grown exponentially in most regulatory jurisdictions. Market analysts are now talking about DSM being a $30 billion industry by the end of the decade. If the large volume of DSM-program investments was not enough to highlight the importance of evaluation, then the introduction of regulatory incentives has really focused the spotlight. This handbook was developed through a process that involved many of those people who represent the diverse constituencies of DSM-program evaluation. We have come to recognize the many technical disciplines that must be employed to evaluate DSM programs. An analysis might start out based on the principles of utility load research to find out what happened, but a combination of engineering and statistical methods must be used to triangulate'' an estimate of what would have happened without the program. The difference, of course, is that elusive but prized result of evaluation: what happened as the direct result of the DSM program. Technical performance of DSM measures is not the sole determinant of the answer, either. We also recognize the importance of such behavioral attributes of DSM as persistence and free ridership. Finally, DSM evaluation is meaningless without attention to planning an approach, communicating results to relevant decision-makers, and focusing as much on the process as the impacts of the program. These topics are all covered in this handbook.

  6. Assessment of net lost revenue adjustment mechanisms for utility DSM programs

    SciTech Connect (OSTI)

    Baxter, L.W.

    1995-01-01

    Utility shareholders can lose money on demand-side management (DSM) investments between rate cases. Several industry analysts argue that the revenues lost from utility DSM programs are an important financial disincentive to utility DSM investment. A key utility regulatory reform undertaken since 1989 allows utilities to recover the lost revenues incurred through successful operation of DSM programs. Explicitly defined net lost revenue adjustment (NLRA) mechanisms are states` preferred approach to lost revenue recovery from DSM programs. This report examines the experiences states and utilities are having with the NLRA approach. The report has three objectives. First, we determine whether NLRA is a feasible and successful approach to removing the lost-revenue disincentive to utility operation of DSM programs. Second, we identify the conditions linked to successful implementation of NLRA mechanisms in different states and assess whether NLRA has changed utility investment behavior. Third, we suggest improvements to NLRA mechanisms. We first identify states with NLRA mechanisms where utilities are recovering lost revenues from DSM programs. We interview staff at regulatory agencies in all these states and utility staff in four states. These interviews focus on the status of NLRA, implementation issues, DSM measurement issues, and NLRA results. We also analyze regulatory agency orders on NLRA, as well as associated testimony, reports, and utility lost revenue recovery filings. Finally, we use qualitative and quantitative indicators to assess NLRA`s effectiveness. Contrary to the concerns raised by some industry analysts, our results indicate NLRA is a feasible approach to the lost-revenue disincentive.

  7. Electric-utility DSM programs: 1990 data and forecasts to 2000

    SciTech Connect (OSTI)

    Hirst, E.

    1992-06-01

    In April 1992, the Energy Information Administration (EIA) released data on 1989 and 1990 electric-utility demand-site management (DMS) programs. These data represent a census of US utility DSM programs, with reports of utility expenditures, energy savings, and load reductions caused by these programs. In addition, EIA published utility estimates of the costs and effects of these programs from 1991 to 2000. These data provide the first comprehensive picture of what utilities are spending and accomplishing by utility, state, and region. This report presents, summarizes, and interprets the 1990 data and the utility forecasts of their DSM-program expenditures and impacts to the year 2000. Only utilities with annual sales greater than 120 GWh were required to report data on their DSM programs to EIA. Of the 1194 such utilities, 363 reported having a DSM program that year. These 363 electric utilities spent $1.2 billion on their DSM programs in 1990, up from $0.9 billion in 1989. Estimates of energy savings (17,100 GWh in 1990 and 14,800 GWh in 1989) and potential reductions in peak demand (24,400 MW in 1990 and about 19,400 MW in 1989) also showed substantial increases. Overall, utility DSM expenditures accounted for 0.7% of total US electric revenues, while the reductions in energy and demand accounted for 0.6% and 4.9% of their respective 1990 national totals. The investor-owned utilities accounted for 70 to 90% of the totals for DSM costs, energy savings, and demand reductions. The public utilities reported larger percentage reductions in peak demand and energy smaller percentage DSM expenditures. These averages hide tremendous variations across utilities. Utility forecasts of DSM expenditures and effects show substantial growth in both absolute and relative terms.

  8. Implementing and managing a DSM program: Central Hudson`s dollar $avers commercial/industrial rebate program

    SciTech Connect (OSTI)

    Voltz, M.F.

    1996-01-01

    Demand-Side Management (DSM) program managers at utilities throughout the United States are faced with the challenge of achieving DSM goals while minimizing program costs in order to mitigate rate impacts. Many utilities are also allowed to earn a shareholder equity incentive based upon the cost effectiveness of DSM programs (shared savings type incentive). Program goals must be achieved in a market which is constantly evolving. This paper presents Central Hudson Gas & Electric Corporations`s experience over the past 4 years implementing and managing a commercial industrial (C/I) efficient lighting rebate program which has been marketed as the Dollar $avers Lighting rebate program.

  9. A framework for improving the cost-effectiveness of DSM program evaluations

    SciTech Connect (OSTI)

    Sonnenblick, R.; Eto, J.

    1995-09-01

    The prudence of utility demand-side management (DSM) investments hinges on their performance, yet evaluating performance is complicated because the energy saved by DSM programs can never be observed directly but only inferred. This study frames and begins to answer the following questions: (1) how well do current evaluation methods perform in improving confidence in the measurement of energy savings produced by DSM programs; (2) in view of this performance, how can limited evaluation resources be best allocated to maximize the value of the information they provide? The authors review three major classes of methods for estimating annual energy savings: tracking database (sometimes called engineering estimates), end-use metering, and billing analysis and examine them in light of the uncertainties in current estimates of DSM program measure lifetimes. The authors assess the accuracy and precision of each method and construct trade-off curves to examine the costs of increases in accuracy or precision. Several approaches for improving evaluations for the purpose of assessing program cost effectiveness are demonstrated. The methods can be easily generalized to other evaluation objectives, such as shared savings incentive payments.

  10. Impact of the Demand-Side Management (DSM) Program structure on the cost-effectiveness of energy efficiency projects

    SciTech Connect (OSTI)

    Stucky, D.J.; Shankle, S.A.; Dixon, D.R.; Elliott, D.B.

    1994-12-01

    Pacific Northwest Laboratory (PNL) analyzed the cost-effective energy efficiency potential of Fort Drum, a customer of the Niagara Mohawk Power Corporation (NMPC) in Watertown, New York. Significant cost-effective investments were identified, even without any demand-side management (DSM) incentives from NMPC. Three NMPC DSM programs were then examined to determine the impact of participation on the cost-effective efficiency potential at the Fort. The following three utility programs were analyzed: (1) utility rebates to be paid back through surcharges, (2) a demand reduction program offered in conjunction with an energy services company, and (3) utility financing. Ultimately, utility rebates and financing were found to be the best programs for the Fort. This paper examines the influence that specific characteristics of the DSM programs had on the decision-making process of one customer. Fort Drum represents a significant demand-side resource, whose decisions regarding energy efficiency investments are based on life-cycle cost analysis subject to stringent capital constraints. The structures of the DSM programs offered by NMPC affect the cost-effectiveness of potential efficiency investments and the ability of the Fort to obtain sufficient capital to implement the projects. This paper compares the magnitude of the cost-effective resource available under each program, and the resulting level of energy and demand savings. The results of this analysis can be used to examine how DSM program structures impact the decision-making process of federal and large commercial customers.

  11. Developing and Enhancing Workforce Training Programs: Number...

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

    Developing and Enhancing Workforce Training Programs: Number of Projects by State Developing and Enhancing Workforce Training Programs: Number of Projects by State Map of the ...

  12. A scoping study on energy-efficiency market transformation by California Utility DSM Programs

    SciTech Connect (OSTI)

    Eto, J.; Prahl, R.; Schlegel, J.

    1996-07-01

    Market transformation has emerged as a central policy objective for future publicly-funded energy-efficiency programs in California. California Public Utilities Commission (CPUC) Decision 95-12-063 calls for public funding to shift to activities designed to transform the energy-efficiency market. The CPUC envisions that funding {open_quotes}would only be needed for specific and limited periods of time to cause the market to be transformed{close_quotes}. At the same time, the CPUC also acknowledges that {open_quotes}there are many definitions of market transformation{close_quotes} ... and does {open_quotes}not attempt to refine those definitions today{close_quotes}. We argue that a definition of market transformation is essential. The literature is now replete with definitions, and an operational definition is needed for the CPUC to decide on which programs should be supported with public funds. The CPUC decision initially indicated a preference for programs that do not provide financial assistance 4-efficiency programs that rely on financial assistance to customers. However, energy customers have traditionally accounted for a substantial portion of California utility`s DSM programs, so the CPUC`s direction to use ratepayer funds to support programs that will transform the market raises critical questions about how to analyze what has happened in order to plan effectively for the future: Which utility energy-efficiency programs, including those that provide financial assistance to customers, have had market transforming effects? To what extent do current regulatory rules and practices encourage or discourage utilities from running programs that are designed to transform the market? Should the rules and programs be modified, and, if so, how, to promote market transformation?

  13. Table A51. Number of Establishments by Sponsorship of Any Programs of Demand

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

    1. Number of Establishments by Sponsorship of Any Programs of Demand-Side Management through" " Electric Utility and Natural Gas Utility, by Industry Group and Selected Industries, 1994" ,," "," ",," "," ",," "," "," "," " ,," "," ","Any Programs"," "," ","Any Programs"," "," ",," " ,," "," of DSM

  14. State Program Advisory Number 8. Directive (Final)

    SciTech Connect (OSTI)

    Not Available

    1991-03-01

    The directive discusses State and Regional Programs Branch, which has periodically issued State Programs Advisories (SPAs) to update the 'State Consolidated Authorization Manual' (SCRAM) as new RCRA program policies, regulations, and self-implementing statutory provisions come into effect. Since the SCRAM was recently replaced by the State Authorization Manual (SAM) which includes RCRA program changes through 6/30/89, current SPAs (SPA 8 and higher) will now update the SAM. SPA 8, covers RCRA program changes for the period 7/1/89 - 12/31/89. Included are 7 new revision checklists, model Attorney General's Statement language for the changes covered by the SPA, and other revised materials. A revision to the First Third Scheduled Wastes is included here. SPA 8 introduces Revision Checklist 70 which covers changes to Part 124 which were inadvertently not included as checklists in previous guidance.

  15. Summary of California DSM impact evaluation studies

    SciTech Connect (OSTI)

    Brown, M.A.; Mihlmester, P.E.

    1994-10-01

    Over the past several years, four of the largest investor-owned California utilities have completed more than 50 evaluation studies designed to measure the energy and demand impacts of their demand-side management (DSM) programs. These four are: Pacific Gas and Electric (PG and E), Southern California Edison (SCE), Southern California Gas (SoCalGas), and San diego Gas and Electric (SDG and E). These studies covered residential, commercial, industrial, and agricultural DSM programs and provided a wealth of information on program impacts. The objective of this report is to summarize the results of these DSM evaluation studies in order to describe what DSM has achieved in California, to assess how well these achievements were forecast, and to compare the effectiveness of different types of DSM programs. This report documents the sizable investment made by the California utilities in their 1990--92 DSM programs. Between 1990 and 1992, the four utilities spent $772 million on energy-efficiency/conservation programs. This report also summarizes the realization rates estimated by the 50+ evaluation studies. Realization rates are defined as ex-post net savings estimates divided by ex-ante net savings estimates. Realization rates are summarized for 158 programs and program segments.

  16. Developing and Enhancing Workforce Training Programs: Number of Projects by

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

    State | Department of Energy Developing and Enhancing Workforce Training Programs: Number of Projects by State Developing and Enhancing Workforce Training Programs: Number of Projects by State Map of the United States showing the location of Workforce Training Projects, funded through the American Recovery and Reinvestment Act Developing and Enhancing Workforce Training Programs: Number of Projects by State (389.21 KB) More Documents & Publications Workforce Development Wind Projects

  17. Do diminishing marginal returns apply to DSM?

    SciTech Connect (OSTI)

    Sioshansi, F.P.

    1994-05-01

    The U.S. electric power industry is currently spending approximately $2 billion annually on demand-side management (DSM) programs, a substantial increase over just a few years ago. The level of DSM spending is expected to continue to grow in the foreseeable future, according to various industry surveys. Environmental benefits are among the chief assumed - and expected - benefits of DSM. In fact, the answer to how much cost-effective and achievable DSM is available depends, to some extent, on whether the value of environmental benefits of DSM is considered explicitly or implicitly. Several states now specifically require the environmental effect of alternative supply or demand options to be considered in utility resource-planning decisions. On the surface, it seems plausible that, assuming the current level of DSM is `good` for the environment, an even more aggressive level of DSM would be even better. Carrying this line of argument a step further would suggest that a highly aggressive DSM strategy, coupled with a heavy dose of nonpolluting renewable energy technologies, would eliminate the need for all new supply-side resources and be the closest thing to achieving nirvana - low-cost, environmentally benign electricity service - in utility resource planning. Those advocating such a strategy argue that is is not only justified from an environmental point of view, but also from an economic perspective, because it is the cheapest course of action to follow.

  18. Utility DSM: off the coasts and into the heartland

    SciTech Connect (OSTI)

    Nadel, Steven; Gold, Rachel

    2010-10-15

    Utility demand-side management efforts began on the coasts but have recently spread to the ''heartland.'' The authors review efforts to develop DSM programs and policies in states that are now ramping up programs, identifying key practices that are often linked with progress in states that are new to DSM and discussing the implications for the 18 states that currently lack significant DSM programs. (author)

  19. TYPES OF COMPLIANCE REQUIREMENTS: CFDA Number Program Title

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

    Number Program Title Activities Allowed or Unallowed Allowable Costs/Cost Principles Cash Management Davis Bacon Act Eligibility Equipment and Real Property Management Matching, Level of Effort, Earmarking Period of Availability of Federal Funds Procurement/ Suspension/ Debarment Program Income Real Property Acquisition/ Relocation Reporting Subrecipient Monitoring NEPA National Historic Preservation Act Special Tests and Provisions 81.036 Inventions and Innovations Yes Yes Yes Yes Yes Yes Yes

  20. DSM and electric utility competitiveness: An Illinois perspective

    SciTech Connect (OSTI)

    Jackson, P.W.

    1994-12-31

    A predominant theme in the current electric utility industry literature is that competitive forces have emerged and may become more prominent. The wholesale bulk power market is alreadly competitive, as non-utility energy service providers already have had a significant impact on that market; this trend was accelerated by the Energy Policy Act of 1992. Although competition at the retail level is much less pervasive, electric utility customers increasingly have greater choice in selecting energy services. These choices may include, depending on the customer, the ability to self-generate, switch fuels, move to a new location, or rely more heavily on demand-side management as a means of controlling electric energy use. This paper explores the subject of how demand-side management (DSM) programs, which are often developed by a utility to satisfy resource requirements as a part of its least-cost planning process, can affect the utility`s ability to compete in the energy services marketplace. In this context, the term `DSM` is used in this paper to refer to those demand-side services and programs which provide resources to the utility`s system. Depending on one`s perspective, DSM programs (so defined) can be viewed either as an enhancement to the competitive position of a utility by enabling it to provide its customers with a broader menu of energy services, simultaneously satisfying the objectives of the utility as well as those of the customers, or as a detractor to a utility`s ability to compete. In the latter case, the concern is with respect to the potential for adverse rate impacts on customers who are not participants in DSM programs. The paper consists of an identification of the pros and cons of DSM as a competitive strategy, the tradeoff which can occur between the cost impacts and rate impacts of DSM, and an examination of alternative strategies for maximizing the utilization of DSM both as a resource and as a competitive strategy.

  1. DSM shareholder incentives: Current designs and economic theory

    SciTech Connect (OSTI)

    Stoft, S.; Eto, J.; Kito, S.

    1995-01-01

    This report reviews recent DSM shareholder incentive designs and performance at 10 US utilities identifies opportunities for regulators to improve the design of DSM shareholder incentive mechanisms to increase the procurement of cost-effective DSM resources. We develop six recommendations: (1) apply shared-savings incentives to DSM resource programs; (2) use markup incentives for individual programs only when net benefits are difficult to measure, but are known to be positive; (3) set expected incentive payments based on covering a utility`s {open_quotes}hidden costs,{close_quotes} which include some transitional management and risk-adjusted opportunity costs; (4) use higher marginal incentives rates than are currently found in practice, but limit total incentive payments by adding a fixed charge; (5) mitigate risks to regulators and utilities by lowering marginal incentive rates at high and low performance levels; and (6) use an aggregate incentive mechanism for all DSM resource programs, with limited exceptions (e.g., information programs where markups are more appropriate).

  2. Net lost revenue from DSM: State policies that work

    SciTech Connect (OSTI)

    Baxter, L.W.

    1995-07-01

    A key utility regulatory reform undertaken since 1989 allows utilities to recover the lost revenue incurred through successful operation of demand-side management (DSM) programs. Net lost revenue adjustment (NLRA) mechanisms are states preferred approach to lost revenue recovery from DSM programs. This paper examines the experiences states and utilities are having with the NLRA approach. The paper has three objectives: (1) determine whether NLRA is a feasible and effective approach to the lost-revenue disincentive for utility DSM programs, (2) identify the conditions linked to effective implementation of NLRA mechanisms and assess whether NLRA has changed utility investment behavior, and (3) suggest improvements to NLRA mechanisms. Contrary to the concerns raised by some industry analysts, our results indicate NLRA is a feasible approach. Seven of the ten states we studied report no substantial problems with their approach. We observe several conditions linked to effective NLRA implementation. Observed changes in utility investment behavior occur after implementation of DSM rate reforms, which include deployment of NLRA mechanisms. Utilities in states with lost revenue recovery invest more than twice as much in DSM as do utilities in other states.

  3. The role of DSM in a competitive market

    SciTech Connect (OSTI)

    Sutherland, R.J.

    1994-10-01

    The author appreciates the opportunity to participate in this NARUC conference and to offer some thoughts on the implications for demand side management (DSM) resulting from increased competition in the electricity and gas businesses. The dominant theme of almost every professional conference in both gas and electricity is that the markets are becoming increasingly competitive and furthermore that increased competition benefits customers and affords opportunities to providers of energy services. However, only part of the effects of increased competition occur through utility DSM programs. A competitive marketplace for electricity and gas would indeed have an effect on utility conservation programs and on utility customers. The following are some of the implications of a competitive market. My presentation is an explanation and defense of these five propositions. (1) Economic efficiency will be enhanced - which increases the level of economic well being of customers and increases the productivity of the U. S. economy. (2) Energy efficiency will decrease, which may also increase our level of economic well-being and economic productivity. (3) Some DSM conservation programs will end, because they fail to pass the market test of competition. Those DSM programs that contribute to the efficient use of energy resources will prosper under competition. (4) The economic well-being of lower and middle income customers will be enhanced, first, by abolishing the DSM based subsidies to high income customers and second by pricing separately the reliability of electric services. (5) Policy goals will have to be justified on their merits - which is the worst fear of some, but the best outcome as viewed by others.

  4. POET-DSM's Integrated Model | Department of Energy

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

    POET-DSM's Integrated Model POET-DSM's Integrated Model Breakout Session 1-C: Bringing Biorefineries into the Mainstream POET-DSM's Integrated Model Doug Berven, Vice President of ...

  5. State Energy Program 2013 Competitive Awards Funding Opportunity Announcement Number: DE-FOA-0000839

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

    U.S. Department of Energy Energy Efficiency and Renewable Energy Golden Field Office State Energy Program 2013 Competitive Awards Funding Opportunity Announcement Number: DE-FOA-0000839 CFDA Number: 81.119 Issue Date: 06/21/2013 Application Due Date: 07/25/2013, 8:59 PM Eastern Time 2 REGISTRATION AND APPLICATION SUBMISSION REQUIREMENTS Registration Requirements: Allow at least 21 days to complete registrations. To submit an application under this announcement, complete the following

  6. Hawaii demand-side management resource assessment. Final report: DSM opportunity report

    SciTech Connect (OSTI)

    1995-08-01

    The Hawaii Demand-Side Management Resource Assessment was the fourth of seven projects in the Hawaii Energy Strategy (HES) program. HES was designed by the Department of Business, Economic Development, and Tourism (DBEDT) to produce an integrated energy strategy for the State of Hawaii. The purpose of Project 4 was to develop a comprehensive assessment of Hawaii`s demand-side management (DSM) resources. To meet this objective, the project was divided into two phases. The first phase included development of a DSM technology database and the identification of Hawaii commercial building characteristics through on-site audits. These Phase 1 products were then used in Phase 2 to identify expected energy impacts from DSM measures in typical residential and commercial buildings in Hawaii. The building energy simulation model DOE-2.1E was utilized to identify the DSM energy impacts. More detailed information on the typical buildings and the DOE-2.1E modeling effort is available in Reference Volume 1, ``Building Prototype Analysis``. In addition to the DOE-2.1E analysis, estimates of residential and commercial sector gas and electric DSM potential for the four counties of Honolulu, Hawaii, Maui, and Kauai through 2014 were forecasted by the new DBEDT DSM Assessment Model. Results from DBEDTs energy forecasting model, ENERGY 2020, were linked with results from DOE-2.1E building energy simulation runs and estimates of DSM measure impacts, costs, lifetime, and anticipated market penetration rates in the DBEDT DSM Model. Through its algorithms, estimates of DSM potential for each forecast year were developed. Using the load shape information from the DOE-2.1E simulation runs, estimates of electric peak demand impacts were developed. 10 figs., 55 tabs.

  7. POET-DSM biorefinery in Iowa | Department of Energy

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

    POET-DSM biorefinery in Iowa POET-DSM biorefinery in Iowa Addthis Cellulosic ethanol biorefinery 1 of 10 Cellulosic ethanol biorefinery The mechanical building (front), solid/liquid separation building (left), and anaerobic digestion building (back) at POET-DSM's Project LIBERTY biorefinery in Emmetsburg, Iowa. Image: Courtesy of POET-DSM Stacking up biomass 2 of 10 Stacking up biomass The biomass stackyard, where corn waste is stored at POET-DSM's Project LIBERTY biorefinery. Image: Courtesy of

  8. State Energy Program 2013 Competitive Awards Funding Opportunity Announcement Number: DE-FOA-0000839

    Broader source: Energy.gov [DOE]

    U.S. Department of Energy (DOE) Weatherization and Intergovernmental Program (WIP) State Energy Program (SEP) Program Year 2013 competitive awards funding opportunity announcement for state energy offices.

  9. Hawaii demand-side management resource assessment. Final report, Reference Volume 3 -- Residential and commercial sector DSM analyses: Detailed results from the DBEDT DSM assessment model; Part 1, Technical potential

    SciTech Connect (OSTI)

    1995-04-01

    The Hawaii Demand-Side Management Resource Assessment was the fourth of seven projects in the Hawaii Energy Strategy (HES) program. HES was designed by the Department of Business, Economic Development, and Tourism (DBEDT) to produce an integrated energy strategy for the State of Hawaii. The purpose of Project 4 was to develop a comprehensive assessment of Hawaii`s demand-side management (DSM) resources. To meet this objective, the project was divided into two phases. The first phase included development of a DSM technology database and the identification of Hawaii commercial building characteristics through on-site audits. These Phase 1 products were then used in Phase 2 to identify expected energy impacts from DSM measures in typical residential and commercial buildings in Hawaii. The building energy simulation model DOE-2.1E was utilized to identify the DSM energy impacts. More detailed information on the typical buildings and the DOE-2.1E modeling effort is available in Reference Volume 1, ``Building Prototype Analysis``. In addition to the DOE-2.1E analysis, estimates of residential and commercial sector gas and electric DSM potential for the four counties of Honolulu, Hawaii, Maui, and Kauai through 2014 were forecasted by the new DBEDT DSM Assessment Model. Results from DBEDTs energy forecasting model, ENERGY 2020, were linked with results from DOE-2.1E building energy simulation runs and estimates of DSM measure impacts, costs, lifetime, and anticipated market penetration rates in the DBEDT DSM Model. Through its algorithms, estimates of DSM potential for each forecast year were developed. Using the load shape information from the DOE-2.1E simulation runs, estimates of electric peak demand impacts were developed. Numerous tables and figures illustrating the technical potential for demand-side management are included.

  10. Transportation energy strategy: Project {number_sign}5 of the Hawaii Energy Strategy Development Program

    SciTech Connect (OSTI)

    1995-08-01

    This study was prepared for the State Department of Business, Economic Development and Tourism (DBEDT) as part of the Hawaii Energy Strategy program. Authority and responsibility for energy planning activities, such as the Hawaii Energy Strategy, rests with the State Energy Resources Coordinator, who is the Director of DBEDT. Hawaii Energy Strategy Study No. 5, Transportation Energy Strategy Development, was prepared to: collect and synthesize information on the present and future use of energy in Hawaii`s transportation sector, examine the potential of energy conservation to affect future energy demand; analyze the possibility of satisfying a portion of the state`s future transportation energy demand through alternative fuels; and recommend a program targeting energy use in the state`s transportation sector to help achieve state goals. The analyses and conclusions of this report should be assessed in relation to the other Hawaii Energy Strategy Studies in developing a comprehensive state energy program. 56 figs., 87 tabs.

  11. Number 2 heating oil/propane program. Final report, 1991/92

    SciTech Connect (OSTI)

    McBrien, J.

    1992-06-01

    During the 1991--92 heating season, the Massachusetts Division of Energy Resources (DOER) participated in a joint data collection program between several state energy offices and the federal Department of Energy`s (DOE) Energy Information Administration (EIA). The purpose of the program was to collect and monitor retail and wholesale heating oil and propane prices and inventories from October, 1991 through March, 1992. This final report begins with an overview of the unique events which had an impact on the reporting period. Next, the report summarizes the results from the residential heating oil and propane price surveys conducted by DOER over the 1991--1992 heating season. The report also incorporates the wholesale heating oil and propane prices and inventories collected by the EIA and distributed to the states. Finally, the report outlines DOER`s use of the data and responses to the events which unfolded during the 1991--1992 heating season.

  12. DSM savings verification through short-term pre-and-post energy monitoring at 90 facilities

    SciTech Connect (OSTI)

    Misuriello, H.

    1994-12-31

    This paper summarizes the DSM impact results obtained from short-term energy measurements performed at sites monitored as part of the Commercial, Industrial and Agricultural (CIA) Retrofit Incentives Evaluation Program sponsored by the Pacific Gas & Electric Company. The DSM measures include those typically found in these sectors; i.e., lighting, motors, irrigation pumps and HVAC modifications. The most important findings from the site measurements are the estimated annual energy and demand savings. Although there may be large differences of projected energy savings for individual sites, when viewed in the aggregate the total energy savings for the program were found to be fairly comparable to engineering estimates. This paper describes the lessons learned from attempting in-situ impact evaluations of DSM savings under both direct and custom rebate approaches. Impact parameters of interest include savings under both direct and custom rebate approaches. Impact parameters of interest include gross first-year savings and load shape impacts. The major method discussed in this paper is short-term before/after field monitoring of affected end-uses; however, the complete impact evaluation method also includes a billing analysis component and a hybrid statistical/engineering model component which relies, in part, on the short-term end-use data.

  13. Highly Efficient Thermostable DSM Cellulases: Why & How?

    SciTech Connect (OSTI)

    Manoj Kumar, PhD

    2011-04-26

    Lignocellulosic biomass is the most abundant, least expensive renewable natural biological resource for the production of biobased products and bioenergy is important for the sustainable development of human civilization in 21st century. For making the fermentable sugars from lignocellulosic biomass, a reduction in cellulase production cost, an improvement in cellulase performance, and an increase in sugar yields are all vital to reduce the processing costs of biorefineries. Improvements in specific cellulase activities for non-complexed cellulase mixtures can be implemented through cellulase engineering based on rational design or directed evolution for each cellulase component enzyme, as well as on the reconstitution of cellulase components. In this paper, we will provide DSM's efforts in cellulase research and developments and focus on limitations. Cellulase improvement strategies based on directed evolution using screening on relevant substrates, screening for higher thermal tolerance based on activity screening approaches such as continuous culture using insoluble cellulosic substrates as a powerful selection tool for enriching beneficial cellulase mutants from the large library. We will illustrate why and how thermostable cellulases are vital for economic delivery of bioproducts from cellulosic biomass using biochemical conversion approach.

  14. DSM Electricity Savings Potential in the Buildings Sector in APP Countries

    SciTech Connect (OSTI)

    McNeil, MIchael; Letschert, Virginie; Shen, Bo; Sathaye, Jayant; de la Ru du Can, Stephane

    2011-01-12

    The global economy has grown rapidly over the past decade with a commensurate growth in the demand for electricity services that has increased a country's vulnerability to energy supply disruptions. Increasing need of reliable and affordable electricity supply is a challenge which is before every Asia Pacific Partnership (APP) country. Collaboration between APP members has been extremely fruitful in identifying potential efficiency upgrades and implementing clean technology in the supply side of the power sector as well established the beginnings of collaboration. However, significantly more effort needs to be focused on demand side potential in each country. Demand side management or DSM in this case is a policy measure that promotes energy efficiency as an alternative to increasing electricity supply. It uses financial or other incentives to slow demand growth on condition that the incremental cost needed is less than the cost of increasing supply. Such DSM measures provide an alternative to building power supply capacity The type of financial incentives comprise of rebates (subsidies), tax exemptions, reduced interest loans, etc. Other approaches include the utilization of a cap and trade scheme to foster energy efficiency projects by creating a market where savings are valued. Under this scheme, greenhouse gas (GHG) emissions associated with the production of electricity are capped and electricity retailers are required to meet the target partially or entirely through energy efficiency activities. Implementation of DSM projects is very much in the early stages in several of the APP countries or localized to a regional part of the country. The purpose of this project is to review the different types of DSM programs experienced by APP countries and to estimate the overall future potential for cost-effective demand-side efficiency improvements in buildings sectors in the 7 APP countries through the year 2030. Overall, the savings potential is estimated to be 1

  15. Complete Genome Sequence of Clostridium clariflavum DSM 19732

    SciTech Connect (OSTI)

    Goodwin, Lynne A.; Davenport, Karen W.; Teshima, Hazuki; Bruce, David; Detter, J. Chris; Tapia, Roxanne; Han, Cliff; Land, Miriam L; Hauser, Loren John; Jeffries, Cynthia; Han, James; Pitluck, Sam; Nolan, Matt; Chen, Amy; Huntemann, Marcel; Mavromatis, K; Mikhailova, Natalia; Liolios, Konstantinos; Woyke, Tanja; Lynd, Lee R

    2012-01-01

    Clostridium clariflavum is a Cluster III Clostridium within the family Clostridiaceae isolated from thermophilic anaerobic sludge (Shiratori et al, 2009). This species is of interest because of its similarity to the model cellulolytic organism Clostridium thermocellum and for the ability of environmental isolates to break down cellulose and hemicellulose. Here we describe features of the 4,897,678 bp long genome and its annotation, consisting of 4,131 proteincoding and 98 RNA genes, for the type strain DSM 19732.

  16. Spent nuclear fuels project: FY 1995 multi-year program plan, WBS {number_sign}1.4

    SciTech Connect (OSTI)

    Denning, J.L.

    1994-09-01

    The mission of the Spent Nuclear Fuel (SNF) program is to safely, reliably, and efficiently manage, condition, transport, and store Department of Energy (DOE)-owned SNF, so that it meets acceptance criteria for disposal in a permanent repository. The Hanford Site Spent Nuclear Fuel strategic plan for accomplishing the project mission is: Establish near-term safe storage in the 105-K Basins; Complete national Environmental Policy Act (NEPA) process to obtain a decision on how and where spent nuclear fuel will be managed on the site; Define and establish alternative interim storage on site or transport off site to support implementation of the NEPA decision; and Define and establish a waste package qualified for final disposition. This report contains descriptions of the following: Work Breakdown Structure; WBS Dictionary; Responsibility Assignment Matrix; Program Logic Diagrams; Program Master Baseline Schedule; Program Performance Baseline Schedule; Milestone List; Milestone Description Sheets; Cost Baseline Summary by Year; Basis of Estimate; Waste Type Data; Planned Staffing; and Fiscal Year Work Plan.

  17. Multi-cluster processor operating only select number of clusters during each phase based on program statistic monitored at predetermined intervals

    DOE Patents [OSTI]

    Balasubramonian, Rajeev; Dwarkadas, Sandhya; Albonesi, David

    2009-02-10

    In a processor having multiple clusters which operate in parallel, the number of clusters in use can be varied dynamically. At the start of each program phase, the configuration option for an interval is run to determine the optimal configuration, which is used until the next phase change is detected. The optimum instruction interval is determined by starting with a minimum interval and doubling it until a low stability factor is reached.

  18. INTERNATIONAL UNION OF OPERATING ENGINEERS NATIONAL HAZMAT PROGRAM - DEWALT RECIPROCATING SAW OENHP{number_sign}: 2001-01, VERSION A

    SciTech Connect (OSTI)

    Unknown

    2002-01-31

    Florida International University's (FIU) Hemispheric Center for Environmental Technology (HCET) evaluated five saws for their effectiveness in cutting specially prepared fiberglass-reinforced plywood crates. These crates were built as surrogates for crates that presently hold radioactively contaminated glove boxes at the Department of Energy's (DOE) Los Alamos facility. The DeWalt reciprocating saw was assessed on August 13, 2001. During the FIU test of efficacy, a team from the Operating Engineers National Hazmat Program (OENHP) evaluated the occupational safety and health issues associated with this technology. The DeWalt reciprocating saw is a hand-held industrial tool used for cutting numerous materials, including wood and various types of metals depending upon the chosen blade. Its design allows for cutting close to floors, corners, and other difficult areas. An adjustable shoe sets the cut at three separate depths. During the demonstration for the dismantling of the fiberglass-reinforced plywood crate, the saw was used for extended continuous cutting, over a period of approximately two hours. The dismantling operation involved vertical and horizontal cuts, saw blade changes, and material handling. During this process, operators experienced vibration to the hand and arm in addition to a temperature rise on the handgrip. The blade of the saw is partially exposed during handling and fully exposed during blade changes. Administrative controls, such as duty time of the operators and the machine, operator training, and personal protective equipment (PPE), such as gloves, should be considered when using the saw in this application. Personal noise sampling indicated that both workers were exposed to noise levels exceeding the Occupational Safety and Health Administration's (OSHA) Action Level of 85 decibels (dBA) with time-weighted averages (TWA's) of 88.3 and 90.6 dBA. Normally, a worker would be placed in a hearing conservation program if his TWA was greater than

  19. Advanced emissions control development program. Quarterly technical progress report {number_sign}4, July 1--September 30, 1995

    SciTech Connect (OSTI)

    Farthing, G.A.

    1995-12-31

    Babcock and Wilcox (B and W) is conducting a five-year project aimed at the development of practical, cost-effective strategies for reducing the emissions of hazardous air pollutants (commonly called air toxics) from coal-fired electric utility plants. The need for air toxic emissions controls will likely arise as the US Environmental Protection Agency proceeds with implementation of Title III of the Clean Air Act Amendments of 1990. Data generated during the program will provide utilities with the technical and economic information necessary to reliably evaluate various air toxics emissions compliance options such as fuel switching, coal cleaning, and flue gas treatment. The development work is being carried out using B and W`s new Clean Environment Development Facility (CEDF) wherein air toxics emissions control strategies can be developed under controlled conditions, and with proven predictability to commercial systems. Tests conducted in the CEDF will provide high quality, repeatable, comparable data over a wide range of coal properties, operating conditions, and emissions control systems. The specific objectives of the project are to: (1) measure and understand the production and partitioning of air toxics species for a variety of steam coals, (2) optimize the air toxics removal performance of conventional flue gas cleanup systems (ESPs, baghouses, scrubbers), (3) develop advanced air toxics emissions control concepts, (4) develop and validate air toxics emissions measurement and monitoring techniques, and (5) establish a comprehensive, self-consistent air toxics data library. Development work is currently concentrated on the capture of mercury, fine particulate, and a variety of inorganic species such as the acid gases (hydrogen chloride, hydrogen fluoride, etc.).

  20. INTERNATIONAL UNION OF OPERATING ENGINEERS NATIONAL HAZMAT PROGRAM - ADAMANT CIRCULAR SAW OENHP{number_sign}: 2001-05, VERSION A

    SciTech Connect (OSTI)

    Unknown

    2002-01-01

    Florida International University's (FIU) Hemispheric Center for Environmental Technology (HCET) evaluated five saws for their effectiveness in cutting up specially prepared fiberglass-reinforced plywood crates. These crates were built as surrogates for crates that presently hold radioactive contaminated glove boxes at the Department of Energy's (DOE) Los Alamos facility. The Adamant circular saw was assessed on August 14, 2001. During the FIU test of efficacy, a team from the Operating Engineers National Hazmat Program (OENHP) evaluated the occupational safety and health issues associated with this technology. The Adamant was only used during a limited ''test'' on a regular plywood crate due to safety considerations of the tool for this application. The Adamant circular saw, a counter-rotating twin-cutter, constructed with blades that work differently than conventional cutting wheels with twin blades, each rotating in opposite directions. It is used to cut wood and metals. Each blade is approximately 8 3/4 inches in diameter with a maximum cutting depth of 2 1/2 inches. The machine has two rotation speeds: 1,900 and 2,900 rotations per minute (rpm). The saw is operated with an interlocked, guarded trigger switch located at the end of the saw opposite the cutting blades. To operate the saw, the safety interlock must be depressed prior to powering the saw with the trigger control. The saw is supported by a handle at the front of the saw near the cutting blades. The top part of the blades is guarded near the handle, with approximately three-fourths of the face of the blades exposed. The Adamant circular saw is an innovative technology used to cut metals and wood. Its safety features include: interlocking switch for powering the saw, overload indicator and shutoff, and an electronic brake that stops the engine immediately when the start button is released. The top part of the blades is guarded near the motor. With approximately three-fourths of the face of the blades

  1. Section Number:

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

    of Plants and Material 10 CFR Part 708 DOE Contractor Employee Protection Program 10 CFR Part 851 Worker Safety and Health Program 40 CFR Part 191 Environmental Radiation ...

  2. Why industry demand-side management programs should be self-directed

    SciTech Connect (OSTI)

    Pritchett, T.; Moody, L. ); Brubaker, M. )

    1993-11-01

    U.S. industry believes in DSM. But it does not believe in the way DSM is being implemented, with its emphasis on mandatory utility surcharge/rebate programs. Self-directed industrial DSM programs would be better for industry - and for utilities as well. Industrial demand-side management, as it is currently practiced, relies heavily on command-and-control-style programs. The authors believe that all parties would benefit if utilities and state public service commissions encouraged the implementation of [open quotes]self-directed[close quotes] industrial DSM programs as an alternative to these mandatory surcharge/rebate-type programs. Here the authors outline industrial experience with existing demand-side management programs, and offer alternative approaches for DSM in large manufacturing facilities. Self-directed industrial programs have numerous advantages over mandatory utility-funded and sponsored DSM programs. Self-directed programs allow an industrial facility to use its own funds to meet its own specific goals, whether they are set on the basis of demand reduction, energy use reduction, spending levels for DSM and environmental activities, or some combination of these or other readily measurable criteria. This flexibility fosters a higher level of cost effectiveness, a more focused and effective approach for optimizing energy usage, larger emission reductions per dollar of expenditure, and more competitive industrial electric rates.

  3. SCE&G (Electric)- Commercial EnergyWise Program

    Broader source: Energy.gov [DOE]

    South Carolina Electric and Gas (SCE&G) provides EnergyWise efficiency incentives to any non-residential customers in its service territory which have not opted out of the DSM programs by...

  4. Evaluation of Public Service Electric & Gas Company`s standard offer program, Volume I

    SciTech Connect (OSTI)

    Goldman, C.A.; Kito, M.S.; Moezzi, M.M.

    1995-07-01

    In May 1993, Public Service Electric and Gas (PSE&G), the largest investor-owned utility in New Jersey, initiated the Standard Offer program, an innovative approach to acquiring demand-side management (DSM) resources. In this program, PSE&G offers longterm contracts with standard terms and conditions to project sponsors, either customers or third-party energy service companies (ESCOs), on a first-come, first-serve basis to fill a resource block. The design includes posted, time-differentiated prices which are paid for energy savings that will be verified over the contract term (5, 10, or 15 years) based on a statewide measurement and verification (M&V) protocol. The design of the Standard Offer differs significantly from DSM bidding programs in several respects. The eligibility requirements and posted prices allow ESCOs and other energy service providers to market and develop projects among customers with few constraints on acceptable end use efficiency technologies. In contrast, in DSM bidding, ESCOs typically submit bids without final commitments from customers and the utility selects a limited number of winning bidders who often agree to deliver a pre-specified mix of savings from various end uses in targeted markets. The major objectives of the LBNL evaluation were to assess market response and customer satisfaction; analyze program costs and cost-effectiveness; review and evaluate the utility`s administration and delivery of the program; examine the role of PSE&G`s energy services subsidiary (PSCRC) in the program and the effect of its involvement on the development of the energy services industry in New Jersey; and discuss the potential applicability of the Standard Offer concept given current trends in the electricity industry (i.e., increasing competition and the prospect of industry restructuring).

  5. Demand-side management program evaluation and the EPA Conservation Verification Protocols. Final report

    SciTech Connect (OSTI)

    Willems, P.; Ciraulo, J.; Smith, B.

    1993-11-01

    The US Environmental Protection Agency (EPA) Conservation Verification Protocols (CVPs) are a set of step-by-step procedures for impact monitoring and evaluation of electric utility demand-side management (DSM) programs. The EPA developed these protocols as part of its mission to implement the Acid Rain Program authorized by Title IV of the Clean Air Amendments of 1990. This report provides an overview of the CVPs and how they can be used by electric utilities in DSM program monitoring and evaluation. Both the CVPs Monitoring Path and Stipulated Path procedures are summarized and reviewed. Several examples are provided to illustrate how to calculate DSM program energy savings using the CVPSs.

  6. Hawaii demand-side management resource assessment. Final report, Reference Volume 4: The DBEDT DSM assessment model user`s manual

    SciTech Connect (OSTI)

    1995-04-01

    The DBEDT DSM Assessment Model (DSAM) is a spreadsheet model developed in Quattro Pro for Windows that is based on the integration of the DBEDT energy forecasting model, ENERGY 2020, with the output from the building energy use simulation model, DOE-2. DOE-2 provides DSM impact estimates for both energy and peak demand. The ``User`s Guide`` is designed to assist DBEDT staff in the operation of DSAM. Supporting information on model structure and data inputs are provided in Volumes 2 and 3 of the Final Report. DSAM is designed to provide DBEDT estimates of the potential DSM resource for each county in Hawaii by measure, program, sector, year, and levelized cost category. The results are provided for gas and electric and for both energy and peak demand. There are two main portions of DSAM, the residential sector and the commercial sector. The basic underlying logic for both sectors are the same. However, there are some modeling differences between the two sectors. The differences are primarily the result of (1) the more complex nature of the commercial sector, (2) memory limitations within Quattro Pro, and (3) the fact that the commercial sector portion of the model was written four months after the residential sector portion. The structure for both sectors essentially consists of a series of input spreadsheets, the portion of the model where the calculations are performed, and a series of output spreadsheets. The output spreadsheets contain both detailed and summary tables and graphs.

  7. Building Retrofit and DSM Study in Jiangsu | Open Energy Information

    Open Energy Info (EERE)

    Natural Resources Defense Council Sector Energy Focus Area Buildings, Energy Efficiency Topics Background analysis, Pathways analysis, Policiesdeployment programs Resource...

  8. Final Report, Center for Programming Models for Scalable Parallel Computing: Co-Array Fortran, Grant Number DE-FC02-01ER25505

    SciTech Connect (OSTI)

    Robert W. Numrich

    2008-04-22

    The major accomplishment of this project is the production of CafLib, an 'object-oriented' parallel numerical library written in Co-Array Fortran. CafLib contains distributed objects such as block vectors and block matrices along with procedures, attached to each object, that perform basic linear algebra operations such as matrix multiplication, matrix transpose and LU decomposition. It also contains constructors and destructors for each object that hide the details of data decomposition from the programmer, and it contains collective operations that allow the programmer to calculate global reductions, such as global sums, global minima and global maxima, as well as vector and matrix norms of several kinds. CafLib is designed to be extensible in such a way that programmers can define distributed grid and field objects, based on vector and matrix objects from the library, for finite difference algorithms to solve partial differential equations. A very important extra benefit that resulted from the project is the inclusion of the co-array programming model in the next Fortran standard called Fortran 2008. It is the first parallel programming model ever included as a standard part of the language. Co-arrays will be a supported feature in all Fortran compilers, and the portability provided by standardization will encourage a large number of programmers to adopt it for new parallel application development. The combination of object-oriented programming in Fortran 2003 with co-arrays in Fortran 2008 provides a very powerful programming model for high-performance scientific computing. Additional benefits from the project, beyond the original goal, include a programto provide access to the co-array model through access to the Cray compiler as a resource for teaching and research. Several academics, for the first time, included the co-array model as a topic in their courses on parallel computing. A separate collaborative project with LANL and PNNL showed how to extend the

  9. Request Number:

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

    3023307 Name: Madeleine Brown Organization: nJa Address: --- -------- -------- -- Country: Phone Number: United States Fax Number: n/a E-mail: --- -------- --------_._------ --- Reasonably Describe Records Description: Please send me a copy of the emails and records relating to the decision to allow the underage son of Bill Gates to tour Hanford in June 2010. Please also send the emails and records that justify the Department of Energy to prevent other minors from visiting B Reactor. Optional

  10. Request Number:

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

    1074438 Name: Gayle Cooper Organization: nla Address: _ Country: United States Phone Number: Fax Number: nla E-mail: . ~===--------- Reasonably Describe Records Description: Information pertaining to the Department of Energy's cost estimate for reinstating pension benefit service years to the Enterprise Company (ENCO) employees who are active plan participants in the Hanford Site Pension Plan. This cost estimate was an outcome of the DOE's Worker Town Hall Meetings held on September 17-18, 2009.

  11. The cost and performance of utility commercial lighting programs. A report from the Database on Energy Efficiency Programs (DEEP) project

    SciTech Connect (OSTI)

    Eto, J.; Vine, E.; Shown, L.; Sonnenblick, R.; Payne, C.

    1994-05-01

    The objective of the Database on Energy Efficiency Programs (DEEP) is to document the measured cost and performance of utility-sponsored, energy-efficiency, demand-side management (DSM) programs. Consistent documentation of DSM programs is a challenging goal because of problems with data consistency, evaluation methodologies, and data reporting formats that continue to limit the usefulness and comparability of individual program results. This first DEEP report investigates the results of 20 recent commercial lighting DSM programs. The report, unlike previous reports of its kind, compares the DSM definitions and methodologies that each utility uses to compute costs and energy savings and then makes adjustments to standardize reported program results. All 20 programs were judged cost-effective when compared to avoided costs in their local areas. At an average cost of 3.9{cents}/kWh, however, utility-sponsored energy efficiency programs are not ``too cheap to meter.`` While it is generally agreed upon that utilities must take active measures to minimize the costs and rate impacts of DSM programs, the authors believe that these activities will be facilitated by industry adoption of standard definitions and reporting formats, so that the best program designs can be readily identified and adopted.

  12. (Document Number)

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

    A TA-53 TOUR FORM/RADIOLOGICAL LOG (Send completed form to MS H831) _____________ _____________________________ _________________________________ Tour Date Purpose of Tour or Tour Title Start Time and Approximate Duration ___________________________ ______________ _______________________ _________________ Tour Point of Contact/Requestor Z# (if applicable) Organization/Phone Number Signature Locations Visited: (Check all that apply, and list any others not shown. Prior approval must be obtained

  13. Programming

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

    Programming Programming Compiling and linking programs on Euclid. Compiling Codes How to compile and link MPI codes on Euclid. Read More » Using the ACML Math Library How to compile and link a code with the ACML library and include the $ACML environment variable. Read More » Process Limits The hard and soft process limits are listed. Read More » Last edited: 2016-04-29 11:35:11

  14. Programming

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

    Programming Programming The genepool system has a diverse set of software development tools and a rich environment for delivering their functionality to users. Genepool has adopted a modular system which has been adapted from the Programming Environments similar to those provided on the Cray systems at NERSC. The Programming Environment is managed by a meta-module named similar to "PrgEnv-gnu/4.6". The "gnu" indicates that it is providing the GNU environment, principally GCC,

  15. Programming

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

    Read More Programming Tuning Options Tips for tuning performance on the Hopper system ... The ACML library is also supported on Hopper and Franklin. Read More PGAS Language ...

  16. Programming

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

    Storage & File Systems Application Performance Data & Analytics Job Logs & Statistics ... Each programming environment contains the full set of compatible compilers and libraries. ...

  17. Utility DSM Rebates for electronic ballasts: National estimates and assessment of market impact (1992 - 1997)

    SciTech Connect (OSTI)

    Busch, C.B.; Atkinson, B.A.; Eto, J.H.; Turiel, I.; McMahon, J.E.

    2000-06-30

    In this report we present national estimates of utility Demand-Side Management (DSM) rebates for electronic fluorescent lamp ballasts during the period of 1992 - 1997. We then compare these trends with developments in the fluorescent ballast market from 1993 - 1998. The analysis indicates that DSM rebates for electronic ballasts peaked in the mid-1990s and declined sharply in 1996 and 1997. In a parallel trend, electronic ballast sales and market share both increased significantly during 1993 - 1994 and increased more slowly in 1996 -1997.

  18. Opportunities for cooperative programs

    SciTech Connect (OSTI)

    Marr, M.J. )

    1994-01-01

    External pressures from the marketplace and regulatory agencies will encourage utilities to work more cooperatively with their largest customers on mutually beneficial issues. This article suggests that a knowledge of utility avoided costs and their use in determining the value of demand-side management (DSM) measures will enable large customers to negotiate custom incentives for cooperative programs resulting in reduced demand on the utilities' systems that will position the utility more advantageously in the coming competitive arena.

  19. Programming

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

    using MPI and OpenMP on NERSC systems, the same does not always exist for other supported parallel programming models such as UPC or Chapel. At the same time, we know that these...

  20. Complete Genome Sequence of the Cellulolytic Thermophile Clostridium thermocellum DSM1313

    SciTech Connect (OSTI)

    Feinberg, Lawrence F; Foden, Justine; Barrett, Trisha; Davenport, Karen W.; Bruce, David; Detter, J. Chris; Tapia, Roxanne; Han, Cliff; Lapidus, Alla L.; Lucas, Susan; Cheng, Jan-Fang; Pitluck, Sam; Woyke, Tanja; Ivanova, N; Mikhailova, Natalia; Land, Miriam L; Hauser, Loren John; Argyros, Aaron; Goodwin, Lynne A.; Hogsett, David; Caiazza, Nicky

    2011-01-01

    Clostridium thermocellum DSM1313 is a thermophilic, anaerobic bacterium with some of the highest rates of cellulose hydrolysis reported. The complete genome sequence reveals a suite of carbohydrate-active enzymes and demonstrates a level of diversity at the species level distinguishing it from the type strain ATCC27405.

  1. Hawaii demand-side management resource assessment. Final report, Reference Volume 5: The DOETRAN user`s manual; The DOE-2/DBEDT DSM forecasting model interface

    SciTech Connect (OSTI)

    1995-04-01

    The DOETRAN model is a DSM database manager, developed to act as an intermediary between the whole building energy simulation model, DOE-2, and the DBEDT DSM Forecasting Model. DOETRAN accepts output data from DOE-2 and TRANslates that into the format required by the forecasting model. DOETRAN operates in the Windows environment and was developed using the relational database management software, Paradox 5.0 for Windows. It is not necessary to have any knowledge of Paradox to use DOETRAN. DOETRAN utilizes the powerful database manager capabilities of Paradox through a series of customized user-friendly windows displaying buttons and menus with simple and clear functions. The DOETRAN model performs three basic functions, with an optional fourth. The first function is to configure the user`s computer for DOETRAN. The second function is to import DOE-2 files with energy and loadshape data for each building type. The third main function is to then process the data into the forecasting model format. As DOETRAN processes the DOE-2 data, graphs of the total electric monthly impacts for each DSM measure appear, providing the user with a visual means of inspecting DOE-2 data, as well as following program execution. DOETRAN provides three tables for each building type for the forecasting model, one for electric measures, gas measures, and basecases. The optional fourth function provided by DOETRAN is to view graphs of total electric annual impacts by measure. This last option allows a comparative view of how one measure rates against another. A section in this manual is devoted to each of the four functions mentioned above, as well as computer requirements and exiting DOETRAN.

  2. Visiting Faculty Program Program Description

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

    covers stipend and travel reimbursement for the 10-week program. Teacherfaculty participants: 1 Program Coordinator: Scott Robbins Email: srobbins@lanl.gov Phone number: 663-5621...

  3. Reactor Materials Program - Baseline Material Property Handbook - Mechanical Properties of 1950's Vintage Stainless Steel Weldment Components, Task Number 89-23-A-1

    SciTech Connect (OSTI)

    Stoner, K.J.

    1999-11-05

    The Process Water System (primary coolant) piping of the nuclear production reactors constructed in the 1950''s at Savannah River Site is comprised primarily of Type 304 stainless steel with Type 308 stainless steel weld filler. A program to measure the mechanical properties of archival PWS piping and weld materials (having approximately six years of service at temperatures between 25 and 100 degrees C) has been completed. The results from the mechanical testing has been synthesized to provide a mechanical properties database for structural analyses of the SRS piping.

  4. Industrial demand-side management programs: What`s happened, what works, what`s needed

    SciTech Connect (OSTI)

    Jordan, J.A.; Nadel, S.M.

    1993-03-01

    In order to analyze experience to date with industrial demand-side management (DSM), a survey of utilities was conducted and a database of industrial DSM programs was prepared. More than eighty utilities and third-party organizations were interviewed. Data were collected via phone, fax, and/or mail from the utilities and entered into a database. In order to limit the scope of this study, the database contains incentive-based, energy-saving programs and not load management or information-only programs (including technical assistance programs). Programs in the database were divided into four categories: two ``prescriptive rebate`` categories and two ``custom rebate`` categories. The database contains 31 incentive-based, energy-saving industrial DSM programs offered by 17 utilities. The appendix to this report summarizes the results approximately 60 industrial DSM programs. Most of the programs included in the appendix, but not in the database, are either C&I programs for which commercial and industrial data were not disaggregated or new industrial DSM programs for which data are not yet available.

  5. Progress report on the scientific investigation program for the Nevada Yucca Mountain site, September 15, 1988--September 30, 1989; Nuclear Waste Policy Act (Section 113), Number 1

    SciTech Connect (OSTI)

    1990-02-01

    The Department of Energy (DOE) has prepared this report on the progress of site characterization activities at Yucca Mountain in southern Nevada. This report is the first of a series of reports that will hereafter be issued at intervals of approximately 6-months during site characterization. The DOE`s plans for site characterization are described in the Site Characterization Plan (SCP) for the Yucca Mountain site. The SCP has been reviewed and commented on by the NRC, the State of Nevada, the affected units of local government, other interested parties, and the public. More detailed information on plans for site characterization is being presented in study plans for the various site characterization activities. This progress report presents short summaries of the status of site characterization activities and cites technical reports and research products that provide more detailed information on the activities. The report provides highlights of work started during the reporting period, work in progress, and work completed and documented during the reporting period. In addition, the report is the vehicle for discussing major changes, if any, to the DOE`s site characterization program resulting from ongoing collection and evaluation of site information; the development of repository and waste-package designs; receipt of performance-assessment results; and changes, if any, that occur in response to external comments on the site characterization programs. 80 refs.

  6. Progress report on the scientific investigation program for the Nevada Yucca Mountain Site, October 1, 1991--March 31, 1992, Number 6

    SciTech Connect (OSTI)

    1992-09-01

    In accordance with the requirements of section 113(b)(3) of the Nuclear Waste Policy Act (NWPA) and 10 CFR 60.18(g), the US Department of Energy (DOE) has prepared this report on the progress of site characterization activities at Yucca Mountain, Nevada, for the period October 1, 1991, through March 31, 1992. This report is the sixth in a series of reports that are issued at intervals of approximately six months during site characterization. Also included in this report are activities such as public outreach and international programs that are not officially part of site characterization. Information on these activities is provided in order to fully integrate all aspects of the Yucca Mountain studies.

  7. Advanced Emissions Control Development Program. Quarterly Technical Progress Report {number_sign}7 for the period: April 1 to June 30, 1996

    SciTech Connect (OSTI)

    Evans, A.P.

    1996-12-31

    Babcock {ampersand} Wilcox (B{ampersand}W) is conducting a five-year project aimed at the development of practical, cost- effective strategies for reducing the emissions of hazardous air pollutants (commonly called air toxics) from coal-fired electric utility plants. The need for air toxic emissions controls may arise as the U. S. Environmental Protection Agency proceeds with implementation of Title III of the Clean Air Act Amendment (CAAA) of 1990. Data generated during the program will provide utilities with the technical and economic information necessary to reliably evaluate various air toxics emissions compliance options such as fuel switching, coal cleaning, and flue gas treatment. The development work is being carried out using B{ampersand}W`s new Clean Environment Development Facility (CEDF) wherein air toxics emissions control strategies can be developed under controlled conditions, and with proven predictability to commercial systems. Tests conducted in the CEDF provide high quality, repeatable, comparable data over a wide range of coal properties, operating conditions, and emissions control systems. Development work to date has concentrated on the capture of mercury, other trace metals, fine particulate, and the inorganic species hydrogen chloride and hydrogen fluoride.

  8. Advanced Emissions Control Development Program. Quarterly Technical Progress Report {number_sign}5 for the period October 1 to December 31, 1995

    SciTech Connect (OSTI)

    Farthing, George A.

    1996-12-31

    Babcock {ampersand} Wilcox (B{ampersand}W) is conducting a five year project aimed at the development of practical, cost- effective strategies for reducing the emissions of hazardous air pollutants (commonly called air toxics) from coal-fired electric utility plants. The need for air toxic emissions controls will likely arise as the U. S. Environmental Protection Agency proceeds with implementation of Title III of the Clean Air Act Amendments of 1990. Data generated during the program will provide utilities with the technical and economic information necessary to reliably evaluate various air toxics emissions compliance options such as fuel switching, coal cleaning, and flue gas treatment. The development work is being carried out using B&W`s new Clean Environment Development Facility (CEDF) wherein air toxics emissions control strategies can be developed under controlled conditions, and with proven predictability to commercial systems. Tests conducted in the CEDF will provide high quality, repeatable, comparable data over a wide range of coal properties, operating conditions, and emissions control systems. The specific objectives of the project are to: (1) measure and understand the production and partitioning of air toxics species for a variety of steam coals, (2) optimize the air toxics removal performance of conventional flue gas cleanup systems (ESPs, baghouses, scrubbers), (3) develop advanced air toxics emissions control concepts, (4) develop and validate air toxics emissions measurement and monitoring techniques, and (5) establish a comprehensive, self-consistent air toxics data library. Development work is currently concentrated on the capture of mercury, fine particulate, and a variety of inorganic species such as the acid gases (hydrogen chloride, hydrogen fluoride, etc.).

  9. Advanced Emissions Control Development Program. Quarterly Technical Progress Report {number_sign}6 for the period: January 1 to March 31, 1996

    SciTech Connect (OSTI)

    Farthing, George A.

    1996-12-31

    Babcock {ampersand} Wilcox (B{ampersand}W) is conducting a five-year project aimed at the development of practical, cost-effective strategies for reducing the emissions of hazardous air pollutants (commonly called air toxics) from coal-fired electric utility plants. The need for air toxic emissions controls will likely arise as the U. S. Environmental Protection Agency proceeds with implementation of Title III of the clean Air Act Amendments of 1990. Data generated during the program will provide utilities with the technical and economic information necessary to reliably evaluate various air toxics emissions compliance options such as fuel switching, coal cleaning, and flue gas treatment. The development work is being carried out using B{ampersand}W`s new Clean Environment Development Facility (CEDF) wherein air toxics emissions control strategies can be developed under controlled conditions, and with proven predictability to commercial systems. Tests conducted in the CEDF will provide high quality, repeatable, comparable data over a wide range of coal properties, operating conditions, and emissions control systems. The specific objectives of the project are to: (1) measure and understand the production and partitioning of air toxics species for a variety of steam coals, (2) optimize the air toxics removal performance of conventional flue gas cleanup systems (ESPs, baghouses, scrubbers), (3) develop advanced air toxics emissions control concepts, (4) develop and validate air toxics emissions measurement and monitoring techniques, and (5) establish a comprehensive, self- consistent air toxics data library. Development work is currently concentrated on the capture of mercury, fine particulate, and a variety of inorganic species such as the acid gases (hydrogen chloride, hydrogen fluoride, etc.).

  10. Report number codes

    SciTech Connect (OSTI)

    Nelson, R.N.

    1985-05-01

    This publication lists all report number codes processed by the Office of Scientific and Technical Information. The report codes are substantially based on the American National Standards Institute, Standard Technical Report Number (STRN)-Format and Creation Z39.23-1983. The Standard Technical Report Number (STRN) provides one of the primary methods of identifying a specific technical report. The STRN consists of two parts: The report code and the sequential number. The report code identifies the issuing organization, a specific program, or a type of document. The sequential number, which is assigned in sequence by each report issuing entity, is not included in this publication. Part I of this compilation is alphabetized by report codes followed by issuing installations. Part II lists the issuing organization followed by the assigned report code(s). In both Parts I and II, the names of issuing organizations appear for the most part in the form used at the time the reports were issued. However, for some of the more prolific installations which have had name changes, all entries have been merged under the current name.

  11. Review of consolidated Edison`s integrated resource bidding program

    SciTech Connect (OSTI)

    Goldman, C.A.; Busch, J.F.; Kahn, E.P.; Baldick, R.; Milne, A.

    1993-07-01

    Competitive bidding has emerged as the dominant method for procuring new resources by US utilities. In New York, the Public Service Commission (NYPSC) ordered the state`s seven investor-owned utilities to develop bidding programs to acquire supply and DSM resource options. Utilities were allowed significant discretion in program design in order to encourage experimentation. Competitive bidding programs pose formidable policy, design, and management challenges for utilities and their regulators. Yet, there have been few detailed case studies of bidding programs, particularly of those utilities that take on the additional challenge of having supply and DSM resources compete head-to-head for a designated block of capacity. To address that need, the New York State Energy Research and Development Authority (NYSERDA), the New York Department of Public Service, and the Department of Energy`s Integrated Resource Planning program asked Lawrence Berkeley Laboratory (LBL) to review the bidding programs of two utilities that tested the integrated ``all-sources`` approach. This study focuses primarily on Consolidated Edison Company of New York`s (Con Edison) bidding program; an earlier report discusses our review of Niagara Mohawk`s program (Goldman et al 1992). We reviewed relevant Commission decisions, utility filings and signed contracts, interviewed utility and regulatory staff, surveyed DSM bidders and a selected sample of DSM non-bidders, and analyzed the bid evaluation system used in ranking bids based on detailed scoring information on individual bids provided by Con Edison.

  12. INTERNATIONAL UNION OF OPERATING ENGINEERS NATIONAL HAZMAT PROGRAM - MILWAUKEE WORM DRIVE CIRCULAR SAW OENHP{number_sign}: 2001-02, VERSION A

    SciTech Connect (OSTI)

    Unknown

    2002-01-05

    Florida International University's (FIU) Hemispheric Center for Environmental Technology (HCET) evaluated five saws for their effectiveness in cutting specially prepared fiberglass-reinforced plywood crates. These crates were built as surrogates for crates that presently hold radioactively contaminated glove boxes at the Department of Energy's (DOE) Los Alamos facility. The Milwaukee worm drive circular saw was assessed on August 14, 2001. During the FIU test of efficacy, a team from the Operating Engineers National Hazmat Program (OENHP) evaluated the occupational safety and health issues associated with this technology. The Milwaukee worm drive circular saw is a hand-held tool with a 7 1/4-inch diameter circular blade for cutting wood. The saw contains a fixed upper and a retractable lower blade guard to prevent access to the blade during use. The unit is operated with an on/off guarded trigger switch; and is supported with a handgrip mounted on top of the saw. An adjustable lever sets the depth of cut. The retractable blade guard permits blind or plunge cuts and protects from blade access during shutdown and blade coast. Kickback, the sudden reaction to a pinched blade, is possible when using this saw and could cause the saw to lift up and out of the work piece toward the operator. Proper work position and firm control of the saw minimizes the potential for a sprain or strain. Care needs to be exercised to support the work piece properly and to not force the tool. Personal noise sampling indicated that one worker was near the Occupational Safety and Health Administration's (OSHA) Action Level of 85 decibels (dBA) while the other was at the Action Level with time-weighted averages (TWA's) of 82.7 and 84.6 dBA, respectively. These data are not entirely representative as they were gathered during a simulation and not at the actual worksite. Additional sampling should be conducted on-site, but the workers should wear hearing protection until it is determined that it

  13. Intergovernmental Programs | Department of Energy

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

    Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs The Office of Environmental Management supports, by means of grants and cooperative agreements, a number of

  14. Industrial end-use forecasting that incorporates DSM and air quality

    SciTech Connect (OSTI)

    Tutt, T.; Flory, J.

    1995-05-01

    The California Energy Commission (CEC) and major enregy utilities in California have generally depended on simple aggregate intensity or economic models to forecast energy use in the process industry sector (which covers large industries employing basic processes to transform raw materials, such as paper mills, glass plants, and cement plants). Two recent trends suggests that the time has come to develop a more disaggregate process industry forecasting model. First, recent efforts to improve air quality, especially by the South Coast Air Quality Management District (SCAQMD), could significantly affect energy use by the process industry by altering the technologies and processes employed in order to reduce emissions. Second, there is a renewed interest in Demand-Side Management (DSM), not only for utility least-cost planning, but also for improving the economic competitiveness and environmental compliance of the pro{minus}cess industries. A disaggregate forecasting model is critical to help the CEC and utilities evaluate both the air quality and DSM impacts on energy use. A crucial obstacle to the development and use of these detailed process industry forecasting models is the lack of good data about disaggregate energy use in the sector. The CEC is nearing completion of a project to begin to overcome this lack of data. The project is testing methds of developing detailed energy use data, collecting an initial database for a large portion of southern California, and providing recommendations and direction for further data collection efforts.

  15. Machinist Pipeline/Apprentice Program Program Description

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

    cost effective than previous time-based programs Moves apprentices to journeyworker status more quickly Program Coordinator: Heidi Hahn Email: hahn@lanl.gov Phone number:...

  16. Number | Open Energy Information

    Open Energy Info (EERE)

    Property:NumOfPlants Property:NumProdWells Property:NumRepWells Property:Number of Color Cameras Property:Number of Devices Deployed Property:Number of Plants included in...

  17. STEM Education Program Inventory

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

    Issue for STEM Education Program Inventory Title of Program* Requestor Contact Information First Name* Last Name* Phone Number* E-mail* Fax Number Institution Name Program Description* Issue Information Leading Organization* Location of Program / Event Program Address Program Website To select multiple options, press CTRL and click. Type of Program (if Other, enter information in the box to the right.)* Workforce Development Student Programs Public Engagement in Life Long Learning

  18. NSR Key Number Retrieval

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

    NSR Key Number Retrieval Pease enter key in the box Submit

  19. DOE/ID-Number

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

    ... by INL's Nuclear Safety Program to verify non-nuclear ... and several smaller citiescommunities (<10,000) located ... the Secretary of Energy designated a portion of ...

  20. DOE/ID-Number

    Office of Environmental Management (EM)

    in the energy sector NSTB National SCADA Test Bed Common Cyber Security Vulnerabilities ... of the National Supervisory Control and Data Acquisition (SCADA) Test Bed (NSTB) program. ...

  1. SES CANDIDATE DEVELOPMENT PROGRAM

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

    NUMBER: EMAIL ADDRESS: ASSIGNMENT LOCATION HOST ORGANIZATION: PURPOSE OF ASSIGNMENT: ... Program Manager.) SES CANDIDATE SIGNATURE DATE HOST SUPERVISOR SIGNATUREORGANIZATION

  2. Student Internship Programs Program Description

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

    for a summer high school student to 75,000 for a Ph.D. student working full-time for a year. Program Coordinator: Scott Robbins Email: srobbins@lanl.gov Phone number: 663-5621...

  3. DOE/ID-Number

    Office of Environmental Management (EM)

    data from short-term tests. To collect the necessary data as part of the R&D program and engineering-scale demonstration, more effective monitoring systems must be developed to...

  4. Summary of Characteristics and Energy Efficiency Demand-side Management Programs in the Southeastern United States

    SciTech Connect (OSTI)

    Glatt, Sandy

    2010-04-01

    This report is the first in a series that seeks to characterize energy supply and industrial sector energy consumption, and summarize successful industrial demand-side management (DSM) programs within each of the eight North American Electric Reliability Corporation (NERC) regions.

  5. New York Natural Gas Number of Commercial Consumers (Number of...

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

    Commercial Consumers (Number of Elements) New York Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers New York Number of Natural Gas ...

  6. New Mexico Natural Gas Number of Commercial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Commercial Consumers (Number of Elements) New Mexico Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers New Mexico Number of Natural ...

  7. North Dakota Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) North Dakota Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers North Dakota Number of Natural ...

  8. Quantum random number generator

    DOE Patents [OSTI]

    Pooser, Raphael C.

    2016-05-10

    A quantum random number generator (QRNG) and a photon generator for a QRNG are provided. The photon generator may be operated in a spontaneous mode below a lasing threshold to emit photons. Photons emitted from the photon generator may have at least one random characteristic, which may be monitored by the QRNG to generate a random number. In one embodiment, the photon generator may include a photon emitter and an amplifier coupled to the photon emitter. The amplifier may enable the photon generator to be used in the QRNG without introducing significant bias in the random number and may enable multiplexing of multiple random numbers. The amplifier may also desensitize the photon generator to fluctuations in power supplied thereto while operating in the spontaneous mode. In one embodiment, the photon emitter and amplifier may be a tapered diode amplifier.

  9. Final Report DOE Supported Activities through the Utility/DOE Matching Grant Program Contract Number DE FG02-95NE38111 For the Period 30 September 1995 through 30 September 2002 Extended until 30 March 2003

    SciTech Connect (OSTI)

    Stubbins, James F.

    2003-08-15

    This report covers activities in the Univesity of Illinois Department of Nulcear, Plasma and Radiological Engineering Matching Grant Program for the period form 30 September 1995 to 30 March 2003. The funds for this program include industrial partner funds which were matched, or nearly matched by DOE-NE. The industrial partner was Commonwealth Edison, which changed its corporate structure and name to Exelon during the course of the contract. The funds from the contract were used to support nuclear engineering educational needs, including undergraduate and graduate students support, purchase of laboratory equipment, support for seminar speakers and conferences, and support for new faculty members. The funds were instrumental in maintaining a first quality nuclear engineering educational program at the University of Illinois.

  10. Quantum random number generation

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

    Ma, Xiongfeng; Yuan, Xiao; Cao, Zhu; Zhang, Zhen; Qi, Bing

    2016-06-28

    Here, quantum physics can be exploited to generate true random numbers, which play important roles in many applications, especially in cryptography. Genuine randomness from the measurement of a quantum system reveals the inherent nature of quantumness -- coherence, an important feature that differentiates quantum mechanics from classical physics. The generation of genuine randomness is generally considered impossible with only classical means. Based on the degree of trustworthiness on devices, quantum random number generators (QRNGs) can be grouped into three categories. The first category, practical QRNG, is built on fully trusted and calibrated devices and typically can generate randomness at amore » high speed by properly modeling the devices. The second category is self-testing QRNG, where verifiable randomness can be generated without trusting the actual implementation. The third category, semi-self-testing QRNG, is an intermediate category which provides a tradeoff between the trustworthiness on the device and the random number generation speed.« less

  11. ALARA notes, Number 8

    SciTech Connect (OSTI)

    Khan, T.A.; Baum, J.W.; Beckman, M.C.

    1993-10-01

    This document contains information dealing with the lessons learned from the experience of nuclear plants. In this issue the authors tried to avoid the `tyranny` of numbers and concentrated on the main lessons learned. Topics include: filtration devices for air pollution abatement, crack repair and inspection, and remote handling equipment.

  12. DOE/ID-Number

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

    Public Preferences Related to Consent-Based Siting of Radioactive Waste Management Facilities for Storage and Disposal: Analyzing Variations over Time, Events, and Program Designs Prepared for US Department of Energy Nuclear Fuel Storage and Transportation Planning Project Hank C. Jenkins-Smith Carol L. Silva Kerry G. Herron Kuhika G. Ripberger Matthew Nowlin Joseph Ripberger Center for Risk and Crisis Management, University of Oklahoma Evaristo "Tito" Bonano Rob P. Rechard Sandia

  13. Document Details Document Number

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

    Document Details Document Number Date of Document Document Title/Description [Links below to each document] D195066340 Not listed. N/A REVISIONS IN STRATIGRAPHIC NOMENCLATURE OF COLUMBIA RIVER BASALT GROUP D196000240 Not listed. N/A EPA DENIAL OF LINER LEACHATE COLLECTION SYSTEM REQUIREMENTS D196005916 Not listed. N/A LATE CENOZOIC STRATIGRAPHY AND TECTONIC EVOLUTION WITHIN SUBSIDING BASIN SOUTH CENTRAL WASHINGTON D196025993 RHO-BWI-ST-14 N/A SUPRABASALT SEDIMENTS OF COLD CREEK SYNCLINE AREA

  14. Stockpile Stewardship Quarterly Volume 1, Number 4

    National Nuclear Security Administration (NNSA)

    1, Number 4 * February 2012 Message from the Assistant Deputy Administrator for Stockpile Stewardship, Chris Deeney Defense Programs Stockpile Stewardship in Action Volume 1, Number 4 Inside this Issue 2 Applying Advanced Simulation Models to Neutron Tube Ion Extraction 3 Advanced Optical Cavities for Subcritical and Hydrodynamic Experiments 5 Progress Toward Ignition on the National Ignition Facility 7 Commissioning URSA Minor: The First LTD-Based Accelerator for Radiography 8 Publication

  15. High quality draft genome sequence of Corynebacterium ulceribovis type strain IMMIB-L1395T (DSM 45146T)

    SciTech Connect (OSTI)

    Yassin, Atteyet F.; Lapidus, Alla; Han, James; Reddy, T. B. K.; Huntemann, Marcel; Pati, Amrita; Ivanova, Natalia; Markowitz, Victor; Woyke, Tanja; Klenk, Hans-Peter; Kyrpides, Nikos C.

    2015-08-05

    We report that the Corynebacterium ulceribovis strain IMMIB L-1395T (= DSM 45146T) is an aerobic to facultative anaerobic, Gram-positive, non-spore-forming, non-motile rod-shaped bacterium that was isolated from the skin of the udder of a cow, in Schleswig Holstein, Germany. The cell wall of C. ulceribovis contains corynemycolic acids. The cellular fatty acids are those described for the genus Corynebacterium, but tuberculostearic acid is not present. Here we describe the features of C. ulceribovis strain IMMIB L-1395T, together with genome sequence information and its annotation. The 2,300,451 bp long genome containing 2,104 protein-coding genes and 54 RNA-encoding genes and is part of the Genomic Encyclopedia of Type Strains, Phase I: the one thousand microbial genomes (KMG) project.

  16. High quality draft genome sequence of Corynebacterium ulceribovis type strain IMMIB-L1395T (DSM 45146T)

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

    Yassin, Atteyet F.; Lapidus, Alla; Han, James; Reddy, T. B. K.; Huntemann, Marcel; Pati, Amrita; Ivanova, Natalia; Markowitz, Victor; Woyke, Tanja; Klenk, Hans-Peter; et al

    2015-08-05

    We report that the Corynebacterium ulceribovis strain IMMIB L-1395T (= DSM 45146T) is an aerobic to facultative anaerobic, Gram-positive, non-spore-forming, non-motile rod-shaped bacterium that was isolated from the skin of the udder of a cow, in Schleswig Holstein, Germany. The cell wall of C. ulceribovis contains corynemycolic acids. The cellular fatty acids are those described for the genus Corynebacterium, but tuberculostearic acid is not present. Here we describe the features of C. ulceribovis strain IMMIB L-1395T, together with genome sequence information and its annotation. The 2,300,451 bp long genome containing 2,104 protein-coding genes and 54 RNA-encoding genes and is partmore » of the Genomic Encyclopedia of Type Strains, Phase I: the one thousand microbial genomes (KMG) project.« less

  17. Modular redundant number systems

    SciTech Connect (OSTI)

    1998-05-31

    With the increased use of public key cryptography, faster modular multiplication has become an important cryptographic issue. Almost all public key cryptography, including most elliptic curve systems, use modular multiplication. Modular multiplication, particularly for the large public key modulii, is very slow. Increasing the speed of modular multiplication is almost synonymous with increasing the speed of public key cryptography. There are two parts to modular multiplication: multiplication and modular reduction. Though there are fast methods for multiplying and fast methods for doing modular reduction, they do not mix well. Most fast techniques require integers to be in a special form. These special forms are not related and converting from one form to another is more costly than using the standard techniques. To this date it has been better to use the fast modular reduction technique coupled with standard multiplication. Standard modular reduction is much more costly than standard multiplication. Fast modular reduction (Montgomery`s method) reduces the reduction cost to approximately that of a standard multiply. Of the fast multiplication techniques, the redundant number system technique (RNS) is one of the most popular. It is simple, converting a large convolution (multiply) into many smaller independent ones. Not only do redundant number systems increase speed, but the independent parts allow for parallelization. RNS form implies working modulo another constant. Depending on the relationship between these two constants; reduction OR division may be possible, but not both. This paper describes a new technique using ideas from both Montgomery`s method and RNS. It avoids the formula problem and allows fast reduction and multiplication. Since RNS form is used throughout, it also allows the entire process to be parallelized.

  18. GEOCENTRIFUGE STUDIES OF FLOW AND TRANSPORT IN POROUS MEDIA, FINAL REPORT FOR GRANT NUMBER DE-FG02-03ER63567 TO THE UNIVERSITY OF IDAHO (RW SMITH), ENVIRONMENTAL MANAGEMENT SCIENCE PROGRAM PROJECT NUMBER 86598, COUPLED FLOW AND REACTIVITY IN VARIABLY SATURATED POROUS MEDIA

    SciTech Connect (OSTI)

    Robert W. Smith; Carl D. Palmer; Earl D. Mattson

    2007-06-15

    Improved models of contaminant migration in heterogeneous, variably saturated porous media are required to better define the long-term stewardship requirements for U.S. Department of Energy (DOE) lands and to assist in the design of effective vadose-zone barriers to contaminant migrations. The development of these improved models requires field and laboratory results to evaluate their efficacy. However, controlled laboratory experiments simulating vadose conditions can require extensive period of time, and often are conducted at condition near saturation rather than the much drier conditions common in many contaminated arid vadose zone sites. Collaborative research undertaken by the Idaho National Laboratory (INL) and the University of Idaho as part of this Environmental Management Science Program project focused on the development and evaluation of geocentrifuge techniques and equipment that allows vadose zone experiments to be conducted for relevant conditions in time frames not possible in conventional bench top experiments. A key and novel aspect of the research was the use of the 2-meter radius geocentrifuge capabilities at the Idaho National Laboratory to conduct unsaturated transport experiments. Specifically, the following activities were conducted ** Reviewing of the theory of unsaturated flow in the geocentrifuge to establish the range of centrifuge accelerations/experimental conditions and the translation of centrifuge results to 1 gravity applications. ** Designing, constructing, and testing of in-flight experimental apparatus allowing the replication of traditional bench top unsaturated transport experiments on the geocentrifuge. ** Performing unsaturated 1-dimenstional column geocentrifuge experiments using conservative tracers to evaluate the effects of increased centrifugal acceleration on derived transport properties and assessing the scaling relationships for these properties. Because the application of geocentrifuge techniques to vadose transport

  19. New Hampshire Natural Gas Number of Commercial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Commercial Consumers (Number of Elements) New Hampshire Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  20. New Hampshire Natural Gas Number of Industrial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Industrial Consumers (Number of Elements) New Hampshire Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  1. New Hampshire Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) New Hampshire Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  2. Virginia Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) Virginia Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  3. Utah Natural Gas Number of Industrial Consumers (Number of Elements...

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

    Industrial Consumers (Number of Elements) Utah Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 ...

  4. Wisconsin Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) Wisconsin Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  5. Virginia Natural Gas Number of Commercial Consumers (Number of...

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

    Commercial Consumers (Number of Elements) Virginia Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  6. Utah Natural Gas Number of Residential Consumers (Number of Elements...

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

    Residential Consumers (Number of Elements) Utah Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  7. Vermont Natural Gas Number of Residential Consumers (Number of...

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

    Residential Consumers (Number of Elements) Vermont Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  8. Utah Natural Gas Number of Commercial Consumers (Number of Elements...

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

    Commercial Consumers (Number of Elements) Utah Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 ...

  9. Virginia Natural Gas Number of Industrial Consumers (Number of...

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

    Industrial Consumers (Number of Elements) Virginia Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  10. West Virginia Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) West Virginia Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  11. Wisconsin Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) Wisconsin Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  12. Vermont Natural Gas Number of Commercial Consumers (Number of...

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

    Commercial Consumers (Number of Elements) Vermont Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  13. West Virginia Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) West Virginia Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  14. Washington Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) Washington Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  15. Washington Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) Washington Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  16. Washington Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) Washington Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  17. Wisconsin Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) Wisconsin Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  18. Vermont Natural Gas Number of Industrial Consumers (Number of...

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

    Industrial Consumers (Number of Elements) Vermont Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  19. West Virginia Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) West Virginia Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  20. New York Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) New York Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  1. New Mexico Natural Gas Number of Residential Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Residential Consumers (Number of Elements) New Mexico Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  2. New Jersey Natural Gas Number of Residential Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Residential Consumers (Number of Elements) New Jersey Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  3. New Mexico Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) New Mexico Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  4. North Carolina Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) North Carolina Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  5. North Carolina Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) North Carolina Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  6. North Dakota Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) North Dakota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  7. North Dakota Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) North Dakota Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  8. North Carolina Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) North Carolina Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  9. Chaotic advection at large Pclet number: Electromagnetically driven experiments, numerical simulations, and theoretical predictions

    SciTech Connect (OSTI)

    Figueroa, Aldo [Facultad de Ciencias, Universidad Autnoma del Estado de Morelos, Cuernavaca, Morelos 62209 (Mexico)] [Facultad de Ciencias, Universidad Autnoma del Estado de Morelos, Cuernavaca, Morelos 62209 (Mexico); Meunier, Patrice; Villermaux, Emmanuel [Aix-Marseille Univ., CNRS, Centrale Marseille, IRPHE, Marseille F-13384 (France)] [Aix-Marseille Univ., CNRS, Centrale Marseille, IRPHE, Marseille F-13384 (France); Cuevas, Sergio; Ramos, Eduardo [Instituto de Energas Renovables, Universidad Nacional Autnoma de Mxico, A.P. 34, Temixco, Morelos 62580 (Mexico)] [Instituto de Energas Renovables, Universidad Nacional Autnoma de Mxico, A.P. 34, Temixco, Morelos 62580 (Mexico)

    2014-01-15

    We present a combination of experiment, theory, and modelling on laminar mixing at large Pclet number. The flow is produced by oscillating electromagnetic forces in a thin electrolytic fluid layer, leading to oscillating dipoles, quadrupoles, octopoles, and disordered flows. The numerical simulations are based on the Diffusive Strip Method (DSM) which was recently introduced (P. Meunier and E. Villermaux, The diffusive strip method for scalar mixing in two-dimensions, J. Fluid Mech. 662, 134172 (2010)) to solve the advection-diffusion problem by combining Lagrangian techniques and theoretical modelling of the diffusion. Numerical simulations obtained with the DSM are in reasonable agreement with quantitative dye visualization experiments of the scalar fields. A theoretical model based on log-normal Probability Density Functions (PDFs) of stretching factors, characteristic of homogeneous turbulence in the Batchelor regime, allows to predict the PDFs of scalar in agreement with numerical and experimental results. This model also indicates that the PDFs of scalar are asymptotically close to log-normal at late stages, except for the large concentration levels which correspond to low stretching factors.

  10. The Program Administrator Cost of Saved Energy for Utility Customer-Funded Energy Efficiency Programs

    SciTech Connect (OSTI)

    Billingsley, Megan A.; Hoffman, Ian M.; Stuart, Elizabeth; Schiller, Steven R.; Goldman, Charles A.; LaCommare, Kristina

    2014-03-19

    End-use energy efficiency is increasingly being relied upon as a resource for meeting electricity and natural gas utility system needs within the United States. There is a direct connection between the maturation of energy efficiency as a resource and the need for consistent, high-quality data and reporting of efficiency program costs and impacts. To support this effort, LBNL initiated the Cost of Saved Energy Project (CSE Project) and created a Demand-Side Management (DSM) Program Impacts Database to provide a resource for policy makers, regulators, and the efficiency industry as a whole. This study is the first technical report of the LBNL CSE Project and provides an overview of the project scope, approach, and initial findings, including: • Providing a proof of concept that the program-level cost and savings data can be collected, organized, and analyzed in a systematic fashion; • Presenting initial program, sector, and portfolio level results for the program administrator CSE for a recent time period (2009-2011); and • Encouraging state and regional entities to establish common reporting definitions and formats that would make the collection and comparison of CSE data more reliable. The LBNL DSM Program Impacts Database includes the program results reported to state regulators by more than 100 program administrators in 31 states, primarily for the years 2009–2011. In total, we have compiled cost and energy savings data on more than 1,700 programs over one or more program-years for a total of more than 4,000 program-years’ worth of data, providing a rich dataset for analyses. We use the information to report costs-per-unit of electricity and natural gas savings for utility customer-funded, end-use energy efficiency programs. The program administrator CSE values are presented at national, state, and regional levels by market sector (e.g., commercial, industrial, residential) and by program type (e.g., residential whole home programs, commercial new

  11. Recent program evaluations: Implications for long-run planning

    SciTech Connect (OSTI)

    Baxter, L.W.; Schultz, D.K.

    1994-06-08

    Demand-side management (DSM) remains the centerpiece of California`s energy policy. Over the coming decade, California plans to meet 30 percent of the state`s incremental electricity demand and 50 percent of its peak demand with (DSM) programs. The major investor-owned utilities in California recently completed the first round of program impact studies for energy efficiency programs implemented in 1990 and 1991. The central focus of this paper is to assess the resource planning and policy implications of Pacific Gas and Electric (PG&E) Company`s recent program evaluations. The paper has three goals. First, we identify and discuss major issues that surfaced from our attempt to apply evaluation results to forecasting and planning questions. Second, we review and summarize the evaluation results for PG&E`s primary energy efficiency programs. Third, we change long-run program assumptions, based on our assessment in the second task, and then examine the impacts of these changes on a recent PG&E demand-side management forecast and resource plan.

  12. Stockpile Stewardship Quarterly, Volume 2, Number 1

    National Nuclear Security Administration (NNSA)

    1 * May 2012 Message from the Assistant Deputy Administrator for Stockpile Stewardship, Chris Deeney Defense Programs Stockpile Stewardship in Action Volume 2, Number 1 Inside this Issue 2 LANL and ANL Complete Groundbreaking Shock Experiments at the Advanced Photon Source 3 Characterization of Activity-Size-Distribution of Nuclear Fallout 5 Modeling Mix in High-Energy-Density Plasma 6 Quality Input for Microscopic Fission Theory 8 Fiber Reinforced Composites Under Pressure: A Case Study in

  13. High-quality draft genome sequence of Gracilimonas tropica CL-CB462T (DSM 19535T), isolated from a Synechococcus culture

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

    Choi, Dong Han; Ahn, Chisang; Jang, Gwang Il; Lapidus, Alla; Han, James; Reddy, T. B. K.; Huntemann, Marcel; Pati, Amrita; Ivanova, Natalia; Markowitz, Victor; et al

    2015-11-11

    Gracilimonas tropica Choi et al. 2009 is a member of order Sphingobacteriales, class Sphingobacteriia. Three species of the genus Gracilimonas have been isolated from marine seawater or a salt mine and showed extremely halotolerant and mesophilic features, although close relatives are extremely halophilic or thermophilic. The type strain of the type species of Gracilimonas, G. tropica DSM19535T, was isolated from a Synechococcus culture which was established from the tropical sea-surface water of the Pacific Ocean. The genome of the strain DSM19535T was sequenced through the Genomic Encyclopedia of Type Strains, Phase I: the one thousand microbial genomes project. Here, wemore » describe the genomic features of the strain. The 3,831,242 bp long draft genome consists of 48 contigs with 3373 protein-coding and 53 RNA genes. Finally, the strain seems to adapt to phosphate limitation and requires amino acids from external environment. In addition, genomic analyses and pasteurization experiment suggested that G. tropica DSM19535T did not form spore.« less

  14. High-quality draft genome sequence of Gracilimonas tropica CL-CB462T (DSM 19535T), isolated from a Synechococcus culture

    SciTech Connect (OSTI)

    Choi, Dong Han; Ahn, Chisang; Jang, Gwang Il; Lapidus, Alla; Han, James; Reddy, T. B. K.; Huntemann, Marcel; Pati, Amrita; Ivanova, Natalia; Markowitz, Victor; Rohde, Manfred; Tindall, Brian; Göker, Markus; Woyke, Tanja; Klenk, Hans-Peter; Kyrpides, Nikos C.; Cho, Byung Cheol

    2015-11-11

    Gracilimonas tropica Choi et al. 2009 is a member of order Sphingobacteriales, class Sphingobacteriia. Three species of the genus Gracilimonas have been isolated from marine seawater or a salt mine and showed extremely halotolerant and mesophilic features, although close relatives are extremely halophilic or thermophilic. The type strain of the type species of Gracilimonas, G. tropica DSM19535T, was isolated from a Synechococcus culture which was established from the tropical sea-surface water of the Pacific Ocean. The genome of the strain DSM19535T was sequenced through the Genomic Encyclopedia of Type Strains, Phase I: the one thousand microbial genomes project. Here, we describe the genomic features of the strain. The 3,831,242 bp long draft genome consists of 48 contigs with 3373 protein-coding and 53 RNA genes. Finally, the strain seems to adapt to phosphate limitation and requires amino acids from external environment. In addition, genomic analyses and pasteurization experiment suggested that G. tropica DSM19535T did not form spore.

  15. Number

    Office of Legacy Management (LM)

    engaged in the production of thorium compounds. The purpose of the trip vas to: l 1. Learn the type of chemical processes employed in the thorium industry (thorium nitrate). 2. ...

  16. Property:NumberOfPrograms | Open Energy Information

    Open Energy Info (EERE)

    25) A Afghanistan + 5 + Albania + 5 + Algeria + 6 + American Samoa + 0 + Andorra + 0 + Angola + 1 + Anguilla + 1 + Antigua and Barbuda + 6 + Argentina + 12 + Armenia + 6 + Aruba +...

  17. Property:NumberOfDOELabPrograms | Open Energy Information

    Open Energy Info (EERE)

    25) A Afghanistan + 3 + Albania + 0 + Algeria + 1 + American Samoa + 0 + Andorra + 0 + Angola + 0 + Anguilla + 1 + Antigua and Barbuda + 1 + Argentina + 1 + Armenia + 0 + Aruba + 1...

  18. Property:NumberOfLowCarbonPrograms | Open Energy Information

    Open Energy Info (EERE)

    25) A Afghanistan + 0 + Albania + 0 + Algeria + 0 + American Samoa + 0 + Andorra + 0 + Angola + 0 + Anguilla + 0 + Antigua and Barbuda + 0 + Argentina + 0 + Armenia + 0 + Aruba + 0...

  19. Property:NumberOfLowCarbonPlanningProgramsAgriculture | Open...

    Open Energy Info (EERE)

    25) A Afghanistan + 0 + Albania + 0 + Algeria + 0 + American Samoa + 0 + Andorra + 0 + Angola + 1 + Anguilla + 0 + Antigua and Barbuda + 1 + Argentina + 4 + Armenia + 2 + Aruba + 0...

  20. Model Fire Protection Program

    Broader source: Energy.gov [DOE]

    To facilitate conformance with its fire safety directives and the implementation of a comprehensive fire protection program, DOE has developed a number of "model" program documents. These include a comprehensive model fire protection program, model fire hazards analyses and assessments, fire protection system inspection and testing procedures, and related material.

  1. Alaska Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Alaska Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 10 11 8 1990's 8 8 10 11 11 9 202 7 7 9 2000's 9 8 9 9 10 12 11 11 6 3 2010's 3 5 3 3 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016 Referring Pages: Number of Natural

  2. Hawaii Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Hawaii Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 27 26 29 2000's 28 28 29 29 29 28 26 27 27 25 2010's 24 24 22 22 23 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016 Referring Pages: Number of Natural Gas Industrial

  3. ARM - Measurement - Particle number concentration

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

    number concentration ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Particle number concentration The number of particles present in any given volume of air. Categories Aerosols Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including those

  4. Total Number of Operable Refineries

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

    Data Series: Total Number of Operable Refineries Number of Operating Refineries Number of Idle Refineries Atmospheric Crude Oil Distillation Operable Capacity (B/CD) Atmospheric Crude Oil Distillation Operating Capacity (B/CD) Atmospheric Crude Oil Distillation Idle Capacity (B/CD) Atmospheric Crude Oil Distillation Operable Capacity (B/SD) Atmospheric Crude Oil Distillation Operating Capacity (B/SD) Atmospheric Crude Oil Distillation Idle Capacity (B/SD) Vacuum Distillation Downstream Charge

  5. Report/Product Number(s) DOE/ER/64701 DOE Award/Contract Number...

    Office of Scientific and Technical Information (OSTI)

    2013 SPONSORING DOE PROGRAM OFFICE DOE Plant Feedstock Genomics SUBJECT CATEGORIES ... We are currently preparing plant material from these selected transgenic plants to assess ...

  6. Compendium of Experimental Cetane Numbers

    SciTech Connect (OSTI)

    Yanowitz, J.; Ratcliff, M. A.; McCormick, R. L.; Taylor, J. D.; Murphy, M. J.

    2014-08-01

    This report is an updated version of the 2004 Compendium of Experimental Cetane Number Data and presents a compilation of measured cetane numbers for pure chemical compounds. It includes all available single compound cetane number data found in the scientific literature up until March 2014 as well as a number of unpublished values, most measured over the past decade at the National Renewable Energy Laboratory. This Compendium contains cetane values for 389 pure compounds, including 189 hydrocarbons and 201 oxygenates. More than 250 individual measurements are new to this version of the Compendium. For many compounds, numerous measurements are included, often collected by different researchers using different methods. Cetane number is a relative ranking of a fuel's autoignition characteristics for use in compression ignition engines; it is based on the amount of time between fuel injection and ignition, also known as ignition delay. The cetane number is typically measured either in a single-cylinder engine or a constant volume combustion chamber. Values in the previous Compendium derived from octane numbers have been removed, and replaced with a brief analysis of the correlation between cetane numbers and octane numbers. The discussion on the accuracy and precision of the most commonly used methods for measuring cetane has been expanded and the data has been annotated extensively to provide additional information that will help the reader judge the relative reliability of individual results.

  7. MENTEE QUESTIONNAIRE Name: Title: Email: Office Phone Number:

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

    MENTEE QUESTIONNAIRE Name: Title: Email: Office Phone Number: Office Address: Why are you interested in the mentoring program? (This information will be included with the invitation to your potential mentor.) What goals do you want to work on during your participation in the mentoring program? Is there someone you would like to be your mentor? Yes No If yes, please list their name and any other possible mentors in order of preference: Expectations of the Mentoring Program How long? 6-months

  8. Maine Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Maine Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 73 73 74 1990's 80 81 80 66 89 74 87 81 110 108 2000's 178 233 66 65 69 69 73 76 82 85 2010's 94 102 108 120 126 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016 Referring

  9. Montana Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Montana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 435 435 428 1990's 457 452 459 462 453 463 466 462 454 397 2000's 71 73 439 412 593 716 711 693 693 396 2010's 384 381 372 372 369 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  10. Wyoming Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Wyoming Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 190 200 230 1990's 284 228 244 194 135 126 170 194 317 314 2000's 308 295 877 179 121 127 133 133 155 130 2010's 120 123 127 132 131 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  11. Nevada Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Nevada Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 93 98 100 1990's 100 113 114 117 119 120 121 93 93 109 2000's 90 90 96 97 179 192 207 220 189 192 2010's 184 177 177 195 218 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016

  12. Arizona Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Arizona Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 358 344 354 1990's 526 532 532 526 519 530 534 480 514 555 2000's 526 504 488 450 414 425 439 395 383 390 2010's 368 371 379 383 386 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  13. Delaware Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Delaware Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 241 233 235 1990's 240 243 248 249 252 253 250 265 257 264 2000's 297 316 182 184 186 179 170 185 165 112 2010's 114 129 134 138 141 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  14. Florida Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Florida Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 575 552 460 1990's 452 377 388 433 481 515 517 561 574 573 2000's 520 518 451 421 398 432 475 467 449 607 2010's 581 630 507 528 520 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  15. Idaho Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Idaho Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 219 132 64 1990's 62 65 66 75 144 167 183 189 203 200 2000's 217 198 194 191 196 195 192 188 199 187 2010's 184 178 179 183 189 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  16. Rhode Island Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) Rhode Island Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,158 1,152 1,122 1990's 1,135 1,107 1,096 1,066 1,064 359 363 336 325 302 2000's 317 283 54 236 223 223 245 256 243 260 2010's 249 245 248 271 266 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release

  17. South Dakota Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) South Dakota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 261 267 270 1990's 275 283 319 355 381 396 444 481 464 445 2000's 416 402 533 526 475 542 528 548 598 598 2010's 580 556 574 566 575 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016

  18. Interim Project Results: United Parcel Service's Second-Generation Hybrid-Electric Delivery Vans (Fact Sheet), Vehicle Technologies Program (VTP)

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

    Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs Intergovernmental Programs The Office of Environmental Management supports, by means of grants and cooperative agreements, a number of

  19. Lessons learned from new construction utility demand side management programs and their implications for implementing building energy codes

    SciTech Connect (OSTI)

    Wise, B.K.; Hughes, K.R.; Danko, S.L.; Gilbride, T.L.

    1994-07-01

    This report was prepared for the US Department of Energy (DOE) Office of Codes and Standards by the Pacific Northwest Laboratory (PNL) through its Building Energy Standards Program (BESP). The purpose of this task was to identify demand-side management (DSM) strategies for new construction that utilities have adopted or developed to promote energy-efficient design and construction. PNL conducted a survey of utilities and used the information gathered to extrapolate lessons learned and to identify evolving trends in utility new-construction DSM programs. The ultimate goal of the task is to identify opportunities where states might work collaboratively with utilities to promote the adoption, implementation, and enforcement of energy-efficient building energy codes.

  20. Departmental Business Instrument Numbering System

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    2005-01-27

    The Order prescribes the procedures for assigning identifying numbers to all Department of Energy (DOE) and National Nuclear Security Administration (NNSA) business instruments. Cancels DOE O 540.1. Canceled by DOE O 540.1B.

  1. Departmental Business Instrument Numbering System

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    2000-12-05

    To prescribe procedures for assigning identifying numbers to all Department of Energy (DOE), including the National Nuclear Security Administration, business instruments. Cancels DOE 1331.2B. Canceled by DOE O 540.1A.

  2. Indiana Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Indiana Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 116,571 119,458 122,803 1990's 124,919 128,223 129,973 131,925 134,336 137,162 139,097 140,515 141,307 145,631 2000's 148,411 148,830 150,092 151,586 151,943 159,649 154,322 155,885 157,223 155,615 2010's 156,557 161,293 158,213 158,965 159,596 - = No Data Reported; -- = Not Applicable; NA = Not

  3. Indiana Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Indiana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,497 5,696 6,196 1990's 6,439 6,393 6,358 6,508 6,314 6,250 6,586 6,920 6,635 19,069 2000's 10,866 9,778 10,139 8,913 5,368 5,823 5,350 5,427 5,294 5,190 2010's 5,145 5,338 5,204 5,178 5,098 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  4. Indiana Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Indiana Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,250,476 1,275,401 1,306,747 1990's 1,327,772 1,358,640 1,377,023 1,402,770 1,438,483 1,463,640 1,489,647 1,509,142 1,531,914 1,570,253 2000's 1,604,456 1,613,373 1,657,640 1,644,715 1,588,738 1,707,195 1,661,186 1,677,857 1,678,158 1,662,663 2010's 1,669,026 1,707,148 1,673,132 1,681,841 1,693,267

  5. Iowa Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Iowa Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 80,797 81,294 82,549 1990's 83,047 84,387 85,325 86,452 86,918 88,585 89,663 90,643 91,300 92,306 2000's 93,836 95,485 96,496 96,712 97,274 97,767 97,823 97,979 98,144 98,416 2010's 98,396 98,541 99,113 99,017 99,182 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  6. Iowa Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Iowa Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,033 1,937 1,895 1990's 1,883 1,866 1,835 1,903 1,957 1,957 2,066 1,839 1,862 1,797 2000's 1,831 1,830 1,855 1,791 1,746 1,744 1,670 1,651 1,652 1,626 2010's 1,528 1,465 1,469 1,491 1,572 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  7. Iowa Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Iowa Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 690,532 689,655 701,687 1990's 706,842 716,088 729,081 740,722 750,678 760,848 771,109 780,746 790,162 799,015 2000's 812,323 818,313 824,218 832,230 839,415 850,095 858,915 865,553 872,980 875,781 2010's 879,713 883,733 892,123 895,414 900,420 - = No Data Reported; -- = Not Applicable; NA = Not

  8. Kansas Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Kansas Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 82,934 83,810 85,143 1990's 85,539 86,874 86,840 87,735 86,457 88,163 89,168 85,018 89,654 86,003 2000's 87,007 86,592 87,397 88,030 86,640 85,634 85,686 85,376 84,703 84,715 2010's 84,446 84,874 84,673 84,969 85,867 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  9. Kansas Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Kansas Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 4,440 4,314 4,366 1990's 4,357 3,445 3,296 4,369 3,560 3,079 2,988 7,014 10,706 5,861 2000's 8,833 9,341 9,891 9,295 8,955 8,300 8,152 8,327 8,098 7,793 2010's 7,664 7,954 7,970 7,877 7,429 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  10. Kansas Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Kansas Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 725,676 733,101 731,792 1990's 747,081 753,839 762,545 777,658 773,357 797,524 804,213 811,975 841,843 824,803 2000's 833,662 836,486 843,353 850,464 855,272 856,761 862,203 858,304 853,125 855,454 2010's 853,842 854,730 854,800 858,572 861,092 - = No Data Reported; -- = Not Applicable; NA = Not

  11. Kentucky Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Kentucky Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 63,024 63,971 65,041 1990's 67,086 68,461 69,466 71,998 73,562 74,521 76,079 77,693 80,147 80,283 2000's 81,588 81,795 82,757 84,110 84,493 85,243 85,236 85,210 84,985 83,862 2010's 84,707 84,977 85,129 85,999 85,318 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  12. Kentucky Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Kentucky Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,391 1,436 1,443 1990's 1,544 1,587 1,608 1,585 1,621 1,630 1,633 1,698 1,864 1,813 2000's 1,801 1,701 1,785 1,695 1,672 1,698 1,658 1,599 1,585 1,715 2010's 1,742 1,705 1,720 1,767 1,780 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  13. Kentucky Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Kentucky Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 596,320 606,106 614,058 1990's 624,477 633,942 644,281 654,664 668,774 685,481 696,989 713,509 726,960 735,371 2000's 744,816 749,106 756,234 763,290 767,022 770,080 770,171 771,047 753,531 754,761 2010's 758,129 759,584 757,790 761,575 760,131 - = No Data Reported; -- = Not Applicable; NA = Not

  14. Louisiana Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Louisiana Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 67,382 66,472 64,114 1990's 62,770 61,574 61,030 62,055 62,184 62,930 62,101 62,270 63,029 62,911 2000's 62,710 62,241 62,247 63,512 60,580 58,409 57,097 57,127 57,066 58,396 2010's 58,562 58,749 63,381 59,147 58,611 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  15. Louisiana Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Louisiana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,617 1,503 1,531 1990's 1,504 1,469 1,452 1,592 1,737 1,383 1,444 1,406 1,380 1,397 2000's 1,318 1,440 1,357 1,291 1,460 1,086 962 945 988 954 2010's 942 920 963 916 883 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  16. Louisiana Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Louisiana Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 952,079 946,970 934,472 1990's 934,007 936,423 940,403 941,294 945,387 957,558 945,967 962,786 962,436 961,925 2000's 964,133 952,753 957,048 958,795 940,400 905,857 868,353 879,612 886,084 889,570 2010's 893,400 897,513 963,688 901,635 899,378 - = No Data Reported; -- = Not Applicable; NA = Not

  17. Maine Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Maine Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3,435 3,731 3,986 1990's 4,250 4,455 4,838 4,979 5,297 5,819 6,414 6,606 6,662 6,582 2000's 6,954 6,936 7,375 7,517 7,687 8,178 8,168 8,334 8,491 8,815 2010's 9,084 9,681 10,179 11,415 11,810 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  18. Maine Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Maine Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 12,134 11,933 11,902 1990's 12,000 12,424 13,766 13,880 14,104 14,917 14,982 15,221 15,646 15,247 2000's 17,111 17,302 17,921 18,385 18,707 18,633 18,824 18,921 19,571 20,806 2010's 21,142 22,461 23,555 24,765 27,047 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  19. Maryland Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Maryland Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 51,252 53,045 54,740 1990's 55,576 61,878 62,858 63,767 64,698 66,094 69,991 69,056 67,850 69,301 2000's 70,671 70,691 71,824 72,076 72,809 73,780 74,584 74,856 75,053 75,771 2010's 75,192 75,788 75,799 77,117 77,846 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  20. Maryland Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Maryland Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,222 5,397 5,570 1990's 5,646 520 514 496 516 481 430 479 1,472 536 2000's 329 795 1,434 1,361 1,354 1,325 1,340 1,333 1,225 1,234 2010's 1,255 1,226 1,163 1,173 1,179 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release

  1. Maryland Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Maryland Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 755,294 760,754 767,219 1990's 774,707 782,373 894,677 807,204 824,137 841,772 871,012 890,195 901,455 939,029 2000's 941,384 959,772 978,319 987,863 1,009,455 1,024,955 1,040,941 1,053,948 1,057,521 1,067,807 2010's 1,071,566 1,077,168 1,078,978 1,099,272 1,101,292 - = No Data Reported; -- = Not

  2. Massachusetts Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) Massachusetts Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 84,636 93,005 92,252 1990's 85,775 88,746 85,873 102,187 92,744 104,453 105,889 107,926 108,832 113,177 2000's 117,993 120,984 122,447 123,006 125,107 120,167 126,713 128,965 242,693 153,826 2010's 144,487 138,225 142,825 144,246 139,556 - = No Data Reported; -- = Not Applicable;

  3. Massachusetts Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) Massachusetts Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,626 7,199 13,057 1990's 6,539 5,006 8,723 7,283 8,019 10,447 10,952 11,058 11,245 8,027 2000's 8,794 9,750 9,090 11,272 10,949 12,019 12,456 12,678 36,928 19,208 2010's 12,751 10,721 10,840 11,063 10,946 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  4. Massachusetts Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Massachusetts Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,082,777 1,100,635 1,114,920 1990's 1,118,429 1,127,536 1,137,911 1,155,443 1,179,869 1,180,860 1,188,317 1,204,494 1,212,486 1,232,887 2000's 1,278,781 1,283,008 1,295,952 1,324,715 1,306,142 1,297,508 1,348,848 1,361,470 1,236,480 1,370,353 2010's 1,389,592 1,408,314 1,447,947

  5. Michigan Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Michigan Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 178,469 185,961 191,474 1990's 195,766 198,890 201,561 204,453 207,629 211,817 214,843 222,726 224,506 227,159 2000's 230,558 225,109 247,818 246,123 246,991 253,415 254,923 253,139 252,382 252,017 2010's 249,309 249,456 249,994 250,994 253,127 - = No Data Reported; -- = Not Applicable; NA = Not

  6. Michigan Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Michigan Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 10,885 11,117 11,452 1990's 11,500 11,446 11,460 11,425 11,308 11,454 11,848 12,233 11,888 14,527 2000's 11,384 11,210 10,468 10,378 10,088 10,049 9,885 9,728 10,563 18,186 2010's 9,332 9,088 8,833 8,497 8,156 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  7. Michigan Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Michigan Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,452,554 2,491,149 2,531,304 1990's 2,573,570 2,609,561 2,640,579 2,677,085 2,717,683 2,767,190 2,812,876 2,859,483 2,903,698 2,949,628 2000's 2,999,737 3,011,205 3,110,743 3,140,021 3,161,370 3,187,583 3,193,920 3,188,152 3,172,623 3,169,026 2010's 3,152,468 3,153,895 3,161,033 3,180,349

  8. Minnesota Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Minnesota Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 88,789 90,256 92,916 1990's 95,474 97,388 99,707 93,062 102,857 103,874 105,531 108,686 110,986 114,127 2000's 116,529 119,007 121,751 123,123 125,133 126,310 129,149 128,367 130,847 131,801 2010's 132,163 132,938 134,394 135,557 136,382 - = No Data Reported; -- = Not Applicable; NA = Not Available;

  9. Minnesota Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Minnesota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,585 2,670 2,638 1990's 2,574 2,486 2,515 2,477 2,592 2,531 2,564 2,233 2,188 2,267 2000's 2,025 1,996 2,029 2,074 2,040 1,432 1,257 1,146 1,131 2,039 2010's 2,106 1,770 1,793 1,870 1,878 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  10. Minnesota Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Minnesota Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 872,148 894,380 911,001 1990's 946,107 970,941 998,201 1,074,631 1,049,263 1,080,009 1,103,709 1,134,019 1,161,423 1,190,190 2000's 1,222,397 1,249,748 1,282,751 1,308,143 1,338,061 1,364,237 1,401,362 1,401,623 1,413,162 1,423,703 2010's 1,429,681 1,436,063 1,445,824 1,459,134 1,472,663 - = No

  11. Mississippi Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Mississippi Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 43,362 44,170 44,253 1990's 43,184 43,693 44,313 45,310 43,803 45,444 46,029 47,311 45,345 47,620 2000's 50,913 51,109 50,468 50,928 54,027 54,936 55,741 56,155 55,291 50,713 2010's 50,537 50,636 50,689 50,153 50,238 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  12. Mississippi Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Mississippi Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,312 1,263 1,282 1990's 1,317 1,314 1,327 1,324 1,313 1,298 1,241 1,199 1,165 1,246 2000's 1,199 1,214 1,083 1,161 996 1,205 1,181 1,346 1,132 1,141 2010's 980 982 936 933 943 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  13. Mississippi Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Mississippi Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 370,094 372,238 376,353 1990's 382,251 386,264 392,155 398,472 405,312 415,123 418,442 423,397 415,673 426,352 2000's 434,501 438,069 435,146 438,861 445,212 445,856 437,669 445,043 443,025 437,715 2010's 436,840 442,479 442,840 445,589 444,423 - = No Data Reported; -- = Not

  14. Missouri Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Missouri Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 96,711 97,939 99,721 1990's 105,164 117,675 125,174 125,571 132,378 130,318 133,445 135,553 135,417 133,464 2000's 133,969 135,968 137,924 140,057 141,258 142,148 143,632 142,965 141,529 140,633 2010's 138,670 138,214 144,906 142,495 143,024 - = No Data Reported; -- = Not Applicable; NA = Not

  15. Missouri Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Missouri Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,832 2,880 3,063 1990's 3,140 3,096 2,989 3,040 3,115 3,033 3,408 3,097 3,151 3,152 2000's 3,094 3,085 2,935 3,115 3,600 3,545 3,548 3,511 3,514 3,573 2010's 3,541 3,307 3,692 3,538 3,497 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  16. Missouri Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Missouri Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,180,546 1,194,985 1,208,523 1990's 1,213,305 1,211,342 1,220,203 1,225,921 1,281,007 1,259,102 1,275,465 1,293,032 1,307,563 1,311,865 2000's 1,324,282 1,326,160 1,340,726 1,343,614 1,346,773 1,348,743 1,353,892 1,354,173 1,352,015 1,348,781 2010's 1,348,549 1,342,920 1,389,910 1,357,740

  17. Montana Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Montana Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 21,382 22,246 22,219 1990's 23,331 23,185 23,610 24,373 25,349 26,329 26,374 27,457 28,065 28,424 2000's 29,215 29,429 30,250 30,814 31,357 31,304 31,817 32,472 33,008 33,731 2010's 34,002 34,305 34,504 34,909 35,205 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  18. Montana Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Montana Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 167,883 171,785 171,156 1990's 174,384 177,726 182,641 188,879 194,357 203,435 205,199 209,806 218,851 222,114 2000's 224,784 226,171 229,015 232,839 236,511 240,554 245,883 247,035 253,122 255,472 2010's 257,322 259,046 259,957 262,122 265,849 - = No Data Reported; -- = Not Applicable; NA = Not

  19. Wyoming Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Wyoming Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 15,342 15,093 14,012 1990's 13,767 14,931 15,064 15,315 15,348 15,580 17,036 15,907 16,171 16,317 2000's 16,366 16,027 16,170 17,164 17,490 17,904 18,016 18,062 19,286 19,843 2010's 19,977 20,146 20,387 20,617 20,894 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  20. Wyoming Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Wyoming Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 113,175 112,126 113,129 1990's 113,598 113,463 114,793 116,027 117,385 119,544 131,910 125,740 127,324 127,750 2000's 129,274 129,897 133,445 135,441 137,434 140,013 142,385 143,644 152,439 153,062 2010's 153,852 155,181 157,226 158,889 160,896 - = No Data Reported; -- = Not Applicable; NA = Not

  1. Nebraska Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Nebraska Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 60,707 61,365 60,377 1990's 60,405 60,947 61,319 60,599 62,045 61,275 61,117 51,661 63,819 53,943 2000's 55,194 55,692 56,560 55,999 57,087 57,389 56,548 55,761 58,160 56,454 2010's 56,246 56,553 56,608 58,005 57,191 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  2. Nebraska Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Nebraska Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 675 684 702 1990's 712 718 696 718 766 2,432 2,234 11,553 10,673 10,342 2000's 10,161 10,504 9,156 9,022 8,463 7,973 7,697 7,668 11,627 7,863 2010's 7,912 7,955 8,160 8,495 8,791 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  3. Nebraska Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Nebraska Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 400,218 403,657 406,723 1990's 407,094 413,354 418,611 413,358 428,201 427,720 439,931 444,970 523,790 460,173 2000's 475,673 476,275 487,332 492,451 497,391 501,279 499,504 494,005 512,013 512,551 2010's 510,776 514,481 515,338 527,397 522,408 - = No Data Reported; -- = Not Applicable; NA = Not

  4. Nevada Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Nevada Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 18,294 18,921 19,924 1990's 20,694 22,124 22,799 23,207 24,521 25,593 26,613 27,629 29,030 30,521 2000's 31,789 32,782 33,877 34,590 35,792 37,093 38,546 40,128 41,098 41,303 2010's 40,801 40,944 41,192 41,710 42,338 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  5. Nevada Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Nevada Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 213,422 219,981 236,237 1990's 256,119 283,307 295,714 305,099 336,353 364,112 393,783 426,221 458,737 490,029 2000's 520,233 550,850 580,319 610,756 648,551 688,058 726,772 750,570 758,315 760,391 2010's 764,435 772,880 782,759 794,150 808,970 - = No Data Reported; -- = Not Applicable; NA = Not

  6. Ohio Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Ohio Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 213,601 219,257 225,347 1990's 233,075 236,519 237,861 240,684 245,190 250,223 259,663 254,991 258,076 266,102 2000's 269,561 269,327 271,160 271,203 272,445 277,767 270,552 272,555 272,899 270,596 2010's 268,346 268,647 267,793 269,081 269,758 - = No Data Reported; -- = Not Applicable; NA = Not

  7. Ohio Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Ohio Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 7,929 8,163 8,356 1990's 8,301 8,479 8,573 8,678 8,655 8,650 8,672 7,779 8,112 8,136 2000's 8,267 8,515 8,111 8,098 7,899 8,328 6,929 6,858 6,806 6,712 2010's 6,571 6,482 6,381 6,554 6,526 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  8. Ohio Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Ohio Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,648,972 2,678,838 2,714,839 1990's 2,766,912 2,801,716 2,826,713 2,867,959 2,921,536 2,967,375 2,994,891 3,041,948 3,050,960 3,111,108 2000's 3,178,840 3,195,584 3,208,466 3,225,908 3,250,068 3,272,307 3,263,062 3,273,791 3,262,716 3,253,184 2010's 3,240,619 3,236,160 3,244,274 3,271,074 3,283,869 -

  9. Oklahoma Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Oklahoma Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 87,824 86,666 86,172 1990's 85,790 86,744 87,120 88,181 87,494 88,358 89,852 90,284 89,711 80,986 2000's 80,558 79,045 80,029 79,733 79,512 78,726 78,745 93,991 94,247 94,314 2010's 92,430 93,903 94,537 95,385 96,004 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  10. Oklahoma Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Oklahoma Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,772 2,689 2,877 1990's 2,889 2,840 2,859 2,912 2,853 2,845 2,843 2,531 3,295 3,040 2000's 2,821 3,403 3,438 3,367 3,283 2,855 2,811 2,822 2,920 2,618 2010's 2,731 2,733 2,872 2,958 3,063 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  11. Oklahoma Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Oklahoma Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 809,171 805,107 806,875 1990's 814,296 824,172 832,677 842,130 845,448 856,604 866,531 872,454 877,236 867,922 2000's 859,951 868,314 875,338 876,420 875,271 880,403 879,589 920,616 923,650 924,745 2010's 914,869 922,240 927,346 931,981 937,237 - = No Data Reported; -- = Not Applicable; NA = Not

  12. Oregon Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Oregon Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 40,967 41,998 43,997 1990's 47,175 55,374 50,251 51,910 53,700 55,409 57,613 60,419 63,085 65,034 2000's 66,893 68,098 69,150 74,515 71,762 73,520 74,683 80,998 76,868 76,893 2010's 77,370 77,822 78,237 79,276 80,480 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  13. Oregon Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Oregon Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 676 1,034 738 1990's 699 787 740 696 765 791 799 704 695 718 2000's 717 821 842 926 907 1,118 1,060 1,136 1,075 1,051 2010's 1,053 1,066 1,076 1,085 1,099 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016

  14. Oregon Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Oregon Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 280,670 288,066 302,156 1990's 326,177 376,166 354,256 371,151 391,845 411,465 433,638 456,960 477,796 502,000 2000's 523,952 542,799 563,744 625,398 595,495 626,685 647,635 664,455 674,421 675,582 2010's 682,737 688,681 693,507 700,211 707,010 - = No Data Reported; -- = Not Applicable; NA = Not

  15. Pennsylvania Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) Pennsylvania Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 166,901 172,615 178,545 1990's 186,772 191,103 193,863 198,299 206,812 209,245 214,340 215,057 216,519 223,732 2000's 228,037 225,911 226,957 227,708 231,051 233,132 231,540 234,597 233,462 233,334 2010's 233,751 233,588 235,049 237,922 239,681 - = No Data Reported; -- = Not

  16. Pennsylvania Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) Pennsylvania Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 6,089 6,070 6,023 1990's 6,238 6,344 6,496 6,407 6,388 6,328 6,441 6,492 6,736 7,080 2000's 6,330 6,159 5,880 5,577 5,726 5,577 5,241 4,868 4,772 4,745 2010's 4,624 5,007 5,066 5,024 5,084 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  17. Pennsylvania Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Pennsylvania Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,237,877 2,271,801 2,291,242 1990's 2,311,795 2,333,377 2,363,575 2,386,249 2,393,053 2,413,715 2,431,909 2,452,524 2,493,639 2,486,704 2000's 2,519,794 2,542,724 2,559,024 2,572,584 2,591,458 2,600,574 2,605,782 2,620,755 2,631,340 2,635,886 2010's 2,646,211 2,667,392 2,678,547

  18. Alabama Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Alabama Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 53 54,306 55,400 56,822 1990's 56,903 57,265 58,068 57,827 60,320 60,902 62,064 65,919 76,467 64,185 2000's 66,193 65,794 65,788 65,297 65,223 65,294 66,337 65,879 65,313 67,674 2010's 68,163 67,696 67,252 67,136 67,806 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  19. Alabama Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Alabama Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2 2,313 2,293 2,380 1990's 2,431 2,523 2,509 2,458 2,477 2,491 2,512 2,496 2,464 2,620 2000's 2,792 2,781 2,730 2,743 2,799 2,787 2,735 2,704 2,757 3,057 2010's 3,039 2,988 3,045 3,143 3,244 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  20. Alabama Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Alabama Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 656 662,217 668,432 683,528 1990's 686,149 700,195 711,043 730,114 744,394 751,890 766,322 781,711 788,464 775,311 2000's 805,689 807,770 806,389 809,754 806,660 809,454 808,801 796,476 792,236 785,005 2010's 778,985 772,892 767,396 765,957 769,418 - = No Data Reported; -- = Not Applicable; NA = Not

  1. Alaska Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Alaska Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 11 11,484 11,649 11,806 1990's 11,921 12,071 12,204 12,359 12,475 12,584 12,732 12,945 13,176 13,409 2000's 13,711 14,002 14,342 14,502 13,999 14,120 14,384 13,408 12,764 13,215 2010's 12,998 13,027 13,133 13,246 13,399 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  2. Alaska Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Alaska Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 66 67,648 68,612 69,540 1990's 70,808 72,565 74,268 75,842 77,670 79,474 81,348 83,596 86,243 88,924 2000's 91,297 93,896 97,077 100,404 104,360 108,401 112,269 115,500 119,039 120,124 2010's 121,166 121,736 122,983 124,411 126,416 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  3. Arizona Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Arizona Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 46 46,702 46,636 46,776 1990's 47,292 53,982 47,781 47,678 48,568 49,145 49,693 50,115 51,712 53,022 2000's 54,056 54,724 56,260 56,082 56,186 56,572 57,091 57,169 57,586 57,191 2010's 56,676 56,547 56,532 56,585 56,649 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  4. Arizona Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Arizona Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 545 567,962 564,195 572,461 1990's 586,866 642,659 604,899 610,337 635,335 661,192 689,597 724,911 764,167 802,469 2000's 846,016 884,789 925,927 957,442 993,885 1,042,662 1,088,574 1,119,266 1,128,264 1,130,047 2010's 1,138,448 1,146,286 1,157,688 1,172,003 1,186,794 - = No Data Reported; -- = Not

  5. Arkansas Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Arkansas Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 60 60,355 61,630 61,848 1990's 61,530 61,731 62,221 62,952 63,821 65,490 67,293 68,413 69,974 71,389 2000's 72,933 71,875 71,530 71,016 70,655 69,990 69,475 69,495 69,144 69,043 2010's 67,987 67,815 68,765 68,791 69,011 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  6. Arkansas Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Arkansas Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1 1,410 1,151 1,412 1990's 1,396 1,367 1,319 1,364 1,417 1,366 1,488 1,336 1,300 1,393 2000's 1,414 1,122 1,407 1,269 1,223 1,120 1,120 1,055 1,104 1,025 2010's 1,079 1,133 990 1,020 1,009 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  7. Arkansas Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Arkansas Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 475 480,839 485,112 491,110 1990's 488,850 495,148 504,722 513,466 521,176 531,182 539,952 544,460 550,017 554,121 2000's 560,055 552,716 553,192 553,211 554,844 555,861 555,905 557,966 556,746 557,355 2010's 549,970 551,795 549,959 549,764 549,034 - = No Data Reported; -- = Not Applicable; NA =

  8. California Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) California Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 413 404,507 407,435 410,231 1990's 415,073 421,278 412,467 411,648 411,140 411,535 408,294 406,803 588,224 416,791 2000's 413,003 416,036 420,690 431,795 432,367 434,899 442,052 446,267 447,160 441,806 2010's 439,572 440,990 442,708 444,342 443,115 - = No Data Reported; -- = Not Applicable; NA =

  9. California Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) California Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 31 44,764 44,680 46,243 1990's 46,048 44,865 40,528 42,748 38,750 38,457 36,613 35,830 36,235 36,435 2000's 35,391 34,893 33,725 34,617 41,487 40,226 38,637 39,134 39,591 38,746 2010's 38,006 37,575 37,686 37,996 37,548 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  10. California Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) California Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 7,626 7,904,858 8,113,034 8,313,776 1990's 8,497,848 8,634,774 8,680,613 8,726,187 8,790,733 8,865,541 8,969,308 9,060,473 9,181,928 9,331,206 2000's 9,370,797 9,603,122 9,726,642 9,803,311 9,957,412 10,124,433 10,329,224 10,439,220 10,515,162 10,510,950 2010's 10,542,584 10,625,190 10,681,916

  11. Colorado Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Colorado Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 108 109,770 110,769 112,004 1990's 112,661 113,945 114,898 115,924 115,994 118,502 121,221 123,580 125,178 129,041 2000's 131,613 134,393 136,489 138,621 138,543 137,513 139,746 141,420 144,719 145,624 2010's 145,460 145,837 145,960 150,145 150,235 - = No Data Reported; -- = Not Applicable; NA = Not

  12. Colorado Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Colorado Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1 896 923 976 1990's 1,018 1,074 1,108 1,032 1,176 1,528 2,099 2,923 3,349 4,727 2000's 4,994 4,729 4,337 4,054 4,175 4,318 4,472 4,592 4,816 5,084 2010's 6,232 6,529 6,906 7,293 7,823 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  13. Colorado Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Colorado Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 925 942,571 955,810 970,512 1990's 983,592 1,002,154 1,022,542 1,044,699 1,073,308 1,108,899 1,147,743 1,183,978 1,223,433 1,265,032 2000's 1,315,619 1,365,413 1,412,923 1,453,974 1,496,876 1,524,813 1,558,911 1,583,945 1,606,602 1,622,434 2010's 1,634,587 1,645,716 1,659,808 1,672,312 1,690,581 -

  14. Connecticut Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Connecticut Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 38 40,886 41,594 43,703 1990's 45,364 45,925 46,859 45,529 45,042 45,935 47,055 48,195 47,110 49,930 2000's 52,384 49,815 49,383 50,691 50,839 52,572 52,982 52,389 53,903 54,510 2010's 54,842 55,028 55,407 55,500 56,591 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  15. Connecticut Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Connecticut Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2 2,709 2,818 2,908 1990's 3,061 2,921 2,923 2,952 3,754 3,705 3,435 3,459 3,441 3,465 2000's 3,683 3,881 3,716 3,625 3,470 3,437 3,393 3,317 3,196 3,138 2010's 3,063 3,062 3,148 4,454 4,217 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  16. Connecticut Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Connecticut Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 400 411,349 417,831 424,036 1990's 428,912 430,078 432,244 427,761 428,157 431,909 433,778 436,119 438,716 442,457 2000's 458,388 458,404 462,574 466,913 469,332 475,221 478,849 482,902 487,320 489,349 2010's 490,185 494,970 504,138 513,492 522,658 - = No Data Reported; -- = Not

  17. Delaware Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Delaware Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 6 6,180 6,566 7,074 1990's 7,485 7,895 8,173 8,409 8,721 9,133 9,518 9,807 10,081 10,441 2000's 9,639 11,075 11,463 11,682 11,921 12,070 12,345 12,576 12,703 12,839 2010's 12,861 12,931 12,997 13,163 13,352 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  18. Delaware Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Delaware Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 81 82,829 84,328 86,428 1990's 88,894 91,467 94,027 96,914 100,431 103,531 106,548 109,400 112,507 115,961 2000's 117,845 122,829 126,418 129,870 133,197 137,115 141,276 145,010 147,541 149,006 2010's 150,458 152,005 153,307 155,627 158,502 - = No Data Reported; -- = Not Applicable; NA = Not

  19. Florida Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Florida Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 41 42,376 43,178 43,802 1990's 43,674 45,012 45,123 47,344 47,851 46,459 47,578 48,251 46,778 50,052 2000's 50,888 53,118 53,794 55,121 55,324 55,479 55,259 57,320 58,125 59,549 2010's 60,854 61,582 63,477 64,772 67,460 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  20. Florida Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Florida Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 442 444,848 446,690 452,544 1990's 457,648 467,221 471,863 484,816 497,777 512,365 521,674 532,790 542,770 556,628 2000's 571,972 590,221 603,690 617,373 639,014 656,069 673,122 682,996 679,265 674,090 2010's 675,551 679,199 686,994 694,210 703,535 - = No Data Reported; -- = Not Applicable; NA = Not

  1. Georgia Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Georgia Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 94 98,809 102,277 106,690 1990's 108,295 109,659 111,423 114,889 117,980 120,122 123,200 123,367 126,050 225,020 2000's 128,275 130,373 128,233 129,867 128,923 128,389 127,843 127,832 126,804 127,347 2010's 124,759 123,454 121,243 126,060 122,573 - = No Data Reported; -- = Not Applicable; NA = Not

  2. Georgia Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Georgia Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3 3,034 3,144 3,079 1990's 3,153 3,124 3,186 3,302 3,277 3,261 3,310 3,310 3,262 5,580 2000's 3,294 3,330 3,219 3,326 3,161 3,543 3,053 2,913 2,890 2,254 2010's 2,174 2,184 2,112 2,242 2,481 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  3. Georgia Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Georgia Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,190 1,237,201 1,275,128 1,308,972 1990's 1,334,935 1,363,723 1,396,860 1,430,626 1,460,141 1,495,992 1,538,458 1,553,948 1,659,730 1,732,865 2000's 1,680,749 1,737,850 1,735,063 1,747,017 1,752,346 1,773,121 1,726,239 1,793,650 1,791,256 1,744,934 2010's 1,740,587 1,740,006 1,739,543 1,805,425

  4. Hawaii Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Hawaii Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,896 2,852 2,842 1990's 2,837 2,786 2,793 3,222 2,805 2,825 2,823 2,783 2,761 2,763 2000's 2,768 2,777 2,781 2,804 2,578 2,572 2,548 2,547 2,540 2,535 2010's 2,551 2,560 2,545 2,627 2,789 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  5. Hawaii Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Hawaii Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 28,502 28,761 28,970 1990's 29,137 29,701 29,805 29,984 30,614 30,492 31,017 30,990 30,918 30,708 2000's 30,751 30,794 30,731 30,473 26,255 26,219 25,982 25,899 25,632 25,466 2010's 25,389 25,305 25,184 26,374 28,919 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  6. Idaho Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Idaho Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 17,482 18,454 18,813 1990's 19,452 20,328 21,145 21,989 22,999 24,150 25,271 26,436 27,697 28,923 2000's 30,018 30,789 31,547 32,274 33,104 33,362 33,625 33,767 37,320 38,245 2010's 38,506 38,912 39,202 39,722 40,229 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  7. Idaho Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Idaho Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 104,824 111,532 113,898 1990's 113,954 126,282 136,121 148,582 162,971 175,320 187,756 200,165 213,786 227,807 2000's 240,399 251,004 261,219 274,481 288,380 301,357 316,915 323,114 336,191 342,277 2010's 346,602 350,871 353,963 359,889 367,394 - = No Data Reported; -- = Not Applicable; NA = Not

  8. Illinois Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Illinois Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 241,367 278,473 252,791 1990's 257,851 261,107 263,988 268,104 262,308 264,756 265,007 268,841 271,585 274,919 2000's 279,179 278,506 279,838 281,877 273,967 276,763 300,606 296,465 298,418 294,226 2010's 291,395 293,213 297,523 282,743 294,391 - = No Data Reported; -- = Not Applicable; NA = Not

  9. Illinois Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Illinois Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 19,460 20,015 25,161 1990's 25,991 26,489 27,178 27,807 25,788 25,929 29,493 28,472 28,063 27,605 2000's 27,348 27,421 27,477 26,698 29,187 29,887 26,109 24,000 23,737 23,857 2010's 25,043 23,722 23,390 23,804 23,829 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  10. Illinois Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Illinois Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3,170,364 3,180,199 3,248,117 1990's 3,287,091 3,320,285 3,354,679 3,388,983 3,418,052 3,452,975 3,494,545 3,521,707 3,556,736 3,594,071 2000's 3,631,762 3,670,693 3,688,281 3,702,308 3,754,132 3,975,961 3,812,121 3,845,441 3,869,308 3,839,438 2010's 3,842,206 3,855,942 3,878,806 3,838,120