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1

Outage Log  

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

For Users Live Status Global Queue Look Scheduled Outages Outage Log Edison Login Node Status Hopper Login Node Status Hopper User Environment Monitoring Carver Login Node Status...

2

Definition: Reduced Sustained Outages | Open Energy Information  

Open Energy Info (EERE)

Outages Outages Jump to: navigation, search Dictionary.png Reduced Sustained Outages A sustained outage is one lasting >5 minutes, excluding major outages and wide-scale outages. The monetary benefit of reducing sustained outages is based on the value of service (VOS) of each customer class. The VOS parameter represents the total cost of a power outage per MWh. This cost includes the value of unserved energy, lost productivity, collateral damage, administrative costs, the value of penalties and performance-based rates. Functions that lead to this benefit can reduce the likelihood that there will be an outage, allow the system to be reconfigured on the fly to help restore service to as many customers as possible, enable a quicker response in the restoration effort, or mitigate the impact of an outage

3

Definition: Reduced Major Outages | Open Energy Information  

Open Energy Info (EERE)

Outages Outages Jump to: navigation, search Dictionary.png Reduced Major Outages A major outage is defined using the beta method, per IEEE Std 1366-2003 (IEEE Power Engineering Society 2004). The monetary benefit of reducing major outages is based on the VOS of each customer class. The VOS parameter represents the total cost of a power outage per MWh. This cost includes the value of unserved energy, lost productivity, collateral damage, the value of penalties and performance-based rates. Functions that lead to this benefit can mitigate major outages by allowing the system to be reconfigured on the fly to help restore service to as many customers as possible, enable a quicker response in the restoration effort, or mitigate the impact of an outage through islanding or alternative power supply.[1]

4

Improving Outage Performance: Outage Optimization Process  

SciTech Connect

Planned outage performance is a key measure of how well an Nuclear Power Plant (NPP) is operated. Performance during planned outages strongly affects virtually all of a plant's performance metrics. In recognition of this fact, NPP operators worldwide have and continue to focus on improving their outage performance. The process of improving outage performance is commonly referred to as 'Outage Optimization' in the industry. This paper starts with a summary of the principles of Outage Optimization. It then provides an overview of a process in common use in the USA and elsewhere to manage the improvement of planned outages. The program described is comprehensive in that it involves managing improvement in both the Preparation and Execution phases of outage management. (author)

LaPlatney, Jere J. [AREVA NP (United States)

2006-07-01T23:59:59.000Z

5

Outage Management Benchmarking Guideline  

Science Conference Proceedings (OSTI)

Benchmarking of power plant outages will help plants target performance improvements to specific elements of a plant outage program in order to improve overall availability, reliability, and safety while decreasing generation costs. EPRI's "Outage Management Benchmarking Guideline" builds on the Institute's fossil and nuclear plant experience with routine maintenance and extends that to outage maintenance processes. The guideline describes the initial steps in an outage benchmarking effort and 13 key ele...

2003-03-26T23:59:59.000Z

6

Outage Effectiveness Measurement Methodology  

Science Conference Proceedings (OSTI)

The efficiency of an outage program and the correctness of the outage process are important to the continuous improvement and long-term success of the plant. This report, based on a collective of industry experience, EPRI publications, and power conference data, is an aid to utility and plant management and staff to understanding the outage effectiveness methods and metrics relative to outage planning, execution, and post-outage operations.

2004-12-15T23:59:59.000Z

7

Managing turbine-generator outages by computer  

SciTech Connect

This article describes software being developed to address the need for computerized planning and documentation programs that can help manage outages. Downsized power-utility companies and the growing demand for independent, competitive engineering and maintenance services have created a need for a computer-assisted planning and technical-direction program for turbine-generator outages. To meet this need, a software tool is now under development that can run on a desktop or laptop personal computer to assist utility personnel and technical directors in outage planning. Total Outage Planning Software (TOPS), which runs on Windows, takes advantage of the mass data storage available with compact-disc technology by archiving the complete outage documentation on CD. Previous outage records can then be indexed, searched, and viewed on a computer with the click of a mouse. Critical-path schedules, parts lists, parts order tracking, work instructions and procedures, custom data sheets, and progress reports can be generated by computer on-site during an outage.

Reinhart, E.R. [Reinhart and Associates, Inc., Austin, TX (United States)

1997-09-01T23:59:59.000Z

8

Extended outages at several nuclear plants led to high outage ...  

U.S. Energy Information Administration (EIA)

Outages at U.S. nuclear power plants so far in 2012 are generally higher than in recent years because of extended forced outages at four nuclear power plants.

9

Transmission outage data collection for multiple related outage events  

SciTech Connect

This paper focuses on the information required to provide a basis for the analysis of forced multiple outage events. It recaps research as well as the bulk transmission outage collection up-rate that was performed. This paper identifies trends and addresses their impact on bulk transmission outage data collection.

Lauby, M.G. (Electric Power Research Inst., Palo Alto, CA (USA)); Maillant, G.R. (Electricite de France (EDF)

1989-01-01T23:59:59.000Z

10

Characteristics and trends in a National Study of Consumer Outage Costs  

E-Print Network (OSTI)

cost per event Outage cost per kWh Peak kW demand Annualcost per event Outage cost per kWh Peak kW demand Annualfrom $3,124 to $1,369. The cost per kWh and cost per peak kW

Lawton, Leora; Eto, Joseph H.; Katz, Aaron; Sullivan, Michael

2003-01-01T23:59:59.000Z

11

Outage dose reduction achievements during shorter refueling outages  

SciTech Connect

Achievement of dose reduction goals has been demonstrated at the Limerick Generating Station during the past three refueling outages in 1995-96. Shorter refueling outages were accomplished by carefully selecting outage work and thoroughly planning the work. Limerick Unit 1 completed its outage in 35 d; Unit 2 in 23 d in 1995; Unit 1 completed its outage in 24 d in 1996. The four previous outages at Unit I had taken from 100 to 127 days. European plants were visited by plant supervisors to develop improved management approaches to optimizing outage performance from work planning to work implement. Cofrentes in Spain and KKL Leibstadt in Switzerland were visited in 1994 because of their similar design and outage durations consistently below 35 d. This paper describes the radiation protection practices observed at European plants and implemented at Limerick to achieve efficiency of work practices and adequacy of radiological controls. Specific radiation protection initiatives discussed include electronic dosimetry system, break areas, wash sinks, scrub suits, zone mapping and self-monitoring. Outage achievements in 1995 and 1996 has assured Limerick continued BWR industry leadership as the lowest annual person-rem BWRs in the U.S..

Harris, W.O.; Taylor, S. [Limerick Generating Station, Sanatoga, PA (United States)

1996-06-01T23:59:59.000Z

12

Total-to-peak ratios of high purity germanium gamma ray detector  

E-Print Network (OSTI)

This study is concerned with the percentage of [gamma]-rays of a certain energy having their energy correctly measured by a high purity Germanium [gamma]-ray detector. The ratio between the total counts and the counts ...

Nelson, Justin Matthew, 1981-

2004-01-01T23:59:59.000Z

13

A framework and review of customer outage costs: Integration and analysis of electric utility outage cost surveys  

E-Print Network (OSTI)

Std Dev Cost Per Annual Cost Per kWh Usage Peak kW AverageStd Dev Cost Per Annual Cost Per kWh Usage Peak kW Average3-2. Logged Outage Cost per Annual kWh Figure 3-3. Logged

Lawton, Leora; Sullivan, Michael; Van Liere, Kent; Katz, Aaron; Eto, Joseph

2003-01-01T23:59:59.000Z

14

Cell outage management in LTE networks  

Science Conference Proceedings (OSTI)

Cell outage management is a functionality aiming to automatically detect and mitigate outages that occur in radio networks due to unexpected failures. We envisage that future radio networks autonomously detect an outage based on measurements, from e.g., ...

M. Amirijoo; L. Jorguseski; T. Kürner; R. Litjens; M. Neuland; L. C. Schmelz; U. Türke

2009-09-01T23:59:59.000Z

15

OpenEI Community - outages  

Open Energy Info (EERE)

have been preparing for an imminent threat that could lead to a substantial and prolonged power outage for utility customers not only on the East Coast, but also as far west as...

16

outages | OpenEI Community  

Open Energy Info (EERE)

66 66 Varnish cache server Home Groups Community Central Green Button Applications Developer Utility Rate FRED: FRee Energy Database More Public Groups Private Groups Features Groups Blog posts Content Stream Documents Discussions Polls Q & A Events Notices My stuff Energy blogs 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2142234866 Varnish cache server outages Home Graham7781's picture Submitted by Graham7781(2002) Super contributor 29 October, 2012 - 14:46 East Coast Utilities prepare for Hurricane Sandy East Coast Hurricane Sandy OpenEI outages storm United States Utility Companies As Hurricane Sandy continues to track towards the coast of the Eastern United States, utility companies have been preparing for an imminent threat that could lead to a substantial and prolonged power outage for utility

17

Definition: Outage Management System | Open Energy Information  

Open Energy Info (EERE)

Outage Management System Outage Management System A software application that can process outage reports from a variety of utility operational systems including SCADA, AMI, and customer phone calls, and display outage information to utility operators. The OMS can help a utility interpret outage information and determine where the likely cause of an outage may be. It can also help the utility optimize its service restoration resources.[1] Related Terms advanced metering infrastructure References ↑ https://www.smartgrid.gov/category/technology/outage_management_system [[C LikeLike UnlikeLike You like this.Sign Up to see what your friends like. ategory: Smart Grid Definitionssmart grid,smart grid, |Template:BASEPAGENAME]]smart grid,smart grid, Retrieved from "http://en.openei.org/w/index.php?title=Definition:Outage_Management_System&oldid=502507

18

Broadcast Outages for NIST Radio Station WWVB  

Science Conference Proceedings (OSTI)

... Numerous short outages while station was undergoing maintenance and testing during daylight hours. WWVB operated at reduced power during ...

19

Development of Methodologies for Technology Deployment for Advanced Outage Control Centers that Improve Outage Coordination, Problem Resolution and Outage Risk Management  

SciTech Connect

This research effort is a part of the Light-Water Reactor Sustainability (LWRS) Program, which is a research and development (R&D) program sponsored by Department of Energy (DOE) and performed in close collaboration with industry R&D programs that provides the technical foundations for licensing and managing the long-term, safe, and economical operation of current nuclear power plants. The LWRS program serves to help the U.S. nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of the plants and extension of the current operating licenses. The long term viability of existing nuclear power plants in the U.S. will depend upon maintaining high capacity factors, avoiding nuclear safety issues and reducing operating costs. The slow progress in the construction on new nuclear power plants has placed in increased importance on maintaining the output of the current fleet of nuclear power plants. Recently expanded natural gas production has placed increased economic pressure on nuclear power plants due to lower cost competition. Until recently, power uprate projects had steadily increased the total output of the U.S. nuclear fleet. Errors made during power plant upgrade projects have now removed three nuclear power plants from the U.S. fleet and economic considerations have caused the permanent shutdown of a fourth plant. Additionally, several utilities have cancelled power uprate projects citing economic concerns. For the past several years net electrical generation from U.S. nuclear power plants has been declining. One of few remaining areas where significant improvements in plant capacity factors can be made is in minimizing the duration of refueling outages. Managing nuclear power plant outages is a complex and difficult task. Due to the large number of complex tasks and the uncertainty that accompanies them, outage durations routinely exceed the planned duration. The ability to complete an outage on or near schedule depends upon the performance of the outage management organization. During an outage, the outage control center (OCC) is the temporary command center for outage managers and provides several critical functions for the successful execution of the outage schedule. Essentially, the OCC functions to facilitate information inflow, assist outage management in processing information and to facilitate the dissemination of information to stakeholders. Currently, outage management activities primarily rely on telephone communication, face to face reports of status and periodic briefings in the OCC. Much of the information displayed in OCCs is static and out of date requiring an evaluation to determine if it is still valid. Several advanced communication and collaboration technologies have shown promise for facilitating the information flow into, across and out of the OCC. Additionally, advances in the areas of mobile worker technologies, computer based procedures and electronic work packages can be leveraged to improve the availability of real time status to outage managers.

Shawn St. Germain; Ronald Farris; Heather Medeman

2013-09-01T23:59:59.000Z

20

Definition: Reduced Momentary Outages | Open Energy Information  

Open Energy Info (EERE)

Momentary Outages Momentary Outages Jump to: navigation, search Dictionary.png Reduced Momentary Outages By locating faults more accurately or adding electricity storage, momentary outages could be reduced or eliminated. Moreover, fewer customers on the same or adjacent distribution feeders would experience the momentary interruptions associated with reclosing. Momentary outages last <5 min in duration. The benefit to consumers is based on the value of service.[1] Related Terms electricity storage technologies, electricity generation, smart grid References ↑ SmartGrid.gov 'Description of Benefits' An in LikeLike UnlikeLike You like this.Sign Up to see what your friends like. line Glossary Definition Retrieved from "http://en.openei.org/w/index.php?title=Definition:Reduced_Momentary_Outages&oldid=493094

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


21

Broadcast Outages for NIST Radio Station WWVB  

Science Conference Proceedings (OSTI)

... Broadcast Outages for WWVB. ... WWVB will be operating at 1/2 power (35 kW) during the daylight hours on weekdays from September 14, 2009 until ...

22

Track NERSC Scheduled and Unscheduled Outages in Google Calendar  

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

Track NERSC Outages in Google Calendar Track NERSC Outages in Google Calendar March 22, 2013 by Jack Deslippe (0 Comments) Outages are now available in Google calendar form. You...

23

North American Electric Reliability Council Outage Announcement |  

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

Council Outage Announcement Council Outage Announcement North American Electric Reliability Council Outage Announcement Starting at about 4:11 p.m. EDT, major losses of electric load occurred in the northeastern United States and Canada in the Eastern Interconnection. Although the exact cause is not known at present, the outages are not the result of a terrorist attack. The areas most affected center around the Great Lakes: Michigan, Ohio, New York City, Ontario, Quebec, northern New Jersey, Massachusetts, and Connecticut. North American Electric Reliability Council Outage Announcement More Documents & Publications Blackout 2003: Final Report on the August 14, 2003 Blackout in the United States and Canada: Causes and Recommendations Blackout 2003: Blackout Final Implementation Report

24

Definition: Sustained Outage | Open Energy Information  

Open Energy Info (EERE)

Sustained Outage Sustained Outage Jump to: navigation, search Dictionary.png Sustained Outage The deenergized condition of a transmission line resulting from a fault or disturbance following an unsuccessful automatic reclosing sequence and/or unsuccessful manual reclosing procedure.[1] View on Wikipedia Wikipedia Definition A power outage (also power cut, blackout, or power failure) is a short- or long-term loss of the electric power to an area. There are many causes of power failures in an electricity network. Examples of these causes include faults at power stations, damage to electric transmission lines, substations or other parts of the distribution system, a short circuit, or the overloading of electricity mains. Power failures are particularly critical at sites where the environment and public safety are

25

Systems and Services Outage Notification Policy  

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

Job Logs & Analytics Job Logs & Analytics Training & Tutorials Software Accounts & Allocations Policies Acknowledge NERSC Allocation Eligibility Allocation Management Computer Security Computer Use Data Management Passwords Queue Scheduling Usage Charges System Outages Data Analytics & Visualization Data Management Policies Science Gateways User Surveys NERSC Users Group User Announcements Help Operations for: Passwords & Off-Hours Status 1-800-66-NERSC, option 1 or 510-486-6821 Account Support https://nim.nersc.gov accounts@nersc.gov 1-800-66-NERSC, option 2 or 510-486-8612 Consulting http://help.nersc.gov consult@nersc.gov 1-800-66-NERSC, option 3 or 510-486-8611 Home » For Users » Policies » System Outages Systems Outage Notification Policy To be considered a scheduled outage, the user community must be notified of

26

Definition: Forced Outage | Open Energy Information  

Open Energy Info (EERE)

Forced Outage Forced Outage Jump to: navigation, search Dictionary.png Forced Outage The removal from service availability of a generating unit, transmission line, or other facility for emergency reasons., The condition in which the equipment is unavailable due to unanticipated failure.[1] Related Terms transmission lines, transmission line References ↑ Glossary of Terms Used in Reliability Standards An i LikeLike UnlikeLike You like this.Sign Up to see what your friends like. nline Glossary Definition Retrieved from "http://en.openei.org/w/index.php?title=Definition:Forced_Outage&oldid=480310" Categories: Definitions ISGAN Definitions What links here Related changes Special pages Printable version Permanent link Browse properties About us Disclaimers Energy blogs Linked Data

27

August 14, 2003 Power Outages Â… Announcement  

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

Ellen P. Vancko Ellen P. Vancko evancko@nerc.com Power Outage Update ⎯ 8/16/2003 11 a.m. EDT The bulk electric transmission system in the United States and Canada has been restored and is operating reliably. Many of the generating units that tripped off line during the outage have returned to service and additional generating units are expected to return to service over the weekend. Virtually all customers have been returned to electric service, although some customers will continue to experience rotating outages due to generating capacity availability. Some rotating outages may also be necessary on Monday depending on the status of the generating units returning to service and the electrical demand. "NERC is conducting a thorough investigation into this event in conjunction with the regional

28

Outage Milestone Manual for Fossil-Fueled Power Plants  

Science Conference Proceedings (OSTI)

The efficiency of an outage program and the correctness of the outage process are important to the continuous improvement and long-term success of a utility and plant. This report--based on collective industry experience; Electric Power Research Institute (EPRI) publications; and outage conference, meeting, and workshop data--provides guidance for utility and plant management and staff involved in outage planning, execution, and post-outage operations and in restarting the planning cycle in preparation f...

2010-10-19T23:59:59.000Z

29

Outage Management Guidelines for Fossil- Fueled Power Plants  

Science Conference Proceedings (OSTI)

The efficiency of an outage program and the correctness of the outage process are important to the continuous improvement and the long-term success of a utility and plant. This report, based on collective industry experience, Electric Power Research Institute (EPRI) publications, and outage conference, meeting, and workshop data, provides guidance for utility/plant management and staff involved in outage planning, execution, and post-outage operations and in restarting the planning cycle in preparation f...

2006-12-22T23:59:59.000Z

30

Multipurpose Outage at a Midsize, Resource-Limited Nonpower Reactor  

SciTech Connect

The University of Florida Training Reactor (UFTR) is a light water-cooled, graphite and light water-moderated, modified Argonaut-type reactor licensed to operate at steady-state power levels up to 100 kW. The UFTR was subject to a unique and lengthy voluntary outage beginning in May 1998 following several months of gradual increases in the normal critical position totaling {approx}0.002 {Delta}k/k. The Nuclear Regulatory Commission (NRC) was updated periodically on the facility status and visited the facility twice during the outage and once since restart to normal operations on August 17, 1999. Various potential causes of this reactivity anomaly were identified. After investigation, each of these causes was eliminated with no specific cause ever identified. Despite all the inherent limitations and especially because of the difficulty of core access, this entire outage was conducted with the perspective of relicensing in 2002. Areas specifically addressed included compensating efforts to preclude loss of user clientele, acquisition of data for facilitating the upcoming conversion from high-enriched uranium (HEU) to low-enriched uranium (LEU), and development of a surveillance plan relicensing database to support the planned license renewal. In summary, this nonpower reactor facility with limited staff has been successful in all three areas.

William G. Vernetson

2000-06-04T23:59:59.000Z

31

Contingency Analysis of Cascading Line Outage Events  

SciTech Connect

As the US power systems continue to increase in size and complexity, including the growth of smart grids, larger blackouts due to cascading outages become more likely. Grid congestion is often associated with a cascading collapse leading to a major blackout. Such a collapse is characterized by a self-sustaining sequence of line outages followed by a topology breakup of the network. This paper addresses the implementation and testing of a process for N-k contingency analysis and sequential cascading outage simulation in order to identify potential cascading modes. A modeling approach described in this paper offers a unique capability to identify initiating events that may lead to cascading outages. It predicts the development of cascading events by identifying and visualizing potential cascading tiers. The proposed approach was implemented using a 328-bus simplified SERC power system network. The results of the study indicate that initiating events and possible cascading chains may be identified, ranked and visualized. This approach may be used to improve the reliability of a transmission grid and reduce its vulnerability to cascading outages.

Thomas L Baldwin; Magdy S Tawfik; Miles McQueen

2011-03-01T23:59:59.000Z

32

Total..........................................................  

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

Housing Units (millions) Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Census Division Total South...

33

Definition: Cascading Outage | Open Energy Information  

Open Energy Info (EERE)

Cascading Outage Cascading Outage Jump to: navigation, search Dictionary.png Cascading Outage The uncontrolled successive loss of system elements triggered by an incident at any location. Cascading results in widespread electric service interruption that cannot be restrained from sequentially spreading beyond an area predetermined by studies.[1] View on Wikipedia Wikipedia Definition A cascading failure is a failure in a system of interconnected parts in which the failure of a part can trigger the failure of successive parts. Such a failure may happen in many types of systems, including power transmission, computer networking, finance and bridges. Cascading failures usually begin when one part of the system fails. When this happens, nearby nodes must then take up the slack for the failed component. This overloads

34

Outage management and health physics issue, 2007  

SciTech Connect

The focus of the May-June issue is on outage management and health physics. Major articles/reports in this issue include: India: a potential commercial opportunity, a U.S. Department of Commerce Report, by Joe Neuhoff and Justin Rathke; The changing climate for nuclear energy, by Skip Bowman, Nuclear Energy Insitute; Selecting protective clothing, by J. Mark Price, Southern California Edison; and Succssful refurbishment outage, by Sudesh K. Gambhir, Omaha Public Power District. Industry innovation articles in this issue are: Containment radiation monitoring spiking, by Michael W. Lantz and Robert Routolo, Arizona Public Service Company; Improved outage performance, by Michael Powell and Troy Wilfong, Arizona Public Service Company, Palo Verde Nuclear Generating Station; Stop repacking valves and achieve leak-free performance, by Kenneth Hart, PPL Susquehanna LLC; and Head assembly upgrade package, by Timothy Petit, Dominion Nuclear.

Agnihotri, Newal (ed.)

2007-05-15T23:59:59.000Z

35

Total..........................................................  

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

Division Total West Mountain Pacific Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

36

Total..........................................................  

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

(millions) Census Division Total South Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC13.7...

37

Total..........................................................  

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

Census Division Total Midwest Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC12.7...

38

Total..........................................................  

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

Census Division Total Northeast Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC11.7...

39

Total..........................................................  

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

Census Division Total South Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

40

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

(millions) Census Division Total West Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC14.7...

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


41

Outage managment and health physics issue, 2008  

SciTech Connect

The focus of the May-June issue is on outage management and health physics. Major articles include: Outage optimization initiatives, by George B. Beam, AREVA NP, Inc.; New plant based on excellent track records, by Jim Scarola, Progress Energy; Meeting customer needs and providing environmental benefits, by Peter S. Hastings, Duke Energy; Plants with 3-D design, by Jack A. Bailey, Tennessee Valley Authority; and Highest quality with exceptional planning, by Jason A. Walls, Duke Energy. Industry innovation articles include: Integrated exposure reduction plan, by Ed Wolfe, Exelon; Performance-based radiation worker training, by Joe Giuffre and Timothy Vriezerma, American Electric Power.

Agnihotri, Newal (ed.)

2008-05-15T23:59:59.000Z

42

Total  

Gasoline and Diesel Fuel Update (EIA)

Total Total .............. 16,164,874 5,967,376 22,132,249 2,972,552 280,370 167,519 18,711,808 1993 Total .............. 16,691,139 6,034,504 22,725,642 3,103,014 413,971 226,743 18,981,915 1994 Total .............. 17,351,060 6,229,645 23,580,706 3,230,667 412,178 228,336 19,709,525 1995 Total .............. 17,282,032 6,461,596 23,743,628 3,565,023 388,392 283,739 19,506,474 1996 Total .............. 17,680,777 6,370,888 24,051,665 3,510,330 518,425 272,117 19,750,793 Alabama Total......... 570,907 11,394 582,301 22,601 27,006 1,853 530,841 Onshore ................ 209,839 11,394 221,233 22,601 16,762 1,593 180,277 State Offshore....... 209,013 0 209,013 0 10,244 260 198,509 Federal Offshore... 152,055 0 152,055 0 0 0 152,055 Alaska Total ............ 183,747 3,189,837 3,373,584 2,885,686 0 7,070 480,828 Onshore ................ 64,751 3,182,782

43

Potomac River Project Outage Schedule Clarification | Department of Energy  

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

Potomac River Project Outage Schedule Clarification Potomac River Project Outage Schedule Clarification Potomac River Project Outage Schedule Clarification Docket No. EO-05-01. Order No. 202-07-02: Based on the most current information we have for both circuits, the new outage dates are listed below: Outage Duration Feeder Out April 30, 2007 - June 1, 2007 Circuit 1 June 2, 2007 - July 1, 2007 Circuit 2 Potomac River Project Outage Schedule Clarification More Documents & Publications Re: Potomac River Generating Station Department of Energy, Case No. EO-05-01: Potomac Electric Power Company (PEPCO) evised plan for transmission outages for the 230 kV circuits Notification of Planned 230kV Outage at Potomac River Generating Station PEPCO Comments on Special Environmental Analysis For Actions Taken Under U.S. Department of Energy Emergency Orders Regarding Operation of the

44

Tracking Laser Coordinate Measurement System Application for Turbine Outage Activities  

Science Conference Proceedings (OSTI)

Tracking Laser Coordinate Measurement System Application for Turbine Outage Activities provides nuclear and fossil personnel with a faster and more accurate method for performing turbine measurement activities during an outage.

2007-12-21T23:59:59.000Z

45

Market Assessment of Refinery Outages Planned for October 2009 ...  

U.S. Energy Information Administration (EIA)

January fuel demand with availability of the refinery process units for distillate and gasoline production net of outages.

46

Fossil Power Plant Outage Scoping and Scope Control  

Science Conference Proceedings (OSTI)

This document provides detailed guidance for outage scope planning and control. It covers such topics as long-range business asset management tracking and inclusion into outage scope and contingency planning. It provides guidance on developing the outage plan, including typical criteria for the baseline budget, developing and using a monitoring plan and metrics, and developing an assessment plan for outage scope development and execution. The scope identification and approval processes are discussed as w...

2007-12-19T23:59:59.000Z

47

Total............................................................  

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

Total................................................................... Total................................................................... 111.1 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546

48

Indication of Potential Cascading Outages Using Measurement Data  

Science Conference Proceedings (OSTI)

Many efforts have been made to avoid blackouts in North America since 1965. However, cascading outages leading to catastrophic blackouts continued to happen. This project focused on investigating a comprehensive monitoring and control framework for prediction, analysis, and mitigation of cascading outages and conducting research on the early indication of potential cascading outages using real-time measurement data.

2010-12-21T23:59:59.000Z

49

A Preliminary Analysis of Network Outages During Hurricane Sandy  

E-Print Network (OSTI)

.2.3.*). To evaluate outages, we require that, historically, at least 10% of the addresses in the block reply to pingsA Preliminary Analysis of Network Outages During Hurricane Sandy USC/ISI Technical Report ISI, linquan, yuri}@isi.edu ABSTRACT This document describes our analysis of Internet outages during

Heidemann, John

50

Peak Power at Peak Efficiency  

Peak Power At Peak Efficiency. 21. st. Industry Growth Forum. October 2008. PJ Piper (857) 350?3100. ... At <$10/bbl oil, QM Power’s electric ...

51

Total...................  

Gasoline and Diesel Fuel Update (EIA)

4,690,065 52,331,397 2,802,751 4,409,699 7,526,898 209,616 1993 Total................... 4,956,445 52,535,411 2,861,569 4,464,906 7,981,433 209,666 1994 Total................... 4,847,702 53,392,557 2,895,013 4,533,905 8,167,033 202,940 1995 Total................... 4,850,318 54,322,179 3,031,077 4,636,500 8,579,585 209,398 1996 Total................... 5,241,414 55,263,673 3,158,244 4,720,227 8,870,422 206,049 Alabama ...................... 56,522 766,322 29,000 62,064 201,414 2,512 Alaska.......................... 16,179 81,348 27,315 12,732 75,616 202 Arizona ........................ 27,709 689,597 28,987 49,693 26,979 534 Arkansas ..................... 46,289 539,952 31,006 67,293 141,300 1,488 California ..................... 473,310 8,969,308 235,068 408,294 693,539 36,613 Colorado...................... 110,924 1,147,743

52

Maintain HCUs on-line, shorten refueling outages  

SciTech Connect

This article examines how removing maintenance of hydraulic control units from the outage scope lets the outage focus available resources on critical-path items, saving significant time and money and enhancing capacity factors. Because of their cost impact, refueling outages are a prime focus of efforts to improve the competitive operation of nuclear powerplants. An approach drawing wide interest is reducing the outage work scope by performing on-line key tasks normally consigned to refueling outages. applying this approach to maintenance of hydraulic control units (HCUs) on boiling-water reactors (BWRs) can be extremely fruitful.

Bell, T.

1996-09-01T23:59:59.000Z

53

Potomac River Project Outage Schedule Clarification | Department of Energy  

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

River Project Outage Schedule Clarification River Project Outage Schedule Clarification Potomac River Project Outage Schedule Clarification Docket No. EO-05-01. Order No. 202-07-02: Based on the most current information we have for both circuits, the new outage dates are listed below: Outage Duration Feeder Out April 30, 2007 - June 1, 2007 Circuit 1 June 2, 2007 - July 1, 2007 Circuit 2 Potomac River Project Outage Schedule Clarification More Documents & Publications Re: Potomac River Generating Station Department of Energy, Case No. EO-05-01: Potomac Electric Power Company (PEPCO) evised plan for transmission outages for the 230 kV circuits PEPCO Comments on Special Environmental Analysis For Actions Taken Under U.S. Department of Energy Emergency Orders Regarding Operation of the Potomac River Generating Station in Alexandria, Virginia

54

North American Electric Reliability Council Power Outage Update |  

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

Power Outage Update Power Outage Update North American Electric Reliability Council Power Outage Update The bulk electric transmission system in the United States and Canada has been restored and is operating reliably. Many of the generating units that tripped off line during the outage have returned to service and additional generating units are expected to return to service over the weekend. Virtually all customers have been returned to electric service, although some customers will continue to experience rotating outages due to generating capacity availability. North American Electric Reliability Council Power Outage Update More Documents & Publications Electric System Update: Sunday August 17, 2003 North American Electric Reliability Council Outage Announcement NORTH AMERICAN ELECTRIC RELIABILITY COUNCIL: Preliminary Disturbance Report

55

Outage management and health physics issue, 2009  

SciTech Connect

The focus of the May-June issue is on outage management and health physics. Major articles include the following: Planning and scheduling to minimize refueling outage, by Pat McKenna, AmerenUE; Prioritizing safety, quality and schedule, by Tom Sharkey, Dominion; Benchmarking to high standards, by Margie Jepson, Energy Nuclear; Benchmarking against U.S. standards, by Magnox North, United Kingdom; Enabling suppliers for new build activity, by Marcus Harrington, GE Hitachi Nuclear Energy; Identifying, cultivating and qualifying suppliers, by Thomas E. Silva, AREVA NP; Creating new U.S. jobs, by Francois Martineau, Areva NP. Industry innovation articles include: MSL Acoustic source load reduction, by Amir Shahkarami, Exelon Nuclear; Dual Methodology NDE of CRDM nozzles, by Michael Stark, Dominion Nuclear; and Electronic circuit board testing, by James Amundsen, FirstEnergy Nuclear Operating Company. The plant profile article is titled The future is now, by Julia Milstead, Progress Energy Service Company, LLC.

Agnihotri, Newal (ed.)

2009-05-15T23:59:59.000Z

56

Outage management and health physics issue, 2006  

SciTech Connect

The focus of the May-June issue is on outage management and health physics. Major articles/reports in this issue include: A design with experience for the U.S., by Michael J. Wallace, Constellation Generation Group; Hope to be among the first, by Randy Hutchinson, Entergy Nuclear; Plans to file COLs in 2008, by Garry Miller, Progress Energy; Evolution of ICRP's recommendations, by Lars-Erik Holm, ICRP; European network on education and training in radiological protection, by Michele Coeck, SCK-CEN, Belgium; Outage managment: an important tool for improving nuclear power plant performance, by Thomas Mazour and Jiri Mandula, IAEA, Austria; and Plant profile: Exploring new paths to excellence, by Anne Thomas, Exelon Nuclear.

Agnihotri, Newal (ed.)

2006-05-15T23:59:59.000Z

57

RESOLVED: Projectb filesystem outage July 9, 2012  

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

RESOLVED: Projectb filesystem outage July 9, 2012 RESOLVED: Projectb filesystem outage July 9, 2012 RESOLVED: Projectb filesystem outage July 9, 2012 July 9, 2012 (0 Comments) The projectb filesystem had a hardware failure that potentially generated I/O errors. The filesystem logs indicate that the earliest abnormal event on the filesystem occurred at 9:19AM and the filesystem was taken down for maintenance at 10:42AM. The filesystem returned to service at 11:20AM. Jobs running on the cluster would not have been able to read from or write to the projectb filesystem between 10:42AM and 11:20AM. Between 9:19AM and 10:42AM one out of the 20 GPFS controllers on projectb was down, and didn't failover (as it should have). This means: 1/20 file I/O operations could have failed between 9:19AM and 10:42AM If your job was performing a large number of short reads and writes, then

58

Advanced Outage and Control Center: Strategies for Nuclear Plant Outage Work Status Capabilities  

Science Conference Proceedings (OSTI)

The research effort is a part of the Light Water Reactor Sustainability (LWRS) Program. LWRS is a research and development program sponsored by the Department of Energy, performed in close collaboration with industry to provide the technical foundations for licensing and managing the long-term, safe and economical operation of current nuclear power plants. The LWRS Program serves to help the US nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of the plants and extension of the current operating licenses. The Outage Control Center (OCC) Pilot Project was directed at carrying out the applied research for development and pilot of technology designed to enhance safe outage and maintenance operations, improve human performance and reliability, increase overall operational efficiency, and improve plant status control. Plant outage management is a high priority concern for the nuclear industry from cost and safety perspectives. Unfortunately, many of the underlying technologies supporting outage control are the same as those used in the 1980’s. They depend heavily upon large teams of staff, multiple work and coordination locations, and manual administrative actions that require large amounts of paper. Previous work in human reliability analysis suggests that many repetitive tasks, including paper work tasks, may have a failure rate of 1.0E-3 or higher (Gertman, 1996). With between 10,000 and 45,000 subtasks being performed during an outage (Gomes, 1996), the opportunity for human error of some consequence is a realistic concern. Although a number of factors exist that can make these errors recoverable, reducing and effectively coordinating the sheer number of tasks to be performed, particularly those that are error prone, has the potential to enhance outage efficiency and safety. Additionally, outage management requires precise coordination of work groups that do not always share similar objectives. Outage managers are concerned with schedule and cost, union workers are concerned with performing work that is commensurate with their trade, and support functions (safety, quality assurance, and radiological controls, etc.) are concerned with performing the work within the plants controls and procedures. Approaches to outage management should be designed to increase the active participation of work groups and managers in making decisions that closed the gap between competing objectives and the potential for error and process inefficiency.

Gregory Weatherby

2012-05-01T23:59:59.000Z

59

Total..........................................................................  

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

25.6 25.6 40.7 24.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.9 1.0 500 to 999........................................................... 23.8 4.6 3.9 9.0 6.3 1,000 to 1,499..................................................... 20.8 2.8 4.4 8.6 5.0 1,500 to 1,999..................................................... 15.4 1.9 3.5 6.0 4.0 2,000 to 2,499..................................................... 12.2 2.3 3.2 4.1 2.6 2,500 to 2,999..................................................... 10.3 2.2 2.7 3.0 2.4 3,000 to 3,499..................................................... 6.7 1.6 2.1 2.1 0.9 3,500 to 3,999..................................................... 5.2 1.1 1.7 1.5 0.9 4,000 or More.....................................................

60

Total..........................................................................  

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

4.2 4.2 7.6 16.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 1.0 0.2 0.8 500 to 999........................................................... 23.8 6.3 1.4 4.9 1,000 to 1,499..................................................... 20.8 5.0 1.6 3.4 1,500 to 1,999..................................................... 15.4 4.0 1.4 2.6 2,000 to 2,499..................................................... 12.2 2.6 0.9 1.7 2,500 to 2,999..................................................... 10.3 2.4 0.9 1.4 3,000 to 3,499..................................................... 6.7 0.9 0.3 0.6 3,500 to 3,999..................................................... 5.2 0.9 0.4 0.5 4,000 or More.....................................................

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


61

Total.........................................................................  

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

Floorspace (Square Feet) Floorspace (Square Feet) Total Floorspace 2 Fewer than 500.................................................. 3.2 Q 0.8 0.9 0.8 0.5 500 to 999.......................................................... 23.8 1.5 5.4 5.5 6.1 5.3 1,000 to 1,499.................................................... 20.8 1.4 4.0 5.2 5.0 5.2 1,500 to 1,999.................................................... 15.4 1.4 3.1 3.5 3.6 3.8 2,000 to 2,499.................................................... 12.2 1.4 3.2 3.0 2.3 2.3 2,500 to 2,999.................................................... 10.3 1.5 2.3 2.7 2.1 1.7 3,000 to 3,499.................................................... 6.7 1.0 2.0 1.7 1.0 1.0 3,500 to 3,999.................................................... 5.2 0.8 1.5 1.5 0.7 0.7 4,000 or More.....................................................

62

Total..........................................................................  

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

. . 111.1 20.6 15.1 5.5 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.4 500 to 999........................................................... 23.8 4.6 3.6 1.1 1,000 to 1,499..................................................... 20.8 2.8 2.2 0.6 1,500 to 1,999..................................................... 15.4 1.9 1.4 0.5 2,000 to 2,499..................................................... 12.2 2.3 1.7 0.5 2,500 to 2,999..................................................... 10.3 2.2 1.7 0.6 3,000 to 3,499..................................................... 6.7 1.6 1.0 0.6 3,500 to 3,999..................................................... 5.2 1.1 0.9 0.3 4,000 or More.....................................................

63

Total..........................................................................  

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

7.1 7.1 7.0 8.0 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.4 Q Q 0.5 500 to 999........................................................... 23.8 2.5 1.5 2.1 3.7 1,000 to 1,499..................................................... 20.8 1.1 2.0 1.5 2.5 1,500 to 1,999..................................................... 15.4 0.5 1.2 1.2 1.9 2,000 to 2,499..................................................... 12.2 0.7 0.5 0.8 1.4 2,500 to 2,999..................................................... 10.3 0.5 0.5 0.4 1.1 3,000 to 3,499..................................................... 6.7 0.3 Q 0.4 0.3 3,500 to 3,999..................................................... 5.2 Q Q Q Q 4,000 or More.....................................................

64

Total..........................................................................  

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

7.1 7.1 19.0 22.7 22.3 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 2.1 0.6 Q 0.4 500 to 999........................................................... 23.8 13.6 3.7 3.2 3.2 1,000 to 1,499..................................................... 20.8 9.5 3.7 3.4 4.2 1,500 to 1,999..................................................... 15.4 6.6 2.7 2.5 3.6 2,000 to 2,499..................................................... 12.2 5.0 2.1 2.8 2.4 2,500 to 2,999..................................................... 10.3 3.7 1.8 2.8 2.1 3,000 to 3,499..................................................... 6.7 2.0 1.4 1.7 1.6 3,500 to 3,999..................................................... 5.2 1.6 0.8 1.5 1.4 4,000 or More.....................................................

65

Total..........................................................................  

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

0.7 0.7 21.7 6.9 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.6 Q Q 500 to 999........................................................... 23.8 9.0 4.2 1.5 3.2 1,000 to 1,499..................................................... 20.8 8.6 4.7 1.5 2.5 1,500 to 1,999..................................................... 15.4 6.0 2.9 1.2 1.9 2,000 to 2,499..................................................... 12.2 4.1 2.1 0.7 1.3 2,500 to 2,999..................................................... 10.3 3.0 1.8 0.5 0.7 3,000 to 3,499..................................................... 6.7 2.1 1.2 0.5 0.4 3,500 to 3,999..................................................... 5.2 1.5 0.8 0.3 0.4 4,000 or More.....................................................

66

Total..........................................................  

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

.. .. 111.1 24.5 1,090 902 341 872 780 441 Total Floorspace (Square Feet) Fewer than 500...................................... 3.1 2.3 403 360 165 366 348 93 500 to 999.............................................. 22.2 14.4 763 660 277 730 646 303 1,000 to 1,499........................................ 19.1 5.8 1,223 1,130 496 1,187 1,086 696 1,500 to 1,999........................................ 14.4 1.0 1,700 1,422 412 1,698 1,544 1,348 2,000 to 2,499........................................ 12.7 0.4 2,139 1,598 Q Q Q Q 2,500 to 2,999........................................ 10.1 Q Q Q Q Q Q Q 3,000 or More......................................... 29.6 0.3 Q Q Q Q Q Q Heated Floorspace (Square Feet) None...................................................... 3.6 1.8 1,048 0 Q 827 0 407 Fewer than 500......................................

67

Total...................................................................  

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

2,033 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546 3,500 to 3,999................................................. 5.2 3,549 2,509 1,508

68

Total...........................................................  

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

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................... 3.2 1.9 0.9 Q Q Q 1.3 2.3 500 to 999........................................... 23.8 10.5 7.3 3.3 1.4 1.2 6.6 12.9 1,000 to 1,499..................................... 20.8 5.8 7.0 3.8 2.2 2.0 3.9 8.9 1,500 to 1,999..................................... 15.4 3.1 4.2 3.4 2.0 2.7 1.9 5.0 2,000 to 2,499..................................... 12.2 1.7 2.7 2.9 1.8 3.2 1.1 2.8 2,500 to 2,999..................................... 10.3 1.2 2.2 2.3 1.7 2.9 0.6 2.0 3,000 to 3,499..................................... 6.7 0.9 1.4 1.5 1.0 1.9 0.4 1.4 3,500 to 3,999..................................... 5.2 0.8 1.2 1.0 0.8 1.5 0.4 1.3 4,000 or More...................................... 13.3 0.9 1.9 2.2 2.0 6.4 0.6 1.9 Heated Floorspace

69

Total...........................................................  

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

14.7 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500.................................... 3.2 0.7 Q 0.3 0.3 0.7 0.6 0.3 Q 500 to 999........................................... 23.8 2.7 1.4 2.2 2.8 5.5 5.1 3.0 1.1 1,000 to 1,499..................................... 20.8 2.3 1.4 2.4 2.5 3.5 3.5 3.6 1.6 1,500 to 1,999..................................... 15.4 1.8 1.4 2.2 2.0 2.4 2.4 2.1 1.2 2,000 to 2,499..................................... 12.2 1.4 0.9 1.8 1.4 2.2 2.1 1.6 0.8 2,500 to 2,999..................................... 10.3 1.6 0.9 1.1 1.1 1.5 1.5 1.7 0.8 3,000 to 3,499..................................... 6.7 1.0 0.5 0.8 0.8 1.2 0.8 0.9 0.8 3,500 to 3,999..................................... 5.2 1.1 0.3 0.7 0.7 0.4 0.5 1.0 0.5 4,000 or More...................................... 13.3

70

Total................................................  

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

.. .. 111.1 86.6 2,522 1,970 1,310 1,812 1,475 821 1,055 944 554 Total Floorspace (Square Feet) Fewer than 500............................. 3.2 0.9 261 336 162 Q Q Q 334 260 Q 500 to 999.................................... 23.8 9.4 670 683 320 705 666 274 811 721 363 1,000 to 1,499.............................. 20.8 15.0 1,121 1,083 622 1,129 1,052 535 1,228 1,090 676 1,500 to 1,999.............................. 15.4 14.4 1,574 1,450 945 1,628 1,327 629 1,712 1,489 808 2,000 to 2,499.............................. 12.2 11.9 2,039 1,731 1,055 2,143 1,813 1,152 Q Q Q 2,500 to 2,999.............................. 10.3 10.1 2,519 2,004 1,357 2,492 2,103 1,096 Q Q Q 3,000 or 3,499.............................. 6.7 6.6 3,014 2,175 1,438 3,047 2,079 1,108 N N N 3,500 to 3,999.............................. 5.2 5.1 3,549 2,505 1,518 Q Q Q N N N 4,000 or More...............................

71

Summary of Market Assessment of Upcoming Planned Refinery Outages  

Gasoline and Diesel Fuel Update (EIA)

Summary of Market Assessment of Upcoming Planned Refinery Outages Summary of Market Assessment of Upcoming Planned Refinery Outages Summary of Market Assessment of Upcoming Planned Refinery Outages Market Assessment of Upcoming Planned Refinery Outages, December 2008 - March 2009 reviews planned U.S. refinery outages from December 2008 though March 2009 in order to identify any regions where outages might create enough supply pressure to impact prices significantly. As required under Section 804 of the Energy Independence and Security Act of 2007 (Pub. L. 110-140), this report reviews the supply implications of planned refinery outages for December 2008 through March 2009, which covers the winter period when demand for distillate fuels (diesel and heating oil) is high. As a result, emphasis in this report is on distillate rather than gasoline. Refinery outages are the result of planned maintenance and unplanned outages. Maintenance is usually scheduled during the times when demand is lowest - in the first quarter and again in the fall. Unplanned outages, which occur for many reasons including mechanical failures, fires, and flooding, can occur at any time.

72

Application of Standard Maintenance Windows in PHWR Outage  

SciTech Connect

The concept of Standard Maintenance Windows has been widely used in the planned outage of light water reactor in the world. However, due to the specific feature of Pressurized Heavy Water Reactor (PHWR), it has not come to a consensus for the PHWR owners to adopt Standard Maintenance Windows for planned outage aiming at the optimization of outage duration. Third Qinshan Nuclear Power Company (TQNPC), with their experience gained in the previous outages and with reference to other PHWR power plants, has identified a set of Standard Maintenance Windows for planned outage. It can be applied to similar PHWR plants and with a few windows that are specific to Qinshan Phase III NPP. The use of these Standard Maintenance Windows in planned outage has been proved to be effective in control shutdown nuclear safety, minimize the unavailability of safety system, improve the efficient utilization of outage duration, and improved the flexibility of outage schedule in the case of emergency issue, which forced the revision of outage schedule. It has also formed a solid foundation for benchmarking. The identification of Standard Maintenance Windows and its application will be discussed with relevant cases for the common improvement of outage duration. (author)

Fuming Jiang [Third Qinshan Nuclear Power Company, Ltd. (China)

2006-07-01T23:59:59.000Z

73

MIMO ARQ with Multi-bit Feedback: Outage Analysis  

E-Print Network (OSTI)

We study the asymptotic outage performance of incremental redundancy automatic repeat request (INR-ARQ) transmission over the multiple-input multiple-output (MIMO) block-fading channels with discrete input constellations. We first show that transmission with random codes using a discrete signal constellation across all transmit antennas achieves the optimal outage diversity given by the Singleton bound. We then analyze the optimal SNR-exponent and outage diversity of INR-ARQ transmission over the MIMO block-fading channel. We show that a significant gain in outage diversity is obtained by providing more than one bit feedback at each ARQ round. Thus, the outage performance of INR-ARQ transmission can be remarkably improved with minimal additional overhead. A suboptimal feedback and power adaptation rule, which achieves the optimal outage diversity, is proposed for MIMO INR-ARQ, demonstrating the benefits provided by multi-bit feedback.

Nguyen, Khoa D; Fabregas, Albert Guillen i; Letzepis, Nick

2010-01-01T23:59:59.000Z

74

Definition: Outage Detection/Reporting | Open Energy Information  

Open Energy Info (EERE)

Outage Detection/Reporting Outage Detection/Reporting Jump to: navigation, search Dictionary.png Outage Detection/Reporting A system utilizing smart meters and AMI that can notify a utility of customer power outages when the power to meters is interrupted. Generally speaking, this can be done by utilizing meters that can send a "last gasp" signal to the head-end system upon losing power, or by periodically polling meters to check status.[1] Related Terms power, advanced metering infrastructure, system References ↑ https://www.smartgrid.gov/category/technology/outage_detectionreporting [[Cat Like Like You like this.Sign Up to see what your friends like. egory: Smart Grid Definitionssmart grid,smart grid, |Template:BASEPAGENAME]]smart grid,smart grid, Retrieved from "http://en.openei.org/w/index.php?title=Definition:Outage_Detection/Reporting&oldid=502576

75

Plant maintenance and outage management issue, 2005  

SciTech Connect

The focus of the January-February issue is on plant maintenance and outage managment. Major articles/reports in this issue include: Dawn of a new era, by Joe Colvin, Nuclear Energy Institute (NEI); Plant profile: Beloyarsk NPP, Russia, by Nikolai Oshkanov, Beloyarsk NPP, Russia; Improving economic performance, by R. Spiegelberg-Planner, John De Mella, and Marius Condu, IAEA; A model for improving performance, by Pet Karns, MRO Software; ASME codes and standards, by Shannon Burke, ASME International; and, Refurbishment programs, by Craig S. Irish, Nuclear Logistics, Inc.

Agnihotri, Newal (ed.)

2005-01-15T23:59:59.000Z

76

Minimize substation outage time by maximizing in-service testing  

Science Conference Proceedings (OSTI)

Most substation maintenance work is based on fixed schedules rather than on known need. Scheduled maintenance is essential and cannot be eliminated entirely, but priority should be given to equipment known to be deteriorated or defective. It makes no sense to perform costly, scheduled outage maintenance work when other equipment is failing because of undetected defects. The following should be included as major elements in an energized testing program: visual inspections; infrared inspection; corona inspection; percent oxygen in gas samples drawn from nitrogen-blanketed transformers; percent total combustible gas in gas samples drawn from nitrogen-blanketed transformers; dissolved gas analysis; oil quality tests; free water in the sample; dissolved water in oil; dissolved metals-in-oil analysis; furfural concentration analysis; SF[sub 6] analysis; battery testing; the substation grounding grid; and protective relays. 4 figs.

Lautenschlager, M. (High Voltage Maintenance Corp., Indianapolis, IN (United States))

1994-05-01T23:59:59.000Z

77

Nuclear outages back within typical range since July following ...  

U.S. Energy Information Administration (EIA)

U.S. nuclear generator outages were above the levels of the previous four years in the second quarter of 2011 but have returned to more typical ...

78

Nuclear outages begin to increase with the start of the ...  

U.S. Energy Information Administration (EIA)

Short-Term Energy Outlook ... Search EIA.gov. A-Z Index; ... several units began to reduce their output to enter into refueling outages, ...

79

Market Assessment of Refinery Outages Planned for October 2010 ...  

U.S. Energy Information Administration (EIA)

distillation and FCC unit outages are projected to be at typical to above typical levels in the second half of 2010, with some months significantly above average in ...

80

Market Assessment of Refinery Outages Planned for March 2010 ...  

U.S. Energy Information Administration (EIA)

DOE/EIA-0641(2010)/1 Market Assessment of Refinery Outages Planned for March 2010 through June 2010 March 2010 Energy Information Administration

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


81

Power outages often spur questions around burying power lines ...  

U.S. Energy Information Administration (EIA)

Smart grid technology, which would allow a utility to pinpoint problems, divert power through other circuits to minimize outages, and optimize crew deployments is ...

82

Minimum-outage broadcast in wireless networks with fading channels  

Science Conference Proceedings (OSTI)

We consider the problem of cooperative broadcasting for minimum outage in wireless networks. We consider wireless multihop broadcast as a set of transmitters that transmit in a certain order. The receiving nodes are able to combine all the previous transmissions ... Keywords: broadcast, multicast, outage, wireless networks

Tolga Girici; Gulizar Duygu Kurt

2010-07-01T23:59:59.000Z

83

New tensioning equipment saves critical path time in nuclear outage  

SciTech Connect

This article examines the selection and application of new tensioning equipment for TVA`s Browns Ferry Nuclear Plant. The new device would reduce refueling outage time and radiation exposure, and require fewer personnel to operate. Results of the equipment performance during the refueling outage and problems encountered and resolved are described.

NONE

1995-10-01T23:59:59.000Z

84

A stochastic model for the measurement of electricity outage costs  

SciTech Connect

The measurement of customer outage costs has recently become an important subject of research for electric utilities. This paper uses a stochastic dynamic model as the starting point in developing a market-based method for the evaluation of outage costs. Specifically, the model postulates that once an electricity outage occurs, all production activity stops. Full production is resumed once the electricity outage is over. This process repeats itself indefinitely. The business customer maximizes his expected discounted profits (the expected value of the firm), taking into account his limited ability to respond to repeated random electricity outages. The model is applied to 11 industrial branches in Israel. The estimates exhibit a large variation across branches. 34 refs., 3 tabs.

Grosfeld-Nir, A.; Tishler, A. (Tel Aviv Univ. (Israel))

1993-01-01T23:59:59.000Z

85

Homeowners: Respond to Power Outages | Department of Energy  

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

Power Outages Power Outages Homeowners: Respond to Power Outages Homeowners: Respond to Power Outages After a disaster, electric utilities and government officials will first work to restore power to critical infrastructure like power plants and transmission lines, water treatment facilities, and telecommunications networks, and also to hospitals, critical care facilities, and emergency response agencies. It may take several days or even weeks to restore power to individual homeowners, but here's what you can do to help prepare and recover power more quickly: Charge mobile devices-If you have power, charge your cell phones, laptops, and other mobile devices so they'll have the maximum amount of battery power stored in the event of a power outage. These devices will help you communicate with your power company, and they'll help you stay

86

U.S. - Canada Power System Outage Task Force: Final Report on...  

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

- Canada Power System Outage Task Force: Final Report on the Implementation of Task Force Recommendations U.S. - Canada Power System Outage Task Force: Final Report on the...

87

Technology Integration Initiative In Support of Outage Management  

SciTech Connect

Plant outage management is a high priority concern for the nuclear industry from cost and safety perspectives. Often, command and control during outages is maintained in the outage control center where many of the underlying technologies supporting outage control are the same as those used in the 1980’s. This research reports on the use of advanced integrating software technologies and hand held mobile devices as a means by which to reduce cycle time, improve accuracy, and enhance transparency among outage team members. This paper reports on the first phase of research supported by the DOE Light Water Reactor Sustainability (LWRS) Program that is performed in close collaboration with industry to examine the introduction of newly available technology allowing for safe and efficient outage performance. It is thought that this research will result in: improved resource management among various plant stakeholder groups, reduced paper work, and enhanced overall situation awareness for the outage control center management team. A description of field data collection methods, including personnel interview data, success factors, end-user evaluation and integration of hand held devices in achieving an integrated design are also evaluated. Finally, the necessity of obtaining operations cooperation support in field studies and technology evaluation is acknowledged.

Gregory Weatherby; David Gertman

2012-07-01T23:59:59.000Z

88

Economic Benefits of Increasing Electric Grid Resilience to Weather Outages  

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

Economic Benefits of Increasing Electric Grid Resilience to Weather Economic Benefits of Increasing Electric Grid Resilience to Weather Outages Economic Benefits of Increasing Electric Grid Resilience to Weather Outages In June 2011, President Obama released A Policy Framework for the 21st Century Grid which set out a four-pillared strategy for modernizing the electric grid. The initiative directed billions of dollars toward investments in 21st century smart grid technologies focused at increasing the grid's efficiency, reliability, and resilience, and making it less vulnerable to weather-related outages and reducing the time it takes to restore power after an outage occurs. Grid resilience is increasingly important as climate change increases the frequency and intensity of severe weather. Greenhouse gas emissions are elevating air and water temperatures around the world. Scientific research

89

A statistical model for risk management of electric outage forecasts  

Science Conference Proceedings (OSTI)

Risk management of power outages caused by severe weather events, such as hurricanes, tornadoes, and thunderstorms, plays an important role in electric utility distribution operations. Damage prediction based on weather forecasts on an appropriate spatial ...

H. Li; L. A. Treinish; J. R. M. Hosking

2010-05-01T23:59:59.000Z

90

Abstract--Integration of asset management and outage management tasks for distribution system is proposed and  

E-Print Network (OSTI)

and evaluation of the influence of optimization on the cost of system outage is elaborated. Potential benefit as the maximum tolerable value. #12;7 V. OPTIMIZED OUTAGE COST THROUGH RISK-BASED ASSESSMENT 1. Optimized outage cost through risk-based assessment Risk-based analysis is used to estimate outage cost in this paper

Kezunovic, Mladen

91

Overview of Common Mode Outages in Power Systems  

SciTech Connect

This paper is a result of ongoing activity carried out by Probability Applications for Common Mode Events (PACME) Task Force under the Reliability Risk and Probability Applications (RRPA) Subcommittee. The paper is intended to constitute a valid source of information and references about dealing with common-mode outages in power systems reliability analysis. This effort involves reviewing published literature and presenting state-of-the-art research and practical applications in the area of common-mode outages. Evaluation of available outage statistics show that there is a definite need for collective effort from academia and industry to not only recommended procedures for data collection and monitoring but also to provide appropriate mathematical models to assess such events.

Papic, Milorad; Awodele , Kehinde; Billinton, Roy; Dent, Chris; Eager, Dan; Hamoud, Gomaa; Jirutitijaroen, Panida; Kumbale, Murali; Mitra, Joydeep; Samaan, Nader A.; Schneider, Alex; Singh, Chanan

2012-11-10T23:59:59.000Z

92

Lassoing Line Outages in the Smart Power Grid  

E-Print Network (OSTI)

Fast and accurate unveiling of power line outages is of paramount importance not only for preventing faults that may lead to blackouts, but also for routine monitoring and control tasks of the smart grid, including state estimation and optimal power flow. Existing approaches are either challenged by the \\emph{combinatorial complexity} issues involved, and are thus limited to identifying single- and double-line outages; or, they invoke less pragmatic assumptions such as \\emph{conditionally independent} phasor angle measurements available across the grid. Using only a subset of voltage phasor angle data, the present paper develops a near real-time algorithm for identifying multiple line outages at the affordable complexity of solving a quadratic program via block coordinate descent iterations. The novel approach relies on reformulating the DC linear power flow model as a \\emph{sparse} overcomplete expansion, and leveraging contemporary advances in compressive sampling and variable selection using the least-abso...

Zhu, Hao

2011-01-01T23:59:59.000Z

93

A Review of Power Outages and Restoration Following the June 2012 Derecho  

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

This report reviews power outages and restoration efforts following the June 29, 2012 Derecho and compares them to outages and restoration efforts following other spring and summer storms in the...

94

Notification of Planned 230kV Outage at Potomac River Generating...  

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

to provide notification of any and all 230kV planned and unplanned outages at Potomac River Generating Station. Notification of Planned 230kV Outage at Potomac River Generating...

95

Mitigation of Animal-Caused Outages For Distribution Lines and Substations  

Science Conference Proceedings (OSTI)

A significant number of electric outages throughout North America are caused by animals -- mammals, birds, snakes, etc. These animal-caused outages are increasingly common in both urban and residential areas. By taking a pro-active approach to mitigating outages, utilities will spare the lives of wildlife and address the increasing pressures from environmental groups and concerned utility customers. This document describes a study designed to mitigate animal-caused outages for distribution lines and subs...

1999-12-20T23:59:59.000Z

96

96 IEEE power & energy magazine march/april 2005 THE MASSIVE POWER OUTAGE OF  

E-Print Network (OSTI)

of power outages. These devices, which came into play during last year's blackout, typically perform for more outages and the increased cost of out- ages at the consumer level. We can-- and must96 IEEE power & energy magazine march/april 2005 T THE MASSIVE POWER OUTAGE OF August 2003

Amin, S. Massoud

97

A Framework and Review of Customer Outage Costs: Integration and Analysis of  

E-Print Network (OSTI)

by Region, Season, Day of Week, and Year 36 Table 5-2. Average Outage Costs by Duration 36 Table 5, if a calculation of the average outage cost for a given year is calculated it would be heavily influenced and Day of Week and Year of Study This problem surfaces for many of the calculations of outage costs

98

Environmental determinants of unscheduled residential outages in the electrical power distribution of Phoenix, Arizona  

E-Print Network (OSTI)

problem. We model electric interruptions using outage data between the years of 2002 and 2005 across, and interactions between the two. We model electric interruptions using outage data for the years 2002;22:117­21. [14] Fritts TH. Economic costs of electrical system instability and power outages caused by snakes

99

Nuclear Maintenance Applications Center: Effective Refueling Outage Preparation and Execution Guidance--Revision to 1014480  

Science Conference Proceedings (OSTI)

This report provides updated, current guidance to assist outage managers and teams during preparation and execution phases of a nuclear refueling outage. Included is guidance on how the outage activities support long-range and strategic plans developed by the site or fleet of units.

2011-12-13T23:59:59.000Z

100

A framework and review of customer outage costs: Integration and analysis of electric utility outage cost surveys  

Science Conference Proceedings (OSTI)

A clear understanding of the monetary value that customers place on reliability and the factors that give rise to higher and lower values is an essential tool in determining investment in the grid. The recent National Transmission Grid Study recognizes the need for this information as one of growing importance for both public and private decision makers. In response, the U.S. Department of Energy has undertaken this study, as a first step toward addressing the current absence of consistent data needed to support better estimates of the economic value of electricity reliability. Twenty-four studies, conducted by eight electric utilities between 1989 and 2002 representing residential and commercial/industrial (small, medium and large) customer groups, were chosen for analysis. The studies cover virtually all of the Southeast, most of the western United States, including California, rural Washington and Oregon, and the Midwest south and east of Chicago. All variables were standardized to a consistent metric and dollar amounts were adjusted to the 2002 CPI. The data were then incorporated into a meta-database in which each outage scenario (e.g., the lost of electric service for one hour on a weekday summer afternoon) is treated as an independent case or record both to permit comparisons between outage characteristics and to increase the statistical power of analysis results. Unadjusted average outage costs and Tobit models that estimate customer damage functions are presented. The customer damage functions express customer outage costs for a given outage scenario and customer class as a function of location, time of day, consumption, and business type. One can use the damage functions to calculate outage costs for specific customer types. For example, using the customer damage functions, the cost experienced by an ''average'' customer resulting from a 1 hour summer afternoon outage is estimated to be approximately $3 for a residential customer, $1,200 for small-medium commercial and industrial customer, and $82,000 for large commercial and industrial customer. Future work to improve the quality and coverage of information on the value of electricity reliability to customers is described.

Lawton, Leora; Sullivan, Michael; Van Liere, Kent; Katz, Aaron; Eto, Joseph

2003-11-01T23:59:59.000Z

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


101

Notice of Unplanned Outage at the Mirant Potomac River Plant | Department  

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

Unplanned Outage at the Mirant Potomac River Plant Unplanned Outage at the Mirant Potomac River Plant Notice of Unplanned Outage at the Mirant Potomac River Plant Docket No. EO-05-01. Order No. 202-05-03: Pursuant to the United States Department of Energy ("DOE") Order No_ 202-05-3, issued December 20, 2005 ("DOE Potomac River Order"), Pepco hereby files this notice of an unplanned outage of one of the 230kV circuits serving the Potomac River Substation, and through that station, the District of Columbia. Notice of Unplanned Outage at the Mirant Potomac River Plant More Documents & Publications Re: Potomac River Generating Station Department of Energy, Case No. EO-05-01: Potomac Electric Power Company (PEPCO) Concerning Planned Outages of the 230 kV circuits Further Notice of 230kV Circuit Planned Outages

102

Notification of Planned 230kV Outage at Potomac River Generating Station |  

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

Notification of Planned 230kV Outage at Potomac River Generating Notification of Planned 230kV Outage at Potomac River Generating Station Notification of Planned 230kV Outage at Potomac River Generating Station Docket No. EO-05-01. In accordance with DOE Order No. 202-05-03 Pepco is required to provide notification of any and all 230kV planned outages at Potomac River Generating Station. On Tuesday February 20, 2007 Potomac Electric Power Company (Pepco) will be taking a planned outage on the 23106 high voltage circuit between the Palmer's Corner Substation and the Potomac River Generating Station. Notification of Planned 230kV Outage at Potomac River Generating Station More Documents & Publications Re: Potomac River Generating Station Department of Energy Case No. EO-05-01: Advanced Notice of Power Outages. Special Environmental Analysis For Actions Taken under U.S. Department of

103

Further Notice of 230kV Circuit Planned Outages | Department of Energy  

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

Further Notice of 230kV Circuit Planned Outages Further Notice of 230kV Circuit Planned Outages Further Notice of 230kV Circuit Planned Outages Docket No. EO-05-01. Order No. 202-05-03: Pursuant 10 the United States Department of Energy "DOE") Order No. 102-05-3, issued December 20, 2005 ("DOE Potomac River Order''), Pepco hereby files this Further Notice Of 230kV Circuit Planned Outages serving the Potomac River Substation, and through thaI station, the District of Columbia. Further Notice of 230kV Circuit Planned Outages More Documents & Publications Re: Potomac River Generating Station Department of Energy, Case No. EO-05-01: Potomac Electric Power Company (PEPCO) Concerning Planned Outages of the 230 kV circuits Docket No. EO-05-01: Further Notice of 230kV Circuit Planned Outages

104

Further Notice of 230kV Circuit Planned Outages | Department of Energy  

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

Further Notice of 230kV Circuit Planned Outages Further Notice of 230kV Circuit Planned Outages Further Notice of 230kV Circuit Planned Outages Docket No. EO-05-01. Order No. 202-05-03: Pursuant 10 the United States Department of Energy "DOE") Order No. 102-05-3, issued December 20, 2005 ("DOE Potomac River Order''), Pepco hereby files this Further Notice Of 230kV Circuit Planned Outages serving the Potomac River Substation, and through thaI station, the District of Columbia. Further Notice of 230kV Circuit Planned Outages More Documents & Publications Docket No. EO-05-01: Further Notice of 230kV Circuit Planned Outages Re: Potomac River Generating Station Department of Energy, Case No. EO-05-01: Potomac Electric Power Company (PEPCO) Concerning Planned Outages of the 230 kV circuits

105

HPSS Outage Tue Mar 19 - Fri Mar 22  

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

HPSS HPSS Outage Tue Mar 19 - Fri Mar 22 HPSS Outage Tue Mar 19 - Fri Mar 22 March 12, 2013 by Francesca Verdier (0 Comments) The NERSC HPSS "User" system (archive.nersc.gov) will be down for four days from Tue Mar 19 07:00 to Fri Mar 22 17:00). The system will be upgraded from HPSS version 6.2 to version 7.3. This new version of the HPSS server software is not compatible with current GridFTP servers. This means the NERSC HPSS systems will not support any grid-based transfer methods (including GlobusOnline) following the upgrade. We expect to install a fix for this problem during a scheduled downtime by the end of April. This is a major upgrade that will require users of the HPSS User system to switch to new versions of the HPSS client software tools hsi and htar.

106

Model validation for the August 10, 1996 WSCC system outage  

SciTech Connect

A major power outage occurred in western North America on August 10, 1996. In this paper the authors describe simulation of the disturbance using a transient stability program. Initially, the sequence of events was simulated using the standard WSCC dynamic data base, and the simulations did not agree with the disturbance recordings. Several model additions and data modifications were made before the simulations approximated the disturbance recordings. These model changes are discussed in the paper.

Kosterev, D.N.; Taylor, C.W.; Mittelstadt, W.A. [Bonneville Power Administration, Portland, OR (United States). Transmission Operations and Planning

1999-08-01T23:59:59.000Z

107

Common Information Model Meter Outage Nominal Interoperability Test Procedure  

Science Conference Proceedings (OSTI)

The CIM Meter Outage Nominal Interoperability Test Procedure is one in a series of EPRI CIM Interoperability Test Procedures (ETIPs) created by EPRI whose purpose is to thoroughly document the actors, interfaces, and test steps for the interoperability testing of specific parts of the International Electrotechnical Commission (IEC) Common Information Model (CIM) standard. The Test Procedures are initially being used for EPRI demonstration tests and are intended, over time, to form the basis of a set of C...

2011-12-16T23:59:59.000Z

108

Examination of the Exacter Outage-Avoidance System  

Science Conference Proceedings (OSTI)

A routine inspection program is one tool that utilities can use to reduce failures on their circuits and minimize customer outages. By identifying problems for repair before they develop into failures, an inspection program can be a cost-effective method for enhancing the quality and reliability of electric service. The present methods used to detect and locate underperforming power system hardware can be time consuming and can involve physical complexities and require line crews with bucket trucks to tr...

2009-11-30T23:59:59.000Z

109

Risk Assessment of Cascading Outages: Methodologies and Challenges  

Science Conference Proceedings (OSTI)

Abstract- This paper is a result of ongoing activity carried out by Understanding, Prediction, Mitigation and Restoration of Cascading Failures Task Force under IEEE Computer Analytical Methods Subcommittee (CAMS). The task force's previous papers are focused on general aspects of cascading outages such as understanding, prediction, prevention and restoration from cascading failures. This is the first of two new papers, which extend this previous work to summarize the state of the art in cascading failure risk analysis methodologies and modeling tools. This paper is intended to be a reference document to summarize the state of the art in the methodologies for performing risk assessment of cascading outages caused by some initiating event(s). A risk assessment should cover the entire potential chain of cascades starting with the initiating event(s) and ending with some final condition(s). However, this is a difficult task and heuristic approaches and approximations have been suggested. This paper discusses different approaches to this and suggests directions for future development of methodologies. The second paper summarizes the state of the art in modeling tools for risk assessment of cascading outages.

Vaiman, Marianna; Bell, Keith; Chen, Yousu; Chowdhury, Badrul; Dobson, Ian; Hines, Paul; Papic, Milorad; Miller, Stephen; Zhang, Pei

2012-05-31T23:59:59.000Z

110

Outage-Efficient Downlink Transmission Without Transmit Channel State Information  

E-Print Network (OSTI)

This paper investigates downlink transmission over a quasi-static fading Gaussian broadcast channel (BC), to model delay-sensitive applications over slowly time-varying fading channels. System perfor-mance is characterized by outage achievable rate regions. In contrast to most previous work, here the problem is studied under the key assumption that the transmitter only knows the probability distributions of the fading coefficients, but not their realizations. For scalar-input channels, two coding schemes are proposed. The first scheme is called blind dirty paper coding (B-DPC), which utilizes a robustness property of dirty paper coding to perform precoding at the transmitter. The second scheme is called statistical superposition coding (S-SC), in which each receiver adaptively performs successive decoding with the process statistically governed by the realized fading. Both B-DPC and S-SC schemes lead to the same outage achievable rate region, which always dominates that of time-sharing, irrespective of the particular fading distributions. The S-SC scheme can be extended to BCs with multiple transmit antennas. Index Terms Broadcast channel, (blind) dirty paper coding, downlink, non-ergodic fading, outage achievable rate region, quasi-static fading, (statistical) superposition coding

Wenyi Zhang; Shivaprasad Kotagiri; Student Member; J. Nicholas Laneman; Senior Member

2007-01-01T23:59:59.000Z

111

Abstract--Cascading outages can cause large blackouts, and a variety of methods are emerging to study this challenging topic.  

E-Print Network (OSTI)

1 Abstract-- Cascading outages can cause large blackouts, and a variety of methods are emerging Analysis, Risk Analysis, Preventing Cascades. I. INTRODUCTION A cascading outage is a sequence of events component outages (based on [1] and [2]). In some cases cascading outages halt before the sequence results

Hines, Paul

112

Docket No. EO-05-01: Further Notice of 230kV Circuit Planned Outages |  

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

Further Notice of 230kV Circuit Planned Further Notice of 230kV Circuit Planned Outages Docket No. EO-05-01: Further Notice of 230kV Circuit Planned Outages Docket No. EO-05-01. Pursuant to the United States Department of Energy Order No. 202-05-03, issued December 20, 2005 directing Mirant Potomac River to generate electricity at Potomac River Generating Station, PEPCO hereby files this Further Notice of 230kV Circuit Planned Outages. Docket No. EO-05-01: Further Notice of 230kV Circuit Planned Outages More Documents & Publications Further Notice of 230kV Circuit Planned Outages Re: Potomac River Generating Station Department of Energy, Case No. EO-05-01: Potomac Electric Power Company (PEPCO) Concerning Planned Outages of the 230 kV circuits Re: Potomac River Generating Station Department of Energy Case No.

113

Study, outlines why outages go long, short, or on-time  

SciTech Connect

A recent report by a nuclear industry professional, based on a survey of outage managers at US nuclear power plants, declares that [open quotes]preplanned outage schedules appear to be grossly inaccurate, and the outage management planners and schedulers do not have a grasp of the requirements and/or the resources needed to complete the actual activities on schedule.[close quotes] It declares that [open quotes]the scheduled duration of a planned outage must be realistic.[close quotes] The study identifies personnel, planning and scheduling, and equipment/hardware as [open quotes]the primary reasons why refueling outages and outage activities finished ahead of, right on, or behind schedule.[close quotes

Not Available

1993-09-01T23:59:59.000Z

114

Outage Closeout and Unit Restart Guidelines for Fossil-Fueled Power Plants  

Science Conference Proceedings (OSTI)

Outage closeout planning and execution and successful restart are as important as the efforts going into an outage. Detailed planning and execution are required to ensure that schedules are met, tests are completed in a timely fashion, training is completed, and that lessons learned are captured for use in future outages, both planned and forced. Effective closure and restart activities result in a smoother return to service and more reliable operation. This project is based upon collective industry expe...

2008-12-22T23:59:59.000Z

115

Notification of Planned 230kV Outage at Potomac River Generating Station  

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

Sent: Wednesday, May 16, 2007 4:49 PM To: #DOE_Notification@pepco.com Subject: Notification of Planned 230kV Outage at Potomac River Generating Station To Whom It May Concern: This morning Pepco and PJM observed that the generation at the Potomac River Generating Station was having difficulty matching the station generation requirement to the Potomac River area load. Mirant has also informed Pepco and PJM that several generating units were experiencing equipment problems which required them to reduce unit and total plant output. Based on these observations and information received from Mirant, Pepco has elected to cease the current work activities underway on xxxxx high voltage circuit and we will be placing this transmission line back in service this afternoon.

116

Notification of Planned 230kV Outage at Potomac River Generating...  

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

The next planned outage on xxxxx high voltage circuit between Palmers Corner Substation and the Potomac River Generating Station is scheduled for Sunday, June 3, 2007 and will...

117

A Study of Outage Management Practices at Selected U.S. Nuclear Plants  

SciTech Connect

This paper presents insights gained from a study of the outage management practices at a number of U.S. nuclear plants. The objective of the study was to conduct an in-depth review of the current practices of outage management at these selected plants and identify important factors that have contributed to the recent success of their outage performance. Two BWR-4, three BWR-6, and two 3-loop Westinghouse PWR plants were selected for this survey. The results of this study can be used to formulate outage improvement efforts for nuclear plants in other countries. (author)

Lin, James C. [ABSG Consulting Inc., Irvine, CA (United States)

2002-07-01T23:59:59.000Z

118

Synthesis of power plant outage schedules. Final technical report, April 1995-January 1996  

SciTech Connect

This document provides a report on the creation of domain theories in the power plant outage domain. These were developed in conjunction with the creation of a demonstration system of advanced scheduling technology for the outage problem. In 1994 personnel from Rome Laboratory (RL), Kaman Science (KS), Kestrel Institute, and the Electric Power Research Institute (EPRI) began a joint project to develop scheduling tools for power plant outage activities. This report describes our support for this joint effort. The project uses KIDS (Kestrel Interactive Development System) to generate schedulers from formal specifications of the power plant domain outage activities.

Smith, D.R.

1997-07-01T23:59:59.000Z

119

Department of Energy Order No. 202-05-03 Notice of Planned Outages...  

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

Outages, in Sequence During January 2006 More Documents & Publications Re: Potomac River Generating Station Department of Energy, Case No. EO-05-01: Potomac Electric Power...

120

Draft!07"18"2011! 1 Turning the Tide on Outages1  

E-Print Network (OSTI)

mitigate outages during the harshest weather, terrorist attacks, or natural disasters. This system into IIT Main Campus's current infrastructure. The initiative's approach is to implement local microgrids

Amin, S. Massoud

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


121

Oil Peak or Panic?  

SciTech Connect

In this balanced consideration of the peak-oil controversy, Gorelick comes down on the side of the optimists.

Greene, David L [ORNL

2010-01-01T23:59:59.000Z

122

Current industry practices in bulk transmission outage data collection and analysis  

SciTech Connect

This paper focuses on the state-of-the-art bulk transmission outage data collection and analysis. Included in this discussion is the motivation for interest, single/multiple outage event analysis, and identification of where to obtain data on weather conditions which impact the performance of bulk transmission.

Not Available

1992-02-01T23:59:59.000Z

123

A Tight Lower Bound to the Outage Probability of Discrete-Input Block-Fading Channels  

Science Conference Proceedings (OSTI)

In this correspondence, a tight lower bound to the outage probability of discrete-input Nakagami-m block-fading channels is proposed. The approach permits an efficient method for numerical evaluation of the bound, providing an additional tool for system ... Keywords: Block-fading channel, diversity, error probability, outage probability, rate-diversity tradeoff, signal-to-noise ratio (SNR)-exponent

K. D. Nguyen; A. Guillen i Fabregas; L. K. Rasmussen

2007-11-01T23:59:59.000Z

124

Market Assessment of Planned Refinery Outages March Â… June 2009  

Gasoline and Diesel Fuel Update (EIA)

09)/1 09)/1 Market Assessment of Planned Refinery Outages March - June 2009 March 2009 Energy Information Administration Office of Oil and Gas U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy position of the U.S. Department of Energy or any other organization. Service Reports are prepared by the Energy Information Administration upon special request and are based on assumptions specified by the requestor.

125

Microsoft Word - 112706 Final Outage Letter PUBLIC.doc  

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

CRITICAL ENERGY INFRASTRUCTURE INFORMATION CRITICAL ENERGY INFRASTRUCTURE INFORMATION REMOVED FOR PRIVILEGED TREATMENT November 27, 2006 Lawrence Mansueti Office of Electricity Delivery and Energy Reliability U.S. Department of Energy Rm. 8H-033 1000 Independence Avenue Washington, D.C. 20585 Re: Potomac River Generating Station Department of Energy Case No. EO-05-01 Dear Mr. Mansueti: Potomac Electric Power Company ("Pepco"), on behalf of itself and PJM Interconnection, L.L.C. ("PJM"), is providing you with information regarding the planned transmission outages that are scheduled for the upcoming months. In accordance with its internal procedures developed pursuant to the December 20, 2005 order in the captioned proceeding, Order No. 202-05-03 ("December 20 Order"), Pepco will provide

126

Peaks Over Threshold Plot  

Science Conference Proceedings (OSTI)

... CAPTURE POT.OUT PEAKS OVER THRESHOLD PLOT Y17 R END OF CAPTURE . SKIP 0 READ DPST2F.DAT ITER NPOINTS THRESH R2 XR . ...

2010-12-06T23:59:59.000Z

127

Automated Critical Peak Pricing Field Tests: Program Description and Results  

E-Print Network (OSTI)

Usage: The total effective energy charge for usage duringUsage: The total effective energy charge for usage duringtotal effective TOU energy rates through offsetting summer on-peak and part-peak rate credits for usage

Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Xu, Peng

2006-01-01T23:59:59.000Z

128

Analysis of Country-wide Internet Outages Caused by Censorship  

E-Print Network (OSTI)

In the first months of 2011, Internet communications were disrupted in several North African countries in response to civilian protests and threats of civil war. In this paper we analyze episodes of these disruptions in two countries: Egypt and Libya. Our analysis relies on multiple sources of large-scale data already available to academic researchers: BGP interdomain routing control plane data; unsolicited data plane traffic to unassigned address space; active macroscopic traceroute measurements; RIR delegation files; and MaxMind’s geolocation database. We used the latter two data sets to determine which IP address ranges were allocated to entities within each country, and then mapped these IP addresses of interest to BGP-announced address ranges (prefixes) and origin ASes using publicly available BGP data repositories in the U.S. and Europe. We then analyzed observable activity related to these sets of prefixes and ASes throughout the censorship episodes. Using both control plane and data plane data sets in combination allowed us to narrow down which forms of Internet access disruption were implemented in a given region over time. Among other insights, we detected what we believe were Libya’s attempts to test firewallbased blocking before they executed more aggressive BGP-based disconnection. Our methodology could be used, and automated, to detect outages or similar macroscopically disruptive events in other geographic or topological regions.

Alberto Dainotti; Kimberly C. Claffy; Michele Russo; Claudio Squarcella; Marco Chiesa; Antonio Pescapé; Emile Aben

2011-01-01T23:59:59.000Z

129

No (Brain)power Outage at a Competition Like No Other  

Office of Science (SC) Website

No (Brain)power Outage at a Competition Like No Other News In the News In Focus 2013 2012 2011 2010 2009 2008 2007 2006 2005 Presentations & Testimony Recovery Act Contact...

130

U.S. - Canada Power System Outage Task Force: Final Report on the  

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

- Canada Power System Outage Task Force: Final Report on the - Canada Power System Outage Task Force: Final Report on the Implementation of Task Force Recommendations U.S. - Canada Power System Outage Task Force: Final Report on the Implementation of Task Force Recommendations On August 14, 2003, the largest power blackout in North American history affected an area with an estimated 50 million people and 61,800 megawatts (MW) of electric load in the states of Ohio, Michigan, Pennsylvania, New York, Vermont, Massachusetts, Connecticut and New Jersey, and the Canadian province of Ontario. U.S. - Canada Power System Outage Task Force: Final Report on the Implementation of Task Force Recommendations More Documents & Publications Blackout 2003: Blackout Final Implementation Report Blackout 2003: The August 14, 2003 Blackout One Year Later: Actions Taken

131

Notification of Planned 230kV Outage at Potomac River Generating...  

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

The next planned outage on xxxxx high voltage circuit between xxxxx and xxxxx is tentatively scheduled for Saturday May 19, 2007 and will begin at 4:00 AM with a scheduled return...

132

Efficient algorithms for outage minimization in parallel fading channels with limited feedback  

Science Conference Proceedings (OSTI)

In this paper, we address the optimal power allocation problem for minimizing the notion of information theoretic outage for an M parallel block-Rayleigh-fading channels using a finite rate power codebook (limited feedback). In contrast to the ...

YuanYuan He; Subhrakanti Dey

2009-09-01T23:59:59.000Z

133

A Novel Dynamic Voltage Restorer with Outage Handling Capability Using Fuzzy Logic Controler  

Science Conference Proceedings (OSTI)

This paper presents a novel dynamic voltage restorer (DVR) capable of handling deep sags including outage on a low voltage distribution system. The DVR recovers sags up to 10% of nominal voltage; otherwise, it will operate as an uninterruptible power ...

M. Ashari; T. Hiyama; M. Pujiantara; H. Suryoatmojo; M. Hery Purnomo

2007-09-01T23:59:59.000Z

134

ORNL Network Outage, Saturday, June 12, 6:00-8:00 a.m.  

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

June 12, 2010, 6:00 a.m. to 8:00 a.m. EDT All externally accessible ORNL servers, including the ORNL DAAC Web Site, http:daac.ornl.gov will experience brief network outages...

135

Notification of Planned 230kV Outage at Potomac River Generating Station |  

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

In accordance with DOE Order No. 202-05-03 Pepco is In accordance with DOE Order No. 202-05-03 Pepco is required to provide notification of any and all 230kV planned outages at Potomac River Generating Station. On Tuesday February 20, 2007 Potomac Electric Power Company (Pepco) will be taking a planned outage on the 23106 high voltage circuit between the Palmer's Corner Substation and the Potomac River Generating Station. Notification of Planned 230kV Outage at Potomac River Generating Station More Documents & Publications Re: Potomac River Generating Station Department of Energy Case No. EO-05-01: Advanced Notice of Power Outages. Special Environmental Analysis For Actions Taken under U.S. Department of Energy Emergency Orders Regarding Operation of the Potomac River Generating Station in Alexandria, Virginia

136

A Review of Power Outages and Restoration Following the June 2012 Derecho |  

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

A Review of Power Outages and Restoration Following the June 2012 A Review of Power Outages and Restoration Following the June 2012 Derecho A Review of Power Outages and Restoration Following the June 2012 Derecho August 7, 2012 - 11:16am Addthis The Office of Electricity Delivery and Energy Reliability has released a report that reviews power outages and restoration efforts following the June 29, 2012 Derecho and compares them to outages and restoration efforts following other spring and summer storms in the Ohio Valley and Mid-Atlantic regions. View the Report. Addthis Related Articles Salazar, Chu Announce Major Offshore Wind Initiatives A Review of Power Outages and Restoration Following the June 2012 Derecho Response to Hurricane Irene - Restoring Power on the East Coast President Barack Obama listens to Acting Energy Secretary Daniel B. Poneman during a meeting with electric utility CEOs and trade association representatives at the Department of Energy in Washington, D.C., May 8, 2013. | Official White House Photo by Pete Souza.

137

PEAK READING VOLTMETER  

DOE Patents (OSTI)

An improvement in peak reading voltmeters is described, which provides for storing an electrical charge representative of the magnitude of a transient voltage pulse and thereafter measuring the stored charge, drawing oniy negligible energy from the storage element. The incoming voltage is rectified and stored in a condenser. The voltage of the capacitor is applied across a piezoelectric crystal between two parallel plates. Amy change in the voltage of the capacitor is reflected in a change in the dielectric constant of the crystal and the capacitance between a second pair of plates affixed to the crystal is altered. The latter capacitor forms part of the frequency determlning circuit of an oscillator and means is provided for indicating the frequency deviation which is a measure of the peak voltage applied to the voltmeter.

Dyer, A.L.

1958-07-29T23:59:59.000Z

138

The Year of Peak Production  

U.S. Energy Information Administration (EIA)

When world conventional oil production will peak is, of course, the bottom-line question. It has already peaked in the United States, in 1970.

139

ORNL Network Outage, Friday, April 15, 9:30 p.m. to Date  

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

Outage Outage All externally accessible ORNL servers, including the ORNL DAAC Web Site, http://daac.ornl.gov are experiencing network outages or slow connectivity at this time. The ORNL Information Technology's Cyber Security Program is working hard to restore full external functionality. We apologize for this inconvenience and appreciate your patience during our down time. At this time you can explore our Web site and access data products including MODIS Land Products Subsets, albeit slowly. The following tools: Mercury (Simple Search and Advanced Product Search) WebGIS Spatial Data Access Tool (SDAT) Thematic Real-time Environmental Distributed Data Services (THREDDS) Data Server (TDS) as well as the following Web Sites: Mast-DC FLUXNET are not available. You may experience problems signing-in or

140

Power Outages Update: Post-Tropical Cyclone Sandy | Department of Energy  

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

Outages Update: Post-Tropical Cyclone Sandy Outages Update: Post-Tropical Cyclone Sandy Power Outages Update: Post-Tropical Cyclone Sandy October 29, 2012 - 9:37pm Addthis Sandy made landfall as a post-tropical cyclone on the southern coast of New Jersey near Atlantic City at 8 p.m. with top sustained winds of 80 mph. | Photo courtesy of NOAA Sandy made landfall as a post-tropical cyclone on the southern coast of New Jersey near Atlantic City at 8 p.m. with top sustained winds of 80 mph. | Photo courtesy of NOAA Dan Leistikow Dan Leistikow Former Director, Office of Public Affairs As of 8:00 pm EDT on October 29, there were more than 3.6 million customers without power in the affected states. The Energy Department is continuing to monitor the progress of the storm throughout the night and will publish

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


141

Market Assessment of Refinery Outages Planned for March 2011 through June 2011  

Gasoline and Diesel Fuel Update (EIA)

Assessment of Refinery Assessment of Refinery Outages Planned for March 2011 through June 2011 APRIL 2011 www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration / Market Assessment of Planned Refinery Outages / March 2011 - June 2011 ii This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other Federal agencies. U.S. Energy Information Administration / Market Assessment of Planned Refinery Outages /

142

1 On Downlink Transmission Without Transmit Channel State Information and With Outage Constraints  

E-Print Network (OSTI)

This paper investigates downlink transmission over a quasi-static fading Gaussian broadcast channel (BC), to model delay-sensitive applications over slowly time-varying fading channels. System performance is characterized by the outage capacity region. In contrast to most previous work, here the problem is studied under the key assumption that the transmitter knows only the probability distributions of the fading coefficients, not their realizations. For scalar-input channels, two coding schemes are studied. The first scheme is called blind dirty paper coding (B-DPC), which utilizes a robustness property of dirty paper coding to perform precoding at the transmitter. The second scheme is called statistical superposition coding (S-SC), in which each receiver adaptively performs successive decoding with the process statistically governed by the realized fading. Both B-DPC and S-SC schemes achieve the outage capacity region, which dominates the outage rate region of time-sharing, irrespective of the particular

Wenyi Zhang; Shiva Prasad Kotagiri; J. Nicholas Laneman; Senior Member

2009-01-01T23:59:59.000Z

143

Automatic Scheduling of Outages of Nuclear Power Plants with Time Windows  

E-Print Network (OSTI)

We report on a successful project for transference of advanced AI technology into the domain of planning of outages of nuclear power plants as part of DOD's dual-use program. ROMAN (Rome Lab Outage Manager) is the prototype system that was developed as a result of this project. ROMAN's main innovation compared to the current state of the art of outage management tools is its capability to automatically enforce safety constraints during the planning and scheduling phase. Another innovative aspect of ROMAN is the generation of more robust schedules that are feasible over time windows. In other words, ROMAN generates a family of schedules by assigning time intervals as start times to activities rather than single point start times, without afecting the overall duration of the project. ROMAN uses a constraint satisfaction paradigm combining a global search tactic with constraint propagation. The derivation of very specialized representations for the constraints to perform efficient propaga...

Carla P. Gomes

1996-01-01T23:59:59.000Z

144

Pepco Update on Current Construction Work and Mirant Generation Needs for Pepco's Planned June Line Outage  

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

May 25, 2007 May 25, 2007 Kevin Kolevar Director of the Office of Electricity Deliverability and Energy Reliability Department of Energy 1000 Independence Ave., SW Washington, DC 20585 Dear Mr. Kolevar, DOE has requested that Pepco provide an update on the current work to install two new 230 kilovolt circuits into Potomac River substation and to evaluate the need for generation from the Potomac River plant to support the anticipated line outage during June, 2007. An outage on one of the 230 kV circuits is currently underway and is currently scheduled to be completed by June 2, 2007. Mirant has supported this outage with generation required to match the Potomac River area load from the substation. This has required the operation of all 5 generating units located at

145

The detection, prevention and mitigation of cascading outages in the power system  

E-Print Network (OSTI)

This dissertation studies the causes and mechanism of power system cascading outages and develops new methods and new tools to help detect, prevent and mitigate the outages. Three effective solutions: a steady state control scheme, a transient stability control scheme, and an interactive system-wide and local scheme have been proposed using those new methods and tools. A steady state control scheme can help detect and prevent the possible cascading outage at its initial slow steady state progress stage. It uses new methods and new tools to solve the line overload, congestion or bus high/low voltage problems. New methods, such as vulnerability index (VI), margin index (MI), network contribution factor (NCF), topology processing and selected minimum load shedding (SMLS), and new tools, such as transmission network control based on a network contribution factor (NCF) method, generator control based on a generator distribution factor (GDF) method, and load control based on a load distribution factor (LDF) method have been proposed and developed. A transient stability control scheme can help prevent and mitigate the possible cascading outage at its transient progress stage if there is enough time to take action. It uses one Lyapunov direct method, potential energy boundary surface (PEBS) method, and sensitivity analysis of transient energy margin for fast stabilizing control. The results are verified by the accurate time-domain transient stability analysis method. The interactive scheme takes advantage of accurate system-wide and local information and analysis results, uses some techniques from both steady state control and transient stability control, works at both the system-wide level and local substation level, monitors the system all the time, and takes actions when needed to help detect, prevent and mitigate the possible cascading outage. Comprehensive simulation studies have been implemented using the IEEE 14- bus, 24-bus, 39-bus and 118-bus systems and promising results show the ability of the proposed solutions to help detect, prevent and mitigate cascading outages.

Song, Hongbiao

2006-12-01T23:59:59.000Z

146

Nuclear power plants undergo seasonal scheduled outages - Today in ...  

U.S. Energy Information Administration (EIA)

Uranium fuel, nuclear reactors, generation, spent fuel. Total Energy. ... Privacy/Security Copyright & Reuse Accessibility. Related Sites U.S. Department of Energy

147

Nuclear Safety Risk Management in Refueling Outage of Qinshan Nuclear Power Plant  

SciTech Connect

The NPP is used to planning maintenance, in-service inspection, surveillance test, fuel handling and design modification in the refueling outage; the operator response capability will be reduced plus some of the plant systems out of service or loss of power at this time. Based on 8 times refueling outage experiences of the Qinshan NPP, this article provide some good practice and lesson learned for the nuclear safety risk management focus at four safety function areas of Residual Heat Removal Capability, Inventory Control, Power availability and Reactivity control. (authors)

Meijing Wu; Guozhang Shen [Qinshan Nuclear power company (China)

2006-07-01T23:59:59.000Z

148

Outage Performance of OFDM-Based Selective Decode-and-Forward Cooperative Networks Over Nakagami-m Fading Channels  

Science Conference Proceedings (OSTI)

In this paper, we investigate the outage performance of OFDM-based selective decode-and-forward cooperative networks over independent but not necessarily identically distributed (i.n.i.d.) Nakagami-m fading channels, with integer values of parameter ... Keywords: Cooperative communication, Nakagami-m fading, OFDM, Outage probability

Wendong Yang; Weiwei Yang; Yueming Cai

2011-02-01T23:59:59.000Z

149

Outage Performance of Dual-Hop AF Relay Channels with Co-Channel Interferences over Rayleigh Fading  

Science Conference Proceedings (OSTI)

This paper studies the outage performance of a dual-hop amplify-and-forward (AF) relay fading channel in an interference-limited environment. The relay and destination nodes are corrupted by multiple co-channel Rayleigh interferences. New exact closed-form ... Keywords: Amplify and-forward relay, Co-channel interference, Nonregenerative relay, Outage probability, Rayleigh fading

Aleksandra M. Cvetkovi?; Dejan N. Mili?; Aleksandar S. Cvetkovi?; Mihajlo Stefanovi?

2013-06-01T23:59:59.000Z

150

Cross-layer interaction between spatial and multi-user diversity in selective feedback systems: outage capacity analysis  

Science Conference Proceedings (OSTI)

In this paper, we explore spatial vs. multi-user diversity tradeoffs in terms of outage capacity for a non-homogeneous cellular system with selective feedback. More precisely, we analytically derive an upper bound of the outage capacity of both a SISO ... Keywords: cross-layer designs, multi-antenna schemes, multi-user diversity, selective scheduling, spatial diversity, wireless systems

José López Vicario; Carles Antón-Haro

2006-07-01T23:59:59.000Z

151

96 IEEE power & energy magazine march/april 2005 THE MASSIVE POWER OUTAGE OF  

E-Print Network (OSTI)

collaboration among economists, scientists, and engineers to slowly but surely transform the power grid96 IEEE power & energy magazine march/april 2005 T THE MASSIVE POWER OUTAGE OF August 2003 underscored the vulnerabil- ity of our nation's power grid and the fact that this vital yet complex infrastruc

Amin, S. Massoud

152

Using Remaining Battery lifetime information and Relaying to decrease Outage Probability of a Mobile  

E-Print Network (OSTI)

Using Remaining Battery lifetime information and Relaying to decrease Outage Probability is to demonstrate that by employing relaying and using the remaining battery lifetime information of Mobile is determined based on the remaining battery lifetime of the MT. We assume a linear relationship between

Singh, Suresh

153

ORNL NASA DAAC Web Site Outage, Saturday May 15 from 3:00 a.m...  

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

Outage, Saturday, May 15, 2010 3:00 a.m.-5:00 p.m. EDT The ORNL DAAC Web site will be unavailable between 3:00 a.m. and 5:00 p.m., Eastern Daylight Time (EDT), on Saturday, May 15,...

154

Mitigating Cascading Outages on Power Systems: Recent Research Approaches and Emerging Methods  

Science Conference Proceedings (OSTI)

The August 14, 2003 and August 10, 1996 wide area outages are two examples of the cascading failure of a large portion of the North American power grid. Methods of better understanding, predicting, and preventing cascading failures, as well as restoring the power system after such failure, were the topics of a recent NSF/EPRI workshop.

2005-12-19T23:59:59.000Z

155

Unit-Contingent Power Purchase Agreement and Asymmetric Information About Plant Outage  

Science Conference Proceedings (OSTI)

This paper analyzes a unit-contingent power purchase agreement between an electricity distributor and a power plant. Under such a contract the distributor pays the plant a fixed price if the plant is operational and nothing if plant outage occurs. Pricing ... Keywords: electricity industry, risk allocation, spot market, unit-contingent contract

Owen Q. Wu; Volodymyr Babich

2012-04-01T23:59:59.000Z

156

An Efficient Energy Curtailment Scheme For Outage Management in Smart Grid  

E-Print Network (OSTI)

An Efficient Energy Curtailment Scheme For Outage Management in Smart Grid Wayes Tushar§, Jian--In this paper an efficient energy curtailment scheme is studied, which enables the power users of a smart grid. Considering the advantages of a two-way communications infrastructure for any future smart grid, a non

Durrani, Salman

157

Cognitive Multiple Access Network with Outage Margin in the Primary System  

E-Print Network (OSTI)

This paper investigates the problem of spectrally efficient operation of a multiuser uplink cognitive radio system in the presence of a single primary link. The secondary system applies opportunistic interference cancelation (OIC) and decode the primary signal when such an opportunity is created. We derive the achievable rate in the secondary system when OIC is used. This scheme has a practical significance, since it enables rate adaptation without requiring any action from the primary system. The \\emph{exact} expressions for outage probability of the primary user are derived, when the primary system is exposed to interference from secondary users. Moreover, approximated formulas and tight lower and upper bounds for the ergodic sum-rate capacity of the secondary network are found. Next, the power allocation is investigated in the secondary system for maximizing the sum-rate under an outage constraint at the primary system. We formulate the power optimization problem in various scenarios depending on the avail...

Maham, Behrouz; Zhou, Xiangyun; Hjørungnes, Are

2011-01-01T23:59:59.000Z

158

Peak Oil, Peak Energy Mother Nature Bats Last  

E-Print Network (OSTI)

Peak Oil, Peak Energy Mother Nature Bats Last Martin Sereno 1 Feb 2011 (orig. talk: Nov 2004) #12;Oil is the Lifeblood of Industrial Civilization · 80 million barrels/day, 1000 barrels/sec, 1 cubicPods to the roads themselves) · we're not "addicted to oil" -- that's like saying a person has an "addiction

Sereno, Martin

159

Peak Oil, Peak Energy Mother Nature Bats Last  

E-Print Network (OSTI)

/Predicted (2006) Discovery, Production FSU (former Soviet Union) history Soviet Union collapse 80's oil pricePeak Oil, Peak Energy Mother Nature Bats Last Martin Sereno 1 Feb 2011 (orig. talk: Nov 2004) #12;Oil is the Lifeblood of Industrial Civilization · 80 million barrels/day, 1000 barrels/sec, 1 cubic

Sereno, Martin

160

Texas Nuclear Profile - Comanche Peak  

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

Comanche Peak" "Unit","Summer capacity (mw)","Net generation (thousand mwh)","Summer capacity factor (percent)","Type","Commercial operation date","License expiration date"...

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


161

Peak oil: diverging discursive pipelines.  

E-Print Network (OSTI)

??Peak oil is the claimed moment in time when global oil production reaches its maximum rate and henceforth forever declines. It is highly controversial as… (more)

Doctor, Jeff

2012-01-01T23:59:59.000Z

162

1 Outage-Efficient Downlink Transmission Without Transmit Channel State Information  

E-Print Network (OSTI)

This paper investigates downlink transmission over a quasi-static fading Gaussian broadcast channel (BC), to model delay-sensitive applications over slowly time-varying fading channels. System performance is characterized by outage achievable rate regions. In contrast to most previous work, here the problem is studied under the key assumption that the transmitter only knows the probability distributions of the fading coefficients, but not their realizations. For scalar-input channels, two coding schemes are proposed. The first scheme is called blind dirty paper coding (B-DPC), which utilizes a robustness property of dirty paper coding to perform precoding at the transmitter. The second scheme is called statistical superposition coding (S-SC), in which each receiver adaptively performs successive decoding with the process statistically governed by the realized fading. Both B-DPC and S-SC schemes lead to the same outage achievable rate region, which always dominates that of time-sharing, irrespective of the particular fading distributions. The S-SC scheme can be extended to BCs with multiple transmit antennas. Index Terms Broadcast channel, (blind) dirty paper coding, downlink, non-ergodic fading, outage achievable rate region, quasi-static fading, (statistical) superposition coding

Wenyi Zhang; Shivaprasad Kotagiri; Student Member; J. Nicholas Laneman; Senior Member

2008-01-01T23:59:59.000Z

163

Peaks in Raindrop Size Distributions  

Science Conference Proceedings (OSTI)

The multipeak behavior of raindrop size distributions has been studied. Peaks have been found for distinct drop diameters: 0.7, 1.0, 1.9, and possibly 3.2 mm. The probability is about 65% that at least one of these peaks exists in an observed ...

M. Steiner; A. Waldvogel

1987-10-01T23:59:59.000Z

164

Black Peak and Enchantments - CECM  

E-Print Network (OSTI)

Black Peak, North Cascades. A nice two day outing. We hiked on the Maple Pass trail, from Hwy. 20, to Heather Pass, and then on a path to Lewis lake, where ...

165

Fast Detection and Mitigation of Cascading Outages in the Power System  

E-Print Network (OSTI)

This dissertation studies the causes and mechanism of power system cascading outages and proposes the improved interactive scheme between system-wide and local levels of monitoring and control to quickly detect, classify and mitigate the cascading outages in power system. A novel method for evaluating the vulnerability of individual components as well as the whole power system, which is named as weighted vulnerability analysis, is developed. Betweenness centrality is used to measure the importance of each bus and transmission line in the modeled power system network, which is in turn used to determine the weights for the weighted vulnerability index. It features fast reaction time and achieves higher accuracy when dealing with the cascading outage detection, classification and mitigation over the traditional methods. The overload problem due to power flow redistribution after one line tripped is a critical factor contributing to the cascading outages. A parallel corridor searching method is proposed to quickly identify the most vulnerable components after tripping a transmission line. The power system topology model can be simplified into state graph after searching the domains for each generator, the commons for each bus, and links between the commons. The parallel corridor will be determined by searching the links and commons in system topology graph for the given state of power system operation. During stressed operating state, either stable or unstable power swing may have impacts on distance relay judgment and lead to relay misoperation, which will result in the power system lines being tripped and as a consequence power system operating state becoming even more stressful. At the local level, an enhanced fault detection tool during power system swing is developed to reduce the chance of relay misoperation. Comprehensive simulation studies have been implemented by using the IEEE 39-bus and 118-bus test systems. The results are promising because: The results from weighted vulnerability analysis could provide better system situational awareness and accurate information about the disturbance; The results form parallel corridor search method could identify the most vulnerable lines after power re-distribution, which will give operator time to take remedial actions; The results from new travelling wave and wavelet transform based fault detection could reduce the impact of relay misoperation.

Pang, Chengzong

2011-12-01T23:59:59.000Z

166

Off peak ice storage generation  

DOE Green Energy (OSTI)

Due to the high costs associated with peak demand charges imposed by most electrical companies today, various means of shifting the peak HVAC load have been identified by the industry. This paper discusses the results of a study based upon a building site located in the high desert of the southwestern United States that evaluated ice storage as a mechanism of operating cost reductions. The discussion addresses both the seasonal and the annual cost and energy impacts of an ice storage system when used in place of an air-to-air heat pump system.

Davis, R.E.; Cerbo, F.J.

1985-01-01T23:59:59.000Z

167

Key Issues for the control of refueling outage duration and costs in PWR Nuclear Power Plants  

SciTech Connect

For several years, EDF, within the framework of the CIDEM1 project and in collaboration with some German Utilities, has undertaken a detailed review of the operating experience both of its own NPP and of foreign units, in order to improve the performances of future units under design, particularly the French-German European Pressurized Reactor (EPR) project. This review made it possible to identify the key issues allowing to decrease the duration of refueling and maintenance outages. These key issues can be classified in 3 categories Design, Maintenance and Logistic Support, Outage Management. Most of the key issues in the design field and some in the logistic support field have been studied and could be integrated into the design of any future PWR unit, as for the EPR project. Some of them could also be adapted to current plants, provided they are feasible and profitable. The organization must be tailored to each country, utility or period: it widely depends on the power production environment, particularly in a deregulation context. (author)

Degrave, Claude [Electricite de France, EDF-SEPTEN, 12-14 avenue Dutrievoz 69628 Villeurbanne Cedex (France)

2002-07-01T23:59:59.000Z

168

Analytical Tools to Predict Distribution Outage Restoration Load. Final Project Report.  

Science Conference Proceedings (OSTI)

The main activity of this project has been twofold: (1) development of a computer model to predict CLPU(Cold Load Pickup) and (2) development of a field measurement and analysis method to obtain the input parameters of the CLPU model. The field measurement and analysis method is called the Step-Voltage-Test (STEPV). The Kootenai Electric Cooperative Appleway 51 feeder in Coeur d`Alene was selected for analysis in this project and STEPV tests were performed in winters of 92 and 93. The STEPV data was analyzed (method and results presented within this report) to obtain the Appleway 51 feeder parameters for prediction by the CLPU model. One only CLPU record was obtained in winter 1994. Unfortunately, the actual CLPU was not dramatic (short outage and moderate temperature) and did not display cyclic restoration current. A predicted Appleway 51 feeder CLPU was generated using the parameters obtained via the STEPV measurement/analysis/algorithm method at the same ambient temperature and outage duration as the measured actual CLPU. The predicted CLPU corresponds reasonably well with the single actual CLPU data obtained in winter 1994 on the Appleway 51 feeder.

Law, John

1994-11-14T23:59:59.000Z

169

Peaks, Plans and (Persnickety) Prices  

Reports and Publications (EIA)

This presentation provides information about EIA's estimates of working gas peak storage capacity, and the development of the natural gas storage industry. Natural gas shale and the need for high deliverability storage are identified as key drivers in natural gas storage capacity development. The presentation also provides estimates of planned storage facilities through 2012.

Information Center

2010-10-28T23:59:59.000Z

170

Peak Population: Timing and Influences of Peak Energy on the World and the United States  

E-Print Network (OSTI)

Peak energy is the notion that the world’s total production of usable energy will reach a maximum value and then begin an inexorable decline. Ninety-two percent of the world’s energy is currently derived from the non-renewable sources (oil, coal, natural gas and nuclear). As each of these non-renewable sources individually peaks in production, we can see total energy production peak. The human population is tightly correlated with global energy production, as agriculture and material possessions are energy intensive. It follows that peak energy should have a significant effect on world population. Using a set of mathematical models, including M King Hubbert’s oil peak mathematics, we prepared three models. The first approached the peak energy and population problem from the point of view of a “black-box” homogeneous world. The second model divides the world into ten major regions to study the global heterogeneity of the peak energy and population question. Both of these models include various scenarios for how the world population will develop based on available energy and per capita consumption of that energy. The third model examines energy and climate change within the forty-eight contiguous American states in order to identify some of the “best” and some of the “worst” states in which to live in the year 2050. The black box model indicates that peak energy will occur in 2026 at a maximum production of 104.1 billion barrels of oil equivalent (BBOE). Total energy production in 2011 was 92.78 BBOE. Three scenarios of different energy consumption rates suggest a peak world population occurring between 2026 and 2036, at 7.6-8.3 billion. The regional model indicates that even as each region protects its own energy resources, most of the world will reach peak energy by 2030, and world populations peak between 7.5 and 9 billion. A certain robustness in our conclusion is warranted as similar numbers were obtained via two separate approaches. The third model used several different parameters in order to ascertain that, in general, states that are projected to slow towards flat-line population growth and to become milder due to climate change such as Rhode Island, New York and Ohio are far more suitable with regard to an energy limited world than states that are projected to grow in population as well as become less mild due to climate change such as Texas, Arizona and Nevada. Each of these models in its own way foreshadows necessary changes that the world will experience as the 21st century progresses. The economies of the world have been, and continue to be, built on energy. When energy production is unable to continue growing it must follow that economies will be unable to grow. As the world approaches and passes peak energy, the standard of living in the less developed areas of the world cannot improve without sacrifices being made in the developed world.

Warner, Kevin 1987-

2012-12-01T23:59:59.000Z

171

METHOD OF PEAK CURRENT MEASUREMENT  

DOE Patents (OSTI)

The measurement and recording of peak electrical currents are described, and a method for utilizing the magnetic field of the current to erase a portion of an alternating constant frequency and amplitude signal from a magnetic mediums such as a magnetic tapes is presented. A portion of the flux from the current carrying conductor is concentrated into a magnetic path of defined area on the tape. After the current has been recorded, the tape is played back. The amplitude of the signal from the portion of the tape immediately adjacent the defined flux area and the amplitude of the signal from the portion of the tape within the area are compared with the amplitude of the signal from an unerased portion of the tape to determine the percentage of signal erasure, and thereby obtain the peak value of currents flowing in the conductor.

Baker, G.E.

1959-01-20T23:59:59.000Z

172

Evaluation of concurrent peak responses  

SciTech Connect

This report deals with the problem of combining two or more concurrent responses which are induced by dynamic loads acting on nuclear power plant structures. Specifically, the acceptability of using the square root of the sum of the squares (SRSS) value of peak values as the combined response is investigated. Emphasis is placed on the establishment of a simplified criterion that is convenient and relatively easy to use by design engineers.

Wang, P.C.; Curreri, J.; Reich, M.

1983-01-01T23:59:59.000Z

173

Peak shaving through resource buffering  

E-Print Network (OSTI)

Abstract. We introduce and solve a new problem inspired by energy pricing schemes in which a client is billed for peak usage. At each timeslot the system meets an energy demand through a combination of a new request, an unreliable amount of free source energy (e.g. solar or wind power), and previously received energy. The added piece of infrastructure is the battery, which can store surplus energy for future use. More generally, the demands could represent required amounts of energy, water, or any other tenable resource which can be obtained in advance and held until needed. In a feasible solution, each demand must be supplied on time, through a combination of newly requested energy, energy withdrawn from the battery, and free source. The goal is to minimize the maximum request. In the online version of this problem, the algorithm must determine each request without knowledge of future demands or free source availability, with the goal of maximizing the amount by which the peak is reduced. We give efficient optimal algorithms for the offline problem, with and without a bounded battery. We also show how to find the optimal offline battery size, given the requirement that the final battery level equals the initial battery level. Finally, we give efficient Hn-competitive algorithms assuming the peak effective demand is revealed in advance, and provide matching lower bounds. 1

Amotz Bar-noy; Matthew P. Johnson; Ou Liu

2007-01-01T23:59:59.000Z

174

Definition: Variable Peak Pricing | Open Energy Information  

Open Energy Info (EERE)

Variable Peak Pricing Variable Peak Pricing Jump to: navigation, search Dictionary.png Variable Peak Pricing Variable Peak Pricing (VPP) is a hybrid of time-of-use and real-time pricing where the different periods for pricing are defined in advance (e.g., on-peak=6 hours for summer weekday afternoon; off-peak= all other hours in the summer months), but the price established for the on-peak period varies by utility and market conditions.[1] Related Terms real-time pricing References ↑ https://www.smartgrid.gov/category/technology/variable_peak_pricing [[C LikeLike UnlikeLike You like this.Sign Up to see what your friends like. ategory: Smart Grid Definitionssmart grid,off-peak,on-peak,smart grid, |Template:BASEPAGENAME]]smart grid,off-peak,on-peak,smart grid, Retrieved from "http://en.openei.org/w/index.php?title=Definition:Variable_Peak_Pricing&oldid=50262

175

Comments from the Virginia Department of Environmental Quality on PEPCO's Intention to Commence Planned Transmission Outages  

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

COMMONWEALTH of VIRGINIA COMMONWEALTH of VIRGINIA DEPARTMENT OF ENVIRONMENTAL QUALITY Street address: 629 East Main Street, Richmond, Virginia 23219 Mailing address: P.O. Box 10009, Richmond, Virginia 23240 Fax (804) 698-4500 TDD (804) 698-4021 www.deq.virginia.gov W. Tayloe Murphy, Jr. Secretary of Natural Resources Robert G. Burnley Director (804) 698-4000 1-800-592-5482 January 5, 2006 The Honorable Samuel W. Bodman Secretary of Energy United States Department of Energy 1000 Independence Avenue, S.W. Washington, D.C. 20585 Re: District of Columbia Public Service Commission Docket No. EO-05-01 Dear Secretary Bodman: The Virginia Department of Environmental Quality (DEQ) strongly opposes the Potomac Electric Power Company's (PEPCO) intention to commence planned maintenance outages of the

176

Market Assessment of Refinery Outages Planned for October 2009 through January 2010  

Gasoline and Diesel Fuel Update (EIA)

09)/2 09)/2 Market Assessment of Refinery Outages Planned for October 2009 through January 2010 November 2009 Energy Information Administration Office of Oil and Gas U.S. Department of Energy Washington, DC 20585 This report was prepared by the U.S. Energy Information Administration (EIA), the independent statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views herein should not be construed as representing those of the Department or the Administration. Preface and Contacts The Energy Information Administration (EIA) is the independent statistical and analytical

177

ORNL Network Outage, Friday, April 15, 9:30 p.m. to Date  

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

Updated 4/25/2011 Updated 4/25/2011 All externally accessible ORNL servers, including the ORNL DAAC Web Site, http://daac.ornl.gov are experiencing network outages or slow connectivity at this time. We apologize for this inconvenience and appreciate your patience during our down time. At this time you can explore our Web site and access data products including MODIS Land Products Subsets, albeit slowly. However, the following Web sites and tools have been taken off the Internet and are not available: Mercury (DAAC Simple Search and Advanced Product Search) WebGIS Spatial Data Access Tool (SDAT) Thematic Real-time Environmental Distributed Data Services (THREDDS) Data Server (TDS) MAST-DC FLUXNET Beija-flor (at ORNL) You may experience problems signing-in or registering with our Web site.

178

Market Assessment of Refinery Outages Planned for October 2010 through January 2011  

Gasoline and Diesel Fuel Update (EIA)

10)/2 10)/2 Market Assessment of Refinery Outages Planned for October 2010 through January 2011 November 2010 Energy Information Administration Office of Petroleum, Gas, and Biofuels Analysis U.S. Department of Energy Washington, DC 20585 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other Federal agencies. E nergy Information Adminis tration Market As s es s ment of P lanned R

179

A Review of Power Outages and Restoration Following the June 2012 Derecho  

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

August 2012 August 2012 A Review of Power Outages and Restoration Following the June 2012 Derecho Infrastructure Security and Energy Restoration Office of Electricity Delivery and Energy Reliability U.S. Department of Energy For Further Information This report was prepared by the Office of Electricity Delivery and Energy Reliability under the direction of Patricia Hoffman, Assistant Secretary, and William Bryan, Deputy Assistant Secretary. Specific questions about this report may be directed to Alice Lippert, Senior Technical Advisor (alice.lippert@hq.doe.gov). (Cover image from the National Weather Service) OE/ISER 8/6/2012 1 Background On June 29, 2012, a major storm system known as a derecho ("deh-REY-cho") formed and

180

Reducing Duration of Refueling Outage by Optimizing Core Design and Shuffling Sequence  

SciTech Connect

Reducing the duration of refueling outage is possible by optimizing the core design and the shuffling sequence. For both options software tools have been developed that have been applied to the three most recent cycles of the Borssele plant in the Netherlands. Applicability of the shuffling sequence optimization to boiling water reactors has been demonstrated by a comparison to a recent shuffle plan used in the Hatch plant located in the United States. Their uses have shown that both core design and shuffling sequence optimization can be exploited to reduce the time needed for reloading a core with an in-core shuffling scheme. Ex-core shuffling schemes for pressurized water reactors can still have substantial benefit from a core design using a minimized number of insert shuffles.

Wakker, P.H.; Verhagen, F.C.M.; Bloois, J.T. van; Sutton, W.R. III

2005-07-15T23:59:59.000Z

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


181

Outage probability and channel capacity for the Nth best relay selection AF relaying over INID Rayleigh fading channels  

Science Conference Proceedings (OSTI)

Cooperative diversity systems have recently been proposed as a way to form virtual antenna schemes without utilizing collocated multiple antennas. In this paper, we consider the Nth best opportunistic amplify-and-forward (AF) cooperative diversity ... Keywords: Nth best OAF, INID Rayleigh fading channels, channel capacity, cooperative diversity, outage probability

K. Ko; C. Woo

2012-11-01T23:59:59.000Z

182

Understanding the Benefits of Dispersed Grid-Connected Photovoltaics: From Avoiding the Next Major Outage to Taming Wholesale Power Markets  

SciTech Connect

Thanks to new solar resource assessment techniques using cloud cover data available from geostationary satellites, it is apparent that grid-connected PV installations can serve to enhance electric grid reliability, preventing or hastening recovery from major power outages and serving to mitigate extreme price spikes in wholesale energy markets. (author)

Letendre, Steven E.; Perez, Richard

2006-07-15T23:59:59.000Z

183

SnowPeak Energy | Open Energy Information  

Open Energy Info (EERE)

it. SnowPeak Energy is a company located in Reno, Nevada . References "SnowPeak Energy" Retrieved from "http:en.openei.orgwindex.php?titleSnowPeakEnergy&oldid35121...

184

Peak Electricity Impacts of Residential Water Use  

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

Peak Electricity Impacts of Residential Water Use Title Peak Electricity Impacts of Residential Water Use Publication Type Report LBNL Report Number LBNL-5736E Year of Publication...

185

national total  

U.S. Energy Information Administration (EIA)

AC Argentina AR Aruba AA Bahamas, The BF Barbados BB Belize BH Bolivia BL Brazil BR Cayman Islands CJ ... World Total ww NA--Table Posted: December 8, ...

186

A Fresh Look at Weather Impact on Peak Electricity Demand and...  

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

Building simulation, Energy use, Peak electricity demand, Typical meteorological year, Weather data Abstract Buildings consume more than one third of the world's total primary...

187

Natural gas consumption has two peaks each year - Today in Energy ...  

U.S. Energy Information Administration (EIA)

Consumption of natural gas is seasonal, with consumption patterns among end-use sectors highly driven by weather. Total natural gas consumption peaks during the ...

188

Peak load management: Potential options  

SciTech Connect

This report reviews options that may be alternatives to transmission construction (ATT) applicable both generally and at specific locations in the service area of the Bonneville Power Administration (BPA). Some of these options have potential as specific alternatives to the Shelton-Fairmount 230-kV Reinforcement Project, which is the focus of this study. A listing of 31 peak load management (PLM) options is included. Estimated costs and normalized hourly load shapes, corresponding to the respective base load and controlled load cases, are considered for 15 of the above options. A summary page is presented for each of these options, grouped with respect to its applicability in the residential, commercial, industrial, and agricultural sectors. The report contains comments on PLM measures for which load shape management characteristics are not yet available. These comments address the potential relevance of the options and the possible difficulty that may be encountered in characterizing their value should be of interest in this investigation. The report also identifies options that could improve the efficiency of the three customer utility distribution systems supplied by the Shelton-Fairmount Reinforcement Project. Potential cogeneration options in the Olympic Peninsula are also discussed. These discussions focus on the options that appear to be most promising on the Olympic Peninsula. Finally, a short list of options is recommended for investigation in the next phase of this study. 9 refs., 24 tabs.

Englin, J.E.; De Steese, J.G.; Schultz, R.W.; Kellogg, M.A.

1989-10-01T23:59:59.000Z

189

Total Imports  

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

Data Series: Imports - Total Imports - Crude Oil Imports - Crude Oil, Commercial Imports - by SPR Imports - into SPR by Others Imports - Total Products Imports - Total Motor Gasoline Imports - Finished Motor Gasoline Imports - Reformulated Gasoline Imports - Reformulated Gasoline Blended w/ Fuel Ethanol Imports - Other Reformulated Gasoline Imports - Conventional Gasoline Imports - Conv. Gasoline Blended w/ Fuel Ethanol Imports - Conv. Gasoline Blended w/ Fuel Ethanol, Ed55 & Ed55 Imports - Other Conventional Gasoline Imports - Motor Gasoline Blend. Components Imports - Motor Gasoline Blend. Components, RBOB Imports - Motor Gasoline Blend. Components, RBOB w/ Ether Imports - Motor Gasoline Blend. Components, RBOB w/ Alcohol Imports - Motor Gasoline Blend. Components, CBOB Imports - Motor Gasoline Blend. Components, GTAB Imports - Motor Gasoline Blend. Components, Other Imports - Fuel Ethanol Imports - Kerosene-Type Jet Fuel Imports - Distillate Fuel Oil Imports - Distillate F.O., 15 ppm Sulfur and Under Imports - Distillate F.O., > 15 ppm to 500 ppm Sulfur Imports - Distillate F.O., > 500 ppm to 2000 ppm Sulfur Imports - Distillate F.O., > 2000 ppm Sulfur Imports - Residual Fuel Oil Imports - Propane/Propylene Imports - Other Other Oils Imports - Kerosene Imports - NGPLs/LRGs (Excluding Propane/Propylene) Exports - Total Crude Oil and Products Exports - Crude Oil Exports - Products Exports - Finished Motor Gasoline Exports - Kerosene-Type Jet Fuel Exports - Distillate Fuel Oil Exports - Residual Fuel Oil Exports - Propane/Propylene Exports - Other Oils Net Imports - Total Crude Oil and Products Net Imports - Crude Oil Net Imports - Petroleum Products Period: Weekly 4-Week Avg.

190

Plant Outage Time Savings Provided by Subcritical Physics Testing at Vogtle Unit 2  

SciTech Connect

The most recent core reload design verification physics testing done at Southern Nuclear Company's (SNC) Vogtle Unit 2, performed prior to initial power operations in operating cycle 12, was successfully completed while the reactor was at least 1% {delta}K/K subcritical. The testing program used was the first application of the Subcritical Physics Testing (SPT) program developed by the Westinghouse Electric Company LLC. The SPT program centers on the application of the Westinghouse Subcritical Rod Worth Measurement (SRWM) methodology that was developed in cooperation with the Vogtle Reactor Engineering staff. The SRWM methodology received U. S. Nuclear Regulatory Commission (NRC) approval in August of 2005. The first application of the SPT program occurred at Vogtle Unit 2 in October of 2005. The results of the core design verification measurements obtained during the SPT program demonstrated excellent agreement with prediction, demonstrating that the predicted core characteristics were in excellent agreement with the actual operating characteristics of the core. This paper presents an overview of the SPT Program used at Vogtle Unit 2 during operating cycle 12, and a discussion of the critical path outage time savings the SPT program is capable of providing. (authors)

Cupp, Philip [Southern Nuclear Company (United States); Heibel, M.D. [Westinghouse Electric Company, LLC (United States)

2006-07-01T23:59:59.000Z

191

Effective Personnel Exposure Control in Shortened Refueling Outages: Final Report: Review of Remote Monitoring Systems in Radiation Protection Applications  

Science Conference Proceedings (OSTI)

Remote monitoring technology (RMT) significantly enhances worker protection and reduces worker radiation exposure, particularly during shortened refueling outages. This report provides a brief description of the hardware and features of remote monitoring systems, then focuses on nuclear plant experiences in applying such systems for enhanced radiation protection. It also discusses EPRI's RMT research program and formation of the RMT Working Group to support research in this area. Such information will gr...

2003-12-02T23:59:59.000Z

192

Experience Based Interview Process for Power Plant Management: With a Pilot Application to Aging of Outage Support Equipment  

Science Conference Proceedings (OSTI)

Plant managers are responsible for ensuring that their facilities meet strategic asset management goals in an increasingly competitive power generation marketplace. This report describes an experience based interview (EBI) method for capturing the knowledge of plant staff to more efficiently identify technical or operational issues and make management decisions that protect assets. Included is a demonstration of the method in a pilot application to aging of support equipment that could impact outages in ...

1999-04-05T23:59:59.000Z

193

Peak Oil Food Network | Open Energy Information  

Open Energy Info (EERE)

Network Network Jump to: navigation, search Name Peak Oil Food Network Place Crested Butte, Colorado Zip 81224 Website http://www.PeakOilFoodNetwork. References Peak Oil Food Network[1] LinkedIn Connections This article is a stub. You can help OpenEI by expanding it. The Peak Oil Food Network is a networking organization located in Crested Butte, Colorado, and is open to the general public that seeks to promote the creation of solutions to the challenge of food production impacted by the peak phase of global oil production. Private citizens are encouraged to join and contribute by adding comments, writing blog posts or adding to discussions about food and oil related topics. Peak Oil Food Network can be followed on Twitter at: http://www.Twitter.com/PeakOilFoodNtwk Peak Oil Food Network on Twitter

194

STAFF FORECAST OF 2007 PEAK STAFFREPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION STAFF FORECAST OF 2007 PEAK DEMAND STAFFREPORT June 2006 CEC-400.................................................................................. 9 Sources of Forecast Error....................................................................... .................11 Tables Table 1: Revised versus September 2005 Peak Demand Forecast ......................... 2

195

Peak Underground Working Natural Gas Storage Capacity  

U.S. Energy Information Administration (EIA)

Peak Working Natural Gas Capacity. Data and Analysis from the Energy Information Administration (U.S. Dept. of Energy)

196

Determination of Hydrogen Peak Temperatures and Trapping ...  

Science Conference Proceedings (OSTI)

Presentation Title, Determination of Hydrogen Peak Temperatures and Trapping Energies of Various Lattice Defects In Iron Using Thermal Desorption ...

197

Definition: On-Peak | Open Energy Information  

Open Energy Info (EERE)

Definition Definition Edit with form History Facebook icon Twitter icon » Definition: On-Peak Jump to: navigation, search Dictionary.png On-Peak Those hours or other periods defined by NAESB business practices, contract, agreements, or guides as periods of higher electrical demand.[1] View on Wikipedia Wikipedia Definition Peak demand is used to refer to a historically high point in the sales record of a particular product. In terms of energy use, peak demand describes a period of strong consumer demand. Also Known As peak load Related Terms demand, peak demand References ↑ Glossary of Terms Used in Reliability Standards Temp Like Like You like this.Sign Up to see what your friends like. late:ISGANAttributionsmart grid,smart grid, Retrieved from "http://en.openei.org/w/index.php?title=Definition:On-Peak&oldid=502536"

198

Mt Peak Utility | Open Energy Information  

Open Energy Info (EERE)

Peak Utility Peak Utility Jump to: navigation, search Name Mt Peak Utility Facility Mt Peak Utility Sector Wind energy Facility Type Small Scale Wind Facility Status In Service Owner Mnt Peak Utility Energy Purchaser Mnt Peak Utility Location Midlothian TX Coordinates 32.42144978°, -97.02427357° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":32.42144978,"lon":-97.02427357,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

199

Flexible Coal: Evolution from Baseload to Peaking Plant (Brochure)  

Science Conference Proceedings (OSTI)

Twenty-first century power systems, with higher penetration levels of low-carbon energy, smart grids, and other emerging technologies, will favor resources that have low marginal costs and provide system flexibility (e.g., the ability to cycle on and off to follow changes in variable renewable energy plant output). Questions remain about both the fate of coal plants in this scenario and whether they can cost-effectively continue to operate if they cycle routinely. The experience from the CGS plant demonstrates that coal plants can become flexible resources. This flexibility - namely the ability to cycle on and off and run at lower output (below 40% of capacity) - requires limited hardware modifications but extensive modifications to operational practice. Cycling does damage the plant and impact its life expectancy compared to baseload operations. Nevertheless, strategic modifications, proactive inspections and training programs, among other operational changes to accommodate cycling, can minimize the extent of damage and optimize the cost of maintenance. CGS's cycling, but not necessarily the associated price tag, is replicable. Context - namely, power market opportunities and composition of the generation fleet - will help determine for other coal plants the optimal balance between the level of cycling-related forced outages and the level of capital investment required to minimize those outages. Replicating CGS's experience elsewhere will likely require a higher acceptance of forced outages than regulators and plant operators are accustomed to; however, an increase in strategic maintenance can minimize the impact on outage rates.

Cochran, J.; Lew, D.; Kumar, N.

2013-12-01T23:59:59.000Z

200

Optimization of Demand Response Through Peak Shaving  

E-Print Network (OSTI)

Jul 5, 2013 ... Optimization of Demand Response Through Peak Shaving. G. Zakeri(g.zakeri *** at*** auckland.ac.nz) D. Craigie(David.Craigie ***at*** ...

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


201

An Innovative Approach Towards National Peak Load Management  

E-Print Network (OSTI)

An innovative approach was developed and implemented in eight governmental buildings to reduce their load during the peak demand hours in summer of 2007. The innovative approach implemented in these buildings included pre-closing treatment (PCT) between 13:00 and 14:00 h and time-of-day control (TDC) after 14:00 h for air conditioning (A/C) and lighting systems. PCT realized an overall reduction of 3.43 MW, a saving of 11.7% of the buildings peak power demand; while TDC realized a total savings of 8.67 MW at 15:00 h, a saving of 30.7% of the buildings peak power demand at that hour. The temperature build up inside the buildings due to PCT and TDC was within the acceptable range, which validated the technical viability of these measures. The implementation of the innovative approach in the eight governmental buildings with a total measured peak demand of 29.3 MW achieved a reduction of 8.89 MW. This power is now available to other users leading to financial savings of $13.5 million for the nation towards the cost of constructing new power plants and distribution network equipment. More importantly, this reduction in peak power demand of well over 30% involved zero or limited expenditure. A nationwide implementation of this innovative approach in all the governmental and institutional buildings is likely to reduce the national peak power demand by 154 MW which amounts to a capital savings of $232 million towards the cost of new power generation equipment and distribution network.

Al-Mulla, A.; Maheshwari, G. P.; Al-Nakib, D.; ElSherbini, A.; Alghimlas, F.; Al-Taqi, H.; Al-Hadban, Y.

2008-10-01T23:59:59.000Z

202

A distributed approach to taming peak demand  

Science Conference Proceedings (OSTI)

A significant portion of all energy capacity is wasted in over-provisioning to meet peak demand. The current state-of-the-art in reducing peak demand requires central authorities to limit device usage directly, and are generally reactive. We apply techniques ...

Michael Sabolish; Ahmed Amer; Thomas M. Kroeger

2012-06-01T23:59:59.000Z

203

FINAL STAFF FORECAST OF 2008 PEAK DEMAND  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION FINAL STAFF FORECAST OF 2008 PEAK DEMAND STAFFREPORT June 2007 CEC-200 of the information in this paper. #12;Abstract This document describes staff's final forecast of 2008 peak demand demand forecasts for the respective territories of the state's three investor-owned utilities (IOUs

204

Non-OPEC oil supply outages remain above year-ago level - Today in ...  

U.S. Energy Information Administration (EIA)

Includes hydropower, solar, wind, geothermal, biomass and ethanol. Nuclear & Uranium. Uranium fuel, nuclear reactors, generation, spent fuel. Total Energy.

205

Storm Peak Lab Cloud Property Validation  

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

Storm Peak Lab Cloud Storm Peak Lab Cloud Property Validation Experiment (STORMVEX) Operated by the Atmospheric Radiation Measurement (ARM) Climate Research Facility for the U.S. Department of Energy, the second ARM Mobile Facility (AMF2) begins its inaugural deployment November 2010 in Steamboat Springs, Colorado, for the Storm Peak Lab Cloud Property Validation Experiment, or STORMVEX. For six months, the comprehensive suite of AMF2 instruments will obtain measurements of cloud and aerosol properties at various sites below the heavily instrumented Storm Peak Lab, located on Mount Werner at an elevation of 3220 meters. The correlative data sets that will be created from AMF2 and Storm Peak Lab will equate to between 200 and 300 in situ aircraft flight hours in liquid, mixed phase, and precipitating

206

Definition: Peak Demand | Open Energy Information  

Open Energy Info (EERE)

Peak Demand Peak Demand Jump to: navigation, search Dictionary.png Peak Demand The highest hourly integrated Net Energy For Load within a Balancing Authority Area occurring within a given period (e.g., day, month, season, or year)., The highest instantaneous demand within the Balancing Authority Area.[1] View on Wikipedia Wikipedia Definition Peak demand is used to refer to a historically high point in the sales record of a particular product. In terms of energy use, peak demand describes a period of strong consumer demand. Related Terms Balancing Authority Area, energy, demand, balancing authority, smart grid References ↑ Glossary of Terms Used in Reliability Standards An inli LikeLike UnlikeLike You like this.Sign Up to see what your friends like. ne Glossary Definition Retrieved from

207

The Boson peak in supercooled water  

E-Print Network (OSTI)

We perform extensive molecular dynamics simulations of the TIP4P/2005 model of water to investigate the origin of the Boson peak reported in experiments on supercooled water in nanoconfined pores, and in hydration water around proteins. We find that the onset of the Boson peak in supercooled bulk water coincides with the crossover to a predominantly low-density-like liquid below the Widom line $T_W$. The frequency and onset temperature of the Boson peak in our simulations of bulk water agree well with the results from experiments on nanoconfined water. Our results suggest that the Boson peak in water is not an exclusive effect of confinement. We further find that, similar to other glass-forming liquids, the vibrational modes corresponding to the Boson peak are spatially extended and are related to transverse phonons found in the parent crystal, here ice Ih.

Pradeep Kumar; K. Thor Wikfeldt; Daniel Schlesinger; Lars G. M. Pettersson; H. E. Stanley

2013-05-19T23:59:59.000Z

208

Above-normal outages of U.S. nuclear capacity persist at the start ...  

U.S. Energy Information Administration (EIA)

Uranium fuel, nuclear reactors, generation, spent fuel. Total Energy. ... Privacy/Security Copyright & Reuse Accessibility. Related Sites U.S. Department of Energy

209

U.S. nuclear outages back within five-year range - Today in Energy ...  

U.S. Energy Information Administration (EIA)

Uranium fuel, nuclear reactors, generation, spent fuel. Total Energy. ... Privacy/Security Copyright & Reuse Accessibility. Related Sites U.S. Department of Energy

210

Automated Demand Response for Critical Peak Pricing  

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

Automated Demand Response for Critical Peak Pricing Speaker(s): Naoya Motegi Date: June 9, 2005 - 12:00pm Location: Bldg. 90 California utilities have been exploring the use of...

211

Peak Underground Working Natural Gas Storage Capacity  

Gasoline and Diesel Fuel Update (EIA)

Note: 1) 'Demonstrated Peak Working Gas Capacity' is the sum of the highest storage inventory level of working gas observed in each facility over the prior 5-year period as...

212

Peak Load Shifting by Thermal Energy Storage  

Science Conference Proceedings (OSTI)

This technical update from the Electric Power Research Institute (EPRI) reviews the technology of storing energy in hot water and explores the potential for implementing this form of thermal energy storagethrough means of smart electric water heatersas a way to shift peak load on the electric grid. The report presents conceptual background, discusses strategies for peak load shifting and demand response, documents a series of laboratory tests conducted on a representative model of smart water heater, and...

2011-12-14T23:59:59.000Z

213

Measured Peak Equipment Loads in Laboratories  

SciTech Connect

This technical bulletin documents measured peak equipment load data from 39 laboratory spaces in nine buildings across five institutions. The purpose of these measurements was to obtain data on the actual peak loads in laboratories, which can be used to rightsize the design of HVAC systems in new laboratories. While any given laboratory may have unique loads and other design considerations, these results may be used as a 'sanity check' for design assumptions.

Mathew, Paul A.

2007-09-12T23:59:59.000Z

214

Microgrid Dispatch for Macrogrid Peak-Demand Mitigation  

E-Print Network (OSTI)

Dispatch for Macrogrid Peak- Demand Mitigation NicholasDispatch for Macrogrid Peak-Demand Mitigation Nicholasdetermine whether the peak demand on the substation feeder

DeForest, Nicholas

2013-01-01T23:59:59.000Z

215

Peak Underground Working Natural Gas Storage Capacity  

Gasoline and Diesel Fuel Update (EIA)

Methodology Methodology Methodology Demonstrated Peak Working Gas Capacity Estimates: Estimates are based on aggregation of the noncoincident peak levels of working gas inventories at individual storage fields as reported monthly over a 60-month period ending in April 2010 on Form EIA-191M, "Monthly Natural Gas Underground Storage Report." The months of measurement for the peak storage volumes by facilities may differ; i.e., the months do not necessarily coincide. As such, the noncoincident peak for any region is at least as big as any monthly volume in the historical record. Data from Form EIA-191M, "Monthly Natural Gas Underground Storage Report," are collected from storage operators on a field-level basis. Operators can report field-level data either on a per reservoir basis or on an aggregated reservoir basis. It is possible that if all operators reported on a per reservoir basis that the demonstrated peak working gas capacity would be larger. Additionally, these data reflect inventory levels as of the last day of the report month, and a facility may have reached a higher inventory on a different day of the report month, which would not be recorded on Form EIA-191M.

216

Short-Term Energy Outlook Supplement: 2013 Outlook for Gulf of Mexico Hurricane-Related Production Outages  

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

2013 Outlook for Gulf of Mexico 2013 Outlook for Gulf of Mexico Hurricane-Related Production Outages June 2013 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | STEO Supplement: 2013 Hurricane Outlook i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other federal agencies. June 2013 U.S. Energy Information Administration | STEO Supplement: 2013 Hurricane Outlook 1

217

Pilot Peak Geothermal Project | Open Energy Information  

Open Energy Info (EERE)

Pilot Peak Geothermal Project Pilot Peak Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Pilot Peak Geothermal Project Project Location Information Coordinates 38.342266666667°, -118.10361111111° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":38.342266666667,"lon":-118.10361111111,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

218

Peak Underground Working Natural Gas Storage Capacity  

Gasoline and Diesel Fuel Update (EIA)

Definitions Definitions Definitions Since 2006, EIA has reported two measures of aggregate capacity, one based on demonstrated peak working gas storage, the other on working gas design capacity. Demonstrated Peak Working Gas Capacity: This measure sums the highest storage inventory level of working gas observed in each facility over the 5-year range from May 2005 to April 2010, as reported by the operator on the Form EIA-191M, "Monthly Underground Gas Storage Report." This data-driven estimate reflects actual operator experience. However, the timing for peaks for different fields need not coincide. Also, actual available maximum capacity for any storage facility may exceed its reported maximum storage level over the last 5 years, and is virtually certain to do so in the case of newly commissioned or expanded facilities. Therefore, this measure provides a conservative indicator of capacity that may understate the amount that can actually be stored.

219

Silver Peak Geothermal Project | Open Energy Information  

Open Energy Info (EERE)

Silver Peak Geothermal Project Silver Peak Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Silver Peak Geothermal Project Project Location Information Coordinates 37.755°, -117.63472222222° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.755,"lon":-117.63472222222,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

220

Silver Peak Geothermal Area | Open Energy Information  

Open Energy Info (EERE)

Silver Peak Geothermal Area Silver Peak Geothermal Area Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Geothermal Resource Area: Silver Peak Geothermal Area Contents 1 Area Overview 2 History and Infrastructure 3 Regulatory and Environmental Issues 4 Exploration History 5 Well Field Description 6 Geology of the Area 7 Geofluid Geochemistry 8 NEPA-Related Analyses (5) 9 Exploration Activities (26) 10 References Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"TERRAIN","zoom":6,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"500px","height":"300px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.746167220142,"lon":-117.60267734528,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

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


221

Desert Peak Geothermal Area | Open Energy Information  

Open Energy Info (EERE)

Desert Peak Geothermal Area Desert Peak Geothermal Area Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Geothermal Resource Area: Desert Peak Geothermal Area Contents 1 Area Overview 2 History and Infrastructure 3 Regulatory and Environmental Issues 4 Exploration History 5 Well Field Description 6 Geology of the Area 7 Geofluid Geochemistry 8 NEPA-Related Analyses (3) 9 Exploration Activities (8) 10 References Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"TERRAIN","zoom":6,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"500px","height":"300px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":39.75,"lon":-118.95,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

222

2304 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 55, NO. 5, MAY 2009 Service-Outage-Based Power and Rate Control for  

E-Print Network (OSTI)

and the receiver and use the channel state information (CSI) to dynamically adapt transmit power and rate according function. The service-outage-based power and rate allocation problem is stated below. In the following, we.g., wireless RF communication, dynamic allocation of resources, e.g., transmit power and in- formation rate

Franceschetti, Massimo

223

Multiple Attractor in Newton -Leipnik System, Peak to Peak dynamics and Chaos Control  

E-Print Network (OSTI)

The chaotic properties of Newton-Leipnik system are discussed from the view point of strange attractors. Previously, two strange attractors of this system were illustrated which occured from two different initial conditions under the same parameter condition. It is found that above system also exhibits multiple attractors under different parameter values but same initial condition and we have shown the existence of three other strange attractors with varying dimensionality under different parametric conditions. The properties of these attractors are then analyzed on the basis of Lyapunov exponents, power spectra, recurrence analysis and peak-to-peak dynamics. The peak-to-peak dynamics relies on the low dimensionality of the chaotic attractor and allows to approximately model the system. Peak-to-peak plot along with return-time plot are then effectively used to solve the optimal control problem of the system which reverts the system to a periodic situation.

Biswambhar Rakshit; Papri Saha; A. Roy Chowdhury

2005-01-07T23:59:59.000Z

224

Vad är Peak Oil och existerar det?; What is Peak Oil and does it exist?.  

E-Print Network (OSTI)

?? The purpose of this study is the reports of Peak Oil in Swedish newspapers. In otherwords, how do the news portray or describe the… (more)

Wälimaa, Peter

2013-01-01T23:59:59.000Z

225

Desert Peak Geothermal Area | Open Energy Information  

Open Energy Info (EERE)

Desert Peak Geothermal Area Desert Peak Geothermal Area (Redirected from Desert Peak Area) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Geothermal Resource Area: Desert Peak Geothermal Area Contents 1 Area Overview 2 History and Infrastructure 3 Regulatory and Environmental Issues 4 Exploration History 5 Well Field Description 6 Geology of the Area 7 Geofluid Geochemistry 8 NEPA-Related Analyses (3) 9 Exploration Activities (8) 10 References Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"TERRAIN","zoom":6,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"500px","height":"300px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":39.75,"lon":-118.95,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

226

GeoPeak Energy | Open Energy Information  

Open Energy Info (EERE)

GeoPeak Energy GeoPeak Energy Jump to: navigation, search Logo: GeoPeak Energy Name GeoPeak Energy Address 285 Davidson Avenue Place Somerset, New Jersey Zip 08873 Sector Solar Product Residential and Commercial PV Solar Installations Number of employees 11-50 Company Type For Profit Phone number 732-377-3700 Website http://www.geopeakenergy.com Coordinates 40.5326723°, -74.5284554° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":40.5326723,"lon":-74.5284554,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

227

Silver Peak Geothermal Area | Open Energy Information  

Open Energy Info (EERE)

Silver Peak Geothermal Area Silver Peak Geothermal Area (Redirected from Silver Peak Area) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Geothermal Resource Area: Silver Peak Geothermal Area Contents 1 Area Overview 2 History and Infrastructure 3 Regulatory and Environmental Issues 4 Exploration History 5 Well Field Description 6 Geology of the Area 7 Geofluid Geochemistry 8 NEPA-Related Analyses (5) 9 Exploration Activities (26) 10 References Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"TERRAIN","zoom":6,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"500px","height":"300px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.746167220142,"lon":-117.60267734528,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

228

Wave Modeling—Missing the Peaks  

Science Conference Proceedings (OSTI)

The paper analyzes the capability of the present wave models of properly reproducing the conditions during and at the peak of severe and extreme storms. After providing evidence that this is often not the case, the reasons for it are explored. ...

Luigi Cavaleri

2009-11-01T23:59:59.000Z

229

The Inevitable Peaking of World Oil Production  

E-Print Network (OSTI)

The era of plentiful, low-cost petroleum is approaching an end. ? Without massive mitigation the problem will be pervasive and long lasting. Oil peaking represents a liquid fuels problem, not an “energy crisis”. ? Governments will have to take the initiative on a timely basis. ? In every crisis, there are always opportunities for those that act decisively.

Robert L. Hirsch

2005-01-01T23:59:59.000Z

230

Definition: Critical Peak Rebates | Open Energy Information  

Open Energy Info (EERE)

Rebates Rebates Jump to: navigation, search Dictionary.png Critical Peak Rebates When utilities observe or anticipate high wholesale market prices or power system emergency conditions, they may call critical events during pre-specified time periods (e.g., 3 p.m.-6 p.m. summer weekday afternoons), the price for electricity during these time periods remains the same but the customer is refunded at a single, predetermined value for any reduction in consumption relative to what the utility deemed the customer was expected to consume.[1] Related Terms electricity generation References ↑ https://www.smartgrid.gov/category/technology/critical_peak_rebates [[C LikeLike UnlikeLike You like this.Sign Up to see what your friends like. ategory: Smart Grid Definitions|Template:BASEPAGENAME]]

231

Peak Oil Awareness Network | Open Energy Information  

Open Energy Info (EERE)

Awareness Network Awareness Network Jump to: navigation, search Name Peak Oil Awareness Network Place Crested Butte, Colorado Zip 81224 Website http://www.PeakOilAwarenessNet Coordinates 38.8697146°, -106.9878231° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":38.8697146,"lon":-106.9878231,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

232

Definition: Critical Peak Pricing | Open Energy Information  

Open Energy Info (EERE)

Pricing Pricing Jump to: navigation, search Dictionary.png Critical Peak Pricing When utilities observe or anticipate high wholesale market prices or power system emergency conditions, they may call critical events during a specified time period (e.g., 3 p.m.-6 p.m. on a hot summer weekday), the price for electricity during these time periods is substantially raised. Two variants of this type of rate design exist: one where the time and duration of the price increase are predetermined when events are called and another where the time and duration of the price increase may vary based on the electric grid's need to have loads reduced;[1] Related Terms electricity generation References ↑ https://www.smartgrid.gov/category/technology/critical_peak_pricing Ret LikeLike UnlikeLike

233

What Goes Up Must Come Down? An Economic Analysis of Peak Oil ?  

E-Print Network (OSTI)

While world oil production and reserves have been increasing since 1859, ‘peak oil ’ analysts claim that production is on the cusp of a period of sustained decline. I first subject the peak oil model to a number of robustness tests. The peak oil assumption of a linear relationship between the ratio of production to cumulative production and cumulative production is rejected using data from different regions, time periods, and commodities. The peak oil model predicts a single peak in discoveries, followed by peak in proved reserves, then a peak in production. Yet, world discoveries have had four distinct peaks since 1950, and world proved reserves have continued to rise. Second, I derive an economic model of oil supply in which scarcity occurs both in total reserves and in the quality of those reserves. Depletion raises drilling costs and reduces the size of undiscovered pools. Technological change driven by learning-by-doing offsets Ricardian depletion effects. The peak oil predictions are shown to be a special case of the more general model.

John R. Boyce; I Thank Scott Taylor; Linda Nøstbakken For Allowing

2009-01-01T23:59:59.000Z

234

Peak power tracking for a solar buck charger  

E-Print Network (OSTI)

This thesis discusses the design, implementation, and testing of a buck converter with peak power tracking. The peak power tracker uses a perturb and observe algorithm to actively track the solar panel's peak power point ...

Cohen, Jeremy Michael, M. Eng. Massachusetts Institute of Technology

2010-01-01T23:59:59.000Z

235

An Analysis of loss of Decay Heat Removal Trends and Initialing Event Frequencies (1989-1988): Outage Risk Assessment and Management (ORAM) Technology  

Science Conference Proceedings (OSTI)

Operating experience shows that U.S. nuclear industry initiatives have been effective at reducing the frequency and severity of reactor coolant system loss of inventory and decay heat removal incidents during shutdown. This report -- part of EPRI's Outage Risk Assessment and Management (ORAM) technology transfer efforts -- documents operating experience from 1989-1998 and compiles initiating event frequency and recovery probabilities for use in support of probabilistic shutdown safety studies.

1999-10-20T23:59:59.000Z

236

An Analysis of Loss of Decay Heat Removal Trends and Initiating Event Frequencies (1989 - 2000): Outage Risk Assessment and Manageme nt (ORAM) Technology  

Science Conference Proceedings (OSTI)

Operating experience shows that U.S. nuclear industry initiatives have been effective at reducing the long-term frequency and severity of reactor coolant system loss of inventory and decay heat removal incidents during shutdown. This report -- part of EPRI's Outage Risk Assessment and Management (ORAM (TM)) technology transfer efforts -- documents operating experience from 1989-2000 and compiles initiating event frequency and recovery probabilities for use in support of probabilistic shutdown safety stud...

2001-11-30T23:59:59.000Z

237

Mercury Vapor At Desert Peak Area (Varekamp & Buseck, 1983) ...  

Open Energy Info (EERE)

Mercury Vapor At Desert Peak Area (Varekamp & Buseck, 1983) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Mercury Vapor At Desert Peak Area...

238

The Year of Peak Production - Energy Information Administration  

U.S. Energy Information Administration (EIA)

When world conventional oil production will peak is, of course, the bottom-line question. It has already peaked in the United States, in 1970.

239

Residential implementation of critical-peak pricing of electricity  

E-Print Network (OSTI)

L.R. Modeling alternative residential peak-load electricitydemand response to residential critical peak pricing (CPP)analysis of California residential customer response to

Herter, Karen

2006-01-01T23:59:59.000Z

240

Definition: Circuit Peak Load Management | Open Energy Information  

Open Energy Info (EERE)

Circuit Peak Load Management Jump to: navigation, search Dictionary.png Circuit Peak Load Management An application utilizing sensors, information processors, communications, and...

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


241

Estimates of Peak Underground Working Gas Storage Capacity in the ...  

U.S. Energy Information Administration (EIA)

Estimates of Peak Underground Working Gas Storage Capacity in the United States, 2009 Update The aggregate peak capacity for U.S. underground natural gas storage is ...

242

Magnetotellurics At Silver Peak Area (DOE GTP) | Open Energy...  

Open Energy Info (EERE)

Silver Peak Area (DOE GTP) Exploration Activity Details Location Silver Peak Area Exploration Technique Magnetotellurics Activity Date Usefulness not indicated DOE-funding Unknown...

243

Multispectral Imaging At Silver Peak Area (DOE GTP) | Open Energy...  

Open Energy Info (EERE)

Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Multispectral Imaging At Silver Peak Area (DOE GTP) Exploration...

244

Development Wells At Silver Peak Area (DOE GTP) | Open Energy...  

Open Energy Info (EERE)

Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Development Wells At Silver Peak Area (DOE GTP) Exploration Activity...

245

Ground Magnetics At Silver Peak Area (DOE GTP) | Open Energy...  

Open Energy Info (EERE)

Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Ground Magnetics At Silver Peak Area (DOE GTP) Exploration Activity...

246

Microgrid Dispatch for Macrogrid Peak-Demand Mitigation  

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

Dispatch for Macrogrid Peak-Demand Mitigation Title Microgrid Dispatch for Macrogrid Peak-Demand Mitigation Publication Type Conference Proceedings Refereed Designation Refereed...

247

Peak Sun Silicon Corp | Open Energy Information  

Open Energy Info (EERE)

Corp Corp Jump to: navigation, search Name Peak Sun Silicon Corp Place Carlsbad, California Zip 92008 Product US-based manufacturer of granular electronic-grade polysilicon for the PV industry. Coordinates 31.60396°, -100.641609° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":31.60396,"lon":-100.641609,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

248

Energy and Society (ER100/PP184/ER200/PP284) Fall 2011 Topics: Thermodynamics of energy systems; Peak Oil; Energy economics. Problem Set #3 Solutions  

E-Print Network (OSTI)

; Peak Oil; Energy economics. Problem Set #3 Solutions Due October 6. Grade by October 18. Total Points: Thermodynamics of energy systems; Peak Oil; Energy economics. Problem Set #3 Solutions Due October 6. Grade/PP284) Fall 2011 Topics: Thermodynamics of energy systems; Peak Oil; Energy economics. Problem Set #3

Kammen, Daniel M.

249

Reduce power outages  

SciTech Connect

A case history shows the cost-effectiveness of doing a reliability study on a new, grassroots refinery constructed in Venezuela. Constructing grassroots refineries in developing countries pose many challenges, especially when considering electrical power and steam supplies. Without dependable electrical and steam sources, the refinery will not operate according to design expectations. Consequently, utility systems are critical and expensive challenges that must be considered early in design. Because of tighter operating budgets, refiners are equally interested in cutting out system overdesign. Redundant backup systems are damaging in capital and operating expenditures. Using reliability analysis techniques, designers can evaluate the reliability, availability and maintainability of operating systems. In the following example, a Venezuelan operating company used a reliability analysis to: assess onstream factors for the refinery`s power plant; identify critical equipment that have the greatest impact on available electrical and steam sources; and achieve a cost-effective equipment configuration that eliminates redundant backup systems. Results from the study allowed decision-makers to initiate objective plans and created an equipment-failure database that will service the refinery for its useful life.

Goyal, R. [BAPCO, Awali (Bahrain); Ramirez, R. [Corpoven S.A., Caracas (Venezuela)

1995-06-01T23:59:59.000Z

250

SunPeak Solar LLC | Open Energy Information  

Open Energy Info (EERE)

SunPeak Solar LLC Jump to: navigation, search Name SunPeak Solar LLC Place Palm Desert, California Zip 92260 Product US project developer and asset manager, focussing on PV...

251

A Multimethod analysis of the Phenomenon of Peak-Oil.  

E-Print Network (OSTI)

??El concepto de Peak-Oil (el cénit del petróleo) es complejo y a menudo malentendido. Después de aclarar que el Peak-Oil es tanto un problema de… (more)

Kerschner, Christian

2012-01-01T23:59:59.000Z

252

Modeling-Computer Simulations At Desert Peak Area (Wisian & Blackwell...  

Open Energy Info (EERE)

navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Modeling-Computer Simulations At Desert Peak Area (Wisian & Blackwell, 2004) Exploration Activity...

253

Scaling distributed energy storage for grid peak reduction  

Science Conference Proceedings (OSTI)

Reducing peak demand is an important part of ongoing smart grid research efforts. To reduce peak demand, utilities are introducing variable rate electricity prices. Recent efforts have shown how variable rate pricing can incentivize consumers to use ... Keywords: battery, electricity, energy, grid, peak shaving

Aditya Mishra, David Irwin, Prashant Shenoy, Ting Zhu

2013-01-01T23:59:59.000Z

254

SNAP fuel temperature peaking with cusps in coolant channel  

SciTech Connect

Reactor Fuel Elements--temperature peaking in SNAP due to surrounding rods; systems for nuclear auxiliary power (SNAP)--reactor fuel temperataure peaking due to surrounding fuel rods; temeprature--calculations of peaking of, in SNAP fuel due to sourround fuel rods.

Treuenfels, E. W.

1963-07-19T23:59:59.000Z

255

Distributed Battery Control for Peak Power Shaving in Datacenters  

E-Print Network (OSTI)

Distributed Battery Control for Peak Power Shaving in Datacenters Baris Aksanli and Tajana Rosing to shave peak power demands. Our novel distributed battery control design has no performance impact, reduces the peak power needs, and accurately estimates and maximizes the battery lifetime. We demonstrate

Simunic, Tajana

256

Total Crude by Pipeline  

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

Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign Crude by Trucks Period: Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign Crude by Trucks Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Product Area 2007 2008 2009 2010 2011 2012 View

257

Energy and Society (ER100/PP184/ER200/PP284) Fall 2012 Topics: Thermodynamics of energy systems; Peak Oil; Energy economics. Problem Set #3 Solutions  

E-Print Network (OSTI)

; Peak Oil; Energy economics. Problem Set #3 Solutions Total Points: 103 [ER100/PP184], 133 [ER200/PP284 of energy systems; Peak Oil; Energy economics. Problem Set #3 Solutions Total Points: 103 [ER100/PP184], 133 chillers v. Thermally enhanced oil recovery (Other answers acceptable) e) Approximately what percent

Kammen, Daniel M.

258

Energy and Society (ER100/PP184/ER200/PP284) Fall 2012 Topics: Thermodynamics of energy systems; Power plant emissions; Peak Oil Problem Set #3  

E-Print Network (OSTI)

; Power plant emissions; Peak Oil Problem Set #3 Due October 4, in class, or before 5pm outside 310; Peak Oil Problem Set #3 Due October 4, in class, or before 5pm outside 310 Barrows Total Points: 100 of California's total oil/gas generation capacity is cogenerated? [Hint: Sort the spreadsheet by GENERAL

Kammen, Daniel M.

259

Promoting Employment Across Kansas (PEAK) (Kansas) | Department of Energy  

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

Promoting Employment Across Kansas (PEAK) (Kansas) Promoting Employment Across Kansas (PEAK) (Kansas) Promoting Employment Across Kansas (PEAK) (Kansas) < Back Eligibility Agricultural Commercial Construction Developer Fuel Distributor Industrial Utility Savings Category Alternative Fuel Vehicles Hydrogen & Fuel Cells Buying & Making Electricity Water Home Weatherization Solar Wind Program Info State Kansas Program Type Corporate Tax Incentive Provider Commerce Promoting Employment Across Kansas (PEAK) allows for the retention of employee payroll withholding taxes for qualified companies or third parties performing services on behalf of such companies. This program offers qualified companies the ability to retain 95 percent of their payroll withholding tax for up to five to seven years. PEAK is available to new

260

CORRELATION BETWEEN PEAK ENERGY AND PEAK LUMINOSITY IN SHORT GAMMA-RAY BURSTS  

Science Conference Proceedings (OSTI)

A correlation between the peak luminosity and the peak energy has been found by Yonetoku et al. as L{sub p} {proportional_to}E{sup 2.0}{sub p,i} for 11 pre-Swift long gamma-ray bursts (GRBs). In this study, for a greatly expanded sample of 148 long GRBs in the Swift era, we find that the correlation still exists, but most likely with a slightly different power-law index, i.e., L{sub p} {proportional_to} E{sup 1.7}{sub p,i}. In addition, we have collected 17 short GRBs with necessary data. We find that the correlation of L{sub p} {proportional_to} E{sup 1.7}{sub p,i} also exists for this sample of short events. It is argued that the radiation mechanism of both long and short GRBs should be similar, i.e., of quasi-thermal origin caused by the photosphere, with the dissipation occurring very near the central engine. Some key parameters of the process are constrained. Our results suggest that the radiation processes of both long and short bursts may be dominated by thermal emission, rather than by the single synchrotron radiation. This might put strong physical constraints on the theoretical models.

Zhang, Z. B.; Chen, D. Y. [Department of Physics, College of Sciences, Guizhou University, Guiyang 550025 (China); Huang, Y. F., E-mail: sci.zbzhang@gzu.edu.cn, E-mail: hyf@nju.edu.cn [Department of Astronomy, Nanjing University, Nanjing 210093 (China)

2012-08-10T23:59:59.000Z

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


261

Monitoring System Used to Identify, Track and Allocate Peak Demand Costs  

E-Print Network (OSTI)

In 1994, Thomson Consumer Electronics (RCA) purchased a UtiliTRACK® Monitoring System for a plant in Indianapolis, Indiana primarily to allow utility costs to be billed to individual departments within Thomson as well as to outside organizations leasing space on the site. The most common way to distribute monthly electric costs within a facility when consumption by area or department is available through submetering or other means, is to apply the average cost per KWH from the utility bill to the individual consumption figures. Thomson initially used the data from the UtiliTRACK System in this way. As the plant engineer worked with system data on a daily basis and began to develop a much better understanding of the plant's electrical profile, it was clear that the percentage contribution by department or area to the plant's peak demand was not the same as that assigned based solely upon consumption. With a monthly peak exceeding 8 MW and peak demand charges accounting for more than 60% of the monthly electric bill, he realized that to be accurate and fair, costs must be allocated based both on consumption and peak demand. He asked UtiliTRACK to develop a method for tracking and allocating peak demand costs. The resulting software continuously tracks the total plant demand (the sum of 3 utility meters) and records the contribution of each monitored point at the time the peak occurs. The resulting reports and graphs not only enable the owner to accurately allocate peak demand costs but also provide a means for tracking and managing peaks on a continuous basis.

Holmes, W. A.

1998-04-01T23:59:59.000Z

262

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Released: September, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings...

263

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings*...

264

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Released: September, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings*...

265

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings...

266

Peak power identification on power bumps during test application  

Science Conference Proceedings (OSTI)

Peak power during test can seriously impact circuit performance as well as the power safety for both CUT and tester. In this paper, we propose a method of layout-aware weighted switching activity identification flow that evaluates peak current/power ... Keywords: CMOS device, peak power identification, power bumps, test application, layout-aware weighted switching activity identification flow, dynamic power model, parasitic capacitance, resistance network, power bus, power delivery path, IR-drop, commercial power sign-off analysis tool

Wei Zhao; M. Tehranipoor

2011-07-01T23:59:59.000Z

267

Sustained Peak Low Cycle Fatigue: The Role of Coatings  

Science Conference Proceedings (OSTI)

The growth process continued by a combined process of oxidation and creep. ... of a model developed for crack growth during sustained peak low cycle fatigue.

268

Peak-shape functions for Neutron Time of Flight  

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

(Draft)-dec. 2003 Introduction A reorganization of the subroutines calculating the peak shape function and derivatives for time of flight neutron powder diffraction has been...

269

Flexible Coal: Evolution from Baseload to Peaking Plant (Brochure...  

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

the transformation of power systems Flexible Coal Evolution from Baseload to Peaking Plant The experience cited in this paper is from a generating station with multiple units...

270

Residential implementation of critical-peak pricing of electricity  

E-Print Network (OSTI)

to time-of-day electricity pricing: first empirical results.S. The trouble with electricity markets: understandingresidential peak-load electricity rate structures. Journal

Herter, Karen

2006-01-01T23:59:59.000Z

271

Gas Flux Sampling At Desert Peak Area (Lechler And Coolbaugh...  

Open Energy Info (EERE)

Page Edit History Facebook icon Twitter icon Gas Flux Sampling At Desert Peak Area (Lechler And Coolbaugh, 2007) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home...

272

Flow Shop Scheduling with Peak Power Consumption Constraints  

E-Print Network (OSTI)

enterprises; for example, many energy providers use time-of-use (TOU) tariffs ( e.g. Babu and Ashok. 2008). Peak power consumption has also received some ...

273

Residential implementation of critical-peak pricing of electricity  

E-Print Network (OSTI)

residential peak-load electricity rate structures. Journalefficiency efforts. Keywords: electricity rates, residentialmust suffer higher electricity rates to pay for the bill

Herter, Karen

2006-01-01T23:59:59.000Z

274

Residential implementation of critical-peak pricing of electricity  

E-Print Network (OSTI)

Modeling alternative residential peak-load electricity rateKeywords: electricity rates, residential electricity, demandrates be targeted to the largest residential users of electricity,

Herter, Karen

2006-01-01T23:59:59.000Z

275

Poster: Thermal Energy Storage for Electricity Peak-demand Mitigation...  

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

Poster: Thermal Energy Storage for Electricity Peak-demand Mitigation: A Solution in Developing and Developed World Alike Title Poster: Thermal Energy Storage for Electricity...

276

Reducing Peak Demand to Defer Power Plant Construction in Oklahoma  

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

Reducing Peak Demand to Defer Power Plant Construction in Oklahoma Located in the heart of "Tornado Alley," Oklahoma Gas & Electric Company's (OG&E) electric grid faces significant...

277

Methods and apparatus for reducing peak wind turbine loads ...  

A method for reducing peak loads of wind turbines in a changing wind environment includes measuring or estimating an instantaneous wind speed and direction at the ...

278

Structural Analysis of the Desert Peak-Brady Geothermal Fields...  

Open Energy Info (EERE)

mapping, delineation of Tertiary strata, analysis of faults and folds, and a new gravity survey have elucidated the structural controls on the Desert Peak and Brady...

279

Evaluation of Peak Heat Release Rates in Electrical Cabinet Fires  

Science Conference Proceedings (OSTI)

The purpose of this report is to reanalyze the peak heat release rates (HRRs) from fires occurring in electrical cabinets of nuclear power plants.

2012-02-23T23:59:59.000Z

280

Flow shop scheduling with peak power consumption constraints  

E-Print Network (OSTI)

Mar 29, 2012 ... In particular, we consider a flow shop scheduling problem with a restriction on peak power consumption, in addition to the traditional ...

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


281

Peak Oil: Knowledge, Attitudes, and Programming Activities in Public Health.  

E-Print Network (OSTI)

??Peak Oil, or the world reaching the maximum rate of petroleum extraction, poses risks such as depletion of energy resources, amplification of existing threats of… (more)

Tuckerman, Samantha Lynn

2012-01-01T23:59:59.000Z

282

Geothermometry At Silver Peak Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Silver Peak Area (DOE GTP) Exploration Activity Details Location...

283

Microgrid Dispatch for Macrogrid Peak-Demand Mitigation  

E-Print Network (OSTI)

N ATIONAL L ABORATORY Microgrid Dispatch for Macrogrid Peak-equal opportunity employer. Microgrid Dispatch for Macrogridutility customers, microgrid solutions – the installation of

DeForest, Nicholas

2013-01-01T23:59:59.000Z

284

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other...

285

ENSO Impacts on Peak Wind Gusts in the United States  

Science Conference Proceedings (OSTI)

Changes in the peak wind gust magnitude in association with the warm and cold phases of the El Niño–Southern Oscillation (ENSO) are identified over the contiguous United States. All calculations of the peak wind gust are differences in the ...

Jesse Enloe; James J. O'Brien; Shawn R. Smith

2004-04-01T23:59:59.000Z

286

Green Scheduling: Scheduling of Control Systems for Peak Power Reduction  

E-Print Network (OSTI)

approaches for load shifting and model predictive control have been proposed, we present an alternative approach to reduce the peak power for a set of control systems. The proposed model is intuitive, scalableGreen Scheduling: Scheduling of Control Systems for Peak Power Reduction Truong Nghiem, Madhur Behl

Pappas, George J.

287

Energy solutions for CO2 emission peak and subsequent decline  

E-Print Network (OSTI)

Energy solutions for CO2 emission peak and subsequent decline Edited by Leif Sønderberg Petersen and Hans Larsen Risø-R-1712(EN) September 2009 Proceedings Risø International Energy Conference 2009 #12;Editors: Leif Sønderberg Petersen and Hans Larsen Title: Energy solutions for CO2 emission peak

288

Diesel Rig Mechanical Peaking System Based on Flywheel Storage Technolgy  

Science Conference Proceedings (OSTI)

Flywheel energy storage technology is an emerging energy storage technology, there is a great development in recent years promising energy storage technology, with a large energy storage, high power, no pollution, use of broad, simple maintenance, enabling ... Keywords: Flywheel energy storage technology, mechanical peaking, diesel rig, peak motor

Shuguang Liu, Jia Wang

2012-07-01T23:59:59.000Z

289

Evaluation of Travis Peak gas reservoirs, west margin of the East Texas Basin  

E-Print Network (OSTI)

Gas production from low-permeability (tight) gas sandstones is increasingly important in the USA as conventional gas reservoirs are being depleted, and its importance will increase worldwide in future decades. Travis Peak tight sandstones have produced gas since the 1940s. In this study, well log, 2D seismic, core, and production data were used to evaluate the geologic setting and reservoir characteristics of the Travis Peak formation. The primary objective was to assess the potential for basinward extension of Travis Peak gas production along the west margin of the East Texas Basin. Along the west margin of the East Texas Basin, southeast-trending Travis Peak sandstones belts were deposited by the Ancestral Red River fluvial-deltaic system. The sandstones are fine-grained, moderately well sorted, subangular to subrounded, quartz arenites and subarkoses; reservoir quality decreases with depth, primarily due to diagenetic quartz overgrowths. Evaluation of drilling mud densities suggests that strata deeper than 12,500 ft may be overpressured. Assessment of the geothermal gradient (1.6 °F/100 ft) indicates that overpressure may be relict, resulting from hydrocarbon generation by Smackover and Bossier formation potential source rocks. In the study area, Travis Peak cumulative gas production was 1.43 trillion cubic feet from January 1, 1961, through December 31, 2005. Mean daily gas production from 923 wells was 925,000 cubic ft/well/day, during the best year of production. The number of Travis Peak gas wells in “high-cost” (tight sandstone) fields increased from 18 in the decade 1966-75 to 333 in the decade 1996-2005, when high-cost fields accounted for 33.2% of the Travis Peak gas production. However, 2005 gas production from high cost fields accounted for 63.2% of the Travis Peak total production, indicating that production from high-cost gas wells has increased markedly. Along the west margin of the East Texas Basin, hydrocarbon occurs in structural, stratigraphic, and combination traps associated with salt deformation. Downdip extension of Travis Peak production will depend on the (1) burial history and diagenesis, (2) reservoir sedimentary facies, and (3) structural setting. Potential Travis Peak hydrocarbon plays include: updip pinch-outs of sandstones; sandstone pinch-outs at margins of salt-withdrawal basins; domal traps above salt structures; and deepwater sands.

Li, Yamin

2007-05-01T23:59:59.000Z

290

Emcore/SunPeak Solar Power Plant | Open Energy Information  

Open Energy Info (EERE)

Emcore/SunPeak Solar Power Plant Emcore/SunPeak Solar Power Plant < Emcore Jump to: navigation, search Name Emcore/SunPeak Solar Power Plant Facility Emcore/SunPeak Sector Solar Facility Type Concentrating Photovoltaic Developer SunPeak Solar Location Albuquerque, New Mexico Coordinates 35.0844909°, -106.6511367° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":35.0844909,"lon":-106.6511367,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

291

U.S. Total Exports  

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

TX Roma, TX Total to Portugal Sabine Pass, LA Total to Russia Kenai, AK Total to South Korea Freeport, TX Sabine Pass, LA Total to Spain Cameron, LA Sabine Pass, LA Total to...

292

U.S. Total Exports  

Gasoline and Diesel Fuel Update (EIA)

Rio Bravo, TX Roma, TX Total to Portugal Sabine Pass, LA Total to Russia Total to South Korea Freeport, TX Sabine Pass, LA Total to Spain Cameron, LA Sabine Pass, LA Total to...

293

21 briefing pages total  

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

briefing pages total p. 1 briefing pages total p. 1 Reservist Differential Briefing U.S. Office of Personnel Management December 11, 2009 p. 2 Agenda - Introduction of Speakers - Background - References/Tools - Overview of Reservist Differential Authority - Qualifying Active Duty Service and Military Orders - Understanding Military Leave and Earnings Statements p. 3 Background 5 U.S.C. 5538 (Section 751 of the Omnibus Appropriations Act, 2009, March 11, 2009) (Public Law 111-8) Law requires OPM to consult with DOD Law effective first day of first pay period on or after March 11, 2009 (March 15 for most executive branch employees) Number of affected employees unclear p. 4 Next Steps

294

Peaking World Oil Production: Impacts, Mitigation and Risk Management  

E-Print Network (OSTI)

The peaking of world oil production presents the U.S. and the world with an unprecedented risk management problem. As peaking is approached, liquid fuel prices and price volatility will increase dramatically, and, without timely mitigation, the economic, social, and political costs will be unprecedented. Viable mitigation options exist on both the supply and demand sides, but to have substantial impact, they must be initiated more than a decade in advance of peaking. In 2003, the world consumed nearly 80 million barrels per day (MM bpd) of oil. U.S. consumption was almost 20 MM bpd,

Robert L. Hirsch; Roger H. Bezdek; Robert M. Wendling

2005-01-01T23:59:59.000Z

295

Cooling commercial buildings with off-peak power  

Science Conference Proceedings (OSTI)

Large commercial buildings use more electricity for cooling than for heating, and can account for 40% of summer peak demand. A cool storage technique in which compressors chill or freeze water during off-peak periods and the water is circulated during peak hours is in use in 100 commercial buildings. Reports indicate that these systems are economical, although little information is available, but engineers are hesitant to incorporate them because of possible damage from leaks or rust and other uncertainties. The Electric Power Research Institute is evaluating the performance of several systems to answer some of the operating and maintenance questions raised by engineers. 3 references, 3 figures. (DCK)

Lihach, N.; Rabl, V.

1983-10-01T23:59:59.000Z

296

Barge Truck Total  

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

Barge Barge Truck Total delivered cost per short ton Shipments with transportation rates over total shipments Total delivered cost per short ton Shipments with transportation rates over total shipments Year (nominal) (real) (real) (percent) (nominal) (real) (real) (percent) 2008 $6.26 $5.77 $36.50 15.8% 42.3% $6.12 $5.64 $36.36 15.5% 22.2% 2009 $6.23 $5.67 $52.71 10.8% 94.8% $4.90 $4.46 $33.18 13.5% 25.1% 2010 $6.41 $5.77 $50.83 11.4% 96.8% $6.20 $5.59 $36.26 15.4% 38.9% Annual Percent Change First to Last Year 1.2% 0.0% 18.0% - - 0.7% -0.4% -0.1% - - Latest 2 Years 2.9% 1.7% -3.6% - - 26.6% 25.2% 9.3% - - - = No data reported or value not applicable STB Data Source: The Surface Transportation Board's 900-Byte Carload Waybill Sample EIA Data Source: Form EIA-923 Power Plant Operations Report

297

Summary Max Total Units  

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

Max Total Units Max Total Units *If All Splits, No Rack Units **If Only FW, AC Splits 1000 52 28 28 2000 87 59 35 3000 61 33 15 4000 61 33 15 Totals 261 153 93 ***Costs $1,957,500.00 $1,147,500.00 $697,500.00 Notes: added several refrigerants removed bins from analysis removed R-22 from list 1000lb, no Glycol, CO2 or ammonia Seawater R-404A only * includes seawater units ** no seawater units included *** Costs = (total units) X (estimate of $7500 per unit) 1000lb, air cooled split systems, fresh water Refrig Voltage Cond Unit IF-CU Combos 2 4 5 28 References Refrig Voltage C-U type Compressor HP R-404A 208/1/60 Hermetic SA 2.5 R-507 230/1/60 Hermetic MA 2.5 208/3/60 SemiHerm SA 1.5 230/3/60 SemiHerm MA 1.5 SemiHerm HA 1.5 1000lb, remote rack systems, fresh water Refrig/system Voltage Combos 12 2 24 References Refrig/system Voltage IF only

298

EA-1921: Silver Peak Area Geothermal Exploration Project Environmental  

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

921: Silver Peak Area Geothermal Exploration Project 921: Silver Peak Area Geothermal Exploration Project Environmental Assessment, Esmeralda County, Nevada EA-1921: Silver Peak Area Geothermal Exploration Project Environmental Assessment, Esmeralda County, Nevada SUMMARY The Bureau of Land Management (BLM)(lead agency) and DOE are jointly preparing this EA, which evaluates the potential environmental impacts of a project proposed by Rockwood Lithium Inc (Rockwood), formerly doing business as Chemetall Foote Corporation. Rockwood has submitted to the BLM, Tonopah Field Office, an Operations Plan for the construction, operation, and maintenance of the Silver Peak Area Geothermal Exploration Project within Esmeralda County, Nevada. The purpose of the project is to determine subsurface temperatures, confirm the existence of geothermal resources, and

299

Resistivity Tomography At Silver Peak Area (DOE GTP) | Open Energy  

Open Energy Info (EERE)

source source History View New Pages Recent Changes All Special Pages Semantic Search/Querying Get Involved Help Apps Datasets Community Login | Sign Up Search Page Edit History Facebook icon Twitter icon » Resistivity Tomography At Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Single-Well and Cross-Well Resistivity At Silver Peak Area (DOE GTP) Exploration Activity Details Location Silver Peak Area Exploration Technique Single-Well and Cross-Well Resistivity Activity Date Usefulness not indicated DOE-funding Unknown References (1 January 2011) GTP ARRA Spreadsheet Retrieved from "http://en.openei.org/w/index.php?title=Resistivity_Tomography_At_Silver_Peak_Area_(DOE_GTP)&oldid=689883" Categories:

300

Track B - Critical Guidance for Peak Performance Homes | Department of  

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

Track B - Critical Guidance for Peak Performance Homes Track B - Critical Guidance for Peak Performance Homes Track B - Critical Guidance for Peak Performance Homes Presentations from Track B, Critical Guidance for Peak Performance Homes of the U.S. Department of Energy Building America program's 2012 Residential Energy Efficiency Stakeholder Meeting are provided below as Adobe Acrobat PDFs. These presentations for this track covered the following topics: Ventilation Strategies in High Performance Homes; Combustion Safety in Tight Houses; Implementation Program Case Studies; Field Testing from Start to Finish; and Humidity Control and Analysis. why_we_ventilate.pdf formaldehyde_new_homes.pdf whole_bldg_ventilation.pdf combustion_safety_codes.pdf combustion_diagnostics.pdf test_protocols_results.pdf utility_incentive_programs.pdf

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


301

EA-1921: Silver Peak Area Geothermal Exploration Project Environmental  

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

921: Silver Peak Area Geothermal Exploration Project 921: Silver Peak Area Geothermal Exploration Project Environmental Assessment, Esmeralda County, Nevada EA-1921: Silver Peak Area Geothermal Exploration Project Environmental Assessment, Esmeralda County, Nevada SUMMARY The Bureau of Land Management (BLM)(lead agency) and DOE are jointly preparing this EA, which evaluates the potential environmental impacts of a project proposed by Rockwood Lithium Inc (Rockwood), formerly doing business as Chemetall Foote Corporation. Rockwood has submitted to the BLM, Tonopah Field Office, an Operations Plan for the construction, operation, and maintenance of the Silver Peak Area Geothermal Exploration Project within Esmeralda County, Nevada. The purpose of the project is to determine subsurface temperatures, confirm the existence of geothermal resources, and

302

Multispectral Imaging At Silver Peak Area (Laney, 2005) | Open Energy  

Open Energy Info (EERE)

Laney, 2005) Laney, 2005) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Multispectral Imaging At Silver Peak Area (Laney, 2005) Exploration Activity Details Location Silver Peak Area Exploration Technique Multispectral Imaging Activity Date Usefulness not indicated DOE-funding Unknown Notes Geology and Geophysics of Geothermal Systems, Gregory Nash, 2005. A third objective was testing ASTER multispectral data for small-scale mapping of the geology of the northern Silver Peak Range, Nevada near the Fish Lake Valley geothermal field. References Patrick Laney (2005) Federal Geothermal Research Program Update - Fiscal Year 2004 Retrieved from "http://en.openei.org/w/index.php?title=Multispectral_Imaging_At_Silver_Peak_Area_(Laney,_2005)&oldid=511017"

303

Airport quotas and peak hour pricing : theory and practice  

E-Print Network (OSTI)

This report examines the leading theoretical studies not only of airport peak-hour pricing but also of the congestion costs associated with airport delays and presents a consistent formulation of both. The report also ...

Odoni, Amedeo R.

1976-01-01T23:59:59.000Z

304

Residential Response to Critical Peak Pricing of Electricity  

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

Residential Response to Critical Peak Pricing of Electricity Speaker(s): Karen Herter Date: June 30, 2005 - 12:00pm Location: Bldg. 90 A recent California study collected detailed...

305

Automated Critical Peak Pricing Field Tests: Program Description and Results  

E-Print Network (OSTI)

E-2: Baseline Peak and Maximum Demand Savings at Each Auto-45 Table 4-8: Maximum Demand saving by Site and Non-and the non-coincident maximum demand savings. If all twelve

Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Xu, Peng

2006-01-01T23:59:59.000Z

306

Transient Peak Currents in Permanent Magnet Synchronous Motors  

E-Print Network (OSTI)

Transient Peak Currents in Permanent Magnet Synchronous Motors for Symmetrical Short Circuits Terms-- Permanent magnet synchronous motor, short circuit, protection measure, transient behavior I 33095 Paderborn, Germany Abstract--To enable constant-power areas with permanent magnet synchronous

Noé, Reinhold

307

Off peak cooling using an ice storage system  

E-Print Network (OSTI)

The electric utilities in the United States have entered a period of slow growth due to a combination of increased capital costs and a staggering rise in the costs for fuel. In addition to this, the rise in peak power ...

Quinlan, Edward Michael

1980-01-01T23:59:59.000Z

308

Structural Analysis of the Desert Peak-Brady Geothermal Fields,  

Open Energy Info (EERE)

Structural Analysis of the Desert Peak-Brady Geothermal Fields, Structural Analysis of the Desert Peak-Brady Geothermal Fields, Northwestern Nevada: Implications for Understanding Linkages Between Northeast-Trending Structures and Geothermal Reservoirs in the Humboldt Structural Zone Jump to: navigation, search OpenEI Reference LibraryAdd to library Conference Paper: Structural Analysis of the Desert Peak-Brady Geothermal Fields, Northwestern Nevada: Implications for Understanding Linkages Between Northeast-Trending Structures and Geothermal Reservoirs in the Humboldt Structural Zone Abstract Detailed geologic mapping, delineation of Tertiary strata, analysis of faults and folds, and a new gravity survey have elucidated the structural controls on the Desert Peak and Brady geothermal fields in the Hot Springs Mountains of northwestern Nevada. The fields lie within the Humboldt

309

Twin Peaks Motel Space Heating Low Temperature Geothermal Facility | Open  

Open Energy Info (EERE)

Peaks Motel Space Heating Low Temperature Geothermal Facility Peaks Motel Space Heating Low Temperature Geothermal Facility Jump to: navigation, search Name Twin Peaks Motel Space Heating Low Temperature Geothermal Facility Facility Twin Peaks Motel Sector Geothermal energy Type Space Heating Location Ouray, Colorado Coordinates 38.0227716°, -107.6714487° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[]}

310

Silver Peak, Nevada: Energy Resources | Open Energy Information  

Open Energy Info (EERE)

Peak, Nevada: Energy Resources Peak, Nevada: Energy Resources (Redirected from Silver Peak, NV) Jump to: navigation, search Name Silver Peak, Nevada Equivalent URI DBpedia GeoNames ID 5512346 Coordinates 37.7549309°, -117.6348148° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.7549309,"lon":-117.6348148,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

311

The Annual Peak in the SST Anomaly Spectrum  

Science Conference Proceedings (OSTI)

The manner in which monthly mean sea surface temperature anomalies (SSTAs) show enhanced variance at the annual period in the extratropics (an annual peak in the variance spectrum) is illustrated by observations and model simulations. A mechanism,...

Jens Möller; Dietmar Dommenget; Vladimir A. Semenov

2008-06-01T23:59:59.000Z

312

Potential of solar cooling systems for peak demand reduction  

DOE Green Energy (OSTI)

We investigated the technical feasibility of solar cooling for peak demand reduction using a building energy simulation program (DOE2.1D). The system studied was an absorption cooling system with a thermal coefficient of performance of 0.8 driven by a solar collector system with an efficiency of 50% with no thermal storage. The analysis for three different climates showed that, on the day with peak cooling load, about 17% of the peak load could be met satisfactorily with the solar-assisted cooling system without any thermal storage. A performance availability analysis indicated that the solar cooling system should be designed for lower amounts of available solar resources that coincide with the hours during which peak demand reduction is required. The analysis indicated that in dry climates, direct-normal concentrating collectors work well for solar cooling; however, in humid climates, collectors that absorb diffuse radiation work better.

Pesaran, A.A. [National Renewable Energy Lab., Golden, CO (United States); Neymark, J. [Neymark (Joel), Golden, CO (United States)

1994-11-01T23:59:59.000Z

313

Fossil fuel-fired peak heating for geothermal greenhouses  

SciTech Connect

This report examines the capital and operating costs for fossil fuel-fired peak heating systems in geothermally (direct use) heated greenhouses. Issues covered include equipment capital costs, fuel requirements, maintenance and operating costs, system control and integration into conventional hot water greenhouse heating systems. Annual costs per square foot of greenhouse floor area are developed for three climates: Helena, MT; Klamath Falls, OR and San Bernardino, CA, for both boiler and individual unit heater peaking systems. In most applications, peaking systems sized for 60% of the peak load are able to satisfy over 95% of the annual heating requirements and cost less than $0.15 per square foot per year to operate. The propane-fired boiler system has the least cost of operation in all but Helena, MT climate.

Rafferty, K.

1996-12-01T23:59:59.000Z

314

Jiminy Peak Ski Resort Wind Farm | Open Energy Information  

Open Energy Info (EERE)

Jiminy Peak Ski Resort Wind Farm Jiminy Peak Ski Resort Wind Farm Jump to: navigation, search Name Jiminy Peak Ski Resort Wind Farm Facility Jiminy Peak Ski Resort Sector Wind energy Facility Type Community Wind Facility Status In Service Owner Jiminy Peak Mountain Resort Developer Sustainable Energy Developments Energy Purchaser Jiminy Peak Mountain Resort Location Hancock MA Coordinates 42.5554°, -73.2898° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":42.5554,"lon":-73.2898,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

315

Observation of low magnetic field density peaks in helicon plasma  

SciTech Connect

Single density peak has been commonly observed in low magnetic field (<100 G) helicon discharges. In this paper, we report the observations of multiple density peaks in low magnetic field (<100 G) helicon discharges produced in the linear helicon plasma device [Barada et al., Rev. Sci. Instrum. 83, 063501 (2012)]. Experiments are carried out using argon gas with m = +1 right helical antenna operating at 13.56 MHz by varying the magnetic field from 0 G to 100 G. The plasma density varies with varying the magnetic field at constant input power and gas pressure and reaches to its peak value at a magnetic field value of {approx}25 G. Another peak of smaller magnitude in density has been observed near 50 G. Measurement of amplitude and phase of the axial component of the wave using magnetic probes for two magnetic field values corresponding to the observed density peaks indicated the existence of radial modes. Measured parallel wave number together with the estimated perpendicular wave number suggests oblique mode propagation of helicon waves along the resonance cone boundary for these magnetic field values. Further, the observations of larger floating potential fluctuations measured with Langmuir probes at those magnetic field values indicate that near resonance cone boundary; these electrostatic fluctuations take energy from helicon wave and dump power to the plasma causing density peaks.

Barada, Kshitish K.; Chattopadhyay, P. K.; Ghosh, J.; Kumar, Sunil; Saxena, Y. C. [Institute for Plasma Research, Bhat, Gandhinagar 382428 (India)

2013-04-15T23:59:59.000Z

316

Peaking of world oil production: Impacts, mitigation, & risk management  

SciTech Connect

The peaking of world oil production presents the U.S. and the world with an unprecedented risk management problem. As peaking is approached, liquid fuel prices and price volatility will increase dramatically, and, without timely mitigation, the economic, social, and political costs will be unprecedented. Viable mitigation options exist on both the supply and demand sides, but to have substantial impact, they must be initiated more than a decade in advance of peaking.... The purpose of this analysis was to identify the critical issues surrounding the occurrence and mitigation of world oil production peaking. We simplified many of the complexities in an effort to provide a transparent analysis. Nevertheless, our study is neither simple nor brief. We recognize that when oil prices escalate dramatically, there will be demand and economic impacts that will alter our simplified assumptions. Consideration of those feedbacks will be a daunting task but one that should be undertaken. Our aim in this study is to-- • Summarize the difficulties of oil production forecasting; • Identify the fundamentals that show why world oil production peaking is such a unique challenge; • Show why mitigation will take a decade or more of intense effort; • Examine the potential economic effects of oil peaking; • Describe what might be accomplished under three example mitigation scenarios. • Stimulate serious discussion of the problem, suggest more definitive studies, and engender interest in timely action to mitigate its impacts.

Hirsch, R.L. (SAIC); Bezdek, Roger (MISI); Wendling, Robert (MISI)

2005-02-01T23:59:59.000Z

317

U.S. Total Exports  

Annual Energy Outlook 2012 (EIA)

NY Waddington, NY Sumas, WA Sweetgrass, MT Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to India Freeport, TX Sabine Pass, LA Total to Japan...

318

Automated Critical Peak Pricing Field Tests: 2006 Pilot Program Description and Results  

E-Print Network (OSTI)

together  during  this  peak  demand period to use power 21 Peak Demand Baseline study.  Their average peak demand reduction was 14% of the 

Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila

2007-01-01T23:59:59.000Z

319

Demonstration of Smart Building Controls to Manage Building Peak Loads: Innovative Non-Wires Technologies  

SciTech Connect

As a part of the non-wires solutions effort, BPA in partnership with Pacific Northwest National Laboratory (PNNL) is exploring the use of two distributed energy resources (DER) technologies in the City of Richland. In addition to demonstrating the usefulness of the two DER technologies in providing peak demand relief, evaluation of remote direct load control (DLC) is also one of the primary objectives of this demonstration. The concept of DLC, which is used to change the energy use profile during peak hours of the day, is not new. Many utilities have had success in reducing demand at peak times to avoid building new generation. It is not the need for increased generation that is driving the use of direct load control in the Northwest, but the desire to avoid building additional transmission capacity. The peak times at issue total between 50 and 100 hours a year. A transmission solution to the problem would cost tens of millions of dollars . And since a ?non wires? solution is just as effective and yet costs much less, the capital dollars for construction can be used elsewhere on the grid where building new transmission is the only alternative. If by using DLC, the electricity use can be curtailed, shifted to lower use time periods or supplemented through local generation, the existing system can be made more reliable and cost effective.

Katipamula, Srinivas; Hatley, Darrel D.

2004-12-22T23:59:59.000Z

320

The Impact of Residential Air Conditioner Charging and Sizing on Peak Electrical Demand  

E-Print Network (OSTI)

Electric utilities have had a number of air conditioner rebate and maintenance programs for many years. The purpose of these programs was to improve the efficiency of the stock of air conditioning equipment and provide better demand-side management. This paper examines the effect of refrigerant charging (proper servicing of the equipment), system sizing, and efficiency on the steady-state, coincident peak utility demand of a residential central air conditioning system. The study is based on the results of laboratory tests of a three-ton, capillary tube expansion, split-system air conditioner, system capacity and efficiency data available from manufacturer's literature, and assumptions about relative sizing of the equipment to cooling load on a residence. A qualitative discussion is provided concerning the possible impacts of transient operation and total energy use on utility program decisions. The analysis indicates that proper sizing of the unit is the largest factor affecting energy demand of the three factors (sizing, charging, and efficiency) studied in this paper. For typical oversizing of units to cooling loads in houses, both overcharging and undercharging showed significant negative impact on peak demand. The impacts of SEER changes in utility peak demand were found to be virtually independent of oversizing. For properly sized units, there was a small peak benefit to higher efficiency air conditioners.

Neal, L.; O'Neal, D. L.

1992-05-01T23:59:59.000Z

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


321

Storing hydroelectricity to meet peak-hour demand  

Science Conference Proceedings (OSTI)

This paper reports on pumped storage plants which have become an effective way for some utility companies that derive power from hydroelectric facilities to economically store baseload energy during off-peak hours for use during peak hourly demands. According to the Electric Power Research Institute (EPRI) in Palo Alto, Calif., 36 of these plants provide approximately 20 gigawatts, or about 3 percent of U.S. generating capacity. During peak-demand periods, utilities are often stretched beyond their capacity to provide power and must therefore purchase it from neighboring utilities. Building new baseload power plants, typically nuclear or coal-fired facilities that run 24 hours per day seven days a week, is expensive, about $1500 per kilowatt, according to Robert Schainker, program manager for energy storage at the EPRI. Schainker the that building peaking plants at $400 per kilowatt, which run a few hours a day on gas or oil fuel, is less costly than building baseload plants. Operating them, however, is more expensive because peaking plants are less efficient that baseload plants.

Valenti, M.

1992-04-01T23:59:59.000Z

322

Total Sales of Kerosene  

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

End Use: Total Residential Commercial Industrial Farm All Other Period: End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2007 2008 2009 2010 2011 2012 View History U.S. 492,702 218,736 269,010 305,508 187,656 81,102 1984-2012 East Coast (PADD 1) 353,765 159,323 198,762 237,397 142,189 63,075 1984-2012 New England (PADD 1A) 94,635 42,570 56,661 53,363 38,448 15,983 1984-2012 Connecticut 13,006 6,710 8,800 7,437 7,087 2,143 1984-2012 Maine 46,431 19,923 25,158 24,281 17,396 7,394 1984-2012 Massachusetts 7,913 3,510 5,332 6,300 2,866 1,291 1984-2012 New Hampshire 14,454 6,675 8,353 7,435 5,472 1,977 1984-2012

323

Reducing Peak Demand to Defer Power Plant Construction in Oklahoma  

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

Reducing Peak Demand to Defer Power Plant Construction in Oklahoma Reducing Peak Demand to Defer Power Plant Construction in Oklahoma Located in the heart of "Tornado Alley," Oklahoma Gas & Electric Company's (OG&E) electric grid faces significant challenges from severe weather, hot summers, and about 2% annual load growth. To better control costs and manage electric reliability under these conditions, OG&E is pursuing demand response strategies made possible by implementation of smart grid technologies, tools, and techniques from 2010-2012. The objective is to engage customers in lowering peak demand using smart technologies in homes and businesses and to achieve greater efficiencies on the distribution system. The immediate goal: To defer two 165 MW power plants currently planned for

324

Silver Peak, Nevada: Energy Resources | Open Energy Information  

Open Energy Info (EERE)

Peak, Nevada: Energy Resources Peak, Nevada: Energy Resources Jump to: navigation, search Name Silver Peak, Nevada Equivalent URI DBpedia GeoNames ID 5512346 Coordinates 37.7549309°, -117.6348148° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.7549309,"lon":-117.6348148,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

325

Price Server System for Automated Critical Peak Pricing  

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

Price Server System for Automated Critical Peak Pricing Price Server System for Automated Critical Peak Pricing Speaker(s): David S. Watson Date: June 3, 2005 - 12:00pm Location: 90-3148 Overview of current California Energy Commission (CEC)/Demand Response Research Center (DRRC) Auto-CPP project: This summer, some select commercial CPP customers of PG&E will have the option of joining the Automated Critical Peak Pricing pilot. The pilot will have the same tariffs as standard CPP programs, but will include an added feature: automated shedding of electric loads. Through use of the Price Server System, day-ahead CPP event signals initiated by PG&E will ultimately cause electric loads to be automatically curtailed on commercial customer sites. These optional predetermined shed strategies will occur without

326

Cuttings Analysis At Desert Peak Area (Laney, 2005) | Open Energy  

Open Energy Info (EERE)

Desert Peak Area (Laney, 2005) Desert Peak Area (Laney, 2005) Exploration Activity Details Location Desert Peak Area Exploration Technique Cuttings Analysis Activity Date Usefulness not indicated DOE-funding Unknown Notes Remote Sensing for Exploration and Mapping of Geothermal Resources, Wendy Calvin, 2005. Task 1: Detailed analysis of hyperspectral imagery obtained in summer of 2003 over Brady's Hot Springs region was completed and validated (Figure 1). This analysis provided a local map of both sinter and tufa deposits surrounding the Ormat plant, identified fault extensions not previously recognized from field mapping and has helped constrain where to put additional wells that were drilled at the site. Task 2: Initial analysis of Landsat and ASTER data for Buffalo Valley and Pyramid Lake was

327

Peak polarity overturn for charged particles in laser ablation process  

Science Conference Proceedings (OSTI)

The charged particles emitted during laser ablation off a brass target are detected using a metal probe in air. A special phenomenon is found in the recorded signals: following a giant electromagnetic peak observed immediately after the emission of the pulsed laser, a minor peak occurs whose polarity merely depends on the distance between the probe and the laser focal spot on the target. Under the condition of our experiment, the overturn point is 1.47 mm, i.e., the minor peak remains negative when the probe distance is less than 1.47 mm; it becomes positive while the probe is set at a distance beyond 1.47 mm. A hypothesis is proposed to explain the overturn that takes the flight behavior of the charged particles both in plasma and propagating shock wave into consideration.

Zhang, P.; Ji, Y. J.; Lai, X. M.; Bian, B. M.; Li, Z. H. [Department of Information Physics and Engineering, Nanjing University of Science and Technology, Nanjing 210094 (China)

2006-07-01T23:59:59.000Z

328

Potential Peak Load Reductions From Residential Energy Efficient Upgrades  

E-Print Network (OSTI)

The demand for electricity is continuing to grow at a substantial rate. Utilities are interested in managing this growth's peak demand for a number of reasons including: costly construction of new generation capacity can be deferred; the reliability of the distribution network can be improved; and added environmental pollution can be minimized. Energy efficiency improvements, especially through residential programs, are increasingly being used to mitigate this rise in peak demand. This paper examines the potential peak load reductions from residential energy efficiency upgrades in hot and humid climates. First, a baseline scenario is established. Then, the demand and consumption impacts of individual upgrade measures are assessed. Several of these upgrades are then combined into a package to assess the synergistic demand and energy impacts. A sensitivity analysis is then performed to assess the impacts of housing characteristics on estimated demand and energy savings. Finally, the demand, energy, and environmental impacts are estimated at the community level.

Meisegeier, D.; Howes, M.; King, D.; Hall, J.

2002-01-01T23:59:59.000Z

329

Desert Peak II Geothermal Facility | Open Energy Information  

Open Energy Info (EERE)

II Geothermal Facility II Geothermal Facility Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Desert Peak II Geothermal Facility General Information Name Desert Peak II Geothermal Facility Facility Desert Peak II Sector Geothermal energy Location Information Location Churchill, Nevada Coordinates 39.753854931241°, -118.95378112793° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":39.753854931241,"lon":-118.95378112793,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

330

Scenario Analysis of Peak Demand Savings for Commercial Buildings with  

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

Scenario Analysis of Peak Demand Savings for Commercial Buildings with Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California Title Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California Publication Type Conference Paper LBNL Report Number LBNL-3636e Year of Publication 2010 Authors Yin, Rongxin, Sila Kiliccote, Mary Ann Piette, and Kristen Parrish Conference Name 2010 ACEEE Summer Study on Energy Efficiency in Buildings Conference Location Pacific Grove, CA Keywords demand response and distributed energy resources center, demand response research center, demand shifting (pre-cooling), DRQAT Abstract This paper reports on the potential impact of demand response (DR) strategies in commercial buildings in California based on the Demand Response Quick Assessment Tool (DRQAT), which uses EnergyPlus simulation prototypes for office and retail buildings. The study describes the potential impact of building size, thermal mass, climate, and DR strategies on demand savings in commercial buildings. Sensitivity analyses are performed to evaluate how these factors influence the demand shift and shed during the peak period. The whole-building peak demand of a commercial building with high thermal mass in a hot climate zone can be reduced by 30% using an optimized demand response strategy. Results are summarized for various simulation scenarios designed to help owners and managers understand the potential savings for demand response deployment. Simulated demand savings under various scenarios were compared to field-measured data in numerous climate zones, allowing calibration of the prototype models. The simulation results are compared to the peak demand data from the Commercial End-Use Survey for commercial buildings in California. On the economic side, a set of electricity rates are used to evaluate the impact of the DR strategies on economic savings for different thermal mass and climate conditions. Our comparison of recent simulation to field test results provides an understanding of the DR potential in commercial buildings.

331

Total Marketed Production ..............  

Gasoline and Diesel Fuel Update (EIA)

billion cubic feet per day) billion cubic feet per day) Total Marketed Production .............. 68.95 69.77 70.45 71.64 71.91 71.70 71.46 71.57 72.61 72.68 72.41 72.62 70.21 71.66 72.58 Alaska ......................................... 1.04 0.91 0.79 0.96 1.00 0.85 0.77 0.93 0.97 0.83 0.75 0.91 0.93 0.88 0.87 Federal GOM (a) ......................... 3.93 3.64 3.44 3.82 3.83 3.77 3.73 3.50 3.71 3.67 3.63 3.46 3.71 3.70 3.62 Lower 48 States (excl GOM) ...... 63.97 65.21 66.21 66.86 67.08 67.08 66.96 67.14 67.92 68.18 68.02 68.24 65.58 67.07 68.09 Total Dry Gas Production .............. 65.46 66.21 66.69 67.79 68.03 67.83 67.61 67.71 68.69 68.76 68.50 68.70 66.55 67.79 68.66 Gross Imports ................................ 8.48 7.60 7.80 7.95 8.27 7.59 7.96 7.91 7.89 7.17 7.61 7.73 7.96 7.93 7.60 Pipeline ........................................

332

Total Biofuels Consumption (2005 - 2009) Total annual biofuels...  

Open Energy Info (EERE)

Total Biofuels Consumption (2005 - 2009) Total annual biofuels consumption (Thousand Barrels Per Day) for 2005 - 2009 for over 230 countries and regions.      ...

333

SCHOOL OF HISTORY & PHILOSOPHY Peak Carbon. Climate change and energy  

E-Print Network (OSTI)

SCHOOL OF HISTORY & PHILOSOPHY Peak Carbon. Climate change and energy policy ARTS2241 S2, 2010 #12 to be overcome before Australia can make deep cuts in greenhouse emissions, particularly from energy generation AIMS · Create awareness of the `bigger picture' that connects concerns over climate change and energy

Green, Donna

334

Scalable Scheduling of Building Control Systems for Peak Demand Reduction  

E-Print Network (OSTI)

is model predictive control (MPC) ([6], [7]). In [6] the authors inves- tigated MPC for thermal energyScalable Scheduling of Building Control Systems for Peak Demand Reduction Truong X. Nghiem, Madhur operation of sub- systems such as heating, ventilating, air conditioning and refrigeration (HVAC&R) systems

Pappas, George J.

335

Performance of a voltage peak detection-based flickermeter  

Science Conference Proceedings (OSTI)

Voltage fluctuations and rapid voltage changes lead to lamps flickering and disturbance of visual perception may occur consequently. For evaluation of the flicker severity level by means of voltage measurement there was developed an instrument called ... Keywords: Matlab Simulink, flickermeter, interharmonics, performance analysis, voltage fluctuation, voltage peak detection

Jiri Drapela

2009-12-01T23:59:59.000Z

336

Peak Dose Assessment for Proposed DOE-PPPO Authorized Limits  

Science Conference Proceedings (OSTI)

The Oak Ridge Institute for Science and Education (ORISE), a U.S. Department of Energy (DOE) prime contractor, was contracted by the DOE Portsmouth/Paducah Project Office (DOE-PPPO) to conduct a peak dose assessment in support of the Authorized Limits Request for Solid Waste Disposal at Landfill C-746-U at the Paducah Gaseous Diffusion Plant (DOE-PPPO 2011a). The peak doses were calculated based on the DOE-PPPO Proposed Single Radionuclides Soil Guidelines and the DOE-PPPO Proposed Authorized Limits (AL) Volumetric Concentrations available in DOE-PPPO 2011a. This work is provided as an appendix to the Dose Modeling Evaluations and Technical Support Document for the Authorized Limits Request for the C-746-U Landfill at the Paducah Gaseous Diffusion Plant, Paducah, Kentucky (ORISE 2012). The receptors evaluated in ORISE 2012 were selected by the DOE-PPPO for the additional peak dose evaluations. These receptors included a Landfill Worker, Trespasser, Resident Farmer (onsite), Resident Gardener, Recreational User, Outdoor Worker and an Offsite Resident Farmer. The RESRAD (Version 6.5) and RESRAD-OFFSITE (Version 2.5) computer codes were used for the peak dose assessments. Deterministic peak dose assessments were performed for all the receptors and a probabilistic dose assessment was performed only for the Offsite Resident Farmer at the request of the DOE-PPPO. In a deterministic analysis, a single input value results in a single output value. In other words, a deterministic analysis uses single parameter values for every variable in the code. By contrast, a probabilistic approach assigns parameter ranges to certain variables, and the code randomly selects the values for each variable from the parameter range each time it calculates the dose (NRC 2006). The receptor scenarios, computer codes and parameter input files were previously used in ORISE 2012. A few modifications were made to the parameter input files as appropriate for this effort. Some of these changes included increasing the time horizon beyond 1,050 years (yr), and using the radionuclide concentrations provided by the DOE-PPPO as inputs into the codes. The deterministic peak doses were evaluated within time horizons of 70 yr (for the Landfill Worker and Trespasser), 1,050 yr, 10,000 yr and 100,000 yr (for the Resident Farmer [onsite], Resident Gardener, Recreational User, Outdoor Worker and Offsite Resident Farmer) at the request of the DOE-PPPO. The time horizons of 10,000 yr and 100,000 yr were used at the request of the DOE-PPPO for informational purposes only. The probabilistic peak of the mean dose assessment was performed for the Offsite Resident Farmer using Technetium-99 (Tc-99) and a time horizon of 1,050 yr. The results of the deterministic analyses indicate that among all receptors and time horizons evaluated, the highest projected dose, 2,700 mrem/yr, occurred for the Resident Farmer (onsite) at 12,773 yr. The exposure pathways contributing to the peak dose are ingestion of plants, external gamma, and ingestion of milk, meat and soil. However, this receptor is considered an implausible receptor. The only receptors considered plausible are the Landfill Worker, Recreational User, Outdoor Worker and the Offsite Resident Farmer. The maximum projected dose among the plausible receptors is 220 mrem/yr for the Outdoor Worker and it occurs at 19,045 yr. The exposure pathways contributing to the dose for this receptor are external gamma and soil ingestion. The results of the probabilistic peak of the mean dose analysis for the Offsite Resident Farmer indicate that the average (arithmetic mean) of the peak of the mean doses for this receptor is 0.98 mrem/yr and it occurs at 1,050 yr. This dose corresponds to Tc-99 within the time horizon of 1,050 yr.

DELIS MALDONADO

2012-06-01T23:59:59.000Z

337

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Released: September, 2008 Released: September, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings* ........................... 3,037 115 397 384 52 1,143 22 354 64 148 357 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 386 19 43 18 11 93 7 137 8 12 38 5,001 to 10,000 .......................... 262 12 35 17 5 83 4 56 6 9 35 10,001 to 25,000 ........................ 407 20 46 44 8 151 3 53 9 19 54 25,001 to 50,000 ........................ 350 15 55 50 9 121 2 34 7 16 42 50,001 to 100,000 ...................... 405 16 57 65 7 158 2 29 6 18 45 100,001 to 200,000 .................... 483 16 62 80 5 195 1 24 Q 31 56 200,001 to 500,000 .................... 361 8 51 54 5 162 1 9 8 19 43 Over 500,000 ............................. 383 8 47 56 3 181 2 12 8 23 43 Principal Building Activity

338

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings ............................. 91.0 33.0 7.2 6.1 7.0 18.7 2.7 5.3 1.0 2.2 7.9 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 99.0 30.7 6.7 2.7 7.1 13.9 7.1 19.9 1.1 1.7 8.2 5,001 to 10,000 .......................... 80.0 30.1 5.5 2.6 6.1 13.6 5.2 8.2 0.8 1.4 6.6 10,001 to 25,000 ........................ 71.0 28.2 4.5 4.1 4.1 14.5 2.3 4.5 0.8 1.6 6.5 25,001 to 50,000 ........................ 79.0 29.9 6.8 5.9 6.3 14.9 1.7 3.9 0.8 1.8 7.1 50,001 to 100,000 ...................... 88.7 31.6 7.6 7.6 6.5 19.6 1.7 3.4 0.7 2.0 8.1 100,001 to 200,000 .................... 104.2 39.1 8.2 8.9 7.9 22.9 1.1 2.9 Q 3.2 8.7 200,001 to 500,000 ....................

339

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings ............................. 91.0 33.0 7.2 6.1 7.0 18.7 2.7 5.3 1.0 2.2 7.9 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 99.0 30.7 6.7 2.7 7.1 13.9 7.1 19.9 1.1 1.7 8.2 5,001 to 10,000 .......................... 80.0 30.1 5.5 2.6 6.1 13.6 5.2 8.2 0.8 1.4 6.6 10,001 to 25,000 ........................ 71.0 28.2 4.5 4.1 4.1 14.5 2.3 4.5 0.8 1.6 6.5 25,001 to 50,000 ........................ 79.0 29.9 6.8 5.9 6.3 14.9 1.7 3.9 0.8 1.8 7.1 50,001 to 100,000 ...................... 88.7 31.6 7.6 7.6 6.5 19.6 1.7 3.4 0.7 2.0 8.1 100,001 to 200,000 .................... 104.2 39.1 8.2 8.9 7.9 22.9 1.1 2.9 Q 3.2 8.7 200,001 to 500,000 ....................

340

Determination of Total Petroleum Hydrocarbons (TPH) Using Total Carbon Analysis  

SciTech Connect

Several methods have been proposed to replace the Freon(TM)-extraction method to determine total petroleum hydrocarbon (TPH) content. For reasons of cost, sensitivity, precision, or simplicity, none of the replacement methods are feasible for analysis of radioactive samples at our facility. We have developed a method to measure total petroleum hydrocarbon content in aqueous sample matrixes using total organic carbon (total carbon) determination. The total carbon content (TC1) of the sample is measured using a total organic carbon analyzer. The sample is then contacted with a small volume of non-pokar solvent to extract the total petroleum hydrocarbons. The total carbon content of the resultant aqueous phase of the extracted sample (TC2) is measured. Total petroleum hydrocarbon content is calculated (TPH = TC1-TC2). The resultant data are consistent with results obtained using Freon(TM) extraction followed by infrared absorbance.

Ekechukwu, A.A.

2002-05-10T23:59:59.000Z

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


341

U.S. Total Exports  

Gasoline and Diesel Fuel Update (EIA)

Babb, MT Havre, MT Port of Morgan, MT Pittsburg, NH Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Sweetgrass, MT Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to India Freeport, TX Sabine Pass, LA Total to Japan Cameron, LA Kenai, AK Sabine Pass, LA Total to Mexico Douglas, AZ Nogales, AZ Calexico, CA Ogilby Mesa, CA Otay Mesa, CA Alamo, TX Clint, TX Del Rio, TX Eagle Pass, TX El Paso, TX Hidalgo, TX McAllen, TX Penitas, TX Rio Bravo, TX Roma, TX Total to Portugal Sabine Pass, LA Total to Russia Total to South Korea Freeport, TX Sabine Pass, LA Total to Spain Cameron, LA Sabine Pass, LA Total to United Kingdom Sabine Pass, LA Period: Monthly Annual

342

A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of  

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

Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year ActualWeather Data Title A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year ActualWeather Data Publication Type Journal Year of Publication 2013 Authors Hong, Tianzhen, Wen-Kuei Chang, and Hung-Wen Lin Keywords Actual meteorological year, Building simulation, Energy use, Peak electricity demand, Typical meteorological year, Weather data Abstract Buildings consume more than one third of the world's total primary energy. Weather plays a unique and significant role as it directly affects the thermal loads and thus energy performance of buildings. The traditional simulated energy performance using Typical Meteorological Year (TMY) weather data represents the building performance for a typical year, but not necessarily the average or typical long-term performance as buildings with different energy systems and designs respond differently to weather changes. Furthermore, the single-year TMY simulations do not provide a range of results that capture yearly variations due to changing weather, which is important for building energy management, and for performing risk assessments of energy efficiency investments. This paper employs large-scale building simulation (a total of 3162 runs) to study the weather impact on peak electricity demand and energy use with the 30-year (1980 to 2009) Actual Meteorological Year (AMY) weather data for three types of office buildings at two design efficiency levels, across all 17 ASHRAE climate zones. The simulated results using the AMY data are compared to those from the TMY3 data to determine and analyze the differences. Besides further demonstration, as done by other studies, that actual weather has a significant impact on both the peak electricity demand and energy use of buildings, the main findings from the current study include: 1) annual weather variation has a greater impact on the peak electricity demand than it does on energy use in buildings; 2) the simulated energy use using the TMY3 weather data is not necessarily representative of the average energy use over a long period, and the TMY3 results can be significantly higher or lower than those from the AMY data; 3) the weather impact is greater for buildings in colder climates than warmer climates; 4) the weather impact on the medium-sized office building was the greatest, followed by the large office and then the small office; and 5) simulated energy savings and peak demand reduction by energy conservation measures using the TMY3 weather data can be significantly underestimated or overestimated. It is crucial to run multi-decade simulations with AMY weather data to fully assess the impact of weather on the long-term performance of buildings, and to evaluate the energy savings potential of energy conservation measures for new and existing buildings from a life cycle perspective.

343

ARM - Field Campaign - Colorado: The Storm Peak Lab Cloud Property  

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

govCampaignsColorado: The Storm Peak Lab Cloud Property Validation govCampaignsColorado: The Storm Peak Lab Cloud Property Validation Experiment (STORMVEX) Campaign Links STORMVEX Website Related Campaigns Colorado: CFH/CMH Deployment to StormVEx 2011.02.01, Mace, AMF Colorado: SP2 Deployment at StormVEx 2010.11.15, Sedlacek, AMF Colorado : Cavity Attenuated Phase Shift 2010.11.15, Massoli, AMF Colorado: Infrared Thermometer (IRT) 2010.11.15, Mace, AMF Colorado: StormVEX Aerosol Size Distribution 2010.11.15, Hallar, AMF Colorado: Direct Measurements of Snowfall 2010.11.15, McCubbin, AMF Colorado: Thunderhead Radiative Flux Analysis Campaign 2010.11.15, Long, AMF Colorado: Ice Nuclei and Cloud Condensation Nuclei Characterization 2010.11.15, Cziczo, AMF Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA.

344

The SECIS instrument on the Lomnicky Peak Observatory  

E-Print Network (OSTI)

Heating mechanisms of the solar corona will be investigated at the high-altitude solar observatory Lomnicky Peak of the Astronomical Institute of SAS (Slovakia) using its mid-size Lyot coronagraph and post-focal instrument SECIS provided by Astronomical Institute of the University of Wroclaw (Poland). The data will be studied with respect to the energy transport and release responsible for heating the solar corona to temperatures of mega-Kelvins. In particular investigations will be focused on detection of possible high-frequency MHD waves in the solar corona. The scientific background of the project, technical details of the SECIS system modified specially for the Lomnicky Peak coronagraph, and inspection of the test data are described in the paper.

Ambroz, J; Rudawy, P; Rybak, J; Phillips, K J H

2010-01-01T23:59:59.000Z

345

Categorical Exclusion for Pinnacle Peak Substation PCB contaminated Electrical  

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

Categorical Exclusion for Pinnacle Peak Substation PCB contaminated Electrical Equipment Removal Project located north of Phoenix, Maricopa County, Arizona RECORD OF CATEGORICAL EXCLUSION DETERMINATION A. Proposed Action: Western proposes drain and dispose of PCB contaminated oil from two bushings, and decontaminate one· bushing and rack, break apart PCB contaminated concrete and excavate PCB contaminated soil at Pinnacle Peak Substation. Western will be use existing access roads and vehicles such as cranes, backhoes, dozers, bucket trucks, crew trucks and pickup trucks to bring personnel and equipment to the work area. This work is necessary to maintain the safety and reliability of the bulk electrical system. The project is located in Maricopa County, Arizona. The attached map shows the

346

Firing Excess Refinery Butane in Peaking Gas Turbines  

E-Print Network (OSTI)

New environmentally-driven regulations for motor gasoline volatility will significantly alter refinery light ends supply/demand balancing. This, in turn, will impact refinery economics. This paper presumes that one outcome will be excess refinery normal butane production, which will reduce refinery normal butane value and price. Explored is an opportunity for a new use for excess refinery normal butane- as a fuel for utility peaking gas turbines which currently fire kerosene and #2 oil. Our paper identifies the fundamental driving forces which are changing refinery butane economics, examines how these forces influence refinery production, and evaluates the potential for using normal butanes as peaking utility gas turbine fuel, especially on the US East Coast.

Pavone, A.; Schreiber, H.; Zwillenberg, M.

1989-09-01T23:59:59.000Z

347

Application of Thermal Storage, Peak Shaving and Cogeneration for Hospitals  

E-Print Network (OSTI)

Energy costs of hospitals can be managed by employing various strategies to control peak electrical demand (KW) while at the same time providing additional security of operation in the event that an equipment failure or a disruption of power from the electric utility occurs. Some electric utilities offer their customers demand (KW) reduction rate incentives. Many hospitals have additional emergency back-up needs for electrical energy. Demand is relatively constant in many hospitals due to high internal loads. These factors coupled with the present competitive alternate fuel market and present opportunities for hospitals to significantly reduce operating costs and provide additional stand-by or back-up electric sources. This paper employs a hospital case study to define and illustrate three energy planning strategies applicable to hospitals. These strategies are peak shaving, thermal storage, cogeneration and/or paralleling with the electric utility.

McClure, J. D.; Estes, J. M.; Estes, M. C.

1987-01-01T23:59:59.000Z

348

Analyses of Magnetic-Field Peak-Exposure Summary Measures  

Science Conference Proceedings (OSTI)

Past emphasis on exposure characterization and analyses for magnetic fields has been on measures of central tendency, such as long-term time-weighted average (TWA) exposure. Past emphasis on exposure characterization and analyses for magnetic fields has been on measures of central tendency such as long-term time-weighted average (TWA) exposure. This report examines peak exposure measures such as the maximum and 99th percentile of measurements during a day. EPRI sponsored this study to enhance industry kn...

2003-11-19T23:59:59.000Z

349

Density Forecasting for Long-Term Peak Electricity Demand  

E-Print Network (OSTI)

Long-term electricity demand forecasting plays an important role in planning for future generation facilities and transmission augmentation. In a long-term context, planners must adopt a probabilistic view of potential peak demand levels. Therefore density forecasts (providing estimates of the full probability distributions of the possible future values of the demand) are more helpful than point forecasts, and are necessary for utilities to evaluate and hedge the financial risk accrued by demand variability and forecasting uncertainty. This paper proposes a new methodology to forecast the density of long-term peak electricity demand. Peak electricity demand in a given season is subject to a range of uncertainties, including underlying population growth, changing technology, economic conditions, prevailing weather conditions (and the timing of those conditions), as well as the general randomness inherent in individual usage. It is also subject to some known calendar effects due to the time of day, day of week, time of year, and public holidays. A comprehensive forecasting solution is described in this paper. First, semi-parametric additive models are used to estimate the relationships between demand and the driver variables, including temperatures, calendar effects and some demographic and economic variables. Then the demand distributions are forecasted by using a mixture of temperature simulation, assumed future economic scenarios, and residual bootstrapping. The temperature simulation is implemented through a new seasonal bootstrapping method with variable blocks. The proposed methodology has been used to forecast the probability distribution of annual and weekly peak electricity demand for South Australia since 2007. The performance of the methodology is evaluated by comparing the forecast results with the actual demand of the summer 2007–2008.

Rob J. Hyndman; Shu Fan

2009-01-01T23:59:59.000Z

350

Wanxiang Silicon Peak Electronics Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Wanxiang Silicon Peak Electronics Co Ltd Wanxiang Silicon Peak Electronics Co Ltd Jump to: navigation, search Name Wanxiang Silicon-Peak Electronics Co Ltd Place Kaihua, Zhejiang Province, China Zip 324300 Sector Solar Product Maker of monocrystalline silicon ingots and wafers and subsidiary of the Wanxiang Group which includes solar cell and module maker Wanxiang Solar. Coordinates 29.140209°, 118.405113° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":29.140209,"lon":118.405113,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

351

Deconvolution of mixed gamma emitters using peak parameters  

SciTech Connect

When evaluating samples containing mixtures of nuclides using gamma spectroscopy the situation sometimes arises where the nuclides present have photon emissions that cannot be resolved by the detector. An example of this is mixtures of {sup 241}Am and plutonium that have L x-ray emissions with slightly different energies which cannot be resolved using a high-purity germanium detector. It is possible to deconvolute the americium L x-rays from those plutonium based on the {sup 241}Am 59.54 keV photon. However, this requires accurate knowledge of the relative emission yields. Also, it often results in high uncertainties in the plutonium activity estimate due to the americium yields being approximately an order of magnitude greater than those for plutonium. In this work, an alternative method of determining the relative fraction of plutonium in mixtures of {sup 241}Am and {sup 239}Pu based on L x-ray peak location and shape parameters is investigated. The sensitivity and accuracy of the peak parameter method is compared to that for conventional peak decovolution.

Gadd, Milan S [Los Alamos National Laboratory; Garcia, Francisco [Los Alamos National Laboratory; Magadalena, Vigil M [Los Alamos National Laboratory

2011-01-14T23:59:59.000Z

352

Application of Building Precooling to Reduce Peak Cooling Requirements  

E-Print Network (OSTI)

A building cooling control strategy was developed and tested for a 1.4 million square foot (130,000 square meter) office building located in Hoffman Estates, IL. The goal of the control strategy was to utilize building thermal mass to limit the peak cooling load for continued building operation in the event of the loss of one of the four central chiller units. The algorithm was first developed and evaluated through simulation and then evaluated through tests on two identical buildings. The east building utilized the existing building control strategy while the west building used the precooling strategy developed for this project. Consistent with simulation predictions, the precooling control strategy successfully limited the peak load to 75 % of the cooling capacity for the west building, while the east building operated at 100 % of capacity. Precooling of the building mass provided an economical alternative to the purchase of an additional chiller unit. The estimated cost of installing an additional chiller was approximately $500,000. Computer models developed for this project also showed that precooling based upon cooling cost minimization could result in savings of approximately $25,000 per month during the peak cooling season. The building model was validated with experimental results and could be used in the development of a cost minimization strategy.

Kevin R. Keeney; James E. Braun, Ph.D.

1997-01-01T23:59:59.000Z

353

K2 Energy Solutions formerly Peak Energy Solutions | Open Energy  

Open Energy Info (EERE)

Energy Solutions formerly Peak Energy Solutions Energy Solutions formerly Peak Energy Solutions Jump to: navigation, search Name K2 Energy Solutions (formerly Peak Energy Solutions) Place Henderson, Nevada Zip 89074 Product Nevada-based designer and fabricator of Lithium Iron Phosphate (LFP) batteries for such applications as EVs, power tools and larger-scale storage. Coordinates 38.83461°, -82.140509° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":38.83461,"lon":-82.140509,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

354

Combinatorial aspects of total positivity  

E-Print Network (OSTI)

In this thesis I study combinatorial aspects of an emerging field known as total positivity. The classical theory of total positivity concerns matrices in which all minors are nonnegative. While this theory was pioneered ...

Williams, Lauren Kiyomi

2005-01-01T23:59:59.000Z

355

Peak Demand Reduction from Pre-Cooling with Zone Temperature Reset in an Office Building  

E-Print Network (OSTI)

Peak Demand Reduction from Pre-Cooling with Zone TemperatureUniversity of California. Peak Demand Reduction from Pre-shifted in time and the peak demand is reduced. The building

Xu, Peng

2010-01-01T23:59:59.000Z

356

Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California  

E-Print Network (OSTI)

Scenario Analysis of Peak Demand Savings for CommercialScenario Analysis of Peak Demand Savings for CommercialThe whole-building peak demand of a commercial building with

Yin, Rongxin

2010-01-01T23:59:59.000Z

357

Peak demand reduction from pre-cooling with zone temperature reset in an office building  

E-Print Network (OSTI)

an Energy-Efficient Economy. Peak Demand Reduction from Pre-No. DE-AC03-76SF00098. Peak Demand Reduction from Pre-shifted in time and the peak demand is reduced. The building

Xu, Peng; Haves, Philip; Piette, Mary Ann; Braun, James

2004-01-01T23:59:59.000Z

358

Extended outages at several nuclear plants led to high outage ...  

U.S. Energy Information Administration (EIA)

Southern California Edison's San Onofre Nuclear ... and Progress's handling of the Crystal River repairs became an issue in the company's recent merger with ...

359

Testing an Ice Storage System for Peak Load Reduction  

Science Conference Proceedings (OSTI)

Ice storage systems allow for the offset of peak building cooling power by allowing the building operator to choose a convenient window for making ice and then using that ice, rather than a traditional cooling system, to provide space cooling. For the past several years, the Electric Power Research Institute (EPRI) has tested the Ice Bear 30, a 30 ton-hour system designed to operate independently of the unitary system. This report describes the testing and its results, based on work performed at a field ...

2011-04-21T23:59:59.000Z

360

Home cogeneration system can augment peak power requirements  

SciTech Connect

The use of internal combustion engines to supplement peak power generation to homeowners is suggested. As in a car heater, internal combustion engines would recover heat from the radiators to heat the house. The IC, inlet and outlet lines, thermostat, muffler (''critical''), induction generator, and reverse power delay are schematicized. Synchronous generators are not recommended. Disadvantages include the potential pollution, high capital cost, and the resistance of homeowners ''acquainted with the problems of owning a car.'' A simple method to determine the economics of home cogeneration is given. Special consideration is paid to the induction generator, and the engine starter.

Krishnan, K.R.

1983-06-01T23:59:59.000Z

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


361

Peak load control energy saving and cycling system  

SciTech Connect

A control system for limiting peak load demand and/or saving electrical energy by cycling the individual loads within an electrical distribution system is described. Electrical power usage in a distribution system is continuously monitored and compared to a pre-set limit. Loads can be added and cycled according to a limit set by the operator. Loads can also be dropped in response to a signal proportional to the electrical power usage in a distribution system within limits defined by the operator.

Burch, J.

1976-10-19T23:59:59.000Z

362

Total correlations and mutual information  

E-Print Network (OSTI)

In quantum information theory it is generally accepted that quantum mutual information is an information-theoretic measure of total correlations of a bipartite quantum state. We argue that there exist quantum states for which quantum mutual information cannot be considered as a measure of total correlations. Moreover, for these states we propose a different way of quantifying total correlations.

Zbigniew Walczak

2008-06-30T23:59:59.000Z

363

Mercury Vapor At Silver Peak Area (Henkle, Et Al., 2005) | Open...  

Open Energy Info (EERE)

Mercury Vapor At Silver Peak Area (Henkle, Et Al., 2005) Exploration Activity Details Location Silver Peak Area Exploration Technique Mercury Vapor Activity Date Usefulness useful...

364

Water Sampling At Silver Peak Area (Henkle, Et Al., 2005) | Open...  

Open Energy Info (EERE)

Water Sampling At Silver Peak Area (Henkle, Et Al., 2005) Exploration Activity Details Location Silver Peak Area Exploration Technique Water Sampling Activity Date Usefulness...

365

Flow Test At Silver Peak Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Flow Test At Silver Peak Area (DOE GTP) Exploration Activity Details Location Silver Peak Area...

366

Density Log at Silver Peak Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Density Log at Silver Peak Area (DOE GTP) Exploration Activity Details...

367

Rock Density At Silver Peak Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

Density At Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Rock Density At Silver Peak Area (DOE GTP) Exploration...

368

2-M Probe At Silver Peak Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

Silver Peak Area (DOE GTP) Exploration Activity Details Location Silver Peak Area Exploration Technique 2-M Probe Activity Date Usefulness not indicated DOE-funding Unknown...

369

Gamma Log At Silver Peak Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Gamma Log At Silver Peak Area (DOE GTP) Exploration Activity Details...

370

Anisotropic Sliding Dynamics, Peak Effect, and Metastability in Stripe Systems  

E-Print Network (OSTI)

A variety of soft and hard condensed matter systems are known to form stripe patterns. Here we use numerical simulations to analyze how such stripe states depin and slide when interacting with a random substrate and with driving in different directions with respect to the orientation of the stripes. Depending on the strength and density of the substrate disorder, we find that there can be pronounced anisotropy in the transport produced by different dynamical flow phases. We also find a disorder-induced "peak effect" similar to that observed for superconducting vortex systems, which is marked by a transition from elastic depinning to a state where the stripe structure fragments or partially disorders at depinning. Under the sudden application of a driving force, we observe pronounced metastability effects similar to those found near the order-disorder transition associated with the peak effect regime for three-dimensional superconducting vortices. The characteristic transient time required for the system to reach a steady state diverges in the region where the flow changes from elastic to disordered. We also find that anisotropy of the flow persists in the presence of thermal disorder when thermally-induced particle hopping along the stripes dominates. The thermal effects can wash out the effects of the quenched disorder, leading to a thermally-induced stripe state. We map out the dynamical phase diagram for this system, and discuss how our results could be explored in electron liquid crystal systems, type-1.5 superconductors, and pattern-forming colloidal assemblies.

C. J. Olson Reichhardt; C. Reichhardt; A. R. Bishop

2010-11-03T23:59:59.000Z

371

Estimation of Lightning Stroke Peak Current as a Function of Peak Electric Field and the Normalized Amplitude of Signal Strength: Corrections and Improvements  

Science Conference Proceedings (OSTI)

The authors have made connections and improvements to published equations relating the peak current and the peak electric field intensity for return strokes of cloud-to-ground lightning. The original published equations were derived from ...

Y. P. Liaw; D. R. Cook; D. L. Sisterson

1996-06-01T23:59:59.000Z

372

Evaluation of potential severe accidents during low power and shutdown operations at Grand Gulf, Unit 1. Volume 5: Analysis of core damage frequency from seismic events for plant operational state 5 during a refueling outage  

SciTech Connect

In 1989 the US Nuclear Regulatory Commission (NRC) initiated an extensive program to examine carefully the potential risks during low-power and shutdown operations. The program included two parallel projects, one at Sandia National Laboratories studying a boiling water reactor (Grand Gulf), and the other at Brookhaven National Laboratory studying a pressurized water reactor (Surry Unit 1). Both the Sandia and Brookhaven projects have examined only accidents initiated by internal plant faults---so-called ``internal initiators.`` This project, which has explored the likelihood of seismic-initiated core damage accidents during refueling outage conditions, is complementary to the internal-initiator analyses at Brookhaven and Sandia. This report covers the seismic analysis at Grand Gulf. All of the many systems modeling assumptions, component non-seismic failure rates, and human effort rates that were used in the internal-initiator study at Grand Gulf have been adopted here, so that the results of the study can be as comparable as possible. Both the Sandia study and this study examine only one shutdown plant operating state (POS) at Grand Gulf, namely POS 5 representing cold shutdown during a refueling outage. This analysis has been limited to work analogous to a level-1 seismic PRA, in which estimates have been developed for the core-damage frequency from seismic events during POS 5. The results of the analysis are that the core-damage frequency for earthquake-initiated accidents during refueling outages in POS 5 is found to be quite low in absolute terms, less than 10{sup {minus}7}/year.

Budnitz, R.J. [Future Resources Associates, Inc., Berkeley, CA (United States); Davis, P.R. [PRD Consulting (United States); Ravindra, M.K.; Tong, W.H. [EQE International, Inc., Irvine, CA (United States)

1994-08-01T23:59:59.000Z

373

Total....................................................................................  

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

5.6 5.6 17.7 7.9 Personal Computers Do Not Use a Personal Computer.................................. 35.5 8.1 5.6 2.5 Use a Personal Computer.............................................. 75.6 17.5 12.1 5.4 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 14.1 10.0 4.0 Laptop Model............................................................. 16.9 3.4 2.1 1.3 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 3.4 2.5 0.9 2 to 15 Hours............................................................. 29.1 7.0 4.8 2.3 16 to 40 Hours........................................................... 13.5 2.8 2.1 0.7 41 to 167 Hours......................................................... 6.3

374

Total...................................................................  

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

15.2 15.2 7.8 1.0 1.2 3.3 1.9 For Two Housing Units............................. 0.9 Q N Q 0.6 N Heat Pump.................................................. 9.2 7.4 0.3 Q 0.7 0.5 Portable Electric Heater............................... 1.6 0.8 Q Q Q 0.3 Other Equipment......................................... 1.9 0.7 Q Q 0.7 Q Fuel Oil........................................................... 7.7 5.5 0.4 0.8 0.9 0.2 Steam or Hot Water System........................ 4.7 2.9 Q 0.7 0.8 N For One Housing Unit.............................. 3.3 2.9 Q Q Q N For Two Housing Units............................. 1.4 Q Q 0.5 0.8 N Central Warm-Air Furnace........................... 2.8 2.4 Q Q Q 0.2 Other Equipment......................................... 0.3 0.2 Q N Q N Wood..............................................................

375

Total...............................................................  

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

Do Not Have Cooling Equipment................. Do Not Have Cooling Equipment................. 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment.............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment............................... 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Air-Conditioning Equipment 1, 2 Central System............................................ 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat Pump.............................. 53.5 9.4 13.6 10.7 7.1 12.7 5.4 14.5 With a Heat Pump................................... 12.3 1.7 2.8 2.8 1.6 3.4 1.0 2.7 Window/Wall Units...................................... 28.9 10.5 8.1 4.5 2.7 3.1 6.7 14.1 1 Unit....................................................... 14.5 5.8 4.3 2.0 1.1 1.3 3.4 7.4 2 Units.....................................................

376

Total.............................................................................  

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

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.4 1.0 0.4 2 Times A Day...................................................... 24.6 5.8 3.5 2.3 Once a Day........................................................... 42.3 10.7 7.8 2.9 A Few Times Each Week...................................... 27.2 5.6 4.0 1.6 About Once a Week.............................................. 3.9 0.9 0.6 0.3 Less Than Once a Week....................................... 4.1 1.1 0.7 0.4 No Hot Meals Cooked........................................... 0.9 Q Q N Conventional Oven Use an Oven......................................................... 109.6 25.3 17.6 7.7 More Than Once a Day..................................... 8.9 1.3 0.8 0.5 Once a Day.......................................................

377

Total...............................................................  

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

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Personal Computers Do Not Use a Personal Computer ........... 35.5 17.1 10.8 4.2 1.8 1.6 10.3 20.6 Use a Personal Computer......................... 75.6 9.6 18.0 16.4 11.3 20.3 6.4 17.9 Number of Desktop PCs 1.......................................................... 50.3 8.3 14.2 11.4 7.2 9.2 5.3 14.2 2.......................................................... 16.2 0.9 2.6 3.7 2.9 6.2 0.8 2.6 3 or More............................................. 9.0 0.4 1.2 1.3 1.2 5.0 0.3 1.1 Number of Laptop PCs 1.......................................................... 22.5 2.2 4.6 4.5 2.9 8.3 1.4 4.0 2.......................................................... 4.0 Q 0.4 0.6 0.4 2.4 Q 0.5 3 or More............................................. 0.7 Q Q Q Q 0.4 Q Q Type of Monitor Used on Most-Used PC Desk-top

378

Total...............................................................  

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

20.6 20.6 25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer ........... 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer......................... 75.6 13.7 17.5 26.6 17.8 Number of Desktop PCs 1.......................................................... 50.3 9.3 11.9 18.2 11.0 2.......................................................... 16.2 2.9 3.5 5.5 4.4 3 or More............................................. 9.0 1.5 2.1 2.9 2.5 Number of Laptop PCs 1.......................................................... 22.5 4.7 4.6 7.7 5.4 2.......................................................... 4.0 0.6 0.9 1.5 1.1 3 or More............................................. 0.7 Q Q Q 0.3 Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 7.9 11.4 15.4 10.2 Flat-panel LCD.................................

379

Total................................................................  

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

111.1 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Do Not Have Space Heating Equipment....... 1.2 0.5 0.3 0.2 Q 0.2 0.3 0.6 Have Main Space Heating Equipment.......... 109.8 26.2 28.5 20.4 13.0 21.8 16.3 37.9 Use Main Space Heating Equipment............ 109.1 25.9 28.1 20.3 12.9 21.8 16.0 37.3 Have Equipment But Do Not Use It.............. 0.8 0.3 0.3 Q Q N 0.4 0.6 Main Heating Fuel and Equipment Natural Gas.................................................. 58.2 12.2 14.4 11.3 7.1 13.2 7.6 18.3 Central Warm-Air Furnace........................ 44.7 7.5 10.8 9.3 5.6 11.4 4.6 12.0 For One Housing Unit........................... 42.9 6.9 10.3 9.1 5.4 11.3 4.1 11.0 For Two Housing Units......................... 1.8 0.6 0.6 Q Q Q 0.4 0.9 Steam or Hot Water System..................... 8.2 2.4 2.5 1.0 1.0 1.3 1.5 3.6 For One Housing Unit...........................

380

Total...........................................................  

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

Q Q Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions)

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


381

Total........................................................................  

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

25.6 25.6 40.7 24.2 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.7 Have Main Space Heating Equipment.................. 109.8 20.5 25.6 40.3 23.4 Use Main Space Heating Equipment.................... 109.1 20.5 25.6 40.1 22.9 Have Equipment But Do Not Use It...................... 0.8 N N Q 0.6 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 18.4 13.6 14.7 Central Warm-Air Furnace................................ 44.7 6.1 16.2 11.0 11.4 For One Housing Unit................................... 42.9 5.6 15.5 10.7 11.1 For Two Housing Units................................. 1.8 0.5 0.7 Q 0.3 Steam or Hot Water System............................. 8.2 4.9 1.6 1.0 0.6 For One Housing Unit................................... 5.1 3.2 1.1 0.4

382

Total...........................................................................  

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

0.6 0.6 15.1 5.5 Do Not Have Cooling Equipment............................. 17.8 4.0 2.4 1.7 Have Cooling Equipment.......................................... 93.3 16.5 12.8 3.8 Use Cooling Equipment........................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it.......................... 1.9 0.3 Q Q Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 6.0 5.2 0.8 Without a Heat Pump........................................... 53.5 5.5 4.8 0.7 With a Heat Pump............................................... 12.3 0.5 0.4 Q Window/Wall Units.................................................. 28.9 10.7 7.6 3.1 1 Unit................................................................... 14.5 4.3 2.9 1.4 2 Units.................................................................

383

Total.......................................................................  

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

4.2 4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer ................... 35.5 6.4 2.2 4.2 Use a Personal Computer................................ 75.6 17.8 5.3 12.5 Number of Desktop PCs 1.................................................................. 50.3 11.0 3.4 7.6 2.................................................................. 16.2 4.4 1.3 3.1 3 or More..................................................... 9.0 2.5 0.7 1.8 Number of Laptop PCs 1.................................................................. 22.5 5.4 1.5 3.9 2.................................................................. 4.0 1.1 0.3 0.8 3 or More..................................................... 0.7 0.3 Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)...........................

384

Total....................................................................................  

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

111.1 47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer.................................. 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer.............................................. 75.6 30.3 12.5 18.1 14.7 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 22.9 9.8 14.1 11.9 Laptop Model............................................................. 16.9 7.4 2.7 4.0 2.9 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 5.7 1.8 2.9 3.2 2 to 15 Hours............................................................. 29.1 11.9 5.1 6.5 5.7 16 to 40 Hours........................................................... 13.5 5.5 2.5 3.3 2.2 41 to 167 Hours.........................................................

385

Total........................................................................  

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

7.1 7.1 19.0 22.7 22.3 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.2 Q Have Main Space Heating Equipment.................. 109.8 46.3 18.9 22.5 22.1 Use Main Space Heating Equipment.................... 109.1 45.6 18.8 22.5 22.1 Have Equipment But Do Not Use It...................... 0.8 0.7 Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 27.0 11.9 14.9 4.3 Central Warm-Air Furnace................................ 44.7 19.8 8.6 12.8 3.6 For One Housing Unit................................... 42.9 18.8 8.3 12.3 3.5 For Two Housing Units................................. 1.8 1.0 0.3 0.4 Q Steam or Hot Water System............................. 8.2 4.4 2.1 1.4 0.3 For One Housing Unit................................... 5.1 2.1 1.6 1.0

386

Total........................................................................  

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

15.1 15.1 5.5 Do Not Have Space Heating Equipment............... 1.2 Q Q Q Have Main Space Heating Equipment.................. 109.8 20.5 15.1 5.4 Use Main Space Heating Equipment.................... 109.1 20.5 15.1 5.4 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 9.1 2.3 Central Warm-Air Furnace................................ 44.7 6.1 5.3 0.8 For One Housing Unit................................... 42.9 5.6 4.9 0.7 For Two Housing Units................................. 1.8 0.5 0.4 Q Steam or Hot Water System............................. 8.2 4.9 3.6 1.3 For One Housing Unit................................... 5.1 3.2 2.2 1.0 For Two Housing Units.................................

387

Total.................................................................  

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

49.2 49.2 15.1 15.6 11.1 7.0 5.2 8.0 Have Cooling Equipment............................... 93.3 31.3 15.1 15.6 11.1 7.0 5.2 8.0 Use Cooling Equipment................................ 91.4 30.4 14.6 15.4 11.1 6.9 5.2 7.9 Have Equipment But Do Not Use it............... 1.9 1.0 0.5 Q Q Q Q Q Do Not Have Cooling Equipment................... 17.8 17.8 N N N N N N Air-Conditioning Equipment 1, 2 Central System............................................. 65.9 3.9 15.1 15.6 11.1 7.0 5.2 8.0 Without a Heat Pump................................ 53.5 3.5 12.9 12.7 8.6 5.5 4.2 6.2 With a Heat Pump..................................... 12.3 0.4 2.2 2.9 2.5 1.5 1.0 1.8 Window/Wall Units........................................ 28.9 27.5 0.5 Q 0.3 Q Q Q 1 Unit......................................................... 14.5 13.5 0.3 Q Q Q N Q 2 Units.......................................................

388

Total........................................................................  

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

7.1 7.1 7.0 8.0 12.1 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.2 Have Main Space Heating Equipment.................. 109.8 7.1 6.8 7.9 11.9 Use Main Space Heating Equipment.................... 109.1 7.1 6.6 7.9 11.4 Have Equipment But Do Not Use It...................... 0.8 N Q N 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 3.8 0.4 3.8 8.4 Central Warm-Air Furnace................................ 44.7 1.8 Q 3.1 6.0 For One Housing Unit................................... 42.9 1.5 Q 3.1 6.0 For Two Housing Units................................. 1.8 Q N Q Q Steam or Hot Water System............................. 8.2 1.9 Q Q 0.2 For One Housing Unit................................... 5.1 0.8 Q N Q For Two Housing Units.................................

389

Total........................................................................  

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

5.6 5.6 17.7 7.9 Do Not Have Space Heating Equipment............... 1.2 Q Q N Have Main Space Heating Equipment.................. 109.8 25.6 17.7 7.9 Use Main Space Heating Equipment.................... 109.1 25.6 17.7 7.9 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 18.4 13.1 5.3 Central Warm-Air Furnace................................ 44.7 16.2 11.6 4.7 For One Housing Unit................................... 42.9 15.5 11.0 4.5 For Two Housing Units................................. 1.8 0.7 0.6 Q Steam or Hot Water System............................. 8.2 1.6 1.2 0.4 For One Housing Unit................................... 5.1 1.1 0.9 Q For Two Housing Units.................................

390

Total...........................................................................  

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

4.2 4.2 7.6 16.6 Do Not Have Cooling Equipment............................. 17.8 10.3 3.1 7.3 Have Cooling Equipment.......................................... 93.3 13.9 4.5 9.4 Use Cooling Equipment........................................... 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it.......................... 1.9 1.0 Q 0.8 Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat Pump........................................... 53.5 8.7 3.2 5.5 With a Heat Pump............................................... 12.3 1.7 0.7 1.0 Window/Wall Units.................................................. 28.9 3.6 0.6 3.0 1 Unit................................................................... 14.5 2.9 0.5 2.4 2 Units.................................................................

391

Total...........................................................  

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

Q Q Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005

392

Total....................................................................................  

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

Personal Computers Personal Computers Do Not Use a Personal Computer.................................. 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer.............................................. 75.6 26.6 14.5 4.1 7.9 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 20.5 11.0 3.4 6.1 Laptop Model............................................................. 16.9 6.1 3.5 0.7 1.9 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 5.0 2.6 1.0 1.3 2 to 15 Hours............................................................. 29.1 10.3 5.9 1.6 2.9 16 to 40 Hours........................................................... 13.5 4.1 2.3 0.6 1.2 41 to 167 Hours.........................................................

393

Total..............................................................  

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

,171 ,171 1,618 1,031 845 630 401 Census Region and Division Northeast................................................... 20.6 2,334 1,664 562 911 649 220 New England.......................................... 5.5 2,472 1,680 265 1,057 719 113 Middle Atlantic........................................ 15.1 2,284 1,658 670 864 627 254 Midwest...................................................... 25.6 2,421 1,927 1,360 981 781 551 East North Central.................................. 17.7 2,483 1,926 1,269 999 775 510 West North Central................................. 7.9 2,281 1,930 1,566 940 796 646 South.......................................................... 40.7 2,161 1,551 1,295 856 615 513 South Atlantic......................................... 21.7 2,243 1,607 1,359 896 642 543 East South Central.................................

394

Total.........................................................................................  

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

..... ..... 111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer...................................... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer.................................................. 75.6 4.2 5.0 5.3 9.0 Most-Used Personal Computer Type of PC Desk-top Model............................................................. 58.6 3.2 3.9 4.0 6.7 Laptop Model................................................................. 16.9 1.0 1.1 1.3 2.4 Hours Turned on Per Week Less than 2 Hours......................................................... 13.6 0.7 0.9 0.9 1.4 2 to 15 Hours................................................................. 29.1 1.7 2.1 1.9 3.4 16 to 40 Hours............................................................... 13.5 0.9 0.9 0.9 1.8 41 to 167 Hours.............................................................

395

Total.............................................................................  

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

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 2.6 0.7 1.9 2 Times A Day...................................................... 24.6 6.6 2.0 4.6 Once a Day........................................................... 42.3 8.8 2.9 5.8 A Few Times Each Week...................................... 27.2 4.7 1.5 3.1 About Once a Week.............................................. 3.9 0.7 Q 0.6 Less Than Once a Week....................................... 4.1 0.7 0.3 0.4 No Hot Meals Cooked........................................... 0.9 0.2 Q Q Conventional Oven Use an Oven......................................................... 109.6 23.7 7.5 16.2 More Than Once a Day..................................... 8.9 1.7 0.4 1.3 Once a Day.......................................................

396

Total..............................................................................  

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

0.7 0.7 21.7 6.9 12.1 Do Not Have Cooling Equipment................................ 17.8 1.4 0.8 0.2 0.3 Have Cooling Equipment............................................. 93.3 39.3 20.9 6.7 11.8 Use Cooling Equipment.............................................. 91.4 38.9 20.7 6.6 11.7 Have Equipment But Do Not Use it............................. 1.9 0.5 Q Q Q Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 32.1 17.6 5.2 9.3 Without a Heat Pump.............................................. 53.5 23.2 10.9 3.8 8.4 With a Heat Pump................................................... 12.3 9.0 6.7 1.4 0.9 Window/Wall Units..................................................... 28.9 8.0 3.4 1.7 2.9 1 Unit......................................................................

397

Total....................................................................  

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

14.7 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Household Size 1 Person.......................................................... 30.0 4.6 2.5 3.7 3.2 5.4 5.5 3.7 1.6 2 Persons......................................................... 34.8 4.3 1.9 4.4 4.1 5.9 5.3 5.5 3.4 3 Persons......................................................... 18.4 2.5 1.3 1.7 1.9 2.9 3.5 2.8 1.6 4 Persons......................................................... 15.9 1.9 0.8 1.5 1.6 3.0 2.5 3.1 1.4 5 Persons......................................................... 7.9 0.8 0.4 1.0 1.1 1.2 1.1 1.5 0.9 6 or More Persons........................................... 4.1 0.5 0.3 0.3 0.6 0.5 0.7 0.8 0.4 2005 Annual Household Income Category Less than $9,999............................................. 9.9 1.9 1.1 1.3 0.9 1.7 1.3 1.1 0.5 $10,000 to $14,999..........................................

398

Total....................................................................................  

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

25.6 25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer.............................................. 75.6 13.7 17.5 26.6 17.8 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 10.4 14.1 20.5 13.7 Laptop Model............................................................. 16.9 3.3 3.4 6.1 4.1 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 2.4 3.4 5.0 2.9 2 to 15 Hours............................................................. 29.1 5.2 7.0 10.3 6.6 16 to 40 Hours........................................................... 13.5 3.1 2.8 4.1 3.4 41 to 167 Hours.........................................................

399

Total....................................................................................  

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

4.2 4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.4 2.2 4.2 Use a Personal Computer.............................................. 75.6 17.8 5.3 12.5 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 13.7 4.2 9.5 Laptop Model............................................................. 16.9 4.1 1.1 3.0 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 2.9 0.9 2.0 2 to 15 Hours............................................................. 29.1 6.6 2.0 4.6 16 to 40 Hours........................................................... 13.5 3.4 0.9 2.5 41 to 167 Hours......................................................... 6.3

400

Total..................................................................  

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

33.0 33.0 8.0 3.4 5.9 14.4 1.2 Do Not Have Cooling Equipment..................... 17.8 6.5 1.6 0.9 1.3 2.4 0.2 Have Cooling Equipment................................. 93.3 26.5 6.5 2.5 4.6 12.0 1.0 Use Cooling Equipment.................................. 91.4 25.7 6.3 2.5 4.4 11.7 0.8 Have Equipment But Do Not Use it................. 1.9 0.8 Q Q 0.2 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 14.1 3.6 1.5 2.1 6.4 0.6 Without a Heat Pump.................................. 53.5 12.4 3.1 1.3 1.8 5.7 0.6 With a Heat Pump....................................... 12.3 1.7 0.6 Q 0.3 0.6 Q Window/Wall Units....................................... 28.9 12.4 2.9 1.0 2.5 5.6 0.4 1 Unit.......................................................... 14.5 7.3 1.2 0.5 1.4 3.9 0.2 2 Units.........................................................

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


401

Total....................................................................................  

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

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day................................................. 8.2 3.7 1.6 1.4 1.5 2 Times A Day.............................................................. 24.6 10.8 4.1 4.3 5.5 Once a Day................................................................... 42.3 17.0 7.2 8.7 9.3 A Few Times Each Week............................................. 27.2 11.4 4.7 6.4 4.8 About Once a Week..................................................... 3.9 1.7 0.6 0.9 0.8 Less Than Once a Week.............................................. 4.1 2.2 0.6 0.8 0.5 No Hot Meals Cooked................................................... 0.9 0.4 Q Q Q Conventional Oven Use an Oven................................................................. 109.6 46.2 18.8

402

Total...................................................................  

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

Single-Family Units Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) At Home Behavior Home Used for Business

403

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 2.1 1.8 0.3 Have Cooling Equipment............................................ 93.3 23.5 16.0 7.5 Use Cooling Equipment............................................. 91.4 23.4 15.9 7.5 Have Equipment But Do Not Use it............................ 1.9 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 17.3 11.3 6.0 Without a Heat Pump............................................. 53.5 16.2 10.6 5.6 With a Heat Pump................................................. 12.3 1.1 0.8 0.4 Window/Wall Units.................................................. 28.9 6.6 4.9 1.7 1 Unit..................................................................... 14.5 4.1 2.9 1.2 2 Units...................................................................

404

Total..............................................................................  

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

20.6 20.6 25.6 40.7 24.2 Do Not Have Cooling Equipment................................ 17.8 4.0 2.1 1.4 10.3 Have Cooling Equipment............................................. 93.3 16.5 23.5 39.3 13.9 Use Cooling Equipment.............................................. 91.4 16.3 23.4 38.9 12.9 Have Equipment But Do Not Use it............................. 1.9 0.3 Q 0.5 1.0 Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 6.0 17.3 32.1 10.5 Without a Heat Pump.............................................. 53.5 5.5 16.2 23.2 8.7 With a Heat Pump................................................... 12.3 0.5 1.1 9.0 1.7 Window/Wall Units..................................................... 28.9 10.7 6.6 8.0 3.6 1 Unit......................................................................

405

Total..........................................................  

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

60,000 to 79,999 80,000 or More Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

406

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

Usage Indicators by U.S. Census Region, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators U.S. Census Region Northeast Midwest South West Energy Information...

407

Total..........................................................  

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

Homes Million U.S. Housing Units Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.7...

408

Total..........................................................  

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

Homes Million U.S. Housing Units Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC4.7...

409

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

Self-Reported) City Town Suburbs Rural Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC8.7...

410

Total..........................................................  

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

East North Central West North Central Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

411

Total..........................................................  

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

U.S. Housing Units Home Electronics Usage Indicators Table HC10.12 Home Electronics Usage Indicators by U.S. Census Region, 2005 Housing Units (millions) Energy Information...

412

Total..........................................................  

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

U.S. Housing Units Home Electronics Usage Indicators Table HC8.12 Home Electronics Usage Indicators by UrbanRural Location, 2005 Housing Units (millions) Energy Information...

413

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

7.0 7.7 6.6 Have Equipment But Do Not Use it... 1.9 Q N Q 0.6 Air-Conditioning Equipment 1, 2 Central System......

414

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

Air-Conditioning Equipment 1, 2 Central System... 65.9 47.5 4.0 2.8 7.9 3.7 Without a Heat Pump... 53.5...

415

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

91.4 23.4 15.9 7.5 Have Equipment But Do Not Use it... 1.9 Q Q Q Air-Conditioning Equipment 1, 2 Central System......

416

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

18.0 Have Equipment But Do Not Use it... 1.9 0.9 0.3 0.3 0.4 Air-Conditioning Equipment 1, 2 Central System......

417

Total..........................................................  

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

m... 3.2 0.2 Q 0.1 Telephone and Office Equipment CellMobile Telephone... 84.8 14.9 11.1 3.9 Cordless...

418

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

m... 3.2 0.9 0.7 Q Telephone and Office Equipment CellMobile Telephone... 84.8 19.3 13.2 6.1 Cordless...

419

Total..........................................................  

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

Q 0.5 Q Q Monitor is Turned Off... 0.5 N Q Q Q Q N Q Use of Internet Have Access to Internet Yes... 66.9...

420

Total..........................................................  

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

Four Most Populated States New York Florida Texas California Million U.S. Housing Units Home Electronics Usage Indicators Table HC15.12 Home Electronics Usage Indicators by Four...

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


421

Total  

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

Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending...

422

Total  

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

Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Fuel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending...

423

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer ... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer......

424

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

... 25.8 2.8 5.8 5.5 3.8 7.9 1.4 5.1 Use of Most-Used Ceiling Fan Used All Summer... 18.7 4.2 4.9 4.1 2.1 3.4 2.4 6.3...

425

Total..........................................................  

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

Heating Characteristics Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC5.4 Space Heating...

426

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

at All... 2.9 1.1 0.5 Q 0.4 Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools......

427

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

3.3 Not Used at All... 2.9 0.7 0.5 Q Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools... 54.9...

428

Total..........................................................  

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

3.6 Not Used at All... 2.9 0.8 0.3 0.4 Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools... 54.9...

429

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

1.1 Not Used at All... 2.9 0.4 Q 0.2 Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools... 54.9...

430

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

at All... 2.9 1.4 0.4 0.4 0.7 Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools......

431

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) At Home Behavior Home Used for Business Yes......

432

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

... 34.3 1.2 0.9 2.2 2.9 5.4 7.0 8.2 6.6 Adequacy of Insulation Well Insulated... 29.5 1.5 0.9 2.3 2.7 4.1...

433

Total.............................................................................  

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

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.2 1.0 0.2 2 Times A Day...................................................... 24.6 4.0 2.7 1.2 Once a Day........................................................... 42.3 7.9 5.4 2.5 A Few Times Each Week...................................... 27.2 6.0 4.8 1.2 About Once a Week.............................................. 3.9 0.6 0.5 Q Less Than Once a Week....................................... 4.1 0.6 0.4 Q No Hot Meals Cooked........................................... 0.9 0.3 Q Q Conventional Oven Use an Oven......................................................... 109.6 20.3 14.9 5.4 More Than Once a Day..................................... 8.9 1.4 1.2 0.3 Once a Day.......................................................

434

Total...............................................................  

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

47.1 47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer ........... 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer......................... 75.6 30.3 12.5 18.1 14.7 Number of Desktop PCs 1.......................................................... 50.3 21.1 8.3 10.7 10.1 2.......................................................... 16.2 6.2 2.8 4.1 3.0 3 or More............................................. 9.0 2.9 1.4 3.2 1.6 Number of Laptop PCs 1.......................................................... 22.5 9.1 3.6 6.0 3.8 2.......................................................... 4.0 1.5 0.6 1.3 0.7 3 or More............................................. 0.7 0.3 Q Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 17.7 7.5 10.2 9.6 Flat-panel LCD.................................

435

Total........................................................  

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

111.1 24.5 1,090 902 341 872 780 441 Census Region and Division Northeast............................................. 20.6 6.7 1,247 1,032 Q 811 788 147 New England.................................... 5.5 1.9 1,365 1,127 Q 814 748 107 Middle Atlantic.................................. 15.1 4.8 1,182 978 Q 810 800 159 Midwest................................................ 25.6 4.6 1,349 1,133 506 895 810 346 East North Central............................ 17.7 3.2 1,483 1,239 560 968 842 351 West North Central........................... 7.9 1.4 913 789 329 751 745 337 South................................................... 40.7 7.8 881 752 572 942 873 797 South Atlantic................................... 21.7 4.9 875 707 522 1,035 934 926 East South Central........................... 6.9 0.7 Q Q Q 852 826 432 West South Central..........................

436

Total...............................................................  

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

0.7 0.7 21.7 6.9 12.1 Personal Computers Do Not Use a Personal Computer ........... 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer......................... 75.6 26.6 14.5 4.1 7.9 Number of Desktop PCs 1.......................................................... 50.3 18.2 10.0 2.9 5.3 2.......................................................... 16.2 5.5 3.0 0.7 1.8 3 or More............................................. 9.0 2.9 1.5 0.5 0.8 Number of Laptop PCs 1.......................................................... 22.5 7.7 4.3 1.1 2.4 2.......................................................... 4.0 1.5 0.9 Q 0.4 3 or More............................................. 0.7 Q Q Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 15.4 7.9 2.8 4.8 Flat-panel LCD.................................

437

Total.................................................................  

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

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day.............................. 8.2 2.9 2.5 1.3 0.5 1.0 2.4 4.6 2 Times A Day........................................... 24.6 6.5 7.0 4.3 3.2 3.6 4.8 10.3 Once a Day................................................ 42.3 8.8 9.8 8.7 5.1 10.0 5.0 12.9 A Few Times Each Week........................... 27.2 5.6 7.2 4.7 3.3 6.3 3.2 7.5 About Once a Week................................... 3.9 1.1 1.1 0.6 0.5 0.6 0.4 1.4 Less Than Once a Week............................ 4.1 1.3 1.0 0.9 0.5 0.4 0.7 1.4 No Hot Meals Cooked................................ 0.9 0.5 Q Q Q Q 0.2 0.5 Conventional Oven Use an Oven.............................................. 109.6 26.1 28.5 20.2 12.9 21.8 16.3 37.8 More Than Once a Day..........................

438

Total..................................................................  

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

. . 111.1 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Do Not Have Cooling Equipment..................... 17.8 3.9 1.8 2.2 2.1 3.1 2.6 1.7 0.4 Have Cooling Equipment................................. 93.3 10.8 5.6 10.3 10.4 15.8 16.0 15.6 8.8 Use Cooling Equipment.................................. 91.4 10.6 5.5 10.3 10.3 15.3 15.7 15.3 8.6 Have Equipment But Do Not Use it................. 1.9 Q Q Q Q 0.6 0.4 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 3.7 2.6 6.1 6.8 11.2 13.2 13.9 8.2 Without a Heat Pump.................................. 53.5 3.6 2.3 5.5 5.8 9.5 10.1 10.3 6.4 With a Heat Pump....................................... 12.3 Q 0.3 0.6 1.0 1.7 3.1 3.6 1.7 Window/Wall Units....................................... 28.9 7.3 3.2 4.5 3.7 4.8 3.0 1.9 0.7 1 Unit..........................................................

439

Total..............................................  

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

111.1 86.6 2,720 1,970 1,310 1,941 1,475 821 1,059 944 554 Census Region and Division Northeast.................................... 20.6 13.9 3,224 2,173 836 2,219 1,619 583 903 830 Q New England.......................... 5.5 3.6 3,365 2,154 313 2,634 1,826 Q 951 940 Q Middle Atlantic........................ 15.1 10.3 3,167 2,181 1,049 2,188 1,603 582 Q Q Q Midwest...................................... 25.6 21.0 2,823 2,239 1,624 2,356 1,669 1,336 1,081 961 778 East North Central.................. 17.7 14.5 2,864 2,217 1,490 2,514 1,715 1,408 907 839 553 West North Central................. 7.9 6.4 2,729 2,289 1,924 1,806 1,510 1,085 1,299 1,113 1,059 South.......................................... 40.7 33.0 2,707 1,849 1,563 1,605 1,350 954 1,064 970 685 South Atlantic......................... 21.7 16.8 2,945 1,996 1,695 1,573 1,359 909 1,044 955

440

Total.................................................................................  

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

... ... 111.1 20.6 15.1 5.5 Do Not Have Cooling Equipment................................. 17.8 4.0 2.4 1.7 Have Cooling Equipment............................................. 93.3 16.5 12.8 3.8 Use Cooling Equipment............................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it............................. 1.9 0.3 Q Q Type of Air-Conditioning Equipment 1, 2 Central System.......................................................... 65.9 6.0 5.2 0.8 Without a Heat Pump.............................................. 53.5 5.5 4.8 0.7 With a Heat Pump................................................... 12.3 0.5 0.4 Q Window/Wall Units.................................................... 28.9 10.7 7.6 3.1 1 Unit.......................................................................

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


441

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 8.5 2.7 2.6 4.0 Have Cooling Equipment............................................ 93.3 38.6 16.2 20.1 18.4 Use Cooling Equipment............................................. 91.4 37.8 15.9 19.8 18.0 Have Equipment But Do Not Use it............................ 1.9 0.9 0.3 0.3 0.4 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 25.8 10.9 16.6 12.5 Without a Heat Pump............................................. 53.5 21.2 9.7 13.7 8.9 With a Heat Pump................................................. 12.3 4.6 1.2 2.8 3.6 Window/Wall Units.................................................. 28.9 13.4 5.6 3.9 6.1 1 Unit.....................................................................

442

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 10.3 3.1 7.3 Have Cooling Equipment............................................ 93.3 13.9 4.5 9.4 Use Cooling Equipment............................................. 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it............................ 1.9 1.0 Q 0.8 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat Pump............................................. 53.5 8.7 3.2 5.5 With a Heat Pump................................................. 12.3 1.7 0.7 1.0 Window/Wall Units.................................................. 28.9 3.6 0.6 3.0 1 Unit..................................................................... 14.5 2.9 0.5 2.4 2 Units...................................................................

443

Total..................................................................  

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

78.1 78.1 64.1 4.2 1.8 2.3 5.7 Do Not Have Cooling Equipment..................... 17.8 11.3 9.3 0.6 Q 0.4 0.9 Have Cooling Equipment................................. 93.3 66.8 54.7 3.6 1.7 1.9 4.8 Use Cooling Equipment.................................. 91.4 65.8 54.0 3.6 1.7 1.9 4.7 Have Equipment But Do Not Use it................. 1.9 1.1 0.8 Q N Q Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 51.7 43.9 2.5 0.7 1.6 3.1 Without a Heat Pump.................................. 53.5 41.1 34.8 2.1 0.5 1.2 2.6 With a Heat Pump....................................... 12.3 10.6 9.1 0.4 Q 0.3 0.6 Window/Wall Units....................................... 28.9 16.5 12.0 1.3 1.0 0.4 1.7 1 Unit.......................................................... 14.5 7.2 5.4 0.5 0.2 Q 0.9 2 Units.........................................................

444

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 1.4 0.8 0.2 0.3 Have Cooling Equipment............................................ 93.3 39.3 20.9 6.7 11.8 Use Cooling Equipment............................................. 91.4 38.9 20.7 6.6 11.7 Have Equipment But Do Not Use it............................ 1.9 0.5 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 32.1 17.6 5.2 9.3 Without a Heat Pump............................................. 53.5 23.2 10.9 3.8 8.4 With a Heat Pump................................................. 12.3 9.0 6.7 1.4 0.9 Window/Wall Units.................................................. 28.9 8.0 3.4 1.7 2.9 1 Unit.....................................................................

445

Total........................................................................  

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

4.2 4.2 7.6 16.6 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.7 Have Main Space Heating Equipment.................. 109.8 23.4 7.5 16.0 Use Main Space Heating Equipment.................... 109.1 22.9 7.4 15.4 Have Equipment But Do Not Use It...................... 0.8 0.6 Q 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 14.7 4.6 10.1 Central Warm-Air Furnace................................ 44.7 11.4 4.0 7.4 For One Housing Unit................................... 42.9 11.1 3.8 7.3 For Two Housing Units................................. 1.8 0.3 Q Q Steam or Hot Water System............................. 8.2 0.6 0.3 0.3 For One Housing Unit................................... 5.1 0.4 0.2 0.1 For Two Housing Units.................................

446

Total..............................................................  

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

Do Not Have Cooling Equipment................ Do Not Have Cooling Equipment................ 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment.............................. 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Type of Air-Conditioning Equipment 1, 2 Central System.......................................... 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat Pump.............................. 53.5 9.4 13.6 10.7 7.1 12.7 5.4 14.5 With a Heat Pump................................... 12.3 1.7 2.8 2.8 1.6 3.4 1.0 2.7 Window/Wall Units................................... 28.9 10.5 8.1 4.5 2.7 3.1 6.7 14.1 1 Unit...................................................... 14.5 5.8 4.3 2.0 1.1 1.3 3.4 7.4 2 Units....................................................

447

Evaluation of potential severe accidents during low power and shutdown operations at Grand Gulf, Unit 1. Analysis of core damage frequency from internal events for plant operational state 5 during a refueling outage. Internal events appendices K to M  

Science Conference Proceedings (OSTI)

This report provides supporting documentation for various tasks associated with the performance of the probabilistic risk assessment for Plant Operational State 5 (approximately Cold Shutdown as defined by Grand Gulf Technical Specifications) during a refueling outage at Grand Gulf, Unit 1 as documented in Volume 2, Part 1 of NUREG/CR-6143. The report contains the following appendices: K - HEP Locator Files; L - Supporting Information for the Plant Damage State Analysis; M - Summary of Results from the Coarse Screening Analysis - Phase 1A.

Forester, J.; Yakle, J.; Walsh, B. [Science Applications International Corp., Albuquerque, NM (United States); Darby, J. [Science and Engineering Associates, Inc., Albuquerque, NM (United States); Whitehead, D.; Staple, B.; Brown, T. [Sandia National Labs., Albuquerque, NM (United States)

1994-07-01T23:59:59.000Z

448

10-MW GTO converter for battery peaking service  

SciTech Connect

A bidirectional 18-pulse voltage source converter utilizing gate turn-off thyristors (GTO's) is described. The converter, which is rated 10 MVA, was placed in service in early 1988 to connect an energy storage battery to a utility grid. The converter is rated and controlled to operate in all four quadrants (discharge, charge, leading vars, or lagging vars) at the full 10-MVA rating. It is capable of independent rapid control of real and reactive power with a transient response of 16 ms to changes in commanded value of real or reactive power. Thus it is usable as a reactive power controller (static var control), voltage control, frequency control, power system stabilizer, or as a real power peaking station. For use as a reactive power controller only, no battery would be needed. The design, construction, control, and application of the converter are described, and performance data taken at factory power test and at the installation are given.

Walker, L.H. (Drive Development Engineering, Drive Systems, General Electric Co., Salem, VA (US))

1990-01-01T23:59:59.000Z

449

Implications of "peak oil" for atmospheric CO2 and climate  

E-Print Network (OSTI)

Peaking of global oil production may have a large effect on future atmospheric CO2 amount and climate change, depending upon choices made for subsequent energy sources. We suggest that, if estimates of oil and gas reserves by the Energy Information Administration are realistic, it is feasible to keep atmospheric CO2 from exceeding approximately 450 ppm, provided that future exploitation of the huge reservoirs of coal and unconventional fossil fuels incorporates carbon capture and sequestration. Existing coal-fired power plants, without sequestration, must be phased out before mid-century to achieve this limit on atmospheric CO2. We also suggest that it is important to "stretch" oil reserves via energy efficiency, thus avoiding the need to extract liquid fuels from coal or unconventional fossil fuels. We argue that a rising price on carbon emissions is probably needed to keep CO2 beneath the 450 ppm ceiling.

Kharecha, P A

2007-01-01T23:59:59.000Z

450

Idle Operating Total Stream Day  

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

3 3 Idle Operating Total Stream Day Barrels per Idle Operating Total Calendar Day Barrels per Atmospheric Crude Oil Distillation Capacity Idle Operating Total Operable Refineries Number of State and PAD District a b b 11 10 1 1,293,200 1,265,200 28,000 1,361,700 1,329,700 32,000 ............................................................................................................................................... PAD District I 1 1 0 182,200 182,200 0 190,200 190,200 0 ................................................................................................................................................................................................................................................................................................ Delaware......................................

451

China Total Cloud Amount Trends  

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

Trends in Total Cloud Amount Over China DOI: 10.3334CDIACcli.008 data Data image Graphics Investigator Dale P. Kaiser Carbon Dioxide Information Analysis Center, Environmental...

452

Petrology, geochronology, and chemical evolution of the Twin Peaks Rhyolite Domes, Utah  

DOE Green Energy (OSTI)

Two distinct sequences of silicic volcanism at the Twin Peaks volcanic field, Millard County, Utah, spanned periods from 2.74 +- .10 to 2.54 +- .09 m.y. and 2.43 +- .08 to 2.35 +- .08 m.y., and produced a total exposed volume of 4 km/sup 3/ of rhyolites and volcanoclastics. Wet chemical, x-ray fluorescence, microprobe, atomic absorption, and neutron activation methods have been employed to obtain a wide range of chemical data on whole rock and mineral separate samples. Calculated distribution coefficients are comparable to previously published values for high silica rocks. Each sequence is characterized by a systematic trend from < 72% to > 76% SiO/sub 2/. Accompanying this increase in SiO/sub 2/ over time are increases in Rb, Y, Sb, Cs, U, Th, HREE and decreases in Mg, Co, Fe, Sr, Ba, and LREE. Decreases in temperature and fO/sub 2/ and an increase in fH/sub 2/O are also indicated. These trends are very similar to gradients observed in ash flow tuffs erupted instantaneously from compositionally zoned magma chambers. Chemical evolution at Twin Peaks was dominated by the same mechanism of liquid state differentiation which produce the compositional zonation in larger silicic magma chambers.

Crecraft, H.R.; Nash, W.P.; Evans, S.H. Jr.

1980-05-01T23:59:59.000Z

453

ON THERMALIZATION IN GAMMA-RAY BURST JETS AND THE PEAK ENERGIES OF PHOTOSPHERIC SPECTRA  

Science Conference Proceedings (OSTI)

The low-energy spectral slopes of the prompt emission of most gamma-ray bursts (GRBs) are difficult to reconcile with radiatively efficient optically thin emission models irrespective of the radiation mechanism. An alternative is to ascribe the radiation around the spectral peak to a thermalization process occurring well inside the Thomson photosphere. This quasi-thermal spectrum can evolve into the observed non-thermal shape by additional energy release at moderate to small Thomson optical depths, which can readily give rise to the hard spectral tail. The position of the spectral peak is determined by the temperature and Lorentz factor of the flow in the thermalization zone, where the total number of photons carried by the jet is established. To reach thermalization, dissipation alone is not sufficient and photon generation requires an efficient emission/absorption process in addition to scattering. We perform a systematic study of all relevant photon production mechanisms searching for possible conditions in which thermalization can take place. We find that a significant fraction of the available energy should be dissipated at intermediate radii, {approx}10{sup 10} to a few Multiplication-Sign 10{sup 11} cm, and the flow there should be relatively slow: the bulk Lorentz factor could not exceed a few tens for all but the most luminous bursts with the highest E {sub pk} values. The least restrictive constraint for successful thermalization, {Gamma} {approx}bursts. We examine the implications of these results to different GRB photospheric emission models.

Vurm, Indrek; Piran, Tsvi [Racah Institute of Physics, Hebrew University of Jerusalem, Jerusalem 91904 (Israel)] [Racah Institute of Physics, Hebrew University of Jerusalem, Jerusalem 91904 (Israel); Lyubarsky, Yuri, E-mail: indrek.vurm@gmail.com [Physics Department, Ben-Gurion University, P.O. Box 653, Beer-Sheva 84105 (Israel)] [Physics Department, Ben-Gurion University, P.O. Box 653, Beer-Sheva 84105 (Israel)

2013-02-20T23:59:59.000Z

454

Duct Leakage Impacts on Airtightness, Infiltration, and Peak Electrical Demand in Florida Homes  

E-Print Network (OSTI)

Testing for duct leakage was done in 155 homes. Tracer gas tests found that infiltration rates were three times greater when the air handler was operating than when it was off. Infiltration averaged 0.85 air changes per hour (ach) with the air handler (AH) operating continuously and 0.29 ach with the AH off. Return leaks were found to average 10.3% of AH total flow. House airtightness, in 90 of these homes, determined by blower door testing, averaged 12.58 air changes per hour at 50 Pascals (ACHSO). When the duct registers were sealed, ACHSO decreased to 11.04, indicating that 12.2% of the house leaks were in the duct system. Duct leaks have a dramatic impact upon peak electrical demand. Based on theoretical analysis, a fifteen percent return leak from the attic can increase cooling electrical demand by 100%. Duct repairs in a typical. electrically heated Florida home reduce winter peak demand by about 1.6 kW per house at about one-sixth the cost of building new electrical generation capacity.

Cummings, J. B.; Tooley, J. J.; Moyer, N.

1990-01-01T23:59:59.000Z

455

PEAKING OF WORLD OIL PRODUCTION: IMPACTS, MITIGATION, & RISK MANAGEMENT  

E-Print Network (OSTI)

sands are an important unconventional energy re- source. The total inplace volume of heavy-oil is muchFrequency dependent elastic properties and attenuation in heavy-oil sands: comparison between mea) properties of heavy-oil sands over a range of frequencies (2 - 2000Hz) covering the seismic bandwidth

Laughlin, Robert B.

456

total energy | OpenEI  

Open Energy Info (EERE)

total energy total energy Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 1, and contains only the reference case. The dataset uses quadrillion BTUs, and quantifies the energy prices using U.S. dollars. The data is broken down into total production, imports, exports, consumption, and prices for energy types. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO consumption EIA export import production reference case total energy Data application/vnd.ms-excel icon AEO2011: Total Energy Supply, Disposition, and Price Summary - Reference Case (xls, 112.8 KiB) Quality Metrics Level of Review Peer Reviewed

457

Silver Peak Innovative Exploration Project Geothermal Project | Open Energy  

Open Energy Info (EERE)

Innovative Exploration Project Geothermal Project Innovative Exploration Project Geothermal Project Jump to: navigation, search Last modified on July 22, 2011. Project Title Silver Peak Innovative Exploration Project Project Type / Topic 1 Recovery Act: Geothermal Technologies Program Project Type / Topic 2 Validation of Innovative Exploration Technologies Project Description The scope of this three phase project includes tasks to validate a variety of innovative exploration and drilling technologies which aim to accurately characterize the geothermal site and thereby reduce project risk. Phase 1 exploration will consist of two parts: 1) surface and near surface investigations and 2) subsurface geophysical surveys and modeling. The first part of Phase 1 includes: a hyperspectral imaging survey (to map thermal anomalies and geothermal indicator minerals), shallow temperature probe measurements, and drilling of temperature gradient wells to depths of 1000 feet. In the second part of Phase 1, 2D & 3D geophysical modeling and inversion of gravity, magnetic, and magnetotelluric datasets will be used to image the subsurface. This effort will result in the creation of a 3D model composed of structural, geological, and resistivity components. The 3D model will then be combined with the temperature data to create an integrated model that will be used to prioritize drill target locations.

458

Dick Cheney, Peak Oil and the Final Count Down  

E-Print Network (OSTI)

In the April 2004 issue of the magazine the Middle East I found a statement that Vice-President Dick Cheney had made in a speech at the London Institute of Petroleum Autumn lunch in 1999 when he was Chairman of Halliburton. A key passage from his speech was: “That means by 2010 we will need on the order of an additional fifty million barrels a day.” It suggested that he was fully aware of the issue of peak oil. A full text of the talk had been available on the website of the Institute of Petroleum, but has now been removed (wwww.petroleum.co.uk/speeches.htm). Nevertheless, further research did bring to light a printed version, dated 24.08.00, as follows: Dick Cheney: “From the standpoint of the oil industry obviously- and I'll talk a little later on about gas- for over a hundred years we as an industry have had to deal with the pesky problem that once you find oil and pump it out of the ground you've got to turn around and find more or go out of business. Producing oil is obviously a self-depleting activity. Every year you've got to find and develop reserves equal to your output just to stand still, just to stay even. This is as true for companies as well in the broader

Kjell Aleklett

2004-01-01T23:59:59.000Z

459

Residential implementation of critical-peak pricing ofelectricity  

SciTech Connect

This paper investigates how critical-peak pricing (CPP)affects households with different usage and income levels, with the goalof informing policy makers who are considering the implementation of CPPtariffs in the residential sector. Using a subset of data from theCalifornia Statewide Pricing Pilot of 2003-2004, average load changeduring summer events, annual percent bill change, and post-experimentsatisfaction ratings are calculated across six customer segments,categorized by historical usage and income levels. Findings show thathigh-use customers respond significantly more in kW reduction than dolow-use customers, while low-use customers save significantly more inpercentage reduction of annual electricity bills than do high-usecustomers results that challenge the strategy of targeting only high-usecustomers for CPP tariffs. Across income levels, average load and billchanges were statistically indistinguishable, as were satisfaction ratesresults that are compatible with a strategy of full-scale implementationof CPP rates in the residential sector. Finally, the high-use customersearning less than $50,000 annually were the most likely of the groups tosee bill increases about 5 percent saw bill increases of 10 percent ormore suggesting that any residential CPP implementation might considertargeting this customer group for increased energy efficiencyefforts.

Herter, Karen

2006-06-29T23:59:59.000Z

460

Fracture Permeability Evolution in Desert Peak Quartz Monzonite  

SciTech Connect

Fracture flow experiments are being conducted on quartz monzonite core from the Desert Peak East EGS site, Churchill County, Nevada. The flow experiments are conducted at temperatures of 167-169 C and 5.5 MPa confining pressure through artificial fractures. Two injection fluids, a saline solution and a silica-bearing solution, have been used to date. Flow rates are typically 0.02 mL/min, but other rates have been used. The fracture surfaces are characterized with a contact profilometer. The profilometry data demonstrate that it is possible to fabricate statistically similar fracture surfaces and enable us to map aperture variations, which we use in numerical simulations. Effluent samples are collected for chemical analysis. The fluid pressure gradient is measured across the specimen and effective hydraulic apertures are calculated. The experiments show a reduction in permeability over time for both injection fluids, but a more rapid loss of permeability was observed for the silica-bearing solution. The calculated hydraulic aperture is observed to decrease by 17% for the saline solution and 75% for the silica-bearing fluid, respectively. Electrical resistivity measurements, which are sensitive to the ionic content of the pore fluid, provide additional evidence of fluid-rock interactions.

Carlson, S R; Roberts, J J; Detwiler, R L; Viani, B E; Roberts, S K

2005-05-10T23:59:59.000Z

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


461

U.S. Total Exports  

Annual Energy Outlook 2012 (EIA)

Springs, VT U.S. Pipeline Total from Mexico Ogilby, CA Otay Mesa, CA Galvan Ranch, TX LNG Imports from Algeria LNG Imports from Australia LNG Imports from Brunei LNG Imports...

462

Nuclear Hydrogen for Peak Electricity Production and Spinning Reserve  

Science Conference Proceedings (OSTI)

Nuclear energy can be used to produce hydrogen. The key strategic question is this: ''What are the early markets for nuclear hydrogen?'' The answer determines (1) whether there are incentives to implement nuclear hydrogen technology today or whether the development of such a technology could be delayed by decades until a hydrogen economy has evolved, (2) the industrial partners required to develop such a technology, and (3) the technological requirements for the hydrogen production system (rate of production, steady-state or variable production, hydrogen purity, etc.). Understanding ''early'' markets for any new product is difficult because the customer may not even recognize that the product could exist. This study is an initial examination of how nuclear hydrogen could be used in two interconnected early markets: the production of electricity for peak and intermediate electrical loads and spinning reserve for the electrical grid. The study is intended to provide an initial description that can then be used to consult with potential customers (utilities, the Electric Power Research Institute, etc.) to better determine the potential real-world viability of this early market for nuclear hydrogen and provide the starting point for a more definitive assessment of the concept. If this set of applications is economically viable, it offers several unique advantages: (1) the market is approximately equivalent in size to the existing nuclear electric enterprise in the United States, (2) the entire market is within the utility industry and does not require development of an external market for hydrogen or a significant hydrogen infrastructure beyond the utility site, (3) the technology and scale match those of nuclear hydrogen production, (4) the market exists today, and (5) the market is sufficient in size to justify development of nuclear hydrogen production techniques independent of the development of any other market for hydrogen. These characteristics make it an ideal early market for nuclear hydrogen.

Forsberg, C.W.

2005-01-20T23:59:59.000Z

463

Peak CO2? China's Emissions Trajectories to 2050  

SciTech Connect

As a result of soaring energy demand from a staggering pace of economic growth and the related growth of energy-intensive industry, China overtook the United States to become the world's largest contributor to CO{sub 2} emissions in 2007. At the same time, China has taken serious actions to reduce its energy and carbon intensity by setting both short-term energy intensity reduction goal for 2006 to 2010 as well as long-term carbon intensity reduction goal for 2020. This study focuses on a China Energy Outlook through 2050 that assesses the role of energy efficiency policies in transitioning China to a lower emission trajectory and meeting its intensity reduction goals. In the past years, LBNL has established and significantly enhanced the China End-Use Energy Model based on the diffusion of end-use technologies and other physical drivers of energy demand. This model presents an important new approach for helping understand China's complex and dynamic drivers of energy consumption and implications of energy efficiency policies through scenario analysis. A baseline ('Continued Improvement Scenario') and an alternative energy efficiency scenario ('Accelerated Improvement Scenario') have been developed to assess the impact of actions already taken by the Chinese government as well as planned and potential actions, and to evaluate the potential for China to control energy demand growth and mitigate emissions. It is a common belief that China's CO{sub 2} emissions will continue to grow throughout this century and will dominate global emissions. The findings from this research suggest that this will not likely be the case because of saturation effects in appliances, residential and commercial floor area, roadways, railways, fertilizer use, and urbanization will peak around 2030 with slowing population growth. The baseline and alternative scenarios also demonstrate that the 2020 goals can be met and underscore the significant role that policy-driven energy efficiency improvements will play in carbon mitigation along with a decarbonized power supply through greater renewable and non-fossil fuel generation.

Zhou, Nan; Fridley, David G.; McNeil, Michael; Zheng, Nina; Ke, Jing; Levine, Mark

2011-05-01T23:59:59.000Z

464

Back-Up/ Peak Shaving Fuel Cell System  

SciTech Connect

This Final Report covers the work executed by Plug Power from 8/11/03 – 10/31/07 statement of work for Topic 2: advancing the state of the art of fuel cell technology with the development of a new generation of commercially viable, stationary, Back-up/Peak-Shaving fuel cell systems, the GenCore II. The Program cost was $7.2 M with the Department of Energy share being $3.6M and Plug Power’s share being $3.6 M. The Program started in August of 2003 and was scheduled to end in January of 2006. The actual program end date was October of 2007. A no cost extension was grated. The Department of Energy barriers addressed as part of this program are: Technical Barriers for Distributed Generation Systems: o Durability o Power Electronics o Start up time Technical Barriers for Fuel Cell Components: o Stack Material and Manufacturing Cost o Durability o Thermal and water management Background The next generation GenCore backup fuel cell system to be designed, developed and tested by Plug Power under the program is the first, mass-manufacturable design implementation of Plug Power’s GenCore architected platform targeted for battery and small generator replacement applications in the telecommunications, broadband and UPS markets. The next generation GenCore will be a standalone, H2 in-DC-out system. In designing the next generation GenCore specifically for the telecommunications market, Plug Power is teaming with BellSouth Telecommunications, Inc., a leading industry end user. The final next generation GenCore system is expected to represent a market-entry, mass-manufacturable and economically viable design. The technology will incorporate: • A cost-reduced, polymer electrolyte membrane (PEM) fuel cell stack tailored to hydrogen fuel use • An advanced electrical energy storage system • A modular, scalable power conditioning system tailored to market requirements • A scaled-down, cost-reduced balance of plant (BOP) • Network Equipment Building Standards (NEBS), UL and CE certifications.

Staudt, Rhonda L.

2008-05-28T23:59:59.000Z

465

Peak Tracking by Simultaneous Inversion: Toward a One-Step Acoustic Tomography Analysis  

Science Conference Proceedings (OSTI)

A number of geophysical observing techniques, including ocean acoustic tomography, obtain sequences of records of which the observed relative maxima (“peaks”) are used to infer properties of the system via inversions. Traditionally, these peaks ...

Uwe Send

1996-10-01T23:59:59.000Z

466

Production of Hydrogen at the Forecourt Using Off-Peak Electricity: June 2005 (Milestone Report)  

DOE Green Energy (OSTI)

This milestone report provides information about the production of hydrogen at the forecourt using off-peak electricity as well as the Hydrogen Off-Peak Electricity (HOPE) model.

Levene, J. I.

2007-02-01T23:59:59.000Z

467

OG&E Uses Time-Based Rate Program to Reduce Peak Demand  

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

The VPP rates during the five-hour peak period vary daily depending on the cost of electricity. The VPP also includes a critical peak price (CPP) component that is...

468

Design and evaluation of seasonal storage hydrogen peak electricity supply system  

E-Print Network (OSTI)

The seasonal storage hydrogen peak electricity supply system (SSHPESS) is a gigawatt-year hydrogen storage system which stores excess electricity produced as hydrogen during off-peak periods and consumes the stored hydrogen ...

Oloyede, Isaiah Olanrewaju

2011-01-01T23:59:59.000Z

469

Microsoft Word - BUGS_The Next Smart Grid Peak Resource Final...  

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

April 15, 2010 DOENETL-20101406 Backup Generators (BUGS): The Next Smart Grid Peak Resource Backup Generators (BUGS): The Next Smart Grid Peak Resource v1.0 ii DISCLAIMER This...

470

Preparing for the Peak: Energy Security and Atlantic Canada 1 Larry Hughes  

E-Print Network (OSTI)

region that will be particularly vulnerable to peak oil, since almost all of the region's oil is imported is destined for markets outside the region. This paper examines some of the potential impacts of peak oil the reliance on refined petroleum products for space heating and transportation. When peak oil production

Hughes, Larry

471

Peak production in an oil depletion model with triangular field profiles  

E-Print Network (OSTI)

Peak production in an oil depletion model with triangular field profiles Dudley Stark School;1 Introduction M. King Hubbert [5] used curve fitting to predict that the peak of oil produc- tion in the U.S.A. would occur between 1965 and 1970. Oil production in the U.S.A. actually peaked in 1970 and has been

Stark, Dudley

472

Available online at www.sciencedirect.com Future world oil production: growth, plateau, or peak?  

E-Print Network (OSTI)

Available online at www.sciencedirect.com Future world oil production: growth, plateau, or peak considers how long world oil production can continue to grow or if it will eventually plateau or peak and then decline. The paper concludes with the observation that whether peak oil has already occurred

Ito, Garrett

473

Result Demonstration Report Pigweed Control in Grain Sorghum Using Peak. 1996 to 1999  

E-Print Network (OSTI)

74 78 Peak + Methylated Oil 0.75 oz + 1 pt 78 88 93 1) WAT = Weeks after treatment application. #12Result Demonstration Report Pigweed Control in Grain Sorghum Using Peak. 1996 to 1999 Brent Bean Summary Studies were conducted from 1996 to 1999 to evaluate pigweed control in grain sorghum using Peak

Mukhtar, Saqib

474

Implications of ``peak oil'' for atmospheric CO2 and climate Pushker A. Kharecha1  

E-Print Network (OSTI)

Implications of ``peak oil'' for atmospheric CO2 and climate Pushker A. Kharecha1 and James E environments. If conventional oil production peaks within the next few decades, it may have a large effect., and J. E. Hansen (2008), Implications of ``peak oil'' for atmospheric CO2 and climate, Global Biogeochem

475

Compact Totally Disconnected Moufang Buildings  

E-Print Network (OSTI)

Let $\\Delta$ be a spherical building each of whose irreducible components is infinite, has rank at least 2 and satisfies the Moufang condition. We show that $\\Delta$ can be given the structure of a topological building that is compact and totally disconnected precisely when $\\Delta$ is the building at infinity of a locally finite affine building.

Grundhofer, T; Van Maldeghem, H; Weiss, R M

2010-01-01T23:59:59.000Z

476

Total Imports of Residual Fuel  

Annual Energy Outlook 2012 (EIA)

2007 2008 2009 2010 2011 2012 View History U.S. Total 135,676 127,682 120,936 133,646 119,888 93,672 1936-2012 PAD District 1 78,197 73,348 69,886 88,999 79,188 59,594 1981-2012...

477

Evaluation of potential severe accidents during low power and shutdown operations at Grand Gulf, Unit 1: Analysis of core damage frequency from internal events for Plant Operational State 5 during a refueling outage. Volume 2, Part 3: Internal Events Appendices I and J  

SciTech Connect

This report provides supporting documentation for various tasks associated with the performance of the probablistic risk assessment for Plant Operational State 5 during a refueling outage at Grand Gulf, Unit 1 as documented in Volume 2, Part 1 of NUREG/CR-6143.

Yakle, J. [Science Applications International Corp., Albuquerque, NM (United States); Darby, J. [Science and Engineering Associates, Inc., Albuquerque, NM (United States); Whitehead, D.; Staple, B. [Sandia National Labs., Albuquerque, NM (United States)

1994-06-01T23:59:59.000Z

478

Buildings","Total  

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

L2. Floorspace Lit by Lighting Types (Non-Mall Buildings), 1999" L2. Floorspace Lit by Lighting Types (Non-Mall Buildings), 1999" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings* ...............",61707,58693,49779,6496,37150,3058,5343,1913 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",6750,5836,4878,757,3838,231,109,162 "5,001 to 10,000 ..............",7940,7166,5369,1044,4073,288,160,109 "10,001 to 25,000 .............",10534,9773,7783,1312,5712,358,633,232

479

Performance Period Total Fee Paid  

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

Period Period Total Fee Paid 4/29/2012 - 9/30/2012 $418,348 10/1/2012 - 9/30/2013 $0 10/1/2013 - 9/30/2014 $0 10/1/2014 - 9/30/2015 $0 10/1/2015 - 9/30/2016 $0 Cumulative Fee Paid $418,348 Contract Type: Cost Plus Award Fee Contract Period: $116,769,139 November 2011 - September 2016 $475,395 $0 Fee Information Total Estimated Contract Cost $1,141,623 $1,140,948 $1,140,948 $5,039,862 $1,140,948 Maximum Fee $5,039,862 Minimum Fee Fee Available Portage, Inc. DE-DT0002936 EM Contractor Fee Site: MOAB Uranium Mill Tailings - MOAB, UT Contract Name: MOAB Uranium Mill Tailings Remedial Action Contract September 2013 Contractor: Contract Number:

480

Buildings","Total  

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

L1. Floorspace Lit by Lighting Type for Non-Mall Buildings, 1995" L1. Floorspace Lit by Lighting Type for Non-Mall Buildings, 1995" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings*",54068,51570,45773,6746,34910,1161,3725,779 "Building Floorspace" "(Square Feet)" "1,001 to 5,000",6272,5718,4824,986,3767,50,22,54 "5,001 to 10,000",7299,6667,5728,1240,4341,61,169,45 "10,001 to 25,000",10829,10350,8544,1495,6442,154,553,"Q"

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


481

ARM - Measurement - Total cloud water  

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

cloud water cloud water 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 : Total cloud water The total concentration (mass/vol) of ice and liquid water particles in a cloud; this includes condensed water content (CWC). Categories Cloud Properties 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 recorded for diagnostic or quality assurance purposes. External Instruments NCEPGFS : National Centers for Environment Prediction Global Forecast System Field Campaign Instruments CSI : Cloud Spectrometer and Impactor PDI : Phase Doppler Interferometer

482

Buildings","Total  

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

L3. Floorspace Lit by Lighting Type (Non-Mall Buildings), 2003" L3. Floorspace Lit by Lighting Type (Non-Mall Buildings), 2003" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings* ...............",64783,62060,51342,5556,37918,4004,4950,2403 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",6789,6038,4826,678,3932,206,76,124 "5,001 to 10,000 ..............",6585,6090,4974,739,3829,192,238,248 "10,001 to 25,000 .............",11535,11229,8618,1197,6525,454,506,289

483

Model of peak separation in the gamma lightcurve of the Vela pulsar  

E-Print Network (OSTI)

The separation $\\del$ between two peaks in the gamma-ray pulse profile is calculated as a function of energy for several polar cap models with curvature-radiation-induced cascades. The Monte Carlo results are interpreted with the help of analytical approximations and discussed in view of the recent data analysis for the Vela pulsar (Kanbach 1999). We find that the behaviour of $\\del$ as a function of photon energy $\\epsilon$ depends primarily on local values of the magnetic field, $B_{\\rm local}$, in the region where electromagnetic cascades develop. For low values of $B_{\\rm local}$ ($ \\et$, in hollow-column models the separation $\\del$ increases (whereas in filled-column model it decreases) rapidly with increasing $\\epsilon$, at a rate of $\\sim 0.28$ of the total phase per decade of photon energy. The existence of critical energy $\\et$ is a direct consequence of one-photon magnetic absorption effects. In general, $\\et$ is located close to the high-energy cutoff of the spectrum, thus photon statistics at $\\et$ should be very low. That will make difficult to verify the existence of $\\et$ in real gamma-ray pulsars. Spectral properties of the Vela pulsar would favour those models which use low values of magnetic field in the emission region ($B_{\\rm local} \\simless 10^{11}$ G) which in turn implies a constant value of the predicted $\\del$ within EGRET range.

J. Dyks; B. Rudak

2000-03-04T23:59:59.000Z

484

Total Adjusted Sales of Kerosene  

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

End Use: Total Residential Commercial Industrial Farm All Other Period: End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2007 2008 2009 2010 2011 2012 View History U.S. 492,702 218,736 269,010 305,508 187,656 81,102 1984-2012 East Coast (PADD 1) 353,765 159,323 198,762 237,397 142,189 63,075 1984-2012 New England (PADD 1A) 94,635 42,570 56,661 53,363 38,448 15,983 1984-2012 Connecticut 13,006 6,710 8,800 7,437 7,087 2,143 1984-2012 Maine 46,431 19,923 25,158 24,281 17,396 7,394 1984-2012 Massachusetts 7,913 3,510 5,332 6,300 2,866 1,291 1984-2012 New Hampshire 14,454 6,675 8,353 7,435 5,472 1,977 1984-2012

485

Solar total energy project Shenandoah  

DOE Green Energy (OSTI)

This document presents the description of the final design for the Solar Total Energy System (STES) to be installed at the Shenandoah, Georgia, site for utilization by the Bleyle knitwear plant. The system is a fully cascaded total energy system design featuring high temperature paraboloidal dish solar collectors with a 235 concentration ratio, a steam Rankine cycle power conversion system capable of supplying 100 to 400 kW(e) output with an intermediate process steam take-off point, and a back pressure condenser for heating and cooling. The design also includes an integrated control system employing the supervisory control concept to allow maximum experimental flexibility. The system design criteria and requirements are presented including the performance criteria and operating requirements, environmental conditions of operation; interface requirements with the Bleyle plant and the Georgia Power Company lines; maintenance, reliability, and testing requirements; health and safety requirements; and other applicable ordinances and codes. The major subsystems of the STES are described including the Solar Collection Subysystem (SCS), the Power Conversion Subsystem (PCS), the Thermal Utilization Subsystem (TUS), the Control and Instrumentation Subsystem (CAIS), and the Electrical Subsystem (ES). Each of these sections include design criteria and operational requirements specific to the subsystem, including interface requirements with the other subsystems, maintenance and reliability requirements, and testing and acceptance criteria. (WHK)

None

1980-01-10T23:59:59.000Z

486

Grantee Total Number of Homes  

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

Grantee Grantee Total Number of Homes Weatherized through November 2011 [Recovery Act] Total Number of Homes Weatherized through November 2011 (Calendar Year 2009 - November 2011) [Recovery Act + Annual Program Funding] Alabama 6,704 7,867 1 Alaska 443 2,363 American Samoa 304 410 Arizona 6,354 7,518 Arkansas 5,231 6,949 California 41,649 50,002 Colorado 12,782 19,210 Connecticut 8,940 10,009 2 Delaware** 54 54 District of Columbia 962 1,399 Florida 18,953 20,075 Georgia 13,449 14,739 Guam 574 589 Hawaii 604 1,083 Idaho** 4,470 6,614 Illinois 35,530 44,493 Indiana** 18,768 21,689 Iowa 8,794 10,202 Kansas 6,339 7,638 Kentucky 7,639 10,902 Louisiana 4,698 6,946 Maine 5,130 6,664 Maryland 8,108 9,015 Massachusetts 17,687 21,645 Michigan 29,293 37,137 Minnesota 18,224 22,711 Mississippi 5,937 6,888 Missouri 17,334 20,319 Montana 3,310 6,860 Navajo Nation

487

Impact of Smart Grid Technologies on Peak Load to 2050 | Open Energy  

Open Energy Info (EERE)

Impact of Smart Grid Technologies on Peak Load to 2050 Impact of Smart Grid Technologies on Peak Load to 2050 Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Impact of Smart Grid Technologies on Peak Load to 2050 Focus Area: Crosscutting Topics: Deployment Data Website: www.iea.org/papers/2011/smart_grid_peak_load.pdf Equivalent URI: cleanenergysolutions.org/content/impact-smart-grid-technologies-peak-l Language: English Policies: "Deployment Programs,Regulations" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Demonstration & Implementation Regulations: Cost Recovery/Allocation This working paper analyses the evolution of peak load demand to 2050 in four key regions: Organisation for Economic Co-operation and Development

488

Offset-free rail-to-rail derandomizing peak detect-and-hold circuit  

Science Conference Proceedings (OSTI)

A peak detect-and-hold circuit eliminates errors introduced by conventional amplifiers, such as common-mode rejection and input voltage offset. The circuit includes an amplifier, three switches, a transistor, and a capacitor. During a detect-and-hold phase, a hold voltage at a non-inverting in put terminal of the amplifier tracks an input voltage signal and when a peak is reached, the transistor is switched off, thereby storing a peak voltage in the capacitor. During a readout phase, the circuit functions as a unity gain buffer, in which the voltage stored in the capacitor is provided as an output voltage. The circuit is able to sense signals rail-to-rail and can readily be modified to sense positive, negative, or peak-to-peak voltages. Derandomization may be achieved by using a plurality of peak detect-and-hold circuits electrically connected in parallel.

DeGeronimo, Gianluigi (Nesconset, NY); O'Connor, Paul (Bellport, NY); Kandasamy, Anand (Coram, NY)

2003-01-01T23:59:59.000Z

489

Influence of Air Conditioner Operation on Electricity Use and Peak Demand  

E-Print Network (OSTI)

Electricity demand due to occupant controlled room air conditioners in a large mater-metered apartment building is analyzed. Hourly data on the electric demand of the building and of individual air conditioners are used in analyses of annual and time-of-day peaks. Effects of occupant schedules and behavior are examined. We conclude that room air conditioners cause a sharp annual peak demand because occupants have strongly varying thresholds with respect to toleration of high indoor temperatures. However, time-or-day peaking is smoothed by air conditioning in this building due to significant off-peak operation of air conditioners by some occupants. If occupants were billed directly for electricity, off-peak use would probably diminish making the peaks more pronounced and exacerbating the utility company's load management problems. Future studies of this type in individually metered apartment buildings are recommended.

McGarity, A. E.; Feuermann, D.; Kempton, W.; Norford, L. K.

1987-01-01T23:59:59.000Z

490

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 Capacity (B/SD) Thermal Cracking Downstream Charge Capacity (B/SD) Thermal Cracking Total Coking Downstream Charge Capacity (B/SD) Thermal Cracking Delayed Coking Downstream Charge Capacity (B/SD Thermal Cracking Fluid Coking Downstream Charge Capacity (B/SD) Thermal Cracking Visbreaking Downstream Charge Capacity (B/SD) Thermal Cracking Other/Gas Oil Charge Capacity (B/SD) Catalytic Cracking Fresh Feed Charge Capacity (B/SD) Catalytic Cracking Recycle Charge Capacity (B/SD) Catalytic Hydro-Cracking Charge Capacity (B/SD) Catalytic Hydro-Cracking Distillate Charge Capacity (B/SD) Catalytic Hydro-Cracking Gas Oil Charge Capacity (B/SD) Catalytic Hydro-Cracking Residual Charge Capacity (B/SD) Catalytic Reforming Charge Capacity (B/SD) Catalytic Reforming Low Pressure Charge Capacity (B/SD) Catalytic Reforming High Pressure Charge Capacity (B/SD) Catalytic Hydrotreating/Desulfurization Charge Capacity (B/SD) Catalytic Hydrotreating Naphtha/Reformer Feed Charge Cap (B/SD) Catalytic Hydrotreating Gasoline Charge Capacity (B/SD) Catalytic Hydrotreating Heavy Gas Oil Charge Capacity (B/SD) Catalytic Hydrotreating Distillate Charge Capacity (B/SD) Catalytic Hydrotreating Kerosene/Jet Fuel Charge Capacity (B/SD) Catalytic Hydrotreating Diesel Fuel Charge Capacity (B/SD) Catalytic Hydrotreating Other Distillate Charge Capacity (B/SD) Catalytic Hydrotreating Residual/Other Charge Capacity (B/SD) Catalytic Hydrotreating Residual Charge Capacity (B/SD) Catalytic Hydrotreating Other Oils Charge Capacity (B/SD) Fuels Solvent Deasphalting Charge Capacity (B/SD) Catalytic Reforming Downstream Charge Capacity (B/CD) Total Coking Downstream Charge Capacity (B/CD) Catalytic Cracking Fresh Feed Downstream Charge Capacity (B/CD) Catalytic Hydro-Cracking Downstream Charge Capacity (B/CD) Period:

491

The role of building technologies in reducing and controlling peak electricity demand  

E-Print Network (OSTI)

power in real time (costs per kWh at time of system peak canto large increases in marginal costs per kWh, because of the

Koomey, Jonathan; Brown, Richard E.

2002-01-01T23:59:59.000Z

492

Pressure Temperature Log At Silver Peak Area (DOE GTP) | Open Energy  

Open Energy Info (EERE)

source source History View New Pages Recent Changes All Special Pages Semantic Search/Querying Get Involved Help Apps Datasets Community Login | Sign Up Search Page Edit History Facebook icon Twitter icon » Pressure Temperature Log At Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Pressure Temperature Log At Silver Peak Area (DOE GTP) Exploration Activity Details Location Silver Peak Area Exploration Technique Pressure Temperature Log Activity Date Usefulness not indicated DOE-funding Unknown References (1 January 2011) GTP ARRA Spreadsheet Retrieved from "http://en.openei.org/w/index.php?title=Pressure_Temperature_Log_At_Silver_Peak_Area_(DOE_GTP)&oldid=511053" Categories: Exploration Activities

493

Indoor Air Quality Impacts of a Peak Load Shedding Strategy for...  

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

Abstract Mock Critical Peak Pricing (CPP) events were implemented in a Target retail store in the San Francisco Bay Area by shutting down some of the building's...

494

Thermal Gradient Holes At Silver Peak Area (DOE GTP) | Open Energy...  

Open Energy Info (EERE)

Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Thermal Gradient Holes At Silver Peak Area (DOE GTP) Exploration Activity Details Location...

495

Thermal And-Or Near Infrared At Silver Peak Area (DOE GTP) |...  

Open Energy Info (EERE)

Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Thermal And-Or Near Infrared At Silver Peak Area (DOE GTP) Exploration Activity Details...

496

The role of building technologies in reducing and controlling peak electricity demand  

E-Print Network (OSTI)

AND CONTROLLING PEAK ELECTRICITY DEMAND Jonathan Koomey* andData to Improve Electricity Demand Forecasts–Final Report.further research. Electricity demand varies constantly. At

Koomey, Jonathan; Brown, Richard E.

2002-01-01T23:59:59.000Z

497

A new approach for modeling the peak utility impacts from a proposed CUAC standard  

E-Print Network (OSTI)

an October-peaking load profile, rather than a more credibleof the space cooling load profiles for the months ofcommercial space cooling load profile for ECAR. This figure

LaCommare, Kristina Hamachi; Gumerman, Etan; Marnay, Chris; Chan, Peter; Coughlin, Katie

2004-01-01T23:59:59.000Z

498

Food production after peak oil| Oregon's Willamette river basin as a bioregional case study.  

E-Print Network (OSTI)

?? Agriculture will experience radical new challenges in the next forty years. Peak oil, which is likely to occur before 2020, will result in potentially… (more)

Hruska, Tracy

2010-01-01T23:59:59.000Z

499

Investigation of Peak Load Reduction Strategies in Residential Buildings in Cooling Dominated Climates.  

E-Print Network (OSTI)

??This investigation of peak load reduction strategies in residential buildings contributes to the global international efforts in reducing energy consumption and is related directly to… (more)

Atallah, Fady

2013-01-01T23:59:59.000Z

500

Total quality management implementation guidelines  

SciTech Connect

These Guidelines were designed by the Energy Quality Council to help managers and supervisors in the Department of Energy Complex bring Total Quality Management to their organizations. Because the Department is composed of a rich mixture of diverse organizations, each with its own distinctive culture and quality history, these Guidelines are intended to be adapted by users to meet the particular needs of their organizations. For example, for organizations that are well along on their quality journeys and may already have achieved quality results, these Guidelines will provide a consistent methodology and terminology reference to foster their alignment with the overall Energy quality initiative. For organizations that are just beginning their quality journeys, these Guidelines will serve as a startup manual on quality principles applied in the Energy context.

Not Available

1993-12-01T23:59:59.000Z